diff --git a/.github/workflows/cross-platform-parity-ci.yml b/.github/workflows/cross-platform-parity-ci.yml
index bb7dcbf8e4..45ce231743 100644
--- a/.github/workflows/cross-platform-parity-ci.yml
+++ b/.github/workflows/cross-platform-parity-ci.yml
@@ -1,18 +1,16 @@
 # SPDX-License-Identifier: AGPL-3.0-only
 # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
 
-# Runs installer parity and autostart opt-out tests on Windows and macOS.
+# Runs installer parity and autostart opt-out tests across all three platforms.
 #
-# Why: that test is the guard that install.sh and install.ps1 stay in
-# sync, but today it only runs on ubuntu-latest (auto-discovered by
-# studio-backend-ci.yml's "Repo tests (CPU)" job). The test reads both
-# installer scripts, and on Windows Path.read_text() defaults to the
-# cp1252 locale encoding, so a non-cp1252 byte in install.sh (it already
-# contains a U+274C) raises UnicodeDecodeError there even though Linux and
-# macOS default to UTF-8. The reads were pinned to encoding="utf-8" in
-# #6166; this job keeps that from silently regressing by exercising the
-# test on the platforms it claims parity for. Pure pytest, no GPU,
-# sub-second, so the matrix is cheap.
+# Why: the parity test guards that install.sh and install.ps1 stay in sync.
+# It originally ran only on ubuntu-latest through studio-backend-ci.yml.
+# On Windows, Path.read_text() defaults to the cp1252 locale encoding, so a
+# non-cp1252 byte in install.sh raises UnicodeDecodeError even though Linux
+# and macOS default to UTF-8. The reads were pinned to encoding="utf-8" in
+# #6166; this matrix keeps that from silently regressing. Pure pytest, no GPU,
+# sub-second, so the matrix is cheap. Linux also runs the POSIX rollback test
+# under dash, matching the supported curl-to-sh installer path.
 
 name: Cross-platform parity
 
@@ -23,6 +21,8 @@ on:
       - 'install.ps1'
       - 'tests/test_installer_skip_autostart.py'
       - 'tests/python/test_cross_platform_parity.py'
+      - 'tests/sh/test_install_rollback_lifecycle.sh'
+      - 'tests/studio/test_install_rollback_lifecycle.ps1'
       - '.github/workflows/cross-platform-parity-ci.yml'
   push:
     branches: [main]
@@ -31,6 +31,8 @@ on:
       - 'install.ps1'
       - 'tests/test_installer_skip_autostart.py'
       - 'tests/python/test_cross_platform_parity.py'
+      - 'tests/sh/test_install_rollback_lifecycle.sh'
+      - 'tests/studio/test_install_rollback_lifecycle.ps1'
       - '.github/workflows/cross-platform-parity-ci.yml'
   workflow_dispatch:
 
@@ -47,7 +49,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [windows-latest, macos-latest]
+        os: [ubuntu-latest, windows-latest, macos-latest]
     runs-on: ${{ matrix.os }}
     timeout-minutes: 10
     steps:
@@ -67,3 +69,10 @@ jobs:
           tests/python/test_cross_platform_parity.py
           tests/test_installer_skip_autostart.py
           -q
+      - name: PowerShell rollback lifecycle tests
+        if: runner.os == 'Windows'
+        shell: pwsh
+        run: pwsh -NoProfile -File tests/studio/test_install_rollback_lifecycle.ps1
+      - name: POSIX rollback lifecycle tests
+        if: runner.os == 'Linux'
+        run: sh tests/sh/test_install_rollback_lifecycle.sh
diff --git a/.github/workflows/studio-ui-smoke.yml b/.github/workflows/studio-ui-smoke.yml
index 30280c281e..97eb07b2d8 100644
--- a/.github/workflows/studio-ui-smoke.yml
+++ b/.github/workflows/studio-ui-smoke.yml
@@ -231,12 +231,69 @@ jobs:
           mkdir -p logs/playwright_extra
           python tests/studio/playwright_extra_ui.py
 
+      - name: UI font size scaling regression (Playwright)
+        env:
+          BASE_URL: http://127.0.0.1:18894
+          STUDIO_PW: ${{ env.STUDIO_EXTRA_NEW_PW }}
+          PW_ART_DIR: logs/playwright_fontscale
+        run: |
+          mkdir -p logs/playwright_fontscale
+          python tests/studio/playwright_ui_font_scale.py
+
       - name: Stop second Unsloth
         if: always()
         run: |
           kill "${STUDIO_EXTRA_PID}" 2>/dev/null || true
           sleep 2
 
+      # Model-picker per-model-config regression (PR #7207 re-land of #6647).
+      # Fourth Unsloth on its own port; loads the tiny GGUF and drives the
+      # picker's run-settings surface: Context Length persists across a reload,
+      # Reset clears the stored override (never pins it), and the infra models
+      # (RAG embedder + llama.cpp probe) stay hidden from the picker.
+      - name: Reset auth + boot Unsloth for model-config tests (port 18898)
+        run: |
+          unsloth studio reset-password
+          mkdir -p logs
+          UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18898 \
+            > logs/studio_modelcfg.log 2>&1 &
+          echo "STUDIO_MODELCFG_PID=$!" >> "$GITHUB_ENV"
+
+      - name: Wait for /api/health on 18898
+        run: |
+          for i in $(seq 1 180); do
+            if curl -fs "http://127.0.0.1:18898/api/health" > /tmp/health4.json; then
+              jq -e '.status == "healthy"' /tmp/health4.json && break
+            fi
+            sleep 1
+          done
+          jq -e '.status == "healthy"' /tmp/health4.json
+
+      - name: Pass bootstrap pw for model-config test
+        run: |
+          NEW="CIModelCfg-$(python -c 'import secrets; print(secrets.token_urlsafe(16))')"
+          echo "::add-mask::$NEW"
+          echo "STUDIO_MODELCFG_NEW_PW=$NEW" >> "$GITHUB_ENV"
+
+      - name: Drive model-picker per-model-config with Playwright
+        env:
+          BASE_URL: http://127.0.0.1:18898
+          STUDIO_NEW_PW: ${{ env.STUDIO_MODELCFG_NEW_PW }}
+          PW_ART_DIR: logs/playwright_modelcfg
+          STUDIO_UI_STRICT: '1'
+          GGUF_REPO: ${{ env.GGUF_REPO }}
+          GGUF_VARIANT: ${{ env.GGUF_VARIANT }}
+          STUDIO_MODEL_HINT: gemma-3-270m
+        run: |
+          mkdir -p logs/playwright_modelcfg
+          python tests/studio/playwright_model_config.py
+
+      - name: Stop fourth Unsloth
+        if: always()
+        run: |
+          kill "${STUDIO_MODELCFG_PID}" 2>/dev/null || true
+          sleep 2
+
       # IME + multilingual paste regression (issue #5318 / PR #5327).
       # Third Unsloth on its own port so a hang here cannot poison the
       # earlier UI tests. No GGUF -- the bug surface is the composer.
@@ -297,12 +354,15 @@ jobs:
           path: |
             logs/studio.log
             logs/studio_extra.log
+            logs/studio_modelcfg.log
             logs/studio_ime.log
             logs/install.log
             logs/server-logs/
             logs/playwright
             logs/playwright-permissions-*
             logs/playwright_extra
+            logs/playwright_fontscale
+            logs/playwright_modelcfg
             logs/playwright_ime
             logs/studio-permissions-*.log
           retention-days: 7
diff --git a/README.md b/README.md
index 6aa8f4f4c3..514454f985 100644
--- a/README.md
+++ b/README.md
@@ -86,6 +86,13 @@ Replace `claude` with any supported agent:
 | OpenCode | `unsloth start opencode` |
 | Pi Coding Agent | `unsloth start pi` |
 
+Claude Code, Codex, OpenCode and Pi can keep their current model and use Unsloth as a local
+subagent:
+
+```bash
+unsloth start claude --as-subagent --model unsloth/model-GGUF:quant
+```
+
 ## 📥 Install
 Unsloth can be used in two ways: through **[Unsloth Studio](https://unsloth.ai/docs/new/studio/)**, the web UI, or through **Unsloth Core**, the code-based version. Each has different requirements.
 
diff --git a/install.ps1 b/install.ps1
index 6e059ee0dd..c06f3a1120 100644
--- a/install.ps1
+++ b/install.ps1
@@ -1416,13 +1416,82 @@ exit 0
             $suffix++
             $candidate = Join-Path $StudioHome "unsloth_studio.rollback.$stamp.$PID.$suffix"
         }
-        Move-Item -LiteralPath $ExistingDir -Destination $candidate -ErrorAction Stop
         $script:StudioVenvRollbackDir = $candidate
         $script:StudioVenvRollbackTarget = $ExistingDir
         $script:StudioVenvRollbackActive = $true
+        # Publish the rollback state before the atomic rename so interruption
+        # cannot land after Move-Item but before cleanup knows where the old venv went.
+        try {
+            Move-Item -LiteralPath $ExistingDir -Destination $candidate -ErrorAction Stop
+        } catch {
+            # A collision or ordinary rename failure leaves the original in place.
+            # Keep state active only when the rename happened before interruption.
+            if (Test-Path -LiteralPath $ExistingDir) {
+                $script:StudioVenvRollbackActive = $false
+                $script:StudioVenvRollbackDir = $null
+            }
+            throw
+        }
         substep "previous environment preserved for rollback"
     }
 
+    function Remove-StudioVenvTreeWithRetry {
+        param(
+            [Parameter(Mandatory = $true)][string]$Path,
+            [Parameter(Mandatory = $true)][string]$Label
+        )
+        $lastError = $null
+        for ($attempt = 1; $attempt -le 3; $attempt++) {
+            try {
+                Remove-Item -LiteralPath $Path -Recurse -Force -ErrorAction Stop
+            } catch {
+                $lastError = $_.Exception.Message
+            }
+            if (-not (Test-Path -LiteralPath $Path)) { return $true }
+            if ($attempt -lt 3) { Start-Sleep -Milliseconds (250 * $attempt) }
+        }
+        Write-Host "[WARN] Could not remove $Label at $Path" -ForegroundColor Yellow
+        if ($lastError) { Write-Host "       $lastError" -ForegroundColor Yellow }
+        return $false
+    }
+
+    function Test-StudioVenvRollbackMustBePreserved {
+        param([Parameter(Mandatory = $true)][System.IO.FileSystemInfo]$Rollback)
+        # Preserve anything outside the installer's timestamp.PID[.suffix] format.
+        if ($Rollback.Name -notmatch '^unsloth_studio\.rollback\.[0-9]{14}\.([0-9]+)(?:\.[0-9]+)?$') {
+            return $true
+        }
+        $ownerPid = 0
+        if (-not [int]::TryParse($Matches[1], [ref]$ownerPid)) { return $true }
+        if ($ownerPid -eq $PID) { return $true }
+        return $null -ne (Get-Process -Id $ownerPid -ErrorAction SilentlyContinue)
+    }
+
+    function Remove-StaleStudioVenvRollbacks {
+        try {
+            $rollbacks = @(
+                Get-ChildItem -LiteralPath $StudioHome -Directory -Force -ErrorAction Stop |
+                    Where-Object { $_.Name -like 'unsloth_studio.rollback.*' }
+            )
+        } catch {
+            Write-Host "[WARN] Could not inspect stale environment rollbacks in $StudioHome" -ForegroundColor Yellow
+            Write-Host "       $($_.Exception.Message)" -ForegroundColor Yellow
+            return
+        }
+        foreach ($rollback in $rollbacks) {
+            if (($rollback.Attributes -band [System.IO.FileAttributes]::ReparsePoint) -ne 0) {
+                Write-Host "[WARN] Refusing to remove rollback reparse point $($rollback.FullName)" -ForegroundColor Yellow
+                continue
+            }
+            # A concurrent installer may have moved its live venv aside. The PID
+            # in the generated name keeps this run from deleting its rescue copy.
+            if (Test-StudioVenvRollbackMustBePreserved -Rollback $rollback) { continue }
+            if (Remove-StudioVenvTreeWithRetry -Path $rollback.FullName -Label "stale environment rollback") {
+                substep "removed stale environment rollback $($rollback.Name)"
+            }
+        }
+    }
+
     function Restore-StudioVenvRollback {
         if (-not $script:StudioVenvRollbackActive) { return }
         $backup = $script:StudioVenvRollbackDir
@@ -1434,7 +1503,9 @@ exit 0
         substep "restoring previous environment after failed install..." "Yellow"
         try {
             if (Test-Path -LiteralPath $target) {
-                Remove-Item -LiteralPath $target -Recurse -Force -ErrorAction SilentlyContinue
+                if (-not (Remove-StudioVenvTreeWithRetry -Path $target -Label "incomplete environment")) {
+                    throw "Could not remove incomplete environment at $target"
+                }
             }
             Move-Item -LiteralPath $backup -Destination $target -Force -ErrorAction Stop
             substep "restored previous environment"
@@ -1449,13 +1520,17 @@ exit 0
     function Complete-StudioVenvRollback {
         if (-not $script:StudioVenvRollbackActive) { return }
         $backup = $script:StudioVenvRollbackDir
-        if ($backup -and (Test-Path -LiteralPath $backup)) {
-            Remove-Item -LiteralPath $backup -Recurse -Force -ErrorAction SilentlyContinue
-        }
+        # The replacement is committed. Disable restoration before deleting the
+        # backup so interruption cannot restore a partially deleted environment.
         $script:StudioVenvRollbackActive = $false
         $script:StudioVenvRollbackDir = $null
+        if ($backup -and (Test-Path -LiteralPath $backup)) {
+            Remove-StudioVenvTreeWithRetry -Path $backup -Label "environment rollback" | Out-Null
+        }
     }
 
+    $studioVenvReplacementCommitted = $false
+    try {
     if (Test-Path -LiteralPath $VenvPython) {
         # why: matching guard to the .venv branch below -- in env-mode
         # $StudioHome is a user-chosen workspace, so refuse to nuke an
@@ -1844,7 +1919,7 @@ exit 0
                 $nameArchTable = @(
                     @{ P = "9070 XT|9080";                                        A = "gfx1201" }  # RDNA 4 (RX 9070 XT / 9080)
                     @{ P = "9070|9060";                                           A = "gfx1200" }  # RDNA 4 (RX 9070 / 9060)
-                    @{ P = "8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max"; A = "gfx1151" }  # RDNA 3.5 (Strix Halo: Radeon 8060S/8050S/8040S iGPU, Ryzen AI Max+)
+                    @{ P = "8065S|8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max"; A = "gfx1151" }  # RDNA 3.5 (Strix Halo + Gorgon Halo: Radeon 8065S/8060S/8050S/8040S iGPU, Ryzen AI Max / Max+)
                     @{ P = "890M|880M|860M|840M|Strix Point|Krackan|HX 37[05]|AI 9 HX|AI 9 36[05]|AI 7 35[05]|AI 5 34[05]|AI 7 PRO 35|AI 5 33"; A = "gfx1150" }  # RDNA 3.5 (Strix/Krackan Point: Radeon 890M/880M iGPU, Ryzen AI 9 HX 370/375)
                     @{ P = "RX 7900|RX 7800|RX 7700(?!S)|PRO W7900|PRO W7800|PRO W7700"; A = "gfx1100" }  # RDNA 3 desktop/workstation (Navi 31)
                     @{ P = "RX 7600|RX 7700S|RX 7650|PRO W7600|PRO W7500|PRO V710"; A = "gfx1102" }  # RDNA 3 (Navi 33)
@@ -2030,16 +2105,18 @@ exit 0
     # _strip_index_url_credentials (install.sh / py / setup.ps1).
     function Remove-IndexUrlCredentials {
         param([string]$Url)
-        $sep = $Url.IndexOf('://')
+        # Ordinal, not culture-aware: on non-English locales (e.g. th-TH) linguistic
+        # IndexOf treats "://" as ignorable, mis-locates it, and crashes Substring (issue #7279).
+        $sep = $Url.IndexOf('://', [System.StringComparison]::Ordinal)
         if ($sep -lt 0) { return $Url }
         $scheme = $Url.Substring(0, $sep)
         $rest = $Url.Substring($sep + 3)
         # Drop query / fragment (may hold auth tokens).
         $q = $rest.IndexOfAny([char[]]('?', '#'))
         if ($q -ge 0) { $rest = $rest.Substring(0, $q) }
-        $slash = $rest.IndexOf('/')
+        $slash = $rest.IndexOf('/', [System.StringComparison]::Ordinal)
         $authority = if ($slash -ge 0) { $rest.Substring(0, $slash) } else { $rest }
-        $at = $authority.LastIndexOf('@')
+        $at = $authority.LastIndexOf('@', [System.StringComparison]::Ordinal)
         $host_ = if ($at -ge 0) { $authority.Substring($at + 1) } else { $authority }
         if ($slash -ge 0) { return "${scheme}://${host_}$($rest.Substring($slash))" }
         return "${scheme}://${host_}"
@@ -2128,6 +2205,10 @@ exit 0
             "gfx1151" = "gfx1151";     "gfx1150" = "gfx1150"       # RDNA 3.5 (Strix Halo/Point)
             "gfx1103" = "gfx110X-all"; "gfx1102" = "gfx110X-all"   # RDNA 3
             "gfx1101" = "gfx110X-all"; "gfx1100" = "gfx110X-all"
+            "gfx1036" = "gfx103X-all"; "gfx1035" = "gfx103X-all"   # RDNA 2 (RX 6000)
+            "gfx1034" = "gfx103X-all"; "gfx1033" = "gfx103X-all"
+            "gfx1032" = "gfx103X-all"; "gfx1031" = "gfx103X-all"
+            "gfx1030" = "gfx103X-all"
             "gfx90a"  = "gfx90a";      "gfx908"  = "gfx908"        # MI200/MI100
         }
         # gfx120X (RDNA 4) and gfx1151/gfx1150 (Strix) have a null-pointer bug in
@@ -2266,7 +2347,7 @@ exit 0
         if ($SkipTorch) {
             # No-torch: install unsloth + unsloth-zoo with --no-deps, then
             # runtime deps (typer, safetensors, transformers, etc.) with --no-deps.
-            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (migrated no-torch)" { uv pip install --python $VenvPython --no-deps --reinstall-package unsloth --reinstall-package unsloth-zoo "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3" }
+            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (migrated no-torch)" { uv pip install --python $VenvPython --no-deps --reinstall-package unsloth --reinstall-package unsloth-zoo "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4" }
             if ($baseInstallExit -eq 0) {
                 # Resolve pydantic WITH deps so pip pins pydantic-core
                 # to the matching version (no-torch-runtime.txt below
@@ -2280,7 +2361,7 @@ exit 0
                 }
             }
         } else {
-            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (migrated)" { uv pip install --python $VenvPython --reinstall-package unsloth --reinstall-package unsloth-zoo "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3" }
+            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (migrated)" { uv pip install --python $VenvPython --reinstall-package unsloth --reinstall-package unsloth-zoo "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4" }
         }
         if ($baseInstallExit -ne 0) {
             Write-Host "[ERROR] Failed to install unsloth (exit code $baseInstallExit)" -ForegroundColor Red
@@ -2354,7 +2435,7 @@ exit 0
         if ($SkipTorch) {
             # No-torch: install unsloth + unsloth-zoo with --no-deps, then
             # runtime deps (typer, safetensors, transformers, etc.) with --no-deps.
-            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (no-torch)" { uv pip install --python $VenvPython --no-deps --upgrade-package unsloth --upgrade-package unsloth-zoo "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3" }
+            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (no-torch)" { uv pip install --python $VenvPython --no-deps --upgrade-package unsloth --upgrade-package unsloth-zoo "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4" }
             if ($baseInstallExit -eq 0) {
                 # Same pydantic-with-deps trick as the migrated branch.
                 $baseInstallExit = Invoke-InstallCommandRetry -Label "install pydantic" { uv pip install --python $VenvPython pydantic }
@@ -2366,7 +2447,7 @@ exit 0
                 }
             }
         } elseif ($StudioLocalInstall) {
-            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (local)" { uv pip install --python $VenvPython --upgrade-package unsloth "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3" }
+            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (local)" { uv pip install --python $VenvPython --upgrade-package unsloth "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4" }
         } else {
             $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth" { uv pip install --python $VenvPython --upgrade-package unsloth -- "$PackageName" }
         }
@@ -2394,7 +2475,7 @@ exit 0
         Write-TauriLog "STEP" "Installing unsloth"
         substep "installing unsloth (this may take a few minutes)..."
         if ($StudioLocalInstall) {
-            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (auto torch backend)" { uv pip install --python $VenvPython "unsloth-zoo>=2026.7.3" "unsloth>=2026.7.3" --torch-backend=auto }
+            $baseInstallExit = Invoke-InstallCommandRetry -Label "install unsloth (auto torch backend)" { uv pip install --python $VenvPython "unsloth-zoo>=2026.7.4" "unsloth>=2026.7.4" --torch-backend=auto }
             if ($baseInstallExit -ne 0) {
                 Write-Host "[ERROR] Failed to install unsloth (exit code $baseInstallExit)" -ForegroundColor Red
                 return (Exit-InstallFailure "Failed to install unsloth (exit code $baseInstallExit)" $baseInstallExit)
@@ -2420,6 +2501,13 @@ exit 0
         }
     }
 
+    $installedPackageVersion = (& $VenvPython -c "from importlib.metadata import version; import sys; print(version(sys.argv[1]))" $PackageName 2>$null | Out-String).Trim()
+    if ($LASTEXITCODE -eq 0 -and $installedPackageVersion) {
+        step $PackageName "$installedPackageVersion installed"
+    } else {
+        substep "[WARN] installed $PackageName version could not be determined" "Yellow"
+    }
+
     # ── Enforce the installed torch flavor matches the detected GPU build ──
     # PEP 440 ignores the +cpu/+cuXXX/+rocm local label in a version range, so uv
     # keeps a stale torch==X+cpu against a CUDA index and setup.ps1 then loops on
@@ -2675,6 +2763,13 @@ exit 0
     }
     Refresh-SessionPath  # sync current session with registry
     Complete-StudioVenvRollback
+    $studioVenvReplacementCommitted = $true
+    Remove-StaleStudioVenvRollbacks
+    } finally {
+        if (-not $studioVenvReplacementCommitted) {
+            Restore-StudioVenvRollback
+        }
+    }
 
     # Env-mode session export AFTER Refresh-SessionPath; otherwise a legacy
     # User PATH entry (Machine > User > current $env:Path) would win.
diff --git a/install.sh b/install.sh
index c02552628f..44d51490f7 100755
--- a/install.sh
+++ b/install.sh
@@ -475,14 +475,20 @@ _start_studio_venv_replacement() {
     _stamp=$(date +%Y%m%d%H%M%S 2>/dev/null || echo "time")
     _candidate="$STUDIO_HOME/unsloth_studio.rollback.$_stamp.$$"
     _suffix=0
-    while [ -e "$_candidate" ]; do
+    while [ -e "$_candidate" ] || [ -L "$_candidate" ]; do
         _suffix=$((_suffix + 1))
         _candidate="$STUDIO_HOME/unsloth_studio.rollback.$_stamp.$$.$_suffix"
     done
-    mv "$_existing_dir" "$_candidate"
     _VENV_ROLLBACK_DIR="$_candidate"
     _VENV_ROLLBACK_TARGET="$_existing_dir"
     _VENV_ROLLBACK_ACTIVE=true
+    # Publish the rollback state before the atomic rename so a signal cannot
+    # land after mv but before the exit handlers know where the old venv went.
+    if ! mv "$_existing_dir" "$_candidate"; then
+        _VENV_ROLLBACK_ACTIVE=false
+        _VENV_ROLLBACK_DIR=""
+        return 1
+    fi
     substep "previous environment preserved for rollback"
 }
 
@@ -503,13 +509,68 @@ _restore_studio_venv_replacement() {
     fi
 }
 
-_commit_studio_venv_replacement() {
-    [ "$_VENV_ROLLBACK_ACTIVE" = true ] || return 0
-    if [ -n "$_VENV_ROLLBACK_DIR" ] && [ -d "$_VENV_ROLLBACK_DIR" ]; then
-        rm -rf "$_VENV_ROLLBACK_DIR" || true
+_studio_venv_rollback_must_be_preserved() {
+    _rollback_name=${1##*/}
+    _rollback_metadata=${_rollback_name#unsloth_studio.rollback.}
+    _rollback_stamp=${_rollback_metadata%%.*}
+    _rollback_process=${_rollback_metadata#*.}
+    # Preserve anything outside the installer's timestamp.PID[.suffix] format.
+    [ "$_rollback_process" != "$_rollback_metadata" ] || return 0
+    case "$_rollback_stamp" in
+        time) ;;
+        ''|*[!0-9]*) return 0 ;;
+        *) [ "${#_rollback_stamp}" -eq 14 ] || return 0 ;;
+    esac
+    _rollback_pid=${_rollback_process%%.*}
+    case "$_rollback_pid" in
+        ''|*[!0-9]*) return 0 ;;
+    esac
+    _rollback_suffix=${_rollback_process#*.}
+    if [ "$_rollback_suffix" != "$_rollback_process" ]; then
+        case "$_rollback_suffix" in ''|*[!0-9]*) return 0 ;; esac
     fi
-    _VENV_ROLLBACK_ACTIVE=false
-    _VENV_ROLLBACK_DIR=""
+    kill -0 "$_rollback_pid" 2>/dev/null
+}
+
+_prune_stale_studio_venv_rollbacks() {
+    for _stale_rollback in "$STUDIO_HOME"/unsloth_studio.rollback.*; do
+        [ -d "$_stale_rollback" ] || continue
+        if [ -L "$_stale_rollback" ]; then
+            echo "⚠️  Refusing to remove rollback symlink $_stale_rollback" >&2
+            continue
+        fi
+        # A concurrent installer may have moved its live venv aside. The PID in
+        # the generated name keeps this successful run from deleting its rescue copy.
+        _studio_venv_rollback_must_be_preserved "$_stale_rollback" && continue
+        if rm -rf "$_stale_rollback"; then
+            substep "removed stale environment rollback ${_stale_rollback##*/}"
+        else
+            echo "⚠️  Could not remove stale environment rollback $_stale_rollback" >&2
+        fi
+    done
+}
+
+_commit_studio_venv_replacement() {
+    if [ "$_VENV_ROLLBACK_ACTIVE" = true ]; then
+        _rollback_to_remove="$_VENV_ROLLBACK_DIR"
+        # The new environment is already committed. Clear the restore state
+        # before deletion so an interrupt cannot replace it with a half-deleted backup.
+        _VENV_ROLLBACK_ACTIVE=false
+        _VENV_ROLLBACK_DIR=""
+        if [ -n "$_rollback_to_remove" ] && [ -d "$_rollback_to_remove" ]; then
+            if ! rm -rf "$_rollback_to_remove"; then
+                echo "⚠️  Could not remove environment rollback $_rollback_to_remove" >&2
+            fi
+        fi
+    fi
+    # Only prune older orphaned copies after the replacement has succeeded, so
+    # an interrupted install never discards the last known-good environment.
+    _prune_stale_studio_venv_rollbacks
+}
+
+_cleanup_install_temporaries() {
+    [ -n "${_UV_OVERRIDE_TMPDIR:-}" ] && rm -rf "$_UV_OVERRIDE_TMPDIR" 2>/dev/null || true
+    [ -n "${_UNSLOTH_TORCH_OVERRIDES:-}" ] && rm -f "$_UNSLOTH_TORCH_OVERRIDES" 2>/dev/null || true
 }
 
 _on_install_exit() {
@@ -517,15 +578,28 @@ _on_install_exit() {
     if [ "$_status" -ne 0 ]; then
         _restore_studio_venv_replacement
     fi
-    [ -n "${_UV_OVERRIDE_TMPDIR:-}" ] && rm -rf "$_UV_OVERRIDE_TMPDIR" 2>/dev/null || true
-    [ -n "${_UNSLOTH_TORCH_OVERRIDES:-}" ] && rm -f "$_UNSLOTH_TORCH_OVERRIDES" 2>/dev/null || true
+    _cleanup_install_temporaries
     exit "$_status"
 }
+
+_on_install_signal() {
+    _signal_status="$1"
+    # EXIT is disabled to avoid a second cleanup pass. Ignore further termination
+    # signals until the old environment is back in place.
+    trap - EXIT
+    trap '' HUP INT TERM
+    _restore_studio_venv_replacement
+    _cleanup_install_temporaries
+    exit "$_signal_status"
+}
 # Empty so an inherited value never reaches the trap's rm; only temp paths this
 # script creates below (spaced-path dir, torch-trio overrides) are removed.
 _UV_OVERRIDE_TMPDIR=""
 _UNSLOTH_TORCH_OVERRIDES=""
 trap _on_install_exit EXIT
+trap '_on_install_signal 129' HUP
+trap '_on_install_signal 130' INT
+trap '_on_install_signal 143' TERM
 
 # ── Helper: download a URL to a file (supports curl and wget) ──
 download() {
@@ -1636,7 +1710,7 @@ _maybe_reroute_strixhalo_to_2404() {
     # CUDA_VISIBLE_DEVICES=""/-1 and the /proc/driver/nvidia fallback for PATH/timeout gaps.
     if _has_usable_nvidia_gpu; then return 0; fi
     # Strix APUs show in /proc/cpuinfo; discrete cards don't, so also try WMI. Either reroutes.
-    if ! grep -qiE 'Ryzen AI Max|Radeon 80[0-9]0S|Strix Halo' /proc/cpuinfo 2>/dev/null \
+    if ! grep -qiE 'Ryzen AI Max|Radeon 80[0-9][05]S|Strix Halo' /proc/cpuinfo 2>/dev/null \
        && ! _wsl_amd_gpu_name >/dev/null 2>&1; then
         return 0
     fi
@@ -2115,18 +2189,148 @@ _has_amd_rocm_gpu() {
          amd-smi list 2>/dev/null | awk '/^GPU[[:space:]]*[:\[][[:space:]]*[0-9]/{ found=1 } END{ exit !found }'; then
         return 0
     elif [ -e /dev/kfd ] && \
-         awk 'FNR==1{ gpu=0; amd=0 } /gpu_id/{ gpu=($2+0>0) } /vendor_id/{ amd=($2==4098) } \
-              gpu && amd { found=1 } END{ exit !found }' \
+         awk '/vendor_id/ && $2 == 4098 { found = 1 } END { exit !found }' \
              /sys/class/kfd/kfd/topology/nodes/*/properties 2>/dev/null; then
-        # vendor_id 4098 = 0x1002 (AMD). NVIDIA open kernel module (driver
-        # 560+) can register KFD topology nodes with non-zero gpu_id but
-        # vendor_id 4318 (0x10DE). Require AMD vendor to avoid misrouting
-        # NVIDIA-only hosts to the ROCm install path.
+        # vendor_id 4098 = 0x1002 (AMD) marks a GPU node: the KFD CPU node
+        # reports vendor_id 0, so any 4098 node is an AMD GPU. NVIDIA's open
+        # kernel module (driver 560+) registers KFD nodes as vendor_id 4318
+        # (0x10DE), so this never false-positives on NVIDIA-only hosts.
+        # The prior check also required a gpu_id line, but gpu_id is a SIBLING
+        # sysfs file, not a line in properties -- it never matched, so the
+        # fallback silently missed every ROCm-less AMD host (issue: fresh
+        # Arch/CachyOS boxes reporting "no GPU detected").
         return 0
     fi
     return 1
 }
 
+# Returns 0 if an AMD display GPU is on the PCI bus even when ROCm can't use it
+# (e.g. a Strix Halo iGPU with no /dev/kfd). Only sharpens the "no GPU detected"
+# hint. vendor 0x1002 = AMD/ATI; class 0x03* = display controller.
+_amd_gpu_present_via_pci() {
+    [ -d /sys/bus/pci/devices ] || return 1
+    for _pci_vendor in /sys/bus/pci/devices/*/vendor; do
+        [ -r "$_pci_vendor" ] || continue
+        read -r _v < "$_pci_vendor" 2>/dev/null || continue
+        [ "$_v" = "0x1002" ] || continue
+        _cls="${_pci_vendor%vendor}class"
+        [ -r "$_cls" ] || continue
+        read -r _c < "$_cls" 2>/dev/null || continue
+        case "$_c" in 0x03*) return 0 ;; esac
+    done
+    return 1
+}
+
+# Map a gfx arch to the AMD pip index family (mirrors install.ps1 $archFamilyMap).
+_amd_arch_index_family_for_gfx() {
+    case "$1" in
+        gfx1201|gfx1200) echo gfx120X-all ;;
+        gfx1151) echo gfx1151 ;;
+        gfx1150) echo gfx1150 ;;
+        gfx1103|gfx1102|gfx1101|gfx1100) echo gfx110X-all ;;
+        gfx1036|gfx1035|gfx1034|gfx1033|gfx1032|gfx1031|gfx1030) echo gfx103X-all ;;
+        gfx90a) echo gfx90a ;;
+        gfx908) echo gfx908 ;;
+        *) return 1 ;;
+    esac
+}
+
+# Map a GPU marketing name to gfx arch (kept in sync with install.ps1 nameArchTable).
+_infer_amd_gfx_arch_from_gpu_name() {
+    case "$1" in
+        *"9070 XT"*|*9080*) echo gfx1201 ;;
+        *9070*|*9060*) echo gfx1200 ;;
+        *"8065S"*|*"8060S"*|*"8050S"*|*"8040S"*|*"Strix Halo"*|*"Ryzen AI Max"*|*"AI Max"*) echo gfx1151 ;;
+        *"890M"*|*"880M"*|*"860M"*|*"840M"*|*"Strix Point"*|*"Krackan"*|*"HX 37"*|*"AI 9 HX"*|*"AI 9 36"*|*"AI 7 35"*|*"AI 5 34"*|*"AI 7 PRO 35"*|*"AI 5 33"*) echo gfx1150 ;;
+        *"RX 7600"*|*"RX 7700S"*|*"RX 7650"*|*"PRO W7600"*|*"PRO W7500"*|*"PRO V710"*) echo gfx1102 ;;
+        *"RX 7900"*|*"RX 7800"*|*"RX 7700"*|*"PRO W7900"*|*"PRO W7800"*|*"PRO W7700"*) echo gfx1100 ;;
+        *"780M"*|*"760M"*|*"740M"*|*"Phoenix"*|*"Hawk Point"*|*"Z1 Extreme"*|*"Z2 Extreme"*) echo gfx1103 ;;
+        *"RX 6900"*|*"RX 6800"*|*"RX 6750"*|*"RX 6700"*|*"PRO W6800"*|*"PRO W6900"*) echo gfx1030 ;;
+        *"RX 6650"*|*"RX 6600"*|*"PRO W6600"*|*"PRO W6650"*) echo gfx1032 ;;
+        *"RX 6500"*|*"RX 6400"*|*"RX 6300"*|*"PRO W6400"*|*"PRO W6500"*) echo gfx1034 ;;
+        *) return 1 ;;
+    esac
+}
+
+# Best-effort gfx inference when ROCm tools can't see the GPU (unslothai#7301).
+# Mirrors install.ps1 arch resolution on Windows ($HasROCm false, $ROCmGfxArch set).
+_infer_linux_amd_gfx_arch() {
+    if [ -n "${UNSLOTH_ROCM_GFX_ARCH:-}" ]; then
+        printf '%s\n' "$(printf '%s' "$UNSLOTH_ROCM_GFX_ARCH" | tr '[:upper:]' '[:lower:]')"
+        return 0
+    fi
+    # On WSL /proc/cpuinfo and lspci still report the host APU, but without the
+    # ROCDXG bridge (librocdxg over /dev/dxg) the AMD wheels can't reach the GPU;
+    # keep the CPU fallback there unless that runtime is present (the explicit
+    # override above still wins). Mirrors install_python_stack.py.
+    _gpu_evidence=""
+    if [ -e /dev/dxg ] || grep -qi microsoft /proc/version 2>/dev/null; then
+        for _d in /opt/rocm/lib /opt/rocm/lib64 /opt/rocm-*/lib /opt/rocm-*/lib64; do
+            { [ -e "$_d/librocdxg.so" ] || [ -e "$_d/librocdxg.so.1" ]; } && _rocdxg=1 && break
+        done
+        [ -n "${_rocdxg:-}" ] || return 1
+        # WSL enumerates no PCI display device; /dev/dxg + librocdxg IS the
+        # GPU evidence there.
+        _gpu_evidence=1
+    elif _amd_gpu_present_via_pci; then
+        _gpu_evidence=1
+    fi
+    # /proc/cpuinfo leaks the HOST CPU model into VMs/containers that received
+    # no AMD GPU, so the CPU-model text alone is not GPU evidence: require an
+    # AMD display device (PCI vendor 0x1002, class 0x03*) before trusting it.
+    # The lspci fallback below needs no gate; an AMD display line IS evidence.
+    if [ -n "$_gpu_evidence" ] && grep -qiE 'Ryzen AI Max|Radeon 80[0-9][05]S|Strix Halo' /proc/cpuinfo 2>/dev/null; then
+        echo gfx1151
+        return 0
+    fi
+    if [ -n "$_gpu_evidence" ] && grep -qiE '890M|880M|860M|840M|Strix Point|Krackan|HX 37[05]|AI 9 HX|AI 9 36[05]|AI 7 35[05]|AI 5 34[05]|AI 7 PRO 35|AI 5 33' /proc/cpuinfo 2>/dev/null; then
+        echo gfx1150
+        return 0
+    fi
+    if command -v lspci >/dev/null 2>&1; then
+        # A non-AMD controller can enumerate first (Intel/ASPEED before an AMD
+        # dGPU), so scan every display-class line and take the first AMD one
+        # that maps. The vendor guard is case-SENSITIVE (a -i "ATI" would match
+        # "CorporATIon" on every Intel/NVIDIA line); whole-line matching also
+        # survives the 0000: PCI domain prefix. Mirrors install_python_stack.py.
+        _amd_disp=$(lspci -nn 2>/dev/null | grep -E 'VGA compatible controller|3D controller|Display controller' | grep -E 'AMD|ATI' || true)
+        while IFS= read -r _ln; do
+            [ -n "$_ln" ] || continue
+            if _gfx=$(_infer_amd_gfx_arch_from_gpu_name "$_ln"); then
+                echo "$_gfx"
+                return 0
+            fi
+        done <<EOF
+$_amd_disp
+EOF
+    fi
+    return 1
+}
+
+# Reads the AMD gfx arch for wheel-index decisions: a user-set
+# UNSLOTH_ROCM_GFX_ARCH is authoritative (lowercased), else rocminfo, then
+# amd-smi. rocminfo/amd-smi honor ROCR/HIP_VISIBLE_DEVICES, so a container mask
+# (e.g. ROCR_VISIBLE_DEVICES=-1) would hide a GPU that the env-independent KFD
+# detection still sees -- the tool probes run with the masks cleared. Prints the
+# gfx token(s) or nothing when unreadable, and always returns 0 (a failing probe
+# as the last command would trip set -e in callers' assignments). Shared by
+# get_torch_index_url's gfx gate and the runtime-less reroute gate so the two
+# can never disagree on what "readable" means.
+_probe_amd_gfx_arch() {
+    _ensure_rocm_probe_env
+    _pg=$(printf '%s' "${UNSLOTH_ROCM_GFX_ARCH:-}" | tr '[:upper:]' '[:lower:]')
+    if [ -z "$_pg" ] && command -v rocminfo >/dev/null 2>&1; then
+        _pg=$( (unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES; rocminfo 2>/dev/null) | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
+    fi
+    if [ -z "$_pg" ] && command -v amd-smi >/dev/null 2>&1; then
+        _pg=$( (unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES; amd-smi list 2>/dev/null) | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
+        if [ -z "$_pg" ]; then
+            _pg=$( (unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES; amd-smi static --asic 2>/dev/null) | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
+        fi
+    fi
+    printf '%s\n' "$_pg"
+}
+
 # ── Detect GPU and choose PyTorch index URL ──
 # Mirrors Get-TorchIndexUrl in install.ps1.
 # On CPU-only machines this returns the cpu index, avoiding the solver
@@ -2180,6 +2384,29 @@ get_torch_index_url() {
         if ! _has_amd_rocm_gpu; then
             echo "$_base/cpu"; return
         fi
+        # A generic rocm index is only safe when the gfx arch is readable: the
+        # Strix reroute (gfx1150/1151 -> arch-specific index) learns gfx from
+        # rocminfo/amd-smi, so if those are missing OR do not enumerate the GPU, an
+        # unknown-arch box might be Strix and would get the broken _grouped_mm
+        # wheels. Probe via the shared helper (override first, then rocminfo/amd-smi
+        # with visibility masks cleared); if the arch is unreadable, never guess a
+        # rocm index. A KFD-only host whose arch is still inferable from hardware
+        # IDs (PCI/cpuinfo/lspci) returns the cpu index and lets the runtime-less
+        # reroute below upgrade it to AMD per-arch wheels -- the reroute gate uses
+        # this same probe, so the handoff can't misfire. Only when inference fails
+        # too is CPU final, with the actionable warning.
+        _amd_gfx_probe=$(_probe_amd_gfx_arch)
+        if [ -z "$_amd_gfx_probe" ]; then
+            if _amd_inferred_gfx=$(_infer_linux_amd_gfx_arch 2>/dev/null) && \
+               [ -n "$_amd_inferred_gfx" ] && \
+               _amd_arch_index_family_for_gfx "$_amd_inferred_gfx" >/dev/null 2>&1; then
+                echo "[WARN] AMD GPU detected but rocminfo/amd-smi can't read its gfx arch -- inferring $_amd_inferred_gfx from hardware IDs." >&2
+                echo "$_base/cpu"; return
+            fi
+            echo "[WARN] AMD GPU detected but its gfx arch can't be read (rocminfo/amd-smi missing or not enumerating the GPU) -- installing CPU-only PyTorch." >&2
+            echo "[WARN] For GPU PyTorch, install or repair rocminfo/amd-smi (e.g. sudo pacman -S rocm-hip-sdk) and re-run this installer." >&2
+            echo "$_base/cpu"; return
+        fi
         # AMD GPU confirmed -- detect ROCm version
         _rocm_tag=""
         _rocm_tag=$({ command -v amd-smi >/dev/null 2>&1 && \
@@ -2196,7 +2423,11 @@ get_torch_index_url() {
             { command -v rpm >/dev/null 2>&1 && \
                 ver="$(rpm -q --qf '%{VERSION}\n' rocm-core 2>/dev/null)" && \
                 [ -n "$ver" ] && \
-                printf '%s\n' "$ver" | awk -F'[.-]' '{print "rocm"$1"."$2; exit}'; }) 2>/dev/null
+                printf '%s\n' "$ver" | awk -F'[.-]' '{print "rocm"$1"."$2; exit}'; }) 2>/dev/null || _rocm_tag=""
+        # ^ || guard: when EVERY version source is missing (e.g. rocminfo present
+        # but rocm-core not installed, so dpkg-query/rpm exit 1), the whole ||
+        # chain fails and set -e would kill the installer BEFORE the actionable
+        # no-version WARN below -- exactly the fresh-install case it exists for.
         # Validate _rocm_tag: must match "rocmX.Y" with major >= 1
         case "$_rocm_tag" in
             rocm[1-9]*.[0-9]*) : ;;  # valid (major >= 1)
@@ -2232,12 +2463,27 @@ get_torch_index_url() {
             esac
             return
         fi
-        # AMD GPU confirmed by rocminfo/amd-smi but ROCm version could not be
-        # read from any source (amd-smi, /opt/rocm/.info/version, hipconfig,
-        # dpkg, rpm).  Warn explicitly rather than silently installing CPU PyTorch.
-        echo "[WARN] AMD GPU detected but ROCm version could not be determined -- falling back to CPU-only PyTorch" >&2
-        echo "[WARN] Ensure one of the following is accessible: amd-smi, hipconfig, /opt/rocm/.info/version, rocm-core package" >&2
-        echo "[WARN] To install ROCm: https://rocm.docs.amd.com/en/latest/deploy/linux/index.html" >&2
+        # AMD GPU confirmed (rocminfo/amd-smi or the KFD topology fallback) but
+        # no ROCm/HIP install was found to read the version from (amd-smi,
+        # /opt/rocm/.info/version, hipconfig, dpkg, rpm). This is the common
+        # fresh-install case: the GPU is real, but with no ROCm userspace the
+        # correct PyTorch build can't be selected. Warn with an actionable fix
+        # rather than silently installing CPU PyTorch.
+        # A user-set UNSLOTH_ROCM_GFX_ARCH seeded the probe above, so rocminfo/
+        # amd-smi may still be unable to see the GPU; when the named arch maps to
+        # a wheel family, the runtime-less reroute (gated on the override) will
+        # install the AMD per-arch wheels -- a CPU-only warning here would be
+        # false for that path. Defer like the inferable-arch branch does.
+        if [ -n "${UNSLOTH_ROCM_GFX_ARCH:-}" ] && \
+           _amd_arch_index_family_for_gfx "$_amd_gfx_probe" >/dev/null 2>&1; then
+            echo "[WARN] AMD GPU detected with no readable ROCm version, but UNSLOTH_ROCM_GFX_ARCH=$_amd_gfx_probe is set -- routing to AMD per-arch wheels." >&2
+            echo "$_base/cpu"; return
+        fi
+        echo "[WARN] AMD GPU detected, but no ROCm/HIP install was found to select the matching GPU PyTorch build -- falling back to CPU-only PyTorch." >&2
+        echo "[WARN] Install the ROCm/HIP SDK, then re-run this installer:" >&2
+        echo "[WARN]   Arch / CachyOS : sudo pacman -S rocm-hip-sdk" >&2
+        echo "[WARN]   other distros  : https://rocm.docs.amd.com/en/latest/deploy/linux/index.html" >&2
+        echo "[WARN] Minimum required for version detection: amd-smi, hipconfig, /opt/rocm/.info/version, or the rocm-core package." >&2
         echo "$_base/cpu"; return
     fi
     # Parse CUDA version from nvidia-smi output (POSIX-safe, no grep -P).
@@ -2649,7 +2895,7 @@ _maybe_bootstrap_rocm_wsl() {
     [ -e /dev/dxg ] || return 0
     # Strix APUs show in /proc/cpuinfo (the CPU model); discrete cards don't, so also
     # ask the Windows host. Either signal suffices; the bootstrap detects arch from rocminfo.
-    if ! grep -qiE 'Ryzen AI Max|Radeon 80[0-9]0S|Strix Halo' /proc/cpuinfo 2>/dev/null \
+    if ! grep -qiE 'Ryzen AI Max|Radeon 80[0-9][05]S|Strix Halo' /proc/cpuinfo 2>/dev/null \
        && ! _wsl_amd_gpu_name >/dev/null 2>&1; then
         return 0
     fi
@@ -2735,6 +2981,72 @@ fi
 
 TORCH_INDEX_URL=$(get_torch_index_url)
 
+# Linux: ROCm runtime missing but a supported AMD gfx arch is inferable (Strix Halo
+# in /proc/cpuinfo, lspci marketing name, UNSLOTH_ROCM_GFX_ARCH). Route to AMD's
+# per-arch wheels like install.ps1 does on Windows (unslothai#7301).
+# Gated on the runtime probes NOT naming a gfx: either no AMD GPU is detected at
+# all (_has_amd_rocm_gpu false), or the GPU is visible only through the
+# env-independent KFD topology while rocminfo/amd-smi can't read its arch
+# (KFD-only host, unslothai#7314 -- before the KFD detection fix these hosts
+# reached this reroute via the false branch, so the empty-probe condition
+# preserves that routing). A */cpu index chosen WITH a readable gfx
+# (unsupported/unreadable ROCm version, after its own warning) is a deliberate
+# fallback -- rerouting it would contradict that decision, and stays excluded
+# because the shared probe returns its gfx. An explicit UNSLOTH_ROCM_GFX_ARCH
+# override stays authoritative either way.
+if [ "$_torch_index_pinned" = false ] && [ "$SKIP_TORCH" = false ] && \
+   ! _has_usable_nvidia_gpu && \
+   { [ -n "${UNSLOTH_ROCM_GFX_ARCH:-}" ] || ! _has_amd_rocm_gpu || \
+     [ -z "$(_probe_amd_gfx_arch)" ]; } && \
+   case "$(uname -s)" in Linux) true ;; *) false ;; esac && \
+   case "$_ARCH" in x86_64|amd64) true ;; *) false ;; esac; then
+    # ROCm torch wheels are x86_64-only; get_torch_index_url returns CPU on other
+    # arches, so an inferred/overridden gfx must not reroute arm64 to AMD wheels.
+    case "$TORCH_INDEX_URL" in
+        */cpu)
+            _linux_inferred_gfx=$(_infer_linux_amd_gfx_arch 2>/dev/null || true)
+            if [ -n "$_linux_inferred_gfx" ]; then
+                _amd_family=$(_amd_arch_index_family_for_gfx "$_linux_inferred_gfx") || _amd_family=""
+                if [ -n "$_amd_family" ]; then
+                    _amd_mirror="${UNSLOTH_AMD_ROCM_MIRROR:-https://repo.amd.com/rocm/whl}"
+                    while [ "${_amd_mirror%/}" != "$_amd_mirror" ]; do
+                        _amd_mirror="${_amd_mirror%/}"
+                    done
+                    TORCH_INDEX_URL="${_amd_mirror}/${_amd_family}/"
+                    # Hand the inferred arch to setup.sh (llama.cpp): it re-probes
+                    # ROCm on its own, and on these runtime-less hosts its probes
+                    # find nothing, so without this it classifies the box as
+                    # non-ROCm and installs the CPU prebuilt while torch just got
+                    # AMD per-arch wheels. setup.sh and install_llama_prebuilt.py
+                    # both honor UNSLOTH_ROCM_GFX_ARCH, so exporting it is the
+                    # whole handoff (a user-set override re-exports unchanged).
+                    export UNSLOTH_ROCM_GFX_ARCH="$_linux_inferred_gfx"
+                    case "$_linux_inferred_gfx" in
+                        gfx1201|gfx1200|gfx1151|gfx1150)
+                            TORCH_CONSTRAINT="torch>=2.11.0,<2.12.0"
+                            TORCHVISION_CONSTRAINT="torchvision>=0.26.0,<0.27.0"
+                            TORCHAUDIO_CONSTRAINT="torchaudio>=2.11.0,<2.12.0"
+                            ;;
+                    esac
+                    echo "" >&2
+                    # KFD-only hosts reach this reroute with /dev/kfd present
+                    # (that's what detected them), so don't claim it's missing.
+                    if _has_amd_rocm_gpu; then
+                        echo "  [WARN] AMD GPU visible via the kernel driver (KFD) but rocminfo/amd-smi can't read its gfx arch; using $_linux_inferred_gfx." >&2
+                    else
+                        echo "  [WARN] ROCm runtime not visible (/dev/kfd, rocminfo, amd-smi) but $_linux_inferred_gfx inferred." >&2
+                    fi
+                    echo "  [WARN] Routing to AMD arch-specific wheels ($(_strip_index_url_credentials "$TORCH_INDEX_URL"))." >&2
+                    echo "  [WARN] These wheels bundle their own ROCm runtime; install the kernel stack for native compute:" >&2
+                    echo "  [WARN]   https://docs.unsloth.ai/get-started/install-and-update/amd" >&2
+                    echo "  [WARN] Tip: set UNSLOTH_ROCM_GFX_ARCH=$_linux_inferred_gfx to skip inference next time." >&2
+                    echo "" >&2
+                fi
+            fi
+            ;;
+    esac
+fi
+
 # Export the resolved torch backend ("cuda", "rocm", or "cpu") so that
 # downstream scripts (setup.sh -> install_python_stack.py) know what was
 # chosen here and can skip ROCm-specific repair steps on CUDA/CPU hosts.
@@ -2818,29 +3130,64 @@ case "$TORCH_INDEX_URL" in
         fi
         ;;
 esac
-# ── Strix Halo / Strix Point: force rocm7.2 wheels, bypass Radeon repo ───────
-# gfx1151 (Strix Halo) and gfx1150 (Strix Point) have a ROCm 7.1 driver bug
-# that causes a segfault in torch._grouped_mm (moe_utils.py line 167).
-# The Radeon repo now ships cp313 wheels for rocm-rel-7.1, so when
-# _amd_gpu_radeon=true the installer silently lands on the broken combo.
-# Detect these GPUs when TORCH_INDEX_URL is rocm7.1 and override to rocm7.2.
-case "$TORCH_INDEX_URL" in
-    */rocm7.1|*/rocm7.1.*)
+# 0 when a rocmX.Y index leaf ($1, the final path segment) is older than floor
+# $2.$3 (int compare, so rocm7.2 < rocm7.13). Non-rocm leaves (gfx*, cu*, cpu) and
+# non-numeric versions return 1. Leaf-based (like $_torch_index_leaf) so a mirror
+# base holding its own rocm token compares the family leaf, not the base path.
+_rocm_leaf_below() {
+    case "$1" in rocm[0-9]*.[0-9]*) : ;; *) return 1 ;; esac
+    _rb=${1#rocm}; _maj=${_rb%%.*}; _min=${_rb#*.}; _min=${_min%%.*}
+    case "$_maj$_min" in *[!0-9]*) return 1 ;; esac
+    if [ "$_maj" -lt "$2" ]; then return 0; fi
+    if [ "$_maj" -eq "$2" ] && [ "$_min" -lt "$3" ]; then return 0; fi
+    return 1
+}
+# ── Strix Halo / Strix Point: route to the AMD arch-specific index ───────────
+# gfx1151/gfx1150 need torch 2.11+rocm7.13 from repo.amd.com/rocm/whl/gfx<arch>/,
+# which carries AMD's real fixes (the rocm7.1 _grouped_mm segfault, moe_utils.py:167,
+# and later Strix kernel bugs). Every generic pytorch.org index below rocm7.13 lacks
+# them (and the Radeon repo can be offline, unslothai#7264), so reroute a detected
+# Strix GPU whenever the picked index is older than the arch build -- covers today's
+# rocm6.0-7.2 and any future 7.x < 7.13; rocm7.13+ already has the fixes, so leave it.
+case "$_torch_index_leaf" in
+    rocm[0-9]*)
         # Collect every gfx token in rocminfo / amd-smi enumeration order
         # (skip duplicates), then index by HIP_VISIBLE_DEVICES /
         # ROCR_VISIBLE_DEVICES so a mixed Strix iGPU + non-Strix dGPU box
         # where the user selected the dGPU does NOT get rerouted to the
         # Strix per-gfx index.
-        _gfx_all=""
-        if command -v rocminfo >/dev/null 2>&1; then
-            _gfx_all=$(rocminfo 2>/dev/null | grep -oE 'gfx[1-9][0-9a-z]{2,3}')
+        # || true on each probe: no gfx match makes grep exit 1, which under
+        # set -euo pipefail would abort the installer before the next fallback
+        # runs (now that the case matches every rocm* index, not just rocm7.1).
+        # A user-supplied UNSLOTH_ROCM_GFX_ARCH overrides probing (mirrors setup.sh
+        # and the display block), so a Strix override still reaches the arch index.
+        _gfx_all=$(printf '%s' "${UNSLOTH_ROCM_GFX_ARCH:-}" | tr '[:upper:]' '[:lower:]')
+        if [ -z "$_gfx_all" ] && command -v rocminfo >/dev/null 2>&1; then
+            _gfx_all=$(rocminfo 2>/dev/null | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
         fi
         if [ -z "$_gfx_all" ] && command -v amd-smi >/dev/null 2>&1; then
-            _gfx_all=$(amd-smi list 2>/dev/null | grep -oE 'gfx[1-9][0-9a-z]{2,3}')
+            _gfx_all=$(amd-smi list 2>/dev/null | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
             # PowerShell paths also probe `amd-smi static --asic`; mirror it
             # so a host with hipinfo-less amd-smi reports the gfx target.
             if [ -z "$_gfx_all" ]; then
-                _gfx_all=$(amd-smi static --asic 2>/dev/null | grep -oE 'gfx[1-9][0-9a-z]{2,3}')
+                _gfx_all=$(amd-smi static --asic 2>/dev/null | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
+            fi
+        fi
+        # get_torch_index_url reads the arch with ROCR/HIP masks cleared, so a
+        # mask hiding every agent (e.g. ROCR_VISIBLE_DEVICES=-1) still lands
+        # here on a generic rocm index; re-probe unmasked or a masked-out Strix
+        # box keeps the broken generic wheels. Partial masks never get here
+        # (they enumerate at least one agent above) and keep their selection.
+        # ${VAR+x} (not :-): a SET-but-empty mask also hides every agent and
+        # must trigger the re-probe too.
+        if [ -z "$_gfx_all" ] && [ -n "${ROCR_VISIBLE_DEVICES+x}${HIP_VISIBLE_DEVICES+x}" ]; then
+            if command -v rocminfo >/dev/null 2>&1; then
+                _gfx_all=$( (unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES; rocminfo 2>/dev/null) | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
+            fi
+            if [ -z "$_gfx_all" ] && command -v amd-smi >/dev/null 2>&1; then
+                _gfx_all=$( (unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES; amd-smi list 2>/dev/null) | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
+                [ -z "$_gfx_all" ] && \
+                    _gfx_all=$( (unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES; amd-smi static --asic 2>/dev/null) | grep -oE 'gfx[1-9][0-9a-z]{2,3}' || true)
             fi
         fi
         _runtime_gfx=""
@@ -2865,13 +3212,14 @@ case "$TORCH_INDEX_URL" in
         case "$_runtime_gfx" in
             gfx1151|gfx1150) _strix_gfx="$_runtime_gfx" ;;
         esac
-        if [ -n "$_strix_gfx" ]; then
+        # Skip rocm7.13+ generic indexes: they already ship the fixes, so the
+        # arch build (rocm7.13) would be a downgrade rather than a rescue.
+        if [ -n "$_strix_gfx" ] && _rocm_leaf_below "$_torch_index_leaf" 7 13; then
             echo "" >&2
-            echo "  [WARN] $_strix_gfx (Strix) + ROCm 7.1 detected -- known _grouped_mm segfault" >&2
-            echo "  [WARN] ROCm 7.1 wheels are broken for gfx1150/gfx1151 (moe_utils.py:167)" >&2
-            echo "  [WARN] Routing to AMD arch-specific index (torch 2.11+rocm7.13 has the real fix)" >&2
-            echo "  [WARN] Upgrade ROCm to 7.2+ to use the standard index:" >&2
-            echo "  [WARN]   https://rocm.docs.amd.com/en/latest/deploy/linux/index.html" >&2
+            echo "  [WARN] $_strix_gfx (Strix) detected -- routing to the AMD arch-specific index" >&2
+            echo "  [WARN] torch 2.11+rocm7.13 has AMD's real gfx1150/gfx1151 fixes (the ROCm 7.1" >&2
+            echo "  [WARN] _grouped_mm segfault, moe_utils.py:167, and later Strix kernel bugs)," >&2
+            echo "  [WARN] and is more reliable than the rocm7.2 index or an offline Radeon repo." >&2
             echo "" >&2
             # AMD's arch-specific index serves torch 2.11.0+rocm7.13.0 which has AMD's
             # actual fix for the gfx1151/gfx1150 _grouped_mm kernel bug -- preferred
@@ -2960,7 +3308,7 @@ elif case "$TORCH_INDEX_URL" in */rocm*|*/gfx*) true ;; *) false ;; esac; then
         case "$_gpu_disp_mkt" in
             *"9070 XT"*|*9080*)                                                                            _gpu_disp_gfx="gfx1201" ;;  # RDNA 4
             *9070*|*9060*)                                                                                 _gpu_disp_gfx="gfx1200" ;;  # RDNA 4
-            *"8060S"*|*"8050S"*|*"8040S"*|*"Strix Halo"*|*"Ryzen AI Max"*|*"AI Max"*) _gpu_disp_gfx="gfx1151" ;;  # RDNA 3.5 (Strix Halo: Radeon 8060S/8050S/8040S iGPU, Ryzen AI Max+)
+            *"8065S"*|*"8060S"*|*"8050S"*|*"8040S"*|*"Strix Halo"*|*"Ryzen AI Max"*|*"AI Max"*) _gpu_disp_gfx="gfx1151" ;;  # RDNA 3.5 (Strix Halo + Gorgon Halo: Radeon 8065S/8060S/8050S/8040S iGPU, Ryzen AI Max / Max+)
             *"890M"*|*"880M"*|*"860M"*|*"840M"*|*"Strix Point"*|*"Krackan"*|*"HX 37"*|*"AI 9 HX"*|*"AI 9 36"*|*"AI 7 35"*|*"AI 5 34"*|*"AI 7 PRO 35"*|*"AI 5 33"*) _gpu_disp_gfx="gfx1150" ;;  # RDNA 3.5 (Strix/Krackan Point: Radeon 890M/880M iGPU, Ryzen AI 9 HX 370/375)
             *"RX 7600"*|*"RX 7700S"*|*"RX 7650"*|*"PRO W7600"*|*"PRO W7500"*|*"PRO V710"*)                  _gpu_disp_gfx="gfx1102" ;;  # RDNA 3 (Navi 33)
             *"RX 7900"*|*"RX 7800"*|*"RX 7700"*|*"PRO W7900"*|*"PRO W7800"*|*"PRO W7700"*)                  _gpu_disp_gfx="gfx1100" ;;  # RDNA 3 desktop / workstation (Navi 31)
@@ -2995,6 +3343,17 @@ elif case "$TORCH_INDEX_URL" in */rocm*|*/gfx*) true ;; *) false ;; esac; then
 elif [ "$OS" = "macos" ] && [ "$_ARCH" = "arm64" ]; then
     # Apple Silicon: PyTorch gets Metal (MPS) acceleration over unified memory, so not CPU-only.
     step "gpu" "Apple Silicon (Metal, unified memory)"
+elif _has_amd_rocm_gpu; then
+    if [ "$_torch_index_pinned" = true ]; then
+        # An explicit UNSLOTH_TORCH_INDEX_URL/_FAMILY pin skipped all probing;
+        # do not claim ROCm is unusable when a CPU/other index was requested.
+        step "gpu" "AMD GPU (torch index pinned: $_torch_index_leaf)" "$C_WARN"
+    else
+        # AMD GPU visible to the kernel but the torch index stayed CPU: no usable
+        # ROCm userspace to pick a wheel. "none" would repeat the false diagnosis
+        # this installer used to give.
+        step "gpu" "AMD GPU (no usable ROCm -- CPU fallback)" "$C_WARN"
+    fi
 else
     step "gpu" "none (CPU-only)" "$C_WARN"
 fi
@@ -3003,8 +3362,17 @@ fi
 case "$TORCH_INDEX_URL" in
     */cpu)
         if [ "$SKIP_TORCH" = false ] && [ "$OS" != "macos" ]; then
-            substep "No GPU detected -- installing CPU-only PyTorch." "$C_WARN"
-            if [ "$OS" = "wsl" ]; then
+            if [ "$_torch_index_pinned" = true ]; then
+                # An explicit CPU pin is a request, not a detection failure:
+                # skip the SDK guidance (ROCm may be perfectly healthy here).
+                substep "CPU-only PyTorch (index pinned via UNSLOTH_TORCH_INDEX_URL / _FAMILY)."
+            elif _has_amd_rocm_gpu; then
+                substep "AMD GPU detected, but no usable ROCm/HIP install -- installing CPU-only PyTorch." "$C_WARN"
+                substep "Install the ROCm/HIP SDK and re-run this installer for GPU PyTorch." "$C_WARN"
+            else
+                substep "No GPU detected -- installing CPU-only PyTorch." "$C_WARN"
+            fi
+            if [ "$OS" = "wsl" ] && [ "$_torch_index_pinned" = false ]; then
                 # WSL + no GPU detected (detection above found nothing). Common
                 # cause: an AMD GPU whose ROCm-on-WSL runtime isn't exposed yet --
                 # /dev/dxg present (graphics) but no ROCm runtime.
@@ -3031,6 +3399,13 @@ case "$TORCH_INDEX_URL" in
                 substep "  driver is current; or run unsloth/scripts/install_rocm_wsl_strixhalo.sh yourself."
             else
                 substep "AMD ROCm users: see https://docs.unsloth.ai/get-started/install-and-update/amd"
+                # Only when ROCm truly can't see the GPU: a detected-but-too-old
+                # ROCm (rocminfo works, wheels need 6.0+) has its own guidance.
+                if ! _has_amd_rocm_gpu && _amd_gpu_present_via_pci; then
+                    substep "An AMD GPU is on the PCI bus but ROCm cannot see it (no /dev/kfd," "$C_WARN"
+                    substep "  rocminfo, or amd-smi). Install the ROCm kernel stack so /dev/kfd exists;"
+                    substep "  Strix Halo (gfx1151/gfx1150) needs a recent kernel (6.11+) and ROCm 7.x."
+                fi
             fi
             substep "Re-run with --no-torch for GGUF-only (faster, no PyTorch):"
             substep "  curl -fsSL https://unsloth.ai/install.sh | sh -s -- --no-torch"
@@ -3096,7 +3471,7 @@ if [ "$_MIGRATED" = true ]; then
         # to prevent transitive torch resolution.
         run_install_cmd_retry "install unsloth (migrated no-torch)" uv pip install --python "$_VENV_PY" --no-deps \
             --reinstall-package unsloth --reinstall-package unsloth-zoo \
-            "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3"
+            "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4"
         # Resolve pydantic WITH deps so pip pins pydantic-core to the
         # matching version (no-torch-runtime.txt below is --no-deps).
         # All transitive deps are torch-free.
@@ -3113,7 +3488,7 @@ if [ "$_MIGRATED" = true ]; then
         run_install_cmd_retry "install unsloth (migrated)" uv pip install --python "$_VENV_PY" \
             ${_UNSLOTH_TORCH_OVERRIDES:+--overrides "$_UNSLOTH_TORCH_OVERRIDES"} \
             --reinstall-package unsloth --reinstall-package unsloth-zoo \
-            "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3" ${_MLX_LM_EXCLUDE_ARG:-}
+            "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4" ${_MLX_LM_EXCLUDE_ARG:-}
         [ -n "$_UNSLOTH_TORCH_OVERRIDES" ] && rm -f "$_UNSLOTH_TORCH_OVERRIDES"
         _UNSLOTH_TORCH_OVERRIDES=""
     fi
@@ -3337,7 +3712,7 @@ elif [ -n "$TORCH_INDEX_URL" ]; then
         # runtime deps (typer, safetensors, transformers, etc.) with --no-deps.
         run_install_cmd_retry "install unsloth (no-torch)" uv pip install --python "$_VENV_PY" --no-deps \
             --upgrade-package unsloth --upgrade-package unsloth-zoo \
-            "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3"
+            "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4"
         # Same pydantic-with-deps trick as the migrated branch.
         run_install_cmd_retry "install pydantic (with deps for compatible core)" \
             uv pip install --python "$_VENV_PY" pydantic
@@ -3356,7 +3731,7 @@ elif [ -n "$TORCH_INDEX_URL" ]; then
     elif [ "$STUDIO_LOCAL_INSTALL" = true ]; then
         run_install_cmd_retry "install unsloth (local)" uv pip install --python "$_VENV_PY" \
             ${_UNSLOTH_TORCH_OVERRIDES:+--overrides "$_UNSLOTH_TORCH_OVERRIDES"} \
-            --upgrade-package unsloth "unsloth>=2026.7.3" "unsloth-zoo>=2026.7.3"
+            --upgrade-package unsloth "unsloth>=2026.7.4" "unsloth-zoo>=2026.7.4"
         substep "overlaying local repo (editable)..."
         run_install_cmd "overlay local repo" uv pip install --python "$_VENV_PY" -e "$_REPO_ROOT" --no-deps
         substep "overlaying unsloth-zoo from git main..."
@@ -3384,7 +3759,7 @@ else
     tauri_log "STEP" "Installing Unsloth"
     substep "installing unsloth (this may take a few minutes)..."
     if [ "$STUDIO_LOCAL_INSTALL" = true ]; then
-        run_install_cmd_retry "install unsloth (auto torch backend)" uv pip install --python "$_VENV_PY" "unsloth-zoo>=2026.7.3" "unsloth>=2026.7.3" --torch-backend=auto
+        run_install_cmd_retry "install unsloth (auto torch backend)" uv pip install --python "$_VENV_PY" "unsloth-zoo>=2026.7.4" "unsloth>=2026.7.4" --torch-backend=auto
         substep "overlaying local repo (editable)..."
         run_install_cmd "overlay local repo" uv pip install --python "$_VENV_PY" -e "$_REPO_ROOT" --no-deps
         substep "overlaying unsloth-zoo from git main..."
@@ -3396,6 +3771,15 @@ else
     fi
 fi
 
+_installed_package_version=$("$_VENV_PY" -c \
+    'from importlib.metadata import version; import sys; print(version(sys.argv[1]))' \
+    "$PACKAGE_NAME" 2>/dev/null || true)
+if [ -n "$_installed_package_version" ]; then
+    step "$PACKAGE_NAME" "$_installed_package_version installed"
+else
+    substep "[WARN] installed $PACKAGE_NAME version could not be determined" "$C_WARN"
+fi
+
 # ── Enforce the installed torch flavor matches the detected GPU build ──
 # PEP 440 ignores the +cpu/+cuXXX/+rocm local label in a version range, so uv
 # keeps a stale torch==X+cpu against a GPU index and the venv silently trains on
diff --git a/scripts/build_whisper_cpp.sh b/scripts/build_whisper_cpp.sh
new file mode 100755
index 0000000000..9f7e4d4ef3
--- /dev/null
+++ b/scripts/build_whisper_cpp.sh
@@ -0,0 +1,71 @@
+#!/bin/sh
+# Build whisper.cpp's whisper-server for Studio's GGUF dictation engine.
+#
+# Installs into the managed Studio home so the backend's binary discovery
+# (core/inference/stt_ggml_sidecar.py::find_whisper_server_binary) picks it up:
+#   <UNSLOTH_STUDIO_HOME>/whisper.cpp/build/bin/whisper-server   (custom home)
+#   ~/.unsloth/whisper.cpp/build/bin/whisper-server              (default)
+#
+# Usage:
+#   ./scripts/build_whisper_cpp.sh              # build the pinned tag
+#   WHISPER_CPP_TAG=v1.9.0 ./scripts/build_whisper_cpp.sh
+#
+# Requires: git, cmake, a C/C++ toolchain (the same prerequisites as a
+# llama.cpp source build). GPU backends are auto-detected by whisper.cpp's
+# CMake (Metal on macOS; set GGML_CUDA=1 to force a CUDA build on Linux).
+
+set -eu
+
+WHISPER_CPP_SOURCE="${WHISPER_CPP_SOURCE:-https://github.com/ggml-org/whisper.cpp}"
+WHISPER_CPP_TAG="${WHISPER_CPP_TAG:-v1.9.1}"
+
+STUDIO_HOME="${UNSLOTH_STUDIO_HOME:-${STUDIO_HOME:-}}"
+CUSTOM_STUDIO_HOME=false
+if [ -n "$STUDIO_HOME" ]; then
+    CUSTOM_STUDIO_HOME=true
+    INSTALL_DIR="$STUDIO_HOME/whisper.cpp"
+else
+    INSTALL_DIR="$HOME/.unsloth/whisper.cpp"
+fi
+
+command -v git >/dev/null 2>&1 || { echo "ERROR: git is required" >&2; exit 1; }
+command -v cmake >/dev/null 2>&1 || { echo "ERROR: cmake is required" >&2; exit 1; }
+
+# Same policy as studio/setup.sh's _assert_studio_owned_or_absent: never delete
+# a directory under a custom Studio home unless Studio itself created it (the
+# marker file below). Protects a user-managed whisper.cpp/src from rm -rf.
+STUDIO_OWNED_MARKER=".unsloth-studio-owned"
+if [ "$CUSTOM_STUDIO_HOME" = true ] && [ -e "$INSTALL_DIR" ] && \
+   [ ! -f "$INSTALL_DIR/$STUDIO_OWNED_MARKER" ]; then
+    echo "ERROR: $INSTALL_DIR already exists and is not marked as an Unsloth-owned whisper.cpp build tree." >&2
+    echo "       Move it aside or choose an empty UNSLOTH_STUDIO_HOME before re-running." >&2
+    exit 1
+fi
+
+echo "==> Building whisper.cpp ($WHISPER_CPP_TAG) into $INSTALL_DIR"
+mkdir -p "$INSTALL_DIR"
+: > "$INSTALL_DIR/$STUDIO_OWNED_MARKER"
+
+if [ ! -d "$INSTALL_DIR/src/.git" ]; then
+    rm -rf "$INSTALL_DIR/src"
+    git clone --depth 1 --branch "$WHISPER_CPP_TAG" "$WHISPER_CPP_SOURCE" "$INSTALL_DIR/src"
+else
+    git -C "$INSTALL_DIR/src" fetch --depth 1 origin "$WHISPER_CPP_TAG"
+    git -C "$INSTALL_DIR/src" checkout FETCH_HEAD
+fi
+
+CMAKE_FLAGS="-DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=OFF"
+if [ "${GGML_CUDA:-0}" = "1" ]; then
+    CMAKE_FLAGS="$CMAKE_FLAGS -DGGML_CUDA=ON"
+fi
+
+# shellcheck disable=SC2086
+cmake -S "$INSTALL_DIR/src" -B "$INSTALL_DIR/src/build" $CMAKE_FLAGS
+NCPU="$(getconf _NPROCESSORS_ONLN 2>/dev/null || echo 4)"
+cmake --build "$INSTALL_DIR/src/build" --config Release --target whisper-server -j"$NCPU"
+
+mkdir -p "$INSTALL_DIR/build/bin"
+cp "$INSTALL_DIR/src/build/bin/whisper-server" "$INSTALL_DIR/build/bin/whisper-server"
+
+echo "==> Installed $INSTALL_DIR/build/bin/whisper-server"
+"$INSTALL_DIR/build/bin/whisper-server" --help >/dev/null 2>&1 && echo "==> Binary runs OK"
diff --git a/scripts/scan_packages_baseline.json b/scripts/scan_packages_baseline.json
index 1f7bc8dcc0..65b8d2b11c 100644
--- a/scripts/scan_packages_baseline.json
+++ b/scripts/scan_packages_baseline.json
@@ -1545,6 +1545,78 @@
       "severity": "HIGH",
       "evidence": "Obfusc: L836:         code = compile(module, \"<werkzeug routing>\", \"exec\")\nExec: L736:         exec(code, globs, locs)",
       "evidence_hash": "5c0992c90f05c772abd94d00784f157de337e1f8567f8b3aee1b15e46c96cd5d"
+    },
+    {
+      "package": "unsloth-zoo",
+      "file": "tests/test_mlx_save_export_regressions.py",
+      "check": "Writes to /tmp and executes (staged dropper)",
+      "severity": "CRITICAL",
+      "evidence": "L165:         temporary_location=\"/tmp/ignored\", sha256:ab5c587f9ec31a0cc10ee55698ab133a417148d9d3f371bbc81b1e13fa119c13",
+      "evidence_hash": "93a11159147aad94f353ec4d2e0b8486b256abef88cd96d741813222cd32b138"
+    },
+    {
+      "package": "unsloth-zoo",
+      "file": "tests/test_vision_collator_audio.py",
+      "check": "Writes to /tmp and executes (staged dropper)",
+      "severity": "CRITICAL",
+      "evidence": "L111:         out = extract_audio_info(msgs({\"type\": \"audio\", key: \"/tmp/a.wav\"})) sha256:2efe23ffbe2b91b8403aec9b700736919b59e5ca770f8e1f5501651b44b7d398",
+      "evidence_hash": "d416b79dd17b24214f3f7653ac01354507d7bf0fc464dee30a4a4b8998f063ba"
+    },
+    {
+      "package": "openai",
+      "file": "openai/_base_client.py",
+      "check": "C2 polling/beaconing loop detected",
+      "severity": "CRITICAL",
+      "evidence": "L274:         while True: sha256:90a38e5c1e26893c7c273354143612640e9a9c0f079d3e2b60612d79f24e80a6",
+      "evidence_hash": "1022e8e8649436ec64a98a9d9141d085452c49549fd2157b0278fc369a83ac66"
+    },
+    {
+      "package": "openai",
+      "file": "openai/auth/_workload.py",
+      "check": "Accesses cloud metadata/IMDS AND makes network calls",
+      "severity": "CRITICAL",
+      "evidence": "IMDS: L97:             url = \"http://169.254.169.254/metadata/identity/oauth2/token\" | L150:             url = \"http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/identity\"\nNetwork: L78:     http_client: httpx.Client | None = None, | L109:                 with httpx.Client() as client: | L134:     http_client: httpx.Client | None = None, | L156:                 with httpx.Client() as client: | L251:         exchange_client = DefaultHttpx2Client(follow_redirects=False) if self._use_httpx2 else httpx.Client()",
+      "evidence_hash": "9717e51cb961dc14c458955d91a1e48e3753997346ecea0106bded3a8d64bfe0"
+    },
+    {
+      "package": "openai",
+      "file": "openai/resources/beta/responses/responses.py",
+      "check": "C2 polling/beaconing loop detected",
+      "severity": "CRITICAL",
+      "evidence": "L4000:         while True: sha256:f8ab538118daba9ec06e27399dbdc90a4521c3390e6a47a6348a1f180a83effd",
+      "evidence_hash": "31481ea83c687acc27144d72d3832d4fb98dd1c79fb5e0ddd85080de95997b9f"
+    },
+    {
+      "package": "openai",
+      "file": "openai/resources/realtime/realtime.py",
+      "check": "C2 polling/beaconing loop detected",
+      "severity": "CRITICAL",
+      "evidence": "L311:         while True: sha256:5b63313072aae9ca28677e03426513ccf12221e4f4e0ea6c31efbe09790633b5",
+      "evidence_hash": "05e1af469d651b51673763a7c4cdf759af9472fb627b7b470adc28cc237bd650"
+    },
+    {
+      "package": "openai",
+      "file": "openai/resources/responses/responses.py",
+      "check": "C2 polling/beaconing loop detected",
+      "severity": "CRITICAL",
+      "evidence": "L3951:         while True: sha256:d68ef896bf0743ca430cfacb9a3353da1f3b9c51c3a21b6450a07a32b55aa2ac",
+      "evidence_hash": "160eecdd79b521bffbe8476f782b69a0724c35d1b19376a7600807165fd54f9f"
+    },
+    {
+      "package": "unsloth-zoo",
+      "file": "tests/test_gemma4_forced_float32_ple_dtype.py",
+      "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval",
+      "severity": "HIGH",
+      "evidence": "Obfusc: L277:     compile(rewritten + _GEMMA4_PLE_CAST_HELPER, \"<gemma4-ple-generated>\", \"exec\") | L440:     compile(on, \"<gemma4-ple-append>\", \"exec\") | L468:     compile(generated, \"<gemma4-ple-crosspath>\", \"exec\")\nExec: L19:     exec(_GEMMA4_PLE_CAST_HELPER, namespace)",
+      "evidence_hash": "a85e24d8e7c431563cbd83b70f91a3b971abde0f37083d68e70984147960cc70"
+    },
+    {
+      "package": "unsloth-zoo",
+      "file": "tests/test_vision_collator_audio.py",
+      "check": "Writes to /tmp and executes (staged dropper)",
+      "severity": "CRITICAL",
+      "evidence": "L111:         out = extract_audio_info(msgs({\"type\": \"audio\", key: \"/tmp/a.wav\"})) sha256:022f81dd21acfc6a35a058de96132834c218404a9e37b3d09a7768a8c8f6c728",
+      "evidence_hash": "2d1e75446af120d9133a42aa8af426a839d3434d9dc109cc1d6c1b22ca1ddb75"
     }
   ]
 }
diff --git a/studio/backend/auth/terminal_prompt.py b/studio/backend/auth/terminal_prompt.py
index e855f4078b..925404f47d 100644
--- a/studio/backend/auth/terminal_prompt.py
+++ b/studio/backend/auth/terminal_prompt.py
@@ -236,6 +236,10 @@ def prompt_for_password_change(
                 out.write(f"Password must be at least {min_length} characters; try again.\n")
                 out.flush()
                 continue
+            if any(ch.isspace() for ch in new_password):
+                out.write("Password cannot contain spaces; try again.\n")
+                out.flush()
+                continue
             if is_current_password(new_password):
                 out.write(
                     "New password must differ from the current bootstrap password; try again.\n"
diff --git a/studio/backend/cloudflare_tunnel.py b/studio/backend/cloudflare_tunnel.py
index b1ddc74c32..78fce0c70a 100644
--- a/studio/backend/cloudflare_tunnel.py
+++ b/studio/backend/cloudflare_tunnel.py
@@ -20,6 +20,7 @@ import shutil
 import subprocess
 import sys
 import threading
+import time
 from pathlib import Path
 from typing import Optional, Tuple
 
@@ -40,6 +41,22 @@ _RELEASE_BASE = "https://github.com/cloudflare/cloudflared/releases/latest/downl
 _READY_TIMEOUT = 15.0  # seconds to wait for the URL + a registered edge connection
 _DOWNLOAD_TIMEOUT = 60  # urlopen timeout for the one-time binary download
 
+# A registered edge connection does not mean the hostname resolves yet, so the
+# URL is fetched once before it is advertised.
+_PUBLIC_PROBE_PATH = "/api/health"
+_PUBLIC_PROBE_MARKER = "Unsloth UI Backend"
+# One deadline for DNS propagation + the health probe, bounding the startup stall.
+_PUBLIC_PROBE_TIMEOUT = 45.0
+_PUBLIC_PROBE_ATTEMPT_TIMEOUT = 5.0
+_PUBLIC_PROBE_RETRY_DELAY = 1.0
+
+# Wait for the hostname via DoH first: an early OS lookup negative-caches the
+# NXDOMAIN for up to 30 min.
+_DNS_POLL_DELAY = 2.0
+# Retry transient DoH failures, but give up fast when DoH is blocked outright.
+_DNS_MAX_DOH_ERRORS = 3
+_DOH_URL = "https://cloudflare-dns.com/dns-query?name={host}&type=A"
+
 
 def _windows_hidden_kwargs() -> dict:
     """Suppress a child console window on Windows; no-op elsewhere."""
@@ -191,6 +208,59 @@ def ensure_cloudflared() -> Optional[str]:
         return None
 
 
+def _wait_for_dns(host: str, deadline: float) -> None:
+    import json
+    import urllib.request
+
+    errors = 0
+    while True:
+        answered = False
+        try:
+            req = urllib.request.Request(
+                _DOH_URL.format(host = host),
+                headers = {"Accept": "application/dns-json", "User-Agent": "unsloth-studio"},
+            )
+            with urllib.request.urlopen(req, timeout = 5) as response:
+                answered = bool(json.loads(response.read(65536)).get("Answer"))
+            errors = 0
+        except Exception:
+            errors += 1
+            if errors >= _DNS_MAX_DOH_ERRORS:
+                return
+        if answered:
+            return
+        remaining = deadline - time.monotonic()
+        if remaining <= 0:
+            return
+        time.sleep(min(_DNS_POLL_DELAY, remaining))
+
+
+def verify_public_url(url: str, timeout: float = _PUBLIC_PROBE_TIMEOUT) -> bool:
+    import json
+    import urllib.request
+    from urllib.parse import urlsplit
+
+    deadline = time.monotonic() + timeout
+    host = urlsplit(url).hostname
+    if host:
+        _wait_for_dns(host, deadline)
+
+    probe_url = f"{url.rstrip('/')}{_PUBLIC_PROBE_PATH}"
+    while True:
+        try:
+            req = urllib.request.Request(probe_url, headers = {"User-Agent": "unsloth-studio"})
+            with urllib.request.urlopen(req, timeout = _PUBLIC_PROBE_ATTEMPT_TIMEOUT) as response:
+                body = response.read(4096)
+            if json.loads(body).get("service") == _PUBLIC_PROBE_MARKER:
+                return True
+        except Exception:
+            pass
+        remaining = deadline - time.monotonic()
+        if remaining <= 0:
+            return False
+        time.sleep(min(_PUBLIC_PROBE_RETRY_DELAY, remaining))
+
+
 class CloudflareTunnel:
     """A cloudflared quick tunnel to http://localhost:<port>. Best-effort throughout.
 
@@ -322,11 +392,12 @@ def start_studio_tunnel(port: int, timeout: float = _READY_TIMEOUT) -> Optional[
     """Start a quick tunnel and return its public URL once it is actually
     serving, or None (best-effort).
 
-    Waits for cloudflared to both mint the URL and register an edge connection
-    before returning, so the caller never advertises a URL that yields Cloudflare
-    error 1033 (HTTP 530). If a URL is minted but no connection registers within
-    the window (e.g. quic is blocked on this network), retries once forcing the
-    http2 protocol. On any failure the tunnel is stopped and None is returned.
+    Waits for cloudflared to both mint the URL and register an edge connection,
+    then fetches /api/health over the public URL, so the caller never advertises
+    a link that yields Cloudflare error 1033 (HTTP 530) or an unresolvable host.
+    If a URL is minted but no connection registers within the window (e.g. quic
+    is blocked on this network), retries once forcing the http2 protocol. On any
+    failure the tunnel is stopped and None is returned.
     """
     global _active_tunnel, _shutdown_requested
     binary = ensure_cloudflared()
@@ -349,9 +420,13 @@ def start_studio_tunnel(port: int, timeout: float = _READY_TIMEOUT) -> Optional[
             prior, _active_tunnel = _active_tunnel, tunnel
         if prior is not None:
             prior.stop()
+        registered = False
         try:
             tunnel.start()
             url = tunnel.wait_for_ready(timeout)
+            registered = url is not None
+            if url and not verify_public_url(url):
+                url = None
         except Exception:
             url = None
         if url:
@@ -371,6 +446,9 @@ def start_studio_tunnel(port: int, timeout: float = _READY_TIMEOUT) -> Optional[
         # http2 will not help, so do not burn another window on it.
         if not saw_url:
             return None
+        # probe failure after registering is DNS propagation; http2 would not help
+        if registered:
+            return None
     return None
 
 
diff --git a/studio/backend/core/data_recipe/jobs/manager.py b/studio/backend/core/data_recipe/jobs/manager.py
index 0e0044702e..135c9fccf6 100644
--- a/studio/backend/core/data_recipe/jobs/manager.py
+++ b/studio/backend/core/data_recipe/jobs/manager.py
@@ -27,7 +27,6 @@ from .constants import (
 )
 from .parse import apply_update, coerce_event, parse_log_message
 from .types import Job
-from .worker import run_job_process
 from loggers import get_logger
 
 logger = get_logger(__name__)
@@ -169,12 +168,18 @@ class JobManager:
                 native_path_secret_removed_for_child_start,
                 run_without_native_path_secret,
             )
+            from utils.hf_cache_settings import child_environment_for_spawn, get_hf_cache_paths
 
-            with native_path_secret_removed_for_child_start():
+            cache_env = get_hf_cache_paths().child_env({})
+
+            with (
+                child_environment_for_spawn(cache_env),
+                native_path_secret_removed_for_child_start(),
+            ):
                 mp_q = _CTX.Queue()
                 proc = _CTX.Process(
                     target = run_without_native_path_secret,
-                    args = (run_job_process,),
+                    args = ("core.data_recipe.jobs.worker", "run_job_process", cache_env),
                     kwargs = {"event_queue": mp_q, "recipe": recipe, "run": run_payload},
                     daemon = True,
                 )
diff --git a/studio/backend/core/export/orchestrator.py b/studio/backend/core/export/orchestrator.py
index 6d1a928f2e..aaf48615f0 100644
--- a/studio/backend/core/export/orchestrator.py
+++ b/studio/backend/core/export/orchestrator.py
@@ -230,16 +230,20 @@ class ExportOrchestrator:
             native_path_secret_removed_for_child_start,
             run_without_native_path_secret,
         )
+        from utils.hf_cache_settings import child_environment_for_spawn, get_hf_cache_paths
 
-        from .worker import run_export_process
+        cache_env = get_hf_cache_paths().child_env({})
 
-        with native_path_secret_removed_for_child_start():
+        with (
+            child_environment_for_spawn(cache_env),
+            native_path_secret_removed_for_child_start(),
+        ):
             self._cmd_queue = _CTX.Queue()
             self._resp_queue = _CTX.Queue()
 
             self._proc = _CTX.Process(
                 target = run_without_native_path_secret,
-                args = (run_export_process,),
+                args = ("core.export.worker", "run_export_process", cache_env),
                 kwargs = {
                     "cmd_queue": self._cmd_queue,
                     "resp_queue": self._resp_queue,
diff --git a/studio/backend/core/inference/audio_codecs.py b/studio/backend/core/inference/audio_codecs.py
index 93c7da72cb..b59f2bcce0 100644
--- a/studio/backend/core/inference/audio_codecs.py
+++ b/studio/backend/core/inference/audio_codecs.py
@@ -76,8 +76,14 @@ class AudioCodecManager:
         if self._snac_model is not None:
             return
         from snac import SNAC
+        from utils.hf_cache_settings import active_hf_hub_cache
 
-        self._snac_model = SNAC.from_pretrained("hubertsiuzdak/snac_24khz").to(device).eval()
+        # Route weights to the selected cache; this can run in the main process.
+        self._snac_model = (
+            SNAC.from_pretrained("hubertsiuzdak/snac_24khz", cache_dir = active_hf_hub_cache())
+            .to(device)
+            .eval()
+        )
         logger.info("Loaded SNAC codec (24kHz)")
 
     def _load_bicodec(
diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index 2c7433f7a4..fc58442a79 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -247,6 +247,59 @@ def _wsl_system_rocm_lib_dirs() -> "list[str]":
     return out
 
 
+def _bundled_hip_present(binary_dir: str) -> bool:
+    """True when a prebuilt bundle ships its own HIP backend library."""
+    if not binary_dir:
+        return False
+    try:
+        # Glob the version suffix (libggml-hip.so, .so.0, .so.0.11.1) the same
+        # way the installer's runtime health check matches libggml-hip.so*.
+        return any(Path(str(binary_dir)).glob("libggml-hip.so*"))
+    except OSError:
+        return False
+
+
+def _native_linux_system_rocm_lib_dirs(binary_dir: str = "") -> "list[str]":
+    """System ROCm lib dir(s) to prepend before a prebuilt's bundled HIP, on native Linux.
+
+    The bundled bare-metal HIP runtime can mismatch the host amdkfd driver and crash
+    in hsa_init(); prepending the whole system ROCm lib dir loads a driver-matched,
+    version-consistent stack (libhsa-runtime64 / libamdhip64 / librocblas) ahead of it.
+    The whole dir is deliberate: mixing the bundle's rocBLAS with a different-version
+    system HIP/ROCR risks missing symbols. UNSLOTH_LLAMA_NO_SYSTEM_ROCM=1 keeps the pure
+    bundle (for a host whose system ROCm lacks this arch); no-op on WSL / non-Linux.
+    """
+    if os.environ.get("UNSLOTH_LLAMA_NO_SYSTEM_ROCM") == "1":
+        return []
+    if sys.platform != "linux" or os.path.exists("/dev/dxg"):
+        return []
+    if not os.path.exists("/dev/kfd"):
+        return []
+    if not _bundled_hip_present(binary_dir):
+        return []
+    # Env-configured ROCm root first; /opt/rocm only as a fallback so a stale
+    # /opt/rocm doesn't shadow the driver-matching install these vars point at.
+    candidates = []
+    for var in ("HIP_PATH", "HIP_PATH_57", "ROCM_PATH"):
+        val = os.environ.get(var)
+        if val:
+            candidates.append(val)
+    candidates.append("/opt/rocm")
+    out: "list[str]" = []
+    seen: "set[str]" = set()
+    for base in candidates:
+        for lib_sub in ("lib", "lib64"):
+            d = os.path.join(base, lib_sub)
+            if d in seen:
+                continue
+            seen.add(d)
+            if os.path.exists(os.path.join(d, "libhsa-runtime64.so")) or os.path.exists(
+                os.path.join(d, "libhsa-runtime64.so.1")
+            ):
+                out.append(d)
+    return out
+
+
 # Plan-without-action re-prompt state now lives in tool_call_parser (imported above).
 
 # Default max_tokens to the effective context when known. The floor is high
@@ -526,7 +579,14 @@ def _swa_entry_from_layer_types(lt) -> Optional[object]:
 def _fetch_swa_entry_from_hf(repo_id: str) -> Optional[object]:
     try:
         from huggingface_hub import hf_hub_download
-        cfg_path = hf_hub_download(repo_id, "config.json", repo_type = "model")
+        from utils.hf_cache_settings import active_hf_hub_cache
+
+        cfg_path = hf_hub_download(
+            repo_id,
+            "config.json",
+            repo_type = "model",
+            cache_dir = active_hf_hub_cache(),
+        )
         with open(cfg_path) as f:
             cfg = json.load(f)
     except Exception:
@@ -928,6 +988,7 @@ def _cached_hf_snapshot_file(
     filename: str,
     *,
     expected_size: Optional[int] = None,
+    cache_dir: Optional[str] = None,
 ) -> Optional[str]:
     """Return a cached snapshot file even when HF's current-ref probe misses it."""
     if not filename:
@@ -936,8 +997,22 @@ def _cached_hf_snapshot_file(
     if not parts or any(part in (".", "..") for part in parts):
         return None
     try:
-        from utils.models.model_config import _iter_hf_cache_snapshots
-        for snap in _iter_hf_cache_snapshots(repo_id):
+        if cache_dir is None:
+            from utils.models.model_config import _iter_hf_cache_snapshots
+            snapshots = _iter_hf_cache_snapshots(repo_id)
+        else:
+            from hub.utils.hf_cache_state import iter_active_repo_cache_dirs
+            snapshots = (
+                snapshot
+                for repo_dir in iter_active_repo_cache_dirs(
+                    "model",
+                    repo_id,
+                    root = Path(cache_dir),
+                )
+                for snapshot in (repo_dir / "snapshots").glob("*")
+                if snapshot.is_dir()
+            )
+        for snap in snapshots:
             candidate = snap.joinpath(*parts)
             if not candidate.is_file():
                 continue
@@ -1179,6 +1254,16 @@ def _snapshot_dir_of(path: str) -> Optional[Path]:
     return None
 
 
+def _hub_cache_dir_for_snapshot_path(path: Optional[str]) -> Optional[str]:
+    """Return the HF Hub cache root that owns a snapshot-contained path."""
+    if not path:
+        return None
+    snapshot = _snapshot_dir_of(path)
+    if snapshot is None or snapshot.parent.name != "snapshots":
+        return None
+    return str(snapshot.parent.parent.parent)
+
+
 def _companion_snapshot_sibling(
     near_path: str, pick: Callable[[list[str]], Optional[str]]
 ) -> Optional[str]:
@@ -2859,12 +2944,25 @@ class LlamaCppBackend:
         on the ordinal->physical mapping."""
         try:
             import torch
-            is_rocm = getattr(torch.version, "hip", None) is not None
+
+            # Same ROCm detection as _emit_child_gpu_visibility: AMD SDK wheels
+            # leave version.hip unset but encode "rocm" in __version__. The two
+            # must agree, else an inherited ROCR mask reads back as "no mask",
+            # ordinal 0 is labelled physical 0, and the child's new ROCR pin
+            # re-exposes the GPU the inherited mask was hiding.
+            is_rocm = (
+                getattr(torch.version, "hip", None) is not None
+                or "rocm" in getattr(torch, "__version__", "").lower()
+            )
         except Exception:
             is_rocm = False
         if is_rocm:
             hip_v = os.environ.get("HIP_VISIBLE_DEVICES")
-            rocr_v = os.environ.get("ROCR_VISIBLE_DEVICES")
+            # ROCR_VISIBLE_DEVICES is a Linux ROCr variable; Windows HIP has no
+            # ROCr layer, so a stray ROCR var there does not mask the runtime and
+            # must not be read as the ordinal->physical mapping (mirrors the
+            # Windows gate in _emit_child_gpu_visibility).
+            rocr_v = None if sys.platform == "win32" else os.environ.get("ROCR_VISIBLE_DEVICES")
             cvd = (
                 hip_v
                 if hip_v is not None
@@ -2882,20 +2980,52 @@ class LlamaCppBackend:
             return None
 
     @staticmethod
-    def _emit_child_gpu_visibility(env: dict, pinned: str) -> None:
-        """Write the child's GPU visibility mask (CUDA, plus the HIP mirror on
-        ROCm, where narrowing only CUDA_VISIBLE_DEVICES leaves an AMD child
-        seeing the full set). Do NOT also set ROCR_VISIBLE_DEVICES: ROCR and HIP
-        mask at different layers, so the same indices apply twice -- ROCR reduces
-        and re-indexes from 0, then a non-zero HIP pin points out of range, HIP
-        enumerates 0 devices, and llama.cpp falls back to CPU. The HIP mask alone
-        narrows correctly; clear any inherited ROCR mask so it can't double up."""
+    def _emit_child_gpu_visibility(
+        env: dict,
+        pinned: str,
+        *,
+        prefer_rocr: bool = False,
+    ) -> None:
+        """Write the child's GPU visibility mask: CUDA, plus a ROCm mirror on AMD
+        (masking only CUDA_VISIBLE_DEVICES leaves an AMD child seeing every GPU).
+
+        Default: HIP_VISIBLE_DEVICES, clearing any inherited ROCR mask so the two
+        can't stack (ROCR re-indexes from 0, then a non-zero HIP pin points out of
+        range, HIP sees 0 devices, and llama.cpp falls back to CPU).
+
+        prefer_rocr masks at the ROCr/HSA layer instead (clearing HIP). A HIP mask
+        filters only AFTER the HSA runtime enumerates every agent, and that
+        enumeration segfaults at startup on a GPU the build has no kernels for
+        (e.g. a gfx1103 iGPU under a gfx110X prebuilt), before llama-server logs a
+        line. ROCR drops the device at the driver layer, consuming physical ids.
+        The CPU-only sentinel ("-1") has no portable ROCR spelling, so it keeps
+        the HIP mask. Windows keeps the HIP mask too: ROCR_VISIBLE_DEVICES is a
+        Linux ROCr variable (Windows HIP has no ROCr layer), so the ROCR pin
+        would be dead there while the cleared HIP mask stops selecting."""
         env["CUDA_VISIBLE_DEVICES"] = pinned
         try:
             import torch as _torch
-            if getattr(_torch.version, "hip", None) is not None:
-                env["HIP_VISIBLE_DEVICES"] = pinned
-                env.pop("ROCR_VISIBLE_DEVICES", None)
+
+            # torch.version.hip is set on ROCm, None on CUDA; AMD SDK wheels may
+            # leave it unset but encode "rocm" in __version__ (mirrors detect_hardware).
+            if (
+                getattr(_torch.version, "hip", None) is not None
+                or "rocm" in getattr(_torch, "__version__", "").lower()
+            ):
+                if prefer_rocr and pinned != "-1" and sys.platform != "win32":
+                    env["ROCR_VISIBLE_DEVICES"] = pinned
+                    env.pop("HIP_VISIBLE_DEVICES", None)
+                    # ROCR re-indexes the visible agents from 0, and with HIP
+                    # cleared HIP honours CUDA_VISIBLE_DEVICES -- so it must carry
+                    # the post-ROCR ordinals (0..N-1), not the physical ids, else a
+                    # non-zero pick points out of range and HIP sees 0 devices (the
+                    # same stacking the default path avoids by clearing ROCR).
+                    env["CUDA_VISIBLE_DEVICES"] = ",".join(
+                        str(i) for i in range(len(pinned.split(",")))
+                    )
+                else:
+                    env["HIP_VISIBLE_DEVICES"] = pinned
+                    env.pop("ROCR_VISIBLE_DEVICES", None)
         except Exception as e:
             logger.debug("Failed to set ROCm visibility env vars for child: %s", e)
 
@@ -2930,7 +3060,21 @@ class LlamaCppBackend:
             logger.debug("Could not read reported GPU order for split pin: %s", e)
         if order is None:
             order = sorted(inherited)
-        LlamaCppBackend._emit_child_gpu_visibility(env, ",".join(str(i) for i in order))
+        # Re-emit at the layer that produced the mapping. A parent masked only
+        # via ROCR_VISIBLE_DEVICES hides agents at the driver layer, and the
+        # default HIP re-emission clears that mask -- HSA then enumerates every
+        # agent again and can segfault at startup on an unsupported GPU the
+        # parent was hiding (the crash prefer_rocr exists to avoid). Linux-only,
+        # mirroring _resolve_visible_physical_ids: on Windows a stray ROCR var
+        # is dead and was not the mapping's source.
+        prefer_rocr = (
+            sys.platform != "win32"
+            and env.get("HIP_VISIBLE_DEVICES") is None
+            and env.get("ROCR_VISIBLE_DEVICES") is not None
+        )
+        LlamaCppBackend._emit_child_gpu_visibility(
+            env, ",".join(str(i) for i in order), prefer_rocr = prefer_rocr
+        )
 
     @staticmethod
     def _amd_apu_wants_unified_memory(gpu_indices = None) -> bool:
@@ -3592,6 +3736,9 @@ class LlamaCppBackend:
             lib_dirs.extend(_wsl_system_rocm_lib_dirs())
             if lib_dirs:
                 env.setdefault("HSA_ENABLE_DXG_DETECTION", "1")
+            # Native Linux AMD: system ROCm libs before the bundle's HIP runtime,
+            # which can be incompatible with the host amdkfd driver.
+            lib_dirs.extend(_native_linux_system_rocm_lib_dirs(binary_dir))
             lib_dirs.append(binary_dir)
             _arch = platform.machine()  # x86_64, aarch64, etc.
 
@@ -4955,6 +5102,9 @@ class LlamaCppBackend:
         touching the shared one; defaults to the shared event.
         """
         cancel_event = cancel_event if cancel_event is not None else self._cancel_event
+        from utils.hf_cache_settings import get_hf_cache_paths
+
+        download_cache_dir = str(get_hf_cache_paths().hub_cache)
         try:
             import huggingface_hub  # noqa: F401 -- presence check only
         except ImportError:
@@ -5050,7 +5200,11 @@ class LlamaCppBackend:
                     if not p.size:
                         continue
                     try:
-                        cached_path = try_to_load_from_cache(hf_repo, p.path)
+                        cached_path = try_to_load_from_cache(
+                            hf_repo,
+                            p.path,
+                            cache_dir = download_cache_dir,
+                        )
                     except Exception:
                         cached_path = None
                     if (
@@ -5061,6 +5215,7 @@ class LlamaCppBackend:
                             hf_repo,
                             p.path,
                             expected_size = p.size,
+                            cache_dir = download_cache_dir,
                         )
                     if isinstance(cached_path, str) and os.path.exists(cached_path):
                         try:
@@ -5074,12 +5229,8 @@ class LlamaCppBackend:
             total_download_bytes = max(0, total_bytes - already_cached_bytes)
 
             if total_download_bytes > 0:
-                cache_dir = os.environ.get(
-                    "HF_HUB_CACHE",
-                    str(Path.home() / ".cache" / "huggingface" / "hub"),
-                )
-                Path(cache_dir).mkdir(parents = True, exist_ok = True)
-                free_bytes = shutil.disk_usage(cache_dir).free
+                Path(download_cache_dir).mkdir(parents = True, exist_ok = True)
+                free_bytes = shutil.disk_usage(download_cache_dir).free
 
                 total_gb = total_download_bytes / (1024**3)
                 free_gb = free_bytes / (1024**3)
@@ -5097,7 +5248,7 @@ class LlamaCppBackend:
                         # surface the disk shortfall for the requested variant.
                         raise RuntimeError(
                             f"Not enough disk space to download {gguf_filename}. "
-                            f"Only {free_gb:.1f} GB free in {cache_dir}"
+                            f"Only {free_gb:.1f} GB free in {download_cache_dir}"
                         )
                     smaller = self._find_smallest_fitting_variant(
                         hf_repo,
@@ -5128,7 +5279,7 @@ class LlamaCppBackend:
                     else:
                         raise RuntimeError(
                             f"Not enough disk space to download any variant. "
-                            f"Only {free_gb:.1f} GB free in {cache_dir}"
+                            f"Only {free_gb:.1f} GB free in {download_cache_dir}"
                         )
         except RuntimeError:
             raise
@@ -5151,6 +5302,7 @@ class LlamaCppBackend:
                 cancel_event = cancel_event,
                 on_status = lambda m: logger.info(m),
                 force_download = force,
+                cache_dir = download_cache_dir,
             )
             for shard in gguf_extra_shards:
                 if cancel_event.is_set():
@@ -5162,6 +5314,7 @@ class LlamaCppBackend:
                     hf_token,
                     cancel_event = cancel_event,
                     force_download = force,
+                    cache_dir = download_cache_dir,
                 )
         except Exception as e:
             if isinstance(e, RuntimeError) and "Cancelled" in str(e):
@@ -5207,6 +5360,12 @@ class LlamaCppBackend:
                 logger.info("Reusing cached %s: %s", label, cached)
                 return cached
 
+        from utils.hf_cache_settings import get_hf_cache_paths
+
+        companion_cache_dir = _hub_cache_dir_for_snapshot_path(near_path) or str(
+            get_hf_cache_paths().hub_cache
+        )
+
         if _hub_download_in_flight(hf_repo):
             logger.info("Skipping %s download while a hub download is active", label)
             return None
@@ -5241,7 +5400,7 @@ class LlamaCppBackend:
         if target is None:
             try:
                 from utils.models.model_config import _iter_hf_cache_snapshots
-                for snap in _iter_hf_cache_snapshots(hf_repo):
+                for snap in _iter_hf_cache_snapshots(hf_repo, companion_cache_dir):
                     rel_files = _gguf_snapshot_files(snap)
                     target = pick(rel_files)
                     if target is not None:
@@ -5259,7 +5418,11 @@ class LlamaCppBackend:
         # hf_hub_download with hf_repo would miss the canonical file and silently
         # drop the companion. _cached_hf_snapshot_file scans every case variant.
         if _hf_env_offline():
-            cached = _cached_hf_snapshot_file(hf_repo, target)
+            cached = _cached_hf_snapshot_file(
+                hf_repo,
+                target,
+                cache_dir = companion_cache_dir,
+            )
             if cached:
                 logger.info("Resolved %s from local HF cache: %s", label, cached)
                 return cached
@@ -5272,6 +5435,7 @@ class LlamaCppBackend:
                 target,
                 hf_token,
                 cancel_event = cancel_event,
+                cache_dir = companion_cache_dir,
             )
         except Exception as e:
             logger.warning(f"Could not download {label}: {e}")
@@ -5302,7 +5466,12 @@ class LlamaCppBackend:
             near_path = near_path,
         )
 
-    def _cached_repo_mtp_drafter(self, hf_repo: str) -> Optional[str]:
+    def _cached_repo_mtp_drafter(
+        self,
+        hf_repo: str,
+        *,
+        cache_dir: Optional[str] = None,
+    ) -> Optional[str]:
         """A drafter already in this repo's local HF cache, reused offline when a
         fresh copy can't be fetched. Prefers a repo-root ``mtp-*.gguf`` across all
         cached snapshots; else an existing ``MTP/`` copy (any precision -- the
@@ -5312,7 +5481,12 @@ class LlamaCppBackend:
 
             roots: list[Path] = []
             subdirs: list[Path] = []
-            for snap in _iter_hf_cache_snapshots(hf_repo):  # newest first
+            snapshots = (
+                _iter_hf_cache_snapshots(hf_repo)
+                if cache_dir is None
+                else _iter_hf_cache_snapshots(hf_repo, cache_dir)
+            )
+            for snap in snapshots:  # newest first
                 for f in sorted(_gguf_snapshot_files(snap)):
                     if _is_companion_gguf_path(f) and "mmproj" not in f.lower():
                         (roots if "/" not in f else subdirs).append(snap / f)
@@ -5365,7 +5539,10 @@ class LlamaCppBackend:
         # current cached file and refetch a changed one, so skip the probe here
         # rather than pair new weights with a stale draft.
         if _hf_env_offline():
-            cached = self._cached_repo_mtp_drafter(hf_repo)
+            cached = self._cached_repo_mtp_drafter(
+                hf_repo,
+                cache_dir = _hub_cache_dir_for_snapshot_path(near_path),
+            )
             if cached:
                 logger.info(f"Reusing cached MTP drafter (offline): {cached}")
                 return cached
@@ -7684,7 +7861,12 @@ class LlamaCppBackend:
                     # default FASTEST_FIRST order (#5025).
                     if gpu_ids:
                         env["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
-                    self._emit_child_gpu_visibility(env, ",".join(str(i) for i in gpu_indices))
+                    # Mask on AMD at the ROCr/HSA layer: HIP-only masking still
+                    # enumerates every agent first, which segfaults on a deselected
+                    # unsupported GPU (e.g. gfx1103 iGPU under a gfx110X prebuilt).
+                    self._emit_child_gpu_visibility(
+                        env, ",".join(str(i) for i in gpu_indices), prefer_rocr = True
+                    )
                 elif manual_tensor_split_emitted and not is_vulkan_backend:
                     # A manual per-GPU ratio across ALL GPUs (no explicit pick, so
                     # no CUDA_VISIBLE_DEVICES mask above): the UI built the
@@ -8046,6 +8228,20 @@ class LlamaCppBackend:
                             # an OS-killed text-only retry still gets the OOM message.
                             _retry_rc = self._process.poll() if self._process is not None else None
                             self._kill_process()
+                            # If the text-only retry ALSO hard-crashed (a signal, not
+                            # OOM/timeout), the vision projector was never the cause:
+                            # llama-server is faulting during GPU/driver init. Say so
+                            # -- with the ROCm fix -- instead of blaming the mmproj.
+                            if self._is_signal_crash(_retry_rc):
+                                raise RuntimeError(
+                                    "llama-server crashed at startup on both the vision "
+                                    "and text-only attempts -- a GPU driver/runtime "
+                                    "initialization crash, not a model or vision-projector "
+                                    "problem. This often means an unsupported secondary "
+                                    "GPU; on AMD/ROCm, hide it with ROCR_VISIBLE_DEVICES "
+                                    "(e.g. ROCR_VISIBLE_DEVICES=0 exposes only the first "
+                                    "GPU) before launching Unsloth Studio."
+                                )
                             raise RuntimeError(
                                 "Vision projector incompatible with this llama.cpp "
                                 "build, and the text-only retry also failed: "
diff --git a/studio/backend/core/inference/local_model_resolver.py b/studio/backend/core/inference/local_model_resolver.py
index 64ab38ec75..9e3eaeda3f 100644
--- a/studio/backend/core/inference/local_model_resolver.py
+++ b/studio/backend/core/inference/local_model_resolver.py
@@ -146,6 +146,7 @@ def _build_index() -> dict[str, _LocalGgufEntry]:
         _is_hidden_model,
     )
     from utils.paths import legacy_hf_cache_dir, hf_default_cache_dir, lmstudio_model_dirs
+    from utils.hf_cache_settings import known_hf_hub_caches
 
     index: dict[str, _LocalGgufEntry] = {}
     seen_hf: set[str] = set()
@@ -174,7 +175,12 @@ def _build_index() -> dict[str, _LocalGgufEntry]:
     except Exception as exc:
         logger.debug("auto-switch: ./models scan failed: %s", exc)
     try:
-        for hf_dir in (_resolve_hf_cache_dir(), legacy_hf_cache_dir(), hf_default_cache_dir()):
+        for hf_dir in (
+            *known_hf_hub_caches(),
+            _resolve_hf_cache_dir(),
+            legacy_hf_cache_dir(),
+            hf_default_cache_dir(),
+        ):
             found += _scan_hf_once(hf_dir)
     except Exception as exc:
         logger.debug("auto-switch: HF cache scan failed: %s", exc)
diff --git a/studio/backend/core/inference/mlx_inference.py b/studio/backend/core/inference/mlx_inference.py
index e78c93b6f3..d19c67a01a 100644
--- a/studio/backend/core/inference/mlx_inference.py
+++ b/studio/backend/core/inference/mlx_inference.py
@@ -181,19 +181,27 @@ def _vlm_messages_have_tool_history(messages):
     )
 
 
-def _build_generation_stats(prompt_n, prompt_tps, gen_n, gen_tps):
+def _build_generation_stats(
+    prompt_n,
+    prompt_tps,
+    gen_n,
+    gen_tps,
+    cached_n = 0,
+):
     """Map mlx stream stats onto the usage/timings shape llama-server emits."""
     prompt_n = int(prompt_n or 0)
     gen_n = int(gen_n or 0)
+    cached_n = int(cached_n or 0)
     prompt_tps = float(prompt_tps or 0.0)
     gen_tps = float(gen_tps or 0.0)
     prompt_ms = (prompt_n / prompt_tps * 1000.0) if prompt_tps > 0 else 0.0
     predicted_ms = (gen_n / gen_tps * 1000.0) if gen_tps > 0 else 0.0
+    total_prompt_n = prompt_n + cached_n
     return {
         "usage": {
-            "prompt_tokens": prompt_n,
+            "prompt_tokens": total_prompt_n,
             "completion_tokens": gen_n,
-            "total_tokens": prompt_n + gen_n,
+            "total_tokens": total_prompt_n + gen_n,
         },
         "timings": {
             "prompt_n": prompt_n,
@@ -204,11 +212,123 @@ def _build_generation_stats(prompt_n, prompt_tps, gen_n, gen_tps):
             "predicted_ms": predicted_ms,
             "predicted_per_token_ms": (predicted_ms / gen_n) if gen_n > 0 else 0.0,
             "predicted_per_second": gen_tps,
-            "cache_n": 0,
+            "cache_n": cached_n,
         },
     }
 
 
+PROMPT_CACHE_ENTRIES = 6
+PROMPT_CACHE_MEMORY_FRACTION = 0.15
+PROMPT_CACHE_FALLBACK_BYTES = 2 * 1024**3
+
+
+def _mlx_prompt_cache_api():
+    try:
+        from mlx_lm.models.cache import (
+            LRUPromptCache,
+            can_trim_prompt_cache,
+            make_prompt_cache,
+            trim_prompt_cache,
+        )
+    except ImportError:
+        return None
+    return LRUPromptCache, make_prompt_cache, can_trim_prompt_cache, trim_prompt_cache
+
+
+def _prompt_cache_max_bytes(recommended_gb = None):
+    override = os.environ.get("UNSLOTH_MLX_PROMPT_CACHE_BYTES")
+    if override:
+        try:
+            return max(int(override), 0)
+        except ValueError:
+            logger.warning("Ignoring non-integer UNSLOTH_MLX_PROMPT_CACHE_BYTES=%r", override)
+    if recommended_gb:
+        return int(recommended_gb * 1e9 * PROMPT_CACHE_MEMORY_FRACTION)
+    return PROMPT_CACHE_FALLBACK_BYTES
+
+
+def _flatten_kv_entries(cache):
+    for entry in cache:
+        nested = getattr(entry, "caches", None)
+        if nested is None:
+            yield entry
+        else:
+            yield from _flatten_kv_entries(nested)
+
+
+def _kv_prefix_coverage(cache):
+    covered = None
+    for entry in _flatten_kv_entries(cache):
+        offset = getattr(entry, "offset", None)
+        if offset is None:
+            return None
+        if getattr(entry, "start_position", 0):
+            return None
+        window = getattr(entry, "max_size", None)
+        if window is not None and offset > window:
+            return None
+        if covered is None:
+            covered = offset
+        elif covered != offset:
+            return None
+    return covered
+
+
+class _MLXPromptCacheHistory:
+    def __init__(self, max_entries, max_bytes):
+        api = _mlx_prompt_cache_api()
+        if api is None:
+            raise RuntimeError("mlx-lm is too old for LRUPromptCache")
+        lru_cls, make, can_trim, trim = api
+        self._make_prompt_cache = make
+        self._can_trim = can_trim
+        self._trim = trim
+        self._max_bytes = max_bytes
+        self._lru = lru_cls(max_size = max_entries, max_bytes = max_bytes)
+
+    def fetch(self, model, key, tokens):
+        cache, rest = self._lru.fetch_nearest_cache(key, list(tokens))
+        if cache is not None:
+            if rest:
+                return cache, list(rest)
+            if self._can_trim(cache) and self._trim(cache, 1) == 1:
+                return cache, list(tokens[-1:])
+        if len(tokens) > 1:
+            head = list(tokens[:-1])
+            cache, rest = self._lru.fetch_nearest_cache(key, head)
+            if cache is not None:
+                covered = len(head) - len(rest)
+                return cache, list(tokens[covered:])
+        return self._make_prompt_cache(model), list(tokens)
+
+    def insert(self, key, tokens, cache):
+        # An over-budget entry evicts itself and every other conversation.
+        nbytes = sum(getattr(entry, "nbytes", 0) for entry in cache)
+        if nbytes > self._max_bytes:
+            logger.debug(
+                "MLX prompt cache: skipping %.2f GB entry over the %.2f GB budget",
+                nbytes / 1e9,
+                self._max_bytes / 1e9,
+            )
+            return
+        covered = _kv_prefix_coverage(cache)
+        if covered is None:
+            logger.debug("MLX prompt cache: skipping cache with unverifiable prefix coverage")
+            return
+        tokens = list(tokens)
+        if covered > len(tokens):
+            logger.debug(
+                "MLX prompt cache: cache covers %d tokens but only %d were tracked",
+                covered,
+                len(tokens),
+            )
+            return
+        tokens = tokens[:covered]
+        if not tokens:
+            return
+        self._lru.insert_cache(key, tokens, cache)
+
+
 def _mlx_distributed_rank_size(group = None):
     """Return ``(rank, world_size)`` for an optional MLX distributed group."""
     if group is None:
@@ -313,6 +433,55 @@ class MLXInferenceBackend:
         # Recorded for unload to release pinned memory back to the OS.
         self._memory_limits_applied = {}
 
+        self._prompt_cache_history = None
+        self._prompt_cache_unavailable = False
+
+    def _prompt_cache(self):
+        if self._prompt_cache_history is not None or self._prompt_cache_unavailable:
+            return self._prompt_cache_history
+        max_bytes = _prompt_cache_max_bytes(self._memory_limits_applied.get("recommended_gb"))
+        if max_bytes <= 0:
+            self._prompt_cache_unavailable = True
+            logger.info("MLX prompt cache disabled by budget")
+            return None
+        try:
+            self._prompt_cache_history = _MLXPromptCacheHistory(
+                PROMPT_CACHE_ENTRIES,
+                max_bytes,
+            )
+        except Exception as exc:
+            self._prompt_cache_unavailable = True
+            logger.info("MLX prompt cache unavailable (%s); prefilling every request", exc)
+            return None
+        logger.info(
+            "MLX prompt cache: %d entries, %.2f GB budget",
+            PROMPT_CACHE_ENTRIES,
+            max_bytes / 1e9,
+        )
+        return self._prompt_cache_history
+
+    def _clear_prompt_cache(self):
+        self._prompt_cache_history = None
+        self._prompt_cache_unavailable = False
+
+    def _prepare_prompt_cache(self, prompt, adapter_state):
+        history = self._prompt_cache()
+        if history is None:
+            return prompt, None, None, None, 0
+        try:
+            tokenizer = self._tokenizer
+            bos = getattr(tokenizer, "bos_token", None)
+            add_special_tokens = bos is None or not prompt.startswith(bos)
+            tokens = list(tokenizer.encode(prompt, add_special_tokens = add_special_tokens))
+            if not tokens:
+                return prompt, None, None, None, 0
+            key = f"{self.active_model_name}|{adapter_state!r}"
+            cache, rest = history.fetch(self._model, key, tokens)
+        except Exception as exc:
+            logger.debug("MLX prompt cache lookup failed: %s", exc)
+            return prompt, None, None, None, 0
+        return rest, cache, key, tokens, len(tokens) - len(rest)
+
     def _configure_memory_limits(self):
         """Apply Metal memory caps before loading a model.
 
@@ -535,6 +704,7 @@ class MLXInferenceBackend:
         self._distributed_world_size = 1
         if self.active_model_name == model_name:
             self.active_model_name = None
+        self._clear_prompt_cache()
         gc.collect()
         mx.clear_cache()
 
@@ -731,24 +901,34 @@ class MLXInferenceBackend:
         # <think> prefix on every native-protocol snapshot just as the normal
         # decoding path does below.
         normalized_output = think_prefix
-        logger.info(
-            "Generating: prompt_len=%d, max_tokens=%d, model=%s, tokenizer=%s",
-            len(prompt),
-            max_new_tokens,
-            type(self._model).__name__,
-            type(self._tokenizer).__name__,
-        )
         with self._generation_lock, _temporary_mlx_adapter_state(self._model, _adapter_state):
+            (
+                gen_prompt,
+                prompt_cache,
+                cache_key,
+                prompt_tokens,
+                cached_n,
+            ) = self._prepare_prompt_cache(prompt, _adapter_state)
+            logger.info(
+                "Generating: prompt_len=%d, cached=%d, max_tokens=%d, model=%s, tokenizer=%s",
+                len(prompt),
+                cached_n,
+                max_new_tokens,
+                type(self._model).__name__,
+                type(self._tokenizer).__name__,
+            )
             final_response = None
             try:
                 # Enter request-scoped model state before yielding any response.
                 if think_prefix:
                     yield think_prefix
                 gen_kwargs = dict(
-                    prompt = prompt,
+                    prompt = gen_prompt,
                     max_tokens = max_new_tokens,
                     sampler = sampler,
                 )
+                if prompt_cache is not None:
+                    gen_kwargs["prompt_cache"] = prompt_cache
                 if logits_processors is not None:
                     gen_kwargs["logits_processors"] = logits_processors
                 for response in stream_generate(
@@ -757,6 +937,7 @@ class MLXInferenceBackend:
                     **gen_kwargs,
                 ):
                     final_response = response
+                    token_ids.append(response.token)
                     if preserve_native_channels:
                         piece = getattr(response, "text", None) or ""
                         delta = normalizer.feed(piece)
@@ -764,7 +945,6 @@ class MLXInferenceBackend:
                             normalized_output += delta
                             yield normalized_output
                     else:
-                        token_ids.append(response.token)
                         cumulative = self._tokenizer.decode(
                             token_ids,
                             skip_special_tokens = True,
@@ -773,6 +953,13 @@ class MLXInferenceBackend:
 
                     if cancel_event and cancel_event.is_set():
                         break
+                if prompt_cache is not None and prompt_tokens is not None:
+                    history = self._prompt_cache_history
+                    if history is not None:
+                        try:
+                            history.insert(cache_key, prompt_tokens + token_ids, prompt_cache)
+                        except Exception as exc:
+                            logger.debug("MLX prompt cache insert failed: %s", exc)
             except Exception as e:
                 import traceback
                 logger.error("stream_generate failed:\n%s", traceback.format_exc())
@@ -785,6 +972,7 @@ class MLXInferenceBackend:
                         getattr(final_response, "prompt_tps", 0.0),
                         getattr(final_response, "generation_tokens", 0),
                         getattr(final_response, "generation_tps", 0.0),
+                        cached_n,
                     )
         if normalizer is not None:
             cancelled = cancel_event is not None and cancel_event.is_set()
diff --git a/studio/backend/core/inference/orchestrator.py b/studio/backend/core/inference/orchestrator.py
index eaa474d9b8..409132d605 100644
--- a/studio/backend/core/inference/orchestrator.py
+++ b/studio/backend/core/inference/orchestrator.py
@@ -54,9 +54,8 @@ class GenStreamError(str):
     """A stream chunk carrying a real backend/generation error, not model text.
 
     Subclasses str so existing display/logging consumers are unaffected, while
-    callers that must abort a distributed run on error (raise_on_streamed_error)
-    can distinguish a real error from model output whose visible text starts with
-    "Error:" by checking isinstance(chunk, GenStreamError).
+    callers can distinguish a real error from model output whose visible text
+    starts with "Error:" by checking isinstance(chunk, GenStreamError).
     """
 
     __slots__ = ("public",)
@@ -218,10 +217,14 @@ class InferenceOrchestrator:
             native_path_secret_removed_for_child_start,
             run_without_native_path_secret,
         )
+        from utils.hf_cache_settings import child_environment_for_spawn, get_hf_cache_paths
 
-        from .worker import run_inference_process
+        cache_env = get_hf_cache_paths().child_env({})
 
-        with native_path_secret_removed_for_child_start():
+        with (
+            child_environment_for_spawn(cache_env),
+            native_path_secret_removed_for_child_start(),
+        ):
             self._cmd_queue = _CTX.Queue()
             self._resp_queue = _CTX.Queue()
             self._cancel_event = _CTX.Event()
@@ -229,7 +232,7 @@ class InferenceOrchestrator:
 
             self._proc = _CTX.Process(
                 target = run_without_native_path_secret,
-                args = (run_inference_process,),
+                args = ("core.inference.worker", "run_inference_process", cache_env),
                 kwargs = {
                     "cmd_queue": self._cmd_queue,
                     "resp_queue": self._resp_queue,
diff --git a/studio/backend/core/inference/stt_ggml_sidecar.py b/studio/backend/core/inference/stt_ggml_sidecar.py
new file mode 100644
index 0000000000..02b376dea5
--- /dev/null
+++ b/studio/backend/core/inference/stt_ggml_sidecar.py
@@ -0,0 +1,876 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""whisper.cpp (GGML/GGUF) speech-to-text sidecar for Studio dictation.
+
+Runs the same curated Whisper checkpoints as the Transformers sidecar
+(stt_sidecar.py) through whisper.cpp's `whisper-server`, ~2.5x faster at
+identical quality on Apple Silicon and CPU because its Metal/CPU kernels run
+the weights in f16 where PyTorch MPS requires fp32.
+
+Owns a single `whisper-server` subprocess bound to 127.0.0.1 on an ephemeral
+port; the model loads on demand, stays warm between dictations, and unloads
+after the same keep-alive as the Transformers sidecar. Curated GGML checkpoints
+are single files from `unslothai/whisper-*-GGUF`, downloaded directly rather
+than through the Model Hub (whose variant planner only handles `.gguf` chat
+layouts).
+
+Binary discovery mirrors `_find_llama_server_binary`: env override, then managed
+Studio home, then PATH. With no binary the engine is unavailable and dictation
+falls back to the Transformers sidecar; `scripts/build_whisper_cpp.sh` installs
+the binary.
+"""
+
+from __future__ import annotations
+
+import io
+import json
+import os
+import re
+import shutil
+import socket
+import subprocess
+import sys
+import threading
+import time
+import urllib.request
+import uuid
+import wave
+from contextlib import contextmanager
+from pathlib import Path
+from typing import Iterator, Optional
+
+from loggers import get_logger
+
+from core.inference.stt_sidecar import (
+    STT_KEEP_ALIVE_SECONDS,
+    SttAudioDecodeError,
+    SttLanguageError,
+    SttLoadCancelledError,
+    SttModelIdError,
+    SttModelNotDownloadedError,
+    SttUnavailableError,
+    _decode_audio_bounded,
+    _known_whisper_languages,
+    _TARGET_SAMPLE_RATE,
+    _training_active,
+    normalize_whisper_language,
+)
+from utils.prebuilt.child_env import isolate_home, scrub_env, wsl_system_rocm_lib_dirs
+from utils.prebuilt.runtime_libs import dedupe_existing_dirs
+from utils.prebuilt.whisper_layout import lookup_marker
+from utils.process_lifetime import adopt_pid, child_popen_kwargs, forget_pid
+
+logger = get_logger(__name__)
+
+# Curated GGML checkpoints, one repo per model. Keys match the Transformers
+# sidecar's ids so the frontend reuses one picker; values are the single file
+# inside each repo.
+GGML_STT_REPOS: dict[str, str] = {
+    "tiny": "unslothai/whisper-tiny-GGUF",
+    "base": "unslothai/whisper-base-GGUF",
+    "small": "unslothai/whisper-small-GGUF",
+    "large-v3-turbo": "unslothai/whisper-large-v3-turbo-GGUF",
+    "large-v3": "unslothai/whisper-large-v3-GGUF",
+}
+GGML_STT_MODELS: dict[str, str] = {
+    "tiny": "whisper-tiny.bin",
+    "base": "whisper-base.bin",
+    "small": "whisper-small.bin",
+    "large-v3-turbo": "whisper-large-v3-turbo.bin",
+    "large-v3": "whisper-large-v3.bin",
+}
+DEFAULT_GGML_STT_MODEL = "small"
+
+_SERVER_START_TIMEOUT_SECONDS = 120.0
+_TRANSCRIBE_TIMEOUT_SECONDS = 600.0
+
+
+class SttEngineUnavailableError(SttUnavailableError):
+    """whisper-server is not installed; the GGUF dictation engine is off."""
+
+
+def resolve_ggml_model_id(model: Optional[str]) -> str:
+    """Validate a curated GGML model id. Custom repos are not supported here."""
+    if model is None or not str(model).strip():
+        return DEFAULT_GGML_STT_MODEL
+    normalized = str(model).strip()
+    if normalized in GGML_STT_MODELS:
+        return normalized
+    raise SttModelIdError(
+        f"STT model '{model}' is not a curated GGUF dictation model. "
+        f"Choose one of: {', '.join(GGML_STT_MODELS)}."
+    )
+
+
+def _managed_whisper_cpp_dir() -> Path:
+    """`<STUDIO_HOME>/whisper.cpp` in custom mode, else `~/.unsloth/whisper.cpp`.
+
+    Mirrors `managed_node_dir` / `_find_llama_server_binary` so managed runtimes
+    share one parent directory.
+    """
+    legacy = Path.home() / ".unsloth" / "whisper.cpp"
+    try:
+        from utils.paths.storage_roots import studio_root
+
+        resolved = studio_root()
+        legacy_studio = Path.home() / ".unsloth" / "studio"
+        try:
+            is_legacy = resolved.resolve() == legacy_studio.resolve()
+        except (OSError, ValueError):
+            is_legacy = resolved == legacy_studio
+        return legacy if is_legacy else (resolved / "whisper.cpp")
+    except (ImportError, OSError, ValueError):
+        override = (
+            os.environ.get("UNSLOTH_STUDIO_HOME") or os.environ.get("STUDIO_HOME") or ""
+        ).strip()
+        if override:
+            try:
+                return Path(override).expanduser().resolve() / "whisper.cpp"
+            except (OSError, ValueError):
+                return Path(override).expanduser() / "whisper.cpp"
+        return legacy
+
+
+def find_whisper_server_binary() -> Optional[str]:
+    """Locate the whisper-server binary.
+
+    Search order:
+    1. WHISPER_SERVER_PATH environment variable (direct path to binary)
+    2. UNSLOTH_WHISPER_CPP_PATH env var (custom whisper.cpp install dir)
+    3. managed dir: <STUDIO_HOME or ~/.unsloth>/whisper.cpp/{,build/bin/}whisper-server
+    4. whisper-server on PATH
+    """
+    binary_name = "whisper-server.exe" if sys.platform == "win32" else "whisper-server"
+
+    def _layout_candidates(d: Path) -> list[Path]:
+        cands = [d / binary_name, d / "build" / "bin" / binary_name]
+        if sys.platform == "win32":
+            cands.append(d / "build" / "bin" / "Release" / binary_name)
+        return cands
+
+    env_path = os.environ.get("WHISPER_SERVER_PATH")
+    if env_path:
+        p = Path(env_path)
+        if _is_runnable(p):
+            return str(p)
+
+    custom_dir = os.environ.get("UNSLOTH_WHISPER_CPP_PATH")
+    if custom_dir:
+        for p in _layout_candidates(Path(custom_dir)):
+            if _is_runnable(p):
+                return str(p)
+
+    for p in _layout_candidates(_managed_whisper_cpp_dir()):
+        if _is_runnable(p):
+            return str(p)
+
+    return shutil.which(binary_name)
+
+
+def _is_runnable(p: Path) -> bool:
+    """A real whisper-server is an executable file. On Windows os.access(X_OK) is
+    effectively an existence check; on Unix it rejects a non-executable stub so a
+    half-written or wrong-mode file isn't mistaken for the server."""
+    return p.is_file() and (sys.platform == "win32" or os.access(p, os.X_OK))
+
+
+def _whisper_install_marker(binary: str) -> Optional[dict]:
+    """The prebuilt install marker above ``binary``, or None (source/custom builds)."""
+    return lookup_marker(binary).marker
+
+
+def slim_runtime_intact(binary: str) -> bool:
+    """True unless the marker says slim and the linked ggml runtime is missing
+    beside the server. New markers record the exact wired filenames
+    (linked_libraries), all of which must be present; legacy markers without the
+    field fall back to the per-OS core ggml name globs. A broken slim install
+    reads as engine-unavailable (reinstall via `unsloth studio update`), never a
+    crash at load."""
+    lookup = lookup_marker(binary)
+    marker = lookup.marker
+    if lookup.invalid or marker is None:
+        return not lookup.slim_collision
+    if not marker or marker.get("install_kind") != "slim":
+        return True
+    if lookup.authoritative:
+        valid = marker.get("component") == "whisper.cpp"
+        valid = valid and isinstance(marker.get("schema_version"), int)
+        valid = valid and all(
+            isinstance(marker.get(key), str) and marker[key]
+            for key in ("release_tag", "backend", "paired_llama_tag")
+        )
+        valid = valid and isinstance(marker.get("linked_libraries"), list)
+        valid = valid and bool(marker.get("linked_libraries"))
+        valid = valid and all(
+            isinstance(name, str) and name and Path(name).name == name
+            for name in marker["linked_libraries"]
+        )
+        if not valid:
+            return False
+    bin_dir = Path(binary).parent
+    linked = marker.get("linked_libraries")
+    if isinstance(linked, list) and linked and all(isinstance(name, str) for name in linked):
+        intact = all((bin_dir / name).is_file() for name in linked)
+    else:
+        if sys.platform == "win32":
+            required = ("ggml.dll", "ggml-base.dll")
+        elif sys.platform == "darwin":
+            required = ("libggml*.dylib", "libggml-base*.dylib")
+        else:
+            required = ("libggml.so*", "libggml-base.so*")
+        intact = all(any(p.is_file() for p in bin_dir.glob(pattern)) for pattern in required)
+    runtime_dirs = marker.get("linked_runtime_directories")
+    if intact and isinstance(runtime_dirs, list) and runtime_dirs:
+        intact = all(
+            isinstance(name, str)
+            and name
+            and (bin_dir / name).is_dir()
+            and any(path.is_file() for path in (bin_dir / name).rglob("*"))
+            for name in runtime_dirs
+        )
+    if intact and marker.get("backend") == "rocm":
+        expected_runtime_dirs = set() if sys.platform == "win32" else {"hipblaslt", "rocblas"}
+        intact = (
+            marker.get("runtime_wiring_version") == 2
+            and isinstance(runtime_dirs, list)
+            and set(runtime_dirs) == expected_runtime_dirs
+        )
+    if not intact:
+        logger.warning(
+            "slim whisper install is missing its linked ggml runtime at "
+            f"{bin_dir}; run `unsloth studio update` to reinstall it"
+        )
+    return intact
+
+
+def is_available() -> bool:
+    binary = find_whisper_server_binary()
+    if binary is None:
+        return False
+    if not slim_runtime_intact(binary):
+        return False
+    try:
+        import av  # noqa: F401
+    except Exception:
+        # No PyAV means every transcription 501s on decode.
+        return False
+    return True
+
+
+def ensure_engine_available() -> str:
+    binary = find_whisper_server_binary()
+    if binary is None:
+        raise SttEngineUnavailableError(
+            "The local transcription runtime is not installed. Run "
+            "`unsloth studio update` to install it."
+        )
+    if not slim_runtime_intact(binary):
+        raise SttEngineUnavailableError(
+            "The local transcription runtime is missing its paired ggml "
+            "libraries. Run `unsloth studio update` to reinstall it."
+        )
+    return binary
+
+
+# ---------------------------------------------------------------------------
+# whisper-server child-process environment
+# ---------------------------------------------------------------------------
+# Build the whisper-server env: prepend the binary dir (co-located libs win, and
+# a backstop where the loader ignores the rpath) and scrub secret-bearing vars the
+# binary never needs. On WSL2 ROCm the system HIP libs go first, since a bundle's
+# bare-metal HIP cannot drive /dev/dxg. A CUDA bundle ships libggml-cuda.so but not
+# libcudart/libcublas (paired with the user's PyTorch), so add the
+# CUDA-from-PyTorch runtime dirs the selection gated on, else the backend cannot
+# resolve a runtime that lives only in wheels. Mirrors llama's binary_env(); the
+# scrub/WSL/dedupe helpers live in utils.prebuilt.
+
+# Module-level aliases keep the historical patch points for tests and callers.
+_wsl_system_rocm_lib_dirs = wsl_system_rocm_lib_dirs
+_dedupe_existing_dirs = dedupe_existing_dirs
+
+
+def _whisper_server_child_env(binary: str) -> dict[str, str]:
+    """Env for the whisper-server subprocess: secrets scrubbed, home/profile vars
+    repointed at a managed scratch dir (a downloaded binary must not see the real
+    home's token caches), co-located libs on the loader path, WSL system HIP first
+    on WSL2 ROCm."""
+    env = scrub_env(os.environ)
+    isolate_home(env, str(_managed_whisper_cpp_dir() / ".child_home"))
+    bin_dir = str(Path(binary).parent)
+    # A CUDA bundle needs the CUDA-from-PyTorch wheel dirs so libcudart/libcublas
+    # resolve at launch when they live only in site-packages/nvidia/*/lib. Placed
+    # after bin_dir so co-located libs still win; empty for other bundles.
+    cuda_runtime_dirs: list[str] = []
+    bundle_dir = Path(bin_dir)
+    has_cuda_module = any(
+        path.is_file()
+        for pattern in ("libggml-cuda.so*", "ggml-cuda*.dll")
+        for path in bundle_dir.glob(pattern)
+    )
+    if has_cuda_module:
+        try:
+            from utils.prebuilt.runtime_libs import python_runtime_dirs
+            cuda_runtime_dirs = python_runtime_dirs()
+        except Exception:
+            cuda_runtime_dirs = []
+    if sys.platform == "win32":
+        var, lead = "PATH", [bin_dir, *cuda_runtime_dirs]
+    elif sys.platform == "darwin":
+        var, lead = "DYLD_LIBRARY_PATH", [bin_dir]
+    else:
+        var, lead = "LD_LIBRARY_PATH", [bin_dir, *cuda_runtime_dirs]
+        wsl_rocm = _wsl_system_rocm_lib_dirs()
+        if wsl_rocm:
+            lead = [*wsl_rocm, bin_dir, *cuda_runtime_dirs]
+            env.setdefault("HSA_ENABLE_DXG_DETECTION", "1")
+    existing = [p for p in env.get(var, "").split(os.pathsep) if p]
+    env[var] = os.pathsep.join(_dedupe_existing_dirs([*lead, *existing]))
+    return env
+
+
+# ---------------------------------------------------------------------------
+# Model file download (single files; deliberately outside the Model Hub flow)
+# ---------------------------------------------------------------------------
+
+
+def _cached_model_path(model_id: str) -> Optional[str]:
+    """Path of a fully downloaded GGML file in the shared HF cache, else None."""
+    from huggingface_hub import hf_hub_download
+    try:
+        return hf_hub_download(
+            repo_id = GGML_STT_REPOS[model_id],
+            filename = GGML_STT_MODELS[model_id],
+            local_files_only = True,
+        )
+    except Exception:
+        return None
+
+
+class _GgmlDownloadState:
+    """Tracks one background hf_hub_download of a curated GGML file."""
+
+    def __init__(self) -> None:
+        self._lock = threading.Lock()
+        self._thread: Optional[threading.Thread] = None
+        self._model_id: Optional[str] = None
+        self._error: Optional[str] = None
+        self._total_bytes: Optional[int] = None
+        self._etag: Optional[str] = None
+
+    def status(self) -> dict:
+        with self._lock:
+            downloading = self._thread is not None and self._thread.is_alive()
+            return {
+                "downloading": downloading,
+                "model": self._model_id if downloading else None,
+                "error": self._error,
+                "bytes_total": self._total_bytes if downloading else None,
+                "bytes_done": self._incomplete_bytes() if downloading else None,
+            }
+
+    def _incomplete_bytes(self) -> Optional[int]:
+        """Best-effort progress: size of the in-flight blob in the HF cache.
+
+        hf_hub_download writes ``blobs/<etag>.incomplete``; prefer this file's
+        etag, else the largest in-flight blob.
+        """
+        try:
+            from huggingface_hub.constants import HF_HUB_CACHE
+
+            # Caller may hold the non-reentrant self._lock; bare reads are safe.
+            model_id = self._model_id
+            if not model_id:
+                return None
+            repo_dir = (
+                Path(HF_HUB_CACHE)
+                / f"models--{GGML_STT_REPOS[model_id].replace('/', '--')}"
+                / "blobs"
+            )
+            if not repo_dir.is_dir():
+                return None
+            etag = self._etag
+            if etag:
+                target = repo_dir / f"{etag}.incomplete"
+                if target.is_file():
+                    return target.stat().st_size
+            sizes = [p.stat().st_size for p in repo_dir.glob("*.incomplete") if p.is_file()]
+            return max(sizes) if sizes else None
+        except Exception:
+            return None
+
+    def start(
+        self,
+        model_id: str,
+        hf_token: Optional[str] = None,
+    ) -> None:
+        model_id = resolve_ggml_model_id(model_id)
+        with self._lock:
+            if self._thread is not None and self._thread.is_alive():
+                if self._model_id == model_id:
+                    return
+                raise SttModelIdError(
+                    f"Another GGUF dictation model ('{self._model_id}') is still "
+                    "downloading; wait for it to finish."
+                )
+            self._model_id = model_id
+            self._error = None
+            self._total_bytes = None
+            self._etag = None
+            thread = threading.Thread(target = self._run, args = (model_id, hf_token), daemon = True)
+            self._thread = thread
+            thread.start()
+
+    def _run(self, model_id: str, hf_token: Optional[str]) -> None:
+        repo_id = GGML_STT_REPOS[model_id]
+        filename = GGML_STT_MODELS[model_id]
+        try:
+            from huggingface_hub import (
+                get_hf_file_metadata,
+                hf_hub_download,
+                hf_hub_url,
+            )
+            try:
+                # One HEAD request for the total and etag.
+                meta = get_hf_file_metadata(hf_hub_url(repo_id, filename), token = hf_token or None)
+                with self._lock:
+                    self._total_bytes = meta.size
+                    self._etag = meta.etag
+            except Exception:
+                pass
+            hf_hub_download(
+                repo_id = repo_id,
+                filename = filename,
+                token = hf_token or None,
+            )
+        except Exception as exc:
+            logger.warning("GGUF STT download failed for %s: %s", model_id, exc)
+            with self._lock:
+                self._error = f"Download failed for '{model_id}'."
+
+
+_download_state = _GgmlDownloadState()
+
+
+def start_model_download(model: Optional[str], hf_token: Optional[str] = None) -> None:
+    _download_state.start(resolve_ggml_model_id(model), hf_token)
+
+
+def download_status() -> dict:
+    return _download_state.status()
+
+
+# ---------------------------------------------------------------------------
+# WAV packaging
+# ---------------------------------------------------------------------------
+
+
+def _pcm_to_wav_bytes(decoded_audio) -> bytes:
+    """Wrap decoded float32 mono 16 kHz PCM into an in-memory 16-bit WAV."""
+    import numpy as np
+
+    clipped = np.clip(decoded_audio, -1.0, 1.0)
+    pcm16 = (clipped * 32767.0).astype("<i2")
+    buf = io.BytesIO()
+    with wave.open(buf, "wb") as w:
+        w.setnchannels(1)
+        w.setsampwidth(2)
+        w.setframerate(_TARGET_SAMPLE_RATE)
+        w.writeframes(pcm16.tobytes())
+    return buf.getvalue()
+
+
+# ---------------------------------------------------------------------------
+# Sidecar
+# ---------------------------------------------------------------------------
+
+
+class GgmlSttSidecar:
+    """Owns one whisper-server subprocess and proxies dictation to it."""
+
+    def __init__(self, keep_alive_seconds: float = STT_KEEP_ALIVE_SECONDS) -> None:
+        self._lock = threading.RLock()
+        self._process: Optional[subprocess.Popen] = None
+        self._port: Optional[int] = None
+        self._model_id: Optional[str] = None
+        self._idle_timer: Optional[threading.Timer] = None
+        self._idle_generation = 0
+        self._keep_alive_seconds = keep_alive_seconds
+        # Set while whisper-server starts so training admission can account for
+        # the accelerator memory it is about to bind. Read without the lock.
+        self._loading = False
+        # A still-starting whisper-server is cancellable so training can preempt
+        # it before it binds accelerator memory. Assigned inside self._lock but
+        # acted on without it: cancel_pending_load() runs while load() holds the
+        # lock, so the event is the source of truth and terminating the process
+        # is a best-effort fast path.
+        self._load_cancel_event: Optional[threading.Event] = None
+        self._starting_process: Optional[subprocess.Popen] = None
+        # Set before the updater waits for _lock, then kept set while it owns
+        # the lock and atomically replaces the managed install tree. New loads
+        # fail fast instead of starting a process from files being swapped.
+        self._update_in_progress = False
+
+    @property
+    def loaded_model(self) -> Optional[str]:
+        # Lock-free status read (like stt_sidecar.py): transcribe() holds
+        # self._lock for the whole inference call (up to
+        # _TRANSCRIBE_TIMEOUT_SECONDS), and status polls plus training admission
+        # must not block behind it. _process_alive() snapshots self._process
+        # before poll(), which subprocess guards with _waitpid_lock, so a
+        # concurrent unload is safe.
+        return self._model_id if self._process_alive() else None
+
+    @property
+    def device(self) -> Optional[str]:
+        return "whisper.cpp" if self._process_alive() else None
+
+    def is_loading(self) -> bool:
+        # True only while whisper-server is starting (seconds to bind its GPU
+        # backend); load() sets and clears the flag around that window.
+        return self._loading
+
+    @property
+    def keep_alive_seconds(self) -> float:
+        return self._keep_alive_seconds
+
+    def _process_alive(self) -> bool:
+        # Snapshot self._process once: a concurrent unload() nulls it under the
+        # lock, so lock-free readers would otherwise re-read None between the
+        # truthiness check and .poll().
+        process = self._process
+        return process is not None and process.poll() is None
+
+    # -- idle unload ------------------------------------------------------
+
+    def _cancel_idle_unload_locked(self) -> None:
+        self._idle_generation += 1
+        if self._idle_timer is not None:
+            self._idle_timer.cancel()
+            self._idle_timer = None
+
+    def _schedule_idle_unload_locked(self) -> None:
+        self._cancel_idle_unload_locked()
+        if not self._process_alive():
+            return
+        generation = self._idle_generation
+        timer = threading.Timer(self._keep_alive_seconds, self._idle_unload, args = (generation,))
+        timer.daemon = True
+        self._idle_timer = timer
+        timer.start()
+
+    def _idle_unload(self, generation: int) -> None:
+        with self._lock:
+            if generation != self._idle_generation:
+                return
+            logger.info("Unloading idle GGUF STT model %s", self._model_id)
+            self._release_locked()
+
+    # -- process lifecycle -------------------------------------------------
+
+    def _release_locked(self) -> None:
+        self._cancel_idle_unload_locked()
+        process = self._process
+        self._process = None
+        self._port = None
+        self._model_id = None
+        if process is not None and process.poll() is None:
+            process.terminate()
+            try:
+                process.wait(timeout = 10)
+            except subprocess.TimeoutExpired:
+                process.kill()
+                process.wait(timeout = 10)
+        if process is not None:
+            forget_pid(process.pid)
+
+    def unload(self) -> None:
+        with self._lock:
+            self._release_locked()
+
+    def _raise_if_update_in_progress(self) -> None:
+        if self._update_in_progress:
+            raise SttEngineUnavailableError(
+                "The local transcription runtime is being updated. Try dictation again shortly."
+            )
+
+    @contextmanager
+    def update_maintenance(self) -> Iterator[bool]:
+        """Block new loads while the managed whisper.cpp tree is replaced.
+
+        The flag is published before waiting for an existing transcription to
+        release ``_lock``. Holding that lock across the yielded installer phase
+        prevents Windows from relocking the executable and prevents every host
+        from starting a process against a partially swapped tree. The yielded
+        value records whether a warm model had to be unloaded.
+        """
+        self._update_in_progress = True
+        try:
+            with self._lock:
+                model_was_active = self._process_alive()
+                self._release_locked()
+                yield model_was_active
+        finally:
+            self._update_in_progress = False
+
+    def cancel_pending_load(self) -> bool:
+        # Preempt a starting whisper-server so training does not launch while it
+        # binds accelerator memory. load() holds self._lock for the whole startup,
+        # so act without the lock: signal abort and terminate the starting
+        # process. _wait_for_server observes the event and raises, then load()
+        # reaps the process and releases the lock.
+        if not self._loading:
+            return False
+        event = self._load_cancel_event
+        if event is None:
+            return False
+        event.set()
+        process = self._starting_process
+        if process is not None and process.poll() is None:
+            try:
+                process.terminate()
+            except Exception:
+                pass
+        return True
+
+    def wait_for_load_to_settle(self) -> None:
+        # load() holds self._lock across startup and cancel cleanup, so acquiring
+        # it blocks until a cancelled server is killed, reaped, and its
+        # accelerator memory released.
+        with self._lock:
+            pass
+
+    @staticmethod
+    def _reserve_free_port() -> tuple[socket.socket, int]:
+        """Bind an ephemeral port and keep the socket held.
+
+        The caller closes the reservation immediately before spawning
+        whisper-server, shrinking the window in which another local process
+        could bind the port. SO_REUSEADDR lets the child rebind right after.
+        """
+        s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+        s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+        s.bind(("127.0.0.1", 0))
+        return s, s.getsockname()[1]
+
+    def _ensure_model_downloaded(self, model_id: str) -> str:
+        path = _cached_model_path(model_id)
+        if path is None:
+            raise SttModelNotDownloadedError(
+                f"STT model '{model_id}' (GGUF) is not downloaded. "
+                "Download it in Settings, then Voice, before loading it."
+            )
+        return path
+
+    def load(self, model: Optional[str] = None) -> None:
+        """Start (or switch) whisper-server for the requested curated model."""
+        self._raise_if_update_in_progress()
+        model_id = resolve_ggml_model_id(model)
+        with self._lock:
+            self._raise_if_update_in_progress()
+            binary = ensure_engine_available()
+            if self._process_alive() and self._model_id == model_id:
+                self._schedule_idle_unload_locked()
+                return
+            model_path = self._ensure_model_downloaded(model_id)
+            self._release_locked()
+            reservation, port = self._reserve_free_port()
+            command = [binary, "-m", model_path, "--host", "127.0.0.1", "--port", str(port)]
+            marker = _whisper_install_marker(binary)
+            if _training_active():
+                # Keep whisper.cpp off the accelerator during training (like the
+                # Transformers sidecar's CPU choice) so a mid-training dictation
+                # cannot reclaim the VRAM training just freed.
+                command.append("--no-gpu")
+            elif marker is not None and marker.get("backend") == "cpu":
+                # A deliberate CPU install must stay CPU: the slim wiring links
+                # every llama ggml backend (including CUDA/ROCm), so without
+                # this flag a cpu-selected install would still grab the GPU.
+                command.append("--no-gpu")
+            logger.info(
+                "Starting whisper-server for STT model %s on 127.0.0.1:%s",
+                model_id,
+                port,
+            )
+            cancel_event = threading.Event()
+            self._load_cancel_event = cancel_event
+            self._loading = True
+            try:
+                # Release the reservation as late as possible: whisper-server
+                # binds the port moments after this close.
+                reservation.close()
+                process = subprocess.Popen(
+                    command,
+                    stdout = subprocess.DEVNULL,
+                    stderr = subprocess.DEVNULL,
+                    stdin = subprocess.DEVNULL,
+                    # Co-located GPU libs on the loader path (WSL system HIP first),
+                    # secrets scrubbed from the downloaded binary's env.
+                    env = _whisper_server_child_env(binary),
+                    # Die with Studio (Linux PDEATHSIG, Windows job) so a crash
+                    # never orphans a server holding the model.
+                    **child_popen_kwargs(),
+                )
+                self._starting_process = process
+                adopt_pid(process.pid)  # terminate_all backstop for graceful exits
+                try:
+                    self._wait_for_server(process, port, cancel_event)
+                except Exception:
+                    if process.poll() is None:
+                        process.kill()
+                        process.wait(timeout = 10)
+                    forget_pid(process.pid)
+                    raise
+                self._process = process
+                self._port = port
+                self._model_id = model_id
+                self._schedule_idle_unload_locked()
+            finally:
+                reservation.close()  # no-op when already released before spawn
+                self._loading = False
+                self._load_cancel_event = None
+                self._starting_process = None
+
+    @staticmethod
+    def _wait_for_server(
+        process: subprocess.Popen,
+        port: int,
+        cancel_event: Optional[threading.Event] = None,
+    ) -> None:
+        deadline = time.monotonic() + _SERVER_START_TIMEOUT_SECONDS
+        while time.monotonic() < deadline:
+            if cancel_event is not None and cancel_event.is_set():
+                raise SttLoadCancelledError(
+                    "GGUF STT model loading was cancelled so training could start."
+                )
+            if process.poll() is not None:
+                raise SttEngineUnavailableError(
+                    "The local transcription runtime exited before becoming "
+                    "ready; the model file may be corrupt or unsupported."
+                )
+            # Require a whisper-server-specific response twice, with the managed
+            # child alive around each probe. An arbitrary local process that won
+            # the bind race would otherwise be mistaken for the sidecar and
+            # receive the user's microphone audio.
+            if GgmlSttSidecar._probe_is_whisper_server(process, port) and (
+                GgmlSttSidecar._probe_is_whisper_server(process, port)
+            ):
+                return
+            time.sleep(0.2)
+        raise SttEngineUnavailableError("The local transcription runtime did not start in time.")
+
+    @staticmethod
+    def _probe_is_whisper_server(process: subprocess.Popen, port: int) -> bool:
+        """One readiness probe: our child is alive and the responder looks like
+        whisper.cpp's server (its index page and errors identify whisper)."""
+        if process.poll() is not None:
+            return False
+        try:
+            req = urllib.request.Request(f"http://127.0.0.1:{port}/", method = "GET")
+            with urllib.request.urlopen(req, timeout = 2) as response:
+                body = response.read(65536)
+        except Exception:
+            return False
+        if process.poll() is not None:
+            return False
+        return b"whisper" in body.lower()
+
+    # -- transcription ------------------------------------------------------
+
+    def transcribe(
+        self,
+        audio: bytes,
+        model: Optional[str] = None,
+        language: Optional[str] = None,
+        fast: bool = False,
+    ) -> dict:
+        """Transcribe encoded audio bytes via whisper-server.
+
+        Accepts any container PyAV can decode (same validation and caps as the
+        Transformers sidecar). Returns {text, language, duration, model}.
+        """
+        self._raise_if_update_in_progress()
+        ensure_engine_available()
+        model_id = resolve_ggml_model_id(model)
+        lang = normalize_whisper_language(language)
+        known_languages = _known_whisper_languages()
+        if lang is not None and known_languages is not None and lang not in known_languages:
+            raise SttLanguageError(
+                f"Language '{language}' is not supported by STT model '{model_id}'."
+            )
+        # Reject a missing model before decoding so a long clip does not burn CPU
+        # only to 409 (matches the Transformers sidecar's preflight).
+        self._ensure_model_downloaded(model_id)
+        decoded_audio = _decode_audio_bounded(audio)
+        wav_bytes = _pcm_to_wav_bytes(decoded_audio)
+        with self._lock:
+            try:
+                self.load(model_id)
+                text = self._post_inference(wav_bytes, lang, fast)
+            finally:
+                self._schedule_idle_unload_locked()
+        duration = (len(decoded_audio) / _TARGET_SAMPLE_RATE) if len(decoded_audio) else None
+        return {
+            "text": text,
+            "language": lang,
+            "duration": duration,
+            "model": model_id,
+        }
+
+    def _post_inference(self, wav_bytes: bytes, lang: Optional[str], fast: bool) -> str:
+        boundary = uuid.uuid4().hex
+        fields = {
+            "temperature": "0.0",
+            "response_format": "json",
+            # Match the Transformers sidecar: 5-way beam search, greedy for fast.
+            "beam_size": "1" if fast else "5",
+            "language": lang or "auto",
+        }
+        parts: list[bytes] = []
+        for name, value in fields.items():
+            parts.append(
+                (
+                    f"--{boundary}\r\nContent-Disposition: form-data; "
+                    f'name="{name}"\r\n\r\n{value}\r\n'
+                ).encode()
+            )
+        parts.append(
+            (
+                f"--{boundary}\r\nContent-Disposition: form-data; "
+                'name="file"; filename="dictation.wav"\r\n'
+                "Content-Type: audio/wav\r\n\r\n"
+            ).encode()
+            + wav_bytes
+            + b"\r\n"
+        )
+        parts.append(f"--{boundary}--\r\n".encode())
+        body = b"".join(parts)
+        req = urllib.request.Request(
+            f"http://127.0.0.1:{self._port}/inference",
+            data = body,
+            headers = {"Content-Type": f"multipart/form-data; boundary={boundary}"},
+        )
+        try:
+            with urllib.request.urlopen(req, timeout = _TRANSCRIBE_TIMEOUT_SECONDS) as resp:
+                payload = json.load(resp)
+        except SttAudioDecodeError:
+            raise
+        except Exception as exc:
+            raise SttEngineUnavailableError(
+                "The local transcription runtime did not answer the request."
+            ) from exc
+        text = payload.get("text")
+        if not isinstance(text, str):
+            raise SttAudioDecodeError("Could not decode the audio.")
+        # whisper.cpp joins segments with newlines; dictation wants one line.
+        return " ".join(part.strip() for part in text.splitlines() if part.strip()).strip()
+
+
+_sidecar: Optional[GgmlSttSidecar] = None
+
+
+def get_ggml_stt_sidecar() -> GgmlSttSidecar:
+    global _sidecar
+    if _sidecar is None:
+        _sidecar = GgmlSttSidecar()
+    return _sidecar
diff --git a/studio/backend/core/inference/stt_sidecar.py b/studio/backend/core/inference/stt_sidecar.py
new file mode 100644
index 0000000000..7ac7e93c87
--- /dev/null
+++ b/studio/backend/core/inference/stt_sidecar.py
@@ -0,0 +1,1130 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""
+Standalone speech-to-text (STT) sidecar for dictation.
+
+Loads a Whisper model (via Transformers) in the backend process, separate from
+the chat model's inference subprocess, so dictation works with any chat model
+without evicting it. Curated defaults plus any Transformers-compatible Whisper
+repo; weights come through Studio's Model Hub and stay warm briefly between
+dictations. CUDA runs float16; MPS and CPU run float32.
+"""
+
+from __future__ import annotations
+
+import gc
+import hashlib
+import io
+import json
+import os
+import re
+import threading
+import uuid
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Optional
+
+from loggers import get_logger
+
+logger = get_logger(__name__)
+
+# Multilingual Whisper defaults: stable API/UI id -> Hub repository. A request
+# may instead pass a validated Hugging Face `owner/model` id.
+STT_MODELS: dict[str, str] = {
+    "tiny": "unsloth/whisper-tiny",
+    "base": "unsloth/whisper-base",
+    "small": "unsloth/whisper-small",
+    "large-v3-turbo": "unsloth/whisper-large-v3-turbo",
+    "large-v3": "unsloth/whisper-large-v3",
+}
+DEFAULT_STT_MODEL = "small"
+STT_KEEP_ALIVE_SECONDS = 5 * 60
+_HF_REPO_ID = re.compile(r"^[A-Za-z0-9][A-Za-z0-9._-]{0,95}/[A-Za-z0-9][A-Za-z0-9._-]{0,95}$")
+_HF_COMMIT_SHA = re.compile(r"^[0-9a-f]{40}$")
+
+# Bound decoded PCM length so a crafted upload cannot exhaust memory (callers
+# also cap the encoded bytes).
+_MAX_AUDIO_SECONDS = 30 * 60
+_TARGET_SAMPLE_RATE = 16000
+
+# Non-weight files WhisperProcessor/WhisperForConditionalGeneration may load.
+# Weight selection is built from pinned Hub metadata so repositories publishing
+# both formats do not download the same checkpoint twice.
+_STT_SNAPSHOT_SUPPORT_FILES = (
+    "config.json",
+    "generation_config.json",
+    "preprocessor_config.json",
+    "processor_config.json",
+    "tokenizer.json",
+    "tokenizer_config.json",
+    "vocab.json",
+    "merges.txt",
+    "normalizer.json",
+    "special_tokens_map.json",
+    "added_tokens.json",
+)
+_STT_SAFETENSORS_INDEX = "model.safetensors.index.json"
+_STT_PYTORCH_INDEX = "pytorch_model.bin.index.json"
+_STT_SAFETENSORS_WEIGHTS = "model.safetensors"
+_STT_PYTORCH_WEIGHTS = "pytorch_model.bin"
+_STT_REVISION_RECORD_VERSION = 1
+
+
+@dataclass(frozen = True)
+class _SelectedHubFile:
+    path: str
+    size: int
+    blob_key: Optional[str]
+
+
+@dataclass(frozen = True)
+class _CachedSttSnapshot:
+    path: Optional[Path]
+    is_multilingual: Optional[bool]
+
+
+class SttUnavailableError(RuntimeError):
+    """The STT backend (PyTorch/Transformers or PyAV) is not installed."""
+
+
+class SttLoadCancelledError(RuntimeError):
+    """An in-flight STT model load was cancelled for training."""
+
+
+class SttModelNotDownloadedError(RuntimeError):
+    """The selected model is not complete in the shared Hub cache."""
+
+
+class SttModelIdError(ValueError):
+    """The requested custom model is not a valid Hugging Face repository id."""
+
+
+class SttModelCompatibilityError(ValueError):
+    """The requested repository is not a Transformers Whisper checkpoint."""
+
+
+class SttAudioDecodeError(ValueError):
+    """The uploaded bytes could not be decoded as audio."""
+
+
+class SttAudioTooLongError(ValueError):
+    """The decoded audio exceeds the bounded transcription duration."""
+
+
+class SttLanguageError(ValueError):
+    """The requested language is not supported by the selected STT model."""
+
+
+_WHISPER_LANGUAGE_ALIASES = {
+    # Legacy/browser BCP-47 primaries whose Whisper code differs.
+    "cmn": "zh",
+    "fil": "tl",
+    "in": "id",
+    "iw": "he",
+    "ji": "yi",
+    "nb": "no",
+    "nn": "no",
+}
+
+
+def normalize_whisper_language(language: Optional[str]) -> Optional[str]:
+    """Convert a BCP-47 locale into the short code Whisper expects."""
+    if not language:
+        return None
+    normalized = language.strip().replace("_", "-").lower()
+    if not normalized or normalized == "auto":
+        return None
+    primary = normalized.split("-", 1)[0]
+    return _WHISPER_LANGUAGE_ALIASES.get(primary, primary)
+
+
+def _known_whisper_languages() -> Optional[frozenset[str]]:
+    """Return Whisper's language codes without constructing/loading a model."""
+    try:
+        from transformers.models.whisper.tokenization_whisper import LANGUAGES
+    except Exception:
+        # Transformers unavailable or the constant moved: skip the check.
+        return None
+    return frozenset(LANGUAGES)
+
+
+def ensure_stt_available() -> None:
+    """Raise when the complete local Whisper backend cannot be imported."""
+    try:
+        import av  # noqa: F401
+        import torch  # noqa: F401
+        import transformers  # noqa: F401
+    except Exception as exc:
+        raise SttUnavailableError(
+            "Speech-to-text needs PyTorch, Transformers, and PyAV. "
+            "Run `unsloth studio update` to install them."
+        ) from exc
+
+
+def is_available() -> bool:
+    """True when the complete local Whisper backend can be imported."""
+    try:
+        ensure_stt_available()
+    except SttUnavailableError:
+        return False
+    return True
+
+
+def resolve_model_id(model: Optional[str]) -> str:
+    """Resolve a curated id or validate a custom Hugging Face repository."""
+    if not model:
+        return DEFAULT_STT_MODEL
+    normalized = model.strip()
+    if normalized in STT_MODELS:
+        return normalized
+    if _HF_REPO_ID.fullmatch(normalized):
+        return normalized
+    raise SttModelIdError(
+        "STT model must be one of Studio's defaults or a Hugging Face "
+        "repository in 'owner/model' form."
+    )
+
+
+def resolve_model_repo(model_id: str) -> str:
+    """Return the Hub repository for a curated or custom model id."""
+    resolved = resolve_model_id(model_id)
+    return STT_MODELS.get(resolved, resolved)
+
+
+def _is_whisper_config(config: object) -> bool:
+    """True when Hub/local config metadata identifies a Whisper ASR model."""
+    if not isinstance(config, dict):
+        return False
+    model_type = config.get("model_type")
+    if isinstance(model_type, str) and model_type.strip().lower() == "whisper":
+        return True
+    architectures = config.get("architectures")
+    return isinstance(architectures, list) and any(
+        isinstance(name, str) and name == "WhisperForConditionalGeneration"
+        for name in architectures
+    )
+
+
+def _read_json_object(path: Path) -> dict:
+    try:
+        with open(path, "r", encoding = "utf-8") as file:
+            value = json.load(file)
+        return value if isinstance(value, dict) else {}
+    except Exception:
+        return {}
+
+
+def _active_hf_hub_cache() -> Path:
+    """Return the active Hub cache while respecting runtime test overrides."""
+    explicit = (os.environ.get("HF_HUB_CACHE") or "").strip()
+    if explicit:
+        return Path(explicit).expanduser()
+    hf_home = (os.environ.get("HF_HOME") or "").strip()
+    if hf_home:
+        return Path(hf_home).expanduser() / "hub"
+    from huggingface_hub.constants import HF_HUB_CACHE
+
+    return Path(HF_HUB_CACHE)
+
+
+def _repo_cache_dir(repo: str) -> Path:
+    return _active_hf_hub_cache() / f"models--{repo.replace('/', '--')}"
+
+
+def _revision_record_path(repo: str) -> Path:
+    from utils.paths.storage_roots import cache_root
+    digest = hashlib.sha256(repo.encode("utf-8")).hexdigest()
+    return cache_root() / "stt-revisions" / f"{digest}.json"
+
+
+def _write_revision_record(repo: str, revision: str) -> None:
+    """Persist immutable identity only, never an HF-cache absolute path."""
+    if not _HF_COMMIT_SHA.fullmatch(revision):
+        return
+    path = _revision_record_path(repo)
+    tmp = path.with_name(f".{path.name}.tmp-{uuid.uuid4().hex[:8]}")
+    try:
+        path.parent.mkdir(parents = True, exist_ok = True)
+        with tmp.open("w", encoding = "utf-8") as handle:
+            json.dump(
+                {
+                    "version": _STT_REVISION_RECORD_VERSION,
+                    "repo": repo,
+                    "revision": revision,
+                },
+                handle,
+            )
+            handle.flush()
+            os.fsync(handle.fileno())
+        os.replace(tmp, path)
+    except OSError as exc:
+        logger.debug("Could not persist STT revision for %s: %s", repo, exc)
+        try:
+            tmp.unlink(missing_ok = True)
+        except OSError:
+            pass
+
+
+def _read_revision_record(repo: str) -> Optional[str]:
+    payload = _read_json_object(_revision_record_path(repo))
+    if payload.get("version") != _STT_REVISION_RECORD_VERSION or payload.get("repo") != repo:
+        return None
+    revision = payload.get("revision")
+    return revision if isinstance(revision, str) and _HF_COMMIT_SHA.fullmatch(revision) else None
+
+
+def _safe_snapshot_for_revision(repo: str, revision: str) -> Optional[Path]:
+    """Resolve a canonical SHA below this repository's active snapshots dir."""
+    if not _HF_COMMIT_SHA.fullmatch(revision):
+        return None
+    snapshots = _repo_cache_dir(repo) / "snapshots"
+    candidate = snapshots / revision
+    try:
+        snapshots_resolved = snapshots.resolve()
+        candidate_resolved = candidate.resolve()
+    except (OSError, RuntimeError):
+        return None
+    if snapshots_resolved not in candidate_resolved.parents or not candidate_resolved.is_dir():
+        return None
+    return candidate_resolved
+
+
+def _snapshot_usable(model_id: str, snapshot: Path) -> bool:
+    if not _snapshot_is_complete(snapshot):
+        return False
+    if model_id not in STT_MODELS:
+        return _is_whisper_config(_read_json_object(snapshot / "config.json"))
+    return True
+
+
+def _find_complete_cached_snapshot(model: Optional[str]) -> Optional[Path]:
+    """Find one complete local snapshot without contacting the Hub."""
+    model_id = resolve_model_id(model)
+    repo = resolve_model_repo(model_id)
+
+    recorded = _read_revision_record(repo)
+    if recorded:
+        snapshot = _safe_snapshot_for_revision(repo, recorded)
+        if snapshot is not None and _snapshot_usable(model_id, snapshot):
+            return snapshot
+
+    ref = _repo_cache_dir(repo) / "refs" / "main"
+    try:
+        revision = ref.read_text(encoding = "utf-8").strip()
+    except OSError:
+        revision = ""
+    snapshot = _safe_snapshot_for_revision(repo, revision)
+    if snapshot is not None and _snapshot_usable(model_id, snapshot):
+        _write_revision_record(repo, revision)
+        return snapshot
+
+    snapshots = _repo_cache_dir(repo) / "snapshots"
+    try:
+        revisions = sorted(
+            (
+                (path.stat().st_mtime_ns, path.name)
+                for path in snapshots.iterdir()
+                if path.is_dir() and _HF_COMMIT_SHA.fullmatch(path.name)
+            ),
+            reverse = True,
+        )
+    except OSError:
+        return None
+    for _mtime, revision in revisions:
+        snapshot = _safe_snapshot_for_revision(repo, revision)
+        if snapshot is not None and _snapshot_usable(model_id, snapshot):
+            _write_revision_record(repo, revision)
+            return snapshot
+    return None
+
+
+def _selected_file_from_sibling(sibling) -> _SelectedHubFile:
+    lfs = getattr(sibling, "lfs", None)
+    blob_key = getattr(lfs, "sha256", None) or getattr(sibling, "blob_id", None)
+    return _SelectedHubFile(
+        path = sibling.rfilename,
+        size = max(0, int(getattr(sibling, "size", 0) or 0)),
+        blob_key = blob_key if isinstance(blob_key, str) and blob_key else None,
+    )
+
+
+def _select_snapshot_files(info, load_index) -> tuple[_SelectedHubFile, ...]:
+    """Select support files and exactly one complete Transformers weight format."""
+    siblings = {
+        sibling.rfilename: sibling
+        for sibling in (getattr(info, "siblings", None) or [])
+        if isinstance(getattr(sibling, "rfilename", None), str)
+    }
+    selected = {name for name in _STT_SNAPSHOT_SUPPORT_FILES if name in siblings}
+
+    index_name: Optional[str] = None
+    if _STT_SAFETENSORS_INDEX in siblings:
+        index_name = _STT_SAFETENSORS_INDEX
+    elif _STT_SAFETENSORS_WEIGHTS in siblings:
+        selected.add(_STT_SAFETENSORS_WEIGHTS)
+    elif _STT_PYTORCH_INDEX in siblings:
+        index_name = _STT_PYTORCH_INDEX
+    elif _STT_PYTORCH_WEIGHTS in siblings:
+        selected.add(_STT_PYTORCH_WEIGHTS)
+    else:
+        raise SttModelCompatibilityError("The STT repository has no complete model weights.")
+
+    if index_name is not None:
+        weight_map = load_index(index_name).get("weight_map")
+        if not isinstance(weight_map, dict) or not weight_map:
+            raise SttModelCompatibilityError(f"Invalid checkpoint index '{index_name}'.")
+        shards = set(weight_map.values())
+        if not all(isinstance(shard, str) and shard in siblings for shard in shards):
+            raise SttModelCompatibilityError(f"Checkpoint index '{index_name}' has missing shards.")
+        selected.add(index_name)
+        selected.update(shards)
+
+    return tuple(_selected_file_from_sibling(siblings[name]) for name in sorted(selected))
+
+
+def validate_remote_model(model: Optional[str], hf_token: Optional[str] = None) -> dict:
+    """Verify a custom Hub repository is Whisper-compatible without downloading weights."""
+    model_id = resolve_model_id(model)
+    repo = resolve_model_repo(model_id)
+    if model_id in STT_MODELS:
+        return {"model": model_id, "repo": repo}
+
+    try:
+        from huggingface_hub import HfApi
+        info = HfApi(token = hf_token or False).model_info(
+            repo,
+            expand = ["config", "sha"],
+            timeout = 10,
+        )
+    except Exception as exc:
+        raise SttModelCompatibilityError(
+            f"Could not verify STT model '{model_id}'. "
+            "Check that the repository exists and your Hugging Face token can access it."
+        ) from exc
+
+    if not _is_whisper_config(getattr(info, "config", None)):
+        raise SttModelCompatibilityError(
+            f"STT model '{model_id}' is not a compatible Transformers Whisper model."
+        )
+    revision = getattr(info, "sha", None)
+    if not isinstance(revision, str) or not _HF_COMMIT_SHA.fullmatch(revision):
+        raise SttModelCompatibilityError(
+            f"Could not resolve an immutable revision for STT model '{model_id}'."
+        )
+    # The commit that was validated; the download pins to it so the repo cannot
+    # be swapped between validation and snapshot_download (TOCTOU).
+    return {"model": model_id, "repo": repo, "revision": revision}
+
+
+def _is_missing_local_model_error(exc: BaseException) -> bool:
+    """Recognize a local-cache-only miss by name/message, without importing HF
+    internals (tolerates huggingface_hub/Transformers moving the exception)."""
+    current: Optional[BaseException] = exc
+    seen: set[int] = set()
+    while current is not None and id(current) not in seen:
+        seen.add(id(current))
+        if type(current).__name__ in ("LocalEntryNotFoundError", "EntryNotFoundError"):
+            return True
+        message = str(current).lower()
+        if "local_files_only" in message or "does not appear to have a file" in message:
+            return True
+        current = current.__cause__ or current.__context__
+    return False
+
+
+def _snapshot_is_complete(snapshot: Path) -> bool:
+    """True when a cached snapshot holds every file loading needs.
+
+    An aborted download can leave only metadata behind, and an offline lookup
+    cannot know the repo's full file list, so verify config, preprocessor,
+    tokenizer, and weights directly. is_file() follows cache symlinks, so a
+    link from an interrupted blob download does not count.
+    """
+    index = next(
+        (
+            snapshot / name
+            for name in ("model.safetensors.index.json", "pytorch_model.bin.index.json")
+            if (snapshot / name).is_file()
+        ),
+        None,
+    )
+    if index is not None:
+        # Sharded checkpoint (safetensors or PyTorch): every shard must exist.
+        weight_map = _read_json_object(index).get("weight_map")
+        if not isinstance(weight_map, dict) or not weight_map:
+            return False
+        has_weights = all((snapshot / shard).is_file() for shard in set(weight_map.values()))
+    else:
+        has_weights = any(
+            (snapshot / name).is_file() for name in (_STT_SAFETENSORS_WEIGHTS, _STT_PYTORCH_WEIGHTS)
+        )
+    # WhisperProcessor needs the tokenizer: either the fast tokenizer.json or
+    # the slow vocab.json + merges.txt pair.
+    has_tokenizer = (snapshot / "tokenizer.json").is_file() or (
+        (snapshot / "vocab.json").is_file() and (snapshot / "merges.txt").is_file()
+    )
+    return (
+        has_weights
+        and has_tokenizer
+        and (snapshot / "config.json").is_file()
+        and (snapshot / "preprocessor_config.json").is_file()
+    )
+
+
+def is_model_downloaded(model: Optional[str]) -> bool:
+    """True when a usable Whisper snapshot exists in the local HF cache."""
+    try:
+        return _find_complete_cached_snapshot(model) is not None
+    except Exception:
+        return False
+
+
+class _SnapshotDownloadState:
+    """Tracks one background snapshot_download of a dictation repository.
+
+    Like stt_ggml_sidecar's tracker, but a Transformers checkpoint is a whole
+    repo, so progress is the byte count of its cache blobs.
+    """
+
+    def __init__(self) -> None:
+        self._lock = threading.Lock()
+        self._thread: Optional[threading.Thread] = None
+        self._model_id: Optional[str] = None
+        self._repo: Optional[str] = None
+        self._error: Optional[str] = None
+        self._total_bytes: Optional[int] = None
+        self._selected_files: tuple[_SelectedHubFile, ...] = ()
+        self._complete = False
+
+    def status(self) -> dict:
+        with self._lock:
+            downloading = self._thread is not None and self._thread.is_alive()
+            show_progress = downloading or self._complete
+            return {
+                "downloading": downloading,
+                "model": self._model_id if downloading else None,
+                "error": self._error,
+                "bytes_total": self._total_bytes if show_progress else None,
+                "bytes_done": self._blob_bytes() if show_progress else None,
+            }
+
+    def _blob_bytes(self) -> Optional[int]:
+        """Best-effort progress: bytes in the repo's HF cache blobs.
+
+        Counts only the selected support files and one selected weight format,
+        including in-progress ``.incomplete`` blobs.
+        """
+        try:
+            # Caller may hold the non-reentrant self._lock; a bare read is safe.
+            repo = self._repo
+            selected_files = self._selected_files
+            if not repo or not selected_files:
+                return None
+            blobs = _repo_cache_dir(repo) / "blobs"
+            if not blobs.is_dir():
+                return 0
+            done = 0
+            for selected in selected_files:
+                if not selected.blob_key:
+                    continue
+                complete = blobs / selected.blob_key
+                incomplete = blobs / f"{selected.blob_key}.incomplete"
+                candidate = complete if complete.is_file() else incomplete
+                if candidate.is_file():
+                    done += min(candidate.stat().st_size, selected.size)
+            total = self._total_bytes
+            return min(done, total) if total is not None else done
+        except Exception:
+            return None
+
+    def start(
+        self,
+        model_id: str,
+        hf_token: Optional[str] = None,
+        revision: Optional[str] = None,
+    ) -> None:
+        model_id = resolve_model_id(model_id)
+        with self._lock:
+            if self._thread is not None and self._thread.is_alive():
+                if self._model_id == model_id:
+                    return
+                raise SttModelIdError(
+                    f"Another dictation model ('{self._model_id}') is still "
+                    "downloading; wait for it to finish."
+                )
+            self._model_id = model_id
+            self._repo = resolve_model_repo(model_id)
+            self._error = None
+            self._total_bytes = None
+            self._selected_files = ()
+            self._complete = False
+            thread = threading.Thread(
+                target = self._run, args = (self._repo, hf_token, revision), daemon = True
+            )
+            self._thread = thread
+            thread.start()
+
+    def _run(
+        self,
+        repo: str,
+        hf_token: Optional[str],
+        revision: Optional[str] = None,
+    ) -> None:
+        try:
+            from huggingface_hub import HfApi, hf_hub_download, snapshot_download
+
+            info = HfApi(token = hf_token or None).model_info(
+                repo,
+                revision = revision,
+                files_metadata = True,
+                timeout = 30,
+            )
+            if not revision:
+                revision = getattr(info, "sha", None)
+            if not isinstance(revision, str) or not _HF_COMMIT_SHA.fullmatch(revision):
+                raise SttModelCompatibilityError(
+                    f"Could not resolve an immutable revision for STT model '{repo}'."
+                )
+
+            def load_index(filename: str) -> dict:
+                path = hf_hub_download(
+                    repo_id = repo,
+                    filename = filename,
+                    revision = revision,
+                    token = hf_token or None,
+                )
+                return _read_json_object(Path(path))
+
+            selected_files = _select_snapshot_files(info, load_index)
+            total = sum(selected.size for selected in selected_files)
+            with self._lock:
+                self._selected_files = selected_files
+                self._total_bytes = total or None
+            snapshot = Path(
+                snapshot_download(
+                    repo_id = repo,
+                    revision = revision,
+                    allow_patterns = [selected.path for selected in selected_files],
+                    token = hf_token or None,
+                )
+            )
+            if not _snapshot_is_complete(snapshot):
+                raise SttModelCompatibilityError(
+                    f"Downloaded STT snapshot for '{repo}' is incomplete."
+                )
+            _write_revision_record(repo, revision)
+            with self._lock:
+                self._complete = True
+        except Exception as exc:
+            logger.warning("STT snapshot download failed for %s: %s", repo, exc)
+            with self._lock:
+                self._error = f"Download failed for '{repo}'."
+
+
+_download_state = _SnapshotDownloadState()
+
+
+def start_model_download(
+    model: Optional[str],
+    hf_token: Optional[str] = None,
+    revision: Optional[str] = None,
+) -> None:
+    _download_state.start(resolve_model_id(model), hf_token, revision = revision)
+
+
+def download_status() -> dict:
+    return _download_state.status()
+
+
+def _training_active() -> bool:
+    try:
+        from core.training import get_training_backend
+        return bool(get_training_backend().is_training_active())
+    except Exception:
+        return False
+
+
+def _clear_device_cache(device: Optional[str]) -> None:
+    gc.collect()
+    try:
+        import torch
+        if device == "cuda":
+            torch.cuda.empty_cache()
+        elif device == "mps":
+            torch.mps.empty_cache()
+    except Exception:
+        pass
+
+
+def _pick_device():
+    """Return (device, torch_dtype) for the Whisper model.
+
+    CUDA uses float16. MPS and CPU use float32: Whisper's decoder is unstable in
+    float16 on MPS and degenerates into repeated tokens.
+    """
+    try:
+        import torch
+
+        # New loads use CPU during training; a resident GPU model may stay put
+        # when the training admission check confirms enough headroom.
+        training_active = _training_active()
+        if not training_active and torch.cuda.is_available():
+            return "cuda", torch.float16
+        if (
+            not training_active
+            and getattr(torch.backends, "mps", None) is not None
+            and torch.backends.mps.is_available()
+        ):
+            return "mps", torch.float32
+        return "cpu", torch.float32
+    except Exception as exc:
+        logger.debug("STT device detection failed, using CPU: %s", exc)
+        import torch
+        return "cpu", torch.float32
+
+
+def _decode_audio_bounded(audio: bytes):
+    """Decode to 16 kHz mono PCM without buffering unbounded audio.
+
+    A small, highly-compressed upload can expand far past the encoded request
+    limit once decoded, so decode frame-by-frame and enforce the sample cap as
+    frames arrive, then hand the array straight to Whisper.
+    """
+    try:
+        import av
+        import numpy as np
+        from av.error import FFmpegError, InvalidDataError
+    except ImportError as exc:
+        raise SttUnavailableError(
+            "Speech-to-text needs the PyAV package to decode audio. "
+            "Run `unsloth studio update` to install it."
+        ) from exc
+
+    max_samples = _MAX_AUDIO_SECONDS * _TARGET_SAMPLE_RATE
+    sample_count = 0
+    raw_buffer = io.BytesIO()
+    resampler = av.audio.resampler.AudioResampler(
+        format = "s16",
+        layout = "mono",
+        rate = _TARGET_SAMPLE_RATE,
+    )
+    # Group frames before resampling so short clips need one resampler call
+    # rather than one per codec frame.
+    fifo = av.audio.fifo.AudioFifo()
+
+    def write_frame(frame) -> None:
+        nonlocal sample_count
+        array = frame.to_ndarray()
+        sample_count += array.size
+        if sample_count > max_samples:
+            max_minutes = _MAX_AUDIO_SECONDS // 60
+            unit = "minute" if max_minutes == 1 else "minutes"
+            raise SttAudioTooLongError(f"Audio must be {max_minutes} {unit} or shorter.")
+        raw_buffer.write(array)
+
+    try:
+        with av.open(io.BytesIO(audio), mode = "r", metadata_errors = "ignore") as container:
+            if not container.streams.audio:
+                raise SttAudioDecodeError("Could not decode the audio.")
+            frames = iter(container.decode(audio = 0))
+            while True:
+                try:
+                    frame = next(frames)
+                except StopIteration:
+                    break
+                except InvalidDataError:
+                    # Skip a corrupt frame rather than fail the whole transcription.
+                    continue
+                frame.pts = None
+                fifo.write(frame)
+                if fifo.samples >= 500000:
+                    for resampled in resampler.resample(fifo.read()):
+                        write_frame(resampled)
+            if fifo.samples > 0:
+                for resampled in resampler.resample(fifo.read()):
+                    write_frame(resampled)
+            for resampled in resampler.resample(None):
+                write_frame(resampled)
+    except (SttAudioDecodeError, SttAudioTooLongError):
+        raise
+    except (FFmpegError, ValueError, RuntimeError) as exc:
+        raise SttAudioDecodeError("Could not decode the audio.") from exc
+    finally:
+        del fifo, resampler
+
+    if sample_count == 0:
+        raise SttAudioDecodeError("Could not decode the audio.")
+    decoded = np.frombuffer(raw_buffer.getbuffer(), dtype = np.int16).astype(np.float32)
+    decoded /= 32768.0
+    return decoded
+
+
+class WhisperSttSidecar:
+    """Lazily loaded Whisper model with idle eviction. Thread-safe."""
+
+    def __init__(self, keep_alive_seconds: float = STT_KEEP_ALIVE_SECONDS) -> None:
+        self._engine = None
+        self._model_id: Optional[str] = None
+        self._device: Optional[str] = None
+        self._lock = threading.RLock()
+        self._load_state_lock = threading.Lock()
+        self._loading = False
+        self._load_cancel_event: Optional[threading.Event] = None
+        self._keep_alive_seconds = max(0.0, keep_alive_seconds)
+        self._idle_timer: Optional[threading.Timer] = None
+        self._idle_generation = 0
+
+    @property
+    def loaded_model(self) -> Optional[str]:
+        return self._model_id
+
+    @property
+    def device(self) -> Optional[str]:
+        return self._device
+
+    def is_loading(self) -> bool:
+        with self._load_state_lock:
+            return self._loading
+
+    def cancel_pending_load(self) -> bool:
+        """Cancel a model load without waiting for the model lock."""
+        with self._load_state_lock:
+            event = self._load_cancel_event
+            if not self._loading or event is None:
+                return False
+            event.set()
+            return True
+
+    def wait_for_load_to_settle(self) -> None:
+        """Block until any in-flight load() has exited and freed its memory.
+
+        load() holds self._lock throughout, including the from_pretrained()/
+        .to(device) allocation and cancel cleanup, so acquiring the lock here
+        waits for that memory to be freed.
+        """
+        with self._lock:
+            pass
+
+    def _begin_load(self) -> threading.Event:
+        event = threading.Event()
+        with self._load_state_lock:
+            self._load_cancel_event = event
+            self._loading = True
+        return event
+
+    def _end_load(self, event: threading.Event) -> None:
+        with self._load_state_lock:
+            if self._load_cancel_event is event:
+                self._load_cancel_event = None
+                self._loading = False
+
+    @staticmethod
+    def _raise_if_load_cancelled(event: threading.Event) -> None:
+        if event.is_set():
+            raise SttLoadCancelledError("STT model loading was cancelled so training could start.")
+
+    @property
+    def keep_alive_seconds(self) -> float:
+        return self._keep_alive_seconds
+
+    def _cancel_idle_unload_locked(self) -> None:
+        self._idle_generation += 1
+        timer = self._idle_timer
+        self._idle_timer = None
+        if timer is not None:
+            timer.cancel()
+
+    def _schedule_idle_unload_locked(self) -> None:
+        self._cancel_idle_unload_locked()
+        if self._engine is None or self._keep_alive_seconds <= 0:
+            return
+        generation = self._idle_generation
+        timer = threading.Timer(
+            self._keep_alive_seconds,
+            self._idle_unload,
+            args = (generation,),
+        )
+        timer.daemon = True
+        self._idle_timer = timer
+        timer.start()
+
+    def _idle_unload(self, generation: int) -> None:
+        with self._lock:
+            if generation != self._idle_generation or self._engine is None:
+                return
+            logger.info("Unloading idle STT model %s", self._model_id)
+            self._release_engine_locked()
+
+    def _release_engine_locked(self) -> None:
+        self._cancel_idle_unload_locked()
+        engine = self._engine
+        device = self._device
+        self._engine = None
+        self._model_id = None
+        self._device = None
+        del engine
+        _clear_device_cache(device)
+
+    def _build_model(self, snapshot_path: str, device: str, dtype, cancel_event: threading.Event):
+        """Load a Whisper model + processor from the local Hub cache.
+
+        local_files_only keeps the Model Hub the only download path; a cache
+        miss raises so the caller can surface SttModelNotDownloadedError.
+        """
+        import torch
+        from transformers import WhisperForConditionalGeneration, WhisperProcessor
+
+        processor = None
+        model = None
+        try:
+            processor = WhisperProcessor.from_pretrained(snapshot_path, local_files_only = True)
+            self._raise_if_load_cancelled(cancel_event)
+            model = WhisperForConditionalGeneration.from_pretrained(
+                snapshot_path, torch_dtype = dtype, local_files_only = True
+            )
+            self._raise_if_load_cancelled(cancel_event)
+            model.to(torch.device(device))
+            self._raise_if_load_cancelled(cancel_event)
+            model.eval()
+            return model, processor
+        except SttLoadCancelledError:
+            model = None
+            processor = None
+            _clear_device_cache(device)
+            raise
+
+    def _ensure_model_downloaded(self, model_id: str) -> _CachedSttSnapshot:
+        """Validate the local snapshot before decode or model replacement.
+
+        Returns the checkpoint's multilingual flag when local metadata provides
+        it. Curated defaults are known multilingual.
+        """
+        model_id = resolve_model_id(model_id)
+        with self._lock:
+            if self._engine is not None and self._model_id == model_id:
+                resident_model = (
+                    self._engine[0] if isinstance(self._engine, (tuple, list)) else self._engine
+                )
+                generation_config = getattr(resident_model, "generation_config", None)
+                is_multilingual = getattr(generation_config, "is_multilingual", None)
+                return _CachedSttSnapshot(
+                    path = None,
+                    is_multilingual = is_multilingual if isinstance(is_multilingual, bool) else None,
+                )
+        snapshot_path = _find_complete_cached_snapshot(model_id)
+        if snapshot_path is None:
+            raise SttModelNotDownloadedError(
+                f"STT model '{model_id}' is not downloaded. "
+                "Download it in Settings, then Voice, before loading it."
+            )
+
+        if model_id in STT_MODELS:
+            return _CachedSttSnapshot(path = snapshot_path, is_multilingual = True)
+
+        if not _is_whisper_config(_read_json_object(snapshot_path / "config.json")):
+            raise SttModelCompatibilityError(
+                f"STT model '{model_id}' is not a compatible Transformers Whisper model."
+            )
+        generation_config = _read_json_object(snapshot_path / "generation_config.json")
+        is_multilingual = generation_config.get("is_multilingual")
+        if isinstance(is_multilingual, bool):
+            return _CachedSttSnapshot(path = snapshot_path, is_multilingual = is_multilingual)
+        if resolve_model_repo(model_id).lower().endswith(".en"):
+            return _CachedSttSnapshot(path = snapshot_path, is_multilingual = False)
+        return _CachedSttSnapshot(path = snapshot_path, is_multilingual = None)
+
+    def load(self, model: Optional[str] = None):
+        """Load (or switch to) a model, reusing it if already resident.
+
+        Returns a ``(model, processor)`` pair.
+        """
+        model_id = resolve_model_id(model)
+        with self._lock:
+            ensure_stt_available()
+            if self._engine is not None and self._model_id == model_id:
+                self._schedule_idle_unload_locked()
+                return self._engine
+            import torch
+
+            cancel_event = self._begin_load()
+            candidate = None
+            device: Optional[str] = None
+            try:
+                cached = self._ensure_model_downloaded(model_id)
+                snapshot_path = cached.path
+                if snapshot_path is None:
+                    raise SttModelNotDownloadedError(
+                        f"STT model '{model_id}' is not downloaded. "
+                        "Download it in Settings, then Voice, before loading it."
+                    )
+                self._raise_if_load_cancelled(cancel_event)
+                device, dtype = _pick_device()
+                self._release_engine_locked()
+                logger.info("Loading STT model %s (%s) on %s", model_id, snapshot_path, device)
+
+                def not_downloaded(cause: BaseException) -> SttModelNotDownloadedError:
+                    return SttModelNotDownloadedError(
+                        f"STT model '{model_id}' is not downloaded. "
+                        "Download it in Settings, then Voice, before loading it."
+                    )
+
+                retry_on_cpu = False
+                try:
+                    candidate = self._build_model(str(snapshot_path), device, dtype, cancel_event)
+                    self._raise_if_load_cancelled(cancel_event)
+                except SttLoadCancelledError:
+                    raise
+                except Exception as exc:
+                    if _is_missing_local_model_error(exc):
+                        raise not_downloaded(exc) from exc
+                    if device == "cpu":
+                        raise
+                    logger.warning("STT load on %s failed (%s); retrying on CPU", device, exc)
+                    retry_on_cpu = True
+                if retry_on_cpu:
+                    # Retry outside the handler: live exception state pins frames
+                    # referencing the partly loaded model, so leave it before
+                    # clearing the cache to release that memory.
+                    _clear_device_cache(device)
+                    try:
+                        candidate = self._build_model(
+                            str(snapshot_path),
+                            "cpu",
+                            torch.float32,
+                            cancel_event,
+                        )
+                        self._raise_if_load_cancelled(cancel_event)
+                    except SttLoadCancelledError:
+                        raise
+                    except Exception as cpu_exc:
+                        if _is_missing_local_model_error(cpu_exc):
+                            raise not_downloaded(cpu_exc) from cpu_exc
+                        raise
+                    device = "cpu"
+                with self._load_state_lock:
+                    self._raise_if_load_cancelled(cancel_event)
+                    self._engine = candidate
+                    self._model_id = model_id
+                    self._device = device
+                    self._load_cancel_event = None
+                    self._loading = False
+                self._schedule_idle_unload_locked()
+                logger.info("STT model %s ready on %s", model_id, device)
+                return self._engine
+            except SttLoadCancelledError:
+                candidate = None
+                self._release_engine_locked()
+                _clear_device_cache(device)
+                raise
+            finally:
+                self._end_load(cancel_event)
+
+    def _transcribe_decoded(self, model_id: str, decoded_audio, generate_kwargs: dict) -> str:
+        """Run Whisper on already-decoded 16 kHz mono PCM and return text.
+
+        Feeds a pre-decoded array so nothing here touches the Transformers audio
+        path (torchcodec/ffmpeg). Splits into 30s windows (Whisper's receptive
+        field); short clips take one pass.
+        """
+        import torch
+
+        model, processor = self.load(model_id)
+        effective_generate_kwargs = dict(generate_kwargs)
+        generation_config = getattr(model, "generation_config", None)
+        if getattr(generation_config, "is_multilingual", None) is False:
+            # English-only checkpoints fix language and task in their generation
+            # config, and Transformers rejects passing them here.
+            effective_generate_kwargs.pop("task", None)
+            effective_generate_kwargs.pop("language", None)
+        window = 30 * _TARGET_SAMPLE_RATE
+        target_dtype = getattr(model, "dtype", None)
+        parts: list[str] = []
+        with torch.no_grad():
+            for start in range(0, max(len(decoded_audio), 1), window):
+                segment = decoded_audio[start : start + window]
+                if segment.size == 0:
+                    continue
+                inputs = processor(
+                    segment,
+                    sampling_rate = _TARGET_SAMPLE_RATE,
+                    return_tensors = "pt",
+                )
+                features = inputs.input_features.to(model.device)
+                if target_dtype is not None:
+                    features = features.to(target_dtype)
+                generated = model.generate(features, **effective_generate_kwargs)
+                text = processor.batch_decode(generated, skip_special_tokens = True)
+                parts.append(text[0] if text else "")
+        return " ".join(part.strip() for part in parts if part.strip()).strip()
+
+    def transcribe(
+        self,
+        audio: bytes,
+        model: Optional[str] = None,
+        language: Optional[str] = None,
+        fast: bool = False,
+    ) -> dict:
+        """Transcribe encoded audio bytes to text.
+
+        Accepts any container PyAV can decode: wav, mp3, opus/webm, ogg,
+        m4a/aac. Returns {text, language, duration, model}.
+        """
+        # Reject a missing runtime up front, before the cache and bounded decode.
+        ensure_stt_available()
+        # A set language beats auto-detect. API takes BCP-47; Whisper wants short
+        # codes like en or fr.
+        lang = normalize_whisper_language(language)
+        # Pin the requested id: another request may switch the resident model
+        # mid-transcription, so sidecar state is not this request's identity.
+        model_id = resolve_model_id(model)
+        known_languages = _known_whisper_languages()
+        if lang is not None and known_languages is not None and lang not in known_languages:
+            raise SttLanguageError(
+                f"Language '{language}' is not supported by STT model '{model_id}'."
+            )
+        cached = self._ensure_model_downloaded(model_id)
+        if cached.is_multilingual is False and lang not in (None, "en"):
+            raise SttLanguageError(
+                f"Language '{language}' is not supported by English-only STT model '{model_id}'."
+            )
+        decoded_audio = _decode_audio_bounded(audio)
+        # condition_on_prev_tokens=False stops a fresh clip inheriting prior
+        # context, which causes runaway repeats.
+        generate_kwargs = {
+            "task": "transcribe",
+            "condition_on_prev_tokens": False,
+            "num_beams": 5,
+        }
+        if lang is not None:
+            generate_kwargs["language"] = lang
+        if fast:
+            # Short voiced clips: greedy decoding drops beam search for latency.
+            generate_kwargs["num_beams"] = 1
+        # Serialize inference with model switches and unloads.
+        with self._lock:
+            try:
+                text = self._transcribe_decoded(model_id, decoded_audio, generate_kwargs)
+            finally:
+                self._schedule_idle_unload_locked()
+        duration = (len(decoded_audio) / _TARGET_SAMPLE_RATE) if len(decoded_audio) else None
+        return {
+            "text": text,
+            "language": lang,
+            "duration": duration,
+            "model": model_id,
+        }
+
+    def unload(self) -> None:
+        with self._lock:
+            self._release_engine_locked()
+
+
+_sidecar: Optional[WhisperSttSidecar] = None
+
+
+def get_stt_sidecar() -> WhisperSttSidecar:
+    global _sidecar
+    if _sidecar is None:
+        _sidecar = WhisperSttSidecar()
+    return _sidecar
diff --git a/studio/backend/core/rag/embed_llama_server.py b/studio/backend/core/rag/embed_llama_server.py
index b141e59422..facd989b27 100644
--- a/studio/backend/core/rag/embed_llama_server.py
+++ b/studio/backend/core/rag/embed_llama_server.py
@@ -188,7 +188,14 @@ class LlamaServerBackend:
         match = [f for f in files if variant in f.lower()] or files
         filename = sorted(match, key = len)[0]
         logger.info("resolving GGUF embedder %s/%s", repo, filename)
-        self._model_path = hf_hub_download(repo_id = repo, filename = filename, token = token)
+        from utils.hf_cache_settings import active_hf_hub_cache
+
+        self._model_path = hf_hub_download(
+            repo_id = repo,
+            filename = filename,
+            token = token,
+            cache_dir = active_hf_hub_cache(),
+        )
         self._model_repo = desired
         self._dim = None
         return self._model_path
diff --git a/studio/backend/core/rag/embeddings.py b/studio/backend/core/rag/embeddings.py
index 15be7f1249..3354585d2a 100644
--- a/studio/backend/core/rag/embeddings.py
+++ b/studio/backend/core/rag/embeddings.py
@@ -22,6 +22,7 @@ from typing import Callable
 
 from utils.hardware.hardware import DeviceType, get_device
 from utils.transformers_dtype import dtype_kwargs
+from utils.utils import hf_env_offline
 
 from . import config
 
@@ -103,9 +104,15 @@ def _st_module_subdirs(name: str, token: str | None) -> tuple[str, ...]:
         else:
             from huggingface_hub import hf_hub_download
             from huggingface_hub.utils import EntryNotFoundError
+            from utils.hf_cache_settings import active_hf_hub_cache
 
             try:
-                local = hf_hub_download(name, "modules.json", token = token or None)
+                local = hf_hub_download(
+                    name,
+                    "modules.json",
+                    token = token or None,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except EntryNotFoundError:
                 return ()
             data = json.loads(open(local).read())
@@ -119,30 +126,55 @@ def _st_module_subdirs(name: str, token: str | None) -> tuple[str, ...]:
         return ()
 
 
-def _guard_model_security(name: str) -> None:
+def _guard_model_security(name: str, local_only: bool = False) -> None:
     """Refuse to load a repo HF flagged as unsafe: a poisoned pickle deserializes inside
     SentenceTransformer regardless of trust_remote_code. Defense in depth behind the
     /settings gate (a name can also arrive via env/default); local paths and unreachable
     scans fail open inside evaluate_file_security. Never bricks the embedder on a gate error.
+
+    ``local_only`` (offline) inspects the local cache; subdir probes are skipped (they'd hit the
+    network and hang, and the offline gate walks the whole snapshot anyway).
     """
     try:
         from utils.security import evaluate_file_security, security_load_subdirs
 
         token = _ambient_hf_token()
-        # Union the audio-model load roots with the ST module dirs so a flagged pickle
-        # directly under a Transformer module dir (0_Transformer/) blocks instead of
-        # passing as an unreferenced nested shard.
-        load_subdirs = tuple(
-            dict.fromkeys((*security_load_subdirs(name, token), *_st_module_subdirs(name, token)))
-        )
-        blocked = evaluate_file_security(name, hf_token = token, load_subdirs = load_subdirs).blocked
+        if local_only:
+            load_subdirs = ()
+        else:
+            # Union audio-model load roots with ST module dirs so a flagged pickle under a
+            # Transformer module dir blocks instead of passing as an unreferenced nested shard.
+            load_subdirs = tuple(
+                dict.fromkeys(
+                    (*security_load_subdirs(name, token), *_st_module_subdirs(name, token))
+                )
+            )
+        blocked = evaluate_file_security(
+            name, hf_token = token, load_subdirs = load_subdirs, local_only_load = local_only
+        ).blocked
     except Exception:
         return
     if blocked:
-        raise UnsafeEmbeddingModelError(
-            f"Embedding model {name!r} is flagged as unsafe by Hugging Face's security "
-            "scan; refusing to load. Set a different RAG embedding model."
+        reason = (
+            "has cached pickle weights that cannot be security-scanned offline and no "
+            "safetensors alternative"
+            if local_only
+            else "is flagged as unsafe by Hugging Face's security scan"
         )
+        raise UnsafeEmbeddingModelError(
+            f"Embedding model {name!r} {reason}; refusing to load. "
+            "Set a different RAG embedding model."
+        )
+
+
+def _st_accepts_local_files_only(st_cls) -> bool:
+    """Whether this SentenceTransformer version accepts local_files_only; passing it to an
+    older constructor raises, so gate on the signature."""
+    try:
+        import inspect
+        return "local_files_only" in inspect.signature(st_cls.__init__).parameters
+    except Exception:
+        return False
 
 
 def _get(model_name: str | None = None):
@@ -150,15 +182,35 @@ def _get(model_name: str | None = None):
     for a ~1.5x speedup at negligible accuracy loss."""
     global _model, _name
     name = model_name or config.effective_embedding_model()
+    # Capture offline state once so the gate and the load agree (no window where the gate is
+    # skipped as offline but the constructor then reaches the network).
+    local_only = hf_env_offline()
     with _lock:
         if _model is None or _name != name:
             _install_torchao_stub_once()
             from sentence_transformers import SentenceTransformer
+            from utils.hf_cache_settings import active_hf_hub_cache
 
             device = _device()
             logger.info("loading embedding model %s on %s", name, device)
-            _guard_model_security(name)
-            _model = SentenceTransformer(name, device = device, model_kwargs = dtype_kwargs("float16"))
+            _guard_model_security(name, local_only)
+            st_kwargs = dict(
+                device = device,
+                cache_folder = active_hf_hub_cache(),
+                model_kwargs = dtype_kwargs("float16"),
+            )
+            load_target = name
+            if local_only:
+                from utils.utils import hf_cache_snapshot_dir
+                snapshot = hf_cache_snapshot_dir(name)
+                if snapshot is not None:
+                    # Load from the local snapshot dir: a local path never touches the Hub, so
+                    # this is offline-safe on ANY sentence-transformers version (even ones
+                    # predating local_files_only).
+                    load_target = str(snapshot)
+                elif _st_accepts_local_files_only(SentenceTransformer):
+                    st_kwargs["local_files_only"] = True
+            _model = SentenceTransformer(load_target, **st_kwargs)
             _name = name
         return _model
 
diff --git a/studio/backend/core/training/resume.py b/studio/backend/core/training/resume.py
index bbd9a895ab..17183484c5 100644
--- a/studio/backend/core/training/resume.py
+++ b/studio/backend/core/training/resume.py
@@ -4,6 +4,8 @@
 """Helpers for validating resumable training outputs."""
 
 import json
+import pickletools
+import zipfile
 from pathlib import Path
 from typing import Optional
 
@@ -33,21 +35,158 @@ def _checkpoint_step(path: Path) -> int:
         return -1
 
 
-def get_resume_checkpoint_path(path_value: str) -> Optional[str]:
+_MODEL_FILES = (
+    "adapter_model.safetensors",
+    "adapter_model.bin",
+    "model.safetensors",
+    "pytorch_model.bin",
+)
+_MODEL_INDEXES = ("model.safetensors.index.json", "pytorch_model.bin.index.json")
+
+
+def _valid_state_file(path: Path, require_tensor: bool = True) -> bool:
+    try:
+        if not path.is_file() or path.stat().st_size == 0:
+            return False
+        if path.suffix == ".safetensors":
+            try:
+                from safetensors import SafetensorError, safe_open
+            except ImportError:
+                return False
+            try:
+                with safe_open(str(path), framework = "np") as state:
+                    return bool(state.keys())
+            except SafetensorError:
+                return False
+        if path.suffix in {".bin", ".pt"}:
+            with zipfile.ZipFile(path) as state:
+                infos = state.infolist()
+                names = [info.filename for info in infos]
+                data_name = next(
+                    (name for name in names if name == "data.pkl" or name.endswith("/data.pkl")),
+                    None,
+                )
+                if data_name is None:
+                    return False
+                data_prefix = data_name.removesuffix("data.pkl") + "data/"
+                operations = list(pickletools.genops(state.read(data_name)))
+                if not operations or operations[-1][0].name != "STOP":
+                    return False
+                if not require_tensor:
+                    return True
+                # Require a non-empty tensor record; a zero-byte one fails torch.load.
+                return any(
+                    info.filename.startswith(data_prefix)
+                    and not info.is_dir()
+                    and info.file_size > 0
+                    for info in infos
+                )
+        # Unrecognized state-file formats are not usable resume state.
+        return False
+    except (OSError, ValueError, zipfile.BadZipFile):
+        return False
+
+
+def _checkpoint_state(path: Path) -> Optional[int]:
+    try:
+        state = json.loads((path / "trainer_state.json").read_text(encoding = "utf-8"))
+        step = state.get("global_step") if isinstance(state, dict) else None
+    except (OSError, UnicodeDecodeError, json.JSONDecodeError):
+        return None
+    if isinstance(step, bool) or not isinstance(step, int) or step < 0:
+        return None
+    directory_step = _checkpoint_step(path)
+    return step if directory_step < 0 or step == directory_step else None
+
+
+_INDEX_SHARD_SUFFIX = {
+    "model.safetensors.index.json": ".safetensors",
+    "pytorch_model.bin.index.json": ".bin",
+}
+
+
+def _valid_indexed_shard(checkpoint: Path, shard: object, expected_suffix: str) -> bool:
+    # Shard must be a relative, in-format path contained in the checkpoint dir.
+    if not isinstance(shard, str) or not shard:
+        return False
+    if Path(shard).is_absolute() or Path(shard).suffix != expected_suffix:
+        return False
+    try:
+        root = checkpoint.resolve(strict = True)
+        candidate = (checkpoint / shard).resolve(strict = True)
+        candidate.relative_to(root)
+    except (OSError, ValueError):
+        return False
+    return _valid_state_file(candidate)
+
+
+def _has_model_state(path: Path) -> bool:
+    if any(_valid_state_file(path / name) for name in _MODEL_FILES):
+        return True
+    for name in _MODEL_INDEXES:
+        try:
+            index = json.loads((path / name).read_text(encoding = "utf-8"))
+            shards = set(index["weight_map"].values())
+        except (
+            AttributeError,
+            OSError,
+            KeyError,
+            TypeError,
+            UnicodeDecodeError,
+            json.JSONDecodeError,
+        ):
+            continue
+        expected_suffix = _INDEX_SHARD_SUFFIX[name]
+        if shards and all(_valid_indexed_shard(path, shard, expected_suffix) for shard in shards):
+            return True
+    return False
+
+
+def is_resume_checkpoint_valid(
+    path: Path,
+    expected_step: Optional[int] = None,
+    backend: Optional[str] = None,
+) -> bool:
+    step = _checkpoint_state(path) if path.is_dir() else None
+    step_valid = step is not None and (expected_step is None or step == expected_step)
+    if backend == "mlx":
+        valid_bundle = _valid_state_file(path / "adapters.safetensors") and _valid_state_file(
+            path / "optimizer_state.safetensors"
+        )
+    else:
+        valid_bundle = (
+            _has_model_state(path)
+            # optimizer/scheduler state can be validly tensor-free (e.g. SGD without
+            # momentum); _has_model_state still requires real model tensors.
+            and _valid_state_file(path / "optimizer.pt", require_tensor = False)
+            and _valid_state_file(path / "scheduler.pt", require_tensor = False)
+        )
+        if backend is None and not valid_bundle:
+            valid_bundle = _valid_state_file(path / "adapters.safetensors") and _valid_state_file(
+                path / "optimizer_state.safetensors"
+            )
+    return step_valid and valid_bundle
+
+
+def get_resume_checkpoint_path(
+    path_value: str, expected_step: Optional[int] = None
+) -> Optional[str]:
     path = resolve_output_dir(path_value)
     if not _is_under_outputs(path) or not path.is_dir():
         return None
-    if (path / "trainer_state.json").is_file():
+    if is_resume_checkpoint_valid(path, expected_step):
         return str(path)
 
-    checkpoints = [
-        child
-        for child in path.glob("checkpoint-*")
-        if child.is_dir() and (child / "trainer_state.json").is_file()
-    ]
-    if not checkpoints:
-        return None
-    return str(max(checkpoints, key = _checkpoint_step))
+    checkpoints = sorted(path.glob("checkpoint-*"), key = _checkpoint_step, reverse = True)
+    return next(
+        (
+            str(checkpoint)
+            for checkpoint in checkpoints
+            if _checkpoint_step(checkpoint) >= 0
+            and is_resume_checkpoint_valid(checkpoint, expected_step)
+        ),
+        None,
+    )
 
 
 def normalize_resume_output_dir(path_value: str) -> str:
@@ -78,9 +217,17 @@ def _uses_s3_dataset(run: dict) -> bool:
 def can_resume_run(run: dict) -> bool:
     if run.get("resumed_later"):
         return False
+    # Set when a stop-and-save failed to write a current-step checkpoint.
+    if run.get("resume_blocked"):
+        return False
     if _uses_s3_dataset(run):
         return False
 
+    status = run.get("status")
+    if status == "error":
+        # A save-time crash can report final_step == total_steps with no artifacts; checkpoint state alone decides resumability.
+        return has_resume_state(run.get("output_dir"))
+
     final_step = run.get("final_step")
     total_steps = run.get("total_steps")
     has_remaining_steps = (
@@ -89,8 +236,4 @@ def can_resume_run(run: dict) -> bool:
         or total_steps <= 0
         or final_step < total_steps
     )
-    return (
-        run.get("status") == "stopped"
-        and has_remaining_steps
-        and has_resume_state(run.get("output_dir"))
-    )
+    return status == "stopped" and has_remaining_steps and has_resume_state(run.get("output_dir"))
diff --git a/studio/backend/core/training/training.py b/studio/backend/core/training/training.py
index b407ba39a5..bfbd11a427 100644
--- a/studio/backend/core/training/training.py
+++ b/studio/backend/core/training/training.py
@@ -754,6 +754,9 @@ class TrainingBackend:
     def __init__(self):
         # Subprocess state
         self._proc: Optional[mp.Process] = None
+        # True from the sidecar-swap handshake until the worker is recorded, so
+        # installs and STT loads treat the startup window as active.
+        self._spawn_in_progress: bool = False
         self._event_queue: Any = None
         self._stop_queue: Any = None
         self._pump_thread: Optional[threading.Thread] = None
@@ -761,6 +764,7 @@ class TrainingBackend:
         # Left True after an abnormal death so _ensure_pump_alive spots a crash.
         self._pump_running: bool = False
         self._lock = threading.Lock()
+        self._run_intent_lock = threading.RLock()
 
         # Stop watchdog: after a stop is requested, escalates to force_terminate()
         # if the worker does not exit on its own within a bounded time. The watched
@@ -773,6 +777,7 @@ class TrainingBackend:
         self._progress = TrainingProgress()
         self._should_stop = False
         self._cancel_requested = False  # True only for stop(save=False)
+        self._cancel_cleanup_output_dir: Optional[str] = None
 
         # Throttled training-status logging to the server log (not one line/step).
         self._last_progress_log_ts: float = 0.0
@@ -792,6 +797,8 @@ class TrainingBackend:
         # Job metadata
         self.current_job_id: Optional[str] = None
         self._output_dir: Optional[str] = None
+        self._resume_source_run_id: Optional[str] = None
+        self._terminal_finalize_payload: Optional[dict] = None
 
         # DB persistence
         self._metric_buffer: list[dict] = []
@@ -819,6 +826,7 @@ class TrainingBackend:
         job_id: str,
         *,
         before_spawn = None,
+        resume_source_run_id: Optional[str] = None,
         **kwargs,
     ) -> bool:
         """Spawn a subprocess to run the full training pipeline.
@@ -924,16 +932,21 @@ class TrainingBackend:
                 config["resolved_gpu_ids"] = resolved_gpu_ids
                 config["gpu_selection"] = gpu_selection
 
-            from .worker import run_training_process
+            from utils.hf_cache_settings import child_environment_for_spawn, get_hf_cache_paths
+
+            cache_env = get_hf_cache_paths().child_env({})
 
             try:
-                with native_path_secret_removed_for_child_start():
+                with (
+                    child_environment_for_spawn(cache_env),
+                    native_path_secret_removed_for_child_start(),
+                ):
                     event_queue = _CTX.Queue()
                     stop_queue = _CTX.Queue()
 
                     proc = _CTX.Process(
                         target = run_without_native_path_secret,
-                        args = (run_training_process,),
+                        args = ("core.training.worker", "run_training_process", cache_env),
                         kwargs = {
                             "event_queue": event_queue,
                             "stop_queue": stop_queue,
@@ -956,6 +969,7 @@ class TrainingBackend:
             self.current_job_id = job_id
             self._should_stop = False
             self._cancel_requested = False
+            self._cancel_cleanup_output_dir = None
             self._complete_seen.clear()
             self._progress = TrainingProgress(
                 is_training = True, status_message = "Initializing training..."
@@ -972,7 +986,10 @@ class TrainingBackend:
             self.eval_loss_history.clear()
             self.eval_step_history.clear()
             self.eval_enabled = False
-            self._output_dir = None
+            self._output_dir = config.get("output_dir") if resume_source_run_id else None
+            self._progress.output_dir = self._output_dir
+            self._resume_source_run_id = resume_source_run_id
+            self._terminal_finalize_payload = None
             self._metric_buffer.clear()
             self._run_finalized = False
             self._db_run_created = False
@@ -982,6 +999,7 @@ class TrainingBackend:
             self._db_started_at = datetime.now(timezone.utc).isoformat()
             # Start each job Xet-first; keep config so a stall can respawn over HTTP.
             self._last_full_config = config
+            self._last_hf_cache_env = cache_env
             self._in_model_load = False
             self._xet_fallback_used = False
             self._needs_xet_respawn = False
@@ -990,6 +1008,17 @@ class TrainingBackend:
             # in history during model loading and a fast terminal worker can't race the
             # pump into a duplicate create/finalize. From here the pump only finalizes.
             self._ensure_db_run_created()
+            if resume_source_run_id and not self._db_run_created:
+                if proc.is_alive():
+                    proc.terminate()
+                proc.join(timeout = 5.0)
+                if proc.is_alive():
+                    proc.kill()
+                    proc.join(timeout = 2.0)
+                self._progress.is_training = False
+                self._progress.error = "Resume checkpoint is no longer available."
+                self._spawn_in_progress = False
+                return False
 
             # Assign handles and start the pump together under the lock so a concurrent
             # poll can't see a live _proc with no pump and spawn a duplicate.
@@ -1011,28 +1040,75 @@ class TrainingBackend:
 
     def stop_training(self, save: bool = True) -> bool:
         """Send stop signal to the training subprocess."""
-        self._should_stop = True
-        if not save:
-            self._cancel_requested = True
-        with self._lock:
-            if self._stop_queue is not None:
-                try:
-                    self._stop_queue.put({"type": "stop", "save": save})
-                except (OSError, ValueError):
-                    pass
-            # Update progress immediately for responsive UI.
-            self._progress.status_message = (
-                "Stopping training and saving checkpoint..." if save else "Cancelling training..."
-            )
-        # Guarantee the run finalizes even if the worker wedges after saving.
-        self._start_stop_watchdog(cancel = not save)
+        with self._run_intent_lock:
+            with self._lock:
+                run_id = self.current_job_id
+            if not save and run_id:
+                persist_error: Optional[Exception] = None
+                for attempt in range(_DB_FINALIZE_RETRIES):
+                    try:
+                        from storage.studio_db import mark_run_cancel_requested
+
+                        self._ensure_db_run_created()
+                        with self._lock:
+                            terminal_payload = self._terminal_finalize_payload
+                            if (
+                                terminal_payload
+                                and terminal_payload.get("expected_job_id") == run_id
+                            ):
+                                return False
+                            if not mark_run_cancel_requested(run_id):
+                                if self._db_run_created:
+                                    return False
+                                raise RuntimeError(
+                                    "Training run disappeared before cancellation persisted"
+                                )
+                            if self.current_job_id != run_id:
+                                return False
+                            self._should_stop = self._cancel_requested = True
+                            self._cancel_cleanup_output_dir = self._output_dir
+                            self._output_dir = self._progress.output_dir = None
+                        persist_error = None
+                        break
+                    except Exception as exc:
+                        persist_error = exc
+                        if attempt + 1 < _DB_FINALIZE_RETRIES:
+                            time.sleep(_DB_FINALIZE_RETRY_S)
+                if persist_error is not None:
+                    raise RuntimeError("Failed to persist Stop-without-Save") from persist_error
+            with self._lock:
+                if self.current_job_id != run_id:
+                    return False
+                if save or not run_id:
+                    self._should_stop = True
+                if not save and not run_id:
+                    self._cancel_requested = True
+                    self._cancel_cleanup_output_dir = self._output_dir
+                    self._output_dir = self._progress.output_dir = None
+                if self._stop_queue is not None:
+                    try:
+                        self._stop_queue.put({"type": "stop", "save": save})
+                    except (OSError, ValueError):
+                        pass
+                self._progress.status_message = (
+                    "Stopping training and saving checkpoint..."
+                    if save
+                    else "Cancelling training..."
+                )
+        self._start_stop_watchdog(cancel = not save, expected_job_id = run_id)
         return True
 
-    def _start_stop_watchdog(self, cancel: bool) -> None:
+    def _start_stop_watchdog(
+        self,
+        cancel: bool,
+        expected_job_id: Optional[str] = None,
+    ) -> None:
         """Start a daemon that force-terminates the worker if a requested stop does not
         exit on its own. No-op if no worker is alive or a live watchdog already watches
         this proc (a stale watchdog on an old proc never blocks a new run's watcher)."""
         with self._lock:
+            if expected_job_id is not None and self.current_job_id != expected_job_id:
+                return
             proc = self._proc
             if proc is None or not proc.is_alive():
                 return
@@ -1113,8 +1189,9 @@ class TrainingBackend:
         watched_job_id: Optional[str] = None,
     ) -> None:
         """Finalize parent state after a force-terminate so the UI leaves "Stopping..."
-        even if the worker is wedged in driver teardown; preserves output_dir so a saved
-        checkpoint is kept. No-ops if a new run already replaced the watched worker, so a
+        even if the worker is wedged in driver teardown; preserves output_dir on a save so
+        the checkpoint is kept, and clears it on a cancel (Stop without saving must not
+        offer resume/export). No-ops if a new run already replaced the watched worker, so a
         stale watchdog never marks a fresh run stopped or drops its handle.
 
         Supersession is checked on both the watched proc and job id: start_training sets
@@ -1134,7 +1211,18 @@ class TrainingBackend:
                 return  # a new run is already starting up; leave its state alone
             run_id = self.current_job_id  # == watched_job_id
             self._progress.is_training = False
-            self._progress.status_message = "Training stopped."
+        terminal_payload = self._terminal_finalize_kwargs()
+        status = terminal_payload["status"]
+        error_message = terminal_payload.get("error_message")
+        output_dir = terminal_payload["output_dir"]
+        clear_output_dir = terminal_payload["clear_output_dir"]
+        resume_blocked = bool(terminal_payload.get("resume_blocked"))
+        with self._lock:
+            if self.current_job_id != run_id:
+                return
+            self._progress.status_message = error_message or "Training stopped."
+            if error_message:
+                self._progress.error = error_message
         # Create the row if a start-time create failed (no-op otherwise; skips when the pump
         # is mid-create, in which case its create-then-finalize records the run instead).
         self._ensure_db_run_created()
@@ -1148,7 +1236,8 @@ class TrainingBackend:
             batch: list = []
             final_step = final_loss = duration = None
             loss_history: list = []
-            output_dir = self._output_dir
+            if clear_output_dir:
+                self._output_dir = self._progress.output_dir = None
             if claim:
                 self._run_finalized = True  # claim this run's finalize
                 batch = list(self._metric_buffer)
@@ -1161,7 +1250,17 @@ class TrainingBackend:
                 loss_history = list(self.loss_history)
         if claim:
             self._finish_stopped_run(
-                run_id, output_dir, batch, final_step, final_loss, duration, loss_history
+                run_id,
+                output_dir,
+                batch,
+                final_step,
+                final_loss,
+                duration,
+                loss_history,
+                status = status,
+                error_message = error_message,
+                clear_output_dir = clear_output_dir,
+                resume_blocked = resume_blocked,
             )
         with self._lock:
             if target_proc is None or self._proc is target_proc:
@@ -1176,6 +1275,10 @@ class TrainingBackend:
         final_loss: Optional[float],
         duration: Optional[float],
         loss_history: list,
+        status: str = "stopped",
+        error_message: Optional[str] = None,
+        clear_output_dir: bool = False,
+        resume_blocked: bool = False,
     ) -> None:
         """Record a force-stopped run finished by its captured id, from state snapshotted
         under the lock. insert_metrics_batch upserts and finish_run is an idempotent UPDATE,
@@ -1194,14 +1297,16 @@ class TrainingBackend:
                 sparkline = downsample(loss_history, 50)
                 finish_run(
                     id = run_id,
-                    status = "stopped",
+                    status = status,
                     ended_at = datetime.now(timezone.utc).isoformat(),
                     final_step = final_step,
                     final_loss = final_loss,
                     duration_seconds = duration,
                     loss_sparkline = _json.dumps(sparkline),
                     output_dir = output_dir,
-                    error_message = None,
+                    error_message = error_message,
+                    clear_output_dir = clear_output_dir,
+                    resume_blocked = resume_blocked,
                 )
                 return
             except Exception:
@@ -1231,7 +1336,7 @@ class TrainingBackend:
                 logger.info("Force-terminating training subprocess (pid=%s)", proc.pid)
                 proc.terminate()
             cancelled = self._cancel_requested
-            output_dir = self._output_dir
+            output_dir = self._cancel_cleanup_output_dir or self._output_dir
 
         if proc is not None:
             proc.join(timeout = 5.0)
@@ -1304,7 +1409,11 @@ class TrainingBackend:
         self._last_full_config = config
         logger.warning("Respawning training worker with HF_HUB_DISABLE_XET=1 after Xet stall")
 
-        from .worker import run_training_process
+        cache_env = getattr(self, "_last_hf_cache_env", None)
+        if not cache_env:
+            from utils.hf_cache_settings import get_hf_cache_paths
+            cache_env = get_hf_cache_paths().child_env({})
+        from utils.hf_cache_settings import child_environment_for_spawn
 
         # This run is active, so an install request 409s rather than proceeds: a reservation seen here
         # is transient (an aborting install or short lazy repair). Wait it out instead of stranding the
@@ -1336,12 +1445,15 @@ class TrainingBackend:
         # crashed respawn cannot wedge is_training_active until restart.
         try:
             try:
-                with native_path_secret_removed_for_child_start():
+                with (
+                    child_environment_for_spawn(cache_env),
+                    native_path_secret_removed_for_child_start(),
+                ):
                     event_queue = _CTX.Queue()
                     stop_queue = _CTX.Queue()
                     new_proc = _CTX.Process(
                         target = run_without_native_path_secret,
-                        args = (run_training_process,),
+                        args = ("core.training.worker", "run_training_process", cache_env),
                         kwargs = {
                             "event_queue": event_queue,
                             "stop_queue": stop_queue,
@@ -1595,17 +1707,60 @@ class TrainingBackend:
                             )
 
                 self._ensure_db_run_created()
-                self._finalize_run_in_db(
-                    status = "stopped" if self._should_stop else "error",
-                    error_message = None
-                    if self._should_stop
-                    else "Training process terminated unexpectedly",
-                )
+                terminal_payload = self._terminal_finalize_kwargs()
+                with self._lock:
+                    if terminal_payload["clear_output_dir"]:
+                        self._output_dir = self._progress.output_dir = None
+                    if terminal_payload.get("error_message"):
+                        self._progress.error = terminal_payload["error_message"]
+                        self._progress.status_message = terminal_payload["error_message"]
+                self._finalize_run_in_db(**terminal_payload)
             except Exception:
                 logger.exception("Training event pump: finalization after worker exit failed")
             self._pump_running = False
             return
 
+    def _has_current_resume_checkpoint(self, output_dir, step) -> bool:
+        # A valid checkpoint at the current step means the stop-and-save landed on
+        # disk even if the worker died before confirming it.
+        if not output_dir or not isinstance(step, int) or step <= 0:
+            return False
+        from core.training.resume import get_resume_checkpoint_path
+        return get_resume_checkpoint_path(output_dir, expected_step = step) is not None
+
+    def _terminal_finalize_kwargs(self) -> dict:
+        with self._lock:
+            job_id = self.current_job_id
+            payload = self._terminal_finalize_payload
+            if payload and payload.get("expected_job_id") == job_id:
+                return dict(payload)
+            cancel, stopped = self._cancel_requested, self._should_stop
+            output_dir = None if cancel else self._output_dir
+            step = self._progress.step
+            existing_error = self._progress.error
+        status, error, blocked = (
+            ("stopped", None, cancel)
+            if stopped
+            else (
+                "error",
+                existing_error or "Training process terminated unexpectedly",
+                False,
+            )
+        )
+        # Block only when no valid current-step checkpoint actually landed.
+        if stopped and not cancel and not self._has_current_resume_checkpoint(output_dir, step):
+            status = "error"
+            error = "Stop and Save ended before a valid current-step checkpoint was written."
+            blocked = True
+        return {
+            "status": status,
+            "error_message": error,
+            "output_dir": output_dir,
+            "clear_output_dir": cancel,
+            "resume_blocked": blocked,
+            "expected_job_id": job_id,
+        }
+
     def _handle_event(self, event: dict) -> None:
         """Apply a subprocess event to local state.
 
@@ -1764,6 +1919,15 @@ class TrainingBackend:
             elif etype == "eval_configured":
                 self.eval_enabled = True
 
+            elif etype == "output_dir":
+                event_output_dir = event.get("output_dir")
+                if self._cancel_requested:
+                    self._cancel_cleanup_output_dir = event_output_dir
+                    self._output_dir = self._progress.output_dir = None
+                else:
+                    self._output_dir = event_output_dir
+                    db_action = "persist_output_dir"
+
             elif etype == "status":
                 self._progress.status_message = event.get("message", "")
                 self._progress.is_training = True
@@ -1778,7 +1942,12 @@ class TrainingBackend:
                 self._complete_seen.set()
                 self._progress.is_training = False
                 self._progress.is_completed = not stopped
-                self._output_dir = event.get("output_dir")
+                event_output_dir = event.get("output_dir")
+                if self._cancel_requested:
+                    self._cancel_cleanup_output_dir = event_output_dir
+                    self._output_dir = None
+                else:
+                    self._output_dir = event_output_dir
                 self._progress.output_dir = self._output_dir
                 self._progress.status_message = msg
                 if not self._db_run_created and self.current_job_id and self._db_config:
@@ -1788,11 +1957,16 @@ class TrainingBackend:
                 db_action_kwargs = {
                     "status": "stopped" if stopped else "completed",
                     "output_dir": self._output_dir,
+                    "clear_output_dir": self._cancel_requested,
+                    "expected_job_id": self.current_job_id,
                 }
+                self._terminal_finalize_payload = dict(db_action_kwargs)
 
             elif etype == "error":
                 self._progress.is_training = False
                 self._progress.error = event.get("error", "Unknown error")
+                if self._cancel_requested:
+                    self._output_dir = self._progress.output_dir = None
                 logger.error("Training error: %s", event.get("error"))
                 stack = event.get("stack", "")
                 if stack:
@@ -1801,29 +1975,36 @@ class TrainingBackend:
                     db_action = "create_and_finalize"
                 else:
                     db_action = "finalize"
+                stop_save_failed = (
+                    self._should_stop
+                    and not self._cancel_requested
+                    and not self._has_current_resume_checkpoint(
+                        self._output_dir, self._progress.step
+                    )
+                )
                 db_action_kwargs = {
-                    "status": "stopped" if self._should_stop else "error",
+                    "status": "stopped"
+                    if self._should_stop
+                    and not stop_save_failed
+                    and not event.get("keep_error_status")
+                    else "error",
                     "error_message": event.get("error", "Unknown error"),
+                    "output_dir": self._output_dir,
+                    "clear_output_dir": self._cancel_requested,
+                    "resume_blocked": stop_save_failed or bool(event.get("resume_blocked")),
+                    "expected_job_id": self.current_job_id,
                 }
+                self._terminal_finalize_payload = dict(db_action_kwargs)
 
         # --- DB I/O outside the lock ---
         if db_action == "create_run":
-            try:
-                from storage.studio_db import create_run
-
-                create_run(
-                    id = db_action_kwargs["job_id"],
-                    model_name = db_action_kwargs["model_name"],
-                    dataset_name = db_action_kwargs["dataset_name"],
-                    config_json = db_action_kwargs["config_json"],
-                    started_at = db_action_kwargs["started_at"],
-                    total_steps = db_action_kwargs["total_steps"],
-                )
-                self._db_run_created = True
+            self._ensure_db_run_created()
+            if self._db_run_created:
                 if db_action_kwargs["total_steps"]:
                     self._db_total_steps_set = True
-            except Exception:
-                logger.warning("Failed to create DB run record", exc_info = True)
+                self._persist_output_dir()
+        elif db_action == "persist_output_dir":
+            self._persist_output_dir()
         elif db_action == "create_and_finalize":
             self._ensure_db_run_created()
             self._finalize_run_in_db(**db_action_kwargs)
@@ -1842,6 +2023,22 @@ class TrainingBackend:
         if etype == "progress":
             self._log_training_progress()
 
+    def _persist_output_dir(self) -> None:
+        with self._lock:
+            if (
+                not self._output_dir
+                or not self.current_job_id
+                or not self._db_run_created
+                or self._cancel_requested
+            ):
+                return
+            run_id, output_dir = self.current_job_id, self._output_dir
+        try:
+            from storage.studio_db import update_run_output_dir
+            update_run_output_dir(run_id, output_dir)
+        except Exception:
+            logger.warning("Failed to persist output_dir", exc_info = True)
+
     def _log_training_progress(self) -> None:
         """One throttled training-status line to the server log (the per-step stream
         still goes to the UI via SSE): first step, then at most every 30s, plus the
@@ -1875,6 +2072,7 @@ class TrainingBackend:
         caller create at a time, and ``_db_run_created`` is published only after
         ``create_run`` commits, so a concurrent finalize never runs ``finish_run`` against a
         not-yet-inserted row (a zero-row UPDATE that would leave the run stuck as running)."""
+        self._run_intent_lock.acquire()
         with self._lock:
             if (
                 self._db_run_created
@@ -1882,6 +2080,7 @@ class TrainingBackend:
                 or not self.current_job_id
                 or not self._db_config
             ):
+                self._run_intent_lock.release()
                 return
             self._db_create_in_progress = True  # only one caller creates
             job_id = self.current_job_id
@@ -1898,6 +2097,12 @@ class TrainingBackend:
                 or _s3_dataset_name(db_config.get("s3_dataset"))
                 or "unknown"
             )
+            with self._lock:
+                if self.current_job_id != job_id:
+                    return
+                output_dir = self._output_dir
+                cancel_requested = self._cancel_requested
+                resumed_from_run_id = self._resume_source_run_id
             create_run(
                 id = job_id,
                 model_name = db_config["model_name"],
@@ -1905,6 +2110,9 @@ class TrainingBackend:
                 config_json = _json.dumps(db_config),
                 started_at = started_at,
                 total_steps = total_steps,
+                output_dir = output_dir,
+                cancel_requested = cancel_requested,
+                resumed_from_run_id = resumed_from_run_id,
             )
             created = True
         except Exception:
@@ -1919,12 +2127,15 @@ class TrainingBackend:
                     if created:
                         self._db_run_created = True  # publish only after the insert commits
                     self._db_create_in_progress = False
+            self._run_intent_lock.release()
 
     def _finalize_run_in_db(
         self,
         status: str,
         error_message: Optional[str] = None,
         output_dir: Optional[str] = None,
+        clear_output_dir: bool = False,
+        resume_blocked: bool = False,
         expected_job_id: Optional[str] = None,
     ) -> None:
         """Flush remaining metrics and mark a run finished in the DB. Claims the finalize
@@ -1947,26 +2158,33 @@ class TrainingBackend:
             duration = self._progress.elapsed_seconds
             loss_history = list(self.loss_history)
         self._flush_metrics_to_db(run_id = run_id)
-        try:
-            from storage.studio_db import finish_run
-            from utils.downsample import downsample
+        for attempt in range(_DB_FINALIZE_RETRIES):
+            try:
+                from storage.studio_db import finish_run
+                from utils.downsample import downsample
 
-            sparkline = downsample(loss_history, 50)
-            finish_run(
-                id = run_id,
-                status = status,
-                ended_at = datetime.now(timezone.utc).isoformat(),
-                final_step = final_step,
-                final_loss = final_loss,
-                duration_seconds = duration,
-                loss_sparkline = _json.dumps(sparkline),
-                output_dir = output_dir,
-                error_message = error_message,
-            )
-        except Exception:
-            with self._lock:
-                self._run_finalized = False  # unclaim so a later flush can retry
-            logger.warning("Failed to finalize run in DB (status=%s)", status, exc_info = True)
+                finish_run(
+                    id = run_id,
+                    status = status,
+                    ended_at = datetime.now(timezone.utc).isoformat(),
+                    final_step = final_step,
+                    final_loss = final_loss,
+                    duration_seconds = duration,
+                    loss_sparkline = _json.dumps(downsample(loss_history, 50)),
+                    output_dir = output_dir,
+                    error_message = error_message,
+                    clear_output_dir = clear_output_dir,
+                    resume_blocked = resume_blocked,
+                )
+                return
+            except Exception:
+                if attempt + 1 < _DB_FINALIZE_RETRIES:
+                    time.sleep(_DB_FINALIZE_RETRY_S)
+                    continue
+                with self._lock:
+                    if self.current_job_id == run_id:
+                        self._run_finalized = False
+                logger.warning("Failed to finalize run in DB (status=%s)", status, exc_info = True)
 
     def _flush_metrics_to_db(self, run_id: Optional[str] = None) -> None:
         """Flush buffered metrics to the DB and update live progress. The target run id,
diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py
index 111f4fdd0f..5ded18ea45 100644
--- a/studio/backend/core/training/worker.py
+++ b/studio/backend/core/training/worker.py
@@ -90,6 +90,79 @@ _FAST_PATH_HOOKS_SKIP_ENV = "UNSLOTH_STUDIO_SKIP_FAST_PATH_HOOKS"
 # run_training_process() and isn't GC'd mid-run.
 _WINDOWS_ROCM_GROUPED_MM_LIB = None
 
+
+def _install_grouped_mm_cpu_fallback(torch_mod, logger, label):
+    """Register a Python mm/bmm fallback for torch._grouped_mm and return the Library.
+
+    RDNA4 (gfx1200/gfx1201) ships a null HIP _grouped_mm kernel on ROCm <= 7.12
+    (fixed in 7.13; ROCm/TheRock #5284). JitDecomp dispatches _grouped_mm to the
+    null kernel and crashes; overriding the CUDA dispatch key bypasses it. Shared
+    by the Windows and Linux ROCm guards. Keep the returned Library referenced so
+    the registration outlives the caller.
+    """
+    import warnings as _warnings
+
+    _gm_lib = torch_mod.library.Library("aten", "IMPL")
+
+    def _grouped_mm_safe_impl(
+        self,
+        mat2,
+        offs = None,
+        bias = None,
+        out_dtype = None,
+    ):
+        """Python mm/bmm fallback for _grouped_mm on gfx120X (null HIP kernel, ROCm <= 7.12)."""
+        _t = torch_mod
+        if offs is None:
+            # No offsets: 2-D -> mm, 3-D batched -> bmm (unconditional mm broke 3-D MoE).
+            if self.dim() == 3 and mat2.dim() == 3:
+                result = _t.bmm(self.contiguous(), mat2.contiguous())
+            elif self.dim() == 3 and mat2.dim() == 2:
+                result = _t.matmul(self.contiguous(), mat2.contiguous())
+            elif self.dim() == 2 and mat2.dim() == 3:
+                result = _t.matmul(self.contiguous(), mat2.contiguous())
+            else:
+                result = _t.mm(self.contiguous(), mat2.contiguous())
+        else:
+            # Grouped: offs[i] is the exclusive end-row of group i.
+            offs_list = offs.tolist()
+            pieces = []
+            prev = 0
+            for idx, end in enumerate(offs_list):
+                end = int(end)
+                a_part = self[prev:end].contiguous()
+                b_part = mat2[idx].contiguous() if mat2.dim() == 3 else mat2.contiguous()
+                pieces.append(_t.mm(a_part, b_part))
+                prev = end
+            # Include trailing rows not covered by offs.
+            if prev < self.shape[0]:
+                a_tail = self[prev:].contiguous()
+                b_tail = mat2[-1].contiguous() if mat2.dim() == 3 else mat2.contiguous()
+                pieces.append(_t.mm(a_tail, b_tail))
+            result = (
+                _t.cat(pieces, dim = 0)
+                if pieces
+                else _t.zeros(0, mat2.shape[-1], device = self.device, dtype = self.dtype)
+            )
+        if bias is not None:
+            result = result + bias
+        if out_dtype is not None:
+            result = result.to(out_dtype)
+        elif result.dtype != self.dtype:
+            result = result.to(self.dtype)
+        return result
+
+    with _warnings.catch_warnings():
+        _warnings.simplefilter("ignore")
+        _gm_lib.impl("_grouped_mm", _grouped_mm_safe_impl, "CUDA")
+    logger.info(
+        "%s: patched _grouped_mm CUDA dispatch (null HIP kernel on gfx120X, "
+        "ROCm <= 7.12 -- bypassed with Python mm fallback)",
+        label,
+    )
+    return _gm_lib
+
+
 # Subprocesses don't inherit os.add_dll_directory registrations. Replicate
 # main.py's Windows ROCm DLL setup so the first `import torch` finds
 # amdhip64.dll. Handles retained at module scope so they aren't GC'd.
@@ -702,8 +775,9 @@ def _rocm_classify_unified_memory(props: Any) -> tuple[str, bool]:
     3. Device-name substring match (last resort when all arch attrs absent;
        AMD SDK / Radeon wheels may not populate them):
          - gfx1150 Strix Point: ``Radeon 890M``, ``Radeon 880M``
-         - gfx1151 Strix Halo:  ``Radeon 8060S`` (Ryzen AI MAX+ 395),
-                                ``Radeon 8050S`` (cut-down SKU)
+         - gfx1151 Strix Halo / Gorgon Halo:  ``Radeon 8065S`` (Ryzen AI
+                                Max+ 495), ``Radeon 8060S`` (Ryzen AI MAX+
+                                395), ``Radeon 8050S`` (cut-down SKU)
     """
     gcn_arch = ""
     for _attr in ("gcnArchName", "gcn_arch_name", "arch_name", "gfx_arch_name"):
@@ -728,7 +802,11 @@ def _rocm_classify_unified_memory(props: Any) -> tuple[str, bool]:
     # Arch attrs absent — fall back to device-name matching.
     dev_lower = (getattr(props, "name", "") or "").lower()
     is_unified = (
-        "890m" in dev_lower or "880m" in dev_lower or "8060s" in dev_lower or "8050s" in dev_lower
+        "890m" in dev_lower
+        or "880m" in dev_lower
+        or "8065s" in dev_lower
+        or "8060s" in dev_lower
+        or "8050s" in dev_lower
     )
     return gcn_arch, is_unified
 
@@ -1840,8 +1918,15 @@ def _run_mlx_training(event_queue, stop_queue, config):
     # Resolve to ~/.unsloth/studio/outputs/ so the export page finds it
     from utils.paths import ensure_dir
 
-    output_dir = _resolve_mlx_output_dir(config, model_name)
+    # Resume must land in the original run dir even when config lacks output_dir.
+    resume_dir = config.get("output_dir", "") or _output_dir_from_resume_checkpoint(
+        resume_from_checkpoint
+    )
+    output_dir = _resolve_mlx_output_dir(
+        {**config, "output_dir": resume_dir} if resume_dir else config, model_name
+    )
     ensure_dir(Path(output_dir))
+    _emit_output_dir(event_queue, output_dir)
 
     # ── 6. Create trainer ──
     eval_steps_val = config.get("eval_steps", 0) or 0
@@ -2067,6 +2152,17 @@ def _run_mlx_training(event_queue, stop_queue, config):
 
     trainer.add_eval_callback(_on_eval)
 
+    _opt_ref = [None]
+    _orig_build_optimizer = getattr(trainer, "_build_optimizer", None)
+
+    if callable(_orig_build_optimizer):
+
+        def _capture_optimizer(total_steps):
+            _opt_ref[0] = _orig_build_optimizer(total_steps)
+            return _opt_ref[0]
+
+        trainer._build_optimizer = _capture_optimizer
+
     # ── 11. Run training ──
     gc.collect()
     mx.synchronize()
@@ -2082,31 +2178,58 @@ def _run_mlx_training(event_queue, stop_queue, config):
         trainer.save_model = _save_model
 
     # ── 12. Save and finalize ──
-    if trainer.stop_requested:
-        if not _stop_save[0]:
-            # Cancel (save=False): skip saving.
-            _send("complete", output_dir = None, status_message = "Training cancelled")
+    def _finish_tracking() -> None:
+        # Runs on every save/finalize exit so TB/W&B never leak on early return.
+        if tb_writer is not None:
+            try:
+                tb_writer.close()
+            except Exception:
+                pass
+        if wandb_run is not None:
+            try:
+                wandb_run.finish()
+            except Exception:
+                pass
+
+    def _stop_checkpoint_ok() -> bool:
+        if _write_mlx_stop_checkpoint(trainer, _opt_ref[0], output_dir):
+            return True
+        _send(
+            "error",
+            error = (
+                "Failed to save a resumable checkpoint after stop. "
+                "Model files were saved, but this run cannot be resumed."
+            ),
+            # A user stop finalizes as 'stopped'; keep this failure's error status so history explains it.
+            keep_error_status = True,
+            # Older checkpoints are stale; resuming would roll back past this stop.
+            resume_blocked = True,
+        )
+        return False
+
+    try:
+        if trainer.stop_requested:
+            if not _stop_save[0]:
+                # Cancel (save=False): skip saving.
+                _send("complete", output_dir = None, status_message = "Training cancelled")
+            else:
+                _send("status", status_message = "Saving stopped model...")
+                mx.synchronize()
+                trainer.save_model(output_dir)
+                # Stop-and-save promises a resumable checkpoint, not just model files.
+                if not _stop_checkpoint_ok():
+                    return
+                _send("complete", output_dir = output_dir, status_message = "Training stopped")
         else:
-            _send("status", status_message = "Saving stopped model...")
+            _send("status", status_message = "Saving model...")
             mx.synchronize()
             trainer.save_model(output_dir)
-            _send("complete", output_dir = output_dir, status_message = "Training stopped")
-    else:
-        _send("status", status_message = "Saving model...")
-        mx.synchronize()
-        trainer.save_model(output_dir)
-        _send("complete", output_dir = output_dir, status_message = "Training completed")
-
-    if tb_writer is not None:
-        try:
-            tb_writer.close()
-        except Exception:
-            pass
-    if wandb_run is not None:
-        try:
-            wandb_run.finish()
-        except Exception:
-            pass
+            # A save-stop can race the natural final save; it made the same promise.
+            if trainer.stop_requested and _stop_save[0] and not _stop_checkpoint_ok():
+                return
+            _send("complete", output_dir = output_dir, status_message = "Training completed")
+    finally:
+        _finish_tracking()
 
 
 def _is_current_process_apple_silicon() -> bool:
@@ -2644,80 +2767,8 @@ def run_training_process(*, event_queue: Any, stop_queue: Any, config: dict) ->
             # so 7.13+ uses the real GPU kernel.
             if not _hip_ver_at_least(7, 13):
                 try:
-                    import warnings as _warnings
-
-                    _gm_lib = _torch_for_rocm.library.Library("aten", "IMPL")
-
-                    def _grouped_mm_safe_impl(
-                        self,
-                        mat2,
-                        offs = None,
-                        bias = None,
-                        out_dtype = None,
-                    ):
-                        """Python mm/bmm fallback for _grouped_mm on gfx1200 (null HIP kernel, ROCm ≤ 7.12)."""
-                        _t = _torch_for_rocm
-                        if offs is None:
-                            # No offsets: 2-D -> mm, 3-D batched -> bmm
-                            # (unconditional mm broke 3-D MoE).
-                            if self.dim() == 3 and mat2.dim() == 3:
-                                result = _t.bmm(self.contiguous(), mat2.contiguous())
-                            elif self.dim() == 3 and mat2.dim() == 2:
-                                # Broadcast 2-D mat2 across the batch dim.
-                                result = _t.matmul(self.contiguous(), mat2.contiguous())
-                            elif self.dim() == 2 and mat2.dim() == 3:
-                                # Broadcast 2-D self across batch via matmul.
-                                result = _t.matmul(self.contiguous(), mat2.contiguous())
-                            else:
-                                result = _t.mm(self.contiguous(), mat2.contiguous())
-                        else:
-                            # Grouped: offs[i] is the exclusive end-row of group i.
-                            offs_list = offs.tolist()
-                            pieces = []
-                            prev = 0
-                            for idx, end in enumerate(offs_list):
-                                end = int(end)
-                                a_part = self[prev:end].contiguous()
-                                if mat2.dim() == 3:
-                                    b_part = mat2[idx].contiguous()
-                                else:
-                                    b_part = mat2.contiguous()
-                                pieces.append(_t.mm(a_part, b_part))
-                                prev = end
-                            # Include trailing rows not covered by offs.
-                            if prev < self.shape[0]:
-                                a_tail = self[prev:].contiguous()
-                                b_tail = (
-                                    mat2[-1].contiguous() if mat2.dim() == 3 else mat2.contiguous()
-                                )
-                                pieces.append(_t.mm(a_tail, b_tail))
-                            result = (
-                                _t.cat(pieces, dim = 0)
-                                if pieces
-                                else _t.zeros(
-                                    0,
-                                    mat2.shape[-1],
-                                    device = self.device,
-                                    dtype = self.dtype,
-                                )
-                            )
-                        if bias is not None:
-                            result = result + bias
-                        if out_dtype is not None:
-                            result = result.to(out_dtype)
-                        elif result.dtype != self.dtype:
-                            result = result.to(self.dtype)
-                        return result
-
-                    with _warnings.catch_warnings():
-                        _warnings.simplefilter("ignore")
-                        _gm_lib.impl("_grouped_mm", _grouped_mm_safe_impl, "CUDA")
-
-                    _WINDOWS_ROCM_GROUPED_MM_LIB = _gm_lib  # prevent GC
-                    logger.info(
-                        "Windows ROCm: patched _grouped_mm CUDA dispatch "
-                        "(null HIP kernel on gfx1200, ROCm ≤ 7.12 — "
-                        "bypassed with Python mm fallback)"
+                    _WINDOWS_ROCM_GROUPED_MM_LIB = _install_grouped_mm_cpu_fallback(
+                        _torch_for_rocm, logger, "Windows ROCm"
                     )
                 except Exception as _patch_exc:
                     logger.warning(
@@ -2731,6 +2782,44 @@ def run_training_process(*, event_queue: Any, stop_queue: Any, config: dict) ->
                     "skipping Python fallback (AMD fixed gfx1200 null kernel in ROCm 7.13)"
                 )
 
+    # ── 1f-linux. Linux ROCm RDNA4 _grouped_mm null kernel ──
+    # The win32 guard above misses Linux: RDNA4 (gfx1200/gfx1201) hits the same null
+    # HIP _grouped_mm kernel at ROCm <= 7.12 (fixed 7.13, ROCm/TheRock #5284). Gate on
+    # arch + HIP < 7.13 so NVIDIA/CUDA and non-RDNA4 AMD are untouched; no-op if fixed.
+    if sys.platform.startswith("linux") and _hw.IS_ROCM:
+        try:
+            _torch_lin = sys.modules.get("torch")
+            if _torch_lin is not None and _torch_lin.cuda.is_available():
+                # Prefer torch.version.hip, else rocmX.Y from torch.__version__ (AMD
+                # SDK / Radeon wheels leave version.hip unset). Unknown version on a
+                # gfx120X build -> assume affected unless it is a post-fix rocmsdk wheel.
+                _hip_str = str(getattr(getattr(_torch_lin, "version", None), "hip", "") or "")
+                _ver = getattr(_torch_lin, "__version__", "").lower()
+                _m = re.match(r"(\d+)\.(\d+)", _hip_str) or re.search(r"rocm(\d+)\.(\d+)", _ver)
+                if _m:
+                    _hip_lt_713 = (int(_m.group(1)), int(_m.group(2))) < (7, 13)
+                else:
+                    _hip_lt_713 = "rocmsdk" not in _ver
+                # Scan every visible GPU (device_map="balanced" can place layers on a
+                # later RDNA4 card, so device 0 is not enough). Match gfx120X by arch,
+                # or by RX 9000 / R9700 name when the wheel omits gcnArchName.
+                _rdna4 = False
+                for _i in range(_torch_lin.cuda.device_count()):
+                    _props = _torch_lin.cuda.get_device_properties(_i)
+                    _lin_arch, _ = _rocm_classify_unified_memory(_props)
+                    _lin_name = (getattr(_props, "name", "") or "").lower()
+                    if _lin_arch.lower() in ("gfx1200", "gfx1201") or (
+                        not _lin_arch and re.search(r"rx\s*90[0-9]0|r9700", _lin_name)
+                    ):
+                        _rdna4 = True
+                        break
+                if _rdna4 and _hip_lt_713:
+                    _WINDOWS_ROCM_GROUPED_MM_LIB = _install_grouped_mm_cpu_fallback(
+                        _torch_lin, logger, "Linux ROCm gfx120X"
+                    )
+        except Exception as _gm_lin_exc:
+            logger.warning("Linux ROCm gfx120X: could not patch _grouped_mm: %s", _gm_lin_exc)
+
     # ── 1g. ROCm OOM guard ──
     # On ROCm, exhausting VRAM can hang the HIP driver instead of raising.
     # set_per_process_memory_fraction caps the allocator so PyTorch raises
@@ -3177,6 +3266,7 @@ def run_training_process(*, event_queue: Any, stop_queue: Any, config: dict) ->
             )
         output_dir = str(resolve_output_dir(output_dir))
         ensure_dir(Path(output_dir))
+        _emit_output_dir(event_queue, output_dir)
 
         tensorboard_dir = config.get("tensorboard_dir")
         if config.get("enable_tensorboard", False):
@@ -3296,6 +3386,61 @@ def _send_status(event_queue: Any, message: str) -> None:
     )
 
 
+def _emit_output_dir(event_queue: Any, output_dir: str) -> None:
+    try:
+        event_queue.put({"type": "output_dir", "output_dir": output_dir, "ts": time.time()})
+    except Exception:
+        pass
+
+
+def _mlx_has_checkpoint_at_step(output_dir, step: int) -> bool:
+    if step <= 0:
+        return False
+    from core.training.resume import is_resume_checkpoint_valid
+    return is_resume_checkpoint_valid(
+        Path(output_dir) / f"checkpoint-{step}", expected_step = step, backend = "mlx"
+    )
+
+
+def _write_mlx_stop_checkpoint(trainer, optimizer, output_dir) -> bool:
+    """Write a full resume checkpoint for a stopped MLX run.
+
+    Returns True when a checkpoint for the current training step exists.
+    """
+    step = int(getattr(trainer, "_global_step", 0) or 0)
+    # A periodic save or a resumed run may already cover the current step.
+    if _mlx_has_checkpoint_at_step(output_dir, step):
+        return True
+    if step <= 0 or optimizer is None:
+        return False
+    ckpt_dir = Path(output_dir) / f"checkpoint-{step}"
+    if ckpt_dir.is_symlink():
+        # Refuse a symlinked dir: it could redirect writes outside output_dir.
+        logger.error("Refusing to write MLX stop checkpoint through symlink: %s", ckpt_dir)
+        return False
+    try:
+        ckpt_dir.mkdir(parents = True, exist_ok = True)
+        from unsloth_zoo.mlx.utils import (
+            save_optimizer_state,
+            save_trainable_adapters,
+            save_trainer_state,
+        )
+
+        save_trainable_adapters(trainer.model, str(ckpt_dir))
+        save_optimizer_state(optimizer, str(ckpt_dir))
+        save_trainer_state(
+            {
+                "global_step": step,
+                "train_loss_history": list(getattr(trainer, "_train_loss_history", [])),
+            },
+            str(ckpt_dir),
+        )
+        logger.info("Saved stop checkpoint to %s", ckpt_dir)
+    except Exception:
+        logger.exception("Failed to write stop checkpoint under %s", output_dir)
+    return _mlx_has_checkpoint_at_step(output_dir, step)
+
+
 def _run_embedding_training(event_queue: Any, stop_queue: Any, config: dict) -> None:
     """Self-contained embedding model training pipeline.
 
@@ -3660,6 +3805,7 @@ def _run_embedding_training(event_queue: Any, stop_queue: Any, config: dict) ->
             config.get("project_name"),
         )
     output_dir = str(resolve_output_dir(output_dir))
+    _emit_output_dir(event_queue, output_dir)
 
     num_epochs = config.get("num_epochs", 2)
     batch_size = config.get("batch_size", 256)
diff --git a/studio/backend/hub/routes/datasets.py b/studio/backend/hub/routes/datasets.py
index edf4f36ac0..7c7cc274d3 100644
--- a/studio/backend/hub/routes/datasets.py
+++ b/studio/backend/hub/routes/datasets.py
@@ -61,9 +61,11 @@ async def list_cached_datasets(current_subject: str = Depends(get_current_subjec
 
 @router.delete("/cached", response_model = DeleteCachedDatasetResponse)
 async def delete_cached_dataset(
-    repo_id: str = Body(..., embed = True), current_subject: str = Depends(get_current_subject)
+    repo_id: str = Body(..., embed = True),
+    cache_path: Optional[str] = Body(None, embed = True),
+    current_subject: str = Depends(get_current_subject),
 ):
-    return await cache_inventory.delete_cached_dataset_response(repo_id)
+    return await cache_inventory.delete_cached_dataset_response(repo_id, cache_path)
 
 
 @router.get("/download-progress", response_model = DownloadProgressResponse)
diff --git a/studio/backend/hub/routes/inventory.py b/studio/backend/hub/routes/inventory.py
index 4b6c179a2b..dc3e3641bc 100644
--- a/studio/backend/hub/routes/inventory.py
+++ b/studio/backend/hub/routes/inventory.py
@@ -28,6 +28,7 @@ from hub.schemas.inventory import (
     CachedModelsResponse,
     DeleteCachedModelResponse,
     GgufVariantsResponse,
+    HiddenModelsResponse,
     LocalModelListResponse,
     ModelsFolderResponse,
     RecommendedFoldersResponse,
@@ -214,6 +215,16 @@ async def list_cached_models(
     return await cache_inventory.list_cached_models_response(hf_token)
 
 
+@router.get("/hidden-models", response_model = HiddenModelsResponse)
+async def list_hidden_models(current_subject: str = Depends(get_current_subject)):
+    import asyncio
+
+    from routes.models import hidden_model_matchers
+
+    needles, exact_ids, exact_paths = await asyncio.to_thread(hidden_model_matchers)
+    return HiddenModelsResponse(needles = needles, exact_ids = exact_ids, exact_paths = exact_paths)
+
+
 @router.delete(
     "/delete-cached",
     response_model = DeleteCachedModelResponse,
@@ -222,7 +233,8 @@ async def list_cached_models(
 async def delete_cached_model(
     repo_id: str = Body(...),
     variant: Optional[str] = Body(None),
+    cache_path: Optional[str] = Body(None),
     hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
-    return await deletion.delete_cached_model_response(repo_id, variant, hf_token)
+    return await deletion.delete_cached_model_response(repo_id, variant, hf_token, cache_path)
diff --git a/studio/backend/hub/schemas/inventory.py b/studio/backend/hub/schemas/inventory.py
index ef95efe2f2..ca0f4658a3 100644
--- a/studio/backend/hub/schemas/inventory.py
+++ b/studio/backend/hub/schemas/inventory.py
@@ -99,6 +99,10 @@ class LocalModelInfo(BaseModel):
         None,
         description = "HF repo id for cached models, e.g. org/model",
     )
+    active_cache: Optional[bool] = Field(
+        None,
+        description = "Whether this HF entry belongs to the current download cache.",
+    )
     base_model: Optional[str] = Field(
         None,
         description = "Base model from adapter_config.json when this is an adapter",
@@ -160,6 +164,7 @@ class CachedRepoBase(BaseModel):
     repo_id: str
     size_bytes: int = 0
     cache_path: Optional[str] = None
+    last_modified: Optional[float] = None
     partial: bool = False
     partial_transport: Optional[str] = None
     inventory_id: Optional[str] = None
@@ -189,6 +194,12 @@ class CachedModelsResponse(BaseModel):
     cached: List[CachedModelRepo] = Field(default_factory = list)
 
 
+class HiddenModelsResponse(BaseModel):
+    needles: List[str] = Field(default_factory = list)
+    exact_ids: List[str] = Field(default_factory = list)
+    exact_paths: List[str] = Field(default_factory = list)
+
+
 class AddScanFolderRequest(BaseModel):
     """Request body for adding a custom scan folder."""
 
diff --git a/studio/backend/hub/services/datasets/cache_inventory.py b/studio/backend/hub/services/datasets/cache_inventory.py
index a180c9df58..c106b62ab7 100644
--- a/studio/backend/hub/services/datasets/cache_inventory.py
+++ b/studio/backend/hub/services/datasets/cache_inventory.py
@@ -20,12 +20,11 @@ from hub.utils import inventory_scan as hf_cache_scan
 from hub.utils.hf_cache_state import (
     purge_partial_repo,
     purge_repo_cache_dirs,
+    resolve_delete_target_root,
     resolve_destructive_case_matches,
 )
 from hub.utils.paths import (
-    hf_default_cache_dir,
     is_valid_repo_id as _is_valid_repo_id,
-    legacy_hf_cache_dir,
     resolve_cached_repo_id_case,
 )
 
@@ -43,38 +42,8 @@ def _collect_hf_cache_scans() -> tuple[list, set[str]]:
 
 
 def _hf_hub_cache_roots() -> list[Path]:
-    roots: list[Path] = []
-    seen: set[str] = set()
-
-    def _add(path: Optional[Path]) -> None:
-        if path is None or not path.is_dir():
-            return
-        try:
-            resolved = str(path.resolve())
-        except OSError:
-            return
-        if resolved in seen:
-            return
-        seen.add(resolved)
-        roots.append(path)
-
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-        _add(Path(HF_HUB_CACHE))
-    except Exception:
-        pass
-
-    hf_hub_cache = os.environ.get("HF_HUB_CACHE")
-    if hf_hub_cache:
-        _add(Path(hf_hub_cache).expanduser())
-
-    hf_home = os.environ.get("HF_HOME")
-    if hf_home:
-        _add(Path(hf_home).expanduser() / "hub")
-
-    _add(legacy_hf_cache_dir())
-    _add(hf_default_cache_dir())
-    return roots
+    from hub.utils.hf_cache_state import hf_cache_roots
+    return hf_cache_roots()
 
 
 def _repo_id_from_hub_dataset_dir(name: str) -> str | None:
@@ -207,6 +176,21 @@ def _repo_id_from_datasets_cache_dir(name: str) -> str | None:
     return repo_id if _is_valid_repo_id(repo_id) else None
 
 
+def _is_processed_dataset_cache_path(repo_id: str, cache_path: str) -> bool:
+    """True when *cache_path* is this repo's processed Arrow cache dir
+    (``<owner>___<repo>`` directly under an HF_DATASETS_CACHE root). Such rows
+    have no Hub ``datasets--`` layout, so they are deleted via the processed
+    path and must not be rejected as an invalid cache_path."""
+    try:
+        resolved = Path(cache_path).expanduser().resolve(strict = False)
+    except (OSError, RuntimeError, ValueError):
+        return False
+    if resolved.name.lower() != repo_id.replace("/", "___").lower():
+        return False
+    roots = {r.resolve(strict = False) for r in _hf_datasets_cache_roots()}
+    return resolved.parent.resolve(strict = False) in roots
+
+
 def _processed_dataset_cache_size(path: Path) -> int:
     total = 0
     try:
@@ -361,7 +345,7 @@ async def list_cached_datasets_response() -> dict:
         ) from exc
 
 
-async def delete_cached_dataset_response(repo_id: str) -> dict:
+async def delete_cached_dataset_response(repo_id: str, cache_path: Optional[str] = None) -> dict:
     """Remove a cached dataset repo from the HF cache."""
     if not _is_valid_repo_id(repo_id):
         raise HTTPException(status_code = 400, detail = "Invalid repo_id format")
@@ -373,22 +357,40 @@ async def delete_cached_dataset_response(repo_id: str) -> dict:
             detail = "Cancel the active download before deleting.",
         )
     try:
-        return await asyncio.to_thread(_delete_cached_dataset_blocking, repo_key)
+        return await asyncio.to_thread(_delete_cached_dataset_blocking, repo_key, cache_path)
     finally:
         downloads.registry.end_delete(repo_key)
         hf_cache_scan.invalidate_hf_cache_scans()
 
 
-def _delete_cached_dataset_blocking(repo_id: str) -> dict:
+def _delete_cached_dataset_blocking(repo_id: str, cache_path: Optional[str] = None) -> dict:
     scans, _seen_roots = _collect_hf_cache_scans()
 
-    candidate_entries = []
+    # Group this dataset's copies by owning cache root, then target exactly one
+    # cache so a delete never removes copies in other, previously selected caches.
+    owners: dict = {}
     for hf_cache in scans:
         for repo_info in hf_cache.repos:
             if str(repo_info.repo_type) != "dataset":
                 continue
-            if repo_info.repo_id.lower() == repo_id.lower():
-                candidate_entries.append((hf_cache, repo_info))
+            if repo_info.repo_id.lower() != repo_id.lower():
+                continue
+            try:
+                owner = Path(repo_info.repo_path).parent.resolve(strict = False)
+            except (OSError, RuntimeError, ValueError):
+                continue
+            owners.setdefault(owner, []).append((hf_cache, repo_info))
+
+    target_root = resolve_delete_target_root("dataset", repo_id, cache_path, owners.keys())
+    # A processed-only dataset row sends its Arrow cache path (<owner>___<repo>
+    # under HF_DATASETS_CACHE), which is not a Hub datasets-- dir, so
+    # resolve_delete_target_root returns None. Accept it and fall through to the
+    # processed-cache delete rather than rejecting a legitimate row.
+    if target_root is None and not (
+        cache_path and _is_processed_dataset_cache_path(repo_id, cache_path)
+    ):
+        raise HTTPException(status_code = 400, detail = "Invalid cache_path")
+    candidate_entries = owners.get(target_root, []) if target_root is not None else []
     matched_repo_ids = resolve_destructive_repo_ids(
         repo_id,
         [str(repo_info.repo_id) for _hf_cache, repo_info in candidate_entries],
@@ -414,7 +416,26 @@ def _delete_cached_dataset_blocking(repo_id: str) -> dict:
                 exc_info = True,
             )
 
-    processed_deleted, processed_failures = _delete_processed_dataset_cache(repo_id)
+    # Restrict the processed Arrow-cache delete to the selected cache's datasets
+    # root so it never removes copies under other cache homes. A processed
+    # cache_path scopes to its own root; a Hub target scopes to the datasets root
+    # sharing its cache home; an unspecified cache_path stays global (legacy).
+    processed_roots: Optional[set[Path]]
+    if not cache_path:
+        processed_roots = None
+    elif _is_processed_dataset_cache_path(repo_id, cache_path):
+        processed_roots = {Path(cache_path).expanduser().resolve(strict = False).parent}
+    else:
+        home = target_root.parent if target_root is not None else None
+        processed_roots = {
+            root.resolve(strict = False)
+            for root in _hf_datasets_cache_roots()
+            if home is not None and root.resolve(strict = False).parent == home
+        }
+
+    processed_deleted, processed_failures = _delete_processed_dataset_cache(
+        repo_id, only_roots = processed_roots
+    )
     failures.extend(processed_failures)
     if failures:
         raise HTTPException(
@@ -427,15 +448,23 @@ def _delete_cached_dataset_blocking(repo_id: str) -> dict:
 
     # ``scan_cache_dir()`` skips blob-only/corrupt repos the revision delete
     # can't touch, yet the fallback scanner shows them; purge the whole dir.
-    cache_purged = purge_repo_cache_dirs("dataset", repo_id)
-    partial_purged = purge_partial_repo("dataset", repo_id)
-    state_purged = download_manifest.purge_all_state_for_repo("dataset", repo_id) > 0
+    # Only for a Hub cache target; a processed-only path has no Hub dir/state.
+    cache_purged = partial_purged = state_purged = False
+    if target_root is not None:
+        cache_purged = purge_repo_cache_dirs("dataset", repo_id, root = target_root)
+        partial_purged = purge_partial_repo("dataset", repo_id, root = target_root)
+        state_purged = (
+            download_manifest.purge_all_state_for_repo("dataset", repo_id, hub_cache = target_root)
+            > 0
+        )
     if not (deleted or processed_deleted or cache_purged or partial_purged or state_purged):
         raise HTTPException(status_code = 404, detail = "Dataset not found in cache")
     return {"status": "deleted", "repo_id": repo_id}
 
 
-def _delete_processed_dataset_cache(repo_id: str) -> tuple[bool, list[str]]:
+def _delete_processed_dataset_cache(
+    repo_id: str, only_roots: Optional[set[Path]] = None
+) -> tuple[bool, list[str]]:
     import shutil
 
     target = repo_id.replace("/", "___")
@@ -443,6 +472,10 @@ def _delete_processed_dataset_cache(repo_id: str) -> tuple[bool, list[str]]:
     deleted = False
     failures: list[str] = []
     for root in _hf_datasets_cache_roots():
+        # Scope to the selected cache's datasets root(s): a delete must not remove
+        # processed copies living under other, previously selected cache homes.
+        if only_roots is not None and root.resolve(strict = False) not in only_roots:
+            continue
         try:
             entries = [
                 entry
diff --git a/studio/backend/hub/services/datasets/downloads.py b/studio/backend/hub/services/datasets/downloads.py
index 5efac562fa..b412a339e9 100644
--- a/studio/backend/hub/services/datasets/downloads.py
+++ b/studio/backend/hub/services/datasets/downloads.py
@@ -159,12 +159,18 @@ async def download_dataset_response(
 
     use_xet = download_lifecycle.resolve_effective_use_xet(body.use_xet)
     transport = download_lifecycle.resolve_transport(use_xet)
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    cache_paths = get_hf_cache_paths()
+    cache_env = cache_paths.child_env({})
 
     claimed, claim_state = _registry.claim(
         key,
         transport,
         repo_type = "dataset",
         repo_id = repo_id,
+        hub_cache = str(cache_paths.hub_cache),
+        xet_cache = str(cache_paths.xet_cache),
     )
     generation = _registry.current_generation(key)
     if not claimed:
@@ -176,7 +182,12 @@ async def download_dataset_response(
             "accepted": _registry.adoptable(key),
             "generation": generation,
         }
-    download_manifest.clear_cancel_marker("dataset", repo_id, None)
+    download_manifest.clear_cancel_marker(
+        "dataset",
+        repo_id,
+        None,
+        hub_cache = cache_paths.hub_cache,
+    )
 
     state = download_lifecycle.launch_worker(
         _registry,
@@ -185,6 +196,7 @@ async def download_dataset_response(
             ["--repo-id", repo_id, "--dataset"],
             hf_token,
             use_xet = use_xet,
+            cache_env = cache_env,
         ),
         hf_token = hf_token,
         label = repo_id,
diff --git a/studio/backend/hub/services/download_lifecycle.py b/studio/backend/hub/services/download_lifecycle.py
index 23f8c7c911..8e14427a56 100644
--- a/studio/backend/hub/services/download_lifecycle.py
+++ b/studio/backend/hub/services/download_lifecycle.py
@@ -11,7 +11,7 @@ import sys
 import time
 import threading
 from pathlib import Path
-from typing import Callable, Optional
+from typing import Callable, Mapping, Optional
 
 from fastapi import HTTPException
 
@@ -57,6 +57,7 @@ def spawn_worker(
     *,
     use_xet: bool,
     protected_blob_hashes: Optional[frozenset[str]] = None,
+    cache_env: Optional[Mapping[str, str]] = None,
 ) -> subprocess.Popen:
     """Spawn the download worker.
 
@@ -68,7 +69,11 @@ def spawn_worker(
     """
     cwd = backend_dir()
     mode = download_registry.TRANSPORT_XET if use_xet else download_registry.TRANSPORT_HTTP
-    env = os.environ.copy()
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    env = get_hf_cache_paths().child_env()
+    if cache_env is not None:
+        env.update(cache_env)
     if protected_blob_hashes:
         env["UNSLOTH_PROTECTED_BLOB_HASHES"] = ",".join(sorted(protected_blob_hashes))
     else:
@@ -230,6 +235,7 @@ def finalize_worker_exit(
         (stderr_data or b"").decode("utf-8", "replace").strip(),
         hf_token = hf_token,
     )
+    metadata = registry.get_job_metadata(key)
     state = classify_exit(rc, cancel_requested = cancel_requested)
     if state == "complete":
         registry.set_job(key, "complete")
@@ -252,13 +258,13 @@ def finalize_worker_exit(
                     repo_type,
                     repo_id,
                     download_registry.variant_from_key(key),
+                    hub_cache = metadata.hub_cache if metadata is not None else None,
                 )
             except Exception as exc:
                 logger.debug(f"clear_cancel_marker failed for {repo_id} (rc=0): {exc}")
     elif state == "cancelled":
         # Read metadata before the terminal set_job so a concurrent eviction
         # can't drop it; the job key is the fallback variant label.
-        metadata = registry.get_job_metadata(key)
         registry.set_job(key, "cancelled")
         logger.info(f"{log_prefix} cancelled: {label} (rc={rc})")
         download_registry.persist_cancel_marker(
@@ -268,6 +274,7 @@ def finalize_worker_exit(
             if metadata is not None and metadata.variant
             else download_registry.variant_from_key(key),
             cancel_marker_transport or transport,
+            hub_cache = metadata.hub_cache if metadata is not None else None,
             logger = logger,
         )
     else:
@@ -303,6 +310,7 @@ def _set_retry_failure_state(
             metadata.transport
             if metadata is not None and metadata.transport
             else fallback_transport,
+            hub_cache = metadata.hub_cache if metadata is not None else None,
             logger = logger,
         )
     return state
@@ -371,6 +379,7 @@ def _try_http_retry(
             repo_type,
             repo_id,
             progress_blob_hashes,
+            root = Path(original_metadata.hub_cache) if original_metadata.hub_cache else None,
         )
         if progress_blob_hashes
         else 0
@@ -403,6 +412,8 @@ def _try_http_retry(
             generation = generation,
             replace_active = True,
             cancel_marker_transport = original_metadata.transport,
+            hub_cache = original_metadata.hub_cache,
+            xet_cache = original_metadata.xet_cache,
         )
         if claimed:
             break
@@ -446,11 +457,24 @@ def _try_http_retry(
         label,
     )
     try:
+        cache_env = (
+            {
+                "HF_HUB_CACHE": original_metadata.hub_cache,
+                "HF_XET_CACHE": original_metadata.xet_cache,
+            }
+            if original_metadata.hub_cache and original_metadata.xet_cache
+            else None
+        )
+        spawn_kwargs = {
+            "use_xet": False,
+            "protected_blob_hashes": peer_hashes or None,
+        }
+        if cache_env is not None:
+            spawn_kwargs["cache_env"] = cache_env
         proc = spawn_worker(
             args,
             hf_token,
-            use_xet = False,
-            protected_blob_hashes = peer_hashes or None,
+            **spawn_kwargs,
         )
     except Exception as exc:
         scrubbed = download_registry.scrub_secrets(str(exc), hf_token = hf_token)
diff --git a/studio/backend/hub/services/models/cache_inventory.py b/studio/backend/hub/services/models/cache_inventory.py
index 54a25482f2..807ec70991 100644
--- a/studio/backend/hub/services/models/cache_inventory.py
+++ b/studio/backend/hub/services/models/cache_inventory.py
@@ -31,9 +31,9 @@ from hub.services.models.common import (
     _is_checkpoint_weight_name,
     _is_gguf_filename,
     _is_main_gguf_filename,
+    _is_mmproj_filename,
     _is_transformers_safetensors_weight_name,
     _local_inventory_id,
-    _prefer_complete_larger,
     _runtime_for_format,
 )
 
@@ -132,6 +132,39 @@ def _repo_has_gguf_files(repo_info) -> bool:
     return _repo_gguf_size_bytes(repo_info) > 0
 
 
+def _blob_mtime(file_obj) -> float:
+    ts = getattr(file_obj, "blob_last_modified", None)
+    if isinstance(ts, (int, float)) and ts > 0:
+        return float(ts)
+    blob_path = getattr(file_obj, "blob_path", None)
+    if blob_path:
+        try:
+            return float(Path(blob_path).stat().st_mtime)
+        except OSError:
+            pass
+    return 0.0
+
+
+def _repo_gguf_last_modified(repo_info) -> float:
+    latest = 0.0
+    for revision in repo_info.revisions:
+        for f in revision.files:
+            if _is_main_gguf_filename(f.file_name):
+                latest = max(latest, _blob_mtime(f))
+    return latest
+
+
+def _repo_has_mmproj(repo_info) -> bool:
+    # An mmproj file only makes a repo vision-capable when it is an actual GGUF
+    # projector; a non-GGUF sidecar (e.g. mmproj_config.json) does not, and the
+    # runtime's projector detection is GGUF-only.
+    return any(
+        _is_gguf_filename(f.file_name) and _is_mmproj_filename(f.file_name)
+        for revision in repo_info.revisions
+        for f in revision.files
+    )
+
+
 def _cached_repo_file_name(file_obj) -> str:
     file_path = getattr(file_obj, "file_path", None)
     if file_path:
@@ -216,24 +249,46 @@ def _repo_gguf_blob_map(repo_info, *, include_companions: bool = False) -> dict[
 def _prefer_cache_row(candidate: dict, existing: Optional[dict]) -> bool:
     if existing is None:
         return True
-    return _prefer_complete_larger(
-        bool(candidate.get("partial")),
-        int(candidate.get("size_bytes") or 0),
-        bool(existing.get("partial")),
-        int(existing.get("size_bytes") or 0),
-    )
+    candidate_partial = bool(candidate.get("partial"))
+    existing_partial = bool(existing.get("partial"))
+    if candidate_partial != existing_partial:
+        return not candidate_partial
+    candidate_active = bool(candidate.get("active_cache"))
+    existing_active = bool(existing.get("active_cache"))
+    if candidate_active != existing_active:
+        return candidate_active
+    return int(candidate.get("size_bytes") or 0) > int(existing.get("size_bytes") or 0)
 
 
 def _cache_inventory_fields(
     repo_id: str,
     model_format: ModelFormat,
     *,
+    repo_path: Optional[Path] = None,
+    snapshot_path: Optional[Path] = None,
+    active_hub_cache: Optional[Path] = None,
     partial: bool = False,
     requires_variant: bool = False,
 ) -> dict:
+    load_id = repo_id
+    active_cache = True
+    if repo_path is not None:
+        try:
+            if active_hub_cache is None:
+                from utils.hf_cache_settings import get_hf_cache_paths
+                active_hub_cache = get_hf_cache_paths().hub_cache
+            active_root = active_hub_cache.resolve(strict = False)
+            cached_root = repo_path.parent.resolve(strict = False)
+            if cached_root != active_root:
+                active_cache = False
+                load_id = str(snapshot_path or repo_path.resolve(strict = False))
+        except (OSError, RuntimeError, ValueError):
+            active_cache = False
+            load_id = str(snapshot_path or repo_path)
     return {
         "inventory_id": _local_inventory_id("cache", model_format, repo_id),
-        "load_id": repo_id,
+        "load_id": load_id,
+        "active_cache": active_cache,
         "model_format": model_format,
         "runtime": _runtime_for_format(model_format),
         "format_variant": None,
@@ -260,6 +315,9 @@ def _is_hidden_infra_repo(*values: str | None) -> bool:
 def _scan_cached_gguf() -> list[dict]:
     """Synchronous HF-cache disk walk for GGUF repos; runs in a worker thread."""
     cache_scans = all_hf_cache_scans()
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    active_hub_cache = get_hf_cache_paths().hub_cache
 
     seen_lower: dict[str, dict] = {}
     for hf_cache in cache_scans:
@@ -271,7 +329,10 @@ def _scan_cached_gguf() -> list[dict]:
                 repo_path = Path(repo_info.repo_path)
                 snapshot_path = _cached_model_snapshot_path(repo_path)
                 total_size = _repo_gguf_size_bytes(repo_info)
-                has_variant_state, variant_state_size = _gguf_variant_state_summary(repo_id)
+                has_variant_state, variant_state_size = _gguf_variant_state_summary(
+                    repo_id,
+                    hub_cache = repo_path.parent,
+                )
                 is_hidden_infra = _is_hidden_infra_repo(
                     repo_id,
                     str(repo_path),
@@ -291,6 +352,7 @@ def _scan_cached_gguf() -> list[dict]:
                     continue
                 key = repo_id.lower()
                 existing = seen_lower.get(key)
+                last_modified = _repo_gguf_last_modified(repo_info)
                 row = {
                     "repo_id": repo_id,
                     "size_bytes": max(total_size, variant_state_size),
@@ -300,19 +362,34 @@ def _scan_cached_gguf() -> list[dict]:
                     # per-variant detail lives on GgufVariantDetail.
                     "partial_transport": None,
                 }
+                last_modified = max(last_modified, (existing or {}).get("last_modified", 0.0))
+                if last_modified > 0:
+                    row["last_modified"] = last_modified
                 row.update(
                     _cache_inventory_fields(
                         repo_id,
                         "gguf",
+                        repo_path = repo_path,
+                        snapshot_path = snapshot_path,
+                        active_hub_cache = active_hub_cache,
                         partial = bool(row["partial"]),
                         requires_variant = True,
                     )
                 )
+                if _repo_has_mmproj(repo_info):
+                    row["capabilities"]["supports_vision"] = True
                 # Visible infra variants remain management-only.
                 if is_hidden_infra:
                     row["capabilities"]["can_chat"] = False
                 if _prefer_cache_row(row, existing):
+                    if existing and existing["capabilities"].get("supports_vision"):
+                        row["capabilities"]["supports_vision"] = True
                     seen_lower[key] = row
+                else:
+                    if last_modified > existing.get("last_modified", 0.0):
+                        existing["last_modified"] = last_modified
+                    if row["capabilities"].get("supports_vision"):
+                        existing["capabilities"]["supports_vision"] = True
             except Exception as e:
                 repo_label = getattr(repo_info, "repo_id", "<unknown>")
                 logger.warning(f"Skipping cached GGUF repo {repo_label}: {e}")
@@ -340,13 +417,14 @@ class _CachedNonGgufPayload(NamedTuple):
     size_bytes: int
     has_runnable_weights: bool
     model_format: ModelFormat
+    last_modified: float
 
 
 def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
-    all_weight_blobs: dict[str, int] = {}
-    adapter_blobs: dict[str, int] = {}
-    safetensors_blobs: dict[str, int] = {}
-    checkpoint_blobs: dict[str, int] = {}
+    all_weight_blobs: dict[str, tuple[int, float]] = {}
+    adapter_blobs: dict[str, tuple[int, float]] = {}
+    safetensors_blobs: dict[str, tuple[int, float]] = {}
+    checkpoint_blobs: dict[str, tuple[int, float]] = {}
     has_config = False
     has_adapter_config = False
     has_adapter_weights = False
@@ -354,12 +432,15 @@ def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
     has_transformers_safetensors = False
     has_checkpoint = False
 
-    def _record_blob(target: dict[str, int], file_obj, rev_id: str, file_name: str) -> None:
+    def _record_blob(
+        target: dict[str, tuple[int, float]], file_obj, rev_id: str, file_name: str
+    ) -> None:
         blob_path = getattr(file_obj, "blob_path", None)
         size = int(file_obj.size_on_disk or 0)
         key = str(blob_path) if blob_path else f"{rev_id}:{file_name}"
-        target[key] = size
-        all_weight_blobs[key] = size
+        value = (size, _blob_mtime(file_obj))
+        target[key] = value
+        all_weight_blobs[key] = value
 
     for revision in repo_info.revisions:
         rev_id = getattr(revision, "commit_hash", None) or str(id(revision))
@@ -403,18 +484,19 @@ def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
         or "unknown"
     )
     if model_format == "adapter":
-        size_bytes = sum(adapter_blobs.values())
+        selected_blobs = adapter_blobs
     elif model_format == "safetensors":
-        size_bytes = sum(safetensors_blobs.values())
+        selected_blobs = safetensors_blobs
     elif model_format == "checkpoint":
-        size_bytes = sum(checkpoint_blobs.values())
+        selected_blobs = checkpoint_blobs
     else:
-        size_bytes = sum(all_weight_blobs.values())
+        selected_blobs = all_weight_blobs
 
     return _CachedNonGgufPayload(
-        size_bytes = size_bytes,
+        size_bytes = sum(size for size, _mtime in selected_blobs.values()),
         has_runnable_weights = model_format != "unknown",
         model_format = model_format,
+        last_modified = max((mtime for _size, mtime in selected_blobs.values()), default = 0.0),
     )
 
 
@@ -435,6 +517,19 @@ def _read_json_object(path: Path) -> dict:
         return {}
 
 
+def _is_whisper_model_config(config: object) -> bool:
+    if not isinstance(config, dict):
+        return False
+    model_type = config.get("model_type")
+    if isinstance(model_type, str) and model_type.strip().lower() == "whisper":
+        return True
+    architectures = config.get("architectures")
+    return isinstance(architectures, list) and any(
+        isinstance(name, str) and name == "WhisperForConditionalGeneration"
+        for name in architectures
+    )
+
+
 def _read_model_card_frontmatter(path: Path) -> dict:
     try:
         text = path.read_text(encoding = "utf-8")
@@ -465,6 +560,8 @@ def _cached_model_local_metadata(repo_path: Path) -> dict:
 
     result: dict = {}
     config = _read_json_object(snapshot / "config.json")
+    if _is_whisper_model_config(config):
+        result["_hidden_stt"] = True
     quant_method = (
         config.get("quantization_config", {}).get("quant_method")
         if isinstance(config.get("quantization_config"), dict)
@@ -491,11 +588,15 @@ def _cached_model_local_metadata(repo_path: Path) -> dict:
 def _scan_cached_models() -> list[dict]:
     """Synchronous HF-cache disk walk for non-GGUF model repos; runs in a worker thread."""
     cache_scans = all_hf_cache_scans()
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    active_hub_cache = get_hf_cache_paths().hub_cache
 
     seen_lower: dict[str, dict] = {}
     inspected = 0
     skipped_gguf = 0
     skipped_no_weights = 0
+    skipped_stt = 0
     for hf_cache in cache_scans:
         for repo_info in hf_cache.repos:
             inspected += 1
@@ -523,6 +624,10 @@ def _scan_cached_models() -> list[dict]:
                     continue
                 key = repo_id.lower()
                 existing = seen_lower.get(key)
+                local_metadata = _cached_model_local_metadata(repo_path)
+                if local_metadata.pop("_hidden_stt", False):
+                    skipped_stt += 1
+                    continue
                 snapshot_partial = hf_cache_scan.is_snapshot_partial(
                     "model",
                     repo_id,
@@ -542,27 +647,40 @@ def _scan_cached_models() -> list[dict]:
                         if snapshot_partial
                         else None
                     ),
-                    **_cached_model_local_metadata(repo_path),
+                    **local_metadata,
                 }
+                last_modified = max(
+                    payload.last_modified,
+                    (existing or {}).get("last_modified", 0.0),
+                )
+                if last_modified > 0:
+                    row["last_modified"] = last_modified
                 row.update(
                     _cache_inventory_fields(
                         repo_id,
                         payload.model_format,
+                        repo_path = repo_path,
+                        snapshot_path = snapshot_path,
+                        active_hub_cache = active_hub_cache,
                         partial = bool(row["partial"]),
                     )
                 )
                 if _prefer_cache_row(row, existing):
                     seen_lower[key] = row
+                elif last_modified > existing.get("last_modified", 0.0):
+                    existing["last_modified"] = last_modified
             except Exception as e:
                 repo_label = getattr(repo_info, "repo_id", "<unknown>")
                 logger.warning(f"Skipping cached model repo {repo_label}: {e}")
                 continue
     cached = sorted(seen_lower.values(), key = lambda c: c["repo_id"])
     logger.info(
-        "Cached model scan: inspected=%d skipped_gguf=%d skipped_no_weights=%d returned=%d",
+        "Cached model scan: inspected=%d skipped_gguf=%d skipped_no_weights=%d "
+        "skipped_stt=%d returned=%d",
         inspected,
         skipped_gguf,
         skipped_no_weights,
+        skipped_stt,
         len(cached),
     )
     return cached
diff --git a/studio/backend/hub/services/models/common.py b/studio/backend/hub/services/models/common.py
index f381bffe9c..4c0e296fdc 100644
--- a/studio/backend/hub/services/models/common.py
+++ b/studio/backend/hub/services/models/common.py
@@ -150,7 +150,9 @@ def _prefer_complete_larger(
     return candidate_size_bytes > existing_size_bytes
 
 
-def _gguf_variant_state_summary(repo_id: str) -> tuple[bool, int]:
+def _gguf_variant_state_summary(
+    repo_id: str, *, hub_cache: Optional[str | Path] = None
+) -> tuple[bool, int]:
     """Whether GGUF variant-scoped state exists and its expected size; a cancelled/in-progress variant may have only manifests/markers/`.incomplete` blobs, which inventory needs to avoid a generic fallback row."""
     from hub.utils import download_manifest
 
@@ -159,10 +161,16 @@ def _gguf_variant_state_summary(repo_id: str) -> tuple[bool, int]:
     for variant, _path in download_manifest.iter_variant_manifests(
         "model",
         repo_id,
+        hub_cache = hub_cache,
     ):
         key = variant.lower()
         variant_keys.add(key)
-        manifest = download_manifest.read_manifest("model", repo_id, variant)
+        manifest = download_manifest.read_manifest(
+            "model",
+            repo_id,
+            variant,
+            hub_cache = hub_cache,
+        )
         if manifest is None:
             continue
         size_by_variant[key] = max(
@@ -172,6 +180,7 @@ def _gguf_variant_state_summary(repo_id: str) -> tuple[bool, int]:
     for variant, _path in download_manifest.iter_variant_markers(
         "model",
         repo_id,
+        hub_cache = hub_cache,
     ):
         variant_keys.add(variant.lower())
     return bool(variant_keys), sum(size_by_variant.values())
@@ -432,8 +441,13 @@ def _local_model_info(
     base_model_source: Optional[str] = None,
     adapter_type: Optional[str] = None,
     training_method: Optional[str] = None,
+    active_cache: Optional[bool] = None,
 ) -> LocalModelInfo:
-    load_id = model_id if source == "hf_cache" and model_id else str(load_path)
+    load_id = (
+        model_id
+        if source == "hf_cache" and model_id and active_cache is not False
+        else str(load_path)
+    )
     semantic_id = model_id or str(load_path)
     return LocalModelInfo(
         id = load_id,
@@ -445,6 +459,7 @@ def _local_model_info(
         ),
         load_id = load_id,
         model_id = model_id,
+        active_cache = active_cache if source == "hf_cache" else None,
         display_name = display_name or (scan_path.stem if scan_path.is_file() else scan_path.name),
         path = str(load_path),
         size_bytes = max(0, int(size_bytes or 0)),
@@ -476,6 +491,7 @@ def _classify_local_path(
     model_id: Optional[str] = None,
     updated_at: Optional[float] = None,
     partial: bool = False,
+    active_cache: Optional[bool] = None,
 ) -> list[LocalModelInfo]:
     load_path = load_path or scan_path
     files = (
@@ -512,6 +528,7 @@ def _classify_local_path(
                 requires_variant = scan_path.is_dir(),
                 format_variant = variant,
                 size_bytes = gguf_size_bytes,
+                active_cache = active_cache,
             )
         )
 
@@ -574,6 +591,7 @@ def _classify_local_path(
                 ),
                 adapter_type = adapter_type if model_format == "adapter" else None,
                 training_method = training_method if model_format == "adapter" else None,
+                active_cache = active_cache,
             )
         )
     elif not rows:
@@ -592,6 +610,7 @@ def _classify_local_path(
                 updated_at = updated_at,
                 partial = partial or trusted_hf_cache_repo,
                 size_bytes = size_bytes,
+                active_cache = active_cache,
             )
         )
 
diff --git a/studio/backend/hub/services/models/deletion.py b/studio/backend/hub/services/models/deletion.py
index 636a223d4e..c736908058 100644
--- a/studio/backend/hub/services/models/deletion.py
+++ b/studio/backend/hub/services/models/deletion.py
@@ -19,8 +19,10 @@ from hub.utils import inventory_scan as hf_cache_scan
 from hub.utils.gguf import extract_quant_label, extract_quant_token
 from hub.utils.hf_cache_state import (
     INCOMPLETE_SUFFIX,
+    iter_repo_cache_dirs,
     purge_partial_repo,
     purge_repo_cache_dirs,
+    resolve_delete_target_root,
 )
 from hub.utils.paths import (
     is_valid_gguf_variant as _is_valid_gguf_variant,
@@ -184,6 +186,7 @@ def _delete_gguf_variant_from_repos(
     hf_token: Optional[str],
     *,
     sibling_active: bool = False,
+    root: Optional[Path] = None,
 ) -> dict:
     failures: list[str] = []
     removed_snapshots = 0
@@ -265,6 +268,7 @@ def _delete_gguf_variant_from_repos(
         hf_token,
         extra_hashes = frozenset(completed_hashes),
         companions = not sibling_active,
+        root = root,
     )
     if incomplete_result.unresolved:
         raise HTTPException(
@@ -276,7 +280,7 @@ def _delete_gguf_variant_from_repos(
             ),
         )
 
-    state_purged = download_manifest.purge_state("model", repo_id, variant)
+    state_purged = download_manifest.purge_state("model", repo_id, variant, hub_cache = root)
     # Reclaim the empty quant folder so it stops 404ing on delete.
     removed_dirs, dir_failures = _remove_empty_variant_dirs(target_repos, variant)
     removed_snap_dirs, snap_dir_failures = _remove_empty_snapshot_dirs(target_repos)
@@ -316,6 +320,8 @@ def reclaim_replaced_gguf_variant(
     variant: str,
     keep_main_hashes: frozenset[str],
     hf_token: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> dict:
     """Prune stale main-GGUF files for a variant after a replacement verified.
 
@@ -366,12 +372,22 @@ def reclaim_replaced_gguf_variant(
             "reason": "scan_failed",
         }
 
+    if hub_cache is None:
+        from utils.hf_cache_settings import get_hf_cache_paths
+        hub_cache = get_hf_cache_paths().hub_cache
+    try:
+        target_hub_cache = Path(hub_cache).expanduser().resolve(strict = False)
+    except (OSError, RuntimeError, ValueError):
+        target_hub_cache = Path(hub_cache).expanduser()
+
     candidate_repos = [
         repo_info
         for hf_cache in cache_scans
         for repo_info in hf_cache.repos
         if str(getattr(repo_info, "repo_type", "")) == "model"
         and str(getattr(repo_info, "repo_id", "")).lower() == repo_id.lower()
+        and getattr(repo_info, "repo_path", None)
+        and Path(repo_info.repo_path).parent.resolve(strict = False) == target_hub_cache
     ]
     try:
         matched_repo_ids = resolve_destructive_repo_ids(
@@ -493,10 +509,24 @@ def reclaim_replaced_gguf_variant(
 
 
 def _loaded_id_matches_repo(loaded_id: str, repo_id: str) -> bool:
-    """True when *loaded_id* is *repo_id* or a file within it; ``/``-boundary aware so ``org/model`` doesn't match sibling ``org/model-v2``."""
+    """Match a loaded repo ID or an on-disk path inside any copy of the repo."""
     rid = repo_id.lower()
     lid = loaded_id.lower()
-    return lid == rid or lid.startswith(f"{rid}/")
+    if lid == rid or lid.startswith(f"{rid}/"):
+        return True
+
+    try:
+        loaded_path = Path(loaded_id).expanduser().resolve(strict = False)
+    except (OSError, RuntimeError, ValueError):
+        return False
+    for repo_dir in iter_repo_cache_dirs("model", repo_id):
+        try:
+            resolved_repo = repo_dir.resolve(strict = False)
+            if loaded_path == resolved_repo or loaded_path.is_relative_to(resolved_repo):
+                return True
+        except (OSError, RuntimeError, ValueError):
+            continue
+    return False
 
 
 def _loaded_repo_variant_blocks_delete(
@@ -560,6 +590,7 @@ async def delete_cached_model_response(
     repo_id: str,
     variant: Optional[str] = None,
     hf_token: Optional[str] = None,
+    cache_path: Optional[str] = None,
 ):
     """Delete a cached model repo (or a specific GGUF variant) from the HF cache.
 
@@ -603,14 +634,19 @@ async def delete_cached_model_response(
         )
         raise HTTPException(status_code = 400, detail = detail)
     try:
-        return await asyncio.to_thread(_delete_cached_model_blocking, repo_id, variant, hf_token)
+        return await asyncio.to_thread(
+            _delete_cached_model_blocking, repo_id, variant, hf_token, cache_path
+        )
     finally:
         downloads.registry.end_delete(repo_key, variant)
         cache_inventory.invalidate_hf_cache_scans()
 
 
 def _delete_cached_model_blocking(
-    repo_id: str, variant: Optional[str], hf_token: Optional[str]
+    repo_id: str,
+    variant: Optional[str],
+    hf_token: Optional[str],
+    cache_path: Optional[str] = None,
 ) -> dict:
     try:
         # If a sibling quant is downloading concurrently, restrict this delete to
@@ -621,13 +657,26 @@ def _delete_cached_model_blocking(
 
         cache_scans = cache_inventory.all_hf_cache_scans()
 
-        candidate_entries = []
+        # A repo can live in several remembered caches. Group its copies by the
+        # cache root that owns each, then target exactly one cache so a delete
+        # never removes copies in other, previously selected caches.
+        owners: dict = {}
         for hf_cache in cache_scans:
             for repo_info in hf_cache.repos:
                 if str(repo_info.repo_type) != "model":
                     continue
-                if repo_info.repo_id.lower() == repo_id.lower():
-                    candidate_entries.append((hf_cache, repo_info))
+                if repo_info.repo_id.lower() != repo_id.lower():
+                    continue
+                try:
+                    owner = Path(repo_info.repo_path).parent.resolve(strict = False)
+                except (OSError, RuntimeError, ValueError):
+                    continue
+                owners.setdefault(owner, []).append((hf_cache, repo_info))
+
+        target_root = resolve_delete_target_root("model", repo_id, cache_path, owners.keys())
+        if target_root is None:
+            raise HTTPException(status_code = 400, detail = "Invalid cache_path")
+        candidate_entries = owners.get(target_root, [])
 
         matched_repo_ids = resolve_destructive_repo_ids(
             repo_id,
@@ -642,10 +691,15 @@ def _delete_cached_model_blocking(
 
         if not target_entries:
             if variant is None:
-                cache_purged = purge_repo_cache_dirs("model", repo_id) or purge_partial_repo(
-                    "model", repo_id
+                cache_purged = purge_repo_cache_dirs(
+                    "model", repo_id, root = target_root
+                ) or purge_partial_repo("model", repo_id, root = target_root)
+                state_purged = (
+                    download_manifest.purge_all_state_for_repo(
+                        "model", repo_id, hub_cache = target_root
+                    )
+                    > 0
                 )
-                state_purged = download_manifest.purge_all_state_for_repo("model", repo_id) > 0
                 if cache_purged or state_purged:
                     return {"status": "deleted", "repo_id": repo_id}
             if variant:
@@ -654,6 +708,7 @@ def _delete_cached_model_blocking(
                     variant,
                     hf_token,
                     companions = not sibling_active,
+                    root = target_root,
                 )
                 if incomplete_result.unresolved:
                     raise HTTPException(
@@ -668,6 +723,7 @@ def _delete_cached_model_blocking(
                     "model",
                     repo_id,
                     variant,
+                    hub_cache = target_root,
                 )
                 if incomplete_result.deleted > 0 or state_purged:
                     return {
@@ -684,6 +740,7 @@ def _delete_cached_model_blocking(
                 [repo for _cache, repo in target_entries],
                 hf_token,
                 sibling_active = sibling_active,
+                root = target_root,
             )
 
         deleted_revisions = False
@@ -702,9 +759,11 @@ def _delete_cached_model_blocking(
             delete_strategy.execute()
             deleted_revisions = True
 
-        cache_purged = purge_repo_cache_dirs("model", repo_id)
-        partial_purged = purge_partial_repo("model", repo_id)
-        state_purged = download_manifest.purge_all_state_for_repo("model", repo_id) > 0
+        cache_purged = purge_repo_cache_dirs("model", repo_id, root = target_root)
+        partial_purged = purge_partial_repo("model", repo_id, root = target_root)
+        state_purged = (
+            download_manifest.purge_all_state_for_repo("model", repo_id, hub_cache = target_root) > 0
+        )
 
         if not (deleted_revisions or cache_purged or partial_purged or state_purged):
             raise HTTPException(status_code = 404, detail = "No revisions found for model")
diff --git a/studio/backend/hub/services/models/downloads.py b/studio/backend/hub/services/models/downloads.py
index 862af0141a..c93b21c082 100644
--- a/studio/backend/hub/services/models/downloads.py
+++ b/studio/backend/hub/services/models/downloads.py
@@ -90,6 +90,7 @@ def _spawn_download_worker(
     hf_token: Optional[str],
     use_xet: bool = True,
     protected_blob_hashes: Optional[frozenset[str]] = None,
+    cache_env: Optional[dict[str, str]] = None,
 ) -> subprocess.Popen:
     args = ["--repo-id", repo_id]
     if variant:
@@ -99,6 +100,7 @@ def _spawn_download_worker(
         hf_token,
         use_xet = use_xet,
         protected_blob_hashes = protected_blob_hashes,
+        cache_env = cache_env,
     )
 
 
@@ -125,6 +127,10 @@ async def download_model_response(body: DownloadModelRequest, hf_token: Optional
     key = _download_job_key(repo_id, variant)
     use_xet = download_lifecycle.resolve_effective_use_xet(body.use_xet)
     transport = download_lifecycle.resolve_transport(use_xet)
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    cache_paths = get_hf_cache_paths()
+    cache_env = cache_paths.child_env({})
     variant_blob_hashes = frozenset()
     variant_progress_blob_hashes = frozenset()
     completed_baseline_bytes = 0
@@ -175,6 +181,8 @@ async def download_model_response(body: DownloadModelRequest, hf_token: Optional
         progress_blob_hashes = variant_progress_blob_hashes,
         completed_baseline_bytes = completed_baseline_bytes,
         admission_check = lambda: not _load_in_flight(repo_id),
+        hub_cache = str(cache_paths.hub_cache),
+        xet_cache = str(cache_paths.xet_cache),
     )
     generation = _registry.current_generation(key)
     if not claimed:
@@ -189,7 +197,12 @@ async def download_model_response(body: DownloadModelRequest, hf_token: Optional
             "accepted": _registry.adoptable(key),
             "generation": generation,
         }
-    download_manifest.clear_cancel_marker("model", repo_id, variant)
+    download_manifest.clear_cancel_marker(
+        "model",
+        repo_id,
+        variant,
+        hub_cache = cache_paths.hub_cache,
+    )
     # Blobs a concurrent same-repo variant is already writing (e.g. a shared
     # mmproj). The worker must not purge these during cache preparation.
     protected_blob_hashes = _registry.peer_blob_hashes(key) if variant else frozenset()
@@ -204,6 +217,7 @@ async def download_model_response(body: DownloadModelRequest, hf_token: Optional
             hf_token,
             use_xet = use_xet,
             protected_blob_hashes = protected_blob_hashes,
+            cache_env = cache_env,
         ),
         hf_token = hf_token,
         label = label,
diff --git a/studio/backend/hub/services/models/folder_browser.py b/studio/backend/hub/services/models/folder_browser.py
index 7d9c3ac665..effb6a32ae 100644
--- a/studio/backend/hub/services/models/folder_browser.py
+++ b/studio/backend/hub/services/models/folder_browser.py
@@ -30,6 +30,7 @@ from hub.utils.paths import (
 )
 from utils.paths.external_media import (
     linux_run_media_mount_roots,
+    macos_volume_roots,
     windows_drive_roots,
 )
 from hub.services.models.common import _safe_is_dir
@@ -187,7 +188,7 @@ def _build_browse_allowlist(
 
     _add(Path.home())
     if media_roots is None:
-        media_roots = linux_run_media_mount_roots()
+        media_roots = [*linux_run_media_mount_roots(), *macos_volume_roots()]
     if drive_roots is None:
         drive_roots = windows_drive_roots()
     for p in media_roots:
@@ -195,6 +196,12 @@ def _build_browse_allowlist(
     for p in drive_roots:
         _add(p)
     _add(_resolve_hf_cache_dir())
+    try:
+        from utils.hf_cache_settings import known_hf_cache_homes
+        for cache_home in known_hf_cache_homes():
+            _add(cache_home)
+    except Exception:  # noqa: BLE001 -- best-effort
+        pass
     try:
         _add(hf_default_cache_dir())
     except Exception:  # noqa: BLE001 -- best-effort
@@ -431,7 +438,7 @@ def browse_folders_response(
 
     # Probe removable-media and Windows drive roots once; the allowlist and
     # chips reuse the result so a disconnected mapped drive isn't scanned twice.
-    media_roots = linux_run_media_mount_roots()
+    media_roots = [*linux_run_media_mount_roots(), *macos_volume_roots()]
     drive_roots = windows_drive_roots()
     # Build the allowlist once -- the sandbox check and suggestion chips share
     # it so chips are always navigable.
diff --git a/studio/backend/hub/services/models/gguf_variants.py b/studio/backend/hub/services/models/gguf_variants.py
index 33f0297ff5..533fd2ca5a 100644
--- a/studio/backend/hub/services/models/gguf_variants.py
+++ b/studio/backend/hub/services/models/gguf_variants.py
@@ -9,6 +9,7 @@ import asyncio
 import threading
 import time
 from collections import OrderedDict
+from pathlib import Path
 from typing import NamedTuple, Optional
 
 from fastapi import HTTPException
@@ -22,6 +23,7 @@ from hub.utils.hf_errors import hf_error_status
 from hub.utils.hf_cache_state import (
     INCOMPLETE_SUFFIX,
     iter_destructive_repo_cache_dirs,
+    repo_cache_dir_name,
 )
 from hub.utils.gguf import (
     extract_quant_label,
@@ -233,8 +235,14 @@ def _manifest_variant_blob_hashes(
     variant: str,
     *,
     include_companions: bool = True,
+    repo_cache_dir: Optional[Path] = None,
 ) -> frozenset[str]:
-    manifest = download_manifest.read_manifest("model", repo_id, variant)
+    manifest = download_manifest.read_manifest(
+        "model",
+        repo_id,
+        variant,
+        hub_cache = repo_cache_dir.parent if repo_cache_dir is not None else None,
+    )
     if manifest is None:
         return frozenset()
     variant_key = variant.lower()
@@ -257,6 +265,7 @@ def gguf_variant_blob_hashes(
     *,
     include_companions: bool = True,
     allow_remote: bool = True,
+    repo_cache_dir: Optional[Path] = None,
 ) -> frozenset[str]:
     key = _variant_blob_hash_cache_key(
         repo_id,
@@ -271,9 +280,9 @@ def gguf_variant_blob_hashes(
         repo_id,
         variant,
         include_companions = include_companions,
+        repo_cache_dir = repo_cache_dir,
     )
     if hashes:
-        _variant_hash_cache_set(key, hashes)
         return hashes
     requirement_key = _variant_hash_cache_key(repo_id, variant, hf_token)
     requirement = _variant_requirement_cache_get(requirement_key)
@@ -287,11 +296,22 @@ def gguf_variant_blob_hashes(
     return frozenset()
 
 
-def _partial_transport_for_variant(repo_id: str, variant: str) -> Optional[str]:
-    return hf_cache_scan.partial_transport_for("model", repo_id, variant)
+def _partial_transport_for_variant(
+    repo_id: str,
+    variant: str,
+    repo_cache_dir: Optional[Path] = None,
+) -> Optional[str]:
+    return hf_cache_scan.partial_transport_for(
+        "model",
+        repo_id,
+        variant,
+        repo_cache_dir,
+    )
 
 
-def _local_main_gguf_blobs_by_quant(repo_id: str) -> dict[str, dict[str, set[str]]]:
+def _local_main_gguf_blobs_by_quant(
+    repo_id: str, repo_cache_dir: Optional[Path] = None
+) -> dict[str, dict[str, set[str]]]:
     """Map quant -> repo-relative expected GGUF filename -> cached blob hashes.
 
     Shared companions are copied into each main-quant bucket so update checks can
@@ -313,6 +333,14 @@ def _local_main_gguf_blobs_by_quant(repo_id: str) -> dict[str, dict[str, set[str
                 continue
             if str(getattr(repo_info, "repo_id", "")).lower() != target_lower:
                 continue
+            if repo_cache_dir is not None:
+                try:
+                    if Path(repo_info.repo_path).resolve(strict = False) != repo_cache_dir.resolve(
+                        strict = False
+                    ):
+                        continue
+                except (AttributeError, OSError, RuntimeError, ValueError):
+                    continue
             for path, hashes in cache_inventory._repo_gguf_blob_map(
                 repo_info,
                 include_companions = True,
@@ -388,6 +416,7 @@ def delete_variant_incomplete_blobs_result(
     *,
     extra_hashes: frozenset[str] = frozenset(),
     companions: bool = True,
+    root: Optional[Path] = None,
 ) -> VariantIncompleteDeleteResult:
     # With a sibling still downloading, ``companions=False`` keeps a shared mmproj
     # from being unlinked out from under it; the repo's last delete reclaims it.
@@ -409,8 +438,9 @@ def delete_variant_incomplete_blobs_result(
         )
     deleted = 0
     # Destructive iterator: only the exact-case match (or abort if ambiguous),
-    # so a case-variant sibling repo's partials are never unlinked.
-    for entry in iter_destructive_repo_cache_dirs("model", repo_id):
+    # so a case-variant sibling repo's partials are never unlinked. ``root`` scopes
+    # the purge to one cache so a delete never touches another cache's partials.
+    for entry in iter_destructive_repo_cache_dirs("model", repo_id, root = root):
         blobs_dir = entry / "blobs"
         if not blobs_dir.is_dir():
             continue
@@ -425,15 +455,37 @@ def delete_variant_incomplete_blobs_result(
     return VariantIncompleteDeleteResult(deleted = deleted, unresolved = False)
 
 
+def _repo_cache_dir_for_request(repo_id: str, local_path: Optional[str]) -> Path:
+    """Resolve the one Hub repo cache represented by this variant request."""
+    expected_name = repo_cache_dir_name("model", repo_id).lower()
+    if local_path:
+        try:
+            local = Path(local_path).expanduser().resolve(strict = False)
+            for candidate in (local, *local.parents):
+                if candidate.name.lower() == expected_name:
+                    return candidate
+        except (OSError, RuntimeError, ValueError):
+            pass
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    return get_hf_cache_paths().hub_cache / repo_cache_dir_name("model", repo_id)
+
+
 def _mark_empty_dir_cleanables(
-    repo_id: str, response: GgufVariantsResponse
+    repo_id: str,
+    response: GgufVariantsResponse,
+    repo_cache_dir: Optional[Path] = None,
 ) -> GgufVariantsResponse:
     """Surface empty leftover ``<quant>/`` folders (interrupted downloads) as
     partial so the UI can delete them -- on local/offline paths too, not just a
     remote listing. A listed quant is flipped to partial; an unlisted one is
     appended as a zero-byte cleanable entry."""
     try:
-        empty_labels = list_empty_gguf_variant_dirs(repo_id)
+        empty_labels = (
+            list_empty_gguf_variant_dirs(repo_id, root = repo_cache_dir.parent)
+            if repo_cache_dir is not None
+            else list_empty_gguf_variant_dirs(repo_id)
+        )
     except Exception as e:
         logger.warning(f"Failed to scan empty GGUF variant folders for {repo_id}: {e}")
         return response
@@ -468,6 +520,11 @@ async def get_gguf_variants_response(
     """
 
     def _compute() -> GgufVariantsResponse:
+        repo_cache_dir = (
+            None if is_local_path(repo_id) else _repo_cache_dir_for_request(repo_id, local_path)
+        )
+        hub_cache = repo_cache_dir.parent if repo_cache_dir is not None else None
+
         def _local_response(
             response_repo_id: str, variants, has_vision: bool
         ) -> GgufVariantsResponse:
@@ -511,6 +568,7 @@ async def get_gguf_variants_response(
                         partial_transport = _partial_transport_for_variant(
                             response_repo_id,
                             v.quant,
+                            repo_cache_dir,
                         ),
                     )
                     for v in variants
@@ -532,7 +590,7 @@ async def get_gguf_variants_response(
 
         local_only = prefer_local_cache or offline
         if local_only:
-            cached = list_gguf_variants_from_hf_cache(repo_id)
+            cached = list_gguf_variants_from_hf_cache(repo_id, root = hub_cache)
             if cached is not None:
                 variants, has_vision = cached
                 return _local_response(repo_id, variants, has_vision)
@@ -540,7 +598,7 @@ async def get_gguf_variants_response(
                 variants, has_vision = list_local_gguf_variants(local_path)
                 if variants or has_vision:
                     return _local_response(repo_id, variants, has_vision)
-            partial = list_partial_gguf_variants_from_state(repo_id)
+            partial = list_partial_gguf_variants_from_state(repo_id, hub_cache = hub_cache)
             if partial is not None:
                 variants, has_vision = partial
                 return _partial_local_response(repo_id, variants, has_vision)
@@ -560,11 +618,11 @@ async def get_gguf_variants_response(
         try:
             variants, has_vision, siblings = list_gguf_variants(repo_id, hf_token = hf_token)
         except Exception:
-            cached = list_gguf_variants_from_hf_cache(repo_id)
+            cached = list_gguf_variants_from_hf_cache(repo_id, root = hub_cache)
             if cached is not None:
                 variants, has_vision = cached
                 return _local_response(repo_id, variants, has_vision)
-            partial = list_partial_gguf_variants_from_state(repo_id)
+            partial = list_partial_gguf_variants_from_state(repo_id, hub_cache = hub_cache)
             if partial is not None:
                 variants, has_vision = partial
                 return _partial_local_response(repo_id, variants, has_vision)
@@ -581,7 +639,7 @@ async def get_gguf_variants_response(
         cached_filenames_by_snapshot: list[dict[str, int]] = []
         cached_quant_bytes_by_snapshot: list[dict[str, int]] = []
         if _is_valid_repo_id(repo_id):
-            for snap in iter_hf_cache_snapshots(repo_id):
+            for snap in iter_hf_cache_snapshots(repo_id, root = hub_cache):
                 try:
                     gguf_paths = list(_iter_gguf_paths(snap))
                 except (OSError, RuntimeError, ValueError) as e:
@@ -694,11 +752,20 @@ async def get_gguf_variants_response(
         partial_quants: set[str] = set()
         partial_quant_transports: dict[str, Optional[str]] = {}
         try:
-            incomplete_hashes = download_registry.incomplete_blob_hashes("model", repo_id)
+            incomplete_hashes = download_registry.incomplete_blob_hashes(
+                "model",
+                repo_id,
+                active_only = True,
+                root = hub_cache,
+            )
         except Exception as e:
             logger.warning(f"Failed to compute partial GGUF variants for {repo_id}: {e}")
             incomplete_hashes = set()
-        scan_snapshot_dir = hf_cache_scan.resolve_snapshot_dir_for_scan("model", repo_id)
+        scan_snapshot_dir = hf_cache_scan.resolve_snapshot_dir_for_scan(
+            "model",
+            repo_id,
+            repo_cache_dir,
+        )
         # Manifest + marker + main incomplete-blob check: catches variants whose
         # download was cancelled or whose expected shards are missing/undersized.
         for variant in variants:
@@ -711,6 +778,7 @@ async def get_gguf_variants_response(
                         variant.quant,
                         hf_token,
                         include_companions = False,
+                        repo_cache_dir = repo_cache_dir,
                     )
                 if hf_cache_scan.is_variant_partial(
                     repo_id,
@@ -718,11 +786,13 @@ async def get_gguf_variants_response(
                     scan_snapshot_dir,
                     incomplete_blob_hashes = incomplete_hashes,
                     variant_blob_hashes = variant_hashes,
+                    repo_cache_dir = repo_cache_dir,
                 ):
                     partial_quants.add(variant.quant)
                     partial_quant_transports[variant.quant] = _partial_transport_for_variant(
                         repo_id,
                         variant.quant,
+                        repo_cache_dir,
                     )
             except Exception as e:
                 logger.warning(
@@ -744,10 +814,14 @@ async def get_gguf_variants_response(
                     partial_quants.add(variant.quant)
                     partial_quant_transports.setdefault(
                         variant.quant,
-                        _partial_transport_for_variant(repo_id, variant.quant),
+                        _partial_transport_for_variant(
+                            repo_id,
+                            variant.quant,
+                            repo_cache_dir,
+                        ),
                     )
 
-        local_blobs_by_quant = _local_main_gguf_blobs_by_quant(repo_id)
+        local_blobs_by_quant = _local_main_gguf_blobs_by_quant(repo_id, repo_cache_dir)
 
         def _variant_detail(v) -> GgufVariantDetail:
             is_partial = v.quant in partial_quants
@@ -790,14 +864,20 @@ async def get_gguf_variants_response(
             if skip:
                 raise
             enriched = _mark_empty_dir_cleanables(
-                repo_id, GgufVariantsResponse(repo_id = repo_id, variants = [])
+                repo_id,
+                GgufVariantsResponse(repo_id = repo_id, variants = []),
+                _repo_cache_dir_for_request(repo_id, local_path),
             )
             if enriched.variants:
                 return enriched
             raise
         if skip:
             return response
-        return _mark_empty_dir_cleanables(repo_id, response)
+        return _mark_empty_dir_cleanables(
+            repo_id,
+            response,
+            _repo_cache_dir_for_request(repo_id, local_path),
+        )
 
     try:
         return await asyncio.to_thread(_compute_with_cleanables)
diff --git a/studio/backend/hub/services/models/local_inventory.py b/studio/backend/hub/services/models/local_inventory.py
index b34532fa35..9cf260b157 100644
--- a/studio/backend/hub/services/models/local_inventory.py
+++ b/studio/backend/hub/services/models/local_inventory.py
@@ -106,11 +106,8 @@ def _is_model_directory_for_scan(path: Path, *, entry_limit: int | None) -> bool
 
 
 def _resolve_hf_cache_dir() -> Path:
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-        return Path(HF_HUB_CACHE)
-    except Exception:
-        return Path.home() / ".cache" / "huggingface" / "hub"
+    from utils.hf_cache_settings import get_hf_cache_paths
+    return get_hf_cache_paths().hub_cache
 
 
 def _scan_models_dir(
@@ -202,7 +199,12 @@ def _hf_repo_dir_has_content(repo_dir: Path) -> bool:
     return False
 
 
-def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[LocalModelInfo]:
+def _scan_hf_cache(
+    cache_dir: Path,
+    *,
+    entry_limit: int | None = None,
+    active_cache: bool = True,
+) -> List[LocalModelInfo]:
     if not _safe_is_dir(cache_dir):
         return []
 
@@ -240,7 +242,10 @@ def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[L
             repo_dir,
         )
         gguf_partial = hf_cache_scan.is_gguf_repo_partial(model_id, repo_dir)
-        has_gguf_variant_state, gguf_variant_state_size = _gguf_variant_state_summary(model_id)
+        has_gguf_variant_state, gguf_variant_state_size = _gguf_variant_state_summary(
+            model_id,
+            hub_cache = cache_dir,
+        )
         snapshot_partial_transport = (
             hf_cache_scan.partial_transport_for(
                 "model",
@@ -252,23 +257,25 @@ def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[L
         )
         resolved = hf_cache_scan.resolve_hf_cache_realpath(repo_dir)
         scan_path = Path(resolved) if resolved else repo_dir
+        load_path = repo_dir if active_cache else scan_path
         # partial=False here; _apply_format_aware_partial below rewrites per-row
         # so a hybrid repo's gguf row doesn't taint its safetensors row.
         rows = _classify_local_path(
             scan_path,
             "hf_cache",
-            load_path = repo_dir,
+            load_path = load_path,
             display_name = model_id.split("/")[-1],
             model_id = model_id,
             updated_at = updated_at,
             partial = False,
+            active_cache = active_cache,
         )
         if not rows:
             if has_gguf_variant_state and gguf_partial:
                 rows = [
                     _local_model_info(
                         scan_path = repo_dir,
-                        load_path = repo_dir,
+                        load_path = load_path,
                         source = "hf_cache",
                         model_format = "gguf",
                         display_name = model_id.split("/")[-1],
@@ -277,6 +284,7 @@ def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[L
                         partial = True,
                         requires_variant = True,
                         size_bytes = gguf_variant_state_size,
+                        active_cache = active_cache,
                     )
                 ]
             else:
@@ -285,13 +293,14 @@ def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[L
                 rows = [
                     _local_model_info(
                         scan_path = repo_dir,
-                        load_path = repo_dir,
+                        load_path = load_path,
                         source = "hf_cache",
                         model_format = "unknown",
                         display_name = model_id.split("/")[-1],
                         model_id = model_id,
                         updated_at = updated_at,
                         partial = snapshot_partial or gguf_partial,
+                        active_cache = active_cache,
                     )
                 ]
         elif (
@@ -302,7 +311,7 @@ def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[L
             rows.append(
                 _local_model_info(
                     scan_path = repo_dir,
-                    load_path = repo_dir,
+                    load_path = load_path,
                     source = "hf_cache",
                     model_format = "gguf",
                     display_name = model_id.split("/")[-1],
@@ -311,6 +320,7 @@ def _scan_hf_cache(cache_dir: Path, *, entry_limit: int | None = None) -> List[L
                     partial = True,
                     requires_variant = True,
                     size_bytes = gguf_variant_state_size,
+                    active_cache = active_cache,
                 )
             )
         rows = _apply_format_aware_partial(
@@ -515,14 +525,39 @@ async def _collect_models_from_default_sources(
     local_models += await _scan_source("HF cache", _scan_hf_cache, hf_cache_dir)
 
     if _safe_is_dir(legacy_hf) and legacy_hf.resolve() != hf_cache_dir.resolve():
-        local_models += await _scan_source("legacy HF cache", _scan_hf_cache, legacy_hf)
+        local_models += await _scan_source(
+            "legacy HF cache",
+            lambda path: _scan_hf_cache(path, active_cache = False),
+            legacy_hf,
+        )
 
     if (
         _safe_is_dir(hf_default)
         and hf_default.resolve() != hf_cache_dir.resolve()
         and hf_default.resolve() != legacy_hf.resolve()
     ):
-        local_models += await _scan_source("default HF cache", _scan_hf_cache, hf_default)
+        local_models += await _scan_source(
+            "default HF cache",
+            lambda path: _scan_hf_cache(path, active_cache = False),
+            hf_default,
+        )
+
+    from utils.hf_cache_settings import known_hf_hub_caches
+
+    seen_hf = {
+        os.path.normcase(str(path.resolve(strict = False)))
+        for path in (hf_cache_dir, legacy_hf, hf_default)
+    }
+    for previous_cache in known_hf_hub_caches():
+        key = os.path.normcase(str(previous_cache.resolve(strict = False)))
+        if key in seen_hf:
+            continue
+        seen_hf.add(key)
+        local_models += await _scan_source(
+            "previous HF cache",
+            lambda path: _scan_hf_cache(path, active_cache = False),
+            previous_cache,
+        )
 
     for lm_dir in lm_dirs:
         local_models += await _scan_source("LM Studio", _scan_lmstudio_dir, lm_dir)
@@ -543,7 +578,11 @@ def _scan_custom_folder(folder_path: Path) -> List[LocalModelInfo]:
                 limit = _MAX_MODELS_PER_CUSTOM_FOLDER,
                 entry_limit = _MAX_CUSTOM_FOLDER_ENTRIES,
             )
-            + _scan_hf_cache(folder_path, entry_limit = _MAX_CUSTOM_FOLDER_ENTRIES)
+            + _scan_hf_cache(
+                folder_path,
+                entry_limit = _MAX_CUSTOM_FOLDER_ENTRIES,
+                active_cache = False,
+            )
             + _scan_lmstudio_dir(folder_path, entry_limit = _MAX_CUSTOM_FOLDER_ENTRIES)
         )
         if m.model_format in supported_formats
@@ -610,12 +649,20 @@ def _dedupe_local_models(local_models: List[LocalModelInfo]) -> list[LocalModelI
             row_key = model.inventory_id or model.id
             key = f"{row_key}\x00custom" if model.source == "custom" else row_key
         existing = deduped.get(key)
-        if existing is None or _prefer_complete_larger(
-            model.partial,
-            model.size_bytes,
-            existing.partial,
-            existing.size_bytes,
-        ):
+        prefer_candidate = existing is None
+        if existing is not None:
+            if model.partial != existing.partial:
+                prefer_candidate = not model.partial
+            elif (model.active_cache is True) != (existing.active_cache is True):
+                prefer_candidate = model.active_cache is True
+            else:
+                prefer_candidate = _prefer_complete_larger(
+                    model.partial,
+                    model.size_bytes,
+                    existing.partial,
+                    existing.size_bytes,
+                )
+        if prefer_candidate:
             deduped[key] = model
     return sorted(
         deduped.values(),
diff --git a/studio/backend/hub/services/snapshot_progress.py b/studio/backend/hub/services/snapshot_progress.py
index 1fdf05e2e5..c3db6fed7a 100644
--- a/studio/backend/hub/services/snapshot_progress.py
+++ b/studio/backend/hub/services/snapshot_progress.py
@@ -86,9 +86,20 @@ def _snapshot_complete_on_disk(
         return False
     if variant is None and hf_cache_scan.repo_cache_dir_has_incomplete_blobs(entry):
         return False
-    if download_manifest.has_cancel_marker(repo_type, repo_id, variant):
+    hub_cache = entry.parent
+    if download_manifest.has_cancel_marker(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = hub_cache,
+    ):
         return False
-    manifest = download_manifest.read_manifest(repo_type, repo_id, variant)
+    manifest = download_manifest.read_manifest(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = hub_cache,
+    )
     if manifest is None:
         return False
     return download_manifest.verify_against_disk(manifest, snapshot_dir).ok
@@ -118,6 +129,8 @@ def compute_snapshot_progress(
         0,
         int(getattr(metadata, "completed_baseline_bytes", 0) or 0),
     )
+    metadata_hub_cache = getattr(metadata, "hub_cache", None)
+    active_root = Path(metadata_hub_cache) if metadata_hub_cache else None
 
     expected_total = max(expected_bytes, 0)
     # Always resolve the revision's blob hashes so stale blobs from a superseded
@@ -134,11 +147,17 @@ def compute_snapshot_progress(
     count_finalized_unscoped = variant is None
 
     readings: list[tuple[int, int, Optional[str], bool]] = []
-    for entry in preferred_repo_cache_dirs(
-        repo_type,
-        repo_id,
-        force_active = force_active,
-    ):
+    cache_dirs = (
+        preferred_repo_cache_dirs(
+            repo_type,
+            repo_id,
+            force_active = force_active,
+            active_root = active_root,
+        )
+        if active_root is not None
+        else preferred_repo_cache_dirs(repo_type, repo_id, force_active = force_active)
+    )
+    for entry in cache_dirs:
         completed_bytes = 0
         in_progress_bytes = 0
         cache_path = hf_cache_scan.resolve_hf_cache_realpath(entry)
diff --git a/studio/backend/hub/tests/test_dataset_services.py b/studio/backend/hub/tests/test_dataset_services.py
index 4890714cd0..6aab07cc46 100644
--- a/studio/backend/hub/tests/test_dataset_services.py
+++ b/studio/backend/hub/tests/test_dataset_services.py
@@ -72,57 +72,115 @@ def test_dataset_cache_scan_merges_raw_and_processed_rows(monkeypatch):
     assert rows[0]["partial"] is False
 
 
-def test_delete_cached_dataset_attempts_all_roots_before_raising(monkeypatch):
+def test_delete_cached_dataset_scopes_delete_to_selected_root(monkeypatch, tmp_path):
+    """A dataset present in the active cache and a previously selected cache is
+    deleted only from the selected root, so the other cache's copy survives."""
     calls = []
-    purged_state = []
+    target_hub = tmp_path / "active" / "hub"
+    other_hub = tmp_path / "previous" / "hub"
+    for hub in (target_hub, other_hub):
+        (hub / "datasets--Org--Data").mkdir(parents = True)
 
     class _DeleteStrategy:
-        def __init__(self, label: str, fail: bool):
+        def __init__(self, label: str):
             self.label = label
-            self.fail = fail
 
         def execute(self):
             calls.append(self.label)
-            if self.fail:
-                raise RuntimeError(f"{self.label} failed")
 
-    class _Cache:
-        def __init__(self, label: str, fail: bool):
-            self.cache_dir = label
-            self.repos = [
+    def _cache(label: str, hub):
+        return SimpleNamespace(
+            cache_dir = label,
+            repos = [
                 SimpleNamespace(
                     repo_type = "dataset",
                     repo_id = "Org/Data",
+                    repo_path = str(hub / "datasets--Org--Data"),
                     revisions = [SimpleNamespace(commit_hash = f"{label}-rev")],
                 )
-            ]
-            self.fail = fail
-
-        def delete_revisions(self, *_revisions):
-            return _DeleteStrategy(self.cache_dir, self.fail)
+            ],
+            delete_revisions = lambda *_revs, _label = label: _DeleteStrategy(_label),
+        )
 
     monkeypatch.setattr(
         cache_inventory,
         "_collect_hf_cache_scans",
-        lambda: ([_Cache("first", True), _Cache("second", False)], set()),
+        lambda: ([_cache("active", target_hub), _cache("previous", other_hub)], set()),
     )
     monkeypatch.setattr(
         cache_inventory,
         "_delete_processed_dataset_cache",
-        lambda _repo_id: (True, []),
+        lambda _repo_id, **_kwargs: (False, []),
     )
     monkeypatch.setattr(
         cache_inventory.download_manifest,
         "purge_all_state_for_repo",
-        lambda *_args: purged_state.append(True) or 1,
+        lambda *_args, **_kwargs: 0,
+    )
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = target_hub),
+    )
+    monkeypatch.setattr(
+        "hub.utils.hf_cache_state.hf_cache_roots",
+        lambda: [target_hub, other_hub],
     )
 
-    with pytest.raises(HTTPException) as exc_info:
-        cache_inventory._delete_cached_dataset_blocking("Org/Data")
+    result = cache_inventory._delete_cached_dataset_blocking("Org/Data")
 
-    assert exc_info.value.status_code == 500
-    assert calls == ["first", "second"]
-    assert purged_state == []
+    assert result == {"status": "deleted", "repo_id": "Org/Data"}
+    # Only the selected (active) cache's revision is deleted; the previous
+    # cache's copy is never touched.
+    assert calls == ["active"]
+    assert not (target_hub / "datasets--Org--Data").exists()
+    assert (other_hub / "datasets--Org--Data").exists()
+
+
+def test_delete_processed_only_dataset_accepts_processed_cache_path(monkeypatch, tmp_path):
+    """A processed-only dataset row sends its Arrow cache path (<owner>___<repo>
+    under HF_DATASETS_CACHE), which is not a Hub datasets-- dir. The delete must
+    accept it and run the processed-cache delete instead of raising 400."""
+    datasets_root = tmp_path / "datasets"
+    processed_dir = datasets_root / "Org___Data"
+    processed_dir.mkdir(parents = True)
+
+    # No Hub-cache copy exists; only the processed Arrow cache holds this repo.
+    monkeypatch.setattr(cache_inventory, "_collect_hf_cache_scans", lambda: ([], set()))
+    monkeypatch.setattr(cache_inventory, "_hf_datasets_cache_roots", lambda: [datasets_root])
+    processed_calls: list[str] = []
+    monkeypatch.setattr(
+        cache_inventory,
+        "_delete_processed_dataset_cache",
+        lambda repo_id, **_kwargs: (processed_calls.append(repo_id) or True, []),
+    )
+
+    result = cache_inventory._delete_cached_dataset_blocking("Org/Data", str(processed_dir))
+
+    assert result == {"status": "deleted", "repo_id": "Org/Data"}
+    assert processed_calls == ["Org/Data"]
+
+
+def test_delete_processed_dataset_scopes_to_selected_root(monkeypatch, tmp_path):
+    """A dataset processed under two HF_DATASETS_CACHE roots is deleted only from
+    the selected root; the copy under the other cache home survives (real delete,
+    not stubbed)."""
+    selected_root = tmp_path / "selected" / "datasets"
+    other_root = tmp_path / "other" / "datasets"
+    for root in (selected_root, other_root):
+        (root / "Org___Data").mkdir(parents = True)
+
+    monkeypatch.setattr(cache_inventory, "_collect_hf_cache_scans", lambda: ([], set()))
+    monkeypatch.setattr(
+        cache_inventory, "_hf_datasets_cache_roots", lambda: [selected_root, other_root]
+    )
+
+    result = cache_inventory._delete_cached_dataset_blocking(
+        "Org/Data", str(selected_root / "Org___Data")
+    )
+
+    assert result == {"status": "deleted", "repo_id": "Org/Data"}
+    assert not (selected_root / "Org___Data").exists()  # the selected copy is deleted
+    assert (other_root / "Org___Data").exists()  # the other cache home is untouched
 
 
 def test_delete_cached_dataset_purges_blob_only_repo_dir(monkeypatch):
@@ -139,22 +197,22 @@ def test_delete_cached_dataset_purges_blob_only_repo_dir(monkeypatch):
     monkeypatch.setattr(
         cache_inventory,
         "_delete_processed_dataset_cache",
-        lambda _repo_id: (False, []),
+        lambda _repo_id, **_kwargs: (False, []),
     )
     monkeypatch.setattr(
         cache_inventory,
         "purge_repo_cache_dirs",
-        lambda _repo_type, repo_id: purged_dirs.append(repo_id) or True,
+        lambda _repo_type, repo_id, **_kwargs: purged_dirs.append(repo_id) or True,
     )
     monkeypatch.setattr(
         cache_inventory,
         "purge_partial_repo",
-        lambda *_args: False,
+        lambda *_args, **_kwargs: False,
     )
     monkeypatch.setattr(
         cache_inventory.download_manifest,
         "purge_all_state_for_repo",
-        lambda *_args: 0,
+        lambda *_args, **_kwargs: 0,
     )
 
     result = cache_inventory._delete_cached_dataset_blocking("Org/Data")
@@ -172,22 +230,22 @@ def test_delete_cached_dataset_absent_everywhere_raises_404(monkeypatch):
     monkeypatch.setattr(
         cache_inventory,
         "_delete_processed_dataset_cache",
-        lambda _repo_id: (False, []),
+        lambda _repo_id, **_kwargs: (False, []),
     )
     monkeypatch.setattr(
         cache_inventory,
         "purge_repo_cache_dirs",
-        lambda *_args: False,
+        lambda *_args, **_kwargs: False,
     )
     monkeypatch.setattr(
         cache_inventory,
         "purge_partial_repo",
-        lambda *_args: False,
+        lambda *_args, **_kwargs: False,
     )
     monkeypatch.setattr(
         cache_inventory.download_manifest,
         "purge_all_state_for_repo",
-        lambda *_args: 0,
+        lambda *_args, **_kwargs: 0,
     )
 
     with pytest.raises(HTTPException) as exc_info:
diff --git a/studio/backend/hub/tests/test_download_manifest_scoping.py b/studio/backend/hub/tests/test_download_manifest_scoping.py
new file mode 100644
index 0000000000..966eeaf0c2
--- /dev/null
+++ b/studio/backend/hub/tests/test_download_manifest_scoping.py
@@ -0,0 +1,62 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import json
+from types import SimpleNamespace
+
+from hub.utils import download_manifest, state_dir
+
+
+def _write_manifest(path, payload):
+    path.parent.mkdir(parents = True, exist_ok = True)
+    path.write_text(json.dumps(payload), encoding = "utf-8")
+
+
+def test_purge_state_preserves_active_legacy_when_deleting_inactive_cache(monkeypatch, tmp_path):
+    """A scoped delete of an inactive cache must not erase the unscoped legacy
+    state, which _legacy_state_applies attributes to the active cache."""
+    active = tmp_path / "active" / "hub"
+    previous = tmp_path / "previous" / "hub"
+    for path in (active, previous):
+        path.mkdir(parents = True)
+
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path / "state")
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = str(active)),
+    )
+
+    # Unowned legacy manifest -> belongs to the active cache.
+    legacy = state_dir.manifest_path("model", "Org/Model")
+    _write_manifest(legacy, {"version": 1})
+    # The inactive cache's own scoped copy is the one being deleted.
+    scoped = state_dir.manifest_path("model", "Org/Model", hub_cache = str(previous))
+    _write_manifest(scoped, {"version": 1, "hub_cache": str(previous)})
+
+    removed = download_manifest.purge_state("model", "Org/Model", hub_cache = str(previous))
+
+    assert removed is True
+    assert not scoped.is_file()  # the inactive cache's copy is gone
+    assert legacy.is_file()  # the active cache's legacy state survives
+
+
+def test_purge_state_removes_legacy_owned_by_the_deleted_cache(monkeypatch, tmp_path):
+    """A legacy file that recorded the deleted cache as its owner is purged."""
+    active = tmp_path / "active" / "hub"
+    previous = tmp_path / "previous" / "hub"
+    for path in (active, previous):
+        path.mkdir(parents = True)
+
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path / "state")
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = str(active)),
+    )
+
+    legacy = state_dir.manifest_path("model", "Org/Model")
+    _write_manifest(legacy, {"version": 1, "hub_cache": str(previous)})
+
+    removed = download_manifest.purge_state("model", "Org/Model", hub_cache = str(previous))
+
+    assert removed is True
+    assert not legacy.is_file()  # owned by the deleted cache -> purged
diff --git a/studio/backend/hub/tests/test_empty_variant_folder.py b/studio/backend/hub/tests/test_empty_variant_folder.py
index 33bf6c6819..3ed8e69e0d 100644
--- a/studio/backend/hub/tests/test_empty_variant_folder.py
+++ b/studio/backend/hub/tests/test_empty_variant_folder.py
@@ -120,10 +120,16 @@ def _force_compute_to_raise(monkeypatch):
 
     monkeypatch.setattr(gguf_variants, "list_gguf_variants", _boom, raising = False)
     monkeypatch.setattr(
-        gguf_variants, "list_gguf_variants_from_hf_cache", lambda repo_id: None, raising = False
+        gguf_variants,
+        "list_gguf_variants_from_hf_cache",
+        lambda repo_id, root = None: None,
+        raising = False,
     )
     monkeypatch.setattr(
-        gguf_variants, "list_partial_gguf_variants_from_state", lambda repo_id: None, raising = False
+        gguf_variants,
+        "list_partial_gguf_variants_from_state",
+        lambda repo_id, hub_cache = None: None,
+        raising = False,
     )
 
 
@@ -133,7 +139,11 @@ def test_get_variants_surfaces_cleanable_when_metadata_fails(monkeypatch):
     import asyncio
 
     _force_compute_to_raise(monkeypatch)
-    monkeypatch.setattr(gguf_variants, "list_empty_gguf_variant_dirs", lambda repo_id: {"UD-IQ1_S"})
+    monkeypatch.setattr(
+        gguf_variants,
+        "list_empty_gguf_variant_dirs",
+        lambda repo_id, root = None: {"UD-IQ1_S"},
+    )
 
     resp = asyncio.run(
         gguf_variants.get_gguf_variants_response(
@@ -152,7 +162,11 @@ def test_get_variants_reraises_when_no_cleanable(monkeypatch):
     from fastapi import HTTPException
 
     _force_compute_to_raise(monkeypatch)
-    monkeypatch.setattr(gguf_variants, "list_empty_gguf_variant_dirs", lambda repo_id: set())
+    monkeypatch.setattr(
+        gguf_variants,
+        "list_empty_gguf_variant_dirs",
+        lambda repo_id, root = None: set(),
+    )
 
     try:
         asyncio.run(
diff --git a/studio/backend/hub/tests/test_model_services.py b/studio/backend/hub/tests/test_model_services.py
index 693d945ee1..fa5862a13c 100644
--- a/studio/backend/hub/tests/test_model_services.py
+++ b/studio/backend/hub/tests/test_model_services.py
@@ -2,6 +2,7 @@
 # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import asyncio
+import json
 import sys
 from pathlib import Path
 from types import SimpleNamespace
@@ -102,6 +103,236 @@ def test_big_endian_detection_ignores_model_name_be_token():
     )
 
 
+def _cached_model_row(tmp_path: Path, *, partial: bool, active_cache: bool | None, size_bytes: int):
+    path = tmp_path / f"cache-{active_cache}-{partial}-{size_bytes}"
+    return model_common._local_model_info(
+        scan_path = path,
+        load_path = path,
+        source = "hf_cache",
+        model_format = "safetensors",
+        model_id = "Org/Model",
+        partial = partial,
+        active_cache = active_cache,
+        size_bytes = size_bytes,
+    )
+
+
+@pytest.mark.parametrize("reverse", [False, True])
+def test_local_inventory_prefers_complete_previous_cache_copy(tmp_path, reverse):
+    active_partial = _cached_model_row(
+        tmp_path,
+        partial = True,
+        active_cache = True,
+        size_bytes = 20,
+    )
+    previous_complete = _cached_model_row(
+        tmp_path,
+        partial = False,
+        active_cache = False,
+        size_bytes = 10,
+    )
+    rows = [active_partial, previous_complete]
+    if reverse:
+        rows.reverse()
+
+    result = local_inventory._dedupe_local_models(rows)
+
+    assert result == [previous_complete]
+
+
+def test_local_inventory_compares_all_non_active_cache_copies(tmp_path):
+    inactive_partial = _cached_model_row(
+        tmp_path,
+        partial = True,
+        active_cache = False,
+        size_bytes = 20,
+    )
+    custom_complete = _cached_model_row(
+        tmp_path,
+        partial = False,
+        active_cache = None,
+        size_bytes = 10,
+    )
+
+    assert local_inventory._dedupe_local_models([inactive_partial, custom_complete]) == [
+        custom_complete
+    ]
+
+
+def test_local_inventory_prefers_active_cache_when_copies_are_equally_complete(tmp_path):
+    previous = _cached_model_row(
+        tmp_path,
+        partial = False,
+        active_cache = False,
+        size_bytes = 20,
+    )
+    active = _cached_model_row(
+        tmp_path,
+        partial = False,
+        active_cache = True,
+        size_bytes = 10,
+    )
+
+    assert local_inventory._dedupe_local_models([previous, active]) == [active]
+
+
+def test_loaded_repo_match_accepts_previous_cache_snapshot_path(monkeypatch, tmp_path):
+    repo_dir = tmp_path / "old-hub" / "models--Org--Model"
+    snapshot = repo_dir / "snapshots" / "revision"
+    snapshot.mkdir(parents = True)
+    monkeypatch.setattr(deletion, "iter_repo_cache_dirs", lambda *_args: iter([repo_dir]))
+
+    assert deletion._loaded_id_matches_repo(str(snapshot), "Org/Model") is True
+    assert deletion._loaded_id_matches_repo(str(snapshot / "model.gguf"), "Org/Model") is True
+    assert deletion._loaded_id_matches_repo(str(tmp_path / "other"), "Org/Model") is False
+
+
+def test_cached_inventory_loads_previous_cache_copy_by_snapshot(monkeypatch, tmp_path):
+    active_hub = tmp_path / "active-hub"
+    previous_repo = tmp_path / "previous-hub" / "models--Org--Model"
+    snapshot = previous_repo / "snapshots" / "revision"
+    snapshot.mkdir(parents = True)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = active_hub),
+    )
+
+    fields = cache_inventory._cache_inventory_fields(
+        "Org/Model",
+        "safetensors",
+        repo_path = previous_repo,
+        snapshot_path = snapshot,
+    )
+
+    assert fields["load_id"] == str(snapshot)
+
+
+def test_cached_inventory_keeps_repo_id_for_active_cache(monkeypatch, tmp_path):
+    active_hub = tmp_path / "active-hub"
+    active_repo = active_hub / "models--Org--Model"
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = active_hub),
+    )
+
+    fields = cache_inventory._cache_inventory_fields(
+        "Org/Model",
+        "safetensors",
+        repo_path = active_repo,
+    )
+
+    assert fields["load_id"] == "Org/Model"
+
+
+def test_cached_inventory_prefers_active_copy_when_completeness_matches():
+    previous = {"partial": False, "active_cache": False, "size_bytes": 200}
+    active = {"partial": False, "active_cache": True, "size_bytes": 100}
+
+    assert cache_inventory._prefer_cache_row(active, previous) is True
+    assert cache_inventory._prefer_cache_row(previous, active) is False
+
+
+def test_cached_inventory_prefers_complete_copy_before_active_cache():
+    previous = {"partial": False, "active_cache": False, "size_bytes": 100}
+    active_partial = {"partial": True, "active_cache": True, "size_bytes": 200}
+
+    assert cache_inventory._prefer_cache_row(previous, active_partial) is True
+    assert cache_inventory._prefer_cache_row(active_partial, previous) is False
+
+
+def test_inventory_scans_every_dynamic_cache_root(monkeypatch, tmp_path):
+    first = tmp_path / "first-hub"
+    second = tmp_path / "second-hub"
+    unreadable = tmp_path / "unreadable-hub"
+    first.mkdir()
+    second.mkdir()
+    unreadable.mkdir()
+    scanned = []
+
+    monkeypatch.setattr(
+        inventory_scan,
+        "hf_cache_roots",
+        lambda: [first, unreadable, second],
+    )
+
+    def scan_cache(cache_dir):
+        path = Path(cache_dir)
+        scanned.append(path)
+        if path == unreadable:
+            raise PermissionError("unreadable")
+        return SimpleNamespace(cache_dir = cache_dir)
+
+    monkeypatch.setattr("huggingface_hub.scan_cache_dir", scan_cache)
+
+    result = inventory_scan._compute_all_hf_cache_scans()
+
+    assert scanned == [first, unreadable, second]
+    assert [Path(scan.cache_dir) for scan in result] == [first, second]
+
+
+def test_inventory_applies_download_state_to_its_owning_cache(monkeypatch, tmp_path):
+    state_root = tmp_path / "state"
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+    repo_id = "Org/Model"
+    repo_name = "models--Org--Model"
+    repo_a = cache_a / repo_name
+    repo_b = cache_b / repo_name
+    snapshot_a = repo_a / "snapshots" / "revision"
+    snapshot_b = repo_b / "snapshots" / "revision"
+    snapshot_a.mkdir(parents = True)
+    snapshot_b.mkdir(parents = True)
+    (snapshot_a / "config.json").write_bytes(b"x")
+    (snapshot_b / "config.json").write_bytes(b"xx")
+
+    monkeypatch.setattr(state_dir, "cache_root", lambda: state_root)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = cache_b),
+    )
+    assert download_manifest.write_manifest(
+        "model",
+        repo_id,
+        None,
+        [download_manifest.ExpectedFile(path = "config.json", size = 2)],
+        "http",
+        hub_cache = cache_a,
+    )
+
+    assert inventory_scan.is_snapshot_partial("model", repo_id, repo_a) is True
+    assert inventory_scan.is_snapshot_partial("model", repo_id, repo_b) is False
+    assert inventory_scan.partial_transport_for("model", repo_id, None, repo_a) == "http"
+    assert inventory_scan.partial_transport_for("model", repo_id, None, repo_b) is None
+
+
+def test_inventory_scopes_cancel_markers_to_their_owning_cache(monkeypatch, tmp_path):
+    state_root = tmp_path / "state"
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+    repo_id = "Org/Model"
+    repo_name = "models--Org--Model"
+    repo_a = cache_a / repo_name
+    repo_b = cache_b / repo_name
+    repo_a.mkdir(parents = True)
+    repo_b.mkdir(parents = True)
+
+    monkeypatch.setattr(state_dir, "cache_root", lambda: state_root)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = cache_b),
+    )
+    assert download_manifest.write_cancel_marker(
+        "model",
+        repo_id,
+        "Q4_K_M",
+        "xet",
+        hub_cache = cache_a,
+    )
+
+    assert inventory_scan.is_variant_partial(repo_id, "Q4_K_M", repo_cache_dir = repo_a) is True
+    assert inventory_scan.is_variant_partial(repo_id, "Q4_K_M", repo_cache_dir = repo_b) is False
+
+
 def test_list_local_gguf_variants_skips_big_endian_sibling(tmp_path):
     (tmp_path / "model-Q4_K_M-be.gguf").write_bytes(b"x" * 100)
     (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"y" * 10)
@@ -163,8 +394,19 @@ def test_download_state_bounds_long_repo_variant_filenames(monkeypatch, tmp_path
         "http",
     )
 
-    marker_path = state_dir.marker_path("model", repo_id, variant)
-    manifest_path = state_dir.manifest_path("model", repo_id, variant)
+    hub_cache = download_manifest._canonical_hub_cache()
+    marker_path = state_dir.marker_path(
+        "model",
+        repo_id,
+        variant,
+        hub_cache = hub_cache,
+    )
+    manifest_path = state_dir.manifest_path(
+        "model",
+        repo_id,
+        variant,
+        hub_cache = hub_cache,
+    )
 
     assert marker_path is not None
     assert manifest_path is not None
@@ -181,6 +423,97 @@ def test_download_state_bounds_long_repo_variant_filenames(monkeypatch, tmp_path
     ]
 
 
+def test_download_state_isolated_across_hub_cache_switches(monkeypatch, tmp_path):
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path)
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+    selected = SimpleNamespace(hub_cache = cache_a)
+
+    from utils import hf_cache_settings
+
+    monkeypatch.setattr(hf_cache_settings, "get_hf_cache_paths", lambda: selected)
+    expected_a = [download_manifest.ExpectedFile(path = "a.gguf", size = 1)]
+    expected_b = [download_manifest.ExpectedFile(path = "b.gguf", size = 2)]
+
+    assert download_manifest.write_manifest("model", "Owner/Repo", "Q4_K_M", expected_a)
+    assert download_manifest.write_cancel_marker("model", "Owner/Repo", "Q4_K_M", "http")
+
+    selected.hub_cache = cache_b
+    assert download_manifest.write_manifest("model", "Owner/Repo", "Q4_K_M", expected_b)
+
+    manifest_b = download_manifest.read_manifest("model", "Owner/Repo", "Q4_K_M")
+    manifest_a = download_manifest.read_manifest(
+        "model",
+        "Owner/Repo",
+        "Q4_K_M",
+        hub_cache = cache_a,
+    )
+
+    assert manifest_b is not None and manifest_b.expected_files == tuple(expected_b)
+    assert manifest_a is not None and manifest_a.expected_files == tuple(expected_a)
+    assert not download_manifest.has_cancel_marker("model", "Owner/Repo", "Q4_K_M")
+    assert download_manifest.has_cancel_marker(
+        "model",
+        "Owner/Repo",
+        "Q4_K_M",
+        hub_cache = cache_a,
+    )
+    assert len(list((tmp_path / "hub-state" / "manifests").rglob("*.json"))) == 2
+
+
+def test_legacy_unscoped_download_state_falls_back_only_for_selected_cache(monkeypatch, tmp_path):
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path)
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = cache_a),
+    )
+    manifest = state_dir.manifest_path("model", "Owner/Repo", "Q4_K_M")
+    marker = state_dir.marker_path("model", "Owner/Repo", "Q4_K_M")
+    assert manifest is not None and marker is not None
+    manifest.write_text(
+        json.dumps(
+            {
+                "version": 1,
+                "repo_id": "Owner/Repo",
+                "variant": "Q4_K_M",
+                "expected_files": [{"path": "model.gguf", "size": 10}],
+                "transport": "http",
+            }
+        ),
+        encoding = "utf-8",
+    )
+    marker.write_text(
+        json.dumps({"version": 1, "repo_id": "Owner/Repo", "variant": "Q4_K_M"}),
+        encoding = "utf-8",
+    )
+
+    assert download_manifest.read_manifest("model", "Owner/Repo", "Q4_K_M") is not None
+    assert download_manifest.has_cancel_marker("model", "Owner/Repo", "Q4_K_M")
+    assert list(download_manifest.iter_variant_manifests("model", "Owner/Repo")) == [
+        ("Q4_K_M", manifest)
+    ]
+    assert list(download_manifest.iter_variant_markers("model", "Owner/Repo")) == [
+        ("Q4_K_M", marker)
+    ]
+    assert (
+        download_manifest.read_manifest(
+            "model",
+            "Owner/Repo",
+            "Q4_K_M",
+            hub_cache = cache_b,
+        )
+        is None
+    )
+    assert not download_manifest.has_cancel_marker(
+        "model",
+        "Owner/Repo",
+        "Q4_K_M",
+        hub_cache = cache_b,
+    )
+
+
 class _RecordingLogger:
     def __init__(self):
         self.warnings = []
@@ -416,8 +749,15 @@ def test_cached_gguf_scan_includes_variant_state_without_completed_gguf(monkeypa
         "Q4_K_M",
         [download_manifest.ExpectedFile(path = "model-Q4_K_M.gguf", size = 4096)],
         "http",
+        hub_cache = repo_path.parent,
+    )
+    assert download_manifest.write_cancel_marker(
+        "model",
+        "Org/PartialGguf",
+        "Q4_K_M",
+        "http",
+        hub_cache = repo_path.parent,
     )
-    assert download_manifest.write_cancel_marker("model", "Org/PartialGguf", "Q4_K_M", "http")
     monkeypatch.setattr(
         cache_inventory,
         "all_hf_cache_scans",
@@ -484,6 +824,7 @@ def test_cached_gguf_scan_keeps_infra_repo_with_user_downloaded_variant(monkeypa
         "Q8_0",
         [download_manifest.ExpectedFile(path = "bge-small-en-v1.5-Q8_0.gguf", size = 35_000_000)],
         "http",
+        hub_cache = Path(embedder.repo_path).parent,
     )
     monkeypatch.setattr(
         cache_inventory,
@@ -1206,6 +1547,7 @@ def test_gguf_progress_counts_completed_mmproj_with_expected_bytes(monkeypatch,
             ),
         ],
         "http",
+        hub_cache = entry.parent,
     )
 
     requirement = gguf_variants._GgufVariantRequirement(
@@ -1292,6 +1634,7 @@ def test_gguf_progress_subtracts_new_job_completed_baseline(monkeypatch, tmp_pat
             ),
         ],
         "http",
+        hub_cache = entry.parent,
     )
 
     requirement = gguf_variants._GgufVariantRequirement(
@@ -1462,6 +1805,7 @@ def test_gguf_progress_complete_on_disk_ignores_full_baseline(monkeypatch, tmp_p
             ),
         ],
         "http",
+        hub_cache = entry.parent,
     )
 
     requirement = gguf_variants._GgufVariantRequirement(
@@ -1861,8 +2205,15 @@ def test_hf_cache_scan_uses_gguf_partial_row_for_variant_state(monkeypatch, tmp_
         "Q4_K_M",
         [download_manifest.ExpectedFile(path = "model-Q4_K_M.gguf", size = 8192)],
         "http",
+        hub_cache = cache_dir,
+    )
+    assert download_manifest.write_cancel_marker(
+        "model",
+        "Org/PartialGguf",
+        "Q4_K_M",
+        "http",
+        hub_cache = cache_dir,
     )
-    assert download_manifest.write_cancel_marker("model", "Org/PartialGguf", "Q4_K_M", "http")
     monkeypatch.setattr(local_inventory, "_classify_local_path", lambda *_args, **_kwargs: [])
     monkeypatch.setattr(
         local_inventory.hf_cache_scan,
@@ -2117,7 +2468,7 @@ def test_gguf_variants_partial_marker_overrides_size_only_downloaded(monkeypatch
     monkeypatch.setattr(
         gguf_variants,
         "iter_hf_cache_snapshots",
-        lambda _repo_id: [snapshot],
+        lambda _repo_id, root = None: [snapshot],
     )
     monkeypatch.setattr(
         gguf_variants,
@@ -2136,6 +2487,70 @@ def test_gguf_variants_partial_marker_overrides_size_only_downloaded(monkeypatch
     assert result.variants[0].partial is True
 
 
+def test_gguf_variants_scopes_partial_state_to_requested_cache(monkeypatch, tmp_path):
+    async def _run_inline(fn, *args, **kwargs):
+        return fn(*args, **kwargs)
+
+    repo_id = "Org/SharedRepo"
+    repo_name = "models--Org--SharedRepo"
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+    repo_a = cache_a / repo_name
+    snapshot_a = repo_a / "snapshots" / "revision"
+    snapshot_a.mkdir(parents = True)
+    (snapshot_a / "model-Q8_0.gguf").write_bytes(b"complete")
+    blobs_b = cache_b / repo_name / "blobs"
+    blobs_b.mkdir(parents = True)
+    (blobs_b / "q8-hash.incomplete").write_bytes(b"partial")
+
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path / "state")
+    monkeypatch.setattr(gguf_variants.asyncio, "to_thread", _run_inline)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = cache_b),
+    )
+    assert download_manifest.write_cancel_marker(
+        "model",
+        repo_id,
+        "Q8_0",
+        "http",
+        hub_cache = cache_b,
+    )
+    monkeypatch.setattr(
+        gguf_variants,
+        "list_gguf_variants",
+        lambda *_args, **_kwargs: (
+            [
+                SimpleNamespace(
+                    filename = "model-Q8_0.gguf",
+                    quant = "Q8_0",
+                    display_label = None,
+                    size_bytes = 8,
+                )
+            ],
+            False,
+            [
+                SimpleNamespace(
+                    rfilename = "model-Q8_0.gguf",
+                    size = 8,
+                    lfs = SimpleNamespace(sha256 = "q8-hash"),
+                )
+            ],
+        ),
+    )
+    monkeypatch.setattr(cache_inventory, "all_hf_cache_scans", lambda: [])
+
+    result = asyncio.run(
+        gguf_variants.get_gguf_variants_response(
+            repo_id,
+            local_path = str(repo_a),
+        )
+    )
+
+    assert result.variants[0].downloaded is True
+    assert result.variants[0].partial is False
+
+
 def test_download_registry_repo_keys_are_case_insensitive():
     registry = download_registry.DownloadRegistry()
 
@@ -2444,6 +2859,34 @@ def test_prepare_cache_for_transport_purges_only_requested_hashes(monkeypatch, t
     assert (blobs / "shared-mmproj.incomplete").exists()
 
 
+def test_prepare_cache_for_transport_uses_captured_root(monkeypatch, tmp_path):
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+    repo_name = "models--Org--Repo"
+    partial_a = cache_a / repo_name / "blobs" / "blob.incomplete"
+    partial_b = cache_b / repo_name / "blobs" / "blob.incomplete"
+    partial_a.parent.mkdir(parents = True)
+    partial_b.parent.mkdir(parents = True)
+    partial_a.write_bytes(b"a")
+    partial_b.write_bytes(b"b")
+    monkeypatch.setattr(
+        download_registry,
+        "hf_cache_root",
+        lambda create = False, root = None: root or cache_b,
+    )
+
+    purged = download_registry.prepare_cache_for_transport(
+        "model",
+        "Org/Repo",
+        download_registry.TRANSPORT_HTTP,
+        root = cache_a,
+    )
+
+    assert purged == 1
+    assert not partial_a.exists()
+    assert partial_b.exists()
+
+
 def _vision_cache_root(monkeypatch, tmp_path):
     root = tmp_path / "hub"
     blobs = root / "models--Org--Vision" / "blobs"
@@ -2802,6 +3245,47 @@ def test_shutdown_skips_marker_for_worker_that_exits_cleanly(monkeypatch):
     assert markers == ["Org/Cut"]
 
 
+def test_orphan_reaper_uses_worker_cache_root_after_setting_changes(monkeypatch, tmp_path):
+    workers = tmp_path / "workers"
+    workers.mkdir()
+    cache_a = tmp_path / "cache-a" / "hub"
+    cache_b = tmp_path / "cache-b" / "hub"
+    partial = cache_a / "models--Org--Model" / "blobs" / "abc.incomplete"
+    partial.parent.mkdir(parents = True)
+    partial.write_bytes(b"partial")
+    cache_b.mkdir(parents = True)
+    monkeypatch.setattr(state_dir, "workers_dir", lambda: workers)
+    monkeypatch.setattr(download_registry, "_process_alive", lambda _pid: False)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = cache_b),
+    )
+    markers = []
+    monkeypatch.setattr(
+        download_registry,
+        "persist_cancel_marker",
+        lambda *args, **kwargs: markers.append(args),
+    )
+    metadata = download_registry.DownloadMetadata(
+        repo_type = "model",
+        repo_id = "Org/Model",
+        variant = None,
+        transport = download_registry.TRANSPORT_HTTP,
+        hub_cache = str(cache_a),
+        xet_cache = str(tmp_path / "cache-a" / "xet"),
+    )
+    download_registry.write_worker_breadcrumb("org/model", 1234, metadata)
+    [breadcrumb] = list(workers.iterdir())
+    payload = json.loads(breadcrumb.read_text(encoding = "utf-8"))
+    assert payload["hub_cache"] == str(cache_a)
+    assert payload["xet_cache"] == str(tmp_path / "cache-a" / "xet")
+
+    download_registry.reap_orphan_workers()
+
+    assert markers == [("model", "Org/Model", None, "http")]
+    assert list(workers.iterdir()) == []
+
+
 def test_model_claim_register_cancel_uses_registry_marker_owner(monkeypatch):
     killed = []
 
@@ -3125,12 +3609,19 @@ def _build_variant_cache_repo(repo_dir, blob_specs, snapshot_links):
     return repo
 
 
-def _patch_variant_delete_side_effects(monkeypatch):
+def _patch_variant_delete_side_effects(monkeypatch, hub_cache = None):
     monkeypatch.setattr(
         deletion.download_manifest,
         "purge_state",
         lambda *_args, **_kwargs: False,
     )
+    # The repo under test lives in this cache; make it the active one so the
+    # delete scopes to it (default target root is the active hub cache).
+    if hub_cache is not None:
+        monkeypatch.setattr(
+            "utils.hf_cache_settings.get_hf_cache_paths",
+            lambda: SimpleNamespace(hub_cache = hub_cache),
+        )
 
 
 def test_snapshot_progress_filters_stale_blobs(monkeypatch, tmp_path):
@@ -3308,7 +3799,7 @@ def test_delete_variant_keeps_blob_shared_with_other_snapshot(monkeypatch, tmp_p
         "all_hf_cache_scans",
         lambda: [SimpleNamespace(repos = [repo])],
     )
-    _patch_variant_delete_side_effects(monkeypatch)
+    _patch_variant_delete_side_effects(monkeypatch, tmp_path)
 
     result = deletion._delete_cached_model_blocking("Org/Repo-GGUF", "Q4_K_M", None)
 
@@ -3335,7 +3826,7 @@ def test_delete_variant_unlinks_unshared_blob(monkeypatch, tmp_path):
         "all_hf_cache_scans",
         lambda: [SimpleNamespace(repos = [repo])],
     )
-    _patch_variant_delete_side_effects(monkeypatch)
+    _patch_variant_delete_side_effects(monkeypatch, tmp_path)
 
     result = deletion._delete_cached_model_blocking("Org/Repo-GGUF", "Q4_K_M", None)
 
@@ -3361,7 +3852,7 @@ def test_delete_variant_surfaces_locked_file_as_conflict(monkeypatch, tmp_path):
         "all_hf_cache_scans",
         lambda: [SimpleNamespace(repos = [repo])],
     )
-    _patch_variant_delete_side_effects(monkeypatch)
+    _patch_variant_delete_side_effects(monkeypatch, tmp_path)
 
     real_unlink = Path.unlink
 
diff --git a/studio/backend/hub/utils/download_manifest.py b/studio/backend/hub/utils/download_manifest.py
index 5366689296..ac0ccb5490 100644
--- a/studio/backend/hub/utils/download_manifest.py
+++ b/studio/backend/hub/utils/download_manifest.py
@@ -77,6 +77,7 @@ class Manifest:
     started_at: str
     expected_files: tuple[ExpectedFile, ...]
     transport: Optional[str] = None
+    hub_cache: Optional[str] = None
 
 
 @dataclass(frozen = True)
@@ -86,6 +87,78 @@ class VerifyResult:
     size_mismatched: tuple[str, ...]
 
 
+def _canonical_hub_cache(hub_cache: Optional[str | Path] = None) -> Optional[str]:
+    if hub_cache is None:
+        try:
+            from utils.hf_cache_settings import get_hf_cache_paths
+            hub_cache = get_hf_cache_paths().hub_cache
+        except Exception:
+            return None
+    try:
+        return str(Path(hub_cache).expanduser().resolve(strict = False))
+    except (OSError, RuntimeError, ValueError):
+        return str(hub_cache)
+
+
+def _read_state_payload(path: Path) -> Optional[dict]:
+    try:
+        data = json.loads(path.read_text(encoding = "utf-8"))
+    except (OSError, ValueError) as exc:
+        logger.debug("Could not read Hub state %s: %s", path, exc)
+        return None
+    return data if isinstance(data, dict) else None
+
+
+def _legacy_state_applies(
+    path: Path,
+    requested_hub_cache: Optional[str],
+    *,
+    fail_closed: bool = False,
+) -> bool:
+    """Whether an old unscoped state file belongs to the requested cache.
+
+    Transitional files that recorded their cache keep that ownership. Older
+    files with no ownership can only be attributed to the currently selected
+    cache, which matches the single-cache behavior under which they were
+    written without leaking them into remembered inactive caches.
+    """
+    data = _read_state_payload(path)
+    if data is not None:
+        recorded = data.get("hub_cache")
+        if isinstance(recorded, str) and recorded:
+            return _canonical_hub_cache(recorded) == requested_hub_cache
+    elif not fail_closed:
+        return False
+    return requested_hub_cache == _canonical_hub_cache()
+
+
+def _state_read_path(
+    path_factory,
+    repo_type: RepoType,
+    repo_id: str,
+    variant: Optional[str],
+    hub_cache: Optional[str | Path],
+    *,
+    fail_closed: bool = False,
+) -> Optional[Path]:
+    requested = _canonical_hub_cache(hub_cache)
+    scoped = path_factory(repo_type, repo_id, variant, hub_cache = requested)
+    try:
+        if scoped is not None and scoped.is_file():
+            return scoped
+    except OSError:
+        pass
+    legacy = path_factory(repo_type, repo_id, variant)
+    if legacy is None or legacy == scoped:
+        return None
+    try:
+        if not legacy.is_file():
+            return None
+    except OSError:
+        return None
+    return legacy if _legacy_state_applies(legacy, requested, fail_closed = fail_closed) else None
+
+
 def _atomic_write_json(path: Path, payload: dict) -> bool:
     # Per-write uuid suffix so a concurrent caller or a stale tmp from a
     # previous crash cannot collide with the in-flight write.
@@ -124,6 +197,8 @@ def write_manifest(
     variant: Optional[str],
     expected_files: Sequence[ExpectedFile],
     transport: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> bool:
     """Write/overwrite the manifest for this triple. Best-effort.
 
@@ -131,7 +206,13 @@ def write_manifest(
     worst-case fallback is the pre-fix scanner behavior (one missed
     partial detection), which is no regression.
     """
-    path = manifest_path(repo_type, repo_id, variant)
+    recorded_hub_cache = _canonical_hub_cache(hub_cache)
+    path = manifest_path(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = recorded_hub_cache,
+    )
     if path is None:
         return False
     payload = {
@@ -149,6 +230,7 @@ def write_manifest(
             for f in expected_files
         ],
         "transport": transport,
+        "hub_cache": recorded_hub_cache,
     }
     return _atomic_write_json(path, payload)
 
@@ -157,6 +239,8 @@ def read_manifest(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> Optional[Manifest]:
     """Return the manifest if present and parseable; ``None`` otherwise.
 
@@ -171,15 +255,17 @@ def read_manifest(
     ``_MANIFEST_VERSION`` and widen this check) or live under a different
     filename, so an incompatible payload can never mis-classify rows.
     """
-    path = manifest_path(repo_type, repo_id, variant)
+    path = _state_read_path(
+        manifest_path,
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache,
+    )
     if path is None or not path.is_file():
         return None
-    try:
-        data = json.loads(path.read_text(encoding = "utf-8"))
-    except (OSError, ValueError) as exc:
-        logger.debug("Could not read manifest %s: %s", path, exc)
-        return None
-    if not isinstance(data, dict):
+    data = _read_state_payload(path)
+    if data is None:
         return None
     if data.get("version") != _MANIFEST_VERSION:
         logger.debug(
@@ -216,6 +302,7 @@ def read_manifest(
         started_at = str(data.get("started_at", "")),
         expected_files = tuple(expected),
         transport = transport if transport in ("http", "xet") else None,
+        hub_cache = data.get("hub_cache") if isinstance(data.get("hub_cache"), str) else None,
     )
 
 
@@ -289,6 +376,8 @@ def write_cancel_marker(
     repo_id: str,
     variant: Optional[str] = None,
     transport: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> bool:
     """Record that this triple was cancelled. Idempotent across repeated cancels.
 
@@ -296,7 +385,13 @@ def write_cancel_marker(
     inventory rows so the UI labels HTTP retries as continuable and XET
     retries as full redownloads. None is accepted for forward-compat.
     """
-    path = marker_path(repo_type, repo_id, variant)
+    recorded_hub_cache = _canonical_hub_cache(hub_cache)
+    path = marker_path(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = recorded_hub_cache,
+    )
     if path is None:
         return False
     payload = {
@@ -306,6 +401,7 @@ def write_cancel_marker(
         "variant": variant,
         "transport": transport,
         "cancelled_at": datetime.now(timezone.utc).isoformat(),
+        "hub_cache": recorded_hub_cache,
     }
     return _atomic_write_json(path, payload)
 
@@ -314,6 +410,8 @@ def read_cancel_marker_transport(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> Optional[str]:
     """Return the transport recorded in the cancel marker, or ``None`` if no
     marker exists or it is unreadable.
@@ -330,15 +428,17 @@ def read_cancel_marker_transport(
       ``None`` keeps the neutral "Retry" label.
     * Unknown future versions → ``None`` (unknown layout, unknown transport).
     """
-    path = marker_path(repo_type, repo_id, variant)
+    path = _state_read_path(
+        marker_path,
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache,
+    )
     if path is None or not path.is_file():
         return None
-    try:
-        data = json.loads(path.read_text(encoding = "utf-8"))
-    except (OSError, ValueError) as exc:
-        logger.debug("Could not read cancel marker %s: %s", path, exc)
-        return None
-    if not isinstance(data, dict):
+    data = _read_state_payload(path)
+    if data is None:
         return None
     version = data.get("version")
     if version == _LEGACY_MARKER_VERSION:
@@ -351,10 +451,30 @@ def read_cancel_marker_transport(
     return None
 
 
+def _all_matching_state_paths(
+    parent: Optional[Path], repo_type: RepoType, repo_id: str, variant: Optional[str]
+) -> tuple[Path, ...]:
+    if parent is None:
+        return ()
+    legacy_path = (
+        manifest_path(repo_type, repo_id, variant)
+        if parent.name == "manifests"
+        else marker_path(repo_type, repo_id, variant)
+    )
+    if legacy_path is None:
+        return ()
+    try:
+        return tuple(path for path in parent.rglob(legacy_path.name) if path.is_file())
+    except OSError:
+        return ()
+
+
 def clear_cancel_marker(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> None:
     """Remove the cancel marker for this triple if present.
 
@@ -362,31 +482,48 @@ def clear_cancel_marker(
     download-start (a fresh attempt supersedes prior cancel state) and
     again at successful completion (cleans up if the start clear failed).
     """
-    path = marker_path(repo_type, repo_id, variant)
-    if path is None:
-        return
-    try:
-        path.unlink(missing_ok = True)
-    except OSError as exc:
-        logger.debug("Could not clear cancel marker %s: %s", path, exc)
+    requested = _canonical_hub_cache(hub_cache)
+    path = marker_path(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = requested,
+    )
+    legacy = marker_path(repo_type, repo_id, variant)
+    paths = [path]
+    if (
+        legacy is not None
+        and legacy != path
+        and _legacy_state_applies(legacy, requested, fail_closed = True)
+    ):
+        paths.append(legacy)
+    for target in paths:
+        if target is None:
+            continue
+        try:
+            target.unlink(missing_ok = True)
+        except OSError as exc:
+            logger.debug("Could not clear cancel marker %s: %s", target, exc)
 
 
 def has_cancel_marker(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> bool:
-    """File-existence check only. Body is never read.
-
-    Fail-closed: a corrupt marker still returns ``True`` because the
-    file's existence is the signal (the user once cancelled this
-    triple, even if the body is unreadable).
-    """
-    path = marker_path(repo_type, repo_id, variant)
-    if path is None:
-        return False
+    """Return whether a cancel marker applies to the selected cache."""
+    path = _state_read_path(
+        marker_path,
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache,
+        fail_closed = True,
+    )
     try:
-        return path.is_file()
+        return path is not None and path.is_file()
     except OSError:
         return False
 
@@ -395,48 +532,124 @@ def delete_manifest(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> bool:
-    path = manifest_path(repo_type, repo_id, variant)
-    if path is None:
-        return False
-    try:
-        if not path.is_file():
-            return False
-        path.unlink()
-        return True
-    except OSError as exc:
-        logger.debug("Could not delete manifest %s: %s", path, exc)
-        return False
+    requested = _canonical_hub_cache(hub_cache)
+    path = manifest_path(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = requested,
+    )
+    legacy = manifest_path(repo_type, repo_id, variant)
+    paths = [path]
+    if legacy is not None and legacy != path and _legacy_state_applies(legacy, requested):
+        paths.append(legacy)
+    removed = False
+    for target in paths:
+        if target is None:
+            continue
+        try:
+            if target.is_file():
+                target.unlink()
+                removed = True
+        except OSError as exc:
+            logger.debug("Could not delete manifest %s: %s", target, exc)
+    return removed
 
 
 def purge_state(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> bool:
     """Remove manifest + cancel marker for this triple. Returns ``True``
-    when anything was present on disk before the call. Idempotent."""
-    marker_existed = has_cancel_marker(repo_type, repo_id, variant)
-    manifest_removed = delete_manifest(repo_type, repo_id, variant)
-    clear_cancel_marker(repo_type, repo_id, variant)
-    return marker_existed or manifest_removed
+    when anything was present on disk before the call. Idempotent.
+
+    With ``hub_cache`` set, only that cache's scoped state (plus any legacy
+    unscoped file that belongs to it) is removed, so purging one cache's copy
+    never clears another cache's resumable/cancel state."""
+    if hub_cache is None:
+        paths = (
+            *_all_matching_state_paths(manifests_dir(), repo_type, repo_id, variant),
+            *_all_matching_state_paths(cancelled_dir(), repo_type, repo_id, variant),
+        )
+    else:
+        requested = _canonical_hub_cache(hub_cache)
+        candidates = [
+            manifest_path(repo_type, repo_id, variant, hub_cache = hub_cache),
+            marker_path(repo_type, repo_id, variant, hub_cache = hub_cache),
+        ]
+        # Legacy unscoped state is shared: an unowned file belongs to the active
+        # cache (per _legacy_state_applies), so only purge it when it belongs to
+        # the cache being deleted -- else deleting an inactive cache would erase
+        # the active cache's resume/cancel state.
+        for path_factory in (manifest_path, marker_path):
+            legacy = path_factory(repo_type, repo_id, variant)
+            if legacy is not None and _legacy_state_applies(legacy, requested):
+                candidates.append(legacy)
+        paths = tuple(p for p in candidates if p is not None)
+    removed = False
+    for path in paths:
+        try:
+            if path.is_file():
+                path.unlink()
+                removed = True
+        except OSError as exc:
+            logger.debug("Could not purge Hub state %s: %s", path, exc)
+    return removed
 
 
-def purge_all_state_for_repo(repo_type: RepoType, repo_id: str) -> int:
+def purge_all_state_for_repo(
+    repo_type: RepoType,
+    repo_id: str,
+    *,
+    hub_cache: Optional[str | Path] = None,
+) -> int:
     """Remove the snapshot-level manifest + marker AND every variant-keyed
     manifest + marker for this repo. Used by the route delete handlers so
     scanner state never outlives the cache it described. Returns the count
-    of (repo, variant) triples that had any state on disk."""
+    of (repo, variant) triples that had any state on disk.
+
+    With ``hub_cache`` set, only that cache's scoped state (plus any legacy
+    unscoped file) is enumerated and removed, so deleting one cache's copy does
+    not clear another cache's resumable/cancel state."""
     removed = 0
-    if purge_state(repo_type, repo_id, None):
+    if purge_state(repo_type, repo_id, None, hub_cache = hub_cache):
         removed += 1
     variants: set[str] = set()
-    for variant, _ in iter_variant_manifests(repo_type, repo_id):
-        variants.add(variant)
-    for variant, _ in iter_variant_markers(repo_type, repo_id):
-        variants.add(variant)
+    prefix = variant_filename_prefix(repo_type, repo_id)
+    if hub_cache is None:
+        search = [(p, True) for p in (manifests_dir(), cancelled_dir()) if p is not None]
+    else:
+        # This cache's scoped dir (parent of its scoped path) plus the legacy
+        # unscoped base; glob (not rglob) so other caches' dirs are not swept.
+        search = []
+        for scoped, base in (
+            (manifest_path(repo_type, repo_id, None, hub_cache = hub_cache), manifests_dir()),
+            (marker_path(repo_type, repo_id, None, hub_cache = hub_cache), cancelled_dir()),
+        ):
+            if scoped is not None:
+                search.append((scoped.parent, False))
+            if base is not None:
+                search.append((base, False))
+    for parent, recursive in search:
+        try:
+            entries = tuple(
+                parent.rglob(f"{prefix}*.json") if recursive else parent.glob(f"{prefix}*.json")
+            )
+        except OSError:
+            continue
+        for entry in entries:
+            if not entry.is_file():
+                continue
+            fallback = entry.stem[len(prefix) :]
+            variants.add(_variant_from_state_file(entry, fallback))
     for variant in variants:
-        if purge_state(repo_type, repo_id, variant):
+        if purge_state(repo_type, repo_id, variant, hub_cache = hub_cache):
             removed += 1
     return removed
 
@@ -453,35 +666,83 @@ def _variant_from_state_file(path: Path, fallback: str) -> str:
 
 
 def _iter_variant_state_files(
-    parent: Optional[Path], repo_type: RepoType, repo_id: str
+    parent: Optional[Path],
+    repo_type: RepoType,
+    repo_id: str,
+    hub_cache: Optional[str | Path],
+    *,
+    cancel_markers: bool,
 ) -> Iterator[tuple[str, Path]]:
     if parent is None:
         return
-    prefix = variant_filename_prefix(repo_type, repo_id)
-    try:
-        entries = list(parent.iterdir())
-    except OSError:
+    path_factory = marker_path if cancel_markers else manifest_path
+    requested = _canonical_hub_cache(hub_cache)
+    scoped_probe = path_factory(
+        repo_type,
+        repo_id,
+        None,
+        hub_cache = requested,
+    )
+    if scoped_probe is None:
         return
-    for entry in entries:
-        if not entry.is_file() or not entry.name.endswith(".json"):
+    prefix = variant_filename_prefix(repo_type, repo_id)
+    seen: set[str] = set()
+    for directory, legacy in ((scoped_probe.parent, False), (parent, True)):
+        if legacy and directory == scoped_probe.parent:
             continue
-        stem = entry.name[: -len(".json")]
-        if not stem.lower().startswith(prefix):
+        try:
+            entries = list(directory.iterdir())
+        except OSError:
             continue
-        variant = stem[len(prefix) :]
-        if variant:
-            yield _variant_from_state_file(entry, variant), entry
+        for entry in entries:
+            if not entry.is_file() or not entry.name.endswith(".json"):
+                continue
+            stem = entry.name[: -len(".json")]
+            if not stem.lower().startswith(prefix) or entry.name in seen:
+                continue
+            if legacy and not _legacy_state_applies(
+                entry,
+                requested,
+                fail_closed = cancel_markers,
+            ):
+                continue
+            fallback = stem[len(prefix) :]
+            if fallback:
+                seen.add(entry.name)
+                yield _variant_from_state_file(entry, fallback), entry
 
 
-def iter_variant_manifests(repo_type: RepoType, repo_id: str) -> Iterator[tuple[str, Path]]:
+def iter_variant_manifests(
+    repo_type: RepoType,
+    repo_id: str,
+    *,
+    hub_cache: Optional[str | Path] = None,
+) -> Iterator[tuple[str, Path]]:
     """Yield (variant, manifest_path) for every variant-keyed manifest
     written for this repo. Used by is_gguf_repo_partial to enumerate all
     variants present on disk so the all-variants-broken gate can run."""
-    yield from _iter_variant_state_files(manifests_dir(), repo_type, repo_id)
+    yield from _iter_variant_state_files(
+        manifests_dir(),
+        repo_type,
+        repo_id,
+        hub_cache,
+        cancel_markers = False,
+    )
 
 
-def iter_variant_markers(repo_type: RepoType, repo_id: str) -> Iterator[tuple[str, Path]]:
+def iter_variant_markers(
+    repo_type: RepoType,
+    repo_id: str,
+    *,
+    hub_cache: Optional[str | Path] = None,
+) -> Iterator[tuple[str, Path]]:
     """Yield (variant, marker_path) for every variant-keyed cancel marker.
     Companion to iter_variant_manifests: catches variants cancelled
     before download-start ever wrote a manifest (very early failures)."""
-    yield from _iter_variant_state_files(cancelled_dir(), repo_type, repo_id)
+    yield from _iter_variant_state_files(
+        cancelled_dir(),
+        repo_type,
+        repo_id,
+        hub_cache,
+        cancel_markers = True,
+    )
diff --git a/studio/backend/hub/utils/download_registry.py b/studio/backend/hub/utils/download_registry.py
index b6bdee3bce..9e2b7d1a6d 100644
--- a/studio/backend/hub/utils/download_registry.py
+++ b/studio/backend/hub/utils/download_registry.py
@@ -129,6 +129,8 @@ def write_worker_breadcrumb(key: str, pid: int, metadata: Optional["DownloadMeta
         "cancel_marker_transport": metadata.cancel_marker_transport
         if metadata is not None
         else None,
+        "hub_cache": metadata.hub_cache if metadata is not None else None,
+        "xet_cache": metadata.xet_cache if metadata is not None else None,
     }
     tmp = path.with_name(f".{path.name}.tmp-{pid}")
     try:
@@ -236,6 +238,7 @@ def _settle_orphaned_download(
     repo_id: Optional[str],
     variant: Optional[str],
     transport: Optional[str],
+    hub_cache: Optional[str] = None,
 ) -> None:
     """Persist a cancel marker for a reaped orphan still mid-download so the next
     launch settles it to a resumable "cancelled" state instead of a phantom-running
@@ -251,18 +254,42 @@ def _settle_orphaned_download(
         return
     from hub.utils import download_manifest
 
-    manifest = download_manifest.read_manifest(repo_type, repo_id, variant)
+    cache_root = Path(hub_cache) if isinstance(hub_cache, str) and hub_cache else None
+
+    manifest = download_manifest.read_manifest(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = cache_root,
+    )
     if repo_type == "model" and variant and manifest is None:
         return
     if manifest is None:
-        if not has_active_incomplete_blobs(repo_type, repo_id):
+        if not has_active_incomplete_blobs(repo_type, repo_id, root = cache_root):
             return
     else:
-        if _manifest_verifies_against_active_cache(repo_type, repo_id, manifest):
+        if _manifest_verifies_against_active_cache(
+            repo_type,
+            repo_id,
+            manifest,
+            root = cache_root,
+        ):
             return
-        if not _manifest_has_active_incomplete_blobs(repo_type, repo_id, manifest):
+        if not _manifest_has_active_incomplete_blobs(
+            repo_type,
+            repo_id,
+            manifest,
+            root = cache_root,
+        ):
             return
-    persist_cancel_marker(repo_type, repo_id, variant, transport, logger = logger)
+    persist_cancel_marker(
+        repo_type,
+        repo_id,
+        variant,
+        transport,
+        hub_cache = hub_cache,
+        logger = logger,
+    )
 
 
 def reap_orphan_workers() -> None:
@@ -309,6 +336,7 @@ def reap_orphan_workers() -> None:
                 repo_id,
                 data.get("variant"),
                 data.get("cancel_marker_transport") or data.get("transport"),
+                data.get("hub_cache"),
             )
         except Exception as exc:
             logger.debug("Reaper failed for breadcrumb %s: %s", entry, exc)
@@ -355,8 +383,13 @@ def _purge_incomplete_blobs(
     return removed
 
 
-def _iter_active_snapshot_dirs(repo_type: str, repo_id: str) -> Iterator[Path]:
-    for entry in iter_active_repo_cache_dirs(repo_type, repo_id):
+def _iter_active_snapshot_dirs(
+    repo_type: str,
+    repo_id: str,
+    *,
+    root: Optional[Path] = None,
+) -> Iterator[Path]:
+    for entry in iter_active_repo_cache_dirs(repo_type, repo_id, root = root):
         snapshots_dir = entry / "snapshots"
         if not snapshots_dir.is_dir():
             continue
@@ -369,24 +402,41 @@ def _iter_active_snapshot_dirs(repo_type: str, repo_id: str) -> Iterator[Path]:
                 yield snapshot
 
 
-def _manifest_verifies_against_active_cache(repo_type: str, repo_id: str, manifest) -> bool:
+def _manifest_verifies_against_active_cache(
+    repo_type: str,
+    repo_id: str,
+    manifest,
+    *,
+    root: Optional[Path] = None,
+) -> bool:
     from hub.utils import download_manifest
-    for snapshot_dir in _iter_active_snapshot_dirs(repo_type, repo_id):
+    for snapshot_dir in _iter_active_snapshot_dirs(repo_type, repo_id, root = root):
         if download_manifest.verify_against_disk(manifest, snapshot_dir).ok:
             return True
     return False
 
 
-def _manifest_has_active_incomplete_blobs(repo_type: str, repo_id: str, manifest) -> bool:
+def _manifest_has_active_incomplete_blobs(
+    repo_type: str,
+    repo_id: str,
+    manifest,
+    *,
+    root: Optional[Path] = None,
+) -> bool:
     if not getattr(manifest, "variant", None):
-        return has_active_incomplete_blobs(repo_type, repo_id)
+        return has_active_incomplete_blobs(repo_type, repo_id, root = root)
     expected_hashes = frozenset(
         expected.sha256 for expected in manifest.expected_files if expected.sha256
     )
     if not expected_hashes:
-        return has_active_incomplete_blobs(repo_type, repo_id)
+        return has_active_incomplete_blobs(repo_type, repo_id, root = root)
     return bool(
-        incomplete_blob_hashes(repo_type, repo_id, active_only = True).intersection(expected_hashes)
+        incomplete_blob_hashes(
+            repo_type,
+            repo_id,
+            active_only = True,
+            root = root,
+        ).intersection(expected_hashes)
     )
 
 
@@ -459,6 +509,7 @@ def prepare_cache_for_transport(
     only_blob_hashes: Optional[frozenset[str]] = None,
     companion_blob_hashes: Optional[frozenset[str]] = None,
     protected_blob_hashes: Optional[frozenset[str]] = None,
+    root: Optional[Path] = None,
 ) -> int:
     """Guarantee any pre-existing ``.incomplete`` blobs are SAFE to resume under
     *mode*. Returns the number of partial blobs purged for untrusted provenance.
@@ -485,14 +536,13 @@ def prepare_cache_for_transport(
     they are excluded from every purge so a shared companion is never deleted
     mid-write.
 
-    Scope: only the active ``HF_HUB_CACHE`` root is inspected. That suffices for
-    resume safety because ``snapshot_download`` runs without a ``cache_dir``
-    override and so can only read or resume a ``.incomplete`` under this same
-    active root. Markers are written for the new mode before returning.
+    Scope: ``root`` selects the cache captured by the caller. It defaults to the
+    active ``HF_HUB_CACHE`` root for workers that inherit their cache through
+    the environment. Markers are written for the new mode before returning.
     """
     if mode not in VALID_TRANSPORTS:
         raise ValueError(f"Invalid transport mode: {mode!r}")
-    root = hf_cache_root(create = True)
+    root = hf_cache_root(create = True) if root is None else hf_cache_root(create = True, root = root)
     if root is None:
         return 0
     target = target_dir_name(repo_type, repo_id)
@@ -618,10 +668,11 @@ def incomplete_blob_hashes(
     repo_id: str,
     *,
     active_only: bool = False,
+    root: Optional[Path] = None,
 ) -> set[str]:
     out: set[str] = set()
     entries = (
-        iter_active_repo_cache_dirs(repo_type, repo_id)
+        iter_active_repo_cache_dirs(repo_type, repo_id, root = root)
         if active_only
         else iter_repo_cache_dirs(repo_type, repo_id)
     )
@@ -638,16 +689,24 @@ def incomplete_blob_hashes(
     return out
 
 
-def completed_blob_bytes(repo_type: str, repo_id: str, blob_hashes: frozenset[str]) -> int:
-    """Sum finalized blob bytes for *blob_hashes* in the active HF cache root.
+def completed_blob_bytes(
+    repo_type: str,
+    repo_id: str,
+    blob_hashes: frozenset[str],
+    *,
+    root: Optional[Path] = None,
+) -> int:
+    """Sum finalized blob bytes for *blob_hashes* in a single HF cache root.
 
-    A worker only writes to the active ``HF_HUB_CACHE`` root, so a baseline must
-    ignore legacy/default roots that ``snapshot_download`` won't reuse this run.
+    A worker only writes to its captured ``HF_HUB_CACHE`` root, so a baseline
+    must be scoped to that root (``root``), not re-resolved to whatever cache is
+    active now; otherwise a runtime cache switch makes the retry baseline count
+    bytes from the wrong disk.
     """
     if not blob_hashes:
         return 0
     total = 0
-    for entry in iter_active_repo_cache_dirs(repo_type, repo_id):
+    for entry in iter_active_repo_cache_dirs(repo_type, repo_id, root = root):
         blobs_dir = entry / "blobs"
         if not blobs_dir.is_dir():
             continue
@@ -712,6 +771,8 @@ class DownloadMetadata:
     # Bytes already complete before this job started; not counted as this run's
     # progress.
     completed_baseline_bytes: int = 0
+    hub_cache: Optional[str] = None
+    xet_cache: Optional[str] = None
 
 
 @dataclass(frozen = True)
@@ -752,6 +813,7 @@ def persist_cancel_marker(
     variant: Optional[str],
     transport: Optional[str],
     *,
+    hub_cache: Optional[str] = None,
     logger = logger,
 ) -> None:
     if not repo_type or not repo_id:
@@ -763,6 +825,7 @@ def persist_cancel_marker(
             repo_id,
             variant,
             transport = transport,
+            hub_cache = hub_cache,
         ):
             logger.debug("write_cancel_marker returned False for %s", repo_id)
     except Exception as exc:
@@ -971,6 +1034,7 @@ class DownloadRegistry:
                 metadata_to_persist.repo_id,
                 metadata_to_persist.variant,
                 metadata_to_persist.transport,
+                hub_cache = metadata_to_persist.hub_cache,
             )
         return False
 
@@ -1033,6 +1097,8 @@ class DownloadRegistry:
         replace_active: bool = False,
         metadata_transport: Optional[str] = None,
         cancel_marker_transport: Optional[str] = None,
+        hub_cache: Optional[str] = None,
+        xet_cache: Optional[str] = None,
     ) -> tuple[bool, str]:
         key = normalize_job_key(key)
         repo = _repo_of_key(key)
@@ -1106,6 +1172,8 @@ class DownloadRegistry:
                         0,
                         int(completed_baseline_bytes or 0),
                     ),
+                    hub_cache = hub_cache,
+                    xet_cache = xet_cache,
                 )
                 if cancel_marker_transport is not None:
                     self._cancel_marker_transports[key] = cancel_marker_transport
@@ -1386,6 +1454,7 @@ class DownloadRegistry:
                     metadata.repo_id,
                     metadata.variant,
                     metadata.cancel_marker_transport or metadata.transport,
+                    hub_cache = metadata.hub_cache,
                 )
         reaped: list[tuple[str, subprocess.Popen, Optional[DownloadMetadata]]] = []
         for key, proc, metadata in live:
@@ -1401,6 +1470,7 @@ class DownloadRegistry:
                         metadata.repo_id,
                         metadata.variant,
                         metadata.cancel_marker_transport or metadata.transport,
+                        hub_cache = metadata.hub_cache,
                     )
                 continue
             reaped.append((key, proc, metadata))
@@ -1421,6 +1491,7 @@ class DownloadRegistry:
                     metadata.repo_id,
                     metadata.variant,
                     metadata.cancel_marker_transport or metadata.transport,
+                    hub_cache = metadata.hub_cache,
                 )
 
 
diff --git a/studio/backend/hub/utils/gguf.py b/studio/backend/hub/utils/gguf.py
index 2e3de125f1..eb768db5d6 100644
--- a/studio/backend/hub/utils/gguf.py
+++ b/studio/backend/hub/utils/gguf.py
@@ -253,11 +253,16 @@ def _env_offline() -> bool:
     ) or os.environ.get("TRANSFORMERS_OFFLINE", "").lower() in ("1", "true", "yes")
 
 
-def iter_hf_cache_snapshots(repo_id: str):
-    from hub.utils.hf_cache_state import iter_repo_cache_dirs
+def iter_hf_cache_snapshots(repo_id: str, root: Optional[Path] = None):
+    from hub.utils.hf_cache_state import iter_active_repo_cache_dirs, iter_repo_cache_dirs
 
     snapshots: list[Path] = []
-    for repo_dir in iter_repo_cache_dirs("model", repo_id):
+    repo_dirs = (
+        iter_active_repo_cache_dirs("model", repo_id, root = root)
+        if root is not None
+        else iter_repo_cache_dirs("model", repo_id)
+    )
+    for repo_dir in repo_dirs:
         snapshots_dir = repo_dir / "snapshots"
         if not snapshots_dir.is_dir():
             continue
@@ -276,12 +281,17 @@ def iter_hf_cache_snapshots(repo_id: str):
     yield from snapshots
 
 
-def list_empty_gguf_variant_dirs(repo_id: str) -> set[str]:
+def list_empty_gguf_variant_dirs(repo_id: str, root: Optional[Path] = None) -> set[str]:
     """Quant labels present only as an EMPTY snapshot ``<quant>/`` folder (an
     interrupted split download); a quant with shards in any snapshot is excluded."""
     empty: dict[str, str] = {}
     nonempty: set[str] = set()
-    for snapshot in iter_hf_cache_snapshots(repo_id):
+    snapshots = (
+        iter_hf_cache_snapshots(repo_id, root = root)
+        if root is not None
+        else iter_hf_cache_snapshots(repo_id)
+    )
+    for snapshot in snapshots:
         try:
             entries = list(snapshot.iterdir())
         except OSError:
@@ -303,8 +313,15 @@ def list_empty_gguf_variant_dirs(repo_id: str) -> set[str]:
     return {label for key, label in empty.items() if key not in nonempty}
 
 
-def list_gguf_variants_from_hf_cache(repo_id: str) -> Optional[tuple[list[GgufVariantInfo], bool]]:
-    for snapshot in iter_hf_cache_snapshots(repo_id):
+def list_gguf_variants_from_hf_cache(
+    repo_id: str, root: Optional[Path] = None
+) -> Optional[tuple[list[GgufVariantInfo], bool]]:
+    snapshots = (
+        iter_hf_cache_snapshots(repo_id, root = root)
+        if root is not None
+        else iter_hf_cache_snapshots(repo_id)
+    )
+    for snapshot in snapshots:
         variants, has_vision = list_local_gguf_variants(str(snapshot))
         if variants or has_vision:
             return variants, has_vision
@@ -312,7 +329,7 @@ def list_gguf_variants_from_hf_cache(repo_id: str) -> Optional[tuple[list[GgufVa
 
 
 def list_partial_gguf_variants_from_state(
-    repo_id: str,
+    repo_id: str, hub_cache: Optional[Path] = None
 ) -> Optional[tuple[list[GgufVariantInfo], bool]]:
     """Reconstruct GGUF variants from download manifests/markers alone.
 
@@ -328,10 +345,26 @@ def list_partial_gguf_variants_from_state(
     # original-casing label over a lowercased cancel marker for the same variant.
     seen: set[str] = set()
     ordered: list[str] = []
-    for source in (
-        download_manifest.iter_variant_manifests("model", repo_id),
-        download_manifest.iter_variant_markers("model", repo_id),
-    ):
+    sources = (
+        (
+            download_manifest.iter_variant_manifests("model", repo_id),
+            download_manifest.iter_variant_markers("model", repo_id),
+        )
+        if hub_cache is None
+        else (
+            download_manifest.iter_variant_manifests(
+                "model",
+                repo_id,
+                hub_cache = hub_cache,
+            ),
+            download_manifest.iter_variant_markers(
+                "model",
+                repo_id,
+                hub_cache = hub_cache,
+            ),
+        )
+    )
+    for source in sources:
         for variant, _path in source:
             key = variant.lower()
             if key not in seen:
@@ -343,7 +376,16 @@ def list_partial_gguf_variants_from_state(
     variants: list[GgufVariantInfo] = []
     has_vision = False
     for variant in ordered:
-        manifest = download_manifest.read_manifest("model", repo_id, variant)
+        manifest = (
+            download_manifest.read_manifest("model", repo_id, variant)
+            if hub_cache is None
+            else download_manifest.read_manifest(
+                "model",
+                repo_id,
+                variant,
+                hub_cache = hub_cache,
+            )
+        )
         main_filename: Optional[str] = None
         size_bytes = 0
         companion_bytes = 0
diff --git a/studio/backend/hub/utils/hf_cache_state.py b/studio/backend/hub/utils/hf_cache_state.py
index 22c948b683..49a28c813c 100644
--- a/studio/backend/hub/utils/hf_cache_state.py
+++ b/studio/backend/hub/utils/hf_cache_state.py
@@ -29,12 +29,10 @@ def _safe_is_dir(path: Path) -> bool:
         return False
 
 
-def hf_cache_root(*, create: bool = False) -> Optional[Path]:
-    try:
-        from huggingface_hub import constants as hf_constants
-    except ImportError:
-        return None
-    root = Path(hf_constants.HF_HUB_CACHE)
+def hf_cache_root(*, create: bool = False, root: Optional[Path] = None) -> Optional[Path]:
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    root = root or get_hf_cache_paths().hub_cache
     if create:
         try:
             root.mkdir(parents = True, exist_ok = True)
@@ -46,6 +44,7 @@ def hf_cache_root(*, create: bool = False) -> Optional[Path]:
 
 def hf_cache_roots() -> list[Path]:
     from hub.utils.paths import hf_default_cache_dir, legacy_hf_cache_dir
+    from utils.hf_cache_settings import known_hf_hub_caches
 
     roots: list[Path] = []
     seen: set[str] = set()
@@ -62,7 +61,8 @@ def hf_cache_roots() -> list[Path]:
         seen.add(key)
         roots.append(path)
 
-    _add(hf_cache_root())
+    for configured in known_hf_hub_caches():
+        _add(configured)
     _add(legacy_hf_cache_dir())
     _add(hf_default_cache_dir())
     return roots
@@ -181,12 +181,22 @@ def iter_repo_cache_dirs(repo_type: str, repo_id: str) -> Iterator[Path]:
             continue
 
 
-def iter_destructive_repo_cache_dirs(repo_type: str, repo_id: str) -> Iterator[Path]:
+def iter_destructive_repo_cache_dirs(
+    repo_type: str,
+    repo_id: str,
+    *,
+    root: Optional[Path] = None,
+) -> Iterator[Path]:
     target = repo_cache_dir_name(repo_type, repo_id)
     folded_target = target.lower()
-    for root in hf_cache_roots():
+    if root is not None:
+        scoped = hf_cache_root(root = root)
+        bases = [scoped] if scoped is not None else []
+    else:
+        bases = hf_cache_roots()
+    for base in bases:
         try:
-            entries = [entry for entry in root.iterdir() if entry.name.lower() == folded_target]
+            entries = [entry for entry in base.iterdir() if entry.name.lower() == folded_target]
         except OSError:
             continue
         matched_names = resolve_destructive_case_matches(
@@ -200,8 +210,13 @@ def iter_destructive_repo_cache_dirs(repo_type: str, repo_id: str) -> Iterator[P
                 yield entry
 
 
-def iter_active_repo_cache_dirs(repo_type: str, repo_id: str) -> Iterator[Path]:
-    root = hf_cache_root()
+def iter_active_repo_cache_dirs(
+    repo_type: str,
+    repo_id: str,
+    *,
+    root: Optional[Path] = None,
+) -> Iterator[Path]:
+    root = hf_cache_root(root = root)
     if root is None:
         return
     target = target_dir_name(repo_type, repo_id)
@@ -218,12 +233,13 @@ def preferred_repo_cache_dirs(
     repo_id: str,
     *,
     force_active: bool = False,
+    active_root: Optional[Path] = None,
 ) -> list[Path]:
-    active_entries = list(iter_active_repo_cache_dirs(repo_type, repo_id))
+    active_entries = list(iter_active_repo_cache_dirs(repo_type, repo_id, root = active_root))
     if active_entries:
         return active_entries
     if force_active:
-        root = hf_cache_root()
+        root = hf_cache_root(root = active_root)
         if root is not None:
             canonical = repo_cache_dir_name(repo_type, repo_id)
             return [root / canonical]
@@ -237,8 +253,13 @@ def has_incomplete_blobs(repo_type: str, repo_id: str) -> bool:
     return False
 
 
-def has_active_incomplete_blobs(repo_type: str, repo_id: str) -> bool:
-    for entry in iter_active_repo_cache_dirs(repo_type, repo_id):
+def has_active_incomplete_blobs(
+    repo_type: str,
+    repo_id: str,
+    *,
+    root: Optional[Path] = None,
+) -> bool:
+    for entry in iter_active_repo_cache_dirs(repo_type, repo_id, root = root):
         if repo_cache_dir_has_incomplete_blobs(entry):
             return True
     return False
@@ -273,9 +294,14 @@ def _prune_empty_dirs(root: Path) -> bool:
     return removed
 
 
-def purge_partial_repo(repo_type: str, repo_id: str) -> bool:
+def purge_partial_repo(
+    repo_type: str,
+    repo_id: str,
+    *,
+    root: Optional[Path] = None,
+) -> bool:
     removed = False
-    for entry in iter_destructive_repo_cache_dirs(repo_type, repo_id):
+    for entry in iter_destructive_repo_cache_dirs(repo_type, repo_id, root = root):
         blobs_dir = entry / "blobs"
         if blobs_dir.is_dir():
             for blob in blobs_dir.iterdir():
@@ -290,9 +316,14 @@ def purge_partial_repo(repo_type: str, repo_id: str) -> bool:
     return removed
 
 
-def purge_repo_cache_dirs(repo_type: str, repo_id: str) -> bool:
+def purge_repo_cache_dirs(
+    repo_type: str,
+    repo_id: str,
+    *,
+    root: Optional[Path] = None,
+) -> bool:
     removed = False
-    for entry in iter_destructive_repo_cache_dirs(repo_type, repo_id):
+    for entry in iter_destructive_repo_cache_dirs(repo_type, repo_id, root = root):
         try:
             if entry.is_symlink() or not entry.is_dir():
                 continue
@@ -301,3 +332,59 @@ def purge_repo_cache_dirs(repo_type: str, repo_id: str) -> bool:
         except FileNotFoundError:
             continue
     return removed
+
+
+def scoped_delete_root(repo_type: str, repo_id: str, cache_path: Optional[str]) -> Optional[Path]:
+    """Resolve the single cache root a delete of this repo may touch.
+
+    Returns the active hub cache when *cache_path* is falsy, the owning cache
+    root when *cache_path* points inside a known cache, or ``None`` when
+    *cache_path* is set but not inside any known cache (caller should reject).
+    This keeps a delete of one inventory row from removing copies in other,
+    previously selected caches.
+    """
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    if not cache_path:
+        return Path(get_hf_cache_paths().hub_cache).resolve(strict = False)
+    try:
+        resolved = Path(cache_path).expanduser().resolve(strict = False)
+    except (OSError, RuntimeError, ValueError):
+        return None
+    expected = repo_cache_dir_name(repo_type, repo_id).lower()
+    repo_dir = next(
+        (
+            candidate
+            for candidate in (resolved, *resolved.parents)
+            if candidate.name.lower() == expected
+        ),
+        None,
+    )
+    if repo_dir is None:
+        return None
+    allowed = {r.resolve(strict = False) for r in hf_cache_roots()}
+    root = repo_dir.parent.resolve(strict = False)
+    return root if root in allowed else None
+
+
+def resolve_delete_target_root(
+    repo_type: str, repo_id: str, cache_path: Optional[str], owner_roots
+) -> Optional[Path]:
+    """Pick the single cache root a delete of this repo should target.
+
+    An explicit *cache_path* wins (``None`` when it is not a known cache, so the
+    caller can reject it). Otherwise prefer the active cache when it holds a
+    copy, else the sole cache that does -- so a model that lives only in a
+    previously selected cache stays deletable while other caches are untouched.
+    """
+    if cache_path:
+        return scoped_delete_root(repo_type, repo_id, cache_path)
+    from utils.hf_cache_settings import get_hf_cache_paths
+
+    active = Path(get_hf_cache_paths().hub_cache).resolve(strict = False)
+    roots = list(owner_roots)
+    if active in roots:
+        return active
+    if len(roots) == 1:
+        return roots[0]
+    return active
diff --git a/studio/backend/hub/utils/inventory_scan.py b/studio/backend/hub/utils/inventory_scan.py
index 57ad7f6655..058fdf9b65 100644
--- a/studio/backend/hub/utils/inventory_scan.py
+++ b/studio/backend/hub/utils/inventory_scan.py
@@ -36,7 +36,7 @@ from hub.utils.state_dir import RepoType
 from hub.utils.hf_cache_state import (
     INCOMPLETE_SUFFIX,
     has_incomplete_blobs,
-    hf_cache_root,
+    hf_cache_roots,
     iter_repo_cache_dirs,
     latest_snapshot_dir,
     repo_cache_dir_has_incomplete_blobs,
@@ -127,33 +127,13 @@ def all_hf_cache_scans() -> list:
 
 def _compute_all_hf_cache_scans() -> list:
     from huggingface_hub import scan_cache_dir
-    from hub.utils.paths import legacy_hf_cache_dir, hf_default_cache_dir
 
     scans: list = []
-    seen: set[str] = set()
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-
-        active = Path(HF_HUB_CACHE).resolve()
-        seen.add(str(active))
-        if active.is_dir():
-            scans.append(scan_cache_dir())
-    except Exception as exc:
-        logger.warning("Could not scan active HF cache: %s", exc)
-
-    for extra_fn in (legacy_hf_cache_dir, hf_default_cache_dir):
+    for cache_root in hf_cache_roots():
         try:
-            extra = extra_fn()
-            # is_dir()/resolve() can raise on an inaccessible path; skip it.
-            if not extra.is_dir():
-                continue
-            resolved = str(extra.resolve())
-            if resolved in seen:
-                continue
-            seen.add(resolved)
-            scans.append(scan_cache_dir(cache_dir = str(extra)))
+            scans.append(scan_cache_dir(cache_dir = str(cache_root)))
         except Exception as exc:
-            logger.warning("Could not scan HF cache %s: %s", extra_fn.__name__, exc)
+            logger.warning("Could not scan HF cache %s: %s", cache_root, exc)
     return scans
 
 
@@ -224,16 +204,8 @@ def _compose_partial(*signals: Callable[[], bool]) -> bool:
     return any(signal() for signal in signals)
 
 
-def _state_applies_to_repo_cache_dir(repo_cache_dir: Optional[Path]) -> bool:
-    if repo_cache_dir is None:
-        return True
-    root = hf_cache_root()
-    if root is None:
-        return False
-    try:
-        return repo_cache_dir.resolve().parent == root.resolve()
-    except OSError:
-        return False
+def _hub_cache_for_repo_dir(repo_cache_dir: Optional[Path]) -> Optional[Path]:
+    return repo_cache_dir.parent if repo_cache_dir is not None else None
 
 
 def _legacy_partial(
@@ -285,12 +257,24 @@ def _repo_cache_dir_has_non_gguf_broken_snapshot_symlinks(repo_cache_dir: Path)
     return False
 
 
-def _gguf_variant_manifest_blob_hashes(repo_id: str) -> frozenset[str]:
+def _gguf_variant_manifest_blob_hashes(
+    repo_id: str, repo_cache_dir: Optional[Path] = None
+) -> frozenset[str]:
     from hub.utils import download_manifest
 
     hashes: set[str] = set()
-    for variant, _path in download_manifest.iter_variant_manifests("model", repo_id):
-        manifest = download_manifest.read_manifest("model", repo_id, variant)
+    hub_cache = _hub_cache_for_repo_dir(repo_cache_dir)
+    for variant, _path in download_manifest.iter_variant_manifests(
+        "model",
+        repo_id,
+        hub_cache = hub_cache,
+    ):
+        manifest = download_manifest.read_manifest(
+            "model",
+            repo_id,
+            variant,
+            hub_cache = hub_cache,
+        )
         if manifest is None:
             continue
         for expected in manifest.expected_files:
@@ -315,7 +299,7 @@ def _snapshot_legacy_partial(
 ) -> bool:
     if repo_type != "model":
         return _legacy_partial(repo_type, repo_id, repo_cache_dir)
-    ignored_hashes = _gguf_variant_manifest_blob_hashes(repo_id)
+    ignored_hashes = _gguf_variant_manifest_blob_hashes(repo_id, repo_cache_dir)
     if repo_cache_dir is not None:
         return _repo_cache_dir_has_snapshot_legacy_partial(
             repo_cache_dir,
@@ -375,9 +359,12 @@ def _manifest_partial(
 ) -> bool:
     from hub.utils import download_manifest
 
-    if not _state_applies_to_repo_cache_dir(repo_cache_dir):
-        return False
-    manifest = download_manifest.read_manifest(repo_type, repo_id, variant)
+    manifest = download_manifest.read_manifest(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = _hub_cache_for_repo_dir(repo_cache_dir),
+    )
     if manifest is None:
         return False
     resolved = (
@@ -452,10 +439,13 @@ def is_snapshot_partial(
     A manifest without a resolvable snapshot is partial: the worker got
     far enough to record expectations but did not leave a usable snapshot."""
     from hub.utils import download_manifest
-
-    state_applies = _state_applies_to_repo_cache_dir(repo_cache_dir)
     return _compose_partial(
-        lambda: state_applies and download_manifest.has_cancel_marker(repo_type, repo_id, None),
+        lambda: download_manifest.has_cancel_marker(
+            repo_type,
+            repo_id,
+            None,
+            hub_cache = _hub_cache_for_repo_dir(repo_cache_dir),
+        ),
         lambda: _snapshot_legacy_partial(repo_type, repo_id, repo_cache_dir),
         lambda: _manifest_partial(
             repo_type,
@@ -484,10 +474,13 @@ def is_variant_partial(
     caller is checking many variants of the same repo (see
     is_gguf_repo_partial for that usage)."""
     from hub.utils import download_manifest
-
-    state_applies = _state_applies_to_repo_cache_dir(repo_cache_dir)
     return _compose_partial(
-        lambda: state_applies and download_manifest.has_cancel_marker("model", repo_id, variant),
+        lambda: download_manifest.has_cancel_marker(
+            "model",
+            repo_id,
+            variant,
+            hub_cache = _hub_cache_for_repo_dir(repo_cache_dir),
+        ),
         lambda: bool(
             incomplete_blob_hashes
             and variant_blob_hashes
@@ -526,22 +519,38 @@ def is_gguf_repo_partial(repo_id: str, repo_cache_dir: Optional[Path] = None) ->
     from hub.utils import download_manifest
 
     has_legacy_partial = _legacy_partial("model", repo_id, repo_cache_dir)
-    state_applies = _state_applies_to_repo_cache_dir(repo_cache_dir)
     snapshot_dir = resolve_snapshot_dir_for_scan(
         "model",
         repo_id,
         repo_cache_dir,
     )
     variants: set[str] = set(_completed_gguf_variants(snapshot_dir))
-    if state_applies:
-        for variant, _path in download_manifest.iter_variant_manifests(
-            "model",
-            repo_id,
+    hub_cache = _hub_cache_for_repo_dir(repo_cache_dir)
+    for variant, _path in download_manifest.iter_variant_manifests(
+        "model",
+        repo_id,
+        hub_cache = hub_cache,
+    ):
+        if (
+            download_manifest.read_manifest(
+                "model",
+                repo_id,
+                variant,
+                hub_cache = hub_cache,
+            )
+            is not None
         ):
             variants.add(variant)
-        for variant, _path in download_manifest.iter_variant_markers(
+    for variant, _path in download_manifest.iter_variant_markers(
+        "model",
+        repo_id,
+        hub_cache = hub_cache,
+    ):
+        if download_manifest.has_cancel_marker(
             "model",
             repo_id,
+            variant,
+            hub_cache = hub_cache,
         ):
             variants.add(variant)
     if not variants:
@@ -576,14 +585,19 @@ def partial_transport_for(
     available."""
     from hub.utils import download_manifest
 
-    if not _state_applies_to_repo_cache_dir(repo_cache_dir):
-        return None
+    hub_cache = _hub_cache_for_repo_dir(repo_cache_dir)
     marker_transport = download_manifest.read_cancel_marker_transport(
         repo_type,
         repo_id,
         variant,
+        hub_cache = hub_cache,
     )
     if marker_transport is not None:
         return marker_transport
-    manifest = download_manifest.read_manifest(repo_type, repo_id, variant)
+    manifest = download_manifest.read_manifest(
+        repo_type,
+        repo_id,
+        variant,
+        hub_cache = hub_cache,
+    )
     return manifest.transport if manifest is not None else None
diff --git a/studio/backend/hub/utils/paths.py b/studio/backend/hub/utils/paths.py
index 5435202565..81621edcf9 100644
--- a/studio/backend/hub/utils/paths.py
+++ b/studio/backend/hub/utils/paths.py
@@ -277,12 +277,8 @@ def _memo_drop(memo_key: tuple[str, str]) -> None:
 
 
 def _hf_hub_cache_dir() -> Path:
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-        return Path(HF_HUB_CACHE)
-    except Exception as exc:
-        logger.debug("Could not read huggingface_hub HF_HUB_CACHE, using default: %s", exc)
-        return Path.home() / ".cache" / "huggingface" / "hub"
+    from utils.hf_cache_settings import get_hf_cache_paths
+    return get_hf_cache_paths().hub_cache
 
 
 def _hf_hub_cache_dirs() -> list[Path]:
@@ -300,7 +296,10 @@ def _hf_hub_cache_dirs() -> list[Path]:
         seen.add(key)
         roots.append(resolved)
 
-    _add(_hf_hub_cache_dir())
+    from utils.hf_cache_settings import known_hf_hub_caches
+
+    for configured in known_hf_hub_caches():
+        _add(configured)
     try:
         _add(legacy_hf_cache_dir())
         _add(hf_default_cache_dir())
diff --git a/studio/backend/hub/utils/state_dir.py b/studio/backend/hub/utils/state_dir.py
index 898c03c87d..4650b97381 100644
--- a/studio/backend/hub/utils/state_dir.py
+++ b/studio/backend/hub/utils/state_dir.py
@@ -8,9 +8,10 @@ so it survives ``huggingface-cli delete-cache`` and any other HF-side
 cache lifecycle. Two subdirectories:
 
     <studio cache>/hub-state/
-        manifests/   <key>.json   per-download expected-files manifest
-        cancelled/   <key>.json   per-download cancel marker
+        manifests/cache-<digest>/<key>.json   expected-files manifest
+        cancelled/cache-<digest>/<key>.json   cancel marker
 
+The cache digest isolates state for the same repo across selectable Hub caches.
 The ``<key>`` mirrors HF's cache dir naming while the resulting manifest,
 cancel-marker, and atomic-write temp filenames fit common filesystem basename
 limits. Very long repo IDs use a stable hash in the state key:
@@ -29,6 +30,7 @@ configuration failure.
 from __future__ import annotations
 
 import hashlib
+import os
 import re
 from pathlib import Path
 from typing import Literal, Optional, get_args
@@ -55,6 +57,7 @@ _STATE_EXTENSION = ".json"
 # _atomic_write_json writes ".<target>.tmp-<8hex>" beside the final file.
 _ATOMIC_WRITE_TMP_OVERHEAD = len(".") + len(".tmp-") + 8
 _MAX_VARIANT_FRAGMENT_LENGTH = 64
+_CACHE_SCOPE_DIGEST_LENGTH = 32
 
 
 def state_root() -> Optional[Path]:
@@ -130,13 +133,32 @@ def _entry_key(repo_type: RepoType, repo_id: str, variant: Optional[str]) -> str
     return f"{variant_filename_prefix(repo_type, repo_id)}{variant_fragment}"
 
 
+def _cache_scope(parent: Path, hub_cache: Optional[str | Path]) -> Optional[Path]:
+    if hub_cache is None:
+        return parent
+    normalized = os.path.normcase(str(Path(hub_cache).expanduser()))
+    digest = hashlib.sha256(normalized.encode("utf-8")).hexdigest()[:_CACHE_SCOPE_DIGEST_LENGTH]
+    scoped = parent / f"cache-{digest}"
+    try:
+        scoped.mkdir(parents = True, exist_ok = True)
+    except OSError as exc:
+        logger.debug("Could not create cache-scoped Hub state dir %s: %s", scoped, exc)
+        return None
+    return scoped
+
+
 def manifest_path(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> Optional[Path]:
     """Path to the manifest file for this triple. May or may not exist."""
     parent = _subdir(_MANIFESTS_SUBDIR)
+    if parent is None:
+        return None
+    parent = _cache_scope(parent, hub_cache)
     if parent is None:
         return None
     return parent / f"{_entry_key(repo_type, repo_id, variant)}.json"
@@ -146,9 +168,14 @@ def marker_path(
     repo_type: RepoType,
     repo_id: str,
     variant: Optional[str] = None,
+    *,
+    hub_cache: Optional[str | Path] = None,
 ) -> Optional[Path]:
     """Path to the cancel-marker file for this triple. May or may not exist."""
     parent = _subdir(_CANCELLED_SUBDIR)
+    if parent is None:
+        return None
+    parent = _cache_scope(parent, hub_cache)
     if parent is None:
         return None
     return parent / f"{_entry_key(repo_type, repo_id, variant)}.json"
diff --git a/studio/backend/hub/workers/hf_download.py b/studio/backend/hub/workers/hf_download.py
index e45357d311..9ff394b009 100644
--- a/studio/backend/hub/workers/hf_download.py
+++ b/studio/backend/hub/workers/hf_download.py
@@ -661,6 +661,7 @@ def _download_gguf_variant(repo_id: str, variant: str, hf_token: str | None, mod
                 variant,
                 plan.main_hashes,
                 hf_token,
+                hub_cache = Path(snapshot_path).parents[2],
             )
         except Exception as e:
             print(
diff --git a/studio/backend/main.py b/studio/backend/main.py
index f686e29bf5..a538f935ff 100644
--- a/studio/backend/main.py
+++ b/studio/backend/main.py
@@ -289,6 +289,7 @@ from fastapi import Depends, FastAPI, HTTPException, Query, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
 from fastapi.responses import FileResponse, HTMLResponse, Response
+from starlette.middleware.gzip import GZipMiddleware
 from pathlib import Path
 from datetime import datetime
 
@@ -308,12 +309,14 @@ from routes import (
     training_router,
 )
 from routes.llama import router as llama_router
+from routes.whisper import router as whisper_router
 from routes.preview import router as preview_router
 from hub.routes import (
     inventory_router as hub_inventory_router,
     datasets_router as hub_datasets_router,
     token_router as hub_token_router,
 )
+from picker.routes import templates_router as picker_templates_router
 from hub.schemas.downloads import TransportCapabilities
 from hub.utils.download_registry import (
     get_download_transport_capabilities,
@@ -753,6 +756,8 @@ app.add_middleware(SecurityHeadersMiddleware)
 # headroom; non-upload routes keep the default body cap.
 import json as _json_for_413  # noqa: E402
 from utils.upload_limits import (  # noqa: E402
+    STT_AUDIO_JSON_MAX_BYTES,
+    STT_AUDIO_RAW_MAX_BYTES,
     UNSTRUCTURED_RECIPE_UPLOAD_MAX_BYTES,
     default_request_body_limit_bytes,
     upload_request_limit_bytes,
@@ -763,6 +768,7 @@ _BODY_PROTECTED_PREFIXES = (
     "/v1/completions",
     "/p/",
     "/api/inference",
+    "/api/picker",
     "/api/data-recipe",
     "/api/datasets",
     "/api/hub",
@@ -790,6 +796,14 @@ def _get_upload_passthrough_request_max_bytes(path: str) -> int:
     return default_request_body_limit_bytes()
 
 
+def _get_request_body_max_bytes(path: str) -> int:
+    if path.startswith("/api/inference/audio/transcribe/raw"):
+        return STT_AUDIO_RAW_MAX_BYTES
+    if path.startswith("/api/inference/audio/transcribe"):
+        return STT_AUDIO_JSON_MAX_BYTES
+    return default_request_body_limit_bytes()
+
+
 async def _send_411(send) -> None:
     payload = _json_for_413.dumps(
         {"detail": "Content-Length required for upload requests."},
@@ -832,12 +846,14 @@ class MaxBodyMiddleware:
         app,
         max_bytes_getter,
         protected_prefixes: tuple,
+        request_max_bytes_getter = None,
         upload_passthrough_prefixes: tuple = (),
         upload_passthrough_max_bytes_getter = None,
     ):
         self.app = app
         self.max_bytes_getter = max_bytes_getter
         self.protected_prefixes = protected_prefixes
+        self.request_max_bytes_getter = request_max_bytes_getter
         self.upload_passthrough_prefixes = upload_passthrough_prefixes
         self.upload_passthrough_max_bytes_getter = upload_passthrough_max_bytes_getter
 
@@ -854,6 +870,14 @@ class MaxBodyMiddleware:
         except Exception:
             return int(self.max_bytes_getter())
 
+    def _request_max_bytes(self, path: str) -> int:
+        if self.request_max_bytes_getter is None:
+            return int(self.max_bytes_getter())
+        try:
+            return int(self.request_max_bytes_getter(path))
+        except Exception:
+            return int(self.max_bytes_getter())
+
     async def __call__(self, scope, receive, send):
         if scope["type"] != "http":
             await self.app(scope, receive, send)
@@ -866,7 +890,7 @@ class MaxBodyMiddleware:
             await self.app(scope, receive, send)
             return
 
-        max_bytes = int(self.max_bytes_getter())
+        max_bytes = self._request_max_bytes(path)
         declared = None
         for name, value in scope.get("headers", []):
             if name == b"content-length":
@@ -931,6 +955,7 @@ app.add_middleware(
     MaxBodyMiddleware,
     max_bytes_getter = default_request_body_limit_bytes,
     protected_prefixes = _BODY_PROTECTED_PREFIXES,
+    request_max_bytes_getter = _get_request_body_max_bytes,
     upload_passthrough_prefixes = _BODY_UPLOAD_PASSTHROUGH_PREFIXES,
     upload_passthrough_max_bytes_getter = _get_upload_passthrough_request_max_bytes,
 )
@@ -989,11 +1014,13 @@ app.include_router(prompts_router, prefix = "/api/prompts", tags = ["prompts"])
 app.include_router(datasets_router, prefix = "/api/datasets", tags = ["datasets"])
 app.include_router(data_recipe_router, prefix = "/api/data-recipe", tags = ["data-recipe"])
 app.include_router(llama_router, prefix = "/api/llama", tags = ["llama"])
+app.include_router(whisper_router, prefix = "/api/whisper", tags = ["whisper"])
 app.include_router(export_router, prefix = "/api/export", tags = ["export"])
 app.include_router(rag_router, prefix = "/api/rag", tags = ["rag"])
 app.include_router(training_history_router, prefix = "/api/train", tags = ["training-history"])
 app.include_router(hub_inventory_router, prefix = "/api/hub", tags = ["hub"])
 app.include_router(hub_datasets_router, prefix = "/api/hub/datasets", tags = ["hub"])
+app.include_router(picker_templates_router, prefix = "/api/picker", tags = ["picker"])
 app.include_router(hub_token_router, prefix = "/api/hub", tags = ["hub"])
 
 # Re-wrap client-error responses on the /v1/* surface into OpenAI/Anthropic
@@ -1509,6 +1536,34 @@ def _should_inject_bootstrap(request: Request) -> bool:
     return _is_local_bootstrap_request(request)
 
 
+_IMMUTABLE_ASSET_CACHE_CONTROL = "public, max-age=31536000, immutable"
+
+
+class ImmutableStaticFiles(StaticFiles):
+    """Serve Vite's content-hashed assets without browser revalidation."""
+
+    def file_response(
+        self,
+        full_path,
+        stat_result,
+        scope,
+        status_code = 200,
+    ):
+        response = super().file_response(full_path, stat_result, scope, status_code)
+        response.headers["Cache-Control"] = _IMMUTABLE_ASSET_CACHE_CONTROL
+        return response
+
+
+class _AssetGZipMiddleware(GZipMiddleware):
+    """Serve range requests uncompressed; gzip + 206 mislabels Content-Range."""
+
+    async def __call__(self, scope, receive, send):
+        if scope["type"] == "http" and any(key == b"range" for key, _ in scope["headers"]):
+            await self.app(scope, receive, send)
+            return
+        await super().__call__(scope, receive, send)
+
+
 def setup_frontend(app: FastAPI, build_path: Path):
     """Mount frontend static files (optional)"""
     if not build_path.exists():
@@ -1516,7 +1571,12 @@ def setup_frontend(app: FastAPI, build_path: Path):
 
     assets_dir = build_path / "assets"
     if assets_dir.exists():
-        app.mount("/assets", StaticFiles(directory = assets_dir), name = "assets")
+        assets_app = _AssetGZipMiddleware(
+            ImmutableStaticFiles(directory = assets_dir),
+            minimum_size = 1024,
+            compresslevel = 6,
+        )
+        app.mount("/assets", assets_app, name = "assets")
 
     def _build_index_response(request: Request) -> Response:
         content = (build_path / "index.html").read_bytes()
diff --git a/studio/backend/models/inference.py b/studio/backend/models/inference.py
index d51d35189b..c7e5ffa36b 100644
--- a/studio/backend/models/inference.py
+++ b/studio/backend/models/inference.py
@@ -18,6 +18,8 @@ from pydantic import (
     model_validator,
 )
 
+from picker.schemas import MAX_CHAT_TEMPLATE_BYTES
+
 
 class LoadRequest(BaseModel):
     """Request to load a model for inference"""
@@ -54,8 +56,16 @@ class LoadRequest(BaseModel):
     @field_validator("chat_template_override")
     @classmethod
     def normalize_blank_chat_template_override(cls, value: Optional[str]) -> Optional[str]:
-        if value is not None and value.strip() == "":
+        if value is None:
             return None
+        # Char count is a lower bound on UTF-8 byte length: reject an oversized
+        # template before spending work encoding it.
+        if len(value) > MAX_CHAT_TEMPLATE_BYTES:
+            raise ValueError(f"Chat template exceeds the {MAX_CHAT_TEMPLATE_BYTES}-byte limit.")
+        if value.strip() == "":
+            return None
+        if len(value.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES:
+            raise ValueError(f"Chat template exceeds the {MAX_CHAT_TEMPLATE_BYTES}-byte limit.")
         return value
 
     cache_type_kv: Optional[str] = Field(
@@ -177,6 +187,32 @@ class UnloadRequest(BaseModel):
     model_path: str = Field(..., description = "Model identifier to unload")
 
 
+class TranscribeRequest(BaseModel):
+    """Speech-to-text request for the dictation STT sidecar."""
+
+    audio: str = Field(..., description = "Base64-encoded audio (any common format)")
+    model: Optional[str] = Field(None, description = "STT model id; defaults server-side")
+    language: Optional[str] = Field(None, description = "BCP-47 language, or 'auto'/None to detect")
+    fast: bool = Field(
+        False,
+        description = "Use low-latency single-candidate decoding for dictation",
+    )
+    engine: Optional[str] = Field(
+        None,
+        description = "STT engine: 'transformers' (default) or 'gguf' (whisper.cpp)",
+    )
+
+
+class SttLoadRequest(BaseModel):
+    """Warm the STT sidecar with a model without transcribing."""
+
+    model: Optional[str] = Field(None, description = "STT model id; defaults server-side")
+    engine: Optional[str] = Field(
+        None,
+        description = "STT engine: 'transformers' (default) or 'gguf' (whisper.cpp)",
+    )
+
+
 class ValidateModelRequest(BaseModel):
     """Check whether an identifier resolves to a ModelConfig; does NOT load weights."""
 
@@ -206,6 +242,13 @@ class ValidateModelRequest(BaseModel):
         description = "Also read the native context length from the local GGUF header. "
         "Opt-in so the normal load preflight doesn't pay for a cache scan it doesn't need.",
     )
+    include_chat_template: bool = Field(
+        False,
+        description = "Also read the embedded chat template from the local GGUF header, so a "
+        "native (picked / drag-drop) file's default template can be shown before it is loaded. "
+        "Opt-in and, like include_context_length, a metadata-only probe that skips the training "
+        "guard. Only the leased file's own embedded template is read, never sibling sidecars.",
+    )
 
 
 class TransformersUpgradeInfo(BaseModel):
@@ -266,6 +309,11 @@ class ValidateModelResponse(BaseModel):
         description = "MoE expert-layer count (the manual --n-cpu-moe ceiling), read from the GGUF "
         "header alongside context_length; 0 for dense models, None when not read.",
     )
+    chat_template: Optional[str] = Field(
+        None,
+        description = "Embedded GGUF chat template, read from the header when include_chat_template "
+        "is set (native lease-backed picks); None for non-GGUF, over-cap, or not-read templates.",
+    )
     # Additive fields; the consuming consent dialog ships in a follow-up frontend PR.
     requires_transformers_upgrade: bool = Field(
         False,
diff --git a/studio/backend/models/models.py b/studio/backend/models/models.py
index 54e88fed58..df6725c9c9 100644
--- a/studio/backend/models/models.py
+++ b/studio/backend/models/models.py
@@ -178,6 +178,14 @@ class LocalModelInfo(BaseModel):
         None,
         description = "HF repo id for cached models, e.g. org/model",
     )
+    active_cache: Optional[bool] = Field(
+        None,
+        description = "Whether an HF model belongs to the current download cache.",
+    )
+    partial: bool = Field(
+        False,
+        description = "Whether the cached model has an incomplete download.",
+    )
     model_format: Optional[str] = Field(
         None,
         description = "Detected weights format ('gguf' when known). Lets the UI "
diff --git a/studio/backend/models/training.py b/studio/backend/models/training.py
index 0b50f63b95..0f88b78f9f 100644
--- a/studio/backend/models/training.py
+++ b/studio/backend/models/training.py
@@ -505,6 +505,13 @@ class TrainingStartRequest(BaseModel):
         description = "S3 bucket configuration for loading datasets from AWS S3. Requires boto3 to be installed.",
     )
 
+    @field_validator("target_modules", mode = "before")
+    @classmethod
+    def _normalize_target_modules(cls, value: Any) -> Any:
+        # Sanitized non-LoRA history stores the unused value as null; treat it as a
+        # fresh request's omitted/default empty list on resume.
+        return [] if value is None else value
+
     @model_validator(mode = "after")
     def _validate_streaming_splits(self) -> "TrainingStartRequest":
         # Streaming load_dataset does not accept HF slice syntax (e.g. "train[:50%]"
diff --git a/studio/backend/picker/__init__.py b/studio/backend/picker/__init__.py
new file mode 100644
index 0000000000..32014236c6
--- /dev/null
+++ b/studio/backend/picker/__init__.py
@@ -0,0 +1,2 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
diff --git a/studio/backend/picker/routes/__init__.py b/studio/backend/picker/routes/__init__.py
new file mode 100644
index 0000000000..c0e988c8bb
--- /dev/null
+++ b/studio/backend/picker/routes/__init__.py
@@ -0,0 +1,6 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from .templates import router as templates_router
+
+__all__ = ["templates_router"]
diff --git a/studio/backend/picker/routes/templates.py b/studio/backend/picker/routes/templates.py
new file mode 100644
index 0000000000..02b8bf7184
--- /dev/null
+++ b/studio/backend/picker/routes/templates.py
@@ -0,0 +1,45 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from __future__ import annotations
+
+import asyncio
+from typing import Optional
+
+from fastapi import APIRouter, Body, Depends, Query
+
+from auth.authentication import get_current_subject
+from hub.dependencies import get_hf_token
+
+from ..schemas import (
+    MAX_CHAT_TEMPLATE_BYTES,
+    ModelTemplateResponse,
+    ValidateChatTemplateRequest,
+    ValidateChatTemplateResponse,
+)
+from ..service import read_default_chat_template, validate_chat_template
+
+router = APIRouter()
+
+
+@router.post("/validate-chat-template", response_model = ValidateChatTemplateResponse)
+async def validate_chat_template_route(
+    body: ValidateChatTemplateRequest = Body(...),
+    current_subject: str = Depends(get_current_subject),
+) -> ValidateChatTemplateResponse:
+    return await asyncio.to_thread(validate_chat_template, body.template)
+
+
+@router.get("/chat-template/{model_name:path}", response_model = ModelTemplateResponse)
+async def get_default_chat_template_route(
+    model_name: str,
+    gguf_variant: Optional[str] = Query(None),
+    hf_token: Optional[str] = Depends(get_hf_token),
+    current_subject: str = Depends(get_current_subject),
+) -> ModelTemplateResponse:
+    template = await asyncio.to_thread(
+        read_default_chat_template, model_name, hf_token, gguf_variant
+    )
+    if template is not None and len(template.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES:
+        template = None
+    return ModelTemplateResponse(model_name = model_name, chat_template = template)
diff --git a/studio/backend/picker/schemas.py b/studio/backend/picker/schemas.py
new file mode 100644
index 0000000000..b4f956188f
--- /dev/null
+++ b/studio/backend/picker/schemas.py
@@ -0,0 +1,32 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from typing import Optional
+
+from pydantic import BaseModel, Field, field_validator
+
+# Mirror the frontend's 64 KiB chat-template contract (per-model-config.ts) at
+# the API boundary so a direct caller cannot make Jinja parse an oversized
+# template. MaxBodyMiddleware only caps the whole request body, not this field.
+MAX_CHAT_TEMPLATE_BYTES = 65_536
+
+
+class ValidateChatTemplateRequest(BaseModel):
+    template: str = Field(default = "")
+
+    @field_validator("template")
+    @classmethod
+    def _enforce_template_size(cls, value: str) -> str:
+        if len(value.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES:
+            raise ValueError(f"Chat template exceeds the {MAX_CHAT_TEMPLATE_BYTES}-byte limit.")
+        return value
+
+
+class ValidateChatTemplateResponse(BaseModel):
+    valid: bool
+    error: Optional[str] = None
+
+
+class ModelTemplateResponse(BaseModel):
+    model_name: str
+    chat_template: Optional[str] = None
diff --git a/studio/backend/picker/service.py b/studio/backend/picker/service.py
new file mode 100644
index 0000000000..ccf9c3e152
--- /dev/null
+++ b/studio/backend/picker/service.py
@@ -0,0 +1,432 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+import re
+from pathlib import Path
+from typing import Optional
+
+from hub.services.models.folder_browser import (
+    _build_browse_allowlist,
+    _is_path_inside_allowlist,
+)
+from hub.utils.gguf import extract_quant_label, iter_hf_cache_snapshots
+from utils.models.gguf_metadata import read_gguf_chat_template
+from utils.models.model_config import (
+    _extract_quant_label,
+    _is_big_endian_gguf_path,
+    _is_mmproj,
+    _is_mtp_drafter,
+)
+from utils.hf_cache_settings import active_hf_hub_cache
+from utils.paths.path_utils import (
+    is_local_path,
+    normalize_path,
+    resolve_cached_repo_id_case,
+)
+
+from .schemas import MAX_CHAT_TEMPLATE_BYTES, ValidateChatTemplateResponse
+
+logger = logging.getLogger(__name__)
+
+_VALID_REPO_ID = re.compile(r"^[A-Za-z0-9._-]+/[A-Za-z0-9._-]+$")
+
+
+def _is_valid_repo_id(repo_id: str) -> bool:
+    return bool(_VALID_REPO_ID.fullmatch(repo_id))
+
+
+_TOKENIZER_CONFIG_PATHS = ("tokenizer_config.json", "LLM/tokenizer_config.json")
+_JINJA_TEMPLATE_PATHS = ("chat_template.jinja", "LLM/chat_template.jinja")
+_PROCESSOR_TEMPLATE_PATHS = ("chat_template.json", "LLM/chat_template.json")
+
+# Cap sidecar reads so a malformed or hostile metadata file cannot exhaust memory
+# before its template is size-checked. The JSON envelope may exceed a bare template
+# (it carries other tokenizer metadata); the extracted template is still bounded by
+# MAX_CHAT_TEMPLATE_BYTES downstream.
+MAX_TEMPLATE_METADATA_BYTES = 4 * 1024 * 1024
+
+
+def _read_bounded_text(path: Path, limit: int) -> Optional[str]:
+    """Read at most `limit` bytes of UTF-8 text; None if larger or unreadable."""
+    try:
+        with path.open("rb") as f:
+            data = f.read(limit + 1)
+    except OSError:
+        return None
+    if len(data) > limit:
+        return None
+    try:
+        return data.decode("utf-8")
+    except UnicodeError:
+        return None
+
+
+def _leaf_inside_allowlist(path: Path, allow_roots: Optional[list[Path]]) -> bool:
+    # Block symlinked children from escaping the validated directory (realpath-checked).
+    # None = trusted caller (HF cache / remote download).
+    return allow_roots is None or _is_path_inside_allowlist(path, allow_roots)
+
+
+def validate_chat_template(template: str) -> ValidateChatTemplateResponse:
+    text = (template or "").strip()
+    if not text:
+        return ValidateChatTemplateResponse(valid = True, error = None)
+    # Import Jinja lazily: optional at runtime (e.g. GGUF-only installs), so a
+    # missing dependency must not crash API startup.
+    try:
+        from jinja2 import TemplateError
+        from jinja2.ext import Extension
+        from jinja2.sandbox import ImmutableSandboxedEnvironment
+    except ImportError:
+        return ValidateChatTemplateResponse(valid = True, error = None)
+
+    class _GenerationTag(Extension):
+        # Accept Transformers' {% generation %} assistant-mask tag so a pasted HF
+        # chat template validates (we only parse it).
+        tags = {"generation"}
+
+        def parse(self, parser):
+            next(parser.stream)
+            return parser.parse_statements(["name:endgeneration"], drop_needle = True)
+
+    try:
+        env = ImmutableSandboxedEnvironment(
+            trim_blocks = True,
+            lstrip_blocks = True,
+            extensions = ["jinja2.ext.loopcontrols", _GenerationTag],
+        )
+        env.parse(text)
+        return ValidateChatTemplateResponse(valid = True, error = None)
+    except TemplateError as exc:
+        message = getattr(exc, "message", None) or str(exc)
+        lineno = getattr(exc, "lineno", None)
+        if lineno:
+            message = f"Line {lineno}: {message}"
+        return ValidateChatTemplateResponse(valid = False, error = message)
+    except Exception as exc:
+        return ValidateChatTemplateResponse(valid = False, error = str(exc))
+
+
+def _chat_template_from_tokenizer_config(config: dict) -> Optional[str]:
+    if not isinstance(config, dict):
+        return None
+    raw = config.get("chat_template")
+    if isinstance(raw, str) and raw.strip():
+        return raw
+    if isinstance(raw, list):
+        fallback: Optional[str] = None
+        for entry in raw:
+            if not isinstance(entry, dict):
+                continue
+            template = entry.get("template")
+            if not isinstance(template, str):
+                continue
+            if entry.get("name") == "default":
+                return template
+            if fallback is None:
+                fallback = template
+        return fallback
+    return None
+
+
+def _chat_template_from_jinja_file(
+    dir_path: Path, allow_roots: Optional[list[Path]] = None
+) -> Optional[str]:
+    for rel in _JINJA_TEMPLATE_PATHS:
+        template_file = dir_path / rel
+        if not template_file.exists() or not _leaf_inside_allowlist(template_file, allow_roots):
+            continue
+        try:
+            if template_file.stat().st_size > MAX_CHAT_TEMPLATE_BYTES:
+                continue
+            template = template_file.read_text(encoding = "utf-8")
+        except Exception:
+            continue
+        if template.strip():
+            return template
+    return None
+
+
+def _chat_template_from_processor_payload(payload: object) -> Optional[str]:
+    # processor chat_template.json may be the template string itself or a
+    # {name: template} map, not only a tokenizer_config-shaped object.
+    if isinstance(payload, str):
+        return payload if payload.strip() else None
+    template = _chat_template_from_tokenizer_config(payload)  # type: ignore[arg-type]
+    if template:
+        return template
+    if isinstance(payload, dict):
+        # Named-template map: prefer "default", else the first non-empty entry
+        # (mirrors the tokenizer-config list fallback).
+        default = payload.get("default")
+        if isinstance(default, str) and default.strip():
+            return default
+        for value in payload.values():
+            if isinstance(value, str) and value.strip():
+                return value
+    return None
+
+
+def _chat_template_from_processor_json(
+    dir_path: Path, allow_roots: Optional[list[Path]] = None
+) -> Optional[str]:
+    for rel in _PROCESSOR_TEMPLATE_PATHS:
+        config_file = dir_path / rel
+        if not config_file.exists() or not _leaf_inside_allowlist(config_file, allow_roots):
+            continue
+        raw = _read_bounded_text(config_file, MAX_TEMPLATE_METADATA_BYTES)
+        if raw is None:
+            continue
+        try:
+            payload = json.loads(raw)
+        except Exception:
+            continue
+        template = _chat_template_from_processor_payload(payload)
+        if template:
+            return template
+    return None
+
+
+def _chat_template_from_tokenizer_dir(
+    dir_path: Path, allow_roots: Optional[list[Path]] = None
+) -> Optional[str]:
+    jinja = _chat_template_from_jinja_file(dir_path, allow_roots)
+    if jinja:
+        return jinja
+    for rel in _TOKENIZER_CONFIG_PATHS:
+        config_file = dir_path / rel
+        if not config_file.exists() or not _leaf_inside_allowlist(config_file, allow_roots):
+            continue
+        raw = _read_bounded_text(config_file, MAX_TEMPLATE_METADATA_BYTES)
+        if raw is None:
+            continue
+        try:
+            config = json.loads(raw)
+        except Exception:
+            continue
+        template = _chat_template_from_tokenizer_config(config)
+        if template:
+            return template
+    return _chat_template_from_processor_json(dir_path, allow_roots)
+
+
+_GGUF_SCAN_MAX_DEPTH = 2
+
+
+def _iter_ggufs(dir_path: Path) -> list[Path]:
+    if dir_path == dir_path.parent:
+        return []
+    root = str(dir_path)
+    found: list[Path] = []
+    for current, dirs, files in os.walk(root, followlinks = False):
+        rel = os.path.relpath(current, root)
+        depth = 0 if rel == os.curdir else rel.count(os.sep) + 1
+        if depth >= _GGUF_SCAN_MAX_DEPTH:
+            dirs[:] = []
+        for name in files:
+            if not name.lower().endswith(".gguf") or _is_mmproj(name):
+                continue
+            path = Path(current) / name
+            try:
+                rel = path.relative_to(dir_path).as_posix()
+            except ValueError:
+                rel = name
+            quant = _extract_quant_label(rel)
+            if _is_mtp_drafter(rel) or _is_big_endian_gguf_path(rel, quant):
+                continue
+            found.append(path)
+    return found
+
+
+def _variant_matches(relative_path: str, needle: str) -> bool:
+    quant = _extract_quant_label(relative_path).lower()
+    if quant == needle:
+        return True
+    if extract_quant_label(relative_path).lower() == needle:
+        return True
+    prefix = f"{needle}-"
+    if not quant.startswith(prefix):
+        return False
+    suffix = quant[len(prefix) :]
+    if not suffix.endswith("bpw"):
+        return False
+    value = suffix[:-3]
+    return bool(value) and value.replace(".", "", 1).isdigit()
+
+
+_GGUF_SPLIT_INDEX_RE = re.compile(r"-(\d{3,})-of-\d{3,}$", re.IGNORECASE)
+
+
+def _is_nonfirst_gguf_split(path: Path) -> bool:
+    match = _GGUF_SPLIT_INDEX_RE.search(path.stem)
+    return match is not None and int(match.group(1)) != 1
+
+
+def _find_gguf_in_dir(dir_path: Path, gguf_variant: Optional[str]) -> Optional[Path]:
+    try:
+        ggufs = sorted(_iter_ggufs(dir_path))
+    except OSError:
+        return None
+    if not ggufs:
+        return None
+    needle = (gguf_variant or "").strip().lower()
+    if needle:
+        for path in ggufs:
+            try:
+                relative = path.relative_to(dir_path).as_posix()
+            except ValueError:
+                relative = path.name
+            if _variant_matches(relative, needle):
+                return path
+        return None
+    candidates = [path for path in ggufs if not _is_nonfirst_gguf_split(path)] or ggufs
+    try:
+        return max(candidates, key = lambda path: path.stat().st_size)
+    except OSError:
+        return candidates[0]
+
+
+def _chat_template_from_dir(
+    dir_path: Path,
+    gguf_variant: Optional[str] = None,
+    allow_roots: Optional[list[Path]] = None,
+) -> Optional[str]:
+    def from_gguf() -> Optional[str]:
+        gguf = _find_gguf_in_dir(dir_path, gguf_variant)
+        if gguf is None or not _leaf_inside_allowlist(gguf, allow_roots):
+            return None
+        return read_gguf_chat_template(str(gguf))
+
+    # Sidecar tokenizer files (chat_template.jinja / tokenizer_config.json) are the
+    # author's maintained template and supersede the GGUF's possibly-stale embedded
+    # copy. The variant only picks the GGUF fallback, so tokenizer-first precedence
+    # holds whether or not a variant is given.
+    return _chat_template_from_tokenizer_dir(dir_path, allow_roots) or from_gguf()
+
+
+def read_default_chat_template(
+    model_name: str,
+    hf_token: Optional[str] = None,
+    gguf_variant: Optional[str] = None,
+) -> Optional[str]:
+    if not isinstance(model_name, str) or not model_name.strip():
+        return None
+    name = model_name.strip()
+
+    if is_local_path(name):
+        try:
+            target = Path(normalize_path(name)).expanduser()
+            allow_roots = _build_browse_allowlist()
+            if not _is_path_inside_allowlist(target, allow_roots):
+                logger.debug("Refused chat template read outside allowed folders: %s", name)
+                return None
+            if name.lower().endswith(".gguf"):
+                # Prefer a maintained sidecar next to the file over the GGUF's
+                # embedded copy (tokenizer-first precedence, as elsewhere).
+                sidecar = _chat_template_from_tokenizer_dir(target.parent, allow_roots)
+                if sidecar:
+                    return sidecar
+                return read_gguf_chat_template(str(target))
+            return _chat_template_from_dir(target, gguf_variant, allow_roots)
+        except Exception as exc:
+            logger.debug("Could not read local chat template for %s: %s", name, exc)
+            return None
+
+    if not _is_valid_repo_id(name):
+        return None
+
+    resolved = resolve_cached_repo_id_case(name)
+
+    try:
+        # Resolve within each cached revision, newest first. A revision's sidecar
+        # supersedes its own embedded GGUF copy, but must not override a newer
+        # revision, so precedence stays per-snapshot rather than global.
+        for snapshot in iter_hf_cache_snapshots(resolved):
+            template = _chat_template_from_dir(snapshot, gguf_variant)
+            if template:
+                return template
+    except Exception as exc:
+        logger.debug("Could not read cached chat template for %s: %s", resolved, exc)
+
+    try:
+        from huggingface_hub import HfApi, hf_hub_download
+
+        _api = HfApi()
+
+        def _remote_exceeds_cap(rel: str) -> bool:
+            # Best-effort: skip the download when the remote's advertised size
+            # exceeds the cap, so a maliciously large sidecar is never fetched.
+            try:
+                infos = _api.get_paths_info(resolved, [rel], repo_type = "model", token = hf_token)
+            except Exception:
+                return False
+            for info in infos:
+                size = getattr(info, "size", None)
+                if (
+                    getattr(info, "path", None) == rel
+                    and isinstance(size, int)
+                    and size > MAX_TEMPLATE_METADATA_BYTES
+                ):
+                    return True
+            return False
+
+        def _download_text(rel: str) -> Optional[str]:
+            if _remote_exceeds_cap(rel):
+                return None
+            try:
+                path = hf_hub_download(
+                    resolved,
+                    rel,
+                    token = hf_token,
+                    cache_dir = active_hf_hub_cache(),
+                )
+                return _read_bounded_text(Path(path), MAX_TEMPLATE_METADATA_BYTES)
+            except Exception:
+                return None
+
+        for rel in _JINJA_TEMPLATE_PATHS:
+            template = _download_text(rel)
+            if not template or not template.strip():
+                continue
+            # A raw Jinja sidecar is the whole template, so it must fit the route's
+            # response cap (the local path skips oversized .jinja too). Download stays
+            # bounded at MAX_TEMPLATE_METADATA_BYTES so a large JSON embedding a small
+            # template still extracts below, but an over-cap Jinja is dropped so the
+            # search falls through to the tokenizer/processor template.
+            if len(template.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES:
+                continue
+            return template
+
+        for rel in _TOKENIZER_CONFIG_PATHS:
+            raw = _download_text(rel)
+            if not raw:
+                continue
+            try:
+                config = json.loads(raw)
+            except Exception:
+                continue
+            template = _chat_template_from_tokenizer_config(config)
+            if template:
+                return template
+
+        for rel in _PROCESSOR_TEMPLATE_PATHS:
+            raw = _download_text(rel)
+            if not raw:
+                continue
+            try:
+                payload = json.loads(raw)
+            except Exception:
+                continue
+            template = _chat_template_from_processor_payload(payload)
+            if template:
+                return template
+
+        return None
+    except Exception as exc:
+        logger.debug("Could not fetch chat template for %s: %s", resolved, exc)
+        return None
diff --git a/studio/backend/requirements/extras.txt b/studio/backend/requirements/extras.txt
index 1baf2b6f2d..1601ccbfae 100644
--- a/studio/backend/requirements/extras.txt
+++ b/studio/backend/requirements/extras.txt
@@ -10,6 +10,7 @@ omegaconf
 einx
 pyloudnorm
 openai-whisper
+av                               # PyAV: decode dictation audio (webm/opus/mp3/…) for the Whisper STT sidecar
 uroman                           # 4.0 MB - used for Outetts.
 MeCab                            # 19.9 MB - used for Outetts.
 inflect                          # number-to-words, required by OuteTTS
diff --git a/studio/backend/requirements/no-torch-runtime.txt b/studio/backend/requirements/no-torch-runtime.txt
index 378fb33a60..847e89823b 100644
--- a/studio/backend/requirements/no-torch-runtime.txt
+++ b/studio/backend/requirements/no-torch-runtime.txt
@@ -7,7 +7,7 @@
 # (current PyPI metadata still declares torch as a hard dep).
 
 # unsloth direct deps (from pyproject.toml [project].dependencies)
-typer
+typer>=0.12.0
 # typer's full runtime dep tree. Required explicitly because this
 # file is installed with --no-deps. On Linux/Mac CI runners these
 # are often cached transitively; on a fresh windows-latest venv they
diff --git a/studio/backend/routes/auth.py b/studio/backend/routes/auth.py
index d779c8784e..1acc48e3a3 100644
--- a/studio/backend/routes/auth.py
+++ b/studio/backend/routes/auth.py
@@ -494,6 +494,11 @@ async def change_password(
             status_code = status.HTTP_401_UNAUTHORIZED,
             detail = "Current password is incorrect",
         )
+    if any(ch.isspace() for ch in payload.new_password):
+        raise HTTPException(
+            status_code = status.HTTP_400_BAD_REQUEST,
+            detail = "New password cannot contain spaces",
+        )
     if payload.current_password == payload.new_password:
         raise HTTPException(
             status_code = status.HTTP_400_BAD_REQUEST,
diff --git a/studio/backend/routes/datasets.py b/studio/backend/routes/datasets.py
index 5456080f34..331eb5e1e0 100644
--- a/studio/backend/routes/datasets.py
+++ b/studio/backend/routes/datasets.py
@@ -23,40 +23,6 @@ def _is_valid_repo_id(repo_id: str) -> bool:
     return bool(_VALID_REPO_ID.fullmatch(repo_id))
 
 
-_dataset_size_cache: dict[str, int] = {}
-
-
-def _get_dataset_size_cached(repo_id: str) -> int:
-    if repo_id in _dataset_size_cache:
-        return _dataset_size_cache[repo_id]
-    try:
-        from huggingface_hub import dataset_info as hf_dataset_info
-
-        info = hf_dataset_info(repo_id, token = None, files_metadata = True)
-        total = sum(s.size for s in info.siblings if getattr(s, "size", None))
-        _dataset_size_cache[repo_id] = total
-        return total
-    except Exception:
-        return 0
-
-
-def _resolve_hf_cache_realpath(repo_dir: Path) -> Optional[str]:
-    """Resolved realpath for a HF cache repo dir: most-recent snapshot, else cache root.
-
-    Mirrors routes/models.py; duplicated here to keep this module self-contained.
-    """
-    try:
-        snapshots_dir = repo_dir / "snapshots"
-        if snapshots_dir.is_dir():
-            snaps = [s for s in snapshots_dir.iterdir() if s.is_dir()]
-            if snaps:
-                latest = max(snaps, key = lambda s: s.stat().st_mtime)
-                return str(latest.resolve())
-        return str(repo_dir.resolve())
-    except Exception:
-        return None
-
-
 backend_path = Path(__file__).parent.parent.parent
 if str(backend_path) not in sys.path:
     sys.path.insert(0, str(backend_path))
@@ -64,6 +30,7 @@ if str(backend_path) not in sys.path:
 from utils.datasets import check_dataset_format
 from utils.upload_limits import get_upload_limit_bytes, get_upload_limit_label
 from auth.authentication import get_current_subject
+from hub.dependencies import get_hf_token
 
 router = APIRouter()
 logger = get_logger(__name__)
@@ -292,11 +259,13 @@ def _download_hf_metadata(*, repo_id: str, repo_files: list[str], token: str | N
 
     try:
         from huggingface_hub import hf_hub_download
+        from utils.hf_cache_settings import active_hf_hub_cache
         local_path = hf_hub_download(
             repo_id = repo_id,
             filename = metadata_file,
             repo_type = "dataset",
             token = token,
+            cache_dir = active_hf_hub_cache(),
         )
     except Exception as exc:
         logger.warning(f"Could not read HF dataset metadata for {repo_id}: {exc}")
@@ -525,77 +494,15 @@ def list_local_datasets(
 @router.get("/download-progress")
 async def get_dataset_download_progress(
     repo_id: str = Query(..., description = "HuggingFace dataset repo ID, e.g. 'unsloth/LaTeX_OCR'"),
+    hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
-    """Return download progress for a HuggingFace dataset repo.
-
-    Mirrors ``GET /api/models/download-progress`` but scans the
-    ``datasets--owner--name`` cache dir under HF_HUB_CACHE, where in-progress
-    download bytes are visible. Returns ``cache_path`` so the UI can show it.
-    """
-    _empty = {
-        "downloaded_bytes": 0,
-        "expected_bytes": 0,
-        "progress": 0,
-        "cache_path": None,
-    }
-    try:
-        if not _is_valid_repo_id(repo_id):
-            return _empty
-
-        from huggingface_hub import constants as hf_constants
-
-        cache_dir = Path(hf_constants.HF_HUB_CACHE)
-        target = f"datasets--{repo_id.replace('/', '--')}".lower()
-        completed_bytes = 0
-        in_progress_bytes = 0
-        cache_path: Optional[str] = None
-
-        if cache_dir.is_dir():
-            for entry in cache_dir.iterdir():
-                if entry.name.lower() != target:
-                    continue
-                cache_path = _resolve_hf_cache_realpath(entry)
-                blobs_dir = entry / "blobs"
-                if not blobs_dir.is_dir():
-                    break
-                for f in blobs_dir.iterdir():
-                    if not f.is_file():
-                        continue
-                    if f.name.endswith(".incomplete"):
-                        in_progress_bytes += f.stat().st_size
-                    else:
-                        completed_bytes += f.stat().st_size
-                break
-
-        downloaded_bytes = completed_bytes + in_progress_bytes
-        if downloaded_bytes == 0:
-            return {**_empty, "cache_path": cache_path}
-
-        expected_bytes = _get_dataset_size_cached(repo_id)
-        if expected_bytes <= 0:
-            return {
-                "downloaded_bytes": downloaded_bytes,
-                "expected_bytes": 0,
-                "progress": 0,
-                "cache_path": cache_path,
-            }
-
-        # 95% threshold (as in the model endpoint): HF blob dedup makes
-        # completed_bytes drift under expected_bytes; inter-file gaps look "done".
-        if completed_bytes >= expected_bytes * 0.95:
-            progress = 1.0
-        else:
-            progress = min(downloaded_bytes / expected_bytes, 0.99)
-        return {
-            "downloaded_bytes": downloaded_bytes,
-            "expected_bytes": expected_bytes,
-            "progress": round(progress, 3),
-            "cache_path": cache_path,
-        }
-    except Exception as e:
-        logger.warning(f"Error checking dataset download progress for {repo_id}: {e}")
-        return _empty
+    """Compatibility route backed by the shared multi-cache progress service."""
+    from hub.services.datasets import downloads
+    return await downloads.get_dataset_download_progress_response(
+        repo_id,
+        hf_token = hf_token,
+    )
 
 
 @router.post("/check-format", response_model = CheckFormatResponse)
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index afd942e9a5..b6bbbdfb5f 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -29,6 +29,8 @@ import re as _re
 from utils.models import extract_model_size_b as _extract_model_size_b
 
 from utils.api_errors import openai_error_body, anthropic_error_body
+from utils.upload_limits import STT_AUDIO_B64_MAX_CHARS, STT_AUDIO_RAW_MAX_BYTES
+from hub.dependencies import get_hf_token
 from core.inference.orchestrator import GenStreamError, GenStreamErrorRaised
 from core.inference.llama_admission import (
     LlamaAdmissionCancelled,
@@ -1692,6 +1694,8 @@ async def _aiter_llama_stream_items(
 from models.inference import (
     LoadRequest,
     UnloadRequest,
+    TranscribeRequest,
+    SttLoadRequest,
     GenerateRequest,
     LoadResponse,
     LoadProgressResponse,
@@ -3406,9 +3410,8 @@ async def _acquire_swap_gate() -> None:
         await asyncio.sleep(0.02)
 
 
-# Counts in-flight auto-switch requests per (target, variant). The busy guard
-# subtracts same-target waiters so concurrent requests for one model load once
-# instead of each 409-ing the other.
+# Counts auto-switch requests queued to load each (target, variant). They are not
+# generating, so the drain wait below excludes them from the active inference count.
 _auto_switch_waiters: dict[tuple[str, str], int] = {}
 _auto_switch_waiters_guard = threading.Lock()
 
@@ -3426,35 +3429,31 @@ def _note_switch_waiter(key: tuple[str, str], delta: int) -> None:
             _auto_switch_waiters.pop(key, None)
 
 
-def _same_target_waiters(key: tuple[str, str]) -> int:
+def _switch_waiter_count() -> int:
     with _auto_switch_waiters_guard:
-        return _auto_switch_waiters.get(key, 0)
+        return sum(max(0, count) for count in _auto_switch_waiters.values())
 
 
-# A second waiter map keyed by the raw requested model, registered before the
-# (slow) resolve. The middleware counts a concurrent same-model request as
-# in-flight before it resolves and joins _auto_switch_waiters, so without this
-# the first request would see it as an unrelated request and 409.
-_auto_switch_request_waiters: dict[str, int] = {}
-_auto_switch_request_waiters_guard = threading.Lock()
+async def _wait_for_model_switch_idle(*, current_request_counted: bool) -> None:
+    """Wait until a model replacement cannot interrupt active inference.
 
-
-def _request_waiter_key(requested_model: str) -> str:
-    return requested_model.strip().lower()
-
-
-def _note_request_waiter(key: str, delta: int) -> None:
-    with _auto_switch_request_waiters_guard:
-        n = _auto_switch_request_waiters.get(key, 0) + delta
-        if n > 0:
-            _auto_switch_request_waiters[key] = n
-        else:
-            _auto_switch_request_waiters.pop(key, None)
-
-
-def _same_request_waiters(key: str) -> int:
-    with _auto_switch_request_waiters_guard:
-        return _auto_switch_request_waiters.get(key, 0)
+    The caller holds ``inference_lifecycle_gate``, which prevents new inference
+    from starting while existing requests drain. Auto-switch requests that have
+    resolved their targets are scheduler waiters, not active generations, so
+    exclude them to avoid a queue deadlock.
+    """
+    from core.inference.llama_keepwarm import other_inference_request_count
+    while True:
+        queued_switches = _switch_waiter_count()
+        if current_request_counted and queued_switches > 0:
+            queued_switches -= 1
+        active_others = other_inference_request_count(
+            current_request_counted = current_request_counted,
+            include_pending = False,
+        )
+        if active_others <= queued_switches:
+            return
+        await asyncio.sleep(0.02)
 
 
 def _llama_public_model_id(llama_backend, fallback: Optional[str] = None) -> Optional[str]:
@@ -3582,7 +3581,6 @@ async def _maybe_auto_switch_model(
     from core.inference.local_model_resolver import resolve_local_gguf
     from core.inference.llama_keepwarm import (
         get_last_unloaded_model,
-        other_inference_request_count,
         inference_lifecycle_gate,
     )
 
@@ -3603,12 +3601,7 @@ async def _maybe_auto_switch_model(
     if not auto_switch_on and get_auto_unload_idle_seconds() <= 0:
         return
 
-    # Register by the raw requested model before resolving (which can be slow):
-    # the middleware already counts a concurrent same-model request as in-flight,
-    # so the busy guard must know it shares this target even while it resolves.
-    request_key = _request_waiter_key(requested_model)
-    _note_request_waiter(request_key, 1)
-    try:
+    async def _resolve_and_switch() -> None:
         # Off the loop: a cold-cache rebuild walks several model dirs + HF caches.
         # With auto-switch off (or an omitted-model reload-only request), skip the
         # resolve so only the reload-stash path runs and no name is ever matched.
@@ -3706,6 +3699,7 @@ async def _maybe_auto_switch_model(
             )
         key = _switch_key(override_id, variant)
         _note_switch_waiter(key, 1)
+        waiter_noted = True
         try:
             async with _auto_switch_lock():
                 # The asyncio lock is per loop; add a process-wide gate so a swap on
@@ -3718,31 +3712,6 @@ async def _maybe_auto_switch_model(
                         if _already_serving():
                             _record_serving_alias()
                             return
-                        # Single slot: refuse a cross-model swap while another inference
-                        # request is active rather than killing its response. Requests
-                        # heading to this same target (by resolved id or raw name) are
-                        # excluded, so concurrent requests for one model load once. A
-                        # pending request is still in the middleware, not generating, so
-                        # it is not counted here.
-                        same_others = max(
-                            _same_target_waiters(key) - 1, _same_request_waiters(request_key) - 1, 0
-                        )
-                        others = other_inference_request_count(
-                            current_request_counted = True, include_pending = False
-                        )
-                        # Not gated on the GGUF being loaded: _load_model_impl also
-                        # tears down an active Unsloth backend before loading a GGUF,
-                        # so refuse whenever any other inference request is in flight.
-                        if others > same_others:
-                            raise HTTPException(
-                                status_code = 409,
-                                detail = openai_error_body(
-                                    "Cannot switch models while another inference request is in progress.",
-                                    status = 409,
-                                    code = "model_switch_busy",
-                                    param = "model",
-                                ),
-                            )
                         # Apply this model's saved launch flags so the swap honors the config.
                         override = get_model_override(override_id)
                         load_kwargs = {"model_path": target_id, "gguf_variant": variant}
@@ -3757,16 +3726,22 @@ async def _maybe_auto_switch_model(
                             LoadRequest(**load_kwargs),
                             fastapi_request,
                             current_subject,
+                            current_request_counted = True,
                         )
                         # Advertise the repo id (not the concrete load path) as the loaded
                         # model's public id and override key for /v1/models and idle stash.
                         get_llama_cpp_backend()._openai_advertised_id = override_id
                 finally:
+                    # Deregister before releasing the gate: otherwise a swap on another
+                    # loop counts this finished request as queued and unloads its model.
+                    _note_switch_waiter(key, -1)
+                    waiter_noted = False
                     _auto_switch_process_lock.release()
         finally:
-            _note_switch_waiter(key, -1)
-    finally:
-        _note_request_waiter(request_key, -1)
+            if waiter_noted:
+                _note_switch_waiter(key, -1)
+
+    await _resolve_and_switch()
 
 
 async def _auto_switch_from_request_body(request: Request, current_subject: str):
@@ -4186,6 +4161,15 @@ def _maybe_unsupported_message(msg: str) -> str:
     return msg
 
 
+def _raise_if_sidecar_swap_in_progress() -> None:
+    from utils.transformers_version import sidecar_swap_in_progress
+    if sidecar_swap_in_progress():
+        raise HTTPException(
+            status_code = 409,
+            detail = "A transformers installation is in progress. Retry when it completes.",
+        )
+
+
 @router.post("/load", response_model = LoadResponse)
 async def load_model(
     request: LoadRequest,
@@ -4206,24 +4190,23 @@ async def load_model(
     # install can reserve while this request queues on the gate, so the pre-gate
     # check alone is only a fast path.
     from core.inference.llama_keepwarm import inference_lifecycle_gate
-    from utils.transformers_version import sidecar_swap_in_progress
 
-    _swap_409 = HTTPException(
-        status_code = 409,
-        detail = "A transformers installation is in progress. Retry when it completes.",
-    )
-    if sidecar_swap_in_progress():
-        raise _swap_409
+    _raise_if_sidecar_swap_in_progress()
     # Hold the lifecycle gate across the load so idle auto-unload can't unload the
     # model mid-load. Auto-switch calls _load_model_impl directly since it already
     # holds this gate.
     async with inference_lifecycle_gate():
-        if sidecar_swap_in_progress():
-            raise _swap_409
+        _raise_if_sidecar_swap_in_progress()
         return await _load_model_impl(request, fastapi_request, current_subject)
 
 
-async def _load_model_impl(request: LoadRequest, fastapi_request: Request, current_subject: str):
+async def _load_model_impl(
+    request: LoadRequest,
+    fastapi_request: Request,
+    current_subject: str,
+    *,
+    current_request_counted: bool = False,
+):
     from core.inference.llama_cpp import LlamaServerNotFoundError
 
     # A new load starts here; arm the progress throttle so this load's first
@@ -4557,6 +4540,13 @@ async def _load_model_impl(request: LoadRequest, fastapi_request: Request, curre
                         ),
                     )
 
+            # Keep the resident model alive until every active generation finishes;
+            # the caller's lifecycle gate blocks new starts.
+            await _wait_for_model_switch_idle(current_request_counted = current_request_counted)
+            # A sidecar install can reserve the gate while inference drains, after the
+            # route-level checks above, so recheck before replacing either backend.
+            _raise_if_sidecar_swap_in_progress()
+
             # Unload any active Unsloth model only after every hub conflict check.
             if unsloth_backend.active_model_name:
                 logger.info(
@@ -4767,6 +4757,8 @@ async def _load_model_impl(request: LoadRequest, fastapi_request: Request, curre
 
         # Unload any active GGUF model first
         llama_backend = get_llama_cpp_backend()
+        await _wait_for_model_switch_idle(current_request_counted = current_request_counted)
+        _raise_if_sidecar_swap_in_progress()
         if llama_backend.is_loaded:
             logger.info("Unloading GGUF model before loading Unsloth model")
             llama_backend.unload_model()
@@ -5144,10 +5136,10 @@ async def validate_model(
                 latest_tier_active_for, config.identifier, request.hf_token
             ):
                 effective_load_in_4bit = False
-        # A metadata-only probe just reads the GGUF header and allocates no VRAM,
-        # so it must not be refused by the training guard. Real loads validate
-        # without include_context_length and /load applies the guard again.
-        if not request.include_context_length:
+        # A metadata-only probe reads the GGUF header and allocates no VRAM, so the
+        # training guard must not refuse it. Real loads omit include_context_length /
+        # include_chat_template, and /load applies the guard again.
+        if not (request.include_context_length or request.include_chat_template):
             # Match /load's inherited llama.cpp extras and parallel slot count so
             # validation cannot pass a smaller estimate than the subsequent load.
             effective_extra_args = _resolve_inherited_extra_args(
@@ -5189,9 +5181,15 @@ async def validate_model(
         context_length: Optional[int] = None
         layer_count: Optional[int] = None
         moe_layer_count: Optional[int] = None
-        if request.include_context_length and is_gguf:
+        chat_template: Optional[str] = None
+        # Both header probes read the same local GGUF, so resolve it once.
+        if (request.include_context_length or request.include_chat_template) and is_gguf:
             from hub.utils.gguf import resolve_local_gguf_path
-            from utils.models.gguf_metadata import read_gguf_staged_dims
+            from picker.schemas import MAX_CHAT_TEMPLATE_BYTES
+            from utils.models.gguf_metadata import (
+                read_gguf_chat_template,
+                read_gguf_staged_dims,
+            )
 
             # Best-effort: a header-read failure must never fail validation of an
             # otherwise-valid model (the outer except turns it into a 400).
@@ -5207,13 +5205,24 @@ async def validate_model(
                         model_identifier, request.gguf_variant
                     )
                 if local_gguf:
-                    # Header walk reads tokenizer arrays for dense models (tens of
-                    # ms); keep it off the event loop.
-                    dims = await asyncio.to_thread(read_gguf_staged_dims, local_gguf)
-                    if dims:
-                        context_length = dims["context_length"]
-                        layer_count = dims["layer_count"]
-                        moe_layer_count = dims["moe_layer_count"]
+                    if request.include_context_length:
+                        # Header walk reads tokenizer arrays (tens of ms); keep it
+                        # off the event loop.
+                        dims = await asyncio.to_thread(read_gguf_staged_dims, local_gguf)
+                        if dims:
+                            context_length = dims["context_length"]
+                            layer_count = dims["layer_count"]
+                            moe_layer_count = dims["moe_layer_count"]
+                    if request.include_chat_template:
+                        # Read only the leased GGUF's own embedded template (the copy
+                        # llama.cpp loads), never a sibling sidecar: the native grant
+                        # authorizes just this path, so neighbours would be scope escalation.
+                        raw_template = await asyncio.to_thread(read_gguf_chat_template, local_gguf)
+                        if (
+                            raw_template is not None
+                            and len(raw_template.encode("utf-8")) <= MAX_CHAT_TEMPLATE_BYTES
+                        ):
+                            chat_template = raw_template
             except Exception as e:
                 logger.debug("Header probe failed for %s: %s", model_log_label, e)
 
@@ -5232,6 +5241,7 @@ async def validate_model(
             context_length = context_length,
             layer_count = layer_count,
             moe_layer_count = moe_layer_count,
+            chat_template = chat_template,
             requires_transformers_upgrade = transformers_upgrade is not None,
             transformers_upgrade = transformers_upgrade,
         )
@@ -6107,6 +6117,342 @@ async def generate_audio(
     )
 
 
+# =====================================================================
+# Speech-to-text (STT) sidecar  (/audio/transcribe, /audio/stt/*)
+# =====================================================================
+
+
+def _resolve_stt_engine(engine: Optional[str]) -> str:
+    """Normalize the requested STT engine name; default is Transformers."""
+    normalized = (engine or "transformers").strip().lower()
+    if normalized in ("", "transformers", "whisper"):
+        return "transformers"
+    if normalized in ("gguf", "ggml", "whisper_cpp", "whisper.cpp"):
+        return "gguf"
+    raise HTTPException(
+        status_code = 422,
+        detail = f"Unknown STT engine '{engine}'. Use 'transformers' or 'gguf'.",
+    )
+
+
+def _resolve_serving_stt_engine(engine: Optional[str]) -> str:
+    """Resolve the engine that will actually serve a model.
+
+    whisper.cpp (gguf) only accepts curated ids, which Transformers serves too,
+    so when whisper-server is not installed (the common case: `unsloth studio
+    update` does not yet build it) fall back to Transformers instead of 501-ing
+    on every recording. Used for download/load/transcribe; unload targets a
+    specific engine via _resolve_stt_engine.
+    """
+    resolved = _resolve_stt_engine(engine)
+    if resolved == "gguf":
+        from core.inference import stt_ggml_sidecar
+        if not stt_ggml_sidecar.is_available():
+            return "transformers"
+    return resolved
+
+
+def _stt_sidecar_for(engine: str):
+    if engine == "gguf":
+        from core.inference.stt_ggml_sidecar import get_ggml_stt_sidecar
+        return get_ggml_stt_sidecar()
+    from core.inference.stt_sidecar import get_stt_sidecar
+    return get_stt_sidecar()
+
+
+@studio_router.get("/audio/stt/status")
+async def stt_status(
+    model: Optional[str] = None, current_subject: str = Depends(get_current_subject)
+):
+    """Report STT availability and which model, if any, is resident.
+
+    ``model`` extends the Transformers ``downloaded_models`` check to a
+    custom Hugging Face repository beyond the curated defaults.
+    """
+    from core.inference import stt_ggml_sidecar, stt_sidecar
+    from core.inference.stt_sidecar import (
+        DEFAULT_STT_MODEL,
+        STT_MODELS,
+        get_stt_sidecar,
+        is_available,
+    )
+
+    sidecar = get_stt_sidecar()
+    ggml = stt_ggml_sidecar.get_ggml_stt_sidecar()
+    transformers_downloaded = [
+        model_id for model_id in STT_MODELS if stt_sidecar.is_model_downloaded(model_id)
+    ]
+    if model and model not in STT_MODELS and stt_sidecar.is_model_downloaded(model):
+        transformers_downloaded.append(model)
+    return JSONResponse(
+        content = {
+            "available": is_available(),
+            "loaded_model": sidecar.loaded_model,
+            "loading": sidecar.is_loading(),
+            "device": sidecar.device,
+            "keep_alive_seconds": sidecar.keep_alive_seconds,
+            "default_model": DEFAULT_STT_MODEL,
+            "models": list(STT_MODELS.keys()),
+            # Transformers engine, same shape as "gguf" below so clients read
+            # either generically. Top-level fields above kept for old clients.
+            "transformers": {
+                "available": is_available(),
+                "loaded_model": sidecar.loaded_model,
+                "loading": sidecar.is_loading(),
+                "device": sidecar.device,
+                "keep_alive_seconds": sidecar.keep_alive_seconds,
+                "default_model": DEFAULT_STT_MODEL,
+                "models": list(STT_MODELS.keys()),
+                "downloaded_models": transformers_downloaded,
+                "download": stt_sidecar.download_status(),
+            },
+            # whisper.cpp (GGUF) engine.
+            "gguf": {
+                "available": stt_ggml_sidecar.is_available(),
+                "loaded_model": ggml.loaded_model,
+                "loading": ggml.is_loading(),
+                "device": ggml.device,
+                "keep_alive_seconds": ggml.keep_alive_seconds,
+                "default_model": stt_ggml_sidecar.DEFAULT_GGML_STT_MODEL,
+                "models": list(stt_ggml_sidecar.GGML_STT_MODELS.keys()),
+                "downloaded_models": [
+                    model_id
+                    for model_id in stt_ggml_sidecar.GGML_STT_MODELS
+                    if stt_ggml_sidecar._cached_model_path(model_id) is not None
+                ],
+                "download": stt_ggml_sidecar.download_status(),
+            },
+        }
+    )
+
+
+@studio_router.post("/audio/stt/download")
+async def stt_download(
+    payload: SttLoadRequest,
+    current_subject: str = Depends(get_current_subject),
+    hf_token: Optional[str] = Depends(get_hf_token),
+):
+    """Start a background download of a dictation model.
+
+    Both engines download directly (a GGML checkpoint is a single file the Model
+    Hub's GGUF variant planner cannot express; a Transformers checkpoint is a
+    whole snapshot). Progress is reported by /audio/stt/status.
+    """
+    from core.inference import stt_ggml_sidecar, stt_sidecar
+    from core.inference.stt_sidecar import (
+        SttModelCompatibilityError,
+        SttModelIdError,
+        validate_remote_model,
+    )
+
+    engine = _resolve_serving_stt_engine(payload.engine)
+    module = stt_ggml_sidecar if engine == "gguf" else stt_sidecar
+    try:
+        # Transformers accepts custom `owner/model` repos, so confirm the repo is
+        # a Whisper checkpoint (metadata-only) before snapshot_download pulls a
+        # possibly-large non-STT repo into the shared cache. Curated ids
+        # short-circuit; GGUF only accepts curated ids, so it needs no check.
+        if engine != "gguf":
+            validated = await asyncio.to_thread(validate_remote_model, payload.model, hf_token)
+            # Pin the download to the commit that was just validated so the
+            # repo cannot be swapped between validation and snapshot_download.
+            await asyncio.to_thread(
+                module.start_model_download,
+                payload.model,
+                hf_token,
+                validated.get("revision"),
+            )
+        else:
+            await asyncio.to_thread(module.start_model_download, payload.model, hf_token)
+    except SttModelIdError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    except SttModelCompatibilityError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    return JSONResponse(content = module.download_status())
+
+
+@studio_router.post("/audio/stt/load")
+async def stt_load(payload: SttLoadRequest, current_subject: str = Depends(get_current_subject)):
+    """Load the selected STT model after the user starts local dictation."""
+    from core.inference.stt_sidecar import (
+        SttLoadCancelledError,
+        SttModelCompatibilityError,
+        SttModelIdError,
+        SttModelNotDownloadedError,
+        SttUnavailableError,
+        get_stt_sidecar,
+    )
+
+    sidecar = _stt_sidecar_for(_resolve_serving_stt_engine(payload.engine))
+    try:
+        await asyncio.to_thread(sidecar.load, payload.model)
+    except SttModelNotDownloadedError as e:
+        raise HTTPException(status_code = 409, detail = str(e))
+    except SttUnavailableError as e:
+        raise HTTPException(status_code = 501, detail = str(e))
+    except SttLoadCancelledError as e:
+        raise HTTPException(status_code = 409, detail = str(e))
+    except SttModelIdError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    except SttModelCompatibilityError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    except Exception as e:
+        logger.error(f"STT load error: {e}", exc_info = True)
+        raise HTTPException(status_code = 500, detail = safe_error_detail(e))
+    return JSONResponse(content = {"loaded_model": sidecar.loaded_model, "device": sidecar.device})
+
+
+@studio_router.post("/audio/stt/validate")
+async def stt_validate(
+    payload: SttLoadRequest,
+    current_subject: str = Depends(get_current_subject),
+    hf_token: Optional[str] = Depends(get_hf_token),
+):
+    """Verify a Hub repository is a Whisper checkpoint before downloading it."""
+    from core.inference.stt_sidecar import (
+        SttModelCompatibilityError,
+        SttModelIdError,
+        validate_remote_model,
+    )
+
+    try:
+        result = await asyncio.to_thread(validate_remote_model, payload.model, hf_token)
+    except (SttModelIdError, SttModelCompatibilityError) as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    return JSONResponse(content = result)
+
+
+@studio_router.post("/audio/stt/unload")
+async def stt_unload(
+    engine: Optional[str] = None, current_subject: str = Depends(get_current_subject)
+):
+    """Release the local STT model when dictation is idle.
+
+    Without an engine, both sidecars unload so an engine switch in Voice
+    settings always frees whichever backend was resident.
+    """
+    if engine is None:
+        engines = ["transformers", "gguf"]
+    else:
+        # Use the serving resolver: a "gguf" pick without whisper-server is
+        # actually served by the Transformers fallback, so unload must target
+        # that same engine or the resident model is never freed.
+        engines = [_resolve_serving_stt_engine(engine)]
+    # Attempt every engine even if one raises, so failing to unload one never
+    # skips freeing the other (both can be resident after a switch).
+    failed: list[str] = []
+    for name in engines:
+        try:
+            await asyncio.to_thread(_stt_sidecar_for(name).unload)
+        except Exception as exc:  # noqa: BLE001 - report after attempting all engines
+            logger.warning("Failed to unload STT engine '%s': %s", name, exc)
+            failed.append(name)
+    if failed:
+        raise HTTPException(
+            status_code = 500,
+            detail = f"Failed to unload STT engine(s): {', '.join(failed)}",
+        )
+    return JSONResponse(content = {"loaded_model": None, "device": None})
+
+
+async def _transcribe_audio_bytes(
+    raw: bytes,
+    model: Optional[str],
+    language: Optional[str],
+    fast: bool,
+    engine: Optional[str] = None,
+) -> JSONResponse:
+    """Run STT for already-decoded request bytes."""
+    from core.inference.stt_sidecar import (
+        SttAudioDecodeError,
+        SttAudioTooLongError,
+        SttLanguageError,
+        SttLoadCancelledError,
+        SttModelCompatibilityError,
+        SttModelIdError,
+        SttModelNotDownloadedError,
+        SttUnavailableError,
+    )
+
+    if not raw:
+        raise HTTPException(status_code = 400, detail = "Audio is empty.")
+    if len(raw) > _MAX_AUDIO_RAW_BYTES:
+        raise HTTPException(status_code = 413, detail = "Audio is too large.")
+
+    sidecar = _stt_sidecar_for(_resolve_serving_stt_engine(engine))
+    try:
+        result = await asyncio.to_thread(
+            sidecar.transcribe,
+            raw,
+            model,
+            language,
+            fast,
+        )
+    except SttUnavailableError as e:
+        raise HTTPException(status_code = 501, detail = str(e))
+    except SttLoadCancelledError as e:
+        raise HTTPException(status_code = 409, detail = str(e))
+    except SttModelNotDownloadedError as e:
+        raise HTTPException(status_code = 409, detail = str(e))
+    except SttModelIdError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    except SttModelCompatibilityError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    except SttLanguageError as e:
+        raise HTTPException(status_code = 422, detail = str(e))
+    except SttAudioTooLongError as e:
+        raise HTTPException(status_code = 413, detail = str(e))
+    except SttAudioDecodeError as e:
+        raise HTTPException(status_code = 400, detail = str(e))
+    except Exception as e:
+        logger.error(f"Transcription error: {e}", exc_info = True)
+        raise HTTPException(status_code = 500, detail = safe_error_detail(e))
+    return JSONResponse(content = result)
+
+
+@studio_router.post("/audio/transcribe")
+async def transcribe_audio(
+    payload: TranscribeRequest, current_subject: str = Depends(get_current_subject)
+):
+    """Transcribe dictation audio to text via the STT sidecar.
+
+    Runs alongside the chat model without evicting it, so any model (including
+    text-only ones) can be driven by voice.
+    """
+    b64 = payload.audio or ""
+    if not b64:
+        raise HTTPException(status_code = 400, detail = "No audio provided.")
+    if len(b64) > _MAX_AUDIO_B64_CHARS:
+        raise HTTPException(status_code = 413, detail = "Audio is too large.")
+    try:
+        raw = base64.b64decode(b64, validate = True)
+    except Exception:
+        raise HTTPException(status_code = 400, detail = "Audio is not valid base64.")
+    return await _transcribe_audio_bytes(
+        raw, payload.model, payload.language, payload.fast, payload.engine
+    )
+
+
+@studio_router.post("/audio/transcribe/raw")
+async def transcribe_audio_raw(
+    request: Request,
+    model: Optional[str] = None,
+    language: Optional[str] = None,
+    fast: bool = False,
+    engine: Optional[str] = None,
+    current_subject: str = Depends(get_current_subject),
+):
+    """Transcribe a raw audio body without base64 or JSON conversion overhead."""
+    chunks: list[bytes] = []
+    size = 0
+    async for chunk in request.stream():
+        size += len(chunk)
+        if size > _MAX_AUDIO_RAW_BYTES:
+            raise HTTPException(status_code = 413, detail = "Audio is too large.")
+        chunks.append(chunk)
+    return await _transcribe_audio_bytes(b"".join(chunks), model, language, fast, engine)
+
+
 # =====================================================================
 # OpenAI-Compatible Chat Completions  (/chat/completions)
 # =====================================================================
@@ -6148,8 +6494,8 @@ def _decode_audio_base64(b64: str) -> np.ndarray:
 # cap the encoded length to bound the upload. _MAX_AUDIO_SECONDS additionally
 # bounds the *decoded* length, since a small compressed file (opus/flac/etc.)
 # can expand to a far larger PCM array than the encoded-size cap implies.
-_MAX_AUDIO_RAW_BYTES = 25 * 1024 * 1024
-_MAX_AUDIO_B64_CHARS = _MAX_AUDIO_RAW_BYTES * 4 // 3
+_MAX_AUDIO_RAW_BYTES = STT_AUDIO_RAW_MAX_BYTES
+_MAX_AUDIO_B64_CHARS = STT_AUDIO_B64_MAX_CHARS
 _MAX_AUDIO_SECONDS = 30 * 60
 _WAV_HEADER_BYTES = 44
 _MIN_TRANSCODE_AUDIO_SAMPLE_RATE = 8000
@@ -7078,7 +7424,7 @@ async def openai_chat_completions(
     if payload.provider_id or payload.provider_type:
         # External provider: this request won't touch the local GGUF, so drop it
         # from the keep-warm count or its in-flight stream would falsely block a
-        # concurrent local auto-switch with model_switch_busy.
+        # concurrent local model switch from proceeding.
         from core.inference.llama_keepwarm import untrack_current_request
 
         untrack_current_request(request.scope)
diff --git a/studio/backend/routes/llama.py b/studio/backend/routes/llama.py
index 540647e3bc..84b89ad7d5 100644
--- a/studio/backend/routes/llama.py
+++ b/studio/backend/routes/llama.py
@@ -1,7 +1,7 @@
 # SPDX-License-Identifier: AGPL-3.0-only
 # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-"""llama.cpp prebuilt update endpoints.
+"""llama.cpp prebuilt update endpoints -- the single main update item.
 
 GET  /api/llama/update-status  -> is a newer prebuilt available + job state
 POST /api/llama/update         -> download + atomically swap to the latest
@@ -9,13 +9,19 @@ POST /api/llama/update         -> download + atomically swap to the latest
 Detection reuses utils.llama_cpp_freshness; the swap reuses
 install_llama_prebuilt.py via utils.llama_cpp_update. Both fail open so the UI
 never blocks on a missing marker / offline GitHub.
+
+whisper.cpp updates piggyback here: the status payload carries a whisper
+sub-status (update_available is the llama OR whisper union) and the apply job
+chains a whisper phase after the llama phase when whisper is behind, with a
+per-phase breakdown in job.phases. All pre-existing top-level fields keep
+their shape, so older clients keep working unchanged.
 """
 
 from __future__ import annotations
 
 import asyncio
 import threading
-from typing import Optional
+from typing import Literal, Optional
 
 from fastapi import APIRouter, Depends, Query
 from pydantic import BaseModel, Field
@@ -38,6 +44,31 @@ class LlamaUpdateJob(BaseModel):
     progress: Optional[float] = Field(None, description = "0..1 while running, 1 on success.")
     started_at: Optional[str] = None
     finished_at: Optional[str] = None
+    phases: Optional[dict] = Field(
+        None,
+        description = (
+            "Per-phase breakdown of a chained llama+whisper job "
+            "(name -> state/progress/to_tag/...); None for pre-chaining jobs."
+        ),
+    )
+
+
+class WhisperSubStatus(BaseModel):
+    """The whisper piggyback inside the llama update item."""
+
+    update_available: bool = Field(
+        False, description = "True when the chained apply would run a whisper phase."
+    )
+    installed_tag: Optional[str] = None
+    latest_tag: Optional[str] = None
+    update_size_bytes: Optional[int] = None
+    skip_reason: Optional[str] = Field(
+        None,
+        description = (
+            "Why the whisper phase would be skipped "
+            "(up_to_date | local_link | source_build | not_installed | ...)."
+        ),
+    )
 
 
 class LlamaUpdateStatusResponse(BaseModel):
@@ -46,7 +77,18 @@ class LlamaUpdateStatusResponse(BaseModel):
         description = "True when the install came from an Unsloth prebuilt (has a marker).",
     )
     update_available: bool = Field(
-        False, description = "True when the latest release is genuinely newer than the install."
+        False,
+        description = (
+            "True when an update would do something: llama.cpp is behind OR the "
+            "whisper piggyback is behind."
+        ),
+    )
+    llama_update_available: bool = Field(
+        False, description = "True when the latest llama.cpp release is newer than the install."
+    )
+    update_component: Optional[Literal["llama", "whisper"]] = Field(
+        None,
+        description = "Component whose versions the combined update banner should display.",
     )
     stale: bool = Field(
         False, description = "Update available AND install older than the staleness threshold."
@@ -62,6 +104,9 @@ class LlamaUpdateStatusResponse(BaseModel):
     update_size_bytes: Optional[int] = Field(
         None, description = "Download size of the prebuilt Update would fetch, in bytes."
     )
+    whisper: Optional[WhisperSubStatus] = Field(
+        None, description = "Whisper piggyback sub-status; None when the probe is unavailable."
+    )
     job: LlamaUpdateJob = Field(default_factory = LlamaUpdateJob)
 
 
diff --git a/studio/backend/routes/models.py b/studio/backend/routes/models.py
index 0806c2f513..3c0d6ff4ba 100644
--- a/studio/backend/routes/models.py
+++ b/studio/backend/routes/models.py
@@ -60,13 +60,52 @@ def _safe_is_dir(path) -> bool:
 
 
 # Shared with the hub inventory scans; keep the private aliases so existing
-# importers (core.inference.local_model_resolver, tests) stay valid.
+# importers stay valid. ``_HF_REPO_ID_RE`` is the Hub repo id shape ("owner/name");
+# anything else is treated as a local filesystem path.
 from utils.hidden_models import (
+    _HF_REPO_ID_RE,
+    _existing_resolved_path,
     _safe_resolve,
     is_hidden_model as _is_hidden_model,
 )
 
 
+def hidden_model_matchers() -> tuple[list[str], list[str], list[str]]:
+    """Substring needles, exact repo ids, and exact resolved paths identifying
+    infra models (the RAG embedder and the llama.cpp install validation probe)
+    that pickers hide. Served by the ``/api/hub/hidden-models`` endpoint. A
+    configured HF-repo embedder is published as its exact lowercased repo id
+    (mirroring ``utils.hidden_models.is_hidden_model``) and a local-path
+    embedder as its exact resolved path only: a generic basename like "model"
+    must not substring-hide unrelated chat models."""
+    from core.rag import config as rag_config
+
+    needles = [
+        # The validation probe's repo and its exact filename. The filename carries
+        # .gguf so it won't hide unrelated repos like ``user/stories260K-finetune-GGUF``.
+        "ggml-org/models",
+        "stories260k.gguf",
+    ]
+    exact_ids: list[str] = []
+    exact_paths: list[str] = []
+    for model in (
+        rag_config.effective_embedding_model(),
+        rag_config.effective_gguf_repo(),
+    ):
+        # Resolve an existing local path before the repo-id regex: a local embedder
+        # shaped like "models/embedder" is an exact path, not a Hub repo id.
+        existing_path = _existing_resolved_path(model)
+        if existing_path:
+            exact_paths.append(existing_path.lower())
+        elif _HF_REPO_ID_RE.match(model):
+            exact_ids.append(model.lower())
+        else:
+            resolved = _safe_resolve(Path(model).expanduser())
+            if resolved:
+                exact_paths.append(resolved.lower())
+    return needles, exact_ids, exact_paths
+
+
 backend_path = Path(__file__).parent.parent.parent
 if str(backend_path) not in sys.path:
     sys.path.insert(0, str(backend_path))
@@ -91,6 +130,7 @@ try:
         _pick_best_gguf,
         _extract_quant_label,
         _is_big_endian_gguf_path,
+        _is_mtp_drafter,
         is_audio_input_type,
     )
     from core.inference import get_inference_backend
@@ -123,6 +163,7 @@ except ImportError:
         _pick_best_gguf,
         _extract_quant_label,
         _is_big_endian_gguf_path,
+        _is_mtp_drafter,
         is_audio_input_type,
     )
     from core.inference import get_inference_backend
@@ -183,11 +224,8 @@ def derive_model_type(
 
 def _resolve_hf_cache_dir() -> Path:
     """Resolve local HF cache root used by hub downloads."""
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-        return Path(HF_HUB_CACHE)
-    except Exception:
-        return Path.home() / ".cache" / "huggingface" / "hub"
+    from utils.hf_cache_settings import get_hf_cache_paths
+    return get_hf_cache_paths().hub_cache
 
 
 def _is_model_directory(d: Path) -> bool:
@@ -329,10 +367,12 @@ def _scan_models_dir(models_dir: Path, *, limit: int | None = None) -> List[Loca
     return found
 
 
-def _scan_hf_cache(cache_dir: Path) -> List[LocalModelInfo]:
+def _scan_hf_cache(cache_dir: Path, *, active_cache: bool = True) -> List[LocalModelInfo]:
     if not cache_dir.exists() or not cache_dir.is_dir():
         return []
 
+    from hub.utils import inventory_scan as hf_cache_scan
+
     found: List[LocalModelInfo] = []
     for repo_dir in cache_dir.glob("models--*"):
         if not repo_dir.is_dir():
@@ -348,13 +388,21 @@ def _scan_hf_cache(cache_dir: Path) -> List[LocalModelInfo]:
         except OSError:
             updated_at = None
 
+        partial = hf_cache_scan.is_snapshot_partial("model", model_id, repo_dir)
+        partial = partial or hf_cache_scan.is_gguf_repo_partial(model_id, repo_dir)
+
+        load_id = model_id
+        if not active_cache:
+            load_id = _resolve_hf_cache_realpath(repo_dir) or str(repo_dir.resolve())
         found.append(
             LocalModelInfo(
-                id = model_id,
+                id = load_id,
                 model_id = model_id,
                 display_name = model_id.split("/")[-1],
-                path = str(repo_dir),
+                path = load_id if not active_cache else str(repo_dir),
                 source = "hf_cache",
+                active_cache = active_cache,
+                partial = partial,
                 updated_at = updated_at,
             ),
         )
@@ -735,26 +783,34 @@ def collect_local_models(models_root: Path) -> List[LocalModelInfo]:
         legacy_hf_cache_dir,
         lmstudio_model_dirs,
     )
+    from utils.hf_cache_settings import known_hf_hub_caches
 
     hf_cache_dir = _resolve_hf_cache_dir()
     legacy_hf = legacy_hf_cache_dir()
     hf_default = hf_default_cache_dir()
     lm_dirs = lmstudio_model_dirs()
 
-    local_models = _scan_models_dir(models_root) + _scan_hf_cache(hf_cache_dir)
-
-    # Resolve once; an inaccessible aux cache must skip that scan, not 500.
-    hf_cache_real = _safe_resolve(hf_cache_dir)
-    legacy_real = _safe_resolve(legacy_hf)
-    default_real = _safe_resolve(hf_default)
-
-    # Scan legacy Unsloth HF cache for backward compatibility.
-    if _safe_is_dir(legacy_hf) and legacy_real != hf_cache_real:
-        local_models += _scan_hf_cache(legacy_hf)
-
-    # Scan HF system default cache (may differ under env overrides).
-    if _safe_is_dir(hf_default) and default_real != hf_cache_real and default_real != legacy_real:
-        local_models += _scan_hf_cache(hf_default)
+    local_models = _scan_models_dir(models_root)
+    active_cache_real = _safe_resolve(hf_cache_dir)
+    active_cache_key = os.path.normcase(active_cache_real) if active_cache_real else None
+    seen_hf: set[str] = set()
+    for cache_dir in (
+        hf_cache_dir,
+        *known_hf_hub_caches(),
+        legacy_hf,
+        hf_default,
+    ):
+        cache_real = _safe_resolve(cache_dir)
+        if cache_real is None:
+            continue
+        cache_key = os.path.normcase(str(cache_real))
+        if cache_key in seen_hf:
+            continue
+        seen_hf.add(cache_key)
+        local_models += _scan_hf_cache(
+            cache_dir,
+            active_cache = cache_key == active_cache_key,
+        )
 
     # Scan LM Studio directories.
     for lm_dir in lm_dirs:
@@ -776,7 +832,7 @@ def collect_local_models(models_root: Path) -> List[LocalModelInfo]:
                 m
                 for m in (
                     _scan_models_dir(folder_path, limit = _MAX_MODELS_PER_FOLDER)
-                    + _scan_hf_cache(folder_path)
+                    + _scan_hf_cache(folder_path, active_cache = False)
                     + _scan_lmstudio_dir(folder_path)
                 )
                 if not any(p in (".studio_links", "ollama_links") for p in Path(m.path).parts)
@@ -797,13 +853,23 @@ def collect_local_models(models_root: Path) -> List[LocalModelInfo]:
     # even when the model is also in the HF cache.
     deduped: dict[str, LocalModelInfo] = {}
     for model in local_models:
-        key = f"{model.id}\x00custom" if model.source == "custom" else model.id
-        if key not in deduped:
+        semantic_id = model.model_id if model.source == "hf_cache" and model.model_id else model.id
+        key = f"{semantic_id}\x00custom" if model.source == "custom" else semantic_id
+        existing = deduped.get(key)
+        prefer_model = existing is None
+        if existing is not None and model.source == existing.source == "hf_cache":
+            if model.partial != existing.partial:
+                prefer_model = not model.partial
+            elif bool(model.active_cache) != bool(existing.active_cache):
+                prefer_model = bool(model.active_cache)
+            else:
+                prefer_model = (model.updated_at or 0) > (existing.updated_at or 0)
+        if prefer_model:
             deduped[key] = model
 
     models = sorted(
         deduped.values(),
-        key = lambda item: (item.updated_at or 0),
+        key = lambda item: item.updated_at or 0,
         reverse = True,
     )
     return [m for m in models if not _is_hidden_model(m.id, m.model_id, m.path)]
@@ -1161,10 +1227,7 @@ def _build_browse_allowlist(
         legacy_hf_cache_dir,
         well_known_model_dirs,
     )
-    from utils.paths.external_media import (
-        linux_run_media_mount_roots,
-        windows_drive_roots,
-    )
+    from utils.paths import external_media
     from storage.studio_db import list_scan_folders
 
     candidates: list[Path] = []
@@ -1181,9 +1244,12 @@ def _build_browse_allowlist(
 
     _add(Path.home())
     if media_roots is None:
-        media_roots = linux_run_media_mount_roots()
+        media_roots = [
+            *external_media.linux_run_media_mount_roots(),
+            *external_media.macos_volume_roots(),
+        ]
     if drive_roots is None:
-        drive_roots = windows_drive_roots()
+        drive_roots = external_media.windows_drive_roots()
     for p in media_roots:
         _add(p)
     for p in drive_roots:
@@ -1461,10 +1527,7 @@ def browse_folders(
     then hidden (if ``show_hidden=true``).
     """
     from utils.paths import hf_default_cache_dir, well_known_model_dirs
-    from utils.paths.external_media import (
-        linux_run_media_mount_roots,
-        windows_drive_roots,
-    )
+    from utils.paths import external_media
     from storage.studio_db import (
         contains_sensitive_path_component,
         is_denied_system_path,
@@ -1473,8 +1536,11 @@ def browse_folders(
 
     # Probe removable-media and Windows drive roots once; the allowlist and
     # chips reuse the result so a disconnected mapped drive isn't scanned twice.
-    media_roots = linux_run_media_mount_roots()
-    drive_roots = windows_drive_roots()
+    media_roots = [
+        *external_media.linux_run_media_mount_roots(),
+        *external_media.macos_volume_roots(),
+    ]
+    drive_roots = external_media.windows_drive_roots()
     # Build once; the sandbox check and suggestion chips share it.
     allowed_roots = _build_browse_allowlist(media_roots, drive_roots)
 
@@ -1750,9 +1816,11 @@ def _get_model_size_bytes(model_name: str, hf_token: Optional[str] = None) -> Op
 async def get_model_config(
     model_name: str,
     hf_token: Optional[str] = Query(None),
+    header_hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
     """Get configuration for a specific model (wraps load_model_defaults)."""
+    hf_token = _normalize_hf_token(header_hf_token) or _normalize_hf_token(hf_token)
     try:
         if not is_local_path(model_name):
             resolved = resolve_cached_repo_id_case(model_name)
@@ -1991,19 +2059,19 @@ async def discard_remote_code_download(
 
     # Never delete a model that is loaded for inference.
     try:
+        from hub.services.models.deletion import _loaded_id_matches_repo
         from routes.inference import get_llama_cpp_backend
+
         llama_backend = get_llama_cpp_backend()
         if llama_backend.is_loaded and llama_backend.model_identifier:
-            loaded = llama_backend.model_identifier.lower()
-            if loaded == model_name.lower() or loaded.startswith(model_name.lower()):
+            if _loaded_id_matches_repo(llama_backend.model_identifier, model_name):
                 return {"deleted": False, "reason": "loaded"}
     except Exception:
         pass
     try:
         inference_backend = get_inference_backend()
         if inference_backend.active_model_name:
-            active = inference_backend.active_model_name.lower()
-            if active == model_name.lower() or active.startswith(model_name.lower()):
+            if _loaded_id_matches_repo(inference_backend.active_model_name, model_name):
                 return {"deleted": False, "reason": "loaded"}
     except Exception:
         pass
@@ -2471,6 +2539,7 @@ async def get_lora_base_model(lora_path: str, current_subject: str = Depends(get
 async def check_vision_model(
     model_name: str,
     hf_token: Optional[str] = Query(None),
+    header_hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
     """
@@ -2478,6 +2547,7 @@ async def check_vision_model(
 
     This endpoint wraps the backend is_vision_model function.
     """
+    hf_token = _normalize_hf_token(header_hf_token) or _normalize_hf_token(hf_token)
     try:
         logger.info(f"Checking if vision model: {model_name}")
         # Authenticate so a gated/private VLM classifies correctly (else 404 -> non-vision).
@@ -2503,6 +2573,7 @@ async def check_vision_model(
 async def check_embedding_model(
     model_name: str,
     hf_token: Optional[str] = Query(None),
+    header_hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
     """
@@ -2510,6 +2581,7 @@ async def check_embedding_model(
 
     This endpoint wraps the backend is_embedding_model function.
     """
+    hf_token = _normalize_hf_token(header_hf_token) or _normalize_hf_token(hf_token)
     try:
         logger.info(f"Checking if embedding model: {model_name}")
         is_embedding = is_embedding_model(model_name, hf_token = hf_token)
@@ -2541,13 +2613,10 @@ def _read_native_context_length(repo_id: str, is_local: bool) -> Optional[int]:
         if is_local:
             roots = [Path(repo_id)]
         else:
-            from huggingface_hub import constants as hf_constants
-
+            from hub.utils.hf_cache_state import iter_repo_cache_dirs
             if not _is_valid_repo_id(repo_id):
                 return None
-            cache_dir = Path(hf_constants.HF_HUB_CACHE)
-            target = f"models--{repo_id.replace('/', '--')}".lower()
-            roots = [e for e in cache_dir.iterdir() if e.name.lower() == target]
+            roots = list(iter_repo_cache_dirs("model", repo_id))
 
         for root in roots:
             for f in _iter_gguf_paths(root):
@@ -2573,47 +2642,32 @@ def _resolve_quant_gguf(repo_id: str, quant: str, is_local: bool) -> tuple[Optio
     Q8_0 weights). Never raises.
     """
     try:
-        from utils.models.model_config import (
-            _extract_quant_label,
-            _is_big_endian_gguf_path,
-            _is_mtp_drafter,
-        )
-
         if is_local:
             roots = [Path(repo_id)]
         else:
-            from huggingface_hub import constants as hf_constants
+            from hub.utils.hf_cache_state import iter_repo_cache_dirs
 
             if not _is_valid_repo_id(repo_id):
                 return None, 0
-            cache_dir = Path(hf_constants.HF_HUB_CACHE)
-            target = f"models--{repo_id.replace('/', '--')}".lower()
             roots = []
-            for entry in cache_dir.iterdir():
-                if entry.name.lower() == target:
-                    snaps = entry / "snapshots"
-                    if snaps.is_dir():
-                        roots.extend(s for s in snaps.iterdir() if s.is_dir())
+            for entry in iter_repo_cache_dirs("model", repo_id):
+                snaps = entry / "snapshots"
+                if snaps.is_dir():
+                    roots.extend(s for s in snaps.iterdir() if s.is_dir())
 
-        want = quant.lower().replace("-", "").replace("_", "")
+        want = _normalized_quant_label(quant)
         best_total = 0
         best_first: Optional[str] = None
         for root in roots:
             matches: list[tuple[str, Path]] = []
             total = 0
             for f in _iter_gguf_paths(root):
-                if _is_mmproj_filename(f.name):
-                    continue
                 try:
                     rel = f.relative_to(root).as_posix()
                 except ValueError:
                     rel = f.name
-                if _is_mtp_drafter(rel):
-                    continue
-                q = _extract_quant_label(rel)
-                if _is_big_endian_gguf_path(rel, q):
-                    continue
-                if q.lower().replace("-", "").replace("_", "") != want:
+                q = _main_variant_gguf_label(rel)
+                if q is None or _normalized_quant_label(q) != want:
                     continue
                 try:
                     total += f.stat().st_size
@@ -2699,6 +2753,8 @@ async def get_gguf_variants(
     repo_id: str = Query(
         ..., description = "HuggingFace repo ID (e.g. 'unsloth/gemma-3-4b-it-GGUF')"
     ),
+    prefer_local_cache: bool = False,
+    local_path: Optional[str] = None,
     hf_token: Optional[str] = Query(None, description = "HuggingFace token for private repos"),
     hf_token_header: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
@@ -2710,9 +2766,16 @@ async def get_gguf_variants(
 
         response = await hub_gguf_variants.get_gguf_variants_response(
             repo_id,
+            prefer_local_cache = prefer_local_cache,
+            local_path = local_path,
             hf_token = hf_token,
         )
-        local = is_local_path(repo_id)
+        context_model = (
+            local_path
+            if prefer_local_cache and local_path and is_local_path(local_path)
+            else repo_id
+        )
+        local = is_local_path(context_model)
 
         return GgufVariantsResponse(
             repo_id = response.repo_id,
@@ -2734,7 +2797,7 @@ async def get_gguf_variants(
             # The header walk reads tokenizer arrays on dense models (tens of
             # ms per uncached file); keep it off the event loop.
             context_length = await asyncio.to_thread(
-                _read_native_context_length, repo_id, is_local = local
+                _read_native_context_length, context_model, is_local = local
             ),
         )
     except HTTPException:
@@ -2752,69 +2815,17 @@ async def get_gguf_download_progress(
     repo_id: str = Query(..., description = "HuggingFace repo ID"),
     variant: str = Query("", description = "Quantization variant (e.g. UD-TQ1_0)"),
     expected_bytes: int = Query(0, description = "Expected total download size in bytes"),
+    hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
-    """Download progress from cached GGUF files for a specific variant.
-
-    Tracks completed shards in snapshots and in-progress (.incomplete)
-    downloads in the blobs directory.
-    """
-    try:
-        if not _is_valid_repo_id(repo_id):
-            return {
-                "downloaded_bytes": 0,
-                "expected_bytes": expected_bytes,
-                "progress": 0,
-            }
-
-        from huggingface_hub import constants as hf_constants
-
-        cache_dir = Path(hf_constants.HF_HUB_CACHE)
-        target = f"models--{repo_id.replace('/', '--')}".lower()
-        variant_lower = variant.lower().replace("-", "").replace("_", "")
-        downloaded_bytes = 0
-        in_progress_bytes = 0
-        for entry in cache_dir.iterdir():
-            if entry.name.lower() == target:
-                # Completed .gguf files for this variant in snapshots.
-                # Exclude mmproj so a vision adapter can't satisfy a same-label
-                # main variant (e.g. mmproj-F16 vs an F16 weight).
-                for f in _iter_gguf_paths(entry):
-                    if _is_mmproj_filename(f.name):
-                        continue
-                    rel = f.relative_to(entry).as_posix()
-                    quant = _extract_quant_label(rel)
-                    if _is_big_endian_gguf_path(rel, quant):
-                        continue
-                    rel_key = rel.lower().replace("-", "").replace("_", "")
-                    if not variant_lower or variant_lower in rel_key:
-                        try:
-                            downloaded_bytes += f.stat().st_size
-                        except OSError:
-                            continue  # broken symlink / unreadable: skip
-                # In-progress (.incomplete) downloads in blobs.
-                blobs_dir = entry / "blobs"
-                if blobs_dir.is_dir():
-                    for f in blobs_dir.iterdir():
-                        if f.is_file() and f.name.endswith(".incomplete"):
-                            try:
-                                in_progress_bytes += f.stat().st_size
-                            except OSError:
-                                continue
-                break
-
-        total_progress_bytes = downloaded_bytes + in_progress_bytes
-        progress = min(total_progress_bytes / expected_bytes, 0.99) if expected_bytes > 0 else 0
-        # Report 1.0 only when all bytes are in completed files.
-        if expected_bytes > 0 and downloaded_bytes >= expected_bytes:
-            progress = 1.0
-        return {
-            "downloaded_bytes": total_progress_bytes,
-            "expected_bytes": expected_bytes,
-            "progress": round(progress, 3),
-        }
-    except Exception:
-        return {"downloaded_bytes": 0, "expected_bytes": expected_bytes, "progress": 0}
+    """Compatibility route backed by the shared multi-cache progress service."""
+    from hub.services.models import downloads
+    return await downloads.get_gguf_download_progress_response(
+        repo_id,
+        variant = variant,
+        expected_bytes = expected_bytes,
+        hf_token = hf_token,
+    )
 
 
 def _resolve_hf_cache_realpath(repo_dir: Path) -> Optional[str]:
@@ -2839,98 +2850,12 @@ def _resolve_hf_cache_realpath(repo_dir: Path) -> Optional[str]:
 @router.get("/download-progress")
 async def get_download_progress(
     repo_id: str = Query(..., description = "HuggingFace repo ID"),
+    hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
-    """Return download progress for any HuggingFace model repo.
-
-    Checks the local HF cache for completed blobs and in-progress
-    (.incomplete) downloads. Gets the expected total size from the HF API
-    on the first call, then caches it for later polls. Also returns
-    ``cache_path``: the realpath of the snapshot dir (or cache repo root
-    if no snapshot yet) so the UI can show where weights live on disk.
-    """
-    _empty = {
-        "downloaded_bytes": 0,
-        "expected_bytes": 0,
-        "progress": 0,
-        "cache_path": None,
-    }
-    try:
-        if not _is_valid_repo_id(repo_id):
-            return _empty
-
-        from huggingface_hub import constants as hf_constants
-
-        cache_dir = Path(hf_constants.HF_HUB_CACHE)
-        target = f"models--{repo_id.replace('/', '--')}".lower()
-        completed_bytes = 0
-        in_progress_bytes = 0
-        cache_path: Optional[str] = None
-
-        for entry in cache_dir.iterdir():
-            if entry.name.lower() != target:
-                continue
-            cache_path = _resolve_hf_cache_realpath(entry)
-            blobs_dir = entry / "blobs"
-            if not blobs_dir.is_dir():
-                break
-            for f in blobs_dir.iterdir():
-                if not f.is_file():
-                    continue
-                if f.name.endswith(".incomplete"):
-                    in_progress_bytes += f.stat().st_size
-                else:
-                    completed_bytes += f.stat().st_size
-            break
-
-        downloaded_bytes = completed_bytes + in_progress_bytes
-        if downloaded_bytes == 0:
-            return {**_empty, "cache_path": cache_path}
-
-        expected_bytes = _get_repo_size_cached(repo_id)
-        if expected_bytes <= 0:
-            # Total unknown; report bytes only, no percentage.
-            return {
-                "downloaded_bytes": downloaded_bytes,
-                "expected_bytes": 0,
-                "progress": 0,
-                "cache_path": cache_path,
-            }
-
-        # 95% threshold (blob dedup can skew completed_bytes). Do NOT
-        # treat "no .incomplete files" as done: HF downloads sequentially,
-        # so none exist between files even when far from finished.
-        if completed_bytes >= expected_bytes * 0.95:
-            progress = 1.0
-        else:
-            progress = min(downloaded_bytes / expected_bytes, 0.99)
-        return {
-            "downloaded_bytes": downloaded_bytes,
-            "expected_bytes": expected_bytes,
-            "progress": round(progress, 3),
-            "cache_path": cache_path,
-        }
-    except Exception as e:
-        logger.warning(f"Error checking download progress for {repo_id}: {e}")
-        return _empty
-
-
-_repo_size_cache: dict[str, int] = {}
-
-
-def _get_repo_size_cached(repo_id: str) -> int:
-    if repo_id in _repo_size_cache:
-        return _repo_size_cache[repo_id]
-    try:
-        from huggingface_hub import model_info as hf_model_info
-
-        info = hf_model_info(repo_id, token = None, files_metadata = True)
-        total = sum(s.size for s in info.siblings if s.size)
-        _repo_size_cache[repo_id] = total
-        return total
-    except Exception as e:
-        logger.warning(f"Failed to get repo size for {repo_id}: {e}")
-        return 0
+    """Compatibility route backed by the shared multi-cache progress service."""
+    from hub.services.models import downloads
+    return await downloads.get_download_progress_response(repo_id, hf_token = hf_token)
 
 
 def _repo_in_any_hf_cache(model_name: str) -> bool:
@@ -2943,25 +2868,13 @@ def _repo_in_any_hf_cache(model_name: str) -> bool:
     would delete a model they did not download via the scan. Mirrors the cache set in
     ``_all_hf_cache_scans`` but only probes for the one repo dir (cheap, no full scan).
     """
-    from utils.paths import (
-        hf_default_cache_dir,
-        legacy_hf_cache_dir,
-        resolve_cached_repo_id_case,
-    )
+    from utils.paths import resolve_cached_repo_id_case
 
     dirname = f"models--{resolve_cached_repo_id_case(model_name).replace('/', '--')}"
     dirname_lower = dirname.lower()
-    candidates = []
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-        candidates.append(Path(HF_HUB_CACHE))
-    except Exception:
-        pass
-    for fn in (legacy_hf_cache_dir, hf_default_cache_dir):
-        try:
-            candidates.append(fn())
-        except Exception:
-            continue
+    from hub.utils.hf_cache_state import hf_cache_roots
+
+    candidates = hf_cache_roots()
     # resolve_cached_repo_id_case only normalizes the ACTIVE cache, but discard deletes
     # case-insensitively across all caches, so detect case-insensitively too -- else a
     # pre-existing case-variant repo is misreported as scan-created and deleted on decline.
@@ -2985,38 +2898,8 @@ def _all_hf_cache_scans():
     broken symlink, OS-redirected ~/.cache) is skipped, not fatal, so the
     Downloaded list never blanks out and downloads never leak into Recommended.
     """
-    from huggingface_hub import scan_cache_dir
-    from utils.paths import legacy_hf_cache_dir, hf_default_cache_dir
-
-    scans = []
-    # Guard the active cache too: degrade to "no downloads" instead of raising.
-    try:
-        scans.append(scan_cache_dir())
-    except Exception as exc:
-        logger.warning("Could not scan active HF cache: %s", exc)
-
-    seen: set[str] = set()
-    try:
-        # Resolve the active cache dir for dedup.
-        from huggingface_hub.constants import HF_HUB_CACHE
-        seen.add(str(Path(HF_HUB_CACHE).resolve()))
-    except Exception:
-        pass
-
-    for extra_fn in (legacy_hf_cache_dir, hf_default_cache_dir):
-        try:
-            extra = extra_fn()
-            # is_dir()/resolve() can raise on an inaccessible path; skip it.
-            if not extra.is_dir():
-                continue
-            resolved = str(extra.resolve())
-            if resolved in seen:
-                continue
-            seen.add(resolved)
-            scans.append(scan_cache_dir(cache_dir = str(extra)))
-        except Exception as exc:
-            logger.warning("Could not scan HF cache %s: %s", extra_fn.__name__, exc)
-    return scans
+    from hub.utils.inventory_scan import all_hf_cache_scans
+    return all_hf_cache_scans()
 
 
 def _is_gguf_filename(name: str) -> bool:
@@ -3035,6 +2918,22 @@ def _is_main_gguf_filename(name: str) -> bool:
     return _is_gguf_filename(name) and not _is_mmproj_filename(name)
 
 
+def _main_variant_gguf_label(rel_path: str) -> Optional[str]:
+    name = rel_path.rsplit("/", 1)[-1]
+    if not _is_main_gguf_filename(name):
+        return None
+    if _is_mtp_drafter(rel_path):
+        return None
+    label = _extract_quant_label(rel_path)
+    if _is_big_endian_gguf_path(rel_path, label):
+        return None
+    return label
+
+
+def _normalized_quant_label(label: str) -> str:
+    return label.lower().replace("-", "").replace("_", "")
+
+
 def _repo_has_mmproj(repo_info) -> bool:
     """True if the repo ships a GGUF vision adapter (mmproj), so it can
     take image inputs. Cheap: scans already-listed file names only."""
@@ -3127,7 +3026,9 @@ async def list_cached_gguf(current_subject: str = Depends(get_current_subject)):
                     if repo_info.repo_type != "model":
                         continue
                     repo_id = repo_info.repo_id
-                    if _is_hidden_model(repo_id):
+                    # Pass the snapshot path too so the config check also hides
+                    # custom Whisper checkpoints, not just curated repo ids.
+                    if _is_hidden_model(repo_id, str(repo_info.repo_path)):
                         continue
                     total_size = _repo_gguf_size_bytes(repo_info)
                     if total_size == 0:
@@ -3184,7 +3085,9 @@ async def list_cached_models(
                     if repo_info.repo_type != "model":
                         continue
                     repo_id = repo_info.repo_id
-                    if _is_hidden_model(repo_id):
+                    # Pass the snapshot path too so the config check also hides
+                    # custom Whisper checkpoints, not just curated repo ids.
+                    if _is_hidden_model(repo_id, str(repo_info.repo_path)):
                         continue
                     if _repo_has_gguf_files(repo_info):
                         continue
@@ -3242,124 +3145,177 @@ async def list_cached_models(
 async def delete_cached_model(
     repo_id: str = Body(...),
     variant: Optional[str] = Body(None),
+    cache_path: Optional[str] = Body(None),
+    hf_token: Optional[str] = Depends(get_hf_token),
     current_subject: str = Depends(get_current_subject),
 ):
-    """Delete a cached model repo (or a specific GGUF variant) from the HF cache.
+    """Compatibility route backed by the shared multi-cache deletion service."""
+    from hub.services.models import deletion
+    return await deletion.delete_cached_model_response(repo_id, variant, hf_token, cache_path)
 
-    With *variant*, only GGUF files matching that quant label are removed
-    (e.g. ``UD-Q4_K_XL``); otherwise the whole repo is deleted. Refuses
-    if the model is currently loaded for inference.
-    """
+
+def _resolve_cached_model_path(repo_id: str, variant: Optional[str]) -> Path:
+    """Absolute path of a cached repo (newest snapshot dir) or, with *variant*,
+    that quant's main GGUF file (first split of a sharded quant). Paths come
+    from the HF cache scan only, so callers can't probe arbitrary paths."""
+    cache_scans = _all_hf_cache_scans()
+
+    matching_repos = []
+    for hf_cache in cache_scans:
+        for repo_info in hf_cache.repos:
+            if repo_info.repo_type != "model":
+                continue
+            if repo_info.repo_id.lower() == repo_id.lower():
+                matching_repos.append(repo_info)
+    if not matching_repos:
+        raise HTTPException(status_code = 404, detail = "Model not found in cache")
+
+    if variant:
+        want = _normalized_quant_label(variant)
+        candidate_revisions = sorted(
+            (rev for repo_info in matching_repos for rev in repo_info.revisions),
+            key = lambda rev: getattr(rev, "last_modified", 0) or 0,
+            reverse = True,
+        )
+        for rev in candidate_revisions:
+            snapshot = getattr(rev, "snapshot_path", None)
+            matches = []
+            for f in rev.files:
+                p = Path(f.file_path)
+                rel = f.file_name
+                if snapshot:
+                    try:
+                        rel = p.relative_to(snapshot).as_posix()
+                    except ValueError:
+                        pass
+                label = _main_variant_gguf_label(rel)
+                if label is None or _normalized_quant_label(label) != want:
+                    continue
+                if p.exists() or p.is_symlink():
+                    matches.append((rel, p))
+            if matches:
+                # Path-sorted so a sharded quant deterministically yields its first split.
+                return sorted(matches, key = lambda m: m[0].lower())[0][1]
+        raise HTTPException(
+            status_code = 404,
+            detail = f"Variant {variant} not found in cache for {repo_id}",
+        )
+
+    def repo_size(repo_info) -> int:
+        gguf_size = _repo_gguf_size_bytes(repo_info)
+        if gguf_size > 0:
+            return gguf_size
+        return sum(
+            (getattr(f, "size_on_disk", None) or 0)
+            for rev in repo_info.revisions
+            for f in rev.files
+        )
+
+    def repo_last_modified(repo_info) -> float:
+        return max(
+            (getattr(rev, "last_modified", 0) or 0 for rev in repo_info.revisions),
+            default = 0,
+        )
+
+    target_repo = max(
+        matching_repos,
+        key = lambda repo_info: (repo_size(repo_info), repo_last_modified(repo_info)),
+    )
+
+    # Whole repo: the newest revision's snapshot dir holds the visible files.
+    revisions = sorted(
+        (rev for rev in target_repo.revisions if getattr(rev, "snapshot_path", None)),
+        key = lambda rev: getattr(rev, "last_modified", 0) or 0,
+        reverse = True,
+    )
+    for rev in revisions:
+        p = Path(rev.snapshot_path)
+        if p.exists():
+            return p
+    p = Path(target_repo.repo_path)
+    if p.exists():
+        return p
+    raise HTTPException(status_code = 404, detail = "Cached model path not found")
+
+
+def _wsl_reveal_in_explorer(path: Path) -> bool:
+    import subprocess
+
+    from utils.paths.path_utils import _IS_WSL
+
+    if not _IS_WSL:
+        return False
+    try:
+        windows_path = subprocess.run(
+            ["wslpath", "-w", str(path)],
+            capture_output = True,
+            text = True,
+            check = True,
+            timeout = 10,
+        ).stdout.strip()
+        if not windows_path:
+            return False
+        argument = f"/select,{windows_path}" if path.is_file() else windows_path
+        subprocess.Popen(["explorer.exe", argument])
+        return True
+    except (OSError, subprocess.SubprocessError):
+        return False
+
+
+def _reveal_in_file_manager(path: Path) -> None:
+    """Open the OS file manager with *path* selected (best effort per platform)."""
+    import subprocess
+
+    target = str(path)
+    if sys.platform == "darwin":
+        cmd = ["open", "-R", target] if path.is_file() else ["open", target]
+        subprocess.Popen(cmd)
+    elif os.name == "nt":
+        if path.is_file():
+            subprocess.Popen(["explorer", f"/select,{target}"])
+        else:
+            os.startfile(target)  # noqa: S606 - local user's own file manager
+    elif not _wsl_reveal_in_explorer(path):
+        # No cross-desktop "select file" standard on Linux; open the directory.
+        directory = target if path.is_dir() else str(path.parent)
+        subprocess.Popen(["xdg-open", directory])
+
+
+class CachedModelPathResponse(BaseModel):
+    path: str
+    is_dir: bool
+
+
+@router.get("/cached-model-path", response_model = CachedModelPathResponse)
+async def get_cached_model_path(
+    repo_id: str = Query(..., description = "HuggingFace repo ID"),
+    variant: str = Query("", description = "Quantization variant (empty for whole repo)"),
+    current_subject: str = Depends(get_current_subject),
+):
+    """Absolute on-disk path of a cached repo or one of its GGUF variants."""
     if not _is_valid_repo_id(repo_id):
         raise HTTPException(status_code = 400, detail = "Invalid repo_id format")
+    path = await asyncio.to_thread(_resolve_cached_model_path, repo_id, variant.strip() or None)
+    return {"path": str(path), "is_dir": path.is_dir()}
 
-    # Refuse if the model is currently loaded.
+
+@router.post("/reveal-cached-model")
+async def reveal_cached_model(
+    repo_id: str = Body(...),
+    variant: Optional[str] = Body(None),
+    current_subject: str = Depends(get_current_subject),
+):
+    """Reveal a cached repo (or one GGUF variant's file) in the OS file manager."""
+    if not _is_valid_repo_id(repo_id):
+        raise HTTPException(status_code = 400, detail = "Invalid repo_id format")
+    variant = (variant or "").strip() or None
+    path = await asyncio.to_thread(_resolve_cached_model_path, repo_id, variant)
     try:
-        from routes.inference import get_llama_cpp_backend
-        llama_backend = get_llama_cpp_backend()
-        if llama_backend.is_loaded and llama_backend.model_identifier:
-            loaded_id = llama_backend.model_identifier.lower()
-            if loaded_id == repo_id.lower() or loaded_id.startswith(repo_id.lower()):
-                raise HTTPException(
-                    status_code = 400,
-                    detail = "Unload the model before deleting",
-                )
-    except HTTPException:
-        raise
-    except Exception:
-        pass
-
-    try:
-        inference_backend = get_inference_backend()
-        if inference_backend.active_model_name:
-            active = inference_backend.active_model_name.lower()
-            if active == repo_id.lower() or active.startswith(repo_id.lower()):
-                raise HTTPException(
-                    status_code = 400,
-                    detail = "Unload the model before deleting",
-                )
-    except HTTPException:
-        raise
-    except Exception:
-        pass
-
-    try:
-        cache_scans = _all_hf_cache_scans()
-
-        target_repo = None
-        for hf_cache in cache_scans:
-            for repo_info in hf_cache.repos:
-                if repo_info.repo_type != "model":
-                    continue
-                if repo_info.repo_id.lower() == repo_id.lower():
-                    target_repo = repo_info
-                    break
-            if target_repo is not None:
-                break
-
-        if target_repo is None:
-            raise HTTPException(status_code = 404, detail = "Model not found in cache")
-
-        # ── Per-variant GGUF deletion ────────────────────────────
-        if variant:
-            deleted_bytes = 0
-            deleted_count = 0
-            for rev in target_repo.revisions:
-                for f in rev.files:
-                    if not _is_gguf_filename(f.file_name):
-                        continue
-                    quant = _extract_quant_label(f.file_name)
-                    if quant.lower() != variant.lower():
-                        continue
-                    # Delete the blob (data) and the snapshot symlink.
-                    try:
-                        blob = Path(f.blob_path)
-                        snap = Path(f.file_path)
-                        size = blob.stat().st_size if blob.exists() else 0
-                        if snap.exists() or snap.is_symlink():
-                            snap.unlink()
-                        if blob.exists():
-                            blob.unlink()
-                        deleted_bytes += size
-                        deleted_count += 1
-                    except Exception as e:
-                        logger.warning(f"Failed to delete {f.file_name}: {e}")
-
-            if deleted_count == 0:
-                raise HTTPException(
-                    status_code = 404,
-                    detail = f"Variant {variant} not found in cache for {repo_id}",
-                )
-
-            freed_mb = deleted_bytes / (1024 * 1024)
-            logger.info(
-                f"Deleted {deleted_count} file(s) for {repo_id} variant {variant}: "
-                f"{freed_mb:.1f} MB freed"
-            )
-            return {"status": "deleted", "repo_id": repo_id, "variant": variant}
-
-        # ── Full repo deletion ───────────────────────────────────
-        revision_hashes = [rev.commit_hash for rev in target_repo.revisions]
-        if not revision_hashes:
-            raise HTTPException(status_code = 404, detail = "No revisions found for model")
-
-        delete_strategy = hf_cache.delete_revisions(*revision_hashes)
-        logger.info(
-            f"Deleting cached model {repo_id}: "
-            f"{delete_strategy.expected_freed_size_str} will be freed"
-        )
-        delete_strategy.execute()
-
-        return {"status": "deleted", "repo_id": repo_id}
-
-    except HTTPException:
-        raise
+        await asyncio.to_thread(_reveal_in_file_manager, path)
     except Exception as e:
-        logger.error(f"Error deleting cached model {repo_id}: {e}", exc_info = True)
-        raise HTTPException(
-            status_code = 500,
-            detail = "Failed to delete cached model",
-        )
+        logger.error(f"Failed to reveal {path}: {e}")
+        raise HTTPException(status_code = 500, detail = "Failed to open file manager")
+    return {"status": "ok", "path": str(path)}
 
 
 @router.get("/checkpoints", response_model = CheckpointListResponse)
diff --git a/studio/backend/routes/settings.py b/studio/backend/routes/settings.py
index 17e64df918..fef18a9145 100644
--- a/studio/backend/routes/settings.py
+++ b/studio/backend/routes/settings.py
@@ -60,6 +60,7 @@ from utils.embedding_model_settings import (
     set_rag_embedding_model,
     validate_embedding_model,
 )
+from utils.hf_cache_settings import cache_status, get_hf_cache_paths, set_hf_cache_home
 
 router = APIRouter()
 
@@ -89,6 +90,23 @@ class HelperPrecacheResponse(BaseModel):
     disabled_by_env: bool
 
 
+class HuggingFaceCachePayload(BaseModel):
+    cache_home: Optional[str] = Field(default = None, max_length = 4096)
+
+
+class HuggingFaceCacheResponse(BaseModel):
+    cache_home: str
+    hub_cache: str
+    xet_cache: str
+    source: Literal["default", "studio", "environment"]
+    editable: bool
+    is_custom: bool
+    available: bool
+    writable: bool
+    free_bytes: Optional[int] = None
+    environment_variable: Optional[str] = None
+
+
 class OpenAIAutoSwitchPayload(BaseModel):
     enabled: bool
     # None leaves the stored value untouched (partial updates can't clobber it).
@@ -135,6 +153,30 @@ def _helper_precache_response(enabled: bool | None = None) -> HelperPrecacheResp
     )
 
 
+def _hugging_face_cache_response() -> HuggingFaceCacheResponse:
+    return HuggingFaceCacheResponse(**cache_status(get_hf_cache_paths()))
+
+
+@router.get("/hugging-face-cache", response_model = HuggingFaceCacheResponse)
+def get_hugging_face_cache(
+    current_subject: str = Depends(get_current_subject),
+) -> HuggingFaceCacheResponse:
+    return _hugging_face_cache_response()
+
+
+@router.put("/hugging-face-cache", response_model = HuggingFaceCacheResponse)
+def update_hugging_face_cache(
+    payload: HuggingFaceCachePayload, current_subject: str = Depends(get_current_subject)
+) -> HuggingFaceCacheResponse:
+    try:
+        set_hf_cache_home(payload.cache_home)
+    except RuntimeError as exc:
+        raise HTTPException(status_code = 409, detail = str(exc)) from exc
+    except ValueError as exc:
+        raise HTTPException(status_code = 400, detail = str(exc)) from exc
+    return _hugging_face_cache_response()
+
+
 @router.get("/upload-limit", response_model = UploadLimitResponse)
 def get_upload_limit(current_subject: str = Depends(get_current_subject)) -> UploadLimitResponse:
     return _upload_limit_response(get_upload_limit_mb())
@@ -416,6 +458,11 @@ def update_embedding_model(
             log = logger,
         ) from exc
     hf_token = (payload.hf_token or "").strip() or None
+    from utils.utils import hf_env_offline
+
+    # Offline, both the Hub malware scan and the is-embedding check are unreachable and degrade
+    # to the local cache below; capture the state once.
+    local_only_load = hf_env_offline()
     # The env/default model needs no verification; saving it is a no-op override.
     # A local GGUF on the llama-server backend is accepted as-is: it is exactly
     # what the backend loads, and HF metadata cannot verify a local path.
@@ -439,26 +486,41 @@ def update_embedding_model(
         # Fall back to the loader's own token so a gated/private repo is actually scanned
         # (a token-less scan fails open for exactly the repo that would still load).
         scan_token = hf_token or _ambient_hf_token()
-        # Include the ST module dirs (0_Transformer/) so a flagged pickle directly under
-        # one blocks instead of passing as an unreferenced nested shard.
-        load_subdirs = tuple(
-            dict.fromkeys(
-                (
-                    *security_load_subdirs(model, scan_token),
-                    *_st_module_subdirs(model, scan_token),
+        # Offline: subdir probes would hit the network and hang; the offline gate walks the
+        # whole cached snapshot, so no load-subdir hints are needed.
+        if local_only_load:
+            load_subdirs = ()
+        else:
+            # Include ST module dirs (0_Transformer/) so a flagged pickle directly under one
+            # blocks instead of passing as an unreferenced nested shard.
+            load_subdirs = tuple(
+                dict.fromkeys(
+                    (
+                        *security_load_subdirs(model, scan_token),
+                        *_st_module_subdirs(model, scan_token),
+                    )
                 )
             )
-        )
-        if evaluate_file_security(model, hf_token = scan_token, load_subdirs = load_subdirs).blocked:
+        if evaluate_file_security(
+            model,
+            hf_token = scan_token,
+            load_subdirs = load_subdirs,
+            local_only_load = local_only_load,
+        ).blocked:
             # 403, not 409: the client routes every 409 into the forceable "save anyway"
             # flow, but this block is a hard, non-forceable security refusal.
-            raise HTTPException(
-                status_code = 403,
+            if local_only_load:
+                detail = (
+                    f"{model!r} has cached pickle weights that cannot be security-scanned "
+                    "offline and no safetensors alternative, so it cannot be used as the "
+                    "embedding model. Re-download it with safetensors weights while online."
+                )
+            else:
                 detail = (
                     f"{model!r} is flagged as unsafe by Hugging Face's security scan and "
                     "cannot be used as the embedding model."
-                ),
-            )
+                )
+            raise HTTPException(status_code = 403, detail = detail)
     if model != default_embedding_model() and not payload.force and not is_local_gguf:
         from core.rag import config as rag_config
 
@@ -468,15 +530,28 @@ def update_embedding_model(
         # which would wrongly 409 a valid online GGUF embedder.
         gguf_named = _llama_backend_active() and rag_config._names_gguf(model)
         if not gguf_named and not is_embedding_model(model, hf_token = hf_token):
-            raise HTTPException(
-                status_code = 409,
-                detail = (
-                    f"Could not verify {model!r} as an embedding model on "
-                    "Hugging Face (it may be the wrong model type, gated, or "
-                    "you may be offline)."
-                ),
-            )
-        gguf_error = _local_gguf_backend_error(model) or _hf_gguf_backend_error(model, hf_token)
+            # Offline, is_embedding_model can only confirm the ST layout (modules.json); a
+            # transformers-native embedder (e.g. gte-modernbert) is unverifiable without Hub
+            # metadata. If already cached and loadable, accept it rather than raising a 409 that
+            # online would not (ST can load any cached encoder). Uncached -> 409.
+            from utils.utils import hf_cache_snapshot_is_loadable
+
+            # Require a genuinely loadable cache (config + weights), not just a resolved refs/main,
+            # so a metadata-only partial cache still gets the forceable 409.
+            offline_cached = local_only_load and hf_cache_snapshot_is_loadable(model)
+            if not offline_cached:
+                raise HTTPException(
+                    status_code = 409,
+                    detail = (
+                        f"Could not verify {model!r} as an embedding model on "
+                        "Hugging Face (it may be the wrong model type, gated, or "
+                        "you may be offline)."
+                    ),
+                )
+        # The Hub GGUF probe (list_repo_files) can hang offline; skip it. Local check stays.
+        gguf_error = _local_gguf_backend_error(model)
+        if gguf_error is None and not local_only_load:
+            gguf_error = _hf_gguf_backend_error(model, hf_token)
         if gguf_error:
             raise HTTPException(status_code = 409, detail = gguf_error)
     set_rag_embedding_model(model)
diff --git a/studio/backend/routes/training.py b/studio/backend/routes/training.py
index 53b1c4d991..5b10652fdd 100644
--- a/studio/backend/routes/training.py
+++ b/studio/backend/routes/training.py
@@ -109,7 +109,9 @@ async def get_hardware_utilization(current_subject: str = Depends(get_current_su
 @router.get("/hardware/visible")
 async def get_visible_hardware_utilization(current_subject: str = Depends(get_current_subject)):
     from utils.hardware import get_visible_gpu_utilization
-    return get_visible_gpu_utilization()
+
+    # Off the event loop: the ROCm fallbacks shell out (Windows perf counters, sysfs) and the System view polls this route.
+    return await asyncio.to_thread(get_visible_gpu_utilization)
 
 
 @router.post("/start")
@@ -196,6 +198,7 @@ async def start_training(
                 request.local_eval_datasets, "Local eval dataset"
             )
         resume_output_dir: Optional[str] = None
+        resume_run: Optional[dict] = None
         if request.resume_from_checkpoint:
             try:
                 resume_output_dir = normalize_resume_output_dir(request.resume_from_checkpoint)
@@ -208,7 +211,7 @@ async def start_training(
             if not resume_run or not can_resume_run(resume_run):
                 raise HTTPException(
                     status_code = 400,
-                    detail = "Resume checkpoint must belong to a stopped run with saved trainer state.",
+                    detail = "Resume checkpoint must belong to a stopped or errored run with complete saved trainer state.",
                 )
             resume_checkpoint = get_resume_checkpoint_path(resume_output_dir)
             if not resume_checkpoint:
@@ -412,53 +415,39 @@ async def start_training(
             try:
                 from routes.training_vram import (
                     can_keep_chat_during_training,
-                    free_chat_models_for_training,
-                    summarize_resident_chat,
+                    coordinate_models_for_training,
                 )
 
-                resident = summarize_resident_chat()
-                if not resident["any"]:
-                    return
-                if resident.get("loading"):
-                    # In-flight load can't be sized -> free rather than risk OOM.
-                    freed = free_chat_models_for_training(reason = "chat model still loading")
-                    logger.info("Freed in-flight chat load for training: %s", freed)
-                    return
-                keep, info = can_keep_chat_during_training(
-                    model_name = training_kwargs["model_name"],
-                    hf_token = training_kwargs["hf_token"],
-                    training_type = training_kwargs["training_type"],
-                    load_in_4bit = training_kwargs["load_in_4bit"],
-                    batch_size = training_kwargs["batch_size"],
-                    max_seq_length = training_kwargs["max_seq_length"],
-                    lora_rank = training_kwargs["lora_r"],
-                    target_modules = training_kwargs["target_modules"],
-                    gradient_checkpointing = training_kwargs["gradient_checkpointing"],
-                    optimizer = training_kwargs["optim"],
-                    gpu_ids = training_kwargs["gpu_ids"],
-                )
-                if keep:
-                    logger.info(
-                        "Keeping chat model(s) loaded during training "
-                        "(free ~%s GB, needs ~%s GB): %s",
-                        info.get("usable_gb"),
-                        info.get("required_gb"),
-                        resident,
+                def _can_keep_resident_models():
+                    return can_keep_chat_during_training(
+                        model_name = training_kwargs["model_name"],
+                        hf_token = training_kwargs["hf_token"],
+                        training_type = training_kwargs["training_type"],
+                        load_in_4bit = training_kwargs["load_in_4bit"],
+                        batch_size = training_kwargs["batch_size"],
+                        max_seq_length = training_kwargs["max_seq_length"],
+                        lora_rank = training_kwargs["lora_r"],
+                        target_modules = training_kwargs["target_modules"],
+                        gradient_checkpointing = training_kwargs["gradient_checkpointing"],
+                        optimizer = training_kwargs["optim"],
+                        gpu_ids = training_kwargs["gpu_ids"],
                     )
-                else:
-                    freed = free_chat_models_for_training(
-                        reason = "insufficient VRAM to run training alongside chat",
-                    )
-                    logger.info("Freed chat model(s) for training: %s", freed)
+
+                freed = coordinate_models_for_training(_can_keep_resident_models)
+                if freed:
+                    logger.info("Freed models for training: %s", freed)
             except Exception as e:
-                logger.warning("Chat/training VRAM coordination failed; proceeding: %s", e)
+                logger.warning("Inference/training memory coordination failed; proceeding: %s", e)
 
         # The hook runs only once start guards pass -> VRAM freed iff training starts.
         from utils.transformers_version import SidecarSwapInProgress
 
         try:
             success = backend.start_training(
-                job_id = job_id, before_spawn = _free_vram_for_training, **training_kwargs
+                job_id = job_id,
+                before_spawn = _free_vram_for_training,
+                resume_source_run_id = resume_run["id"] if resume_run else None,
+                **training_kwargs,
             )
         except SidecarSwapInProgress as exc:
             # Expected loss of the race against a sidecar install: a retryable
@@ -521,7 +510,10 @@ async def stop_training(
                 status = "idle", message = "No training job is currently running"
             )
 
-        backend.stop_training(save = body.save)
+        if not backend.stop_training(save = body.save):
+            return TrainingStopResponse(
+                status = "idle", message = "No training job is currently running"
+            )
 
         return TrainingStopResponse(
             status = "stopped",
@@ -637,9 +629,9 @@ async def get_training_status(current_subject: str = Depends(get_current_subject
                 "loss": getattr(progress, "loss", None),
                 "learning_rate": getattr(progress, "learning_rate", None),
             }
-            output_dir = getattr(backend, "_output_dir", None)
-            if output_dir:
-                details["output_dir"] = output_dir
+            # Always present: an explicit null tells the client to drop a cached
+            # path (stop without save clears the run's output_dir).
+            details["output_dir"] = getattr(backend, "_output_dir", None) or None
 
         # Metric history for chart recovery after SSE reconnection.
         metric_history = None
diff --git a/studio/backend/routes/training_vram.py b/studio/backend/routes/training_vram.py
index fd96fe2175..83bce8b772 100644
--- a/studio/backend/routes/training_vram.py
+++ b/studio/backend/routes/training_vram.py
@@ -1,15 +1,13 @@
 # SPDX-License-Identifier: AGPL-3.0-only
 # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-"""VRAM coordination between chat/inference and training.
+"""Memory coordination between inference and training.
 
-Decides, from live free VRAM, whether a resident chat model can stay loaded
-during training or must be unloaded, and unloads it across all backends
-(HF/MLX orchestrator + llama.cpp GGUF server). In the route layer because the
-GGUF accessor lives in routes/inference.py; backends are imported lazily.
+Uses live free VRAM to keep resident chat and STT models when they fit. STT is
+evicted before chat when training needs memory.
 """
 
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Callable, Dict, List, Optional, Tuple
 
 from loggers import get_logger
 
@@ -77,6 +75,37 @@ def summarize_resident_chat() -> Dict[str, Any]:
     }
 
 
+def summarize_resident_stt() -> Dict[str, Any]:
+    """Report the resident dictation model (either engine). Never raises."""
+    try:
+        from core.inference.stt_ggml_sidecar import get_ggml_stt_sidecar
+        from core.inference.stt_sidecar import get_stt_sidecar
+
+        sidecar = get_stt_sidecar()
+        model = sidecar.loaded_model
+        device = sidecar.device
+        loading = sidecar.is_loading()
+        # whisper.cpp holds GPU memory via its subprocess, and both engines can be
+        # live at once (engine switch or direct /audio/stt/load). Always fold the
+        # GGUF sidecar in: a resident Transformers model must not mask a GGUF
+        # server still binding its backend, or admission lets training launch into
+        # that startup and OOM.
+        ggml = get_ggml_stt_sidecar()
+        if not model:
+            model = ggml.loaded_model
+            device = device or ggml.device
+        loading = loading or ggml.is_loading()
+        return {
+            "model": model,
+            "device": device,
+            "loading": loading,
+            "any": bool(model or loading),
+        }
+    except Exception as e:
+        logger.warning("Could not inspect STT sidecar: %s", e)
+        return {"model": None, "device": None, "loading": False, "any": False}
+
+
 def can_keep_chat_during_training(
     *,
     model_name: str,
@@ -366,3 +395,110 @@ def free_chat_models_for_training(reason: str) -> List[str]:
         logger.warning("Could not unload GGUF chat model: %s", e)
 
     return freed
+
+
+def free_stt_model_for_training(reason: str) -> List[str]:
+    """Unload the dictation model(s) before training. Never raises.
+
+    The Transformers and GGUF sidecars are freed under independent exception
+    boundaries so a failure unloading one backend never skips freeing the other
+    (both can hold accelerator memory at once after an engine switch).
+    """
+    freed: List[str] = []
+    try:
+        from core.inference.stt_sidecar import get_stt_sidecar
+        sidecar = get_stt_sidecar()
+        if sidecar.is_loading() and sidecar.cancel_pending_load():
+            logger.info("Cancelling STT model load for training (%s)", reason)
+            # The loader may still be in from_pretrained()/.to(device) holding
+            # VRAM; wait for it to observe the cancel and release first.
+            sidecar.wait_for_load_to_settle()
+            # A load that finished before seeing the cancel leaves a resident
+            # model; unload it so training gets the memory back.
+            if sidecar.loaded_model:
+                sidecar.unload()
+            freed.append("stt:loading")
+        else:
+            model = sidecar.loaded_model
+            if model:
+                logger.info("Unloading STT model '%s' for training (%s)", model, reason)
+                sidecar.unload()
+                freed.append(f"stt:{model}")
+    except Exception as e:
+        logger.warning("Could not unload Transformers STT model: %s", e)
+
+    # Check the GGUF sidecar even after a cancelled/failed Transformers unload;
+    # both engines can hold memory at once (engine switch or direct load).
+    try:
+        from core.inference.stt_ggml_sidecar import get_ggml_stt_sidecar
+        ggml = get_ggml_stt_sidecar()
+        if ggml.is_loading() and ggml.cancel_pending_load():
+            logger.info("Cancelling GGUF STT model load for training (%s)", reason)
+            # whisper-server may still be binding its backend; wait for the
+            # cancelled startup to be killed and reaped before training claims
+            # the memory (loaded_model stays unset until it is ready).
+            ggml.wait_for_load_to_settle()
+            if ggml.loaded_model:
+                ggml.unload()
+            freed.append("stt:gguf-loading")
+        else:
+            ggml_model = ggml.loaded_model
+            if ggml_model:
+                logger.info("Unloading GGUF STT model '%s' for training (%s)", ggml_model, reason)
+                ggml.unload()
+                freed.append(f"stt:{ggml_model}")
+    except Exception as e:
+        logger.warning("Could not unload GGUF STT model: %s", e)
+
+    return freed
+
+
+def coordinate_models_for_training(
+    can_keep: Callable[[], Tuple[bool, Dict[str, Any]]],
+) -> List[str]:
+    """Keep resident models when they fit, evicting STT before chat."""
+    resident_chat = summarize_resident_chat()
+    resident_stt = summarize_resident_stt()
+    if not resident_chat["any"] and not resident_stt["any"]:
+        return []
+
+    if resident_chat.get("loading"):
+        freed = free_stt_model_for_training(reason = "chat model still loading")
+        freed += free_chat_models_for_training(reason = "chat model still loading")
+        return freed
+
+    freed: List[str] = []
+    if resident_stt.get("loading"):
+        released_stt = free_stt_model_for_training(reason = "STT model still loading")
+        freed += released_stt
+        resident_stt = (
+            {"model": None, "device": None, "loading": False, "any": False}
+            if released_stt
+            else summarize_resident_stt()
+        )
+        if not resident_chat["any"] and not resident_stt["any"]:
+            return freed
+
+    keep, info = can_keep()
+    if keep:
+        logger.info(
+            "Keeping resident models loaded during training (free ~%s GB, needs ~%s GB): %s",
+            info.get("usable_gb"),
+            info.get("required_gb"),
+            {"chat": resident_chat, "stt": resident_stt},
+        )
+        return freed
+
+    if resident_stt["any"]:
+        freed += free_stt_model_for_training(reason = "insufficient training memory")
+        if not resident_chat["any"]:
+            return freed
+        keep, _info = can_keep()
+        if keep:
+            logger.info("Keeping chat model loaded after freeing STT: %s", resident_chat)
+            return freed
+
+    freed += free_chat_models_for_training(
+        reason = "insufficient VRAM to run training alongside chat",
+    )
+    return freed
diff --git a/studio/backend/routes/whisper.py b/studio/backend/routes/whisper.py
new file mode 100644
index 0000000000..08a8f269ec
--- /dev/null
+++ b/studio/backend/routes/whisper.py
@@ -0,0 +1,74 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""whisper.cpp prebuilt status endpoint.
+
+GET  /api/whisper/update-status  -> is a newer prebuilt available + job state
+
+Detection reuses utils.whisper_cpp_freshness and fails open so the UI never
+blocks on a missing marker / offline GitHub. There is no whisper-only update
+trigger: whisper updates piggyback on the single main update item
+(POST /api/llama/update chains a whisper phase when whisper is behind).
+"""
+
+from __future__ import annotations
+
+import asyncio
+from typing import Optional
+
+from fastapi import APIRouter, Depends, Query
+from pydantic import BaseModel, Field
+
+from auth.authentication import get_current_subject
+from utils.whisper_cpp_update import get_update_status
+
+router = APIRouter()
+
+
+class WhisperUpdateJob(BaseModel):
+    state: str = Field("idle", description = "idle | running | success | error")
+    message: str = ""
+    from_tag: Optional[str] = None
+    to_tag: Optional[str] = None
+    reload_required: Optional[bool] = None
+    error: Optional[str] = None
+    progress: Optional[float] = Field(None, description = "0..1 while running, 1 on success.")
+    started_at: Optional[str] = None
+    finished_at: Optional[str] = None
+
+
+class WhisperUpdateStatusResponse(BaseModel):
+    supported: bool = Field(
+        False,
+        description = "True when the install came from an Unsloth prebuilt (has a marker).",
+    )
+    update_available: bool = Field(
+        False, description = "True when the latest release is genuinely newer than the install."
+    )
+    stale: bool = Field(
+        False, description = "Update available AND install older than the staleness threshold."
+    )
+    installed_tag: Optional[str] = None
+    latest_tag: Optional[str] = None
+    published_repo: Optional[str] = None
+    installed_at_utc: Optional[str] = None
+    age_days: Optional[int] = None
+    source_build: bool = Field(
+        False, description = "True when there is no marker (source build) but a prebuilt is offered."
+    )
+    update_size_bytes: Optional[int] = Field(
+        None, description = "Download size of the prebuilt an update would fetch, in bytes."
+    )
+    job: WhisperUpdateJob = Field(default_factory = WhisperUpdateJob)
+
+
+@router.get("/update-status", response_model = WhisperUpdateStatusResponse)
+async def whisper_update_status(
+    force_refresh: bool = Query(
+        False, description = "Bypass the 24h release cache for an explicit check."
+    ),
+    current_subject: str = Depends(get_current_subject),
+) -> WhisperUpdateStatusResponse:
+    # Off the event loop: detection may probe the host and read GitHub.
+    status = await asyncio.to_thread(get_update_status, force_refresh = force_refresh)
+    return WhisperUpdateStatusResponse(**status)
diff --git a/studio/backend/run.py b/studio/backend/run.py
index 398943cc2c..d9569c46f6 100644
--- a/studio/backend/run.py
+++ b/studio/backend/run.py
@@ -1244,6 +1244,13 @@ def _apply_supplied_password(password_value: "Optional[str]") -> None:
             flush = True,
         )
         sys.exit(1)
+    if any(ch.isspace() for ch in supplied):
+        print(
+            "Error: password cannot contain spaces; not starting.",
+            file = sys.stderr,
+            flush = True,
+        )
+        sys.exit(1)
     if _is_current_password(supplied):
         print(
             "Error: the new password must differ from the current bootstrap "
diff --git a/studio/backend/storage/studio_db.py b/studio/backend/storage/studio_db.py
index d889894d04..6972e7b7ff 100644
--- a/studio/backend/storage/studio_db.py
+++ b/studio/backend/storage/studio_db.py
@@ -192,13 +192,18 @@ def _ensure_schema(conn: sqlite3.Connection) -> None:
             error_message TEXT,
             duration_seconds REAL,
             loss_sparkline TEXT,
-            display_name TEXT
+            display_name TEXT,
+            resume_blocked INTEGER NOT NULL DEFAULT 0
         )
         """
     )
     existing_cols = {row[1] for row in conn.execute("PRAGMA table_info(training_runs)").fetchall()}
     if "display_name" not in existing_cols:
         conn.execute("ALTER TABLE training_runs ADD COLUMN display_name TEXT")
+    if "resume_blocked" not in existing_cols:
+        conn.execute(
+            "ALTER TABLE training_runs ADD COLUMN resume_blocked INTEGER NOT NULL DEFAULT 0"
+        )
     conn.execute(
         """
         CREATE TABLE IF NOT EXISTS training_metrics (
@@ -734,16 +739,43 @@ def create_run(
     config_json: str,
     started_at: str,
     total_steps: Optional[int],
+    *,
+    output_dir: Optional[str] = None,
+    cancel_requested: bool = False,
+    resumed_from_run_id: Optional[str] = None,
 ) -> None:
     conn = get_connection()
     try:
         conn.execute(
             """
-            INSERT INTO training_runs (id, model_name, dataset_name, config_json, started_at, total_steps)
-            VALUES (?, ?, ?, ?, ?, ?)
+            INSERT INTO training_runs (
+                id, model_name, dataset_name, config_json, started_at, total_steps,
+                output_dir, resume_blocked
+            )
+            VALUES (?, ?, ?, ?, ?, ?, ?, ?)
             """,
-            (id, model_name, dataset_name, config_json, started_at, total_steps),
+            (
+                id,
+                model_name,
+                dataset_name,
+                config_json,
+                started_at,
+                total_steps,
+                None if cancel_requested else output_dir,
+                int(cancel_requested),
+            ),
         )
+        if resumed_from_run_id:
+            claimed = conn.execute(
+                """
+                UPDATE training_runs SET resume_blocked = 1
+                WHERE id = ? AND status IN ('stopped', 'error')
+                  AND output_dir = ? AND resume_blocked = 0
+                """,
+                (resumed_from_run_id, output_dir),
+            )
+            if claimed.rowcount != 1:
+                raise RuntimeError("Resume source is no longer available")
         conn.commit()
     finally:
         conn.close()
@@ -786,6 +818,8 @@ def finish_run(
     loss_sparkline: Optional[str] = None,
     output_dir: Optional[str] = None,
     error_message: Optional[str] = None,
+    clear_output_dir: bool = False,
+    resume_blocked: bool = False,
 ) -> None:
     conn = get_connection()
     try:
@@ -793,9 +827,16 @@ def finish_run(
             """
             UPDATE training_runs
             SET status = ?, ended_at = ?, final_step = ?, final_loss = ?,
-                duration_seconds = ?, loss_sparkline = ?, output_dir = ?,
-                error_message = ?
-            WHERE id = ?
+                duration_seconds = ?, loss_sparkline = ?,
+                output_dir = CASE
+                    WHEN resume_blocked = 1 OR ? = 1 THEN NULL
+                    WHEN ? IS NOT NULL THEN ?
+                    WHEN ? IN ('error', 'stopped') THEN output_dir
+                    ELSE NULL
+                END,
+                error_message = ?,
+                resume_blocked = CASE WHEN resume_blocked = 1 OR ? = 1 THEN 1 ELSE ? END
+            WHERE id = ? AND status = 'running'
             """,
             (
                 status,
@@ -804,8 +845,13 @@ def finish_run(
                 final_loss,
                 duration_seconds,
                 loss_sparkline,
+                int(clear_output_dir),
                 output_dir,
+                output_dir,
+                status,
                 error_message,
+                int(clear_output_dir),
+                int(resume_blocked),
                 id,
             ),
         )
@@ -865,6 +911,38 @@ def update_run_display_name(id: str, display_name: Optional[str]) -> None:
         conn.close()
 
 
+def update_run_output_dir(id: str, output_dir: Optional[str]) -> None:
+    conn = get_connection()
+    try:
+        conn.execute(
+            """
+            UPDATE training_runs SET output_dir = ?
+            WHERE id = ? AND status = 'running' AND resume_blocked = 0
+            """,
+            (output_dir, id),
+        )
+        conn.commit()
+    finally:
+        conn.close()
+
+
+def mark_run_cancel_requested(id: str) -> bool:
+    """Clear resume/export state only while the exact run is still active."""
+    conn = get_connection()
+    try:
+        cursor = conn.execute(
+            """
+            UPDATE training_runs SET output_dir = NULL, resume_blocked = 1
+            WHERE id = ? AND status = 'running'
+            """,
+            (id,),
+        )
+        conn.commit()
+        return cursor.rowcount > 0
+    finally:
+        conn.close()
+
+
 def list_runs(limit: int = 50, offset: int = 0) -> dict:
     conn = get_connection()
     try:
@@ -874,15 +952,15 @@ def list_runs(limit: int = 50, offset: int = 0) -> dict:
             SELECT r.id, r.status, r.model_name, r.dataset_name, r.started_at,
                    r.ended_at, r.total_steps, r.final_step, r.final_loss,
                    r.output_dir, r.duration_seconds, r.error_message,
-                   r.loss_sparkline, r.display_name, r.config_json,
+                   r.loss_sparkline, r.display_name, r.config_json, r.resume_blocked,
                    CASE
-                       WHEN r.status = 'stopped'
+                       WHEN r.status IN ('stopped', 'error')
                             AND r.output_dir IS NOT NULL
                             AND EXISTS (
                                 SELECT 1
                                 FROM training_runs newer
                                 WHERE newer.output_dir = r.output_dir
-                                  AND newer.status IN ('stopped', 'completed')
+                                  AND newer.status IN ('stopped', 'completed', 'error', 'running')
                                   AND newer.started_at > r.started_at
                             )
                        THEN 1 ELSE 0
@@ -917,13 +995,13 @@ def get_run(id: str) -> Optional[dict]:
             """
             SELECT r.*,
                    CASE
-                       WHEN r.status = 'stopped'
+                       WHEN r.status IN ('stopped', 'error')
                             AND r.output_dir IS NOT NULL
                             AND EXISTS (
                                 SELECT 1
                                 FROM training_runs newer
                                 WHERE newer.output_dir = r.output_dir
-                                  AND newer.status IN ('stopped', 'completed')
+                                  AND newer.status IN ('stopped', 'completed', 'error', 'running')
                                   AND newer.started_at > r.started_at
                             )
                        THEN 1 ELSE 0
@@ -958,12 +1036,12 @@ def get_resumable_run_by_output_dir(output_dir: str) -> Optional[dict]:
                    0 AS resumed_later
             FROM training_runs r
             WHERE r.output_dir = ?
-              AND r.status = 'stopped'
+              AND r.status IN ('stopped', 'error')
               AND NOT EXISTS (
                   SELECT 1
                   FROM training_runs newer
                   WHERE newer.output_dir = r.output_dir
-                    AND newer.status IN ('stopped', 'completed')
+                    AND newer.status IN ('stopped', 'completed', 'error', 'running')
                     AND newer.started_at > r.started_at
               )
             ORDER BY r.started_at DESC
@@ -1066,8 +1144,12 @@ def cleanup_orphaned_runs() -> None:
         conn.execute(
             """
             UPDATE training_runs
-            SET status = 'error',
-                error_message = 'Server restarted during training',
+            SET status = CASE WHEN resume_blocked = 1 THEN 'stopped' ELSE 'error' END,
+                error_message = CASE
+                    WHEN resume_blocked = 1 THEN NULL
+                    ELSE 'Server restarted during training'
+                END,
+                output_dir = CASE WHEN resume_blocked = 1 THEN NULL ELSE output_dir END,
                 ended_at = ?
             WHERE status = 'running'
             """,
diff --git a/studio/backend/tests/test_cached_gguf_routes.py b/studio/backend/tests/test_cached_gguf_routes.py
index b3e6255d55..6f2c672002 100644
--- a/studio/backend/tests/test_cached_gguf_routes.py
+++ b/studio/backend/tests/test_cached_gguf_routes.py
@@ -66,6 +66,66 @@ def test_iter_gguf_paths_matches_extension_case_insensitively(tmp_path):
     assert result == ["Q4_K_M.gguf", "Q8_0.GGUF"]
 
 
+def test_legacy_hf_scan_uses_snapshot_path_for_inactive_cache(tmp_path):
+    repo = tmp_path / "models--Org--Model"
+    snapshot = repo / "snapshots" / "revision"
+    snapshot.mkdir(parents = True)
+
+    [row] = models_route._scan_hf_cache(tmp_path, active_cache = False)
+
+    assert row.model_id == "Org/Model"
+    assert row.id == str(snapshot.resolve())
+    assert row.path == str(snapshot.resolve())
+
+
+def test_collect_local_models_scans_previous_cache(monkeypatch, tmp_path):
+    active = tmp_path / "active"
+    previous = tmp_path / "previous"
+    active.mkdir()
+    snapshot = previous / "models--Org--Previous" / "snapshots" / "revision"
+    snapshot.mkdir(parents = True)
+
+    monkeypatch.setattr(models_route, "_resolve_hf_cache_dir", lambda: active)
+    monkeypatch.setattr("utils.paths.legacy_hf_cache_dir", lambda: tmp_path / "legacy")
+    monkeypatch.setattr("utils.paths.hf_default_cache_dir", lambda: tmp_path / "default")
+    monkeypatch.setattr("utils.paths.lmstudio_model_dirs", lambda: [])
+    monkeypatch.setattr("utils.hf_cache_settings.known_hf_hub_caches", lambda: [active, previous])
+    monkeypatch.setattr("storage.studio_db.list_scan_folders", lambda: [])
+
+    rows = models_route.collect_local_models(tmp_path / "models")
+
+    previous_row = next(row for row in rows if row.model_id == "Org/Previous")
+    assert previous_row.id == str(snapshot.resolve())
+
+
+def test_collect_local_models_prefers_complete_previous_copy(monkeypatch, tmp_path):
+    active = tmp_path / "active"
+    previous = tmp_path / "previous"
+    active_partial = active / "models--Org--Model" / "blobs" / "abc.incomplete"
+    active_partial.parent.mkdir(parents = True)
+    active_partial.write_bytes(b"partial")
+    snapshot = previous / "models--Org--Model" / "snapshots" / "revision"
+    snapshot.mkdir(parents = True)
+    (snapshot / "model.safetensors").write_bytes(b"complete")
+
+    monkeypatch.setattr(models_route, "_resolve_hf_cache_dir", lambda: active)
+    monkeypatch.setattr("utils.paths.legacy_hf_cache_dir", lambda: tmp_path / "legacy")
+    monkeypatch.setattr("utils.paths.hf_default_cache_dir", lambda: tmp_path / "default")
+    monkeypatch.setattr("utils.paths.lmstudio_model_dirs", lambda: [])
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.known_hf_hub_caches",
+        lambda: [active, previous],
+    )
+    monkeypatch.setattr("storage.studio_db.list_scan_folders", lambda: [])
+
+    rows = models_route.collect_local_models(tmp_path / "models")
+
+    [row] = [row for row in rows if row.model_id == "Org/Model"]
+    assert row.id == str(snapshot.resolve())
+    assert row.partial is False
+    assert row.active_cache is False
+
+
 def test_list_cached_gguf_includes_non_suffix_repo_when_cache_contains_gguf(monkeypatch, tmp_path):
     repo = _repo(
         "HauhauCS/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive",
@@ -131,6 +191,72 @@ def test_is_hidden_model_hides_validation_probe_everywhere():
     assert not models_route._is_hidden_model("user/stories260K-finetune-GGUF")
 
 
+def test_is_hidden_model_hides_dictation_models(tmp_path):
+    assert models_route._is_hidden_model("unsloth/whisper-tiny")
+    assert models_route._is_hidden_model("unsloth/whisper-base")
+    assert models_route._is_hidden_model("unsloth/whisper-small")
+    assert models_route._is_hidden_model("unsloth/whisper-large-v3-turbo")
+    assert models_route._is_hidden_model(
+        "/hf/models--unsloth--whisper-large-v3/snapshots/abc/model.safetensors"
+    )
+    assert not models_route._is_hidden_model("user/whisper-finetune")
+    assert not models_route._is_hidden_model(
+        "C:\\cache\\models--unsloth--whisper-small-finetune\\model.safetensors"
+    )
+    custom = tmp_path / "custom-whisper"
+    custom.mkdir()
+    (custom / "config.json").write_text(
+        '{"model_type": "whisper", "architectures": ["WhisperForConditionalGeneration"]}'
+    )
+    (custom / "model.safetensors").write_bytes(b"weights")
+    assert models_route._is_hidden_model(
+        "user/custom-checkpoint",
+        str(custom / "model.safetensors"),
+    )
+    named_only = tmp_path / "whisper-finetune"
+    named_only.mkdir()
+    (named_only / "config.json").write_text('{"model_type": "llama"}')
+    assert not models_route._is_hidden_model("user/whisper-finetune", str(named_only))
+
+
+def test_list_cached_models_hides_custom_whisper_by_config(monkeypatch, tmp_path):
+    # Regression: the legacy /cached-models picker must pass the snapshot path so
+    # the config check hides a custom (non-curated) Whisper checkpoint; a bare
+    # repo id cannot ("user/whisper-finetune" is not in the curated set).
+    repo_path = tmp_path / "models--user--whisper-finetune"
+    snap = repo_path / "snapshots" / "abc"
+    snap.mkdir(parents = True)
+    (snap / "config.json").write_text(
+        '{"model_type": "whisper", "architectures": ["WhisperForConditionalGeneration"]}'
+    )
+    (snap / "model.safetensors").write_bytes(b"weights")
+
+    captured: list = []
+    real_hidden = models_route._is_hidden_model
+
+    def spy(*values):
+        captured.append(values)
+        return real_hidden(*values)
+
+    monkeypatch.setattr(models_route, "_is_hidden_model", spy)
+    repo = _repo(
+        "user/whisper-finetune",
+        [SimpleNamespace(file_name = "model.safetensors", size_on_disk = 10)],
+        repo_path,
+    )
+    monkeypatch.setattr(
+        models_route, "_all_hf_cache_scans", lambda: [SimpleNamespace(repos = [repo])]
+    )
+
+    result = asyncio.run(
+        models_route.list_cached_models(current_subject = "test-user", hf_token = None)
+    )
+    # The route passed the snapshot path (not just the repo id) ...
+    assert any(str(repo_path) in values for values in captured)
+    # ... so the custom Whisper checkpoint is hidden from the chat picker.
+    assert result["cached"] == []
+
+
 def test_is_hidden_model_matches_repo_ids_exactly(monkeypatch):
     """A custom embedder with a generic basename is hidden by EXACT repo-id
     match only, so unrelated cached repos that merely contain the basename stay
@@ -573,33 +699,14 @@ def _gfile(name: str, size: int, mtime: float) -> SimpleNamespace:
     )
 
 
-def test_all_hf_cache_scans_survives_inaccessible_aux_cache(monkeypatch, tmp_path):
-    """An unreadable auxiliary cache (e.g. an inaccessible
-    ``~/.cache/huggingface/hub``) must be skipped, not abort the scan.
-    Regression guard for ``extra.is_dir()`` raising and wiping the response.
-    """
-    import huggingface_hub
-    import utils.paths as paths_mod
+def test_all_hf_cache_scans_uses_shared_inventory(monkeypatch, tmp_path):
+    from hub.utils import inventory_scan
 
     active = SimpleNamespace(
         repos = [_repo("Org/Active", [_file("Q4_K_M.gguf", 5_000)], tmp_path / "active")]
     )
 
-    def _fake_scan(cache_dir = None):
-        if cache_dir is None:
-            return active
-        raise AssertionError("auxiliary scan should have been skipped")
-
-    class _Boom:
-        def is_dir(self):
-            raise PermissionError(13, "Permission denied")
-
-        def resolve(self):
-            raise PermissionError(13, "Permission denied")
-
-    monkeypatch.setattr(huggingface_hub, "scan_cache_dir", _fake_scan)
-    monkeypatch.setattr(paths_mod, "legacy_hf_cache_dir", lambda: _Boom())
-    monkeypatch.setattr(paths_mod, "hf_default_cache_dir", lambda: _Boom())
+    monkeypatch.setattr(inventory_scan, "all_hf_cache_scans", lambda: [active])
 
     scans = models_route._all_hf_cache_scans()
     assert scans == [active]
@@ -686,13 +793,17 @@ def test_gguf_variants_mmproj_does_not_mark_quant_downloaded(monkeypatch, tmp_pa
         "list_gguf_variants",
         lambda repo_id, hf_token = None: (variants, True, []),
     )
-    monkeypatch.setattr(GV, "_local_main_gguf_blobs_by_quant", lambda _repo_id: {})
+    monkeypatch.setattr(
+        GV,
+        "_local_main_gguf_blobs_by_quant",
+        lambda _repo_id, repo_cache_dir = None: {},
+    )
 
     snap = tmp_path / "models--org--repo" / "snapshots" / "rev"
     snap.mkdir(parents = True)
     (snap / "model-Q4_K_M.gguf").write_bytes(b"x" * 10_000)  # real weight, fully present
     (snap / "mmproj-F16.gguf").write_bytes(b"y" * 20_000)  # mmproj adapter, label "F16"
-    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id: [snap])
+    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id, root = None: [snap])
 
     result = asyncio.run(
         models_route.get_gguf_variants(
@@ -705,6 +816,52 @@ def test_gguf_variants_mmproj_does_not_mark_quant_downloaded(monkeypatch, tmp_pa
     assert flags["F16"] is False
 
 
+def test_gguf_variants_route_scopes_local_probe_to_selected_cache(monkeypatch, tmp_path):
+    snapshot = tmp_path / "inactive" / "models--org--repo" / "snapshots" / "rev"
+    snapshot.mkdir(parents = True)
+    calls = []
+
+    async def scoped_variants(repo_id, **kwargs):
+        calls.append((repo_id, kwargs))
+        return SimpleNamespace(
+            repo_id = repo_id,
+            variants = [],
+            has_vision = False,
+            default_variant = None,
+        )
+
+    context_calls = []
+    monkeypatch.setattr(GV, "get_gguf_variants_response", scoped_variants)
+    monkeypatch.setattr(
+        models_route,
+        "_read_native_context_length",
+        lambda model, *, is_local: context_calls.append((model, is_local)) or 8192,
+    )
+
+    result = asyncio.run(
+        models_route.get_gguf_variants(
+            repo_id = "org/repo",
+            prefer_local_cache = True,
+            local_path = str(snapshot),
+            hf_token = None,
+            current_subject = "test-user",
+        )
+    )
+
+    assert calls == [
+        (
+            "org/repo",
+            {
+                "prefer_local_cache": True,
+                "local_path": str(snapshot),
+                "hf_token": None,
+            },
+        )
+    ]
+    assert context_calls == [(str(snapshot), True)]
+    assert result.context_length == 8192
+
+
 def test_gguf_variants_ignore_big_endian_siblings(monkeypatch, tmp_path):
     siblings = [
         SimpleNamespace(rfilename = "model-Q4_K_M-be.gguf", size = 100),
@@ -726,12 +883,16 @@ def test_gguf_variants_ignore_big_endian_siblings(monkeypatch, tmp_path):
             siblings,
         ),
     )
-    monkeypatch.setattr(GV, "_local_main_gguf_blobs_by_quant", lambda _repo_id: {})
+    monkeypatch.setattr(
+        GV,
+        "_local_main_gguf_blobs_by_quant",
+        lambda _repo_id, repo_cache_dir = None: {},
+    )
 
     snap = tmp_path / "models--org--repo" / "snapshots" / "rev"
     snap.mkdir(parents = True)
     (snap / "model-Q4_K_M.gguf").write_bytes(b"x" * 10)
-    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id: [snap])
+    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id, root = None: [snap])
 
     result = asyncio.run(
         models_route.get_gguf_variants(
@@ -758,12 +919,16 @@ def test_gguf_variants_cached_big_endian_does_not_satisfy_variant(monkeypatch, t
         "list_gguf_variants",
         lambda repo_id, hf_token = None: (variants, False, []),
     )
-    monkeypatch.setattr(GV, "_local_main_gguf_blobs_by_quant", lambda _repo_id: {})
+    monkeypatch.setattr(
+        GV,
+        "_local_main_gguf_blobs_by_quant",
+        lambda _repo_id, repo_cache_dir = None: {},
+    )
 
     snap = tmp_path / "models--org--repo" / "snapshots" / "rev"
     snap.mkdir(parents = True)
     (snap / "model-Q4_K_M-be.gguf").write_bytes(b"x" * 10)
-    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id: [snap])
+    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id, root = None: [snap])
 
     result = asyncio.run(
         models_route.get_gguf_variants(
@@ -774,66 +939,82 @@ def test_gguf_variants_cached_big_endian_does_not_satisfy_variant(monkeypatch, t
     assert result.variants[0].downloaded is False
 
 
-def test_gguf_download_progress_excludes_mmproj(monkeypatch, tmp_path):
-    """A cached mmproj adapter must not count toward a same-label main
-    variant's download progress (mmproj-F16 vs an F16 weight)."""
-    import huggingface_hub.constants as hf_constants
+def test_legacy_gguf_progress_delegates_to_shared_service(monkeypatch):
+    calls = []
 
-    monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
-    snap = tmp_path / "models--org--repo" / "snapshots" / "rev"
-    snap.mkdir(parents = True)
-    (snap / "mmproj-F16.gguf").write_bytes(b"y" * 20_000)  # only the adapter on disk
+    async def shared(repo_id, *, variant, expected_bytes, hf_token):
+        calls.append((repo_id, variant, expected_bytes, hf_token))
+        return {"downloaded_bytes": 10, "expected_bytes": 20, "progress": 0.5}
 
-    result = asyncio.run(
-        models_route.get_gguf_download_progress(
-            repo_id = "org/repo",
-            variant = "F16",
-            expected_bytes = 20_000,
-            current_subject = "test-user",
-        )
+    monkeypatch.setattr(
+        "hub.services.models.downloads.get_gguf_download_progress_response",
+        shared,
     )
 
-    assert result["downloaded_bytes"] == 0
-    assert result["progress"] == 0
-
-
-def test_gguf_download_progress_excludes_big_endian_sibling(monkeypatch, tmp_path):
-    import huggingface_hub.constants as hf_constants
-
-    monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
-    snap = tmp_path / "models--org--repo" / "snapshots" / "rev"
-    snap.mkdir(parents = True)
-    (snap / "model-Q4_K_M-be.gguf").write_bytes(b"y" * 20_000)
-
     result = asyncio.run(
         models_route.get_gguf_download_progress(
             repo_id = "org/repo",
             variant = "Q4_K_M",
-            expected_bytes = 20_000,
+            expected_bytes = 20,
+            hf_token = "token",
             current_subject = "test-user",
         )
     )
 
-    assert result["downloaded_bytes"] == 0
-    assert result["progress"] == 0
+    assert result["progress"] == 0.5
+    assert calls == [("org/repo", "Q4_K_M", 20, "token")]
 
 
-def test_gguf_download_progress_counts_quant_subdir(monkeypatch, tmp_path):
-    import huggingface_hub.constants as hf_constants
+def test_legacy_model_progress_delegates_to_shared_service(monkeypatch):
+    calls = []
 
-    monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
-    snap = tmp_path / "models--org--repo" / "snapshots" / "rev" / "Q4_K_M"
-    snap.mkdir(parents = True)
-    (snap / "foo.gguf").write_bytes(b"x" * 20_000)
+    async def shared(repo_id, *, hf_token):
+        calls.append((repo_id, hf_token))
+        return {"downloaded_bytes": 10, "expected_bytes": 20, "progress": 0.5}
+
+    monkeypatch.setattr(
+        "hub.services.models.downloads.get_download_progress_response",
+        shared,
+    )
 
     result = asyncio.run(
-        models_route.get_gguf_download_progress(
+        models_route.get_download_progress(
             repo_id = "org/repo",
-            variant = "Q4_K_M",
-            expected_bytes = 20_000,
+            hf_token = "token",
             current_subject = "test-user",
         )
     )
 
-    assert result["downloaded_bytes"] == 20_000
-    assert result["progress"] == 1.0
+    assert result["progress"] == 0.5
+    assert calls == [("org/repo", "token")]
+
+
+def test_legacy_delete_delegates_to_shared_service(monkeypatch):
+    calls = []
+
+    async def shared(
+        repo_id,
+        variant,
+        hf_token,
+        cache_path = None,
+    ):
+        calls.append((repo_id, variant, hf_token, cache_path))
+        return {"status": "deleted", "repo_id": repo_id}
+
+    monkeypatch.setattr(
+        "hub.services.models.deletion.delete_cached_model_response",
+        shared,
+    )
+
+    result = asyncio.run(
+        models_route.delete_cached_model(
+            repo_id = "org/repo",
+            variant = None,
+            cache_path = "/data/hf/hub",
+            hf_token = "token",
+            current_subject = "test-user",
+        )
+    )
+
+    assert result == {"status": "deleted", "repo_id": "org/repo"}
+    assert calls == [("org/repo", None, "token", "/data/hf/hub")]
diff --git a/studio/backend/tests/test_change_password_policy.py b/studio/backend/tests/test_change_password_policy.py
new file mode 100644
index 0000000000..c73e9ed839
--- /dev/null
+++ b/studio/backend/tests/test_change_password_policy.py
@@ -0,0 +1,75 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import asyncio
+import importlib.util
+import sys
+from pathlib import Path
+
+import pytest
+from fastapi import HTTPException
+
+_BACKEND_ROOT = Path(__file__).resolve().parents[1]
+if str(_BACKEND_ROOT) not in sys.path:
+    sys.path.insert(0, str(_BACKEND_ROOT))
+
+from models.auth import ChangePasswordRequest  # noqa: E402
+
+# Load routes/auth.py directly so collection does not execute routes/__init__.py,
+# which pulls in the heavy training/models/inference routers.
+_route_path = _BACKEND_ROOT / "routes" / "auth.py"
+_spec = importlib.util.spec_from_file_location("_change_password_route", _route_path)
+assert _spec is not None and _spec.loader is not None
+auth_routes = importlib.util.module_from_spec(_spec)
+_spec.loader.exec_module(auth_routes)
+
+
+@pytest.fixture
+def _user(monkeypatch):
+    monkeypatch.setattr(
+        auth_routes.storage,
+        "get_user_and_secret",
+        lambda username: ("salt", "hash", "jwt-secret", False),
+    )
+    monkeypatch.setattr(
+        auth_routes.hashing,
+        "verify_password",
+        lambda password, salt, pwd_hash: password == "bootstrap-pw",
+    )
+
+
+def _change(new_password):
+    payload = ChangePasswordRequest(
+        current_password = "bootstrap-pw",
+        new_password = new_password,
+    )
+    return asyncio.run(auth_routes.change_password(payload, None, "unsloth"))
+
+
+def test_rejects_whitespace_only_password(_user):
+    with pytest.raises(HTTPException) as excinfo:
+        _change(" " * 8)
+    assert excinfo.value.status_code == 400
+    assert "spaces" in excinfo.value.detail
+
+
+def test_rejects_tabs_and_spaces_password(_user):
+    with pytest.raises(HTTPException) as excinfo:
+        _change(" \t \t \t \t ")
+    assert excinfo.value.status_code == 400
+
+
+def test_rejects_password_containing_spaces(_user):
+    with pytest.raises(HTTPException) as excinfo:
+        _change("correct horse battery")
+    assert excinfo.value.status_code == 400
+    assert "spaces" in excinfo.value.detail
+
+
+def test_allows_password_without_spaces(_user, monkeypatch):
+    monkeypatch.setattr(auth_routes.storage, "update_password", lambda *args, **kwargs: True)
+    monkeypatch.setattr(auth_routes, "create_access_token", lambda subject: "at")
+    monkeypatch.setattr(auth_routes, "create_refresh_token", lambda subject: "rt")
+    token = _change("correct-horse-battery")
+    assert token.access_token == "at"
+    assert token.must_change_password is False
diff --git a/studio/backend/tests/test_chat_load_during_training.py b/studio/backend/tests/test_chat_load_during_training.py
index 7daa4224aa..a5fd71b6a0 100644
--- a/studio/backend/tests/test_chat_load_during_training.py
+++ b/studio/backend/tests/test_chat_load_during_training.py
@@ -801,6 +801,80 @@ class TestValidateRefusesDuringTraining(unittest.TestCase):
             asyncio.run(self.route.validate_model(request, current_subject = "u"))
         self.assertEqual(guard_called, [])
 
+    def _validate_gguf_template(
+        self,
+        *,
+        template,
+        canonical_path = "/picked/model.gguf",
+    ):
+        # Drive validate_model for a native lease-backed GGUF template probe and
+        # capture what the embedded-template reader was called with.
+        from models.inference import ValidateModelRequest
+
+        request = ValidateModelRequest(
+            model_path = "model.gguf",
+            gguf_variant = "Q4_K_M",
+            native_path_lease = "signed-lease",
+            include_chat_template = True,
+        )
+        cfg = SimpleNamespace(
+            identifier = canonical_path,
+            display_name = "model.gguf",
+            is_gguf = True,
+            is_lora = False,
+            is_vision = False,
+            gguf_file = canonical_path,
+            path = None,
+            base_model = None,
+        )
+        import utils.models.gguf_metadata as gguf_meta
+
+        seen = {}
+
+        def _fake_read(path):
+            seen["path"] = path
+            return template
+
+        guard_called = []
+        with (
+            patch.object(
+                self.route,
+                "_resolve_model_identifier_for_request",
+                return_value = (canonical_path, "model.gguf", True),
+            ),
+            patch.object(self.route.ModelConfig, "from_identifier", return_value = cfg),
+            patch.object(self.route, "load_inference_config", return_value = {}),
+            patch.object(gguf_meta, "read_gguf_chat_template", _fake_read),
+            patch.object(
+                self.route,
+                "_guard_chat_load_against_training",
+                lambda *a, **kw: guard_called.append(True),
+            ),
+        ):
+            resp = asyncio.run(self.route.validate_model(request, current_subject = "u"))
+        return resp, seen, guard_called
+
+    def test_include_chat_template_reads_leased_gguf_embedded_template(self):
+        # The picker chat-template GET has no lease plumbing, so a native picked
+        # GGUF surfaces its default template through this lease-aware probe: the
+        # embedded template is read from the granted canonical path and returned.
+        resp, seen, _ = self._validate_gguf_template(template = "{{ messages }}")
+        self.assertEqual(resp.chat_template, "{{ messages }}")
+        # Read strictly the leased file's own embedded template, never a sibling
+        # sidecar: the grant authorizes just this one path.
+        self.assertEqual(seen["path"], "/picked/model.gguf")
+
+    def test_include_chat_template_skips_training_guard(self):
+        # A template-only probe allocates no VRAM, so like include_context_length
+        # it must not be refused by the training guard.
+        _, _, guard_called = self._validate_gguf_template(template = "{{ messages }}")
+        self.assertEqual(guard_called, [])
+
+    def test_include_chat_template_over_cap_is_dropped(self):
+        from picker.schemas import MAX_CHAT_TEMPLATE_BYTES
+        resp, _, _ = self._validate_gguf_template(template = "a" * (MAX_CHAT_TEMPLATE_BYTES + 1))
+        self.assertIsNone(resp.chat_template)
+
 
 # ── _estimate_gguf_required_gb (sizes the same weights the loader loads) ──────
 
diff --git a/studio/backend/tests/test_cloudflare_tunnel.py b/studio/backend/tests/test_cloudflare_tunnel.py
index bb51cabf76..2094d15066 100644
--- a/studio/backend/tests/test_cloudflare_tunnel.py
+++ b/studio/backend/tests/test_cloudflare_tunnel.py
@@ -403,11 +403,234 @@ def test_reader_ignores_api_endpoint_failure_line():
     assert t.error == "cloudflared exited before emitting a tunnel URL"
 
 
+# ── public reachability probe ────────────────────────────────────────
+
+
+class _FakeResponse:
+    def __init__(self, body):
+        self._body = body
+
+    def read(self, size = -1):
+        return self._body
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *exc):
+        return False
+
+
+def _patch_urlopen(monkeypatch, handler):
+    import urllib.request
+    monkeypatch.setattr(urllib.request, "urlopen", lambda req, timeout = None: handler(req))
+
+
+@pytest.fixture(autouse = True)
+def _stub_dns_wait(monkeypatch, request):
+    if request.node.name.startswith("test_verify_public_url"):
+        monkeypatch.setattr(ct, "_wait_for_dns", lambda *a, **kw: None)
+
+
+def test_wait_for_dns_polls_until_answer(monkeypatch):
+    calls = []
+
+    def handler(req):
+        calls.append(req.full_url)
+        if len(calls) < 3:
+            return _FakeResponse(b'{"Status":3}')
+        return _FakeResponse(b'{"Status":0,"Answer":[{"data":"104.16.0.1"}]}')
+
+    _patch_urlopen(monkeypatch, handler)
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    ct._wait_for_dns("words.trycloudflare.com", ct.time.monotonic() + 5)
+    assert len(calls) == 3
+    assert "name=words.trycloudflare.com" in calls[0]
+
+
+def test_wait_for_dns_gives_up_at_deadline(monkeypatch):
+    _patch_urlopen(monkeypatch, lambda req: _FakeResponse(b'{"Status":3}'))
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    ct._wait_for_dns("words.trycloudflare.com", ct.time.monotonic() + 0.05)
+
+
+def test_wait_for_dns_retries_transient_doh_error(monkeypatch):
+    calls = []
+
+    def handler(req):
+        calls.append(req.full_url)
+        if len(calls) < 3:
+            raise OSError("transient")
+        return _FakeResponse(b'{"Status":0,"Answer":[{"data":"104.16.0.1"}]}')
+
+    _patch_urlopen(monkeypatch, handler)
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    ct._wait_for_dns("words.trycloudflare.com", ct.time.monotonic() + 5)
+    assert len(calls) == 3
+
+
+def test_wait_for_dns_bails_on_persistent_doh_errors(monkeypatch):
+    calls = []
+
+    def handler(req):
+        calls.append(req.full_url)
+        raise OSError("blocked")
+
+    _patch_urlopen(monkeypatch, handler)
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    ct._wait_for_dns("words.trycloudflare.com", ct.time.monotonic() + 5)
+    assert len(calls) == ct._DNS_MAX_DOH_ERRORS
+
+
+def test_verify_public_url_accepts_studio_marker(monkeypatch):
+    seen = {}
+
+    def handler(req):
+        seen["url"] = req.full_url
+        return _FakeResponse(b'{"status":"healthy","service":"Unsloth UI Backend"}')
+
+    _patch_urlopen(monkeypatch, handler)
+    assert ct.verify_public_url("https://words.trycloudflare.com") is True
+    assert seen["url"] == "https://words.trycloudflare.com/api/health"
+
+
+def test_verify_public_url_waits_for_dns_first(monkeypatch):
+    order = []
+    monkeypatch.setattr(ct, "_wait_for_dns", lambda host, deadline: order.append(("dns", host)))
+
+    def handler(req):
+        order.append(("probe", req.full_url))
+        return _FakeResponse(b'{"service":"Unsloth UI Backend"}')
+
+    _patch_urlopen(monkeypatch, handler)
+    assert ct.verify_public_url("https://words.trycloudflare.com") is True
+    assert order[0] == ("dns", "words.trycloudflare.com")
+    assert order[1][0] == "probe"
+
+
+def test_verify_public_url_dns_wait_and_probe_share_deadline(monkeypatch):
+    # An exhausted DNS wait leaves the probe a single attempt, not a fresh window.
+    calls = []
+    monkeypatch.setattr(ct, "_wait_for_dns", lambda host, deadline: None)
+
+    def handler(req):
+        calls.append(req.full_url)
+        raise OSError("unreachable")
+
+    _patch_urlopen(monkeypatch, handler)
+    assert ct.verify_public_url("https://words.trycloudflare.com", timeout = 0) is False
+    assert len(calls) == 1
+
+
+def test_verify_public_url_retries_then_succeeds(monkeypatch):
+    calls = []
+
+    def handler(req):
+        calls.append(req.full_url)
+        if len(calls) < 3:
+            raise OSError("Name or service not known")
+        return _FakeResponse(b'{"service":"Unsloth UI Backend"}')
+
+    _patch_urlopen(monkeypatch, handler)
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    assert ct.verify_public_url("https://words.trycloudflare.com") is True
+    assert len(calls) == 3
+
+
+def test_verify_public_url_rejects_unreachable_host(monkeypatch):
+    def handler(req):
+        raise OSError("Name or service not known")
+
+    _patch_urlopen(monkeypatch, handler)
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    assert ct.verify_public_url("https://words.trycloudflare.com", timeout = 0.05) is False
+
+
+def test_verify_public_url_rejects_foreign_responder(monkeypatch):
+    # e.g. a Cloudflare error page: no service marker in the body.
+    _patch_urlopen(monkeypatch, lambda req: _FakeResponse(b"<html>error 1033</html>"))
+    monkeypatch.setattr(ct.time, "sleep", lambda _s: None)
+    assert ct.verify_public_url("https://words.trycloudflare.com", timeout = 0.05) is False
+
+
+@pytest.fixture(autouse = True)
+def _stub_public_probe(monkeypatch, request):
+    # start_studio_tunnel tests use fake hostnames; keep them off the network.
+    if not request.node.name.startswith("test_start_studio_tunnel"):
+        return
+    monkeypatch.setattr(ct, "verify_public_url", lambda url, **kw: True)
+
+
 def test_start_studio_tunnel_no_binary(monkeypatch):
     monkeypatch.setattr(ct, "ensure_cloudflared", lambda: None)
     assert ct.start_studio_tunnel(8080) is None
 
 
+def test_start_studio_tunnel_drops_url_that_is_not_publicly_reachable(monkeypatch):
+    attempts = []
+
+    class _Stub:
+        def __init__(
+            self,
+            port,
+            binary,
+            protocol = None,
+        ):
+            self.url = None
+            attempts.append(protocol)
+
+        def start(self):
+            self.url = "https://words.trycloudflare.com"
+
+        def wait_for_ready(self, timeout):
+            return self.url
+
+        def stop(self):
+            pass
+
+    monkeypatch.setattr(ct, "ensure_cloudflared", lambda: "/bin/cloudflared")
+    monkeypatch.setattr(ct, "CloudflareTunnel", _Stub)
+    monkeypatch.setattr(ct, "verify_public_url", lambda url, **kw: False)
+    assert ct.start_studio_tunnel(8080) is None
+    assert attempts == [None]
+    assert ct._active_tunnel is None
+
+
+def test_start_studio_tunnel_returns_url_once_probe_passes(monkeypatch):
+    probed = []
+
+    class _Stub:
+        def __init__(
+            self,
+            port,
+            binary,
+            protocol = None,
+        ):
+            self.url = None
+            self.protocol = protocol
+
+        def start(self):
+            self.url = "https://words.trycloudflare.com"
+
+        def wait_for_ready(self, timeout):
+            return self.url
+
+        def stop(self):
+            pass
+
+    def _probe(url, **kw):
+        probed.append(url)
+        return True
+
+    monkeypatch.setattr(ct, "ensure_cloudflared", lambda: "/bin/cloudflared")
+    monkeypatch.setattr(ct, "CloudflareTunnel", _Stub)
+    monkeypatch.setattr(ct, "verify_public_url", _probe)
+    try:
+        assert ct.start_studio_tunnel(8080) == "https://words.trycloudflare.com"
+        assert probed == ["https://words.trycloudflare.com"]
+    finally:
+        ct.stop_studio_tunnel()
+
+
 def test_start_studio_tunnel_registers_before_wait(monkeypatch):
     # The tunnel must be visible to stop_studio_tunnel() during the readiness
     # wait, else a shutdown in that window orphans cloudflared.
diff --git a/studio/backend/tests/test_combined_update.py b/studio/backend/tests/test_combined_update.py
new file mode 100644
index 0000000000..b96d3d030c
--- /dev/null
+++ b/studio/backend/tests/test_combined_update.py
@@ -0,0 +1,735 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Hermetic tests for the combined llama+whisper update item.
+
+llama.cpp is the single main update item; whisper.cpp piggybacks on it. These
+pin the union status (update_available = llama behind OR whisper behind), the
+chained apply (llama phase first, whisper phase only when behind), the failure
+policy (llama failure aborts; whisper failure keeps the llama partial success),
+the silent whisper skips, and the backward-compatible payload shape.
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+import time
+from pathlib import Path
+
+import pytest
+
+_BACKEND = Path(__file__).resolve().parents[1]
+if str(_BACKEND) not in sys.path:
+    sys.path.insert(0, str(_BACKEND))
+
+import utils.llama_cpp_freshness as freshness  # noqa: E402
+import utils.llama_cpp_update as upd  # noqa: E402
+import utils.whisper_cpp_freshness as wfresh  # noqa: E402
+import utils.whisper_cpp_update as wupd  # noqa: E402
+
+MARKER = "UNSLOTH_PREBUILT_INFO.json"
+WHISPER_MARKER = "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+
+# The top-level status and job fields that predate the whisper piggyback; the
+# combined payload must stay an exact superset so current UI code keeps working.
+LEGACY_STATUS_FIELDS = {
+    "supported",
+    "update_available",
+    "stale",
+    "installed_tag",
+    "latest_tag",
+    "published_repo",
+    "installed_at_utc",
+    "age_days",
+    "source_build",
+    "update_size_bytes",
+    "job",
+}
+LEGACY_JOB_FIELDS = {
+    "state",
+    "message",
+    "from_tag",
+    "to_tag",
+    "reload_required",
+    "error",
+    "progress",
+    "started_at",
+    "finished_at",
+}
+
+
+class _FakeInstallerPopen:
+    """Stands in for the streamed llama installer process."""
+
+    def __init__(
+        self,
+        cmd,
+        *,
+        returncode = 0,
+        lines = None,
+        on_start = None,
+        **kwargs,
+    ):
+        if on_start is not None:
+            on_start(list(cmd))
+        self.returncode = returncode
+        self.stdout = iter(lines or [])
+
+    def wait(self):
+        return self.returncode
+
+    def kill(self):
+        pass
+
+
+def _patch_llama_installer(
+    monkeypatch,
+    *,
+    returncode = 0,
+    lines = None,
+    on_start = None,
+):
+    # Only intercept the installer invocation: importing routes.inference inside
+    # the worker can Popen unrelated host probes (ldconfig etc).
+    def _popen(cmd, **kw):
+        is_installer = any("install_llama_prebuilt" in str(part) for part in cmd)
+        return _FakeInstallerPopen(
+            cmd,
+            returncode = returncode if is_installer else 0,
+            lines = lines if is_installer else None,
+            on_start = on_start if is_installer else None,
+        )
+
+    monkeypatch.setattr(upd.subprocess, "Popen", _popen)
+
+
+def _write_llama_install(dir_: Path, tag: str) -> str:
+    """Create a fake llama prebuilt install and return the llama-server path."""
+    bin_dir = dir_ / "build" / "bin"
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    binary = bin_dir / "llama-server"
+    binary.write_text("stub")
+    (dir_ / MARKER).write_text(
+        json.dumps(
+            {
+                "tag": tag,
+                "release_tag": tag,
+                "published_repo": "unslothai/llama.cpp",
+                "installed_at_utc": "2020-01-01T00:00:00Z",
+            }
+        )
+    )
+    return str(binary)
+
+
+def _write_whisper_install(
+    dir_: Path,
+    tag: str,
+    backend: str = "cpu",
+) -> str:
+    """Create a fake whisper prebuilt install and return the whisper-server path."""
+    bin_dir = dir_ / "build" / "bin"
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    binary = bin_dir / "whisper-server"
+    binary.write_text("stub")
+    (dir_ / WHISPER_MARKER).write_text(
+        json.dumps(
+            {
+                "release_tag": tag,
+                "upstream_tag": tag.split("-")[0],
+                "published_repo": "unslothai/whisper.cpp",
+                "backend": backend,
+                "installed_at_utc": "2020-01-01T00:00:00Z",
+            }
+        )
+    )
+    return str(binary)
+
+
+@pytest.fixture(autouse = True)
+def _clean_state(monkeypatch, tmp_path):
+    freshness.reset_caches()
+    wfresh.reset_caches()
+    upd._reset_job_for_tests()
+    upd._resolve_memo.clear()
+    wupd._resolve_memo.clear()
+    monkeypatch.setattr(freshness, "_cache_dir", lambda: tmp_path / ".llama_cache")
+    monkeypatch.setattr(wfresh, "_cache_dir", lambda: tmp_path / ".whisper_cache")
+    for var in (
+        "LLAMA_SERVER_PATH",
+        "UNSLOTH_LLAMA_CPP_PATH",
+        "WHISPER_SERVER_PATH",
+        "UNSLOTH_WHISPER_CPP_PATH",
+    ):
+        monkeypatch.delenv(var, raising = False)
+    # Never hit the network in these tests.
+    monkeypatch.setattr(freshness, "_fetch_latest_release_tag", lambda repo, timeout = 5.0: None)
+    monkeypatch.setattr(wfresh, "_fetch_latest_release_tag", lambda repo, timeout = 5.0: None)
+    yield
+    freshness.reset_caches()
+    wfresh.reset_caches()
+    upd._reset_job_for_tests()
+    upd._resolve_memo.clear()
+    wupd._resolve_memo.clear()
+
+
+def _setup_llama(
+    monkeypatch,
+    tmp_path,
+    *,
+    installed = "b9493",
+    latest = "b9518",
+):
+    """Marker-managed llama install; behind when installed != latest."""
+    install_dir = tmp_path / "llama.cpp"
+    binary = _write_llama_install(install_dir, installed)
+    monkeypatch.setattr(upd, "_find_binary", lambda: binary)
+    monkeypatch.setattr(upd, "_installer_script", lambda: tmp_path / "install_llama_prebuilt.py")
+    monkeypatch.setattr(freshness, "_fetch_latest_release_tag", lambda repo, timeout = 5.0: latest)
+    return install_dir
+
+
+def _setup_whisper(
+    monkeypatch,
+    tmp_path,
+    *,
+    installed = "v1.9.1-unsloth.1",
+    latest = "v1.9.2-unsloth.1",
+):
+    """Marker-managed whisper install; behind when latest is newer."""
+    install_dir = tmp_path / "whisper.cpp"
+    binary = _write_whisper_install(install_dir, installed)
+    monkeypatch.setattr(wupd, "_find_binary", lambda: binary)
+    monkeypatch.setattr(wupd, "_installer_script", lambda: tmp_path / "install_whisper_prebuilt.py")
+    monkeypatch.setattr(wfresh, "_fetch_latest_release_tag", lambda repo, timeout = 5.0: latest)
+    return install_dir
+
+
+def _patch_whisper_phase(
+    monkeypatch,
+    events,
+    *,
+    to_tag = "v1.9.2-unsloth.1",
+    error = None,
+):
+    """Record whisper phase runs without touching a real installer."""
+
+    def _run(phase, set_progress):
+        events.append("whisper")
+        if error is not None:
+            raise RuntimeError(error)
+        set_progress(0.5)
+        return {
+            "to_tag": to_tag,
+            "reload_required": False,
+            "message": f"Updated whisper.cpp to {to_tag}.",
+        }
+
+    monkeypatch.setattr(wupd, "run_chained_phase", _run)
+
+
+def _wait_for_job():
+    deadline = time.time() + 10
+    while time.time() < deadline:
+        with upd._job_lock:
+            job = dict(upd._job)
+        if job["state"] in ("success", "error"):
+            return job
+        time.sleep(0.05)
+    with upd._job_lock:
+        return dict(upd._job)
+
+
+# --- status: the single item folds whisper in ---
+
+
+def test_status_payload_is_exact_superset_of_legacy_fields(monkeypatch, tmp_path):
+    _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path)
+    st = upd.get_update_status(force_refresh = True)
+    assert LEGACY_STATUS_FIELDS <= set(st)
+    assert LEGACY_JOB_FIELDS <= set(st["job"])
+    # The new fields ride alongside, never replacing the legacy ones.
+    assert st["llama_update_available"] is True
+    assert st["whisper"]["update_available"] is True
+    assert st["whisper"]["latest_tag"] == "v1.9.2-unsloth.1"
+    assert st["update_component"] == "llama"
+
+
+def test_status_union_whisper_only_surfaces_update(monkeypatch, tmp_path):
+    # llama current, whisper behind: the single item still shows an update.
+    _setup_llama(monkeypatch, tmp_path, installed = "b9518", latest = "b9518")
+    _setup_whisper(monkeypatch, tmp_path)
+    st = upd.get_update_status(force_refresh = True)
+    assert st["llama_update_available"] is False
+    assert st["whisper"]["update_available"] is True
+    assert st["update_available"] is True
+    assert st["update_component"] == "whisper"
+    assert st["installed_tag"] == "b9518"
+    assert st["latest_tag"] == "b9518"
+    assert st["whisper"]["installed_tag"] == "v1.9.1-unsloth.1"
+    assert st["whisper"]["latest_tag"] == "v1.9.2-unsloth.1"
+
+
+def test_status_whisper_current_does_not_flip_union(monkeypatch, tmp_path):
+    _setup_llama(monkeypatch, tmp_path, installed = "b9518", latest = "b9518")
+    _setup_whisper(monkeypatch, tmp_path, installed = "v1.9.2-unsloth.1", latest = "v1.9.2-unsloth.1")
+    st = upd.get_update_status(force_refresh = True)
+    assert st["update_available"] is False
+    assert st["whisper"]["skip_reason"] == "up_to_date"
+    assert st["update_component"] is None
+
+
+def test_status_survives_whisper_probe_failure(monkeypatch, tmp_path):
+    # The piggyback fails open: llama status still works without a whisper probe.
+    _setup_llama(monkeypatch, tmp_path)
+
+    def _boom(*, force_refresh = False):
+        raise RuntimeError("probe exploded")
+
+    monkeypatch.setattr(wupd, "chained_phase_plan", _boom)
+    st = upd.get_update_status(force_refresh = True)
+    assert st["update_available"] is True
+    assert st["whisper"] is None
+
+
+# --- whisper chained_phase_plan: silent skips ---
+
+
+def test_whisper_plan_skips_local_link(monkeypatch, tmp_path):
+    monkeypatch.setattr(wupd, "_find_binary", lambda: str(tmp_path / "whisper-server"))
+    monkeypatch.setattr(wupd, "_active_install_is_local_link", lambda b: True)
+    plan = wupd.chained_phase_plan()
+    assert plan["update_available"] is False
+    assert plan["skip_reason"] == "local_link"
+    assert plan["phase"] is None
+
+
+def test_whisper_plan_skips_source_build(monkeypatch, tmp_path):
+    binary = tmp_path / "whisper.cpp" / "build" / "bin" / "whisper-server"
+    binary.parent.mkdir(parents = True)
+    binary.write_text("stub")  # no marker
+    monkeypatch.setattr(wupd, "_find_binary", lambda: str(binary))
+    plan = wupd.chained_phase_plan()
+    assert plan["skip_reason"] == "source_build"
+    assert plan["phase"] is None
+
+
+def test_whisper_update_targets_canonical_root_when_inner_marker_exists(tmp_path):
+    install_dir = tmp_path / "whisper.cpp"
+    binary = install_dir / "build" / "bin" / "whisper-server"
+    binary.parent.mkdir(parents = True)
+    binary.write_text("stub")
+    (install_dir / WHISPER_MARKER).write_text("{}")
+    (binary.parent / WHISPER_MARKER).write_text("{}")
+    assert wupd._install_dir_for(str(binary)) == install_dir
+
+
+def test_whisper_plan_skips_when_not_installed(monkeypatch):
+    monkeypatch.setattr(wupd, "_find_binary", lambda: None)
+    plan = wupd.chained_phase_plan()
+    assert plan["skip_reason"] == "not_installed"
+    assert plan["phase"] is None
+
+
+def test_whisper_plan_eligible_when_behind(monkeypatch, tmp_path):
+    install_dir = _setup_whisper(monkeypatch, tmp_path)
+    script = tmp_path / "install_whisper_prebuilt.py"
+    script.write_text("stub")
+    plan = wupd.chained_phase_plan(force_refresh = True)
+    assert plan["update_available"] is True
+    assert plan["skip_reason"] is None
+    assert plan["phase"]["install_dir"] == install_dir
+    assert plan["phase"]["repo"] == "unslothai/whisper.cpp"
+    assert plan["phase"]["backend"] == "cpu"
+    # Pin to the exact release the freshness check offered: unpinned, the
+    # installer's download-host /releases/latest pointer can lag published_at
+    # and reinstall an older build in a loop.
+    assert plan["phase"]["pin_release_tag"] == "v1.9.2-unsloth.1"
+
+
+def test_whisper_plan_requires_a_repairable_pair_for_slim_installs(monkeypatch, tmp_path):
+    install_dir = _setup_whisper(monkeypatch, tmp_path)
+    marker_path = install_dir / WHISPER_MARKER
+    marker = json.loads(marker_path.read_text())
+    marker["install_kind"] = "slim"
+    marker_path.write_text(json.dumps(marker))
+    wfresh.reset_caches()
+    monkeypatch.setattr(
+        wupd,
+        "_resolve_prebuilt_for_host",
+        lambda **kwargs: {"prebuilt_available": False},
+    )
+
+    plan = wupd.chained_phase_plan(force_refresh = True)
+    assert plan["update_available"] is False
+    assert plan["skip_reason"] == "paired_llama_unavailable"
+
+    repaired = wupd.chained_phase_plan(
+        force_refresh = True,
+        paired_llama_will_update = True,
+    )
+    assert repaired["update_available"] is True
+    assert repaired["phase"] is not None
+
+
+def test_whisper_phase_pins_installer_to_checked_release(monkeypatch, tmp_path):
+    calls = []
+    monkeypatch.setattr(
+        wupd._flow,
+        "stream_installer",
+        lambda cmd, env, **kw: calls.append(cmd),
+    )
+    monkeypatch.setattr(wupd, "reset_caches", lambda **kw: None)
+    monkeypatch.setattr(wupd, "latest_published_release", lambda repo, **kw: "v9")
+    install_dir = tmp_path / "whisper.cpp"
+    binary = _write_whisper_install(install_dir, "v9")
+    monkeypatch.setattr(wupd, "_find_binary", lambda: binary)
+    wupd.run_chained_phase(
+        {
+            "install_dir": install_dir,
+            "repo": "unslothai/whisper.cpp",
+            "asset": None,
+            "backend": "cpu",
+            "script": tmp_path / "install_whisper_prebuilt.py",
+            "pin_release_tag": "v9",
+        },
+        lambda f: None,
+    )
+    cmd = calls[0]
+    assert "--published-release-tag" in cmd
+    assert cmd[cmd.index("--published-release-tag") + 1] == "v9"
+
+
+def test_whisper_phase_exit_2_is_a_failed_phase(monkeypatch, tmp_path):
+    # No install occurred, so incompatibility must remain an actionable job
+    # error instead of producing a false success toast and hiding the banner.
+    def _raise_exit_2(cmd, env, **kw):
+        raise wupd._flow.InstallerExit(2, "installer exited 2: incompatible release")
+
+    monkeypatch.setattr(wupd._flow, "stream_installer", _raise_exit_2)
+    install_dir = tmp_path / "whisper.cpp"
+    binary = _write_whisper_install(install_dir, "v1")
+    monkeypatch.setattr(wupd, "_find_binary", lambda: binary)
+    with pytest.raises(wupd._flow.InstallerExit) as exc_info:
+        wupd.run_chained_phase(
+            {
+                "install_dir": install_dir,
+                "repo": "unslothai/whisper.cpp",
+                "asset": None,
+                "backend": "cpu",
+                "script": tmp_path / "install_whisper_prebuilt.py",
+                "pin_release_tag": None,
+            },
+            lambda f: None,
+        )
+    assert exc_info.value.returncode == 2
+
+
+def test_llama_update_survives_unavailable_whisper_module(monkeypatch, tmp_path):
+    import builtins
+
+    llama_dir = _setup_llama(monkeypatch, tmp_path)
+    monkeypatch.setattr(upd, "_whisper_chain_status", lambda **kw: None)
+    _patch_llama_installer(
+        monkeypatch,
+        on_start = lambda cmd: _write_llama_install(llama_dir, "b9518"),
+    )
+    real_import = builtins.__import__
+
+    def guarded_import(
+        name,
+        globals = None,
+        locals = None,
+        fromlist = (),
+        level = 0,
+    ):
+        if name == "utils" and "whisper_cpp_update" in fromlist:
+            raise AssertionError("whisper module was re-imported after its failed probe")
+        return real_import(name, globals, locals, fromlist, level)
+
+    monkeypatch.setattr(builtins, "__import__", guarded_import)
+
+    # A failed optional whisper probe must not be followed by an unconditional
+    # import. The valid llama phase still starts and completes.
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert job["phases"]["llama"]["state"] == "success"
+    assert job["phases"]["whisper"]["state"] == "skipped"
+    assert job["phases"]["whisper"]["reason"] == "unavailable"
+
+
+def test_macos_status_uses_compatible_resolver_release(monkeypatch, tmp_path):
+    _setup_whisper(
+        monkeypatch,
+        tmp_path,
+        installed = "v1.9.1-unsloth.1",
+        latest = "v1.9.2-unsloth.1",
+    )
+    monkeypatch.setattr(wupd.sys, "platform", "darwin")
+    monkeypatch.setattr(
+        wupd,
+        "_resolve_prebuilt_for_host",
+        lambda **kw: {
+            "prebuilt_available": True,
+            "release_tag": "v1.9.1-unsloth.1",
+        },
+    )
+
+    status = wupd.get_update_status(force_refresh = True)
+    assert status["latest_tag"] == "v1.9.1-unsloth.1"
+    assert status["update_available"] is False
+    assert status["stale"] is False
+
+
+def test_whisper_phase_integrity_failure_is_not_swallowed(monkeypatch, tmp_path):
+    def _raise_exit_1(cmd, env, **kw):
+        raise wupd._flow.InstallerExit(1, "installer exited 1: checksum mismatch")
+
+    monkeypatch.setattr(wupd._flow, "stream_installer", _raise_exit_1)
+    install_dir = tmp_path / "whisper.cpp"
+    binary = _write_whisper_install(install_dir, "v1")
+    monkeypatch.setattr(wupd, "_find_binary", lambda: binary)
+    with pytest.raises(wupd._flow.InstallerExit, match = "checksum mismatch"):
+        wupd.run_chained_phase(
+            {
+                "install_dir": install_dir,
+                "repo": "unslothai/whisper.cpp",
+                "asset": None,
+                "backend": "cpu",
+                "script": tmp_path / "install_whisper_prebuilt.py",
+                "pin_release_tag": None,
+            },
+            lambda f: None,
+        )
+
+
+# --- apply: the chained job ---
+
+
+def test_apply_runs_llama_then_whisper(monkeypatch, tmp_path):
+    llama_dir = _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path)
+    (tmp_path / "install_whisper_prebuilt.py").write_text("stub")
+
+    events = []
+    _patch_llama_installer(
+        monkeypatch,
+        on_start = lambda cmd: (events.append("llama"), _write_llama_install(llama_dir, "b9518")),
+    )
+    _patch_whisper_phase(monkeypatch, events)
+
+    res = upd.start_update()
+    assert res["started"] is True, res
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert events == ["llama", "whisper"]  # llama phase strictly first
+    assert job["phases"]["llama"]["state"] == "success"
+    assert job["phases"]["llama"]["to_tag"] == "b9518"
+    assert job["phases"]["whisper"]["state"] == "success"
+    assert job["phases"]["whisper"]["to_tag"] == "v1.9.2-unsloth.1"
+    # Legacy top-level fields keep their llama meaning.
+    assert job["from_tag"] == "b9493"
+    assert job["to_tag"] == "b9518"
+    assert "Updated llama.cpp to b9518." in job["message"]
+    assert "Updated whisper.cpp to v1.9.2-unsloth.1." in job["message"]
+    assert job["progress"] == 1.0
+    assert LEGACY_JOB_FIELDS <= set(job)
+
+
+def test_apply_llama_only_when_whisper_current(monkeypatch, tmp_path):
+    llama_dir = _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path, installed = "v1.9.2-unsloth.1", latest = "v1.9.2-unsloth.1")
+
+    events = []
+    _patch_llama_installer(
+        monkeypatch,
+        on_start = lambda cmd: (events.append("llama"), _write_llama_install(llama_dir, "b9518")),
+    )
+    _patch_whisper_phase(monkeypatch, events)
+
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert events == ["llama"]
+    assert job["phases"]["whisper"]["state"] == "skipped"
+    assert job["phases"]["whisper"]["reason"] == "up_to_date"
+
+
+def test_apply_whisper_only_noops_llama(monkeypatch, tmp_path):
+    # llama current + whisper behind: the same single apply runs, with the llama
+    # phase a cheap already-matches no-op and the whisper phase doing the work.
+    _setup_llama(monkeypatch, tmp_path, installed = "b9518", latest = "b9518")
+    _setup_whisper(monkeypatch, tmp_path)
+    (tmp_path / "install_whisper_prebuilt.py").write_text("stub")
+
+    events = []
+    _patch_llama_installer(monkeypatch, on_start = lambda cmd: events.append("llama"))
+    _patch_whisper_phase(monkeypatch, events)
+
+    res = upd.start_update()
+    assert res["started"] is True, res
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert events == ["whisper"]  # the llama installer never ran
+    # The legacy job-level to_tag means "llama tag"; a whisper-only round
+    # leaves it unset so the UI never reports a llama update that never ran.
+    assert job["to_tag"] is None
+    assert job["phases"]["llama"]["state"] == "skipped"
+    assert job["phases"]["llama"]["reason"] == "up_to_date"
+    assert job["phases"]["whisper"]["state"] == "success"
+    assert "Updated whisper.cpp to v1.9.2-unsloth.1." in job["message"]
+
+
+def test_whisper_reload_never_raises_job_reload_flag(monkeypatch, tmp_path):
+    # A whisper-only update that had to unload a warm sidecar reports
+    # reload_required on its phase, but the JOB flag stays down: the chat
+    # frontend resyncs (and clears the local checkpoint) off the job flag,
+    # which must mean "the llama server changed", not "the sidecar restarted".
+    _setup_llama(monkeypatch, tmp_path, installed = "b9518", latest = "b9518")
+    _setup_whisper(monkeypatch, tmp_path)
+    (tmp_path / "install_whisper_prebuilt.py").write_text("stub")
+
+    def _whisper_phase(phase, set_progress):
+        return {
+            "to_tag": "v1.9.2-unsloth.1",
+            "reload_required": True,
+            "message": "Updated whisper.cpp to v1.9.2-unsloth.1.",
+        }
+
+    monkeypatch.setattr(wupd, "run_chained_phase", _whisper_phase)
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert job["phases"]["whisper"]["reload_required"] is True
+    assert not job["reload_required"]
+
+
+def test_apply_refuses_when_both_current(monkeypatch, tmp_path):
+    _setup_llama(monkeypatch, tmp_path, installed = "b9518", latest = "b9518")
+    _setup_whisper(monkeypatch, tmp_path, installed = "v1.9.2-unsloth.1", latest = "v1.9.2-unsloth.1")
+    res = upd.start_update()
+    assert res["started"] is False
+    assert res["reason"] == "up_to_date"
+
+
+def test_apply_llama_failure_aborts_before_whisper(monkeypatch, tmp_path):
+    _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path)
+    (tmp_path / "install_whisper_prebuilt.py").write_text("stub")
+
+    events = []
+    _patch_llama_installer(monkeypatch, returncode = 2, lines = ["boom: disk full\n"])
+    _patch_whisper_phase(monkeypatch, events)
+
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "error", job
+    assert "boom" in (job["error"] or "")
+    assert events == []  # whisper never attempted
+    assert job["phases"]["llama"]["state"] == "error"
+    assert job["phases"]["whisper"]["state"] == "skipped"
+    assert job["phases"]["whisper"]["reason"] == "aborted"
+    assert job["message"] == "llama.cpp update failed."
+
+
+def test_apply_whisper_failure_keeps_llama_partial_success(monkeypatch, tmp_path):
+    llama_dir = _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path)
+    (tmp_path / "install_whisper_prebuilt.py").write_text("stub")
+
+    # An active model makes the llama phase report reload_required.
+    import threading
+    from types import ModuleType
+
+    class _FakeBackend:
+        def __init__(self):
+            self._serial_load_lock = threading.Lock()
+            self._llama_update_in_progress = False
+            self.is_active = True
+
+        def unload_model(self):
+            self.is_active = False
+
+    backend = _FakeBackend()
+    routes_pkg = ModuleType("routes")
+    routes_pkg.__path__ = []
+    inference_mod = ModuleType("routes.inference")
+    inference_mod.get_llama_cpp_backend = lambda: backend
+    monkeypatch.setitem(sys.modules, "routes", routes_pkg)
+    monkeypatch.setitem(sys.modules, "routes.inference", inference_mod)
+
+    events = []
+    _patch_llama_installer(
+        monkeypatch,
+        on_start = lambda cmd: (events.append("llama"), _write_llama_install(llama_dir, "b9518")),
+    )
+    _patch_whisper_phase(monkeypatch, events, error = "whisper installer exploded")
+
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "error", job
+    assert events == ["llama", "whisper"]
+    # The message says both halves: llama landed, whisper did not.
+    assert "Updated llama.cpp to b9518." in job["message"]
+    assert "whisper.cpp update failed." in job["message"]
+    assert "whisper installer exploded" in (job["error"] or "")
+    # The llama phase's reload_required survives the whisper failure.
+    assert job["reload_required"] is True
+    assert job["to_tag"] == "b9518"
+    assert job["phases"]["llama"]["state"] == "success"
+    assert job["phases"]["whisper"]["state"] == "error"
+
+
+def test_apply_skips_whisper_local_link_silently(monkeypatch, tmp_path):
+    llama_dir = _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path)
+    monkeypatch.setattr(wupd, "_active_install_is_local_link", lambda b: True)
+
+    events = []
+    _patch_llama_installer(
+        monkeypatch,
+        on_start = lambda cmd: (events.append("llama"), _write_llama_install(llama_dir, "b9518")),
+    )
+    _patch_whisper_phase(monkeypatch, events)
+
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert events == ["llama"]
+    assert job["phases"]["whisper"]["state"] == "skipped"
+    assert job["phases"]["whisper"]["reason"] == "local_link"
+    assert job["message"] == "Updated llama.cpp to b9518."
+
+
+def test_chained_progress_windows(monkeypatch, tmp_path):
+    # The llama phase fills roughly the first 0.7 slice and whisper the rest.
+    llama_dir = _setup_llama(monkeypatch, tmp_path)
+    _setup_whisper(monkeypatch, tmp_path)
+    (tmp_path / "install_whisper_prebuilt.py").write_text("stub")
+
+    seen = {}
+
+    def _whisper_phase(phase, set_progress):
+        with upd._job_lock:
+            seen["at_whisper_start"] = upd._job["progress"]
+        set_progress(0.5)
+        with upd._job_lock:
+            seen["mid_whisper"] = upd._job["progress"]
+        return {"to_tag": "v1.9.2-unsloth.1", "reload_required": False, "message": "ok"}
+
+    monkeypatch.setattr(wupd, "run_chained_phase", _whisper_phase)
+    _patch_llama_installer(
+        monkeypatch,
+        lines = ["Downloading app.tar.gz: 100.0% (35.0 MiB/35.0 MiB) at 9.0 MiB/s\n"],
+        on_start = lambda cmd: _write_llama_install(llama_dir, "b9518"),
+    )
+
+    assert upd.start_update()["started"] is True
+    job = _wait_for_job()
+    assert job["state"] == "success", job
+    assert seen["at_whisper_start"] == pytest.approx(0.7)
+    assert seen["mid_whisper"] == pytest.approx(0.7 + 0.5 * 0.3)
+    assert job["progress"] == 1.0
diff --git a/studio/backend/tests/test_consent_gate.py b/studio/backend/tests/test_consent_gate.py
index 804221ec7e..181e0c9fad 100644
--- a/studio/backend/tests/test_consent_gate.py
+++ b/studio/backend/tests/test_consent_gate.py
@@ -873,6 +873,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             if fn == "config.json":
                 import json
@@ -899,6 +900,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -932,6 +934,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -972,6 +975,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -1008,6 +1012,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -1037,6 +1042,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -1079,6 +1085,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -1120,6 +1127,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
@@ -1182,6 +1190,7 @@ class TestScannerCoversAllExecutableCode:
             repo,
             fn,
             token = None,
+            cache_dir = None,
         ):
             import json
             import tempfile
diff --git a/studio/backend/tests/test_embedding_model_security_gate.py b/studio/backend/tests/test_embedding_model_security_gate.py
index b3fa98b604..a6c18bd8de 100644
--- a/studio/backend/tests/test_embedding_model_security_gate.py
+++ b/studio/backend/tests/test_embedding_model_security_gate.py
@@ -106,6 +106,56 @@ def test_hard_block_uses_non_forceable_status(client, monkeypatch):
     assert unverified.status_code == 409
 
 
+def test_offline_cached_non_st_model_is_accepted(client, monkeypatch):
+    # Offline, a cached transformers-native embedder (no modules.json) is unverifiable via HF
+    # metadata, but ST can load any cached encoder, so accept it (no 409).
+    c, saved = client
+    monkeypatch.setitem(sys.modules, "utils.security", _security_stub(blocked = False))
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    import utils.models as _models
+    import utils.utils as _uu
+
+    monkeypatch.setattr(_models, "is_embedding_model", lambda *a, **k: False)
+    monkeypatch.setattr(_uu, "hf_cache_snapshot_is_loadable", lambda name: True)
+    r = c.put("/embedding-model", json = {"embedding_model": "acme/gte-modernbert"})
+    assert r.status_code == 200
+    assert saved.get("model") == "acme/gte-modernbert"
+
+
+def test_offline_partial_or_uncached_model_still_409(client, monkeypatch):
+    # Offline but not loadable (uncached or metadata-only partial cache): keep the forceable
+    # 409, since the cache-only load would fail anyway.
+    c, _saved = client
+    monkeypatch.setitem(sys.modules, "utils.security", _security_stub(blocked = False))
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    import utils.models as _models
+    import utils.utils as _uu
+
+    monkeypatch.setattr(_models, "is_embedding_model", lambda *a, **k: False)
+    monkeypatch.setattr(_uu, "hf_cache_snapshot_is_loadable", lambda name: False)
+    r = c.put("/embedding-model", json = {"embedding_model": "acme/uncached-embedder"})
+    assert r.status_code == 409
+
+
+def test_offline_skips_remote_gguf_probe(client, monkeypatch):
+    # Offline + llama backend: the remote GGUF probe (list_repo_files) must be skipped so a
+    # dead-DNS session cannot hang.
+    c, _saved = client
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    monkeypatch.setattr(settings, "_llama_backend_active", lambda: True)
+    monkeypatch.setattr(settings, "_local_gguf_backend_error", lambda model: None)
+
+    def _boom(*a, **k):
+        raise AssertionError("hit the network for the GGUF probe")
+
+    monkeypatch.setattr(settings, "_hf_gguf_backend_error", _boom)
+    import utils.models as _models
+
+    monkeypatch.setattr(_models, "is_embedding_model", lambda *a, **k: True)
+    r = c.put("/embedding-model", json = {"embedding_model": "acme/embedder"})
+    assert r.status_code == 200
+
+
 def test_llama_backend_skips_the_st_pickle_scan(monkeypatch):
     # On the llama-server backend the embedder loads GGUF (inert), not the ST repo's
     # pickle, so a flagged ST repo with a clean GGUF companion must not be rejected here.
diff --git a/studio/backend/tests/test_export_absolute_paths.py b/studio/backend/tests/test_export_absolute_paths.py
index 761ea08e3f..5097f9f53a 100644
--- a/studio/backend/tests/test_export_absolute_paths.py
+++ b/studio/backend/tests/test_export_absolute_paths.py
@@ -158,6 +158,7 @@ def _install_lightweight_backend_stubs(monkeypatch):
     utils_model_config._pick_best_gguf = lambda variants: variants[0] if variants else None
     utils_model_config._extract_quant_label = lambda value: value
     utils_model_config._is_big_endian_gguf_path = lambda *args, **kwargs: False
+    utils_model_config._is_mtp_drafter = lambda *args, **kwargs: False
     utils_model_config.is_audio_input_type = lambda *args, **kwargs: None
     monkeypatch.setitem(
         sys.modules,
diff --git a/studio/backend/tests/test_gguf_load_cache_reuse.py b/studio/backend/tests/test_gguf_load_cache_reuse.py
index 62596fcc8a..6d1fac980b 100644
--- a/studio/backend/tests/test_gguf_load_cache_reuse.py
+++ b/studio/backend/tests/test_gguf_load_cache_reuse.py
@@ -103,6 +103,10 @@ def _build_cache(
 @pytest.fixture
 def hf_cache(tmp_path, monkeypatch):
     monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: _types.SimpleNamespace(hub_cache = tmp_path),
+    )
     monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
     monkeypatch.delenv("TRANSFORMERS_OFFLINE", raising = False)
     return tmp_path
@@ -117,6 +121,61 @@ def _fail_get_paths_info(*_args, **_kwargs):
 
 
 class TestLoadReusesCachedCopy:
+    def test_download_uses_selected_cache_for_lookup_preflight_and_write(
+        self, tmp_path, monkeypatch
+    ):
+        backend = LlamaCppBackend()
+        selected = tmp_path / "selected" / "hub"
+        startup = tmp_path / "startup" / "hub"
+        monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(startup))
+        monkeypatch.setattr(
+            "utils.hf_cache_settings.get_hf_cache_paths",
+            lambda: _types.SimpleNamespace(hub_cache = selected),
+        )
+        seen = {"lookups": [], "disk": [], "downloads": []}
+
+        def cached_lookup(
+            repo_id,
+            filename,
+            *,
+            cache_dir = None,
+            **_kwargs,
+        ):
+            seen["lookups"].append((repo_id, filename, cache_dir))
+            return None
+
+        def disk_usage(path):
+            seen["disk"].append(str(path))
+            return _types.SimpleNamespace(free = 1024)
+
+        def download(repo_id, filename, _token, **kwargs):
+            seen["downloads"].append((repo_id, filename, kwargs.get("cache_dir")))
+            return str(selected / filename)
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch(
+                "huggingface_hub.get_paths_info",
+                lambda _repo, paths, **_kwargs: [
+                    _types.SimpleNamespace(path = path, size = 4) for path in paths
+                ],
+            ),
+            patch("huggingface_hub.try_to_load_from_cache", cached_lookup),
+            patch("core.inference.llama_cpp.shutil.disk_usage", disk_usage),
+            patch(
+                "core.inference.llama_cpp.hf_hub_download_with_xet_fallback",
+                download,
+            ),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(selected / MAIN)
+        assert seen == {
+            "lookups": [(REPO, MAIN, str(selected))],
+            "disk": [str(selected)],
+            "downloads": [(REPO, MAIN, str(selected))],
+        }
+
     def test_online_reuse_after_revision_bump(self, hf_cache):
         """A new repo revision does not replace a complete cached model."""
         backend = LlamaCppBackend()
diff --git a/studio/backend/tests/test_gpu_memory_mode.py b/studio/backend/tests/test_gpu_memory_mode.py
index b17274197f..19ba9e3e05 100644
--- a/studio/backend/tests/test_gpu_memory_mode.py
+++ b/studio/backend/tests/test_gpu_memory_mode.py
@@ -733,20 +733,211 @@ def test_split_pin_without_mask_only_sets_pci_order(monkeypatch):
 
 
 def test_split_pin_mirrors_hip_mask_on_rocm(monkeypatch):
-    # ROCm: the pin must land in HIP_VISIBLE_DEVICES too, and an inherited ROCR
-    # mask is cleared so the mask can't apply twice (ROCR re-indexes, then HIP
-    # would index into the already-reduced set).
+    # ROCm with the mask sourced from HIP: the pin must land in
+    # HIP_VISIBLE_DEVICES too, and an inherited ROCR mask is cleared so the
+    # mask can't apply twice (ROCR re-indexes, then HIP would index into the
+    # already-reduced set).
     _patch_split_pin_env(monkeypatch, inherited = [3, 1], reported = [1, 3])
-    torch_stub = _types.ModuleType("torch")
-    torch_stub.version = _types.SimpleNamespace(hip = "6.0")
-    monkeypatch.setitem(sys.modules, "torch", torch_stub)
-    env = {"CUDA_VISIBLE_DEVICES": "3,1", "ROCR_VISIBLE_DEVICES": "3,1"}
+    _rocm_torch_stub(monkeypatch)
+    env = {
+        "CUDA_VISIBLE_DEVICES": "3,1",
+        "HIP_VISIBLE_DEVICES": "3,1",
+        "ROCR_VISIBLE_DEVICES": "3,1",
+    }
     LlamaCppBackend._pin_visible_gpu_order_for_split(env)
     assert env["CUDA_VISIBLE_DEVICES"] == "1,3"
     assert env["HIP_VISIBLE_DEVICES"] == "1,3"
     assert "ROCR_VISIBLE_DEVICES" not in env
 
 
+def test_split_pin_preserves_inherited_rocr_mask(monkeypatch):
+    # Mask sourced from ROCR alone (e.g. an AMD SDK parent): the pin must
+    # re-emit at the ROCr layer, not swap to HIP -- clearing ROCR re-exposes
+    # every agent to HSA enumeration, which can segfault at startup on an
+    # unsupported GPU the parent mask was hiding (#7272 review). CUDA carries
+    # the post-ROCR ordinals, mirroring the prefer_rocr emission.
+    _patch_split_pin_env(monkeypatch, inherited = [3, 1], reported = [1, 3])
+    _rocm_torch_stub(monkeypatch)
+    env = {"ROCR_VISIBLE_DEVICES": "3,1"}
+    LlamaCppBackend._pin_visible_gpu_order_for_split(env)
+    assert env["ROCR_VISIBLE_DEVICES"] == "1,3"
+    assert env["CUDA_VISIBLE_DEVICES"] == "0,1"
+    assert "HIP_VISIBLE_DEVICES" not in env
+
+
+def test_split_pin_keeps_hip_on_windows_despite_stray_rocr(monkeypatch):
+    # On Windows the ROCR var is dead (no ROCr layer) and the resolver never
+    # reads it, so a stray value must not flip the pin to the ROCR emission:
+    # the HIP mask is the only effective selector there.
+    _patch_split_pin_env(monkeypatch, inherited = [3, 1], reported = [1, 3])
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = "6.0")
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    monkeypatch.setattr(sys, "platform", "win32")
+    env = {"CUDA_VISIBLE_DEVICES": "3,1", "ROCR_VISIBLE_DEVICES": "9"}
+    LlamaCppBackend._pin_visible_gpu_order_for_split(env)
+    assert env["CUDA_VISIBLE_DEVICES"] == "1,3"
+    assert env["HIP_VISIBLE_DEVICES"] == "1,3"
+    assert "ROCR_VISIBLE_DEVICES" not in env
+
+
+def _rocm_torch_stub(monkeypatch):
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = "6.0")
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    # prefer_rocr is Linux-only (ROCR is an ROCr variable); pin the platform so
+    # these Linux-behaviour tests also pass on a Windows dev box.
+    monkeypatch.setattr(sys, "platform", "linux")
+
+
+def test_subset_pin_masks_via_rocr_on_rocm(monkeypatch):
+    # A GPU-subset pin must exclude the rest at the ROCr/HSA layer: HIP masking
+    # still enumerates every agent first, which segfaults the build on an
+    # unsupported deselected GPU (e.g. a gfx1103 iGPU under a gfx110X prebuilt).
+    # ROCR drops it at the driver layer; only one mask is set (HIP cleared).
+    _rocm_torch_stub(monkeypatch)
+    env = {"HIP_VISIBLE_DEVICES": "9"}  # stale/inherited HIP mask must not survive
+    LlamaCppBackend._emit_child_gpu_visibility(env, "0", prefer_rocr = True)
+    assert env["ROCR_VISIBLE_DEVICES"] == "0"
+    assert env["CUDA_VISIBLE_DEVICES"] == "0"
+    assert "HIP_VISIBLE_DEVICES" not in env
+
+
+def test_prefer_rocr_remaps_cuda_to_post_rocr_ordinals(monkeypatch):
+    # ROCR re-indexes the visible agents from 0, and HIP (cleared here) falls back
+    # to CUDA_VISIBLE_DEVICES -- so on the prefer_rocr path CUDA must carry the
+    # post-ROCR ordinals, not the physical ids, else a non-zero pick indexes out
+    # of range and the child sees no GPU and drops to CPU (#7272 review).
+    _rocm_torch_stub(monkeypatch)
+    # Single non-zero GPU: ROCR keeps the physical id, CUDA becomes ordinal 0.
+    env = {}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "1", prefer_rocr = True)
+    assert env["ROCR_VISIBLE_DEVICES"] == "1"
+    assert env["CUDA_VISIBLE_DEVICES"] == "0"
+    assert "HIP_VISIBLE_DEVICES" not in env
+    # Multi-GPU subset: ROCR keeps the physical ids, CUDA is the 0-based ordinals.
+    env = {}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "1,3", prefer_rocr = True)
+    assert env["ROCR_VISIBLE_DEVICES"] == "1,3"
+    assert env["CUDA_VISIBLE_DEVICES"] == "0,1"
+    assert "HIP_VISIBLE_DEVICES" not in env
+
+
+def test_subset_pin_default_still_uses_hip_and_clears_rocr(monkeypatch):
+    # Without prefer_rocr the masking is unchanged: HIP narrows, inherited ROCR
+    # is cleared so the two can't double-mask.
+    _rocm_torch_stub(monkeypatch)
+    env = {"ROCR_VISIBLE_DEVICES": "0,1"}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "1")
+    assert env["HIP_VISIBLE_DEVICES"] == "1"
+    assert "ROCR_VISIBLE_DEVICES" not in env
+
+
+def test_cpu_only_pin_keeps_hip_even_with_prefer_rocr(monkeypatch):
+    # The CPU-only sentinel never routes through ROCR (no portable "hide all"
+    # spelling); it hides every GPU via HIP.
+    _rocm_torch_stub(monkeypatch)
+    env = {}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "-1", prefer_rocr = True)
+    assert env["HIP_VISIBLE_DEVICES"] == "-1"
+    assert "ROCR_VISIBLE_DEVICES" not in env
+
+
+def _amd_sdk_torch_stub(monkeypatch):
+    # AMD SDK wheel: torch.version.hip is None but __version__ encodes rocm.
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = None)
+    torch_stub.__version__ = "2.9.1+rocm7.2.1"
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    monkeypatch.setattr(sys, "platform", "linux")
+
+
+def test_prefer_rocr_falls_back_to_hip_on_windows(monkeypatch):
+    # ROCR_VISIBLE_DEVICES is a Linux ROCr variable (Windows HIP has no ROCr
+    # layer), so on Windows ROCm prefer_rocr must keep the HIP mask or a nonzero
+    # pick loses its only effective selector (#7272 review).
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = "6.0")
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    monkeypatch.setattr(sys, "platform", "win32")
+    env = {"ROCR_VISIBLE_DEVICES": "9"}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "1", prefer_rocr = True)
+    assert env["HIP_VISIBLE_DEVICES"] == "1"
+    assert env["CUDA_VISIBLE_DEVICES"] == "1"
+    assert "ROCR_VISIBLE_DEVICES" not in env
+
+
+def test_amd_sdk_wheel_hip_none_still_masks_rocr(monkeypatch):
+    # An AMD SDK wheel leaves torch.version.hip unset but has "rocm" in __version__.
+    # It must still get the ROCR mask, else only CUDA_VISIBLE_DEVICES is set and an
+    # unsupported iGPU keeps enumerating and can crash llama-server.
+    _amd_sdk_torch_stub(monkeypatch)
+    env = {"HIP_VISIBLE_DEVICES": "9"}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "0", prefer_rocr = True)
+    assert env["ROCR_VISIBLE_DEVICES"] == "0"
+    assert "HIP_VISIBLE_DEVICES" not in env
+
+
+def test_cuda_wheel_hip_none_gets_no_rocm_mask(monkeypatch):
+    # A CUDA wheel (hip=None, no "rocm" in __version__) must NOT get a HIP/ROCR mask
+    # -- only CUDA_VISIBLE_DEVICES -- so the version-string check can't false-positive.
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = None)
+    torch_stub.__version__ = "2.9.1+cu124"
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    env = {}
+    LlamaCppBackend._emit_child_gpu_visibility(env, "0", prefer_rocr = True)
+    assert env["CUDA_VISIBLE_DEVICES"] == "0"
+    assert "ROCR_VISIBLE_DEVICES" not in env
+    assert "HIP_VISIBLE_DEVICES" not in env
+
+
+def test_resolve_physical_ids_reads_rocr_on_amd_sdk_wheel(monkeypatch):
+    # _resolve_visible_physical_ids must use the same ROCm detection as
+    # _emit_child_gpu_visibility: on an AMD SDK wheel (hip=None, rocm in
+    # __version__) an inherited ROCR mask IS the ordinal->physical mapping.
+    # Reading it as "no mask" labels ordinal 0 as physical 0 and the child's
+    # ROCR pin then re-exposes the GPU the mask was hiding (#7272 review).
+    _amd_sdk_torch_stub(monkeypatch)
+    for var in ("HIP_VISIBLE_DEVICES", "CUDA_VISIBLE_DEVICES"):
+        monkeypatch.delenv(var, raising = False)
+    monkeypatch.setenv("ROCR_VISIBLE_DEVICES", "1")
+    assert LlamaCppBackend._resolve_visible_physical_ids() == [1]
+
+
+def test_resolve_physical_ids_ignores_rocr_on_cuda_wheel(monkeypatch):
+    # A CUDA wheel (hip=None, no "rocm") keeps CUDA-only semantics: a stray
+    # ROCR var must not be read as the mask.
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = None)
+    torch_stub.__version__ = "2.9.1+cu124"
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    for var in ("HIP_VISIBLE_DEVICES", "CUDA_VISIBLE_DEVICES"):
+        monkeypatch.delenv(var, raising = False)
+    monkeypatch.setenv("ROCR_VISIBLE_DEVICES", "1")
+    assert LlamaCppBackend._resolve_visible_physical_ids() is None
+
+
+def test_resolve_physical_ids_ignores_rocr_on_windows(monkeypatch):
+    # ROCR_VISIBLE_DEVICES is a Linux ROCr variable: Windows HIP has no ROCr
+    # layer, so a stray ROCR var there does not mask the runtime. Reading it as
+    # the ordinal->physical mapping would label ordinal 0 with a stale ROCR id
+    # while the runtime still enumerates every adapter, so auto-selection could
+    # budget one card and pin another (#7272 review). HIP must still be honoured.
+    torch_stub = _types.ModuleType("torch")
+    torch_stub.version = _types.SimpleNamespace(hip = None)
+    torch_stub.__version__ = "2.9.1+rocm7.2.1"  # AMD SDK wheel
+    monkeypatch.setitem(sys.modules, "torch", torch_stub)
+    monkeypatch.setattr(sys, "platform", "win32")
+    for var in ("HIP_VISIBLE_DEVICES", "CUDA_VISIBLE_DEVICES"):
+        monkeypatch.delenv(var, raising = False)
+    monkeypatch.setenv("ROCR_VISIBLE_DEVICES", "1")
+    assert LlamaCppBackend._resolve_visible_physical_ids() is None
+    # HIP precedence is unchanged on Windows.
+    monkeypatch.setenv("HIP_VISIBLE_DEVICES", "1")
+    assert LlamaCppBackend._resolve_visible_physical_ids() == [1]
+
+
 # ── Diffusion single-device selection ───────────────────────────────────────
 
 
diff --git a/studio/backend/tests/test_hf_cache_settings.py b/studio/backend/tests/test_hf_cache_settings.py
new file mode 100644
index 0000000000..1875d61809
--- /dev/null
+++ b/studio/backend/tests/test_hf_cache_settings.py
@@ -0,0 +1,290 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from __future__ import annotations
+
+import os
+import sys
+import threading
+import time
+from pathlib import Path
+
+import pytest
+
+_BACKEND_DIR = str(Path(__file__).resolve().parent.parent)
+if _BACKEND_DIR not in sys.path:
+    sys.path.insert(0, _BACKEND_DIR)
+
+from hub.services.models.common import _local_model_info
+from utils import hf_cache_settings
+from utils import native_path_leases
+
+
+@pytest.fixture()
+def settings_store(monkeypatch, tmp_path):
+    store = {}
+    monkeypatch.setattr(hf_cache_settings, "_EXPLICIT_CACHE_ENV", {})
+    monkeypatch.setenv("XDG_CACHE_HOME", str(tmp_path / "xdg"))
+    monkeypatch.setattr(
+        "storage.studio_db.get_app_setting",
+        lambda key, fallback = None: store.get(key, fallback),
+    )
+    monkeypatch.setattr(
+        "storage.studio_db.upsert_app_settings",
+        lambda values: store.update(values) or values,
+    )
+    return store
+
+
+def test_studio_cache_switch_is_live_and_keeps_history(settings_store, tmp_path):
+    first = tmp_path / "external-a" / "huggingface"
+    second = tmp_path / "external-b" / "huggingface"
+    first.parent.mkdir()
+    second.parent.mkdir()
+
+    selected = hf_cache_settings.set_hf_cache_home(str(first))
+    assert selected.hub_cache == first / "hub"
+    assert selected.xet_cache == first / "xet"
+    assert selected.child_env({}) == {
+        "HF_HUB_CACHE": str(first / "hub"),
+        "HF_XET_CACHE": str(first / "xet"),
+    }
+
+    hf_cache_settings.set_hf_cache_home(str(second))
+    assert settings_store[hf_cache_settings.CACHE_HISTORY_SETTING_KEY] == [str(first)]
+    assert first / "hub" in hf_cache_settings.known_hf_hub_caches()
+
+    reset = hf_cache_settings.set_hf_cache_home(None)
+    assert reset.source == "default"
+    assert second in hf_cache_settings.known_hf_cache_homes()
+
+
+def test_environment_cache_is_read_only(monkeypatch, tmp_path):
+    custom = tmp_path / "managed"
+    monkeypatch.setattr(
+        hf_cache_settings,
+        "_EXPLICIT_CACHE_ENV",
+        {"HF_HOME": str(custom)},
+    )
+    paths = hf_cache_settings.get_hf_cache_paths()
+    assert paths.source == "environment"
+    assert paths.editable is False
+    assert paths.hub_cache == custom / "hub"
+    with pytest.raises(RuntimeError, match = "environment variable"):
+        hf_cache_settings.set_hf_cache_home(str(tmp_path / "other"))
+
+
+def test_explicit_hub_cache_is_the_displayed_location(monkeypatch, tmp_path):
+    custom_hub = tmp_path / "models-cache"
+    custom_hub.mkdir()
+    monkeypatch.setattr(
+        hf_cache_settings,
+        "_EXPLICIT_CACHE_ENV",
+        {"HF_HUB_CACHE": str(custom_hub)},
+    )
+
+    paths = hf_cache_settings.get_hf_cache_paths()
+    status = hf_cache_settings.cache_status(paths)
+
+    assert paths.cache_home == custom_hub
+    assert paths.hub_cache == custom_hub
+    assert status["cache_home"] == str(custom_hub)
+    assert status["available"] is True
+    assert custom_hub / "hub" not in hf_cache_settings.known_hf_hub_caches()
+
+
+def test_explicit_hub_cache_display_wins_over_hf_home(monkeypatch, tmp_path):
+    hf_home = tmp_path / "hf-home"
+    custom_hub = tmp_path / "other-disk" / "models-cache"
+    hf_home.mkdir()
+    custom_hub.mkdir(parents = True)
+    monkeypatch.setattr(
+        hf_cache_settings,
+        "_EXPLICIT_CACHE_ENV",
+        {"HF_HOME": str(hf_home), "HF_HUB_CACHE": str(custom_hub)},
+    )
+
+    paths = hf_cache_settings.get_hf_cache_paths()
+
+    assert paths.cache_home == custom_hub
+    assert paths.hub_cache == custom_hub
+    assert paths.xet_cache == hf_home / "xet"
+    assert custom_hub / "hub" not in hf_cache_settings.known_hf_hub_caches()
+    assert hf_home / "hub" in hf_cache_settings.known_hf_hub_caches()
+
+
+def test_xet_only_override_keeps_model_cache_editable(settings_store, monkeypatch, tmp_path):
+    xet_cache = tmp_path / "chunks"
+    stored = tmp_path / "stored-cache"
+    settings_store[hf_cache_settings.CACHE_HOME_SETTING_KEY] = str(stored)
+    monkeypatch.setattr(
+        hf_cache_settings,
+        "_EXPLICIT_CACHE_ENV",
+        {"HF_XET_CACHE": str(xet_cache)},
+    )
+
+    paths = hf_cache_settings.get_hf_cache_paths()
+
+    assert paths.cache_home == stored
+    assert paths.hub_cache == stored / "hub"
+    assert paths.xet_cache == xet_cache
+    assert paths.editable is True
+
+    selected = tmp_path / "selected-cache"
+    selected.parent.mkdir(exist_ok = True)
+    updated = hf_cache_settings.set_hf_cache_home(str(selected))
+    assert updated.hub_cache == selected / "hub"
+    assert updated.xet_cache == xet_cache
+
+
+def test_worker_environment_is_applied_before_import(monkeypatch, tmp_path):
+    hub = str(tmp_path / "hub")
+    xet = str(tmp_path / "xet")
+    observed = {}
+
+    class Module:
+        @staticmethod
+        def run():
+            import os
+            return os.environ["HF_HUB_CACHE"], os.environ["HF_XET_CACHE"]
+
+    def fake_import(name):
+        import os
+
+        observed["name"] = name
+        observed["hub"] = os.environ.get("HF_HUB_CACHE")
+        return Module
+
+    monkeypatch.setattr(native_path_leases.importlib, "import_module", fake_import)
+    result = native_path_leases.run_without_native_path_secret(
+        "fake.worker",
+        "run",
+        {"HF_HUB_CACHE": hub, "HF_XET_CACHE": xet},
+    )
+    assert observed == {"name": "fake.worker", "hub": hub}
+    assert result == (hub, xet)
+
+
+def test_spawn_environment_is_applied_then_restored(monkeypatch, tmp_path):
+    hub = str(tmp_path / "hub")
+    xet = str(tmp_path / "xet")
+    monkeypatch.setenv("HF_HUB_CACHE", "parent-hub")
+    monkeypatch.delenv("HF_XET_CACHE", raising = False)
+
+    with hf_cache_settings.child_environment_for_spawn({"HF_HUB_CACHE": hub, "HF_XET_CACHE": xet}):
+        import os
+        assert os.environ["HF_HUB_CACHE"] == hub
+        assert os.environ["HF_XET_CACHE"] == xet
+
+    assert os.environ["HF_HUB_CACHE"] == "parent-hub"
+    assert "HF_XET_CACHE" not in os.environ
+
+
+def test_spawn_environment_supports_nested_contexts(monkeypatch):
+    monkeypatch.setenv("HF_HUB_CACHE", "parent")
+
+    with hf_cache_settings.child_environment_for_spawn({"HF_HUB_CACHE": "outer"}):
+        assert os.environ["HF_HUB_CACHE"] == "outer"
+        with hf_cache_settings.child_environment_for_spawn({"HF_HUB_CACHE": "inner"}):
+            assert os.environ["HF_HUB_CACHE"] == "inner"
+        assert os.environ["HF_HUB_CACHE"] == "outer"
+
+    assert os.environ["HF_HUB_CACHE"] == "parent"
+
+
+def test_spawn_environment_serializes_threads(monkeypatch):
+    monkeypatch.setenv("HF_HUB_CACHE", "parent")
+    first_entered = threading.Event()
+    release_first = threading.Event()
+    observations: list[tuple[str, str]] = []
+
+    def first():
+        with hf_cache_settings.child_environment_for_spawn({"HF_HUB_CACHE": "first"}):
+            observations.append(("first", os.environ["HF_HUB_CACHE"]))
+            first_entered.set()
+            assert release_first.wait(timeout = 2)
+
+    def second():
+        assert first_entered.wait(timeout = 2)
+        with hf_cache_settings.child_environment_for_spawn({"HF_HUB_CACHE": "second"}):
+            observations.append(("second", os.environ["HF_HUB_CACHE"]))
+
+    first_thread = threading.Thread(target = first)
+    second_thread = threading.Thread(target = second)
+    first_thread.start()
+    second_thread.start()
+    assert first_entered.wait(timeout = 2)
+    time.sleep(0.02)
+    assert observations == [("first", "first")]
+    release_first.set()
+    first_thread.join(timeout = 2)
+    second_thread.join(timeout = 2)
+
+    assert observations == [("first", "first"), ("second", "second")]
+    assert os.environ["HF_HUB_CACHE"] == "parent"
+
+
+def test_cache_switch_invalidates_inventory(settings_store, tmp_path, monkeypatch):
+    invalidations = []
+    monkeypatch.setattr(
+        "hub.utils.inventory_scan.invalidate_hf_cache_scans",
+        lambda: invalidations.append(True),
+    )
+    selected = tmp_path / "external" / "huggingface"
+    selected.parent.mkdir()
+
+    hf_cache_settings.set_hf_cache_home(str(selected))
+
+    assert invalidations == [True]
+
+
+def test_cache_validation_write_tests_hub_and_xet(settings_store, tmp_path, monkeypatch):
+    selected = tmp_path / "external" / "huggingface"
+    selected.parent.mkdir()
+    tested = []
+    real_named_temporary_file = hf_cache_settings.tempfile.NamedTemporaryFile
+
+    def recording_write_test(*args, **kwargs):
+        tested.append(Path(kwargs["dir"]))
+        return real_named_temporary_file(*args, **kwargs)
+
+    monkeypatch.setattr(
+        hf_cache_settings.tempfile,
+        "NamedTemporaryFile",
+        recording_write_test,
+    )
+
+    hf_cache_settings.set_hf_cache_home(str(selected))
+
+    assert tested == [selected / "hub", selected / "xet"]
+
+
+def test_cache_validation_rejects_unwritable_child(settings_store, tmp_path, monkeypatch):
+    selected = tmp_path / "external" / "huggingface"
+    selected.parent.mkdir()
+
+    def reject_hub(*args, **kwargs):
+        if Path(kwargs["dir"]).name == "hub":
+            raise PermissionError("read-only")
+        raise AssertionError("xet should not be tested after hub fails")
+
+    monkeypatch.setattr(hf_cache_settings.tempfile, "NamedTemporaryFile", reject_hub)
+
+    with pytest.raises(ValueError, match = "permission"):
+        hf_cache_settings.set_hf_cache_home(str(selected))
+
+
+def test_inactive_cache_model_loads_from_snapshot_path(tmp_path):
+    snapshot = tmp_path / "snapshots" / "revision"
+    snapshot.mkdir(parents = True)
+    row = _local_model_info(
+        scan_path = snapshot,
+        load_path = snapshot,
+        source = "hf_cache",
+        model_format = "safetensors",
+        model_id = "org/model",
+        active_cache = False,
+    )
+    assert row.model_id == "org/model"
+    assert row.active_cache is False
+    assert row.load_id == str(snapshot)
diff --git a/studio/backend/tests/test_hf_xet_fallback.py b/studio/backend/tests/test_hf_xet_fallback.py
index 48aff29659..a037ea2579 100644
--- a/studio/backend/tests/test_hf_xet_fallback.py
+++ b/studio/backend/tests/test_hf_xet_fallback.py
@@ -101,13 +101,23 @@ def test_shim_injects_studio_prepare_on_http_retry(monkeypatch):
     prepared = []
     monkeypatch.setattr(
         "hub.utils.download_registry.prepare_cache_for_transport",
-        lambda repo_type, repo_id, mode, *a, **k: prepared.append((repo_type, repo_id, mode)),
+        lambda repo_type, repo_id, mode, *a, **k: prepared.append(
+            (repo_type, repo_id, mode, k.get("root"))
+        ),
     )
 
-    out = xf.hf_hub_download_with_xet_fallback(DL_REPO, FILE, None)
+    selected_cache = "/captured/hub"
+    out = xf.hf_hub_download_with_xet_fallback(
+        DL_REPO,
+        FILE,
+        None,
+        cache_dir = selected_cache,
+    )
     assert out == "/cache/model.gguf"
     assert seen_disable_xet == [False, True]  # Xet first, then HTTP
-    assert prepared == [("model", DL_REPO, "http")], "shim must run Unsloth's marker-aware prep"
+    assert prepared == [
+        ("model", DL_REPO, "http", Path(selected_cache))
+    ], "shim must prepare the cache captured by the download"
 
 
 def test_shim_snapshot_injects_studio_prepare(monkeypatch):
@@ -120,10 +130,22 @@ def test_shim_snapshot_injects_studio_prepare(monkeypatch):
         return "/tmp/snap-dir"
 
     monkeypatch.setattr(xf, "_shared_snapshot_download_with_xet_fallback", fake_snapshot)
-    out = xf.snapshot_download_with_xet_fallback("org/model")
+    selected_cache = "/captured/hub"
+    out = xf.snapshot_download_with_xet_fallback(
+        "org/model",
+        cache_dir = selected_cache,
+    )
     assert out == "/tmp/snap-dir"
     assert captured["repo_id"] == "org/model"
-    assert captured["prepare_for_http_fn"] is xf._studio_prepare_for_http
+    prepared = []
+    monkeypatch.setattr(
+        "hub.utils.download_registry.prepare_cache_for_transport",
+        lambda repo_type, repo_id, mode, *a, **k: prepared.append(
+            (repo_type, repo_id, mode, k.get("root"))
+        ),
+    )
+    captured["prepare_for_http_fn"]("model", "org/model")
+    assert prepared == [("model", "org/model", "http", Path(selected_cache))]
 
 
 def test_degrades_gracefully_without_shared_helper(monkeypatch):
diff --git a/studio/backend/tests/test_install_resolve_prebuilt.py b/studio/backend/tests/test_install_resolve_prebuilt.py
index 3ebad861ad..02ccc68b11 100644
--- a/studio/backend/tests/test_install_resolve_prebuilt.py
+++ b/studio/backend/tests/test_install_resolve_prebuilt.py
@@ -200,14 +200,9 @@ def _gpu_linux_host(caps):
     )
 
 
-def test_host_is_blackwell_includes_datacenter_parts():
-    assert ilp._host_is_blackwell(_gpu_linux_host(["10.0"])) is True  # B200 sm_100
-    assert ilp._host_is_blackwell(_gpu_linux_host(["10.3"])) is True  # B300 sm_103
-    assert ilp._host_is_blackwell(_gpu_linux_host(["12.0"])) is True  # RTX 50 sm_120
-    assert ilp._host_is_blackwell(_gpu_linux_host(["12.1"])) is True  # DGX Spark sm_121
-    assert ilp._host_is_blackwell(_gpu_linux_host(["9.0"])) is False  # Hopper
-    assert ilp._host_is_blackwell(_gpu_linux_host(["8.0"])) is False  # Ampere
-    assert ilp._host_is_blackwell(_gpu_linux_host(["9.0", "10.0"])) is True  # highest cap wins
+# _host_is_blackwell / _blackwell_min_toolkit_for_host are prebuilt_core
+# re-exports; their value tables moved verbatim to
+# tests/studio/install/test_prebuilt_core.py.
 
 
 def _linux_cuda_artifact(runtime_line, supported_sms, min_sm, max_sm, profile):
@@ -285,16 +280,6 @@ def test_drop_blackwell_incapable_windows_cuda_applies_to_datacenter():
     assert [a.name for a in kept] == [cuda13.name]
 
 
-def test_blackwell_min_toolkit_is_sm_aware():
-    # Family floor is 12.8; sm_103/sm_121 (no native target before 12.9) lift it.
-    f = ilp._blackwell_min_toolkit_for_host
-    assert f(_gpu_linux_host(["10.0"])) == (12, 8)  # B200
-    assert f(_gpu_linux_host(["12.0"])) == (12, 8)  # RTX 50
-    assert f(_gpu_linux_host(["10.3"])) == (12, 9)  # B300
-    assert f(_gpu_linux_host(["12.1"])) == (12, 9)  # DGX Spark
-    assert f(_gpu_linux_host(["10.0", "10.3"])) == (12, 9)  # max across SMs wins
-
-
 def test_sm103_host_drops_cuda128_windows_build():
     # B300 (sm_103) needs cuda-12.9: a legacy win-cuda-12.8 build must be dropped.
     host = _host(
diff --git a/studio/backend/tests/test_install_whisper_prebuilt_checksums.py b/studio/backend/tests/test_install_whisper_prebuilt_checksums.py
new file mode 100644
index 0000000000..19bece9d0c
--- /dev/null
+++ b/studio/backend/tests/test_install_whisper_prebuilt_checksums.py
@@ -0,0 +1,231 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Trust-anchor tests for install_whisper_prebuilt.py.
+
+Whisper verifies each download against the release's own
+whisper-prebuilt-sha256.json checksum index (the same model as
+install_llama_prebuilt.py), not a committed pins file. These pin the index
+parser, the fail-closed behaviour when an asset is not covered, the
+tampered-manifest guard, and the newest-release resolution.
+"""
+
+from __future__ import annotations
+
+import importlib
+import sys
+from pathlib import Path
+
+import pytest
+
+_studio = Path(__file__).resolve().parent.parent.parent
+if str(_studio) not in sys.path:
+    sys.path.insert(0, str(_studio))
+
+iwp = importlib.import_module("install_whisper_prebuilt")
+
+if not hasattr(iwp, "parse_release_checksums"):
+    pytest.skip("checksum-model symbols not present - check branch", allow_module_level = True)
+
+_A = "0" * 64
+_B = "1" * 64
+_TAG = "v1.9.1-unsloth.1"
+_REPO = "unslothai/whisper.cpp"
+
+
+def _index(**overrides) -> dict:
+    payload = {
+        "schema_version": 1,
+        "component": "whisper.cpp",
+        "release_tag": _TAG,
+        "upstream_tag": "v1.9.1",
+        "artifacts": {
+            "whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz": {"sha256": _A},
+            "whisper-v1.9.1-unsloth.1-linux-x64-cuda12-portable.tar.gz": {"sha256": _B},
+        },
+    }
+    payload.update(overrides)
+    return payload
+
+
+# parse_release_checksums / expected_sha256_for are prebuilt_core re-exports;
+# their valid/fail-closed matrix is asserted against the real whisper
+# descriptor in tests/studio/install/test_prebuilt_core.py. The download-host
+# fast-path tests below still route through this module's parse wrapper.
+
+# release tag resolution.
+
+
+def test_resolve_release_tag_explicit_override_passthrough():
+    assert iwp.resolve_release_tag(_REPO, published_release_tag = "v1.9.1-unsloth.2") == (
+        "v1.9.1-unsloth.2"
+    )
+
+
+def test_resolve_release_tag_resolves_newest_when_no_override(monkeypatch):
+    monkeypatch.setattr(iwp, "resolve_newest_release_tag", lambda repo: "v9.9.9-unsloth.9")
+    assert iwp.resolve_release_tag(_REPO, published_release_tag = None) == "v9.9.9-unsloth.9"
+
+
+def test_resolve_newest_release_tag_picks_latest_published(monkeypatch):
+    releases = [
+        {"tag_name": "v1.9.1-unsloth.1", "published_at": "2026-01-01T00:00:00Z"},
+        {"tag_name": "v1.9.1-unsloth.3", "published_at": "2026-03-01T00:00:00Z"},
+        {"tag_name": "v1.9.1-unsloth.2", "published_at": "2026-02-01T00:00:00Z"},
+        {"tag_name": "draft", "published_at": "2026-09-01T00:00:00Z", "draft": True},
+        {"tag_name": "pre", "published_at": "2026-09-01T00:00:00Z", "prerelease": True},
+    ]
+    monkeypatch.setattr(iwp, "fetch_json", lambda url: releases)
+    assert iwp.resolve_newest_release_tag(_REPO) == "v1.9.1-unsloth.3"
+
+
+def test_resolve_newest_release_tag_none_published_fails_closed(monkeypatch):
+    monkeypatch.setattr(iwp, "fetch_json", lambda url: [{"tag_name": "d", "draft": True}])
+    with pytest.raises(iwp.PrebuiltFallback):
+        iwp.resolve_newest_release_tag(_REPO)
+
+
+def test_pins_symbols_are_gone():
+    # The committed-pins trust model was removed in favour of llama's runtime index.
+    for gone in ("load_pins", "pins_path", "resolve_expected_sha256", "PINS_FILENAME"):
+        assert not hasattr(iwp, gone), f"{gone} should have been removed"
+
+
+# Download-host fast path (resolve + fetch the JSON assets with no GitHub API).
+
+_CPU_ASSET = "whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz"
+
+
+def _manifest() -> dict:
+    return {
+        "schema_version": 1,
+        "component": "whisper.cpp",
+        "upstream_tag": "v1.9.1",
+        "artifacts": [{"asset": _CPU_ASSET, "os": "linux", "arch": "x64", "backend": "cpu"}],
+    }
+
+
+def _no_api(monkeypatch):
+    """Fail loudly if any code path touches api.github.com."""
+
+    def _boom(*a, **k):
+        raise AssertionError("api.github.com was used on the fast path")
+
+    monkeypatch.setattr(iwp, "fetch_json", _boom)
+    monkeypatch.setattr(iwp, "github_release", _boom)
+    monkeypatch.setattr(iwp, "fetch_release_bundle", _boom)
+
+
+def test_fetch_release_for_install_prefers_download_host(monkeypatch):
+    _no_api(monkeypatch)
+    monkeypatch.setattr(iwp, "_download_host_latest_release_tag", lambda repo: _TAG)
+
+    def _dhj(url):
+        if url.endswith(iwp.SHA256_ASSET_NAME):
+            return _index()
+        if url.endswith(iwp.MANIFEST_ASSET_NAME):
+            return _manifest()
+        raise AssertionError(f"unexpected url {url}")
+
+    monkeypatch.setattr(iwp, "_download_host_json", _dhj)
+    bundle, checks = iwp.fetch_release_for_install(_REPO, published_release_tag = None)
+    assert bundle.release_tag == _TAG
+    assert checks[_CPU_ASSET] == _A
+    # asset_urls point at the download host (github.com), not the API.
+    assert bundle.asset_urls[iwp.SHA256_ASSET_NAME].startswith(
+        f"https://github.com/{_REPO}/releases/"
+    )
+    assert bundle.asset_urls[_CPU_ASSET].startswith(
+        f"https://github.com/{_REPO}/releases/download/"
+    )
+    walked = iwp._fetch_release_candidate(_REPO, _TAG)
+    assert iwp.SHA256_ASSET_NAME in walked.asset_urls
+    assert _CPU_ASSET in walked.asset_urls
+
+
+def test_fetch_release_for_install_explicit_tag_skips_the_head(monkeypatch):
+    # An explicit tag needs no /releases/latest HEAD: resolving it must not call it.
+    monkeypatch.setattr(
+        iwp,
+        "_download_host_latest_release_tag",
+        lambda repo: (_ for _ in ()).throw(AssertionError("HEAD used for an explicit tag")),
+    )
+    monkeypatch.setattr(
+        iwp,
+        "_download_host_json",
+        lambda url: _index() if url.endswith(iwp.SHA256_ASSET_NAME) else _manifest(),
+    )
+    _no_api(monkeypatch)
+    bundle, checks = iwp.fetch_release_for_install(_REPO, published_release_tag = _TAG)
+    assert bundle.release_tag == _TAG
+
+
+def test_fetch_release_for_install_falls_back_to_api(monkeypatch):
+    # Fast path returns None (e.g. a 404) -> the API path resolves the release.
+    monkeypatch.setattr(iwp, "_resolve_release_via_download_host", lambda repo, tag: None)
+    sentinel = iwp.ReleaseBundle(repo = _REPO, release_tag = _TAG, manifest = _manifest(), asset_urls = {})
+    monkeypatch.setattr(iwp, "resolve_release_tag", lambda repo, *, published_release_tag: _TAG)
+    monkeypatch.setattr(iwp, "fetch_release_bundle", lambda repo, tag: sentinel)
+    monkeypatch.setattr(iwp, "fetch_release_checksums", lambda bundle: {_CPU_ASSET: _A})
+    bundle, checks = iwp.fetch_release_for_install(_REPO, published_release_tag = None)
+    assert bundle is sentinel
+    assert checks == {_CPU_ASSET: _A}
+
+
+def test_resolve_via_download_host_sha_404_returns_none(monkeypatch):
+    import urllib.error
+
+    monkeypatch.setattr(iwp, "_download_host_latest_release_tag", lambda repo: _TAG)
+
+    def _dhj(url):
+        raise urllib.error.HTTPError(url, 404, "not found", {}, None)
+
+    monkeypatch.setattr(iwp, "_download_host_json", _dhj)
+    assert iwp._resolve_release_via_download_host(_REPO, None) is None
+
+
+def test_resolve_via_download_host_tag_mismatch_returns_none(monkeypatch):
+    # A checksum index whose self-reported release_tag disagrees is rejected (None).
+    monkeypatch.setattr(iwp, "_download_host_latest_release_tag", lambda repo: _TAG)
+    monkeypatch.setattr(
+        iwp, "_download_host_json", lambda url: _index(release_tag = "v1.9.1-unsloth.2")
+    )
+    assert iwp._resolve_release_via_download_host(_REPO, None) is None
+
+
+def test_download_host_latest_release_tag_parses_redirect(monkeypatch):
+    class _Resp:
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *a):
+            return False
+
+        def geturl(self):
+            return f"https://github.com/{_REPO}/releases/tag/{_TAG}"
+
+    class _Opener:
+        def open(
+            self,
+            req,
+            timeout = None,
+        ):
+            return _Resp()
+
+    monkeypatch.setattr(iwp, "_URL_OPENER", _Opener())
+    assert iwp._download_host_latest_release_tag(_REPO) == _TAG
+
+
+def test_download_host_latest_release_tag_404_returns_none(monkeypatch):
+    import urllib.error
+
+    class _Opener:
+        def open(
+            self,
+            req,
+            timeout = None,
+        ):
+            raise urllib.error.HTTPError(req.full_url, 404, "nf", {}, None)
+
+    monkeypatch.setattr(iwp, "_URL_OPENER", _Opener())
+    assert iwp._download_host_latest_release_tag(_REPO) is None
diff --git a/studio/backend/tests/test_linux_external_media_paths.py b/studio/backend/tests/test_linux_external_media_paths.py
index b735bd1132..8373cdd6bb 100644
--- a/studio/backend/tests/test_linux_external_media_paths.py
+++ b/studio/backend/tests/test_linux_external_media_paths.py
@@ -254,8 +254,10 @@ def test_legacy_browse_allowlist_includes_linux_run_media_mounts(monkeypatch, tm
     )
     fake_external_media = SimpleNamespace(
         linux_run_media_mount_roots = lambda: [media_root],
+        macos_volume_roots = lambda: [],
         windows_drive_roots = lambda: [],
     )
+    fake_paths.external_media = fake_external_media
     fake_studio_db = SimpleNamespace(
         list_scan_folders = lambda: [],
         contains_sensitive_path_component = studio_db.contains_sensitive_path_component,
diff --git a/studio/backend/tests/test_llama_cpp_update.py b/studio/backend/tests/test_llama_cpp_update.py
index f12384231f..9e23242b97 100644
--- a/studio/backend/tests/test_llama_cpp_update.py
+++ b/studio/backend/tests/test_llama_cpp_update.py
@@ -119,6 +119,9 @@ def _clean_state(monkeypatch, tmp_path):
     monkeypatch.delenv("UNSLOTH_LLAMA_CPP_PATH", raising = False)
     # Never hit the network in these tests.
     monkeypatch.setattr(freshness, "_fetch_latest_release_tag", lambda repo, timeout = 5.0: None)
+    # Keep the whisper piggyback out of the llama-only tests: no host probe, no
+    # whisper phase (test_combined_update.py covers the chained flow).
+    monkeypatch.setattr(upd, "_whisper_chain_status", lambda **kwargs: None)
     yield
     freshness.reset_caches()
     upd._reset_job_for_tests()
diff --git a/studio/backend/tests/test_llama_route.py b/studio/backend/tests/test_llama_route.py
index 0ecfeee018..cc450d55cc 100644
--- a/studio/backend/tests/test_llama_route.py
+++ b/studio/backend/tests/test_llama_route.py
@@ -100,6 +100,21 @@ def test_status_response_exposes_update_size_bytes():
     assert rl.LlamaUpdateStatusResponse(**without).model_dump()["update_size_bytes"] is None
 
 
+def test_status_response_exposes_update_component():
+    model = rl.LlamaUpdateStatusResponse(
+        supported = True,
+        update_available = True,
+        llama_update_available = False,
+        update_component = "whisper",
+        whisper = {
+            "update_available": True,
+            "installed_tag": "v1",
+            "latest_tag": "v2",
+        },
+    )
+    assert model.model_dump()["update_component"] == "whisper"
+
+
 def test_status_handler_runs_off_event_loop(monkeypatch):
     seen = {}
 
diff --git a/studio/backend/tests/test_local_llama_cpp_link.py b/studio/backend/tests/test_local_llama_cpp_link.py
index 6b44f61972..79c9977c84 100644
--- a/studio/backend/tests/test_local_llama_cpp_link.py
+++ b/studio/backend/tests/test_local_llama_cpp_link.py
@@ -21,6 +21,13 @@ from utils import llama_cpp_update as u
 from core.inference.llama_cpp import LlamaCppBackend
 
 
+@pytest.fixture(autouse = True)
+def _no_whisper_piggyback(monkeypatch):
+    # Keep the whisper piggyback probe off the host: these tests exercise the
+    # llama local-link contract only.
+    monkeypatch.setattr(u, "_whisper_chain_status", lambda **kwargs: None)
+
+
 def _make_link(link: Path, target: Path) -> None:
     """Create a directory junction (Windows) / symlink (POSIX); neither needs
     elevation."""
diff --git a/studio/backend/tests/test_middleware.py b/studio/backend/tests/test_middleware.py
index 11aeee6d77..36061b5375 100644
--- a/studio/backend/tests/test_middleware.py
+++ b/studio/backend/tests/test_middleware.py
@@ -14,6 +14,7 @@ import pytest
 from fastapi import FastAPI, HTTPException, Request
 from fastapi.responses import Response
 from fastapi.testclient import TestClient
+from starlette.middleware.gzip import GZipMiddleware
 
 
 _BACKEND_ROOT = Path(__file__).resolve().parents[1]
@@ -33,6 +34,7 @@ def main_module():
 def _make_protected_app(
     max_bytes: int,
     main_module,
+    request_max_bytes_getter = None,
     upload_passthrough_prefixes: tuple = (),
     upload_passthrough_max_bytes_getter = None,
 ):
@@ -40,7 +42,13 @@ def _make_protected_app(
     app.add_middleware(
         main_module.MaxBodyMiddleware,
         max_bytes_getter = lambda: max_bytes,
-        protected_prefixes = ("/v1/chat/completions", "/api/settings", "/api/train"),
+        protected_prefixes = (
+            "/v1/chat/completions",
+            "/api/inference",
+            "/api/settings",
+            "/api/train",
+        ),
+        request_max_bytes_getter = request_max_bytes_getter,
         upload_passthrough_prefixes = upload_passthrough_prefixes,
         upload_passthrough_max_bytes_getter = upload_passthrough_max_bytes_getter,
     )
@@ -67,6 +75,10 @@ def _make_protected_app(
                 total += len(chunk)
         return {"ok": True, "chunks": chunks, "total": total}
 
+    @app.post("/api/inference/audio/transcribe/raw")
+    async def transcribe_raw(request: Request):
+        return {"ok": True, "total": len(await request.body())}
+
     @app.get("/api/train/status")
     async def status_get():
         return {"ok": True, "get": True}
@@ -96,6 +108,43 @@ class TestMaxBodyMiddleware:
         assert r.status_code == 200
         assert r.json()["unprotected"] is True
 
+    def test_route_specific_cap_overrides_default(self, main_module):
+        app = _make_protected_app(
+            4096,
+            main_module,
+            request_max_bytes_getter = lambda path: (
+                128 if path.endswith("/transcribe/raw") else 4096
+            ),
+        )
+        c = TestClient(app)
+
+        rejected = c.post(
+            "/api/inference/audio/transcribe/raw",
+            content = b"x" * 129,
+        )
+        accepted = c.post(
+            "/api/inference/audio/transcribe/raw",
+            content = b"x" * 128,
+        )
+
+        assert rejected.status_code == 413
+        assert accepted.status_code == 200
+        assert accepted.json()["total"] == 128
+
+    def test_stt_routes_use_audio_specific_caps(self, main_module):
+        from utils.upload_limits import (
+            STT_AUDIO_JSON_MAX_BYTES,
+            STT_AUDIO_RAW_MAX_BYTES,
+        )
+        assert (
+            main_module._get_request_body_max_bytes("/api/inference/audio/transcribe/raw")
+            == STT_AUDIO_RAW_MAX_BYTES
+        )
+        assert (
+            main_module._get_request_body_max_bytes("/api/inference/audio/transcribe")
+            == STT_AUDIO_JSON_MAX_BYTES
+        )
+
     def test_settings_put_body_over_cap_rejected(self, main_module):
         app = _make_protected_app(1024, main_module)
         c = TestClient(app)
@@ -471,6 +520,71 @@ class TestSecurityHeadersMiddleware:
         assert b"server" in names
 
 
+class TestFrontendAssets:
+    def test_hashed_assets_are_compressed_and_cached(self, tmp_path, main_module):
+        content = b"export const value = 'responsive';\n" * 200
+        (tmp_path / "page-abc123.js").write_bytes(content)
+        app = FastAPI()
+        assets_app = GZipMiddleware(
+            main_module.ImmutableStaticFiles(directory = tmp_path),
+            minimum_size = 1024,
+            compresslevel = 6,
+        )
+        app.mount("/assets", assets_app, name = "assets")
+
+        response = TestClient(app).get(
+            "/assets/page-abc123.js",
+            headers = {"Accept-Encoding": "gzip"},
+        )
+
+        assert response.status_code == 200
+        assert response.content == content
+        assert response.headers["content-encoding"] == "gzip"
+        assert response.headers["cache-control"] == (main_module._IMMUTABLE_ASSET_CACHE_CONTROL)
+        assert "accept-encoding" in response.headers["vary"].lower()
+
+    def test_asset_revalidation_keeps_immutable_cache_header(self, tmp_path, main_module):
+        (tmp_path / "page-abc123.js").write_text("export {};", encoding = "utf-8")
+        app = FastAPI()
+        app.mount(
+            "/assets",
+            main_module.ImmutableStaticFiles(directory = tmp_path),
+            name = "assets",
+        )
+        client = TestClient(app)
+        first = client.get("/assets/page-abc123.js")
+
+        response = client.get(
+            "/assets/page-abc123.js",
+            headers = {"If-None-Match": first.headers["etag"]},
+        )
+
+        assert response.status_code == 304
+        assert response.headers["cache-control"] == (main_module._IMMUTABLE_ASSET_CACHE_CONTROL)
+
+    def test_range_request_is_not_compressed(self, tmp_path, main_module):
+        content = b"export const value = 'responsive';\n" * 200
+        (tmp_path / "page-abc123.js").write_bytes(content)
+        app = FastAPI()
+        assets_app = main_module._AssetGZipMiddleware(
+            main_module.ImmutableStaticFiles(directory = tmp_path),
+            minimum_size = 1024,
+            compresslevel = 6,
+        )
+        app.mount("/assets", assets_app, name = "assets")
+
+        response = TestClient(app).get(
+            "/assets/page-abc123.js",
+            headers = {"Accept-Encoding": "gzip", "Range": "bytes=0-99"},
+        )
+
+        assert response.status_code == 206
+        assert response.headers.get("content-encoding") != "gzip"
+        assert response.headers["content-range"] == f"bytes 0-99/{len(content)}"
+        assert response.content == content[:100]
+        assert response.headers["cache-control"] == (main_module._IMMUTABLE_ASSET_CACHE_CONTROL)
+
+
 # /api/health auth gate
 
 
diff --git a/studio/backend/tests/test_mlx_inference_backend.py b/studio/backend/tests/test_mlx_inference_backend.py
index fafaea0043..d49a2281a0 100644
--- a/studio/backend/tests/test_mlx_inference_backend.py
+++ b/studio/backend/tests/test_mlx_inference_backend.py
@@ -922,3 +922,413 @@ def test_mlx_vlm_normalizes_native_reasoning_channels(monkeypatch):
         "<think>vision</think>",
         "<think>vision</think> answer",
     ]
+
+
+class _FakeLRUPromptCache:
+    def __init__(
+        self,
+        max_size = 10,
+        max_bytes = 1 << 63,
+    ):
+        self.max_size = max_size
+        self.max_bytes = max_bytes
+        self.entries = {}
+
+    def fetch_nearest_cache(self, key, tokens):
+        import copy
+
+        stored = self.entries.get(key, {})
+        exact = stored.get(tuple(tokens))
+        if exact is not None:
+            return copy.deepcopy(exact), []
+        best = None
+        for candidate, cache in stored.items():
+            if len(candidate) < len(tokens) and tuple(tokens[: len(candidate)]) == candidate:
+                if best is None or len(candidate) > len(best[0]):
+                    best = (candidate, cache)
+        if best is not None:
+            return copy.deepcopy(best[1]), list(tokens[len(best[0]) :])
+        return None, list(tokens)
+
+    def insert_cache(
+        self,
+        key,
+        tokens,
+        prompt_cache,
+        *,
+        cache_type = "assistant",
+    ):
+        import copy
+        self.entries.setdefault(key, {})[tuple(tokens)] = copy.deepcopy(prompt_cache)
+
+
+class _FakeCacheEntry:
+    def __init__(
+        self,
+        offset = 0,
+        nbytes = 1,
+    ):
+        self.offset = offset
+        self.nbytes = nbytes
+
+
+def _install_fake_prompt_cache_api(monkeypatch, trimmable = True):
+    from core.inference import mlx_inference
+
+    def _make_prompt_cache(_model):
+        return [_FakeCacheEntry()]
+
+    def _can_trim_prompt_cache(_cache):
+        return trimmable
+
+    def _trim_prompt_cache(cache, num):
+        cache[0].offset = max(cache[0].offset - num, 0)
+        return num
+
+    monkeypatch.setattr(
+        mlx_inference,
+        "_mlx_prompt_cache_api",
+        lambda: (
+            _FakeLRUPromptCache,
+            _make_prompt_cache,
+            _can_trim_prompt_cache,
+            _trim_prompt_cache,
+        ),
+    )
+
+
+def test_mlx_prompt_cache_max_bytes_budget(monkeypatch):
+    from core.inference.mlx_inference import (
+        PROMPT_CACHE_FALLBACK_BYTES,
+        PROMPT_CACHE_MEMORY_FRACTION,
+        _prompt_cache_max_bytes,
+    )
+
+    monkeypatch.delenv("UNSLOTH_MLX_PROMPT_CACHE_BYTES", raising = False)
+    assert _prompt_cache_max_bytes(None) == PROMPT_CACHE_FALLBACK_BYTES
+    assert _prompt_cache_max_bytes(20.0) == int(20.0 * 1e9 * PROMPT_CACHE_MEMORY_FRACTION)
+
+    monkeypatch.setenv("UNSLOTH_MLX_PROMPT_CACHE_BYTES", "4096")
+    assert _prompt_cache_max_bytes(20.0) == 4096
+    monkeypatch.setenv("UNSLOTH_MLX_PROMPT_CACHE_BYTES", "0")
+    assert _prompt_cache_max_bytes(20.0) == 0
+    monkeypatch.setenv("UNSLOTH_MLX_PROMPT_CACHE_BYTES", "not-a-number")
+    assert _prompt_cache_max_bytes(20.0) == int(20.0 * 1e9 * PROMPT_CACHE_MEMORY_FRACTION)
+
+
+def test_mlx_prompt_cache_never_returns_empty_remainder(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    from core.inference.mlx_inference import _MLXPromptCacheHistory
+
+    history = _MLXPromptCacheHistory(6, 1 << 30)
+    tokens = list(range(10))
+    cache, rest = history.fetch(object(), "key", tokens)
+    assert len(rest) == 10
+    cache[0].offset = len(tokens)
+    history.insert("key", tokens, cache)
+
+    _cache, rest = history.fetch(object(), "key", tokens)
+    assert rest == tokens[-1:]
+
+    longer = tokens + [99, 100]
+    _cache, rest = history.fetch(object(), "key", longer)
+    assert rest == [99, 100]
+
+    _install_fake_prompt_cache_api(monkeypatch, trimmable = False)
+    history = _MLXPromptCacheHistory(6, 1 << 30)
+    cache, _rest = history.fetch(object(), "key", tokens)
+    cache[0].offset = len(tokens)
+    history.insert("key", tokens, cache)
+    _cache, rest = history.fetch(object(), "key", tokens)
+    assert rest == tokens, "untrimmable entry must not be reused"
+
+
+def test_mlx_prompt_cache_key_isolates_adapter_state(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    _install_fake_mlx(monkeypatch)
+    from core.inference.mlx_inference import MLXInferenceBackend
+
+    class _Tok:
+        bos_token = None
+
+        def encode(
+            self,
+            text,
+            add_special_tokens = True,
+        ):
+            return [ord(c) for c in text]
+
+    backend = MLXInferenceBackend()
+    backend._model = object()
+    backend._tokenizer = _Tok()
+    backend.active_model_name = "model-a"
+
+    prompt = "shared prefix"
+    _rest, cache, key, tokens, cached = backend._prepare_prompt_cache(prompt, True)
+    assert cached == 0
+    cache[0].offset = len(tokens)
+    backend._prompt_cache_history.insert(key, tokens, cache)
+
+    _rest, _cache, _key, _tokens, cached_same = backend._prepare_prompt_cache(prompt, True)
+    assert cached_same > 0
+    _rest, _cache, _key, _tokens, cached_flipped = backend._prepare_prompt_cache(prompt, False)
+    assert cached_flipped == 0
+
+
+def _install_fake_text_stack(
+    monkeypatch,
+    token_map,
+    captured,
+    markers = None,
+):
+    import types as _types
+
+    from core.inference import mlx_inference
+
+    _install_fake_mlx(monkeypatch)
+    monkeypatch.setattr(
+        mlx_inference,
+        "_temporary_mlx_adapter_state",
+        lambda _model, _state: __import__("contextlib").nullcontext(),
+    )
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.apply_chat_template_for_generation",
+        lambda _tok, messages, **_kw: messages[-1]["content"],
+    )
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.render_with_native_template_fallback",
+        lambda formatted_prompt, **_kw: SimpleNamespace(
+            prompt = formatted_prompt,
+            reasoning_channel_markers = markers,
+        ),
+    )
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.detect_think_prefill",
+        lambda *_a, **_kw: "",
+    )
+
+    class _Resp:
+        def __init__(self, token, processed):
+            self.token = token
+            self.text = f"<{token}>"
+            self.prompt_tokens = processed
+            self.prompt_tps = 10.0
+            self.generation_tokens = 1
+            self.generation_tps = 5.0
+
+    def _stream_generate(_model, _tokenizer, **kwargs):
+        captured.append(kwargs)
+        processed = len(kwargs["prompt"])
+        cache = kwargs.get("prompt_cache")
+        if cache is not None:
+            cache[0].offset += processed
+        for token in token_map["generated"]:
+            if cache is not None:
+                cache[0].offset += 1
+            yield _Resp(token, processed)
+
+    mlx_lm_pkg = _types.ModuleType("mlx_lm")
+    mlx_lm_pkg.stream_generate = _stream_generate
+    mlx_lm_sample = _types.ModuleType("mlx_lm.sample_utils")
+    mlx_lm_sample.make_sampler = lambda **_kw: object()
+    mlx_lm_sample.make_logits_processors = lambda **_kw: []
+    monkeypatch.setitem(sys.modules, "mlx_lm", mlx_lm_pkg)
+    monkeypatch.setitem(sys.modules, "mlx_lm.sample_utils", mlx_lm_sample)
+
+    class _Tok:
+        bos_token = None
+        chat_template = "x"
+
+        def encode(
+            self,
+            text,
+            add_special_tokens = True,
+        ):
+            return list(token_map[text])
+
+        def decode(
+            self,
+            ids,
+            skip_special_tokens = False,
+        ):
+            return "".join(str(i) for i in ids)
+
+    from core.inference.mlx_inference import MLXInferenceBackend
+
+    backend = MLXInferenceBackend()
+    backend._model = object()
+    backend._tokenizer = _Tok()
+    backend._is_vlm = False
+    backend.active_model_name = "model-a"
+    return backend
+
+
+def _run_turn(backend, prompt):
+    list(
+        backend.generate_chat_response(
+            messages = [{"role": "user", "content": prompt}],
+            max_new_tokens = 4,
+        )
+    )
+
+
+def test_mlx_text_reuses_prompt_cache_on_the_next_turn(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    captured = []
+    token_map = {
+        "P1": [1, 2, 3],
+        "P2": [1, 2, 3, 7, 8, 9, 10],
+        "generated": [7, 8],
+    }
+    backend = _install_fake_text_stack(monkeypatch, token_map, captured)
+
+    _run_turn(backend, "P1")
+    assert captured[0]["prompt"] == [1, 2, 3]
+    assert "prompt_cache" in captured[0]
+    assert backend.last_generation_stats["timings"]["cache_n"] == 0
+
+    _run_turn(backend, "P2")
+    assert captured[1]["prompt"] == [9, 10], "turn two should prefill only the new tail"
+
+    stats = backend.last_generation_stats
+    assert stats["timings"]["cache_n"] == 5
+    assert stats["timings"]["prompt_n"] == 2
+    assert stats["usage"]["prompt_tokens"] == 7
+
+
+def test_mlx_text_without_lru_prompt_cache_prefills_the_full_prompt(monkeypatch):
+    from core.inference import mlx_inference
+
+    monkeypatch.setattr(mlx_inference, "_mlx_prompt_cache_api", lambda: None)
+    captured = []
+    token_map = {"P1": [1, 2, 3], "generated": [7]}
+    backend = _install_fake_text_stack(monkeypatch, token_map, captured)
+
+    _run_turn(backend, "P1")
+    assert captured[0]["prompt"] == "P1"
+    assert "prompt_cache" not in captured[0]
+    assert backend.last_generation_stats["timings"]["cache_n"] == 0
+
+
+def test_mlx_text_tracks_tokens_on_the_native_reasoning_path(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    captured = []
+    token_map = {"P1": [1, 2, 3], "P2": [1, 2, 3, 7, 8, 9], "generated": [7, 8]}
+    backend = _install_fake_text_stack(monkeypatch, token_map, captured, markers = ("<a>", "</a>"))
+
+    _run_turn(backend, "P1")
+    _run_turn(backend, "P2")
+    assert captured[1]["prompt"] == [9]
+
+
+def test_mlx_presence_penalty_latches_the_first_decode_step():
+    mx = pytest.importorskip("mlx.core")
+    import numpy as np
+
+    from core.inference.mlx_inference import _make_mlx_presence_penalty_processor
+
+    processor = _make_mlx_presence_penalty_processor(2.0)
+    logits = mx.zeros((1, 5))
+    out = processor(mx.array([3]), logits)
+    assert np.array_equal(np.array(out), np.zeros((1, 5))), "prompt must not be penalized"
+    out = processor(mx.array([3, 1]), mx.zeros((1, 5)))
+    penalized = np.array(out)[0]
+    assert penalized[1] == -2.0
+    assert penalized[3] == 0.0
+
+
+def test_mlx_prompt_cache_survives_reset_but_not_unload(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    _install_fake_mlx(monkeypatch)
+    sys.modules["mlx.core"].clear_cache = lambda: None
+    from core.inference.mlx_inference import MLXInferenceBackend
+
+    backend = MLXInferenceBackend()
+    backend.active_model_name = "model-a"
+    history = backend._prompt_cache()
+    assert history is not None
+
+    backend.reset_generation_state()
+    assert backend._prompt_cache_history is history
+
+    backend.unload_model("model-a")
+    assert backend._prompt_cache_history is None
+
+
+def test_mlx_prompt_cache_skips_entries_over_budget(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    from core.inference.mlx_inference import _MLXPromptCacheHistory
+
+    history = _MLXPromptCacheHistory(6, 1000)
+    history.insert("key", [1, 2, 3], [_FakeCacheEntry(offset = 3, nbytes = 400)])
+    assert len(history._lru.entries.get("key", {})) == 1
+
+    history.insert("key", list(range(50)), [_FakeCacheEntry(offset = 50, nbytes = 5000)])
+    stored = history._lru.entries.get("key", {})
+    assert tuple([1, 2, 3]) in stored
+    assert tuple(range(50)) not in stored
+
+
+def test_mlx_prompt_cache_keys_on_what_the_kv_covers(monkeypatch):
+    _install_fake_prompt_cache_api(monkeypatch)
+    from core.inference.mlx_inference import _MLXPromptCacheHistory
+
+    class _Entry:
+        def __init__(
+            self,
+            offset,
+            nbytes = 1,
+        ):
+            self.offset = offset
+            self.nbytes = nbytes
+
+    history = _MLXPromptCacheHistory(6, 1 << 30)
+
+    history.insert("key", list(range(10)), [_Entry(offset = 8)])
+    assert tuple(range(8)) in history._lru.entries["key"]
+    assert tuple(range(10)) not in history._lru.entries["key"]
+
+    history.insert("other", list(range(4)), [_Entry(offset = 9)])
+    assert "other" not in history._lru.entries
+
+
+def test_mlx_prompt_cache_only_stores_verifiable_prefix_coverage(monkeypatch):
+    mx = pytest.importorskip("mlx.core")
+    from mlx_lm.models.cache import CacheList, ChunkedKVCache, KVCache, RotatingKVCache
+
+    _install_fake_prompt_cache_api(monkeypatch)
+    from core.inference.mlx_inference import _kv_prefix_coverage, _MLXPromptCacheHistory
+
+    def feed(entry, n):
+        for _ in range(n):
+            block = mx.zeros((1, 2, 1, 4), dtype = mx.float16)
+            entry.update_and_fetch(block, block)
+        mx.eval(entry.state)
+        return entry
+
+    plain = feed(KVCache(), 30)
+    unwrapped = feed(RotatingKVCache(max_size = 100, keep = 2), 30)
+    wrapped = feed(RotatingKVCache(max_size = 10, keep = 2), 30)
+    chunked = feed(ChunkedKVCache(chunk_size = 8), 30)
+    slid = feed(ChunkedKVCache(chunk_size = 8), 30)
+    slid.maybe_trim_front()
+
+    assert _kv_prefix_coverage([plain]) == 30
+    assert _kv_prefix_coverage([unwrapped]) == 30
+    assert _kv_prefix_coverage([chunked]) == 30
+    assert wrapped.offset == 30 and wrapped.state[0].shape[2] == 10
+    assert _kv_prefix_coverage([wrapped]) is None
+    assert slid.start_position > 0
+    assert _kv_prefix_coverage([slid]) is None
+    assert _kv_prefix_coverage([CacheList(feed(KVCache(), 30), feed(KVCache(), 30))]) == 30
+    assert _kv_prefix_coverage([CacheList(feed(KVCache(), 30), wrapped)]) is None
+    assert _kv_prefix_coverage([feed(KVCache(), 30), feed(KVCache(), 29)]) is None
+    assert _kv_prefix_coverage([]) is None
+
+    history = _MLXPromptCacheHistory(6, 1 << 40)
+    for unsafe in (wrapped, slid):
+        history.insert("key", list(range(30)), [unsafe])
+    assert "key" not in history._lru.entries
+
+    history.insert("key", list(range(30)), [plain])
+    assert tuple(range(30)) in history._lru.entries["key"]
diff --git a/studio/backend/tests/test_mlx_stop_checkpoint.py b/studio/backend/tests/test_mlx_stop_checkpoint.py
new file mode 100644
index 0000000000..d4a00cc6c8
--- /dev/null
+++ b/studio/backend/tests/test_mlx_stop_checkpoint.py
@@ -0,0 +1,137 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Regression tests for MLX stop-and-save checkpoint handling."""
+
+import importlib.util
+import json
+import sys
+import types
+from pathlib import Path
+
+import numpy as np
+from safetensors.numpy import save_file
+
+
+_BACKEND = Path(__file__).resolve().parents[1]
+
+
+def _load_worker_module():
+    spec = importlib.util.spec_from_file_location(
+        "training_worker_under_test",
+        _BACKEND / "core" / "training" / "worker.py",
+    )
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+worker = _load_worker_module()
+
+
+class _FakeTrainer:
+    def __init__(self, step: int):
+        self._global_step = step
+        self._train_loss_history = []
+        self.model = object()
+
+
+def _write_checkpoint(out: Path, step: int) -> Path:
+    checkpoint = out / f"checkpoint-{step}"
+    checkpoint.mkdir(parents = True, exist_ok = True)
+    (checkpoint / "trainer_state.json").write_text(
+        json.dumps({"global_step": step}), encoding = "utf-8"
+    )
+    save_file({"weight": np.ones(1, dtype = np.float32)}, checkpoint / "adapters.safetensors")
+    save_file(
+        {"state": np.ones(1, dtype = np.float32)},
+        checkpoint / "optimizer_state.safetensors",
+    )
+    return checkpoint
+
+
+def test_mlx_has_checkpoint_at_step_requires_complete_state(tmp_path):
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 5)
+
+    assert worker._mlx_has_checkpoint_at_step(out, 5) is True
+
+
+def test_write_mlx_stop_checkpoint_returns_true_when_current_step_checkpoint_exists(tmp_path):
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 5)
+
+    assert worker._write_mlx_stop_checkpoint(_FakeTrainer(step = 5), object(), out) is True
+
+
+def test_write_mlx_stop_checkpoint_writes_current_step_when_only_older_checkpoint_exists(
+    tmp_path, monkeypatch
+):
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 5)
+
+    saved_steps: list[int] = []
+
+    def _save_state(_value, path, name):
+        save_file({"state": np.ones(1, dtype = np.float32)}, Path(path, name))
+
+    def _save_trainer_state(state, ckpt_dir, **_kwargs):
+        Path(ckpt_dir, "trainer_state.json").write_text(json.dumps(state), encoding = "utf-8")
+        saved_steps.append(int(state["global_step"]))
+
+    fake_utils = types.SimpleNamespace(
+        save_trainable_adapters = lambda model, path: _save_state(
+            model, path, "adapters.safetensors"
+        ),
+        save_optimizer_state = lambda optimizer, path: _save_state(
+            optimizer, path, "optimizer_state.safetensors"
+        ),
+        save_trainer_state = _save_trainer_state,
+    )
+    monkeypatch.setitem(sys.modules, "unsloth_zoo.mlx.utils", fake_utils)
+
+    assert worker._write_mlx_stop_checkpoint(_FakeTrainer(step = 10), object(), out) is True
+    assert saved_steps == [10]
+    assert (out / "checkpoint-10" / "trainer_state.json").is_file()
+
+
+def test_write_mlx_stop_checkpoint_returns_false_without_optimizer(tmp_path):
+    out = tmp_path / "outputs" / "run_x"
+    out.mkdir(parents = True)
+
+    assert worker._write_mlx_stop_checkpoint(_FakeTrainer(step = 5), None, out) is False
+
+
+def test_write_mlx_stop_checkpoint_rejects_incomplete_current_checkpoint(tmp_path):
+    out = tmp_path / "outputs" / "run_x"
+    ckpt = out / "checkpoint-5"
+    ckpt.mkdir(parents = True)
+    (ckpt / "trainer_state.json").write_text('{"global_step": 5}', encoding = "utf-8")
+
+    assert worker._write_mlx_stop_checkpoint(_FakeTrainer(step = 5), None, out) is False
+
+
+def test_write_mlx_stop_checkpoint_ignores_stale_checkpoint_without_optimizer(tmp_path):
+    # An older checkpoint does not cover the current step, so this still fails.
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 5)
+
+    assert worker._write_mlx_stop_checkpoint(_FakeTrainer(step = 10), None, out) is False
+
+
+def test_write_mlx_stop_checkpoint_returns_false_when_save_fails(tmp_path, monkeypatch):
+    out = tmp_path / "outputs" / "run_x"
+    out.mkdir(parents = True)
+
+    def _boom(*_args, **_kwargs):
+        raise RuntimeError("save failed")
+
+    fake_utils = types.SimpleNamespace(
+        save_trainable_adapters = _boom,
+        save_optimizer_state = lambda *_a, **_k: None,
+        save_trainer_state = lambda *_a, **_k: None,
+    )
+    monkeypatch.setitem(sys.modules, "unsloth_zoo.mlx.utils", fake_utils)
+
+    assert worker._write_mlx_stop_checkpoint(_FakeTrainer(step = 5), object(), out) is False
diff --git a/studio/backend/tests/test_model_picker_regression.py b/studio/backend/tests/test_model_picker_regression.py
new file mode 100644
index 0000000000..f38a4d0b8d
--- /dev/null
+++ b/studio/backend/tests/test_model_picker_regression.py
@@ -0,0 +1,232 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Regression guards for the model-picker per-model-config feature (the set of
+bugs that got the predecessor PR reverted). Pure-function / validation checks
+only, so they run on CPU in the backend pytest job with no model download.
+
+Covers, at the backend layer:
+  - infra-model hiding: the RAG embedder (bge-small-en-v1.5) and the llama.cpp
+    install-validation probe (ggml-org/models / stories260K) stay hidden, while
+    normal chat repos are not hidden;
+  - the HF token is honored from the dedicated header with the query string as a
+    fallback, never the other way around;
+  - the chat-template byte caps reject oversized overrides (both the char-count
+    fast path and the UTF-8 byte path) and the sidecar reader is size-bounded.
+"""
+
+from __future__ import annotations
+
+import sys
+import types
+
+import pytest
+
+# Keep this test runnable without the optional structlog dependency (mirrors
+# tests/test_cached_gguf_routes.py), since importing routes.models pulls it in.
+if "structlog" not in sys.modules:
+
+    class _DummyLogger:
+        def __getattr__(self, _name):
+            return lambda *args, **kwargs: None
+
+    sys.modules["structlog"] = types.SimpleNamespace(
+        BoundLogger = _DummyLogger,
+        get_logger = lambda *args, **kwargs: _DummyLogger(),
+    )
+
+import routes.models as models_route
+from core.rag import config as rag_config
+from hub.dependencies import get_hf_token
+from models.inference import LoadRequest
+from picker.schemas import MAX_CHAT_TEMPLATE_BYTES
+from picker.service import _read_bounded_text
+from utils.hidden_models import is_hidden_model
+
+
+@pytest.fixture(autouse = True)
+def _pin_default_embedder(monkeypatch):
+    """Pin the effective embedder to Studio's static default so hiding is
+    deterministic and cannot depend on ambient RAG config / env."""
+    default = "unsloth/bge-small-en-v1.5"
+    monkeypatch.setattr(rag_config, "EMBEDDING_MODEL", default, raising = False)
+    monkeypatch.setattr(rag_config, "effective_embedding_model", lambda: default)
+    monkeypatch.setattr(rag_config, "effective_gguf_repo", lambda: default)
+    monkeypatch.setattr(rag_config, "default_gguf_repo", lambda: default)
+
+
+# --------------------------------------------------------------------------- #
+# Infra-model hiding (the "infra models resurfaced in the picker" regression)  #
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.parametrize(
+    "value",
+    [
+        "ggml-org/models",  # the probe repo id
+        "unsloth/bge-small-en-v1.5",  # the RAG embedder repo
+        "unsloth/bge-small-en-v1.5-GGUF",  # its GGUF companion
+        "/root/.cache/huggingface/hub/x/stories260K.gguf",  # probe on disk
+        "/root/.cache/x/Stories260K.GGUF",  # case-insensitive
+        r"C:\\models\\stories260K.gguf",  # windows-style path
+        "/opt/models/bge-small-en-v1.5",  # embedder basename folder
+        "/opt/models/bge-small-en-v1.5-Q8_0.gguf",  # suffixed local weight
+    ],
+)
+def test_infra_models_are_hidden(value):
+    assert is_hidden_model(value) is True
+
+
+@pytest.mark.parametrize(
+    "value",
+    [
+        "unsloth/gemma-3-270m-it-GGUF",  # a normal small chat GGUF
+        "unsloth/Qwen3-0.6B",  # a normal non-GGUF chat model
+        "user/stories260K-finetune-GGUF",  # repo id merely contains "stories260k"
+        "user/model-chat",  # generic repo must not be hidden
+        "meta-llama/Llama-3.1-8B-Instruct",
+    ],
+)
+def test_normal_models_are_not_hidden(value):
+    assert is_hidden_model(value) is False
+
+
+def test_is_hidden_model_ignores_empty_values():
+    assert is_hidden_model(None) is False
+    assert is_hidden_model("") is False
+    assert is_hidden_model(None, "", "unsloth/gemma-3-270m-it-GGUF") is False
+
+
+def test_hidden_model_matchers_expose_probe_needles():
+    needles, exact_ids, _exact_paths = models_route.hidden_model_matchers()
+    lowered = [n.lower() for n in needles]
+    assert "ggml-org/models" in lowered
+    assert "stories260k.gguf" in lowered
+    # The configured embedder is exposed as an exact repo id, never as a
+    # basename needle that would substring-hide unrelated chat models.
+    assert "bge-small-en-v1.5" not in lowered
+    assert "unsloth/bge-small-en-v1.5" in exact_ids
+
+
+def test_hidden_model_matchers_custom_repo_publishes_exact_ids(monkeypatch):
+    monkeypatch.setattr(rag_config, "effective_embedding_model", lambda: "org/model")
+    monkeypatch.setattr(rag_config, "effective_gguf_repo", lambda: "org/model-GGUF")
+    needles, exact_ids, exact_paths = models_route.hidden_model_matchers()
+    assert needles == ["ggml-org/models", "stories260k.gguf"]
+    assert "org/model" in exact_ids
+    assert "org/model-gguf" in exact_ids
+    assert exact_paths == []
+
+
+def test_hidden_model_matchers_local_owner_name_path_is_exact_path(monkeypatch, tmp_path):
+    # A local embedder shaped like owner/name that exists on disk must be an
+    # exact resolved path, not a Hub repo id (mirroring is_hidden_model), so the
+    # local row stays hidden instead of showing as a chat model.
+    (tmp_path / "models" / "embedder").mkdir(parents = True)
+    monkeypatch.chdir(tmp_path)
+    monkeypatch.setattr(rag_config, "effective_embedding_model", lambda: "models/embedder")
+    monkeypatch.setattr(rag_config, "effective_gguf_repo", lambda: "ggml-org/models")
+    _needles, exact_ids, exact_paths = models_route.hidden_model_matchers()
+    resolved = str((tmp_path / "models" / "embedder").resolve()).lower()
+    assert resolved in exact_paths
+    assert "models/embedder" not in exact_ids
+
+
+# --------------------------------------------------------------------------- #
+# HF token via header, query string only as a fallback (the token-leak fix)    #
+# --------------------------------------------------------------------------- #
+
+
+def test_get_hf_token_strips_and_returns():
+    assert get_hf_token("  hf_abc ") == "hf_abc"
+
+
+@pytest.mark.parametrize("value", [None, "", "   ", "\n\t"])
+def test_get_hf_token_blank_is_none(value):
+    assert get_hf_token(value) is None
+
+
+@pytest.mark.parametrize(
+    "value,expected",
+    [("  hf_x ", "hf_x"), ("", None), ("   ", None), (None, None), (1234, None)],
+)
+def test_normalize_hf_token(value, expected):
+    assert models_route._normalize_hf_token(value) == expected
+
+
+def test_header_token_wins_over_query():
+    header, query = "hf_header", "hf_query"
+    resolved = models_route._normalize_hf_token(header) or models_route._normalize_hf_token(query)
+    assert resolved == "hf_header"
+
+
+def test_query_token_is_fallback_when_header_absent():
+    resolved = models_route._normalize_hf_token(None) or models_route._normalize_hf_token(
+        "hf_query"
+    )
+    assert resolved == "hf_query"
+
+
+# --------------------------------------------------------------------------- #
+# Chat-template byte caps (the unbounded-template hardening)                    #
+# --------------------------------------------------------------------------- #
+
+
+def _load_request(**overrides):
+    data = {"model_path": "unsloth/test-model-GGUF", "gguf_variant": "Q4_K_M"}
+    data.update(overrides)
+    return LoadRequest.model_validate(data)
+
+
+def test_blank_chat_template_override_normalizes_to_none():
+    assert _load_request(chat_template_override = "   \n\t").chat_template_override is None
+
+
+def test_nonblank_chat_template_override_preserved_verbatim():
+    template = "  {{ messages }}  "
+    assert _load_request(chat_template_override = template).chat_template_override == template
+
+
+def test_chat_template_at_byte_limit_is_accepted():
+    template = "a" * MAX_CHAT_TEMPLATE_BYTES  # exactly the limit, 1 byte/char
+    assert (
+        len(_load_request(chat_template_override = template).chat_template_override)
+        == MAX_CHAT_TEMPLATE_BYTES
+    )
+
+
+def test_chat_template_over_char_limit_is_rejected():
+    with pytest.raises(Exception):  # pydantic ValidationError wrapping ValueError
+        _load_request(chat_template_override = "a" * (MAX_CHAT_TEMPLATE_BYTES + 1))
+
+
+def test_chat_template_over_byte_limit_is_rejected():
+    # Char count stays under the limit but UTF-8 bytes exceed it (3 bytes/char),
+    # so only the byte-count branch can catch this.
+    multibyte = "€" * (MAX_CHAT_TEMPLATE_BYTES // 2)  # euro sign, 3 bytes each
+    assert len(multibyte) <= MAX_CHAT_TEMPLATE_BYTES
+    assert len(multibyte.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES
+    with pytest.raises(Exception):
+        _load_request(chat_template_override = multibyte)
+
+
+def test_read_bounded_text_reads_within_limit(tmp_path):
+    p = tmp_path / "t.json"
+    p.write_text("hello", encoding = "utf-8")
+    assert _read_bounded_text(p, 16) == "hello"
+
+
+def test_read_bounded_text_rejects_over_limit(tmp_path):
+    p = tmp_path / "big.json"
+    p.write_bytes(b"x" * 100)
+    assert _read_bounded_text(p, 50) is None
+
+
+def test_read_bounded_text_at_limit_is_read(tmp_path):
+    p = tmp_path / "exact.json"
+    p.write_bytes(b"x" * 50)
+    assert _read_bounded_text(p, 50) == "x" * 50
+
+
+def test_read_bounded_text_missing_file_is_none(tmp_path):
+    assert _read_bounded_text(tmp_path / "nope.json", 50) is None
diff --git a/studio/backend/tests/test_model_update_robustness.py b/studio/backend/tests/test_model_update_robustness.py
index edf55812e2..d84f8c94a7 100644
--- a/studio/backend/tests/test_model_update_robustness.py
+++ b/studio/backend/tests/test_model_update_robustness.py
@@ -112,13 +112,21 @@ def patch_hub_gguf(monkeypatch):
             blob_ids = [local_blob],
             gguf_files = {"model-Q4_K_M.gguf": 1000},
         )
+        monkeypatch.setattr(
+            "utils.hf_cache_settings.get_hf_cache_paths",
+            lambda: SimpleNamespace(hub_cache = tmp_path),
+        )
         monkeypatch.setattr(
             GV,
             "list_gguf_variants",
             lambda r, hf_token = None: (_variants(), False, [remote_sibling]),
             raising = True,
         )
-        monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id: [snap])
+        monkeypatch.setattr(
+            GV,
+            "iter_hf_cache_snapshots",
+            lambda _repo_id, root = None: [snap],
+        )
         monkeypatch.setattr(
             CI,
             "all_hf_cache_scans",
@@ -217,6 +225,10 @@ def test_variant_update_check_detects_companion_only_update(
             companion_path: 100,
         },
     )
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = tmp_path),
+    )
     siblings = [
         patch_hub_gguf.sibling("model-Q4_K_M.gguf", 1000, "mainsha"),
         patch_hub_gguf.sibling(companion_path, 100, "new-companion"),
@@ -227,7 +239,11 @@ def test_variant_update_check_detects_companion_only_update(
         lambda r, hf_token = None: (_variants(), has_vision, siblings),
         raising = True,
     )
-    monkeypatch.setattr(GV, "iter_hf_cache_snapshots", lambda _repo_id: [snap])
+    monkeypatch.setattr(
+        GV,
+        "iter_hf_cache_snapshots",
+        lambda _repo_id, root = None: [snap],
+    )
     monkeypatch.setattr(
         CI,
         "all_hf_cache_scans",
@@ -314,6 +330,7 @@ def test_cached_model_scan_keeps_local_safetensors_repo(monkeypatch, tmp_path):
                         file_name = "model.safetensors",
                         size_on_disk = 100,
                         blob_path = str(repo_path / "blobs" / "modelsha"),
+                        blob_last_modified = 3_000.0,
                     ),
                 ]
             )
@@ -336,6 +353,98 @@ def test_cached_model_scan_keeps_local_safetensors_repo(monkeypatch, tmp_path):
     assert rows[0]["repo_id"] == "Org/SafeTensorRepo"
     assert rows[0]["model_format"] == "safetensors"
     assert rows[0]["size_bytes"] == 100
+    assert rows[0]["last_modified"] == 3_000.0
+
+
+def test_cached_gguf_scan_keeps_download_timestamp(monkeypatch, tmp_path):
+    repo_path = tmp_path / "models--Org--GgufRepo"
+    repo = SimpleNamespace(
+        repo_id = "Org/GgufRepo",
+        repo_type = "model",
+        repo_path = repo_path,
+        revisions = [
+            SimpleNamespace(
+                files = [
+                    SimpleNamespace(
+                        file_name = "model-Q4_K_M.gguf",
+                        size_on_disk = 100,
+                        blob_path = None,
+                        blob_last_modified = 5_000.0,
+                    ),
+                ]
+            )
+        ],
+    )
+    monkeypatch.setattr(
+        CI,
+        "all_hf_cache_scans",
+        lambda: [SimpleNamespace(repos = [repo])],
+    )
+    monkeypatch.setattr(
+        CI.hf_cache_scan,
+        "is_gguf_repo_partial",
+        lambda *args, **kwargs: False,
+    )
+    monkeypatch.setattr(
+        CI,
+        "_gguf_variant_state_summary",
+        lambda _repo_id, **_kwargs: (False, 0),
+    )
+
+    rows = CI._scan_cached_gguf()
+
+    assert len(rows) == 1
+    assert rows[0]["repo_id"] == "Org/GgufRepo"
+    assert rows[0]["model_format"] == "gguf"
+    assert rows[0]["size_bytes"] == 100
+    assert rows[0]["last_modified"] == 5_000.0
+
+
+def test_cached_model_scan_hides_custom_whisper_repo(monkeypatch, tmp_path):
+    repo_path = tmp_path / "models--Org--CustomWhisper"
+    snapshot = repo_path / "snapshots" / ("a" * 40)
+    snapshot.mkdir(parents = True)
+    (snapshot / "config.json").write_text(
+        '{"model_type": "whisper", "architectures": ["WhisperForConditionalGeneration"]}'
+    )
+    repo = SimpleNamespace(
+        repo_id = "Org/CustomWhisper",
+        repo_type = "model",
+        repo_path = repo_path,
+        revisions = [
+            SimpleNamespace(
+                files = [
+                    SimpleNamespace(
+                        file_name = "config.json",
+                        size_on_disk = 10,
+                        blob_path = None,
+                    ),
+                    SimpleNamespace(
+                        file_name = "model.safetensors",
+                        size_on_disk = 100,
+                        blob_path = str(repo_path / "blobs" / "modelsha"),
+                    ),
+                ]
+            )
+        ],
+    )
+    monkeypatch.setattr(
+        CI,
+        "all_hf_cache_scans",
+        lambda: [SimpleNamespace(repos = [repo])],
+    )
+    monkeypatch.setattr(
+        CI,
+        "_cached_model_snapshot_path",
+        lambda _repo_path: snapshot,
+    )
+    monkeypatch.setattr(
+        CI.hf_cache_scan,
+        "is_snapshot_partial",
+        lambda *args, **kwargs: False,
+    )
+
+    assert CI._scan_cached_models() == []
 
 
 # ── hf_hub_download_with_xet_fallback force_download bypass (X2/F2) ───
@@ -584,7 +693,12 @@ def test_reclaim_replaced_gguf_variant_prunes_old_revision_only(monkeypatch, tmp
     invalidated = []
     monkeypatch.setattr(CI, "invalidate_hf_cache_scans", lambda: invalidated.append(True))
 
-    result = D.reclaim_replaced_gguf_variant(repo_id, "Q4_K_M", frozenset({"NEWsha"}))
+    result = D.reclaim_replaced_gguf_variant(
+        repo_id,
+        "Q4_K_M",
+        frozenset({"NEWsha"}),
+        hub_cache = tmp_path,
+    )
 
     assert result["removed_snapshots"] == 1
     assert result["deleted_blobs"] == 1
@@ -631,8 +745,85 @@ def test_reclaim_replaced_gguf_variant_keeps_no_symlink_current_file(monkeypatch
     monkeypatch.setattr(CI, "all_hf_cache_scans", lambda: [SimpleNamespace(repos = [repo_info])])
     monkeypatch.setattr(CI, "invalidate_hf_cache_scans", lambda: None)
 
-    result = D.reclaim_replaced_gguf_variant(repo_id, "Q4_K_M", frozenset({"REMOTEsha256"}))
+    result = D.reclaim_replaced_gguf_variant(
+        repo_id,
+        "Q4_K_M",
+        frozenset({"REMOTEsha256"}),
+        hub_cache = tmp_path,
+    )
 
     assert snap.exists() is True  # the current file must survive
     assert result["removed_snapshots"] == 0
     assert result["deleted_blobs"] == 0
+
+
+def test_reclaim_replaced_gguf_variant_only_mutates_worker_cache(monkeypatch, tmp_path):
+    repo_id = "org/repo-GGUF"
+    cache_a = tmp_path / "cache-a"
+    cache_b = tmp_path / "cache-b"
+
+    def cached_repo(cache_dir, revision):
+        repo_path = cache_dir / "models--org--repo-GGUF"
+        snap = repo_path / "snapshots" / revision / "model-Q4_K_M.gguf"
+        blob = repo_path / "blobs" / "OLDsha"
+        snap.parent.mkdir(parents = True, exist_ok = True)
+        blob.parent.mkdir(parents = True, exist_ok = True)
+        blob.write_bytes(b"old")
+        snap.symlink_to(blob)
+        return (
+            SimpleNamespace(
+                repo_id = repo_id,
+                repo_type = "model",
+                repo_path = repo_path,
+                revisions = [
+                    SimpleNamespace(
+                        files = [
+                            SimpleNamespace(
+                                file_name = snap.name,
+                                file_path = str(snap),
+                                blob_path = str(blob),
+                            )
+                        ]
+                    )
+                ],
+            ),
+            snap,
+            blob,
+        )
+
+    repo_a, snap_a, blob_a = cached_repo(cache_a, "a" * 40)
+    repo_b, snap_b, blob_b = cached_repo(cache_b, "b" * 40)
+    monkeypatch.setattr(
+        CI,
+        "all_hf_cache_scans",
+        lambda: [SimpleNamespace(repos = [repo_a]), SimpleNamespace(repos = [repo_b])],
+    )
+    monkeypatch.setattr(CI, "invalidate_hf_cache_scans", lambda: None)
+
+    result = D.reclaim_replaced_gguf_variant(
+        repo_id,
+        "Q4_K_M",
+        frozenset({"NEWsha"}),
+        hub_cache = cache_b,
+    )
+
+    assert result["removed_snapshots"] == 1
+    assert snap_b.exists() is False
+    assert blob_b.exists() is False
+    assert snap_a.exists() is True
+    assert blob_a.exists() is True
+
+
+def _mmproj_repo(*file_names: str):
+    return SimpleNamespace(
+        revisions = [SimpleNamespace(files = [SimpleNamespace(file_name = n) for n in file_names])]
+    )
+
+
+def test_repo_has_mmproj_requires_gguf_projector():
+    # A non-GGUF sidecar whose name merely contains "mmproj" must NOT mark the
+    # repo vision-capable; the runtime's projector detection is GGUF-only.
+    assert CI._repo_has_mmproj(_mmproj_repo("model-Q4_K_M.gguf", "mmproj_config.json")) is False
+    assert CI._repo_has_mmproj(_mmproj_repo("model-Q4_K_M.gguf", "README-mmproj.md")) is False
+    # A real GGUF projector still marks the repo vision-capable.
+    assert CI._repo_has_mmproj(_mmproj_repo("model-Q4_K_M.gguf", "mmproj-F16.gguf")) is True
diff --git a/studio/backend/tests/test_models_get_model_config_case_resolution.py b/studio/backend/tests/test_models_get_model_config_case_resolution.py
index 12f6c497ab..a50765898b 100644
--- a/studio/backend/tests/test_models_get_model_config_case_resolution.py
+++ b/studio/backend/tests/test_models_get_model_config_case_resolution.py
@@ -84,7 +84,7 @@ def test_repo_in_any_hf_cache_matches_case_variant_in_legacy_cache(tmp_path, mon
     # covers the active cache; discard deletes case-insensitively, so detection must too,
     # else a decline deletes a pre-existing user repo).
     import utils.paths as paths_pkg
-    import huggingface_hub.constants as hf_constants
+    import hub.utils.paths as hub_paths
 
     active = tmp_path / "active"
     legacy = tmp_path / "legacy"
@@ -96,9 +96,12 @@ def test_repo_in_any_hf_cache_matches_case_variant_in_legacy_cache(tmp_path, mon
 
     # No active-cache variant; case resolution is a no-op here.
     monkeypatch.setattr(paths_pkg, "resolve_cached_repo_id_case", lambda name: name)
-    monkeypatch.setattr(paths_pkg, "legacy_hf_cache_dir", lambda: legacy)
-    monkeypatch.setattr(paths_pkg, "hf_default_cache_dir", lambda: default)
-    monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(active))
+    monkeypatch.setattr(hub_paths, "legacy_hf_cache_dir", lambda: legacy)
+    monkeypatch.setattr(hub_paths, "hf_default_cache_dir", lambda: default)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.known_hf_hub_caches",
+        lambda: [active],
+    )
 
     assert models_route._repo_in_any_hf_cache("unsloth/foo") is True
     # Absent from every cache -> reported absent.
diff --git a/studio/backend/tests/test_offline_embedding_minimal.py b/studio/backend/tests/test_offline_embedding_minimal.py
new file mode 100644
index 0000000000..7ff580c36d
--- /dev/null
+++ b/studio/backend/tests/test_offline_embedding_minimal.py
@@ -0,0 +1,598 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Offline RAG embedding-model handling (issue #6817).
+
+Offline the studio must never call the Hub (a DNS-dead session hangs on retries). Using a fake
+HF cache under a temp HF_HUB_CACHE, assert that offline: is_embedding_model classifies from the
+cached modules.json without the Hub; the file-security gate fails CLOSED on an unscanned pickle
+weight with no safetensors alternative and allows an inert cache; the embedder threads
+local_files_only into the load. Online behavior is unchanged (bounded timeout + cache fallback).
+"""
+
+import sys
+import types
+from pathlib import Path
+from types import SimpleNamespace
+from unittest.mock import patch
+
+import pytest
+
+from utils.security import evaluate_file_security
+from utils.utils import (
+    hf_cache_snapshot_dir,
+    hf_cache_snapshot_is_loadable,
+    hf_env_offline,
+    st_repo_id_candidates,
+)
+
+# Minimal sentence-transformers modules.json (the marker the gate keys on).
+MODULES_JSON = (
+    '[{"idx": 0, "name": "0", "path": "", "type": "sentence_transformers.models.Transformer"}]'
+)
+
+
+def _modules_json(*paths):
+    """modules.json listing one Transformer module per path (a load root)."""
+    import json
+    return json.dumps(
+        [
+            {
+                "idx": i,
+                "name": str(i),
+                "path": p,
+                "type": "sentence_transformers.models.Transformer",
+            }
+            for i, p in enumerate(paths)
+        ]
+    )
+
+
+_COMMIT = "0123456789abcdef0123456789abcdef01234567"
+
+
+def _make_cache(
+    root,
+    repo_id,
+    files,
+    commit = _COMMIT,
+):
+    """Build a canonical HF-cache snapshot (refs/main + snapshots/<commit>/) for repo_id under
+    root from {relpath: contents}; returns the snapshot dir."""
+    from huggingface_hub.file_download import repo_folder_name
+
+    repo_dir = Path(root) / repo_folder_name(repo_id = repo_id, repo_type = "model")
+    (repo_dir / "refs").mkdir(parents = True, exist_ok = True)
+    (repo_dir / "refs" / "main").write_text(commit)
+    snapshot = repo_dir / "snapshots" / commit
+    snapshot.mkdir(parents = True, exist_ok = True)
+    for rel, contents in files.items():
+        path = snapshot / rel
+        path.parent.mkdir(parents = True, exist_ok = True)
+        path.write_text(contents)
+    return snapshot
+
+
+def _no_network():
+    """Patch model_info to fail loudly if any offline path reaches the network."""
+    return patch("huggingface_hub.model_info", side_effect = AssertionError("hit the network"))
+
+
+def _is_embedding_model(*args, **kwargs):
+    from utils.models.model_config import is_embedding_model
+    return is_embedding_model(*args, **kwargs)
+
+
+@pytest.fixture
+def hf_cache(tmp_path, monkeypatch):
+    """Point the HF cache at a fresh temp dir.
+
+    get_hf_cache_paths() reads an import-time env snapshot, not live os.environ,
+    so point it (and thus active_hf_hub_cache + the snapshot lookup's selected
+    root) at this temp cache too."""
+    root = tmp_path / "hub"
+    root.mkdir()
+    monkeypatch.setenv("HF_HOME", str(tmp_path))
+    monkeypatch.setenv("HF_HUB_CACHE", str(root))
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = root),
+    )
+    return root
+
+
+@pytest.fixture(autouse = True)
+def _clean_env(monkeypatch):
+    """Start each test online with an empty detection cache; offline tests opt in."""
+    monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
+    monkeypatch.delenv("TRANSFORMERS_OFFLINE", raising = False)
+    from utils.models import model_config as mc
+
+    mc._embedding_detection_cache.clear()
+    yield
+    mc._embedding_detection_cache.clear()
+
+
+# ── hf_env_offline ───────────────────────────────────────────────
+
+
+@pytest.mark.parametrize("value", ["1", "true", "TRUE", "yes", "on", "  On  "])
+def test_hf_env_offline_true(monkeypatch, value):
+    monkeypatch.setenv("HF_HUB_OFFLINE", value)
+    assert hf_env_offline() is True
+
+
+@pytest.mark.parametrize("value", ["0", "false", "no", "off", ""])
+def test_hf_env_offline_false(monkeypatch, value):
+    monkeypatch.setenv("HF_HUB_OFFLINE", value)
+    assert hf_env_offline() is False
+
+
+def test_hf_env_offline_honors_transformers_flag(monkeypatch):
+    monkeypatch.setenv("TRANSFORMERS_OFFLINE", "1")
+    assert hf_env_offline() is True
+
+
+def test_hf_env_offline_default_false():
+    assert hf_env_offline() is False
+
+
+# ── st_repo_id_candidates ────────────────────────────────────────
+
+
+def test_candidates_slashless_adds_st_alias():
+    assert st_repo_id_candidates("all-MiniLM-L6-v2") == [
+        "all-MiniLM-L6-v2",
+        "sentence-transformers/all-MiniLM-L6-v2",
+    ]
+
+
+def test_candidates_with_org_is_verbatim():
+    assert st_repo_id_candidates("org/model") == ["org/model"]
+
+
+def test_candidates_empty_name():
+    assert st_repo_id_candidates("   ") == []
+
+
+# ── hf_cache_snapshot_dir ────────────────────────────────────────
+
+
+def test_snapshot_dir_resolves_active_commit(hf_cache):
+    snapshot = _make_cache(hf_cache, "org/emb", {"modules.json": MODULES_JSON})
+    assert hf_cache_snapshot_dir("org/emb") == snapshot
+
+
+def test_snapshot_dir_none_when_uncached(hf_cache):
+    assert hf_cache_snapshot_dir("org/missing") is None
+
+
+def test_snapshot_dir_uses_st_alias_for_slashless(hf_cache):
+    snapshot = _make_cache(
+        hf_cache, "sentence-transformers/all-MiniLM-L6-v2", {"modules.json": MODULES_JSON}
+    )
+    assert hf_cache_snapshot_dir("all-MiniLM-L6-v2") == snapshot
+
+
+def test_snapshot_dir_none_when_snapshot_missing(hf_cache):
+    from huggingface_hub.file_download import repo_folder_name
+
+    repo_dir = hf_cache / repo_folder_name(repo_id = "org/broken", repo_type = "model")
+    (repo_dir / "refs").mkdir(parents = True)
+    (repo_dir / "refs" / "main").write_text("deadbeef")  # no snapshots/deadbeef dir
+    assert hf_cache_snapshot_dir("org/broken") is None
+
+
+def test_snapshot_dir_expands_env_vars_in_cache_path(tmp_path, monkeypatch):
+    # An unexpanded $VAR in HF_HUB_CACHE must resolve where the loader looks.
+    real = tmp_path / "hub"
+    real.mkdir()
+    monkeypatch.setenv("MY_HF_CACHE", str(real))
+    monkeypatch.setenv("HF_HUB_CACHE", "$MY_HF_CACHE")
+    monkeypatch.delenv("HF_HOME", raising = False)
+    monkeypatch.delenv("SENTENCE_TRANSFORMERS_HOME", raising = False)
+    snapshot = _make_cache(real, "org/emb", {"modules.json": MODULES_JSON})
+    assert hf_cache_snapshot_dir("org/emb") == snapshot
+
+
+def test_snapshot_dir_uses_sentence_transformers_home(tmp_path, monkeypatch):
+    # ST uses SENTENCE_TRANSFORMERS_HOME as its cache_folder, so the gate must inspect it too.
+    st_home = tmp_path / "st_home"
+    st_home.mkdir()
+    monkeypatch.setenv("SENTENCE_TRANSFORMERS_HOME", str(st_home))
+    monkeypatch.delenv("HF_HUB_CACHE", raising = False)
+    monkeypatch.delenv("HF_HOME", raising = False)
+    snapshot = _make_cache(st_home, "org/emb", {"modules.json": MODULES_JSON})
+    assert hf_cache_snapshot_dir("org/emb") == snapshot
+
+
+def test_snapshot_dir_prefers_selected_cache_over_st_home(tmp_path, monkeypatch):
+    # The RAG loader passes cache_folder=active_hf_hub_cache(), which overrides
+    # SENTENCE_TRANSFORMERS_HOME, so the snapshot + offline security lookup must
+    # search the selected cache even when ST_HOME points elsewhere. Otherwise the
+    # gate scans a cache the model never loads from and a pickle weight in the
+    # selected cache slips through.
+    st_home = tmp_path / "st_home"
+    st_home.mkdir()
+    selected = tmp_path / "hub"
+    selected.mkdir()
+    monkeypatch.setenv("SENTENCE_TRANSFORMERS_HOME", str(st_home))
+    monkeypatch.delenv("HF_HUB_CACHE", raising = False)
+    monkeypatch.delenv("HF_HOME", raising = False)
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: SimpleNamespace(hub_cache = selected),
+    )
+    snapshot = _make_cache(selected, "org/emb", {"modules.json": MODULES_JSON})  # only in selected
+    assert hf_cache_snapshot_dir("org/emb") == snapshot
+
+
+def test_snapshot_is_loadable_with_config_and_weights(hf_cache):
+    _make_cache(hf_cache, "org/emb", {"config.json": "{}", "model.safetensors": "x"})
+    assert hf_cache_snapshot_is_loadable("org/emb") is True
+
+
+def test_snapshot_is_not_loadable_when_metadata_only(hf_cache):
+    # A partial cache (refs/main resolves but no weights) is not loadable.
+    _make_cache(hf_cache, "org/partial", {"config.json": "{}", "modules.json": MODULES_JSON})
+    assert hf_cache_snapshot_is_loadable("org/partial") is False
+
+
+def test_snapshot_is_not_loadable_when_uncached(hf_cache):
+    assert hf_cache_snapshot_is_loadable("org/missing") is False
+
+
+def test_gate_blocks_pickle_in_sentence_transformers_home(tmp_path, monkeypatch):
+    # A pickle under SENTENCE_TRANSFORMERS_HOME must still fail closed offline.
+    st_home = tmp_path / "st_home"
+    st_home.mkdir()
+    monkeypatch.setenv("SENTENCE_TRANSFORMERS_HOME", str(st_home))
+    monkeypatch.delenv("HF_HUB_CACHE", raising = False)
+    monkeypatch.delenv("HF_HOME", raising = False)
+    _make_cache(st_home, "org/pk", {"config.json": "{}", "pytorch_model.bin": "x"})
+    with _no_network():
+        assert evaluate_file_security("org/pk", local_only_load = True).blocked is True
+
+
+# ── is_embedding_model: offline (no network) ─────────────────────
+
+
+def test_offline_true_for_cached_st_model(hf_cache, monkeypatch):
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    _make_cache(hf_cache, "org/emb", {"modules.json": MODULES_JSON, "config.json": "{}"})
+    with _no_network():
+        assert _is_embedding_model("org/emb") is True
+
+
+def test_offline_false_for_cached_non_st_model(hf_cache, monkeypatch):
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    _make_cache(hf_cache, "org/plain", {"config.json": "{}", "model.safetensors": "x"})
+    with _no_network():
+        assert _is_embedding_model("org/plain") is False
+
+
+def test_offline_false_when_uncached(hf_cache, monkeypatch):
+    monkeypatch.setenv("TRANSFORMERS_OFFLINE", "1")
+    with _no_network():
+        assert _is_embedding_model("org/missing") is False
+
+
+def test_offline_slashless_resolves_via_alias(hf_cache, monkeypatch):
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    _make_cache(hf_cache, "sentence-transformers/all-MiniLM-L6-v2", {"modules.json": MODULES_JSON})
+    with _no_network():
+        assert _is_embedding_model("all-MiniLM-L6-v2") is True
+
+
+def test_offline_ignores_stale_online_memo(hf_cache, monkeypatch):
+    # An online lookup memoizes True for an UNCACHED repo (tags say embedding, no weights). Once
+    # offline, is_embedding_model must reclassify from the empty cache and return False, not the
+    # stale online True that would make settings accept a repo _get() cannot load.
+    with patch(
+        "huggingface_hub.model_info",
+        side_effect = lambda *a, **k: SimpleNamespace(
+            tags = ["sentence-transformers"], pipeline_tag = None
+        ),
+    ):
+        assert _is_embedding_model("org/uncached-emb") is True  # memoized True online
+
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    with _no_network():
+        assert _is_embedding_model("org/uncached-emb") is False  # recomputed from empty cache
+
+
+def test_offline_recomputes_after_cache_materializes(hf_cache, monkeypatch):
+    # Because the offline branch never records a memo, once an uncached repo's snapshot
+    # materializes (another process populates the cache) the next call re-reports True.
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    with _no_network():
+        assert _is_embedding_model("org/later") is False  # uncached
+        _make_cache(hf_cache, "org/later", {"modules.json": MODULES_JSON})
+        assert _is_embedding_model("org/later") is True  # cache now present, no stale negative
+
+
+# ── is_embedding_model: online (bounded + fallback) ──────────────
+
+
+def test_online_passes_bounded_timeout(hf_cache):
+    seen = {}
+
+    def _mi(
+        name,
+        token = None,
+        timeout = None,
+        **kw,
+    ):
+        seen["timeout"] = timeout
+        return SimpleNamespace(tags = ["sentence-transformers"], pipeline_tag = None)
+
+    with patch("huggingface_hub.model_info", side_effect = _mi):
+        assert _is_embedding_model("org/emb") is True
+    assert seen["timeout"] == 15.0
+
+
+def test_online_error_falls_back_to_cache_marker(hf_cache):
+    _make_cache(hf_cache, "org/emb", {"modules.json": MODULES_JSON})
+    with patch("huggingface_hub.model_info", side_effect = RuntimeError("dns dead")):
+        assert _is_embedding_model("org/emb") is True
+
+
+def test_online_error_without_cache_returns_false(hf_cache):
+    with patch("huggingface_hub.model_info", side_effect = RuntimeError("dns dead")):
+        assert _is_embedding_model("org/missing") is False
+
+
+# ── evaluate_file_security: offline fail-closed gate ─────────────
+
+
+def _offline_decision(name):
+    return evaluate_file_security(name, local_only_load = True)
+
+
+def test_gate_allows_safetensors_only(hf_cache):
+    _make_cache(hf_cache, "org/st", {"modules.json": MODULES_JSON, "model.safetensors": "x"})
+    with _no_network():
+        assert _offline_decision("org/st").blocked is False
+
+
+def test_gate_blocks_pickle_without_safetensors(hf_cache):
+    _make_cache(hf_cache, "org/pk", {"config.json": "{}", "pytorch_model.bin": "x"})
+    with _no_network():
+        decision = _offline_decision("org/pk")
+    assert decision.blocked is True
+    assert any(u["path"] == "pytorch_model.bin" for u in decision.unsafe_files)
+
+
+def test_gate_allows_pickle_with_safetensors_sibling(hf_cache):
+    _make_cache(hf_cache, "org/both", {"pytorch_model.bin": "x", "model.safetensors": "y"})
+    with _no_network():
+        assert _offline_decision("org/both").blocked is False
+
+
+def test_gate_blocks_sharded_pickle(hf_cache):
+    _make_cache(
+        hf_cache,
+        "org/shard",
+        {
+            "pytorch_model-00001-of-00002.bin": "a",
+            "pytorch_model-00002-of-00002.bin": "b",
+        },
+    )
+    with _no_network():
+        assert _offline_decision("org/shard").blocked is True
+
+
+def test_gate_allows_nothing_cached(hf_cache):
+    with _no_network():
+        assert _offline_decision("org/missing").blocked is False
+
+
+def test_gate_allows_gguf_only(hf_cache):
+    _make_cache(hf_cache, "org/gg", {"model.gguf": "x"})
+    with _no_network():
+        assert _offline_decision("org/gg").blocked is False
+
+
+def test_gate_blocks_pickle_in_module_subdir(hf_cache):
+    # 0_Transformer is a module load root (listed in modules.json), so its pickle blocks.
+    _make_cache(
+        hf_cache,
+        "org/mod",
+        {"modules.json": _modules_json("0_Transformer"), "0_Transformer/pytorch_model.bin": "x"},
+    )
+    with _no_network():
+        assert _offline_decision("org/mod").blocked is True
+
+
+def test_gate_allows_pickle_in_subdir_with_safetensors(hf_cache):
+    _make_cache(
+        hf_cache,
+        "org/mod2",
+        {
+            "modules.json": _modules_json("0_Transformer"),
+            "0_Transformer/pytorch_model.bin": "x",
+            "0_Transformer/model.safetensors": "y",
+        },
+    )
+    with _no_network():
+        assert _offline_decision("org/mod2").blocked is False
+
+
+def test_gate_allows_unreferenced_nested_pickle(hf_cache):
+    # A pickle in a dir NOT referenced by modules.json (e.g. nemo/) is never deserialized, so it
+    # must not block the offline load (matches the online gate).
+    _make_cache(
+        hf_cache,
+        "org/aux",
+        {
+            "modules.json": MODULES_JSON,  # Transformer at the root only
+            "model.safetensors": "w",
+            "nemo/pytorch_model.bin": "x",
+        },
+    )
+    with _no_network():
+        assert _offline_decision("org/aux").blocked is False
+
+
+def test_gate_blocks_adapter_pickle_without_safetensors(hf_cache):
+    _make_cache(hf_cache, "org/ad", {"config.json": "{}", "adapter_model.bin": "x"})
+    with _no_network():
+        decision = _offline_decision("org/ad")
+    assert decision.blocked is True
+    assert any(u["path"] == "adapter_model.bin" for u in decision.unsafe_files)
+
+
+def test_gate_allows_adapter_pickle_with_adapter_safetensors(hf_cache):
+    _make_cache(hf_cache, "org/ad2", {"adapter_model.bin": "x", "adapter_model.safetensors": "y"})
+    with _no_network():
+        assert _offline_decision("org/ad2").blocked is False
+
+
+def test_gate_blocks_base_pickle_with_only_adapter_safetensors_decoy(hf_cache):
+    # A decoy adapter_model.safetensors must NOT suppress a base pytorch_model.bin (the base
+    # loader would still deserialize the unscanned pickle).
+    _make_cache(hf_cache, "org/decoy", {"pytorch_model.bin": "x", "adapter_model.safetensors": "y"})
+    with _no_network():
+        assert _offline_decision("org/decoy").blocked is True
+
+
+def test_gate_blocks_adapter_pickle_with_only_base_safetensors_decoy(hf_cache):
+    # Symmetric: a base model.safetensors must NOT suppress an adapter_model.bin.
+    _make_cache(hf_cache, "org/decoy2", {"adapter_model.bin": "x", "model.safetensors": "y"})
+    with _no_network():
+        assert _offline_decision("org/decoy2").blocked is True
+
+
+def test_gate_reports_snapshot_relative_path(hf_cache):
+    _make_cache(
+        hf_cache,
+        "org/mod3",
+        {"modules.json": _modules_json("0_Transformer"), "0_Transformer/pytorch_model.bin": "x"},
+    )
+    with _no_network():
+        decision = _offline_decision("org/mod3")
+    assert decision.blocked is True
+    assert any(u["path"] == "0_Transformer/pytorch_model.bin" for u in decision.unsafe_files)
+
+
+# ── evaluate_file_security: online path unchanged ────────────────
+
+
+def test_online_default_blocks_unsafe():
+    status = {
+        "scansDone": True,
+        "filesWithIssues": [{"path": "pytorch_model.bin", "level": "unsafe"}],
+    }
+    with patch(
+        "huggingface_hub.model_info",
+        side_effect = lambda *a, **k: SimpleNamespace(security_repo_status = status),
+    ):
+        assert evaluate_file_security("org/x").blocked is True
+
+
+def test_online_default_allows_clean():
+    status = {"scansDone": True, "filesWithIssues": []}
+    with patch(
+        "huggingface_hub.model_info",
+        side_effect = lambda *a, **k: SimpleNamespace(security_repo_status = status),
+    ):
+        assert evaluate_file_security("org/x").blocked is False
+
+
+# ── embeddings guard + loader ────────────────────────────────────
+
+
+def test_guard_offline_blocks_pickle_only(hf_cache):
+    from core.rag.embeddings import UnsafeEmbeddingModelError, _guard_model_security
+    _make_cache(hf_cache, "org/pk", {"config.json": "{}", "pytorch_model.bin": "x"})
+    with _no_network():
+        with pytest.raises(UnsafeEmbeddingModelError):
+            _guard_model_security("org/pk", local_only = True)
+
+
+def test_guard_offline_allows_safetensors(hf_cache):
+    from core.rag.embeddings import _guard_model_security
+    _make_cache(hf_cache, "org/st", {"modules.json": MODULES_JSON, "model.safetensors": "x"})
+    with _no_network():
+        _guard_model_security("org/st", local_only = True)  # must not raise
+
+
+def _install_fake_sentence_transformers(monkeypatch, captured):
+    class FakeSentenceTransformer:
+        def __init__(
+            self,
+            name,
+            *,
+            device = None,
+            model_kwargs = None,
+            local_files_only = False,
+            **kw,
+        ):
+            captured["name"] = name
+            captured["device"] = device
+            captured["local_files_only"] = local_files_only
+
+    module = types.ModuleType("sentence_transformers")
+    module.SentenceTransformer = FakeSentenceTransformer
+    monkeypatch.setitem(sys.modules, "sentence_transformers", module)
+
+
+def test_get_offline_loads_from_local_snapshot(hf_cache, monkeypatch):
+    from core.rag import embeddings
+
+    snapshot = _make_cache(
+        hf_cache, "org/st", {"modules.json": MODULES_JSON, "model.safetensors": "x"}
+    )
+    # TRANSFORMERS_OFFLINE only: a cached model loads from its local snapshot dir (a local path,
+    # never the Hub), offline-safe on ANY sentence-transformers version.
+    monkeypatch.setenv("TRANSFORMERS_OFFLINE", "1")
+    monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
+    monkeypatch.setattr(embeddings, "_model", None, raising = False)
+    monkeypatch.setattr(embeddings, "_name", None, raising = False)
+    monkeypatch.setattr(embeddings, "_install_torchao_stub_once", lambda: None)
+    monkeypatch.setattr(embeddings, "_device", lambda: "cpu")
+    captured = {}
+    _install_fake_sentence_transformers(monkeypatch, captured)
+    with _no_network():
+        embeddings._get("org/st")
+    assert captured["name"] == str(snapshot)
+
+
+def test_get_offline_uncached_uses_local_files_only(tmp_path, monkeypatch):
+    from core.rag import embeddings
+
+    empty = tmp_path / "hub"
+    empty.mkdir()
+    monkeypatch.setenv("HF_HUB_CACHE", str(empty))
+    monkeypatch.delenv("HF_HOME", raising = False)
+    monkeypatch.delenv("SENTENCE_TRANSFORMERS_HOME", raising = False)
+    monkeypatch.setenv("TRANSFORMERS_OFFLINE", "1")
+    monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
+    monkeypatch.setattr(embeddings, "_model", None, raising = False)
+    monkeypatch.setattr(embeddings, "_name", None, raising = False)
+    monkeypatch.setattr(embeddings, "_install_torchao_stub_once", lambda: None)
+    monkeypatch.setattr(embeddings, "_device", lambda: "cpu")
+    # No cache -> repo-id load forced cache-only (fails fast offline, not a hang).
+    monkeypatch.setattr(embeddings, "_guard_model_security", lambda name, local_only = False: None)
+    captured = {}
+    _install_fake_sentence_transformers(monkeypatch, captured)
+    embeddings._get("org/uncached-xyz")
+    assert captured["name"] == "org/uncached-xyz"
+    assert captured["local_files_only"] is True
+
+
+def test_get_online_omits_local_files_only(monkeypatch):
+    from core.rag import embeddings
+
+    monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
+    monkeypatch.delenv("TRANSFORMERS_OFFLINE", raising = False)
+    monkeypatch.setattr(embeddings, "_model", None, raising = False)
+    monkeypatch.setattr(embeddings, "_name", None, raising = False)
+    monkeypatch.setattr(embeddings, "_install_torchao_stub_once", lambda: None)
+    monkeypatch.setattr(embeddings, "_device", lambda: "cpu")
+    # Isolate the loader wiring from the online guard's network calls.
+    monkeypatch.setattr(embeddings, "_guard_model_security", lambda name, local_only = False: None)
+    captured = {}
+    _install_fake_sentence_transformers(monkeypatch, captured)
+    embeddings._get("org/online")
+    assert captured["local_files_only"] is False
diff --git a/studio/backend/tests/test_offline_gguf_cache_fallback.py b/studio/backend/tests/test_offline_gguf_cache_fallback.py
index 295549c443..d1e61d0546 100644
--- a/studio/backend/tests/test_offline_gguf_cache_fallback.py
+++ b/studio/backend/tests/test_offline_gguf_cache_fallback.py
@@ -119,10 +119,21 @@ def _build_cache(
     return snap
 
 
+def _symlink_or_skip(link: Path, target: Path) -> None:
+    try:
+        link.symlink_to(target)
+    except OSError as exc:
+        pytest.skip(f"symlinks unavailable: {exc}")
+
+
 @pytest.fixture
 def hf_cache(tmp_path, monkeypatch):
     """Point ``huggingface_hub.constants.HF_HUB_CACHE`` at a temp dir."""
     monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.get_hf_cache_paths",
+        lambda: _types.SimpleNamespace(hub_cache = tmp_path),
+    )
     return tmp_path
 
 
@@ -220,6 +231,10 @@ class TestGgufVariantFileResolution:
             return f"/fake/{repo_id}/{filename}"
 
         monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
+        monkeypatch.setattr(
+            "utils.hf_cache_settings.get_hf_cache_paths",
+            lambda: _types.SimpleNamespace(hub_cache = tmp_path),
+        )
         with (
             patch(
                 "huggingface_hub.list_repo_files",
@@ -427,6 +442,40 @@ class TestGgufVariantFileResolution:
 
         assert out == str(snap / "mmproj-F16.gguf")
 
+    def test_download_companion_uses_selected_cache_not_import_time_default(
+        self, monkeypatch, tmp_path
+    ):
+        monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+        import_time_cache = tmp_path / "import-time-cache"
+        selected_cache = tmp_path / "selected-cache"
+        monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(import_time_cache))
+        monkeypatch.setattr(
+            "utils.hf_cache_settings.get_hf_cache_paths",
+            lambda: _types.SimpleNamespace(hub_cache = selected_cache),
+        )
+        repo = "unsloth/vision-GGUF"
+        snap = _build_cache(selected_cache, repo, {"mmproj-F16.gguf": 4})
+        backend = LlamaCppBackend()
+
+        offline_error = type("OfflineModeIsEnabled", (Exception,), {})
+
+        def fail_list(*_args, **_kwargs):
+            raise offline_error("offline")
+
+        def fail_download(*_args, **_kwargs):
+            raise AssertionError("selected-cache companion must not download")
+
+        with (
+            patch("huggingface_hub.list_repo_files", fail_list),
+            patch(
+                "core.inference.llama_cpp.hf_hub_download_with_xet_fallback",
+                fail_download,
+            ),
+        ):
+            out = backend._download_mmproj(hf_repo = repo)
+
+        assert out == str(snap / "mmproj-F16.gguf")
+
     def test_download_includes_uppercase_split_gguf_shards(self, monkeypatch, tmp_path):
         backend = LlamaCppBackend()
         downloaded: list[str] = []
@@ -453,6 +502,10 @@ class TestGgufVariantFileResolution:
             return f"/fake/{repo_id}/{filename}"
 
         monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
+        monkeypatch.setattr(
+            "utils.hf_cache_settings.get_hf_cache_paths",
+            lambda: _types.SimpleNamespace(hub_cache = tmp_path),
+        )
         with (
             patch("huggingface_hub.list_repo_files", lambda *_a, **_k: files),
             patch("huggingface_hub.get_paths_info", fake_get_paths_info),
@@ -1084,7 +1137,7 @@ class TestListLocalGgufVariantsSubdir:
         target.write_bytes(b"\0" * 20)
 
         out = _find_local_gguf_by_variant(str(tmp_path), "Q4_K_M")
-        assert out == str(target.resolve())
+        assert out == str(target.absolute())
 
     def test_find_local_gguf_by_variant_skips_big_endian_only_match(self, tmp_path):
         from utils.models.model_config import _find_local_gguf_by_variant
@@ -1094,6 +1147,57 @@ class TestListLocalGgufVariantsSubdir:
 
         assert _find_local_gguf_by_variant(str(tmp_path), "Q4_K_M") is None
 
+    def test_find_local_gguf_by_variant_keeps_split_symlink_name(self, tmp_path):
+        from utils.models.model_config import _find_local_gguf_by_variant
+
+        blobs = tmp_path / "blobs"
+        blobs.mkdir()
+        snap = tmp_path / "snapshots" / "rev" / "BF16"
+        snap.mkdir(parents = True)
+        (tmp_path / "snapshots" / "rev" / "config.json").write_text("{}")
+        for i, sha in enumerate(("aa" * 32, "bb" * 32), start = 1):
+            (blobs / sha).write_bytes(b"\0" * 10)
+            _symlink_or_skip(snap / f"model-BF16-0000{i}-of-00002.gguf", blobs / sha)
+
+        out = _find_local_gguf_by_variant(str(tmp_path / "snapshots" / "rev"), "BF16")
+        assert out is not None
+        assert Path(out).name == "model-BF16-00001-of-00002.gguf"
+
+    def test_detect_gguf_model_keeps_split_symlink_name(self, tmp_path):
+        from utils.models.model_config import detect_gguf_model
+
+        blobs = tmp_path / "blobs"
+        blobs.mkdir()
+        snap = tmp_path / "snapshots" / "rev"
+        snap.mkdir(parents = True)
+        for i, (sha, size) in enumerate((("cc" * 32, 10), ("dd" * 32, 20)), start = 1):
+            (blobs / sha).write_bytes(b"\0" * size)
+            _symlink_or_skip(snap / f"model-BF16-0000{i}-of-00002.gguf", blobs / sha)
+
+        out = detect_gguf_model(str(snap))
+        assert out is not None
+        assert Path(out).name == "model-BF16-00001-of-00002.gguf"
+
+    def test_lone_split_symlink_uses_colocated_target_shards(self, tmp_path):
+        from utils.models.model_config import _find_local_gguf_by_variant, detect_gguf_model
+
+        target_dir = tmp_path / "external" / "BF16"
+        target_dir.mkdir(parents = True)
+        target = target_dir / "model-BF16-00001-of-00002.gguf"
+        target.write_bytes(b"\0" * 10)
+        (target_dir / "model-BF16-00002-of-00002.gguf").write_bytes(b"\0" * 10)
+
+        local = tmp_path / "local"
+        local.mkdir()
+        (local / "config.json").write_text("{}")
+        link = local / target.name
+        _symlink_or_skip(link, target)
+
+        expected = str(target.absolute())
+        assert _find_local_gguf_by_variant(str(local), "BF16") == expected
+        assert detect_gguf_model(str(local)) == expected
+        assert detect_gguf_model(str(link)) == expected
+
     def test_model_config_variant_ignores_big_endian_sibling(self, tmp_path):
         from utils.models.model_config import ModelConfig
 
diff --git a/studio/backend/tests/test_openai_auto_switch.py b/studio/backend/tests/test_openai_auto_switch.py
index 1ee9ef36d3..9c6c20e6b6 100644
--- a/studio/backend/tests/test_openai_auto_switch.py
+++ b/studio/backend/tests/test_openai_auto_switch.py
@@ -68,7 +68,13 @@ class _LoadRecorder:
         request,
         fastapi_request,
         current_subject = None,
+        *,
+        current_request_counted = False,
     ):
+        # Mirror the production load boundary before recording any replacement.
+        await inference_route._wait_for_model_switch_idle(
+            current_request_counted = current_request_counted
+        )
         self.calls.append(request)
         if self.fail:
             from fastapi import HTTPException
@@ -94,7 +100,6 @@ def _wire(monkeypatch, *, enabled, resolves_to, backend, recorder):
     # gate that auto-switch already owns, so it calls the impl directly).
     monkeypatch.setattr(inference_route, "_load_model_impl", recorder)
     monkeypatch.setattr(inference_route, "_auto_switch_waiters", {})
-    monkeypatch.setattr(inference_route, "_auto_switch_request_waiters", {})
 
 
 def _run_hook(model = "some/model"):
@@ -1091,6 +1096,7 @@ def test_build_index_covers_legacy_default_lmstudio_and_custom_roots(monkeypatch
     from pathlib import Path
     import routes.models as models_route
     from utils import paths as upaths
+    from utils import hf_cache_settings
     import storage.studio_db as studio_db
 
     scanned = []
@@ -1111,13 +1117,18 @@ def test_build_index_covers_legacy_default_lmstudio_and_custom_roots(monkeypatch
     )
     monkeypatch.setattr(models_route, "_resolve_hf_cache_dir", lambda: tmp_path / "active")
     monkeypatch.setattr(models_route, "_is_hidden_model", lambda *a, **k: False)
+    monkeypatch.setattr(
+        hf_cache_settings,
+        "known_hf_hub_caches",
+        lambda: [tmp_path / "active", tmp_path / "previous"],
+    )
     monkeypatch.setattr(upaths, "legacy_hf_cache_dir", lambda: tmp_path / "legacy")
     monkeypatch.setattr(upaths, "hf_default_cache_dir", lambda: tmp_path / "default")
     monkeypatch.setattr(upaths, "lmstudio_model_dirs", lambda: [tmp_path / "lmstudio"])
     monkeypatch.setattr(
         studio_db, "list_scan_folders", lambda: [{"path": str(tmp_path / "custom")}]
     )
-    for sub in ("active", "legacy", "default", "lmstudio", "custom"):
+    for sub in ("active", "previous", "legacy", "default", "lmstudio", "custom"):
         (tmp_path / sub).mkdir()
 
     resolver._build_index()
@@ -1126,6 +1137,7 @@ def test_build_index_covers_legacy_default_lmstudio_and_custom_roots(monkeypatch
     lm = {p for k, p in scanned if k == "lm"}
     assert str((tmp_path / "legacy").resolve()) in hf
     assert str((tmp_path / "default").resolve()) in hf
+    assert str((tmp_path / "previous").resolve()) in hf
     assert str((tmp_path / "custom").resolve()) in hf
     assert str((tmp_path / "lmstudio").resolve()) in lm
 
@@ -1205,10 +1217,9 @@ def test_middleware_ignores_non_post(monkeypatch):
 # ── review round 4: swap guard, idle variant identity, load-by-path, stash clear ──
 
 
-def test_auto_switch_refuses_when_another_inference_is_active(monkeypatch):
-    # A cross-model swap must 409 (not kill) while another inference request is in
-    # flight; the requesting call itself is excluded from the count.
-    from fastapi import HTTPException
+def test_auto_switch_waits_for_another_inference_to_finish(monkeypatch):
+    # A cross-model swap queues while another request is generating, then loads
+    # after that request drains. The requesting call itself is excluded.
     from core.inference import llama_keepwarm as kw
 
     backend = _FakeBackend("org/A-GGUF", hf_variant = "Q4_K_M")
@@ -1222,10 +1233,18 @@ def test_auto_switch_refuses_when_another_inference_is_active(monkeypatch):
     )
     monkeypatch.setattr(kw, "_inflight", 2)  # this request + another active one
     monkeypatch.setattr(kw, "_pending", 0)
-    with pytest.raises(HTTPException) as exc:
-        _run_hook("org/B-GGUF:Q8_0")
-    assert exc.value.status_code == 409
-    assert rec.calls == []
+
+    async def _drive():
+        task = asyncio.create_task(
+            inference_route._maybe_auto_switch_model("org/B-GGUF:Q8_0", object(), "tester")
+        )
+        await asyncio.sleep(0.05)
+        assert rec.calls == []
+        kw._note_end()  # the other generation finishes; this request remains counted
+        await asyncio.wait_for(task, timeout = 1)
+
+    asyncio.run(_drive())
+    assert len(rec.calls) == 1
 
 
 def test_auto_switch_swaps_when_only_caller_is_active(monkeypatch):
@@ -1411,13 +1430,12 @@ def test_concurrent_same_target_requests_load_once(monkeypatch):
     monkeypatch.setattr(kw, "_pending", 0)
     inference_route._note_switch_waiter(inference_route._switch_key("org/B-GGUF", "Q8_0"), 1)
     _run_hook("org/B-GGUF:Q8_0")
-    assert len(rec.calls) == 1  # loads once, no 409
+    assert len(rec.calls) == 1
 
 
-def test_swap_still_refused_when_other_request_targets_different_model(monkeypatch):
-    # A concurrent request heading to a different target still blocks the swap: the
-    # same-target exclusion must not swallow a genuinely conflicting request.
-    from fastapi import HTTPException
+def test_queued_different_target_does_not_deadlock_current_swap(monkeypatch):
+    # A concurrent request already queued for another target is not generating,
+    # so it must not prevent the current serialized swap from proceeding.
     from core.inference import llama_keepwarm as kw
 
     backend = _FakeBackend("org/A-GGUF")
@@ -1432,10 +1450,8 @@ def test_swap_still_refused_when_other_request_targets_different_model(monkeypat
     monkeypatch.setattr(kw, "_inflight", 2)
     monkeypatch.setattr(kw, "_pending", 0)
     inference_route._note_switch_waiter(inference_route._switch_key("org/C-GGUF", "Q4_K_M"), 1)
-    with pytest.raises(HTTPException) as exc:
-        _run_hook("org/B-GGUF:Q8_0")
-    assert exc.value.status_code == 409
-    assert rec.calls == []
+    _run_hook("org/B-GGUF:Q8_0")
+    assert len(rec.calls) == 1
 
 
 def test_v1_models_advertises_repo_id_not_load_path(monkeypatch):
@@ -1481,6 +1497,37 @@ def test_load_route_holds_lifecycle_gate(monkeypatch):
     assert "_load_model_impl" in src
 
 
+def test_model_replacements_recheck_sidecar_swap_before_either_backend_is_unloaded():
+    # Both replacement directions drain active inference, then recheck whether a
+    # sidecar install reserved the lifecycle gate during that wait. Exact-model
+    # reuse exits earlier, so an already-loaded model never waits on unrelated inference.
+    import inspect
+
+    src = inspect.getsource(inference_route._load_model_impl)
+    gguf_wait = src.index("await _wait_for_model_switch_idle", src.index("if config.is_gguf:"))
+    gguf_sidecar_check = src.index("_raise_if_sidecar_swap_in_progress()", gguf_wait)
+    unload_unsloth = src.index("unsloth_backend.unload_model", gguf_wait)
+    standard_wait = src.index("await _wait_for_model_switch_idle", gguf_wait + 1)
+    standard_sidecar_check = src.index("_raise_if_sidecar_swap_in_progress()", standard_wait)
+    unload_gguf = src.index("llama_backend.unload_model()", standard_wait)
+    already_loaded = src.index('status = "already_loaded"')
+
+    assert already_loaded < gguf_wait < gguf_sidecar_check < unload_unsloth
+    assert standard_wait < standard_sidecar_check < unload_gguf
+
+
+def test_switch_waiter_deregisters_before_swap_gate_release():
+    # A waiter left registered after the swap gate is released would let a swap on
+    # another event loop count the finished request as still queued, pass the drain
+    # early, and unload the model that request is about to generate against.
+    import inspect
+
+    src = inspect.getsource(inference_route._maybe_auto_switch_model)
+    deregister = src.index("_note_switch_waiter(key, -1)")
+    release = src.index("_auto_switch_process_lock.release()")
+    assert deregister < release
+
+
 def _anthropic_payload(max_tokens = None):
     from models.inference import AnthropicMessagesRequest, AnthropicMessage
     return AnthropicMessagesRequest(
@@ -1519,9 +1566,9 @@ def test_anthropic_400_when_auto_switch_on_and_max_tokens_missing(monkeypatch):
 # ── review round 6: concurrency ordering, external untrack, unload gate, ids ──
 
 
-def test_pending_same_target_request_does_not_force_409(monkeypatch):
+def test_pending_same_target_request_does_not_block_swap(monkeypatch):
     # A second same-target request blocked in the middleware (pending, not yet
-    # generating) must not make the first request 409: pending is excluded.
+    # generating) must not block the first request: pending is excluded.
     from core.inference import llama_keepwarm as kw
 
     backend = _FakeBackend("org/A-GGUF")
@@ -1536,13 +1583,13 @@ def test_pending_same_target_request_does_not_force_409(monkeypatch):
     monkeypatch.setattr(kw, "_inflight", 1)  # just the caller
     monkeypatch.setattr(kw, "_pending", 1)  # second request blocked in middleware
     _run_hook("org/B-GGUF:Q8_0")
-    assert len(rec.calls) == 1  # loads once, no 409
+    assert len(rec.calls) == 1
 
 
-def test_concurrent_same_target_loads_once_while_other_still_resolving(monkeypatch):
+def test_swap_waits_until_concurrent_request_finishes_resolving(monkeypatch):
     # The real middleware counts a concurrent same-model request as in-flight
-    # before it resolves and registers a target waiter. The raw-request waiter,
-    # registered before resolve, must still exclude it so the first request loads.
+    # before it resolves and registers a target waiter. Treat it as active until
+    # its target is known, then recognize it as another queued switch request.
     from core.inference import llama_keepwarm as kw
 
     backend = _FakeBackend("org/A-GGUF")
@@ -1556,10 +1603,20 @@ def test_concurrent_same_target_loads_once_while_other_still_resolving(monkeypat
     )
     monkeypatch.setattr(kw, "_inflight", 2)  # caller + a still-resolving twin
     monkeypatch.setattr(kw, "_pending", 0)
-    # The twin has only registered its raw requested model (not yet a target waiter).
-    inference_route._note_request_waiter(inference_route._request_waiter_key("org/B-GGUF:Q8_0"), 1)
-    _run_hook("org/B-GGUF:Q8_0")
-    assert len(rec.calls) == 1  # loads once, no 409
+    # The twin is still resolving, so it is counted in-flight but has not joined
+    # the concrete target queue yet.
+
+    async def _drive():
+        task = asyncio.create_task(
+            inference_route._maybe_auto_switch_model("org/B-GGUF:Q8_0", object(), "tester")
+        )
+        await asyncio.sleep(0.05)
+        assert rec.calls == []
+        inference_route._note_switch_waiter(inference_route._switch_key("org/B-GGUF", "Q8_0"), 1)
+        await asyncio.wait_for(task, timeout = 1)
+
+    asyncio.run(_drive())
+    assert len(rec.calls) == 1
 
 
 def test_external_untrack_decrements_inflight_and_is_idempotent():
@@ -1595,11 +1652,9 @@ def test_manual_unload_interrupts_even_while_inference_active(monkeypatch):
     assert not backend.is_loaded  # torn down despite the active request
 
 
-def test_auto_switch_refuses_when_unsloth_stream_active(monkeypatch):
+def test_auto_switch_waits_when_unsloth_stream_active(monkeypatch):
     # The GGUF slot is empty but an Unsloth model is streaming (counted in-flight).
-    # _load_model_impl would unload it, so auto-switch must 409, not only when a
-    # GGUF is loaded.
-    from fastapi import HTTPException
+    # The replacement waits for it just as it does for a GGUF generation.
     from core.inference import llama_keepwarm as kw
 
     backend = _FakeBackend(None)  # no GGUF loaded
@@ -1613,10 +1668,18 @@ def test_auto_switch_refuses_when_unsloth_stream_active(monkeypatch):
     )
     monkeypatch.setattr(kw, "_inflight", 2)  # an Unsloth stream + this request
     monkeypatch.setattr(kw, "_pending", 0)
-    with pytest.raises(HTTPException) as exc:
-        _run_hook("org/B-GGUF:Q8_0")
-    assert exc.value.status_code == 409
-    assert rec.calls == []  # the active Unsloth model is not torn down
+
+    async def _drive():
+        task = asyncio.create_task(
+            inference_route._maybe_auto_switch_model("org/B-GGUF:Q8_0", object(), "tester")
+        )
+        await asyncio.sleep(0.05)
+        assert rec.calls == []
+        kw._note_end()
+        await asyncio.wait_for(task, timeout = 1)
+
+    asyncio.run(_drive())
+    assert len(rec.calls) == 1
 
 
 def test_public_model_id_prefers_advertised_over_path():
@@ -3097,6 +3160,8 @@ def test_auto_switch_serializes_across_event_loops(monkeypatch):
         request,
         fastapi_request,
         current_subject = None,
+        *,
+        current_request_counted = False,
     ):
         with slock:
             state["cur"] += 1
@@ -3114,7 +3179,6 @@ def test_auto_switch_serializes_across_event_loops(monkeypatch):
     monkeypatch.setattr(inference_route, "get_llama_cpp_backend", lambda: backend)
     monkeypatch.setattr(inference_route, "_load_model_impl", _slow_load)
     monkeypatch.setattr(inference_route, "_auto_switch_waiters", {})
-    monkeypatch.setattr(inference_route, "_auto_switch_request_waiters", {})
 
     barrier = threading.Barrier(2)
 
diff --git a/studio/backend/tests/test_password_prompt.py b/studio/backend/tests/test_password_prompt.py
index 372d6a2aa4..1af8836065 100644
--- a/studio/backend/tests/test_password_prompt.py
+++ b/studio/backend/tests/test_password_prompt.py
@@ -183,6 +183,22 @@ def test_loop_short_password_reprompts(monkeypatch):
     assert "at least 8 characters" in out
 
 
+def test_loop_whitespace_only_reprompts(monkeypatch):
+    ok, applied, out = _run_loop(monkeypatch, _keys(" " * 8, "long-enough-pw", "long-enough-pw"))
+    assert ok is True
+    assert applied == ["long-enough-pw"]
+    assert "contain spaces" in out
+
+
+def test_loop_password_with_inner_space_reprompts(monkeypatch):
+    ok, applied, out = _run_loop(
+        monkeypatch, _keys("has space pw", "long-enough-pw", "long-enough-pw")
+    )
+    assert ok is True
+    assert applied == ["long-enough-pw"]
+    assert "contain spaces" in out
+
+
 def test_loop_rejects_current_password(monkeypatch):
     ok, applied, out = _run_loop(
         monkeypatch, _keys("bootstrap-pw", "fresh-password", "fresh-password")
diff --git a/studio/backend/tests/test_picker_service.py b/studio/backend/tests/test_picker_service.py
new file mode 100644
index 0000000000..1bdfc135e3
--- /dev/null
+++ b/studio/backend/tests/test_picker_service.py
@@ -0,0 +1,272 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import json
+from types import SimpleNamespace
+
+from picker.service import (
+    MAX_TEMPLATE_METADATA_BYTES,
+    _chat_template_from_dir,
+    _chat_template_from_processor_json,
+    _chat_template_from_tokenizer_config,
+    _chat_template_from_tokenizer_dir,
+    _find_gguf_in_dir,
+    _iter_ggufs,
+    read_default_chat_template,
+    validate_chat_template,
+)
+
+
+def test_iter_ggufs_skips_gguf_companions(tmp_path):
+    mtp_dir = tmp_path / "MTP"
+    mtp_dir.mkdir()
+    main = tmp_path / "model-Q8_0.gguf"
+    main.write_bytes(b"")
+    (tmp_path / "mmproj-F16.gguf").write_bytes(b"")
+    (tmp_path / "mtp-model-Q8_0.gguf").write_bytes(b"")
+    (mtp_dir / "model-Q8_0-MTP.gguf").write_bytes(b"")
+    (tmp_path / "model-Q8_0-be.gguf").write_bytes(b"")
+
+    assert _iter_ggufs(tmp_path) == [main]
+
+
+def test_find_gguf_in_dir_matches_quant_label(tmp_path):
+    mtp_dir = tmp_path / "MTP"
+    mtp_dir.mkdir()
+    main = tmp_path / "model-Q8_0.gguf"
+    main.write_bytes(b"")
+    (mtp_dir / "model-Q8_0-MTP.gguf").write_bytes(b"")
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+
+    assert _find_gguf_in_dir(tmp_path, "Q8_0") == main
+    assert _find_gguf_in_dir(tmp_path, "Q4_K") is None
+
+
+def test_find_gguf_in_dir_without_variant_prefers_largest_model(tmp_path):
+    smaller = tmp_path / "a-model-Q4_K_M.gguf"
+    larger = tmp_path / "z-model-Q8_0.gguf"
+    smaller.write_bytes(b"0")
+    larger.write_bytes(b"00")
+
+    assert _find_gguf_in_dir(tmp_path, None) == larger
+
+
+def test_find_gguf_in_dir_without_variant_prefers_first_split(tmp_path):
+    first = tmp_path / "model-Q4_K_M-00001-of-00003.gguf"
+    second = tmp_path / "model-Q4_K_M-00002-of-00003.gguf"
+    third = tmp_path / "model-Q4_K_M-00003-of-00003.gguf"
+    first.write_bytes(b"0")
+    second.write_bytes(b"000")
+    third.write_bytes(b"00")
+
+    assert _find_gguf_in_dir(tmp_path, None) == first
+
+    first.unlink()
+    assert _find_gguf_in_dir(tmp_path, None) == second
+
+
+def test_find_gguf_in_dir_matches_bpw_variant_base_label(tmp_path):
+    target = tmp_path / "model-IQ4_XS-3.53bpw.gguf"
+    target.write_bytes(b"")
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+
+    assert _find_gguf_in_dir(tmp_path, "IQ4_XS") == target
+    assert _find_gguf_in_dir(tmp_path, "IQ4_XS-3.53bpw") == target
+    assert _find_gguf_in_dir(tmp_path, "Q4_K") is None
+
+
+def test_validate_chat_template_accepts_valid_and_empty():
+    assert validate_chat_template("{{ messages[0].content }}").valid is True
+    assert validate_chat_template("").valid is True
+    assert validate_chat_template("   ").valid is True
+
+
+def test_validate_chat_template_reports_syntax_error_with_line():
+    result = validate_chat_template("{% if %}{% endif %}")
+    assert result.valid is False
+    assert result.error is not None
+    assert result.error.startswith("Line ")
+
+
+def test_chat_template_from_tokenizer_config_reads_string():
+    assert _chat_template_from_tokenizer_config({"chat_template": "HELLO"}) == "HELLO"
+    assert _chat_template_from_tokenizer_config({"chat_template": "   "}) is None
+    assert _chat_template_from_tokenizer_config({}) is None
+
+
+def test_chat_template_from_tokenizer_config_prefers_named_default():
+    config = {
+        "chat_template": [
+            {"name": "tool_use", "template": "TOOL"},
+            {"name": "default", "template": "DEFAULT"},
+        ]
+    }
+    assert _chat_template_from_tokenizer_config(config) == "DEFAULT"
+
+
+def test_chat_template_from_tokenizer_config_falls_back_to_first_entry():
+    config = {
+        "chat_template": [
+            {"name": "tool_use", "template": "TOOL"},
+            {"name": "other", "template": "OTHER"},
+        ]
+    }
+    assert _chat_template_from_tokenizer_config(config) == "TOOL"
+
+
+def test_chat_template_from_tokenizer_dir_prefers_jinja_file(tmp_path):
+    (tmp_path / "chat_template.jinja").write_text("FROM_JINJA", encoding = "utf-8")
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_JINJA"
+
+
+def test_chat_template_from_tokenizer_dir_reads_tokenizer_config(tmp_path):
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_CONFIG"
+
+
+def test_chat_template_from_dir_without_variant_prefers_tokenizer(tmp_path):
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_dir(tmp_path) == "FROM_CONFIG"
+
+
+def test_chat_template_from_dir_with_variant_still_prefers_tokenizer(tmp_path, monkeypatch):
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # Selecting a variant must not flip precedence to the embedded GGUF template.
+    assert _chat_template_from_dir(tmp_path, "Q4_K_M") == "FROM_CONFIG"
+
+
+def test_chat_template_from_dir_with_variant_falls_back_to_gguf(tmp_path, monkeypatch):
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # With no tokenizer sidecar, the embedded GGUF template is still the fallback.
+    assert _chat_template_from_dir(tmp_path, "Q4_K_M") == "FROM_GGUF"
+
+
+def test_chat_template_from_dir_returns_none_when_absent(tmp_path):
+    assert _chat_template_from_dir(tmp_path) is None
+
+
+def test_read_default_chat_template_direct_gguf_prefers_sidecar(tmp_path, monkeypatch):
+    gguf = tmp_path / "model-Q4_K_M.gguf"
+    gguf.write_bytes(b"")
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    monkeypatch.setattr("picker.service._build_browse_allowlist", lambda: [tmp_path])
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # A directly selected .gguf must prefer a maintained sidecar over its embedded copy.
+    assert read_default_chat_template(str(gguf)) == "FROM_CONFIG"
+
+
+def test_read_default_chat_template_direct_gguf_falls_back_to_embedded(tmp_path, monkeypatch):
+    gguf = tmp_path / "model-Q4_K_M.gguf"
+    gguf.write_bytes(b"")
+    monkeypatch.setattr("picker.service._build_browse_allowlist", lambda: [tmp_path])
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # With no sidecar next to the file, the embedded GGUF template is the fallback.
+    assert read_default_chat_template(str(gguf)) == "FROM_GGUF"
+
+
+def test_tokenizer_config_over_size_limit_is_skipped_not_parsed(tmp_path):
+    # An oversized tokenizer_config.json must be skipped before json.loads so a
+    # hostile sidecar cannot exhaust memory.
+    padding = "x" * (MAX_TEMPLATE_METADATA_BYTES + 1024)
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "HELLO", "_pad": padding}), encoding = "utf-8"
+    )
+    assert _chat_template_from_tokenizer_dir(tmp_path) is None
+
+
+def test_processor_json_over_size_limit_is_skipped_not_parsed(tmp_path):
+    padding = "x" * (MAX_TEMPLATE_METADATA_BYTES + 1024)
+    (tmp_path / "chat_template.json").write_text(
+        json.dumps({"default": "HELLO", "_pad": padding}), encoding = "utf-8"
+    )
+    assert _chat_template_from_processor_json(tmp_path) is None
+
+
+def test_tokenizer_config_at_size_limit_is_still_read(tmp_path):
+    # A normal-sized config is unaffected by the bound (regression guard).
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_CONFIG"
+
+
+def test_remote_template_over_size_limit_is_skipped_before_download(monkeypatch):
+    # An uncached Hub repo whose template exceeds the cap must be skipped via the
+    # remote size pre-check, never downloaded.
+    import huggingface_hub
+
+    monkeypatch.setattr("picker.service.resolve_cached_repo_id_case", lambda name: name)
+    monkeypatch.setattr("picker.service.iter_hf_cache_snapshots", lambda resolved: [])
+
+    def _fail_download(*args, **kwargs):
+        raise AssertionError("oversized remote template must not be downloaded")
+
+    def _fake_get_paths_info(self, repo_id, paths, **kwargs):
+        return [SimpleNamespace(path = p, size = MAX_TEMPLATE_METADATA_BYTES + 1) for p in paths]
+
+    monkeypatch.setattr(huggingface_hub, "hf_hub_download", _fail_download)
+    monkeypatch.setattr(huggingface_hub.HfApi, "get_paths_info", _fake_get_paths_info)
+
+    assert read_default_chat_template("org/oversized-model") is None
+
+
+def test_remote_oversized_jinja_falls_through_to_tokenizer_template(tmp_path, monkeypatch):
+    # A raw chat_template.jinja between the response cap (MAX_CHAT_TEMPLATE_BYTES)
+    # and the download bound (MAX_TEMPLATE_METADATA_BYTES) must not be returned: the
+    # route drops it, so the remote path must skip the oversized Jinja and fall
+    # through to the smaller tokenizer_config.json.
+    import huggingface_hub
+    from picker.schemas import MAX_CHAT_TEMPLATE_BYTES
+
+    big_jinja = tmp_path / "chat_template.jinja"
+    big_jinja.write_text("{{ x }}" * (MAX_CHAT_TEMPLATE_BYTES // 4), encoding = "utf-8")
+    assert MAX_CHAT_TEMPLATE_BYTES < big_jinja.stat().st_size < MAX_TEMPLATE_METADATA_BYTES
+    tokenizer_config = tmp_path / "tokenizer_config.json"
+    tokenizer_config.write_text(json.dumps({"chat_template": "SMALL_TEMPLATE"}), encoding = "utf-8")
+    files = {
+        "chat_template.jinja": big_jinja,
+        "tokenizer_config.json": tokenizer_config,
+    }
+    selected_cache = tmp_path / "selected-cache" / "hub"
+    observed_cache_dirs = []
+
+    monkeypatch.setattr("picker.service.resolve_cached_repo_id_case", lambda name: name)
+    monkeypatch.setattr("picker.service.iter_hf_cache_snapshots", lambda resolved: [])
+    monkeypatch.setattr("picker.service.active_hf_hub_cache", lambda: str(selected_cache))
+
+    def _fake_download(repo_id, rel, **kwargs):
+        observed_cache_dirs.append(kwargs.get("cache_dir"))
+        target = files.get(rel)
+        if target is None:
+            raise FileNotFoundError(rel)
+        return str(target)
+
+    def _fake_get_paths_info(self, repo_id, paths, **kwargs):
+        return [
+            SimpleNamespace(
+                path = p,
+                size = files[p].stat().st_size if p in files else 0,
+            )
+            for p in paths
+        ]
+
+    monkeypatch.setattr(huggingface_hub, "hf_hub_download", _fake_download)
+    monkeypatch.setattr(huggingface_hub.HfApi, "get_paths_info", _fake_get_paths_info)
+
+    assert read_default_chat_template("org/big-jinja-model") == "SMALL_TEMPLATE"
+    assert observed_cache_dirs
+    assert set(observed_cache_dirs) == {str(selected_cache)}
diff --git a/studio/backend/tests/test_rag_embeddings.py b/studio/backend/tests/test_rag_embeddings.py
index 28a2f69426..197ae4c495 100644
--- a/studio/backend/tests/test_rag_embeddings.py
+++ b/studio/backend/tests/test_rag_embeddings.py
@@ -5,8 +5,10 @@
 and token counting must be serialized (else threads panic "Already borrowed")."""
 
 import os
+import sys
 import threading
 import time
+from types import SimpleNamespace
 
 import numpy as np
 import pytest
@@ -130,6 +132,35 @@ def test_token_counter_enables_parallelism_only_during_call(monkeypatch):
     assert os.environ.get("TOKENIZERS_PARALLELISM") == "false"  # restored after
 
 
+def test_sentence_transformer_load_uses_live_cache(monkeypatch, tmp_path):
+    observed = {}
+
+    class FakeSentenceTransformer:
+        def __init__(self, name, **kwargs):
+            observed["name"] = name
+            observed.update(kwargs)
+
+    monkeypatch.setitem(
+        sys.modules,
+        "sentence_transformers",
+        SimpleNamespace(SentenceTransformer = FakeSentenceTransformer),
+    )
+    monkeypatch.setattr(embeddings, "_install_torchao_stub_once", lambda: None)
+    monkeypatch.setattr(embeddings, "_guard_model_security", lambda *_a, **_k: None)
+    monkeypatch.setattr(embeddings, "_device", lambda: "cpu")
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.active_hf_hub_cache",
+        lambda: str(tmp_path / "selected-hub"),
+    )
+    embeddings._model = None
+    embeddings._name = None
+
+    embeddings._get("Org/Embedder")
+
+    assert observed["name"] == "Org/Embedder"
+    assert observed["cache_folder"] == str(tmp_path / "selected-hub")
+
+
 class _SentinelLlamaBackend:
     """Stand-in for LlamaServerBackend; never spawns a real server."""
 
diff --git a/studio/backend/tests/test_resolve_quant_gguf.py b/studio/backend/tests/test_resolve_quant_gguf.py
index 840c4d8d4c..a137237e80 100644
--- a/studio/backend/tests/test_resolve_quant_gguf.py
+++ b/studio/backend/tests/test_resolve_quant_gguf.py
@@ -68,8 +68,6 @@ def test_skips_mtp_drafter_for_main_weights(tmp_path):
 
 
 def test_prefers_the_complete_snapshot(tmp_path, monkeypatch):
-    from huggingface_hub import constants as hf_constants
-
     cache = tmp_path / "hub"
     snaps = cache / "models--org--repo" / "snapshots"
     # Partial older snapshot: one small shard.
@@ -78,7 +76,10 @@ def test_prefers_the_complete_snapshot(tmp_path, monkeypatch):
     complete_first = _write(snaps / "bbbb" / "model-00001-of-00002-Q4_K_M.gguf", 30)
     _write(snaps / "bbbb" / "model-00002-of-00002-Q4_K_M.gguf", 40)
 
-    monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(cache))
+    monkeypatch.setattr(
+        "utils.hf_cache_settings.known_hf_hub_caches",
+        lambda: [cache],
+    )
 
     path, total = models_route._resolve_quant_gguf("org/repo", "Q4_K_M", is_local = False)
 
diff --git a/studio/backend/tests/test_rocm_multi_gpu_vram_system_wide.py b/studio/backend/tests/test_rocm_multi_gpu_vram_system_wide.py
new file mode 100644
index 0000000000..bdafdeae9b
--- /dev/null
+++ b/studio/backend/tests/test_rocm_multi_gpu_vram_system_wide.py
@@ -0,0 +1,554 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""The System tab's multi-GPU view must show system-wide VRAM on ROCm (#7072).
+
+When amd-smi is unavailable, get_visible_gpu_utilization fell back to torch,
+whose readings are process-local: a model held by the separate llama-server
+process read as ~0 VRAM used even with the GPU full. These tests cover the
+per-GPU system-wide overlay the multi-device endpoint now applies, matched by
+physical device identity.
+"""
+
+from __future__ import annotations
+
+import importlib
+import sys
+import types
+from pathlib import Path
+
+_BACKEND_DIR = Path(__file__).resolve().parent.parent
+if str(_BACKEND_DIR) not in sys.path:
+    sys.path.insert(0, str(_BACKEND_DIR))
+
+
+def _maybe_stub(name: str, builder):
+    # Stub only if the real module is missing, so we never shadow it for later tests.
+    try:
+        importlib.import_module(name)
+    except ImportError:
+        sys.modules[name] = builder()
+
+
+def _build_loggers_stub():
+    m = types.ModuleType("loggers")
+    m.get_logger = lambda name: __import__("logging").getLogger(name)
+    return m
+
+
+def _build_structlog_stub():
+    m = types.ModuleType("structlog")
+    m.get_logger = lambda *a, **k: __import__("logging").getLogger("stub")
+    return m
+
+
+_maybe_stub("loggers", _build_loggers_stub)
+_maybe_stub("structlog", _build_structlog_stub)
+
+import utils.hardware.hardware as hw  # noqa: E402
+
+
+def _device(
+    index,
+    used,
+    total,
+    *,
+    ordinal = None,
+):
+    return {
+        "index": index,
+        "index_kind": "physical",
+        "visible_ordinal": index if ordinal is None else ordinal,
+        "gpu_utilization_pct": None,
+        "temperature_c": None,
+        "vram_used_gb": used,
+        "vram_total_gb": total,
+        "vram_utilization_pct": round((used / total) * 100, 1) if total > 0 else None,
+        "power_draw_w": None,
+        "power_limit_w": None,
+        "power_utilization_pct": None,
+    }
+
+
+# ── Linux per-card sysfs ──
+
+
+def _fake_drm(tmp_path, monkeypatch, cards):
+    """Fake /sys/class/drm tree; glob returns cards REVERSED so the PCI sort must order them.
+
+    ``cards``: (card_no, pci_bdf, driver, vram) tuples; vram is (used_gb, total_gb)
+    or None for a device with no mem_info_vram_* files.
+    """
+    drivers = tmp_path / "drivers"
+    card_paths = []
+    for card_no, bdf, driver, vram in cards:
+        pci_dir = tmp_path / "pci" / bdf
+        pci_dir.mkdir(parents = True, exist_ok = True)
+        drv_dir = drivers / driver
+        drv_dir.mkdir(parents = True, exist_ok = True)
+        (pci_dir / "driver").symlink_to(drv_dir)
+        if vram is not None:
+            used, total = vram
+            (pci_dir / "mem_info_vram_used").write_text(str(int(used * 1024**3)))
+            (pci_dir / "mem_info_vram_total").write_text(str(int(total * 1024**3)))
+        card_dir = tmp_path / "drm" / f"card{card_no}"
+        card_dir.mkdir(parents = True, exist_ok = True)
+        (card_dir / "device").symlink_to(pci_dir)
+        card_paths.append(str(card_dir))
+    monkeypatch.setattr(hw.glob, "glob", lambda pattern: list(reversed(card_paths)))
+    return card_paths
+
+
+def test_linux_vram_keyed_by_pci_excludes_foreign_adapters(monkeypatch, tmp_path):
+    # Foreign (non-amdgpu) adapters contribute no entry, so they cannot shift ordinals.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_drm(
+        tmp_path,
+        monkeypatch,
+        [
+            (0, "0000:00:02.0", "i915", (0.5, 2.0)),  # foreign adapter: excluded
+            (1, "0000:03:00.0", "amdgpu", (40, 48)),  # AMD device 0
+            (2, "0000:41:00.0", "amdgpu", (1, 8)),  # AMD device 1
+        ],
+    )
+    assert hw._rocm_linux_sysfs_vram_by_pci_gb() == {
+        "0000:03:00.0": (40.0, 48.0),
+        "0000:41:00.0": (1.0, 8.0),
+    }
+
+
+def test_linux_vram_omits_bad_cards_without_shifting(monkeypatch, tmp_path):
+    # A zero-total card has no entry; identity keying means its absence renumbers nothing.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_drm(
+        tmp_path,
+        monkeypatch,
+        [
+            (0, "0000:03:00.0", "amdgpu", (0, 0)),  # zero total -> no entry
+            (1, "0000:41:00.0", "amdgpu", (2, 16)),
+        ],
+    )
+    assert hw._rocm_linux_sysfs_vram_by_pci_gb() == {"0000:41:00.0": (2.0, 16.0)}
+
+
+def test_linux_vram_omits_amd_card_without_vram_files(monkeypatch, tmp_path):
+    # An APU with no mem_info_vram_* files has no entry; the discrete card keeps its address.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_drm(
+        tmp_path,
+        monkeypatch,
+        [
+            (0, "0000:03:00.0", "amdgpu", None),  # APU: no VRAM sysfs files
+            (1, "0000:41:00.0", "amdgpu", (2, 16)),
+        ],
+    )
+    assert hw._rocm_linux_sysfs_vram_by_pci_gb() == {"0000:41:00.0": (2.0, 16.0)}
+
+
+# ── KFD topology: the authoritative ROCm device order ──
+
+
+_AMD = 4098  # 0x1002
+_NVIDIA = 4318  # 0x10DE -- the open kernel module also registers KFD nodes
+
+
+def _fake_kfd(tmp_path, monkeypatch, nodes):
+    """Fake KFD topology nodes tree, returned out of node order so the sort must order it.
+
+    ``nodes``: (node_id, simd_count, location_id, domain, vendor_id); simd_count 0
+    marks a CPU node, location_id None omits the property.
+    """
+    node_paths = []
+    for node_id, simd_count, location_id, domain, vendor_id in nodes:
+        d = tmp_path / "kfd" / str(node_id)
+        d.mkdir(parents = True, exist_ok = True)
+        lines = [f"cpu_cores_count {0 if simd_count else 8}", f"simd_count {simd_count}"]
+        if location_id is not None:
+            lines.append(f"location_id {location_id}")
+        lines.append(f"domain {domain}")
+        if vendor_id is not None:
+            lines.append(f"vendor_id {vendor_id}")
+        (d / "properties").write_text("\n".join(lines) + "\n")
+        node_paths.append(str(d))
+    monkeypatch.setattr(hw.glob, "glob", lambda pattern: list(reversed(node_paths)))
+    return node_paths
+
+
+def test_kfd_lists_gpu_nodes_in_device_order(monkeypatch, tmp_path):
+    # The CPU node (simd_count 0) takes no ordinal; GPU nodes in node-id order are HIP's order.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_kfd(
+        tmp_path,
+        monkeypatch,
+        [
+            (0, 0, None, 0, None),  # CPU node
+            (1, 304, (0x03 << 8) | (0x00 << 3) | 0, 0, _AMD),  # 0000:03:00.0 -> dev 0
+            (2, 304, (0x41 << 8) | (0x00 << 3) | 0, 0, _AMD),  # 0000:41:00.0 -> dev 1
+        ],
+    )
+    assert hw._rocm_kfd_gpu_pci_ids() == ["0000:03:00.0", "0000:41:00.0"]
+
+
+def test_kfd_decodes_domain_device_and_function(monkeypatch, tmp_path):
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_kfd(tmp_path, monkeypatch, [(1, 64, (0xC1 << 8) | (0x1F << 3) | 5, 0x1234, _AMD)])
+    assert hw._rocm_kfd_gpu_pci_ids() == ["1234:c1:1f.5"]
+
+
+def test_kfd_skips_non_amd_gpu_nodes(monkeypatch, tmp_path):
+    # An NVIDIA KFD node is not a HIP device: it must take no ordinal, else it
+    # shifts every AMD GPU and ROCm device 1 resolves to AMD GPU 0.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_kfd(
+        tmp_path,
+        monkeypatch,
+        [
+            (0, 0, None, 0, None),  # CPU
+            (1, 128, (0x01 << 8) | 0, 0, _NVIDIA),  # NVIDIA: no ordinal
+            (2, 304, (0x03 << 8) | 0, 0, _AMD),  # AMD device 0
+            (3, 304, (0x41 << 8) | 0, 0, _AMD),  # AMD device 1
+        ],
+    )
+    assert hw._rocm_kfd_gpu_pci_ids() == ["0000:03:00.0", "0000:41:00.0"]
+
+
+def test_kfd_fails_closed_when_a_gpu_has_no_location(monkeypatch, tmp_path):
+    # Dropping an unplaceable AMD GPU shifts later ordinals; fail closed for the whole map.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _fake_kfd(
+        tmp_path,
+        monkeypatch,
+        [
+            (1, 304, None, 0, _AMD),  # AMD GPU with no location_id
+            (2, 304, (0x41 << 8) | 0, 0, _AMD),
+        ],
+    )
+    assert hw._rocm_kfd_gpu_pci_ids() == []
+
+
+def test_kfd_fails_closed_when_a_node_is_unreadable(monkeypatch, tmp_path):
+    # An unreadable node could be a GPU; assuming otherwise would shift ordinals.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    paths = _fake_kfd(
+        tmp_path,
+        monkeypatch,
+        [
+            (1, 304, (0x03 << 8) | 0, 0, _AMD),
+            (2, 304, (0x41 << 8) | 0, 0, _AMD),
+        ],
+    )
+    (Path(paths[0]) / "properties").unlink()
+    assert hw._rocm_kfd_gpu_pci_ids() == []
+
+
+def test_kfd_absent_yields_no_device_order(monkeypatch):
+    monkeypatch.setattr(hw.glob, "glob", lambda pattern: [])
+    assert hw._rocm_kfd_gpu_pci_ids() == []
+
+
+# ── overlay ──
+
+
+def _patch_pci_map(monkeypatch, bdfs):
+    """Declare the ROCm device order by PCI address (index N is device N) and clear
+    the visibility masks the overlay requires unset.
+    """
+    for var in (
+        "HIP_VISIBLE_DEVICES",
+        "ROCR_VISIBLE_DEVICES",
+        "CUDA_VISIBLE_DEVICES",
+        "GPU_DEVICE_ORDINAL",
+    ):
+        monkeypatch.delenv(var, raising = False)
+    monkeypatch.setattr(hw, "_rocm_kfd_gpu_pci_ids", lambda: list(bdfs))
+
+
+def _pci(n):
+    """A distinct, well-formed PCI address for card n."""
+    return f"0000:{n:02x}:00.0"
+
+
+def test_overlay_windows_is_noop_keeps_torch(monkeypatch):
+    # Windows is intentionally not overlaid (perf counters can't map to ROCm ordinals): keep torch.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Windows")
+    monkeypatch.setattr(
+        hw,
+        "_rocm_linux_sysfs_vram_by_pci_gb",
+        lambda: (_ for _ in ()).throw(AssertionError("sysfs must not run on Windows")),
+    )
+    devices = [_device(0, used = 0.02, total = 8.0)]
+    _patch_pci_map(monkeypatch, [_pci(0)])
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02  # untouched
+
+
+def test_overlay_linux_matches_by_device_ordinal(monkeypatch):
+    # Devices arriving as [index 1, index 0] each get their own GPU's figures by ordinal.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(
+        hw,
+        "_rocm_linux_sysfs_vram_by_pci_gb",
+        lambda: {_pci(0): (30.0, 45.0), _pci(1): (0.5, 8.0)},  # dev 0 big, dev 1 small
+    )
+    devices = [_device(1, used = 0.01, total = 8.0), _device(0, used = 0.02, total = 45.0)]
+    _patch_pci_map(monkeypatch, [_pci(0), _pci(1)])
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.5  # index 1 -> device 1 (small)
+    assert devices[0]["vram_total_gb"] == 8.0
+    assert devices[1]["vram_used_gb"] == 30.0  # index 0 -> device 0 (big)
+    assert devices[1]["vram_total_gb"] == 45.0
+
+
+def test_overlay_linux_ordinal_hole_does_not_shift(monkeypatch):
+    # Device 0's card dropped: index 0 keeps torch, index 1 still maps to ordinal 1 (no compaction).
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(hw, "_rocm_linux_sysfs_vram_by_pci_gb", lambda: {_pci(1): (0.5, 8.0)})
+    devices = [_device(0, used = 0.02, total = 45.0), _device(1, used = 0.01, total = 8.0)]
+    _patch_pci_map(monkeypatch, [_pci(0), _pci(1)])
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02  # no ordinal 0 -> torch kept
+    assert devices[1]["vram_used_gb"] == 0.5  # ordinal 1 -> device 1, not device 0
+
+
+def test_overlay_linux_skips_unified_memory_card(monkeypatch):
+    # Unified-memory APU: the smaller sysfs total must not shrink torch's GTT-backed pool.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(hw, "_rocm_linux_sysfs_vram_by_pci_gb", lambda: {_pci(0): (0.4, 1.0)})
+    devices = [_device(0, used = 12.0, total = 96.0)]  # torch's unified pool
+    _patch_pci_map(monkeypatch, [_pci(0)])
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 12.0
+    assert devices[0]["vram_total_gb"] == 96.0
+
+
+def test_overlay_linux_skips_partitioned_device(monkeypatch):
+    # Partitioned MI300: the whole-card sysfs total dwarfs the partition, so the overlay must not overwrite it.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(hw, "_rocm_linux_sysfs_vram_by_pci_gb", lambda: {_pci(0): (40.0, 192.0)})
+    devices = [_device(0, used = 1.0, total = 24.0)]  # torch partition
+    _patch_pci_map(monkeypatch, [_pci(0)])
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 1.0  # partition figures kept
+    assert devices[0]["vram_total_gb"] == 24.0
+
+
+def test_overlay_linux_out_of_range_index_untouched(monkeypatch):
+    # A masked host exposing physical index 5 with no card 5: keep torch data.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(
+        hw, "_rocm_linux_sysfs_vram_by_pci_gb", lambda: {_pci(0): (30.0, 45.0), _pci(1): (0.5, 8.0)}
+    )
+    devices = [_device(5, used = 0.02, total = 45.0)]
+    _patch_pci_map(monkeypatch, [_pci(0), _pci(1)])
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02
+
+
+def test_overlay_ignores_adapters_rocm_cannot_enumerate(monkeypatch):
+    # A HIP-unenumerable amdgpu adapter has no KFD node, so device 0 resolves to
+    # the supported GPU's own address, never the display card's.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(
+        hw,
+        "_rocm_linux_sysfs_vram_by_pci_gb",
+        # Both in DRM sysfs with similar capacity -- what the total-size guard can't separate.
+        lambda: {_pci(9): (30.0, 45.0), _pci(3): (12.0, 45.0)},
+    )
+    _patch_pci_map(monkeypatch, [_pci(3)])  # KFD lists only the supported GPU
+    devices = [_device(0, used = 0.02, total = 45.0)]  # torch sees that one GPU
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 12.0  # the supported GPU's own figures
+
+
+def test_overlay_skips_masked_subsets(monkeypatch):
+    # Under a mask the index is not verifiably a host ordinal, so keep torch's figures.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _patch_pci_map(monkeypatch, [_pci(0), _pci(1), _pci(2), _pci(3)])
+    monkeypatch.setenv("HIP_VISIBLE_DEVICES", "1,3")
+    monkeypatch.setattr(
+        hw,
+        "_rocm_linux_sysfs_vram_by_pci_gb",
+        lambda: {_pci(1): (30.0, 48.0), _pci(3): (12.0, 48.0)},
+    )
+    devices = [_device(1, used = 0.02, total = 48.0), _device(3, used = 0.01, total = 48.0)]
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02  # torch kept
+    assert devices[1]["vram_used_gb"] == 0.01
+
+
+def test_overlay_skips_device_cgroup_filtered_container(monkeypatch):
+    # A device-cgroup container sets no env var yet compacts torch's indices from
+    # zero while KFD/DRM list every GPU, so the count mismatch must disable the overlay.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _patch_pci_map(monkeypatch, [_pci(0), _pci(1), _pci(2), _pci(3)])  # host has 4
+    monkeypatch.setattr(
+        hw,
+        "_rocm_linux_sysfs_vram_by_pci_gb",
+        lambda: {_pci(0): (30.0, 48.0), _pci(2): (12.0, 48.0)},
+    )
+    devices = [_device(0, used = 0.02, total = 48.0)]  # container sees 1, as index 0
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02  # torch kept, not host GPU 0's 30.0
+
+
+def test_overlay_skips_without_kfd_topology(monkeypatch):
+    # No KFD means no identity to join on; fall back to torch rather than guess.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(hw, "_rocm_kfd_gpu_pci_ids", lambda: [])
+    monkeypatch.setattr(
+        hw,
+        "_rocm_linux_sysfs_vram_by_pci_gb",
+        lambda: (_ for _ in ()).throw(AssertionError("must not read sysfs without KFD")),
+    )
+    devices = [_device(0, used = 0.02, total = 45.0)]
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02
+
+
+def test_overlay_empty_devices_is_noop(monkeypatch):
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    hw._overlay_system_wide_vram([])  # must not raise
+
+
+# ── integration: the ROCm torch fallback applies the overlay ──
+
+
+def test_visible_utilization_rocm_fallback_overlays(monkeypatch):
+    for _var in (
+        "HIP_VISIBLE_DEVICES",
+        "ROCR_VISIBLE_DEVICES",
+        "CUDA_VISIBLE_DEVICES",
+        "GPU_DEVICE_ORDINAL",
+    ):
+        monkeypatch.delenv(_var, raising = False)
+    monkeypatch.setattr(hw, "IS_ROCM", True)
+    monkeypatch.setattr(hw, "get_device", lambda: hw.DeviceType.CUDA)
+    monkeypatch.setattr(hw, "_smi_query", lambda *a, **k: None)  # amd-smi unavailable
+    monkeypatch.setattr(
+        hw,
+        "_get_parent_visible_gpu_spec",
+        lambda: {"raw": None, "numeric_ids": [0, 1], "supports_explicit_gpu_ids": True},
+    )
+    monkeypatch.setattr(hw, "get_parent_visible_gpu_ids", lambda: [0, 1])
+    monkeypatch.setattr(
+        hw,
+        "_torch_get_per_device_info",
+        lambda ids: [
+            {"index": 0, "visible_ordinal": 0, "used_gb": 0.02, "total_gb": 45.0},
+            {"index": 1, "visible_ordinal": 1, "used_gb": 0.01, "total_gb": 8.0},
+        ],
+    )
+    overlaid = []
+    monkeypatch.setattr(
+        hw, "_overlay_system_wide_vram", lambda devices: overlaid.append(len(devices))
+    )
+    result = hw.get_visible_gpu_utilization()
+    assert result["available"] is True
+    assert overlaid == [2]
+
+
+def test_visible_utilization_relative_index_skips_overlay(monkeypatch):
+    # UUID/MIG mask gives relative indices; the overlay matches physical index, so it must not run.
+    monkeypatch.setattr(hw, "IS_ROCM", True)
+    monkeypatch.setattr(hw, "get_device", lambda: hw.DeviceType.CUDA)
+    monkeypatch.setattr(hw, "_smi_query", lambda *a, **k: None)
+    monkeypatch.setattr(
+        hw,
+        "_get_parent_visible_gpu_spec",
+        lambda: {"raw": "GPU-uuid-a", "numeric_ids": None, "supports_explicit_gpu_ids": False},
+    )
+    monkeypatch.setattr(hw, "get_parent_visible_gpu_ids", lambda: [])  # UUID mask
+    monkeypatch.setattr(hw, "_torch_get_physical_gpu_count", lambda: 1)
+    monkeypatch.setattr(
+        hw,
+        "_torch_get_per_device_info",
+        lambda ids: [{"index": 0, "visible_ordinal": 0, "used_gb": 0.02, "total_gb": 8.0}],
+    )
+    called = []
+    monkeypatch.setattr(hw, "_overlay_system_wide_vram", lambda devices: called.append(1))
+    result = hw.get_visible_gpu_utilization()
+    assert result["index_kind"] == "relative"
+    assert called == []
+
+
+def test_visible_utilization_nvidia_fallback_skips_overlay(monkeypatch):
+    monkeypatch.setattr(hw, "IS_ROCM", False)
+    monkeypatch.setattr(hw, "get_device", lambda: hw.DeviceType.CUDA)
+    monkeypatch.setattr(hw, "_smi_query", lambda *a, **k: None)
+    monkeypatch.setattr(
+        hw,
+        "_get_parent_visible_gpu_spec",
+        lambda: {"raw": None, "numeric_ids": [0], "supports_explicit_gpu_ids": True},
+    )
+    monkeypatch.setattr(hw, "get_parent_visible_gpu_ids", lambda: [0])
+    monkeypatch.setattr(
+        hw,
+        "_torch_get_per_device_info",
+        lambda ids: [{"index": 0, "visible_ordinal": 0, "used_gb": 1.0, "total_gb": 24.0}],
+    )
+    called = []
+    monkeypatch.setattr(hw, "_overlay_system_wide_vram", lambda devices: called.append(1))
+    result = hw.get_visible_gpu_utilization()
+    assert result["available"] is True
+    assert called == []
+
+
+def test_any_visibility_mask_is_detected(monkeypatch):
+    # Any of these makes the index not a host-physical ordinal, so each must disable the overlay.
+    for var in (
+        "HIP_VISIBLE_DEVICES",
+        "ROCR_VISIBLE_DEVICES",
+        "CUDA_VISIBLE_DEVICES",
+        "GPU_DEVICE_ORDINAL",
+    ):
+        monkeypatch.delenv(var, raising = False)
+    assert hw._rocm_visibility_mask_active() is False
+    for var in (
+        "HIP_VISIBLE_DEVICES",
+        "ROCR_VISIBLE_DEVICES",
+        "CUDA_VISIBLE_DEVICES",
+        "GPU_DEVICE_ORDINAL",
+    ):
+        monkeypatch.setenv(var, "1")
+        assert hw._rocm_visibility_mask_active() is True, var
+        monkeypatch.setenv(var, "  ")  # empty is not an active filter
+        assert hw._rocm_visibility_mask_active() is False, var
+        monkeypatch.delenv(var, raising = False)
+
+
+def test_overlay_skips_under_gpu_device_ordinal(monkeypatch):
+    # GPU_DEVICE_ORDINAL=1 surfaces GPU 1 as torch ordinal 0, so index 0 is not GPU 0; overlay must not run.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    _patch_pci_map(monkeypatch, [_pci(0)])
+    monkeypatch.setenv("GPU_DEVICE_ORDINAL", "1")
+    monkeypatch.setattr(hw, "_rocm_linux_sysfs_vram_by_pci_gb", lambda: {_pci(0): (30.0, 45.0)})
+    devices = [_device(0, used = 0.02, total = 45.0)]
+    hw._overlay_system_wide_vram(devices)
+    assert devices[0]["vram_used_gb"] == 0.02
+
+
+def test_visible_utilization_delegates_gating_to_the_overlay(monkeypatch):
+    # The call site no longer pre-checks masks; the overlay gates itself, so a physical payload always reaches it.
+    monkeypatch.setenv("ROCR_VISIBLE_DEVICES", "2,3")
+    monkeypatch.setenv("HIP_VISIBLE_DEVICES", "1")
+    monkeypatch.setattr(hw, "IS_ROCM", True)
+    monkeypatch.setattr(hw, "get_device", lambda: hw.DeviceType.CUDA)
+    monkeypatch.setattr(hw, "_smi_query", lambda *a, **k: None)
+    monkeypatch.setattr(
+        hw,
+        "_get_parent_visible_gpu_spec",
+        lambda: {"raw": "1", "numeric_ids": [1], "supports_explicit_gpu_ids": True},
+    )
+    monkeypatch.setattr(hw, "get_parent_visible_gpu_ids", lambda: [1])
+    monkeypatch.setattr(
+        hw,
+        "_torch_get_per_device_info",
+        lambda ids: [{"index": 1, "visible_ordinal": 0, "used_gb": 0.02, "total_gb": 8.0}],
+    )
+    # Real overlay + gating: the layered mask must leave torch's figures.
+    monkeypatch.setattr(hw.platform, "system", lambda: "Linux")
+    monkeypatch.setattr(hw, "_rocm_kfd_gpu_pci_ids", lambda: [_pci(0), _pci(1)])
+    monkeypatch.setattr(hw, "_rocm_linux_sysfs_vram_by_pci_gb", lambda: {_pci(1): (30.0, 8.0)})
+    result = hw.get_visible_gpu_utilization()
+    assert result["index_kind"] == "physical"
+    assert result["devices"][0]["vram_used_gb"] == 0.02  # untouched
diff --git a/studio/backend/tests/test_rocm_oom_guard.py b/studio/backend/tests/test_rocm_oom_guard.py
index 699d0b74f5..ad46f6ee41 100644
--- a/studio/backend/tests/test_rocm_oom_guard.py
+++ b/studio/backend/tests/test_rocm_oom_guard.py
@@ -163,6 +163,9 @@ class TestDeviceNameFallback:
             "AMD Radeon 8060S",
             "Radeon 8050S Graphics",  # cut-down Strix Halo SKU
             "AMD Radeon 8050S",
+            # gfx1151 Gorgon Halo (Ryzen AI Max 400 refresh)
+            "Radeon 8065S Graphics",  # Ryzen AI Max+ 495
+            "AMD Radeon 8065S",
             # case variants
             "RADEON 8060S GRAPHICS",
             "radeon 8050s",
diff --git a/studio/backend/tests/test_setup_cache_env_hf_home.py b/studio/backend/tests/test_setup_cache_env_hf_home.py
index 4520c93a51..c5d5f820a8 100644
--- a/studio/backend/tests/test_setup_cache_env_hf_home.py
+++ b/studio/backend/tests/test_setup_cache_env_hf_home.py
@@ -28,6 +28,9 @@ def _isolate_studio_home(monkeypatch, tmp_path):
 
 
 def _load_storage_roots():
+    # Each test models a fresh backend process. The cache resolver intentionally
+    # snapshots explicit environment variables once per process.
+    sys.modules.pop("utils.hf_cache_settings", None)
     spec = importlib.util.spec_from_file_location("storage_roots_under_test", _STORAGE_ROOTS_PATH)
     module = importlib.util.module_from_spec(spec)
     spec.loader.exec_module(module)
@@ -40,10 +43,10 @@ def _clear_hf_env(monkeypatch):
 
 
 def test_custom_hf_home_seeds_hub_and_xet(monkeypatch, tmp_path):
-    sr = _load_storage_roots()
     _clear_hf_env(monkeypatch)
     custom = tmp_path / "shared" / "huggingface"
     monkeypatch.setenv("HF_HOME", str(custom))
+    sr = _load_storage_roots()
 
     sr._setup_cache_env()
 
@@ -54,9 +57,9 @@ def test_custom_hf_home_seeds_hub_and_xet(monkeypatch, tmp_path):
 
 
 def test_default_when_hf_home_unset(monkeypatch, tmp_path):
-    sr = _load_storage_roots()
     _clear_hf_env(monkeypatch)
     monkeypatch.setenv("XDG_CACHE_HOME", str(tmp_path / "xdg"))
+    sr = _load_storage_roots()
 
     sr._setup_cache_env()
 
@@ -67,11 +70,11 @@ def test_default_when_hf_home_unset(monkeypatch, tmp_path):
 
 
 def test_explicit_hub_cache_is_not_overridden(monkeypatch, tmp_path):
-    sr = _load_storage_roots()
     _clear_hf_env(monkeypatch)
     monkeypatch.setenv("HF_HOME", str(tmp_path / "home"))
     explicit = tmp_path / "explicit" / "hub"
     monkeypatch.setenv("HF_HUB_CACHE", str(explicit))
+    sr = _load_storage_roots()
 
     sr._setup_cache_env()
 
@@ -81,11 +84,11 @@ def test_explicit_hub_cache_is_not_overridden(monkeypatch, tmp_path):
 
 
 def test_legacy_huggingface_hub_cache_alias_is_honored(monkeypatch, tmp_path):
-    sr = _load_storage_roots()
     _clear_hf_env(monkeypatch)
     monkeypatch.setenv("HF_HOME", str(tmp_path / "home"))
     legacy = tmp_path / "legacy" / "hub"
     monkeypatch.setenv("HUGGINGFACE_HUB_CACHE", str(legacy))
+    sr = _load_storage_roots()
 
     sr._setup_cache_env()
 
@@ -96,15 +99,16 @@ def test_legacy_huggingface_hub_cache_alias_is_honored(monkeypatch, tmp_path):
 
 def test_whitespace_hf_home_falls_back_to_default(monkeypatch, tmp_path):
     # A blank/whitespace HF_HOME must not become " /hub"; fall back to default.
-    sr = _load_storage_roots()
     _clear_hf_env(monkeypatch)
     monkeypatch.setenv("HF_HOME", "   ")
     monkeypatch.setenv("XDG_CACHE_HOME", str(tmp_path / "xdg"))
+    sr = _load_storage_roots()
 
     sr._setup_cache_env()
 
     import os
 
+    assert os.environ["HF_HOME"] == str(tmp_path / "xdg" / "huggingface")
     assert os.environ["HF_HUB_CACHE"] == str(tmp_path / "xdg" / "huggingface" / "hub")
 
 
@@ -114,9 +118,9 @@ def test_unwritable_hf_home_does_not_crash(monkeypatch, tmp_path):
     blocker = tmp_path / "blocker"
     blocker.write_text("not a dir")
     unwritable = blocker / "hf"
-    sr = _load_storage_roots()
     _clear_hf_env(monkeypatch)
     monkeypatch.setenv("HF_HOME", str(unwritable))
+    sr = _load_storage_roots()
 
     sr._setup_cache_env()  # must not raise
 
diff --git a/studio/backend/tests/test_stt_download_validation.py b/studio/backend/tests/test_stt_download_validation.py
new file mode 100644
index 0000000000..a612b14531
--- /dev/null
+++ b/studio/backend/tests/test_stt_download_validation.py
@@ -0,0 +1,168 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""The /audio/stt/download route must validate a custom Transformers repo before
+snapshot_download pulls it into the shared HF cache.
+
+Regression for a Codex finding: the Transformers engine accepts arbitrary
+`owner/model` repos, so an authenticated caller could make Studio download a
+large non-STT repository before load-time validation ever ran. Whisper-
+compatibility is now enforced (metadata-only, no weights) before the background
+download starts. The GGUF engine only accepts curated ids, so it is not gated.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+from pathlib import Path
+
+import pytest
+from fastapi import HTTPException
+
+_BACKEND_ROOT = Path(__file__).resolve().parents[1]
+if str(_BACKEND_ROOT) not in sys.path:
+    sys.path.insert(0, str(_BACKEND_ROOT))
+
+import core.inference.stt_ggml_sidecar as ggml_module  # noqa: E402
+import core.inference.stt_sidecar as stt_module  # noqa: E402
+import routes.inference as ri  # noqa: E402
+from core.inference.stt_sidecar import SttModelCompatibilityError  # noqa: E402
+from models.inference import SttLoadRequest  # noqa: E402
+
+
+def _run(coro):
+    return asyncio.run(coro)
+
+
+def test_custom_non_whisper_repo_is_rejected_before_download(monkeypatch):
+    started: list = []
+    validated: list = []
+
+    def fake_validate(model, hf_token = None):
+        validated.append(model)
+        raise SttModelCompatibilityError(
+            f"STT model '{model}' is not a compatible Transformers Whisper model."
+        )
+
+    def fake_download(model, hf_token = None):
+        started.append(model)
+
+    monkeypatch.setattr(stt_module, "validate_remote_model", fake_validate)
+    monkeypatch.setattr(stt_module, "start_model_download", fake_download)
+
+    with pytest.raises(HTTPException) as excinfo:
+        _run(
+            ri.stt_download(
+                SttLoadRequest(model = "owner/chat-model", engine = "transformers"),
+                current_subject = "tester",
+                hf_token = None,
+            )
+        )
+
+    assert excinfo.value.status_code == 422
+    assert validated == ["owner/chat-model"]
+    # The download never starts for a repo that failed the Whisper check.
+    assert started == []
+
+
+def test_validated_transformers_repo_downloads(monkeypatch):
+    started: list = []
+    revision = "a" * 40
+
+    monkeypatch.setattr(
+        stt_module,
+        "validate_remote_model",
+        lambda model, hf_token = None: {"model": model, "revision": revision},
+    )
+    monkeypatch.setattr(
+        stt_module,
+        "start_model_download",
+        lambda model, hf_token = None, revision = None: started.append((model, revision)),
+    )
+    monkeypatch.setattr(stt_module, "download_status", lambda: {"downloading": True})
+
+    resp = _run(
+        ri.stt_download(
+            SttLoadRequest(model = "owner/real-whisper", engine = "transformers"),
+            current_subject = "tester",
+            hf_token = None,
+        )
+    )
+
+    assert resp.status_code == 200
+    assert started == [("owner/real-whisper", revision)]
+
+
+def test_gguf_engine_skips_the_transformers_repo_check(monkeypatch):
+    started: list = []
+
+    def fail_if_called(model, hf_token = None):
+        raise AssertionError("GGUF downloads must not run the Transformers repo check")
+
+    # whisper-server present, so the GGUF request stays on the GGUF engine.
+    monkeypatch.setattr(ggml_module, "is_available", lambda: True)
+    monkeypatch.setattr(stt_module, "validate_remote_model", fail_if_called)
+    monkeypatch.setattr(
+        ggml_module, "start_model_download", lambda model, hf_token = None: started.append(model)
+    )
+    monkeypatch.setattr(ggml_module, "download_status", lambda: {"downloading": True})
+
+    resp = _run(
+        ri.stt_download(
+            SttLoadRequest(model = "small", engine = "gguf"),
+            current_subject = "tester",
+            hf_token = None,
+        )
+    )
+
+    assert resp.status_code == 200
+    assert started == ["small"]
+
+
+def test_resolve_serving_stt_engine_falls_back_when_whisper_server_absent(monkeypatch):
+    # A curated GGUF request downgrades to Transformers when whisper-server is not
+    # installed (both engines serve curated ids), but stays GGUF when it is.
+    monkeypatch.setattr(ggml_module, "is_available", lambda: False)
+    assert ri._resolve_serving_stt_engine("gguf") == "transformers"
+    monkeypatch.setattr(ggml_module, "is_available", lambda: True)
+    assert ri._resolve_serving_stt_engine("gguf") == "gguf"
+    # Transformers is unaffected by whisper-server availability.
+    monkeypatch.setattr(ggml_module, "is_available", lambda: False)
+    assert ri._resolve_serving_stt_engine("transformers") == "transformers"
+
+
+def test_gguf_download_falls_back_to_transformers_when_server_absent(monkeypatch):
+    """Selecting the default curated model on a host without whisper-server must
+    download through the Transformers engine, not 501/dead-end on GGUF."""
+    gguf_started: list = []
+    tf_started: list = []
+
+    monkeypatch.setattr(ggml_module, "is_available", lambda: False)  # no whisper-server
+    # validate_remote_model no-ops curated ids in production; keep it a no-op here.
+    monkeypatch.setattr(
+        stt_module, "validate_remote_model", lambda model, hf_token = None: {"model": model}
+    )
+    monkeypatch.setattr(
+        stt_module,
+        "start_model_download",
+        lambda model, hf_token = None, revision = None: tf_started.append(model),
+    )
+    monkeypatch.setattr(stt_module, "download_status", lambda: {"downloading": True})
+    monkeypatch.setattr(
+        ggml_module,
+        "start_model_download",
+        lambda model, hf_token = None: gguf_started.append(model),
+    )
+
+    resp = _run(
+        ri.stt_download(
+            SttLoadRequest(model = "small", engine = "gguf"),
+            current_subject = "tester",
+            hf_token = None,
+        )
+    )
+
+    assert resp.status_code == 200
+    assert tf_started == ["small"]  # served by Transformers instead of dead-ending on GGUF
+    assert gguf_started == []
diff --git a/studio/backend/tests/test_stt_ggml_sidecar.py b/studio/backend/tests/test_stt_ggml_sidecar.py
new file mode 100644
index 0000000000..686fd8f546
--- /dev/null
+++ b/studio/backend/tests/test_stt_ggml_sidecar.py
@@ -0,0 +1,780 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import http.server
+import io
+import json
+import os
+import sys
+import threading
+import time
+import wave
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+import core.inference.stt_ggml_sidecar as ggml_module
+from core.inference.stt_ggml_sidecar import (
+    DEFAULT_GGML_STT_MODEL,
+    GGML_STT_MODELS,
+    GGML_STT_REPOS,
+    GgmlSttSidecar,
+    SttEngineUnavailableError,
+    find_whisper_server_binary,
+    resolve_ggml_model_id,
+)
+from core.inference.stt_sidecar import (
+    SttLanguageError,
+    SttLoadCancelledError,
+    SttModelIdError,
+    SttModelNotDownloadedError,
+    SttUnavailableError,
+)
+
+
+@pytest.fixture(autouse = True)
+def isolate_runtime_and_stub_audio_decoder(monkeypatch, tmp_path):
+    """Unit tests exercise orchestration, not PyAV container parsing."""
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path / "studio"))
+    monkeypatch.delenv("WHISPER_SERVER_PATH", raising = False)
+    monkeypatch.delenv("UNSLOTH_WHISPER_CPP_PATH", raising = False)
+    monkeypatch.setenv("PATH", "")
+    monkeypatch.setattr(
+        ggml_module,
+        "_decode_audio_bounded",
+        lambda audio: np.zeros(16000, dtype = np.float32),
+    )
+
+
+# ---------------------------------------------------------------------------
+# Model id resolution
+# ---------------------------------------------------------------------------
+
+
+def test_curated_ids_resolve():
+    for model_id in GGML_STT_MODELS:
+        assert resolve_ggml_model_id(model_id) == model_id
+
+
+def test_default_model_resolves_from_none_and_blank():
+    assert resolve_ggml_model_id(None) == DEFAULT_GGML_STT_MODEL
+    assert resolve_ggml_model_id("  ") == DEFAULT_GGML_STT_MODEL
+
+
+def test_custom_repo_ids_are_rejected():
+    with pytest.raises(SttModelIdError):
+        resolve_ggml_model_id("owner/model")
+    with pytest.raises(SttModelIdError):
+        resolve_ggml_model_id("large-v2")
+
+
+def test_curated_ids_mirror_transformers_sidecar():
+    from core.inference.stt_sidecar import STT_MODELS
+    assert list(GGML_STT_MODELS.keys()) == list(STT_MODELS.keys())
+
+
+def test_curated_filenames_match_repo_naming():
+    # unslothai/whisper-<id>-GGUF hosts whisper-<id>.bin; keep the download
+    # filename in lockstep with the repo so it resolves instead of 404ing.
+    for model_id, repo in GGML_STT_REPOS.items():
+        expected = repo.split("/", 1)[1].removesuffix("-GGUF") + ".bin"
+        assert GGML_STT_MODELS[model_id] == expected
+
+
+# ---------------------------------------------------------------------------
+# Binary discovery
+# ---------------------------------------------------------------------------
+
+
+def test_env_binary_override_wins(monkeypatch, tmp_path):
+    binary = tmp_path / "whisper-server"
+    binary.write_text("#!/bin/sh\n")
+    binary.chmod(0o755)  # find_whisper_server_binary requires an executable
+    monkeypatch.setenv("WHISPER_SERVER_PATH", str(binary))
+    assert find_whisper_server_binary() == str(binary)
+
+
+def test_env_dir_override_scans_layouts(monkeypatch, tmp_path):
+    monkeypatch.delenv("WHISPER_SERVER_PATH", raising = False)
+    build_bin = tmp_path / "build" / "bin"
+    build_bin.mkdir(parents = True)
+    binary = build_bin / "whisper-server"
+    binary.write_text("#!/bin/sh\n")
+    binary.chmod(0o755)  # find_whisper_server_binary requires an executable
+    monkeypatch.setenv("UNSLOTH_WHISPER_CPP_PATH", str(tmp_path))
+    assert find_whisper_server_binary() == str(binary)
+
+
+def test_missing_binary_reports_unavailable(monkeypatch, tmp_path):
+    monkeypatch.delenv("WHISPER_SERVER_PATH", raising = False)
+    monkeypatch.setenv("UNSLOTH_WHISPER_CPP_PATH", str(tmp_path / "nope"))
+    monkeypatch.setattr(ggml_module, "_managed_whisper_cpp_dir", lambda: tmp_path / "gone")
+    monkeypatch.setattr(ggml_module.shutil, "which", lambda name: None)
+    assert find_whisper_server_binary() is None
+    assert not ggml_module.is_available()
+    with pytest.raises(SttEngineUnavailableError):
+        ggml_module.ensure_engine_available()
+
+
+def test_non_executable_binary_is_not_runnable(monkeypatch, tmp_path):
+    if sys.platform == "win32":
+        pytest.skip("X_OK is an existence check on Windows")
+    binary = tmp_path / "whisper-server"
+    binary.write_text("#!/bin/sh\n")  # written but not chmod +x
+    monkeypatch.setenv("WHISPER_SERVER_PATH", str(binary))
+    monkeypatch.setattr(ggml_module.shutil, "which", lambda name: None)
+    assert find_whisper_server_binary() is None
+
+
+# ---------------------------------------------------------------------------
+# Slim-install launch guard
+# ---------------------------------------------------------------------------
+
+
+def _slim_install(
+    tmp_path,
+    *,
+    install_kind = "slim",
+    with_ggml = True,
+    linked_libraries = None,
+    backend = "cpu",
+    linked_runtime_directories = None,
+    runtime_wiring_version = None,
+) -> str:
+    """A managed-looking install tree: marker at the root, server in build/bin."""
+    install_dir = tmp_path / "whisper.cpp"
+    bin_dir = install_dir / "build" / "bin"
+    bin_dir.mkdir(parents = True)
+    binary = bin_dir / "whisper-server"
+    binary.write_text("#!/bin/sh\n")
+    binary.chmod(0o755)
+    marker: dict = {
+        "schema_version": 1,
+        "component": "whisper.cpp",
+        "release_tag": "v1.9.1-unsloth.1",
+        "backend": backend,
+        "paired_llama_tag": "b10069-mix-fb3d4ca",
+    }
+    if install_kind is not None:
+        marker["install_kind"] = install_kind
+    if linked_libraries is not None:
+        marker["linked_libraries"] = linked_libraries
+    if linked_runtime_directories is not None:
+        marker["linked_runtime_directories"] = linked_runtime_directories
+        for name in linked_runtime_directories:
+            catalog = bin_dir / name
+            catalog.mkdir()
+            (catalog / "kernel.dat").write_bytes(b"kernel")
+    if runtime_wiring_version is not None:
+        marker["runtime_wiring_version"] = runtime_wiring_version
+    (install_dir / "UNSLOTH_WHISPER_PREBUILT_INFO.json").write_text(json.dumps(marker))
+    if with_ggml:
+        names = (
+            ("ggml.dll", "ggml-base.dll")
+            if sys.platform == "win32"
+            else ("libggml.so.0", "libggml-base.so.0")
+        )
+        for name in names:
+            (bin_dir / name).write_bytes(b"ggml")
+    return str(binary)
+
+
+def test_slim_guard_flags_missing_ggml_links(monkeypatch, tmp_path):
+    # A slim marker whose linked ggml runtime is gone must read as engine
+    # unavailable (reinstall), never crash into a server launch.
+    binary = _slim_install(tmp_path, with_ggml = False)
+    assert ggml_module.slim_runtime_intact(binary) is False
+    monkeypatch.setattr(ggml_module, "find_whisper_server_binary", lambda: binary)
+    assert not ggml_module.is_available()
+    with pytest.raises(SttEngineUnavailableError, match = "ggml"):
+        ggml_module.ensure_engine_available()
+
+
+def test_slim_guard_passes_with_links_in_place(monkeypatch, tmp_path):
+    names = ["libggml.so.0", "libggml-base.so.0"]
+    binary = _slim_install(tmp_path, with_ggml = True, linked_libraries = names)
+    assert ggml_module.slim_runtime_intact(binary) is True
+    monkeypatch.setattr(ggml_module, "find_whisper_server_binary", lambda: binary)
+    assert ggml_module.ensure_engine_available() == binary
+
+
+def test_slim_guard_verifies_the_marker_linked_libraries(monkeypatch, tmp_path):
+    # New markers record the exact wired filenames; one missing name flips the
+    # install to unavailable even when the legacy core ggml names are present.
+    names = ["libggml.dylib", "libggml-base.dylib", "libggml-metal.dylib"]
+    binary = _slim_install(tmp_path, with_ggml = True, linked_libraries = names)
+    bin_dir = Path(binary).parent
+    for name in names[:-1]:
+        (bin_dir / name).write_bytes(b"ggml")
+    assert ggml_module.slim_runtime_intact(binary) is False  # metal dylib absent
+    (bin_dir / names[-1]).write_bytes(b"ggml")
+    assert ggml_module.slim_runtime_intact(binary) is True
+    monkeypatch.setattr(ggml_module, "find_whisper_server_binary", lambda: binary)
+    assert ggml_module.ensure_engine_available() == binary
+
+
+def test_slim_guard_malformed_authoritative_marker_fails_closed(tmp_path):
+    for bad in ("not-a-list", [], [1, 2]):
+        root = tmp_path / f"case_{type(bad).__name__}_{len(str(bad))}"
+        root.mkdir()
+        binary = _slim_install(root, with_ggml = True, linked_libraries = bad)
+        assert ggml_module.slim_runtime_intact(binary) is False
+
+
+def test_slim_guard_prefers_authoritative_root_marker(tmp_path):
+    names = ["libggml.so.0", "libggml-base.so.0"]
+    binary = _slim_install(tmp_path, with_ggml = True, linked_libraries = names)
+    packaging_marker = Path(binary).parent / "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+    packaging_marker.write_text(json.dumps({"backend": "slim", "release_tag": "packaging"}))
+    assert ggml_module._whisper_install_marker(binary)["install_kind"] == "slim"
+    assert ggml_module.slim_runtime_intact(binary) is True
+
+
+def test_slim_guard_rejects_invalid_root_even_with_inner_marker(tmp_path):
+    binary = _slim_install(tmp_path, with_ggml = True, linked_libraries = ["libggml.so.0"])
+    root_marker = Path(binary).parents[2] / "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+    root_marker.write_text("not json")
+    (Path(binary).parent / root_marker.name).write_text(json.dumps({"backend": "slim"}))
+    assert ggml_module.slim_runtime_intact(binary) is False
+
+
+def test_slim_guard_rejects_missing_rocm_catalog(tmp_path):
+    names = ["libggml.so.0", "libggml-base.so.0", "libggml-hip.so"]
+    binary = _slim_install(
+        tmp_path,
+        linked_libraries = names,
+        backend = "rocm",
+        linked_runtime_directories = ["hipblaslt", "rocblas"],
+        runtime_wiring_version = 2,
+    )
+    bin_dir = Path(binary).parent
+    (bin_dir / "libggml-hip.so").write_bytes(b"ggml")
+    assert ggml_module.slim_runtime_intact(binary) is True
+    (bin_dir / "rocblas" / "kernel.dat").unlink()
+    assert ggml_module.slim_runtime_intact(binary) is False
+
+
+def test_slim_guard_accepts_windows_rocm_dll_overlay(monkeypatch, tmp_path):
+    monkeypatch.setattr(ggml_module.sys, "platform", "win32")
+    names = ["ggml.dll", "ggml-base.dll", "ggml-hip.dll", "amdhip64.dll"]
+    binary = _slim_install(
+        tmp_path,
+        linked_libraries = names,
+        backend = "rocm",
+        linked_runtime_directories = [],
+        runtime_wiring_version = 2,
+    )
+    for name in names:
+        (Path(binary).parent / name).write_bytes(b"dll")
+    assert ggml_module.slim_runtime_intact(binary) is True
+
+
+def test_slim_guard_ignores_fat_and_markerless_installs(tmp_path):
+    # Fat installs carry their own ggml; no marker means source/custom build.
+    fat = _slim_install(tmp_path / "fat", install_kind = None, with_ggml = False)
+    assert ggml_module.slim_runtime_intact(fat) is True
+    bare = tmp_path / "bare" / "whisper-server"
+    bare.parent.mkdir(parents = True)
+    bare.write_text("#!/bin/sh\n")
+    assert ggml_module.slim_runtime_intact(str(bare)) is True
+
+
+# ---------------------------------------------------------------------------
+# whisper-server child-process environment
+# ---------------------------------------------------------------------------
+
+
+def _loader_path_var() -> str:
+    return {"win32": "PATH", "darwin": "DYLD_LIBRARY_PATH"}.get(sys.platform, "LD_LIBRARY_PATH")
+
+
+def test_child_env_scrubs_secrets_and_adds_lib_dir(monkeypatch, tmp_path):
+    monkeypatch.setenv("HF_TOKEN", "secret-token")  # exact name
+    monkeypatch.setenv("MY_API_KEY", "nope")  # marker substring
+    monkeypatch.setenv("HTTPS_PROXY", "http://u:p@px:8080")  # url-name
+    monkeypatch.setenv("SOME_REMOTE", "https://u:pw@host/repo")  # url-userinfo value
+    monkeypatch.setenv("STT_KEEPME", "keep")  # benign
+    binary = tmp_path / "whisper-server"
+    binary.write_text("#!/bin/sh\n")
+    env = ggml_module._whisper_server_child_env(str(binary))
+    for scrubbed in ("HF_TOKEN", "MY_API_KEY", "HTTPS_PROXY", "SOME_REMOTE"):
+        assert scrubbed not in env
+    assert env.get("STT_KEEPME") == "keep"
+    assert str(tmp_path.resolve()) in env[_loader_path_var()].split(os.pathsep)
+
+
+def test_child_env_isolates_home_and_cred_locations(monkeypatch, tmp_path):
+    # The downloaded server must not see the real home (token caches live
+    # there) nor explicit cred-store pointers like HF_HOME / NETRC.
+    monkeypatch.setenv("HOME", "/real/home")
+    monkeypatch.setenv("HF_HOME", "/real/hf")
+    monkeypatch.setenv("NETRC", "/real/.netrc")
+    monkeypatch.setattr(ggml_module, "_managed_whisper_cpp_dir", lambda: tmp_path / "managed")
+    binary = tmp_path / "whisper-server"
+    binary.write_text("#!/bin/sh\n")
+    env = ggml_module._whisper_server_child_env(str(binary))
+    assert env["HOME"] == str(tmp_path / "managed" / ".child_home")
+    assert "HF_HOME" not in env
+    assert "NETRC" not in env
+    assert (tmp_path / "managed" / ".child_home").is_dir()
+
+
+def test_child_env_wsl_rocm_prepends_system_hip(monkeypatch, tmp_path):
+    if sys.platform != "linux":
+        pytest.skip("WSL ROCm library precedence is Linux-only")
+    rocm = tmp_path / "rocm-lib"
+    rocm.mkdir()
+    bindir = tmp_path / "bin"
+    bindir.mkdir()
+    binary = bindir / "whisper-server"
+    binary.write_text("#!/bin/sh\n")
+    monkeypatch.setattr(ggml_module, "_wsl_system_rocm_lib_dirs", lambda: [str(rocm)])
+    env = ggml_module._whisper_server_child_env(str(binary))
+    parts = env["LD_LIBRARY_PATH"].split(os.pathsep)
+    assert parts[0] == str(rocm.resolve())  # system HIP wins
+    assert str(bindir.resolve()) in parts  # bundle libs still present
+    assert env.get("HSA_ENABLE_DXG_DETECTION") == "1"
+
+
+def test_child_env_adds_cuda_runtime_dirs_for_cuda_bundle(monkeypatch, tmp_path):
+    # Versioned CUDA backend modules are valid too. They still need the
+    # CUDA-from-PyTorch wheel dirs for libcudart/libcublas at launch.
+    if sys.platform == "darwin":
+        pytest.skip("no CUDA on macOS")
+    import utils.prebuilt.runtime_libs as rl
+
+    bindir = tmp_path / "bin"
+    bindir.mkdir()
+    (bindir / "whisper-server").write_text("#!/bin/sh\n")
+    module_name = "ggml-cuda.dll" if sys.platform == "win32" else "libggml-cuda.so.0"
+    (bindir / module_name).write_text("")
+    cuda_dir = tmp_path / "nvidia" / "cuda_runtime" / "lib"
+    cuda_dir.mkdir(parents = True)
+    monkeypatch.setattr(rl, "python_runtime_dirs", lambda: [str(cuda_dir)])
+    env = ggml_module._whisper_server_child_env(str(bindir / "whisper-server"))
+    parts = env[_loader_path_var()].split(os.pathsep)
+    assert str(bindir.resolve()) in parts
+    assert str(cuda_dir.resolve()) in parts
+    assert parts.index(str(bindir.resolve())) < parts.index(str(cuda_dir.resolve()))
+
+
+def test_child_env_omits_cuda_runtime_dirs_for_cpu_bundle(monkeypatch, tmp_path):
+    # No libggml-cuda.so beside the binary -> a static CPU/Metal bundle -> the CUDA
+    # wheel discovery must not run and must not touch the loader path.
+    if sys.platform == "darwin":
+        pytest.skip("no CUDA on macOS")
+    import utils.prebuilt.runtime_libs as rl
+
+    bindir = tmp_path / "bin"
+    bindir.mkdir()
+    (bindir / "whisper-server").write_text("#!/bin/sh\n")
+    cuda_dir = tmp_path / "nvidia" / "cuda_runtime" / "lib"
+    cuda_dir.mkdir(parents = True)
+    called = {"n": 0}
+
+    def _fake_dirs():
+        called["n"] += 1
+        return [str(cuda_dir)]
+
+    monkeypatch.setattr(rl, "python_runtime_dirs", _fake_dirs)
+    env = ggml_module._whisper_server_child_env(str(bindir / "whisper-server"))
+    parts = env[_loader_path_var()].split(os.pathsep)
+    assert str(cuda_dir.resolve()) not in parts
+    assert called["n"] == 0
+
+
+def test_engine_unavailable_is_stt_unavailable():
+    # Routes map SttUnavailableError to HTTP 501; the engine error must share it.
+    assert issubclass(SttEngineUnavailableError, SttUnavailableError)
+
+
+# ---------------------------------------------------------------------------
+# WAV packaging
+# ---------------------------------------------------------------------------
+
+
+def test_pcm_to_wav_bytes_shape_and_rate():
+    pcm = np.zeros(3200, dtype = np.float32)
+    data = ggml_module._pcm_to_wav_bytes(pcm)
+    with wave.open(io.BytesIO(data)) as w:
+        assert w.getnchannels() == 1
+        assert w.getsampwidth() == 2
+        assert w.getframerate() == 16000
+        assert w.getnframes() == 3200
+
+
+def test_pcm_to_wav_bytes_clips_out_of_range():
+    pcm = np.array([2.0, -2.0], dtype = np.float32)
+    data = ggml_module._pcm_to_wav_bytes(pcm)
+    with wave.open(io.BytesIO(data)) as w:
+        frames = np.frombuffer(w.readframes(2), dtype = "<i2")
+    assert frames[0] == 32767
+    assert frames[1] == -32767
+
+
+# ---------------------------------------------------------------------------
+# Sidecar orchestration
+# ---------------------------------------------------------------------------
+
+
+def _available(monkeypatch):
+    monkeypatch.setattr(ggml_module, "find_whisper_server_binary", lambda: "/bin/echo")
+
+
+def test_transcribe_requires_engine(monkeypatch):
+    monkeypatch.setattr(ggml_module, "find_whisper_server_binary", lambda: None)
+    sidecar = GgmlSttSidecar()
+    with pytest.raises(SttEngineUnavailableError):
+        sidecar.transcribe(b"RIFF")
+
+
+def test_transcribe_rejects_unknown_language(monkeypatch):
+    _available(monkeypatch)
+    sidecar = GgmlSttSidecar()
+    with pytest.raises(SttLanguageError):
+        sidecar.transcribe(b"RIFF", model = "small", language = "xx-QQ")
+
+
+def test_load_requires_downloaded_model(monkeypatch):
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: None)
+    sidecar = GgmlSttSidecar()
+    with pytest.raises(SttModelNotDownloadedError):
+        sidecar.load("small")
+
+
+def test_unloaded_sidecar_reports_nothing_resident():
+    sidecar = GgmlSttSidecar()
+    assert sidecar.loaded_model is None
+    assert sidecar.device is None
+    assert sidecar.is_loading() is False
+    sidecar.unload()  # no-op, must not raise
+
+
+def test_update_maintenance_unloads_and_blocks_new_loads(monkeypatch):
+    class FakeProcess:
+        pid = 4242
+
+        def __init__(self):
+            self.running = True
+
+        def poll(self):
+            return None if self.running else 0
+
+        def terminate(self):
+            self.running = False
+
+        def wait(self, timeout = None):
+            return 0
+
+    monkeypatch.setattr(ggml_module, "forget_pid", lambda _pid: None)
+    sidecar = GgmlSttSidecar()
+    sidecar._process = FakeProcess()
+    sidecar._model_id = "small"
+
+    with sidecar.update_maintenance() as model_was_active:
+        assert model_was_active is True
+        assert sidecar.loaded_model is None
+        with pytest.raises(SttEngineUnavailableError, match = "being updated"):
+            sidecar.load("small")
+
+    assert sidecar._update_in_progress is False
+
+
+def test_server_pid_is_tracked_for_parent_lifetime(monkeypatch):
+    # The spawned server must be adopted for the terminate_all backstop and
+    # forgotten once this sidecar has reaped it.
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+
+    class FakeProcess:
+        pid = 4242
+
+        def __init__(self, *args, **kwargs):
+            self.terminated = False
+
+        def poll(self):
+            return 1 if self.terminated else None
+
+        def terminate(self):
+            self.terminated = True
+
+        def wait(self, timeout = None):
+            return 0
+
+    events = []
+    monkeypatch.setattr(ggml_module.subprocess, "Popen", FakeProcess)
+    monkeypatch.setattr(ggml_module, "adopt_pid", lambda pid: events.append(("adopt", pid)))
+    monkeypatch.setattr(ggml_module, "forget_pid", lambda pid: events.append(("forget", pid)))
+    monkeypatch.setattr(
+        GgmlSttSidecar,
+        "_wait_for_server",
+        staticmethod(lambda process, port, cancel_event = None: None),
+    )
+
+    sidecar = GgmlSttSidecar()
+    sidecar.load("small")
+    assert events == [("adopt", 4242)]
+    sidecar.unload()
+    assert events == [("adopt", 4242), ("forget", 4242)]
+
+
+def test_training_forces_whisper_server_off_gpu(monkeypatch):
+    # Mirror the Transformers sidecar: keep whisper.cpp on CPU during training
+    # so a mid-training dictation cannot reclaim the VRAM training just freed.
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+    commands: list[list[str]] = []
+
+    class FakeProcess:
+        pid = 4242
+
+        def __init__(self, command, *args, **kwargs):
+            commands.append(command)
+
+        def poll(self):
+            return None
+
+        def terminate(self):
+            pass
+
+        def wait(self, timeout = None):
+            return 0
+
+    monkeypatch.setattr(ggml_module.subprocess, "Popen", FakeProcess)
+    monkeypatch.setattr(ggml_module, "adopt_pid", lambda pid: None)
+    monkeypatch.setattr(ggml_module, "forget_pid", lambda pid: None)
+    monkeypatch.setattr(
+        GgmlSttSidecar,
+        "_wait_for_server",
+        staticmethod(lambda process, port, cancel_event = None: None),
+    )
+
+    monkeypatch.setattr(ggml_module, "_training_active", lambda: False)
+    idle = GgmlSttSidecar()
+    idle.load("small")
+    assert "--no-gpu" not in commands[0]
+    assert idle.is_loading() is False
+    idle.unload()
+
+    monkeypatch.setattr(ggml_module, "_training_active", lambda: True)
+    training = GgmlSttSidecar()
+    training.load("small")
+    assert "--no-gpu" in commands[1]
+    training.unload()
+
+
+def test_cpu_root_marker_forces_no_gpu_despite_inner_packaging_marker(monkeypatch, tmp_path):
+    names = ["libggml.so.0", "libggml-base.so.0"]
+    binary = _slim_install(tmp_path, with_ggml = True, linked_libraries = names)
+    (Path(binary).parent / "UNSLOTH_WHISPER_PREBUILT_INFO.json").write_text(
+        json.dumps({"backend": "slim"})
+    )
+    monkeypatch.setattr(ggml_module, "find_whisper_server_binary", lambda: binary)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+    commands: list[list[str]] = []
+
+    class FakeProcess:
+        pid = 4244
+
+        def __init__(self, command, *args, **kwargs):
+            commands.append(command)
+
+        def poll(self):
+            return None
+
+        def terminate(self):
+            pass
+
+        def wait(self, timeout = None):
+            return 0
+
+    monkeypatch.setattr(ggml_module.subprocess, "Popen", FakeProcess)
+    monkeypatch.setattr(ggml_module, "adopt_pid", lambda pid: None)
+    monkeypatch.setattr(ggml_module, "forget_pid", lambda pid: None)
+    monkeypatch.setattr(ggml_module, "_training_active", lambda: False)
+    monkeypatch.setattr(
+        GgmlSttSidecar,
+        "_wait_for_server",
+        staticmethod(lambda process, port, cancel_event = None: None),
+    )
+
+    sidecar = GgmlSttSidecar()
+    sidecar.load("small")
+    assert "--no-gpu" in commands[0]
+    sidecar.unload()
+
+
+def test_startup_is_cancellable_before_training(monkeypatch):
+    # A whisper-server still binding its (Metal/CUDA) backend must be preemptible
+    # so training coordination can stop it before admitting the run, instead of
+    # racing an allocating subprocess.
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+
+    class FakeProcess:
+        pid = 4243
+
+        def __init__(self, *args, **kwargs):
+            self.terminated = False
+            self.killed = False
+
+        def poll(self):
+            return -15 if (self.terminated or self.killed) else None
+
+        def terminate(self):
+            self.terminated = True
+
+        def kill(self):
+            self.killed = True
+
+        def wait(self, timeout = None):
+            return 0
+
+    monkeypatch.setattr(ggml_module.subprocess, "Popen", FakeProcess)
+    monkeypatch.setattr(ggml_module, "adopt_pid", lambda pid: None)
+    monkeypatch.setattr(ggml_module, "forget_pid", lambda pid: None)
+
+    # The server never reports ready, so _wait_for_server loops until cancelled.
+    def never_ready(req, timeout = None):
+        raise OSError("connection refused")
+
+    monkeypatch.setattr(ggml_module.urllib.request, "urlopen", never_ready)
+
+    sidecar = GgmlSttSidecar()
+    result: dict = {}
+
+    def _load():
+        try:
+            sidecar.load("small")
+            result["ok"] = True
+        except Exception as exc:  # noqa: BLE001 - recorded for the assertion below
+            result["error"] = exc
+
+    thread = threading.Thread(target = _load)
+    thread.start()
+    try:
+        deadline = time.monotonic() + 5
+        while time.monotonic() < deadline and not sidecar.is_loading():
+            time.sleep(0.01)
+        assert sidecar.is_loading() is True
+        assert sidecar.cancel_pending_load() is True
+        # Blocks until the cancelled startup has been reaped and the lock freed.
+        sidecar.wait_for_load_to_settle()
+    finally:
+        thread.join(timeout = 5)
+
+    assert thread.is_alive() is False
+    assert isinstance(result.get("error"), SttLoadCancelledError)
+    assert sidecar.is_loading() is False
+    assert sidecar.loaded_model is None
+
+
+class _FakeWhisperHandler(http.server.BaseHTTPRequestHandler):
+    """Stands in for whisper-server's /inference endpoint."""
+
+    response_text = "Hello world.\n Second line."
+
+    def do_POST(self):
+        length = int(self.headers.get("Content-Length", "0"))
+        self.rfile.read(length)
+        body = json.dumps({"text": self.response_text}).encode()
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(body)))
+        self.end_headers()
+        self.wfile.write(body)
+
+    def log_message(self, *args):
+        pass
+
+
+@pytest.fixture()
+def fake_whisper_server():
+    server = http.server.ThreadingHTTPServer(("127.0.0.1", 0), _FakeWhisperHandler)
+    thread = threading.Thread(target = server.serve_forever, daemon = True)
+    thread.start()
+    yield server.server_address[1]
+    server.shutdown()
+
+
+def test_transcribe_joins_segments_one_line(monkeypatch, fake_whisper_server):
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+    sidecar = GgmlSttSidecar()
+
+    def fake_load(model = None):
+        sidecar._port = fake_whisper_server
+        sidecar._model_id = ggml_module.resolve_ggml_model_id(model)
+
+    monkeypatch.setattr(sidecar, "load", fake_load)
+    result = sidecar.transcribe(b"RIFF", model = "small", language = "en", fast = True)
+    assert result["text"] == "Hello world. Second line."
+    assert result["language"] == "en"
+    assert result["model"] == "small"
+    assert result["duration"] == pytest.approx(1.0)
+
+
+def test_transcribe_maps_bad_payload_to_decode_error(monkeypatch, fake_whisper_server):
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+    monkeypatch.setattr(_FakeWhisperHandler, "response_text", None)
+    sidecar = GgmlSttSidecar()
+
+    def fake_load(model = None):
+        sidecar._port = fake_whisper_server
+        sidecar._model_id = ggml_module.resolve_ggml_model_id(model)
+
+    monkeypatch.setattr(sidecar, "load", fake_load)
+    from core.inference.stt_sidecar import SttAudioDecodeError
+
+    with pytest.raises(SttAudioDecodeError):
+        sidecar.transcribe(b"RIFF", model = "small")
+
+
+def test_beam_size_matches_fast_flag(monkeypatch, fake_whisper_server):
+    _available(monkeypatch)
+    monkeypatch.setattr(ggml_module, "_cached_model_path", lambda model_id: "/tmp/ggml.bin")
+    seen: list[bytes] = []
+
+    orig_post = _FakeWhisperHandler.do_POST
+
+    def capture_post(handler):
+        length = int(handler.headers.get("Content-Length", "0"))
+        body = handler.rfile.read(length)
+        seen.append(body)
+        payload = json.dumps({"text": "ok"}).encode()
+        handler.send_response(200)
+        handler.send_header("Content-Type", "application/json")
+        handler.send_header("Content-Length", str(len(payload)))
+        handler.end_headers()
+        handler.wfile.write(payload)
+
+    monkeypatch.setattr(_FakeWhisperHandler, "do_POST", capture_post)
+    try:
+        sidecar = GgmlSttSidecar()
+
+        def fake_load(model = None):
+            sidecar._port = fake_whisper_server
+            sidecar._model_id = ggml_module.resolve_ggml_model_id(model)
+
+        monkeypatch.setattr(sidecar, "load", fake_load)
+        sidecar.transcribe(b"RIFF", model = "small", fast = True)
+        sidecar.transcribe(b"RIFF", model = "small", fast = False)
+    finally:
+        _FakeWhisperHandler.do_POST = orig_post
+    assert b'name="beam_size"\r\n\r\n1' in seen[0]
+    assert b'name="beam_size"\r\n\r\n5' in seen[1]
+    # Dictation defaults to deterministic decoding.
+    assert b'name="temperature"\r\n\r\n0.0' in seen[0]
+
+
+def test_download_rejects_custom_ids():
+    with pytest.raises(SttModelIdError):
+        ggml_module.start_model_download("owner/model")
+
+
+def test_download_status_idle_shape():
+    status = ggml_module.download_status()
+    assert set(status) >= {"downloading", "model", "error"}
diff --git a/studio/backend/tests/test_stt_review_fixes.py b/studio/backend/tests/test_stt_review_fixes.py
new file mode 100644
index 0000000000..e4495506a3
--- /dev/null
+++ b/studio/backend/tests/test_stt_review_fixes.py
@@ -0,0 +1,219 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Regressions for a fresh review pass on the local STT dictation feature:
+
+1. Curated GGUF dictation repos (unslothai/whisper-*-GGUF) must be hidden from
+   chat pickers, not just their Transformers safetensors companions.
+2. The GGUF sidecar's loaded_model/device status accessors must be lock-free so
+   they never block behind an in-flight transcription (which holds self._lock).
+3. A "gguf" unload on a host without whisper-server must target the Transformers
+   fallback that actually served it, and unload-all must attempt both backends
+   even if one raises.
+4. free_stt_model_for_training must free the GGUF sidecar even when the
+   Transformers unload raises (independent exception boundaries).
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+import threading
+from pathlib import Path
+
+import pytest
+from fastapi import HTTPException
+
+_BACKEND_ROOT = Path(__file__).resolve().parents[1]
+if str(_BACKEND_ROOT) not in sys.path:
+    sys.path.insert(0, str(_BACKEND_ROOT))
+
+
+# 1. Hidden-model GGUF companions ------------------------------------------------
+def test_curated_gguf_dictation_repos_are_hidden():
+    from utils.hidden_models import _HIDDEN_STT_REPO_IDS, is_hidden_model
+    for repo in (
+        "unslothai/whisper-tiny-GGUF",
+        "unslothai/whisper-base-GGUF",
+        "unslothai/whisper-small-GGUF",
+        "unslothai/whisper-large-v3-turbo-GGUF",
+        "unslothai/whisper-large-v3-GGUF",
+    ):
+        assert repo in _HIDDEN_STT_REPO_IDS
+        assert is_hidden_model(repo) is True
+        # Case-insensitive, matching how the cache stores the repo id.
+        assert is_hidden_model(repo.lower()) is True
+
+    # A same-prefix but genuinely different repo is NOT hidden.
+    assert is_hidden_model("unslothai/whisper-large-v3-GGUF-finetune") is False
+
+
+# 2. GGUF status accessors are lock-free ----------------------------------------
+def test_gguf_status_accessors_do_not_block_on_the_inference_lock():
+    from core.inference.stt_ggml_sidecar import GgmlSttSidecar
+
+    sidecar = GgmlSttSidecar()
+
+    class _AliveProc:
+        pid = 4321
+
+        def poll(self):
+            return None  # still running
+
+    sidecar._process = _AliveProc()
+    sidecar._model_id = "small"
+
+    holder_has_lock = threading.Event()
+    release = threading.Event()
+
+    def _hold_inference_lock():
+        # Mimic transcribe() holding self._lock across the whole HTTP call.
+        with sidecar._lock:
+            holder_has_lock.set()
+            release.wait(timeout = 5)
+
+    holder = threading.Thread(target = _hold_inference_lock)
+    holder.start()
+    assert holder_has_lock.wait(timeout = 5)
+
+    result: dict = {}
+
+    def _read_status():
+        result["model"] = sidecar.loaded_model
+        result["device"] = sidecar.device
+
+    reader = threading.Thread(target = _read_status)
+    reader.start()
+    reader.join(timeout = 2)
+    blocked = reader.is_alive()
+
+    release.set()
+    holder.join(timeout = 5)
+    reader.join(timeout = 5)
+
+    assert not blocked, "loaded_model/device blocked on self._lock (should be lock-free)"
+    assert result == {"model": "small", "device": "whisper.cpp"}
+
+
+def test_process_alive_snapshots_process_against_concurrent_unload():
+    # _process_alive() must read self._process exactly once. The lock-free
+    # readers (loaded_model/device) can run while unload() nulls self._process;
+    # the old `self._process is not None and self._process.poll() is None` read it
+    # twice, so a null landing between the two reads called None.poll(). A
+    # property that yields the live process on the first read and None afterwards
+    # reproduces that interleaving deterministically.
+    from core.inference.stt_ggml_sidecar import GgmlSttSidecar
+
+    class _AliveProc:
+        def poll(self):
+            return None  # still running
+
+    live = _AliveProc()
+    reads = {"n": 0}
+
+    class _RacingSidecar(GgmlSttSidecar):
+        @property
+        def _process(self):
+            reads["n"] += 1
+            return live if reads["n"] == 1 else None
+
+        @_process.setter
+        def _process(self, value):
+            pass  # __init__ assigns None; the property drives the read
+
+    sidecar = GgmlSttSidecar()
+    sidecar.__class__ = _RacingSidecar  # data descriptor wins over the instance attr
+
+    # Snapshot fix: exactly one read, no AttributeError from a second None read.
+    assert sidecar._process_alive() is True
+    assert reads["n"] == 1
+
+
+# 3. Unload resolves through the serving engine + attempts every backend ---------
+def test_gguf_unload_targets_transformers_fallback_without_whisper_server(monkeypatch):
+    import core.inference.stt_ggml_sidecar as ggml_module
+    import routes.inference as ri
+
+    monkeypatch.setattr(ggml_module, "is_available", lambda: False)  # no whisper-server
+
+    calls: list = []
+
+    class _Sidecar:
+        def __init__(self, name):
+            self.name = name
+
+        def unload(self):
+            calls.append(self.name)
+
+    monkeypatch.setattr(ri, "_stt_sidecar_for", lambda name: _Sidecar(name))
+
+    resp = asyncio.run(ri.stt_unload(engine = "gguf", current_subject = "tester"))
+    assert resp.status_code == 200
+    # gguf is served by the Transformers fallback here, so that is what unloads.
+    assert calls == ["transformers"]
+
+
+def test_unload_all_attempts_both_backends_even_when_one_fails(monkeypatch):
+    import routes.inference as ri
+
+    attempted: list = []
+
+    class _Sidecar:
+        def __init__(self, name):
+            self.name = name
+
+        def unload(self):
+            attempted.append(self.name)
+            if self.name == "transformers":
+                raise RuntimeError("boom")
+
+    monkeypatch.setattr(ri, "_stt_sidecar_for", lambda name: _Sidecar(name))
+
+    with pytest.raises(HTTPException) as excinfo:
+        asyncio.run(ri.stt_unload(engine = None, current_subject = "tester"))
+
+    assert excinfo.value.status_code == 500
+    # gguf is still attempted after the transformers unload raised.
+    assert attempted == ["transformers", "gguf"]
+
+
+# 4. free_stt_model_for_training isolates the two backends -----------------------
+def test_free_stt_frees_gguf_even_when_transformers_unload_raises(monkeypatch):
+    import routes.training_vram as tv
+
+    class _TransformersSidecar:
+        def is_loading(self):
+            return False
+
+        @property
+        def loaded_model(self):
+            return "whisper-small"
+
+        def unload(self):
+            raise RuntimeError("transformers unload failed")
+
+    class _GgmlSidecar:
+        def __init__(self):
+            self.unloaded = False
+
+        def is_loading(self):
+            return False
+
+        @property
+        def loaded_model(self):
+            return None if self.unloaded else "small"
+
+        def unload(self):
+            self.unloaded = True
+
+    ggml = _GgmlSidecar()
+    monkeypatch.setattr(
+        "core.inference.stt_sidecar.get_stt_sidecar", lambda: _TransformersSidecar()
+    )
+    monkeypatch.setattr("core.inference.stt_ggml_sidecar.get_ggml_stt_sidecar", lambda: ggml)
+
+    freed = tv.free_stt_model_for_training("test")
+
+    # The Transformers failure must not skip GGUF eviction.
+    assert ggml.unloaded is True
+    assert any("small" in entry for entry in freed)
diff --git a/studio/backend/tests/test_stt_review_fixes_2.py b/studio/backend/tests/test_stt_review_fixes_2.py
new file mode 100644
index 0000000000..130c43c956
--- /dev/null
+++ b/studio/backend/tests/test_stt_review_fixes_2.py
@@ -0,0 +1,332 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Regressions for the second review pass on the local STT dictation feature:
+
+1. scripts/build_whisper_cpp.sh must not rm -rf a whisper.cpp/src tree under a
+   custom Studio home unless Studio itself created it (ownership marker), the
+   same policy studio/setup.sh applies before its destructive replacements.
+2. _snapshot_is_complete must validate every shard of a sharded PyTorch
+   (pytorch_model.bin.index.json) checkpoint, like the safetensors path.
+3. _snapshot_is_complete must require tokenizer assets (tokenizer.json or
+   vocab.json + merges.txt); weights + config alone decode to blank text.
+4. Custom-repo downloads must pin the revision validated beforehand and
+   restrict snapshot_download to the model/tokenizer/config/preprocessor file
+   classes (TOCTOU + unbounded-download hardening).
+5. The GGML sidecar's readiness probe must not treat an arbitrary local HTTP
+   responder as whisper-server (mic audio would be posted to it), and the port
+   reservation must stay held until just before spawn.
+"""
+
+from __future__ import annotations
+
+import http.server
+import json
+import os
+import socket
+import stat
+import subprocess
+import sys
+import threading
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+_BACKEND_ROOT = Path(__file__).resolve().parents[1]
+if str(_BACKEND_ROOT) not in sys.path:
+    sys.path.insert(0, str(_BACKEND_ROOT))
+
+import core.inference.stt_ggml_sidecar as ggml_module
+import core.inference.stt_sidecar as stt_sidecar_module
+from core.inference.stt_ggml_sidecar import GgmlSttSidecar, SttEngineUnavailableError
+from core.inference.stt_sidecar import validate_remote_model
+
+_BUILD_SCRIPT = _BACKEND_ROOT.parents[1] / "scripts" / "build_whisper_cpp.sh"
+
+
+# 1. build_whisper_cpp.sh ownership gate ----------------------------------------
+
+
+def _stub_tools(tmp_path: Path) -> dict:
+    """PATH with git/cmake stubs so the script never reaches a real build."""
+    bin_dir = tmp_path / "stub-bin"
+    bin_dir.mkdir(exist_ok = True)
+    for tool in ("git", "cmake"):
+        stub = bin_dir / tool
+        stub.write_text("#!/bin/sh\necho stub-%s-invoked >&2\nexit 1\n" % tool)
+        stub.chmod(stub.stat().st_mode | stat.S_IEXEC)
+    env = dict(os.environ)
+    env["PATH"] = f"{bin_dir}:{env['PATH']}"
+    return env
+
+
+def _run_build_script(env: dict) -> subprocess.CompletedProcess:
+    return subprocess.run(
+        ["sh", str(_BUILD_SCRIPT)],
+        env = env,
+        capture_output = True,
+        text = True,
+        timeout = 60,
+    )
+
+
+def test_build_script_refuses_unowned_dir_in_custom_studio_home(tmp_path):
+    home = tmp_path / "studio-home"
+    src = home / "whisper.cpp" / "src"
+    src.mkdir(parents = True)
+    user_file = src / "user-data.txt"
+    user_file.write_text("precious")
+
+    env = _stub_tools(tmp_path)
+    env["UNSLOTH_STUDIO_HOME"] = str(home)
+    result = _run_build_script(env)
+
+    assert result.returncode != 0
+    assert "not marked as an Unsloth-owned" in result.stderr
+    # The unowned tree, and the user's file inside it, survived untouched.
+    assert user_file.read_text() == "precious"
+
+
+def test_build_script_proceeds_when_marker_present(tmp_path):
+    home = tmp_path / "studio-home"
+    install = home / "whisper.cpp"
+    (install / "src").mkdir(parents = True)
+    (install / ".unsloth-studio-owned").write_text("")
+
+    env = _stub_tools(tmp_path)
+    env["UNSLOTH_STUDIO_HOME"] = str(home)
+    result = _run_build_script(env)
+
+    # Past the guard: it fails later at the stubbed git clone, not the gate.
+    assert "not marked as an Unsloth-owned" not in result.stderr
+    assert "stub-git-invoked" in result.stderr
+
+
+def test_build_script_marks_fresh_custom_install_dir(tmp_path):
+    home = tmp_path / "studio-home"
+    home.mkdir()
+
+    env = _stub_tools(tmp_path)
+    env["UNSLOTH_STUDIO_HOME"] = str(home)
+    _run_build_script(env)
+
+    # A directory the script creates is marked so re-runs stay allowed.
+    assert (home / "whisper.cpp" / ".unsloth-studio-owned").is_file()
+
+
+def test_build_script_keeps_legacy_home_behavior(tmp_path):
+    fake_home = tmp_path / "user-home"
+    src = fake_home / ".unsloth" / "whisper.cpp" / "src"
+    src.mkdir(parents = True)
+
+    env = _stub_tools(tmp_path)
+    env.pop("UNSLOTH_STUDIO_HOME", None)
+    env.pop("STUDIO_HOME", None)
+    env["HOME"] = str(fake_home)
+    result = _run_build_script(env)
+
+    # The legacy managed dir is always Studio-owned; no gate, straight to git.
+    assert "not marked as an Unsloth-owned" not in result.stderr
+    assert "stub-git-invoked" in result.stderr
+
+
+# 2 + 3. _snapshot_is_complete --------------------------------------------------
+
+
+def _base_snapshot(tmp_path: Path) -> Path:
+    snap = tmp_path / "snap"
+    snap.mkdir()
+    (snap / "config.json").write_text("{}")
+    (snap / "preprocessor_config.json").write_text("{}")
+    (snap / "tokenizer.json").write_text("{}")
+    return snap
+
+
+def test_sharded_pytorch_snapshot_requires_every_shard(tmp_path):
+    snap = _base_snapshot(tmp_path)
+    index = {
+        "weight_map": {
+            "a": "pytorch_model-00001-of-00002.bin",
+            "b": "pytorch_model-00002-of-00002.bin",
+        }
+    }
+    (snap / "pytorch_model.bin.index.json").write_text(json.dumps(index))
+    (snap / "pytorch_model-00001-of-00002.bin").write_bytes(b"w" * 8)
+
+    # One missing .bin shard must read as incomplete, like the safetensors path.
+    assert stt_sidecar_module._snapshot_is_complete(snap) is False
+
+    (snap / "pytorch_model-00002-of-00002.bin").write_bytes(b"w" * 8)
+    assert stt_sidecar_module._snapshot_is_complete(snap) is True
+
+
+def test_snapshot_without_tokenizer_assets_is_incomplete(tmp_path):
+    snap = _base_snapshot(tmp_path)
+    (snap / "model.safetensors").write_bytes(b"w" * 8)
+    assert stt_sidecar_module._snapshot_is_complete(snap) is True
+
+    # Weights + config but no tokenizer decodes to blank text; not complete.
+    (snap / "tokenizer.json").unlink()
+    assert stt_sidecar_module._snapshot_is_complete(snap) is False
+
+    # The slow vocab.json + merges.txt pair is an accepted alternative.
+    (snap / "vocab.json").write_text("{}")
+    assert stt_sidecar_module._snapshot_is_complete(snap) is False
+    (snap / "merges.txt").write_text("")
+    assert stt_sidecar_module._snapshot_is_complete(snap) is True
+
+
+# 4. Revision pinning and allow_patterns ----------------------------------------
+
+
+def test_validate_remote_model_returns_the_validated_revision(monkeypatch):
+    revision = "a" * 40
+
+    class _FakeApi:
+        def __init__(self, token = None):
+            pass
+
+        def model_info(
+            self,
+            repo,
+            expand = None,
+            timeout = None,
+        ):
+            return SimpleNamespace(config = {"model_type": "whisper"}, sha = revision)
+
+    import huggingface_hub
+
+    monkeypatch.setattr(huggingface_hub, "HfApi", _FakeApi)
+    result = validate_remote_model("someone/custom-whisper")
+    assert result["revision"] == revision
+
+
+def test_download_pins_revision_and_limits_patterns(monkeypatch):
+    captured = {}
+    validated_revision = "a" * 40
+    head_revision = "b" * 40
+
+    def fake_snapshot_download(**kwargs):
+        captured.update(kwargs)
+        return "/cached"
+
+    class _FakeApi:
+        def __init__(self, token = None):
+            pass
+
+        def model_info(
+            self,
+            repo,
+            revision = None,
+            files_metadata = None,
+            timeout = None,
+        ):
+            names = (
+                "config.json",
+                "preprocessor_config.json",
+                "tokenizer.json",
+                "model.safetensors",
+            )
+            siblings = [
+                SimpleNamespace(rfilename = name, size = 10, blob_id = name, lfs = None) for name in names
+            ]
+            return SimpleNamespace(siblings = siblings, sha = head_revision)
+
+    import huggingface_hub
+
+    monkeypatch.setattr(huggingface_hub, "HfApi", _FakeApi)
+    monkeypatch.setattr(huggingface_hub, "snapshot_download", fake_snapshot_download)
+
+    state = stt_sidecar_module._SnapshotDownloadState()
+    # The revision resolved at validation time wins over the current head.
+    state._run("someone/custom-whisper", None, revision = validated_revision)
+    assert captured["revision"] == validated_revision
+    patterns = captured["allow_patterns"]
+    assert "model.safetensors" in patterns and "tokenizer.json" in patterns
+    # No wildcard that would admit arbitrary repo contents.
+    assert "*" not in patterns
+
+    # Without a validated revision (curated repos), pin to the metadata head.
+    captured.clear()
+    state._run("someone/custom-whisper", None)
+    assert captured["revision"] == head_revision
+    assert captured["allow_patterns"]
+
+
+# 5. GGML readiness must identify whisper-server --------------------------------
+
+
+class _CannedHandler(http.server.BaseHTTPRequestHandler):
+    body = b""
+
+    def do_GET(self):  # noqa: N802
+        payload = type(self).body
+        self.send_response(200)
+        self.send_header("Content-Length", str(len(payload)))
+        self.end_headers()
+        self.wfile.write(payload)
+
+    def log_message(self, *args):
+        pass
+
+
+def _serve(body: bytes):
+    handler = type("Handler", (_CannedHandler,), {"body": body})
+    server = http.server.HTTPServer(("127.0.0.1", 0), handler)
+    thread = threading.Thread(target = server.serve_forever, daemon = True)
+    thread.start()
+    return server, server.server_address[1]
+
+
+def _fake_alive_process():
+    return SimpleNamespace(poll = lambda: None, pid = 999999)
+
+
+def test_wait_for_server_rejects_a_foreign_http_responder(monkeypatch):
+    server, port = _serve(b"<html>hello from some other local app</html>")
+    try:
+        monkeypatch.setattr(ggml_module, "_SERVER_START_TIMEOUT_SECONDS", 1.0)
+        with pytest.raises(SttEngineUnavailableError, match = "did not start in time"):
+            GgmlSttSidecar._wait_for_server(_fake_alive_process(), port)
+    finally:
+        server.shutdown()
+
+
+def test_wait_for_server_accepts_the_whisper_server_page(monkeypatch):
+    server, port = _serve(b"<html><title>Whisper.cpp Server</title></html>")
+    try:
+        monkeypatch.setattr(ggml_module, "_SERVER_START_TIMEOUT_SECONDS", 5.0)
+        GgmlSttSidecar._wait_for_server(_fake_alive_process(), port)
+    finally:
+        server.shutdown()
+
+
+def test_probe_requires_the_managed_child_to_be_alive():
+    server, port = _serve(b"whisper")
+    try:
+        dead = SimpleNamespace(poll = lambda: 0, pid = 999999)
+        assert GgmlSttSidecar._probe_is_whisper_server(dead, port) is False
+        assert GgmlSttSidecar._probe_is_whisper_server(_fake_alive_process(), port) is True
+    finally:
+        server.shutdown()
+
+
+def test_port_reservation_is_held_until_released():
+    reservation, port = GgmlSttSidecar._reserve_free_port()
+    try:
+        probe = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+        try:
+            with pytest.raises(OSError):
+                probe.bind(("127.0.0.1", port))
+        finally:
+            probe.close()
+    finally:
+        reservation.close()
+    # Released right before spawn: the port becomes bindable for the child.
+    child = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+    child.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+    try:
+        child.bind(("127.0.0.1", port))
+    finally:
+        child.close()
diff --git a/studio/backend/tests/test_stt_sidecar.py b/studio/backend/tests/test_stt_sidecar.py
new file mode 100644
index 0000000000..3f78845ac7
--- /dev/null
+++ b/studio/backend/tests/test_stt_sidecar.py
@@ -0,0 +1,1262 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import gc
+import io
+import json
+import sys
+import threading
+import time
+import wave
+import weakref
+from pathlib import Path
+from types import SimpleNamespace
+
+import numpy as np
+import pytest
+
+import core.inference.stt_sidecar as stt_sidecar_module
+from core.inference.stt_sidecar import (
+    DEFAULT_STT_MODEL,
+    STT_MODELS,
+    SttAudioDecodeError,
+    SttAudioTooLongError,
+    SttLanguageError,
+    SttLoadCancelledError,
+    SttModelCompatibilityError,
+    SttModelIdError,
+    SttModelNotDownloadedError,
+    SttUnavailableError,
+    WhisperSttSidecar,
+    normalize_whisper_language,
+    resolve_model_id,
+    resolve_model_repo,
+    validate_remote_model,
+)
+
+_REAL_DECODE_AUDIO_BOUNDED = stt_sidecar_module._decode_audio_bounded
+_REAL_ENSURE_STT_AVAILABLE = stt_sidecar_module.ensure_stt_available
+_REAL_SNAPSHOT_IS_COMPLETE = stt_sidecar_module._snapshot_is_complete
+_REAL_FIND_COMPLETE_CACHED_SNAPSHOT = stt_sidecar_module._find_complete_cached_snapshot
+
+
+@pytest.fixture(autouse = True)
+def stub_audio_decoder(monkeypatch):
+    """Unit tests below exercise orchestration, not PyAV container parsing."""
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_decode_audio_bounded",
+        lambda _audio: np.zeros(8000, dtype = np.float32),
+    )
+    monkeypatch.setattr(
+        "huggingface_hub.snapshot_download",
+        lambda **_kwargs: "/cached/model",
+    )
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        lambda _model: Path("/cached/model"),
+    )
+    # The stubbed snapshot path holds no files; snapshot-integrity tests
+    # restore the real check.
+    monkeypatch.setattr(stt_sidecar_module, "_snapshot_is_complete", lambda _snapshot: True)
+    # transcribe() gates on the runtime up front; treat it as present so these
+    # orchestration tests run without PyTorch/Transformers/PyAV installed.
+    # The runtime-specific tests restore the real check.
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", lambda: None)
+
+
+class _CaptureInference:
+    """Stand-in for the model inference step; records how it was called."""
+
+    def __init__(
+        self,
+        text = "hello",
+        mutate = None,
+    ) -> None:
+        self.text = text
+        self.mutate = mutate
+        self.generate_kwargs = None
+
+    def __call__(self, model_id, decoded, generate_kwargs):
+        self.generate_kwargs = generate_kwargs
+        if self.mutate is not None:
+            self.mutate()
+        return self.text
+
+
+def test_five_curated_whisper_models_are_offered():
+    assert STT_MODELS == {
+        "tiny": "unsloth/whisper-tiny",
+        "base": "unsloth/whisper-base",
+        "small": "unsloth/whisper-small",
+        "large-v3-turbo": "unsloth/whisper-large-v3-turbo",
+        "large-v3": "unsloth/whisper-large-v3",
+    }
+    assert all(repo.startswith(("unsloth/", "unslothai/")) for repo in STT_MODELS.values())
+    assert DEFAULT_STT_MODEL in STT_MODELS
+
+
+def test_av_is_required_for_stt_availability(monkeypatch):
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", _REAL_ENSURE_STT_AVAILABLE)
+    monkeypatch.setitem(sys.modules, "torch", SimpleNamespace())
+    monkeypatch.setitem(sys.modules, "transformers", SimpleNamespace())
+    monkeypatch.setitem(sys.modules, "av", None)
+
+    assert stt_sidecar_module.is_available() is False
+
+
+def test_transformers_is_required_for_stt_availability(monkeypatch):
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", _REAL_ENSURE_STT_AVAILABLE)
+    monkeypatch.setitem(sys.modules, "torch", SimpleNamespace())
+    monkeypatch.setitem(sys.modules, "av", SimpleNamespace())
+    monkeypatch.setitem(sys.modules, "transformers", None)
+
+    assert stt_sidecar_module.is_available() is False
+
+
+@pytest.mark.parametrize("missing", ["transformers", "av"])
+def test_load_rejects_an_incomplete_stt_runtime(monkeypatch, missing):
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", _REAL_ENSURE_STT_AVAILABLE)
+    for module in ("torch", "transformers", "av"):
+        monkeypatch.setitem(sys.modules, module, SimpleNamespace())
+    monkeypatch.setitem(sys.modules, missing, None)
+    monkeypatch.setattr(
+        sidecar,
+        "_ensure_model_downloaded",
+        lambda _model: pytest.fail("runtime must be checked before the model cache"),
+    )
+
+    with pytest.raises(SttUnavailableError, match = "needs PyTorch, Transformers, and PyAV"):
+        sidecar.load("small")
+
+
+def test_model_id_accepts_defaults_and_custom_hub_repositories():
+    assert resolve_model_id("tiny") == "tiny"
+    assert resolve_model_id(None) == DEFAULT_STT_MODEL
+    assert resolve_model_id("large-v3") == "large-v3"
+    assert resolve_model_id("openai/whisper-medium") == "openai/whisper-medium"
+    assert resolve_model_repo("tiny") == "unsloth/whisper-tiny"
+    assert resolve_model_repo("openai/whisper-medium") == "openai/whisper-medium"
+
+
+@pytest.mark.parametrize("model", ["tiny-ish", "owner/model/extra", "../model", "owner/"])
+def test_invalid_custom_model_id_is_rejected(model):
+    with pytest.raises(SttModelIdError, match = "owner/model"):
+        resolve_model_id(model)
+
+
+def test_remote_custom_model_validation_requires_whisper_config(monkeypatch):
+    calls = []
+
+    class FakeApi:
+        def __init__(self, token):
+            calls.append(("token", token))
+
+        def model_info(self, repo, **kwargs):
+            calls.append(("model_info", repo, kwargs))
+            return SimpleNamespace(
+                sha = "a" * 40,
+                config = {
+                    "model_type": "whisper",
+                    "architectures": ["WhisperForConditionalGeneration"],
+                },
+            )
+
+    monkeypatch.setattr("huggingface_hub.HfApi", FakeApi)
+
+    result = validate_remote_model("owner/custom-whisper", "hf_private")
+
+    assert result == {
+        "model": "owner/custom-whisper",
+        "repo": "owner/custom-whisper",
+        "revision": "a" * 40,
+    }
+    assert calls == [
+        ("token", "hf_private"),
+        (
+            "model_info",
+            "owner/custom-whisper",
+            {"expand": ["config", "sha"], "timeout": 10},
+        ),
+    ]
+
+
+def test_remote_custom_model_validation_rejects_non_whisper(monkeypatch):
+    class FakeApi:
+        def __init__(self, token):
+            assert token is False
+
+        def model_info(self, _repo, **_kwargs):
+            return SimpleNamespace(
+                config = {
+                    "model_type": "llama",
+                    "architectures": ["LlamaForCausalLM"],
+                }
+            )
+
+    monkeypatch.setattr("huggingface_hub.HfApi", FakeApi)
+
+    with pytest.raises(SttModelCompatibilityError, match = "not a compatible"):
+        validate_remote_model("owner/chat-model")
+
+
+def test_remote_custom_model_validation_requires_an_immutable_sha(monkeypatch):
+    class FakeApi:
+        def __init__(self, token):
+            pass
+
+        def model_info(self, _repo, **_kwargs):
+            return SimpleNamespace(sha = None, config = {"model_type": "whisper"})
+
+    monkeypatch.setattr("huggingface_hub.HfApi", FakeApi)
+
+    with pytest.raises(SttModelCompatibilityError, match = "immutable revision"):
+        validate_remote_model("owner/custom-whisper")
+
+
+def test_fast_transcription_uses_greedy_decoding(monkeypatch):
+    sidecar = WhisperSttSidecar()
+    infer = _CaptureInference()
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", infer)
+
+    result = sidecar.transcribe(b"encoded audio", language = "en", fast = True)
+
+    assert result["text"] == "hello"
+    assert result["duration"] == 0.5
+    assert result["model"] == DEFAULT_STT_MODEL
+    assert infer.generate_kwargs == {
+        "task": "transcribe",
+        "condition_on_prev_tokens": False,
+        "num_beams": 1,
+        "language": "en",
+    }
+
+
+def test_accurate_transcription_keeps_beam_search_default(monkeypatch):
+    sidecar = WhisperSttSidecar()
+    infer = _CaptureInference()
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", infer)
+
+    sidecar.transcribe(b"encoded audio")
+
+    assert infer.generate_kwargs == {
+        "task": "transcribe",
+        "condition_on_prev_tokens": False,
+        "num_beams": 5,
+    }
+
+
+@pytest.mark.parametrize(
+    ("language", "expected"),
+    [
+        (None, None),
+        ("auto", None),
+        ("en-US", "en"),
+        ("en-GB", "en"),
+        ("zh-CN", "zh"),
+        ("ja-JP", "ja"),
+        ("ko-KR", "ko"),
+        ("es-ES", "es"),
+        ("fr-FR", "fr"),
+        ("de-DE", "de"),
+        ("it-IT", "it"),
+        ("pt_BR", "pt"),
+        ("ru-RU", "ru"),
+        ("hi-IN", "hi"),
+        ("ar-SA", "ar"),
+        ("iw-IL", "he"),
+        ("nb-NO", "no"),
+    ],
+)
+def test_normalize_whisper_language_accepts_bcp47(language, expected):
+    assert normalize_whisper_language(language) == expected
+
+
+def test_transcription_normalizes_region_qualified_language(monkeypatch):
+    sidecar = WhisperSttSidecar()
+    infer = _CaptureInference()
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", infer)
+
+    sidecar.transcribe(b"encoded audio", language = "fr-FR")
+
+    assert infer.generate_kwargs["language"] == "fr"
+
+
+def test_english_only_model_rejects_non_english_before_decode(monkeypatch, tmp_path):
+    (tmp_path / "config.json").write_text('{"model_type": "whisper"}')
+    (tmp_path / "generation_config.json").write_text('{"is_multilingual": false}')
+    sidecar = WhisperSttSidecar()
+
+    def should_not_decode(_audio):
+        pytest.fail("English-only language mismatch must be rejected before decode")
+
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        lambda _model: tmp_path,
+    )
+    monkeypatch.setattr(stt_sidecar_module, "_decode_audio_bounded", should_not_decode)
+
+    with pytest.raises(SttLanguageError, match = "English-only"):
+        sidecar.transcribe(
+            b"encoded audio",
+            model = "owner/whisper-small.en",
+            language = "fr-FR",
+        )
+
+
+def test_english_only_model_omits_forbidden_generation_controls(monkeypatch):
+    calls = []
+
+    class FakeTensor:
+        def to(self, *_args):
+            return self
+
+    class FakeProcessor:
+        def __call__(self, *_args, **_kwargs):
+            return SimpleNamespace(input_features = FakeTensor())
+
+        def batch_decode(self, *_args, **_kwargs):
+            return ["hello"]
+
+    class FakeModel:
+        dtype = None
+        device = "cpu"
+        generation_config = SimpleNamespace(is_multilingual = False)
+
+        def generate(self, _features, **kwargs):
+            calls.append(kwargs)
+            return [[1]]
+
+    class NoGrad:
+        def __enter__(self):
+            return None
+
+        def __exit__(self, *_args):
+            return False
+
+    monkeypatch.setitem(sys.modules, "torch", SimpleNamespace(no_grad = NoGrad))
+    sidecar = WhisperSttSidecar()
+    monkeypatch.setattr(sidecar, "load", lambda _model: (FakeModel(), FakeProcessor()))
+
+    text = sidecar._transcribe_decoded(
+        "owner/whisper-small.en",
+        np.zeros(160, dtype = np.float32),
+        {
+            "task": "transcribe",
+            "language": "en",
+            "condition_on_prev_tokens": False,
+            "num_beams": 1,
+        },
+    )
+
+    assert text == "hello"
+    assert calls == [{"condition_on_prev_tokens": False, "num_beams": 1}]
+
+
+def test_unknown_language_is_rejected_before_decode_or_model_load(monkeypatch):
+    sidecar = WhisperSttSidecar()
+
+    def should_not_run(*_args, **_kwargs):
+        pytest.fail("unknown language must be rejected before expensive work")
+
+    monkeypatch.setattr(stt_sidecar_module, "_known_whisper_languages", lambda: frozenset({"en"}))
+    monkeypatch.setattr(stt_sidecar_module, "_decode_audio_bounded", should_not_run)
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", should_not_run)
+
+    with pytest.raises(SttLanguageError, match = "is not supported"):
+        sidecar.transcribe(b"encoded audio", language = "xx-YY")
+
+
+def test_unknown_language_is_not_reported_as_bad_audio(monkeypatch):
+    sidecar = WhisperSttSidecar()
+    infer = _CaptureInference()
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", infer)
+    monkeypatch.setattr(stt_sidecar_module, "_known_whisper_languages", lambda: frozenset({"en"}))
+
+    with pytest.raises(SttLanguageError, match = "is not supported"):
+        sidecar.transcribe(b"encoded audio", language = "xx-YY")
+
+
+def test_transcription_result_keeps_requested_model_id_during_switch(monkeypatch):
+    sidecar = WhisperSttSidecar()
+
+    # Simulate another request changing the mutable resident-model state after
+    # this request pinned its own model id.
+    infer = _CaptureInference(mutate = lambda: setattr(sidecar, "_model_id", "large-v3"))
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", infer)
+
+    result = sidecar.transcribe(b"encoded audio", model = "small")
+
+    assert result["model"] == "small"
+
+
+def test_inference_failure_propagates(monkeypatch):
+    sidecar = WhisperSttSidecar()
+
+    def boom(*_args, **_kwargs):
+        raise RuntimeError("inference failed")
+
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", boom)
+
+    with pytest.raises(RuntimeError, match = "inference failed"):
+        sidecar.transcribe(b"encoded audio")
+
+
+class _FakeModel:
+    def to(self, *_args, **_kwargs):
+        return self
+
+    def eval(self):
+        return self
+
+
+class _FakeTimer:
+    def __init__(
+        self,
+        interval,
+        function,
+        args = (),
+        kwargs = None,
+    ):
+        self.interval = interval
+        self.function = function
+        self.args = args
+        self.kwargs = kwargs or {}
+        self.cancelled = False
+        self.daemon = False
+        self.started = False
+
+    def start(self):
+        self.started = True
+
+    def cancel(self):
+        self.cancelled = True
+
+    def fire(self):
+        self.function(*self.args, **self.kwargs)
+
+
+def _install_fake_torch(monkeypatch):
+    fake_torch = SimpleNamespace(
+        float16 = "float16",
+        float32 = "float32",
+        device = lambda value: value,
+        cuda = SimpleNamespace(is_available = lambda: False),
+        backends = SimpleNamespace(mps = SimpleNamespace(is_available = lambda: False)),
+    )
+    monkeypatch.setitem(sys.modules, "torch", fake_torch)
+    monkeypatch.setitem(sys.modules, "av", SimpleNamespace())
+    return fake_torch
+
+
+def test_load_uses_model_hub_cache_without_implicit_download(monkeypatch):
+    calls = []
+    _install_fake_torch(monkeypatch)
+
+    class FakeWhisperForConditionalGeneration:
+        @classmethod
+        def from_pretrained(cls, repo, **kwargs):
+            calls.append(("model", repo, kwargs))
+            return _FakeModel()
+
+    class FakeWhisperProcessor:
+        @classmethod
+        def from_pretrained(cls, repo, **kwargs):
+            calls.append(("processor", repo, kwargs))
+            return object()
+
+    monkeypatch.setitem(
+        sys.modules,
+        "transformers",
+        SimpleNamespace(
+            WhisperForConditionalGeneration = FakeWhisperForConditionalGeneration,
+            WhisperProcessor = FakeWhisperProcessor,
+        ),
+    )
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("cpu", "float32"))
+
+    WhisperSttSidecar(keep_alive_seconds = 0).load("small")
+
+    assert {(kind, repo) for kind, repo, _ in calls} == {
+        ("processor", "/cached/model"),
+        ("model", "/cached/model"),
+    }
+    # Never fetch weights implicitly; the Model Hub owns downloads.
+    assert all(kwargs.get("local_files_only") is True for _, _, kwargs in calls)
+
+
+def test_model_cache_preflight_uses_shared_offline_resolver(monkeypatch):
+    seen = []
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        lambda model: seen.append(model) or Path("/cached/model"),
+    )
+
+    WhisperSttSidecar(keep_alive_seconds = 0)._ensure_model_downloaded("small")
+
+    assert seen == ["small"]
+
+
+def test_model_cache_preflight_reports_missing_snapshot(monkeypatch):
+    monkeypatch.setattr(stt_sidecar_module, "_find_complete_cached_snapshot", lambda _model: None)
+
+    with pytest.raises(SttModelNotDownloadedError, match = "not downloaded"):
+        WhisperSttSidecar(keep_alive_seconds = 0)._ensure_model_downloaded("large-v3")
+
+
+def test_load_reports_model_hub_cache_miss(monkeypatch):
+    _install_fake_torch(monkeypatch)
+
+    class LocalEntryNotFoundError(RuntimeError):
+        pass
+
+    class MissingWhisperProcessor:
+        @classmethod
+        def from_pretrained(cls, *_args, **_kwargs):
+            raise LocalEntryNotFoundError("not cached")
+
+    monkeypatch.setitem(
+        sys.modules,
+        "transformers",
+        SimpleNamespace(
+            WhisperForConditionalGeneration = object,
+            WhisperProcessor = MissingWhisperProcessor,
+        ),
+    )
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("cpu", "float32"))
+
+    with pytest.raises(SttModelNotDownloadedError, match = "not downloaded"):
+        WhisperSttSidecar(keep_alive_seconds = 0).load("large-v3")
+
+
+def test_unavailable_runtime_is_rejected_before_audio_decode(monkeypatch):
+    sidecar = WhisperSttSidecar()
+
+    def unavailable() -> None:
+        raise SttUnavailableError("needs PyTorch, Transformers, and PyAV")
+
+    def should_not_decode(_audio):
+        pytest.fail("runtime must be checked before audio decode")
+
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", unavailable)
+    monkeypatch.setattr(stt_sidecar_module, "_decode_audio_bounded", should_not_decode)
+
+    with pytest.raises(SttUnavailableError, match = "needs PyTorch"):
+        sidecar.transcribe(b"encoded audio", model = "small")
+
+
+def test_missing_model_is_rejected_before_audio_decode(monkeypatch):
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+
+    def missing(_model_id):
+        raise SttModelNotDownloadedError("not downloaded")
+
+    def should_not_decode(_audio):
+        pytest.fail("missing models must be rejected before audio decode")
+
+    monkeypatch.setattr(sidecar, "_ensure_model_downloaded", missing, raising = False)
+    monkeypatch.setattr(stt_sidecar_module, "_decode_audio_bounded", should_not_decode)
+
+    with pytest.raises(SttModelNotDownloadedError, match = "not downloaded"):
+        sidecar.transcribe(b"encoded audio", model = "large-v3")
+
+
+def test_missing_model_switch_keeps_resident_model(monkeypatch):
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    resident = object()
+    sidecar._engine = resident
+    sidecar._model_id = "small"
+    sidecar._device = "cpu"
+
+    def missing(_model_id):
+        raise SttModelNotDownloadedError("not downloaded")
+
+    monkeypatch.setattr(sidecar, "_ensure_model_downloaded", missing, raising = False)
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", lambda: None)
+    monkeypatch.setattr(
+        sidecar,
+        "_build_model",
+        lambda *_args: pytest.fail("cache miss must be detected before model replacement"),
+    )
+    _install_fake_torch(monkeypatch)
+
+    with pytest.raises(SttModelNotDownloadedError, match = "not downloaded"):
+        sidecar.load("large-v3")
+
+    assert sidecar._engine is resident
+    assert sidecar.loaded_model == "small"
+
+
+def test_incompatible_custom_model_switch_keeps_resident_model(monkeypatch, tmp_path):
+    (tmp_path / "config.json").write_text(
+        '{"model_type": "llama", "architectures": ["LlamaForCausalLM"]}'
+    )
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    resident = (object(), object())
+    sidecar._engine = resident
+    sidecar._model_id = "small"
+    sidecar._device = "cpu"
+    _install_fake_torch(monkeypatch)
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        lambda _model: tmp_path,
+    )
+
+    with pytest.raises(SttModelCompatibilityError, match = "not a compatible"):
+        sidecar.load("owner/chat-model")
+
+    assert sidecar._engine is resident
+    assert sidecar.loaded_model == "small"
+
+
+def test_loaded_model_stays_warm_until_idle_timer_fires(monkeypatch):
+    timers = []
+    _install_fake_torch(monkeypatch)
+
+    def make_timer(*args, **kwargs):
+        timer = _FakeTimer(*args, **kwargs)
+        timers.append(timer)
+        return timer
+
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 300)
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", lambda: None)
+    monkeypatch.setattr(stt_sidecar_module.threading, "Timer", make_timer)
+    monkeypatch.setattr(sidecar, "_build_model", lambda *_args: (object(), object()))
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("cpu", "float32"))
+
+    sidecar.load("small")
+
+    assert sidecar.loaded_model == "small"
+    assert timers[-1].interval == 300
+    assert timers[-1].started
+
+    timers[-1].fire()
+
+    assert sidecar.loaded_model is None
+
+
+def test_reusing_loaded_model_refreshes_idle_timer(monkeypatch):
+    timers = []
+    _install_fake_torch(monkeypatch)
+
+    def make_timer(*args, **kwargs):
+        timer = _FakeTimer(*args, **kwargs)
+        timers.append(timer)
+        return timer
+
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 300)
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", lambda: None)
+    monkeypatch.setattr(stt_sidecar_module.threading, "Timer", make_timer)
+    monkeypatch.setattr(sidecar, "_build_model", lambda *_args: (object(), object()))
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("cpu", "float32"))
+
+    sidecar.load("small")
+    first = timers[-1]
+    sidecar.load("small")
+
+    assert first.cancelled
+    assert timers[-1] is not first
+
+    first.fire()
+
+    assert sidecar.loaded_model == "small"
+
+
+def test_unload_waits_for_inflight_transcription(monkeypatch):
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    started = threading.Event()
+    release = threading.Event()
+
+    def transcribe(*_args):
+        started.set()
+        assert release.wait(timeout = 2)
+        return "hello"
+
+    monkeypatch.setattr(sidecar, "_transcribe_decoded", transcribe)
+    transcribe_thread = threading.Thread(target = lambda: sidecar.transcribe(b"audio"))
+    transcribe_thread.start()
+    assert started.wait(timeout = 2)
+
+    unload_thread = threading.Thread(target = sidecar.unload)
+    unload_thread.start()
+    time.sleep(0.02)
+    assert unload_thread.is_alive()
+
+    release.set()
+    transcribe_thread.join(timeout = 2)
+    unload_thread.join(timeout = 2)
+
+    assert not transcribe_thread.is_alive()
+    assert not unload_thread.is_alive()
+
+
+def test_new_stt_load_uses_cpu_while_training(monkeypatch):
+    fake_torch = SimpleNamespace(
+        float16 = "float16",
+        float32 = "float32",
+        cuda = SimpleNamespace(is_available = lambda: True),
+        backends = SimpleNamespace(mps = SimpleNamespace(is_available = lambda: True)),
+    )
+    monkeypatch.setitem(sys.modules, "torch", fake_torch)
+    monkeypatch.setattr(stt_sidecar_module, "_training_active", lambda: True)
+
+    assert stt_sidecar_module._pick_device() == ("cpu", "float32")
+
+
+def test_new_stt_load_prefers_cuda_when_training_is_idle(monkeypatch):
+    fake_torch = SimpleNamespace(
+        float16 = "float16",
+        float32 = "float32",
+        cuda = SimpleNamespace(is_available = lambda: True),
+        backends = SimpleNamespace(mps = SimpleNamespace(is_available = lambda: False)),
+    )
+    monkeypatch.setitem(sys.modules, "torch", fake_torch)
+    monkeypatch.setattr(stt_sidecar_module, "_training_active", lambda: False)
+
+    assert stt_sidecar_module._pick_device() == ("cuda", "float16")
+
+
+def test_new_stt_load_prefers_mps_when_cuda_is_unavailable(monkeypatch):
+    fake_torch = SimpleNamespace(
+        float16 = "float16",
+        float32 = "float32",
+        cuda = SimpleNamespace(is_available = lambda: False),
+        backends = SimpleNamespace(mps = SimpleNamespace(is_available = lambda: True)),
+    )
+    monkeypatch.setitem(sys.modules, "torch", fake_torch)
+    monkeypatch.setattr(stt_sidecar_module, "_training_active", lambda: False)
+
+    assert stt_sidecar_module._pick_device() == ("mps", "float32")
+
+
+def test_new_stt_load_uses_cpu_without_accelerators(monkeypatch):
+    fake_torch = SimpleNamespace(
+        float16 = "float16",
+        float32 = "float32",
+        cuda = SimpleNamespace(is_available = lambda: False),
+        backends = SimpleNamespace(mps = SimpleNamespace(is_available = lambda: False)),
+    )
+    monkeypatch.setitem(sys.modules, "torch", fake_torch)
+    monkeypatch.setattr(stt_sidecar_module, "_training_active", lambda: False)
+
+    assert stt_sidecar_module._pick_device() == ("cpu", "float32")
+
+
+def test_accelerator_load_failure_retries_on_cpu(monkeypatch):
+    fake_torch = _install_fake_torch(monkeypatch)
+    calls = []
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", lambda: None)
+
+    def build(_repo, device, dtype, _cancel_event):
+        calls.append((device, dtype))
+        if device == "cuda":
+            raise RuntimeError("accelerator allocation failed")
+        return object(), object()
+
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("cuda", "float16"))
+    monkeypatch.setattr(sidecar, "_build_model", build)
+
+    sidecar.load("small")
+
+    assert calls == [("cuda", "float16"), ("cpu", fake_torch.float32)]
+    assert sidecar.device == "cpu"
+
+
+def test_pending_load_can_be_cancelled_without_waiting_for_model_lock(monkeypatch):
+    _install_fake_torch(monkeypatch)
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    build_started = threading.Event()
+    release_build = threading.Event()
+    errors = []
+
+    def build(_repo, _device, _dtype, _cancel_event):
+        build_started.set()
+        assert release_build.wait(timeout = 2)
+        return object(), object()
+
+    def run_load():
+        try:
+            sidecar.load("small")
+        except Exception as exc:
+            errors.append(exc)
+
+    monkeypatch.setattr(stt_sidecar_module, "ensure_stt_available", lambda: None)
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("cpu", "float32"))
+    monkeypatch.setattr(sidecar, "_build_model", build)
+
+    load_thread = threading.Thread(target = run_load)
+    load_thread.start()
+    assert build_started.wait(timeout = 2)
+
+    result = []
+    cancel_thread = threading.Thread(target = lambda: result.append(sidecar.cancel_pending_load()))
+    cancel_thread.start()
+    cancel_thread.join(timeout = 2)
+
+    assert not cancel_thread.is_alive()
+    assert result == [True]
+    assert load_thread.is_alive()
+
+    release_build.set()
+    load_thread.join(timeout = 2)
+
+    assert not load_thread.is_alive()
+    assert len(errors) == 1
+    assert isinstance(errors[0], SttLoadCancelledError)
+    assert sidecar.loaded_model is None
+    assert sidecar.is_loading() is False
+
+
+def _wav_bytes(sample_count: int, sample_rate: int = 16000) -> bytes:
+    output = io.BytesIO()
+    with wave.open(output, "wb") as wav:
+        wav.setnchannels(1)
+        wav.setsampwidth(2)
+        wav.setframerate(sample_rate)
+        wav.writeframes(np.zeros(sample_count, dtype = np.int16).tobytes())
+    return output.getvalue()
+
+
+def test_bounded_decoder_returns_16khz_float_pcm():
+    pytest.importorskip("av")
+
+    decoded = _REAL_DECODE_AUDIO_BOUNDED(_wav_bytes(1600))
+
+    assert decoded.dtype == np.float32
+    assert decoded.shape == (1600,)
+
+
+def test_bounded_decoder_rejects_audio_as_soon_as_sample_cap_is_crossed(monkeypatch):
+    pytest.importorskip("av")
+    monkeypatch.setattr(stt_sidecar_module, "_MAX_AUDIO_SECONDS", 1)
+
+    with pytest.raises(SttAudioTooLongError, match = "Audio must"):
+        _REAL_DECODE_AUDIO_BOUNDED(_wav_bytes(16001))
+
+
+def test_bounded_decoder_resamples_stereo_48khz_to_mono_16khz():
+    pytest.importorskip("av")
+    output = io.BytesIO()
+    frames = np.zeros((4800, 2), dtype = np.int16)
+    with wave.open(output, "wb") as wav:
+        wav.setnchannels(2)
+        wav.setsampwidth(2)
+        wav.setframerate(48000)
+        wav.writeframes(frames.tobytes())
+
+    decoded = _REAL_DECODE_AUDIO_BOUNDED(output.getvalue())
+
+    assert decoded.dtype == np.float32
+    assert 1590 <= len(decoded) <= 1610
+
+
+@pytest.mark.parametrize("audio", [b"", b"not audio", b"RIFF\x00\x00"])
+def test_bounded_decoder_rejects_malformed_audio(audio):
+    pytest.importorskip("av")
+
+    with pytest.raises(SttAudioDecodeError, match = "Could not decode"):
+        _REAL_DECODE_AUDIO_BOUNDED(audio)
+
+
+def test_bounded_decoder_rejects_container_without_audio_stream(monkeypatch):
+    class FakeFFmpegError(Exception):
+        pass
+
+    class FakeResampler:
+        def __init__(self, **_kwargs):
+            pass
+
+    class FakeFifo:
+        samples = 0
+
+    class FakeContainer:
+        streams = SimpleNamespace(audio = [])
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *_args):
+            return False
+
+    fake_av = SimpleNamespace(
+        audio = SimpleNamespace(
+            resampler = SimpleNamespace(AudioResampler = FakeResampler),
+            fifo = SimpleNamespace(AudioFifo = FakeFifo),
+        ),
+        open = lambda *_args, **_kwargs: FakeContainer(),
+    )
+    monkeypatch.setitem(sys.modules, "av", fake_av)
+    monkeypatch.setitem(
+        sys.modules,
+        "av.error",
+        SimpleNamespace(
+            FFmpegError = FakeFFmpegError,
+            InvalidDataError = FakeFFmpegError,
+        ),
+    )
+
+    with pytest.raises(SttAudioDecodeError, match = "Could not decode"):
+        _REAL_DECODE_AUDIO_BOUNDED(b"video-only")
+
+
+def test_unload_releases_model_and_device():
+    sidecar = WhisperSttSidecar()
+    sidecar._engine = object()
+    sidecar._model_id = "small"
+    sidecar._device = "cpu"
+
+    sidecar.unload()
+
+    assert sidecar.loaded_model is None
+    assert sidecar.device is None
+
+
+# ---------------------------------------------------------------------------
+# Snapshot download tracking
+# ---------------------------------------------------------------------------
+
+
+def _write_complete_snapshot(snapshot: Path, *, model_type: str = "whisper") -> None:
+    snapshot.mkdir(parents = True, exist_ok = True)
+    (snapshot / "config.json").write_text(json.dumps({"model_type": model_type}))
+    (snapshot / "preprocessor_config.json").write_text("{}")
+    (snapshot / "tokenizer.json").write_text("{}")
+    (snapshot / "model.safetensors").write_bytes(b"weights")
+
+
+def _sibling(name: str, size: int, key: str):
+    return SimpleNamespace(rfilename = name, size = size, blob_id = key, lfs = None)
+
+
+def test_sha_snapshot_without_main_ref_survives_restart_and_cache_relocation(monkeypatch, tmp_path):
+    repo = "openai/whisper-tiny.en"
+    revision = "c" * 40
+    studio_home = tmp_path / "studio"
+    first_cache = tmp_path / "first-hub"
+    second_cache = tmp_path / "second-hub"
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(studio_home))
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    monkeypatch.setattr(stt_sidecar_module, "_snapshot_is_complete", _REAL_SNAPSHOT_IS_COMPLETE)
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        _REAL_FIND_COMPLETE_CACHED_SNAPSHOT,
+    )
+
+    first = first_cache / "models--openai--whisper-tiny.en" / "snapshots" / revision
+    _write_complete_snapshot(first)
+    monkeypatch.setenv("HF_HUB_CACHE", str(first_cache))
+    stt_sidecar_module._write_revision_record(repo, revision)
+    assert stt_sidecar_module._find_complete_cached_snapshot(repo) == first.resolve()
+
+    second = second_cache / "models--openai--whisper-tiny.en" / "snapshots" / revision
+    _write_complete_snapshot(second)
+    monkeypatch.setenv("HF_HUB_CACHE", str(second_cache))
+    assert stt_sidecar_module._find_complete_cached_snapshot(repo) == second.resolve()
+
+
+def test_corrupt_or_escaping_revision_record_is_ignored(monkeypatch, tmp_path):
+    repo = "openai/whisper-tiny.en"
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path / "studio"))
+    monkeypatch.setenv("HF_HUB_CACHE", str(tmp_path / "hub"))
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        _REAL_FIND_COMPLETE_CACHED_SNAPSHOT,
+    )
+    record = stt_sidecar_module._revision_record_path(repo)
+    record.parent.mkdir(parents = True)
+    record.write_text(json.dumps({"version": 1, "repo": repo, "revision": "../../outside"}))
+    assert stt_sidecar_module._find_complete_cached_snapshot(repo) is None
+
+    outside = tmp_path / "outside"
+    _write_complete_snapshot(outside)
+    snapshots = tmp_path / "hub" / "models--openai--whisper-tiny.en" / "snapshots"
+    snapshots.mkdir(parents = True)
+    (snapshots / ("d" * 40)).symlink_to(outside, target_is_directory = True)
+    assert stt_sidecar_module._find_complete_cached_snapshot(repo) is None
+
+
+def test_adapter_only_snapshot_is_not_complete(tmp_path):
+    (tmp_path / "config.json").write_text('{"model_type": "whisper"}')
+    (tmp_path / "preprocessor_config.json").write_text("{}")
+    (tmp_path / "tokenizer.json").write_text("{}")
+    (tmp_path / "adapter_model.safetensors").write_bytes(b"adapter")
+
+    assert _REAL_SNAPSHOT_IS_COMPLETE(tmp_path) is False
+
+
+def test_snapshot_selection_prefers_safetensors_and_excludes_unrelated_files():
+    info = SimpleNamespace(
+        siblings = [
+            _sibling("config.json", 10, "config"),
+            _sibling("preprocessor_config.json", 20, "preprocessor"),
+            _sibling("tokenizer.json", 30, "tokenizer"),
+            _sibling("model.safetensors", 100, "safe"),
+            _sibling("pytorch_model.bin", 110, "torch"),
+            _sibling("README.md", 1000, "readme"),
+        ]
+    )
+
+    selected = stt_sidecar_module._select_snapshot_files(
+        info, lambda _name: pytest.fail("unsharded selection must not load an index")
+    )
+
+    assert {item.path for item in selected} == {
+        "config.json",
+        "preprocessor_config.json",
+        "tokenizer.json",
+        "model.safetensors",
+    }
+    assert sum(item.size for item in selected) == 160
+
+
+def test_snapshot_selection_includes_every_indexed_shard():
+    info = SimpleNamespace(
+        siblings = [
+            _sibling("config.json", 10, "config"),
+            _sibling("model.safetensors.index.json", 5, "index"),
+            _sibling("model-00001-of-00002.safetensors", 50, "shard1"),
+            _sibling("model-00002-of-00002.safetensors", 60, "shard2"),
+            _sibling("pytorch_model.bin", 120, "torch"),
+        ]
+    )
+
+    selected = stt_sidecar_module._select_snapshot_files(
+        info,
+        lambda name: {
+            "weight_map": {
+                "a": "model-00001-of-00002.safetensors",
+                "b": "model-00002-of-00002.safetensors",
+            }
+        },
+    )
+
+    assert {item.path for item in selected} == {
+        "config.json",
+        "model.safetensors.index.json",
+        "model-00001-of-00002.safetensors",
+        "model-00002-of-00002.safetensors",
+    }
+
+
+def test_progress_counts_only_selected_blobs_and_caps_incomplete_files(monkeypatch, tmp_path):
+    monkeypatch.setenv("HF_HUB_CACHE", str(tmp_path / "hub"))
+    blobs = tmp_path / "hub" / "models--owner--whisper" / "blobs"
+    blobs.mkdir(parents = True)
+    (blobs / "one").write_bytes(b"x" * 10)
+    (blobs / "two.incomplete").write_bytes(b"x" * 30)
+    (blobs / "unrelated").write_bytes(b"x" * 1000)
+    state = stt_sidecar_module._SnapshotDownloadState()
+    state._repo = "owner/whisper"
+    state._selected_files = (
+        stt_sidecar_module._SelectedHubFile("config.json", 10, "one"),
+        stt_sidecar_module._SelectedHubFile("model.safetensors", 20, "two"),
+    )
+    state._total_bytes = 30
+    state._complete = True
+
+    status = state.status()
+
+    assert status["bytes_total"] == 30
+    assert status["bytes_done"] == 30
+
+
+def test_download_metadata_and_snapshot_use_the_same_revision(monkeypatch, tmp_path):
+    revision = "e" * 40
+    calls = []
+    siblings = [
+        _sibling("config.json", 10, "config"),
+        _sibling("preprocessor_config.json", 20, "preprocessor"),
+        _sibling("tokenizer.json", 30, "tokenizer"),
+        _sibling("model.safetensors", 100, "safe"),
+        _sibling("pytorch_model.bin", 110, "torch"),
+    ]
+
+    class FakeApi:
+        def __init__(self, token):
+            pass
+
+        def model_info(self, repo, **kwargs):
+            calls.append(("info", repo, kwargs))
+            return SimpleNamespace(sha = revision, siblings = siblings)
+
+    def fake_snapshot_download(**kwargs):
+        calls.append(("snapshot", kwargs))
+        return str(tmp_path)
+
+    monkeypatch.setattr("huggingface_hub.HfApi", FakeApi)
+    monkeypatch.setattr("huggingface_hub.snapshot_download", fake_snapshot_download)
+    monkeypatch.setattr(
+        "huggingface_hub.hf_hub_download",
+        lambda **_kwargs: pytest.fail("unsharded selection must not load an index"),
+    )
+    monkeypatch.setattr(stt_sidecar_module, "_snapshot_is_complete", lambda _path: True)
+    monkeypatch.setattr(stt_sidecar_module, "_write_revision_record", lambda *_args: None)
+    state = stt_sidecar_module._SnapshotDownloadState()
+
+    state._run("owner/whisper", None, revision)
+
+    assert calls[0] == (
+        "info",
+        "owner/whisper",
+        {"revision": revision, "files_metadata": True, "timeout": 30},
+    )
+    assert calls[1][0] == "snapshot"
+    assert calls[1][1]["revision"] == revision
+    assert "model.safetensors" in calls[1][1]["allow_patterns"]
+    assert "pytorch_model.bin" not in calls[1][1]["allow_patterns"]
+
+
+def test_download_status_is_idle_before_any_download():
+    state = stt_sidecar_module._SnapshotDownloadState()
+
+    status = state.status()
+
+    assert status == {
+        "downloading": False,
+        "model": None,
+        "error": None,
+        "bytes_total": None,
+        "bytes_done": None,
+    }
+
+
+def test_download_rejects_a_second_model_while_one_is_in_flight(monkeypatch):
+    state = stt_sidecar_module._SnapshotDownloadState()
+    release = threading.Event()
+    monkeypatch.setattr(
+        state,
+        "_run",
+        lambda repo, token, revision: release.wait(timeout = 5),
+    )
+
+    state.start("small")
+    try:
+        # Re-requesting the in-flight model is a no-op, not an error.
+        state.start("small")
+        with pytest.raises(SttModelIdError, match = "still"):
+            state.start("tiny")
+        assert state.status()["downloading"] is True
+        assert state.status()["model"] == "small"
+    finally:
+        release.set()
+
+
+def test_download_failure_is_reported_in_status(monkeypatch):
+    state = stt_sidecar_module._SnapshotDownloadState()
+    # Mask huggingface_hub so the import inside _run fails fast.
+    monkeypatch.setitem(sys.modules, "huggingface_hub", None)
+
+    state.start("small")
+    state._thread.join(timeout = 5)
+
+    status = state.status()
+    assert status["downloading"] is False
+    assert "Download failed" in (status["error"] or "")
+
+
+def test_is_model_downloaded_is_false_for_a_cache_miss(monkeypatch):
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        _REAL_FIND_COMPLETE_CACHED_SNAPSHOT,
+    )
+    monkeypatch.setenv("HF_HUB_CACHE", "/nonexistent/stt-test-cache")
+
+    assert stt_sidecar_module.is_model_downloaded("small") is False
+
+
+def test_sharded_snapshot_with_missing_shard_is_not_downloaded(monkeypatch, tmp_path):
+    import json
+
+    monkeypatch.setenv("HF_HUB_CACHE", str(tmp_path / "hub"))
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path / "studio"))
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        _REAL_FIND_COMPLETE_CACHED_SNAPSHOT,
+    )
+    monkeypatch.setattr(stt_sidecar_module, "_snapshot_is_complete", _REAL_SNAPSHOT_IS_COMPLETE)
+    snap = tmp_path / "hub" / "models--unsloth--whisper-small" / "snapshots" / ("a" * 40)
+    snap.mkdir(parents = True)
+    (snap / "config.json").write_bytes(b"{}")
+    (snap / "preprocessor_config.json").write_bytes(b"{}")
+    (snap / "tokenizer.json").write_bytes(b"{}")
+    index = {
+        "weight_map": {
+            "a": "model-00001-of-00002.safetensors",
+            "b": "model-00002-of-00002.safetensors",
+        }
+    }
+    (snap / "model.safetensors.index.json").write_text(json.dumps(index))
+    (snap / "model-00001-of-00002.safetensors").write_bytes(b"w" * 8)
+
+    assert stt_sidecar_module.is_model_downloaded("small") is False
+
+    # Completing the second shard flips the verdict.
+    (snap / "model-00002-of-00002.safetensors").write_bytes(b"w" * 8)
+    assert stt_sidecar_module.is_model_downloaded("small") is True
+
+
+@pytest.mark.parametrize("model_id", ["small", "openai/whisper-medium"])
+def test_preflight_rejects_partial_snapshot(monkeypatch, tmp_path, model_id):
+    # A resolvable snapshot with metadata but no weights must fail preflight,
+    # not survive until load() after the audio has already been decoded.
+    monkeypatch.setenv("HF_HUB_CACHE", str(tmp_path / "hub"))
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path / "studio"))
+    monkeypatch.setattr(
+        stt_sidecar_module,
+        "_find_complete_cached_snapshot",
+        _REAL_FIND_COMPLETE_CACHED_SNAPSHOT,
+    )
+    monkeypatch.setattr(stt_sidecar_module, "_snapshot_is_complete", _REAL_SNAPSHOT_IS_COMPLETE)
+    repo = STT_MODELS.get(model_id, model_id)
+    snapshot = tmp_path / "hub" / f"models--{repo.replace('/', '--')}" / "snapshots" / ("b" * 40)
+    snapshot.mkdir(parents = True)
+    (snapshot / "config.json").write_text('{"model_type": "whisper"}')
+
+    with pytest.raises(SttModelNotDownloadedError, match = "not downloaded"):
+        WhisperSttSidecar(keep_alive_seconds = 0)._ensure_model_downloaded(model_id)
+
+    # Completing the snapshot clears the preflight.
+    (snapshot / "preprocessor_config.json").write_text("{}")
+    (snapshot / "tokenizer.json").write_text("{}")
+    (snapshot / "model.safetensors").write_bytes(b"w" * 8)
+    WhisperSttSidecar(keep_alive_seconds = 0)._ensure_model_downloaded(model_id)
+
+
+def test_cpu_retry_releases_failed_accelerator_load(monkeypatch):
+    _install_fake_torch(monkeypatch)
+    monkeypatch.setattr(stt_sidecar_module, "_pick_device", lambda: ("mps", "float16"))
+
+    class Marker:
+        pass
+
+    seen = {}
+
+    def fake_build(self, repo, device, dtype, cancel_event):
+        if device != "cpu":
+            # The frame local stands in for a partly loaded accelerator model
+            # kept alive only through the raised traceback.
+            marker = Marker()
+            seen["ref"] = weakref.ref(marker)
+            raise RuntimeError("accelerator load failed")
+        gc.collect()
+        seen["alive_during_retry"] = seen["ref"]() is not None
+        return (_FakeModel(), object())
+
+    monkeypatch.setattr(WhisperSttSidecar, "_build_model", fake_build)
+    sidecar = WhisperSttSidecar(keep_alive_seconds = 0)
+    sidecar.load("small")
+
+    # The failed attempt must be collectable before the CPU model loads, or
+    # its accelerator memory stays stranded for the whole retry.
+    assert seen["alive_during_retry"] is False
+    assert sidecar.device == "cpu"
diff --git a/studio/backend/tests/test_trained_model_scan.py b/studio/backend/tests/test_trained_model_scan.py
index 5d74bb7d28..64228cec3c 100644
--- a/studio/backend/tests/test_trained_model_scan.py
+++ b/studio/backend/tests/test_trained_model_scan.py
@@ -97,6 +97,7 @@ def test_lora_identifier_resolves_remote_adapter_base(tmp_path: Path):
         repo,
         fn,
         token = None,
+        cache_dir = None,
     ):
         assert repo == "someone/my-remote-lora"
         assert fn == "adapter_config.json"
@@ -128,6 +129,7 @@ def test_lora_identifier_retries_transient_then_resolves(tmp_path: Path):
         repo,
         fn,
         token = None,
+        cache_dir = None,
     ):
         calls["n"] += 1
         if calls["n"] == 1:
diff --git a/studio/backend/tests/test_training_pump_resilience.py b/studio/backend/tests/test_training_pump_resilience.py
index d75b205f35..e7e47478b5 100644
--- a/studio/backend/tests/test_training_pump_resilience.py
+++ b/studio/backend/tests/test_training_pump_resilience.py
@@ -310,6 +310,80 @@ def test_pump_finalizes_when_read_keeps_raising_on_dead_worker(monkeypatch):
     assert b._pump_running is False
 
 
+def test_interrupted_cancel_clears_in_memory_output_dir(monkeypatch):
+    # Stop-without-save interrupted before its complete event: /status must not
+    # keep serving the cleared run's output_dir.
+    b = TrainingBackend()
+    finalized: dict = {}
+    monkeypatch.setattr(b, "_ensure_db_run_created", lambda: None)
+    monkeypatch.setattr(b, "_finalize_run_in_db", lambda **kw: finalized.update(kw))
+
+    b._proc = _FakeProc(alive = False)
+    b._event_queue = _IdleQueue()
+    b._progress.is_training = True
+    b._should_stop = True
+    b._cancel_requested = True
+    b._output_dir = "/out/x"
+
+    b._pump_loop()
+
+    assert b._output_dir is None
+    assert finalized.get("status") == "stopped"
+    assert finalized.get("output_dir") is None
+    assert finalized.get("clear_output_dir") is True
+
+
+def test_worker_exit_reuses_terminal_stop_save_error(monkeypatch):
+    b = TrainingBackend()
+    finalized: dict = {}
+    monkeypatch.setattr(b, "_ensure_db_run_created", lambda: None)
+    monkeypatch.setattr(b, "_finalize_run_in_db", lambda **kw: finalized.update(kw))
+
+    b._proc = _FakeProc(alive = False)
+    b._event_queue = _IdleQueue()
+    b._progress.is_training = True
+    b._should_stop = True
+    b._cancel_requested = False
+    b._output_dir = "/out/x"
+    b.current_job_id = "job-x"
+    b._terminal_finalize_payload = {
+        "status": "error",
+        "error_message": "checkpoint failed",
+        "output_dir": "/out/x",
+        "clear_output_dir": False,
+        "resume_blocked": True,
+        "expected_job_id": "job-x",
+    }
+
+    b._pump_loop()
+
+    assert b._output_dir == "/out/x"
+    assert finalized.get("status") == "error"
+    assert finalized.get("output_dir") == "/out/x"
+    assert finalized.get("clear_output_dir") is False
+    assert finalized.get("resume_blocked") is True
+
+
+def test_dead_worker_crash_preserves_output_dir(monkeypatch):
+    # A crash (no stop requested) after output_dir was emitted must keep the dir
+    # in the error finalize: checkpoints under it may still exist.
+    b = TrainingBackend()
+    finalized: dict = {}
+    monkeypatch.setattr(b, "_ensure_db_run_created", lambda: None)
+    monkeypatch.setattr(b, "_finalize_run_in_db", lambda **kw: finalized.update(kw))
+
+    b._proc = _FakeProc(alive = False)
+    b._event_queue = _IdleQueue()
+    b._progress.is_training = True
+    b._output_dir = "/out/x"
+
+    b._pump_loop()
+
+    assert finalized.get("status") == "error"
+    assert finalized.get("output_dir") == "/out/x"
+    assert finalized.get("clear_output_dir") is False
+
+
 def test_start_training_clears_stale_pump_running_flag():
     # A prior pump that died abnormally leaves _pump_running True. The next
     # start_training must clear it during reset so the start-time watchdog can't
@@ -492,3 +566,34 @@ def test_db_run_created_before_pump_consumes_events(monkeypatch):
     # The pump observed an already-created run; it would be False if the pump
     # were started before the eager create.
     assert seen["db_created"] is True
+
+
+def test_startup_flag_reports_training_active_before_proc():
+    # Between freeing VRAM and _proc going live, a concurrent STT load must see
+    # training as active so it does not grab the just-freed GPU.
+    b = TrainingBackend()
+    b._spawn_in_progress = True
+    assert b.is_training_active() is True
+
+
+def test_before_spawn_runs_inside_active_window(monkeypatch):
+    # The VRAM-freeing hook must run while training already counts as active, or
+    # an STT load racing it would place Whisper back on the freed GPU.
+    b = TrainingBackend()
+    _stub_spawn(monkeypatch)
+    monkeypatch.setattr(b, "_ensure_db_run_created", lambda: None)
+    monkeypatch.setattr(b, "_pump_loop", lambda: setattr(b, "_pump_running", False))
+
+    active_during_free = {}
+
+    def before_spawn():
+        active_during_free["value"] = b.is_training_active()
+
+    assert b.start_training("job_active_window", model_name = "m", before_spawn = before_spawn) is True
+    if b._pump_thread is not None:
+        b._pump_thread.join(timeout = 2.0)
+
+    assert active_during_free["value"] is True
+    # The transient flag clears, but the live proc keeps training active.
+    assert b._spawn_in_progress is False
+    assert b.is_training_active() is True
diff --git a/studio/backend/tests/test_training_resume.py b/studio/backend/tests/test_training_resume.py
index 91fdac9961..51425b0428 100644
--- a/studio/backend/tests/test_training_resume.py
+++ b/studio/backend/tests/test_training_resume.py
@@ -7,6 +7,9 @@ import importlib.util
 import json
 from pathlib import Path
 
+import pytest
+import torch
+
 
 _BACKEND = Path(__file__).resolve().parents[1]
 
@@ -25,6 +28,30 @@ def _load_resume_module():
 resume = _load_resume_module()
 
 
+def test_resume_request_accepts_sanitized_null_target_modules():
+    from models.training import TrainingStartRequest
+    request = TrainingStartRequest(
+        model_name = "unsloth/Qwen3-0.6B",
+        training_type = "Full Finetuning",
+        format_type = "alpaca",
+        target_modules = None,
+    )
+
+    assert request.target_modules == []
+
+
+def _write_checkpoint(out: Path, step: int) -> Path:
+    checkpoint = out / f"checkpoint-{step}"
+    checkpoint.mkdir(parents = True, exist_ok = True)
+    (checkpoint / "trainer_state.json").write_text(
+        json.dumps({"global_step": step}), encoding = "utf-8"
+    )
+    torch.save({"weight": torch.ones(1)}, checkpoint / "adapter_model.bin")
+    torch.save({"state": {0: torch.ones(1)}}, checkpoint / "optimizer.pt")
+    torch.save({"last_epoch": step}, checkpoint / "scheduler.pt")
+    return checkpoint
+
+
 def _stopped_run(**overrides):
     run = {
         "status": "stopped",
@@ -44,6 +71,36 @@ def test_can_resume_run_allows_checkpointed_non_s3_run(monkeypatch):
     assert resume.can_resume_run(_stopped_run()) is True
 
 
+def test_can_resume_run_allows_errored_run_with_checkpoint(monkeypatch):
+    monkeypatch.setattr(resume, "has_resume_state", lambda _path: True)
+
+    assert resume.can_resume_run(_stopped_run(status = "error")) is True
+
+
+def test_can_resume_run_rejects_errored_run_without_checkpoint(monkeypatch):
+    monkeypatch.setattr(resume, "has_resume_state", lambda _path: False)
+
+    assert resume.can_resume_run(_stopped_run(status = "error")) is False
+
+
+def test_can_resume_run_allows_errored_run_at_final_step(monkeypatch):
+    # A save-time crash records final_step == total_steps; resuming re-runs the
+    # final-save path from the checkpoint.
+    monkeypatch.setattr(resume, "has_resume_state", lambda _path: True)
+
+    run = _stopped_run(status = "error", final_step = 10, total_steps = 10)
+
+    assert resume.can_resume_run(run) is True
+
+
+def test_can_resume_run_rejects_stopped_run_at_final_step(monkeypatch):
+    monkeypatch.setattr(resume, "has_resume_state", lambda _path: True)
+
+    run = _stopped_run(final_step = 10, total_steps = 10)
+
+    assert resume.can_resume_run(run) is False
+
+
 def test_can_resume_run_rejects_s3_dataset_source(monkeypatch):
     monkeypatch.setattr(resume, "has_resume_state", lambda _path: True)
 
@@ -91,3 +148,444 @@ def test_list_runs_includes_config_json_for_resume_policy(monkeypatch, tmp_path)
     result = studio_db.list_runs()
 
     assert result["runs"][0]["config_json"] == config_json
+
+
+def test_crashed_run_with_persisted_output_dir_is_resumable(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 10)
+
+    studio_db.create_run(
+        id = "run-crash",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 20,
+    )
+    studio_db.update_run_output_dir("run-crash", str(out))
+    conn = studio_db.get_connection()
+    conn.execute("UPDATE training_runs SET status = 'error' WHERE id = 'run-crash'")
+    conn.commit()
+    conn.close()
+
+    run = studio_db.get_run("run-crash")
+    assert run["output_dir"] == str(out)
+    assert resume.can_resume_run(run) is True
+
+
+def test_checkpoint_discovery_skips_malformed_newest(monkeypatch, tmp_path):
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    out = tmp_path / "outputs" / "run_x"
+    valid = _write_checkpoint(out, 5)
+    (_write_checkpoint(out, 8) / "scheduler.pt").unlink()
+    malformed = out / "checkpoint-10"
+    malformed.mkdir()
+    (malformed / "trainer_state.json").write_text(json.dumps({"global_step": 10}), encoding = "utf-8")
+    (malformed / "adapter_model.bin").write_bytes(b"not a torch archive")
+    (malformed / "optimizer.pt").write_bytes(b"not a torch archive")
+
+    assert resume.get_resume_checkpoint_path(str(out)) == str(valid)
+
+
+def test_completed_run_keeps_output_dir_and_rejects_stale_cancel(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    studio_db.create_run(
+        id = "r",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 10,
+    )
+    studio_db.update_run_output_dir("r", "/out/x")
+    studio_db.finish_run(
+        id = "r",
+        status = "completed",
+        ended_at = "t",
+        final_step = 2,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = "/out/x",
+        error_message = None,
+    )
+
+    assert studio_db.get_run("r")["output_dir"] == "/out/x"
+    assert studio_db.mark_run_cancel_requested("r") is False
+    assert studio_db.get_run("r")["output_dir"] == "/out/x"
+    assert studio_db.get_run("r")["resume_blocked"] == 0
+
+
+def test_finish_run_clears_output_dir_for_stop_without_save(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    studio_db.create_run(
+        id = "r",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 10,
+    )
+    studio_db.update_run_output_dir("r", "/out/x")
+    studio_db.finish_run(
+        id = "r",
+        status = "stopped",
+        ended_at = "t",
+        final_step = 2,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = None,
+        error_message = None,
+        clear_output_dir = True,
+    )
+
+    assert studio_db.get_run("r")["output_dir"] is None
+    conn = studio_db.get_connection()
+    conn.execute(
+        "UPDATE training_runs SET status = 'running', output_dir = '/out/x', resume_blocked = 0 WHERE id = 'r'"
+    )
+    conn.commit()
+    conn.close()
+    studio_db.mark_run_cancel_requested("r")
+    studio_db.cleanup_orphaned_runs()
+    assert studio_db.get_run("r")["status"] == "stopped"
+    assert studio_db.get_run("r")["output_dir"] is None
+
+
+def test_finish_run_clears_output_dir_on_cancel_error_finalize(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    studio_db.create_run(
+        id = "r",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 10,
+    )
+    studio_db.update_run_output_dir("r", "/out/x")
+    studio_db.finish_run(
+        id = "r",
+        status = "stopped",
+        ended_at = "t",
+        final_step = 2,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = "/out/x",
+        error_message = "worker failed during cancel",
+        clear_output_dir = True,
+    )
+
+    assert studio_db.get_run("r")["output_dir"] is None
+
+
+def test_finish_run_preserves_output_dir_for_interrupted_stop_and_save(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    studio_db.create_run(
+        id = "r",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 10,
+    )
+    studio_db.update_run_output_dir("r", "/out/x")
+    studio_db.finish_run(
+        id = "r",
+        status = "stopped",
+        ended_at = "t",
+        final_step = 2,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = None,
+        error_message = None,
+    )
+
+    assert studio_db.get_run("r")["output_dir"] == "/out/x"
+
+
+def test_resumed_errored_run_is_not_offered_again(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 10)
+
+    studio_db.create_run(
+        id = "run-old",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 20,
+    )
+    studio_db.update_run_output_dir("run-old", str(out))
+    studio_db.finish_run(
+        id = "run-old",
+        status = "error",
+        ended_at = "2026-01-01T00:05:00Z",
+        final_step = 10,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = None,
+        error_message = "killed",
+    )
+    studio_db.create_run(
+        id = "run-new",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-02T00:00:00Z",
+        total_steps = 20,
+        output_dir = str(out),
+        resumed_from_run_id = "run-old",
+    )
+    with pytest.raises(RuntimeError, match = "no longer available"):
+        studio_db.create_run(
+            id = "run-duplicate",
+            model_name = "m",
+            dataset_name = "d",
+            config_json = "{}",
+            started_at = "2026-01-02T00:00:01Z",
+            total_steps = 20,
+            output_dir = str(out),
+            resumed_from_run_id = "run-old",
+        )
+    assert studio_db.get_run("run-duplicate") is None
+    studio_db.finish_run(
+        id = "run-new",
+        status = "error",
+        ended_at = "2026-01-02T00:05:00Z",
+        final_step = 15,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = None,
+        error_message = "killed again",
+    )
+
+    old_run = studio_db.get_run("run-old")
+    new_run = studio_db.get_run("run-new")
+    assert old_run["resumed_later"] == 1
+    assert resume.can_resume_run(old_run) is False
+    assert new_run["resumed_later"] == 0
+    assert resume.can_resume_run(new_run) is True
+    assert studio_db.get_resumable_run_by_output_dir(str(out))["id"] == "run-new"
+
+
+def test_running_continuation_blocks_older_resume(monkeypatch, tmp_path):
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 10)
+
+    studio_db.create_run(
+        id = "run-old",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 20,
+    )
+    studio_db.update_run_output_dir("run-old", str(out))
+    studio_db.finish_run(
+        id = "run-old",
+        status = "error",
+        ended_at = "2026-01-01T00:05:00Z",
+        final_step = 10,
+        final_loss = None,
+        duration_seconds = 1,
+        loss_sparkline = "[]",
+        output_dir = None,
+        error_message = "killed",
+    )
+    studio_db.create_run(
+        id = "run-new",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-02T00:00:00Z",
+        total_steps = 20,
+        output_dir = str(out),
+        resumed_from_run_id = "run-old",
+    )
+
+    old_run = studio_db.get_run("run-old")
+    assert old_run["resumed_later"] == 1
+    assert resume.can_resume_run(old_run) is False
+    assert studio_db.get_resumable_run_by_output_dir(str(out)) is None
+
+
+def test_stop_save_checkpoint_failure_keeps_error_status(monkeypatch, tmp_path):
+    # A stop-and-save whose checkpoint write failed must finalize as an error so
+    # history explains the missing resume state (keep_error_status flag).
+    from core.training.training import TrainingBackend
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    studio_db.create_run(
+        id = "run-failed-save",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 10,
+    )
+    backend = TrainingBackend()
+    backend.current_job_id = "run-failed-save"
+    backend._db_run_created = True
+    backend._should_stop = True
+    backend._handle_event(
+        {
+            "type": "error",
+            "error": "Failed to save a resumable checkpoint after stop.",
+            "keep_error_status": True,
+        }
+    )
+
+    run = studio_db.get_run("run-failed-save")
+    assert run["status"] == "error"
+    assert "resumable checkpoint" in run["error_message"]
+
+
+def test_can_resume_run_rejects_resume_blocked_run(monkeypatch):
+    monkeypatch.setattr(resume, "has_resume_state", lambda _path: True)
+
+    assert resume.can_resume_run(_stopped_run(status = "error", resume_blocked = 1)) is False
+
+
+def test_stop_save_checkpoint_failure_with_stale_checkpoint_is_not_resumable(monkeypatch, tmp_path):
+    # A failed stop-and-save must not offer Resume from an older periodic checkpoint;
+    # that would roll back past the recorded final step.
+    from core.training.training import TrainingBackend
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    out = tmp_path / "outputs" / "run_x"
+    _write_checkpoint(out, 10)
+
+    studio_db.create_run(
+        id = "run-stale-ckpt",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 20,
+    )
+    studio_db.update_run_output_dir("run-stale-ckpt", str(out))
+    backend = TrainingBackend()
+    backend.current_job_id = "run-stale-ckpt"
+    backend._db_run_created = True
+    backend._should_stop = True
+    backend._output_dir = str(out)
+    backend._handle_event(
+        {
+            "type": "error",
+            "error": "Failed to save a resumable checkpoint after stop.",
+            "keep_error_status": True,
+            "resume_blocked": True,
+        }
+    )
+
+    run = studio_db.get_run("run-stale-ckpt")
+    assert run["status"] == "error"
+    assert run["resume_blocked"] == 1
+    assert run["output_dir"] == str(out)
+    assert resume.can_resume_run(run) is False
+
+
+def test_user_stop_error_without_checkpoint_ack_is_blocked(monkeypatch, tmp_path):
+    from core.training.training import TrainingBackend
+    from storage import studio_db
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    monkeypatch.setattr(studio_db, "_schema_ready", False)
+
+    studio_db.create_run(
+        id = "run-user-stop",
+        model_name = "m",
+        dataset_name = "d",
+        config_json = "{}",
+        started_at = "2026-01-01T00:00:00Z",
+        total_steps = 10,
+    )
+    backend = TrainingBackend()
+    backend.current_job_id = "run-user-stop"
+    backend._db_run_created = True
+    backend._should_stop = True
+    backend._handle_event({"type": "error", "error": "interrupted"})
+
+    run = studio_db.get_run("run-user-stop")
+    assert run["status"] == "error" and run["resume_blocked"] == 1
+
+
+def test_terminal_fallback_keeps_resumable_when_current_checkpoint_landed(monkeypatch, tmp_path):
+    # Worker died before its terminal event, but a valid current-step checkpoint
+    # is on disk: the fallback must keep the run resumable, not block it.
+    from core.training.training import TrainingBackend
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    out = tmp_path / "outputs" / "run_ok"
+    _write_checkpoint(out, 7)
+
+    backend = TrainingBackend()
+    backend.current_job_id = "run-ok"
+    backend._should_stop = True
+    backend._output_dir = str(out)
+    backend._progress.step = 7
+
+    kwargs = backend._terminal_finalize_kwargs()
+    assert kwargs["status"] == "stopped"
+    assert kwargs["resume_blocked"] is False
+
+
+def test_terminal_fallback_blocks_when_no_current_checkpoint(monkeypatch, tmp_path):
+    # Same path, but only a stale (older-step) checkpoint exists: must block.
+    from core.training.training import TrainingBackend
+
+    monkeypatch.setenv("UNSLOTH_STUDIO_HOME", str(tmp_path))
+    out = tmp_path / "outputs" / "run_stale"
+    _write_checkpoint(out, 5)
+
+    backend = TrainingBackend()
+    backend.current_job_id = "run-stale"
+    backend._should_stop = True
+    backend._output_dir = str(out)
+    backend._progress.step = 7
+
+    kwargs = backend._terminal_finalize_kwargs()
+    assert kwargs["status"] == "error"
+    assert kwargs["resume_blocked"] is True
diff --git a/studio/backend/tests/test_training_stop_watchdog.py b/studio/backend/tests/test_training_stop_watchdog.py
index 0cd702bce2..cbe2082e82 100644
--- a/studio/backend/tests/test_training_stop_watchdog.py
+++ b/studio/backend/tests/test_training_stop_watchdog.py
@@ -353,7 +353,7 @@ def test_finalize_after_escalation_clears_state(monkeypatch):
     # stopped so the UI leaves "Stopping..." and a new run can start.
     b = TrainingBackend()
     finstop: list = []
-    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a: finstop.append(a))
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: finstop.append(a))
 
     b._proc = _FakeProc(alive = True)  # wedged: still reports alive
     b._should_stop = True
@@ -365,7 +365,7 @@ def test_finalize_after_escalation_clears_state(monkeypatch):
 
     assert b._proc is None, "the wedged handle must be dropped so is_training_active clears"
     assert b._progress.is_training is False
-    assert b._progress.status_message == "Training stopped."
+    assert "valid current-step checkpoint" in b._progress.status_message
     assert finstop and finstop[0][0] == "job_c", "the captured run must be finalized by id"
     assert b.is_training_active() is False
 
@@ -375,7 +375,7 @@ def test_finalize_after_escalation_preserves_output_dir(monkeypatch):
     # must record it even if the watchdog wins the finalize race against the pump.
     b = TrainingBackend()
     finstop: list = []
-    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a: finstop.append(a))
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: finstop.append(a))
 
     b._proc = _FakeProc(alive = True)
     b._should_stop = True
@@ -390,6 +390,28 @@ def test_finalize_after_escalation_preserves_output_dir(monkeypatch):
     assert finstop[0][1] == "/tmp/outputs/run-123"
 
 
+def test_finalize_after_escalation_clears_output_dir_on_cancel(monkeypatch):
+    # Stop-without-saving promises no resume: a cancel that escalates through the
+    # watchdog clears the persisted output_dir, not a checkpoint path.
+    b = TrainingBackend()
+    finstop: list = []
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: finstop.append((a, k)))
+
+    b._proc = _FakeProc(alive = True)
+    b._should_stop = True
+    b._cancel_requested = True
+    b.current_job_id = "job_c"
+    b._db_run_created = True
+    b._output_dir = "/tmp/outputs/run-123"
+
+    b._finalize_stopped_after_escalation(watched_job_id = "job_c")
+
+    assert finstop and finstop[0][0][0] == "job_c"
+    assert finstop[0][0][1] is None, "a cancelled run must not record a checkpoint path"
+    assert finstop[0][1].get("clear_output_dir") is True
+    assert b._output_dir is None, "/status must stop exposing the cancelled run's dir"
+
+
 def test_stop_training_starts_watchdog_only_when_worker_alive(monkeypatch):
     # No worker -> nothing to escalate; the watchdog must not spawn.
     b = TrainingBackend()
@@ -409,7 +431,7 @@ def test_finalize_after_escalation_no_ops_when_superseded(monkeypatch):
     # The escalation finalize must then leave the NEW run untouched, not drop its handle.
     b = TrainingBackend()
     finstop: list = []
-    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a: finstop.append(a))
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: finstop.append(a))
 
     old_proc = _FakeProc(alive = False)  # force-terminated worker we were watching
     new_proc = _FakeProc(alive = True)  # a new run already took over
@@ -430,7 +452,7 @@ def test_finalize_after_escalation_runs_for_its_own_worker(monkeypatch):
     # finalizes the captured run by id.
     b = TrainingBackend()
     finstop: list = []
-    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a: finstop.append(a))
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: finstop.append(a))
 
     proc = _FakeProc(alive = False)
     b._proc = proc
@@ -451,7 +473,7 @@ def test_finalize_after_escalation_no_ops_on_job_change_during_startup(monkeypat
     # catch this even though the proc-only guard would not.
     b = TrainingBackend()
     finstop: list = []
-    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a: finstop.append(a))
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: finstop.append(a))
 
     old_proc = _FakeProc(alive = False)  # old worker, dead; new _proc not installed yet
     b._proc = old_proc  # still the old handle (== target), so proc guard would pass
@@ -509,6 +531,7 @@ def _install_fake_db(monkeypatch):
         recs["insert_ids"].append(job_id),
     )
     fake_db.update_run_progress = lambda **kw: recs["progress_ids"].append(kw.get("id"))
+    fake_db.mark_run_cancel_requested = lambda _run_id: True
     fake_storage.studio_db = fake_db
     monkeypatch.setitem(sys.modules, "storage", fake_storage)
     monkeypatch.setitem(sys.modules, "storage.studio_db", fake_db)
@@ -518,9 +541,48 @@ def _install_fake_db(monkeypatch):
     return recs
 
 
+def test_stop_without_save_creates_missing_row_before_signal(monkeypatch):
+    recs = _install_fake_db(monkeypatch)
+    b = TrainingBackend()
+    b.current_job_id, b._db_config = "job_missing", {"model_name": "m"}
+    b._stop_queue = queue.Queue()
+    assert b.stop_training(save = False) is True
+    assert [run["id"] for run in recs["created"]] == ["job_missing"]
+    assert b._stop_queue.get_nowait() == {"type": "stop", "save": False}
+
+    b._cancel_requested = b._should_stop = False
+    sys.modules["storage.studio_db"].mark_run_cancel_requested = lambda _run_id: False
+    assert b.stop_training(save = False) is False
+    assert not b._cancel_requested and b._stop_queue.empty()
+
+    new_queue = queue.Queue()
+    b.current_job_id, b._db_run_created = "job_old", True
+    b._cancel_requested = b._should_stop = False
+
+    def _supersede(_run_id):
+        b.current_job_id = "job_new"
+        b._stop_queue = new_queue
+        return True
+
+    sys.modules["storage.studio_db"].mark_run_cancel_requested = _supersede
+    assert b.stop_training(save = False) is False
+    assert not b._cancel_requested and new_queue.empty()
+
+
 def test_finalize_run_in_db_single_winner_under_concurrency(monkeypatch):
     # The watchdog and pump can both finalize; only one call may reach finish_run.
     recs = _install_fake_db(monkeypatch)
+    monkeypatch.setitem(_G, "_DB_FINALIZE_RETRY_S", 0.0)
+    attempts = 0
+
+    def flaky_finish(**kw):
+        nonlocal attempts
+        attempts += 1
+        if attempts < 3:
+            raise RuntimeError("database is locked")
+        recs["finished"].append(kw)
+
+    sys.modules["storage.studio_db"].finish_run = flaky_finish
     b = TrainingBackend()
     b.current_job_id = "job_x"
     b._db_run_created = True
@@ -539,6 +601,7 @@ def test_finalize_run_in_db_single_winner_under_concurrency(monkeypatch):
         t.join(timeout = 5)
 
     assert len(recs["finished"]) == 1, f"finalize must run once, got {len(recs['finished'])}"
+    assert attempts == 3
     assert b._run_finalized is True
 
 
@@ -646,7 +709,13 @@ def test_ensure_db_run_created_publishes_only_after_insert(monkeypatch):
     monkeypatch.setitem(sys.modules, "storage", fake_storage)
     monkeypatch.setitem(sys.modules, "storage.studio_db", fake_db)
 
-    b._ensure_db_run_created()
+    b._run_intent_lock.acquire()
+    creator = threading.Thread(target = b._ensure_db_run_created)
+    creator.start()
+    time.sleep(0.02)
+    assert b._db_create_in_progress is False
+    b._run_intent_lock.release()
+    creator.join(timeout = 5)
 
     assert observed["flag_during_create"] is False, "flag must not be published before insert"
     assert observed["in_progress_during_create"] is True
@@ -718,6 +787,7 @@ def test_escalation_finalizes_watched_run_by_id_end_to_end(monkeypatch):
     b = TrainingBackend()
     b.current_job_id = "job_old"
     b._db_run_created = True
+    b._should_stop = True
     b._proc = _FakeProc(alive = False)
     b._progress.is_training = True
     b._progress.step = 42
@@ -726,7 +796,8 @@ def test_escalation_finalizes_watched_run_by_id_end_to_end(monkeypatch):
     b._finalize_stopped_after_escalation(target_proc = b._proc, watched_job_id = "job_old")
 
     assert [f["id"] for f in recs["finished"]] == ["job_old"], "must finish the captured run by id"
-    assert recs["finished"][0]["status"] == "stopped"
+    assert recs["finished"][0]["status"] == "error"
+    assert recs["finished"][0]["resume_blocked"] is True
     assert recs["insert_ids"] == ["job_old"], "buffered metrics must land on the captured run"
     assert b._metric_buffer == [], "the captured batch must be drained"
 
@@ -737,7 +808,7 @@ def test_escalation_defers_when_row_cannot_be_created_here(monkeypatch):
     # so the pump's create-then-finalize records the run. Parent state still clears.
     b = TrainingBackend()
     called: list = []
-    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a: called.append(a))
+    monkeypatch.setattr(b, "_finish_stopped_run", lambda *a, **k: called.append(a))
 
     b._proc = _FakeProc(alive = False)
     b.current_job_id = "job_q"
@@ -785,7 +856,7 @@ def test_escalation_does_not_drop_a_new_runs_handle(monkeypatch):
     new_proc = _FakeProc(alive = True)
     b._proc = old_proc
 
-    def hijack(*a):
+    def hijack(*a, **k):
         b._proc = new_proc  # a new run takes over during the finalize
 
     monkeypatch.setattr(b, "_finish_stopped_run", hijack)
diff --git a/studio/backend/tests/test_training_vram_coexistence.py b/studio/backend/tests/test_training_vram_coexistence.py
index 2bedc46d1f..6683cb9aaa 100644
--- a/studio/backend/tests/test_training_vram_coexistence.py
+++ b/studio/backend/tests/test_training_vram_coexistence.py
@@ -82,6 +82,63 @@ def _patch_backends(inf, llama):
     return patch.dict(sys.modules, {"core.inference": core_inf, "routes.inference": routes_inf})
 
 
+def _fake_stt_sidecar(
+    *,
+    model = None,
+    device = None,
+    loading = False,
+):
+    sidecar = SimpleNamespace(
+        loaded_model = model,
+        device = device,
+        is_loading = lambda: loading,
+    )
+    sidecar.cancel_pending_load = MagicMock(return_value = loading)
+    sidecar.wait_for_load_to_settle = MagicMock()
+    sidecar.unload = MagicMock()
+    return sidecar
+
+
+def _fake_ggml_sidecar(
+    *,
+    model = None,
+    device = None,
+    loading = False,
+):
+    ggml = SimpleNamespace(
+        loaded_model = model,
+        device = device,
+        is_loading = lambda: loading,
+    )
+    ggml.cancel_pending_load = MagicMock(return_value = loading)
+    ggml.wait_for_load_to_settle = MagicMock()
+    ggml.unload = MagicMock()
+    return ggml
+
+
+def _patch_stt(sidecar):
+    stt_module = types.ModuleType("core.inference.stt_sidecar")
+    stt_module.get_stt_sidecar = lambda: sidecar
+    # A fresh import of the GGUF sidecar pulls names from the fake module
+    # above and fails; fake it too so test ordering cannot break that import.
+    ggml_module = types.ModuleType("core.inference.stt_ggml_sidecar")
+    empty_ggml = _fake_ggml_sidecar()
+    ggml_module.get_ggml_stt_sidecar = lambda: empty_ggml
+    return patch.dict(
+        sys.modules,
+        {
+            "core.inference.stt_sidecar": stt_module,
+            "core.inference.stt_ggml_sidecar": ggml_module,
+        },
+    )
+
+
+def _patch_ggml_stt(sidecar):
+    ggml_module = types.ModuleType("core.inference.stt_ggml_sidecar")
+    ggml_module.get_ggml_stt_sidecar = lambda: sidecar
+    return patch.dict(sys.modules, {"core.inference.stt_ggml_sidecar": ggml_module})
+
+
 # ── summarize_resident_chat ──────────────────────────────────────────────────
 
 
@@ -169,6 +226,49 @@ class TestSummarizeResidentChat(_GpuCacheResetMixin, unittest.TestCase):
         self.assertTrue(out["any"])  # GGUF still detected
 
 
+class TestSummarizeResidentStt(_GpuCacheResetMixin, unittest.TestCase):
+    def test_reports_resident_model(self):
+        sidecar = _fake_stt_sidecar(model = "small", device = "cuda")
+        with _patch_stt(sidecar):
+            out = tv.summarize_resident_stt()
+        self.assertEqual(out["model"], "small")
+        self.assertEqual(out["device"], "cuda")
+        self.assertTrue(out["any"])
+        self.assertFalse(out["loading"])
+
+    def test_reports_inflight_load(self):
+        sidecar = _fake_stt_sidecar(loading = True)
+        with _patch_stt(sidecar):
+            out = tv.summarize_resident_stt()
+        self.assertTrue(out["any"])
+        self.assertTrue(out["loading"])
+
+    def test_reports_empty_sidecar(self):
+        with _patch_stt(_fake_stt_sidecar()):
+            out = tv.summarize_resident_stt()
+        self.assertFalse(out["any"])
+
+    def test_reports_resident_gguf_when_transformers_idle(self):
+        ggml = _fake_ggml_sidecar(model = "small", device = "whisper.cpp")
+        with _patch_stt(_fake_stt_sidecar()), _patch_ggml_stt(ggml):
+            out = tv.summarize_resident_stt()
+        self.assertEqual(out["model"], "small")
+        self.assertEqual(out["device"], "whisper.cpp")
+        self.assertTrue(out["any"])
+
+    def test_resident_transformers_does_not_mask_loading_gguf(self):
+        # A Transformers model resident on CPU holds no VRAM, but a GGUF
+        # whisper-server still binding its accelerator backend does; the CPU
+        # model must not hide that in-flight startup from training admission.
+        sidecar = _fake_stt_sidecar(model = "small", device = "cpu")
+        ggml = _fake_ggml_sidecar(loading = True)
+        with _patch_stt(sidecar), _patch_ggml_stt(ggml):
+            out = tv.summarize_resident_stt()
+        self.assertEqual(out["model"], "small")
+        self.assertTrue(out["loading"])
+        self.assertTrue(out["any"])
+
+
 # ── can_keep_during_training (auto mode) ─────────────────────────────────────
 
 
@@ -438,5 +538,151 @@ class TestFreeChatModels(_GpuCacheResetMixin, unittest.TestCase):
         self.assertEqual(freed, ["gguf:gemma.gguf"])
 
 
+class TestFreeSttModel(_GpuCacheResetMixin, unittest.TestCase):
+    def test_unloads_resident_model(self):
+        sidecar = _fake_stt_sidecar(model = "small", device = "cuda")
+        with _patch_stt(sidecar):
+            freed = tv.free_stt_model_for_training(reason = "test")
+        sidecar.unload.assert_called_once()
+        self.assertEqual(freed, ["stt:small"])
+
+    def test_cancels_inflight_load_and_waits_to_settle(self):
+        sidecar = _fake_stt_sidecar(loading = True)
+        with _patch_stt(sidecar):
+            freed = tv.free_stt_model_for_training(reason = "test")
+        sidecar.cancel_pending_load.assert_called_once()
+        # The cancelled loader may still hold VRAM; we wait for it to release.
+        sidecar.wait_for_load_to_settle.assert_called_once()
+        # No model surfaced after the wait, so nothing to unload.
+        sidecar.unload.assert_not_called()
+        self.assertEqual(freed, ["stt:loading"])
+
+    def test_cancels_inflight_load_then_unloads_settled_model(self):
+        # A load that finished before observing the cancel leaves a resident
+        # model behind; it must be unloaded so training reclaims the memory.
+        sidecar = _fake_stt_sidecar(model = "small", loading = True)
+        with _patch_stt(sidecar):
+            freed = tv.free_stt_model_for_training(reason = "test")
+        sidecar.cancel_pending_load.assert_called_once()
+        sidecar.wait_for_load_to_settle.assert_called_once()
+        sidecar.unload.assert_called_once()
+        self.assertEqual(freed, ["stt:loading"])
+
+    def test_cancelled_load_still_unloads_gguf_sidecar(self):
+        # Cancelling a Transformers load must not skip the GGUF sidecar; both
+        # engines can hold memory at once (engine switch or direct load calls).
+        sidecar = _fake_stt_sidecar(loading = True)
+        ggml = _fake_ggml_sidecar(model = "small")
+        with _patch_stt(sidecar), _patch_ggml_stt(ggml):
+            freed = tv.free_stt_model_for_training(reason = "test")
+        sidecar.cancel_pending_load.assert_called_once()
+        ggml.unload.assert_called_once()
+        self.assertEqual(freed, ["stt:loading", "stt:small"])
+
+    def test_leaves_empty_sidecar_alone(self):
+        sidecar = _fake_stt_sidecar()
+        with _patch_stt(sidecar):
+            freed = tv.free_stt_model_for_training(reason = "test")
+        sidecar.unload.assert_not_called()
+        self.assertEqual(freed, [])
+
+    def test_cancels_inflight_gguf_load_and_waits_to_settle(self):
+        # A GGUF whisper-server still in startup has no loaded_model yet, so the
+        # coordinator must cancel and wait for it, not skip it, before training
+        # claims the accelerator memory it is binding.
+        sidecar = _fake_stt_sidecar()  # Transformers idle
+        ggml = _fake_ggml_sidecar(loading = True)
+        with _patch_stt(sidecar), _patch_ggml_stt(ggml):
+            freed = tv.free_stt_model_for_training(reason = "test")
+        ggml.cancel_pending_load.assert_called_once()
+        ggml.wait_for_load_to_settle.assert_called_once()
+        ggml.unload.assert_not_called()  # nothing surfaced after the wait
+        self.assertEqual(freed, ["stt:gguf-loading"])
+
+
+class TestCoordinateModels(_GpuCacheResetMixin, unittest.TestCase):
+    def _run(self, chat, stt, keep_results):
+        keep = MagicMock(side_effect = keep_results)
+        with (
+            patch.object(tv, "summarize_resident_chat", return_value = chat),
+            patch.object(tv, "summarize_resident_stt", return_value = stt),
+            patch.object(
+                tv,
+                "free_stt_model_for_training",
+                return_value = ["stt:small"],
+            ) as free_stt,
+            patch.object(
+                tv,
+                "free_chat_models_for_training",
+                return_value = ["hf:chat"],
+            ) as free_chat,
+        ):
+            freed = tv.coordinate_models_for_training(keep)
+        return freed, keep, free_stt, free_chat
+
+    def test_keeps_everything_when_training_fits(self):
+        chat = {"any": True, "loading": False}
+        stt = {"any": True, "loading": False}
+        freed, keep, free_stt, free_chat = self._run(
+            chat,
+            stt,
+            [(True, {"usable_gb": 40, "required_gb": 10})],
+        )
+        self.assertEqual(freed, [])
+        keep.assert_called_once()
+        free_stt.assert_not_called()
+        free_chat.assert_not_called()
+
+    def test_frees_stt_before_chat(self):
+        chat = {"any": True, "loading": False}
+        stt = {"any": True, "loading": False}
+        freed, keep, free_stt, free_chat = self._run(
+            chat,
+            stt,
+            [
+                (False, {"usable_gb": 8, "required_gb": 10}),
+                (True, {"usable_gb": 12, "required_gb": 10}),
+            ],
+        )
+        self.assertEqual(freed, ["stt:small"])
+        self.assertEqual(keep.call_count, 2)
+        free_stt.assert_called_once()
+        free_chat.assert_not_called()
+
+    def test_frees_chat_when_stt_is_not_enough(self):
+        chat = {"any": True, "loading": False}
+        stt = {"any": True, "loading": False}
+        freed, keep, free_stt, free_chat = self._run(
+            chat,
+            stt,
+            [
+                (False, {"usable_gb": 8, "required_gb": 10}),
+                (False, {"usable_gb": 9, "required_gb": 10}),
+            ],
+        )
+        self.assertEqual(freed, ["stt:small", "hf:chat"])
+        self.assertEqual(keep.call_count, 2)
+        free_stt.assert_called_once()
+        free_chat.assert_called_once()
+
+    def test_frees_loading_models_without_probe(self):
+        chat = {"any": True, "loading": True}
+        stt = {"any": True, "loading": True}
+        freed, keep, free_stt, free_chat = self._run(chat, stt, [])
+        self.assertEqual(freed, ["stt:small", "hf:chat"])
+        keep.assert_not_called()
+        free_stt.assert_called_once()
+        free_chat.assert_called_once()
+
+    def test_cancels_loading_stt_without_probe(self):
+        chat = {"any": False, "loading": False}
+        stt = {"any": True, "loading": True}
+        freed, keep, free_stt, free_chat = self._run(chat, stt, [])
+        self.assertEqual(freed, ["stt:small"])
+        keep.assert_not_called()
+        free_stt.assert_called_once()
+        free_chat.assert_not_called()
+
+
 if __name__ == "__main__":
     unittest.main()
diff --git a/studio/backend/tests/test_transformers_version.py b/studio/backend/tests/test_transformers_version.py
index a6e6803a5c..acb2ec449b 100644
--- a/studio/backend/tests/test_transformers_version.py
+++ b/studio/backend/tests/test_transformers_version.py
@@ -160,6 +160,25 @@ class TestResolveBaseModel:
 class TestRemoteLoraBase:
     """_remote_lora_base reads a remote adapter's base from its Hub adapter_config.json."""
 
+    @pytest.fixture(autouse = True)
+    def _selected_cache_follows_env(self, monkeypatch):
+        # The cache helpers now read the selected cache (get_hf_cache_paths),
+        # which snapshots env at import; make it follow the HF_HUB_CACHE these
+        # tests set so they keep driving the lookup via env.
+        monkeypatch.setattr(
+            "utils.transformers_version.get_hf_cache_paths",
+            lambda: _types.SimpleNamespace(
+                hub_cache = Path(
+                    os.environ.get("HF_HUB_CACHE")
+                    or os.environ.get("HUGGINGFACE_HUB_CACHE")
+                    or os.path.join(
+                        os.environ.get("HF_HOME") or os.path.expanduser("~/.cache/huggingface"),
+                        "hub",
+                    )
+                )
+            ),
+        )
+
     @staticmethod
     def _resp(cfg: dict):
         class _Resp:
@@ -645,6 +664,24 @@ def _hf_response(cfg: dict):
 class TestConfigJsonHfCacheFallback:
     """HF hub cache is consulted only offline or after a failed fetch (never stale online)."""
 
+    @pytest.fixture(autouse = True)
+    def _selected_cache_follows_env(self, monkeypatch):
+        # As above: route the selected-cache lookup through the HF_HUB_CACHE env
+        # these tests set, since get_hf_cache_paths snapshots env at import.
+        monkeypatch.setattr(
+            "utils.transformers_version.get_hf_cache_paths",
+            lambda: _types.SimpleNamespace(
+                hub_cache = Path(
+                    os.environ.get("HF_HUB_CACHE")
+                    or os.environ.get("HUGGINGFACE_HUB_CACHE")
+                    or os.path.join(
+                        os.environ.get("HF_HOME") or os.path.expanduser("~/.cache/huggingface"),
+                        "hub",
+                    )
+                )
+            ),
+        )
+
     def setup_method(self):
         _config_json_cache.clear()
 
diff --git a/studio/backend/tests/test_whisper_cpp_freshness.py b/studio/backend/tests/test_whisper_cpp_freshness.py
new file mode 100644
index 0000000000..69f0c87cee
--- /dev/null
+++ b/studio/backend/tests/test_whisper_cpp_freshness.py
@@ -0,0 +1,156 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Tests for the whisper.cpp prebuilt freshness check.
+
+Pins the whisper-specific version policy: the release-tag parser, the
+is_behind decision matrix (with its downgrade guard), and one end-to-end
+wiring smoke through the shared freshness flow. The shared marker-walk and
+fail-open mechanics are covered by test_llama_cpp_freshness.py.
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+import types as _types
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+
+_BACKEND_DIR = str(Path(__file__).resolve().parent.parent)
+if _BACKEND_DIR not in sys.path:
+    sys.path.insert(0, _BACKEND_DIR)
+
+
+class _NoopLogger:
+    """structlog-style logger: every method swallows positional + kwargs."""
+
+    def __getattr__(self, _name):
+        return lambda *a, **k: None
+
+
+_loggers_stub = _types.ModuleType("loggers")
+_loggers_stub.get_logger = lambda *a, **k: _NoopLogger()
+sys.modules.setdefault("loggers", _loggers_stub)
+
+_structlog_stub = _types.ModuleType("structlog")
+_structlog_stub.get_logger = lambda *a, **k: _NoopLogger()
+sys.modules.setdefault("structlog", _structlog_stub)
+
+import pytest
+
+from utils import whisper_cpp_freshness as fr
+
+
+# Helpers.
+
+
+def _write_marker(install_dir: Path, **overrides) -> Path:
+    payload = {
+        "requested_tag": "latest",
+        "release_tag": "v1.9.1-unsloth.1",
+        "upstream_tag": "v1.9.1",
+        "published_repo": "unslothai/whisper.cpp",
+        "asset": "whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz",
+        "asset_sha256": None,
+        "source": "published",
+        "installed_at_utc": (datetime.now(tz = timezone.utc) - timedelta(days = 1))
+        .isoformat()
+        .replace("+00:00", "Z"),
+    }
+    payload.update(overrides)
+    install_dir.mkdir(parents = True, exist_ok = True)
+    marker = install_dir / "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+    marker.write_text(json.dumps(payload))
+    return marker
+
+
+def _fake_binary(install_dir: Path) -> Path:
+    """Stub whisper-server under the canonical cmake install layout."""
+    bin_dir = install_dir / "build" / "bin"
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    bin_path = bin_dir / "whisper-server"
+    bin_path.write_text("stub\n")
+    return bin_path
+
+
+@pytest.fixture(autouse = True)
+def _reset(monkeypatch, tmp_path):
+    # Isolate disk cache per-test; never touch the real cache.
+    monkeypatch.setattr(fr, "_cache_dir", lambda: tmp_path / ".freshness")
+    fr.reset_caches()
+    yield
+    fr.reset_caches()
+
+
+# parse_release_version.
+
+
+def test_parse_release_version():
+    assert fr.parse_release_version("v1.9.1-unsloth.2") == (1, 9, 1, 2)
+    assert fr.parse_release_version("1.10.0") == (1, 10, 0, 0)  # no v, no serial
+    assert fr.parse_release_version(" v2.0.0-unsloth.10 ") == (2, 0, 0, 10)
+    assert fr.parse_release_version("v1.9") == (1, 9, 0, 0)  # padded
+    assert fr.parse_release_version("nightly") is None
+    assert fr.parse_release_version(None) is None
+    assert fr.parse_release_version("") is None
+
+
+# is_behind decision matrix + downgrade guard.
+
+
+def test_is_behind_serial_bump():
+    assert fr.is_behind("v1.9.1-unsloth.1", "v1.9.1-unsloth.2") is True
+
+
+def test_is_behind_downgrade_guard():
+    # A lower serial or version is never "behind".
+    assert fr.is_behind("v1.9.1-unsloth.2", "v1.9.1-unsloth.1") is False
+    assert fr.is_behind("v1.10.0-unsloth.1", "v1.9.1-unsloth.9") is False
+
+
+def test_is_behind_upstream_bump():
+    assert fr.is_behind("v1.9.1-unsloth.1", "v1.10.0-unsloth.1") is True
+
+
+def test_is_behind_identical_is_false():
+    assert fr.is_behind("v1.9.1-unsloth.1", "v1.9.1-unsloth.1") is False
+
+
+def test_is_behind_unparseable_differs_is_behind():
+    assert fr.is_behind("v1.9.1-unsloth.1", "nightly") is True
+
+
+def test_is_behind_missing_side_fails_open():
+    assert fr.is_behind(None, "v1.9.1-unsloth.2") is False
+    assert fr.is_behind("v1.9.1-unsloth.1", None) is False
+
+
+# check_prebuilt_freshness end-to-end.
+
+
+def test_check_prebuilt_freshness_reports_stale_when_old_and_behind(monkeypatch, tmp_path):
+    _write_marker(
+        tmp_path,
+        release_tag = "v1.9.1-unsloth.1",
+        installed_at_utc = (datetime.now(tz = timezone.utc) - timedelta(days = 10))
+        .isoformat()
+        .replace("+00:00", "Z"),
+    )
+    bin_path = _fake_binary(tmp_path)
+    monkeypatch.setattr(fr, "latest_published_release", lambda *a, **k: "v1.9.1-unsloth.3")
+    info = fr.check_prebuilt_freshness(str(bin_path))
+    assert info["has_marker"] is True
+    assert info["behind"] is True
+    assert info["stale"] is True
+    assert info["installed_tag"] == "v1.9.1-unsloth.1"
+    assert info["latest_tag"] == "v1.9.1-unsloth.3"
+
+
+def test_marker_reader_prefers_install_root_over_packaging_marker(tmp_path):
+    root_marker = _write_marker(tmp_path, release_tag = "v1.9.1-unsloth.2")
+    binary = _fake_binary(tmp_path)
+    (binary.parent / root_marker.name).write_text(
+        json.dumps({"backend": "slim", "release_tag": "archive-metadata"})
+    )
+    assert fr.read_install_marker(str(binary))["release_tag"] == "v1.9.1-unsloth.2"
diff --git a/studio/backend/tests/test_windows_external_drive_paths.py b/studio/backend/tests/test_windows_external_drive_paths.py
index 9686d45c9f..5687612916 100644
--- a/studio/backend/tests/test_windows_external_drive_paths.py
+++ b/studio/backend/tests/test_windows_external_drive_paths.py
@@ -57,6 +57,18 @@ def test_windows_drive_roots_empty_off_windows(monkeypatch):
     assert external_media.windows_drive_roots() == []
 
 
+def test_macos_volume_roots_lists_readable_mounts(monkeypatch, tmp_path):
+    volumes = tmp_path / "Volumes"
+    external = volumes / "External SSD"
+    unreadable = volumes / "Unavailable"
+    external.mkdir(parents = True)
+    unreadable.mkdir()
+    monkeypatch.setattr(external_media.platform, "system", lambda: "Darwin")
+    monkeypatch.setattr(external_media.os, "access", lambda path, _mode: Path(path) == external)
+
+    assert external_media.macos_volume_roots(volumes) == [external]
+
+
 def test_windows_drive_roots_lists_readable_drives(monkeypatch):
     _stub_windows(monkeypatch, {"C", "D", "E"})
 
@@ -204,8 +216,10 @@ def test_browse_allowlist_includes_windows_drive_roots(monkeypatch, tmp_path):
     )
     fake_external_media = SimpleNamespace(
         linux_run_media_mount_roots = lambda: [],
+        macos_volume_roots = lambda: [],
         windows_drive_roots = lambda: [drive_root],
     )
+    fake_paths.external_media = fake_external_media
     fake_studio_db = SimpleNamespace(
         list_scan_folders = lambda: [],
         contains_sensitive_path_component = lambda _p: False,
@@ -270,8 +284,10 @@ def test_build_browse_allowlist_reuses_passed_roots(monkeypatch, tmp_path):
     )
     fake_external_media = SimpleNamespace(
         linux_run_media_mount_roots = _media_roots,
+        macos_volume_roots = lambda: [],
         windows_drive_roots = _drive_roots,
     )
+    fake_paths.external_media = fake_external_media
     fake_studio_db = SimpleNamespace(list_scan_folders = lambda: [])
     monkeypatch.setitem(sys.modules, "utils.paths", fake_paths)
     monkeypatch.setitem(sys.modules, "utils.paths.external_media", fake_external_media)
diff --git a/studio/backend/utils/datasets/format_conversion.py b/studio/backend/utils/datasets/format_conversion.py
index 95c9a00534..9035068c01 100644
--- a/studio/backend/utils/datasets/format_conversion.py
+++ b/studio/backend/utils/datasets/format_conversion.py
@@ -406,10 +406,13 @@ def convert_to_vlm_format(
             elif _image_lookup is not None and image_data in _image_lookup:
                 # Bare filename → resolve via HF repo lookup
                 from huggingface_hub import hf_hub_download
+                from utils.hf_cache_settings import active_hf_hub_cache
+
                 local_path = hf_hub_download(
                     dataset_name,
                     _image_lookup[image_data],
                     repo_type = "dataset",
+                    cache_dir = active_hf_hub_cache(),
                 )
                 image_data = Image.open(local_path).convert("RGB")
             else:
@@ -774,10 +777,13 @@ def convert_sharegpt_with_images_to_vlm_format(
                     return Image.open(BytesIO(f.read())).convert("RGB")
             elif _image_lookup is not None and image_data in _image_lookup:
                 from huggingface_hub import hf_hub_download
+                from utils.hf_cache_settings import active_hf_hub_cache
+
                 local_path = hf_hub_download(
                     dataset_name,
                     _image_lookup[image_data],
                     repo_type = "dataset",
+                    cache_dir = active_hf_hub_cache(),
                 )
                 return Image.open(local_path).convert("RGB")
             else:
diff --git a/studio/backend/utils/datasets/llm_assist.py b/studio/backend/utils/datasets/llm_assist.py
index f7b35e2869..c594e883a8 100644
--- a/studio/backend/utils/datasets/llm_assist.py
+++ b/studio/backend/utils/datasets/llm_assist.py
@@ -58,6 +58,7 @@ def precache_helper_gguf():
     try:
         from huggingface_hub import HfApi, hf_hub_download
         from huggingface_hub.utils import disable_progress_bars, enable_progress_bars
+        from utils.hf_cache_settings import active_hf_hub_cache
 
         disable_progress_bars()
         logging.getLogger("huggingface_hub").setLevel(logging.WARNING)
@@ -76,7 +77,11 @@ def precache_helper_gguf():
                 + (f" (+{len(matching) - 1} shards)" if len(matching) > 1 else "")
             )
             for target in matching:
-                hf_hub_download(repo_id = repo, filename = target)
+                hf_hub_download(
+                    repo_id = repo,
+                    filename = target,
+                    cache_dir = active_hf_hub_cache(),
+                )
             logger.info(f"Helper GGUF cached: {len(matching)} file(s)")
         else:
             logger.warning(f"No GGUF matching variant '{variant}' in {repo}")
diff --git a/studio/backend/utils/hardware/hardware.py b/studio/backend/utils/hardware/hardware.py
index 9fef53e65e..3d312d4b01 100644
--- a/studio/backend/utils/hardware/hardware.py
+++ b/studio/backend/utils/hardware/hardware.py
@@ -734,6 +734,141 @@ def _rocm_linux_sysfs_vram_gb() -> tuple[Optional[float], Optional[float]]:
         return None, None
 
 
+# 0x1002. NVIDIA's open kernel module also registers KFD nodes (vendor_id 0x10DE);
+# a non-AMD node is not a HIP device and must never take an ordinal.
+_AMD_PCI_VENDOR_ID = 4098
+
+
+def _rocm_kfd_gpu_pci_ids() -> list[str]:
+    """PCI addresses of the GPUs ROCm enumerates, in HIP device order.
+
+    Reads /sys/class/kfd/kfd/topology/nodes/<N>/properties, the topology ROCm
+    itself enumerates from: AMD GPU nodes (simd_count > 0 excludes CPUs,
+    vendor_id == AMD excludes NVIDIA) in node-id order are HIP's device order, so
+    position N is ROCm physical device N. Unlike DRM sysfs, an amdgpu adapter HIP
+    cannot enumerate has no node here, so it never consumes an ordinal.
+
+    Returns [] (disabling the overlay) when KFD is absent, and FAILS CLOSED the
+    same way on any unreadable node or an AMD node with no location_id: dropping
+    one would shift every later ordinal and let a similar-capacity GPU pass the
+    total-size guard while showing another card's usage.
+
+    location_id is the kernel's (bus << 8) | devfn; domain is separate.
+    """
+    nodes: list[tuple[int, str]] = []
+    try:
+        node_dirs = glob.glob("/sys/class/kfd/kfd/topology/nodes/*")
+    except Exception:
+        return []
+    for node_dir in node_dirs:
+        m = re.fullmatch(r".*/(\d+)", node_dir)
+        if m is None:
+            continue
+        props: dict[str, int] = {}
+        try:
+            with open(os.path.join(node_dir, "properties")) as f:
+                for line in f:
+                    parts = line.split()
+                    if len(parts) == 2:
+                        try:
+                            props[parts[0]] = int(parts[1])
+                        except ValueError:
+                            continue
+        except OSError:
+            return []  # unreadable node could be a GPU: fail closed, don't shift
+        if props.get("simd_count", 0) <= 0:
+            continue  # CPU node, not a GPU
+        if props.get("vendor_id") != _AMD_PCI_VENDOR_ID:
+            continue  # non-AMD GPU node (NVIDIA open driver): not a HIP device
+        location_id = props.get("location_id")
+        if location_id is None:
+            return []  # an AMD GPU we cannot place: fail closed for the whole map
+        domain = props.get("domain", 0)
+        bus = (location_id >> 8) & 0xFF
+        devfn = location_id & 0xFF
+        bdf = f"{domain:04x}:{bus:02x}:{(devfn >> 3) & 0x1F:02x}.{devfn & 0x7}"
+        nodes.append((int(m.group(1)), bdf))
+    nodes.sort(key = lambda n: n[0])
+    return [bdf for _node_id, bdf in nodes]
+
+
+def _rocm_linux_amdgpu_cards() -> list[tuple[str, int, str]]:
+    """The amdgpu-bound DRM cards in PCI order: ``(pci_bdf, card_no, device_dir)``.
+
+    Membership is by the BOUND DRIVER, not the VRAM sysfs files: an AMD device
+    with incomplete sysfs support (some APUs expose no mem_info_vram_*) still
+    consumes a ROCm ordinal, and dropping it would shift every later card down.
+    PCI order is HIP's default enumeration order, so list position is the ROCm
+    ordinal; card_no is a stable tiebreak when the BDF cannot be resolved.
+
+    NOTE this is a superset of the ROCm-visible set (a HIP-unsupported amdgpu
+    adapter appears too), so callers must check the counts agree before assuming
+    a 1:1 mapping onto torch devices.
+    """
+    if platform.system() != "Linux":
+        return []
+    amd_cards: list[tuple[str, int, str]] = []
+    try:
+        for card_path in glob.glob("/sys/class/drm/card*"):
+            # Match card<N> exactly so connector nodes (card0-DP-1) are skipped.
+            m = re.fullmatch(r".*/card(\d+)", card_path)
+            if m is None:
+                continue
+            dev_dir = os.path.join(card_path, "device")
+            try:
+                driver = os.path.basename(os.path.realpath(os.path.join(dev_dir, "driver")))
+            except OSError:
+                continue
+            if driver != "amdgpu":
+                continue  # foreign adapter: not a ROCm device, takes no ordinal
+            try:
+                bdf = os.path.basename(os.path.realpath(dev_dir))
+            except OSError:
+                bdf = ""
+            amd_cards.append((bdf, int(m.group(1)), dev_dir))
+    except Exception:
+        return []
+    amd_cards.sort(key = lambda c: (c[0], c[1]))
+    return amd_cards
+
+
+def _rocm_linux_sysfs_vram_by_pci_gb() -> dict[str, tuple[float, float]]:
+    """System-wide AMD VRAM via Linux DRM sysfs, keyed by the card's PCI address.
+
+    Reads each card's mem_info_vram_{used,total} (kernel-updated across all
+    processes) so every GPU gets its own figure, unlike _rocm_linux_sysfs_vram_gb
+    which sums the host. Keyed by PCI address, not an ordinal, so the caller can
+    join it to _rocm_kfd_gpu_pci_ids() by identity: DRM card numbers include
+    foreign adapters and this set includes cards HIP does not enumerate, so any
+    ordinal from this list alone can be shifted relative to ROCm's. A card with
+    missing/unreadable/zero-total figures simply has no entry. Empty off Linux.
+    """
+    if platform.system() != "Linux":
+        return {}
+
+    try:
+        by_pci: dict[str, tuple[float, float]] = {}
+        for bdf, _card_no, dev_dir in _rocm_linux_amdgpu_cards():
+            if not bdf:
+                continue
+            try:
+                with open(os.path.join(dev_dir, "mem_info_vram_used")) as f:
+                    used_bytes = int(f.read().strip())
+                with open(os.path.join(dev_dir, "mem_info_vram_total")) as f:
+                    total_bytes = int(f.read().strip())
+            except (OSError, ValueError):
+                continue
+            if total_bytes <= 0:
+                continue
+            by_pci[bdf.lower()] = (
+                round(used_bytes / (1024**3), 2),
+                round(total_bytes / (1024**3), 2),
+            )
+        return by_pci
+    except Exception:
+        return {}
+
+
 # ── Windows AMD/ROCm per-adapter VRAM (issue #7072) ──────────────────────────
 # amd-smi is disabled and hipMemGetInfo reports free==total, so read used from the
 # per-LUID "GPU Adapter Memory" perf counters and take each total from torch, so
@@ -1222,6 +1357,75 @@ def _reconcile_primary_rocm_unified_memory(
     _apply_unified_memory_correction(utilization, torch_devices[0])
 
 
+def _rocm_visibility_mask_active() -> bool:
+    """True when any ROCm/CUDA visibility variable filters the device set."""
+    for var in (
+        "HIP_VISIBLE_DEVICES",
+        "ROCR_VISIBLE_DEVICES",
+        "CUDA_VISIBLE_DEVICES",
+        "GPU_DEVICE_ORDINAL",
+    ):
+        value = os.environ.get(var)
+        if value and value.strip():
+            return True
+    return False
+
+
+def _overlay_system_wide_vram(devices: list[Dict[str, Any]]) -> None:
+    """Replace process-local torch VRAM with system-wide Linux ROCm figures.
+
+    The torch fallback is process-local, so a model served by the separate
+    llama-server process reads as ~0 used even with the GPU full (#7072). DRM
+    sysfs gives per-card figures the kernel updates across all processes. Sources
+    are matched by the device's PHYSICAL index (never list position), and only
+    when NO visibility mask is active and the device count equals the host GPU
+    count; under any mask the index is not a verifiable host ordinal, so torch's
+    figures are kept. Best-effort, in place: a device with no matching card, or a
+    unified-memory APU whose sysfs total is below torch's GTT-backed total, keeps
+    torch's (mirrors _apply_unified_memory_correction).
+
+    Windows is intentionally not overlaid: its per-adapter perf counters cannot be
+    mapped to ROCm ordinals and miss WDDM shared memory, so the multi-GPU view
+    keeps torch there rather than risk misattributing another adapter's usage.
+    """
+    if not devices or platform.system() != "Linux":
+        return
+    # Match by PCI identity, never list position: index N in KFD topology is ROCm
+    # physical device N and carries its PCI address, which DRM sysfs keys on too.
+    # The two gates below verify ``index`` really is a host-physical ordinal
+    # (torch exposes no PCI id to check directly):
+    #   * No visibility mask -- any mask makes ``index`` container/ROCR-relative
+    #     rather than a host ordinal.
+    #   * Device count == host GPU count -- rules out a device-cgroup container
+    #     that sets no env var yet compacts torch's indices from zero.
+    pci_by_ordinal = _rocm_kfd_gpu_pci_ids()
+    if not pci_by_ordinal:
+        return
+    if _rocm_visibility_mask_active() or len(devices) != len(pci_by_ordinal):
+        return
+    vram_by_pci = _rocm_linux_sysfs_vram_by_pci_gb()
+    for dev in devices:
+        index = dev.get("index")
+        if not isinstance(index, int) or not (0 <= index < len(pci_by_ordinal)):
+            continue
+        entry = vram_by_pci.get(pci_by_ordinal[index].lower())
+        if entry is None:
+            continue
+        used, total = entry
+        dev_total = dev.get("vram_total_gb") or 0.0
+        # Overlay only a device that maps 1:1 to the whole card: torch total must
+        # match sysfs total within ~10%. A mismatch either way means a different
+        # memory scope -- a unified-memory APU (sysfs sees only the dedicated
+        # slice, torch the GTT pool) or a partitioned MI300 (sysfs reports the
+        # whole card, dwarfing a partition) -- and overlaying would misstate free
+        # VRAM (a partition would look like it has the whole card free).
+        if dev_total <= 0 or abs(total - dev_total) > 0.1 * dev_total:
+            continue
+        dev["vram_used_gb"] = used
+        dev["vram_total_gb"] = total
+        dev["vram_utilization_pct"] = round((used / total) * 100, 1) if total > 0 else None
+
+
 def get_visible_gpu_utilization() -> Dict[str, Any]:
     device = get_device()
 
@@ -1317,6 +1521,12 @@ def get_visible_gpu_utilization() -> Dict[str, Any]:
                         "power_utilization_pct": None,
                     }
                 )
+            if IS_ROCM and index_kind == "physical":
+                # Swap process-local torch VRAM for system-wide sysfs so a model
+                # held by the separate llama-server process shows up (#7072).
+                # Physical-index only: a relative index (UUID/MIG mask) is not a
+                # host GPU id. The overlay verifies the rest itself.
+                _overlay_system_wide_vram(devices)
             return {
                 "available": True,
                 "backend": _backend_label(device),
diff --git a/studio/backend/utils/hf_cache_settings.py b/studio/backend/utils/hf_cache_settings.py
new file mode 100644
index 0000000000..07d901a3d2
--- /dev/null
+++ b/studio/backend/utils/hf_cache_settings.py
@@ -0,0 +1,362 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Live, persisted Hugging Face cache routing for Unsloth Studio.
+
+Hugging Face reads cache environment variables at import time.  Studio therefore
+owns an explicit cache snapshot for each operation instead of trying to refresh
+``huggingface_hub.constants`` in the long-running API process.
+"""
+
+from __future__ import annotations
+
+import os
+import shutil
+import tempfile
+import threading
+from contextlib import contextmanager
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Iterator, Literal, Mapping, Optional
+
+
+CACHE_HOME_SETTING_KEY = "hugging_face_cache_home"
+CACHE_HISTORY_SETTING_KEY = "hugging_face_cache_history"
+MAX_CACHE_HISTORY = 16
+
+CacheSource = Literal["default", "studio", "environment"]
+
+_CACHE_ENV_KEYS = (
+    "HF_HOME",
+    "HF_HUB_CACHE",
+    "HUGGINGFACE_HUB_CACHE",
+    "HF_XET_CACHE",
+)
+# Imported by storage_roots._setup_cache_env before Studio seeds defaults.
+_EXPLICIT_CACHE_ENV = {
+    key: value.strip()
+    for key in _CACHE_ENV_KEYS
+    if (value := os.environ.get(key)) is not None and value.strip()
+}
+_settings_lock = threading.RLock()
+_spawn_env_lock = threading.RLock()
+
+
+@dataclass(frozen = True)
+class HuggingFaceCachePaths:
+    cache_home: Path
+    hub_cache: Path
+    xet_cache: Path
+    source: CacheSource
+    environment_variable: Optional[str] = None
+
+    @property
+    def editable(self) -> bool:
+        return self.source != "environment"
+
+    @property
+    def is_custom(self) -> bool:
+        return self.source == "studio"
+
+    def child_env(self, base: Optional[Mapping[str, str]] = None) -> dict[str, str]:
+        env = dict(os.environ if base is None else base)
+        # Do not rewrite HF_HOME. It also owns HF's token path, and credentials
+        # must not be moved onto a removable cache volume.
+        env["HF_HUB_CACHE"] = str(self.hub_cache)
+        env["HF_XET_CACHE"] = str(self.xet_cache)
+        env.pop("HUGGINGFACE_HUB_CACHE", None)
+        return env
+
+
+def _default_cache_home() -> Path:
+    xdg = (os.environ.get("XDG_CACHE_HOME") or "").strip()
+    return (Path(xdg).expanduser() if xdg else Path.home() / ".cache") / "huggingface"
+
+
+def _canonical(path: Path | str) -> Path:
+    return Path(path).expanduser().resolve(strict = False)
+
+
+def _environment_paths() -> Optional[HuggingFaceCachePaths]:
+    explicit_home = _EXPLICIT_CACHE_ENV.get("HF_HOME")
+    explicit_hub = _EXPLICIT_CACHE_ENV.get("HF_HUB_CACHE") or _EXPLICIT_CACHE_ENV.get(
+        "HUGGINGFACE_HUB_CACHE"
+    )
+    if not explicit_home and not explicit_hub:
+        return None
+    explicit_xet = _EXPLICIT_CACHE_ENV.get("HF_XET_CACHE")
+    default_home = _default_cache_home()
+    hf_home = _canonical(explicit_home) if explicit_home else default_home
+    hub = _canonical(explicit_hub) if explicit_hub else hf_home / "hub"
+    xet = _canonical(explicit_xet) if explicit_xet else hf_home / "xet"
+    controlling = next(
+        key
+        for key in ("HF_HUB_CACHE", "HUGGINGFACE_HUB_CACHE", "HF_HOME")
+        if key in _EXPLICIT_CACHE_ENV
+    )
+    # Settings describes model downloads, so an explicit hub path is the
+    # displayed/opened location even when HF_HOME points somewhere else for
+    # credentials or XET data.
+    display_home = (
+        (hub.parent if explicit_hub and hub.name.lower() == "hub" else hub)
+        if explicit_hub
+        else hf_home
+    )
+    return HuggingFaceCachePaths(display_home, hub, xet, "environment", controlling)
+
+
+def _stored_cache_home() -> Optional[Path]:
+    try:
+        from storage.studio_db import get_app_setting
+        value = get_app_setting(CACHE_HOME_SETTING_KEY, None)
+    except Exception:
+        return None
+    if not isinstance(value, str) or not value.strip():
+        return None
+    try:
+        return _canonical(value.strip())
+    except (OSError, RuntimeError, ValueError):
+        return None
+
+
+def get_hf_cache_paths() -> HuggingFaceCachePaths:
+    env_paths = _environment_paths()
+    if env_paths is not None:
+        return env_paths
+    stored = _stored_cache_home()
+    if stored is not None:
+        xet = _EXPLICIT_CACHE_ENV.get("HF_XET_CACHE")
+        return HuggingFaceCachePaths(
+            stored,
+            stored / "hub",
+            _canonical(xet) if xet else stored / "xet",
+            "studio",
+        )
+    home = _default_cache_home()
+    xet = _EXPLICIT_CACHE_ENV.get("HF_XET_CACHE")
+    return HuggingFaceCachePaths(
+        home,
+        home / "hub",
+        _canonical(xet) if xet else home / "xet",
+        "default",
+    )
+
+
+def active_hf_hub_cache() -> str:
+    """Return the current hub cache as a string for library call kwargs."""
+
+    return str(get_hf_cache_paths().hub_cache)
+
+
+@contextmanager
+def child_environment_for_spawn(environment: Mapping[str, str]) -> Iterator[None]:
+    """Apply captured env before spawn imports the child entrypoint.
+
+    Applying variables only inside the multiprocessing target can be too late
+    for libraries that snapshot environment variables at import. The lock keeps
+    this short parent-process override atomic through ``Process.start()``.
+    """
+
+    with _spawn_env_lock:
+        missing = object()
+        saved_environment: dict[str, str | object] = {}
+        for key, value in environment.items():
+            saved_environment[key] = os.environ.get(key, missing)
+            os.environ[key] = value
+        try:
+            yield
+        finally:
+            for key, previous in saved_environment.items():
+                if previous is missing:
+                    os.environ.pop(key, None)
+                else:
+                    os.environ[key] = str(previous)
+
+
+def initialize_hf_cache_environment() -> HuggingFaceCachePaths:
+    """Seed import-time HF variables once during backend startup."""
+
+    paths = get_hf_cache_paths()
+    # Preserve an explicit HF_HOME, otherwise keep credentials at the platform
+    # default while routing cache bytes through the selected home.
+    if not os.environ.get("HF_HOME", "").strip():
+        os.environ["HF_HOME"] = str(_default_cache_home())
+    os.environ["HF_HUB_CACHE"] = str(paths.hub_cache)
+    os.environ["HF_XET_CACHE"] = str(paths.xet_cache)
+    if "HUGGINGFACE_HUB_CACHE" not in _EXPLICIT_CACHE_ENV:
+        os.environ.pop("HUGGINGFACE_HUB_CACHE", None)
+    for directory in (paths.hub_cache, paths.xet_cache):
+        try:
+            directory.mkdir(parents = True, exist_ok = True)
+        except OSError:
+            pass
+    return paths
+
+
+def _validate_cache_home(raw_path: str) -> Path:
+    value = raw_path.strip()
+    if not value:
+        raise ValueError("Choose a cache folder.")
+    candidate = Path(value).expanduser()
+    if not candidate.is_absolute():
+        raise ValueError("The Hugging Face cache folder must be an absolute path.")
+    try:
+        resolved = candidate.resolve(strict = False)
+    except (OSError, RuntimeError, ValueError) as exc:
+        raise ValueError("The Hugging Face cache folder is invalid.") from exc
+
+    if resolved.parent == resolved:
+        raise ValueError("Choose a folder inside the filesystem or drive root.")
+    try:
+        from hub.storage.scan_folders import (
+            contains_sensitive_path_component,
+            is_denied_system_path,
+        )
+    except ImportError:
+        contains_sensitive_path_component = is_denied_system_path = None
+    if is_denied_system_path is not None and is_denied_system_path(str(resolved)):
+        raise ValueError("System folders cannot be used for model downloads.")
+    if contains_sensitive_path_component is not None and contains_sensitive_path_component(
+        str(resolved)
+    ):
+        raise ValueError("Credential or config folders cannot be used for model downloads.")
+
+    parent = resolved.parent
+    if not parent.exists() or not parent.is_dir():
+        raise ValueError("The parent folder does not exist.")
+    try:
+        resolved.mkdir(exist_ok = True)
+        if not resolved.is_dir():
+            raise ValueError("The selected cache location is not a folder.")
+        for child in (resolved / "hub", resolved / "xet"):
+            child.mkdir(exist_ok = True)
+            with tempfile.NamedTemporaryFile(prefix = ".unsloth-write-test-", dir = child):
+                pass
+    except PermissionError as exc:
+        raise ValueError("Studio does not have permission to write to this folder.") from exc
+    except OSError as exc:
+        raise ValueError(f"Studio cannot use this cache folder: {exc}") from exc
+    return resolved
+
+
+def _stored_history() -> list[Path]:
+    try:
+        from storage.studio_db import get_app_setting
+        raw = get_app_setting(CACHE_HISTORY_SETTING_KEY, [])
+    except Exception:
+        raw = []
+    if not isinstance(raw, list):
+        return []
+    out: list[Path] = []
+    seen: set[str] = set()
+    for value in raw:
+        if not isinstance(value, str) or not value.strip():
+            continue
+        try:
+            path = _canonical(value)
+        except (OSError, RuntimeError, ValueError):
+            continue
+        key = os.path.normcase(str(path))
+        if key in seen:
+            continue
+        seen.add(key)
+        out.append(path)
+    return out[:MAX_CACHE_HISTORY]
+
+
+def set_hf_cache_home(cache_home: Optional[str]) -> HuggingFaceCachePaths:
+    if _environment_paths() is not None:
+        raise RuntimeError("The Hugging Face cache location is managed by an environment variable.")
+    with _settings_lock:
+        previous = _stored_cache_home()
+        next_home = _validate_cache_home(cache_home) if cache_home is not None else None
+        history = _stored_history()
+        if previous is not None and previous != next_home:
+            history.insert(0, previous)
+        deduped: list[str] = []
+        seen: set[str] = set()
+        for path in history:
+            key = os.path.normcase(str(path))
+            if key in seen or path == next_home:
+                continue
+            seen.add(key)
+            deduped.append(str(path))
+            if len(deduped) >= MAX_CACHE_HISTORY:
+                break
+        from storage.studio_db import upsert_app_settings
+
+        upsert_app_settings(
+            {
+                CACHE_HOME_SETTING_KEY: str(next_home) if next_home is not None else None,
+                CACHE_HISTORY_SETTING_KEY: deduped,
+            }
+        )
+    # Inventory scans are cached independently from settings. Invalidate after
+    # persistence so the next request sees both the new active root and history.
+    from hub.utils.inventory_scan import invalidate_hf_cache_scans
+
+    invalidate_hf_cache_scans()
+    return get_hf_cache_paths()
+
+
+def known_hf_cache_homes() -> list[Path]:
+    paths = get_hf_cache_paths()
+    stored = _stored_cache_home()
+    candidates: list[Path] = []
+    if paths.source != "environment":
+        candidates.append(paths.cache_home)
+    elif explicit_home := _EXPLICIT_CACHE_ENV.get("HF_HOME"):
+        candidates.append(_canonical(explicit_home))
+    if stored is not None:
+        candidates.append(stored)
+    candidates.extend([*_stored_history(), _default_cache_home()])
+    out: list[Path] = []
+    seen: set[str] = set()
+    for candidate in candidates:
+        try:
+            canonical = _canonical(candidate)
+        except (OSError, RuntimeError, ValueError):
+            continue
+        key = os.path.normcase(str(canonical))
+        if key in seen:
+            continue
+        seen.add(key)
+        out.append(canonical)
+    return out
+
+
+def known_hf_hub_caches() -> list[Path]:
+    active = get_hf_cache_paths()
+    out = [active.hub_cache]
+    seen = {os.path.normcase(str(_canonical(active.hub_cache)))}
+    for home in known_hf_cache_homes():
+        hub = _canonical(home / "hub")
+        key = os.path.normcase(str(hub))
+        if key not in seen:
+            seen.add(key)
+            out.append(hub)
+    return out
+
+
+def cache_status(paths: Optional[HuggingFaceCachePaths] = None) -> dict:
+    paths = paths or get_hf_cache_paths()
+    available = paths.cache_home.is_dir()
+    writable = available and os.access(paths.cache_home, os.W_OK | os.X_OK)
+    free_bytes: Optional[int] = None
+    if available:
+        try:
+            free_bytes = int(shutil.disk_usage(paths.cache_home).free)
+        except OSError:
+            pass
+    return {
+        "cache_home": str(paths.cache_home),
+        "hub_cache": str(paths.hub_cache),
+        "xet_cache": str(paths.xet_cache),
+        "source": paths.source,
+        "editable": paths.editable,
+        "is_custom": paths.is_custom,
+        "available": available,
+        "writable": writable,
+        "free_bytes": free_bytes,
+        "environment_variable": paths.environment_variable,
+    }
diff --git a/studio/backend/utils/hf_xet_fallback.py b/studio/backend/utils/hf_xet_fallback.py
index 2628b99a2d..49872f371e 100644
--- a/studio/backend/utils/hf_xet_fallback.py
+++ b/studio/backend/utils/hf_xet_fallback.py
@@ -21,6 +21,8 @@ never triggers the heavy load.
 from __future__ import annotations
 
 import threading
+from functools import partial
+from pathlib import Path
 from typing import Any, Callable, Optional
 
 # Defaults mirror unsloth_zoo.hf_xet_fallback; plain literals so they resolve (including as
@@ -262,13 +264,23 @@ __all__ = [
 ]
 
 
-def _studio_prepare_for_http(repo_type: str, repo_id: str) -> None:
+def _studio_prepare_for_http(
+    repo_type: str,
+    repo_id: str,
+    *,
+    cache_dir: Optional[str] = None,
+) -> None:
     """Unsloth's marker-aware purge before an HTTP resume, keeping the download manager's ``.transport``
     accounting consistent (vs unsloth_zoo's generic default). Guarded: a purge failure is logged,
     not fatal to the retry."""
     try:
         from hub.utils.download_registry import prepare_cache_for_transport
-        prepare_cache_for_transport(repo_type, repo_id, "http")
+        prepare_cache_for_transport(
+            repo_type,
+            repo_id,
+            "http",
+            root = Path(cache_dir) if cache_dir else None,
+        )
     except Exception as exc:
         try:
             from loggers import get_logger
@@ -293,9 +305,13 @@ def hf_hub_download_with_xet_fallback(
     grace_period: float = DEFAULT_GRACE_PERIOD,
     on_status: Optional[Callable[[str], None]] = None,
     force_download: bool = False,
+    cache_dir: Optional[str] = None,
 ) -> str:
     """Single-file download via the shared fallback with Unsloth's marker-aware HTTP-retry prep.
     ``force_download`` re-fetches a newer blob over a cached one (Unsloth's model-update path)."""
+    if cache_dir is None:
+        from utils.hf_cache_settings import get_hf_cache_paths
+        cache_dir = str(get_hf_cache_paths().hub_cache)
     return _shared_hf_hub_download_with_xet_fallback(
         repo_id,
         filename,
@@ -308,11 +324,18 @@ def hf_hub_download_with_xet_fallback(
         grace_period = grace_period,
         on_status = on_status,
         force_download = force_download,
-        prepare_for_http_fn = _studio_prepare_for_http,
+        cache_dir = cache_dir,
+        prepare_for_http_fn = partial(_studio_prepare_for_http, cache_dir = cache_dir),
     )
 
 
 def snapshot_download_with_xet_fallback(repo_id: str, **kwargs: Any) -> str:
     """Whole-repo download via the shared fallback with Unsloth's marker-aware HTTP-retry prep."""
-    kwargs.setdefault("prepare_for_http_fn", _studio_prepare_for_http)
+    if kwargs.get("cache_dir") is None:
+        from utils.hf_cache_settings import get_hf_cache_paths
+        kwargs["cache_dir"] = str(get_hf_cache_paths().hub_cache)
+    kwargs.setdefault(
+        "prepare_for_http_fn",
+        partial(_studio_prepare_for_http, cache_dir = kwargs["cache_dir"]),
+    )
     return _shared_snapshot_download_with_xet_fallback(repo_id, **kwargs)
diff --git a/studio/backend/utils/hidden_models.py b/studio/backend/utils/hidden_models.py
index 20d0bb966e..e7c3181d71 100644
--- a/studio/backend/utils/hidden_models.py
+++ b/studio/backend/utils/hidden_models.py
@@ -9,6 +9,7 @@ which eagerly loads the model-config/checkpoint stack, and without importing
 
 from __future__ import annotations
 
+import json
 import re
 from pathlib import Path
 from typing import Optional
@@ -31,6 +32,61 @@ _DEFAULT_EMBEDDING_REPO_IDS = {
 # fallback for Studio's static default embedder only; configured custom repos
 # remain exact-match-only.
 _DEFAULT_EMBEDDING_PATH_BASENAMES = {"bge-small-en-v1.5"}
+# Curated Whisper dictation checkpoints (STT, never chat), hidden from the chat
+# inventory and pickers: Transformers safetensors repos (unsloth/whisper-*) and
+# their GGUF companions (unslothai/whisper-*-GGUF). Custom checkpoints are caught
+# by config below, but the GGUF companions carry a raw .bin (no config.json), so
+# they must be listed here by id or they leak into chat pickers.
+_HIDDEN_STT_REPO_IDS = frozenset(
+    {
+        "unsloth/whisper-tiny",
+        "unsloth/whisper-base",
+        "unsloth/whisper-small",
+        "unsloth/whisper-large-v3-turbo",
+        "unsloth/whisper-large-v3",
+        "unslothai/whisper-tiny-GGUF",
+        "unslothai/whisper-base-GGUF",
+        "unslothai/whisper-small-GGUF",
+        "unslothai/whisper-large-v3-turbo-GGUF",
+        "unslothai/whisper-large-v3-GGUF",
+    }
+)
+
+
+def _config_is_whisper(path: Path) -> bool:
+    """True if a config.json declares a Whisper model."""
+    try:
+        with open(path, "r", encoding = "utf-8") as file:
+            config = json.load(file)
+    except Exception:
+        return False
+    if not isinstance(config, dict):
+        return False
+    model_type = config.get("model_type")
+    if isinstance(model_type, str) and model_type.strip().lower() == "whisper":
+        return True
+    architectures = config.get("architectures")
+    return isinstance(architectures, list) and any(
+        isinstance(name, str) and name == "WhisperForConditionalGeneration"
+        for name in architectures
+    )
+
+
+def _path_is_whisper_model(value: str) -> bool:
+    """Inspect an existing local model path's config; never hides name-only matches."""
+    if _HF_REPO_ID_RE.fullmatch(value.strip()):
+        return False
+    path = Path(value).expanduser()
+    try:
+        if path.is_file():
+            path = path.parent
+        candidates = [path / "config.json"]
+        snapshots = path / "snapshots"
+        if snapshots.is_dir():
+            candidates.extend(child / "config.json" for child in snapshots.iterdir())
+    except OSError:
+        return False
+    return any(_config_is_whisper(candidate) for candidate in candidates)
 
 
 def _safe_resolve(path: Path) -> Optional[str]:
@@ -79,11 +135,11 @@ def _path_basename_is_default_embedder(value: str) -> bool:
 
 def is_hidden_model(*values: str | None) -> bool:
     """True if any id/path is the RAG embedding model (the effective embedder
-    or its GGUF companion repo) or the llama.cpp install validation probe
-    (ggml-org/models / stories260K), so pickers hide them (GGUF and non-GGUF).
-    None are usable chat models; the probe can be cached as a side effect of
-    installing the prebuilt llama-server and otherwise sorts smallest, so it
-    would be auto-selected.
+    or its GGUF companion repo), the llama.cpp install validation probe
+    (ggml-org/models / stories260K), or a curated/custom Whisper dictation
+    model, so pickers hide them (GGUF and non-GGUF). None are usable chat
+    models; the probe can be cached as a side effect of installing the prebuilt
+    llama-server and otherwise sorts smallest, so it would be auto-selected.
 
     Hub repo ids are matched EXACTLY (case-insensitive full "owner/name"), so a
     custom embedder with a generic basename like "org/model" cannot substring
@@ -97,6 +153,7 @@ def is_hidden_model(*values: str | None) -> bool:
     hidden_repo_ids = {
         _PROBE_REPO_ID.lower(),
         *(repo_id.lower() for repo_id in _DEFAULT_EMBEDDING_REPO_IDS),
+        *(repo_id.lower() for repo_id in _HIDDEN_STT_REPO_IDS),
     }
     exact_paths: list[str] = []
     for model in {
@@ -135,6 +192,9 @@ def is_hidden_model(*values: str | None) -> bool:
             return True
         if _path_contains_repo_id(v, hidden_repo_ids):
             return True
+        # Custom Whisper checkpoints keep no curated repo id, so match by config.
+        if _path_is_whisper_model(v):
+            return True
         if exact_paths:
             resolved = _safe_resolve(Path(v).expanduser())
             if resolved and resolved.lower() in exact_paths:
diff --git a/studio/backend/utils/llama_cpp_freshness.py b/studio/backend/utils/llama_cpp_freshness.py
index 7d077bfa3b..a184fdb3e9 100644
--- a/studio/backend/utils/llama_cpp_freshness.py
+++ b/studio/backend/utils/llama_cpp_freshness.py
@@ -7,28 +7,28 @@ Reads UNSLOTH_PREBUILT_INFO.json (written by install_llama_prebuilt.py)
 and compares the installed release tag against the latest on GitHub.
 Surfaced via main.py:lifespan() and /api/inference/status. Fails open
 on any missing data so we never show a misleading banner.
+
+The mechanics (marker walk-up, GitHub fetch, memo + disk cache, report
+skeleton) live in utils.prebuilt.freshness_flow; this module keeps the
+llama version policy and the per-module caches its tests patch.
 """
 
 from __future__ import annotations
 
-import json
-import os
 import re
-import time
-from datetime import datetime, timezone
+from datetime import datetime
 from pathlib import Path
 from typing import Optional
 
 import structlog
 
+from utils.prebuilt import freshness_flow as _flow
+
 logger = structlog.get_logger(__name__)
 
 # 3 days matches Unsloth's typical llama.cpp release cadence.
 STALENESS_THRESHOLD_DAYS = 3
 
-# 24h TTL keeps the GitHub call off the hot path and within rate limits.
-_RELEASE_CACHE_TTL_SECONDS = 24 * 60 * 60
-
 _INSTALL_MARKER_NAME = "UNSLOTH_PREBUILT_INFO.json"
 
 _marker_cache: dict[str, Optional[dict]] = {}
@@ -49,203 +49,60 @@ def _cache_dir() -> Path:
 def read_install_marker(binary_path: Optional[str]) -> Optional[dict]:
     """Walk up from binary_path to find UNSLOTH_PREBUILT_INFO.json.
     None = no marker (source build / custom path) or invalid JSON."""
-    if not binary_path:
-        return None
-    cached = _marker_cache.get(binary_path)
-    if cached is not None or binary_path in _marker_cache:
-        return cached
-    p = Path(binary_path)
-    marker: Optional[dict] = None
-    # Cover all _find_llama_server_binary layouts (binary is 1-4 dirs deep):
-    for parent in p.parents[:5]:
-        candidate = parent / _INSTALL_MARKER_NAME
-        if candidate.is_file():
-            try:
-                marker = json.loads(candidate.read_text(encoding = "utf-8"))
-            except (OSError, json.JSONDecodeError) as exc:
-                logger.debug(
-                    "failed to parse install marker",
-                    path = str(candidate),
-                    error = str(exc),
-                )
-                marker = None
-            break
-    _marker_cache[binary_path] = marker
-    return marker
-
-
-def _cache_path_for(repo: str) -> Path:
-    safe = repo.replace("/", "__")
-    return _cache_dir() / f"{safe}.json"
+    return _flow.read_install_marker(
+        binary_path,
+        marker_name = _INSTALL_MARKER_NAME,
+        cache = _marker_cache,
+        log_message = "failed to parse install marker",
+    )
 
 
 def _load_disk_cache(repo: str) -> Optional[tuple[float, Optional[str]]]:
-    path = _cache_path_for(repo)
-    try:
-        payload = json.loads(path.read_text(encoding = "utf-8"))
-    except (OSError, json.JSONDecodeError):
-        return None
-    ts = payload.get("fetched_at")
-    tag = payload.get("latest_tag")
-    if not isinstance(ts, (int, float)):
-        return None
-    return float(ts), tag if isinstance(tag, str) else None
+    return _flow.load_disk_cache(repo, _cache_dir())
 
 
 def _save_disk_cache(repo: str, latest_tag: Optional[str]) -> None:
-    path = _cache_path_for(repo)
-    try:
-        path.parent.mkdir(parents = True, exist_ok = True)
-        tmp = path.with_suffix(".tmp")
-        tmp.write_text(
-            json.dumps({"fetched_at": time.time(), "latest_tag": latest_tag}),
-            encoding = "utf-8",
-        )
-        tmp.replace(path)
-    except OSError as exc:
-        logger.debug("freshness cache write failed", repo = repo, error = str(exc))
+    _flow.save_disk_cache(
+        repo, latest_tag, _cache_dir(), log_message = "freshness cache write failed"
+    )
 
 
 def _fetch_latest_release_tag(repo: str, timeout: float = 5.0) -> Optional[str]:
-    """Newest published release tag for `repo`, by publish time.
-
-    Resolves "latest" the way install_llama_prebuilt.py does (newest
-    non-draft/non-prerelease by ``published_at``), NOT via GitHub's
-    ``/releases/latest`` pointer. That pointer sorts by commit date and can lag
-    behind the build the installer actually installs, so detection and apply
-    disagreed -- the cause of the downgrade/sticky banner. None on any failure
-    (offline, rate-limited, etc)."""
-    import urllib.error
-    import urllib.request
-
-    url = f"https://api.github.com/repos/{repo}/releases?per_page=30"
-    headers = {
-        "Accept": "application/vnd.github+json",
-        "User-Agent": "unsloth-studio-freshness-check",
-    }
-    token = os.environ.get("GITHUB_TOKEN") or os.environ.get("GH_TOKEN")
-    if token:
-        headers["Authorization"] = f"Bearer {token}"
-    req = urllib.request.Request(url, headers = headers)
-    try:
-        with urllib.request.urlopen(req, timeout = timeout) as resp:
-            data = json.loads(resp.read().decode("utf-8"))
-    except (
-        urllib.error.URLError,
-        urllib.error.HTTPError,
-        OSError,
-        json.JSONDecodeError,
-    ) as exc:
-        logger.debug("freshness fetch failed", repo = repo, error = str(exc))
-        return None
-    if not isinstance(data, list):
-        return None
-    published = [
-        r
-        for r in data
-        if isinstance(r, dict)
-        and not r.get("draft")
-        and not r.get("prerelease")
-        and isinstance(r.get("tag_name"), str)
-        and r.get("tag_name")
-    ]
-    if not published:
-        return None
-    newest = max(published, key = lambda r: r.get("published_at") or "")
-    return newest["tag_name"]
+    """Newest published release tag for `repo`, by publish time (see
+    freshness_flow for why this is not GitHub's /releases/latest pointer)."""
+    return _flow.fetch_latest_release_tag(repo, timeout, log_message = "freshness fetch failed")
 
 
 def latest_published_release(repo: str, *, force_refresh: bool = False) -> Optional[str]:
     """Latest release tag for `repo`. Memo + disk-cached (24h TTL).
     None when offline and never previously cached."""
-    if not repo:
-        return None
-    now = time.time()
-    if not force_refresh:
-        memo = _release_memo.get(repo)
-        if memo and now - memo[0] < _RELEASE_CACHE_TTL_SECONDS:
-            return memo[1]
-        disk = _load_disk_cache(repo)
-        if disk and now - disk[0] < _RELEASE_CACHE_TTL_SECONDS:
-            _release_memo[repo] = disk
-            return disk[1]
-    latest = _fetch_latest_release_tag(repo)
-    if latest is None:
-        # Keep last-good disk value rather than poisoning with None.
-        disk = _load_disk_cache(repo)
-        if disk:
-            _release_memo[repo] = disk
-            return disk[1]
-        return None
-    _release_memo[repo] = (now, latest)
-    _save_disk_cache(repo, latest)
-    return latest
+    return _flow.latest_published_release(
+        repo,
+        force_refresh = force_refresh,
+        memo = _release_memo,
+        cache_dir = lambda: _cache_dir(),
+        fetch = lambda r: _fetch_latest_release_tag(r),
+        save = lambda r, tag: _save_disk_cache(r, tag),
+    )
 
 
 def _fetch_latest_release_assets(repo: str, timeout: float = 5.0) -> Optional[dict[str, int]]:
     """Asset name -> size (bytes) for the newest published release of `repo`,
     selected exactly like _fetch_latest_release_tag. None on any failure."""
-    import urllib.error
-    import urllib.request
-
-    url = f"https://api.github.com/repos/{repo}/releases?per_page=30"
-    headers = {
-        "Accept": "application/vnd.github+json",
-        "User-Agent": "unsloth-studio-freshness-check",
-    }
-    token = os.environ.get("GITHUB_TOKEN") or os.environ.get("GH_TOKEN")
-    if token:
-        headers["Authorization"] = f"Bearer {token}"
-    req = urllib.request.Request(url, headers = headers)
-    try:
-        with urllib.request.urlopen(req, timeout = timeout) as resp:
-            data = json.loads(resp.read().decode("utf-8"))
-    except (
-        urllib.error.URLError,
-        urllib.error.HTTPError,
-        OSError,
-        json.JSONDecodeError,
-    ) as exc:
-        logger.debug("freshness asset fetch failed", repo = repo, error = str(exc))
-        return None
-    if not isinstance(data, list):
-        return None
-    published = [
-        r
-        for r in data
-        if isinstance(r, dict)
-        and not r.get("draft")
-        and not r.get("prerelease")
-        and isinstance(r.get("tag_name"), str)
-        and r.get("tag_name")
-    ]
-    if not published:
-        return None
-    newest = max(published, key = lambda r: r.get("published_at") or "")
-    assets: dict[str, int] = {}
-    for a in newest.get("assets") or []:
-        name, size = a.get("name"), a.get("size")
-        if isinstance(name, str) and isinstance(size, int):
-            assets[name] = size
-    return assets
+    return _flow.fetch_latest_release_assets(
+        repo, timeout, log_message = "freshness asset fetch failed"
+    )
 
 
 def latest_release_assets(repo: str, *, force_refresh: bool = False) -> Optional[dict[str, int]]:
     """Newest-release asset sizes for `repo`, memoized (24h TTL). None when
     offline and never fetched. In-memory only -- a restart simply re-fetches."""
-    if not repo:
-        return None
-    now = time.time()
-    if not force_refresh:
-        memo = _assets_memo.get(repo)
-        if memo and now - memo[0] < _RELEASE_CACHE_TTL_SECONDS:
-            return memo[1]
-    assets = _fetch_latest_release_assets(repo)
-    if assets is None:
-        memo = _assets_memo.get(repo)
-        return memo[1] if memo else None
-    _assets_memo[repo] = (now, assets)
-    return assets
+    return _flow.latest_release_assets(
+        repo,
+        force_refresh = force_refresh,
+        memo = _assets_memo,
+        fetch = lambda r: _fetch_latest_release_assets(r),
+    )
 
 
 def update_download_size_bytes(
@@ -290,16 +147,7 @@ def update_download_size_bytes(
 
 
 def _parse_installed_at(value: object) -> Optional[datetime]:
-    if not isinstance(value, str) or not value:
-        return None
-    s = value.replace("Z", "+00:00") if value.endswith("Z") else value
-    try:
-        dt = datetime.fromisoformat(s)
-    except ValueError:
-        return None
-    if dt.tzinfo is None:
-        dt = dt.replace(tzinfo = timezone.utc)
-    return dt
+    return _flow.parse_installed_at(value)
 
 
 def parse_base_build(tag: object) -> Optional[int]:
@@ -350,64 +198,27 @@ def check_prebuilt_freshness(
     behind = installed genuinely older than latest (see is_behind).
     stale = behind AND age >= threshold.
     Fails open on missing data (behind/stale stay False)."""
-    out: dict = {
-        "has_marker": False,
-        "stale": False,
-        "behind": False,
-        "installed_tag": None,
-        "latest_tag": None,
-        "installed_at_utc": None,
-        "age_days": None,
-        "published_repo": None,
-        "threshold_days": int(threshold_days),
-    }
-    marker = read_install_marker(binary_path)
-    if not marker:
-        return out
-    out["has_marker"] = True
-    # Display prefers the normalized base ("tag"); comparison below prefers the
-    # full "release_tag" -- deliberately opposite fallbacks.
-    out["installed_tag"] = marker.get("tag") or marker.get("release_tag")
-    out["installed_at_utc"] = marker.get("installed_at_utc")
-    out["published_repo"] = marker.get("published_repo")
-
     # The marker records both a normalized base tag ("tag", e.g. b9596) and the
-    # full release tag ("release_tag", e.g. b9596-mix-<sha>). Compare against the
-    # FULL identity, since GitHub /releases/latest returns the full tag_name --
-    # comparing the normalized base against the full latest is what produced the
-    # permanent "downgrade" banner on every mix release.
-    installed_full = marker.get("release_tag") or marker.get("tag")
-    repo = out["published_repo"]
-    if not repo or not installed_full:
-        return out
-    latest = latest_published_release(repo)
-    out["latest_tag"] = latest
-    out["behind"] = is_behind(installed_full, latest)
-    if not out["behind"]:
-        return out
-
-    installed_at = _parse_installed_at(out["installed_at_utc"])
-    if installed_at is None:
-        return out
-    now = now or datetime.now(tz = timezone.utc)
-    age_seconds = (now - installed_at).total_seconds()
-    out["age_days"] = max(0, int(age_seconds // 86400))
-    if age_seconds >= threshold_days * 86400:
-        out["stale"] = True
-    return out
+    # full release tag ("release_tag", e.g. b9596-mix-<sha>). Display prefers the
+    # normalized base; comparison uses the FULL identity, since GitHub
+    # /releases/latest returns the full tag_name -- comparing the normalized base
+    # against the full latest is what produced the permanent "downgrade" banner
+    # on every mix release. Deliberately opposite fallbacks.
+    return _flow.check_freshness(
+        binary_path,
+        threshold_days = threshold_days,
+        now = now,
+        read_marker = lambda p: read_install_marker(p),
+        latest_release = lambda repo: latest_published_release(repo),
+        behind = lambda installed, latest: is_behind(installed, latest),
+        display_tag = lambda marker: marker.get("tag") or marker.get("release_tag"),
+        compare_tag = lambda marker: marker.get("release_tag") or marker.get("tag"),
+    )
 
 
 def format_stale_warning(info: dict) -> str:
     """Human-readable one-liner for stale prebuilt info."""
-    age = info.get("age_days")
-    installed = info.get("installed_tag") or "unknown"
-    latest = info.get("latest_tag") or "unknown"
-    age_str = f"{age} day{'s' if age != 1 else ''}" if age is not None else "some time"
-    return (
-        f"llama.cpp prebuilt is {age_str} behind: installed "
-        f"{installed}, latest {latest}. Run `unsloth studio update` "
-        f"to refresh."
-    )
+    return _flow.format_stale_warning(info, component = "llama.cpp")
 
 
 def reset_caches(*, drop_disk: bool = False) -> None:
@@ -420,13 +231,8 @@ def reset_caches(*, drop_disk: bool = False) -> None:
     (see its last-good fallback) and the banner could linger. Dropping the disk
     cache makes latest read as None in that offline case, so the banner fails
     open (off) instead of pointing at the just-replaced build."""
-    _marker_cache.clear()
-    _release_memo.clear()
-    _assets_memo.clear()
-    if drop_disk:
-        import shutil
-
-        # _cache_dir() is a dedicated freshness-only subdir; it is re-created on
-        # the next _save_disk_cache. ignore_errors so a missing/locked dir is a
-        # no-op rather than breaking an otherwise successful install.
-        shutil.rmtree(_cache_dir(), ignore_errors = True)
+    _flow.reset_caches(
+        (_marker_cache, _release_memo, _assets_memo),
+        drop_disk = drop_disk,
+        cache_dir = lambda: _cache_dir(),
+    )
diff --git a/studio/backend/utils/llama_cpp_update.py b/studio/backend/utils/llama_cpp_update.py
index 67733bde35..174e6ef4dc 100644
--- a/studio/backend/utils/llama_cpp_update.py
+++ b/studio/backend/utils/llama_cpp_update.py
@@ -17,17 +17,22 @@ Design notes:
   thread; callers poll get_update_status() for the job state.
 - Everything fails open: a missing marker / offline GitHub / source build just
   reports update_available=False and never blocks the app.
+- The mechanics (managed-root resolution, local-link detection, the resolve
+  probe, the streamed installer run) live in utils.prebuilt.update_flow; this
+  module keeps the llama policy and the job dict its callers poll.
+- This is the single main update item: whisper.cpp piggybacks on it. Status
+  folds in a whisper sub-status (update_available becomes the union) and apply
+  chains a whisper phase after the llama phase when whisper is behind (see
+  update_flow.run_chained_update and whisper_cpp_update.chained_phase_plan).
 """
 
 from __future__ import annotations
 
-import json
 import os
 import re
 import subprocess
 import sys
 import threading
-import time
 from pathlib import Path
 from typing import Optional
 
@@ -43,7 +48,7 @@ from utils.llama_cpp_freshness import (
     reset_caches,
     update_download_size_bytes,
 )
-from utils.process_lifetime import child_popen_kwargs
+from utils.prebuilt import update_flow as _flow
 
 logger = structlog.get_logger(__name__)
 
@@ -51,33 +56,18 @@ DEFAULT_PUBLISHED_REPO = "unslothai/llama.cpp"
 _INSTALL_TIMEOUT_SECONDS = 1800  # 30 min ceiling for download + build/validate
 
 # Background job state. Single in-flight update at a time, guarded by _job_lock.
-_JOB_IDLE = "idle"
-_JOB_RUNNING = "running"
-_JOB_SUCCESS = "success"
-_JOB_ERROR = "error"
+_JOB_IDLE = _flow.JOB_IDLE
+_JOB_RUNNING = _flow.JOB_RUNNING
+_JOB_SUCCESS = _flow.JOB_SUCCESS
+_JOB_ERROR = _flow.JOB_ERROR
 
 _job_lock = threading.Lock()
-_job: dict = {
-    "state": _JOB_IDLE,
-    "message": "",
-    "from_tag": None,
-    "to_tag": None,
-    "reload_required": None,
-    "error": None,
-    "progress": None,
-    "started_at": None,
-    "finished_at": None,
-}
+_job: dict = _flow.new_job()
 
-# Matches the installer's download progress lines, e.g.
-# "Downloading x.zip:  35.0% (12.3 MiB/35.1 MiB) at 8.2 MiB/s".
-_PROGRESS_LINE_RE = re.compile(r"(\d+(?:\.\d+)?)%\s*\(")
-# The download dominates the update; extract/validate fill the last slice.
-_DOWNLOAD_PROGRESS_CEILING = 0.95
-
-
-def _utcnow() -> str:
-    return time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+_utcnow = _flow.utcnow
+_is_under = _flow.is_under
+_is_external_link = _flow.is_external_link
+_rocm_install_args = _flow.rocm_install_args
 
 
 def _find_binary() -> Optional[str]:
@@ -94,37 +84,19 @@ def _find_binary() -> Optional[str]:
 
 def _install_dir_for(binary_path: Optional[str]) -> Optional[Path]:
     """The directory holding UNSLOTH_PREBUILT_INFO.json -- i.e. the install root
-    install_llama_prebuilt.py wrote and the one we re-install into. Walks up from
-    the binary the same way read_install_marker() does."""
-    if not binary_path:
-        return None
-    p = Path(binary_path)
-    for parent in p.parents[:5]:
-        if (parent / _INSTALL_MARKER_NAME).is_file():
-            return parent
-    return None
+    install_llama_prebuilt.py wrote and the one we re-install into."""
+    return _flow.install_dir_for(binary_path, marker_name = _INSTALL_MARKER_NAME)
 
 
 def _installer_script() -> Optional[Path]:
-    """Locate install_llama_prebuilt.py. Honours UNSLOTH_LLAMA_INSTALLER, then
-    searches up from this file for both ``<root>/install_llama_prebuilt.py`` and
-    ``<root>/studio/install_llama_prebuilt.py`` so it works in the dev tree and
-    in an installed Unsloth layout."""
-    env = os.environ.get("UNSLOTH_LLAMA_INSTALLER")
-    if env and Path(env).is_file():
-        return Path(env)
-    here = Path(__file__).resolve()
-    for up in here.parents:
-        for cand in (up / "install_llama_prebuilt.py", up / "studio" / "install_llama_prebuilt.py"):
-            if cand.is_file():
-                return cand
-    return None
+    """Locate install_llama_prebuilt.py (UNSLOTH_LLAMA_INSTALLER wins)."""
+    return _flow.find_installer_script(
+        env_var = "UNSLOTH_LLAMA_INSTALLER", script_name = "install_llama_prebuilt.py"
+    )
 
 
 # Markerless (source-build) installs have no UNSLOTH_PREBUILT_INFO.json, so we
-# ask the installer whether an official prebuilt now exists for this host. Memo
-# is 24h; only successful answers are cached so a network blip retries.
-_RESOLVE_TTL_SECONDS = 24 * 60 * 60
+# ask the installer whether an official prebuilt now exists for this host.
 _resolve_memo: dict = {}
 
 
@@ -132,39 +104,12 @@ def _resolve_prebuilt_for_host(*, force_refresh: bool = False) -> Optional[dict]
     """Run install_llama_prebuilt.py --resolve-prebuilt (no download) and return
     {prebuilt_available, repo, release_tag, llama_tag, asset, install_kind} or
     None. Fail-open: any error -> None so a source build never blocks the app."""
-    now = time.time()
-    if not force_refresh and _resolve_memo:
-        if now - _resolve_memo.get("at", 0.0) < _RESOLVE_TTL_SECONDS:
-            return _resolve_memo.get("value")
-    script = _installer_script()
-    if script is None:
-        return None
-    value: Optional[dict] = None
-    try:
-        proc = subprocess.run(
-            [
-                sys.executable,
-                str(script),
-                "--resolve-prebuilt",
-                "latest",
-                "--output-format",
-                "json",
-            ],
-            capture_output = True,
-            text = True,
-            timeout = 60,
-        )
-        out = (proc.stdout or "").strip()
-        if proc.returncode == 0 and out:
-            parsed = json.loads(out.splitlines()[-1])
-            if isinstance(parsed, dict):
-                value = parsed
-    except Exception as exc:  # pragma: no cover - subprocess/json defensive
-        logger.debug("llama update: resolve-prebuilt failed", error = str(exc))
-        value = None
-    if value is not None:  # cache real answers; let failures retry next poll
-        _resolve_memo.update(at = now, value = value)
-    return value
+    return _flow.resolve_prebuilt_for_host(
+        force_refresh = force_refresh,
+        memo = _resolve_memo,
+        installer_script = lambda: _installer_script(),
+        log_message = "llama update: resolve-prebuilt failed",
+    )
 
 
 def _installed_build_number(binary: Optional[str]) -> Optional[int]:
@@ -218,38 +163,16 @@ def get_installed_llama_version() -> Optional[str]:
     return f"b{n}" if n is not None else None
 
 
-def _is_under(path: Path, root: Path) -> bool:
-    try:
-        p, r = path.resolve(), root.resolve()
-    except (OSError, ValueError):
-        p, r = path, root
-    return p == r or r in p.parents
-
-
 def _llama_install_root(binary: Optional[str]) -> Optional[Path]:
     """The Unsloth-managed llama.cpp root the active binary lives under, or None
-    when the binary is unmanaged. Installing anywhere the active binary is not
-    would not replace what _find_llama_server_binary runs (which prefers a pinned
-    LLAMA_SERVER_PATH, then UNSLOTH_LLAMA_CPP_PATH, then a llama.cpp tree), so we
-    refuse rather than silently install into an inactive or foreign tree."""
-    marked = _install_dir_for(binary)
-    if marked is not None:
-        return marked
-    if not binary:
-        return None
-    # LLAMA_SERVER_PATH is an explicit user pin that always wins in discovery;
-    # never auto-replace its tree (even a user's own llama.cpp checkout).
-    if os.environ.get("LLAMA_SERVER_PATH"):
-        return None
-    p = Path(binary)
-    env = os.environ.get("UNSLOTH_LLAMA_CPP_PATH")
-    if env and _is_under(p, Path(env)):
-        return Path(env)
-    for parent in p.parents:
-        if parent.name == "llama.cpp":
-            return parent
-    # PATH / system / custom install: not a managed tree, so do not offer.
-    return None
+    when the binary is unmanaged (see update_flow.managed_install_root)."""
+    return _flow.managed_install_root(
+        binary,
+        marker_root = _install_dir_for(binary),
+        server_path_var = "LLAMA_SERVER_PATH",
+        cpp_path_var = "UNSLOTH_LLAMA_CPP_PATH",
+        dir_name = "llama.cpp",
+    )
 
 
 def _source_build_status(binary: str, *, force_refresh: bool) -> Optional[dict]:
@@ -324,69 +247,83 @@ def _source_build_status(binary: str, *, force_refresh: bool) -> Optional[dict]:
     }
 
 
-def _is_external_link(path: Optional[Path]) -> bool:
-    """True when ``path`` is a --with-llama-cpp-dir local link: a POSIX symlink
-    or a Windows directory junction / reparse point. Such a link resolves into
-    the user's own llama.cpp checkout, so Unsloth must never auto-update it."""
-    if path is None:
-        return False
-    try:
-        if os.path.islink(path):
-            return True
-    except OSError:
-        return False
-    if os.name == "nt":
-        try:
-            import stat
-            attrs = os.lstat(path).st_file_attributes  # type: ignore[attr-defined]
-            return bool(attrs & stat.FILE_ATTRIBUTE_REPARSE_POINT)
-        except (OSError, AttributeError):
-            return False
-    return False
-
-
 def _active_install_is_local_link(binary: Optional[str]) -> bool:
     """True when the active llama-server resolves through a --with-llama-cpp-dir
-    local link at the canonical llama.cpp directory. An update would write
-    through that link into the user's own checkout (or fail), so the install is
-    treated as externally managed: no update is offered or applied. Checks only
-    up to and including the ``llama.cpp`` dir so a symlinked HOME / studio root
-    above it can't trip a false positive."""
-    if not binary:
-        return False
-    for parent in Path(binary).parents:
-        if _is_external_link(parent):
-            return True
-        if parent.name == "llama.cpp":
-            break
-    return False
+    local link at the canonical llama.cpp directory (see
+    update_flow.active_install_is_local_link)."""
+    return _flow.active_install_is_local_link(binary, dir_name = "llama.cpp")
 
 
 def _local_link_status() -> dict:
     """Status payload for a local-link install: unmanaged, no update offered."""
-    with _job_lock:
-        job = dict(_job)
-    return {
-        "supported": False,
-        "update_available": False,
-        "stale": False,
-        "installed_tag": None,
-        "latest_tag": None,
-        "published_repo": None,
-        "installed_at_utc": None,
-        "age_days": None,
-        "source_build": False,
-        "local_link": True,
-        "update_size_bytes": None,
-        "job": job,
+    return _flow.local_link_status(_job, _job_lock)
+
+
+def _whisper_chain_status(
+    *, force_refresh: bool = False, paired_llama_will_update: bool = False
+) -> Optional[dict]:
+    """Whisper's piggyback plan for the combined update item (see
+    whisper_cpp_update.chained_phase_plan). None disables the piggyback --
+    fail-open so whisper can never break the llama status or apply."""
+    try:
+        from utils import whisper_cpp_update
+        return whisper_cpp_update.chained_phase_plan(
+            force_refresh = force_refresh,
+            paired_llama_will_update = paired_llama_will_update,
+        )
+    except Exception as exc:  # pragma: no cover - defensive
+        logger.debug("llama update: whisper piggyback probe failed", error = str(exc))
+        return None
+
+
+def _merge_whisper_status(status: dict, *, force_refresh: bool = False) -> dict:
+    """Fold the whisper sub-status into the llama status payload: the llama
+    update item is the single UI surface, so update_available becomes the union
+    (llama behind OR whisper behind) while llama_update_available keeps the
+    llama-only flag. All pre-existing top-level fields are preserved."""
+    status["llama_update_available"] = bool(status.get("update_available"))
+    plan = _whisper_chain_status(
+        force_refresh = force_refresh,
+        paired_llama_will_update = status["llama_update_available"],
+    )
+    if plan is None:
+        status["whisper"] = None
+        status["update_component"] = "llama" if status["llama_update_available"] else None
+        return status
+    sub = plan.get("status") or {}
+    status["whisper"] = {
+        "update_available": bool(plan.get("update_available")),
+        "installed_tag": sub.get("installed_tag"),
+        "latest_tag": sub.get("latest_tag"),
+        "update_size_bytes": sub.get("update_size_bytes"),
+        "skip_reason": plan.get("skip_reason"),
     }
+    whisper_update_available = bool(plan.get("update_available"))
+    if whisper_update_available:
+        status["update_available"] = True
+    status["update_component"] = (
+        "llama"
+        if status["llama_update_available"]
+        else "whisper"
+        if whisper_update_available
+        else None
+    )
+    return status
 
 
 def get_update_status(*, force_refresh: bool = False) -> dict:
-    """Report whether a newer prebuilt exists plus the current job state.
+    """Report whether an update is available plus the current job state.
 
-    force_refresh bypasses the 24h release cache for an explicit "check now".
+    This is the single main update item: llama.cpp drives it and the whisper
+    piggyback is folded in (see _merge_whisper_status). force_refresh bypasses
+    the 24h release cache for an explicit "check now".
     """
+    status = _llama_only_status(force_refresh = force_refresh)
+    return _merge_whisper_status(status, force_refresh = force_refresh)
+
+
+def _llama_only_status(*, force_refresh: bool = False) -> dict:
+    """The llama.cpp half of get_update_status (no whisper sub-status)."""
     binary = _find_binary()
     # A --with-llama-cpp-dir local link is the user's own tree; never offer to
     # replace it. Bail before any network/freshness work.
@@ -456,33 +393,19 @@ def get_update_status(*, force_refresh: bool = False) -> dict:
     }
 
 
-def _rocm_install_args(asset: Optional[str]) -> list[str]:
-    """Forward --rocm-gfx/--has-rocm from the marker asset, mirroring setup.sh.
-    The installer probe can miss the gfx arch on amd-smi-only hosts; per-gfx
-    ROCm bundles carry the family in the name (rocm-gfx110X), version-tagged
-    bundles only rocm/hip."""
-    if not asset:
-        return []
-    low = asset.lower()
-    if "rocm" not in low and "hip" not in low:
-        return []
-    gfx = re.search(r"-gfx[0-9a-z]+", low)
-    if gfx:
-        # _normalize_forwarded_gfx accepts the family form (gfx110x -> gfx110X).
-        return ["--rocm-gfx", gfx.group(0).lstrip("-")]
-    return ["--has-rocm"]
-
-
-def _run_update(
+def _run_llama_phase(
     install_dir: Path,
     repo: str,
     asset: Optional[str],
     script: Path,
-    pin_release_tag: Optional[str] = None,
+    pin_release_tag: Optional[str],
+    set_progress,
     force_cpu: bool = False,
-) -> None:
-    """Worker: put the backend into a maintenance state, run the installer for
-    the latest prebuilt, then refresh caches so the next load uses the new build.
+) -> dict:
+    """The llama phase of a chained update: put the backend into a maintenance
+    state, run the installer for the latest prebuilt, then refresh caches so the
+    next load uses the new build. Returns {to_tag, reload_required, message};
+    raises on failure.
 
     pin_release_tag pins the installer to that exact published release instead
     of letting it re-resolve "latest" itself (see start_update for why)."""
@@ -530,7 +453,6 @@ def _run_update(
         if force_cpu:
             cmd.append("--force-cpu")
         logger.info("llama update: installing", cmd = " ".join(cmd))
-        # Stream progress lines into job["progress"].
         env = dict(os.environ, UNSLOTH_PROGRESS_PERCENT_STEP = "5")
         # Preserve a Vulkan install across updates: detect_host on a CUDA/ROCm
         # box would otherwise re-route and silently replace the Vulkan build.
@@ -538,44 +460,12 @@ def _run_update(
         # _rocm_install_args).
         if asset and "vulkan" in asset.lower():
             env["UNSLOTH_FORCE_VULKAN"] = "1"
-        proc = subprocess.Popen(
+        _flow.stream_installer(
             cmd,
-            stdout = subprocess.PIPE,
-            stderr = subprocess.STDOUT,
-            text = True,
-            env = env,
-            **child_popen_kwargs(),
+            env,
+            set_progress = set_progress,
+            timeout_seconds = _INSTALL_TIMEOUT_SECONDS,
         )
-        timed_out = threading.Event()
-
-        def _kill_on_timeout() -> None:
-            timed_out.set()
-            proc.kill()
-
-        watchdog = threading.Timer(_INSTALL_TIMEOUT_SECONDS, _kill_on_timeout)
-        watchdog.daemon = True
-        watchdog.start()
-        tail_lines: list[str] = []
-        try:
-            assert proc.stdout is not None
-            for line in proc.stdout:
-                tail_lines.append(line)
-                if len(tail_lines) > 80:
-                    del tail_lines[0]
-                m = _PROGRESS_LINE_RE.search(line)
-                if m is None:
-                    continue
-                fraction = min(float(m.group(1)) / 100.0, 1.0) * _DOWNLOAD_PROGRESS_CEILING
-                with _job_lock:
-                    _job["progress"] = max(_job.get("progress") or 0.0, fraction)
-            returncode = proc.wait()
-        finally:
-            watchdog.cancel()
-        if timed_out.is_set():
-            raise RuntimeError(f"installer timed out after {_INSTALL_TIMEOUT_SECONDS}s")
-        if returncode != 0:
-            tail = "".join(tail_lines).strip()[-1500:]
-            raise RuntimeError(f"installer exited {returncode}: {tail or 'no output'}")
 
         # Drop stale caches so the banner re-checks the swapped marker.
         # If GitHub is offline, latest stays unknown and the banner fails open.
@@ -597,29 +487,18 @@ def _run_update(
         ):
             raise RuntimeError(f"pinned release {pin_release_tag} but installer produced {new_tag}")
 
-        with _job_lock:
-            _job.update(
-                state = _JOB_SUCCESS,
-                message = (
-                    f"Updated llama.cpp to {new_tag}."
-                    + (" Reload your model to use it." if model_was_active else "")
-                ),
-                to_tag = new_tag,
-                reload_required = model_was_active,
-                error = None,
-                progress = 1.0,
-                finished_at = _utcnow(),
-            )
         logger.info("llama update: success", to_tag = new_tag)
+        return {
+            "to_tag": new_tag,
+            "reload_required": model_was_active,
+            "message": (
+                f"Updated llama.cpp to {new_tag}."
+                + (" Reload your model to use it." if model_was_active else "")
+            ),
+        }
     except Exception as exc:
         logger.warning("llama update: failed", error = str(exc))
-        with _job_lock:
-            _job.update(
-                state = _JOB_ERROR,
-                message = "llama.cpp update failed.",
-                error = str(exc),
-                finished_at = _utcnow(),
-            )
+        raise
     finally:
         # Always clear maintenance state.
         if backend is not None:
@@ -629,50 +508,58 @@ def _run_update(
                 pass
 
 
-def start_update() -> dict:
-    """Kick off a background update. Idempotent: a second call while one is
-    running returns the in-flight job rather than starting another."""
+# Combined-job progress split when both phases run (download sizes: the llama
+# bundle dwarfs the whisper one); normalized to 0..1 when a phase is skipped.
+_LLAMA_PHASE_WEIGHT = 0.7
+_WHISPER_PHASE_WEIGHT = 0.3
+
+
+def _plan_llama_phase() -> dict:
+    """Decide how the llama phase of a combined update runs. Returns {"spec"}
+    when llama should install, else {"skip_reason", "refusal"}: skip_reason
+    marks the phase skipped inside a chained job, refusal is the started=False
+    response when the whisper phase has nothing to run either."""
     binary = _find_binary()
     # Refuse to update a --with-llama-cpp-dir local link: installing a prebuilt
     # here would write through the link into the user's own checkout (or fail)
     # and silently drop the link the flag created.
     if _active_install_is_local_link(binary):
         return {
-            "started": False,
-            "reason": "local_link",
-            "message": (
-                "llama.cpp is a local directory linked with --with-llama-cpp-dir; "
-                "Unsloth won't replace it. Update your own llama.cpp checkout instead."
-            ),
-            "job": get_update_status()["job"],
+            "skip_reason": "local_link",
+            "refusal": {
+                "started": False,
+                "reason": "local_link",
+                "message": (
+                    "llama.cpp is a local directory linked with --with-llama-cpp-dir; "
+                    "Unsloth won't replace it. Update your own llama.cpp checkout instead."
+                ),
+            },
         }
     marker = read_install_marker(binary)
     script = _installer_script()
     if script is None:
         return {
-            "started": False,
-            "reason": "installer_missing",
-            "message": "install_llama_prebuilt.py could not be located.",
-            "job": get_update_status()["job"],
+            "skip_reason": "installer_missing",
+            "refusal": {
+                "started": False,
+                "reason": "installer_missing",
+                "message": "install_llama_prebuilt.py could not be located.",
+            },
         }
 
-    # A job already in flight wins over any freshness re-check below (and skips
-    # its network call). The final lock block re-checks to close the TOCTOU.
-    with _job_lock:
-        if _job["state"] == _JOB_RUNNING:
-            return {"started": False, "reason": "already_running", "job": dict(_job)}
-
     if marker:
         # Mirror the detection guard: a direct POST or a stale banner must not
         # start an install when the latest is not actually newer (force a fresh
         # check so a stale 24h cache can't wrongly block a real update either).
-        status = get_update_status(force_refresh = True)
+        status = _llama_only_status(force_refresh = True)
         if not status.get("update_available"):
             return {
-                "started": False,
-                "reason": "up_to_date",
-                "message": "The installed llama.cpp build is already at the latest prebuilt.",
-                "job": status["job"],
+                "skip_reason": "up_to_date",
+                "refusal": {
+                    "started": False,
+                    "reason": "up_to_date",
+                    "message": "The installed llama.cpp build is already at the latest prebuilt.",
+                },
             }
         install_dir = _install_dir_for(binary)
         repo = marker.get("published_repo") or DEFAULT_PUBLISHED_REPO
@@ -693,20 +580,27 @@ def start_update() -> dict:
         src = _source_build_status(binary, force_refresh = True) if binary else None
         if src is None:
             return {
-                "started": False,
-                "reason": "no_prebuilt_available",
-                "message": (
-                    "No official llama.cpp prebuilt is available for this host, "
-                    "so the source build cannot be swapped automatically."
-                ),
-                "job": get_update_status()["job"],
+                "skip_reason": "no_prebuilt_available",
+                "refusal": {
+                    "started": False,
+                    "reason": "no_prebuilt_available",
+                    "message": (
+                        "No official llama.cpp prebuilt is available for this host, "
+                        "so the source build cannot be swapped automatically."
+                    ),
+                },
             }
         if not src.get("update_available"):
             return {
-                "started": False,
-                "reason": "up_to_date",
-                "message": "The installed llama.cpp build is already at or newer than the latest prebuilt.",
-                "job": get_update_status()["job"],
+                "skip_reason": "up_to_date",
+                "refusal": {
+                    "started": False,
+                    "reason": "up_to_date",
+                    "message": (
+                        "The installed llama.cpp build is already at or newer than the "
+                        "latest prebuilt."
+                    ),
+                },
             }
         res = _resolve_prebuilt_for_host()
         install_dir = _llama_install_root(binary)
@@ -721,31 +615,116 @@ def start_update() -> dict:
 
     if install_dir is None:
         return {
-            "started": False,
-            "reason": "no_install_dir",
-            "message": "Could not determine the llama.cpp install directory.",
-            "job": get_update_status()["job"],
+            "skip_reason": "no_install_dir",
+            "refusal": {
+                "started": False,
+                "reason": "no_install_dir",
+                "message": "Could not determine the llama.cpp install directory.",
+            },
         }
+    return {
+        "spec": {
+            "install_dir": install_dir,
+            "repo": repo,
+            "asset": asset,
+            "script": script,
+            "pin_release_tag": pin_release_tag,
+            "from_tag": from_tag,
+            "force_cpu": force_cpu,
+        }
+    }
+
+
+def start_update() -> dict:
+    """Kick off a background update job. The job chains the llama phase (the
+    existing flow) with a whisper phase that runs only when whisper is actually
+    behind; either phase no-ops cleanly when its component is current or
+    unmanaged. Idempotent: a second call while one is running returns the
+    in-flight job rather than starting another."""
+    # A job already in flight wins over any freshness re-check below (and skips
+    # its network calls). The final lock block re-checks to close the TOCTOU.
+    with _job_lock:
+        if _job["state"] == _JOB_RUNNING:
+            return {"started": False, "reason": "already_running", "job": dict(_job)}
+
+    llama_plan = _plan_llama_phase()
+    llama_spec = llama_plan.get("spec")
+    whisper_plan = _whisper_chain_status(
+        force_refresh = True,
+        paired_llama_will_update = llama_spec is not None,
+    )
+    whisper_spec = (whisper_plan or {}).get("phase")
+    if llama_spec is None and whisper_spec is None:
+        # Nothing to run in either phase: answer with the llama refusal so the
+        # existing reasons (local_link / up_to_date / ...) keep their meaning.
+        refusal = dict(llama_plan["refusal"])
+        with _job_lock:
+            refusal["job"] = dict(_job)
+        return refusal
+
+    whisper_run = None
+    if whisper_spec is not None:
+        from utils import whisper_cpp_update as _whisper
+        whisper_run = lambda set_progress: _whisper.run_chained_phase(whisper_spec, set_progress)
+
+    phases = [
+        {
+            "name": "llama",
+            "weight": _LLAMA_PHASE_WEIGHT,
+            "failure_message": "llama.cpp update failed.",
+            "skip_reason": llama_plan.get("skip_reason"),
+            "run": (
+                (
+                    lambda set_progress: _run_llama_phase(
+                        llama_spec["install_dir"],
+                        llama_spec["repo"],
+                        llama_spec["asset"],
+                        llama_spec["script"],
+                        llama_spec["pin_release_tag"],
+                        set_progress,
+                        force_cpu = llama_spec.get("force_cpu", False),
+                    )
+                )
+                if llama_spec
+                else None
+            ),
+        },
+        {
+            "name": "whisper",
+            "weight": _WHISPER_PHASE_WEIGHT,
+            "failure_message": "whisper.cpp update failed.",
+            # The sidecar reload is whisper-internal; it must not trip the
+            # job-level reload flag the chat frontend resyncs on.
+            "affects_job_reload": False,
+            "skip_reason": (whisper_plan or {}).get("skip_reason") or "unavailable",
+            "run": whisper_run,
+        },
+    ]
+    running = " + ".join(
+        name for name, spec in (("llama.cpp", llama_spec), ("whisper.cpp", whisper_spec)) if spec
+    )
 
     with _job_lock:
         if _job["state"] == _JOB_RUNNING:
             return {"started": False, "reason": "already_running", "job": dict(_job)}
         _job.update(
             state = _JOB_RUNNING,
-            message = "Downloading and installing the latest llama.cpp prebuilt...",
-            from_tag = from_tag,
+            message = f"Downloading and installing the latest {running} prebuilt...",
+            from_tag = (llama_spec or {}).get("from_tag"),
             to_tag = None,
             reload_required = None,
             error = None,
             progress = 0.0,
             started_at = _utcnow(),
             finished_at = None,
+            phases = None,
         )
         job_snapshot = dict(_job)
 
     thread = threading.Thread(
-        target = _run_update,
-        args = (install_dir, repo, asset, script, pin_release_tag, force_cpu),
+        target = _flow.run_chained_update,
+        args = (phases,),
+        kwargs = {"job": _job, "job_lock": _job_lock},
         name = "llama-cpp-update",
         daemon = True,
     )
@@ -755,15 +734,4 @@ def start_update() -> dict:
 
 def _reset_job_for_tests() -> None:
     """Test-only: return the job tracker to idle."""
-    with _job_lock:
-        _job.update(
-            state = _JOB_IDLE,
-            message = "",
-            from_tag = None,
-            to_tag = None,
-            reload_required = None,
-            error = None,
-            progress = None,
-            started_at = None,
-            finished_at = None,
-        )
+    _flow.reset_job(_job, _job_lock)
diff --git a/studio/backend/utils/models/gguf_metadata.py b/studio/backend/utils/models/gguf_metadata.py
index 50b3cd3513..749f2c9234 100644
--- a/studio/backend/utils/models/gguf_metadata.py
+++ b/studio/backend/utils/models/gguf_metadata.py
@@ -50,10 +50,14 @@ _CACHE_MAX_ENTRIES = 4096
 # keyed by (file cache key, wanted key). None = key absent / file unreadable.
 _BOOL_CACHE: Dict[Tuple[_CacheKey, str], Optional[bool]] = {}
 
+_STRING_CACHE: Dict[Tuple[_CacheKey, str], Optional[str]] = {}
+
 # GGUF header dims for the staged/deferred-load UI: context_length, layer_count
 # (block_count), and moe_layer_count (block_count minus leading dense layers; 0
 # if not MoE). One cached pass fills all three so the staged sheet can size every
-# slider before the model loads. None = unreadable / not a GGUF.
+# slider before the model loads. None = unreadable / not a GGUF. The native
+# training context length (``{arch}.context_length``) the UI shows before a model
+# loads is read from here via read_gguf_context_length.
 _DIMS_CACHE: Dict[_CacheKey, Optional[Dict[str, Optional[int]]]] = {}
 
 
@@ -408,6 +412,83 @@ def _read_gguf_bool(path: str, wanted_key: str) -> Optional[bool]:
     return result
 
 
+def _parse_gguf_string(path: str, wanted_key: str) -> Optional[str]:
+    try:
+        with open(path, "rb") as f:
+            head = f.read(24)
+            if len(head) < 24:
+                return None
+            magic, _version, _tcount, kv_count = struct.unpack("<IIQQ", head)
+            if magic != _GGUF_MAGIC:
+                return None
+
+            for _ in range(kv_count):
+                try:
+                    klen_bytes = f.read(8)
+                    if len(klen_bytes) < 8:
+                        break
+                    klen = struct.unpack("<Q", klen_bytes)[0]
+                    if klen > 1 << 20:
+                        break
+                    kbytes = f.read(klen)
+                    if len(kbytes) < klen:
+                        break
+                    key = kbytes.decode("utf-8", "replace")
+                    vt_bytes = f.read(4)
+                    if len(vt_bytes) < 4:
+                        break
+                    vtype = struct.unpack("<I", vt_bytes)[0]
+
+                    if key == wanted_key and vtype == 8:
+                        slen_bytes = f.read(8)
+                        if len(slen_bytes) < 8:
+                            break
+                        slen = struct.unpack("<Q", slen_bytes)[0]
+                        if slen > 1 << 22:
+                            break
+                        sbytes = f.read(slen)
+                        if len(sbytes) < slen:
+                            break
+                        return sbytes.decode("utf-8", "replace")
+                    if not _skip_gguf_value(f, vtype):
+                        break
+                except (struct.error, UnicodeDecodeError):
+                    break
+    except OSError as e:
+        logger.debug(f"_parse_gguf_string: cannot open {path}: {e}")
+        return None
+    except Exception as e:
+        logger.debug(f"_parse_gguf_string: parse failure on {path}: {e}")
+        return None
+    return None
+
+
+def _read_gguf_string(path: str, wanted_key: str) -> Optional[str]:
+    fkey = _cache_key(path)
+    if fkey is None:
+        return None
+    ckey = (fkey, wanted_key)
+    with _CACHE_LOCK:
+        if ckey in _STRING_CACHE:
+            return _STRING_CACHE[ckey]
+    result = _parse_gguf_string(path, wanted_key)
+    with _CACHE_LOCK:
+        while len(_STRING_CACHE) >= _CACHE_MAX_ENTRIES:
+            try:
+                _STRING_CACHE.pop(next(iter(_STRING_CACHE)))
+            except StopIteration:
+                break
+        _STRING_CACHE[ckey] = result
+    return result
+
+
+def read_gguf_chat_template(path: str) -> Optional[str]:
+    template = _read_gguf_string(path, "tokenizer.chat_template")
+    if isinstance(template, str) and template.strip():
+        return template
+    return None
+
+
 def read_mmproj_audio_capability(path: str) -> Optional[bool]:
     """``clip.has_audio_encoder`` from an mmproj GGUF (e.g. Gemma 4's
     gemma4ua): ``True``/``False`` if present, ``None`` if absent/unreadable.
diff --git a/studio/backend/utils/models/model_config.py b/studio/backend/utils/models/model_config.py
index dadf103cea..4897f05ce4 100644
--- a/studio/backend/utils/models/model_config.py
+++ b/studio/backend/utils/models/model_config.py
@@ -37,6 +37,7 @@ import yaml
 
 
 from utils.native_path_leases import child_env_without_native_path_secret
+from utils.hf_cache_settings import active_hf_hub_cache, get_hf_cache_paths
 from utils.subprocess_compat import (
     windows_hidden_subprocess_kwargs as _windows_hidden_subprocess_kwargs,
 )
@@ -493,6 +494,7 @@ def load_model_config(
             trust_remote_code = trust_remote_code,
             token = token,
             local_files_only = local_files_only,
+            cache_dir = active_hf_hub_cache(),
         )
 
     if not use_auth:
@@ -503,6 +505,7 @@ def load_model_config(
                 trust_remote_code = trust_remote_code,
                 token = None,
                 local_files_only = local_files_only,
+                cache_dir = active_hf_hub_cache(),
             )
 
     # Default auth (cached tokens)
@@ -510,6 +513,7 @@ def load_model_config(
         model_name,
         trust_remote_code = trust_remote_code,
         local_files_only = local_files_only,
+        cache_dir = active_hf_hub_cache(),
     )
 
 
@@ -624,6 +628,7 @@ def _raw_config_has_vision_config(
                     filename = "config.json",
                     token = hf_token,
                     local_files_only = local_files_only,
+                    cache_dir = active_hf_hub_cache(),
                 )
             )
         config = json.loads(config_path.read_text())
@@ -770,7 +775,7 @@ def _is_vision_model_subprocess(model_name: str, hf_token: Optional[str] = None)
             capture_output = True,
             text = True,
             timeout = 60,
-            env = child_env_without_native_path_secret(),
+            env = get_hf_cache_paths().child_env(child_env_without_native_path_secret()),
             **_windows_hidden_subprocess_kwargs(),
         )
 
@@ -1249,6 +1254,77 @@ def _iter_gguf_files(directory: Path, recursive: bool = False):
             yield f
 
 
+_GGUF_SPLIT_FILE_RE = re.compile(
+    r"^(?P<prefix>.+)-(?P<index>\d{5})-of-(?P<total>\d{5})\.gguf$",
+    re.IGNORECASE,
+)
+
+
+def _colocated_first_split_shard(path: Path) -> tuple[Optional[Path], bool]:
+    """Return shard 1 and whether every shard is beside *path*."""
+    match = _GGUF_SPLIT_FILE_RE.match(path.name)
+    if match is None:
+        return None, False
+
+    prefix = match.group("prefix").casefold()
+    total_text = match.group("total")
+    total = int(total_text)
+    if total < 1:
+        return None, False
+
+    first: Optional[Path] = None
+    indices: set[int] = set()
+    try:
+        siblings = path.parent.iterdir()
+        for sibling in siblings:
+            sibling_match = _GGUF_SPLIT_FILE_RE.match(sibling.name)
+            if (
+                sibling_match is None
+                or sibling_match.group("prefix").casefold() != prefix
+                or sibling_match.group("total") != total_text
+            ):
+                continue
+            try:
+                if not sibling.is_file():
+                    continue
+            except OSError:
+                continue
+            index = int(sibling_match.group("index"))
+            if not 1 <= index <= total:
+                continue
+            indices.add(index)
+            if index == 1:
+                first = sibling
+    except OSError:
+        return None, False
+
+    return first, first is not None and len(indices) == total
+
+
+def _local_gguf_load_path(path: Path) -> Path:
+    """Choose a loadable local path while preserving complete symlink sets."""
+    if _GGUF_SPLIT_FILE_RE.match(path.name) is None:
+        return path.absolute()
+
+    first, complete = _colocated_first_split_shard(path)
+    if complete and first is not None:
+        return first.absolute()
+
+    try:
+        is_symlink = path.is_symlink()
+    except OSError:
+        is_symlink = False
+    if is_symlink:
+        try:
+            target = path.resolve()
+        except OSError:
+            return (first or path).absolute()
+        target_first, _ = _colocated_first_split_shard(target)
+        return (target_first or target).absolute()
+
+    return (first or path).absolute()
+
+
 def detect_mmproj_file(path: str, search_root: Optional[str] = None) -> Optional[str]:
     """Find the mmproj GGUF for a model.
 
@@ -1434,7 +1510,7 @@ def detect_gguf_model(path: str) -> Optional[str]:
         except OSError:
             is_dir = False  # stat() unavailable in the lock window
         if not is_dir:
-            return str(p.absolute())  # absolute() keeps symlink names readable
+            return str(_local_gguf_load_path(p))
         # Directory named "*.gguf": fall through to the dir scan below.
 
     # Case 2: directory containing .gguf files (skip mmproj / MTP drafter)
@@ -1452,7 +1528,7 @@ def detect_gguf_model(path: str) -> Optional[str]:
             gguf_files.append(f)
         gguf_files.sort(key = lambda f: f.stat().st_size, reverse = True)
         if gguf_files:
-            return str(gguf_files[0].resolve())
+            return str(_local_gguf_load_path(gguf_files[0]))
 
     return None
 
@@ -1643,19 +1719,20 @@ def _local_gguf_companion_search_root(selected_path: str, gguf_file: str) -> str
     return str(gguf_dir)
 
 
-def _iter_hf_cache_snapshots(repo_id: str):
+def _iter_hf_cache_snapshots(repo_id: str, cache_dir: Optional[str | Path] = None):
     """Yield HF cache snapshot dirs for *repo_id*, newest first.
 
     Empty if HF_HUB_CACHE is missing, the repo isn't cached, or has no
     snapshots. Repo name match is case-insensitive to handle casing drift
     between download time and lookup.
     """
-    try:
-        from huggingface_hub import constants as hf_constants
-    except Exception:
-        return
-
-    cache_dir = Path(hf_constants.HF_HUB_CACHE)
+    if cache_dir is None:
+        try:
+            from utils.hf_cache_settings import get_hf_cache_paths
+            cache_dir = get_hf_cache_paths().hub_cache
+        except Exception:
+            return
+    cache_dir = Path(cache_dir)
     target = f"models--{repo_id.replace('/', '--')}".lower()
     repo_dirs: list[Path] = []
     try:
@@ -1879,7 +1956,7 @@ def _find_local_gguf_by_variant(directory: str, variant: str) -> Optional[str]:
     For sharded GGUFs (multiple files sharing a quant label), returns the
     first shard (sorted by name), which is what ``llama-server -m`` expects.
 
-    Returns the resolved absolute path, or ``None`` if no match.
+    Returns the absolute path, or ``None`` if no match.
     """
     p = _resolve_gguf_dir(Path(directory))
     if p is None:
@@ -1900,7 +1977,7 @@ def _find_local_gguf_by_variant(directory: str, variant: str) -> Optional[str]:
         matches.append(f)
     matches.sort()
     if matches:
-        return str(matches[0].resolve())
+        return str(_local_gguf_load_path(matches[0]))
     return None
 
 
@@ -1997,6 +2074,7 @@ def download_gguf_file(
         repo_id = repo_id,
         filename = filename,
         token = hf_token,
+        cache_dir = active_hf_hub_cache(),
     )
     return local_path
 
@@ -2005,6 +2083,24 @@ def download_gguf_file(
 _embedding_detection_cache: Dict[tuple, bool] = {}
 
 
+# Bound the Hub lookup so a DNS-dead session fails fast to the cache instead of hanging on retries.
+_HUB_MODEL_INFO_TIMEOUT = 15.0
+
+
+def _embedding_marker_in_hf_cache(model_name: str) -> bool:
+    """True when model_name's cached snapshot carries a modules.json (the ST marker).
+    Cache-only, no network; used offline and as a fallback when the Hub lookup times out."""
+    from utils.utils import hf_cache_snapshot_dir
+
+    snapshot = hf_cache_snapshot_dir(model_name)
+    if snapshot is None:
+        return False
+    try:
+        return (snapshot / "modules.json").is_file()
+    except OSError:
+        return False
+
+
 def is_embedding_model(model_name: str, hf_token: Optional[str] = None) -> bool:
     """Detect embedding/sentence-transformer models via HF metadata.
 
@@ -2019,6 +2115,15 @@ def is_embedding_model(model_name: str, hf_token: Optional[str] = None) -> bool:
     Returns:
         True if embedding model, else False (default for local paths or errors).
     """
+    from utils.utils import hf_env_offline
+
+    # Offline (remote repo): reclassify from the local cache on every call, before/without the
+    # memo. An online lookup can memoize True from tags with no weights cached, so trusting it once
+    # the session goes offline would accept a repo _get() cannot load; a cached negative can also be
+    # invalidated by later cache materialization. The cache probe is local-only, so it's cheap.
+    if not is_local_path(model_name) and hf_env_offline():
+        return _embedding_marker_in_hf_cache(model_name)
+
     cache_key = (model_name, hf_token)
     if cache_key in _embedding_detection_cache:
         return _embedding_detection_cache[cache_key]
@@ -2033,7 +2138,7 @@ def is_embedding_model(model_name: str, hf_token: Optional[str] = None) -> bool:
     try:
         from huggingface_hub import model_info as hf_model_info
 
-        info = hf_model_info(model_name, token = hf_token)
+        info = hf_model_info(model_name, token = hf_token, timeout = _HUB_MODEL_INFO_TIMEOUT)
         tags = set(info.tags or [])
         pipeline_tag = info.pipeline_tag or ""
 
@@ -2054,9 +2159,11 @@ def is_embedding_model(model_name: str, hf_token: Optional[str] = None) -> bool:
         return is_emb
 
     except Exception as e:
+        # Timeout or transient network error: fall back to the local cache marker, don't hard-fail.
         logger.warning(f"Could not determine if {model_name} is embedding model: {e}")
-        _embedding_detection_cache[cache_key] = False
-        return False
+        is_emb = _embedding_marker_in_hf_cache(model_name)
+        _embedding_detection_cache[cache_key] = is_emb
+        return is_emb
 
 
 def _has_model_weight_files(model_dir: Path) -> bool:
@@ -2416,7 +2523,10 @@ def get_base_model_from_lora_identifier(
     for _attempt in range(2):  # one retry: a transient blip must not skip the base
         try:
             cfg_path = hf_hub_download(
-                identifier, "adapter_config.json", token = hf_token if hf_token else None
+                identifier,
+                "adapter_config.json",
+                token = hf_token if hf_token else None,
+                cache_dir = active_hf_hub_cache(),
             )
         except (EntryNotFoundError, RepositoryNotFoundError):
             # No adapter_config.json -> not a resolvable LoRA; caller scans the identifier.
@@ -2796,7 +2906,12 @@ class ModelConfig:
                 try:
                     from huggingface_hub import hf_hub_download
 
-                    config_path = hf_hub_download(identifier, "adapter_config.json", token = hf_token)
+                    config_path = hf_hub_download(
+                        identifier,
+                        "adapter_config.json",
+                        token = hf_token,
+                        cache_dir = active_hf_hub_cache(),
+                    )
                     with open(config_path, "r") as f:
                         adapter_config = json.load(f)
                     base_model = adapter_config.get("base_model_name_or_path")
diff --git a/studio/backend/utils/native_path_leases.py b/studio/backend/utils/native_path_leases.py
index 08671cfe39..3ed7faa7c2 100644
--- a/studio/backend/utils/native_path_leases.py
+++ b/studio/backend/utils/native_path_leases.py
@@ -15,6 +15,7 @@ import base64
 import binascii
 import hashlib
 import hmac
+import importlib
 import json
 import os
 import stat as _stat_module
@@ -35,7 +36,7 @@ _USED_NONCES: dict[str, int] = {}
 _REDACTION_LOCK = threading.Lock()
 _NATIVE_PATH_REDACTIONS: list[str] = []
 _NATIVE_PATH_LABELS: dict[str, str] = {}
-_NATIVE_PATH_ENV_LOCK = threading.Lock()
+_NATIVE_PATH_ENV_LOCK = threading.RLock()
 _SECRET_INIT_LOCK = threading.Lock()
 _CACHED_LEASE_SECRET: bytes | None = None
 _SCRUB_REFCOUNT = 0
@@ -80,7 +81,9 @@ def child_env_without_native_path_secret(env: Mapping[str, str] | None = None) -
     return cleaned
 
 
-def run_without_native_path_secret(target: Callable[..., Any], *args: Any, **kwargs: Any) -> Any:
+def run_without_native_path_secret(
+    target: Callable[..., Any] | str, *args: Any, **kwargs: Any
+) -> Any:
     """Run a multiprocessing child target without the native path lease secret."""
 
     # Runs in the spawned child: bind it to the parent's death (Linux), since
@@ -96,6 +99,11 @@ def run_without_native_path_secret(target: Callable[..., Any], *args: Any, **kwa
     os.environ.pop(LEASE_SECRET_ENV, None)
     _CACHED_LEASE_SECRET = None
     _SCRUB_SAVED_SECRET = None
+    if isinstance(target, str):
+        function_name, environment, *args = args
+        for key, value in environment.items():
+            os.environ[key] = value
+        target = getattr(importlib.import_module(target), function_name)
     return target(*args, **kwargs)
 
 
@@ -107,10 +115,9 @@ def native_path_secret_removed_for_child_start() -> Iterator[None]:
             _SCRUB_SAVED_SECRET = os.environ.pop(LEASE_SECRET_ENV, None)
             _CACHED_LEASE_SECRET = None
         _SCRUB_REFCOUNT += 1
-    try:
-        yield
-    finally:
-        with _NATIVE_PATH_ENV_LOCK:
+        try:
+            yield
+        finally:
             _SCRUB_REFCOUNT -= 1
             if _SCRUB_REFCOUNT == 0 and _SCRUB_SAVED_SECRET is not None:
                 os.environ[LEASE_SECRET_ENV] = _SCRUB_SAVED_SECRET
diff --git a/studio/backend/utils/paths/external_media.py b/studio/backend/utils/paths/external_media.py
index 0ea0477cc7..1a0d2d2746 100644
--- a/studio/backend/utils/paths/external_media.py
+++ b/studio/backend/utils/paths/external_media.py
@@ -131,6 +131,29 @@ def linux_run_media_mount_roots(
     return roots
 
 
+def macos_volume_roots(base: Path | str = "/Volumes") -> list[Path]:
+    """Readable mounted volumes for the macOS folder browser."""
+
+    if platform.system() != "Darwin":
+        return []
+    base_path = Path(base)
+    try:
+        entries = list(base_path.iterdir())
+    except OSError:
+        return []
+    roots: list[Path] = []
+    for entry in entries:
+        if is_sensitive_path_component(entry.name):
+            continue
+        try:
+            resolved = entry.resolve()
+            if resolved.is_dir() and os.access(resolved, os.R_OK | os.X_OK):
+                roots.append(resolved)
+        except (OSError, RuntimeError, ValueError):
+            continue
+    return roots
+
+
 def _active_windows_drive_bitmask() -> int:
     """Active-logical-drive bitmask from ``GetLogicalDrives`` (bit 0 = ``A:``), or ``0`` when unavailable.
 
diff --git a/studio/backend/utils/paths/path_utils.py b/studio/backend/utils/paths/path_utils.py
index e8dabc8954..65541661f1 100644
--- a/studio/backend/utils/paths/path_utils.py
+++ b/studio/backend/utils/paths/path_utils.py
@@ -122,15 +122,8 @@ def is_model_cached(model_name: str) -> bool:
 
 def _hf_hub_cache_dir() -> Path:
     """Return HF cache root honoring HF_HUB_CACHE when available."""
-    try:
-        from huggingface_hub.constants import HF_HUB_CACHE
-        return Path(HF_HUB_CACHE)
-    except Exception as exc:
-        logger.debug(
-            "Could not read huggingface_hub HF_HUB_CACHE, using default hub path: %s",
-            exc,
-        )
-        return Path.home() / ".cache" / "huggingface" / "hub"
+    from utils.hf_cache_settings import get_hf_cache_paths
+    return get_hf_cache_paths().hub_cache
 
 
 def resolve_cached_repo_id_case(model_name: str, use_memo: bool = True) -> str:
diff --git a/studio/backend/utils/paths/storage_roots.py b/studio/backend/utils/paths/storage_roots.py
index 35b8c57e9b..cea3cc61e3 100644
--- a/studio/backend/utils/paths/storage_roots.py
+++ b/studio/backend/utils/paths/storage_roots.py
@@ -277,27 +277,15 @@ def well_known_model_dirs() -> list[Path]:
 def _setup_cache_env() -> None:
     """Set cache env vars for HuggingFace, uv, and vLLM.
 
-    Respects the standard HF cache chain (explicit HF_HOME / HF_HUB_CACHE,
-    then XDG_CACHE_HOME, then ~/.cache/huggingface) and only sets vars the
-    user hasn't, so explicit overrides are honored. A user-set HF_HOME also
-    seeds HF_HUB_CACHE / HF_XET_CACHE (HF defaults them to $HF_HOME/hub and
-    $HF_HOME/xet); without this, models download to and load from the standard
-    cache even when HF_HOME points elsewhere, and both the Xet and HTTP-fallback
-    download paths inherit the same wrong root.
+    Explicit Hugging Face environment variables take precedence over Studio's
+    stored location. Studio seeds import-time variables once, while each later
+    worker receives its own captured cache location.
     """
     root = cache_root()
-    xdg_cache = Path(os.environ.get("XDG_CACHE_HOME", Path.home() / ".cache")).expanduser()
-    # HUGGINGFACE_HUB_CACHE is HF's legacy alias for HF_HUB_CACHE; honor it.
-    if "HF_HUB_CACHE" not in os.environ and os.environ.get("HUGGINGFACE_HUB_CACHE"):
-        os.environ["HF_HUB_CACHE"] = os.environ["HUGGINGFACE_HUB_CACHE"]
-    # Seed the hub/xet caches from HF_HOME when set, else the platform default.
-    # Strip so a blank/whitespace HF_HOME falls back instead of making " /hub".
-    hf_home = (os.environ.get("HF_HOME") or "").strip()
-    hf_base = Path(hf_home).expanduser() if hf_home else xdg_cache / "huggingface"
+    from utils.hf_cache_settings import initialize_hf_cache_environment
+
+    initialize_hf_cache_environment()
     defaults: dict[str, str] = {
-        "HF_HOME": str(hf_base),
-        "HF_HUB_CACHE": str(hf_base / "hub"),
-        "HF_XET_CACHE": str(hf_base / "xet"),
         "UV_CACHE_DIR": str(root / "uv"),
         "VLLM_CACHE_ROOT": str(root / "vllm"),
     }
diff --git a/studio/backend/utils/prebuilt/__init__.py b/studio/backend/utils/prebuilt/__init__.py
new file mode 100644
index 0000000000..c41cd1150d
--- /dev/null
+++ b/studio/backend/utils/prebuilt/__init__.py
@@ -0,0 +1,11 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Backend-importable prebuilt helpers.
+
+The installers reuse install_llama_prebuilt.py directly; this package holds the
+backend-side shapes the studio/ scripts cannot provide (the backend runs with
+studio/backend as its sys.path root): runtime_libs (wheel CUDA dirs), child_env
+(secret scrubbing + WSL ROCm dirs), freshness_flow and update_flow (the shared
+mechanics behind the *_cpp_freshness / *_cpp_update twins).
+"""
diff --git a/studio/backend/utils/prebuilt/child_env.py b/studio/backend/utils/prebuilt/child_env.py
new file mode 100644
index 0000000000..b6b7a40df7
--- /dev/null
+++ b/studio/backend/utils/prebuilt/child_env.py
@@ -0,0 +1,145 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Child-process environment hygiene for the managed ggml servers.
+
+Secret-env scrubbing and the WSL2 ROCm library-dir probe, shared by the STT
+sidecar (and any future launcher of a downloaded binary). Kept in sync with
+install_llama_prebuilt.py's scrub_env / _wsl_system_rocm_lib_dirs; the backend
+cannot import the studio/ installer scripts, so this copy stays importable with
+only the backend root on sys.path.
+"""
+
+from __future__ import annotations
+
+import os
+import re
+from typing import Mapping
+
+SECRET_ENV_EXACT = frozenset(
+    {
+        "HF_TOKEN",
+        "HUGGING_FACE_HUB_TOKEN",
+        "GH_TOKEN",
+        "GITHUB_TOKEN",
+        "WANDB_API_KEY",
+        "OPENAI_API_KEY",
+        "ANTHROPIC_API_KEY",
+        "AWS_ACCESS_KEY_ID",
+        "AWS_SECRET_ACCESS_KEY",
+        "AWS_SESSION_TOKEN",
+        "GOOGLE_APPLICATION_CREDENTIALS",
+        "AZURE_CLIENT_SECRET",
+        "KUBECONFIG",
+        "SSH_AUTH_SOCK",
+    }
+)
+# Case-insensitive substring markers for names we do not enumerate (no bare "KEY").
+SECRET_ENV_MARKERS = (
+    "TOKEN",
+    "SECRET",
+    "PASSWORD",
+    "PASSWD",
+    "PASSPHRASE",
+    "CREDENTIAL",
+    "PRIVATE_KEY",
+    "API_KEY",
+)
+# Proxy / index URLs embed creds in their value; the offline server never needs them.
+SECRET_ENV_URL_NAMES = frozenset(
+    {
+        "HTTP_PROXY",
+        "HTTPS_PROXY",
+        "ALL_PROXY",
+        "FTP_PROXY",
+        "RSYNC_PROXY",
+        "PIP_INDEX_URL",
+        "PIP_EXTRA_INDEX_URL",
+        "UV_INDEX_URL",
+        "UV_DEFAULT_INDEX",
+        "UV_EXTRA_INDEX_URL",
+    }
+)
+# Also drop values with URL userinfo creds (scheme://user:secret@host).
+URL_USERINFO_RE = re.compile(r"://[^/@\s]+@")
+
+
+def is_secret_env_name(name: str) -> bool:
+    upper = name.upper()
+    return (
+        upper in SECRET_ENV_EXACT
+        or upper in SECRET_ENV_URL_NAMES
+        or any(marker in upper for marker in SECRET_ENV_MARKERS)
+    )
+
+
+def scrub_env(env: Mapping[str, str]) -> dict[str, str]:
+    """Copy of ``env`` without secret-bearing names or URL-userinfo values."""
+    return {
+        k: v
+        for k, v in env.items()
+        if not is_secret_env_name(k) and not URL_USERINFO_RE.search(v or "")
+    }
+
+
+# Filesystem pointers a downloaded binary could follow to on-disk credential
+# stores (token caches under $HF_HOME, ~/.netrc, XDG config). Dropped, not
+# repointed; the offline inference server needs none. Mirrors the cred-location
+# list of the tools bypass env (core/inference/tools.py).
+CRED_LOCATION_ENV_NAMES = frozenset(
+    {
+        "HF_HOME",
+        "HF_HUB_CACHE",
+        "HUGGINGFACE_HUB_CACHE",
+        "HF_XET_CACHE",
+        "TRANSFORMERS_CACHE",
+        "HF_DATASETS_CACHE",
+        "XDG_CONFIG_HOME",
+        "XDG_CACHE_HOME",
+        "XDG_DATA_HOME",
+        "NETRC",
+        "BASH_ENV",
+        "GIT_CONFIG_GLOBAL",
+        "GIT_CONFIG_SYSTEM",
+        "GIT_ASKPASS",
+        "SSH_ASKPASS",
+        "HOMEDRIVE",
+        "HOMEPATH",
+    }
+)
+# Home dirs are repointed (not dropped): loaders and SDKs expect them present,
+# but they must not resolve to the user's real profile with its token caches.
+HOME_ENV_NAMES = ("HOME", "USERPROFILE", "APPDATA", "LOCALAPPDATA")
+
+
+def isolate_home(env: dict[str, str], scratch_dir: str) -> dict[str, str]:
+    """Repoint home/profile vars at ``scratch_dir`` and drop credential-store
+    pointers so a compromised downloaded server cannot read token caches or cred
+    files through the environment. Mutates and returns ``env``."""
+    os.makedirs(scratch_dir, exist_ok = True)
+    for name in HOME_ENV_NAMES:
+        if name in env:
+            env[name] = scratch_dir
+    for name in CRED_LOCATION_ENV_NAMES:
+        env.pop(name, None)
+    return env
+
+
+def wsl_system_rocm_lib_dirs() -> list[str]:
+    """System ROCm lib dir(s) to load before a bundle's HIP on WSL2. Strict no-op
+    off WSL (needs /dev/dxg, a "microsoft" /proc/version, and a librocdxg)."""
+    try:
+        if not os.path.exists("/dev/dxg"):
+            return []
+        with open("/proc/version", encoding = "utf-8", errors = "replace") as fh:
+            if "microsoft" not in fh.read().lower():
+                return []
+    except OSError:
+        return []
+    dirs: list[str] = []
+    for d in ("/opt/rocm/lib", "/opt/rocm/lib64"):
+        if os.path.exists(os.path.join(d, "librocdxg.so")) or os.path.exists(
+            os.path.join(d, "librocdxg.so.1")
+        ):
+            dirs.append(d)
+    return dirs
diff --git a/studio/backend/utils/prebuilt/freshness_flow.py b/studio/backend/utils/prebuilt/freshness_flow.py
new file mode 100644
index 0000000000..b90ebf776c
--- /dev/null
+++ b/studio/backend/utils/prebuilt/freshness_flow.py
@@ -0,0 +1,325 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Shared mechanics of the llama.cpp / whisper.cpp prebuilt freshness checks.
+
+The component modules (utils.llama_cpp_freshness / utils.whisper_cpp_freshness)
+keep their public names, per-module caches, and version-comparison policy;
+everything mechanical (marker walk-up, GitHub release fetch, memo + disk cache,
+the freshness report skeleton) lives here, parameterized by call-time callables
+so the modules' monkeypatch seams keep working.
+"""
+
+from __future__ import annotations
+
+import json
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Callable, Optional
+
+import structlog
+
+logger = structlog.get_logger(__name__)
+
+# 24h TTL keeps the GitHub call off the hot path and within rate limits.
+RELEASE_CACHE_TTL_SECONDS = 24 * 60 * 60
+
+
+def read_install_marker(
+    binary_path: Optional[str],
+    *,
+    marker_name: str,
+    cache: dict[str, Optional[dict]],
+    log_message: str,
+) -> Optional[dict]:
+    """Walk up from binary_path to find the install marker JSON.
+    None = no marker (source build / custom path) or invalid JSON."""
+    if not binary_path:
+        return None
+    cached = cache.get(binary_path)
+    if cached is not None or binary_path in cache:
+        return cached
+    p = Path(binary_path)
+    marker: Optional[dict] = None
+    # Cover all managed binary layouts (binary is 1-4 dirs deep).
+    for parent in p.parents[:5]:
+        candidate = parent / marker_name
+        if candidate.is_file():
+            try:
+                marker = json.loads(candidate.read_text(encoding = "utf-8"))
+            except (OSError, json.JSONDecodeError) as exc:
+                logger.debug(log_message, path = str(candidate), error = str(exc))
+                marker = None
+            break
+    cache[binary_path] = marker
+    return marker
+
+
+def cache_path_for(repo: str, cache_dir: Path) -> Path:
+    safe = repo.replace("/", "__")
+    return cache_dir / f"{safe}.json"
+
+
+def load_disk_cache(repo: str, cache_dir: Path) -> Optional[tuple[float, Optional[str]]]:
+    path = cache_path_for(repo, cache_dir)
+    try:
+        payload = json.loads(path.read_text(encoding = "utf-8"))
+    except (OSError, json.JSONDecodeError):
+        return None
+    ts = payload.get("fetched_at")
+    tag = payload.get("latest_tag")
+    if not isinstance(ts, (int, float)):
+        return None
+    return float(ts), tag if isinstance(tag, str) else None
+
+
+def save_disk_cache(
+    repo: str, latest_tag: Optional[str], cache_dir: Path, *, log_message: str
+) -> None:
+    path = cache_path_for(repo, cache_dir)
+    try:
+        path.parent.mkdir(parents = True, exist_ok = True)
+        tmp = path.with_suffix(".tmp")
+        tmp.write_text(
+            json.dumps({"fetched_at": time.time(), "latest_tag": latest_tag}),
+            encoding = "utf-8",
+        )
+        tmp.replace(path)
+    except OSError as exc:
+        logger.debug(log_message, repo = repo, error = str(exc))
+
+
+def _fetch_newest_published_release(
+    repo: str, timeout: float, *, log_message: str
+) -> Optional[dict]:
+    """Newest published (non-draft/non-prerelease) release object for `repo`, by
+    ``published_at``.
+
+    Resolves "latest" the way the installers do, NOT via GitHub's
+    ``/releases/latest`` pointer, which sorts by commit date and can lag the
+    build the installer installs (detection and apply then disagree -- the
+    downgrade/sticky-banner bug). None on any failure (offline, rate-limited)."""
+    import os
+    import urllib.error
+    import urllib.request
+
+    url = f"https://api.github.com/repos/{repo}/releases?per_page=30"
+    headers = {
+        "Accept": "application/vnd.github+json",
+        "User-Agent": "unsloth-studio-freshness-check",
+    }
+    token = os.environ.get("GITHUB_TOKEN") or os.environ.get("GH_TOKEN")
+    if token:
+        headers["Authorization"] = f"Bearer {token}"
+    req = urllib.request.Request(url, headers = headers)
+    try:
+        with urllib.request.urlopen(req, timeout = timeout) as resp:
+            data = json.loads(resp.read().decode("utf-8"))
+    except (
+        urllib.error.URLError,
+        urllib.error.HTTPError,
+        OSError,
+        json.JSONDecodeError,
+    ) as exc:
+        logger.debug(log_message, repo = repo, error = str(exc))
+        return None
+    if not isinstance(data, list):
+        return None
+    published = [
+        r
+        for r in data
+        if isinstance(r, dict)
+        and not r.get("draft")
+        and not r.get("prerelease")
+        and isinstance(r.get("tag_name"), str)
+        and r.get("tag_name")
+    ]
+    if not published:
+        return None
+    return max(published, key = lambda r: r.get("published_at") or "")
+
+
+def fetch_latest_release_tag(
+    repo: str,
+    timeout: float = 5.0,
+    *,
+    log_message: str,
+) -> Optional[str]:
+    """Newest published release tag for `repo`, by publish time. None on failure."""
+    newest = _fetch_newest_published_release(repo, timeout, log_message = log_message)
+    return newest["tag_name"] if newest else None
+
+
+def fetch_latest_release_assets(
+    repo: str,
+    timeout: float = 5.0,
+    *,
+    log_message: str,
+) -> Optional[dict[str, int]]:
+    """Asset name -> size (bytes) for the newest published release of `repo`,
+    selected exactly like fetch_latest_release_tag. None on any failure."""
+    newest = _fetch_newest_published_release(repo, timeout, log_message = log_message)
+    if newest is None:
+        return None
+    assets: dict[str, int] = {}
+    for a in newest.get("assets") or []:
+        name, size = a.get("name"), a.get("size")
+        if isinstance(name, str) and isinstance(size, int):
+            assets[name] = size
+    return assets
+
+
+def latest_published_release(
+    repo: str,
+    *,
+    force_refresh: bool,
+    memo: dict[str, tuple[float, Optional[str]]],
+    cache_dir: Callable[[], Path],
+    fetch: Callable[[str], Optional[str]],
+    save: Callable[[str, Optional[str]], None],
+) -> Optional[str]:
+    """Latest release tag for `repo`. Memo + disk-cached (24h TTL).
+    None when offline and never previously cached."""
+    if not repo:
+        return None
+    now = time.time()
+    if not force_refresh:
+        cached = memo.get(repo)
+        if cached and now - cached[0] < RELEASE_CACHE_TTL_SECONDS:
+            return cached[1]
+        disk = load_disk_cache(repo, cache_dir())
+        if disk and now - disk[0] < RELEASE_CACHE_TTL_SECONDS:
+            memo[repo] = disk
+            return disk[1]
+    latest = fetch(repo)
+    if latest is None:
+        # Keep the last-good disk value rather than poison it with None.
+        disk = load_disk_cache(repo, cache_dir())
+        if disk:
+            memo[repo] = disk
+            return disk[1]
+        return None
+    memo[repo] = (now, latest)
+    save(repo, latest)
+    return latest
+
+
+def latest_release_assets(
+    repo: str,
+    *,
+    force_refresh: bool,
+    memo: dict[str, tuple[float, dict[str, int]]],
+    fetch: Callable[[str], Optional[dict[str, int]]],
+) -> Optional[dict[str, int]]:
+    """Newest-release asset sizes for `repo`, memoized (24h TTL). None when
+    offline and never fetched. In-memory only -- a restart re-fetches."""
+    if not repo:
+        return None
+    now = time.time()
+    if not force_refresh:
+        cached = memo.get(repo)
+        if cached and now - cached[0] < RELEASE_CACHE_TTL_SECONDS:
+            return cached[1]
+    assets = fetch(repo)
+    if assets is None:
+        cached = memo.get(repo)
+        return cached[1] if cached else None
+    memo[repo] = (now, assets)
+    return assets
+
+
+def parse_installed_at(value: object) -> Optional[datetime]:
+    if not isinstance(value, str) or not value:
+        return None
+    s = value.replace("Z", "+00:00") if value.endswith("Z") else value
+    try:
+        dt = datetime.fromisoformat(s)
+    except ValueError:
+        return None
+    if dt.tzinfo is None:
+        dt = dt.replace(tzinfo = timezone.utc)
+    return dt
+
+
+def check_freshness(
+    binary_path: Optional[str],
+    *,
+    threshold_days: int,
+    now: Optional[datetime],
+    read_marker: Callable[[Optional[str]], Optional[dict]],
+    latest_release: Callable[[str], Optional[str]],
+    behind: Callable[[Optional[str], Optional[str]], bool],
+    display_tag: Callable[[dict], Any],
+    compare_tag: Callable[[dict], Any],
+) -> dict:
+    """Freshness report skeleton shared by both components; the component's
+    marker-tag choice and is_behind policy come in as callables. Fails open on
+    missing data (behind/stale stay False)."""
+    out: dict = {
+        "has_marker": False,
+        "stale": False,
+        "behind": False,
+        "installed_tag": None,
+        "latest_tag": None,
+        "installed_at_utc": None,
+        "age_days": None,
+        "published_repo": None,
+        "threshold_days": int(threshold_days),
+    }
+    marker = read_marker(binary_path)
+    if not marker:
+        return out
+    out["has_marker"] = True
+    out["installed_tag"] = display_tag(marker)
+    out["installed_at_utc"] = marker.get("installed_at_utc")
+    out["published_repo"] = marker.get("published_repo")
+
+    installed_full = compare_tag(marker)
+    repo = out["published_repo"]
+    if not repo or not installed_full:
+        return out
+    latest = latest_release(repo)
+    out["latest_tag"] = latest
+    out["behind"] = behind(installed_full, latest)
+    if not out["behind"]:
+        return out
+
+    installed_at = parse_installed_at(out["installed_at_utc"])
+    if installed_at is None:
+        return out
+    now = now or datetime.now(tz = timezone.utc)
+    age_seconds = (now - installed_at).total_seconds()
+    out["age_days"] = max(0, int(age_seconds // 86400))
+    if age_seconds >= threshold_days * 86400:
+        out["stale"] = True
+    return out
+
+
+def format_stale_warning(info: dict, *, component: str) -> str:
+    """Human-readable one-liner for stale prebuilt info."""
+    age = info.get("age_days")
+    installed = info.get("installed_tag") or "unknown"
+    latest = info.get("latest_tag") or "unknown"
+    age_str = f"{age} day{'s' if age != 1 else ''}" if age is not None else "some time"
+    return (
+        f"{component} prebuilt is {age_str} behind: installed "
+        f"{installed}, latest {latest}. Run `unsloth studio update` "
+        f"to refresh."
+    )
+
+
+def reset_caches(
+    caches: tuple[dict, ...], *, drop_disk: bool, cache_dir: Callable[[], Path]
+) -> None:
+    """Drop the in-memory freshness caches; with drop_disk also the on-disk 24h
+    release cache (see the component modules for why)."""
+    for cache in caches:
+        cache.clear()
+    if drop_disk:
+        import shutil
+
+        # cache_dir() is a dedicated freshness-only subdir, re-created on the next
+        # save_disk_cache. ignore_errors so a missing/locked dir is a no-op rather
+        # than breaking an otherwise successful install.
+        shutil.rmtree(cache_dir(), ignore_errors = True)
diff --git a/studio/backend/utils/prebuilt/runtime_libs.py b/studio/backend/utils/prebuilt/runtime_libs.py
new file mode 100644
index 0000000000..6e51fb8246
--- /dev/null
+++ b/studio/backend/utils/prebuilt/runtime_libs.py
@@ -0,0 +1,65 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""CUDA runtime dirs shipped inside Python wheels, for the STT sidecar's child env.
+
+Kept in sync with install_llama_prebuilt.py's python_runtime_dirs; the backend
+cannot import the studio/ installer scripts, so this small copy stays importable
+with only the backend root on sys.path.
+"""
+
+from __future__ import annotations
+
+import site
+import sys
+from pathlib import Path
+from typing import Iterable
+
+
+def dedupe_existing_dirs(paths: Iterable[str | Path]) -> list[str]:
+    unique: list[str] = []
+    seen: set[str] = set()
+    for raw in paths:
+        if not raw:
+            continue
+        try:
+            path = Path(raw).expanduser()
+            if not path.is_dir():
+                continue
+            resolved = str(path.resolve())
+        except (OSError, ValueError):
+            continue
+        if resolved in seen:
+            continue
+        seen.add(resolved)
+        unique.append(resolved)
+    return unique
+
+
+def python_runtime_dirs() -> list[str]:
+    """CUDA runtime dirs shipped inside Python wheels (torch + nvidia-* wheels)."""
+    candidates: list[Path] = []
+    search_roots = [Path(entry) for entry in sys.path if entry]
+    try:
+        search_roots.extend(Path(path) for path in site.getsitepackages())
+    except Exception:
+        pass
+    try:
+        user_site = site.getusersitepackages()
+        if user_site:
+            search_roots.append(Path(user_site))
+    except Exception:
+        pass
+
+    for root in search_roots:
+        if not root.is_dir():
+            continue
+        candidates.extend(root.glob("nvidia/*/lib"))  # Linux convention
+        candidates.extend(root.glob("nvidia/*/bin"))  # legacy modular Windows wheels
+        candidates.extend(root.glob("nvidia/*/bin/x86_64"))  # CUDA 13 Windows wheel layout
+        candidates.extend(root.glob("nvidia/*/bin/x64"))
+        candidates.extend(root.glob("nvidia/*/Library/bin"))  # conda-style repacks
+        candidates.extend(root.glob("nvidia/*/Library/bin/x86_64"))
+        candidates.extend(root.glob("nvidia/*/Library/bin/x64"))
+        candidates.extend(root.glob("torch/lib"))
+    return dedupe_existing_dirs(candidates)
diff --git a/studio/backend/utils/prebuilt/update_flow.py b/studio/backend/utils/prebuilt/update_flow.py
new file mode 100644
index 0000000000..74af0c18f9
--- /dev/null
+++ b/studio/backend/utils/prebuilt/update_flow.py
@@ -0,0 +1,447 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Shared mechanics of the llama.cpp / whisper.cpp in-app prebuilt updates.
+
+The component modules (utils.llama_cpp_update / utils.whisper_cpp_update) keep
+their public names, job dicts, and update policy (version comparison, pinning,
+pre/post install steps); everything mechanical (managed-root resolution,
+local-link detection, the resolve probe, the streamed installer run) lives here,
+parameterized so the modules' monkeypatch seams keep working.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import re
+import subprocess
+import sys
+import threading
+import time
+from pathlib import Path
+from typing import Callable, Optional
+
+import structlog
+
+from utils.process_lifetime import child_popen_kwargs
+
+logger = structlog.get_logger(__name__)
+
+# Markerless (source-build) resolve answers are memoized for 24h; only
+# successful answers are cached so a network blip retries.
+RESOLVE_TTL_SECONDS = 24 * 60 * 60
+
+# Matches the installer's download progress lines, e.g.
+# "Downloading x.zip:  35.0% (12.3 MiB/35.1 MiB) at 8.2 MiB/s".
+PROGRESS_LINE_RE = re.compile(r"(\d+(?:\.\d+)?)%\s*\(")
+# The download dominates the update; extract/validate fill the last slice.
+DOWNLOAD_PROGRESS_CEILING = 0.95
+
+
+class InstallerExit(RuntimeError):
+    """Installer subprocess exited nonzero; carries the exit code so phase
+    runners can special-case contractual codes (whisper's 2 = unavailable)."""
+
+    def __init__(self, returncode: int, message: str) -> None:
+        super().__init__(message)
+        self.returncode = returncode
+
+
+JOB_IDLE = "idle"
+JOB_RUNNING = "running"
+JOB_SUCCESS = "success"
+JOB_ERROR = "error"
+
+# Per-phase states inside a chained job's "phases" breakdown.
+PHASE_PENDING = "pending"
+PHASE_RUNNING = "running"
+PHASE_SUCCESS = "success"
+PHASE_ERROR = "error"
+PHASE_SKIPPED = "skipped"
+
+_IDLE_JOB_FIELDS = dict(
+    state = JOB_IDLE,
+    message = "",
+    from_tag = None,
+    to_tag = None,
+    reload_required = None,
+    error = None,
+    progress = None,
+    started_at = None,
+    finished_at = None,
+    phases = None,
+)
+
+
+def new_job() -> dict:
+    """A fresh idle job-state dict (one per component module)."""
+    return dict(_IDLE_JOB_FIELDS)
+
+
+def reset_job(job: dict, job_lock: threading.Lock) -> None:
+    """Return a job tracker to idle (test seam)."""
+    with job_lock:
+        job.update(_IDLE_JOB_FIELDS)
+
+
+def utcnow() -> str:
+    return time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+
+
+def is_under(path: Path, root: Path) -> bool:
+    try:
+        p, r = path.resolve(), root.resolve()
+    except (OSError, ValueError):
+        p, r = path, root
+    return p == r or r in p.parents
+
+
+def install_dir_for(binary_path: Optional[str], *, marker_name: str) -> Optional[Path]:
+    """The directory holding the install marker: the install root the installer
+    wrote and the one we re-install into. Walks up from the binary like the
+    freshness marker reader does."""
+    if not binary_path:
+        return None
+    p = Path(binary_path)
+    for parent in p.parents[:5]:
+        if (parent / marker_name).is_file():
+            return parent
+    return None
+
+
+def find_installer_script(*, env_var: str, script_name: str) -> Optional[Path]:
+    """Locate the installer script. Honours the env override, then searches up
+    from this file for both ``<root>/<script>`` and ``<root>/studio/<script>`` so
+    it works in the dev tree and in an installed Unsloth layout."""
+    env = os.environ.get(env_var)
+    if env and Path(env).is_file():
+        return Path(env)
+    here = Path(__file__).resolve()
+    for up in here.parents:
+        for cand in (up / script_name, up / "studio" / script_name):
+            if cand.is_file():
+                return cand
+    return None
+
+
+def resolve_prebuilt_for_host(
+    *,
+    force_refresh: bool,
+    memo: dict,
+    installer_script: Callable[[], Optional[Path]],
+    log_message: str,
+    extra_args: tuple[str, ...] = (),
+) -> Optional[dict]:
+    """Run ``<installer> --resolve-prebuilt latest --output-format json`` (no
+    download); return the parsed payload or None. Fail-open: any error -> None so
+    a source build never blocks the app."""
+    now = time.time()
+    cache_key = tuple(extra_args)
+    if not force_refresh and memo.get("key") == cache_key:
+        if now - memo.get("at", 0.0) < RESOLVE_TTL_SECONDS:
+            return memo.get("value")
+    script = installer_script()
+    if script is None:
+        return None
+    value: Optional[dict] = None
+    try:
+        cmd = [
+            sys.executable,
+            str(script),
+            "--resolve-prebuilt",
+            "latest",
+            "--output-format",
+            "json",
+            *extra_args,
+        ]
+        proc = subprocess.run(
+            cmd,
+            capture_output = True,
+            text = True,
+            timeout = 60,
+        )
+        out = (proc.stdout or "").strip()
+        if proc.returncode == 0 and out:
+            parsed = json.loads(out.splitlines()[-1])
+            if isinstance(parsed, dict):
+                value = parsed
+    except Exception as exc:  # pragma: no cover - subprocess/json defensive
+        logger.debug(log_message, error = str(exc))
+        value = None
+    if value is not None:  # cache real answers; let failures retry next poll
+        memo.update(at = now, key = cache_key, value = value)
+    return value
+
+
+def is_external_link(path: Optional[Path]) -> bool:
+    """True when ``path`` is a locally-linked component dir: a POSIX symlink or a
+    Windows junction / reparse point. Such a link resolves into the user's own
+    checkout, so Unsloth must never auto-update it."""
+    if path is None:
+        return False
+    try:
+        if os.path.islink(path):
+            return True
+    except OSError:
+        return False
+    if os.name == "nt":
+        try:
+            import stat
+            attrs = os.lstat(path).st_file_attributes  # type: ignore[attr-defined]
+            return bool(attrs & stat.FILE_ATTRIBUTE_REPARSE_POINT)
+        except (OSError, AttributeError):
+            return False
+    return False
+
+
+def active_install_is_local_link(binary: Optional[str], *, dir_name: str) -> bool:
+    """True when the active server binary resolves through a locally-linked
+    component directory. An update would write through that link into the user's
+    checkout (or fail), so the install is treated as externally managed: none is
+    offered or applied. Checks only up to and including the component dir so a
+    symlinked HOME / studio root above it can't trip a false positive."""
+    if not binary:
+        return False
+    for parent in Path(binary).parents:
+        if is_external_link(parent):
+            return True
+        if parent.name == dir_name:
+            break
+    return False
+
+
+def managed_install_root(
+    binary: Optional[str],
+    *,
+    marker_root: Optional[Path],
+    server_path_var: str,
+    cpp_path_var: str,
+    dir_name: str,
+) -> Optional[Path]:
+    """The Unsloth-managed component root the active binary lives under, or None
+    when unmanaged. Installing where the active binary is not would not replace
+    what discovery runs (a pinned server path, then the custom dir, then a
+    component tree), so we refuse rather than install into an inactive or foreign
+    tree."""
+    if marker_root is not None:
+        return marker_root
+    if not binary:
+        return None
+    # The server-path pin is an explicit user choice that wins in discovery; never
+    # auto-replace its tree (even the user's own checkout).
+    if os.environ.get(server_path_var):
+        return None
+    p = Path(binary)
+    env = os.environ.get(cpp_path_var)
+    if env and is_under(p, Path(env)):
+        return Path(env)
+    for parent in p.parents:
+        if parent.name == dir_name:
+            return parent
+    # PATH / system / custom install: not a managed tree, so do not offer.
+    return None
+
+
+def local_link_status(job: dict, job_lock: threading.Lock) -> dict:
+    """Status payload for a local-link install: unmanaged, no update offered."""
+    with job_lock:
+        snapshot = dict(job)
+    return {
+        "supported": False,
+        "update_available": False,
+        "stale": False,
+        "installed_tag": None,
+        "latest_tag": None,
+        "published_repo": None,
+        "installed_at_utc": None,
+        "age_days": None,
+        "source_build": False,
+        "local_link": True,
+        "update_size_bytes": None,
+        "job": snapshot,
+    }
+
+
+def rocm_install_args(asset: Optional[str]) -> list[str]:
+    """Forward --rocm-gfx/--has-rocm from the marker asset, mirroring setup.sh.
+    The installer probe can miss the gfx arch on amd-smi-only hosts; per-gfx ROCm
+    bundles carry the family in the name (rocm-gfx110X), version-tagged bundles
+    only rocm/hip."""
+    if not asset:
+        return []
+    low = asset.lower()
+    if "rocm" not in low and "hip" not in low:
+        return []
+    gfx = re.search(r"-gfx[0-9a-z]+", low)
+    if gfx:
+        return ["--rocm-gfx", gfx.group(0).lstrip("-")]
+    return ["--has-rocm"]
+
+
+def stream_installer(
+    cmd: list[str],
+    env: dict[str, str],
+    *,
+    timeout_seconds: int,
+    job: Optional[dict] = None,
+    job_lock: Optional[threading.Lock] = None,
+    set_progress: Optional[Callable[[float], None]] = None,
+) -> None:
+    """Run the installer, streaming its progress lines into job["progress"]
+    (or through set_progress when given, e.g. a chained-phase progress window).
+    Raises RuntimeError on timeout or a nonzero exit (with an output tail)."""
+    if set_progress is None:
+        assert job is not None and job_lock is not None
+
+        def set_progress(fraction: float) -> None:
+            with job_lock:
+                job["progress"] = max(job.get("progress") or 0.0, fraction)
+
+    proc = subprocess.Popen(
+        cmd,
+        stdout = subprocess.PIPE,
+        stderr = subprocess.STDOUT,
+        text = True,
+        env = env,
+        **child_popen_kwargs(),
+    )
+    timed_out = threading.Event()
+
+    def _kill_on_timeout() -> None:
+        timed_out.set()
+        proc.kill()
+
+    watchdog = threading.Timer(timeout_seconds, _kill_on_timeout)
+    watchdog.daemon = True
+    watchdog.start()
+    tail_lines: list[str] = []
+    try:
+        assert proc.stdout is not None
+        for line in proc.stdout:
+            tail_lines.append(line)
+            if len(tail_lines) > 80:
+                del tail_lines[0]
+            m = PROGRESS_LINE_RE.search(line)
+            if m is None:
+                continue
+            set_progress(min(float(m.group(1)) / 100.0, 1.0) * DOWNLOAD_PROGRESS_CEILING)
+        returncode = proc.wait()
+    finally:
+        watchdog.cancel()
+    if timed_out.is_set():
+        raise RuntimeError(f"installer timed out after {timeout_seconds}s")
+    if returncode != 0:
+        tail = "".join(tail_lines).strip()[-1500:]
+        raise InstallerExit(returncode, f"installer exited {returncode}: {tail or 'no output'}")
+
+
+def _new_phase_record(spec: dict) -> dict:
+    """Initial breakdown entry for one phase of a chained job."""
+    runnable = spec.get("run") is not None
+    return {
+        "state": PHASE_PENDING if runnable else PHASE_SKIPPED,
+        "reason": None if runnable else spec.get("skip_reason"),
+        "progress": None,
+        "to_tag": None,
+        "reload_required": None,
+        "message": "",
+        "error": None,
+    }
+
+
+def run_chained_update(phases: list[dict], *, job: dict, job_lock: threading.Lock) -> None:
+    """Run update phases in order into one shared job dict (the worker of a
+    combined llama+whisper apply).
+
+    Each phase spec: ``name`` (breakdown key), ``weight`` (progress slice,
+    normalized over runnable phases), ``run`` (callable(set_progress) -> result
+    dict with to_tag/reload_required/message, raises on failure; None = skipped)
+    and ``skip_reason`` / ``failure_message``. A failing phase aborts the chain:
+    later phases are marked skipped (reason "aborted") and the job goes to error,
+    keeping the reload_required and messages of already-succeeded phases so a
+    partial success stays visible."""
+    runnable = [p for p in phases if p.get("run") is not None]
+    total_weight = sum(float(p.get("weight") or 1.0) for p in runnable) or 1.0
+    with job_lock:
+        job["phases"] = {p["name"]: _new_phase_record(p) for p in phases}
+
+    offset = 0.0
+    done_messages: list[str] = []
+    reload_required = False
+    primary_to_tag: Optional[str] = None
+    for index, phase in enumerate(phases):
+        if phase.get("run") is None:
+            continue
+        name = phase["name"]
+        weight = float(phase.get("weight") or 1.0) / total_weight
+        with job_lock:
+            job["phases"][name].update(state = PHASE_RUNNING, progress = 0.0)
+
+        def set_progress(
+            fraction: float,
+            *,
+            _name: str = name,
+            _base: float = offset,
+            _slice: float = weight,
+        ) -> None:
+            f = max(0.0, min(float(fraction), 1.0))
+            with job_lock:
+                record = job["phases"][_name]
+                record["progress"] = max(record.get("progress") or 0.0, f)
+                job["progress"] = max(job.get("progress") or 0.0, _base + f * _slice)
+
+        try:
+            result = phase["run"](set_progress) or {}
+        except Exception as exc:
+            failure = phase.get("failure_message") or f"{name} update failed."
+            with job_lock:
+                job["phases"][name].update(state = PHASE_ERROR, error = str(exc))
+                for later in phases[index + 1 :]:
+                    if later.get("run") is not None:
+                        job["phases"][later["name"]].update(state = PHASE_SKIPPED, reason = "aborted")
+                # A partial success keeps its messages and reload_required so the
+                # caller sees the earlier phase did land.
+                job.update(
+                    state = JOB_ERROR,
+                    message = " ".join(done_messages + [failure]),
+                    to_tag = primary_to_tag,
+                    error = str(exc),
+                    finished_at = utcnow(),
+                )
+                if done_messages:
+                    job["reload_required"] = reload_required
+            return
+        set_progress(1.0)
+        offset += weight
+        with job_lock:
+            job["phases"][name].update(
+                state = PHASE_SUCCESS,
+                to_tag = result.get("to_tag"),
+                reload_required = result.get("reload_required"),
+                message = result.get("message") or "",
+            )
+        if result.get("message"):
+            done_messages.append(result["message"])
+        # Only phases affecting the primary (llama) server may raise the job-level
+        # reload flag: the frontend resyncs chat model state off it, and a
+        # whisper-only sidecar reload must not clear the chat checkpoint. Per-phase
+        # reload_required stays visible under job["phases"].
+        if phase.get("affects_job_reload", True):
+            reload_required = reload_required or bool(result.get("reload_required"))
+            # The legacy job-level to_tag means "the llama build now installed";
+            # a whisper-only round must leave it unset or the UI reports a llama
+            # update that never ran (per-phase to_tag remains under phases).
+            if primary_to_tag is None:
+                primary_to_tag = result.get("to_tag")
+
+    with job_lock:
+        job.update(
+            state = JOB_SUCCESS,
+            message = " ".join(done_messages) or "Already up to date.",
+            to_tag = primary_to_tag,
+            reload_required = reload_required,
+            error = None,
+            progress = 1.0,
+            finished_at = utcnow(),
+        )
diff --git a/studio/backend/utils/prebuilt/whisper_layout.py b/studio/backend/utils/prebuilt/whisper_layout.py
new file mode 100644
index 0000000000..7444e4e707
--- /dev/null
+++ b/studio/backend/utils/prebuilt/whisper_layout.py
@@ -0,0 +1,74 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Canonical whisper.cpp install-root and marker lookup helpers."""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Optional
+
+MARKER_NAME = "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+
+
+@dataclass(frozen = True)
+class MarkerLookup:
+    marker: Optional[dict]
+    root: Optional[Path]
+    authoritative: bool
+    invalid: bool = False
+    slim_collision: bool = False
+
+
+def canonical_install_root(binary_path: Optional[str]) -> Optional[Path]:
+    """Return the managed root for the two supported CMake binary layouts."""
+    if not binary_path:
+        return None
+    parent = Path(binary_path).parent
+    if parent.name == "bin" and parent.parent.name == "build":
+        return parent.parent.parent
+    if (
+        parent.name == "Release"
+        and parent.parent.name == "bin"
+        and parent.parent.parent.name == "build"
+    ):
+        return parent.parent.parent.parent
+    return None
+
+
+def _parse_marker(path: Path) -> tuple[Optional[dict], bool]:
+    try:
+        payload = json.loads(path.read_text(encoding = "utf-8"))
+    except (OSError, json.JSONDecodeError):
+        return None, True
+    return (payload, False) if isinstance(payload, dict) else (None, True)
+
+
+def lookup_marker(binary_path: Optional[str]) -> MarkerLookup:
+    """Prefer the install-root marker over archive metadata beside the binary."""
+    if not binary_path:
+        return MarkerLookup(None, None, False)
+    binary = Path(binary_path)
+    root = canonical_install_root(binary_path)
+    inner_marker = binary.parent / MARKER_NAME
+    inner_payload, _ = _parse_marker(inner_marker) if inner_marker.is_file() else (None, False)
+    slim_collision = bool(
+        inner_payload
+        and (inner_payload.get("install_kind") == "slim" or inner_payload.get("backend") == "slim")
+    )
+    if root is not None:
+        root_marker = root / MARKER_NAME
+        if root_marker.is_file():
+            marker, invalid = _parse_marker(root_marker)
+            return MarkerLookup(marker, root, True, invalid, slim_collision)
+        if slim_collision:
+            return MarkerLookup(None, root, False, True, True)
+
+    for parent in binary.parents[:5]:
+        candidate = parent / MARKER_NAME
+        if candidate.is_file():
+            marker, invalid = _parse_marker(candidate)
+            return MarkerLookup(marker, parent, False, invalid, slim_collision)
+    return MarkerLookup(None, None, False)
diff --git a/studio/backend/utils/security/consent.py b/studio/backend/utils/security/consent.py
index b36131f809..fad52f21bb 100644
--- a/studio/backend/utils/security/consent.py
+++ b/studio/backend/utils/security/consent.py
@@ -147,11 +147,17 @@ def _load_remote_code_configs(model_name: str, hf_token: Optional[str] = None) -
 
         from huggingface_hub import hf_hub_download
         from huggingface_hub.utils import EntryNotFoundError
+        from utils.hf_cache_settings import active_hf_hub_cache
 
         configs = []
         for name in _REMOTE_CODE_CONFIG_FILES:
             try:
-                p = hf_hub_download(repo_id = model_name, filename = name, token = hf_token)
+                p = hf_hub_download(
+                    repo_id = model_name,
+                    filename = name,
+                    token = hf_token,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except EntryNotFoundError:
                 continue  # genuine 404 -> truly absent
             except Exception:
diff --git a/studio/backend/utils/security/file_security.py b/studio/backend/utils/security/file_security.py
index 466f326f18..91d7ad8f0e 100644
--- a/studio/backend/utils/security/file_security.py
+++ b/studio/backend/utils/security/file_security.py
@@ -29,13 +29,35 @@ Policy:
     scanned so a repo cannot dodge the gate by suffixing its name.
 """
 
+import re
 from dataclasses import dataclass, field
+from pathlib import Path
 from typing import Optional
 
 from loggers import get_logger
 
 logger = get_logger(__name__)
 
+# Pickle-format weight files (plain or sharded) that execute code on load; safetensors/gguf
+# are inert. Grouped by weight family so an inert safetensors only suppresses the pickle it
+# actually replaces: the loader won't use an adapter's safetensors for pytorch_model.bin.
+_PICKLE_WEIGHT_RE = re.compile(
+    r"^(model|pytorch_model|adapter_model|consolidated)(-\d+-of-\d+)?"
+    r"\.(bin|pt|pth|ckpt|pkl|pickle)$",
+    re.IGNORECASE,
+)
+# Base-model safetensors set: HF names the base pickle pytorch_model.bin but the safetensors
+# model.safetensors (stems differ), so a base pickle is replaced only by these, not an adapter's.
+_BASE_SAFETENSORS_RE = re.compile(
+    r"^(model(-\d+-of-\d+)?\.safetensors|model\.safetensors\.index\.json)$",
+    re.IGNORECASE,
+)
+# Adapter (PEFT) safetensors set: adapter_model.safetensors, its shards, or index.
+_ADAPTER_SAFETENSORS_RE = re.compile(
+    r"^(adapter_model(-\d+-of-\d+)?\.safetensors|adapter_model\.safetensors\.index\.json)$",
+    re.IGNORECASE,
+)
+
 # Non-blocking levels: clean or not-yet-finished. Anything else (unsafe/suspicious/
 # malicious or a future label) blocks, so Hub schema drift fails CLOSED.
 _NONBLOCKING_LEVELS = frozenset(
@@ -136,6 +158,7 @@ def _indexed_shard_paths(
     try:
         from huggingface_hub import hf_hub_download
         from huggingface_hub.utils import EntryNotFoundError
+        from utils.hf_cache_settings import active_hf_hub_cache
     except Exception:
         return None
 
@@ -144,7 +167,12 @@ def _indexed_shard_paths(
     for prefix in _index_prefixes(load_subdirs):
         for filename in _TRANSFORMERS_INDEX_FILES:
             try:
-                index_path = hf_hub_download(model_name, prefix + filename, token = hf_token or None)
+                index_path = hf_hub_download(
+                    model_name,
+                    prefix + filename,
+                    token = hf_token or None,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except EntryNotFoundError:
                 continue  # definitively absent, not an error
             except Exception:
@@ -265,11 +293,105 @@ def _fetch_security_status(model_name: str, hf_token: Optional[str]):
     return None
 
 
+def _st_load_roots(snapshot: Path) -> list:
+    """Directories a SentenceTransformer load deserializes weights from: the snapshot root plus
+    each module path in modules.json. Local, no network. Mirrors the online gate (which ignores
+    unreferenced nested pickles ST never loads) so the offline gate doesn't over-block."""
+    roots = [snapshot]
+    try:
+        import json
+        modules = json.loads((snapshot / "modules.json").read_text())
+    except (OSError, ValueError):
+        return roots  # no / invalid modules.json -> snapshot root is the only load root
+    for module in modules or ():
+        path = str((module or {}).get("path", "")).strip().strip("/")
+        # Relative module path only; ignore a crafted "../" escape.
+        if path and ".." not in path.split("/"):
+            candidate = snapshot / path
+            if candidate not in roots:
+                roots.append(candidate)
+    return roots
+
+
+def _cached_pickle_weight_files(snapshot: Path) -> list:
+    """Pickle weight files in snapshot's ST load roots, EXCLUDING those whose weight family also
+    ships an inert safetensors in the same dir (the loader prefers it): a base pickle is suppressed
+    only by a base model.safetensors, an adapter pickle only by adapter_model.safetensors -- an
+    unrelated safetensors is no substitute. Load roots only. Raises OSError if the snapshot root is
+    unreadable (caller blocks)."""
+    blocked = []
+    for root in _st_load_roots(snapshot):
+        try:
+            entries = [p for p in root.iterdir() if p.is_file()]
+        except OSError:
+            if root == snapshot:
+                raise  # top-level unreadable -> fail closed
+            continue  # unreadable module subdir: nothing loadable to attest here
+        has_base_safetensors = any(_BASE_SAFETENSORS_RE.match(p.name) for p in entries)
+        has_adapter_safetensors = any(_ADAPTER_SAFETENSORS_RE.match(p.name) for p in entries)
+        for path in entries:
+            if not _PICKLE_WEIGHT_RE.match(path.name):
+                continue
+            is_adapter = path.name.lower().startswith("adapter_model")
+            has_alternative = has_adapter_safetensors if is_adapter else has_base_safetensors
+            if not has_alternative:
+                blocked.append(path)
+    return blocked
+
+
+def _evaluate_local_only(model_name: str) -> FileSecurityDecision:
+    """Offline security gate. The Hub scan is unreachable, so inspect the local cache and fail
+    CLOSED on an unscanned pickle weight with no inert safetensors alternative, rather than
+    failing open or hanging. Safetensors/gguf-only cache loads; nothing cached -> allowed."""
+    from utils.utils import hf_cache_snapshot_dir
+
+    try:
+        snapshot = hf_cache_snapshot_dir(model_name)
+    except Exception:
+        logger.warning("Offline gate: could not resolve the cache for '%s'; blocking.", model_name)
+        return FileSecurityDecision(
+            model_name, True, reason = "offline; could not inspect the local cache"
+        )
+
+    if snapshot is None:
+        return FileSecurityDecision(model_name, False, reason = "offline; nothing cached to load")
+
+    try:
+        pickles = _cached_pickle_weight_files(snapshot)
+    except OSError:
+        logger.warning("Offline gate: could not read the cache for '%s'; blocking.", model_name)
+        return FileSecurityDecision(
+            model_name, True, reason = "offline; could not read the local cache"
+        )
+
+    if not pickles:
+        return FileSecurityDecision(
+            model_name, False, reason = "offline; cached weights are inert (safetensors/gguf)"
+        )
+
+    # Snapshot-relative posix paths (match the online gate; disambiguate same-named pickles).
+    rel_paths = sorted(p.relative_to(snapshot).as_posix() for p in pickles)
+    names = ", ".join(rel_paths)
+    logger.warning(
+        "Blocking offline load of '%s': cached pickle weight(s) cannot be malware-scanned "
+        "offline and have no safetensors alternative (%s).",
+        model_name,
+        names,
+    )
+    return FileSecurityDecision(
+        model_name,
+        True,
+        unsafe_files = [{"path": rel, "level": "unscanned"} for rel in rel_paths],
+        reason = f"offline; unscanned pickle weights with no safetensors alternative: {names}",
+    )
+
+
 def evaluate_file_security(
     model_name: str,
     hf_token: Optional[str] = None,
     *,
     load_subdirs = (),
+    local_only_load: bool = False,
 ) -> FileSecurityDecision:
     """Block a load when HF's security scan flags unsafe serialized files.
 
@@ -280,6 +402,9 @@ def evaluate_file_security(
     ``load_subdirs`` names subdirs the load calls ``from_pretrained`` on (e.g. ``("LLM",)``
     for Spark-TTS / BiCodec, loading ``<snapshot>/LLM``): a flagged file directly under one
     is root-level there and blocks, and an index inside it is honored when scoping shards.
+
+    ``local_only_load`` marks an offline load: with the Hub scan unreachable, inspect the local
+    cache and fail CLOSED on an unscanned pickle weight with no safetensors alternative.
     """
     # Scan the repo the load actually fetches, not the literal alias (which 404s and
     # fails open): the Spark-TTS "<parent>/LLM" alias is really unsloth/<parent> from LLM/.
@@ -295,6 +420,10 @@ def evaluate_file_security(
         # Cannot classify the path -> do not block on that account.
         return FileSecurityDecision(model_name, False, reason = "path check failed; not blocked")
 
+    # Offline: inspect the local cache and fail closed rather than hang on model_info or fail open.
+    if local_only_load:
+        return _evaluate_local_only(model_name)
+
     status = _fetch_security_status(model_name, hf_token)
     if not isinstance(status, dict):
         return FileSecurityDecision(
diff --git a/studio/backend/utils/security/remote_code_scan.py b/studio/backend/utils/security/remote_code_scan.py
index 797e1056f8..583dac94b6 100644
--- a/studio/backend/utils/security/remote_code_scan.py
+++ b/studio/backend/utils/security/remote_code_scan.py
@@ -29,6 +29,7 @@ from dataclasses import dataclass, field
 from typing import Optional
 
 from loggers import get_logger
+from utils.hf_cache_settings import active_hf_hub_cache
 
 logger = get_logger(__name__)
 
@@ -455,7 +456,12 @@ def repo_remote_code_files(model_name: str, hf_token: Optional[str] = None) -> d
         refs = set()
         for cfg_name in REMOTE_CODE_CONFIG_FILES:
             try:
-                cfg_path = hf_hub_download(model_name, cfg_name, token = hf_token)
+                cfg_path = hf_hub_download(
+                    model_name,
+                    cfg_name,
+                    token = hf_token,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except EntryNotFoundError:
                 continue
             except Exception as exc:
@@ -499,7 +505,12 @@ def repo_remote_code_files(model_name: str, hf_token: Optional[str] = None) -> d
         wanted = present_py | (own_refs & repo_file_set)
         for fn in sorted(wanted):
             try:
-                fp = hf_hub_download(model_name, fn, token = hf_token)
+                fp = hf_hub_download(
+                    model_name,
+                    fn,
+                    token = hf_token,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except Exception as exc:
                 # A .py CONFIRMED PRESENT could not be fetched. A partial set would
                 # fingerprint "clean" while transformers later runs this file, so fail
@@ -602,7 +613,12 @@ def external_auto_map_repos(model_name: str, hf_token: Optional[str] = None) ->
 
         for cfg_name in REMOTE_CODE_CONFIG_FILES:
             try:
-                cfg_path = hf_hub_download(model_name, cfg_name, token = hf_token)
+                cfg_path = hf_hub_download(
+                    model_name,
+                    cfg_name,
+                    token = hf_token,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except EntryNotFoundError:
                 continue
             except Exception:
@@ -670,7 +686,12 @@ def _add_external_refs(files: dict, refs, hf_token, model_name: str) -> bool:
             wanted = present_py | set(entry_files)
         for fn in sorted(wanted):
             try:
-                fp = hf_hub_download(repo, fn, token = hf_token)
+                fp = hf_hub_download(
+                    repo,
+                    fn,
+                    token = hf_token,
+                    cache_dir = active_hf_hub_cache(),
+                )
             except Exception as exc:
                 logger.warning(
                     "repo_remote_code_files(%s): external %s:%s unscannable (%s)",
diff --git a/studio/backend/utils/transformers_version.py b/studio/backend/utils/transformers_version.py
index 1fbcc9f46f..475a096248 100644
--- a/studio/backend/utils/transformers_version.py
+++ b/studio/backend/utils/transformers_version.py
@@ -44,6 +44,7 @@ import time
 from pathlib import Path
 
 from utils.native_path_leases import child_env_without_native_path_secret
+from utils.hf_cache_settings import get_hf_cache_paths
 from utils.subprocess_compat import (
     windows_hidden_subprocess_kwargs as _windows_hidden_subprocess_kwargs,
 )
@@ -516,13 +517,10 @@ def _adapter_base_from_hf_cache(model_name: str) -> str | None:
     """
     if not _is_canonical_repo_id(model_name):
         return None
-    hub = (
-        os.environ.get("HF_HUB_CACHE")
-        or os.environ.get("HUGGINGFACE_HUB_CACHE")
-        or os.path.join(
-            os.environ.get("HF_HOME") or os.path.expanduser("~/.cache/huggingface"), "hub"
-        )
-    )
+    # Route through the selected cache: after a no-restart /settings switch the
+    # process HF_HUB_CACHE env is stale, but the model loads from the selected
+    # cache, which get_hf_cache_paths() reflects (the DB switch).
+    hub = str(get_hf_cache_paths().hub_cache)
     repo_dir = Path(hub) / ("models--" + model_name.replace("/", "--"))
     candidates = []
     ref_main = repo_dir / "refs" / "main"
@@ -681,13 +679,10 @@ def _config_json_from_hf_cache(model_name: str) -> dict | None:
     # Only a canonical ``owner/repo`` Hub id maps to a cache dir; reject local paths.
     if not model_name or model_name.count("/") != 1 or model_name[0] in "/.~" or "\\" in model_name:
         return None
-    hub = (
-        os.environ.get("HF_HUB_CACHE")
-        or os.environ.get("HUGGINGFACE_HUB_CACHE")
-        or os.path.join(
-            os.environ.get("HF_HOME") or os.path.expanduser("~/.cache/huggingface"), "hub"
-        )
-    )
+    # Route through the selected cache: after a no-restart /settings switch the
+    # process HF_HUB_CACHE env is stale, but the model loads from the selected
+    # cache, which get_hf_cache_paths() reflects (the DB switch).
+    hub = str(get_hf_cache_paths().hub_cache)
     repo_dir = Path(hub) / ("models--" + model_name.replace("/", "--"))
     candidates = []
     ref_main = repo_dir / "refs" / "main"
@@ -1251,7 +1246,7 @@ def _probe_autoconfig(target_dir: str, model_name: str, hf_token: str | None) ->
     True = parses, False = parse/version failure (escalate), None = transient
     (auth/network/offline/spawn) so the caller fails safe and does not cache.
     """
-    env = child_env_without_native_path_secret()
+    env = get_hf_cache_paths().child_env(child_env_without_native_path_secret())
     if hf_token:
         env["HF_TOKEN"] = hf_token
         # The probe relies on the implicit HF_TOKEN env (no token= arg). Clear any inherited
@@ -1806,7 +1801,7 @@ def _install_to_dir(pkg: str, target_dir: str) -> bool:
             stdout = subprocess.PIPE,
             stderr = subprocess.STDOUT,
             text = True,
-            env = child_env_without_native_path_secret(),
+            env = get_hf_cache_paths().child_env(child_env_without_native_path_secret()),
             **_windows_hidden_subprocess_kwargs(),
         )
         if result.returncode == 0:
@@ -1829,7 +1824,7 @@ def _install_to_dir(pkg: str, target_dir: str) -> bool:
         stdout = subprocess.PIPE,
         stderr = subprocess.STDOUT,
         text = True,
-        env = child_env_without_native_path_secret(),
+        env = get_hf_cache_paths().child_env(child_env_without_native_path_secret()),
         **_windows_hidden_subprocess_kwargs(),
     )
     if result.returncode != 0:
@@ -2458,7 +2453,7 @@ def _ensure_venv_llmcompressor_exists() -> bool:
             stdout = subprocess.PIPE,
             stderr = subprocess.STDOUT,
             text = True,
-            env = child_env_without_native_path_secret(),
+            env = get_hf_cache_paths().child_env(child_env_without_native_path_secret()),
             **_windows_hidden_subprocess_kwargs(),
         )
         last_out = result.stdout or ""
diff --git a/studio/backend/utils/upload_limits.py b/studio/backend/utils/upload_limits.py
index fff0ac423f..662af0f1dd 100644
--- a/studio/backend/utils/upload_limits.py
+++ b/studio/backend/utils/upload_limits.py
@@ -14,6 +14,9 @@ MIN_UPLOAD_LIMIT_MB = 1
 MAX_UPLOAD_LIMIT_MB = 8192
 _BYTES_PER_MB = 1024 * 1024
 MULTIPART_OVERHEAD_BYTES = 10 * _BYTES_PER_MB
+STT_AUDIO_RAW_MAX_BYTES = 25 * _BYTES_PER_MB
+STT_AUDIO_B64_MAX_CHARS = ((STT_AUDIO_RAW_MAX_BYTES + 2) // 3) * 4
+STT_AUDIO_JSON_MAX_BYTES = STT_AUDIO_B64_MAX_CHARS + 64 * 1024
 
 LOCAL_SEED_UPLOAD_MAX_BYTES = 100 * _BYTES_PER_MB
 LOCAL_SEED_UPLOAD_MAX_LABEL = "100MB"
diff --git a/studio/backend/utils/utils.py b/studio/backend/utils/utils.py
index 31f5f31bee..bf8348dd82 100644
--- a/studio/backend/utils/utils.py
+++ b/studio/backend/utils/utils.py
@@ -8,6 +8,7 @@ import structlog
 from loggers import get_logger
 from contextlib import contextmanager
 from pathlib import Path
+from typing import Optional
 import shutil
 import tempfile
 
@@ -15,6 +16,132 @@ import tempfile
 logger = get_logger(__name__)
 
 
+# ── Offline / HF-cache helpers ──────────────────────────────────
+# An offline load must never touch the network (a DNS-dead session hangs on hub retries);
+# these read the local HF cache the load itself uses.
+
+_HF_OFFLINE_TRUE_VALUES = frozenset({"1", "true", "yes", "on"})
+
+
+def hf_env_offline() -> bool:
+    """True when HF_HUB_OFFLINE or TRANSFORMERS_OFFLINE requests offline mode.
+
+    Also honors TRANSFORMERS_OFFLINE (hub honors only HF_HUB_OFFLINE) since users set it
+    to keep transformers loads local.
+    """
+    for var in ("HF_HUB_OFFLINE", "TRANSFORMERS_OFFLINE"):
+        if os.environ.get(var, "").strip().lower() in _HF_OFFLINE_TRUE_VALUES:
+            return True
+    return False
+
+
+def st_repo_id_candidates(model_name: str) -> list:
+    """Repo ids a Sentence-Transformers load may resolve model_name to; a slashless name
+    also resolves under the sentence-transformers/ namespace, so both are candidates."""
+    name = (model_name or "").strip().strip("/")
+    if not name:
+        return []
+    candidates = [name]
+    if "/" not in name:
+        candidates.append(f"sentence-transformers/{name}")
+    return candidates
+
+
+def _expand_path(raw: str) -> Path:
+    """Expand ~ and $VARS as huggingface_hub does, so the gate resolves the loader's dir."""
+    return Path(os.path.expandvars(os.path.expanduser(raw)))
+
+
+def _hf_cache_roots() -> list:
+    """Cache roots to search for a model's local snapshot, most-authoritative first.
+
+    The app's selected hub cache (set via /settings) is searched first: after a
+    no-restart cache switch the process env is stale, yet the loader reads the
+    selected cache via ``cache_folder=active_hf_hub_cache()``, so the snapshot
+    and offline security lookups must match where it actually loads. The env
+    precedence (SENTENCE_TRANSFORMERS_HOME, HF_HUB_CACHE, HF_HOME/hub,
+    ~/.cache/huggingface/hub) follows so a copy still in a previous cache resolves."""
+    roots: list = []
+    seen: set = set()
+
+    def _add(path) -> None:
+        if path is None:
+            return
+        expanded = _expand_path(str(path))
+        key = str(expanded)
+        if key not in seen:
+            seen.add(key)
+            roots.append(expanded)
+
+    try:
+        from utils.hf_cache_settings import get_hf_cache_paths
+        _add(get_hf_cache_paths().hub_cache)
+    except Exception:
+        pass
+
+    if st_home := os.environ.get("SENTENCE_TRANSFORMERS_HOME"):
+        _add(st_home)
+    if hub := (os.environ.get("HF_HUB_CACHE") or os.environ.get("HUGGINGFACE_HUB_CACHE")):
+        _add(hub)
+    if hf_home := os.environ.get("HF_HOME"):
+        _add(_expand_path(hf_home) / "hub")
+    if not roots:
+        _add(Path.home() / ".cache" / "huggingface" / "hub")
+    return roots
+
+
+def hf_cache_snapshot_dir(model_name: str) -> Optional[Path]:
+    """Active local snapshot dir for model_name's main revision, or None if not cached.
+    Reads refs/main then snapshots/<commit>; no network. Tries the ST alias for slashless names."""
+    try:
+        from huggingface_hub.file_download import repo_folder_name
+    except Exception:
+        repo_folder_name = None
+    for cache_root in _hf_cache_roots():
+        for repo_id in st_repo_id_candidates(model_name):
+            try:
+                if repo_folder_name is not None:
+                    folder = repo_folder_name(repo_id = repo_id, repo_type = "model")
+                else:
+                    folder = "models--" + repo_id.replace("/", "--")
+                repo_dir = cache_root / folder
+                ref = repo_dir / "refs" / "main"
+                if not ref.is_file():
+                    continue
+                commit = ref.read_text().strip()
+                if not commit:
+                    continue
+                snapshot = repo_dir / "snapshots" / commit
+                if snapshot.is_dir():
+                    return snapshot
+            except OSError:
+                continue
+    return None
+
+
+# A weight file plus a config distinguishes a real cached model from a metadata-only
+# partial cache that resolves refs/main but would fail at load time.
+_LOADABLE_WEIGHT_SUFFIXES = frozenset({".safetensors", ".bin", ".gguf", ".pt", ".pth", ".ckpt"})
+
+
+def hf_cache_snapshot_is_loadable(model_name: str) -> bool:
+    """True when model_name's snapshot is cached and loadable: a config (config.json or
+    modules.json) plus at least one weight file, not a metadata-only partial cache. No network."""
+    snapshot = hf_cache_snapshot_dir(model_name)
+    if snapshot is None:
+        return False
+    try:
+        has_config = (snapshot / "config.json").is_file() or (snapshot / "modules.json").is_file()
+        if not has_config:
+            return False
+        for path in snapshot.rglob("*"):
+            if path.suffix.lower() in _LOADABLE_WEIGHT_SUFFIXES and path.is_file():
+                return True
+    except OSError:
+        return False
+    return False
+
+
 # ── Client-safe error helpers ───────────────────────────────────
 # Never return raw exception text to clients; log server-side, return generic.
 
diff --git a/studio/backend/utils/whisper_cpp_freshness.py b/studio/backend/utils/whisper_cpp_freshness.py
new file mode 100644
index 0000000000..59749455b1
--- /dev/null
+++ b/studio/backend/utils/whisper_cpp_freshness.py
@@ -0,0 +1,254 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""whisper.cpp prebuilt freshness check.
+
+Reads UNSLOTH_WHISPER_PREBUILT_INFO.json (written by install_whisper_prebuilt.py)
+and compares the installed release tag against the latest on GitHub. Surfaced via
+utils.whisper_cpp_update (GET /api/whisper/update-status and the combined
+llama+whisper update status). Fails open on any missing data so we never show a
+misleading banner.
+
+The mechanics (marker walk-up, GitHub fetch, memo + disk cache, report skeleton)
+live in utils.prebuilt.freshness_flow; this module keeps the whisper version
+policy and the per-module caches its tests patch.
+"""
+
+from __future__ import annotations
+
+import re
+from datetime import datetime
+from pathlib import Path
+from typing import Optional
+
+import structlog
+
+from utils.prebuilt import freshness_flow as _flow
+from utils.prebuilt.whisper_layout import lookup_marker
+
+logger = structlog.get_logger(__name__)
+
+# 3 days matches Unsloth's typical whisper.cpp release cadence.
+STALENESS_THRESHOLD_DAYS = 3
+
+_INSTALL_MARKER_NAME = "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+
+_marker_cache: dict[str, Optional[dict]] = {}
+_release_memo: dict[str, tuple[float, Optional[str]]] = {}
+# Newest-release asset sizes (name -> bytes), memoized like the tag (24h TTL).
+_assets_memo: dict[str, tuple[float, dict[str, int]]] = {}
+
+
+def _cache_dir() -> Path:
+    """Lazy import so tests can stub storage_roots."""
+    try:
+        from utils.paths.storage_roots import cache_root
+        return cache_root() / "whisper_cpp_freshness"
+    except Exception:
+        return Path.home() / ".unsloth" / "studio" / "cache" / "whisper_cpp_freshness"
+
+
+def read_install_marker(binary_path: Optional[str]) -> Optional[dict]:
+    """Walk up from binary_path to find UNSLOTH_WHISPER_PREBUILT_INFO.json.
+    None = no marker (source build / custom path) or invalid JSON."""
+    if not binary_path:
+        return None
+    cached = _marker_cache.get(binary_path)
+    if cached is not None or binary_path in _marker_cache:
+        return cached
+    marker = lookup_marker(binary_path).marker
+    _marker_cache[binary_path] = marker
+    return marker
+
+
+def _load_disk_cache(repo: str) -> Optional[tuple[float, Optional[str]]]:
+    return _flow.load_disk_cache(repo, _cache_dir())
+
+
+def _save_disk_cache(repo: str, latest_tag: Optional[str]) -> None:
+    _flow.save_disk_cache(
+        repo, latest_tag, _cache_dir(), log_message = "whisper freshness cache write failed"
+    )
+
+
+def _fetch_latest_release_tag(repo: str, timeout: float = 5.0) -> Optional[str]:
+    """Newest published release tag for `repo`, by publish time (see
+    freshness_flow for why this is not GitHub's /releases/latest pointer)."""
+    return _flow.fetch_latest_release_tag(
+        repo, timeout, log_message = "whisper freshness fetch failed"
+    )
+
+
+def latest_published_release(repo: str, *, force_refresh: bool = False) -> Optional[str]:
+    """Latest release tag for `repo`. Memo + disk-cached (24h TTL).
+    None when offline and never previously cached."""
+    return _flow.latest_published_release(
+        repo,
+        force_refresh = force_refresh,
+        memo = _release_memo,
+        cache_dir = lambda: _cache_dir(),
+        fetch = lambda r: _fetch_latest_release_tag(r),
+        save = lambda r, tag: _save_disk_cache(r, tag),
+    )
+
+
+def _fetch_latest_release_assets(repo: str, timeout: float = 5.0) -> Optional[dict[str, int]]:
+    """Asset name -> size (bytes) for the newest published release of `repo`,
+    selected exactly like _fetch_latest_release_tag. None on any failure."""
+    return _flow.fetch_latest_release_assets(
+        repo, timeout, log_message = "whisper freshness asset fetch failed"
+    )
+
+
+def latest_release_assets(repo: str, *, force_refresh: bool = False) -> Optional[dict[str, int]]:
+    """Newest-release asset sizes for `repo`, memoized (24h TTL). None when
+    offline and never fetched. In-memory only -- a restart simply re-fetches."""
+    return _flow.latest_release_assets(
+        repo,
+        force_refresh = force_refresh,
+        memo = _assets_memo,
+        fetch = lambda r: _fetch_latest_release_assets(r),
+    )
+
+
+def _asset_platform_suffix(asset: str, installed_tag: Optional[str]) -> Optional[str]:
+    """The tag-independent ``<os>-<arch>-<accel>.<ext>`` suffix identifying this
+    host's bundle, from stripping the ``whisper-<tag>-`` prefix off the installed
+    asset name. Falls back to anchoring on the platform token when the marker tag
+    does not line up with the asset's embedded tag."""
+    if isinstance(installed_tag, str) and installed_tag:
+        tag = installed_tag if installed_tag.startswith("v") else f"v{installed_tag}"
+        prefix = f"whisper-{tag}-"
+        if asset.startswith(prefix):
+            return asset[len(prefix) :]
+    m = re.search(r"-((?:linux|macos|windows)-.*)$", asset)
+    return m.group(1) if m else None
+
+
+def update_download_size_bytes(
+    marker: Optional[dict],
+    latest_tag: Optional[str],
+    repo: Optional[str],
+    *,
+    force_refresh: bool = False,
+) -> Optional[int]:
+    """Download size of the latest-release asset matching this host's installed
+    bundle (same platform/arch/accel suffix). None when there is no marker asset,
+    the latest assets can't be read, or no match.
+
+    Assets are named ``whisper-<tag>-<os>-<arch>-<accel>.<ext>`` and the fork
+    builds every slice itself, so only the publish repo is consulted (no
+    upstream/binary_repo passthrough)."""
+    if not marker or not latest_tag or not repo:
+        return None
+    installed_asset = marker.get("asset")
+    if not isinstance(installed_asset, str) or not installed_asset:
+        return None
+    suffix = _asset_platform_suffix(installed_asset, marker.get("release_tag"))
+    if not suffix:
+        return None
+    assets = latest_release_assets(repo, force_refresh = force_refresh)
+    if not assets:
+        return None
+    latest_v = latest_tag if latest_tag.startswith("v") else f"v{latest_tag}"
+    want = f"whisper-{latest_v}-{suffix}"
+    if want in assets:
+        return assets[want]
+    # Tag formatting can vary; fall back to the platform+accel suffix.
+    for name, size in assets.items():
+        if name.endswith(suffix):
+            return size
+    return None
+
+
+def parse_release_version(tag: object) -> Optional[tuple]:
+    """Comparable key ``(upstream_major, upstream_minor, upstream_patch,
+    unsloth_serial)`` for a tag like ``v1.9.1-unsloth.2``.
+
+    Tolerant of a leading ``v`` and a missing ``-unsloth.N`` suffix (serial then
+    0); the upstream version is padded to major/minor/patch. None when the version
+    component is not purely numeric."""
+    if not isinstance(tag, str):
+        return None
+    s = tag.strip()
+    if not s:
+        return None
+    if s[0] in ("v", "V"):
+        s = s[1:]
+    serial = 0
+    m = re.search(r"-unsloth\.(\d+)$", s)
+    if m:
+        serial = int(m.group(1))
+        s = s[: m.start()]
+    parts = s.split(".")
+    nums: list[int] = []
+    for part in parts:
+        if not part.isdigit():
+            return None
+        nums.append(int(part))
+    if not nums:
+        return None
+    while len(nums) < 3:
+        nums.append(0)
+    return (nums[0], nums[1], nums[2], serial)
+
+
+def is_behind(installed: Optional[str], latest: Optional[str]) -> bool:
+    """Whether `installed` is genuinely behind `latest`.
+
+    - identical tags -> not behind (clears the sticky banner post-update)
+    - both parse -> behind only when the latest version key is strictly greater
+      (a lower/equal version is never "behind" -> downgrade guard)
+    - either fails to parse and they differ -> behind (plain inequality)
+    """
+    if not installed or not latest:
+        return False
+    installed, latest = installed.strip(), latest.strip()
+    if installed == latest:
+        return False
+    installed_key, latest_key = parse_release_version(installed), parse_release_version(latest)
+    if installed_key is not None and latest_key is not None:
+        return latest_key > installed_key
+    # One side is unparseable and the tags already differ: treat as behind.
+    return True
+
+
+def check_prebuilt_freshness(
+    binary_path: Optional[str],
+    *,
+    threshold_days: int = STALENESS_THRESHOLD_DAYS,
+    now: Optional[datetime] = None,
+) -> dict:
+    """Returns {has_marker, stale, behind, installed_tag, latest_tag,
+    installed_at_utc, age_days, published_repo, threshold_days}.
+    behind = installed genuinely older than latest (see is_behind).
+    stale = behind AND age >= threshold.
+    Fails open on missing data (behind/stale stay False)."""
+    # The whisper marker records a single ``release_tag`` (e.g. v1.9.1-unsloth.2);
+    # both display and comparison use it directly.
+    return _flow.check_freshness(
+        binary_path,
+        threshold_days = threshold_days,
+        now = now,
+        read_marker = lambda p: read_install_marker(p),
+        latest_release = lambda repo: latest_published_release(repo),
+        behind = lambda installed, latest: is_behind(installed, latest),
+        display_tag = lambda marker: marker.get("release_tag"),
+        compare_tag = lambda marker: marker.get("release_tag"),
+    )
+
+
+def reset_caches(*, drop_disk: bool = False) -> None:
+    """Drop the in-memory freshness caches. The no-arg form is test-only.
+
+    With ``drop_disk = True`` also delete the on-disk 24h release cache. Used by
+    the post-install/update path: clearing memory alone leaves the stale
+    same-version value on disk, so an offline post-install GitHub refresh would
+    replay it (latest_published_release's last-good fallback) and the banner could
+    linger. Dropping the disk cache makes latest read None in that offline case,
+    so the banner fails open (off) rather than point at the just-replaced build."""
+    _flow.reset_caches(
+        (_marker_cache, _release_memo, _assets_memo),
+        drop_disk = drop_disk,
+        cache_dir = lambda: _cache_dir(),
+    )
diff --git a/studio/backend/utils/whisper_cpp_update.py b/studio/backend/utils/whisper_cpp_update.py
new file mode 100644
index 0000000000..cac37c25fc
--- /dev/null
+++ b/studio/backend/utils/whisper_cpp_update.py
@@ -0,0 +1,490 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""In-app whisper.cpp prebuilt update.
+
+Builds on utils.whisper_cpp_freshness (which detects whether a newer prebuilt
+release exists) and adds the *apply* half: run install_whisper_prebuilt.py to
+download the newest bundle for this host and atomically swap it in, so the next
+model load uses it. Applies only run as the whisper phase of the combined
+llama+whisper update (utils.llama_cpp_update.start_update chains
+run_chained_phase); there is no standalone whisper update trigger.
+
+Design notes:
+- Detection is delegated to check_prebuilt_freshness(). We surface an
+  ``update_available`` flag (installed_tag != latest_tag), laxer than freshness'
+  ``stale`` (which also requires the install to be >= 3 days old). The UI shows
+  the single main update item on update_available.
+- Everything fails open: a missing marker / offline GitHub / source build just
+  reports update_available=False and never blocks the app.
+- The mechanics (managed-root resolution, local-link detection, the resolve
+  probe, the streamed installer run) live in utils.prebuilt.update_flow; this
+  module keeps the whisper policy. The ``job`` dict in the status payload stays
+  idle (kept for response-shape stability): chained applies report progress
+  through the llama job.
+"""
+
+from __future__ import annotations
+
+import os
+import re
+import subprocess
+import sys
+import threading
+from pathlib import Path
+from typing import Optional
+
+import structlog
+
+from utils.prebuilt import update_flow as _flow
+from utils.prebuilt.whisper_layout import canonical_install_root
+from utils.whisper_cpp_freshness import (
+    _INSTALL_MARKER_NAME,
+    check_prebuilt_freshness,
+    is_behind,
+    latest_published_release,
+    latest_release_assets,
+    parse_release_version,
+    read_install_marker,
+    reset_caches,
+    update_download_size_bytes,
+)
+
+logger = structlog.get_logger(__name__)
+
+DEFAULT_PUBLISHED_REPO = "unslothai/whisper.cpp"
+_INSTALL_TIMEOUT_SECONDS = 1800  # 30 min ceiling for download + extract/validate
+
+# Always-idle job payload: whisper applies run inside the chained llama job, so
+# nothing flips this to running. Kept so status payload shapes stay stable.
+_job_lock = threading.Lock()
+_job: dict = _flow.new_job()
+
+_rocm_install_args = _flow.rocm_install_args
+
+
+def _find_binary() -> Optional[str]:
+    """Locate the active whisper-server binary via the STT sidecar's own resolver
+    so update targets exactly what Unsloth runs. Lazy import keeps the heavy
+    inference module off this module's import path."""
+    try:
+        from core.inference.stt_ggml_sidecar import find_whisper_server_binary
+        return find_whisper_server_binary()
+    except Exception as exc:  # pragma: no cover - defensive
+        logger.debug("whisper update: binary discovery failed", error = str(exc))
+        return None
+
+
+def _install_dir_for(binary_path: Optional[str]) -> Optional[Path]:
+    """The directory holding UNSLOTH_WHISPER_PREBUILT_INFO.json: the install root
+    install_whisper_prebuilt.py wrote (``<install-dir>`` whose canonical server is
+    ``build/bin/whisper-server``) and the one we re-install into."""
+    root = canonical_install_root(binary_path)
+    if root is not None and (root / _INSTALL_MARKER_NAME).is_file():
+        return root
+    return _flow.install_dir_for(binary_path, marker_name = _INSTALL_MARKER_NAME)
+
+
+def _installer_script() -> Optional[Path]:
+    """Locate install_whisper_prebuilt.py (UNSLOTH_WHISPER_INSTALLER wins)."""
+    return _flow.find_installer_script(
+        env_var = "UNSLOTH_WHISPER_INSTALLER", script_name = "install_whisper_prebuilt.py"
+    )
+
+
+# Markerless (source-build) installs have no UNSLOTH_WHISPER_PREBUILT_INFO.json,
+# so we ask the installer whether an official prebuilt now exists for this host.
+_resolve_memo: dict = {}
+
+
+def _resolve_prebuilt_for_host(
+    *, force_refresh: bool = False, backend: Optional[str] = None
+) -> Optional[dict]:
+    """Run install_whisper_prebuilt.py --resolve-prebuilt (no download); return
+    {prebuilt_available, repo, release_tag, upstream_tag, backend, asset, os,
+    arch, ...} or None. Fail-open: any error -> None so a source build never
+    blocks the app."""
+    extra_args = ("--backend", backend) if backend else ()
+    return _flow.resolve_prebuilt_for_host(
+        force_refresh = force_refresh,
+        memo = _resolve_memo,
+        installer_script = lambda: _installer_script(),
+        log_message = "whisper update: resolve-prebuilt failed",
+        extra_args = extra_args,
+    )
+
+
+def _installed_whisper_version(binary: Optional[str]) -> Optional[str]:
+    """Best-effort ``v<A.B.C>`` from ``whisper-server --version``. None when the
+    binary is missing, reports no version, or cannot run. Used only for the
+    markerless source-build downgrade guard, so it fails open to None."""
+    if not binary:
+        return None
+    try:
+        proc = subprocess.run([binary, "--version"], capture_output = True, text = True, timeout = 20)
+    except Exception:  # pragma: no cover - defensive
+        return None
+    m = re.search(r"v?(\d+\.\d+\.\d+)", (proc.stderr or "") + (proc.stdout or ""))
+    if not m:
+        return None
+    return f"v{m.group(1)}"
+
+
+def _whisper_install_root(binary: Optional[str]) -> Optional[Path]:
+    """The Unsloth-managed whisper.cpp root the active binary lives under, or None
+    when the binary is unmanaged (see update_flow.managed_install_root)."""
+    return _flow.managed_install_root(
+        binary,
+        marker_root = _install_dir_for(binary),
+        server_path_var = "WHISPER_SERVER_PATH",
+        cpp_path_var = "UNSLOTH_WHISPER_CPP_PATH",
+        dir_name = "whisper.cpp",
+    )
+
+
+def _source_build_status(binary: str, *, force_refresh: bool) -> Optional[dict]:
+    """Update status for a markerless (source-build) install: offer the official
+    prebuilt when one exists for this host and is newer than the installed binary.
+    None -> caller falls through to the no-marker default (unsupported)."""
+    res = _resolve_prebuilt_for_host(force_refresh = force_refresh)
+    if not res or not res.get("prebuilt_available"):
+        return None
+    release_tag = res.get("release_tag")
+    if not release_tag:
+        return None
+    # No resolvable install root (e.g. a pinned WHISPER_SERVER_PATH we cannot
+    # manage) means an apply would not take effect, so do not offer it.
+    if _whisper_install_root(binary) is None:
+        return None
+    installed_tag = _installed_whisper_version(binary)
+    installed_key = parse_release_version(installed_tag) if installed_tag else None
+    latest_key = parse_release_version(release_tag)
+    if installed_key is None or latest_key is None:
+        # Unknown installed/latest version (involuntary source-build case): treat
+        # as behind so we still offer the prebuilt.
+        update_available = True
+    else:
+        # Same downgrade guard as is_behind: only a strictly newer key is behind.
+        update_available = latest_key > installed_key
+    latest = release_tag
+    # Size of the resolved prebuilt, so source builds show it like the marker
+    # path. Fails open to None (offline / asset absent from release).
+    update_size_bytes = None
+    if update_available:
+        asset_name = res.get("asset")
+        if isinstance(asset_name, str) and asset_name:
+            try:
+                assets = latest_release_assets(res.get("repo"), force_refresh = force_refresh)
+                if assets:
+                    update_size_bytes = assets.get(asset_name)
+            except Exception as exc:  # pragma: no cover - network defensive
+                logger.debug("whisper update: source-build size lookup failed", error = str(exc))
+    with _job_lock:
+        job = dict(_job)
+    return {
+        "supported": True,
+        "update_available": update_available,
+        "stale": False,
+        "installed_tag": installed_tag,
+        "latest_tag": latest,
+        "published_repo": res.get("repo"),
+        "installed_at_utc": None,
+        "age_days": None,
+        "source_build": True,
+        "update_size_bytes": update_size_bytes,
+        "job": job,
+    }
+
+
+def _active_install_is_local_link(binary: Optional[str]) -> bool:
+    """True when the active whisper-server resolves through a locally-linked
+    whisper.cpp directory (see update_flow.active_install_is_local_link)."""
+    return _flow.active_install_is_local_link(binary, dir_name = "whisper.cpp")
+
+
+def _local_link_status() -> dict:
+    """Status payload for a local-link install: unmanaged, no update offered."""
+    return _flow.local_link_status(_job, _job_lock)
+
+
+def get_update_status(*, force_refresh: bool = False) -> dict:
+    """Report whether a newer prebuilt exists plus the current job state.
+
+    force_refresh bypasses the 24h release cache for an explicit "check now".
+    """
+    binary = _find_binary()
+    # A locally-linked whisper.cpp dir is the user's own tree; never offer to
+    # replace it. Bail before any network/freshness work.
+    if _active_install_is_local_link(binary):
+        return _local_link_status()
+    marker = read_install_marker(binary)
+
+    # No marker = source build / custom path. Offer the official prebuilt if one
+    # exists for this host.
+    if marker is None and binary is not None:
+        src = _source_build_status(binary, force_refresh = force_refresh)
+        if src is not None:
+            return src
+
+    repo = (marker or {}).get("published_repo") or DEFAULT_PUBLISHED_REPO
+
+    if force_refresh and repo:
+        # Prime the cache so the freshness read below sees the newest tag.
+        try:
+            latest_published_release(repo, force_refresh = True)
+        except Exception as exc:  # pragma: no cover - network defensive
+            logger.debug("whisper update: force refresh failed", error = str(exc))
+
+    freshness = check_prebuilt_freshness(binary)
+    installed = freshness.get("installed_tag")
+    latest = freshness.get("latest_tag")
+    compatible_override = False
+    if sys.platform == "darwin" and marker is not None:
+        # The newest published release may require a newer macOS. Ask the same
+        # host-aware resolver the installer uses so the banner compares against
+        # the newest release this host can actually install, avoiding a repeated
+        # offer of an incompatible release after walkback.
+        resolved = _resolve_prebuilt_for_host(
+            force_refresh = force_refresh,
+            backend = marker.get("backend") if isinstance(marker.get("backend"), str) else None,
+        )
+        compatible_latest = (resolved or {}).get("release_tag")
+        if (resolved or {}).get("prebuilt_available") and isinstance(compatible_latest, str):
+            compatible_override = compatible_latest != latest
+            latest = compatible_latest
+    # `behind` compares the release version with a downgrade guard, so a lagging
+    # /releases/latest or lower published tag can't show a false update
+    # (whisper_cpp_freshness.is_behind).
+    update_available = bool(
+        freshness.get("has_marker")
+        and (
+            is_behind(installed, latest)
+            if sys.platform == "darwin" and marker is not None
+            else freshness.get("behind")
+        )
+    )
+
+    # Size of the prebuilt Update would download, for the banner. Only when an
+    # update is offered; fails open to None (offline / no matching asset).
+    update_size_bytes = None
+    if update_available and not compatible_override:
+        try:
+            update_size_bytes = update_download_size_bytes(
+                marker,
+                latest,
+                freshness.get("published_repo") or repo,
+                force_refresh = force_refresh,
+            )
+        except Exception as exc:  # pragma: no cover - network defensive
+            logger.debug("whisper update: size lookup failed", error = str(exc))
+
+    with _job_lock:
+        job = dict(_job)
+
+    return {
+        "supported": bool(freshness.get("has_marker")),
+        "update_available": update_available,
+        "stale": bool(update_available and freshness.get("stale")),
+        "installed_tag": installed,
+        "latest_tag": latest,
+        "published_repo": freshness.get("published_repo") or repo,
+        "installed_at_utc": freshness.get("installed_at_utc"),
+        "age_days": freshness.get("age_days"),
+        "source_build": False,
+        "update_size_bytes": update_size_bytes,
+        "job": job,
+    }
+
+
+def _install_latest(
+    install_dir: Path,
+    repo: str,
+    asset: Optional[str],
+    backend: Optional[str],
+    script: Path,
+    set_progress,
+    pin_release_tag: Optional[str] = None,
+) -> dict:
+    """Replace whisper.cpp while the sidecar blocks every new load."""
+    try:
+        from core.inference.stt_ggml_sidecar import get_ggml_stt_sidecar
+        sidecar = get_ggml_stt_sidecar()
+    except Exception as exc:
+        # Replacing the tree without the singleton's maintenance barrier would
+        # reopen the Windows executable-lock and stale-process races. Fail closed.
+        raise RuntimeError("could not coordinate the whisper.cpp sidecar update") from exc
+
+    # update_maintenance publishes its guard before waiting for an existing
+    # transcription, unloads the warm server, and holds the sidecar lock across
+    # the complete atomic install. No new process can relock or outlive the tree.
+    with sidecar.update_maintenance() as model_was_active:
+        return _install_latest_while_blocked(
+            install_dir,
+            repo,
+            asset,
+            backend,
+            script,
+            set_progress,
+            pin_release_tag = pin_release_tag,
+            model_was_active = model_was_active,
+        )
+
+
+def _install_latest_while_blocked(
+    install_dir: Path,
+    repo: str,
+    asset: Optional[str],
+    backend: Optional[str],
+    script: Path,
+    set_progress,
+    *,
+    pin_release_tag: Optional[str],
+    model_was_active: bool,
+) -> dict:
+    """Run the installer with the sidecar already in update maintenance."""
+
+    cmd = [
+        sys.executable,
+        str(script),
+        "--install-dir",
+        str(install_dir),
+        "--whisper-tag",
+        "latest",
+        "--published-repo",
+        repo,
+    ]
+    # Preserve the installed accelerator across updates. Left unpinned the
+    # installer re-detects the host, fine on unchanged hardware but able to
+    # reroute a deliberate choice (e.g. cpu on a GPU box); forwarding the marker's
+    # backend keeps the same slice.
+    if isinstance(backend, str) and backend:
+        cmd.extend(["--backend", backend])
+    if pin_release_tag:
+        cmd.extend(["--published-release-tag", pin_release_tag])
+    cmd.extend(_rocm_install_args(asset))
+    logger.info("whisper update: installing", cmd = " ".join(cmd))
+    env = dict(os.environ, UNSLOTH_PROGRESS_PERCENT_STEP = "5")
+    # Every nonzero exit is a failed phase. In particular, exit 2 means the
+    # requested release was incompatible and no install happened, so reporting
+    # success would hide the banner and toast an update that never landed.
+    _flow.stream_installer(
+        cmd,
+        env,
+        set_progress = set_progress,
+        timeout_seconds = _INSTALL_TIMEOUT_SECONDS,
+    )
+
+    # Drop stale caches so the banner re-checks the swapped marker. If GitHub is
+    # offline, latest stays unknown and the banner fails open.
+    reset_caches(drop_disk = True)
+    try:
+        latest_published_release(repo, force_refresh = True)
+    except Exception as exc:  # pragma: no cover - network defensive
+        logger.debug("whisper update: post-install freshness refresh failed", error = str(exc))
+    new_marker = read_install_marker(_find_binary())
+    new_tag = (new_marker or {}).get("release_tag")
+    logger.info("whisper update: success", to_tag = new_tag)
+    return {
+        "to_tag": new_tag,
+        "reload_required": model_was_active,
+        "message": (
+            f"Updated whisper.cpp to {new_tag}."
+            + (" Reload your model to use it." if model_was_active else "")
+        ),
+    }
+
+
+def chained_phase_plan(
+    *, force_refresh: bool = False, paired_llama_will_update: bool = False
+) -> dict:
+    """Whisper's side of the combined llama+whisper update item.
+
+    Returns {status, update_available, skip_reason, phase}: `status` is the
+    marker-path status dict (or a minimal one when whisper is skipped),
+    `update_available` says the chained apply would run a whisper phase, and
+    `phase` carries what run_chained_phase needs. Only marker-managed installs are
+    chained: local links, source builds and unmanaged/pinned paths are silently
+    skipped so whisper can never block a llama update. Never raises; failures
+    degrade to a skip."""
+    binary = _find_binary()
+    if _active_install_is_local_link(binary):
+        return {
+            "status": _local_link_status(),
+            "update_available": False,
+            "skip_reason": "local_link",
+            "phase": None,
+        }
+    marker = read_install_marker(binary)
+    if marker is None:
+        # No marker: whisper is absent or a source/custom build. The standalone
+        # utils API can update source builds; the chain does not.
+        return {
+            "status": None,
+            "update_available": False,
+            "skip_reason": "source_build" if binary else "not_installed",
+            "phase": None,
+        }
+    status = get_update_status(force_refresh = force_refresh)
+    plan: dict = {"status": status, "update_available": False, "skip_reason": None, "phase": None}
+    if not status.get("update_available"):
+        # Skew note: when llama just updated but whisper is already latest, a slim
+        # install keeps hardlinks to the OLD llama ggml inodes -- still the exact
+        # build whisper was installed against, so skipping is correct and needs no
+        # re-wiring. A whisper phase that does run re-wires via the installer
+        # (prepare_runtime_payload).
+        plan["skip_reason"] = "up_to_date"
+        return plan
+    if marker.get("install_kind") == "slim" and not paired_llama_will_update:
+        # A slim install can only be refreshed from a completed managed llama
+        # prebuilt. Ask the installer through its read-only resolver so local
+        # links, markerless/current source builds, and incomplete managed trees
+        # never produce an Update button that can only fail. When the llama
+        # phase will run first, it supplies the repaired pairing instead.
+        resolved = _resolve_prebuilt_for_host(
+            force_refresh = force_refresh,
+            backend = marker.get("backend") if isinstance(marker.get("backend"), str) else None,
+        )
+        if not (resolved or {}).get("prebuilt_available"):
+            plan["skip_reason"] = "paired_llama_unavailable"
+            return plan
+    script = _installer_script()
+    if script is None:
+        plan["skip_reason"] = "installer_missing"
+        return plan
+    install_dir = _install_dir_for(binary)
+    if install_dir is None:
+        plan["skip_reason"] = "no_install_dir"
+        return plan
+    plan["update_available"] = True
+    plan["phase"] = {
+        "install_dir": install_dir,
+        "repo": marker.get("published_repo") or DEFAULT_PUBLISHED_REPO,
+        "asset": marker.get("asset"),
+        "backend": marker.get("backend"),
+        "script": script,
+        # Install exactly the release the check offered: the installer's unpinned
+        # "latest" prefers the download-host /releases/latest pointer, which sorts
+        # by commit date and can lag the published_at pick the freshness check
+        # used, reinstalling an older build in a loop (the #6219 class the llama
+        # phase pins against). Not on macOS: the llama phase is unpinned there
+        # (walk-back to an os-compatible release), so pinning whisper to the
+        # newest tag could be an impossible pairing (min_os / requires_llama_tag)
+        # on every retry.
+        "pin_release_tag": None if sys.platform == "darwin" else status.get("latest_tag"),
+    }
+    return plan
+
+
+def run_chained_phase(phase: dict, set_progress) -> dict:
+    """Run the whisper phase of a combined update (spec from chained_phase_plan):
+    same unload/install/cache-refresh path as the standalone job, reporting
+    progress through the chained job's window rather than whisper's own."""
+    return _install_latest(
+        phase["install_dir"],
+        phase["repo"],
+        phase["asset"],
+        phase["backend"],
+        phase["script"],
+        set_progress,
+        pin_release_tag = phase.get("pin_release_tag"),
+    )
diff --git a/studio/frontend/src/app/auth-guards.ts b/studio/frontend/src/app/auth-guards.ts
index 6849f380b8..a3523ac580 100644
--- a/studio/frontend/src/app/auth-guards.ts
+++ b/studio/frontend/src/app/auth-guards.ts
@@ -23,19 +23,47 @@ interface AuthStatus {
   requires_password_change: boolean;
 }
 
+const AUTH_STATUS_TTL_MS = 30_000;
+let authStatusCheckedAt = 0;
+let authStatusRequest: Promise<AuthStatus> | null = null;
+
+function hasFreshAuthStatus(): boolean {
+  return (
+    authStatusCheckedAt !== 0 &&
+    Date.now() - authStatusCheckedAt < AUTH_STATUS_TTL_MS
+  );
+}
+
 async function fetchAuthStatus(): Promise<AuthStatus> {
-  try {
-    const res = await fetch(apiUrl("/api/auth/status"));
-    if (!res.ok) return { initialized: true, requires_password_change: mustChangePassword() };
-    const status = (await res.json()) as AuthStatus;
-    // Server truth wins; keep localStorage in sync both ways.
-    if (status.requires_password_change !== mustChangePassword()) {
-      setMustChangePassword(status.requires_password_change);
+  if (authStatusRequest) return authStatusRequest;
+
+  const request = (async () => {
+    try {
+      const res = await fetch(apiUrl("/api/auth/status"));
+      if (!res.ok) {
+        return {
+          initialized: true,
+          requires_password_change: mustChangePassword(),
+        };
+      }
+      const status = (await res.json()) as AuthStatus;
+      authStatusCheckedAt = Date.now();
+      // Server truth wins; keep localStorage in sync both ways.
+      if (status.requires_password_change !== mustChangePassword()) {
+        setMustChangePassword(status.requires_password_change);
+      }
+      return status;
+    } catch {
+      return {
+        initialized: true,
+        requires_password_change: mustChangePassword(),
+      };
     }
-    return status;
-  } catch {
-    return { initialized: true, requires_password_change: mustChangePassword() };
-  }
+  })().finally(() => {
+    authStatusRequest = null;
+  });
+  authStatusRequest = request;
+  return request;
 }
 
 function authRedirect(to: "/login" | "/change-password"): never {
@@ -49,12 +77,17 @@ export async function requireAuth(): Promise<void> {
   }
 
   if (await hasActiveSession()) {
-    const { requires_password_change } = await fetchAuthStatus();
-    if (requires_password_change || mustChangePassword()) {
-      authRedirect("/change-password");
+    // Reconcile periodically so local-only routes cannot outlive a server-side
+    // password-change requirement, while nearby route switches stay local.
+    if (mustChangePassword() || !hasFreshAuthStatus()) {
+      const { requires_password_change } = await fetchAuthStatus();
+      if (requires_password_change || mustChangePassword()) {
+        authRedirect("/change-password");
+      }
     }
     return;
   }
+
   const status = await fetchAuthStatus();
   if (status.requires_password_change || mustChangePassword()) {
     authRedirect("/change-password");
diff --git a/studio/frontend/src/app/provider.tsx b/studio/frontend/src/app/provider.tsx
index a7e9469cfc..e6c89b9cd7 100644
--- a/studio/frontend/src/app/provider.tsx
+++ b/studio/frontend/src/app/provider.tsx
@@ -51,9 +51,12 @@ async function showSetupWindow(isCurrent: WindowLayoutGuard): Promise<void> {
   const { getCurrentWindow, LogicalSize } = await import(
     "@tauri-apps/api/window"
   );
+  const { invoke } = await import("@tauri-apps/api/core");
   if (!isCurrent()) return;
 
   const win = getCurrentWindow();
+  await invoke("reset_app_window_layout_initialized");
+  if (!isCurrent()) return;
   await win.setResizable(false);
   if (!isCurrent()) return;
   await win.setSize(new LogicalSize(SETUP_WINDOW_WIDTH, SETUP_WINDOW_HEIGHT));
@@ -98,18 +101,20 @@ async function applyAppWindowLayout(
   if (!isCurrent()) return;
 
   const win = getCurrentWindow();
-  // Decide first-launch vs restore from the on-disk state file BEFORE touching the
-  // window. Probing the window after restoreStateCurrent is unreliable: on GTK,
-  // set_size on a hidden window is deferred until show(), so innerSize() reads a
-  // stale value and a baseline fallback would overwrite the queued restore. On
-  // macOS the same probe works, hence the inconsistency between prior iterations.
-  const hasSavedState = await invoke<boolean>("has_saved_window_state");
+  // Setup-window activity may create plugin state before the full app is ever
+  // shown, so use a dedicated full-app marker to decide whether restoration is
+  // appropriate. Keep checking plugin state so a missing/corrupt state file
+  // falls back to a monitor-safe centered layout.
+  const [hasInitializedAppLayout, hasSavedState] = await Promise.all([
+    invoke<boolean>("has_initialized_app_window_layout"),
+    invoke<boolean>("has_saved_window_state"),
+  ]);
   if (!isCurrent()) return;
 
   await win.setResizable(true);
   if (!isCurrent()) return;
 
-  if (hasSavedState) {
+  if (hasInitializedAppLayout && hasSavedState) {
     // Subsequent launch: plugin restores size/position/maximized, with built-in
     // off-screen protection for positions saved on a now-disconnected display.
     await restoreStateCurrent(
@@ -144,6 +149,9 @@ async function applyAppWindowLayout(
   });
   if (!isCurrent()) return;
   await enforceMinimumWindowSize(win, LogicalSize, isCurrent);
+
+  if (!isCurrent()) return;
+  await invoke("mark_app_window_layout_initialized");
 }
 
 async function showWindowFallback(): Promise<void> {
diff --git a/studio/frontend/src/app/routes/__root.tsx b/studio/frontend/src/app/routes/__root.tsx
index e23892e020..7137fd6f96 100644
--- a/studio/frontend/src/app/routes/__root.tsx
+++ b/studio/frontend/src/app/routes/__root.tsx
@@ -196,9 +196,6 @@ function RootLayout() {
         chatRuntime.setActiveThreadId(null);
         chatRuntime.setActiveProjectId(null);
         chatRuntime.setIncognito(false);
-        // Detach the staging UI but keep any in-flight download running, like Hub.
-        if (chatRuntime.pendingSelection)
-          chatRuntime.abandonStagedModel({ keepDownload: true });
         void navigate({
           to: "/chat",
           search: { new: crypto.randomUUID() },
@@ -221,10 +218,6 @@ function RootLayout() {
     chatRuntime.setActiveProjectId(null);
     chatRuntime.setActiveThreadId(null);
     chatRuntime.setIncognito(false);
-    // Leaving chat must not kill an in-flight download: detach the staging UI
-    // but keep the transfer running in the manager, like a Hub download.
-    if (chatRuntime.pendingSelection)
-      chatRuntime.abandonStagedModel({ keepDownload: true });
   }, [isChatRoute]);
 
   return (
@@ -281,7 +274,7 @@ function RootLayout() {
                     initial={{ opacity: 0 }}
                     animate={{ opacity: 1 }}
                     exit={{ opacity: 0 }}
-                    transition={{ duration: 0.15 }}
+                    transition={{ duration: 0.06 }}
                     className="flex min-h-0 min-w-0 flex-1 basis-0 flex-col overflow-visible"
                   >
                     <Suspense fallback={<RouteFallback />}>
diff --git a/studio/frontend/src/app/routes/data-recipes.tsx b/studio/frontend/src/app/routes/data-recipes.tsx
index c35e63da5f..22f87821af 100644
--- a/studio/frontend/src/app/routes/data-recipes.tsx
+++ b/studio/frontend/src/app/routes/data-recipes.tsx
@@ -1,15 +1,13 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { createRoute } from "@tanstack/react-router";
-import { lazy } from "react";
+import { createRoute, lazyRouteComponent } from "@tanstack/react-router";
 import { requireAuth } from "../auth-guards";
 import { Route as rootRoute } from "./__root";
 
-const DataRecipesPage = lazy(() =>
-  import("@/features/data-recipes").then((m) => ({
-    default: m.DataRecipesPage,
-  })),
+const DataRecipesPage = lazyRouteComponent(
+  () => import("@/features/data-recipes"),
+  "DataRecipesPage",
 );
 
 export const Route = createRoute({
diff --git a/studio/frontend/src/app/routes/export.tsx b/studio/frontend/src/app/routes/export.tsx
index 40118c6a92..5a7b586f19 100644
--- a/studio/frontend/src/app/routes/export.tsx
+++ b/studio/frontend/src/app/routes/export.tsx
@@ -1,15 +1,13 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { createRoute } from "@tanstack/react-router";
-import { lazy } from "react";
+import { createRoute, lazyRouteComponent } from "@tanstack/react-router";
 import { requireAuth } from "../auth-guards";
 import { Route as rootRoute } from "./__root";
 
-const ExportPage = lazy(() =>
-  import("@/features/export/export-page").then((m) => ({
-    default: m.ExportPage,
-  })),
+const ExportPage = lazyRouteComponent(
+  () => import("@/features/export/export-page"),
+  "ExportPage",
 );
 
 export type ExportSearch = {
diff --git a/studio/frontend/src/app/routes/hub.tsx b/studio/frontend/src/app/routes/hub.tsx
index c623ef9848..2207490e44 100644
--- a/studio/frontend/src/app/routes/hub.tsx
+++ b/studio/frontend/src/app/routes/hub.tsx
@@ -1,15 +1,13 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { createRoute } from "@tanstack/react-router";
-import { lazy } from "react";
+import { createRoute, lazyRouteComponent } from "@tanstack/react-router";
 import { requireAuth } from "../auth-guards";
 import { Route as rootRoute } from "./__root";
 
-const ModelsPage = lazy(() =>
-  import("@/features/hub/hub-page").then((m) => ({
-    default: m.ModelsPage,
-  })),
+const ModelsPage = lazyRouteComponent(
+  () => import("@/features/hub/hub-page"),
+  "ModelsPage",
 );
 
 export interface ModelsSearch {
@@ -31,7 +29,11 @@ export const Route = createRoute({
     const model = search.model;
     if (typeof model === "string" && model.length > 0) next.model = model;
     const section = search.section;
-    if (section === "trending" || section === "latest" || section === "finetune") {
+    if (
+      section === "trending" ||
+      section === "latest" ||
+      section === "finetune"
+    ) {
       next.section = section;
     }
     const kind = search.kind;
diff --git a/studio/frontend/src/app/routes/projects.tsx b/studio/frontend/src/app/routes/projects.tsx
index c63b1d5838..17f58ef631 100644
--- a/studio/frontend/src/app/routes/projects.tsx
+++ b/studio/frontend/src/app/routes/projects.tsx
@@ -1,15 +1,13 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { createRoute } from "@tanstack/react-router";
-import { lazy } from "react";
+import { createRoute, lazyRouteComponent } from "@tanstack/react-router";
 import { requireAuth } from "../auth-guards";
 import { Route as rootRoute } from "./__root";
 
-const ProjectsPage = lazy(() =>
-  import("@/features/chat/projects-page").then((m) => ({
-    default: m.ProjectsPage,
-  })),
+const ProjectsPage = lazyRouteComponent(
+  () => import("@/features/chat/projects-page"),
+  "ProjectsPage",
 );
 
 export const Route = createRoute({
diff --git a/studio/frontend/src/app/routes/studio.tsx b/studio/frontend/src/app/routes/studio.tsx
index ae7f445e94..798044bf64 100644
--- a/studio/frontend/src/app/routes/studio.tsx
+++ b/studio/frontend/src/app/routes/studio.tsx
@@ -1,15 +1,13 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { createRoute } from "@tanstack/react-router";
-import { lazy } from "react";
+import { createRoute, lazyRouteComponent } from "@tanstack/react-router";
 import { requireAuth } from "../auth-guards";
 import { Route as rootRoute } from "./__root";
 
-const StudioPage = lazy(() =>
-  import("@/features/studio/studio-page").then((m) => ({
-    default: m.StudioPage,
-  })),
+const StudioPage = lazyRouteComponent(
+  () => import("@/features/studio/studio-page"),
+  "StudioPage",
 );
 
 export const Route = createRoute({
diff --git a/studio/frontend/src/components/app-sidebar.tsx b/studio/frontend/src/components/app-sidebar.tsx
index b8601b00f6..a6f64243ad 100644
--- a/studio/frontend/src/components/app-sidebar.tsx
+++ b/studio/frontend/src/components/app-sidebar.tsx
@@ -45,6 +45,7 @@ import { Spinner } from "@/components/ui/spinner";
 import { Switch } from "@/components/ui/switch";
 import { useAnimatedThemeToggle } from "@/components/ui/animated-theme-toggler";
 import {
+  getClientPlatform,
   shouldUseCustomWindowTitlebar,
   shouldUseNativeMacWindowTitlebar,
 } from "@/components/tauri/window-titlebar";
@@ -55,6 +56,7 @@ import {
   Archive03Icon,
   ArrowRight02Icon,
   BadgeInfoIcon,
+  BubbleChatIcon,
   ChefHatIcon,
   CloudIcon,
   CpuIcon,
@@ -93,7 +95,12 @@ import {
 import { Tooltip as TooltipPrimitive } from "radix-ui";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { ChevronDown, Moon } from "lucide-react";
-import { Link, useNavigate, useRouterState } from "@tanstack/react-router";
+import {
+  Link,
+  useNavigate,
+  useRouter,
+  useRouterState,
+} from "@tanstack/react-router";
 import {
   archiveChatItem,
   ChatSearchDialog,
@@ -103,6 +110,7 @@ import {
   deleteChatItem,
   listStoredChatThreads,
   moveChatItemToProject,
+  notifyChatHistoryUpdated,
   renameChatItem,
   renameChatProject,
   useChatRuntimeStore,
@@ -110,6 +118,7 @@ import {
   useChatSearchStore,
   useChatSidebarItems,
   usePinnedChatsStore,
+  usePinnedProjectsStore,
   useChatPreferencesStore,
   type ProjectRecord,
   type SidebarItem,
@@ -135,7 +144,15 @@ import {
 } from "@/features/training";
 import type { TrainingRunSummary } from "@/features/training";
 import { useExportRuntimeStore } from "@/features/export";
-import { useEffect, useMemo, useRef, useState, type ReactNode } from "react";
+import {
+  Fragment,
+  useEffect,
+  useMemo,
+  useRef,
+  useState,
+  type ReactNode,
+} from "react";
+import { isDownloadCancelled } from "@/lib/native-files";
 import { toast } from "@/lib/toast";
 import { ShutdownDialog } from "@/components/shutdown-dialog";
 import { translate, useT, type TranslationKey } from "@/i18n";
@@ -193,6 +210,9 @@ const TestTubeOutlineIcon = TestTube01Icon.slice(
 
 type ConversationExportFormat = "raw-jsonl" | "csv" | "sharegpt-jsonl";
 
+// A pinned project shows this many recent chats before "Show more".
+const PINNED_PROJECT_CHAT_LIMIT = 4;
+
 const CHAT_EXPORT_OPTIONS: Array<{
   label: string;
   format: ConversationExportFormat;
@@ -256,6 +276,10 @@ function createNavigationNonce(): string {
   return `${Date.now()}-${Math.random().toString(36).slice(2, 10)}`;
 }
 
+function preloadSilently(request: Promise<unknown>): void {
+  void request.catch(() => undefined);
+}
+
 function NavItem({
   icon,
   label,
@@ -267,6 +291,7 @@ function NavItem({
   className,
   spinner,
   tooltip,
+  onIntent,
 }: {
   icon: typeof ZapIcon;
   label: string;
@@ -277,6 +302,7 @@ function NavItem({
   dataTour?: string;
   className?: string;
   spinner?: boolean;
+  onIntent?: () => void;
   // Overrides the hover tooltip (defaults to `label`). Used to explain why a
   // disabled item (e.g. Train/Export on a chat-only host) is greyed out.
   tooltip?: string;
@@ -288,12 +314,14 @@ function NavItem({
           tooltip={tooltip ?? label}
           disabled={disabled}
           onClick={onClick}
+          onPointerEnter={disabled ? undefined : onIntent}
+          onFocus={disabled ? undefined : onIntent}
           isActive={active}
           data-tour={dataTour}
           className="sidebar-nav-btn h-[33px] rounded-full gap-[8.5px] pl-3 pr-2.5 font-medium group-data-[collapsible=icon]:px-2.5 group-data-[collapsible=icon]:!w-[32px] group-data-[collapsible=icon]:mx-auto"
         >
           <HugeiconsIcon icon={icon} strokeWidth={1.75} className="size-icon! shrink-0 group-hover/menu-button:animate-icon-pop" />
-          <span className="text-[14.5px] leading-[19px] tracking-nav">{label}</span>
+          <span className="text-ui-14p5 leading-ui-19 tracking-nav">{label}</span>
           {spinner && (
             <Spinner className="ml-auto size-3.5 shrink-0 text-muted-foreground group-data-[collapsible=icon]:hidden" />
           )}
@@ -316,6 +344,8 @@ export function AppSidebar() {
   );
   const [usesCustomTitlebar] = useState(shouldUseCustomWindowTitlebar);
   const [usesNativeMacTitlebar] = useState(shouldUseNativeMacWindowTitlebar);
+  // Mac uses Cmd, others use Ctrl. Not Tauri-gated, so it's right on web too.
+  const [isMacPlatform] = useState(() => getClientPlatform().includes("mac"));
   const { pathname, search } = useRouterState({
     select: (s) => ({
       pathname: s.location.pathname,
@@ -324,6 +354,7 @@ export function AppSidebar() {
   });
   const { togglePinned, isMobile, setOpenMobile } = useSidebar();
   const navigate = useNavigate();
+  const router = useRouter();
 
   // Web update detection: `webUpdate` is non-null only when the installed
   // (PyPI) version is behind the latest release, so the card is hidden by
@@ -430,14 +461,63 @@ export function AppSidebar() {
       ),
     [allChatItems, pinnedIdSet],
   );
-  // Pinned chats, in pin order (most recent first).
+  const [pinnedOpen, setPinnedOpen] = useState(true);
+  // "Projects" section: projects the user pinned, in pin order (most recent
+  // first). The section only appears once at least one project is pinned.
+  const pinnedProjectIds = usePinnedProjectsStore((s) => s.pinnedIds);
+  const unpinProject = usePinnedProjectsStore((s) => s.unpin);
+  const pinnedProjectRecords = useMemo(() => {
+    const byId = new Map(projects.map((p) => [p.id, p]));
+    return pinnedProjectIds
+      .map((id) => byId.get(id))
+      .filter((p): p is ProjectRecord => Boolean(p));
+  }, [projects, pinnedProjectIds]);
+  // Pinned chats, in pin order (most recent first). Includes chats that live
+  // inside a project: pinning promotes a chat into this list, and it is removed
+  // from the project's nested list below so it never shows twice.
   const pinnedChatItems = useMemo(() => {
     const byId = new Map(allChatItems.map((item) => [item.id, item]));
     return pinnedIds
       .map((id) => byId.get(id))
       .filter((item): item is SidebarItem => Boolean(item));
   }, [allChatItems, pinnedIds]);
-  const [pinnedOpen, setPinnedOpen] = useState(true);
+  // A pinned project reveals its recent chats (most recent first) nested below.
+  // Pinned chats are excluded here since they render in the pinned-chats list.
+  const chatsByProjectId = useMemo(() => {
+    const map = new Map<string, SidebarItem[]>();
+    for (const item of allChatItems) {
+      if (!item.projectId) continue;
+      if (pinnedIdSet.has(item.id)) continue;
+      const list = map.get(item.projectId);
+      if (list) list.push(item);
+      else map.set(item.projectId, [item]);
+    }
+    for (const list of map.values())
+      list.sort((a, b) => b.updatedAt - a.updatedAt);
+    return map;
+  }, [allChatItems, pinnedIdSet]);
+  // Default expanded (not collapsed); the row toggles this. Show-more reveals
+  // chats past the first PINNED_PROJECT_CHAT_LIMIT.
+  const [collapsedProjectIds, setCollapsedProjectIds] = useState<Set<string>>(
+    () => new Set(),
+  );
+  const [expandedChatProjectIds, setExpandedChatProjectIds] = useState<
+    Set<string>
+  >(() => new Set());
+  const toggleProjectCollapsed = (id: string) =>
+    setCollapsedProjectIds((prev) => {
+      const next = new Set(prev);
+      if (next.has(id)) next.delete(id);
+      else next.add(id);
+      return next;
+    });
+  const toggleProjectShowAll = (id: string) =>
+    setExpandedChatProjectIds((prev) => {
+      const next = new Set(prev);
+      if (next.has(id)) next.delete(id);
+      else next.add(id);
+      return next;
+    });
   const storeThreadId = useChatRuntimeStore((s) => s.activeThreadId);
   const setActiveThreadId = useChatRuntimeStore((s) => s.setActiveThreadId);
   const anyChatRunning = useChatRuntimeStore((s) =>
@@ -717,6 +797,8 @@ export function AppSidebar() {
     const shouldDeleteProjectFiles =
       target.kind === "project" && deleteProjectFiles;
     setConfirmingDelete(null);
+    // Reset so the next project delete never inherits this checkbox.
+    setDeleteProjectFiles(false);
     if (target.kind === "chat") {
       await deleteChatWithCleanup(target.item);
       return;
@@ -726,7 +808,20 @@ export function AppSidebar() {
         await deleteChatProject(target.project.id, {
           deleteFiles: shouldDeleteProjectFiles,
         });
-        if (activeProjectId === target.project.id) {
+        // Refresh chat history so the project's reparented chats don't linger
+        // as stale top-level rows.
+        notifyChatHistoryUpdated();
+        // activeProjectId is only the ?project= param; on a thread-only URL the
+        // project is resolved from the thread into the runtime store, so check
+        // that too or we strand the user on a now-deleted thread. Only redirect
+        // from a chat route: the runtime store value can be stale elsewhere.
+        const runtimeProjectId =
+          useChatRuntimeStore.getState().activeProjectId;
+        if (
+          isChatRoute &&
+          (activeProjectId === target.project.id ||
+            runtimeProjectId === target.project.id)
+        ) {
           useChatRuntimeStore.getState().setActiveProjectId(null);
           navigate({ to: "/chat", search: { new: createNavigationNonce() } });
         }
@@ -809,12 +904,15 @@ export function AppSidebar() {
         ? "sidebar-row-action group-hover/project-chat-item:opacity-100 group-hover/project-chat-item:pointer-events-auto focus-visible:opacity-100 focus-visible:pointer-events-auto"
         : "sidebar-row-action group-hover/recent-item:opacity-100 group-hover/recent-item:pointer-events-auto focus-visible:opacity-100 focus-visible:pointer-events-auto";
     const buttonClass = cn(
-      "sidebar-nav-btn h-[33px] cursor-pointer rounded-full pr-4 text-[14.5px] leading-[19px] tracking-nav font-medium",
+      "sidebar-nav-btn h-[33px] cursor-pointer rounded-full pr-4 text-ui-14p5 leading-ui-19 tracking-nav font-medium",
       // pl-3 (12px) over the content's pl-1.5 (6px) = 18px, aligning the
       // title with the nav items above.
       variant === "project" ? "pl-[39px]" : "pl-3",
+      // Pinned chats carry a chat icon, so add the nav-item icon gap.
+      isPinned && variant !== "project" && "gap-[8.5px]",
       variant === "project"
-        ? "group-hover/project-chat-item:pr-6 group-has-[.sidebar-row-action[data-state=open]]/project-chat-item:pr-6"
+        ? // Room for the hover pin quick-action plus the kebab.
+          "group-hover/project-chat-item:pr-14 group-has-[.sidebar-row-action[data-state=open]]/project-chat-item:pr-8"
         : isPinned
           ? // Pinned rows show an extra unpin button on hover, so reserve more room
             // (pr-8 when the menu is open keeps the unpin button clear of the title).
@@ -841,7 +939,7 @@ export function AppSidebar() {
             aria-label={translate("shell.dialog.renameChat.placeholder")}
             className={cn(
               // No pill or box; edit in place as plain highlighted text.
-              "text-foreground h-[33px] w-full border-0 bg-transparent pr-4 text-[14.5px] leading-[19px] font-medium tracking-nav outline-none",
+              "text-foreground h-[33px] w-full border-0 bg-transparent pr-4 text-ui-14p5 leading-ui-19 font-medium tracking-nav outline-none",
               variant === "project" ? "pl-[39px]" : "pl-3",
             )}
           />
@@ -874,10 +972,43 @@ export function AppSidebar() {
             closeMobileIfOpen();
           }}
         >
+          {isPinned && variant !== "project" && (
+            <HugeiconsIcon icon={BubbleChatIcon} strokeWidth={1.75} className="size-icon! shrink-0" />
+          )}
           <span className="truncate">
             {pendingRename?.id === item.id ? pendingRename.title : item.title}
           </span>
         </SidebarMenuButton>
+        {variant === "project" && (
+          <button
+            type="button"
+            onClick={(e) => {
+              e.stopPropagation();
+              togglePinnedChat(item.id);
+            }}
+            aria-label={isPinned ? "Unpin chat" : "Pin chat"}
+            className="sidebar-row-action is-unpin-action group-hover/project-chat-item:opacity-100 group-hover/project-chat-item:pointer-events-auto focus-visible:opacity-100 focus-visible:pointer-events-auto"
+          >
+            <span className="sidebar-row-action-glyph">
+              <HugeiconsIcon icon={isPinned ? PinOffIcon : PinIcon} strokeWidth={1.75} className="size-icon" />
+            </span>
+          </button>
+        )}
+        {variant === "recent" && isPinned && (
+          <button
+            type="button"
+            onClick={(e) => {
+              e.stopPropagation();
+              togglePinnedChat(item.id);
+            }}
+            aria-label="Unpin chat"
+            className="sidebar-row-action is-unpin-action group-hover/recent-item:opacity-100 group-hover/recent-item:pointer-events-auto focus-visible:opacity-100 focus-visible:pointer-events-auto"
+          >
+            <span className="sidebar-row-action-glyph">
+              <HugeiconsIcon icon={PinOffIcon} strokeWidth={1.75} className="size-icon" />
+            </span>
+          </button>
+        )}
         <DropdownMenu>
           <DropdownMenuTrigger asChild>
             <button
@@ -957,11 +1088,13 @@ export function AppSidebar() {
                         const ids = item.type === "single"
                           ? [item.id]
                           : (await listStoredChatThreads({ pairId: item.id })).map((t) => t.id);
-                        await Promise.all(
-                          ids.map((id) => exportConversationByFormat(id, format)),
-                        );
-                      } catch {
-                        toast.error("Export failed.");
+                        for (const id of ids) {
+                          await exportConversationByFormat(id, format);
+                        }
+                      } catch (error) {
+                        if (!isDownloadCancelled(error)) {
+                          toast.error("Export failed.");
+                        }
                       }
                     }}
                   >
@@ -997,28 +1130,6 @@ export function AppSidebar() {
             </DropdownMenuItem>
           </DropdownMenuContent>
         </DropdownMenu>
-        {isPinned ? (
-          <Tooltip>
-            <TooltipPrimitive.Trigger asChild>
-              <button
-                type="button"
-                onClick={(e) => {
-                  e.stopPropagation();
-                  unpinChat(item.id);
-                }}
-                aria-label="Unpin chat"
-                className={cn(actionClass, "is-unpin-action")}
-              >
-                <span className="sidebar-row-action-glyph">
-                  <HugeiconsIcon icon={PinOffIcon} strokeWidth={1.75} className="size-4" />
-                </span>
-              </button>
-            </TooltipPrimitive.Trigger>
-            <TooltipContent side="bottom" sideOffset={6} className="tooltip-compact">
-              Unpin
-            </TooltipContent>
-          </Tooltip>
-        ) : null}
       </SidebarMenuItem>
     );
   }
@@ -1073,40 +1184,70 @@ export function AppSidebar() {
                   aria-disabled={chatDisabled}
                   tabIndex={chatDisabled ? -1 : undefined}
                 >
+                  {/* Logo lockup follows the UI font size at half rate:
+                      base + (root scale - 1) * 8px. Exact base sizes at 16px. */}
                   <img
                     src="/circle-logo-small.png"
                     alt="Unsloth"
-                    className="h-[34px] w-[34px] rounded-full object-cover"
+                    className="h-[calc(26px+0.5rem*var(--ui-font-scale,1))] w-[calc(26px+0.5rem*var(--ui-font-scale,1))] rounded-full object-cover"
                   />
-                  <span className="font-heading text-[21px] font-semibold tracking-[0em] leading-none text-black dark:text-white dark:tracking-[0.02em]">
+                  <span className="font-heading text-[calc(13px+0.5rem*var(--ui-font-scale,1))] font-semibold tracking-[0em] leading-none text-black dark:text-white dark:tracking-[0.02em]">
                     unsloth
                   </span>
-                  <span className="nav-badge ml-0.5 inline-flex items-center justify-center rounded-full border border-nav-beta-border px-[5px] pt-[3px] pb-[2px] text-[8px] font-medium leading-none tracking-[0.04em] text-nav-fg-muted antialiased subpixel-antialiased shadow-[0_1px_2px_rgba(0,0,0,0.06)] dark:shadow-[0_1px_2px_rgba(0,0,0,0.35)]">
+                  <span className="nav-badge ml-0.5 inline-flex items-center justify-center rounded-full border border-nav-beta-border px-[5px] pt-[3px] pb-[2px] text-[calc(0.5rem*var(--ui-font-scale,1))] font-medium leading-none tracking-[0.04em] text-nav-fg-muted antialiased subpixel-antialiased shadow-[0_1px_2px_rgba(0,0,0,0.06)] dark:shadow-[0_1px_2px_rgba(0,0,0,0.35)]">
                     {t("shell.beta")}
                   </span>
                 </Link>
               )}
-              {!isMobile && (
+              <div className="flex items-center gap-0.5">
                 <Tooltip>
                   <TooltipPrimitive.Trigger asChild>
                     <button
                       type="button"
-                      onClick={togglePinned}
+                      onClick={() => {
+                        useChatSearchStore.getState().open();
+                        closeMobileIfOpen();
+                      }}
                       className="inline-flex h-[33px] w-[32px] cursor-pointer items-center justify-center rounded-[10px] text-nav-icon-idle dark:text-nav-fg-muted transition-colors hover:bg-nav-surface-hover hover:text-black dark:hover:text-white focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
-                      aria-label={t("shell.aria.closeSidebar")}
+                      aria-label={t("shell.navigation.search")}
                     >
-                      <HugeiconsIcon icon={LayoutAlignLeftIcon} strokeWidth={1.75} className="size-icon" />
+                      <HugeiconsIcon icon={Search01Icon} strokeWidth={1.75} className="size-icon" />
                     </button>
                   </TooltipPrimitive.Trigger>
                   <TooltipContent
                     side="bottom"
                     sideOffset={6}
-                    className="tooltip-compact"
+                    className="tooltip-compact flex items-center gap-1.5"
+                    hidden={isMobile}
                   >
-                    {t("shell.aria.closeSidebar")}
+                    {t("shell.navigation.search")}
+                    <kbd className="rounded bg-black/10 px-1 py-px text-ui-10 font-medium leading-none dark:bg-white/15">
+                      {isMacPlatform ? "⌘K" : "Ctrl+K"}
+                    </kbd>
                   </TooltipContent>
                 </Tooltip>
-              )}
+                {!isMobile && (
+                  <Tooltip>
+                    <TooltipPrimitive.Trigger asChild>
+                      <button
+                        type="button"
+                        onClick={togglePinned}
+                        className="inline-flex h-[33px] w-[32px] cursor-pointer items-center justify-center rounded-[10px] text-nav-icon-idle dark:text-nav-fg-muted transition-colors hover:bg-nav-surface-hover hover:text-black dark:hover:text-white focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
+                        aria-label={t("shell.aria.closeSidebar")}
+                      >
+                        <HugeiconsIcon icon={LayoutAlignLeftIcon} strokeWidth={1.75} className="size-icon" />
+                      </button>
+                    </TooltipPrimitive.Trigger>
+                    <TooltipContent
+                      side="bottom"
+                      sideOffset={6}
+                      className="tooltip-compact"
+                    >
+                      {t("shell.aria.closeSidebar")}
+                    </TooltipContent>
+                  </Tooltip>
+                )}
+              </div>
             </div>
             {!isMobile && (
               <div className="relative z-10 hidden group-data-[collapsible=icon]:flex h-[33px] items-center justify-center w-full">
@@ -1138,8 +1279,10 @@ export function AppSidebar() {
       {/* Uniform pl-1.5 pr-2 keeps every hover pill the same width, inset from the edge. */}
       <SidebarGroup
         className={cn(
-          "group-data-[collapsible=icon]:px-0 pl-1.5 pr-2 pb-px shrink-0",
+          "group-data-[collapsible=icon]:px-0 pl-1.5 pr-2 shrink-0 transition-[padding]",
           showCompactMacBrand ? "pt-0" : "pt-[9px]",
+          // Scrolled: New Chat is pinned, give a little gap below it.
+          scrolled ? "pb-[5px]" : "pb-px",
         )}
       >
         <SidebarGroupContent>
@@ -1172,10 +1315,18 @@ export function AppSidebar() {
                 openNewChat(null);
               }}
             />
+            {/* Search sits in the header when the brand row is shown (mac/web).
+                Hide this row there, but keep it in the collapsed rail. On custom
+                titlebars (win/linux) there's no header button, so keep the row. */}
             <NavItem
               icon={Search01Icon}
               label={t("shell.navigation.search")}
               active={false}
+              className={
+                showSidebarBrand
+                  ? "hidden group-data-[collapsible=icon]:block"
+                  : undefined
+              }
               onClick={() => {
                 useChatSearchStore.getState().open();
                 closeMobileIfOpen();
@@ -1208,6 +1359,18 @@ export function AppSidebar() {
         <SidebarGroup className="group-data-[collapsible=icon]:px-0 pl-1.5 pr-2 py-0 shrink-0">
           <SidebarGroupContent>
             <SidebarMenu>
+              <NavItem
+                icon={DashboardCircleIcon}
+                label={t("shell.navigation.hub")}
+                active={pathname === "/hub" || pathname.startsWith("/hub/")}
+                onClick={() => {
+                  navigate({ to: "/hub" });
+                  closeMobileIfOpen();
+                }}
+                onIntent={() => {
+                  preloadSilently(router.preloadRoute({ to: "/hub" }));
+                }}
+              />
               <NavItem
                 icon={Folder01Icon}
                 label="Projects"
@@ -1218,6 +1381,9 @@ export function AppSidebar() {
                   navigate({ to: "/projects" });
                   closeMobileIfOpen();
                 }}
+                onIntent={() => {
+                  preloadSilently(router.preloadRoute({ to: "/projects" }));
+                }}
                 className="group/projects-item relative"
               >
                 <button
@@ -1240,15 +1406,6 @@ export function AppSidebar() {
                   </span>
                 </button>
               </NavItem>
-              <NavItem
-                icon={DashboardCircleIcon}
-                label={t("shell.navigation.hub")}
-                active={pathname === "/hub" || pathname.startsWith("/hub/")}
-                onClick={() => {
-                  navigate({ to: "/hub" });
-                  closeMobileIfOpen();
-                }}
-              />
               {/* Train has a labelled section when expanded; plain icon here only when collapsed. */}
               <NavItem
                 icon={TestTubeOutlineIcon}
@@ -1264,6 +1421,9 @@ export function AppSidebar() {
                   navigate({ to: "/studio" });
                   closeMobileIfOpen();
                 }}
+                onIntent={() => {
+                  preloadSilently(router.preloadRoute({ to: "/studio" }));
+                }}
                 className="hidden group-data-[collapsible=icon]:block"
               />
             </SidebarMenu>
@@ -1293,6 +1453,9 @@ export function AppSidebar() {
                       navigate({ to: "/studio" });
                       closeMobileIfOpen();
                     }}
+                    onIntent={() => {
+                      preloadSilently(router.preloadRoute({ to: "/studio" }));
+                    }}
                   />
                   <NavItem
                     icon={ChefHatIcon}
@@ -1302,6 +1465,16 @@ export function AppSidebar() {
                       navigate({ to: "/data-recipes" });
                       closeMobileIfOpen();
                     }}
+                    onIntent={() => {
+                      preloadSilently(
+                        router.preloadRoute({ to: "/data-recipes" }),
+                      );
+                      preloadSilently(
+                        import("@/features/data-recipes").then((module) =>
+                          module.preloadRecipes(),
+                        ),
+                      );
+                    }}
                   />
                   <NavItem
                     icon={DownloadSquare01Icon}
@@ -1312,6 +1485,14 @@ export function AppSidebar() {
                       navigate({ to: "/export" });
                       closeMobileIfOpen();
                     }}
+                    onIntent={() => {
+                      preloadSilently(router.preloadRoute({ to: "/export" }));
+                      preloadSilently(
+                        import(
+                          "@/features/export/export-navigation-cache"
+                        ).then((module) => module.preloadExportData()),
+                      );
+                    }}
                   />
                 </SidebarMenu>
               </SidebarGroupContent>
@@ -1319,28 +1500,156 @@ export function AppSidebar() {
           </SidebarGroup>
         </Collapsible>
 
-        {/* Pinned chats: own section above Recents */}
-        {!isStudioRoute && !showTrainingRecents && pinnedChatItems.length > 0 && (
-          <Collapsible open={pinnedOpen} onOpenChange={setPinnedOpen} asChild>
-            <SidebarGroup className="group-data-[collapsible=icon]:hidden px-0 py-0">
-              <SidebarGroupLabel className={cn("sidebar-sticky-label sidebar-sticky-label-following", scrolled && "is-scrolled")} asChild>
-                <CollapsibleTrigger className="cursor-pointer flex w-full items-center gap-1 group/sb-collap">
-                  Pinned
-                  <ChevronDown className="size-3.5 opacity-0 transition-[transform,opacity] duration-200 group-hover/sb-collap:opacity-100 group-focus-visible/sb-collap:opacity-100 data-[state=open]:rotate-0 [[data-state=closed]_&]:rotate-[-90deg] [[data-state=closed]_&]:opacity-100" />
-                </CollapsibleTrigger>
-              </SidebarGroupLabel>
-              <CollapsibleContent>
-                <SidebarGroupContent className="pl-1.5 pr-2">
-                  <SidebarMenu>
-                    {pinnedChatItems.map((item) =>
-                      renderChatSidebarItem(item, "recent"),
-                    )}
-                  </SidebarMenu>
-                </SidebarGroupContent>
-              </CollapsibleContent>
-            </SidebarGroup>
-          </Collapsible>
-        )}
+        {/* Pinned: pinned projects (with their chats) and pinned chats */}
+        {!isStudioRoute &&
+          !showTrainingRecents &&
+          (pinnedProjectRecords.length > 0 ||
+            pinnedChatItems.length > 0) && (
+            <Collapsible open={pinnedOpen} onOpenChange={setPinnedOpen} asChild>
+              <SidebarGroup className="group-data-[collapsible=icon]:hidden px-0 py-0">
+                <SidebarGroupLabel className={cn("sidebar-sticky-label sidebar-sticky-label-following", scrolled && "is-scrolled")} asChild>
+                  <CollapsibleTrigger className="cursor-pointer flex w-full items-center gap-1 group/sb-collap">
+                    Pinned
+                    <ChevronDown className="size-3.5 opacity-0 transition-[transform,opacity] duration-200 group-hover/sb-collap:opacity-100 group-focus-visible/sb-collap:opacity-100 data-[state=open]:rotate-0 [[data-state=closed]_&]:rotate-[-90deg] [[data-state=closed]_&]:opacity-100" />
+                  </CollapsibleTrigger>
+                </SidebarGroupLabel>
+                <CollapsibleContent>
+                  <SidebarGroupContent className="pl-1.5 pr-2">
+                    <SidebarMenu>
+                      {pinnedProjectRecords.map((project) => {
+                        const projectChats =
+                          chatsByProjectId.get(project.id) ?? [];
+                        const expanded = !collapsedProjectIds.has(project.id);
+                        const showAll = expandedChatProjectIds.has(project.id);
+                        const visibleChats =
+                          expanded && !showAll
+                            ? projectChats.slice(0, PINNED_PROJECT_CHAT_LIMIT)
+                            : projectChats;
+                        return (
+                        <Fragment key={project.id}>
+                        <SidebarMenuItem
+                          className="group/recent-item relative"
+                        >
+                          <SidebarMenuButton
+                            // Highlight the folder only on the project home; when
+                            // a chat inside it is open, only that chat row is active.
+                            isActive={activeProjectId === project.id && !activeThreadId}
+                            onClick={() => toggleProjectCollapsed(project.id)}
+                            className="sidebar-nav-btn h-[33px] rounded-full gap-[8.5px] pl-3 pr-2.5 font-medium group-hover/recent-item:pr-16 group-has-[.sidebar-row-action[data-state=open]]/recent-item:pr-8"
+                          >
+                            <HugeiconsIcon icon={Folder01Icon} strokeWidth={1.75} className="size-icon! shrink-0" />
+                            <span className="truncate text-ui-14p5 leading-ui-19 tracking-nav">{project.name}</span>
+                          </SidebarMenuButton>
+                          {/* New chat in this project */}
+                          <button
+                            type="button"
+                            aria-label="New chat"
+                            onClick={(e) => {
+                              e.stopPropagation();
+                              openNewChat(project.id);
+                            }}
+                            className="sidebar-row-action is-unpin-action group-hover/recent-item:opacity-100 group-hover/recent-item:pointer-events-auto focus-visible:opacity-100 focus-visible:pointer-events-auto"
+                          >
+                            <span className="sidebar-row-action-glyph">
+                              <HugeiconsIcon icon={PencilEdit02Icon} strokeWidth={1.75} className="size-icon" />
+                            </span>
+                          </button>
+                          {/* Project options */}
+                          <DropdownMenu>
+                            <DropdownMenuTrigger asChild>
+                              <button
+                                type="button"
+                                onClick={(e) => e.stopPropagation()}
+                                aria-label="Project options"
+                                className="sidebar-row-action group-hover/recent-item:opacity-100 group-hover/recent-item:pointer-events-auto focus-visible:opacity-100 focus-visible:pointer-events-auto"
+                              >
+                                <span className="sidebar-row-action-glyph">
+                                  <HugeiconsIcon icon={MoreVerticalIcon} strokeWidth={1.75} className="size-icon" />
+                                </span>
+                              </button>
+                            </DropdownMenuTrigger>
+                            <DropdownMenuContent
+                              side="bottom"
+                              align="start"
+                              sideOffset={0}
+                              className="unsloth-plus-menu menu-flat-destructive w-56"
+                            >
+                              <DropdownMenuItem onSelect={() => openProject(project.id)}>
+                                <HugeiconsIcon icon={Folder01Icon} strokeWidth={1.75} className="size-icon" />
+                                <span>Project home</span>
+                              </DropdownMenuItem>
+                              <DropdownMenuItem onSelect={() => openNewChat(project.id)}>
+                                <HugeiconsIcon icon={PencilEdit02Icon} strokeWidth={1.75} className="size-icon" />
+                                <span>New chat</span>
+                              </DropdownMenuItem>
+                              <DropdownMenuItem
+                                onSelect={() => {
+                                  // Seed the shared draft so the dialog opens
+                                  // with the current name, not stale text.
+                                  setRenameDraft(project.name);
+                                  setRenamingTarget({
+                                    kind: "project",
+                                    project,
+                                    current: project.name,
+                                  });
+                                }}
+                              >
+                                <HugeiconsIcon icon={Edit03Icon} strokeWidth={1.75} className="size-icon" />
+                                <span>Rename project</span>
+                              </DropdownMenuItem>
+                              <DropdownMenuItem onSelect={() => unpinProject(project.id)}>
+                                <HugeiconsIcon icon={PinOffIcon} strokeWidth={1.75} className="size-icon" />
+                                <span>Unpin project</span>
+                              </DropdownMenuItem>
+                              <DropdownMenuSeparator />
+                              <DropdownMenuItem
+                                variant="destructive"
+                                onSelect={() => {
+                                  // Start each delete with the file toggle off:
+                                  // Cancel closes programmatically and skips the
+                                  // dialog onOpenChange reset.
+                                  setDeleteProjectFiles(false);
+                                  setConfirmingDelete({ kind: "project", project });
+                                }}
+                              >
+                                <HugeiconsIcon icon={Delete02Icon} strokeWidth={1.75} className="size-icon" />
+                                <span>Delete project</span>
+                              </DropdownMenuItem>
+                            </DropdownMenuContent>
+                          </DropdownMenu>
+                        </SidebarMenuItem>
+                        {expanded &&
+                          visibleChats.map((chat) =>
+                            renderChatSidebarItem(chat, "project"),
+                          )}
+                        {expanded &&
+                          projectChats.length > PINNED_PROJECT_CHAT_LIMIT && (
+                            <SidebarMenuItem>
+                              <SidebarMenuButton
+                                onClick={() => toggleProjectShowAll(project.id)}
+                                // Force the muted token: .sidebar-nav-btn's own
+                                // color rule outweighs a plain text utility, so
+                                // Show more would otherwise match the chat rows.
+                                className="sidebar-nav-btn h-[30px] rounded-full pl-9 pr-4 font-medium text-nav-fg-muted!"
+                              >
+                                <span className="text-ui-13 leading-ui-18 tracking-nav">
+                                  {showAll ? "Show less" : "Show more"}
+                                </span>
+                              </SidebarMenuButton>
+                            </SidebarMenuItem>
+                          )}
+                        </Fragment>
+                        );
+                      })}
+                      {pinnedChatItems.map((item) =>
+                        renderChatSidebarItem(item, "recent"),
+                      )}
+                    </SidebarMenu>
+                  </SidebarGroupContent>
+                </CollapsibleContent>
+              </SidebarGroup>
+            </Collapsible>
+          )}
 
         {!isStudioRoute && !showTrainingRecents && (
           <Collapsible open={chatOpen} onOpenChange={setChatOpen} asChild>
@@ -1402,7 +1711,7 @@ export function AppSidebar() {
                       >
                         <SidebarMenuButton
                           isActive={isActiveRun}
-                          className="sidebar-nav-btn h-auto flex-col items-start gap-0.5 py-[5px] rounded-[14px] pl-3 pr-7 text-[14.5px] tracking-nav font-medium"
+                          className="sidebar-nav-btn h-auto flex-col items-start gap-0.5 py-[5px] rounded-[14px] pl-3 pr-7 text-ui-14p5 tracking-nav font-medium"
                           onClick={() => {
                             setSelectedHistoryRunId(run.id);
                             // From Recipes/Export, jump to Train so the run's
@@ -1422,7 +1731,7 @@ export function AppSidebar() {
                             <span className="truncate">
                               {getTrainingRunDisplayTitle(run)}
                             </span>
-                            <span className="ml-auto mr-0.5 shrink-0 text-[10px] text-muted-foreground">
+                            <span className="ml-auto mr-0.5 shrink-0 text-ui-10 text-muted-foreground">
                               {formatRelativeShort(run.started_at)}
                             </span>
                           </div>
@@ -1523,11 +1832,11 @@ export function AppSidebar() {
                   />
                 </span>
                 <div className="flex min-w-0 flex-col gap-px leading-tight group-data-[collapsible=icon]:hidden">
-                  <span className="truncate font-heading text-[13.5px] font-semibold text-nav-fg">
+                  <span className="truncate font-heading text-ui-13p5 font-semibold text-nav-fg">
                     {t("shell.updateAvailable")}
                   </span>
                   {updateVersion && (
-                    <span className="truncate text-[11.5px] text-muted-foreground">
+                    <span className="truncate text-ui-11p5 text-muted-foreground">
                       v{updateVersion}
                     </span>
                   )}
@@ -1564,8 +1873,8 @@ export function AppSidebar() {
                   {/* min-w-0 so long names truncate instead of overflowing;
                       pr on the button reserves room for the settings cog */}
                   <div className="flex min-w-0 flex-1 flex-col gap-px leading-tight group-data-[collapsible=icon]:hidden">
-                    <span className="truncate font-heading text-[13.5px] tracking-[0.025em] dark:tracking-[0.04em] font-semibold text-nav-fg">{displayTitle}</span>
-                    <span className="truncate text-[11.5px] tracking-nav text-muted-foreground">Unsloth</span>
+                    <span className="truncate font-heading text-ui-13p5 tracking-[0.025em] dark:tracking-[0.04em] font-semibold text-nav-fg">{displayTitle}</span>
+                    <span className="truncate text-ui-11p5 tracking-nav text-muted-foreground">Unsloth</span>
                   </div>
                 </SidebarMenuButton>
               </DropdownMenuTrigger>
diff --git a/studio/frontend/src/components/assistant-ui/audio-player.tsx b/studio/frontend/src/components/assistant-ui/audio-player.tsx
index 8836eddff5..51ea646498 100644
--- a/studio/frontend/src/components/assistant-ui/audio-player.tsx
+++ b/studio/frontend/src/components/assistant-ui/audio-player.tsx
@@ -100,7 +100,7 @@ export const AudioPlayer: FC<AudioPlayerProps> = ({ src }) => {
           onChange={handleSeek}
           className="h-1.5 w-full cursor-pointer accent-primary"
         />
-        <div className="flex justify-between text-[10px] text-muted-foreground">
+        <div className="flex justify-between text-ui-10 text-muted-foreground">
           <span>{formatTime(progress)}</span>
           <span>{formatTime(duration)}</span>
         </div>
diff --git a/studio/frontend/src/components/assistant-ui/chat-dictation-bar.tsx b/studio/frontend/src/components/assistant-ui/chat-dictation-bar.tsx
new file mode 100644
index 0000000000..64b0b46735
--- /dev/null
+++ b/studio/frontend/src/components/assistant-ui/chat-dictation-bar.tsx
@@ -0,0 +1,231 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { Spinner } from "@/components/ui/spinner";
+import {
+  cancelActiveStudioDictation,
+  subscribeDictationLevel,
+} from "@/features/chat";
+import { useAui, useAuiState } from "@assistant-ui/react";
+import { CheckIcon, XIcon } from "lucide-react";
+import { type FC, useEffect, useRef, useState } from "react";
+import { TooltipIconButton } from "./tooltip-icon-button";
+
+// Dense row of dots that rise into centered recording bars.
+const BAR_COUNT = 84;
+// Peak height multiple for the loudest audio (dot is 4px). Under the 40px pill
+// so bars don't touch the edges.
+const MAX_SCALE = 8;
+// Time for a sample to slide one bar-width left (drift speed). Bars interpolate
+// between samples each frame, so a slower interval stays smooth.
+const PUSH_INTERVAL_MS = 165;
+// If no real mic level arrives for this long (e.g. Web Audio unavailable), fall
+// back to a gentle idle shimmer so the bar stays alive.
+const IDLE_AFTER_MS = 450;
+const WAVE_BAR_IDS = Array.from(
+  { length: BAR_COUNT },
+  (_, index) => `wave-bar-${index}`,
+);
+
+function formatElapsed(ms: number): string {
+  const total = Math.floor(ms / 1000);
+  const m = Math.floor(total / 60);
+  const s = total % 60;
+  return `${m}:${s.toString().padStart(2, "0")}`;
+}
+
+/**
+ * Recording UI shown in place of the composer input: a live waveform with
+ * discard and confirm on the right. Confirm transcribes; discard keeps the
+ * existing composer text.
+ */
+export const ChatDictationBar: FC = () => {
+  const aui = useAui();
+  const isDictating = useAuiState((s) => s.composer.dictation != null);
+  const [transcribing, setTranscribing] = useState(false);
+  const [elapsed, setElapsed] = useState(0);
+  const transcribingRef = useRef(false);
+  // Extra slot: newest sample lands here; the last visible bar slides toward it.
+  const barsRef = useRef<number[]>(new Array(BAR_COUNT + 1).fill(0));
+  const rowRef = useRef<HTMLDivElement | null>(null);
+
+  useEffect(() => {
+    if (!isDictating) {
+      return;
+    }
+
+    const startedAt = Date.now();
+    let peak = 0; // loudest level seen since the last waveform advance
+    let smoothed = 0;
+    let lastLevelAt = 0;
+    const barEls = rowRef.current
+      ? Array.from(rowRef.current.children).filter(
+          (el): el is HTMLElement => el instanceof HTMLElement,
+        )
+      : [];
+    // Paint the bars imperatively (not via React state) so the waveform does not
+    // thrash renders. The spans carry no style prop, so React never overwrites
+    // these transforms on an elapsed-timer re-render. At rest each is a round dot
+    // (scaleY 1); louder audio scales it into a thin centered bar.
+    for (const el of barEls) {
+      el.style.transform = "scaleY(1)";
+      el.style.opacity = "0.62";
+    }
+
+    // Push one new sample, dropping the oldest.
+    const commitSample = () => {
+      const bars = barsRef.current;
+      let level = peak;
+      peak = 0;
+      if (Date.now() - lastLevelAt > IDLE_AFTER_MS) {
+        level = 0.075 + 0.055 * (1 + Math.sin(Date.now() / 360));
+      }
+      // Quiet speech needs a perceptual lift. Fast attack, slower release:
+      // removes twitching while preserving clear peaks.
+      const visual = Math.min(1, Math.max(0, level) ** 0.62 * 1.45);
+      smoothed =
+        visual >= smoothed
+          ? smoothed * 0.2 + visual * 0.8
+          : smoothed * 0.78 + visual * 0.22;
+      bars.push(smoothed);
+      while (bars.length > BAR_COUNT + 1) {
+        bars.shift();
+      }
+    };
+
+    // Keep the loudest mic level between advances so downsampling to
+    // PUSH_INTERVAL_MS doesn't swallow peaks in quiet gaps.
+    const unsub = subscribeDictationLevel((level) => {
+      if (level > peak) {
+        peak = level;
+      }
+      lastLevelAt = Date.now();
+    });
+
+    // Repaint every frame; bars interpolate between samples so the wave glides.
+    // Timer updates at most once per second.
+    let lastPushAt = performance.now();
+    let shownSecond = -1;
+    let raf = 0;
+
+    const frame = () => {
+      raf = requestAnimationFrame(frame);
+      if (transcribingRef.current) {
+        return;
+      }
+
+      const now = performance.now();
+      const bars = barsRef.current;
+      let steps = 0;
+      while (now - lastPushAt >= PUSH_INTERVAL_MS && steps < BAR_COUNT + 1) {
+        commitSample();
+        lastPushAt += PUSH_INTERVAL_MS;
+        steps++;
+      }
+      // Drop stale backlog if rAF was paused (tab backgrounded).
+      if (now - lastPushAt >= PUSH_INTERVAL_MS) {
+        lastPushAt = now;
+      }
+
+      const phase = Math.min(1, (now - lastPushAt) / PUSH_INTERVAL_MS);
+      for (let i = 0; i < barEls.length; i++) {
+        // Bar i drifts toward its right neighbour as phase goes 0 to 1.
+        const a = bars[i] ?? 0;
+        const b = bars[i + 1] ?? a;
+        const v = a + (b - a) * phase;
+        barEls[i].style.transform = `scaleY(${1 + v * (MAX_SCALE - 1)})`;
+        barEls[i].style.opacity = `${0.62 + v * 0.38}`;
+      }
+
+      const elapsedMs = Date.now() - startedAt;
+      const second = Math.floor(elapsedMs / 1000);
+      if (second !== shownSecond) {
+        shownSecond = second;
+        setElapsed(elapsedMs);
+      }
+    };
+    raf = requestAnimationFrame(frame);
+
+    // Reset in cleanup (dictation end or unmount) so the next session starts
+    // fresh, without a synchronous setState in the effect body.
+    return () => {
+      unsub();
+      cancelAnimationFrame(raf);
+      transcribingRef.current = false;
+      setTranscribing(false);
+      setElapsed(0);
+      barsRef.current = new Array(BAR_COUNT + 1).fill(0);
+    };
+  }, [isDictating]);
+
+  if (!isDictating) {
+    return null;
+  }
+
+  const discard = () => {
+    cancelActiveStudioDictation();
+  };
+
+  const confirm = () => {
+    // Freeze the timer + waveform before the transcription round trip completes
+    // and the session ends.
+    transcribingRef.current = true;
+    setTranscribing(true);
+    aui.composer().stopDictation();
+  };
+
+  return (
+    <fieldset
+      // order-2 places the bar in the input's slot after the left "+" tools.
+      className="unsloth-dictation-bar order-2 m-0 flex min-w-0 flex-1 items-center gap-2 border-0 p-0"
+      aria-label="Voice recording"
+    >
+      <div
+        ref={rowRef}
+        aria-hidden="true"
+        className="unsloth-dictation-wave grid h-10 min-w-0 flex-1 items-center overflow-hidden px-2"
+        style={{
+          gridTemplateColumns: `repeat(${BAR_COUNT}, minmax(1px, 3px))`,
+          justifyContent: "space-between",
+        }}
+      >
+        {WAVE_BAR_IDS.map((barId) => (
+          <span
+            key={barId}
+            className="h-1 w-full origin-center rounded-full bg-foreground opacity-[0.62] will-change-transform"
+          />
+        ))}
+      </div>
+      <span className="shrink-0 tabular-nums text-sm text-muted-foreground">
+        {formatElapsed(elapsed)}
+      </span>
+      <div className="flex shrink-0 items-center gap-1">
+        <TooltipIconButton
+          type="button"
+          tooltip="Discard recording"
+          aria-label="Discard recording"
+          variant="ghost"
+          onClick={discard}
+          className="size-8 rounded-full text-muted-foreground hover:text-foreground"
+        >
+          <XIcon className="size-5" />
+        </TooltipIconButton>
+        <TooltipIconButton
+          type="button"
+          tooltip={transcribing ? "Transcribing…" : "Stop and transcribe"}
+          aria-label="Stop and transcribe"
+          variant="default"
+          onClick={confirm}
+          disabled={transcribing}
+          className="size-8 rounded-full"
+        >
+          {transcribing ? (
+            <Spinner className="size-4" />
+          ) : (
+            <CheckIcon className="size-5" />
+          )}
+        </TooltipIconButton>
+      </div>
+    </fieldset>
+  );
+};
diff --git a/studio/frontend/src/components/assistant-ui/message-response-details-sheet.tsx b/studio/frontend/src/components/assistant-ui/message-response-details-sheet.tsx
index cca61b766a..8b2e9e37ea 100644
--- a/studio/frontend/src/components/assistant-ui/message-response-details-sheet.tsx
+++ b/studio/frontend/src/components/assistant-ui/message-response-details-sheet.tsx
@@ -207,7 +207,7 @@ function DetailRow({
 }) {
   if (value == null || value === "") return null;
   return (
-    <div className="grid grid-cols-[8.5rem_minmax(0,1fr)] items-start gap-3 text-[13px]">
+    <div className="grid grid-cols-[8.5rem_minmax(0,1fr)] items-start gap-3 text-ui-13">
       <span className="text-muted-foreground">{label}</span>
       <span
         className={cn(
diff --git a/studio/frontend/src/components/assistant-ui/message-timing.tsx b/studio/frontend/src/components/assistant-ui/message-timing.tsx
index 8d40f587ad..e0a111820b 100644
--- a/studio/frontend/src/components/assistant-ui/message-timing.tsx
+++ b/studio/frontend/src/components/assistant-ui/message-timing.tsx
@@ -86,7 +86,7 @@ export const MessageTiming: FC<{
           data-slot="message-timing-trigger"
           aria-label="Message timing"
           className={cn(
-            "flex items-center rounded-[10px] p-1 font-mono text-chat-icon-fg text-[13px] tabular-nums transition-colors hover:bg-chat-icon-bg-hover hover:text-chat-icon-fg-hover",
+            "flex items-center rounded-[10px] p-1 font-mono text-chat-icon-fg text-ui-13 tabular-nums transition-colors hover:bg-chat-icon-bg-hover hover:text-chat-icon-fg-hover",
             className,
           )}
         >
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts b/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
deleted file mode 100644
index 08492ab480..0000000000
--- a/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
+++ /dev/null
@@ -1,79 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-// Per-model pre-load inference settings, persisted in localStorage so the load
-// dialog can offer "Remember settings for <model>". GGUF picks only: every
-// field is a llama.cpp load knob, so all save/restore call sites gate on
-// GGUF-ness (a non-GGUF blob would only snapshot leftover standing values).
-
-const KEY = "unsloth_load_settings";
-
-export interface RememberedLoadSettings {
-  contextLength: number | null;
-  kvCacheDtype: string | null;
-  speculativeType: string | null;
-  specDraftNMax: number | null;
-  tensorParallel: boolean;
-  // GPU Memory controls. Optional so an older blob (which lacked them) still
-  // parses, leaving the live knobs untouched on apply. The mode is kept with the
-  // manual knobs (gpuLayers/nCpuMoe are ignored outside Manual mode). A null
-  // selectedGpuIds is meaningful (all GPUs), so it's distinguished from absent.
-  // The per-GPU split ratio is deliberately NOT remembered: it's positionally
-  // bound to the exact GPU set/order and unvalidated, so it would mismatch.
-  gpuMemoryMode?: "auto" | "manual";
-  gpuLayers?: number;
-  nCpuMoe?: number;
-  selectedGpuIds?: number[] | null;
-}
-
-// Storage key for a pick's remembered settings, scoped per quant (the VRAM-budget
-// knobs differ per quant). An HF repo collapses its GGUF variants into one `id`,
-// so fold the variant in. Local .gguf paths are already file-specific; native
-// drag-drop files key by display label, so same-named files share an entry.
-export function rememberedLoadSettingsKey(selection: {
-  id: string;
-  ggufVariant?: string | null;
-}): string {
-  return selection.ggufVariant
-    ? `${selection.id}::${selection.ggufVariant}`
-    : selection.id;
-}
-
-function readAll(): Record<string, RememberedLoadSettings> {
-  try {
-    return JSON.parse(localStorage.getItem(KEY) ?? "{}");
-  } catch {
-    return {};
-  }
-}
-
-function writeAll(all: Record<string, RememberedLoadSettings>) {
-  try {
-    localStorage.setItem(KEY, JSON.stringify(all));
-  } catch {
-    // Ignore quota / unavailable storage.
-  }
-}
-
-export function loadRememberedLoadSettings(
-  key: string,
-): RememberedLoadSettings | null {
-  return readAll()[key] ?? null;
-}
-
-export function saveRememberedLoadSettings(
-  key: string,
-  settings: RememberedLoadSettings,
-) {
-  const all = readAll();
-  all[key] = settings;
-  writeAll(all);
-}
-
-export function clearRememberedLoadSettings(key: string) {
-  const all = readAll();
-  if (key in all) {
-    delete all[key];
-    writeAll(all);
-  }
-}
diff --git a/studio/frontend/src/components/assistant-ui/reasoning.tsx b/studio/frontend/src/components/assistant-ui/reasoning.tsx
index 9788c73605..97891e9358 100644
--- a/studio/frontend/src/components/assistant-ui/reasoning.tsx
+++ b/studio/frontend/src/components/assistant-ui/reasoning.tsx
@@ -163,7 +163,7 @@ function ReasoningContent({
     <CollapsibleContent
       data-slot="reasoning-content"
       className={cn(
-        "aui-reasoning-content relative overflow-hidden text-foreground/85 text-[13.5px] outline-none",
+        "aui-reasoning-content relative overflow-hidden text-foreground/85 text-ui-13p5 outline-none",
         "group/collapsible-content ease-out",
         "data-[state=closed]:animate-collapsible-up",
         "data-[state=open]:animate-collapsible-down",
diff --git a/studio/frontend/src/components/assistant-ui/sources.tsx b/studio/frontend/src/components/assistant-ui/sources.tsx
index 18c62fc87f..3a7bf14e45 100644
--- a/studio/frontend/src/components/assistant-ui/sources.tsx
+++ b/studio/frontend/src/components/assistant-ui/sources.tsx
@@ -52,7 +52,7 @@ function SourceIcon({
       <span
         data-slot="source-icon-fallback"
         className={cn(
-          `flex ${sizeClass} shrink-0 items-center justify-center rounded-sm bg-muted font-medium text-[10px]`,
+          `flex ${sizeClass} shrink-0 items-center justify-center rounded-sm bg-muted font-medium text-ui-10`,
           className,
         )}
         {...props}
diff --git a/studio/frontend/src/components/assistant-ui/thread.tsx b/studio/frontend/src/components/assistant-ui/thread.tsx
index 32fbd61e09..43a0c43950 100644
--- a/studio/frontend/src/components/assistant-ui/thread.tsx
+++ b/studio/frontend/src/components/assistant-ui/thread.tsx
@@ -34,6 +34,11 @@ import { RenderHtmlToolUI } from "@/components/assistant-ui/tool-ui-render-html"
 import { PythonToolUI } from "@/components/assistant-ui/tool-ui-python";
 import { TerminalToolUI } from "@/components/assistant-ui/tool-ui-terminal";
 import { WebSearchToolUI } from "@/components/assistant-ui/tool-ui-web-search";
+import { ChatDictationBar } from "@/components/assistant-ui/chat-dictation-bar";
+import {
+  isStudioDictationAvailable,
+  notifyStudioDictationUnavailable,
+} from "@/features/chat";
 import { TooltipIconButton } from "@/components/assistant-ui/tooltip-icon-button";
 import {
   IntentAwareScrollProvider,
@@ -102,6 +107,7 @@ import { applyQwenThinkingParams } from "@/features/chat/utils/qwen-params";
 import { isTauri } from "@/lib/api-base";
 import { copyToClipboard } from "@/lib/copy-to-clipboard";
 import { MicIcon } from "@/lib/mic-icon";
+import { downloadFile, isDownloadCancelled } from "@/lib/native-files";
 import { toast } from "@/lib/toast";
 import { Tick02Icon } from "@/lib/tick-icon";
 import { cn } from "@/lib/utils";
@@ -175,6 +181,7 @@ import {
 } from "react";
 import { create } from "zustand";
 import { extractTaggedText, updateThreadMessage } from "@/features/chat/utils/update-thread-message";
+import { useIsMobile } from "@/hooks/use-mobile";
 
 // True while a file is dragged anywhere over the chat page, so the composer
 // can show its "Drop files here" affordance.
@@ -1147,7 +1154,7 @@ const GeneratedImageViewportOverlay: FC<{
               Generated image
             </p>
             {overlay.metadata ? (
-              <p className="truncate text-[11px] font-medium text-muted-foreground">
+              <p className="truncate text-ui-11 font-medium text-muted-foreground">
                 {overlay.metadata}
               </p>
             ) : null}
@@ -1369,7 +1376,13 @@ export const ProjectComposer: FC<{
 }> = ({ disabled, placeholder }) => {
   return (
     <GeneratedImageOverlayProvider>
-      <ComposerAnimated disabled={disabled} placeholder={placeholder} />
+      {/* New chat in a project: queuing follow-ups here misbinds the thread,
+          so the queue only runs once the user is inside a chat session. */}
+      <ComposerAnimated
+        disabled={disabled}
+        placeholder={placeholder}
+        disableQueue
+      />
     </GeneratedImageOverlayProvider>
   );
 };
@@ -1379,11 +1392,17 @@ const ComposerAnimated: FC<{
   placeholder?: string;
   threadId?: string | null;
   menuSide?: "top" | "bottom";
-}> = ({ disabled, threadId, menuSide }) => {
+  disableQueue?: boolean;
+}> = ({ disabled, threadId, menuSide, disableQueue }) => {
   return (
     <div className="relative mx-auto min-w-0 w-full max-w-[46rem]">
       <div className="relative z-10 w-full">
-        <Composer disabled={disabled} threadId={threadId} menuSide={menuSide} />
+        <Composer
+          disabled={disabled}
+          threadId={threadId}
+          menuSide={menuSide}
+          disableQueue={disableQueue}
+        />
       </div>
     </div>
   );
@@ -1418,8 +1437,10 @@ const Composer: FC<{
   placeholder?: string;
   threadId?: string | null;
   menuSide?: "top" | "bottom";
-}> = ({ disabled, threadId, menuSide }) => {
+  disableQueue?: boolean;
+}> = ({ disabled, threadId, menuSide, disableQueue }) => {
   const aui = useAui();
+  const isDictating = useAuiState((s) => s.composer.dictation != null);
   const pageDragging = useContext(PageDragContext);
   const { overlay, closeOverlay } = useGeneratedImageOverlay();
   const setImageToolsEnabled = useChatRuntimeStore(
@@ -1435,14 +1456,16 @@ const Composer: FC<{
   const mcpEnabledForChat = useChatRuntimeStore((s) => s.mcpEnabledForChat);
   const ragEnabled = useChatRuntimeStore((s) => s.ragEnabled);
   // More than 4 pills: collapse to icons only. Search, Code, and permissions
-  // always show; Images, RAG, Canvas and MCP are conditional.
-  const pillsCompact =
+  // always show; Images, RAG, Canvas and MCP are conditional. Narrow viewports
+  // collapse too: the labelled row is wider than a phone-width composer.
+  const isMobile = useIsMobile();
+  const pillCount =
     3 +
-      (ragEnabled ? 1 : 0) +
-      (supportsBuiltinImageGeneration ? 1 : 0) +
-      (artifactsEnabled ? 1 : 0) +
-      (mcpEnabledForChat ? 1 : 0) >
-    4;
+    (ragEnabled ? 1 : 0) +
+    (supportsBuiltinImageGeneration ? 1 : 0) +
+    (artifactsEnabled ? 1 : 0) +
+    (mcpEnabledForChat ? 1 : 0);
+  const pillsCompact = isMobile || pillCount > 4;
   const activeThreadId = useChatRuntimeStore((s) => s.activeThreadId);
   const setPendingImageEditReference = useChatRuntimeStore(
     (s) => s.setPendingImageEditReference,
@@ -1725,6 +1748,11 @@ const Composer: FC<{
 
       if (threadIsRunning || promptQueueActive) {
         event.preventDefault();
+        // Project new-chat composer: never queue, just ask the user to wait.
+        if (disableQueue) {
+          toast.error("Wait for the current response to finish");
+          return;
+        }
         if (!canQueueCurrentPrompt) {
           if (overlay || hasAttachments || hasPendingAudio) {
             toast.error(
@@ -1802,6 +1830,7 @@ const Composer: FC<{
       composerText,
       createPromptQueueTarget,
       disabled,
+      disableQueue,
       hasAttachments,
       hasPendingAudio,
       interceptSend,
@@ -1821,85 +1850,113 @@ const Composer: FC<{
 
   const startQueue = useCallback(
     (items: string[], waitForCurrentRun = threadIsRunning) => {
+      // Saved-prompt Run-list calls this directly, so honour disableQueue here
+      // too: queuing from the project new-chat composer misbinds the thread.
+      if (disableQueue) return;
       startPromptQueue(items, createPromptQueueTarget(), waitForCurrentRun);
     },
-    [createPromptQueueTarget, threadIsRunning],
+    [createPromptQueueTarget, threadIsRunning, disableQueue],
   );
 
   const queueContextValue: PromptQueueCallbacks = { startQueue, stopQueue };
 
   const composerContent = (
     <>
-      <ComposerAttachments />
-      <PendingAudioChip />
-      <ThreadDocumentsBar
-        threadId={referenceThreadId}
-        onIndexingChange={handleIndexingChange}
-      />
-      <ToolStatusDisplay />
+      {!isDictating ? (
+        <>
+          <ComposerAttachments />
+          <PendingAudioChip />
+        </>
+      ) : null}
+      {/* Keep indexing state subscribed while dictating, but hide its chips so
+          the waveform stays the composer's only status indicator. */}
+      <div className={isDictating ? "hidden" : "contents"}>
+        <ThreadDocumentsBar
+          threadId={referenceThreadId}
+          onIndexingChange={handleIndexingChange}
+        />
+      </div>
+      {!isDictating ? <ToolStatusDisplay /> : null}
       <div
         className="unsloth-composer-line"
         // The permission pill is always visible, so keep the two-row layout
-        // expanded and leave the primary tool toggles accessible in every mode.
-        data-expanded="true"
+        // expanded whenever not dictating; dictation collapses to the bar.
+        data-expanded={!isDictating ? "true" : "false"}
+        data-dictating={isDictating ? "true" : undefined}
       >
         <div
           className="unsloth-composer-left"
           data-pill-compact={pillsCompact ? "true" : undefined}
         >
           <ComposerToolsMenu side={effectiveMenuSide} />
-          {/* Permission-level pill: always visible and opens the permission
-              level dropdown. */}
-          <PermissionModeComposerPill side={effectiveMenuSide} />
-          <WebSearchToggle />
-          <CodeToolsToggle />
-          <ImagesToggle />
-          <KnowledgeBaseComposerButton side={effectiveMenuSide} />
-          {artifactsEnabled ? <ArtifactsToggle /> : null}
-          {mcpEnabledForChat ? (
-            <McpComposerButton side={effectiveMenuSide} />
+          {/* While dictating, show only the "+"; hide the pill and tool toggles
+              so the waveform is the sole status indicator. */}
+          {!isDictating ? (
+            <>
+              {/* Permission-level pill: always visible, opens the level dropdown. */}
+              <PermissionModeComposerPill side={effectiveMenuSide} />
+              <WebSearchToggle />
+              <CodeToolsToggle />
+              <ImagesToggle />
+              <KnowledgeBaseComposerButton side={effectiveMenuSide} />
+              {artifactsEnabled ? <ArtifactsToggle /> : null}
+              {mcpEnabledForChat ? (
+                <McpComposerButton side={effectiveMenuSide} />
+              ) : null}
+            </>
           ) : null}
         </div>
-        <ComposerPrimitive.Input
-          placeholder={
-            overlay ? "Type your edits for your image" : "Ask anything"
-          }
-          ref={inputRef}
-          className="aui-composer-input unsloth-composer-input"
-          minRows={1}
-          maxRows={12}
-          autoFocus={!disabled}
-          disabled={disabled}
-          aria-label={overlay ? "Image edit instructions" : "Message input"}
-          // dir="auto": browser picks LTR/RTL from the first strong char;
-          // no effect on Latin / CJK / Devanagari.
-          dir="auto"
-          {...inputProps}
-        />
-        <ComposerRightControls
-          disabled={
-            disabled ||
-            !hasSendableContent ||
-            isComposing ||
-            hasPendingAttachments
-          }
-          queueDisabled={!canQueueCurrentPrompt}
-          onQueueClick={() => {
-            const queuedPrompt = composerText.trim();
-            if (queuedPrompt.length === 0) {
-              return;
-            }
-            flushResourcesSync(() => {
-              aui.composer().setText("");
-            });
-            startPromptQueue([queuedPrompt], createPromptQueueTarget(), true);
-          }}
-          onSendClick={interceptSend}
-          onStopClick={stopQueue}
-          pendingSend={pendingSend}
-          menuSide={effectiveMenuSide}
-          queueThreadIds={promptQueueThreadIds}
-        />
+        {isDictating ? (
+          // The recording UI replaces the input and send controls; only the
+          // left plus stays visible alongside it.
+          <ChatDictationBar />
+        ) : (
+          <>
+            <ComposerPrimitive.Input
+              placeholder={
+                overlay ? "Type your edits for your image" : "Ask anything"
+              }
+              ref={inputRef}
+              className="aui-composer-input unsloth-composer-input"
+              minRows={1}
+              maxRows={12}
+              autoFocus={!disabled}
+              disabled={disabled}
+              aria-label={overlay ? "Image edit instructions" : "Message input"}
+              // dir="auto": browser picks LTR/RTL from the first strong char;
+              // no effect on Latin / CJK / Devanagari.
+              dir="auto"
+              {...inputProps}
+            />
+            <ComposerRightControls
+              disabled={
+                disabled ||
+                !hasSendableContent ||
+                isComposing ||
+                hasPendingAttachments
+              }
+              // disableQueue (project new-chat composer) also blocks the queue
+              // button, so a running thread shows Stop instead of Queue.
+              queueDisabled={disableQueue || !canQueueCurrentPrompt}
+              onQueueClick={() => {
+                if (disableQueue) return;
+                const queuedPrompt = composerText.trim();
+                if (queuedPrompt.length === 0) {
+                  return;
+                }
+                flushResourcesSync(() => {
+                  aui.composer().setText("");
+                });
+                startPromptQueue([queuedPrompt], createPromptQueueTarget(), true);
+              }}
+              onSendClick={interceptSend}
+              onStopClick={stopQueue}
+              pendingSend={pendingSend}
+              menuSide={effectiveMenuSide}
+              queueThreadIds={promptQueueThreadIds}
+            />
+          </>
+        )}
       </div>
     </>
   );
@@ -2911,9 +2968,9 @@ const ComposerToolsMenu: FC<{ side?: "top" | "bottom" }> = ({
           <DropdownMenuItem
             onSelect={() => {
               if (!activeThreadId) return;
-              exportConversationRawJsonl(activeThreadId).catch(() =>
-                toast.error("Export failed."),
-              );
+              exportConversationRawJsonl(activeThreadId).catch((error) => {
+                if (!isDownloadCancelled(error)) toast.error("Export failed.");
+              });
             }}
           >
             Raw JSONL
@@ -2921,9 +2978,9 @@ const ComposerToolsMenu: FC<{ side?: "top" | "bottom" }> = ({
           <DropdownMenuItem
             onSelect={() => {
               if (!activeThreadId) return;
-              exportConversationCsv(activeThreadId).catch(() =>
-                toast.error("Export failed."),
-              );
+              exportConversationCsv(activeThreadId).catch((error) => {
+                if (!isDownloadCancelled(error)) toast.error("Export failed.");
+              });
             }}
           >
             CSV
@@ -2931,9 +2988,9 @@ const ComposerToolsMenu: FC<{ side?: "top" | "bottom" }> = ({
           <DropdownMenuItem
             onSelect={() => {
               if (!activeThreadId) return;
-              exportConversationShareGPT(activeThreadId).catch(() =>
-                toast.error("Export failed."),
-              );
+              exportConversationShareGPT(activeThreadId).catch((error) => {
+                if (!isDownloadCancelled(error)) toast.error("Export failed.");
+              });
             }}
           >
             ShareGPT JSONL
@@ -3333,32 +3390,36 @@ const ComposerRightControls: FC<{
     findPromptQueueEntry(s, queueThreadIds),
   );
   const isQueueRunning = Boolean(queueEntry);
+  const aui = useAui();
+  // Keep the mic clickable: if the engine can't run here, explain and point to
+  // the local model instead of disabling the button.
+  const startDictation = () => {
+    if (!isStudioDictationAvailable()) {
+      notifyStudioDictationUnavailable();
+      return;
+    }
+    try {
+      aui.composer().startDictation();
+    } catch {
+      notifyStudioDictationUnavailable();
+    }
+  };
   return (
     <div className="aui-composer-action-wrapper flex shrink-0 items-center gap-1.5">
       <ReasoningToggle side={menuSide} />
+      {/* Starts dictation; the recording bar then covers the input row and owns
+          the stop and discard actions. */}
       <ComposerPrimitive.If dictation={false}>
-        <ComposerPrimitive.Dictate asChild={true}>
-          <TooltipIconButton
-            tooltip="Dictate"
-            aria-label="Dictate"
-            variant="ghost"
-            className="size-8 rounded-full text-foreground"
-          >
-            <MicIcon className="size-5" />
-          </TooltipIconButton>
-        </ComposerPrimitive.Dictate>
-      </ComposerPrimitive.If>
-      <ComposerPrimitive.If dictation={true}>
-        <ComposerPrimitive.StopDictation asChild={true}>
-          <TooltipIconButton
-            tooltip="Stop dictation"
-            aria-label="Stop dictation"
-            variant="ghost"
-            className="size-8 rounded-full text-destructive"
-          >
-            <SquareIcon className="size-3 animate-pulse fill-current" />
-          </TooltipIconButton>
-        </ComposerPrimitive.StopDictation>
+        <TooltipIconButton
+          tooltip="Dictate"
+          aria-label="Dictate"
+          type="button"
+          variant="ghost"
+          className="size-8 rounded-full text-foreground"
+          onClick={startDictation}
+        >
+          <MicIcon className="size-5" />
+        </TooltipIconButton>
       </ComposerPrimitive.If>
       <AuiIf condition={({ thread }) => !thread.isRunning && !isQueueRunning}>
         <ComposerPrimitive.Send asChild={true}>
@@ -3516,14 +3577,14 @@ const DiffusionCanvas: FC = () => {
     canvas.total > 0 ? `step ${canvas.step + 1}/${canvas.total}` : "denoising";
   return (
     <div className="aui-diffusion-canvas my-1.5 overflow-hidden rounded-lg border border-primary/20 bg-primary/[0.03]">
-      <div className="flex items-center gap-2 border-b border-primary/10 px-3 py-1.5 text-[11px] font-medium text-primary/80">
+      <div className="flex items-center gap-2 border-b border-primary/10 px-3 py-1.5 text-ui-11 font-medium text-primary/80">
         <span className="inline-block size-1.5 animate-pulse rounded-full bg-primary" />
         <span>Denoising</span>
         <span className="opacity-60">
           block {canvas.block + 1} - {stepLabel}
         </span>
       </div>
-      <pre className="max-h-[60vh] overflow-auto whitespace-pre-wrap px-3 py-2 font-mono text-[12.5px] leading-relaxed text-foreground/90">
+      <pre className="max-h-[60vh] overflow-auto whitespace-pre-wrap px-3 py-2 font-mono text-ui-12p5 leading-relaxed text-foreground/90">
         {canvas.text}
       </pre>
     </div>
@@ -3597,7 +3658,7 @@ const AssistantMessage: FC = () => {
 
   return (
     <MessagePrimitive.Root
-      className="group/assistant-message aui-assistant-message-root relative mx-auto min-w-0 w-full max-w-(--thread-content-max-width) pt-0.5 pb-4 text-[15.5px] [font-weight:410] tracking-[0.01em] dark:tracking-[0.02em]"
+      className="group/assistant-message aui-assistant-message-root relative mx-auto min-w-0 w-full max-w-(--thread-content-max-width) pt-0.5 pb-4 text-ui-15p5 [font-weight:410] tracking-[0.01em] dark:tracking-[0.02em]"
       data-role="assistant"
     >
       <div className="aui-assistant-message-content wrap-break-word min-w-0 text-[#0d0d0d] dark:text-foreground leading-relaxed">
@@ -3710,7 +3771,7 @@ const ForkCountBadge: FC = () => {
   if (count <= 0) return null;
   return (
     <span
-      className="mx-1 inline-flex items-center gap-1 rounded-sm bg-primary/10 px-1.5 py-0.5 text-[10px] font-medium text-primary"
+      className="mx-1 inline-flex items-center gap-1 rounded-sm bg-primary/10 px-1.5 py-0.5 text-ui-10 font-medium text-primary"
       title={`${count} fork${count === 1 ? "" : "s"} from this message`}
     >
       <GitBranchIcon strokeWidth={1.75} className="size-3" />
@@ -3896,6 +3957,21 @@ const EditAssistantMessageButton: FC = () => {
   );
 };
 
+async function exportMessageMarkdown(content: string): Promise<void> {
+  try {
+    await downloadFile(
+      content,
+      `message-${Date.now()}.md`,
+      "text/markdown",
+    );
+  } catch (error) {
+    if (!isDownloadCancelled(error)) {
+      toast.error("Could not save Markdown export.", {
+        description: error instanceof Error ? error.message : String(error),
+      });
+    }
+  }
+}
 const AssistantActionBar: FC = () => {
   const { forkMessage, forkDisabled } = useForkMessageAction();
   const [detailsOpen, setDetailsOpen] = useState(false);
@@ -3964,7 +4040,10 @@ const AssistantActionBar: FC = () => {
               <GitBranchIcon strokeWidth={1.75} className="size-icon" />
               Fork in new chat
             </ActionBarMorePrimitive.Item>
-            <ActionBarPrimitive.ExportMarkdown asChild={true}>
+            <ActionBarPrimitive.ExportMarkdown
+              asChild={true}
+              onExport={exportMessageMarkdown}
+            >
               <ActionBarMorePrimitive.Item className="aui-action-bar-more-item flex cursor-pointer select-none items-center gap-2 rounded-[12px] px-3 py-2 text-sm outline-none hover:bg-accent hover:text-accent-foreground focus:bg-accent focus:text-accent-foreground">
                 <HugeiconsIcon
                   icon={Download01Icon}
@@ -4017,7 +4096,7 @@ const UserMessageAudio: FC = () => {
 const UserMessage: FC = () => {
   return (
     <MessagePrimitive.Root
-      className="aui-user-message-root fade-in slide-in-from-bottom-1 mx-auto flex w-full max-w-(--thread-content-max-width) animate-in flex-col items-end gap-y-2 pt-6 pb-4 text-[15.5px] [font-weight:410] tracking-[0.01em] dark:tracking-[0.02em] duration-150"
+      className="aui-user-message-root fade-in slide-in-from-bottom-1 mx-auto flex w-full max-w-(--thread-content-max-width) animate-in flex-col items-end gap-y-2 pt-6 pb-4 text-ui-15p5 [font-weight:410] tracking-[0.01em] dark:tracking-[0.02em] duration-150"
       data-role="user"
     >
       <UserMessageAttachments />
@@ -4128,7 +4207,7 @@ const BranchPicker: FC<BranchPickerPrimitive.Root.Props> = ({
     <BranchPickerPrimitive.Root
       hideWhenSingleBranch={true}
       className={cn(
-        "aui-branch-picker-root inline-flex items-center text-chat-icon-fg text-[13px]",
+        "aui-branch-picker-root inline-flex items-center text-chat-icon-fg text-ui-13",
         className,
       )}
       {...rest}
@@ -4142,7 +4221,7 @@ const BranchPicker: FC<BranchPickerPrimitive.Root.Props> = ({
           <ChevronLeftIcon strokeWidth={1.25} className="size-[36px]" />
         </button>
       </BranchPickerPrimitive.Previous>
-      <span className="aui-branch-picker-state font-mono text-[13px] tabular-nums">
+      <span className="aui-branch-picker-state font-mono text-ui-13 tabular-nums">
         <BranchPickerPrimitive.Number />/<BranchPickerPrimitive.Count />
       </span>
       <BranchPickerPrimitive.Next asChild={true}>
diff --git a/studio/frontend/src/components/assistant-ui/tool-ui-python.tsx b/studio/frontend/src/components/assistant-ui/tool-ui-python.tsx
index 1b3dd22000..1e816132b8 100644
--- a/studio/frontend/src/components/assistant-ui/tool-ui-python.tsx
+++ b/studio/frontend/src/components/assistant-ui/tool-ui-python.tsx
@@ -8,7 +8,7 @@ import { getAuthToken } from "@/features/auth/session";
 import type { ToolCallMessagePartComponent } from "@assistant-ui/react";
 import { useToolArgsStatus } from "@assistant-ui/react";
 import { code as codePlugin } from "@streamdown/code";
-import { CodeIcon, CopyIcon } from "lucide-react";
+import { CodeIcon, CopyIcon, DownloadIcon } from "lucide-react";
 import { Tick02Icon } from "@/lib/tick-icon";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { Spinner } from "@/components/ui/spinner";
@@ -83,22 +83,98 @@ function CopyBtn({ text }: { text: string }) {
   );
 }
 
-/** Syntax-highlighted code via Streamdown + shiki; inherits parent container. */
-function HighlightedCode({ code: source, language }: { code: string; language: string }) {
-  const markdown = useMemo(
-    () => `\`\`\`${language}\n${truncate(source)}\n\`\`\``,
-    [source, language],
-  );
+/** Save the executed script as a .py file via a client-side Blob (no server file serving). */
+function DownloadBtn({ code, name = "script.py" }: { code: string; name?: string }) {
+  const download = useCallback(() => {
+    if (typeof document === "undefined") {
+      return;
+    }
+    try {
+      const blob = new Blob([code], { type: "text/x-python" });
+      const url = URL.createObjectURL(blob);
+      const anchor = document.createElement("a");
+      anchor.href = url;
+      anchor.download = name;
+      document.body.appendChild(anchor);
+      anchor.click();
+      anchor.remove();
+      // Revoke next tick, after the click consumes the URL.
+      setTimeout(() => URL.revokeObjectURL(url), 0);
+    } catch {
+      // Best-effort: never break the transcript over a download.
+    }
+  }, [code, name]);
+
   return (
-    <div className="max-h-48 overflow-auto text-xs [&_pre]:!m-0 [&_pre]:!bg-transparent [&_pre]:!p-0 [&_pre]:!text-xs [&_[data-streamdown=code-block]]:!my-0 [&_[data-streamdown=code-block]]:!p-3 [&_[data-streamdown=code-block]]:!border-0">
-      <Streamdown
-        mode="static"
-        plugins={{ code: codePlugin }}
-        controls={{ code: false }}
-        shikiTheme={SHIKI_THEME}
-      >
-        {markdown}
-      </Streamdown>
+    <button
+      type="button"
+      onClick={download}
+      className="inline-flex items-center gap-1 rounded px-1.5 py-0.5 text-xs text-muted-foreground transition-colors hover:bg-muted hover:text-foreground"
+      aria-label="Download script"
+    >
+      <DownloadIcon className="size-3" />
+      Download
+    </button>
+  );
+}
+
+/** Syntax-highlighted code via Streamdown + shiki; inherits parent container.
+ * The script is always in the DOM (a plain monospace placeholder), but shiki
+ * only tokenizes once the block scrolls near the viewport, so a long transcript
+ * with many scripts doesn't highlight every one up front. Falls back to
+ * immediate highlight when IntersectionObserver is unavailable (SSR / tests). */
+function HighlightedCode({ code: source, language }: { code: string; language: string }) {
+  const display = useMemo(() => truncate(source), [source]);
+  const markdown = useMemo(
+    () => `\`\`\`${language}\n${display}\n\`\`\``,
+    [display, language],
+  );
+  const containerRef = useRef<HTMLDivElement>(null);
+  const [highlight, setHighlight] = useState(
+    () => typeof IntersectionObserver === "undefined",
+  );
+  useEffect(() => {
+    if (highlight) return;
+    const el = containerRef.current;
+    if (!el) return;
+    const io = new IntersectionObserver(
+      (entries) => {
+        if (entries.some((entry) => entry.isIntersecting)) {
+          setHighlight(true);
+          io.disconnect();
+        }
+      },
+      // Highlight just before the block enters view so it's colorized by the
+      // time the user reaches it, without tokenizing off-screen scripts.
+      { rootMargin: "200px" },
+    );
+    io.observe(el);
+    return () => io.disconnect();
+  }, [highlight]);
+  return (
+    <div
+      ref={containerRef}
+      className="max-h-48 overflow-auto text-xs [&_pre]:!m-0 [&_pre]:!bg-transparent [&_pre]:!p-0 [&_pre]:!text-xs [&_[data-streamdown=code-block]]:!my-0 [&_[data-streamdown=code-block]]:!p-3 [&_[data-streamdown=code-block]]:!border-0"
+    >
+      {highlight ? (
+        <Streamdown
+          mode="static"
+          plugins={{ code: codePlugin }}
+          controls={{ code: false }}
+          shikiTheme={SHIKI_THEME}
+        >
+          {markdown}
+        </Streamdown>
+      ) : (
+        // A div, not a <pre>: the container's [&_pre]:!p-0 would override a
+        // <pre>'s padding and shift the content by p-3 when shiki swaps in. Keep
+        // the same p-3, and whitespace-pre (not pre-wrap) so long lines scroll in
+        // the container's overflow-auto exactly like the highlighted <pre>, rather
+        // than wrapping taller and then collapsing when shiki swaps in.
+        <div className="whitespace-pre p-3 font-mono text-xs text-muted-foreground">
+          {display}
+        </div>
+      )}
     </div>
   );
 }
@@ -153,23 +229,32 @@ const PythonToolUIImpl: ToolCallMessagePartComponent = ({
   const authToken = getAuthToken();
 
   return (
-    // Open when mounted mid-run so live output shows; collapsed from history.
+    // Run status and output collapse from history, but the script source is
+    // rendered outside ToolFallbackContent so it stays visible on reopen (#7165).
     <ToolFallbackRoot defaultOpen={isRunning}>
       <ToolFallbackTrigger
         toolName={firstLine ? `Python: ${firstLine}` : "Python"}
         status={status}
         icon={CodeIcon}
       />
+      {code && (
+        <div className="mt-1 pl-5">
+          <div className="border-l-2 border-muted-foreground/20 pl-2">
+            <div className="flex items-center justify-between">
+              <span className="text-xs font-medium text-muted-foreground">
+                script
+              </span>
+              <div className="flex items-center gap-1">
+                <CopyBtn text={code} />
+                <DownloadBtn code={code} />
+              </div>
+            </div>
+            <HighlightedCode code={code} language="python" />
+          </div>
+        </div>
+      )}
       <ToolFallbackContent>
         <div className="border-l-2 border-muted-foreground/20 pl-2">
-          {/* Code + copy */}
-          {code && (
-            <div className="flex justify-end">
-              <CopyBtn text={code} />
-            </div>
-          )}
-          {code && <HighlightedCode code={code} language="python" />}
-
           {/* Output */}
           {isRunning ? (
             <>
diff --git a/studio/frontend/src/components/assistant-ui/tool-ui-render-html.tsx b/studio/frontend/src/components/assistant-ui/tool-ui-render-html.tsx
index 6ab0afad6f..d9c1fbaf6d 100644
--- a/studio/frontend/src/components/assistant-ui/tool-ui-render-html.tsx
+++ b/studio/frontend/src/components/assistant-ui/tool-ui-render-html.tsx
@@ -123,7 +123,7 @@ const RenderHtmlToolUIImpl: ToolCallMessagePartComponent = ({
                 ? "Canvas interrupted"
                 : "Canvas unavailable"}
           </span>
-          <span className="truncate text-[11px] leading-none text-muted-foreground">
+          <span className="truncate text-ui-11 leading-none text-muted-foreground">
             {errorText ??
               (isStaleGeneratingArtifact
                 ? "Refresh stopped this preview"
diff --git a/studio/frontend/src/components/floating-monitor.tsx b/studio/frontend/src/components/floating-monitor.tsx
index e38e2e5882..80501a518c 100644
--- a/studio/frontend/src/components/floating-monitor.tsx
+++ b/studio/frontend/src/components/floating-monitor.tsx
@@ -139,7 +139,7 @@ export function FloatingMonitor() {
               className="space-y-3 overflow-hidden"
             >
               <div className="space-y-1">
-                <div className="flex justify-between text-[11px] font-medium font-mono">
+                <div className="flex justify-between text-ui-11 font-medium font-mono">
                   <span>{t("settings.resources.liveMonitor.ram")}</span>
                   <span
                     className={cn("tabular-nums", usageTextClass(ramPercent))}
@@ -159,7 +159,7 @@ export function FloatingMonitor() {
 
               {hasGpu && (
                 <div className="space-y-1">
-                  <div className="flex justify-between text-[11px] font-medium font-mono">
+                  <div className="flex justify-between text-ui-11 font-medium font-mono">
                     <span className="truncate flex-1 pr-2">
                       {t("settings.resources.liveMonitor.vram")}{" "}
                       {devices.length > 1
diff --git a/studio/frontend/src/components/llama-update-banner.tsx b/studio/frontend/src/components/llama-update-banner.tsx
index 3db15ffe30..2729558630 100644
--- a/studio/frontend/src/components/llama-update-banner.tsx
+++ b/studio/frontend/src/components/llama-update-banner.tsx
@@ -93,16 +93,17 @@ export function LlamaUpdateBanner({
     });
 
   async function handleUpdate() {
+    const component = status?.component ?? "llama.cpp";
     const result = await apply();
     if (result?.ok) {
       const updatedTag = result.tag ?? status?.latest_tag ?? "the latest build";
       const reloadHint = result.reloadRequired
         ? " Reload your model to use it."
         : "";
-      toast.success(`llama.cpp updated to ${updatedTag}.${reloadHint}`);
+      toast.success(`${component} updated to ${updatedTag}.${reloadHint}`);
     } else if (result) {
       toast.error(
-        `llama.cpp update failed: ${result.error ?? "unknown error"}`,
+        `${component} update failed: ${result.error ?? "unknown error"}`,
       );
     }
   }
@@ -113,6 +114,7 @@ export function LlamaUpdateBanner({
     status != null &&
     (status.update_available || applying);
   const sizeBytes = status?.update_size_bytes ?? null;
+  const component = status?.component ?? "llama.cpp";
   const sizeLabel =
     sizeBytes && sizeBytes > 0
       ? `${Math.round(sizeBytes / (1024 * 1024))} MB`
@@ -142,7 +144,7 @@ export function LlamaUpdateBanner({
             type="button"
             onClick={dismiss}
             className="absolute top-2.5 right-3 flex size-6 items-center justify-center rounded-full text-muted-foreground/60 transition-colors hover:bg-muted hover:text-foreground"
-            aria-label="Dismiss llama.cpp update notification"
+            aria-label={`Dismiss ${component} update notification`}
           >
             <svg
               aria-hidden="true"
@@ -170,7 +172,7 @@ export function LlamaUpdateBanner({
           />
           <div className="min-w-0">
             <p className="font-heading text-base font-medium text-foreground">
-              {applying ? "Updating llama.cpp..." : "New llama.cpp update"}
+              {applying ? `Updating ${component}...` : `New ${component} update`}
             </p>
             <p className="mt-0.5 text-xs text-muted-foreground">
               {status?.installed_tag ?? "unknown"} &rarr;{" "}
@@ -178,7 +180,7 @@ export function LlamaUpdateBanner({
                 {status?.latest_tag ?? ""}
               </span>
             </p>
-            <p className="mt-1 text-[11px] text-muted-foreground/70">
+            <p className="mt-1 text-ui-11 text-muted-foreground/70">
               {sizeLabel ? `${sizeLabel} download · ` : ""}No restart needed
               after update
             </p>
@@ -189,7 +191,7 @@ export function LlamaUpdateBanner({
           <div
             className="mb-1.5 mt-4 h-1 overflow-hidden rounded-full bg-muted"
             role="progressbar"
-            aria-label="Updating llama.cpp"
+            aria-label={`Updating ${component}`}
             aria-valuemin={0}
             aria-valuemax={100}
             aria-valuenow={
@@ -209,7 +211,7 @@ export function LlamaUpdateBanner({
             <Button
               size="sm"
               variant="ghost"
-              className="h-auto rounded-full px-3 py-2 text-[13px] font-medium text-foreground"
+              className="h-auto rounded-full px-3 py-2 text-ui-13 font-medium text-foreground"
               onClick={snooze}
               data-testid="llama-update-snooze-button"
             >
@@ -218,7 +220,7 @@ export function LlamaUpdateBanner({
             <Button
               size="sm"
               // Align pill edge with card padding.
-              className="-mr-1 h-auto rounded-full px-3.5 py-2 text-[13px]"
+              className="-mr-1 h-auto rounded-full px-3.5 py-2 text-ui-13"
               onClick={handleUpdate}
               data-testid="llama-update-button"
             >
diff --git a/studio/frontend/src/components/navbar.tsx b/studio/frontend/src/components/navbar.tsx
index 44387f2480..1165705888 100644
--- a/studio/frontend/src/components/navbar.tsx
+++ b/studio/frontend/src/components/navbar.tsx
@@ -22,7 +22,7 @@ export function Navbar() {
     );
   }
   return (
-    <header className="absolute top-0 inset-x-0 z-40 h-[48px] pointer-events-none">
+    <header className="absolute top-0 inset-x-0 z-[45] h-[48px] pointer-events-none">
       <div className="flex h-full items-start pt-[11px] pl-2">
         <SidebarTrigger className="pointer-events-auto !size-[34px]" />
       </div>
diff --git a/studio/frontend/src/components/section-card.tsx b/studio/frontend/src/components/section-card.tsx
index e894749494..3720cf48bd 100644
--- a/studio/frontend/src/components/section-card.tsx
+++ b/studio/frontend/src/components/section-card.tsx
@@ -77,7 +77,7 @@ export function SectionCard({
           <div className="flex items-center gap-2 pb-1">
             <h3 className="text-sm font-semibold">{title}</h3>
             {badge && (
-              <span className="rounded-full bg-control-accent/15 px-2 py-0.5 text-[10px] font-semibold text-control-accent">
+              <span className="rounded-full bg-control-accent/15 px-2 py-0.5 text-ui-10 font-semibold text-control-accent">
                 {badge}
               </span>
             )}
diff --git a/studio/frontend/src/components/shutdown-dialog.tsx b/studio/frontend/src/components/shutdown-dialog.tsx
index e3e6ca9920..8f746c9414 100644
--- a/studio/frontend/src/components/shutdown-dialog.tsx
+++ b/studio/frontend/src/components/shutdown-dialog.tsx
@@ -52,8 +52,8 @@ export function ShutdownDialog({
     onAfterShutdown?.();
     document.body.innerHTML = `
       <div style="display:flex;flex-direction:column;align-items:center;justify-content:center;height:100vh;font-family:sans-serif;gap:12px">
-        <p style="font-size:1.1rem;font-weight:600;margin:0">Unsloth Studio has stopped.</p>
-        <p style="font-size:0.9rem;color:#888;margin:0">You can now close this tab.</p>
+        <p style="font-size:calc(1.1rem * var(--ui-font-scale, 1));font-weight:600;margin:0">Unsloth Studio has stopped.</p>
+        <p style="font-size:calc(0.9rem * var(--ui-font-scale, 1));color:#888;margin:0">You can now close this tab.</p>
       </div>`;
   };
 
diff --git a/studio/frontend/src/components/tauri/startup-screen.tsx b/studio/frontend/src/components/tauri/startup-screen.tsx
index 678051b36b..74ed2f2cbe 100644
--- a/studio/frontend/src/components/tauri/startup-screen.tsx
+++ b/studio/frontend/src/components/tauri/startup-screen.tsx
@@ -72,7 +72,7 @@ function DiagnosticsCopyActions({
           readOnly
           value={manualReport}
           onFocus={(event) => event.currentTarget.select()}
-          className="h-32 w-full max-w-md resize-none rounded-lg border border-border/50 bg-muted/30 p-2 font-mono text-[10px] text-muted-foreground"
+          className="h-32 w-full max-w-md resize-none rounded-lg border border-border/50 bg-muted/30 p-2 font-mono text-ui-10 text-muted-foreground"
         />
       )}
     </div>
diff --git a/studio/frontend/src/components/tauri/update-banner.tsx b/studio/frontend/src/components/tauri/update-banner.tsx
index 4fe8a54377..6f5e655889 100644
--- a/studio/frontend/src/components/tauri/update-banner.tsx
+++ b/studio/frontend/src/components/tauri/update-banner.tsx
@@ -142,7 +142,7 @@ export function UpdateBanner({
                     </span>
                   </p>
                 )}
-                <p className="mt-1 text-[11px] text-muted-foreground/70">
+                <p className="mt-1 text-ui-11 text-muted-foreground/70">
                   {showFailure
                     ? "Backend recovered. Diagnostics are still available."
                     : isManualLinuxPackage
@@ -166,7 +166,7 @@ export function UpdateBanner({
                   <Button
                     size="sm"
                     variant="ghost"
-                    className="h-auto rounded-full px-3 py-2 text-[13px] font-medium text-foreground"
+                    className="h-auto rounded-full px-3 py-2 text-ui-13 font-medium text-foreground"
                     onClick={() => {
                       handleCopyDiagnostics().catch(console.error);
                     }}
@@ -176,14 +176,14 @@ export function UpdateBanner({
                   <Button
                     size="sm"
                     variant="ghost"
-                    className="h-auto rounded-full px-3 py-2 text-[13px] font-medium text-foreground"
+                    className="h-auto rounded-full px-3 py-2 text-ui-13 font-medium text-foreground"
                     onClick={onDismiss}
                   >
                     Later
                   </Button>
                   <Button
                     size="sm"
-                    className="-mr-1 h-auto rounded-full px-3.5 py-2 text-[13px]"
+                    className="-mr-1 h-auto rounded-full px-3.5 py-2 text-ui-13"
                     onClick={onInstall}
                     disabled={installDisabled}
                   >
@@ -195,14 +195,14 @@ export function UpdateBanner({
                   <Button
                     size="sm"
                     variant="ghost"
-                    className="h-auto rounded-full px-3 py-2 text-[13px] font-medium text-foreground"
+                    className="h-auto rounded-full px-3 py-2 text-ui-13 font-medium text-foreground"
                     onClick={onDismiss}
                   >
                     Remind me later
                   </Button>
                   <Button
                     size="sm"
-                    className="-mr-1 h-auto rounded-full px-3.5 py-2 text-[13px]"
+                    className="-mr-1 h-auto rounded-full px-3.5 py-2 text-ui-13"
                     onClick={onInstall}
                     disabled={installDisabled}
                   >
@@ -219,7 +219,7 @@ export function UpdateBanner({
                 readOnly={true}
                 value={manualReport}
                 onFocus={(event) => event.currentTarget.select()}
-                className="mt-2 h-28 w-full resize-none rounded-lg border border-border/50 bg-muted/30 p-2 font-mono text-[10px] text-muted-foreground"
+                className="mt-2 h-28 w-full resize-none rounded-lg border border-border/50 bg-muted/30 p-2 font-mono text-ui-10 text-muted-foreground"
               />
             )}
           </div>
diff --git a/studio/frontend/src/components/tauri/update-screen.tsx b/studio/frontend/src/components/tauri/update-screen.tsx
index 3199425f69..d37e6873ae 100644
--- a/studio/frontend/src/components/tauri/update-screen.tsx
+++ b/studio/frontend/src/components/tauri/update-screen.tsx
@@ -72,7 +72,7 @@ function LogViewer({ logs }: { logs: string[] }) {
   return (
     <div
       ref={scrollRef}
-      className="mt-4 h-[180px] w-full max-w-xl overflow-y-auto rounded-lg border border-border/40 bg-muted/30 p-3 font-mono text-[11px] leading-relaxed text-muted-foreground"
+      className="mt-4 h-[180px] w-full max-w-xl overflow-y-auto rounded-lg border border-border/40 bg-muted/30 p-3 font-mono text-ui-11 leading-relaxed text-muted-foreground"
     >
       {logs.map((line, i) => (
         <div key={i} className="whitespace-pre-wrap break-all">
@@ -197,7 +197,7 @@ export function UpdateScreen({
             readOnly
             value={manualReport}
             onFocus={(event) => event.currentTarget.select()}
-            className="mt-2 h-32 w-full max-w-xl resize-none rounded-lg border border-border/50 bg-muted/30 p-2 font-mono text-[10px] text-muted-foreground"
+            className="mt-2 h-32 w-full max-w-xl resize-none rounded-lg border border-border/50 bg-muted/30 p-2 font-mono text-ui-10 text-muted-foreground"
           />
         )}
 
diff --git a/studio/frontend/src/components/tauri/window-titlebar.tsx b/studio/frontend/src/components/tauri/window-titlebar.tsx
index d86af54f79..6a0ff8741a 100644
--- a/studio/frontend/src/components/tauri/window-titlebar.tsx
+++ b/studio/frontend/src/components/tauri/window-titlebar.tsx
@@ -40,7 +40,7 @@ type NavigatorWithUserAgentData = Navigator & {
   };
 };
 
-function getClientPlatform(): string {
+export function getClientPlatform(): string {
   if (typeof navigator === "undefined") {
     return "";
   }
@@ -115,7 +115,7 @@ export function WindowTitlebar({
       ? "var(--studio-sidebar-expanded-width,17.5rem)"
       : "var(--studio-sidebar-collapsed-width,3rem)"
     : "0px";
-  const contentBorderLeft = `calc(${sidebarWidth} + 12px)`;
+  const contentBorderLeft = pinned ? `calc(${sidebarWidth} + 12px)` : "0px";
 
   const refreshMaximized = useCallback(async () => {
     if (!enabled) {
@@ -232,10 +232,10 @@ export function WindowTitlebar({
         )}
         aria-label="Window titlebar"
       >
-        {showSidebarSurface && (
+        {showSidebarSurface && pinned && (
           <div
             aria-hidden="true"
-            className="pointer-events-none absolute top-full h-3 w-px -translate-x-px bg-sidebar"
+            className="pointer-events-none absolute top-full size-3 -translate-x-px bg-sidebar"
             style={{ left: sidebarWidth }}
           />
         )}
@@ -246,7 +246,7 @@ export function WindowTitlebar({
             style={{ left: contentBorderLeft, right: 0 }}
           />
         )}
-        {showSidebarSurface && (
+        {showSidebarSurface && pinned && (
           <div
             aria-hidden="true"
             className="pointer-events-none absolute top-full size-3 -translate-x-px rounded-tl-[12px] border-l border-t border-sidebar-border bg-background"
@@ -257,7 +257,7 @@ export function WindowTitlebar({
           <div
             className={cn(
               "pointer-events-auto absolute left-0 top-0 flex h-full min-w-0 items-center",
-              pinned ? "gap-2 px-3" : "justify-center",
+              pinned ? "gap-2 pl-3" : "justify-center",
             )}
             style={{ width: sidebarWidth }}
             onMouseDown={handleDragMouseDown}
@@ -273,7 +273,7 @@ export function WindowTitlebar({
                     draggable={false}
                     className="size-5 shrink-0 rounded-[6px] object-cover"
                   />
-                  <span className="min-w-0 truncate text-[13px] font-semibold leading-none tracking-[0.01em] text-nav-fg">
+                  <span className="min-w-0 truncate text-ui-13 font-semibold leading-none tracking-[0.01em] text-nav-fg">
                     Unsloth Studio
                   </span>
                 </div>
diff --git a/studio/frontend/src/components/ui/calendar.tsx b/studio/frontend/src/components/ui/calendar.tsx
index 6ace64bed6..6ea80b9c88 100644
--- a/studio/frontend/src/components/ui/calendar.tsx
+++ b/studio/frontend/src/components/ui/calendar.tsx
@@ -93,7 +93,7 @@ function Calendar({
         table: "w-full border-collapse",
         weekdays: cn("flex", defaultClassNames.weekdays),
         weekday: cn(
-          "text-muted-foreground rounded-(--cell-radius) flex-1 font-normal text-[0.8rem] select-none",
+          "text-muted-foreground rounded-(--cell-radius) flex-1 font-normal text-[calc(0.8rem*var(--ui-font-scale,1))] select-none",
           defaultClassNames.weekday,
         ),
         week: cn("flex w-full mt-2", defaultClassNames.week),
@@ -102,7 +102,7 @@ function Calendar({
           defaultClassNames.week_number_header,
         ),
         week_number: cn(
-          "text-[0.8rem] select-none text-muted-foreground",
+          "text-[calc(0.8rem*var(--ui-font-scale,1))] select-none text-muted-foreground",
           defaultClassNames.week_number,
         ),
         day: cn(
diff --git a/studio/frontend/src/components/ui/combobox.tsx b/studio/frontend/src/components/ui/combobox.tsx
index 11ba03a3e8..07202d30ae 100644
--- a/studio/frontend/src/components/ui/combobox.tsx
+++ b/studio/frontend/src/components/ui/combobox.tsx
@@ -7,6 +7,7 @@
 
 import { Combobox as ComboboxPrimitive } from "@base-ui/react";
 import * as React from "react";
+import { useWheelScrollRef } from "@/hooks";
 import { createContext, useState } from "react";
 
 import { Button } from "@/components/ui/button";
@@ -100,13 +101,19 @@ function ComboboxInput({
   disabled = false,
   showTrigger = true,
   showClear = false,
+  startAddon,
   ...props
 }: ComboboxPrimitive.Input.Props & {
   showTrigger?: boolean;
   showClear?: boolean;
+  /** Optional leading content (e.g. a search icon) rendered before the input. */
+  startAddon?: React.ReactNode;
 }): React.ReactElement {
   return (
     <InputGroup className={cn("w-auto", className)}>
+      {startAddon && (
+        <InputGroupAddon align="inline-start">{startAddon}</InputGroupAddon>
+      )}
       <ComboboxPrimitive.Input
         render={<InputGroupInput disabled={disabled} />}
         {...props}
@@ -195,8 +202,11 @@ function ComboboxList({
   className,
   ...props
 }: ComboboxPrimitive.List.Props): React.ReactElement {
+  const listRef = useWheelScrollRef<HTMLDivElement>();
+
   return (
     <ComboboxPrimitive.List
+      ref={listRef}
       data-slot="combobox-list"
       className={cn(
         "no-scrollbar max-h-[min(calc(--spacing(72)---spacing(9)),calc(var(--available-height)---spacing(9)))] scroll-py-1 overflow-y-auto p-1 data-empty:p-0 overflow-y-auto overscroll-contain",
diff --git a/studio/frontend/src/components/ui/copyable-error-chip.tsx b/studio/frontend/src/components/ui/copyable-error-chip.tsx
index 595df5cf62..b9759f111c 100644
--- a/studio/frontend/src/components/ui/copyable-error-chip.tsx
+++ b/studio/frontend/src/components/ui/copyable-error-chip.tsx
@@ -72,7 +72,7 @@ export function CopyableErrorChip({
             onClick={handleCopy}
             aria-label={copied ? "Copied" : "Copy error message"}
             className={cn(
-              "inline-flex items-center gap-1 rounded-md border border-border/60 px-2 py-1 text-[11px] text-muted-foreground transition-colors hover:bg-muted/60 focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+              "inline-flex items-center gap-1 rounded-md border border-border/60 px-2 py-1 text-ui-11 text-muted-foreground transition-colors hover:bg-muted/60 focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
               copied && "border-emerald-500/40 text-emerald-600 dark:text-emerald-500",
             )}
           >
diff --git a/studio/frontend/src/components/ui/data-table.tsx b/studio/frontend/src/components/ui/data-table.tsx
index 31a93b7449..391007b2e6 100644
--- a/studio/frontend/src/components/ui/data-table.tsx
+++ b/studio/frontend/src/components/ui/data-table.tsx
@@ -100,7 +100,7 @@ export function DataTable<TData, TValue>({
                 {row.getVisibleCells().map((cell) => (
                   <TableCell
                     key={cell.id}
-                    className="border-r border-border/20 last:border-r-0 text-[13px] py-3 px-4 align-top whitespace-normal"
+                    className="border-r border-border/20 last:border-r-0 text-ui-13 py-3 px-4 align-top whitespace-normal"
                   >
                     {flexRender(cell.column.columnDef.cell, cell.getContext())}
                   </TableCell>
diff --git a/studio/frontend/src/components/ui/dropdown-menu.tsx b/studio/frontend/src/components/ui/dropdown-menu.tsx
index ea6dbbb6e7..65cf123965 100644
--- a/studio/frontend/src/components/ui/dropdown-menu.tsx
+++ b/studio/frontend/src/components/ui/dropdown-menu.tsx
@@ -39,6 +39,7 @@ function DropdownMenuContent({
   className,
   align = "start",
   sideOffset = 0,
+  children,
   ...props
 }: React.ComponentProps<typeof DropdownMenuPrimitive.Content>) {
   return (
@@ -51,11 +52,21 @@ function DropdownMenuContent({
           // The 3px alignment nudge must be margin, not translate: a transform
           // here makes this scroll container the containing block for nested
           // position:fixed submenu wrappers, clipping every submenu.
-          "data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 bg-popover text-popover-foreground min-w-48 rounded-lg p-1 duration-100 z-50 max-h-(--radix-dropdown-menu-content-available-height) w-[calc(var(--radix-dropdown-menu-trigger-width)_+_6px)] data-[align=start]:-ml-[3px] data-[align=end]:ml-[3px] origin-(--radix-dropdown-menu-content-transform-origin) overflow-x-hidden overflow-y-auto data-[state=closed]:overflow-hidden",
+          "data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 bg-popover text-popover-foreground min-w-48 rounded-lg p-1 duration-100 z-50 max-h-(--radix-dropdown-menu-content-available-height) w-[calc(var(--radix-dropdown-menu-trigger-width)_+_6px)] data-[align=start]:-ml-[3px] data-[align=end]:ml-[3px] origin-(--radix-dropdown-menu-content-transform-origin) flex flex-col overflow-hidden",
           className,
         )}
         {...props}
-      />
+      >
+        {/* Scroll an inner viewport, not the rounded surface: a scrollbar on
+            the surface squares its corners in WebKit. The surface padding
+            insets the scrollbar clear of the curve. */}
+        <div
+          data-slot="dropdown-menu-viewport"
+          className="min-h-0 flex-1 overflow-x-hidden overflow-y-auto"
+        >
+          {children}
+        </div>
+      </DropdownMenuPrimitive.Content>
     </DropdownMenuPrimitive.Portal>
   );
 }
@@ -307,7 +318,7 @@ function DropdownMenuSubContent({
             isMobile && contentWidth === 0 ? "hidden" : style?.visibility,
         }}
         className={cn(
-          "data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 bg-popover text-popover-foreground min-w-36 max-w-[calc(100vw-2rem)] rounded-lg p-1 duration-100 z-50 origin-(--radix-dropdown-menu-content-transform-origin) overflow-hidden",
+          "data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 bg-popover text-popover-foreground min-w-36 max-w-[calc(100vw-32px)] rounded-lg p-1 duration-100 z-50 origin-(--radix-dropdown-menu-content-transform-origin) overflow-hidden",
           className,
         )}
         {...props}
diff --git a/studio/frontend/src/components/ui/input-group.tsx b/studio/frontend/src/components/ui/input-group.tsx
index 55984452f0..7ec7a2e3d4 100644
--- a/studio/frontend/src/components/ui/input-group.tsx
+++ b/studio/frontend/src/components/ui/input-group.tsx
@@ -122,7 +122,7 @@ function InputGroupInput({
     <Input
       data-slot="input-group-control"
       className={cn(
-        "rounded-none border-0 bg-transparent shadow-none ring-0 focus-visible:ring-0 aria-invalid:ring-0 dark:bg-transparent flex-1",
+        "rounded-none border-0 bg-transparent shadow-none ring-0 focus-visible:ring-0 aria-invalid:ring-0 dark:bg-transparent dark:focus-visible:bg-transparent flex-1",
         className,
       )}
       {...props}
diff --git a/studio/frontend/src/components/ui/select.tsx b/studio/frontend/src/components/ui/select.tsx
index 925cc45b36..1bb95848f7 100644
--- a/studio/frontend/src/components/ui/select.tsx
+++ b/studio/frontend/src/components/ui/select.tsx
@@ -126,7 +126,7 @@ function SelectContent({
         data-slot="select-content"
         data-align-trigger={position === "item-aligned"}
         className={cn(
-          "bg-popover text-popover-foreground font-heading data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 min-w-36 rounded-xl p-1 corner-squircle duration-100 relative z-50 max-h-(--radix-select-content-available-height) origin-(--radix-select-content-transform-origin) overflow-x-hidden overflow-y-auto ",
+          "bg-popover text-popover-foreground font-heading data-open:animate-in data-closed:animate-out data-closed:fade-out-0 data-open:fade-in-0 data-closed:zoom-out-95 data-open:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 min-w-36 rounded-xl p-1 corner-squircle duration-100 relative z-50 max-h-(--radix-select-content-available-height) origin-(--radix-select-content-transform-origin) flex flex-col overflow-hidden",
           // No popper translate offset: the menu sits flush against the trigger.
           className,
         )}
@@ -135,10 +135,18 @@ function SelectContent({
         {...props}
       >
         <SelectScrollUpButton />
+        {/* The Radix viewport is the scroller (not the rounded surface, whose
+            scrollbar would square its corners in WebKit; not a wrapper, which
+            would blind Radix's scroll handling). The surface padding insets
+            the scrollbar clear of the curve. */}
         <SelectPrimitive.Viewport
           data-position={position}
+          // Inline: Radix injects a scrollbar-width:none stylesheet rule that
+          // Firefox lets win over author !important.
+          style={{ scrollbarWidth: "thin" }}
           className={cn(
-            "data-[position=popper]:h-[var(--radix-select-trigger-height)] data-[position=popper]:w-full data-[position=popper]:min-w-[var(--radix-select-trigger-width)]",
+            "min-h-0 flex-1 overflow-x-hidden overflow-y-auto",
+            "data-[position=popper]:w-full data-[position=popper]:min-w-[var(--radix-select-trigger-width)]",
             position === "popper" && "",
           )}
         >
diff --git a/studio/frontend/src/components/ui/sidebar.tsx b/studio/frontend/src/components/ui/sidebar.tsx
index 4eb37d4e89..0fe82eb428 100644
--- a/studio/frontend/src/components/ui/sidebar.tsx
+++ b/studio/frontend/src/components/ui/sidebar.tsx
@@ -471,7 +471,7 @@ function SidebarGroupLabel({
       data-slot="sidebar-group-label"
       data-sidebar="group-label"
       className={cn(
-        "text-[#94a3b8] dark:text-[#666] ring-sidebar-ring h-auto pt-3 pb-2 px-4 rounded-md text-[10px] font-semibold uppercase tracking-[0em] group-data-[collapsible=icon]:-mt-8 group-data-[collapsible=icon]:opacity-0 focus-visible:ring-1 [&>svg]:size-3 flex shrink-0 items-center outline-hidden [&>svg]:shrink-0",
+        "text-[#94a3b8] dark:text-[#666] ring-sidebar-ring h-auto pt-3 pb-2 px-4 rounded-md text-ui-10 font-semibold uppercase tracking-[0em] group-data-[collapsible=icon]:-mt-8 group-data-[collapsible=icon]:opacity-0 focus-visible:ring-1 [&>svg]:size-3 flex shrink-0 items-center outline-hidden [&>svg]:shrink-0",
         className
       )}
       {...props}
diff --git a/studio/frontend/src/components/web/update-banner.tsx b/studio/frontend/src/components/web/update-banner.tsx
index 55ef06166b..d8ae92bf5f 100644
--- a/studio/frontend/src/components/web/update-banner.tsx
+++ b/studio/frontend/src/components/web/update-banner.tsx
@@ -132,7 +132,7 @@ export function WebUpdateBanner({
                 href={RELEASE_NOTES_URL}
                 target="_blank"
                 rel="noopener noreferrer"
-                className="-ml-2 whitespace-nowrap rounded-full px-2.5 py-2 text-[13px] font-medium text-foreground transition-colors hover:bg-muted"
+                className="-ml-2 whitespace-nowrap rounded-full px-2.5 py-2 text-ui-13 font-medium text-foreground transition-colors hover:bg-muted"
                 data-testid="web-update-release-notes-link"
               >
                 Release notes
@@ -142,7 +142,7 @@ export function WebUpdateBanner({
                 <Button
                   size="sm"
                   variant="ghost"
-                  className="h-auto rounded-full px-3 py-2 text-[13px] font-medium text-foreground"
+                  className="h-auto rounded-full px-3 py-2 text-ui-13 font-medium text-foreground"
                   onClick={snooze}
                   data-testid="web-update-snooze-button"
                 >
@@ -151,7 +151,7 @@ export function WebUpdateBanner({
                 <Button
                   size="sm"
                   // -mr optically aligns the filled pill's edge with the card padding
-                  className="-mr-1 h-auto rounded-full px-3.5 py-2 text-[13px]"
+                  className="-mr-1 h-auto rounded-full px-3.5 py-2 text-ui-13"
                   onClick={handleCopyCommand}
                   data-testid="web-update-copy-button"
                 >
diff --git a/studio/frontend/src/config/training.ts b/studio/frontend/src/config/training.ts
index 873e9aa203..10f7e93e5e 100644
--- a/studio/frontend/src/config/training.ts
+++ b/studio/frontend/src/config/training.ts
@@ -92,6 +92,19 @@ export const OPTIMIZER_OPTIONS: ReadonlyArray<{ value: string; label: string }>
   { value: "adamw_torch_fused", label: "AdamW (PyTorch Fused)" },
 ];
 
+// Optimizers the MLX trainer actually supports on Apple Silicon. Values must
+// match SUPPORTED_MLX_OPTIMIZERS in unsloth-zoo's mlx/trainer.py; on MLX the
+// bitsandbytes/torch names above have no meaning and are remapped to plain
+// AdamW, so Studio offers this list instead when running on a Mac.
+export const MLX_OPTIMIZER_OPTIONS: ReadonlyArray<{ value: string; label: string }> = [
+  { value: "adamw", label: "AdamW" },
+  { value: "adam", label: "Adam" },
+  { value: "lion", label: "Lion" },
+  { value: "muon", label: "Muon" },
+  { value: "sgd", label: "SGD" },
+  { value: "adafactor", label: "Adafactor" },
+];
+
 export const LR_SCHEDULER_OPTIONS: ReadonlyArray<{ value: string; label: string }> = [
   { value: "linear", label: "Linear" },
   { value: "cosine", label: "Cosine" },
diff --git a/studio/frontend/src/features/auth/components/auth-form.tsx b/studio/frontend/src/features/auth/components/auth-form.tsx
index 73db10d41b..72181b8e4f 100644
--- a/studio/frontend/src/features/auth/components/auth-form.tsx
+++ b/studio/frontend/src/features/auth/components/auth-form.tsx
@@ -196,8 +196,10 @@ export function AuthForm({ mode }: AuthFormProps): ReactElement | null {
     !isLoginMode &&
     (currentPassword.length < 8 ||
       newPassword.length < 8 ||
+      /\s/.test(newPassword) ||
       newPassword !== confirmPassword ||
       currentPassword === newPassword);
+  const showWhitespaceWarning = !isLoginMode && /\s/.test(newPassword);
   const showPasswordMismatchWarning =
     !isLoginMode &&
     newPassword.length > 0 &&
@@ -222,6 +224,10 @@ export function AuthForm({ mode }: AuthFormProps): ReactElement | null {
         setError("New password must be at least 8 characters.");
         return;
       }
+      if (/\s/.test(newPassword)) {
+        setError("New password cannot contain spaces.");
+        return;
+      }
       if (newPassword !== confirmPassword) {
         setError("Passwords do not match.");
         return;
@@ -425,13 +431,17 @@ export function AuthForm({ mode }: AuthFormProps): ReactElement | null {
             </div>
             <p
               className={`min-h-4 text-xs ${
-                showPasswordMismatchWarning ? "text-destructive" : "text-muted-foreground"
+                showWhitespaceWarning || showPasswordMismatchWarning
+                  ? "text-destructive"
+                  : "text-muted-foreground"
               }`}
               aria-live="polite"
             >
-              {showPasswordMismatchWarning
-                ? "Please ensure passwords match."
-                : "Must be at least 8 characters."}
+              {showWhitespaceWarning
+                ? "New password cannot contain spaces."
+                : showPasswordMismatchWarning
+                  ? "Please ensure passwords match."
+                  : "Must be at least 8 characters."}
             </p>
           </>
         )}
@@ -439,7 +449,11 @@ export function AuthForm({ mode }: AuthFormProps): ReactElement | null {
         {helperText && (
           <p className="text-center text-sm text-amber-600">{helperText}</p>
         )}
-        {error && <p className="text-center text-sm text-destructive">{error}</p>}
+        {error && (
+          <p className="text-center text-sm text-destructive [overflow-wrap:anywhere]">
+            {error}
+          </p>
+        )}
 
         <Button
           type="submit"
diff --git a/studio/frontend/src/features/chat/adapters/dictation-level.ts b/studio/frontend/src/features/chat/adapters/dictation-level.ts
new file mode 100644
index 0000000000..e38060ba0e
--- /dev/null
+++ b/studio/frontend/src/features/chat/adapters/dictation-level.ts
@@ -0,0 +1,91 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+type LevelListener = (level: number) => void;
+type FrameListener = (rawRms: number, now: number) => void;
+
+const levelListeners = new Set<LevelListener>();
+
+/** Subscribe to the live microphone level (0..1) during dictation. */
+export function subscribeDictationLevel(listener: LevelListener): () => void {
+  levelListeners.add(listener);
+  return () => {
+    levelListeners.delete(listener);
+  };
+}
+
+function publishLevel(level: number): void {
+  for (const listener of levelListeners) {
+    listener(level);
+  }
+}
+
+/**
+ * Start a lightweight Web Audio meter for the shared recording waveform and
+ * optional voice-activity detection. Returns an idempotent cleanup function.
+ */
+export function startDictationLevelMeter(
+  source: MediaStream,
+  onFrame?: FrameListener,
+): () => void {
+  let audioContext: AudioContext | null = null;
+  let levelRaf = 0;
+  let stopped = false;
+
+  const stop = () => {
+    if (stopped) {
+      return;
+    }
+    stopped = true;
+    if (levelRaf) {
+      cancelAnimationFrame(levelRaf);
+    }
+    levelRaf = 0;
+    audioContext?.close().catch(() => {
+      // A closing or already-closed context is harmless.
+    });
+    audioContext = null;
+    publishLevel(0);
+  };
+
+  try {
+    const Ctx =
+      window.AudioContext ||
+      (window as unknown as { webkitAudioContext?: typeof AudioContext })
+        .webkitAudioContext;
+    if (!Ctx) {
+      return stop;
+    }
+    audioContext = new Ctx();
+    audioContext.resume().catch(() => {
+      // Some browsers resume automatically after microphone permission.
+    });
+    const node = audioContext.createMediaStreamSource(source);
+    const analyser = audioContext.createAnalyser();
+    analyser.fftSize = 512;
+    node.connect(analyser);
+    const data = new Uint8Array(analyser.frequencyBinCount);
+    const tick = () => {
+      if (stopped) {
+        return;
+      }
+      analyser.getByteTimeDomainData(data);
+      let sum = 0;
+      for (const sample of data) {
+        const value = (sample - 128) / 128;
+        sum += value * value;
+      }
+      const rms = Math.sqrt(sum / data.length);
+      onFrame?.(rms, performance.now());
+      // Perceptual boost so normal speech remains clearly visible.
+      publishLevel(Math.min(1, rms * 3.2));
+      levelRaf = requestAnimationFrame(tick);
+    };
+    levelRaf = requestAnimationFrame(tick);
+  } catch {
+    // The waveform is cosmetic; recording can continue without Web Audio.
+    stop();
+  }
+
+  return stop;
+}
diff --git a/studio/frontend/src/features/chat/adapters/studio-dictation-adapter.tsx b/studio/frontend/src/features/chat/adapters/studio-dictation-adapter.tsx
new file mode 100644
index 0000000000..d637a32b0d
--- /dev/null
+++ b/studio/frontend/src/features/chat/adapters/studio-dictation-adapter.tsx
@@ -0,0 +1,139 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useSettingsDialogStore } from "@/features/settings/stores/settings-dialog-store";
+import {
+  type DictationEngine,
+  useVoiceSettingsStore,
+} from "@/features/settings/stores/voice-settings-store";
+import { toast } from "@/lib/toast";
+import type { DictationAdapter } from "@assistant-ui/react";
+import { StudioModelDictationAdapter } from "./studio-model-dictation-adapter";
+import {
+  type StudioDictationSession,
+  StudioWebSpeechDictationAdapter,
+} from "./studio-web-speech-dictation-adapter";
+
+// The one live dictation session, so the recording bar's discard (X) can cancel
+// it without going through assistant-ui (which only exposes stop, i.e.
+// transcribe). Cancelling emits no transcript, so composer text is untouched.
+let activeSession: StudioDictationSession | null = null;
+
+/** Discard the current dictation without transcribing. Safe to call when idle. */
+export function cancelActiveStudioDictation(): void {
+  const session = activeSession;
+  activeSession = null;
+  session?.cancel();
+}
+
+/**
+ * Routes dictation to the engine chosen in Voice settings, resolved at listen()
+ * time so switching engines applies without reloading the chat runtime.
+ */
+/** Both local engines (Transformers and GGUF) record via MediaRecorder. */
+function usesModelRecording(dictationEngine: DictationEngine): boolean {
+  return dictationEngine === "model";
+}
+
+export class StudioDictationAdapter implements DictationAdapter {
+  // Chat linked in Recent dictations. undefined follows the active single chat;
+  // null records no chat (composers outside it, e.g. Compare).
+  private readonly chatId: string | null | undefined;
+
+  constructor(options: { chatId?: string | null } = {}) {
+    this.chatId = options.chatId;
+  }
+
+  static isSupported(
+    dictationEngine: DictationEngine = useVoiceSettingsStore.getState()
+      .dictationEngine,
+  ): boolean {
+    return usesModelRecording(dictationEngine)
+      ? StudioModelDictationAdapter.isSupported()
+      : StudioWebSpeechDictationAdapter.isSupported();
+  }
+
+  listen(): StudioDictationSession {
+    const session = this.createSession();
+    // A second entry point (chat, Compare, settings test) replaces the active
+    // session; cancel the old one so it cannot keep the mic open or save a
+    // transcript with no discard button pointing at it.
+    cancelActiveStudioDictation();
+    activeSession = session;
+    // Forget the session once it ends so a later cancel is a no-op.
+    const clear = () => {
+      if (activeSession === session) {
+        activeSession = null;
+      }
+    };
+    session.onSpeechEnd(clear);
+    session.onEnd?.(clear);
+    return session;
+  }
+
+  private createSession(): StudioDictationSession {
+    const { dictationEngine } = useVoiceSettingsStore.getState();
+    if (usesModelRecording(dictationEngine)) {
+      if (StudioModelDictationAdapter.isSupported()) {
+        return new StudioModelDictationAdapter({ chatId: this.chatId }).listen();
+      }
+      throw new Error(
+        "Local model dictation is not supported in this browser.",
+      );
+    }
+    if (StudioWebSpeechDictationAdapter.isSupported()) {
+      return new StudioWebSpeechDictationAdapter({ chatId: this.chatId }).listen();
+    }
+    throw new Error("Browser dictation is not supported in this browser.");
+  }
+}
+
+/** Whether dictation can run now for the chosen engine. */
+export function isStudioDictationAvailable(
+  dictationEngine: DictationEngine = useVoiceSettingsStore.getState()
+    .dictationEngine,
+): boolean {
+  return StudioDictationAdapter.isSupported(dictationEngine);
+}
+
+/** Explain why dictation can't start and point the user to the local model. */
+export function notifyStudioDictationUnavailable(
+  dictationEngine: DictationEngine = useVoiceSettingsStore.getState()
+    .dictationEngine,
+): void {
+  // Both engines need a secure context (localhost or HTTPS).
+  if (typeof window !== "undefined" && !window.isSecureContext) {
+    toast.error("Voice typing needs a secure connection.", {
+      description:
+        "Open Studio at http://127.0.0.1 (localhost) or over HTTPS to dictate.",
+    });
+    return;
+  }
+  if (usesModelRecording(dictationEngine)) {
+    // Defensive: MediaRecorder is effectively always present here.
+    toast.error("Voice recording isn't available in this browser.");
+    return;
+  }
+  // Browser Web Speech is missing (e.g. Firefox). Stack text and button so the
+  // action sits below, not squeezed into a side column.
+  const toastId = toast.error("Voice typing isn't available in this browser.", {
+    description: (
+      <div className="mt-0.5 flex flex-col items-start gap-2 pb-1.5">
+        <span>
+          Choose the local speech-to-text model in Voice settings to dictate
+          here.
+        </span>
+        <button
+          type="button"
+          onClick={() => {
+            useSettingsDialogStore.getState().openDialog("voice");
+            toast.dismiss(toastId);
+          }}
+          className="rounded-full bg-foreground px-2.5 pt-1 pb-1.5 text-xs font-medium text-background transition-colors hover:bg-foreground/90"
+        >
+          Open Voice settings
+        </button>
+      </div>
+    ),
+  });
+}
diff --git a/studio/frontend/src/features/chat/adapters/studio-model-dictation-adapter.ts b/studio/frontend/src/features/chat/adapters/studio-model-dictation-adapter.ts
new file mode 100644
index 0000000000..8546e3eeab
--- /dev/null
+++ b/studio/frontend/src/features/chat/adapters/studio-model-dictation-adapter.ts
@@ -0,0 +1,637 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { authFetch } from "@/features/auth";
+import { hubTokenHeader } from "@/features/hub/lib/hub-token-header";
+import {
+  applyDictationDictionary,
+  isCuratedSttModel,
+  recordRecentDictation,
+  resolveModelDictationLanguage,
+  useVoiceSettingsStore,
+} from "@/features/settings/stores/voice-settings-store";
+import type { DictationAdapter } from "@assistant-ui/react";
+import { toast } from "sonner";
+import { startDictationLevelMeter } from "./dictation-level";
+import {
+  type StudioDictationSession,
+  isMissingDeviceError,
+  resolveDictationChatId,
+} from "./studio-web-speech-dictation-adapter";
+
+// Fine timeslice so the buffer is ready the moment a segment is cut or stopped.
+const SEGMENT_TIMESLICE_MS = 250;
+// Whisper pads input to 30s. Short dictation stays one clip; long dictation cuts
+// at the first pause after 20s or before the 30s boundary.
+const MIN_SEGMENT_MS = 20_000;
+const MAX_SEGMENT_MS = 28_000;
+const SILENCE_CUT_MS = 280;
+// Raw RMS (0..1) above which a frame counts as speech (well above the room floor
+// after noise suppression).
+const VOICE_RMS = 0.015;
+
+// Prefer Opus (small, widely supported); fall back to whatever the browser
+// records. The backend decodes any of these with PyAV.
+const PREFERRED_MIME_TYPES = [
+  "audio/webm;codecs=opus",
+  "audio/webm",
+  "audio/ogg;codecs=opus",
+  "audio/mp4",
+];
+
+function pickMimeType(): string | undefined {
+  if (typeof MediaRecorder === "undefined") return undefined;
+  for (const type of PREFERRED_MIME_TYPES) {
+    if (MediaRecorder.isTypeSupported(type)) return type;
+  }
+  return undefined;
+}
+
+const stopStream = (stream: MediaStream | null) => {
+  for (const track of stream?.getTracks() ?? []) {
+    track.stop();
+  }
+};
+
+/** Backend STT engine, decided by the model: curated ids run GGML through
+ * whisper.cpp; a custom HF repo is safetensors and runs through Transformers. */
+export type SttEngine = "transformers" | "gguf";
+
+export function sttEngineFor(model: string): SttEngine {
+  return isCuratedSttModel(model) ? "gguf" : "transformers";
+}
+
+/** POST audio to the STT sidecar and return the transcript. */
+export async function transcribeAudioBlob(
+  blob: Blob,
+  options: {
+    model?: string;
+    language?: string;
+    engine?: SttEngine;
+    signal?: AbortSignal;
+  } = {},
+): Promise<string> {
+  const settings = useVoiceSettingsStore.getState();
+  const model = options.model ?? settings.sttModel;
+  const language = resolveModelDictationLanguage(
+    model,
+    options.language ?? settings.dictationLanguage,
+  );
+  const engine = options.engine ?? sttEngineFor(model);
+  const params = new URLSearchParams({ model, fast: "true", engine });
+  if (language) params.set("language", language);
+  const response = await authFetch(
+    `/api/inference/audio/transcribe/raw?${params.toString()}`,
+    {
+      method: "POST",
+      headers: { "Content-Type": blob.type || "application/octet-stream" },
+      body: blob,
+      signal: options.signal,
+    },
+  );
+  if (!response.ok) {
+    const body = (await response.json().catch(() => null)) as {
+      detail?: string;
+    } | null;
+    const detail = body?.detail ?? `HTTP ${response.status}`;
+    if (response.status === 501) {
+      throw new Error(
+        "Speech-to-text is not available on this server. Run `unsloth studio update` to install it.",
+      );
+    }
+    throw new Error(detail);
+  }
+  const data = (await response.json()) as { text?: string };
+  return (data.text ?? "").trim();
+}
+
+export interface SttDownloadStatus {
+  downloading: boolean;
+  model: string | null;
+  error: string | null;
+  bytes_total: number | null;
+  bytes_done: number | null;
+}
+
+export interface SttEngineStatus {
+  available: boolean;
+  loaded_model: string | null;
+  loading: boolean;
+  device: string | null;
+  keep_alive_seconds: number;
+  default_model: string;
+  models: string[];
+  downloaded_models: string[];
+  download: SttDownloadStatus;
+}
+
+export interface SttStatus {
+  available: boolean;
+  loaded_model: string | null;
+  loading: boolean;
+  device: string | null;
+  keep_alive_seconds: number;
+  default_model: string;
+  models: string[];
+  /** Per-engine state; absent on servers predating the engine split. */
+  transformers?: SttEngineStatus;
+  gguf?: SttEngineStatus;
+}
+
+// Keep load/unload requests ordered so a new recording cannot race an unload
+// still finishing for the previous one.
+let sttLifecycle: Promise<void> = Promise.resolve();
+
+function queueSttLifecycle(operation: () => Promise<void>): Promise<void> {
+  const result = sttLifecycle.catch(() => {}).then(operation);
+  sttLifecycle = result.catch(() => {});
+  return result;
+}
+
+/** Report whether STT is installed and which model, if any, is resident.
+ * Passing a model extends the downloaded check to custom repos. */
+export async function fetchSttStatus(
+  refreshKey?: number,
+  model?: string,
+): Promise<SttStatus> {
+  const params = new URLSearchParams();
+  if (refreshKey !== undefined) params.set("refresh", String(refreshKey));
+  if (model) params.set("model", model);
+  const query = params.toString();
+  const response = await authFetch(
+    `/api/inference/audio/stt/status${query ? `?${query}` : ""}`,
+  );
+  if (!response.ok) throw new Error(`HTTP ${response.status}`);
+  return (await response.json()) as SttStatus;
+}
+
+/** Verify a custom Hub repository is a Transformers Whisper checkpoint. */
+export async function validateSttModel(
+  model: string,
+  hfToken?: string,
+): Promise<void> {
+  const response = await authFetch("/api/inference/audio/stt/validate", {
+    method: "POST",
+    headers: {
+      "Content-Type": "application/json",
+      ...hubTokenHeader(hfToken),
+    },
+    body: JSON.stringify({ model }),
+  });
+  if (!response.ok) {
+    const body = (await response.json().catch(() => null)) as {
+      detail?: string;
+    } | null;
+    throw new Error(body?.detail ?? `HTTP ${response.status}`);
+  }
+}
+
+/** Load a selected model that is already downloaded. */
+export function loadSttModel(model: string, engine?: SttEngine): Promise<void> {
+  const resolvedEngine = engine ?? sttEngineFor(model);
+  return queueSttLifecycle(async () => {
+    const response = await authFetch("/api/inference/audio/stt/load", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ model, engine: resolvedEngine }),
+    });
+    if (!response.ok) {
+      const body = (await response.json().catch(() => null)) as {
+        detail?: string;
+      } | null;
+      throw new Error(body?.detail ?? `HTTP ${response.status}`);
+    }
+  });
+}
+
+/** Start a background download of a dictation model. */
+export async function startSttDownload(
+  model: string,
+  hfToken?: string,
+): Promise<void> {
+  const response = await authFetch("/api/inference/audio/stt/download", {
+    method: "POST",
+    headers: {
+      "Content-Type": "application/json",
+      ...hubTokenHeader(hfToken),
+    },
+    body: JSON.stringify({ model, engine: sttEngineFor(model) }),
+  });
+  if (!response.ok) {
+    const body = (await response.json().catch(() => null)) as {
+      detail?: string;
+    } | null;
+    throw new Error(body?.detail ?? `HTTP ${response.status}`);
+  }
+}
+
+/** Release the local STT model and its RAM/VRAM allocations. */
+export function unloadSttModel(): Promise<void> {
+  return queueSttLifecycle(async () => {
+    const response = await authFetch("/api/inference/audio/stt/unload", {
+      method: "POST",
+    });
+    if (!response.ok) {
+      const body = (await response.json().catch(() => null)) as {
+        detail?: string;
+      } | null;
+      throw new Error(body?.detail ?? `HTTP ${response.status}`);
+    }
+  });
+}
+
+/**
+ * Local model dictation. Short recordings use one pass; long ones split near
+ * Whisper's 30s window. Confirm keeps text, discard removes it, and either
+ * releases the microphone immediately.
+ */
+export class StudioModelDictationAdapter implements DictationAdapter {
+  private readonly chatId: string | null | undefined;
+
+  constructor(options: { chatId?: string | null } = {}) {
+    this.chatId = options.chatId;
+  }
+
+  static isSupported(): boolean {
+    return (
+      typeof window !== "undefined" &&
+      window.isSecureContext &&
+      typeof MediaRecorder !== "undefined" &&
+      navigator.mediaDevices?.getUserMedia !== undefined
+    );
+  }
+
+  listen(): DictationAdapter.Session {
+    if (!StudioModelDictationAdapter.isSupported()) {
+      throw new Error("Recording is not supported in this browser.");
+    }
+
+    // Pin the model, language, and linked chat chosen when recording began, so a
+    // mid-session settings change or thread switch cannot affect later segments
+    // or relink the saved transcript.
+    const { sttModel: sessionModel, dictationLanguage } =
+      useVoiceSettingsStore.getState();
+    const sessionLanguage = resolveModelDictationLanguage(
+      sessionModel,
+      dictationLanguage,
+    );
+    const sessionEngine = sttEngineFor(sessionModel);
+    const sessionChatId = resolveDictationChatId(this.chatId);
+
+    const speechStartCallbacks = new Set<() => void>();
+    const speechEndCallbacks = new Set<
+      (result: DictationAdapter.Result) => void
+    >();
+    const speechCallbacks = new Set<
+      (result: DictationAdapter.Result) => void
+    >();
+    const endCallbacks = new Set<() => void>();
+
+    let stream: MediaStream | null = null;
+    let ended = false;
+    let cancelled = false;
+    let finalizing = false;
+    const abortController = new AbortController();
+    const mimeType = pickMimeType();
+    // Shared waveform meter also feeds this adapter's pause detector.
+    let stopLevelMeter = () => {
+      // Replaced after microphone access succeeds.
+    };
+    let onAudioFrame: (rawRms: number, now: number) => void = () => {};
+
+    let resolveEnded: (() => void) | null = null;
+    const endedPromise = new Promise<void>((resolve) => {
+      resolveEnded = resolve;
+    });
+
+    // --- Background transcription pipeline ---------------------------------
+    // Each segment is a self-contained clip transcribed on its own; results are
+    // stored by index so the final text keeps its order.
+    type Segment = {
+      index: number;
+      chunks: Blob[];
+      startedAt: number;
+      voiced: boolean;
+      recorder: MediaRecorder;
+    };
+    const results: string[] = [];
+    const queue: { index: number; blob: Blob }[] = [];
+    let worker = false;
+    let currentSeg: Segment | null = null;
+    let segCounter = 0;
+    let pendingRecorders = 0;
+    let silenceMs = 0;
+    let lastFrameAt = 0;
+    let cutting = false;
+    let finalCutDone = false;
+    let reportedTranscriptionError = false;
+
+    const reportTranscriptionError = (error: unknown) => {
+      if (reportedTranscriptionError || cancelled || ended) return;
+      reportedTranscriptionError = true;
+      const message =
+        error instanceof Error && error.message
+          ? error.message
+          : "A recorded segment could not be transcribed.";
+      console.error("STT transcription error:", error);
+      toast.error(message);
+    };
+
+    const buildTranscript = () =>
+      results
+        .filter((part) => part?.trim())
+        .join(" ")
+        .trim();
+
+    const finishSession = (
+      reason: "stopped" | "cancelled" | "error",
+      transcript?: string,
+    ) => {
+      if (ended) return;
+      ended = true;
+      stopLevelMeter();
+      if (currentSeg && currentSeg.recorder.state !== "inactive") {
+        try {
+          currentSeg.recorder.stop();
+        } catch {
+          // ignore
+        }
+      }
+      session.status = { type: "ended", reason };
+      stopStream(stream);
+      stream = null;
+      const corrected = transcript ? applyDictationDictionary(transcript) : "";
+      if (reason !== "cancelled" && corrected) {
+        for (const callback of speechCallbacks) {
+          callback({ transcript: corrected, isFinal: true });
+        }
+        recordRecentDictation(corrected, sessionChatId);
+      }
+      for (const callback of speechEndCallbacks) {
+        callback({ transcript: corrected });
+      }
+      for (const callback of endCallbacks) callback();
+      resolveEnded?.();
+    };
+
+    // Finish once the final segment has been cut and the queue has drained.
+    const maybeComplete = () => {
+      if (ended || cancelled || !finalizing || !finalCutDone) return;
+      if (pendingRecorders === 0 && queue.length === 0 && !worker) {
+        finishSession("stopped", buildTranscript());
+      }
+    };
+
+    // Transcribe queued segments one at a time so the backend is never flooded.
+    const processQueue = () => {
+      if (worker || cancelled || ended) return;
+      const item = queue.shift();
+      if (!item) {
+        maybeComplete();
+        return;
+      }
+      worker = true;
+      void (async () => {
+        try {
+          const text = await transcribeAudioBlob(item.blob, {
+            model: sessionModel,
+            language: sessionLanguage,
+            engine: sessionEngine,
+            signal: abortController.signal,
+          });
+          if (!cancelled) results[item.index] = text;
+        } catch (error) {
+          if (!cancelled && !abortController.signal.aborted) {
+            // Keep transcribed segments, but never hide that part was lost.
+            reportTranscriptionError(error);
+          }
+        } finally {
+          worker = false;
+          processQueue();
+        }
+      })();
+    };
+
+    // Every non-empty recording is transcribed. The RMS meter only shapes
+    // segment boundaries; a quiet microphone or suspended AudioContext can keep
+    // it below VOICE_RMS for real speech, so it must never discard audio.
+    // Whisper returns an empty transcript for genuine silence.
+    const enqueueSegment = (index: number, blob: Blob) => {
+      if (blob.size > 0) {
+        queue.push({ index, blob });
+        processQueue();
+      } else {
+        results[index] = "";
+        maybeComplete();
+      }
+    };
+
+    // Start recording a fresh segment on the shared mic stream.
+    const startSegment = () => {
+      if (ended || cancelled || !stream) return;
+      const seg: Segment = {
+        index: segCounter++,
+        chunks: [],
+        startedAt: performance.now(),
+        voiced: false,
+        recorder: new MediaRecorder(
+          stream,
+          mimeType ? { mimeType } : undefined,
+        ),
+      };
+      currentSeg = seg;
+      silenceMs = 0;
+      seg.recorder.addEventListener("dataavailable", (event) => {
+        if (event.data.size > 0) seg.chunks.push(event.data);
+      });
+      seg.recorder.addEventListener("stop", () => {
+        pendingRecorders = Math.max(0, pendingRecorders - 1);
+        if (cancelled || ended) {
+          maybeComplete();
+          return;
+        }
+        const blob = new Blob(seg.chunks, {
+          type: seg.recorder.mimeType || "audio/webm",
+        });
+        enqueueSegment(seg.index, blob);
+      });
+      pendingRecorders += 1;
+      try {
+        seg.recorder.start(SEGMENT_TIMESLICE_MS);
+      } catch (error) {
+        pendingRecorders = Math.max(0, pendingRecorders - 1);
+        if (currentSeg === seg) currentSeg = null;
+        throw error;
+      }
+    };
+
+    // Close the current segment at a pause and open the next, so recording stays
+    // continuous while each clip is independently decodable.
+    const cutSegment = () => {
+      const seg = currentSeg;
+      if (cutting || !seg || finalizing) return;
+      cutting = true;
+      const rec = seg.recorder;
+      if (rec.state !== "inactive") {
+        rec.addEventListener(
+          "stop",
+          () => {
+            cutting = false;
+          },
+          { once: true },
+        );
+        try {
+          rec.stop();
+        } catch {
+          cutting = false;
+        }
+      } else {
+        cutting = false;
+      }
+      startSegment();
+    };
+
+    // Pause detector: mark voiced frames. Short dictations stay one segment; long
+    // ones cut at a pause after the target duration, or at the hard limit.
+    onAudioFrame = (rawRms, now) => {
+      const seg = currentSeg;
+      if (!seg || finalizing) {
+        lastFrameAt = now;
+        return;
+      }
+      if (rawRms > VOICE_RMS) {
+        seg.voiced = true;
+        silenceMs = 0;
+      } else if (lastFrameAt) {
+        silenceMs += now - lastFrameAt;
+      }
+      lastFrameAt = now;
+      const duration = now - seg.startedAt;
+      const pauseBreak =
+        seg.voiced && duration > MIN_SEGMENT_MS && silenceMs > SILENCE_CUT_MS;
+      if (!cutting && (pauseBreak || duration > MAX_SEGMENT_MS)) {
+        cutSegment();
+      }
+    };
+
+    const session: StudioDictationSession = {
+      status: { type: "starting" },
+      stop: async () => {
+        if (!ended && !finalizing) {
+          finalizing = true;
+          // Stop publishing zero-valued frames at once so the UI can switch to
+          // its transcription shimmer.
+          stopLevelMeter();
+          const seg = currentSeg;
+          // Cut the final segment (its buffer survives) so only the short tail is
+          // left to transcribe, then release the mic immediately.
+          if (seg && seg.recorder.state !== "inactive") {
+            seg.recorder.addEventListener(
+              "stop",
+              () => {
+                finalCutDone = true;
+                maybeComplete();
+              },
+              { once: true },
+            );
+            try {
+              seg.recorder.stop();
+            } catch {
+              finalCutDone = true;
+              maybeComplete();
+            }
+          } else {
+            finalCutDone = true;
+            maybeComplete();
+          }
+          stopStream(stream);
+          stream = null;
+        }
+        await endedPromise;
+      },
+      cancel: () => {
+        if (ended) return;
+        cancelled = true;
+        finalizing = true;
+        abortController.abort();
+        finishSession("cancelled");
+      },
+      onSpeechStart: (callback) => {
+        speechStartCallbacks.add(callback);
+        return () => {
+          speechStartCallbacks.delete(callback);
+        };
+      },
+      onSpeechEnd: (callback) => {
+        speechEndCallbacks.add(callback);
+        return () => {
+          speechEndCallbacks.delete(callback);
+        };
+      },
+      onSpeech: (callback) => {
+        speechCallbacks.add(callback);
+        return () => {
+          speechCallbacks.delete(callback);
+        };
+      },
+      onEnd: (callback: () => void) => {
+        endCallbacks.add(callback);
+        return () => {
+          endCallbacks.delete(callback);
+        };
+      },
+    };
+
+    void (async () => {
+      try {
+        const { micDeviceId } = useVoiceSettingsStore.getState();
+        const baseAudio: MediaTrackConstraints = {
+          echoCancellation: true,
+          noiseSuppression: true,
+        };
+        try {
+          stream = await navigator.mediaDevices.getUserMedia({
+            audio:
+              micDeviceId && micDeviceId !== "default"
+                ? { ...baseAudio, deviceId: { exact: micDeviceId } }
+                : baseAudio,
+          });
+        } catch (error) {
+          // Saved mic may be unplugged; fall back to the default.
+          if (micDeviceId !== "default" && isMissingDeviceError(error)) {
+            stream = await navigator.mediaDevices.getUserMedia({
+              audio: baseAudio,
+            });
+          } else {
+            throw error;
+          }
+        }
+        if (ended || cancelled) {
+          stopStream(stream);
+          stream = null;
+          return;
+        }
+        // Warm the model only after mic access. The backend loads cache-only
+        // and never downloads here.
+        void loadSttModel(sessionModel, sessionEngine).catch(
+          reportTranscriptionError,
+        );
+        stopLevelMeter = startDictationLevelMeter(stream, (rawRms, now) => {
+          onAudioFrame(rawRms, now);
+        });
+        startSegment();
+        session.status = { type: "running" };
+        for (const callback of speechStartCallbacks) callback();
+      } catch (error) {
+        const message = isMissingDeviceError(error)
+          ? "No microphone was found for dictation."
+          : "Dictation could not access the microphone.";
+        console.error("STT microphone error:", error);
+        toast.error(message);
+        finishSession("error");
+      }
+    })();
+
+    return session;
+  }
+}
diff --git a/studio/frontend/src/features/chat/adapters/studio-speech-synthesis-adapter.ts b/studio/frontend/src/features/chat/adapters/studio-speech-synthesis-adapter.ts
index 5e6a76e949..3a5042f61d 100644
--- a/studio/frontend/src/features/chat/adapters/studio-speech-synthesis-adapter.ts
+++ b/studio/frontend/src/features/chat/adapters/studio-speech-synthesis-adapter.ts
@@ -6,17 +6,19 @@ import { useVoiceSettingsStore } from "@/features/settings/stores/voice-settings
 import { toast } from "@/lib/toast";
 import type { SpeechSynthesisAdapter } from "@assistant-ui/react";
 
-/** Voice for a stored voiceURI; undefined lets the browser pick. */
+/** Voice for a stored voiceURI. "default" resolves to the voice the platform
+ * marks as its default, so the "System default" choice means what it says
+ * instead of falling back to a curated pick. Undefined lets the browser pick. */
 export function findTtsVoice(
   voiceURI: string,
 ): SpeechSynthesisVoice | undefined {
   if (typeof window === "undefined" || !window.speechSynthesis) {
     return undefined;
   }
-  if (!voiceURI || voiceURI === "default") return undefined;
-  return window.speechSynthesis
-    .getVoices()
-    .find((voice) => voice.voiceURI === voiceURI);
+  if (!voiceURI) return undefined;
+  const voices = window.speechSynthesis.getVoices();
+  if (voiceURI === "default") return voices.find((voice) => voice.default);
+  return voices.find((voice) => voice.voiceURI === voiceURI);
 }
 
 // macOS novelty and legacy Eloquence voices that sound robotic and flood the picker.
@@ -59,19 +61,54 @@ function voiceBaseName(voice: SpeechSynthesisVoice): string {
   return name;
 }
 
+// Well-known natural English voices, best first. Breaks ties when the name
+// carries no quality hint, so basic voices are not just alphabetical.
+const PREFERRED_VOICE_NAMES = [
+  "samantha",
+  "alex",
+  "ava",
+  "allison",
+  "susan",
+  "tom",
+  "daniel",
+  "serena",
+  "karen",
+  "moira",
+  "tessa",
+  "fiona",
+];
+
+// Quality tier from vendor hints in the voice name.
 function voiceQualityScore(voice: SpeechSynthesisVoice): number {
   const name = voice.name.toLowerCase();
   let score = 0;
-  if (name.includes("premium")) score += 8;
-  if (name.includes("enhanced")) score += 7;
-  if (name.includes("natural") || name.includes("neural")) score += 6;
-  if (name.includes("siri")) score += 6;
-  if (name.includes("google")) score += 5;
-  if (name.includes("microsoft")) score += 4;
-  if (voice.default) score += 3;
+  if (name.includes("premium")) score += 100;
+  if (name.includes("siri")) score += 90;
+  if (name.includes("enhanced")) score += 80;
+  if (name.includes("natural") || name.includes("neural")) score += 70;
+  if (name.includes("google")) score += 40;
+  if (name.includes("microsoft")) score += 30;
   return score;
 }
 
+// Higher for voices in the user's exact region, then the same language.
+function voiceLocaleScore(voice: SpeechSynthesisVoice): number {
+  const navLang =
+    typeof navigator !== "undefined" && navigator.language
+      ? navigator.language.toLowerCase()
+      : "en-us";
+  const lang = voice.lang.toLowerCase().replace("_", "-");
+  if (lang === navLang) return 2;
+  if (langBase(lang) === langBase(navLang)) return 1;
+  return 0;
+}
+
+// Rank in the preferred list, best first; 0 when the voice is not listed.
+function voicePreferredRank(voice: SpeechSynthesisVoice): number {
+  const index = PREFERRED_VOICE_NAMES.indexOf(voiceBaseName(voice));
+  return index === -1 ? 0 : PREFERRED_VOICE_NAMES.length - index;
+}
+
 function langBase(tag: string): string {
   return tag.toLowerCase().split(/[-_]/)[0] ?? "";
 }
@@ -86,8 +123,8 @@ const MAX_CURATED_VOICES = 20;
 export function curateSystemVoices(
   voices: SpeechSynthesisVoice[],
   selectedVoiceURI?: string,
+  dictationLanguage = useVoiceSettingsStore.getState().dictationLanguage,
 ): SpeechSynthesisVoice[] {
-  const { dictationLanguage } = useVoiceSettingsStore.getState();
   const wantedLangs = new Set<string>(["en"]);
   if (typeof navigator !== "undefined" && navigator.language) {
     wantedLangs.add(langBase(navigator.language));
@@ -107,12 +144,33 @@ export function curateSystemVoices(
   });
 
   kept.sort((a, b) => {
-    const scoreDiff = voiceQualityScore(b) - voiceQualityScore(a);
-    if (scoreDiff !== 0) return scoreDiff;
+    const quality = voiceQualityScore(b) - voiceQualityScore(a);
+    if (quality !== 0) return quality;
+    const locale = voiceLocaleScore(b) - voiceLocaleScore(a);
+    if (locale !== 0) return locale;
+    const preferred = voicePreferredRank(b) - voicePreferredRank(a);
+    if (preferred !== 0) return preferred;
+    const byDefault = Number(b.default) - Number(a.default);
+    if (byDefault !== 0) return byDefault;
     return a.name.localeCompare(b.name);
   });
 
-  const curated = kept.slice(0, MAX_CURATED_VOICES);
+  // macOS reports some voices twice (compact + enhanced) under one name. Keep
+  // one per name and language, preferring the selected voice then the best
+  // ranked, so no duplicates show.
+  const keyOf = (voice: SpeechSynthesisVoice) =>
+    `${voiceBaseName(voice)}|${voice.lang.toLowerCase()}`;
+  const winners = new Map<string, string>();
+  for (const voice of kept) {
+    const key = keyOf(voice);
+    if (!winners.has(key)) winners.set(key, voice.voiceURI);
+    if (voice.voiceURI === selectedVoiceURI) winners.set(key, voice.voiceURI);
+  }
+  const deduped = kept.filter(
+    (voice) => winners.get(keyOf(voice)) === voice.voiceURI,
+  );
+
+  const curated = deduped.slice(0, MAX_CURATED_VOICES);
   if (
     selectedVoiceURI &&
     selectedVoiceURI !== "default" &&
@@ -126,6 +184,22 @@ export function curateSystemVoices(
   return curated;
 }
 
+/**
+ * Best voice when none is chosen. The browser default on macOS is often a
+ * robotic legacy voice, so fall back to the top curated voice instead.
+ */
+function defaultTtsVoice(): SpeechSynthesisVoice | undefined {
+  if (typeof window === "undefined" || !window.speechSynthesis) {
+    return undefined;
+  }
+  const voices = window.speechSynthesis.getVoices();
+  return (
+    curateSystemVoices(voices)[0] ??
+    voices.find((voice) => voice.default) ??
+    voices[0]
+  );
+}
+
 /** Build an utterance from the current Voice settings. */
 export function createConfiguredUtterance(
   text: string,
@@ -133,7 +207,7 @@ export function createConfiguredUtterance(
   const { ttsVoiceURI, ttsRate, ttsPitch, ttsVolume } =
     useVoiceSettingsStore.getState();
   const utterance = new SpeechSynthesisUtterance(text);
-  const voice = findTtsVoice(ttsVoiceURI);
+  const voice = findTtsVoice(ttsVoiceURI) ?? defaultTtsVoice();
   if (voice) {
     utterance.voice = voice;
     utterance.lang = voice.lang;
@@ -272,8 +346,14 @@ export class StudioSpeechSynthesisAdapter implements SpeechSynthesisAdapter {
       if (res.status.type === "ended") return;
       // Surface genuine read-aloud failures; a cancelled/interrupted utterance
       // is a normal stop, not an error, and must not toast.
-      if (reason === "error" && error !== "interrupted" && error !== "canceled") {
-        toast.error(error instanceof Error ? error.message : "Read aloud failed.");
+      if (
+        reason === "error" &&
+        error !== "interrupted" &&
+        error !== "canceled"
+      ) {
+        toast.error(
+          error instanceof Error ? error.message : "Read aloud failed.",
+        );
       }
       res.status = { type: "ended", reason, error };
       for (const handler of subscribers) handler();
diff --git a/studio/frontend/src/features/chat/adapters/studio-web-speech-dictation-adapter.ts b/studio/frontend/src/features/chat/adapters/studio-web-speech-dictation-adapter.ts
index b7a8e904ed..fb0e4fc0ab 100644
--- a/studio/frontend/src/features/chat/adapters/studio-web-speech-dictation-adapter.ts
+++ b/studio/frontend/src/features/chat/adapters/studio-web-speech-dictation-adapter.ts
@@ -1,6 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import { useSettingsDialogStore } from "@/features/settings/stores/settings-dialog-store";
 import {
   applyDictationDictionary,
   recordRecentDictation,
@@ -9,6 +10,39 @@ import {
 } from "@/features/settings/stores/voice-settings-store";
 import type { DictationAdapter } from "@assistant-ui/react";
 import { toast } from "sonner";
+import { useChatRuntimeStore } from "../stores/chat-runtime-store";
+import { startDictationLevelMeter } from "./dictation-level";
+
+/** Chat open while dictating, so the saved dictation can link back to it. */
+export function activeDictationChatId(): string | undefined {
+  return useChatRuntimeStore.getState().activeThreadId ?? undefined;
+}
+
+/**
+ * Resolve the chat a saved dictation links to. undefined falls back to the
+ * active single chat; null (composers without one, e.g. Compare) means none.
+ */
+export function resolveDictationChatId(
+  chatId: string | null | undefined,
+): string | undefined {
+  if (chatId === undefined) return activeDictationChatId();
+  return chatId ?? undefined;
+}
+
+// Reused id so repeated network failures replace, not stack, the same toast.
+const NETWORK_TOAST_ID = "dictation-network-offline";
+
+// Short grace for the browser to finalize its latest interim hypothesis. If it
+// doesn't, promote that text instead of stalling on a finalization spinner.
+const STOP_FINALIZATION_GRACE_MS = 350;
+
+/**
+ * A dictation session with an extra onEnd hook (not part of the assistant-ui
+ * interface) so non-runtime callers can reset when the session ends by itself.
+ */
+export type StudioDictationSession = DictationAdapter.Session & {
+  onEnd?: (callback: () => void) => () => void;
+};
 
 const getSpeechRecognitionAPI = ():
   | SpeechRecognitionConstructor
@@ -18,7 +52,9 @@ const getSpeechRecognitionAPI = ():
 };
 
 const stopStream = (stream: MediaStream | null) => {
-  stream?.getTracks().forEach((track) => track.stop());
+  for (const track of stream?.getTracks() ?? []) {
+    track.stop();
+  }
 };
 
 const mediaErrorName = (error: unknown): unknown =>
@@ -48,7 +84,10 @@ export const describeMediaError = (error: unknown): string => {
     : "Dictation could not access the microphone.";
 };
 
-export const describeSpeechError = (error: string, message?: string): string => {
+export const describeSpeechError = (
+  error: string,
+  message?: string,
+): string => {
   if (error === "not-allowed") {
     return "Speech recognition was blocked by the browser. Check microphone permissions for this Unsloth page.";
   }
@@ -68,18 +107,21 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
   private readonly language: string | undefined;
   private readonly continuous: boolean;
   private readonly interimResults: boolean;
+  private readonly chatId: string | null | undefined;
 
   constructor(
     options: {
       language?: string;
       continuous?: boolean;
       interimResults?: boolean;
+      chatId?: string | null;
     } = {},
   ) {
     // Resolved from Voice settings at listen() time unless overridden.
     this.language = options.language;
     this.continuous = options.continuous ?? true;
     this.interimResults = options.interimResults ?? true;
+    this.chatId = options.chatId;
   }
 
   static isSupported(): boolean {
@@ -101,6 +143,9 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
     recognition.lang = this.language ?? resolveDictationLanguage();
     recognition.continuous = this.continuous;
     recognition.interimResults = this.interimResults;
+    // Pin the linked chat now so a thread switch during finalization cannot
+    // relink the transcript to the newly opened chat.
+    const sessionChatId = resolveDictationChatId(this.chatId);
 
     const speechStartCallbacks = new Set<() => void>();
     const speechEndCallbacks = new Set<
@@ -109,22 +154,38 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
     const speechCallbacks = new Set<
       (result: DictationAdapter.Result) => void
     >();
+    const endCallbacks = new Set<() => void>();
 
     let stream: MediaStream | null = null;
     let finalTranscript = "";
     let ended = false;
     let started = false;
+    let stopping = false;
+    let stopRequestedAt = 0;
+    let stopFallbackTimer = 0;
+    let stopLevelMeter = () => {
+      // Replaced after microphone access succeeds.
+    };
+    const interimParts = new Map<number, string>();
     let resolveEnded: (() => void) | null = null;
     const endedPromise = new Promise<void>((resolve) => {
       resolveEnded = resolve;
     });
 
-    const session: DictationAdapter.Session = {
+    const session: StudioDictationSession = {
       status: { type: "starting" },
 
       stop: async () => {
         if (!ended && started) {
+          stopping = true;
+          stopRequestedAt = performance.now();
           recognition.stop();
+          // Ending the track now gives the browser an audio endpoint to finalize
+          // and releases the mic without waiting on its remote speech service.
+          stopLevelMeter();
+          stopStream(stream);
+          stream = null;
+          scheduleStopFallback();
         } else if (!ended) {
           finish("stopped");
         }
@@ -132,11 +193,9 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
       },
 
       cancel: () => {
-        if (!ended && started) {
-          recognition.abort();
-        } else if (!ended) {
-          finish("cancelled");
-        }
+        if (ended) return;
+        if (started) recognition.abort();
+        finish("cancelled");
       },
 
       onSpeechStart: (callback) => {
@@ -159,23 +218,75 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
           speechCallbacks.delete(callback);
         };
       },
+
+      // Beyond DictationAdapter: lets callers reset UI when the session ends on
+      // its own (silence, error), not just via stop().
+      onEnd: (callback: () => void) => {
+        endCallbacks.add(callback);
+        return () => {
+          endCallbacks.delete(callback);
+        };
+      },
     };
 
+    const currentInterimTranscript = () =>
+      [...interimParts.entries()]
+        .sort(([a], [b]) => a - b)
+        .map(([, transcript]) => transcript.trim())
+        .filter(Boolean)
+        .join(" ");
+
+    const promoteInterim = () => {
+      const interim = currentInterimTranscript();
+      interimParts.clear();
+      if (!interim) return false;
+      const corrected = applyDictationDictionary(interim).trim();
+      if (!corrected) return false;
+      finalTranscript = finalTranscript
+        ? `${finalTranscript} ${corrected}`
+        : corrected;
+      return true;
+    };
+
+    function scheduleStopFallback(): void {
+      if (!stopping || ended || stopFallbackTimer) return;
+      const elapsed = performance.now() - stopRequestedAt;
+      const delay = Math.max(0, STOP_FINALIZATION_GRACE_MS - elapsed);
+      stopFallbackTimer = window.setTimeout(() => {
+        stopFallbackTimer = 0;
+        if (!ended) {
+          promoteInterim();
+          finish("stopped");
+          recognition.abort();
+        }
+      }, delay);
+    }
+
     const finish = (reason: "stopped" | "cancelled" | "error") => {
       if (ended) return;
       ended = true;
+      stopping = false;
+      if (stopFallbackTimer) window.clearTimeout(stopFallbackTimer);
+      stopFallbackTimer = 0;
       session.status = { type: "ended", reason };
+      stopLevelMeter();
       stopStream(stream);
       stream = null;
-      if (finalTranscript) {
-        for (const callback of speechEndCallbacks) {
-          callback({ transcript: finalTranscript });
+      const transcript = reason === "cancelled" ? "" : finalTranscript;
+      if (transcript) {
+        for (const callback of speechCallbacks) {
+          callback({ transcript, isFinal: true });
         }
-        if (reason !== "cancelled") {
-          recordRecentDictation(finalTranscript);
-        }
-        finalTranscript = "";
+        recordRecentDictation(transcript, sessionChatId);
       }
+      // assistant-ui uses this callback to leave dictation mode; required even
+      // for silence and cancelled recordings.
+      for (const callback of speechEndCallbacks) {
+        callback({ transcript });
+      }
+      finalTranscript = "";
+      interimParts.clear();
+      for (const callback of endCallbacks) callback();
       resolveEnded?.();
     };
 
@@ -188,6 +299,7 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
     });
 
     recognition.addEventListener("result", (event) => {
+      if (ended) return;
       const speechEvent = event as SpeechRecognitionEvent;
       for (
         let i = speechEvent.resultIndex;
@@ -198,6 +310,7 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
         if (!result) continue;
         const transcript = result[0]?.transcript ?? "";
         if (result.isFinal) {
+          interimParts.delete(i);
           const corrected = applyDictationDictionary(transcript);
           // Join final chunks with a single space so recorded transcripts do
           // not merge words when a browser omits leading whitespace.
@@ -207,25 +320,34 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
               ? `${finalTranscript} ${trimmed}`
               : trimmed;
           }
-          for (const callback of speechCallbacks) {
-            callback({ transcript: corrected, isFinal: true });
-          }
         } else {
-          for (const callback of speechCallbacks) {
-            callback({ transcript, isFinal: false });
-          }
+          interimParts.set(i, transcript);
         }
       }
+      const interim = currentInterimTranscript();
+      if (interim) {
+        scheduleStopFallback();
+      }
     });
 
     recognition.addEventListener("end", () => {
+      if (ended) {
+        return;
+      }
+      promoteInterim();
       finish("stopped");
     });
 
     recognition.addEventListener("error", (event) => {
+      if (ended) return;
       const errorEvent = event as SpeechRecognitionErrorEvent;
       if (errorEvent.error === "aborted") {
-        finish("cancelled");
+        if (stopping) {
+          promoteInterim();
+          finish("stopped");
+        } else {
+          finish("cancelled");
+        }
         return;
       }
       const description = describeSpeechError(
@@ -233,7 +355,22 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
         errorEvent.message,
       );
       console.error("Dictation error:", errorEvent.error, errorEvent.message);
-      toast.error(description);
+      if (errorEvent.error === "network") {
+        // Online speech service unreachable; point the user to the offline
+        // local engine (the toast opens Voice settings).
+        toast.error("No internet connection", {
+          id: NETWORK_TOAST_ID,
+          description:
+            "Browser dictation needs the online speech service. Switch to Local in Voice settings and pick a local STT model to dictate offline.",
+          action: {
+            label: "Open Voice settings",
+            onClick: () =>
+              useSettingsDialogStore.getState().openDialog("voice"),
+          },
+        });
+      } else {
+        toast.error(description);
+      }
       finish("error");
     });
 
@@ -275,6 +412,7 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
             "NotFoundError",
           );
         }
+        stopLevelMeter = startDictationLevelMeter(stream);
         try {
           recognition.start(audioTrack);
         } catch (error) {
@@ -285,6 +423,7 @@ export class StudioWebSpeechDictationAdapter implements DictationAdapter {
             "Dictation start(audioTrack) failed; retrying start().",
             error,
           );
+          stopLevelMeter();
           stopStream(stream);
           stream = null;
           recognition.start();
diff --git a/studio/frontend/src/features/chat/api/chat-adapter.ts b/studio/frontend/src/features/chat/api/chat-adapter.ts
index 7083f02288..d4861e8a3a 100644
--- a/studio/frontend/src/features/chat/api/chat-adapter.ts
+++ b/studio/frontend/src/features/chat/api/chat-adapter.ts
@@ -2,10 +2,7 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { getAuthToken } from "@/features/auth";
-import {
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
+import { resolveInitialConfig } from "@/features/model-picker";
 import { projectHasSources } from "@/features/rag/api/rag-api";
 import { apiUrl } from "@/lib/api-base";
 import { parseParamCountB } from "@/lib/model-size";
@@ -46,7 +43,7 @@ import {
   type PendingImageEditReference,
   type RagAutoInject,
   GPU_LAYERS_AUTO,
-  loadedGpuMemoryFieldsUnlessStaged,
+  loadedGpuMemoryFields,
   reconcilePersistedGpuIds,
   resolveLoadedSpeculativeSettings,
   resolveSpeculativeSettingsForLoad,
@@ -1407,6 +1404,7 @@ const GGUF_KNOWN_QUANT_RE =
 
 type AutoLoadCandidate = {
   id: string;
+  loadId?: string | null;
   kind: LastLocalModelKind;
   ggufVariant: string | null;
   maxSeqLength: number;
@@ -1533,68 +1531,60 @@ async function autoLoadSmallestModel(): Promise<{
       return false;
     }
     const currentStore = useChatRuntimeStore.getState();
-    // Blobs are saved for GGUF picks only (the sheet gates on it), so don't
-    // let a legacy non-GGUF blob feed a stale context/spec choice into a
-    // safetensors auto-load.
-    const remembered =
-      candidate.kind === "gguf"
-        ? loadRememberedLoadSettings(
-            rememberedLoadSettingsKey({
-              id: candidate.id,
-              ggufVariant: candidate.ggufVariant,
-            }),
-          )
-        : null;
+    const modelPath = candidate.loadId ?? candidate.id;
+    const { config } = resolveInitialConfig(candidate.id, candidate.ggufVariant);
     const effectiveMaxSeqLength = resolveLoadMaxSeqLength({
       modelId: candidate.id,
       ggufVariant: candidate.ggufVariant,
       isGguf: candidate.kind === "gguf",
-      customContextLength: remembered?.contextLength ?? null,
+      customContextLength: config.customContextLength,
       ggufContextLength: null,
       currentCheckpoint: currentStore.params.checkpoint,
       activeGgufVariant: currentStore.activeGgufVariant,
-      maxSeqLength: candidate.maxSeqLength,
+      maxSeqLength: config.maxSeqLength ?? candidate.maxSeqLength,
       presetSource: currentStore.activePresetSource,
     });
-    // The GPU knobs are per-model, so read them from the same remembered
-    // settings that fed effectiveMaxSeqLength -- on a background auto-load the
-    // live store holds session defaults, not the saved Manual mode / layer pin /
-    // GPU pick. Absent fields fall back like applyRememberedLoadSettings: the
-    // mode to the store (a persisted standing preference), the per-model knobs to
-    // their defaults. The saved GPU pick is reconciled against the GPUs present
-    // now, like the interactive restore.
+    // The GPU knobs are per-model, so read them from the same per-model config
+    // that fed effectiveMaxSeqLength -- on a background auto-load the live store
+    // holds session defaults, not the saved Manual mode / layer pin / GPU pick.
+    // Absent fields fall back like the interactive restore: the mode to the store
+    // (a persisted standing preference), the per-model knobs to their defaults.
+    // The saved GPU pick is reconciled against the GPUs present now.
     const effectiveGpuMemoryMode =
-      remembered?.gpuMemoryMode ?? currentStore.gpuMemoryMode;
-    const effectiveGpuLayers = remembered?.gpuLayers ?? GPU_LAYERS_AUTO;
-    const effectiveNCpuMoe = remembered?.nCpuMoe ?? 0;
-    if (remembered?.selectedGpuIds != null) {
+      config.gpuMemoryMode ?? currentStore.gpuMemoryMode;
+    const effectiveGpuLayers = config.gpuLayers ?? GPU_LAYERS_AUTO;
+    const effectiveNCpuMoe = config.nCpuMoe ?? 0;
+    if (config.selectedGpuIds != null) {
       // Warm the device cache first: on a cold cache the reconcile passes the
       // saved pick through unvalidated, and a stale cross-host pick then fails
       // the load with the picker hidden.
       await ensureGpuDeviceCache();
     }
     const effectiveGpuIds =
-      remembered?.selectedGpuIds !== undefined
-        ? reconcilePersistedGpuIds(remembered.selectedGpuIds)
+      config.selectedGpuIds !== undefined
+        ? reconcilePersistedGpuIds(config.selectedGpuIds)
         : null;
     // Under Manual GPU memory + Auto layers, llama.cpp's --fit owns context
     // sizing, so send 0 (or the pinned length). GGUF-only; a no-op otherwise.
-    // The context pin is per-model too, so it comes from remembered settings,
-    // not the live store.
+    // The context pin is per-model too, so it comes from the saved config, not
+    // the live store.
     const fitMaxSeqLength = resolveFitMaxSeqLength(
       candidate.kind === "gguf",
       effectiveGpuMemoryMode,
       effectiveGpuLayers,
-      remembered?.contextLength ?? null,
+      config.customContextLength ?? null,
       effectiveMaxSeqLength,
     );
     const effectiveSpeculativeType =
-      remembered?.speculativeType ?? specSettings.speculativeType;
+      config.speculativeType ?? specSettings.speculativeType;
     const effectiveSpecDraftNMax =
-      remembered?.specDraftNMax ?? specSettings.specDraftNMax;
+      config.specDraftNMax ?? specSettings.specDraftNMax;
+    const effectiveChatTemplateOverride = config.chatTemplateOverride?.trim()
+      ? config.chatTemplateOverride
+      : null;
     if (
       !(await canAutoLoad({
-        model_path: candidate.id,
+        model_path: modelPath,
         max_seq_length: fitMaxSeqLength,
         is_lora: false,
         gguf_variant: candidate.ggufVariant,
@@ -1614,17 +1604,18 @@ async function autoLoadSmallestModel(): Promise<{
     }
     loadAttempts += 1;
     const loadResp = await loadModel({
-      model_path: candidate.id,
+      model_path: modelPath,
       hf_token: hfToken,
       max_seq_length: fitMaxSeqLength,
       load_in_4bit: true,
       is_lora: false,
       gguf_variant: candidate.ggufVariant,
       trust_remote_code: trustRemoteCode,
-      cache_type_kv: remembered?.kvCacheDtype ?? null,
+      chat_template_override: effectiveChatTemplateOverride,
+      cache_type_kv: config.kvCacheDtype,
       speculative_type: effectiveSpeculativeType,
       spec_draft_n_max: effectiveSpecDraftNMax,
-      tensor_parallel: remembered?.tensorParallel ?? false,
+      tensor_parallel: config.tensorParallel,
       // GGUF-only: the safetensors fallback loads via HF auto-placement (no
       // explicit pins). The split ratio is deliberately never remembered
       // (positionally bound to an exact GPU set), so auto-load leaves llama.cpp's
@@ -1638,25 +1629,34 @@ async function autoLoadSmallestModel(): Promise<{
           }
         : {}),
     });
-    saveSpeculativeType(effectiveSpeculativeType);
+    // Only persist the global preference when the value came from the global
+    // settings. A per-model config's choice must stay load-local, or autoloading
+    // a remembered model on startup would rewrite the global default.
+    if (config.speculativeType == null) {
+      saveSpeculativeType(effectiveSpeculativeType);
+    }
     // Self-gates on is_gguf (skips diffusion), so persists only for a real GGUF load.
     persistGpuMemoryModeOnLoad(loadResp, effectiveGpuMemoryMode);
+    const loadedModelId = loadResp.model || modelPath;
     useChatRuntimeStore
       .getState()
-      .setCheckpoint(candidate.id, candidate.ggufVariant ?? undefined);
+      .setCheckpoint(loadedModelId, candidate.ggufVariant ?? undefined);
     const store = useChatRuntimeStore.getState();
     store.setModelRequiresTrustRemoteCode(
       loadResp.requires_trust_remote_code ?? false,
     );
     store.setParams({
       ...store.params,
+      ...(candidate.kind === "gguf"
+        ? {}
+        : { maxSeqLength: effectiveMaxSeqLength }),
       maxTokens:
         candidate.kind === "gguf"
           ? loadResp.context_length ?? 131072
           : effectiveMaxSeqLength,
     });
     const autoModel: ChatModelSummary = {
-      id: candidate.id,
+      id: loadedModelId,
       name: loadResp.display_name ?? candidate.id,
       isVision: loadResp.is_vision ?? false,
       isLora: loadResp.is_lora ?? false,
@@ -1665,7 +1665,7 @@ async function autoLoadSmallestModel(): Promise<{
       audioType: loadResp.audio_type ?? null,
       hasAudioInput: loadResp.has_audio_input ?? false,
     };
-    if (!store.models.some((m) => m.id === candidate.id)) {
+    if (!store.models.some((m) => m.id === loadedModelId)) {
       store.setModels([...store.models, autoModel]);
     }
     if (candidate.kind === "gguf") {
@@ -1676,7 +1676,7 @@ async function autoLoadSmallestModel(): Promise<{
       const keepCustomCtx = resolveManualAutoCtxPin(
         effectiveGpuMemoryMode,
         effectiveGpuLayers,
-        remembered?.contextLength ?? null,
+        config.customContextLength ?? null,
       );
       useChatRuntimeStore.setState({
         ggufContextLength: loadResp.context_length ?? 131072,
@@ -1694,13 +1694,14 @@ async function autoLoadSmallestModel(): Promise<{
         loadedKvCacheDtype: loadResp.cache_type_kv ?? null,
         tensorParallel: loadResp.tensor_parallel ?? false,
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
-        ...loadedGpuMemoryFieldsUnlessStaged(loadResp, {
-          customContextLength: keepCustomCtx,
-        }),
+        ...loadedGpuMemoryFields(loadResp),
         loadedCustomContextLength: keepCustomCtx,
         defaultChatTemplate: loadResp.chat_template ?? null,
-        chatTemplateOverride: null,
-        loadedChatTemplateOverride: null,
+        chatTemplateOverride: effectiveChatTemplateOverride,
+        loadedChatTemplateOverride: effectiveChatTemplateOverride,
+        // Retain the saved requested context so re-saving the config keeps the
+        // override; null stays null (auto/VRAM-fit).
+        customContextLength: config.customContextLength,
         loadedIsMultimodal: isMultimodalResponse(loadResp),
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
         ...resolveLoadedSpeculativeSettings(loadResp),
@@ -1720,10 +1721,11 @@ async function autoLoadSmallestModel(): Promise<{
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
         // Non-GGUF response: clears any stale GPU baseline a prior manual-GPU
         // GGUF load left, matching the interactive/status sibling load paths.
-        ...loadedGpuMemoryFieldsUnlessStaged(loadResp),
+        ...loadedGpuMemoryFields(loadResp),
         defaultChatTemplate: loadResp.chat_template ?? null,
-        chatTemplateOverride: null,
-        loadedChatTemplateOverride: null,
+        chatTemplateOverride: effectiveChatTemplateOverride,
+        loadedChatTemplateOverride: effectiveChatTemplateOverride,
+        customContextLength: null,
         ...resolveLoadedSpeculativeSettings(loadResp),
         loadedIsMultimodal: isMultimodalResponse(loadResp),
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
@@ -1750,7 +1752,10 @@ async function autoLoadSmallestModel(): Promise<{
         const repo = findCachedRepo(ggufRepos, lastLoaded.id);
         if (repo && lastLoaded.ggufVariant) {
           try {
-            const variants = await listGgufVariants(repo.repo_id);
+            const variants = await listGgufVariants(repo.repo_id, undefined, {
+              preferLocalCache: true,
+              localPath: repo.cache_path,
+            });
             const variant = variants.variants.find(
               (entry) =>
                 entry.downloaded &&
@@ -1767,6 +1772,7 @@ async function autoLoadSmallestModel(): Promise<{
               if (
                 await loadAutoLoadCandidate({
                   id: repo.repo_id,
+                  loadId: repo.load_id,
                   kind: "gguf",
                   ggufVariant: variant.quant,
                   maxSeqLength: 0,
@@ -1795,6 +1801,7 @@ async function autoLoadSmallestModel(): Promise<{
             if (
               await loadAutoLoadCandidate({
                 id: repo.repo_id,
+                loadId: repo.load_id,
                 kind: "model",
                 ggufVariant: null,
                 maxSeqLength: store.params.maxSeqLength,
@@ -1824,7 +1831,10 @@ async function autoLoadSmallestModel(): Promise<{
       for (const repo of sorted) {
         if (loadAttempts >= MAX_AUTO_LOAD_ATTEMPTS) break;
         try {
-          const variants = await listGgufVariants(repo.repo_id);
+          const variants = await listGgufVariants(repo.repo_id, undefined, {
+            preferLocalCache: true,
+            localPath: repo.cache_path,
+          });
           const downloaded = variants.variants
             .filter((v) => v.downloaded && isAutoLoadableGgufVariant(v))
             .sort((a, b) => a.size_bytes - b.size_bytes);
@@ -1840,6 +1850,7 @@ async function autoLoadSmallestModel(): Promise<{
             if (
               await loadAutoLoadCandidate({
                 id: repo.repo_id,
+                loadId: repo.load_id,
                 kind: "gguf",
                 ggufVariant: variant.quant,
                 maxSeqLength: 0,
@@ -1874,6 +1885,7 @@ async function autoLoadSmallestModel(): Promise<{
           if (
             await loadAutoLoadCandidate({
               id: repo.repo_id,
+              loadId: repo.load_id,
               kind: "model",
               ggufVariant: null,
               maxSeqLength: 4096,
@@ -1988,7 +2000,7 @@ async function autoLoadSmallestModel(): Promise<{
         loadedKvCacheDtype: loadResp.cache_type_kv ?? null,
         tensorParallel: loadResp.tensor_parallel ?? false,
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
-        ...loadedGpuMemoryFieldsUnlessStaged(loadResp),
+        ...loadedGpuMemoryFields(loadResp),
         // Drives the GPU Memory controls' diffusion gate; set alongside the
         // GPU fields on every load path so the gate can't read stale.
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
diff --git a/studio/frontend/src/features/chat/api/chat-api.ts b/studio/frontend/src/features/chat/api/chat-api.ts
index 475bd0f801..ffaf099f29 100644
--- a/studio/frontend/src/features/chat/api/chat-api.ts
+++ b/studio/frontend/src/features/chat/api/chat-api.ts
@@ -33,6 +33,7 @@ import type {
 } from "../types/api";
 
 export const CHAT_HISTORY_UPDATED_EVENT = "unsloth-chat-history-updated";
+export const CHAT_PROJECTS_UPDATED_EVENT = "unsloth-chat-projects-updated";
 
 /**
  * Thrown when the chat SSE stream ends without a terminal signal (`[DONE]` or a
@@ -55,6 +56,13 @@ export function notifyChatHistoryUpdated(): void {
   }
 }
 
+function notifyChatProjectsUpdated(): void {
+  notifyChatHistoryUpdated();
+  if (typeof window !== "undefined") {
+    window.dispatchEvent(new Event(CHAT_PROJECTS_UPDATED_EVENT));
+  }
+}
+
 function parseErrorText(status: number, body: unknown): string {
   if (body && typeof body === "object") {
     const detail = (body as { detail?: unknown }).detail;
@@ -235,6 +243,7 @@ export async function resolveToolConfirmation(
 
 export interface CachedGgufRepo {
   repo_id: string;
+  load_id?: string | null;
   size_bytes: number;
   cache_path: string;
   /** Epoch seconds of the newest downloaded quant; sorts Downloaded
@@ -344,24 +353,28 @@ export async function listLocalModels(
 export async function listCachedGguf(
   signal?: AbortSignal,
 ): Promise<CachedGgufRepo[]> {
-  const response = await authFetch("/api/models/cached-gguf", { signal });
+  const response = await authFetch("/api/hub/cached-gguf", { signal });
   const data = await parseJsonOrThrow<{ cached: CachedGgufRepo[] }>(response);
   return data.cached;
 }
 
 export interface CachedModelRepo {
   repo_id: string;
+  load_id?: string | null;
   size_bytes: number;
   /** Epoch seconds of the newest downloaded weight file; sorts Downloaded
    * newest-first. Optional for older-backend compatibility. */
   last_modified?: number;
+  /** Owning cache dir; sent so a delete targets this copy, not the active
+   * cache. Optional for older-backend compatibility. */
+  cache_path?: string | null;
 }
 
 export async function listCachedModels(
   hfToken?: string | null,
   signal?: AbortSignal,
 ): Promise<CachedModelRepo[]> {
-  const response = await authFetch("/api/models/cached-models", {
+  const response = await authFetch("/api/hub/cached-models", {
     headers: hubTokenHeader(hfToken),
     signal,
   });
@@ -369,14 +382,33 @@ export async function listCachedModels(
   return data.cached;
 }
 
-export async function deleteCachedModel(
+export interface CachedModelPath {
+  path: string;
+  is_dir: boolean;
+}
+
+/** Absolute on-disk path of a cached repo or one of its GGUF variants. */
+export async function getCachedModelPath(
+  repoId: string,
+  variant?: string,
+): Promise<CachedModelPath> {
+  const params = new URLSearchParams({ repo_id: repoId });
+  if (variant) params.set("variant", variant);
+  const response = await authFetch(
+    `/api/models/cached-model-path?${params.toString()}`,
+  );
+  return parseJsonOrThrow<CachedModelPath>(response);
+}
+
+/** Reveal a cached repo (or one GGUF variant's file) in the OS file manager. */
+export async function revealCachedModel(
   repoId: string,
   variant?: string,
 ): Promise<void> {
   const payload: Record<string, string> = { repo_id: repoId };
   if (variant) payload.variant = variant;
-  const response = await authFetch("/api/models/delete-cached", {
-    method: "DELETE",
+  const response = await authFetch("/api/models/reveal-cached-model", {
+    method: "POST",
     headers: { "Content-Type": "application/json" },
     body: JSON.stringify(payload),
   });
@@ -644,7 +676,7 @@ export async function saveChatProject(
     body: JSON.stringify(project),
   });
   const saved = await parseJsonOrThrow<ProjectRecord>(response);
-  notifyChatHistoryUpdated();
+  notifyChatProjectsUpdated();
   return saved;
 }
 
@@ -661,7 +693,7 @@ export async function updateChatProject(
     },
   );
   const project = await parseJsonOrThrow<ProjectRecord>(response);
-  notifyChatHistoryUpdated();
+  notifyChatProjectsUpdated();
   return project;
 }
 
@@ -677,7 +709,7 @@ export async function deleteChatProject(
     { method: "DELETE" },
   );
   await parseJsonOrThrow<ProjectRecord>(response);
-  notifyChatHistoryUpdated();
+  notifyChatProjectsUpdated();
 }
 
 export async function listChatMessages(
@@ -893,8 +925,19 @@ export async function browseFolders(
 export async function listGgufVariants(
   repoId: string,
   hfToken?: string,
+  options?: {
+    preferLocalCache?: boolean;
+    localPath?: string | null;
+  },
 ): Promise<GgufVariantsResponse> {
   const params = new URLSearchParams({ repo_id: repoId });
+  if (options?.preferLocalCache) {
+    params.set("prefer_local_cache", "true");
+  }
+  const localPath = options?.localPath?.trim();
+  if (localPath) {
+    params.set("local_path", localPath);
+  }
   const response = await authFetch(`/api/models/gguf-variants?${params}`, {
     headers: hubTokenHeader(hfToken),
   });
diff --git a/studio/frontend/src/features/chat/artifacts/artifact-card.tsx b/studio/frontend/src/features/chat/artifacts/artifact-card.tsx
index 0345dc6e2a..531b17522d 100644
--- a/studio/frontend/src/features/chat/artifacts/artifact-card.tsx
+++ b/studio/frontend/src/features/chat/artifacts/artifact-card.tsx
@@ -145,12 +145,12 @@ export function ArtifactCard({
             <span className="truncate text-sm font-medium leading-tight text-foreground">
               {isCode ? "HTML Code" : artifact.title}
             </span>
-            <span className="truncate text-[11px] leading-none text-muted-foreground">
+            <span className="truncate text-ui-11 leading-none text-muted-foreground">
               HTML canvas
             </span>
           </span>
           {isStreaming && !isCode ? (
-            <span className="shimmer shrink-0 rounded-full bg-primary/10 px-2 py-0.5 text-[10px] font-medium text-primary motion-reduce:animate-none">
+            <span className="shimmer shrink-0 rounded-full bg-primary/10 px-2 py-0.5 text-ui-10 font-medium text-primary motion-reduce:animate-none">
               Generating
             </span>
           ) : null}
diff --git a/studio/frontend/src/features/chat/chat-page.tsx b/studio/frontend/src/features/chat/chat-page.tsx
index 217eaf8b6d..e46ea0ac46 100644
--- a/studio/frontend/src/features/chat/chat-page.tsx
+++ b/studio/frontend/src/features/chat/chat-page.tsx
@@ -2,24 +2,50 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import {
+  applyModelLoadConfigToRuntime,
+  currentRuntimePerModelConfig,
   type DeletedModelRef,
   type ExternalModelOption,
   type LoraModelOption,
   type ModelOption,
   ModelSelector,
-} from "@/components/assistant-ui/model-selector";
-import {
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
+  type ModelSelectorChangeMeta,
+  type PerModelConfig,
+  resolveInitialConfig,
+  SidebarModelConfig,
+  useActiveModelConfig,
+} from "@/features/model-picker";
 import { ProjectComposer, Thread } from "@/components/assistant-ui/thread";
 import { CopyableErrorChip } from "@/components/ui/copyable-error-chip";
 import {
   DropdownMenu,
   DropdownMenuContent,
   DropdownMenuItem,
+  DropdownMenuSeparator,
+  DropdownMenuSub,
+  DropdownMenuSubContent,
+  DropdownMenuSubTrigger,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
+import {
+  AlertDialog,
+  AlertDialogAction,
+  AlertDialogCancel,
+  AlertDialogContent,
+  AlertDialogDescription,
+  AlertDialogFooter,
+  AlertDialogHeader,
+  AlertDialogTitle,
+} from "@/components/ui/alert-dialog";
+import { Button } from "@/components/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import { Input } from "@/components/ui/input";
 import {
   ResizableHandle,
   ResizablePanel,
@@ -27,10 +53,10 @@ import {
 } from "@/components/ui/resizable";
 import { useSidebar } from "@/components/ui/sidebar";
 import { Tooltip, TooltipContent } from "@/components/ui/tooltip";
-import { useLatestRef } from "@/features/hub/hooks/use-latest-ref";
 import {
   DOWNLOAD_KIND,
   downloadManager,
+  useRepoDownload,
 } from "@/features/hub/download-manager";
 import {
   type NativeIntent,
@@ -43,14 +69,23 @@ import {
 } from "@/features/native-intents";
 import { GuidedTour, useGuidedTourController } from "@/features/tour";
 import { isTauri } from "@/lib/api-base";
+import { isDownloadCancelled } from "@/lib/native-files";
 import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import {
+  Archive03Icon,
   BubbleChatTemporaryIcon,
+  Delete02Icon,
+  Download01Icon,
   Edit03Icon,
+  Folder01Icon,
   Folder02Icon,
+  FolderExportIcon,
   LayoutAlignRightIcon,
+  MoreHorizontalIcon,
   MoreVerticalIcon,
+  PinIcon,
+  PinOffIcon,
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useNavigate } from "@tanstack/react-router";
@@ -68,7 +103,7 @@ import {
   useState,
 } from "react";
 import type { PanelImperativeHandle } from "react-resizable-panels";
-import { listLocalModels } from "./api/chat-api";
+import { listLocalModels, notifyChatHistoryUpdated } from "./api/chat-api";
 import { ArtifactSurface } from "./artifacts/artifact-surface";
 import {
   clearAutoOpenedArtifacts,
@@ -87,13 +122,21 @@ import {
 } from "./external-providers";
 import { useChatModelRuntime } from "./hooks/use-chat-model-runtime";
 import type { SelectedModelInput } from "./hooks/use-chat-model-runtime";
-import { useChatProjects } from "./hooks/use-chat-projects";
+import {
+  deleteChatProject,
+  moveChatItemToProject,
+  renameChatProject,
+  useChatProjects,
+} from "./hooks/use-chat-projects";
 import {
   type SidebarItem,
+  archiveChatItem,
+  deleteChatItem,
   renameChatItem,
   useChatSidebarItems,
 } from "./hooks/use-chat-sidebar-items";
-import { useStagedModelPreparation } from "./hooks/use-staged-model-preparation";
+import { usePinnedChatsStore } from "./stores/pinned-chats-store";
+import { usePinnedProjectsStore } from "./stores/pinned-projects-store";
 import {
   clearTrainingCompareHandoff,
   getTrainingCompareHandoff,
@@ -128,10 +171,8 @@ import {
   hasGgufSource,
   isDownloadableHubRepo,
   loadOptionalBool,
-  pendingSelectionMatches,
   useChatRuntimeStore,
 } from "./stores/chat-runtime-store";
-import type { PendingModelSelection } from "./stores/chat-runtime-store";
 import { useChatPreferencesStore } from "./stores/chat-preferences-store";
 import { useExternalProvidersStore } from "./stores/external-providers-store";
 import { buildChatTourSteps } from "./tour";
@@ -385,6 +426,7 @@ type CompareModelSelection = {
   id: string;
   isLora: boolean;
   ggufVariant?: string;
+  config?: PerModelConfig;
 };
 
 function modelMatchesDeleted(
@@ -609,7 +651,7 @@ const LoraCompareContent = memo(function LoraCompareContent({
           handleName="base"
           header={
             <div className="shrink-0 px-3 py-1.5">
-              <span className="text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
+              <span className="text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
                 Base Model
               </span>
             </div>
@@ -624,7 +666,7 @@ const LoraCompareContent = memo(function LoraCompareContent({
           borderClassName="border-t border-border/60 md:border-t-0 md:border-l"
           header={
             <div className="shrink-0 px-3 py-1.5 text-start md:text-end md:pr-[calc(4rem+var(--studio-chat-header-right-inset,var(--studio-window-control-inset,0px)))]">
-              <span className="text-[10px] font-semibold uppercase tracking-wider text-primary">
+              <span className="text-ui-10 font-semibold uppercase tracking-wider text-primary">
                 Fine-tuned
               </span>
             </div>
@@ -645,6 +687,8 @@ function GeneralCompareHeader({
   loraModels,
   externalModels,
   value,
+  selectedConfig,
+  selectedGgufVariant,
   onValueChange,
   onFoldersChange,
   onModelsChange,
@@ -655,9 +699,11 @@ function GeneralCompareHeader({
   loraModels: LoraModelOption[];
   externalModels: ExternalModelOption[];
   value: string;
+  selectedConfig?: PerModelConfig | null;
+  selectedGgufVariant?: string | null;
   onValueChange: (
     id: string,
-    meta: { isLora: boolean; ggufVariant?: string },
+    meta: ModelSelectorChangeMeta,
   ) => void;
   onFoldersChange?: () => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
@@ -684,6 +730,8 @@ function GeneralCompareHeader({
         loraModels={loraModels}
         externalModels={externalModels}
         value={value}
+        selectedConfig={selectedConfig}
+        selectedGgufVariant={selectedGgufVariant}
         onValueChange={onValueChange}
         onFoldersChange={onFoldersChange}
         onModelsChange={onModelsChange}
@@ -811,11 +859,14 @@ const GeneralCompareContent = memo(function GeneralCompareContent({
               loraModels={loraModels}
               externalModels={externalModels}
               value={model1.id}
+              selectedConfig={model1.config}
+              selectedGgufVariant={model1.ggufVariant}
               onValueChange={(id, meta) =>
                 setModel1({
                   id,
                   isLora: meta.isLora,
                   ggufVariant: meta.ggufVariant,
+                  config: meta.config,
                 })
               }
               onFoldersChange={onFoldersChange}
@@ -838,11 +889,14 @@ const GeneralCompareContent = memo(function GeneralCompareContent({
               loraModels={loraModels}
               externalModels={externalModels}
               value={model2.id}
+              selectedConfig={model2.config}
+              selectedGgufVariant={model2.ggufVariant}
               onValueChange={(id, meta) =>
                 setModel2({
                   id,
                   isLora: meta.isLora,
                   ggufVariant: meta.ggufVariant,
+                  config: meta.config,
                 })
               }
               onFoldersChange={onFoldersChange}
@@ -863,6 +917,47 @@ function formatProjectChatDate(timestamp: number): string {
   }).format(new Date(timestamp));
 }
 
+// Unique thread nonce; falls back off crypto.randomUUID for non-secure
+// (HTTP LAN) contexts where it is unavailable.
+function createThreadNonce(): string {
+  if (typeof globalThis.crypto?.randomUUID === "function") {
+    return globalThis.crypto.randomUUID();
+  }
+  return `${Date.now()}-${Math.random().toString(36).slice(2, 10)}`;
+}
+
+// Chat export formats, mirroring the sidebar chat menu.
+type ProjectChatExportFormat = "raw-jsonl" | "csv" | "sharegpt-jsonl";
+const PROJECT_CHAT_EXPORT_OPTIONS: Array<{
+  label: string;
+  format: ProjectChatExportFormat;
+}> = [
+  { label: "Raw JSONL", format: "raw-jsonl" },
+  { label: "CSV", format: "csv" },
+  { label: "ShareGPT JSONL", format: "sharegpt-jsonl" },
+];
+
+async function exportProjectConversation(
+  threadId: string,
+  format: ProjectChatExportFormat,
+): Promise<void> {
+  const exports = await import("./prompt-storage/prompt-storage-dialog");
+  if (format === "raw-jsonl") return exports.exportConversationRawJsonl(threadId);
+  if (format === "csv") return exports.exportConversationCsv(threadId);
+  return exports.exportConversationShareGPT(threadId);
+}
+
+async function exportProjectChatItem(
+  item: SidebarItem,
+  format: ProjectChatExportFormat,
+): Promise<void> {
+  const ids =
+    item.type === "single"
+      ? [item.id]
+      : (await listStoredChatThreads({ pairId: item.id })).map((t) => t.id);
+  for (const id of ids) await exportProjectConversation(id, format);
+}
+
 function extractMessageText(content: MessageRecord["content"]): string {
   if (typeof content === "string") {
     return content;
@@ -897,6 +992,9 @@ function ProjectLanding({
   items: SidebarItem[];
 }): ReactElement {
   const navigate = useNavigate();
+  // Gates body-portaled surfaces so they can't linger or act while the landing
+  // is off-route (e.g. behind another tab).
+  const active = useChatActive();
   const activeThreadId = useChatRuntimeStore((s) => s.activeThreadId);
   const initialActiveThreadRef = useRef<string | null>(null);
   const [projectTab, setProjectTab] = useState<"chats" | "sources">("chats");
@@ -904,7 +1002,7 @@ function ProjectLanding({
     null,
   );
   const [newThreadNonce, setNewThreadNonce] = useState(() =>
-    crypto.randomUUID(),
+    createThreadNonce(),
   );
   const [previews, setPreviews] = useState<
     Record<string, { snippet: string; date: string }>
@@ -923,13 +1021,65 @@ function ProjectLanding({
     title: string;
   } | null>(null);
 
+  // Project-level options (the header kebab menu).
+  const pinnedProjectIds = usePinnedProjectsStore((s) => s.pinnedIds);
+  const togglePinProject = usePinnedProjectsStore((s) => s.togglePin);
+  const projectPinned = pinnedProjectIds.includes(projectId);
+  const [renamingProject, setRenamingProject] = useState(false);
+  const [projectNameDraft, setProjectNameDraft] = useState("");
+  const [deletingProject, setDeletingProject] = useState(false);
+
+  async function handleProjectExport(
+    format: ProjectChatExportFormat,
+  ): Promise<void> {
+    try {
+      const threads = await listStoredChatThreads({
+        projectId,
+        includeArchived: false,
+      });
+      const ids = [...new Set(threads.map((t) => t.id))];
+      for (const id of ids) await exportProjectConversation(id, format);
+    } catch (error) {
+      if (!isDownloadCancelled(error)) toast.error("Export failed.");
+    }
+  }
+
+  async function commitProjectRename(): Promise<void> {
+    const name = projectNameDraft.trim();
+    setRenamingProject(false);
+    if (!name || name === projectName) return;
+    try {
+      await renameChatProject(projectId, name);
+    } catch (err) {
+      toast.error("Failed to rename project", {
+        description: err instanceof Error ? err.message : undefined,
+      });
+    }
+  }
+
+  async function commitProjectDelete(): Promise<void> {
+    setDeletingProject(false);
+    try {
+      await deleteChatProject(projectId);
+      // Refresh chat history so the project's now-deleted chats don't linger
+      // in the sidebar, matching the sidebar delete path.
+      notifyChatHistoryUpdated();
+      useChatRuntimeStore.getState().setActiveProjectId(null);
+      navigate({ to: "/chat", search: { new: createThreadNonce() } });
+    } catch (err) {
+      toast.error("Failed to delete project", {
+        description: err instanceof Error ? err.message : undefined,
+      });
+    }
+  }
+
   useEffect(() => {
     initialActiveThreadRef.current =
       useChatRuntimeStore.getState().activeThreadId;
     useChatRuntimeStore.getState().setActiveThreadId(null);
     useChatRuntimeStore.getState().setContextUsage(null);
     setPendingNewThreadId(null);
-    setNewThreadNonce(crypto.randomUUID());
+    setNewThreadNonce(createThreadNonce());
     setRenamingId(null);
     setPendingRename(null);
   }, [projectId]);
@@ -964,16 +1114,98 @@ function ProjectLanding({
     [renameDraft],
   );
 
+  // Full chat actions, matching the sidebar chat menu.
+  const { projects } = useChatProjects();
+  const pinnedChatIds = usePinnedChatsStore((s) => s.pinnedIds);
+  const togglePinnedChat = usePinnedChatsStore((s) => s.togglePin);
+  const confirmDeleteChats = useChatPreferencesStore(
+    (s) => s.confirmDeleteChats,
+  );
+  const pinnedChatIdSet = useMemo(
+    () => new Set(pinnedChatIds),
+    [pinnedChatIds],
+  );
+  const [confirmingDelete, setConfirmingDelete] = useState<SidebarItem | null>(
+    null,
+  );
+
+  // Landing has no active thread selected, so the onView callback here is a
+  // no-op; the items list refreshes itself once storage emits its update.
+  const noopView = useCallback(() => {}, []);
+
+  const handleArchive = useCallback(
+    async (item: SidebarItem) => {
+      try {
+        await archiveChatItem(item, activeThreadId ?? undefined, noopView);
+      } catch (err) {
+        toast.error("Failed to archive chat", {
+          description: err instanceof Error ? err.message : undefined,
+        });
+      }
+    },
+    [activeThreadId, noopView],
+  );
+
+  const runDelete = useCallback(
+    async (item: SidebarItem) => {
+      try {
+        await deleteChatItem(item, activeThreadId ?? undefined, noopView);
+      } catch (err) {
+        toast.error("Failed to delete chat", {
+          description: err instanceof Error ? err.message : undefined,
+        });
+      }
+    },
+    [activeThreadId, noopView],
+  );
+
+  const handleDelete = useCallback(
+    (item: SidebarItem) => {
+      if (confirmDeleteChats) setConfirmingDelete(item);
+      else void runDelete(item);
+    },
+    [confirmDeleteChats, runDelete],
+  );
+
+  const handleMoveToProject = useCallback(
+    async (item: SidebarItem, targetId: string | null) => {
+      try {
+        await moveChatItemToProject(item, targetId);
+      } catch (err) {
+        toast.error("Failed to move chat", {
+          description: err instanceof Error ? err.message : undefined,
+        });
+      }
+    },
+    [],
+  );
+
+  const handleExport = useCallback(
+    async (item: SidebarItem, format: ProjectChatExportFormat) => {
+      try {
+        await exportProjectChatItem(item, format);
+      } catch (error) {
+        if (!isDownloadCancelled(error)) toast.error("Export failed.");
+      }
+    },
+    [],
+  );
+
   useEffect(() => {
     if (!activeThreadId) {
-      setPendingNewThreadId(null);
+      // Leaving a created chat for a new one: rotate the nonce so the runtime
+      // switches to a fresh thread instead of appending to the old chat.
+      if (pendingNewThreadId) {
+        setNewThreadNonce(createThreadNonce());
+        setPendingNewThreadId(null);
+      }
       return;
     }
     if (activeThreadId === initialActiveThreadRef.current) {
       return;
     }
     setPendingNewThreadId(activeThreadId);
-  }, [activeThreadId]);
+  }, [activeThreadId, pendingNewThreadId]);
 
   useEffect(() => {
     let cancelled = false;
@@ -1037,8 +1269,8 @@ function ProjectLanding({
             } as CSSProperties
           }
         >
-          {/* 46rem matches the composer so every block shares the same edges. */}
-          <div className="mx-auto flex w-full max-w-[46rem] flex-col pt-[120px] pb-14">
+          {/* Slightly narrower than the composer max; every block shares this. */}
+          <div className="mx-auto flex w-full max-w-[44rem] flex-col pt-[120px] pb-14">
             <div className="mb-12 flex items-center gap-4">
               <span className="flex size-13 shrink-0 items-center justify-center rounded-[18px] bg-muted text-foreground/80">
                 <HugeiconsIcon
@@ -1047,9 +1279,64 @@ function ProjectLanding({
                   className="size-6.5"
                 />
               </span>
-              <h1 className="truncate font-sans text-[30px] font-medium leading-tight tracking-normal text-foreground">
+              <h1 className="min-w-0 flex-1 truncate font-sans text-ui-30 font-medium leading-tight tracking-normal text-foreground">
                 {projectName}
               </h1>
+              <DropdownMenu>
+                <DropdownMenuTrigger asChild={true}>
+                  <button
+                    type="button"
+                    aria-label="Project options"
+                    className="inline-flex size-9 shrink-0 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-muted hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring data-[state=open]:bg-muted data-[state=open]:text-foreground"
+                  >
+                    <HugeiconsIcon icon={MoreHorizontalIcon} strokeWidth={1.75} className="size-5" />
+                  </button>
+                </DropdownMenuTrigger>
+                <DropdownMenuContent
+                  side="bottom"
+                  align="end"
+                  sideOffset={6}
+                  className="unsloth-plus-menu menu-flat-destructive w-52"
+                >
+                  <DropdownMenuItem
+                    onSelect={() => {
+                      setProjectNameDraft(projectName);
+                      setRenamingProject(true);
+                    }}
+                  >
+                    <HugeiconsIcon icon={Edit03Icon} strokeWidth={1.75} className="size-icon" />
+                    <span>Rename project</span>
+                  </DropdownMenuItem>
+                  <DropdownMenuItem onSelect={() => togglePinProject(projectId)}>
+                    <HugeiconsIcon icon={projectPinned ? PinOffIcon : PinIcon} strokeWidth={1.75} className="size-icon" />
+                    <span>{projectPinned ? "Unpin project" : "Pin project"}</span>
+                  </DropdownMenuItem>
+                  <DropdownMenuSub>
+                    <DropdownMenuSubTrigger>
+                      <HugeiconsIcon icon={Download01Icon} strokeWidth={1.75} className="size-icon" />
+                      <span>Export</span>
+                    </DropdownMenuSubTrigger>
+                    <DropdownMenuSubContent className="unsloth-plus-menu w-48">
+                      {PROJECT_CHAT_EXPORT_OPTIONS.map(({ label, format }) => (
+                        <DropdownMenuItem
+                          key={format}
+                          onSelect={() => void handleProjectExport(format)}
+                        >
+                          {label}
+                        </DropdownMenuItem>
+                      ))}
+                    </DropdownMenuSubContent>
+                  </DropdownMenuSub>
+                  <DropdownMenuSeparator />
+                  <DropdownMenuItem
+                    variant="destructive"
+                    onSelect={() => setDeletingProject(true)}
+                  >
+                    <HugeiconsIcon icon={Delete02Icon} strokeWidth={1.75} className="size-icon" />
+                    <span>Delete project</span>
+                  </DropdownMenuItem>
+                </DropdownMenuContent>
+              </DropdownMenu>
             </div>
 
             <ProjectComposer
@@ -1062,7 +1349,7 @@ function ProjectLanding({
                 type="button"
                 onClick={() => setProjectTab("chats")}
                 data-active={projectTab === "chats"}
-                className="h-10 rounded-full px-5 text-[14px] font-semibold transition-colors data-[active=true]:bg-muted data-[active=true]:text-foreground data-[active=false]:text-muted-foreground data-[active=false]:hover:bg-nav-surface-hover"
+                className="h-10 rounded-full px-5 text-ui-14 font-semibold transition-colors data-[active=true]:bg-muted data-[active=true]:text-foreground data-[active=false]:text-muted-foreground data-[active=false]:hover:bg-nav-surface-hover"
               >
                 Chats
               </button>
@@ -1070,12 +1357,9 @@ function ProjectLanding({
                 type="button"
                 onClick={() => setProjectTab("sources")}
                 data-active={projectTab === "sources"}
-                className="flex h-10 items-center gap-1.5 rounded-full px-5 text-[14px] font-semibold transition-colors data-[active=true]:bg-muted data-[active=true]:text-foreground data-[active=false]:text-muted-foreground data-[active=false]:hover:bg-nav-surface-hover"
+                className="h-10 rounded-full px-5 text-ui-14 font-semibold transition-colors data-[active=true]:bg-muted data-[active=true]:text-foreground data-[active=false]:text-muted-foreground data-[active=false]:hover:bg-nav-surface-hover"
               >
                 Sources
-                <span className="rounded-full bg-emerald-500/10 px-2 py-1 text-[10px] font-semibold leading-none text-emerald-700 dark:text-emerald-300">
-                  New
-                </span>
               </button>
             </div>
 
@@ -1111,9 +1395,17 @@ function ProjectLanding({
                               setRenameDraft(event.target.value)
                             }
                             onKeyDown={(event) => {
+                              // Ignore keydowns fired mid-IME-composition (CJK)
+                              // so a candidate-confirming Enter or candidate-
+                              // cancelling Escape does not commit/cancel the
+                              // rename. Guard before the key branch so Escape is
+                              // covered too (isComposing on WebKit, 229 on Chromium).
+                              if (
+                                event.nativeEvent.isComposing ||
+                                event.keyCode === 229
+                              )
+                                return;
                               if (event.key === "Enter") {
-                                if (event.nativeEvent.isComposing || event.keyCode === 229)
-                                  return;
                                 event.preventDefault();
                                 skipRenameBlurRef.current = true;
                                 void commitRename(item);
@@ -1133,13 +1425,8 @@ function ProjectLanding({
                             onFocus={(event) => event.currentTarget.select()}
                             maxLength={120}
                             aria-label="Rename chat"
-                            className="w-full border-0 bg-transparent text-[15px] font-semibold leading-5 text-foreground outline-none"
+                            className="w-full border-0 bg-transparent text-ui-15 font-semibold leading-5 text-foreground outline-none"
                           />
-                          {preview?.snippet ? (
-                            <div className="mt-0.5 truncate text-[14px] leading-5 text-muted-foreground">
-                              {preview.snippet}
-                            </div>
-                          ) : null}
                         </div>
                       </div>
                     );
@@ -1163,16 +1450,11 @@ function ProjectLanding({
                         className="flex min-h-[58px] min-w-0 flex-1 items-center gap-4 rounded-full px-4 py-2 text-left"
                       >
                         <div className="min-w-0 flex-1">
-                          <div className="truncate text-[15px] font-semibold leading-5 text-foreground">
+                          <div className="truncate text-ui-15 font-semibold leading-5 text-foreground">
                             {displayTitle}
                           </div>
-                          {preview?.snippet ? (
-                            <div className="mt-0.5 truncate text-[14px] leading-5 text-muted-foreground">
-                              {preview.snippet}
-                            </div>
-                          ) : null}
                         </div>
-                        <span className="shrink-0 text-[14px] text-muted-foreground transition-opacity max-md:opacity-0 pointer-coarse:opacity-0 group-hover:opacity-0 group-has-[[data-state=open]]:opacity-0">
+                        <span className="shrink-0 text-ui-14 text-muted-foreground transition-opacity max-md:opacity-0 pointer-coarse:opacity-0 group-hover:opacity-0 group-has-[[data-state=open]]:opacity-0">
                           {preview?.date ??
                             formatProjectChatDate(item.createdAt)}
                         </span>
@@ -1196,7 +1478,7 @@ function ProjectLanding({
                           side="bottom"
                           align="end"
                           sideOffset={4}
-                          className="unsloth-plus-menu w-56"
+                          className="unsloth-plus-menu menu-flat-destructive w-56"
                         >
                           <DropdownMenuItem onSelect={() => openRename(item)}>
                             <HugeiconsIcon
@@ -1206,6 +1488,106 @@ function ProjectLanding({
                             />
                             <span>Rename</span>
                           </DropdownMenuItem>
+                          <DropdownMenuItem
+                            onSelect={() => togglePinnedChat(item.id)}
+                          >
+                            <HugeiconsIcon
+                              icon={
+                                pinnedChatIdSet.has(item.id)
+                                  ? PinOffIcon
+                                  : PinIcon
+                              }
+                              strokeWidth={1.75}
+                              className="size-icon"
+                            />
+                            <span>
+                              {pinnedChatIdSet.has(item.id)
+                                ? "Unpin chat"
+                                : "Pin chat"}
+                            </span>
+                          </DropdownMenuItem>
+                          <DropdownMenuSub>
+                            <DropdownMenuSubTrigger>
+                              <HugeiconsIcon
+                                icon={FolderExportIcon}
+                                strokeWidth={1.75}
+                                className="size-icon"
+                              />
+                              <span>Move to project</span>
+                            </DropdownMenuSubTrigger>
+                            <DropdownMenuSubContent className="unsloth-plus-menu w-52">
+                              <DropdownMenuItem
+                                disabled={item.projectId !== projectId}
+                                onSelect={() =>
+                                  void handleMoveToProject(item, null)
+                                }
+                              >
+                                <span>Recents</span>
+                              </DropdownMenuItem>
+                              {projects.map((p) => (
+                                <DropdownMenuItem
+                                  key={p.id}
+                                  disabled={item.projectId === p.id}
+                                  onSelect={() =>
+                                    void handleMoveToProject(item, p.id)
+                                  }
+                                >
+                                  <HugeiconsIcon
+                                    icon={Folder01Icon}
+                                    strokeWidth={1.75}
+                                    className="size-icon"
+                                  />
+                                  <span className="truncate">{p.name}</span>
+                                </DropdownMenuItem>
+                              ))}
+                            </DropdownMenuSubContent>
+                          </DropdownMenuSub>
+                          <DropdownMenuSub>
+                            <DropdownMenuSubTrigger>
+                              <HugeiconsIcon
+                                icon={Download01Icon}
+                                strokeWidth={1.75}
+                                className="size-icon"
+                              />
+                              <span>Export</span>
+                            </DropdownMenuSubTrigger>
+                            <DropdownMenuSubContent className="unsloth-plus-menu w-52">
+                              {PROJECT_CHAT_EXPORT_OPTIONS.map(
+                                ({ label, format }) => (
+                                  <DropdownMenuItem
+                                    key={format}
+                                    onSelect={() =>
+                                      void handleExport(item, format)
+                                    }
+                                  >
+                                    {label}
+                                  </DropdownMenuItem>
+                                ),
+                              )}
+                            </DropdownMenuSubContent>
+                          </DropdownMenuSub>
+                          <DropdownMenuSeparator />
+                          <DropdownMenuItem
+                            onSelect={() => void handleArchive(item)}
+                          >
+                            <HugeiconsIcon
+                              icon={Archive03Icon}
+                              strokeWidth={1.75}
+                              className="size-icon"
+                            />
+                            <span>Archive</span>
+                          </DropdownMenuItem>
+                          <DropdownMenuItem
+                            variant="destructive"
+                            onSelect={() => handleDelete(item)}
+                          >
+                            <HugeiconsIcon
+                              icon={Delete02Icon}
+                              strokeWidth={1.75}
+                              className="size-icon"
+                            />
+                            <span>Delete</span>
+                          </DropdownMenuItem>
                         </DropdownMenuContent>
                       </DropdownMenu>
                     </div>
@@ -1216,6 +1598,96 @@ function ProjectLanding({
           </div>
         </div>
       )}
+      <AlertDialog
+        open={active && confirmingDelete !== null}
+        onOpenChange={(open) => {
+          if (!open) setConfirmingDelete(null);
+        }}
+      >
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>Delete chat</AlertDialogTitle>
+            <AlertDialogDescription>
+              This permanently deletes "{confirmingDelete?.title}". This cannot
+              be undone.
+            </AlertDialogDescription>
+          </AlertDialogHeader>
+          <AlertDialogFooter>
+            <AlertDialogCancel>Cancel</AlertDialogCancel>
+            <AlertDialogAction
+              onClick={() => {
+                const target = confirmingDelete;
+                setConfirmingDelete(null);
+                if (target) void runDelete(target);
+              }}
+            >
+              Delete
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
+      <Dialog
+        open={active && renamingProject}
+        onOpenChange={(open) => {
+          if (!open) setRenamingProject(false);
+        }}
+      >
+        <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-md">
+          <DialogHeader>
+            <DialogTitle>Rename project</DialogTitle>
+          </DialogHeader>
+          <Input
+            value={projectNameDraft}
+            onChange={(e) => setProjectNameDraft(e.target.value)}
+            onKeyDown={(e) => {
+              if (e.key === "Enter") {
+                e.preventDefault();
+                void commitProjectRename();
+              }
+            }}
+            autoFocus={true}
+            maxLength={120}
+            placeholder="Project name"
+            aria-label="Project name"
+            className="focus-visible:border-input focus-visible:ring-0"
+          />
+          <DialogFooter className="flex-wrap gap-2 sm:justify-end">
+            <Button type="button" variant="ghost" onClick={() => setRenamingProject(false)}>
+              Cancel
+            </Button>
+            <Button
+              type="button"
+              onClick={() => void commitProjectRename()}
+              disabled={
+                !projectNameDraft.trim() || projectNameDraft.trim() === projectName
+              }
+            >
+              Save
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+      <AlertDialog
+        open={active && deletingProject}
+        onOpenChange={(open) => {
+          if (!open) setDeletingProject(false);
+        }}
+      >
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>Delete project</AlertDialogTitle>
+            <AlertDialogDescription>
+              Delete "{projectName}"? Its chats will be permanently deleted.
+            </AlertDialogDescription>
+          </AlertDialogHeader>
+          <AlertDialogFooter>
+            <AlertDialogCancel>Cancel</AlertDialogCancel>
+            <AlertDialogAction onClick={() => void commitProjectDelete()}>
+              Delete
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
     </ChatRuntimeProvider>
   );
 }
@@ -1236,6 +1708,13 @@ export function validateChatSearch(search: Record<string, unknown>): ChatSearch
   };
 }
 
+type PendingHubAutoLoad = {
+  selection: SelectedModelInput;
+  contextKey: string;
+  originCheckpoint: string;
+  originGgufVariant: string | null;
+};
+
 // `search` comes from RootLayout (not useSearch) so ChatPage stays mounted off-route
 // (keeping an in-flight generation alive), frozen to the last /chat search. `active`
 // is false off-route: close body-portaled surfaces and stop route-specific listeners
@@ -1248,30 +1727,6 @@ export function ChatPage({
 
   const settingsOpen = useChatRuntimeStore((s) => s.settingsPanelOpen);
   const setSettingsOpen = useChatRuntimeStore((s) => s.setSettingsPanelOpen);
-  // Deferred-load staging: downloads a staged GGUF (if needed) and reads its
-  // header context so the sheet can show the context slider before the load.
-  // autoLoad picks instead load the cached file as soon as the download ends;
-  // selectModel is defined below, so the load runs through a ref.
-  const autoLoadStagedRef = useRef<
-    ((pending: PendingModelSelection) => void) | null
-  >(null);
-  const stagedDownload = useStagedModelPreparation({
-    onAutoLoad: (pending) => autoLoadStagedRef.current?.(pending),
-  });
-  // Abandon a staged pick: the store action cancels its in-flight download and
-  // reverts the edited knobs, so nothing lingers after the user walks away.
-  const abandonStaged = useCallback(() => {
-    useChatRuntimeStore.getState().abandonStagedModel();
-  }, []);
-  // Detach a staged pick on navigation without cancelling its download: the
-  // transfer keeps running in the manager and lands in cache, like Hub.
-  const detachStaged = useCallback(() => {
-    useChatRuntimeStore.getState().abandonStagedModel({ keepDownload: true });
-  }, []);
-  // Tracks whether the chat page is still mounted, so a staged-load failure that
-  // resolves after the user left chat doesn't resurrect the abandoned pick.
-  const mountedRef = useRef(true);
-  useEffect(() => () => void (mountedRef.current = false), []);
   const incognito = useChatRuntimeStore((s) => s.incognito);
   const setIncognito = useChatRuntimeStore((s) => s.setIncognito);
   const incognitoLabel = incognito
@@ -1363,6 +1818,9 @@ export function ChatPage({
   const ggufContextLength = useChatRuntimeStore(
     (state) => state.ggufContextLength,
   );
+  const ggufNativeContextLength = useChatRuntimeStore(
+    (state) => state.ggufNativeContextLength,
+  );
   const contextUsage = useChatRuntimeStore((state) => state.contextUsage);
   const modelsFromStore = useChatRuntimeStore((state) => state.models);
   const lorasFromStore = useChatRuntimeStore((state) => state.loras);
@@ -1440,39 +1898,37 @@ export function ChatPage({
     refreshRef.current = refresh;
     selectModelRef.current = selectModel;
   }, [refresh, selectModel]);
-  // Load a cached autoLoad pick once its download finishes. The sheet was never
-  // opened, so on a load failure just drop the orphaned staged knobs. The knobs
-  // were already seeded on stage, so keepSpeculative only when a config was
-  // saved -- otherwise the standing speculative preference should win.
-  autoLoadStagedRef.current = (pending) => {
-    // Blobs are saved for GGUF picks only (the sheet gates on it), so don't
-    // let a legacy non-GGUF blob claim a seeded config here.
-    const remembered = hasGgufSource(pending)
-      ? loadRememberedLoadSettings(rememberedLoadSettingsKey(pending))
-      : null;
-    void selectModel({
-      ...pending,
-      isDownloaded: true,
-      forceReload: true,
-      keepSpeculative: remembered != null,
-      throwOnError: true,
-    }).catch(() => {
-      const store = useChatRuntimeStore.getState();
-      // selectModel only clears pendingSelection on success, so a failed
-      // auto-load leaves our staged pick (and its edited load knobs) behind.
-      // Abandon it when it is still the active stage; otherwise just revert the
-      // settings if the stage was already cleared by something else.
-      if (pendingSelectionMatches(store.pendingSelection, pending)) {
-        store.abandonStagedModel();
-      } else if (!store.pendingSelection) {
-        store.resetModelSettingsToLoaded();
-      }
-    });
-  };
+  const rememberedConfigFor = useCallback(
+    (selection: {
+      id: string;
+      ggufVariant?: string | null;
+      source?: string;
+    }) => {
+      if (selection.source === "external") return null;
+      const resolved = resolveInitialConfig(selection.id, selection.ggufVariant);
+      return resolved.remembered ? resolved.config : null;
+    },
+    [],
+  );
   const isExternalModel = useMemo(
     () => isExternalModelId(inferenceParams.checkpoint),
     [inferenceParams.checkpoint],
   );
+  const {
+    checkpoint: runtimeCheckpoint,
+    isGguf: runtimeModelIsGguf,
+    config: activeModelConfig,
+  } = useActiveModelConfig();
+  const activeModelIsGguf =
+    runtimeCheckpoint != null && !isExternalModel && runtimeModelIsGguf;
+  const activeModelIsLora = useMemo(() => {
+    const checkpoint = inferenceParams.checkpoint;
+    if (!checkpoint || isExternalModel) return false;
+    const model = modelsFromStore.find((entry) => entry.id === checkpoint);
+    if (model) return model.isLora;
+    const lora = lorasFromStore.find((entry) => entry.id === checkpoint);
+    return lora?.exportType === "lora";
+  }, [inferenceParams.checkpoint, isExternalModel, modelsFromStore, lorasFromStore]);
   const reasoningEnabled = useChatRuntimeStore((s) => s.reasoningEnabled);
   const reasoningStyle = useChatRuntimeStore((s) => s.reasoningStyle);
   const reasoningEffort = useChatRuntimeStore((s) => s.reasoningEffort);
@@ -1783,75 +2239,21 @@ export function ChatPage({
     closeArtifactSurface();
   }, [activeThreadId, closeArtifactSurface, selectedArtifact, view]);
 
-  // Abandon a staged (not-yet-loaded) pick when the chat context actually
-  // changes — switching threads, leaving single view, or starting a new chat /
-  // project — so a stale Load button can't resurface in a different context.
-  // New Chat keeps activeThreadId null and only bumps the `new` search nonce, so
-  // the key includes the route identity, not just the thread. Mirrors the
-  // incognito reset pattern. (Route exit is handled in __root.tsx, which runs
-  // after this unmounts.) Clear only on a real change, never on mount: staging
-  // from the Hub sets pendingSelection then navigates here, and clearing on
-  // mount would wipe it. Comparing the previous context (rather than a first-run
-  // flag) is also safe under StrictMode's double-invoke and component remounts.
-  const chatContextKey = `${view.mode}|${activeThreadId ?? ""}|${search.new ?? ""}|${search.project ?? ""}`;
-  const chatContextKeyRef = useLatestRef(chatContextKey);
-  const prevChatContextRef = useRef<string | null>(null);
-  useEffect(() => {
-    const prev = prevChatContextRef.current;
-    prevChatContextRef.current = chatContextKey;
-    if (prev === null || prev === chatContextKey) return;
-    detachStaged();
-  }, [chatContextKey, detachStaged]);
-
   const hasActiveModel = Boolean(inferenceParams.checkpoint);
-  // Load immediately, or — when "Load on selection" is off — stage the pick so
-  // its load options can be set first. Shared by the main selector, native
-  // drag-drop/picker, and the dropped-file chip (the Hub stages via the store).
+  const chatContextKey = `${view.mode}|${activeThreadId ?? ""}|${search.new ?? ""}|${search.project ?? ""}`;
+  const [pendingHubAutoLoad, setPendingHubAutoLoad] =
+    useState<PendingHubAutoLoad | null>(null);
   const stageOrLoad = useCallback(
     async (selection: SelectedModelInput) => {
       const store = useChatRuntimeStore.getState();
-      // An un-cached HF repo (GGUF variant or a full non-GGUF snapshot) downloads
-      // through the manager first (global indicator), then auto-loads. Everything
-      // else -- cached picks, local/native files, LoRA, external -- loads now.
       const wantManagerDownload =
         isDownloadableHubRepo(selection) && !selection.isDownloaded;
-      if (
-        (!hasGgufSource(selection) && !wantManagerDownload) ||
-        (store.loadOnSelection && selection.isDownloaded)
-      ) {
-        // Detach any staged pick first so its edited knobs (e.g. a custom
-        // context length) don't leak into this immediate load -- resolveLoad
-        // reads customContextLength before checking the target is GGUF. Detach
-        // (not abandon) keeps its download running.
-        detachStaged();
-        // Load-on-selection skips the sheet, so seed the saved knobs here the
-        // way the sheet's restore effect would; the switch would otherwise reset
-        // the remembered speculative choice (keepSpeculative below prevents it).
-        const remembered = hasGgufSource(selection)
-          ? loadRememberedLoadSettings(rememberedLoadSettingsKey(selection))
-          : null;
-        if (remembered) store.applyRememberedLoadSettings(remembered);
-        await selectModel(
-          remembered ? { ...selection, keepSpeculative: true } : selection,
-        );
-        return;
-      }
-      // Loads can't queue behind each other, but a download is independent: if
-      // the pick needs downloading, start it in the manager so it runs alongside
-      // the load. Nothing to download (already on device) just waits.
       if (store.modelLoading) {
-        // Both an uncached non-GGUF snapshot (wantManagerDownload) and an
-        // uncached remote GGUF quant download through the manager, so either can
-        // run in the background while another model loads. wantManagerDownload
-        // excludes GGUF by design, so the GGUF case is checked separately.
         const wantBackgroundDownload =
           wantManagerDownload ||
           (selection.source === "hub" &&
             hasGgufSource(selection) &&
             !selection.isDownloaded);
-        // The model currently loading already downloads as part of its own load
-        // (the /load flow fetches before setting the checkpoint), so re-picking
-        // it must not kick off a second transfer against the same cache.
         const isLoadingThisPick =
           !!loadingModel &&
           normalizeModelRef(loadingModel.id) ===
@@ -1862,11 +2264,6 @@ export function ChatPage({
             description: "It's downloading as part of the load in progress.",
           });
         } else if (wantBackgroundDownload) {
-          // Only claim the download started once a job is actually created. A
-          // transport conflict records state that is only resolvable from the
-          // Hub download card, so point the user there instead of showing a
-          // success toast for a transfer that never began; "busy" and "error"
-          // already surface their own toasts.
           const outcome = await downloadManager.requestStart({
             kind: DOWNLOAD_KIND.MODEL,
             repoId: selection.id,
@@ -1879,9 +2276,14 @@ export function ChatPage({
                 "It'll be ready to load once the current model finishes.",
             });
           } else if (outcome === "conflict") {
-            toast.info("Resume this download from the Hub", {
+            toast.info("Resume this download from Models", {
               description:
-                "An earlier partial download used a different transport. Open the Hub tab to resume or restart it.",
+                "An earlier partial download used a different transport. Open the Models tab to resume or restart it.",
+            });
+          } else if (outcome === "busy") {
+            toast.info("Download already in progress", {
+              description:
+                "Another download for this model is still running. Reselect it once that finishes to load it.",
             });
           }
         } else {
@@ -1891,23 +2293,128 @@ export function ChatPage({
         }
         return;
       }
-      // Detach the prior staged pick (keeping its download) before rebinding, so
-      // a second pick downloads alongside the first instead of cancelling it.
-      detachStaged();
-      store.stageModel({
-        id: selection.id,
-        isLora: selection.isLora,
-        ggufVariant: selection.ggufVariant,
-        isDownloaded: selection.isDownloaded,
-        expectedBytes: selection.expectedBytes,
-        nativePathToken: selection.nativePathToken,
-        isGguf: selection.isGguf,
-        isHubRepo: wantManagerDownload || undefined,
-        autoLoad: store.loadOnSelection,
+      const wantManagerStage =
+        wantManagerDownload ||
+        (selection.source === "hub" &&
+          hasGgufSource(selection) &&
+          !selection.isDownloaded);
+      if (wantManagerStage) {
+        setPendingHubAutoLoad((current) =>
+          current &&
+          current.selection.id === selection.id &&
+          (current.selection.ggufVariant ?? null) ===
+            (selection.ggufVariant ?? null) &&
+          current.contextKey === chatContextKey &&
+          current.originCheckpoint === store.params.checkpoint &&
+          current.originGgufVariant === store.activeGgufVariant
+            ? current
+            : {
+                selection,
+                contextKey: chatContextKey,
+                originCheckpoint: store.params.checkpoint,
+                originGgufVariant: store.activeGgufVariant,
+              },
+        );
+        return;
+      }
+      setPendingHubAutoLoad(null);
+      const previousConfig = currentRuntimePerModelConfig({
+        includeMaxSeqLength: true,
+      });
+      const hasAppliedConfig = applyModelLoadConfigToRuntime(
+        selection.config ?? rememberedConfigFor(selection),
+      );
+      await selectModel({
+        ...selection,
+        ...(hasAppliedConfig ? { keepSpeculative: true } : {}),
+        previousConfig,
       });
     },
-    [detachStaged, selectModel, loadingModel],
+    [selectModel, loadingModel, rememberedConfigFor, chatContextKey],
   );
+  useRepoDownload({
+    kind: DOWNLOAD_KIND.MODEL,
+    repoId: pendingHubAutoLoad?.selection.id ?? "__hub_autoload_idle__",
+    activeVariant: pendingHubAutoLoad?.selection.ggufVariant ?? null,
+    onComplete: (variant) => {
+      const pending = pendingHubAutoLoad;
+      if (
+        !pending ||
+        (pending.selection.ggufVariant ?? null) !== (variant ?? null)
+      ) {
+        return;
+      }
+      setPendingHubAutoLoad(null);
+      const store = useChatRuntimeStore.getState();
+      if (
+        !active ||
+        pending.contextKey !== chatContextKey ||
+        normalizeModelRef(pending.originCheckpoint) !==
+          normalizeModelRef(store.params.checkpoint) ||
+        pending.originGgufVariant !== store.activeGgufVariant
+      ) {
+        return;
+      }
+      void stageOrLoad({ ...pending.selection, isDownloaded: true });
+    },
+    onError: (variant) => {
+      if (
+        pendingHubAutoLoad &&
+        (pendingHubAutoLoad.selection.ggufVariant ?? null) === (variant ?? null)
+      ) {
+        setPendingHubAutoLoad(null);
+      }
+    },
+    onCancelled: (variant) => {
+      if (
+        pendingHubAutoLoad &&
+        (pendingHubAutoLoad.selection.ggufVariant ?? null) === (variant ?? null)
+      ) {
+        setPendingHubAutoLoad(null);
+      }
+    },
+  });
+  useEffect(() => {
+    const pending = pendingHubAutoLoad;
+    if (!pending) return;
+    let active = true;
+    void (async () => {
+      const outcome = await downloadManager.requestStart({
+        kind: DOWNLOAD_KIND.MODEL,
+        repoId: pending.selection.id,
+        variant: pending.selection.ggufVariant ?? null,
+        expectedBytes: pending.selection.expectedBytes ?? 0,
+      });
+      if (!active) return;
+      if (outcome === "started") {
+        toast.info("Downloading model", {
+          description: "It'll load automatically once the download finishes.",
+        });
+        return;
+      }
+      if (outcome === "conflict") {
+        // Keep pendingHubAutoLoad bound so this surface's cleanup does not wipe
+        // the conflict just recorded by requestStart (which the toast points the
+        // user to); resolving it from the Hub completes the download and this
+        // surface's onComplete auto-loads, mirroring the "started" branch.
+        toast.info("Resume this download from Models", {
+          description:
+            "An earlier partial download used a different transport. Open the Models tab to resume or restart it.",
+        });
+        return;
+      }
+      if (outcome === "busy") {
+        toast.info("Download already in progress", {
+          description:
+            "Another download for this model is still running. Reselect it once that finishes to load it.",
+        });
+      }
+      setPendingHubAutoLoad((current) => (current === pending ? null : current));
+    })();
+    return () => {
+      active = false;
+    };
+  }, [pendingHubAutoLoad]);
   const loadNativeModelIntent = useCallback(
     async (intent: NativeIntent, loadingDescription: string) => {
       const label =
@@ -1915,6 +2422,7 @@ export function ChatPage({
       await stageOrLoad({
         id: label,
         nativePathToken: intent.path.token,
+        nativePathExpiresAtMs: intent.path.expiresAtMs ?? null,
         isDownloaded: true,
         loadingDescription,
         forceReload: true,
@@ -1965,28 +2473,20 @@ export function ChatPage({
   const handleCheckpointChange = useCallback(
     (
       value: string,
-      meta?: {
-        source?: string;
-        isLora: boolean;
-        ggufVariant?: string;
-        isDownloaded?: boolean;
-        expectedBytes?: number;
-        isGguf?: boolean;
-      },
+      meta?: ModelSelectorChangeMeta,
     ) => {
       const store = useChatRuntimeStore.getState();
       const currentCheckpoint = store.params.checkpoint;
       const currentVariant = store.activeGgufVariant;
-      if (
-        !value ||
-        (value === currentCheckpoint &&
-          (meta?.ggufVariant ?? null) === (currentVariant ?? null))
-      )
+      if (!value) return;
+      setPendingHubAutoLoad(null);
+      const isSameLoadedModel =
+        value === currentCheckpoint &&
+        (meta?.ggufVariant ?? null) === (currentVariant ?? null);
+      if (isSameLoadedModel && !meta?.forceReload) {
         return;
+      }
       if (meta?.source === "external" || isExternalModelId(value)) {
-        // Switching to an external model abandons any staged local pick: cancel
-        // its download too (setCheckpoint below only clears the pending + knobs).
-        abandonStaged();
         const selectedExternal = parseExternalModelId(value);
         const selectedProvider = selectedExternal
           ? externalProvidersForChat.find(
@@ -2087,6 +2587,7 @@ export function ChatPage({
           ggufMaxContextLength: null,
           ggufNativeContextLength: null,
           activeNativePathToken: null,
+          activeNativePathExpiresAtMs: null,
           // Clear previous-model counters, else the relaxed external-provider
           // render gate shows stale stats until the next completion.
           contextUsage: null,
@@ -2158,19 +2659,18 @@ export function ChatPage({
           source: meta?.source,
           isLora: meta?.isLora,
           ggufVariant: meta?.ggufVariant,
-          isDownloaded: meta?.isDownloaded,
+          isDownloaded: meta?.isDownloaded || isSameLoadedModel,
           expectedBytes: meta?.expectedBytes,
           isGguf: meta?.isGguf,
+          config: meta?.config,
+          nativePathToken: meta?.nativePathToken,
+          nativePathExpiresAtMs: meta?.nativePathExpiresAtMs,
+          forceReload: isSameLoadedModel || undefined,
         };
-        // "Load on selection" off: stage the model and open settings so its
-        // load knobs (tensor parallel, context length…) can be set, then it
-        // loads once via the sheet's Load button. The currently loaded model
-        // stays put until the user commits.
         await stageOrLoad(selection);
       })();
     },
     [
-      abandonStaged,
       activeThreadId,
       externalProvidersForChat,
       modelsFromStore,
@@ -2178,6 +2678,45 @@ export function ChatPage({
       view,
     ],
   );
+  const handleReloadActiveModel = useCallback(
+    (config: PerModelConfig) => {
+      const checkpoint = inferenceParams.checkpoint;
+      if (!checkpoint) return;
+      const runtime = useChatRuntimeStore.getState();
+      const nativeToken = runtime.activeNativePathToken;
+      const nativeExpiry = runtime.activeNativePathExpiresAtMs;
+      // A file-picked GGUF is reachable only via its native path token, which
+      // the desktop host prunes after a TTL. Reusing an expired token makes the
+      // reload fail with an opaque error, so prompt the user to re-select the
+      // file instead.
+      if (nativeToken && nativeExpiry != null && Date.now() >= nativeExpiry) {
+        toast.error("This local model file's access has expired.", {
+          description: "Re-select the model file to reload it.",
+        });
+        return;
+      }
+      handleCheckpointChange(checkpoint, {
+        source: "local",
+        isLora: activeModelIsLora,
+        ggufVariant: activeGgufVariant ?? undefined,
+        // Without the native token the reload validates the display label as a
+        // repo and fails.
+        nativePathToken: nativeToken ?? undefined,
+        nativePathExpiresAtMs: nativeExpiry,
+        isGguf: activeModelIsGguf,
+        isDownloaded: true,
+        config,
+        forceReload: true,
+      });
+    },
+    [
+      inferenceParams.checkpoint,
+      activeGgufVariant,
+      activeModelIsLora,
+      activeModelIsGguf,
+      handleCheckpointChange,
+    ],
+  );
   const handleEject = useCallback(() => {
     void (async () => {
       if (await ejectModel()) {
@@ -2446,12 +2985,27 @@ export function ChatPage({
 
         const state = useChatRuntimeStore.getState();
         const targetLora = pickBestLoraForBase(state.loras, handoff.baseModel);
+        const selectWithConfig = async (
+          selection: Pick<SelectedModelInput, "id" | "isLora">,
+        ) => {
+          const previousConfig = currentRuntimePerModelConfig({
+            includeMaxSeqLength: true,
+          });
+          const hasAppliedConfig = applyModelLoadConfigToRuntime(
+            rememberedConfigFor(selection),
+          );
+          await selectModelRef.current({
+            ...selection,
+            ...(hasAppliedConfig ? { keepSpeculative: true } : {}),
+            previousConfig,
+          });
+        };
         if (targetLora) {
           console.info("[chat-handoff] loading lora", {
             id: targetLora.id,
             baseModel: targetLora.baseModel,
           });
-          await selectModelRef.current({ id: targetLora.id, isLora: true });
+          await selectWithConfig({ id: targetLora.id, isLora: true });
           if (canceled) return;
           useChatRuntimeStore.getState().setActiveThreadId(null);
           useChatRuntimeStore.getState().setContextUsage(null);
@@ -2468,10 +3022,7 @@ export function ChatPage({
           console.info("[chat-handoff] no lora match, loading base", {
             id: handoff.baseModel,
           });
-          await selectModelRef.current({
-            id: handoff.baseModel,
-            isLora: false,
-          });
+          await selectWithConfig({ id: handoff.baseModel, isLora: false });
           if (canceled) return;
         } else {
           console.warn("[chat-handoff] no lora/base match found", {
@@ -2491,7 +3042,7 @@ export function ChatPage({
     return () => {
       canceled = true;
     };
-  }, [active, navigate]);
+  }, [active, navigate, rememberedConfigFor]);
 
   const tourSteps = useMemo(
     () =>
@@ -2580,6 +3131,8 @@ export function ChatPage({
                 externalModels={externalModels}
                 value={inferenceParams.checkpoint}
                 activeGgufVariant={activeGgufVariant}
+                activeModelConfig={activeModelConfig}
+                activeGgufContextLength={ggufContextLength}
                 onValueChange={handleCheckpointChange}
                 onEject={handleEject}
                 onFoldersChange={refreshLocalModels}
@@ -2596,7 +3149,7 @@ export function ChatPage({
               />
             )}
             {incognito && view.mode === "single" && (
-              <div className="flex h-[var(--studio-chat-control-height,34px)] shrink-0 items-center gap-1.5 self-center rounded-full bg-primary/10 px-2.5 font-medium text-[13px] text-primary">
+              <div className="flex h-[var(--studio-chat-control-height,34px)] shrink-0 items-center gap-1.5 self-center rounded-full bg-primary/10 px-2.5 font-medium text-ui-13 text-primary">
                 <HugeiconsIcon
                   icon={BubbleChatTemporaryIcon}
                   strokeWidth={2}
@@ -2608,7 +3161,7 @@ export function ChatPage({
             {view.mode !== "compare" && currentProjectId && (
               <nav
                 aria-label="Project location"
-                className="flex h-[var(--studio-chat-control-height,34px)] min-w-0 items-center gap-1.5 self-center text-[13.5px] tracking-nav text-muted-foreground"
+                className="flex h-[var(--studio-chat-control-height,34px)] min-w-0 items-center gap-1.5 self-center text-ui-13p5 tracking-nav text-muted-foreground"
               >
                 <ProjectSwitcher
                   currentProject={currentProject}
@@ -2633,7 +3186,12 @@ export function ChatPage({
               <NativeModelChip
                 intent={pendingNativeModelIntent}
                 nativeReadsDisabled={!nativePathLeasesSupported}
-                onLoad={(selection) => stageOrLoad(selection)}
+                onLoad={() =>
+                  loadNativeModelIntent(
+                    pendingNativeModelIntent,
+                    "Loading selected local GGUF model.",
+                  )
+                }
               />
             ) : null}
             {loadingModel && loadToastDismissed ? (
@@ -2790,13 +3348,22 @@ export function ChatPage({
         open={active && settingsOpen}
         onOpenChange={(open) => {
           setSettingsOpen(open);
-          // Closing the sheet abandons a staged (not-yet-loaded) pick: cancel its
-          // download and revert the staged knobs so nothing lingers as a dirty
-          // edit (or a background download) on the loaded model.
-          if (!open) abandonStaged();
         }}
         params={inferenceParams}
         onParamsChange={setInferenceParams}
+        modelConfig={
+          view.mode !== "compare" && activeModelConfig && !modelLoading ? (
+            <SidebarModelConfig
+              modelId={inferenceParams.checkpoint}
+              ggufVariant={activeGgufVariant ?? null}
+              isGguf={activeModelIsGguf}
+              nativeContextLength={ggufNativeContextLength}
+              loadedContextLength={ggufContextLength}
+              loadedConfig={activeModelConfig}
+              onReload={handleReloadActiveModel}
+            />
+          ) : null
+        }
         isExternalModel={isExternalModel}
         providerCapabilities={activeProviderCapabilities}
         activeExternalProvider={activeExternalProvider}
@@ -2808,67 +3375,6 @@ export function ChatPage({
           );
         }}
         externalProviderType={activeExternalProviderType}
-        loadingModel={loadingModel}
-        onReloadModel={() => {
-          const state = useChatRuntimeStore.getState();
-          if (state.params.checkpoint) {
-            selectModel({
-              id: state.params.checkpoint,
-              ggufVariant: state.activeGgufVariant ?? undefined,
-              // A native (drag-drop / picked) GGUF's checkpoint is only a display
-              // label, so the reload needs its path token to re-mint a lease --
-              // else applying the now-exposed GPU/context controls can't resolve
-              // the file. Null for non-native loads, which reload by id as before.
-              nativePathToken: state.activeNativePathToken ?? undefined,
-              forceReload: true,
-              isDownloaded: true,
-              loadingDescription: "Reloading with updated chat template.",
-            });
-          }
-        }}
-        onLoadPendingModel={() => {
-          const pending = useChatRuntimeStore.getState().pendingSelection;
-          if (!pending) return;
-          const keyAtLoad = chatContextKey;
-          // forceReload: the staged model isn't loaded yet, so bypass the
-          // same-checkpoint dedupe. keepSpeculative: honor the speculative mode
-          // set on the sidebar.
-          void selectModel({
-            ...pending,
-            forceReload: true,
-            keepSpeculative: true,
-            throwOnError: true,
-          }).catch(() => {
-            // Recoverable failure (expired token, gated repo, OOM…): the pick is
-            // cleared only on success, so it normally stays staged with edited
-            // knobs intact — nothing to restore.
-            const store = useChatRuntimeStore.getState();
-            // Still staged (this pick, or a newer one queued meanwhile): leave it.
-            if (store.pendingSelection) return;
-            // Cleared mid-load (sheet closed / switched chats). Re-stage only if
-            // the staged-load is still wanted: same chat context, sheet still
-            // open, page still mounted.
-            const stillWanted =
-              mountedRef.current &&
-              store.settingsPanelOpen &&
-              chatContextKeyRef.current === keyAtLoad;
-            if (stillWanted) {
-              store.setPendingSelection(pending);
-            } else {
-              // Abandoned (closed the sheet / switched chats / left chat): drop
-              // the orphaned staged knob edits so they don't linger as dirty
-              // settings over the loaded model.
-              store.resetModelSettingsToLoaded();
-            }
-          });
-        }}
-        stagedDownloadFraction={stagedDownload.progress?.fraction ?? null}
-        onCancelStagedDownload={() =>
-          stagedDownload.cancelDownload(
-            useChatRuntimeStore.getState().pendingSelection?.ggufVariant ??
-              null,
-          )
-        }
       />
     </div>
     </ChatActiveContext.Provider>
diff --git a/studio/frontend/src/features/chat/chat-providers-dialog.tsx b/studio/frontend/src/features/chat/chat-providers-dialog.tsx
index e39955e576..bfe7c71918 100644
--- a/studio/frontend/src/features/chat/chat-providers-dialog.tsx
+++ b/studio/frontend/src/features/chat/chat-providers-dialog.tsx
@@ -997,7 +997,7 @@ export function ChatProvidersSettings({
 
   if (page === "form") {
     return (
-      <div className="-mt-3 flex min-h-0 flex-col gap-2">
+      <div className="@container -mt-3 flex min-h-0 flex-col gap-2">
         <header className="flex items-center gap-2 pr-8">
           <Button
             type="button"
@@ -1024,7 +1024,7 @@ export function ChatProvidersSettings({
         <div className="flex max-w-[760px] flex-col gap-3">
           <section className="overflow-hidden rounded-[8px] border border-border/70 bg-muted/[0.12]">
             <div className="divide-y divide-border/60">
-              <div className="grid grid-cols-[minmax(150px,0.8fr)_minmax(260px,1.2fr)] items-center gap-4 px-4 py-3 max-sm:grid-cols-1">
+              <div className="grid grid-cols-[minmax(140px,0.8fr)_minmax(0,1.2fr)] items-center gap-4 px-4 py-3 @max-[520px]:grid-cols-1">
                 <div className="flex min-w-0 flex-col gap-0.5">
                   <Label
                     htmlFor="provider-preset"
@@ -1113,7 +1113,7 @@ export function ChatProvidersSettings({
               </div>
 
               {showApiKeyField ? (
-                <div className="grid grid-cols-[minmax(150px,0.8fr)_minmax(260px,1.2fr)] items-center gap-4 px-4 py-3 max-sm:grid-cols-1">
+                <div className="grid grid-cols-[minmax(140px,0.8fr)_minmax(0,1.2fr)] items-center gap-4 px-4 py-3 @max-[520px]:grid-cols-1">
                   <div className="flex min-w-0 flex-col gap-0.5">
                     <Label
                       htmlFor="provider-api-key"
@@ -1152,7 +1152,7 @@ export function ChatProvidersSettings({
               ) : null}
 
               {isCustomProvider ? (
-                <div className="grid grid-cols-[minmax(150px,0.8fr)_minmax(260px,1.2fr)] items-center gap-4 px-4 py-3 max-sm:grid-cols-1">
+                <div className="grid grid-cols-[minmax(140px,0.8fr)_minmax(0,1.2fr)] items-center gap-4 px-4 py-3 @max-[520px]:grid-cols-1">
                   <Label
                     htmlFor="provider-custom-name"
                     className="text-sm font-medium"
@@ -1173,7 +1173,7 @@ export function ChatProvidersSettings({
               ) : null}
 
               {isCustomProvider ? (
-                <div className="grid grid-cols-[minmax(150px,0.8fr)_minmax(260px,1.2fr)] items-center gap-4 px-4 py-3 max-sm:grid-cols-1">
+                <div className="grid grid-cols-[minmax(140px,0.8fr)_minmax(0,1.2fr)] items-center gap-4 px-4 py-3 @max-[520px]:grid-cols-1">
                   <div className="flex min-w-0 flex-col gap-0.5">
                     <Label
                       htmlFor="provider-base-url"
@@ -1197,7 +1197,7 @@ export function ChatProvidersSettings({
               ) : null}
 
               {showReasoningToggle ? (
-                <div className="grid grid-cols-[minmax(150px,0.8fr)_minmax(260px,1.2fr)] items-center gap-4 px-4 py-3 max-sm:grid-cols-1">
+                <div className="grid grid-cols-[minmax(140px,0.8fr)_minmax(0,1.2fr)] items-center gap-4 px-4 py-3 @max-[520px]:grid-cols-1">
                   <Label
                     htmlFor="provider-is-reasoning"
                     className="text-sm font-medium"
@@ -1303,7 +1303,7 @@ export function ChatProvidersSettings({
                     </p>
                     {availableModels.length > 0 ? (
                       <div className="space-y-3 rounded-[8px] border border-border/70 bg-background/50 p-3">
-                        <div className="grid grid-cols-[112px_minmax(220px,330px)_auto] items-center gap-3 max-sm:grid-cols-1">
+                        <div className="grid grid-cols-[minmax(90px,auto)_minmax(0,1fr)_auto] items-center gap-3 @max-[520px]:grid-cols-1">
                           <span className="whitespace-nowrap text-xs font-medium text-muted-foreground">
                             {availableModelsLabel}
                           </span>
@@ -1395,7 +1395,7 @@ export function ChatProvidersSettings({
                   <div className="space-y-3 px-4 py-4">
                     {availableModels.length === 0 ? null : (
                       <>
-                        <div className="grid grid-cols-[112px_minmax(220px,330px)_auto] items-center gap-3 max-sm:grid-cols-1">
+                        <div className="grid grid-cols-[minmax(90px,auto)_minmax(0,1fr)_auto] items-center gap-3 @max-[520px]:grid-cols-1">
                           <span className="whitespace-nowrap text-xs font-medium text-muted-foreground">
                             {availableModelsLabel}
                           </span>
@@ -1556,7 +1556,7 @@ export function ChatProvidersSettings({
         </div>
         <p
           id="chat-connections-description"
-          className="max-w-md text-[11px] leading-snug text-muted-foreground/65 sm:text-right"
+          className="max-w-md text-ui-11 leading-snug text-muted-foreground/65 sm:text-right"
         >
           When off, all connections are disabled.
         </p>
@@ -1616,7 +1616,7 @@ export function ChatProvidersSettings({
                           <span className="truncate text-sm font-medium text-foreground">
                             {provider.name}
                           </span>
-                          <span className="shrink-0 rounded-[6px] border border-control-accent/15 bg-control-accent/8 px-1.5 py-0.5 text-[10px] leading-none text-control-accent">
+                          <span className="shrink-0 rounded-[6px] border border-control-accent/15 bg-control-accent/8 px-1.5 py-0.5 text-ui-10 leading-none text-control-accent">
                             {provider.models.length}{" "}
                             {provider.models.length === 1 ? "model" : "models"}
                           </span>
@@ -1631,7 +1631,7 @@ export function ChatProvidersSettings({
                           ) : null}
                         </div>
                         <div
-                          className="mt-1 truncate text-[11px] leading-4 text-muted-foreground/80"
+                          className="mt-1 truncate text-ui-11 leading-4 text-muted-foreground/80"
                           title={provider.models.join(", ")}
                         >
                           {modelSummary}
diff --git a/studio/frontend/src/features/chat/chat-settings-sheet.tsx b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
index bd22cc4f55..672ab2b2d3 100644
--- a/studio/frontend/src/features/chat/chat-settings-sheet.tsx
+++ b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
@@ -1,19 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import {
-  Alert,
-  AlertDescription,
-  AlertTitle,
-} from "@/components/ui/alert";
 import { Button } from "@/components/ui/button";
-import { Checkbox } from "@/components/ui/checkbox";
-import {
-  clearRememberedLoadSettings,
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-  saveRememberedLoadSettings,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
 import {
   Dialog,
   DialogContent,
@@ -29,7 +17,7 @@ import {
   DropdownMenuSeparator,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
-import { Input } from "@/components/ui/input";
+import { InfoHint } from "@/components/ui/info-hint";
 import {
   InputGroup,
   InputGroupAddon,
@@ -50,27 +38,22 @@ import {
   SheetTitle,
 } from "@/components/ui/sheet";
 import { Slider } from "@/components/ui/slider";
-import { Spinner } from "@/components/ui/spinner";
 import { Switch } from "@/components/ui/switch";
 import { Textarea } from "@/components/ui/textarea";
-import { InfoHint } from "@/components/ui/info-hint";
 import { Tooltip, TooltipContent } from "@/components/ui/tooltip";
-import { useGpuDevices } from "@/hooks/use-gpu-info";
-import { useIsMobile } from "@/hooks/use-mobile";
+import { NumericValueInput, snapToStep } from "@/features/model-picker";
+import { RetrievalSettingsSection } from "@/features/rag";
 import { useLlamaUpdateCheck } from "@/hooks/use-llama-update-check";
-import { cn } from "@/lib/utils";
-import {
-  ArrowTurnBackwardIcon,
-  Edit03Icon,
-  LayoutAlignRightIcon,
-} from "@hugeicons/core-free-icons";
+import { useIsMobile } from "@/hooks/use-mobile";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { toast } from "@/lib/toast";
+import { cn } from "@/lib/utils";
+import { Edit03Icon, LayoutAlignRightIcon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { Braces, ChevronDown, ExternalLink } from "lucide-react";
 import { Tooltip as TooltipPrimitive } from "radix-ui";
 import { Fragment, type ReactNode } from "react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "@/lib/toast";
 import { OpenAICodeExecSection } from "./components/openai-code-exec-section";
 import { PermissionModeDropdown } from "./permission-mode-select";
 import { resyncInferenceStatusAfterServerModelChange } from "./hooks/use-chat-model-runtime";
@@ -78,8 +61,8 @@ import {
   type ExternalProviderConfig,
   getExternalProviderApiKey,
   parseExternalModelId,
-  supportsProviderPromptCaching,
   supportsProviderPromptCacheTtl,
+  supportsProviderPromptCaching,
 } from "./external-providers";
 import {
   BUILTIN_PRESETS,
@@ -99,15 +82,7 @@ import {
   providerSupportsBuiltinCodeExecution,
   providerSupportsFastMode,
 } from "./provider-capabilities";
-import {
-  GPU_LAYERS_AUTO,
-  distributeByWeight,
-  isPendingGguf,
-  pendingSelectionMatches,
-  rebalanceSplit,
-  useChatRuntimeStore,
-} from "./stores/chat-runtime-store";
-import { RetrievalSettingsSection } from "@/features/rag/components/retrieval-settings-section";
+import { useChatRuntimeStore } from "./stores/chat-runtime-store";
 import type { InferenceParams } from "./types/runtime";
 
 export { defaultInferenceParams, type Preset } from "./presets/preset-policy";
@@ -130,7 +105,7 @@ function getPromptVariablesError(raw: string): string | null {
       return null;
     }
   } catch {
-    return "Use valid JSON, for example { \"env\": \"staging\" }.";
+    return 'Use valid JSON, for example { "env": "staging" }.';
   }
   return "Variables must be a JSON object.";
 }
@@ -139,112 +114,7 @@ function hasPromptVariableSyntax(prompt: string): boolean {
   return PROMPT_VARIABLE_PATTERN.test(prompt);
 }
 
-/**
- * Editable numeric value display, shared by every slider value and the Context
- * Length input. An <input> that looks like text (shows `displayValue ?? value`,
- * so "Off"/"Max" labels render) until focus, when it swaps to the raw number,
- * selects it, and accepts free text. Commits on blur/Enter, reverts on Escape.
- * Clamping happens on commit so typing intermediate values isn't fought.
- */
-function snapToStep(
-  value: number,
-  step: number,
-  min?: number,
-  max?: number,
-): number {
-  const lo = min ?? Number.NEGATIVE_INFINITY;
-  const hi = max ?? Number.POSITIVE_INFINITY;
-  const clamped = Math.min(Math.max(value, lo), hi);
-  const stepStr = String(step);
-  const decimals = stepStr.includes(".") ? stepStr.split(".")[1].length : 0;
-  const base = Number.isFinite(lo) ? lo : 0;
-  const snapped = base + Math.round((clamped - base) / step) * step;
-  const reclamped = Math.min(Math.max(snapped, lo), hi);
-  return Number(reclamped.toFixed(decimals));
-}
-
-function NumericValueInput({
-  value,
-  min,
-  max,
-  step,
-  onChange,
-  displayValue,
-  className,
-  ariaLabel,
-  size: sizeAttr,
-  disabled = false,
-}: {
-  value: number;
-  min?: number;
-  max?: number;
-  step: number;
-  onChange: (v: number) => void;
-  displayValue?: string;
-  className?: string;
-  ariaLabel?: string;
-  size?: number;
-  disabled?: boolean;
-}) {
-  const [focused, setFocused] = useState(false);
-  const [draft, setDraft] = useState("");
-  const cancelBlurCommitRef = useRef(false);
-
-  const commit = (raw: string) => {
-    const parsed = Number.parseFloat(raw);
-    if (!Number.isFinite(parsed)) {
-      return;
-    }
-    const final = snapToStep(parsed, step, min, max);
-    if (final !== value) {
-      onChange(final);
-    }
-  };
-
-  const displayed = focused ? draft : (displayValue ?? String(value));
-
-  return (
-    <input
-      type="text"
-      inputMode="decimal"
-      disabled={disabled}
-      size={sizeAttr}
-      /* Fixed 4ch pill; grows only when a longer value would clip. */
-      style={{ width: `calc(${Math.max(displayed.length, 4)}ch + 18px)` }}
-      value={displayed}
-      aria-label={ariaLabel}
-      onFocus={(e) => {
-        cancelBlurCommitRef.current = false;
-        setDraft(String(value));
-        setFocused(true);
-        // Defer select() so it runs after the value swap above.
-        const target = e.currentTarget;
-        requestAnimationFrame(() => target.select());
-      }}
-      onBlur={() => {
-        if (cancelBlurCommitRef.current) {
-          cancelBlurCommitRef.current = false;
-        } else {
-          commit(draft);
-        }
-        setFocused(false);
-      }}
-      onChange={(e) => setDraft(e.target.value)}
-      onKeyDown={(e) => {
-        if (e.key === "Enter") {
-          e.currentTarget.blur();
-        } else if (e.key === "Escape") {
-          cancelBlurCommitRef.current = true;
-          setDraft(String(value));
-          e.currentTarget.blur();
-        }
-      }}
-      className={cn("panel-number-input", className)}
-    />
-  );
-}
-
-function ParamSlider({
+export function ParamSlider({
   label,
   value,
   min,
@@ -271,7 +141,7 @@ function ParamSlider({
     <div className="space-y-3.5">
       <div className="flex items-center justify-between gap-3">
         <div className="flex min-w-0 items-center gap-1.5">
-          <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+          <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
             {label}
           </span>
           {info && <InfoHint>{info}</InfoHint>}
@@ -285,6 +155,7 @@ function ParamSlider({
           displayValue={displayValue}
           ariaLabel={label}
           size={valueSize ?? 4}
+          className="panel-number-input"
           disabled={disabled}
         />
       </div>
@@ -378,15 +249,14 @@ function CollapsibleSection({
   };
 
   const headerClasses = cn(
-    "flex w-full items-center justify-between text-[12px] font-medium normal-case tracking-[0.04em] text-nav-fg-muted transition-colors focus-visible:outline-none focus-visible:ring-0",
+    "flex w-full items-center justify-between text-ui-12 font-medium normal-case tracking-[0.04em] text-nav-fg-muted transition-colors focus-visible:outline-none focus-visible:ring-0",
     first ? "pt-4 pb-5" : "py-5",
   );
 
   return (
     <div
       className={cn(
-        !first &&
-          "border-t border-black/[0.13] dark:border-white/[0.09]",
+        !first && "border-t border-black/[0.13] dark:border-white/[0.09]",
       )}
     >
       {labelHref ? (
@@ -458,6 +328,7 @@ interface ChatSettingsPanelProps {
   onOpenChange?: (open: boolean) => void;
   params: InferenceParams;
   onParamsChange: (params: InferenceParams) => void;
+  modelConfig?: ReactNode;
   isExternalModel?: boolean;
   /**
    * Sampling-param capabilities for the active external provider, or `null` for
@@ -472,21 +343,6 @@ interface ChatSettingsPanelProps {
    * Max Tokens floor in the slider.
    */
   externalProviderType?: string | null;
-  onReloadModel?: () => void;
-  /** The in-flight load (id + GGUF variant + native path token), or null when
-   *  idle. Used to show a loading state for the staged pick only — not for an
-   *  unrelated load or a cancel's background unload. */
-  loadingModel?: {
-    id: string;
-    ggufVariant?: string | null;
-    nativePathToken?: string | null;
-  } | null;
-  /** Loads the staged `pendingSelection` (deferred "Load on selection" flow). */
-  onLoadPendingModel?: () => void;
-  /** Download progress (0–1) for a staged GGUF being fetched, or null when idle. */
-  stagedDownloadFraction?: number | null;
-  /** Cancels the in-flight staged download (paired with abandoning the stage). */
-  onCancelStagedDownload?: () => void;
 }
 
 export function ChatSettingsPanel({
@@ -494,16 +350,12 @@ export function ChatSettingsPanel({
   onOpenChange,
   params,
   onParamsChange,
+  modelConfig = null,
   isExternalModel = false,
   providerCapabilities = null,
   activeExternalProvider = null,
   onExternalProviderChange,
   externalProviderType = null,
-  onReloadModel,
-  loadingModel = null,
-  onLoadPendingModel,
-  stagedDownloadFraction,
-  onCancelStagedDownload,
 }: ChatSettingsPanelProps) {
   // Local models show every knob; providerCapabilities is only consulted when
   // isExternalModel. Unknown providers fall back to the OpenAI-compat shape via
@@ -518,64 +370,23 @@ export function ChatSettingsPanel({
   const showPresencePenalty =
     !isExternalModel || Boolean(providerCapabilities?.presencePenalty);
   const isMobile = useIsMobile();
-  const pendingSelection = useChatRuntimeStore((s) => s.pendingSelection);
-  // "Loading" only when the in-flight load IS this staged pick (full id + GGUF
-  // variant + native token match), not an unrelated load or a cancel's
-  // background unload. The variant matters: a different quant of the same repo
-  // staged mid-load must not read as this one loading.
-  const stagedLoading =
-    loadingModel != null &&
-    pendingSelectionMatches(pendingSelection, {
-      id: loadingModel.id,
-      ggufVariant: loadingModel.ggufVariant,
-      nativePathToken: loadingModel.nativePathToken,
-    });
-  // Load settings are snapshotted at click time; lock them while loading.
-  const modelControlsDisabled = stagedLoading;
-  const abandonStagedModel = useChatRuntimeStore((s) => s.abandonStagedModel);
-  const resetModelSettingsToLoaded = useChatRuntimeStore(
-    (s) => s.resetModelSettingsToLoaded,
+  const isLoadedGguf = useChatRuntimeStore((s) => s.activeGgufVariant) != null;
+  const currentCheckpoint = params.checkpoint;
+  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
+  // Direct-file / custom-folder GGUFs load without a variant label but still
+  // report a GGUF context, so detect them via the context and the checkpoint
+  // suffix too (mirrors the chat page's activeModelIsGguf). Otherwise Max Tokens
+  // would fall back to params.maxSeqLength instead of the loaded GGUF context.
+  const isGguf =
+    isLoadedGguf ||
+    ggufContextLength != null ||
+    (currentCheckpoint?.toLowerCase().endsWith(".gguf") ?? false);
+  const ggufMaxContextLength = useChatRuntimeStore(
+    (s) => s.ggufMaxContextLength,
   );
-  // A staged GGUF pick (deferred load) shows the GGUF load knobs so they can be
-  // set before the single load.
-  const pendingIsGguf = isPendingGguf(pendingSelection);
-  // Short, human-readable name for the staged pick (HF ids carry an org prefix;
-  // native picks are already a display label). Drives the "staged, not loaded"
-  // callout so it's obvious the selection hasn't loaded yet.
-  const stagedLabel = (() => {
-    const id = pendingSelection?.id ?? "";
-    const slash = id.lastIndexOf("/");
-    const base = slash >= 0 ? id.slice(slash + 1) : id;
-    return base || id;
-  })();
-  const activeNativePathToken = useChatRuntimeStore(
-    (s) => s.activeNativePathToken,
-  );
-  const loadedGgufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
-  // A GGUF loaded from a native path / direct .gguf has no HF variant, so key
-  // off the same signal the status hydration uses -- variant OR native token OR
-  // a GGUF context -- else the GPU Memory controls hide for a loaded local GGUF.
-  const isLoadedGguf =
-    useChatRuntimeStore((s) => s.activeGgufVariant) != null ||
-    activeNativePathToken != null ||
-    loadedGgufContextLength != null;
-  // While a pick is staged the sheet configures *that* model, so its GGUF-ness
-  // (not the currently loaded model's) decides whether the GGUF-only controls
-  // show. Otherwise a staged non-GGUF Hub repo would inherit the loaded GGUF's
-  // context/KV/speculative controls.
-  const isGguf = pendingSelection != null ? pendingIsGguf : isLoadedGguf;
-  // The Model section (and Load button) shows for any staged pick, even when the
-  // currently active model is external.
-  const hasModelContent =
-    pendingSelection != null ||
-    (!isExternalModel && (isGguf || Boolean(params.checkpoint)));
+  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
   const speculativeType = useChatRuntimeStore((s) => s.speculativeType);
-  const setSpeculativeType = useChatRuntimeStore((s) => s.setSpeculativeType);
-  const loadedSpeculativeType = useChatRuntimeStore(
-    (s) => s.loadedSpeculativeType,
-  );
   const specFallbackReason = useChatRuntimeStore((s) => s.specFallbackReason);
-  // Only binary fallback states are solved by a newer prebuilt.
   const mtpUpdatable =
     specFallbackReason === "binary_no_mtp" ||
     specFallbackReason === "binary_outdated";
@@ -597,65 +408,27 @@ export function ChatSettingsPanel({
         `llama.cpp updated to ${result.tag ?? "the latest build"}.${reloadHint}`,
       );
     } else {
-      toast.error(`llama.cpp update failed: ${result.error ?? "unknown error"}`);
+      toast.error(
+        `llama.cpp update failed: ${result.error ?? "unknown error"}`,
+      );
     }
   }, [applyLlamaUpdate]);
-  const specDraftNMax = useChatRuntimeStore((s) => s.specDraftNMax);
-  const setSpecDraftNMax = useChatRuntimeStore((s) => s.setSpecDraftNMax);
-  const loadedSpecDraftNMax = useChatRuntimeStore(
-    (s) => s.loadedSpecDraftNMax,
-  );
-  const currentCheckpoint = params.checkpoint;
-  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
-  const ggufMaxContextLength = useChatRuntimeStore(
-    (s) => s.ggufMaxContextLength,
-  );
-  const ggufNativeContextLength = useChatRuntimeStore(
-    (s) => s.ggufNativeContextLength,
-  );
-  const kvCacheDtype = useChatRuntimeStore((s) => s.kvCacheDtype);
-  const setKvCacheDtype = useChatRuntimeStore((s) => s.setKvCacheDtype);
-  const applyRememberedLoadSettings = useChatRuntimeStore(
-    (s) => s.applyRememberedLoadSettings,
-  );
-  const loadedKvCacheDtype = useChatRuntimeStore((s) => s.loadedKvCacheDtype);
-  const tensorParallel = useChatRuntimeStore((s) => s.tensorParallel);
-  const setTensorParallel = useChatRuntimeStore((s) => s.setTensorParallel);
-  const loadedTensorParallel = useChatRuntimeStore(
-    (s) => s.loadedTensorParallel,
-  );
-  const gpuMemoryMode = useChatRuntimeStore((s) => s.gpuMemoryMode);
-  const setGpuMemoryMode = useChatRuntimeStore((s) => s.setGpuMemoryMode);
-  const loadedGpuMemoryMode = useChatRuntimeStore((s) => s.loadedGpuMemoryMode);
-  const loadedIsDiffusion = useChatRuntimeStore((s) => s.loadedIsDiffusion);
-  const gpuLayers = useChatRuntimeStore((s) => s.gpuLayers);
-  const setGpuLayers = useChatRuntimeStore((s) => s.setGpuLayers);
-  const loadedGpuLayers = useChatRuntimeStore((s) => s.loadedGpuLayers);
-  const nCpuMoe = useChatRuntimeStore((s) => s.nCpuMoe);
-  const setNCpuMoe = useChatRuntimeStore((s) => s.setNCpuMoe);
-  const loadedNCpuMoe = useChatRuntimeStore((s) => s.loadedNCpuMoe);
-  const splitRatio = useChatRuntimeStore((s) => s.splitRatio);
-  const setSplitRatio = useChatRuntimeStore((s) => s.setSplitRatio);
-  const loadedSplitRatio = useChatRuntimeStore((s) => s.loadedSplitRatio);
-  const ggufLayerCount = useChatRuntimeStore((s) => s.ggufLayerCount);
-  const moeLayerCount = useChatRuntimeStore((s) => s.moeLayerCount);
-  const selectedGpuIds = useChatRuntimeStore((s) => s.selectedGpuIds);
-  const setSelectedGpuIds = useChatRuntimeStore((s) => s.setSelectedGpuIds);
-  const loadedGpuIds = useChatRuntimeStore((s) => s.loadedGpuIds);
-  const gpuDevices = useGpuDevices();
-  const chatTemplateOverride = useChatRuntimeStore(
-    (s) => s.chatTemplateOverride,
-  );
-  const loadedChatTemplateOverride = useChatRuntimeStore(
-    (s) => s.loadedChatTemplateOverride,
-  );
-  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
-  const loadedCustomContextLength = useChatRuntimeStore(
-    (s) => s.loadedCustomContextLength,
-  );
-  const setCustomContextLength = useChatRuntimeStore(
-    (s) => s.setCustomContextLength,
-  );
+  const loadedEffectiveContext = customContextLength ?? ggufContextLength;
+  const showSpecFallback =
+    !isExternalModel &&
+    isGguf &&
+    specFallbackReason != null &&
+    (speculativeType === "auto" ||
+      speculativeType === "mtp" ||
+      speculativeType === "mtp+ngram");
+  const showContextVramWarning =
+    !isExternalModel &&
+    isGguf &&
+    ggufMaxContextLength != null &&
+    loadedEffectiveContext != null &&
+    loadedEffectiveContext > ggufMaxContextLength;
+  const showLoadedDiagnostics = showSpecFallback || showContextVramWarning;
+  const hasModelContent = showLoadedDiagnostics;
   const setActivePresetSource = useChatRuntimeStore(
     (s) => s.setActivePresetSource,
   );
@@ -666,170 +439,7 @@ export function ChatSettingsPanel({
   const setActivePreset = useChatRuntimeStore((s) => s.setActivePreset);
   const settingsHydrated = useChatRuntimeStore((s) => s.settingsHydrated);
 
-  // A staged (not-yet-loaded) GGUF carries its own header context length on
-  // pendingSelection, so the slider can use the staged model's real ceiling
-  // without reading the loaded model's `ggufContextLength`.
-  const stagedContextLength = pendingSelection?.contextLength ?? null;
-  // "Remember settings next time" tick for a staged model. Seeds the store from
-  // the saved per-model settings on stage, so the sheet opens with what was used
-  // last time; the tick reflects whether a saved entry exists.
-  const [remember, setRemember] = useState(false);
-  // Keyed per quant: a different variant of the same repo has its own settings.
-  const pendingKey = pendingSelection
-    ? rememberedLoadSettingsKey(pendingSelection)
-    : null;
-  useEffect(() => {
-    if (!pendingKey) return;
-    // GGUF-only, like the stageOrLoad / Hub restore paths: every remembered
-    // field is a llama.cpp knob, so a non-GGUF pick has nothing to restore --
-    // and applying its blob would clobber the standing gpuMemoryMode with a
-    // stale snapshot (the save on Load below is gated the same way).
-    const saved = pendingIsGguf ? loadRememberedLoadSettings(pendingKey) : null;
-    setRemember(saved != null);
-    if (saved) applyRememberedLoadSettings(saved);
-  }, [pendingKey, pendingIsGguf, applyRememberedLoadSettings]);
-  // While staging, the sheet reflects the STAGED model, so its header context
-  // takes precedence over the loaded model's (which may differ or be larger).
-  const baseContext = pendingIsGguf ? stagedContextLength : ggufContextLength;
-  const baseNativeContext = pendingIsGguf
-    ? stagedContextLength
-    : ggufNativeContextLength;
-  // Context controls render once we actually have a ceiling: for a staged GGUF,
-  // once its header metadata arrives (post-download); otherwise post-load.
-  const showContextControl = pendingIsGguf
-    ? stagedContextLength != null
-    : isLoadedGguf;
-  const stagedDownloading =
-    stagedDownloadFraction != null && stagedDownloadFraction < 1;
-  const ctxDisplayValue = customContextLength ?? baseContext ?? "";
-  const ctxMaxValue = baseNativeContext ?? baseContext ?? null;
-  const kvDirty = kvCacheDtype !== loadedKvCacheDtype;
-  const ctxDirty = customContextLength !== loadedCustomContextLength;
-  const specDirty = speculativeType !== loadedSpeculativeType;
-  const specDraftDirty = specDraftNMax !== loadedSpecDraftNMax;
-  const tpDirty = tensorParallel !== (loadedTensorParallel ?? false);
-  // A loaded diffusion GGUF runs mode-agnostic (pins all layers on one GPU,
-  // ignores --fit/--gpu-layers), so the GPU Memory mode + manual controls don't
-  // apply -- hide them and don't let the preserved standing mode read as dirty.
-  // The GPU picker still applies (diffusion pins the chosen device). A staged pick
-  // keeps the controls (a pending pick's diffusion-ness isn't known until load).
-  const gpuModeApplies =
-    isGguf && (pendingSelection != null || !loadedIsDiffusion);
-  const gpuDirty =
-    gpuModeApplies && gpuMemoryMode !== (loadedGpuMemoryMode ?? "auto");
-  const isManual = gpuModeApplies && gpuMemoryMode === "manual";
-  // Manual with the GPU Layers slider at "Auto" (leftmost): --fit owns the whole
-  // layout, so the offload knobs (MoE, split, TP) don't apply.
-  const autoLayers = isManual && gpuLayers < 0;
-  // GPUs actually in use: the picked subset, or all visible when none picked.
-  const gpusInUse = selectedGpuIds ?? gpuDevices.map((d) => d.index);
-  // The picker must keep one GPU selected.
-  const singleGpuInUse = gpusInUse.length <= 1;
-  // TP needs at least two GPUs because tensor split is a no-op on one and may
-  // abort. Auto layers hides TP because --fit aborts under --split-mode tensor.
-  const tpDisabled = singleGpuInUse;
-  // Manual gpu-layers ceiling = model layer count + 1 (else a safe fallback):
-  // llama.cpp counts the output layer as one more offloadable layer past the
-  // repeating blocks ("offloaded 33/33" needs -ngl 33 on a 32-block model), so
-  // the slider max must reach it or full offload is unreachable. While staging,
-  // use the staged model's layer count (read from its header).
-  const stagedLayerCount = pendingSelection?.layerCount ?? null;
-  const modelLayerCount = pendingIsGguf ? stagedLayerCount : ggufLayerCount;
-  const gpuLayersMax = modelLayerCount != null ? modelLayerCount + 1 : 256;
-  // MoE-offload slider: shown only for MoE models, capped at their MoE-layer
-  // count. While staging, use the staged model's count (read from its header);
-  // otherwise the loaded model's.
-  const stagedMoeLayerCount = pendingSelection?.moeLayerCount ?? null;
-  const moeLayersMax = pendingIsGguf
-    ? (stagedMoeLayerCount ?? 0)
-    : (moeLayerCount ?? 0);
-  const showMoeSlider = isManual && !autoLayers && moeLayersMax > 0;
-  // gpuLayers always counts; MoE only with an explicit layer count (see above).
-  const manualDirty =
-    isManual &&
-    (gpuLayers !== loadedGpuLayers ||
-      (!autoLayers && nCpuMoe !== (loadedNCpuMoe ?? 0)));
-  // GPU picker: only meaningful on multi-GPU, and only when the reported
-  // indices are physical (relative ordinals from a parent CUDA_VISIBLE_DEVICES
-  // mask can't be mapped back to pin a device). null = use all (auto).
-  const showGpuPicker =
-    isGguf &&
-    gpuDevices.length > 1 &&
-    gpuDevices.every((d) => d.physicalIndex);
-  const isGpuChecked = (index: number) =>
-    selectedGpuIds === null || selectedGpuIds.includes(index);
-  const toggleGpu = (index: number) => {
-    const all = gpuDevices.map((d) => d.index);
-    const current = selectedGpuIds ?? all;
-    const next = current.includes(index)
-      ? current.filter((i) => i !== index)
-      : [...current, index].sort((a, b) => a - b);
-    if (next.length === 0) return; // keep at least one GPU selected
-    setSelectedGpuIds(next.length === all.length ? null : next);
-    // The per-GPU split is positional, so any change to the set of GPUs in use
-    // invalidates it: drop it (the sliders fall back to the VRAM-weighted
-    // default). TP needs 2+ GPUs, so disable it when only one remains.
-    setSplitRatio(null);
-    if (next.length <= 1) {
-      setTensorParallel(false);
-    }
-  };
-  const gpuIdsKey = (ids: number[] | null) => (ids === null ? "auto" : ids.join(","));
-  const gpuIdsDirty = gpuIdsKey(selectedGpuIds) !== gpuIdsKey(loadedGpuIds);
-  // Per-GPU layer split (--tensor-split): manual + 2+ GPUs in use. One slider
-  // per GPU, each a layer count; together they sum to the GPU Layers total.
-  const showSplitRatio =
-    isManual && !autoLayers && showGpuPicker && gpusInUse.length > 1;
-  // The total the per-GPU counts sum to (the GPU Layers slider value); 0 under
-  // Auto, where the split is hidden. The devices behind the GPUs in use, for
-  // labels + the VRAM-weighted default.
-  const splitTotal = Math.max(0, Math.min(gpuLayers, gpuLayersMax));
-  const gpusInUseDevices = gpusInUse.map(
-    (i) => gpuDevices.find((d) => d.index === i) ?? null,
-  );
-  // Displayed per-GPU counts. splitRatio is a stable reference balance (only a
-  // slider edit changes it), rescaled to the current total; deriving rather than
-  // mutating it on GPU Layers changes keeps the balance intact when the total
-  // passes through low values or Auto. No saved split: free-VRAM-weighted default
-  // (llama.cpp's unset default splits by free VRAM, so the first edit starts from
-  // the default's placement, not a total-VRAM ratio that can land layers on a
-  // busy GPU). A genuine 0 (a full GPU) is a real weight, not missing data: the
-  // probe's no-data case degrades to the total server-side, and an all-zero list
-  // falls back to an even split in distributeByWeight. Not yet sent.
-  const splitCounts =
-    splitRatio && splitRatio.length === gpusInUse.length
-      ? distributeByWeight(splitTotal, splitRatio)
-      : distributeByWeight(
-          splitTotal,
-          gpusInUseDevices.map((d) => d?.memoryFreeGb ?? d?.memoryTotalGb ?? 1),
-        );
-  const setSplitCount = (k: number, v: number) =>
-    setSplitRatio(rebalanceSplit(splitTotal, splitCounts, k, v));
-  const splitRatioDirty =
-    isManual &&
-    !autoLayers &&
-    JSON.stringify(splitRatio ?? null) !== JSON.stringify(loadedSplitRatio ?? null);
-  // Auto-fit context (Manual + Auto layers): <= 0 means "Auto" (--fit sizes it);
-  // a positive value pins it. Surface the length --fit chose once it's loaded.
-  const fitCtxAuto = autoLayers && (customContextLength ?? 0) <= 0;
-  const loadedAutoLayers =
-    loadedGpuMemoryMode === "manual" && (loadedGpuLayers ?? GPU_LAYERS_AUTO) < 0;
-  const fitResolvedCtx =
-    fitCtxAuto && loadedAutoLayers ? ggufContextLength : null;
-  // A saved chat-template override is a reload-time setting too, so surface
-  // Apply for a template-only edit (otherwise it could never be applied).
-  const templateDirty = chatTemplateOverride !== loadedChatTemplateOverride;
-  const modelSettingsDirty =
-    kvDirty ||
-    ctxDirty ||
-    specDirty ||
-    specDraftDirty ||
-    tpDirty ||
-    gpuDirty ||
-    manualDirty ||
-    gpuIdsDirty ||
-    splitRatioDirty ||
-    templateDirty;
+  const baseContext = ggufContextLength;
   const [presetNameInput, setPresetNameInput] = useState(activePreset);
   const [systemPromptEditorOpen, setSystemPromptEditorOpen] = useState(false);
   const [systemPromptDraft, setSystemPromptDraft] = useState("");
@@ -855,8 +465,7 @@ export function ChatSettingsPanel({
       BUILTIN_PRESETS.find((preset) => preset.name === activePreset) ?? null,
     [activePreset],
   );
-  const hasUnsavedPresetChanges = useMemo(
-    () => {
+  const hasUnsavedPresetChanges = useMemo(() => {
       if (activePresetDefinition == null) {
         return false;
       }
@@ -864,9 +473,7 @@ export function ChatSettingsPanel({
         return activePresetSource === "modified";
       }
       return !isSamePresetConfig(activePresetDefinition.params, params);
-    },
-    [activePresetDefinition, activePresetSource, params],
-  );
+  }, [activePresetDefinition, activePresetSource, params]);
   const presetSaveState = useMemo(
     () =>
       getPresetSaveState({
@@ -895,6 +502,14 @@ export function ChatSettingsPanel({
   const externalSelection = currentCheckpoint
     ? parseExternalModelId(currentCheckpoint)
     : null;
+  const maxTokensMax = isExternalModel
+      ? getExternalMaxOutputTokens(
+          externalProviderType,
+          externalSelection?.modelId,
+        )
+      : isGguf && baseContext
+        ? baseContext
+        : Math.max(64, params.maxSeqLength);
   const showOpenAICodeExecSection =
     activeExternalProvider != null &&
     providerSupportsBuiltinCodeExecution(
@@ -977,8 +592,7 @@ export function ChatSettingsPanel({
       return;
     }
     const fallbackPreset =
-      BUILTIN_PRESETS.find((preset) => preset.name === "Default") ??
-      null;
+      BUILTIN_PRESETS.find((preset) => preset.name === "Default") ?? null;
     const next = customPresets.filter((preset) => preset.name !== name);
     setCustomPresets(next);
     if (activePreset === name) {
@@ -1081,16 +695,16 @@ export function ChatSettingsPanel({
       {/* Header is outside the scroll area so the scrollbar never shifts the close button. */}
       <div className="flex h-[48px] shrink-0 items-start gap-2 bg-panel-surface pl-[18px] pr-[16px] pt-[11px]">
         {isMobile ? (
-          <span className="flex h-[34px] flex-1 items-center text-[16px] font-semibold tracking-[0em] dark:tracking-[0.015em] text-nav-fg">
+          <span className="flex h-[34px] flex-1 items-center text-ui-16 font-semibold tracking-[0em] dark:tracking-[0.015em] text-nav-fg">
             Run settings
           </span>
         ) : (
           <>
-            <span className="flex h-[34px] flex-1 items-center text-[16px] font-semibold tracking-[0em] dark:tracking-[0.015em] text-nav-fg">
+            <span className="flex h-[34px] flex-1 items-center text-ui-16 font-semibold tracking-[0em] dark:tracking-[0.015em] text-nav-fg">
               Run settings
             </span>
             <Tooltip>
-              <TooltipPrimitive.Trigger asChild>
+                <TooltipPrimitive.Trigger asChild={true}>
                 <button
                   type="button"
                   onClick={() => onOpenChange?.(false)}
@@ -1121,611 +735,57 @@ export function ChatSettingsPanel({
         className="run-settings-scroll relative min-h-0 flex-1 overflow-y-auto"
       >
       <div className="px-[18px] pt-3">
-        {hasModelContent && (
-        <CollapsibleSection label="Model" defaultOpen={true} first>
-          <div className="flex flex-col gap-4 pt-1">
-            {pendingSelection && (
-              <Alert className="rounded-[14px] border-primary/30 bg-primary/5 px-3 py-2">
-                <AlertTitle className="text-[12px] font-medium">
-                  {stagedLoading
-                    ? `Loading ${stagedLabel}…`
-                    : `${stagedLabel} is staged, not loaded yet`}
-                </AlertTitle>
-                <AlertDescription className="text-[11.5px] leading-[1.45] text-muted-foreground">
-                  {stagedLoading
-                    ? "Applying your settings."
-                    : "Set the options below, then choose Load model to load it."}
-                </AlertDescription>
-              </Alert>
-            )}
-            {isGguf && (
-              <>
-                {showContextControl && (autoLayers ? (
-                  <div className="space-y-3.5">
-                    <div className="flex items-center justify-between gap-3">
-                      <div className="flex min-w-0 items-center gap-1.5">
-                        <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                          Context Length
-                        </span>
-                        <InfoHint>
-                          Auto: llama.cpp's --fit sizes the context to fit VRAM.
-                          Set a length to pin it instead -- --fit then optimizes
-                          GPU layer offload around it. The length --fit chose
-                          shows here after loading.
-                        </InfoHint>
-                      </div>
-                      <NumericValueInput
-                        value={fitCtxAuto ? 0 : (customContextLength ?? 0)}
-                        displayValue={fitCtxAuto ? "Auto" : undefined}
-                        min={0}
-                        max={ctxMaxValue ?? undefined}
-                        step={1}
-                        onChange={(v) => {
-                          setCustomContextLength(v > 0 ? v : null);
-                        }}
-                        ariaLabel="Context Length"
-                        size={8}
-                        disabled={modelControlsDisabled}
-                      />
-                    </div>
-                    <Slider
-                      min={0}
-                      max={ctxMaxValue ?? 4096}
-                      step={1024}
-                      value={[
-                        fitCtxAuto
-                          ? 0
-                          : Math.min(
-                              customContextLength ?? 0,
-                              ctxMaxValue ?? 4096,
-                            ),
-                      ]}
-                      onValueChange={([v]) => {
-                        // Far-left snaps to Auto; otherwise to the nearest 1024.
-                        if (v < 512) {
-                          setCustomContextLength(null);
-                        } else {
-                          setCustomContextLength(Math.round(v / 1024) * 1024);
-                        }
-                      }}
-                      className="panel-slider"
-                      disabled={modelControlsDisabled}
-                    />
-                    {fitResolvedCtx != null && (
-                      <p className="text-[11px] text-nav-fg/40">
-                        llama.cpp loaded {fitResolvedCtx.toLocaleString()} tokens.
-                      </p>
-                    )}
-                  </div>
-                ) : (
-                <div className="space-y-3.5">
-                  <div className="flex items-center justify-between gap-3">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      Context Length
-                    </span>
-                    <NumericValueInput
-                      value={
-                        typeof ctxDisplayValue === "number"
-                          ? ctxDisplayValue
-                          : (baseContext ?? 0)
-                      }
-                      min={128}
-                      max={ctxMaxValue ?? undefined}
-                      step={1}
-                      onChange={(v) => {
-                        setCustomContextLength(
-                          v === (baseContext ?? 0) ? null : v,
-                        );
-                      }}
-                      ariaLabel="Context Length"
-                      size={8}
-                      disabled={modelControlsDisabled}
-                    />
-                  </div>
-                  <Slider
-                    min={1024}
-                    max={ctxMaxValue ?? 4096}
-                    step={1024}
-                    value={[
-                      Math.min(
-                        typeof ctxDisplayValue === "number"
-                          ? ctxDisplayValue
-                          : (baseContext ?? 4096),
-                        ctxMaxValue ?? 4096,
-                      ),
-                    ]}
-                    onValueChange={([v]) => {
-                      const snapped = Math.round(v);
-                      setCustomContextLength(
-                        snapped === (baseContext ?? 0) ? null : snapped,
-                      );
-                    }}
-                    className="panel-slider"
-                    disabled={modelControlsDisabled}
-                  />
-                  {ggufMaxContextLength != null &&
-                    typeof ctxDisplayValue === "number" &&
-                    ctxDisplayValue > ggufMaxContextLength && (
-                      <p className="text-[11px] text-amber-500">
-                        Exceeds estimated VRAM capacity (
-                        {ggufMaxContextLength.toLocaleString()} tokens). The
-                        model may use system RAM.
-                      </p>
-                    )}
-                </div>
-                ))}
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      KV Cache Dtype
-                    </span>
-                    <InfoHint>
-                      Lower KV cache precision to save VRAM at the cost of some
-                      quality. f16/bf16 are full precision; q8_0/q5_1/q4_1 are
-                      quantized.
-                    </InfoHint>
-                  </div>
-                  <div className="flex shrink-0 items-center gap-1.5">
-                    <Select
-                      disabled={modelControlsDisabled}
-                      value={kvCacheDtype ?? "f16"}
-                      onValueChange={(v) => {
-                        setKvCacheDtype(v === "f16" ? null : v);
-                      }}
-                    >
-                      <SelectTrigger
-                        animateRadius={false}
-                        icon={ChevronDownStandardIcon}
-                        iconClassName="size-3.5"
-                        className="grid h-7 w-[64px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
-                      >
-                        <SelectValue />
-                      </SelectTrigger>
-                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-                        <SelectItem value="f16">f16</SelectItem>
-                        <SelectItem value="bf16">bf16</SelectItem>
-                        <SelectItem value="q8_0">q8_0</SelectItem>
-                        <SelectItem value="q5_1">q5_1</SelectItem>
-                        <SelectItem value="q4_1">q4_1</SelectItem>
-                      </SelectContent>
-                    </Select>
-                  </div>
-                </div>
-                {isGguf && (
-                  <>
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      Speculative Decoding
-                    </span>
-                    <InfoHint>
-                      Faster generation with 0% accuracy hit. Auto picks
-                      MTP / ngram-mod based on the model and platform.
-                      Pick MTP, Ngram, or MTP+Ngram to force a specific
-                      strategy on both GPU and CPU.
-                    </InfoHint>
-                  </div>
-                  <div className="flex shrink-0 items-center gap-1.5">
-                    <Select
-                      disabled={modelControlsDisabled}
-                      value={speculativeType ?? "auto"}
-                      onValueChange={(v) => {
-                        setSpeculativeType(v);
-                        if (v !== "mtp" && v !== "mtp+ngram") {
-                          setSpecDraftNMax(null);
-                        }
-                      }}
-                    >
-                      <SelectTrigger
-                        animateRadius={false}
-                        icon={ChevronDownStandardIcon}
-                        iconClassName="size-3.5"
-                        className="grid h-7 w-[124px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
-                        data-test-id="speculative-type-select"
-                      >
-                        <SelectValue />
-                      </SelectTrigger>
-                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-                        <SelectItem value="auto">Auto</SelectItem>
-                        <SelectItem value="mtp">MTP</SelectItem>
-                        <SelectItem value="ngram">Ngram</SelectItem>
-                        <SelectItem value="mtp+ngram">MTP+Ngram</SelectItem>
-                        <SelectItem value="off">Off</SelectItem>
-                      </SelectContent>
-                    </Select>
-                  </div>
-                </div>
-                {specFallbackReason &&
-                  (speculativeType === "auto" ||
-                    speculativeType === "mtp" ||
-                    speculativeType === "mtp+ngram") && (
-                    <div className="rounded-lg bg-amber-500/[0.08] px-3 py-2 text-[12px] leading-[1.4] text-nav-fg/80">
-                      <p>
-                        {specFallbackReason === "mla_mtp_disabled"
-                          ? "MTP is disabled by default for this model architecture because it currently runs slower than standard decoding. Select MTP above to force it."
-                          : specFallbackReason === "runtime_error"
-                          ? "MTP could not start for this model on the installed llama.cpp build, so it is running without speculative decoding."
-                          : specFallbackReason === "drafter_not_found"
-                            ? "This model supports MTP, but its drafter file could not be downloaded, so MTP is off and it falls back to n-gram speculative decoding where the llama.cpp build supports it. Check your network connection or Hugging Face access, then reload the model to retry the drafter."
-                            : "MTP is not available in the installed llama.cpp build, so this model is running without it." +
-                              (llamaUpdateStatus?.update_available
+        {(hasModelContent || modelConfig) && (
+              <CollapsibleSection label="Model" defaultOpen={true} first={true}>
+            <div className="flex flex-col gap-3 pt-1">
+              {modelConfig}
+              {showSpecFallback && (
+                <div className="rounded-lg bg-amber-500/[0.08] px-3 py-2 text-ui-12 leading-[1.4] text-nav-fg/80">
+                  <p>
+                    {specFallbackReason === "mla_mtp_disabled"
+                      ? "MTP is disabled by default for this model architecture because it currently runs slower than standard decoding. Choose MTP in the model picker to force it."
+                      : specFallbackReason === "runtime_error"
+                        ? "MTP could not start for this model on the installed llama.cpp build, so it is running without speculative decoding."
+                        : specFallbackReason === "drafter_not_found"
+                          ? "This model supports MTP, but its drafter file could not be downloaded, so MTP is off and it falls back to n-gram speculative decoding where the llama.cpp build supports it. Check your network connection or Hugging Face access, then reload the model to retry the drafter."
+                          : `MTP is not available in the installed llama.cpp build, so this model is running without it.${
+                              llamaUpdateStatus?.update_available
                                 ? " Update llama.cpp to enable it."
-                                : "")}
-                      </p>
-                      {mtpUpdatable && llamaUpdateStatus?.update_available && (
-                        <Button
-                          size="sm"
-                          className="corner-squircle mt-2 h-7 text-[12px]"
-                          onClick={handleMtpUpdate}
-                          disabled={llamaUpdating}
-                          data-test-id="mtp-update-button"
-                        >
-                          {llamaUpdating ? "Updating..." : "Update llama.cpp"}
-                        </Button>
-                      )}
-                    </div>
-                  )}
-                {(speculativeType === "mtp" ||
-                  speculativeType === "mtp+ngram") && (
-                  <div className="flex items-center justify-between gap-3">
-                    <div className="flex min-w-0 items-center gap-1.5">
-                      <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                        Draft Tokens
-                      </span>
-                      <InfoHint>
-                        Max MTP draft tokens per step
-                        (--spec-draft-n-max). Lower = less wasted
-                        draft decode; higher = bigger speedup when
-                        acceptance stays high. Default: 2 on GPU,
-                        3 on CPU/Mac.
-                      </InfoHint>
-                    </div>
-                    <Input
-                      type="number"
-                      disabled={modelControlsDisabled}
-                      min={1}
-                      max={16}
-                      step={1}
-                      value={specDraftNMax ?? ""}
-                      placeholder="auto"
-                      onChange={(e) => {
-                        const raw = e.target.value;
-                        if (raw === "") {
-                          setSpecDraftNMax(null);
-                          return;
-                        }
-                        const parsed = Number.parseInt(raw, 10);
-                        if (Number.isFinite(parsed)) {
-                          const clamped = Math.max(1, Math.min(16, parsed));
-                          setSpecDraftNMax(clamped);
-                        }
-                      }}
-                      data-test-id="spec-draft-n-max-input"
-                      aria-label="Speculative decoding draft tokens"
-                      className="h-7 w-[88px] rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 py-0 text-[13px] font-medium text-nav-fg outline-none focus-visible:ring-0"
-                    />
-                  </div>
-                )}
-                  </>
-                )}
-                {gpuModeApplies && (
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      GPU Memory
-                    </span>
-                    <InfoHint>
-                      <div className="flex flex-col gap-1.5">
-                        <div>
-                          <span className="font-medium">Default:</span> Unsloth
-                          fits the model and context to your GPUs.
-                        </div>
-                        <div>
-                          <span className="font-medium">Manual:</span> set GPU
-                          Layers yourself. Leave it on Auto to let llama.cpp size
-                          the context and offload overflow (including MoE experts)
-                          to RAM.
-                        </div>
-                      </div>
-                    </InfoHint>
-                  </div>
-                  <div className="flex shrink-0 items-center gap-1.5">
-                    <Select
-                      value={gpuMemoryMode}
-                      onValueChange={(v) => {
-                        setGpuMemoryMode(v as "auto" | "manual");
-                      }}
-                      // An in-flight staged load already snapshotted its
-                      // settings, so edits here could not apply -- disable like
-                      // the sibling context/KV/spec controls.
-                      disabled={modelControlsDisabled}
-                    >
-                      <SelectTrigger
-                        animateRadius={false}
-                        icon={ChevronDownStandardIcon}
-                        iconClassName="size-3.5"
-                        className="grid h-7 w-[136px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-transparent bg-black/[0.04] dark:bg-white/[0.05] hover:bg-black/[0.06] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
-                        data-test-id="gpu-memory-mode-select"
-                      >
-                        <SelectValue />
-                      </SelectTrigger>
-                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-                        <SelectItem value="auto">Default</SelectItem>
-                        <SelectItem value="manual">Manual</SelectItem>
-                      </SelectContent>
-                    </Select>
-                  </div>
-                </div>
-                )}
-                {isManual && (
-                  <>
-                    <ParamSlider
-                      label="GPU Layers"
-                      value={Math.max(GPU_LAYERS_AUTO, Math.min(gpuLayers, gpuLayersMax))}
-                      min={GPU_LAYERS_AUTO}
-                      max={gpuLayersMax}
-                      step={1}
-                      onChange={setGpuLayers}
-                      disabled={modelControlsDisabled}
-                      displayValue={autoLayers ? "Auto" : undefined}
-                      valueSize={6}
-                      info={
-                        <>
-                          Layers to keep on the GPU (--gpu-layers); the rest run
-                          on CPU. Auto lets llama.cpp size the split (and the
-                          context) to fit VRAM. At the maximum, the whole model
-                          is on the GPU.
-                        </>
-                      }
-                    />
-                    {showMoeSlider && (
-                      <ParamSlider
-                        label="MoE Layers on CPU"
-                        value={Math.min(nCpuMoe, moeLayersMax)}
-                        min={0}
-                        max={moeLayersMax}
-                        step={1}
-                        onChange={setNCpuMoe}
-                        disabled={modelControlsDisabled}
-                        valueSize={6}
-                        info={
-                          <>
-                            Keep the experts of this many MoE layers on the CPU
-                            (--n-cpu-moe) to save VRAM. 0 = all experts on the
-                            GPU; at the maximum, all are on the CPU.
-                          </>
-                        }
-                      />
-                    )}
-                    {showSplitRatio && (
-                      <div className="space-y-3.5">
-                        <div className="flex min-w-0 items-center gap-1.5">
-                          <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                            Layers per GPU
-                          </span>
-                          <InfoHint>
-                            Splits GPU Layers across GPUs (--tensor-split).
-                            Without Tensor Parallelism each value is the layer
-                            count on that GPU; with it, every GPU holds a slice
-                            of each layer, so the values are only a ratio.
-                          </InfoHint>
-                        </div>
-                        {gpusInUseDevices.map((d, k) => (
-                          <ParamSlider
-                            key={d?.index ?? k}
-                            label={`GPU ${d?.index ?? k}`}
-                            value={Math.min(splitCounts[k] ?? 0, splitTotal)}
-                            min={0}
-                            max={splitTotal}
-                            step={1}
-                            onChange={(v) => setSplitCount(k, v)}
-                            valueSize={6}
-                            disabled={modelControlsDisabled}
-                          />
-                        ))}
-                      </div>
-                    )}
-                  </>
-                )}
-                {showGpuPicker && (
-                  <div className="space-y-2">
-                    <div className="flex min-w-0 items-center gap-1.5">
-                      <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                        GPUs
-                      </span>
-                      <InfoHint>
-                        Which GPUs this model may use. Unchecked GPUs are hidden
-                        from llama.cpp (CUDA_VISIBLE_DEVICES, or
-                        HIP_VISIBLE_DEVICES on ROCm). Leave all checked to use
-                        every GPU. At least one GPU must stay selected.
-                      </InfoHint>
-                    </div>
-                    <div className="flex flex-col gap-2">
-                      {gpuDevices.map((d) => (
-                        <div
-                          key={d.index}
-                          className="flex items-center justify-between gap-3"
-                        >
-                          <span className="min-w-0 truncate text-[12px] text-nav-fg/80">
-                            GPU {d.index}: {d.name}
-                            {d.memoryTotalGb
-                              ? ` · ${Math.round(d.memoryTotalGb)} GB`
-                              : ""}
-                          </span>
-                          <Switch
-                            className="panel-switch shrink-0"
-                            checked={isGpuChecked(d.index)}
-                            onCheckedChange={() => toggleGpu(d.index)}
-                            data-test-id={`gpu-pick-${d.index}`}
-                            disabled={
-                              modelControlsDisabled ||
-                              (isGpuChecked(d.index) && singleGpuInUse)
-                            }
-                          />
-                        </div>
-                      ))}
-                    </div>
-                  </div>
-                )}
-                {gpuModeApplies && !autoLayers && (
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      Tensor Parallelism
-                    </span>
-                    <InfoHint>
-                      No effect on a single GPU. On multi-GPU setups, improves
-                      tokens/sec during generation when using dense models. MoE
-                      models don't benefit and can be much slower.
-                    </InfoHint>
-                  </div>
-                  <Switch
-                    className="panel-switch shrink-0"
-                    checked={tensorParallel}
-                    onCheckedChange={setTensorParallel}
-                    disabled={tpDisabled || modelControlsDisabled}
-                    data-test-id="tensor-parallel-switch"
-                  />
-                </div>
-                )}
-              </>
-            )}
-            {/* No persistent "enable custom code" toggle: it is consented per model
-                via the load-time review dialog. */}
-            {/* Apply/Reset belongs to the model-reload settings above (context
-                length, KV cache, speculative decoding). Render it here, before
-                the Chat Template row, so it never reads as attached to Chat
-                Template (which is edited via its own dialog). When a model is
-                staged (deferred load), Load/Cancel takes its place: there's
-                nothing loaded to "apply" against yet. */}
-            {pendingSelection ? (
-              <div className="flex flex-col gap-4">
-                {stagedDownloading && (
-                  <p className="text-[11px] text-muted-foreground">
-                    Downloading…{" "}
-                    {Math.round((stagedDownloadFraction ?? 0) * 100)}%
+                                : ""
+                            }`}
                   </p>
-                )}
-                {/* GGUF picks only: a non-GGUF pick shows none of the load
-                    knobs the blob captures, so there is nothing to remember. */}
-                {pendingIsGguf && (
-                  <label className="flex cursor-pointer items-center gap-2 pb-1.5 text-[12px] text-muted-foreground">
-                    <Checkbox
-                      className="size-3.5 rounded-full [&_[data-slot=checkbox-indicator]_svg]:size-2.5"
-                      checked={remember}
-                      onCheckedChange={(v) => setRemember(v === true)}
-                      // The save/clear already ran in the Load click handler, so
-                      // a mid-load toggle could not apply -- lock it like the knobs.
-                      disabled={modelControlsDisabled}
-                    />
-                    Remember settings next time
-                  </label>
-                )}
-                {stagedLoading ? (
-                  // Mid-load: nothing to load or abandon until it settles, so disable.
-                  <Button
-                    type="button"
-                    disabled
-                    size="sm"
-                    className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav bg-primary text-primary-foreground hover:bg-primary/90"
-                  >
-                    <Spinner className="size-3.5" />
-                    Loading…
-                  </Button>
-                ) : (
-                  <div className="grid grid-cols-2 gap-3">
+                  {mtpUpdatable && llamaUpdateStatus?.update_available && (
                     <Button
-                      type="button"
-                      onClick={() => {
-                        // Persist (or clear) this model's load knobs before loading.
-                        // Context is stored as the override (null = auto), never the
-                        // resolved native value, so restoring can't force an OOM.
-                        // GGUF-only, like the restore effect: saving for a
-                        // non-GGUF pick would snapshot leftover standing values
-                        // its hidden controls never showed.
-                        const pid = pendingIsGguf ? pendingKey : null;
-                        if (pid) {
-                          if (remember) {
-                            saveRememberedLoadSettings(pid, {
-                              contextLength: customContextLength,
-                              kvCacheDtype,
-                              speculativeType,
-                              specDraftNMax,
-                              tensorParallel,
-                              gpuMemoryMode,
-                              gpuLayers,
-                              nCpuMoe,
-                              selectedGpuIds,
-                            });
-                          } else {
-                            clearRememberedLoadSettings(pid);
-                          }
-                        }
-                        onLoadPendingModel?.();
-                      }}
-                      // Disabled while a different model is mid-load: selectModel
-                      // refuses a concurrent load, so the click could only toast.
-                      disabled={stagedDownloading || loadingModel != null}
                       size="sm"
-                      className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav bg-primary text-primary-foreground hover:bg-primary/90"
+                      className="corner-squircle mt-2 h-7 text-ui-12"
+                      onClick={handleMtpUpdate}
+                      disabled={llamaUpdating}
+                      data-test-id="mtp-update-button"
                     >
-                      {loadingModel != null ? "Another model loading…" : "Load model"}
+                      {llamaUpdating ? "Updating..." : "Update llama.cpp"}
                     </Button>
-                    <Button
-                      type="button"
-                      variant="outline"
-                      size="sm"
-                      onClick={() => {
-                        // Cancel abandons the stage; if a download is mid-flight,
-                        // stop it too rather than leaving it running headless.
-                        if (stagedDownloading) onCancelStagedDownload?.();
-                        abandonStagedModel();
-                      }}
-                      className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav text-muted-foreground"
-                    >
-                      Cancel
-                    </Button>
-                  </div>
-                )}
-              </div>
-            ) : modelSettingsDirty ? (
-              <div className="flex flex-wrap gap-1.5">
-                <Button
-                  type="button"
-                  onClick={() => onReloadModel?.()}
-                  size="sm"
-                  className="h-7 px-3 text-[12px] font-medium tracking-nav bg-primary/92 text-primary-foreground hover:bg-primary"
-                >
-                  Apply
-                </Button>
-                <Button
-                  type="button"
-                  variant="outline"
-                  size="sm"
-                  onClick={() => resetModelSettingsToLoaded()}
-                  className="h-7 px-3 text-[12px] font-medium tracking-nav text-muted-foreground"
-                >
-                  Reset
-                </Button>
-              </div>
-            ) : null}
-            {/* The template override is a load-time knob too (applied on the next
-                reload) and the in-flight load already snapshotted it, so lock its
-                editors like the sibling controls -- a mid-load save would be
-                silently clobbered by the load response despite its toast. */}
-            <ChatTemplateFields disabled={modelControlsDisabled} />
-          </div>
-        </CollapsibleSection>
+                  )}
+                </div>
+              )}
+              {showContextVramWarning && (
+                <p className="text-ui-11 text-amber-500">
+                  Context length exceeds the estimated VRAM capacity (
+                      {ggufMaxContextLength?.toLocaleString()} tokens). The
+                      model may use system RAM.
+                </p>
+              )}
+            </div>
+          </CollapsibleSection>
         )}
 
         <CollapsibleSection
           label="Preset"
           defaultOpen={true}
-          first={!hasModelContent}
+          first={!hasModelContent && !modelConfig}
         >
           <div className="flex flex-col gap-3 pt-1">
             <DropdownMenu>
-              <DropdownMenuTrigger asChild>
+                  <DropdownMenuTrigger asChild={true}>
                 <div
                   className="w-full min-w-0 cursor-pointer outline-none focus-visible:outline-none"
                   aria-label="Open preset list"
@@ -1752,7 +812,7 @@ export function ChatSettingsPanel({
                       maxLength={80}
                       autoComplete="off"
                       className={cn(
-                        "!h-9 min-h-0 min-w-0 self-stretch !pl-3.5 !pr-2 py-0 text-[13px] font-medium leading-9 text-nav-fg md:text-[13px]",
+                        "!h-9 min-h-0 min-w-0 self-stretch !pl-3.5 !pr-2 py-0 text-ui-13 font-medium leading-9 text-nav-fg md:text-ui-13",
                         presetSaveState.isSaveReady &&
                           "placeholder:text-primary/50",
                       )}
@@ -1792,7 +852,7 @@ export function ChatSettingsPanel({
                         }
                         applyPreset(p.name);
                       }}
-                      className="flex min-h-9 items-center px-3 py-0 text-[13px] font-medium leading-[1.4] tracking-nav"
+                      className="flex min-h-9 items-center px-3 py-0 text-ui-13 font-medium leading-[1.4] tracking-nav"
                     >
                       {p.name}
                     </DropdownMenuItem>
@@ -1809,10 +869,12 @@ export function ChatSettingsPanel({
                 type="button"
                 onClick={() => savePresetWithName(presetNameInput)}
                 disabled={!(settingsHydrated && presetSaveState.canSubmit)}
-                variant={presetSaveState.isSaveReady ? "default" : "outline"}
+                    variant={
+                      presetSaveState.isSaveReady ? "default" : "outline"
+                    }
                 size="sm"
                 className={cn(
-                  "h-9 w-full rounded-full text-[13px] font-medium tracking-nav",
+                  "h-9 w-full rounded-full text-ui-13 font-medium tracking-nav",
                   presetSaveState.isSaveReady &&
                     "bg-primary text-primary-foreground hover:bg-primary/90",
                 )}
@@ -1827,7 +889,7 @@ export function ChatSettingsPanel({
                 disabled={!(settingsHydrated && activeCustomPreset)}
                 variant="outline"
                 size="sm"
-                className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav text-muted-foreground"
+                className="h-9 w-full rounded-full text-ui-13 font-medium tracking-nav text-muted-foreground"
                 title={
                   activeCustomPreset
                     ? activeBuiltinPreset
@@ -1846,11 +908,12 @@ export function ChatSettingsPanel({
           <CollapsibleSection label="Provider" defaultOpen={true}>
             <div className="flex items-center justify-between gap-3 pt-1">
               <div className="flex min-w-0 items-center gap-1.5">
-                <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
                   Prompt caching
                 </span>
                 <InfoHint>
-                  Reuse compatible prompt prefixes for lower latency and cost.
+                      Reuse compatible prompt prefixes for lower latency and
+                      cost.
                 </InfoHint>
               </div>
               <Switch
@@ -1868,15 +931,15 @@ export function ChatSettingsPanel({
             {showPromptCacheTtlControl && promptCachingEnabled ? (
               <div className="flex items-center justify-between gap-3 pt-3">
                 <div className="flex min-w-0 items-center gap-1.5">
-                  <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                  <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
                     Cache TTL
                   </span>
                   <InfoHint>
                     Anthropic exposes a 5 minute and a 1 hour ephemeral
-                    cache pool. The 1 hour pool costs 2x base input on
-                    write vs 1.25x for 5 minute, but reads stay 0.1x for
-                    both, so a single read landing more than 5 minutes
-                    after the write pays off the premium.
+                        cache pool. The 1 hour pool costs 2x base input on write
+                        vs 1.25x for 5 minute, but reads stay 0.1x for both, so
+                        a single read landing more than 5 minutes after the
+                        write pays off the premium.
                   </InfoHint>
                 </div>
                 <Select
@@ -1905,7 +968,7 @@ export function ChatSettingsPanel({
             {showFastModeControl ? (
               <div className="flex items-center justify-between gap-3 pt-3">
                 <div className="flex min-w-0 items-center gap-1.5">
-                  <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                  <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
                     Fast mode
                   </span>
                   <InfoHint>
@@ -1944,7 +1007,7 @@ export function ChatSettingsPanel({
           onLabelClick={openSystemPromptEditor}
           headerAction={
             <Tooltip>
-              <TooltipPrimitive.Trigger asChild>
+                  <TooltipPrimitive.Trigger asChild={true}>
                 <button
                   type="button"
                   onClick={openSystemPromptEditor}
@@ -1993,14 +1056,13 @@ export function ChatSettingsPanel({
               placeholder="Example: You are a helpful assistant..."
               aria-label="System prompt"
               className={cn(
-                "block size-full resize-none bg-transparent px-3.5 py-2.5 text-left text-[13px] font-medium leading-relaxed text-nav-fg outline-none placeholder:text-muted-foreground",
+                "block size-full resize-none bg-transparent px-3.5 py-2.5 text-left text-ui-13 font-medium leading-relaxed text-nav-fg outline-none placeholder:text-muted-foreground",
                 systemPromptOverflows && "cursor-pointer",
               )}
             />
           </div>
         </CollapsibleSection>
 
-
         <CollapsibleSection label="Sampling" defaultOpen={true}>
           <div className="flex flex-col gap-5 pt-1">
             {showTemperature ? (
@@ -2071,21 +1133,12 @@ export function ChatSettingsPanel({
                 max={2}
                 step={0.1}
                 onChange={set("presencePenalty")}
-                displayValue={params.presencePenalty === 0 ? "Off" : undefined}
+                    displayValue={
+                      params.presencePenalty === 0 ? "Off" : undefined
+                    }
                 info="Penalizes any token that has already appeared at least once, encouraging the model to introduce new topics. 0 = off."
               />
             ) : null}
-            {!isExternalModel && !isGguf && (
-              <ParamSlider
-                label="Max Seq Length"
-                value={params.maxSeqLength}
-                min={128}
-                max={32768}
-                step={128}
-                onChange={set("maxSeqLength")}
-                info="Maximum context window size in tokens — input prompt plus generated output combined. Capped by the model's trained limit."
-              />
-            )}
             <ParamSlider
               label="Max Tokens"
               value={params.maxTokens}
@@ -2094,31 +1147,24 @@ export function ChatSettingsPanel({
                   ? getExternalMinOutputTokens(externalProviderType)
                   : 64
               }
-              max={
-                // A staged GGUF caps to its own context even over an active
-                // external model (the staged model is what will load).
-                !pendingIsGguf && isExternalModel
-                  ? getExternalMaxOutputTokens(
-                      externalProviderType,
-                      externalSelection?.modelId,
-                    )
-                  : isGguf && baseContext
-                    ? baseContext
-                    : 32768
-              }
+              max={maxTokensMax}
               step={64}
               onChange={set("maxTokens")}
               displayValue={
                 isGguf && baseContext && params.maxTokens >= baseContext
                   ? "Max"
-                  : undefined
+                  : !isExternalModel &&
+                      !isGguf &&
+                      params.maxTokens >= maxTokensMax
+                    ? "Max"
+                    : undefined
               }
               info="Maximum number of tokens to generate per response. Generation stops at this limit or when the model emits an end-of-sequence token."
             />
           </div>
         </CollapsibleSection>
 
-        {!isExternalModel ? (
+            {isExternalModel ? null : (
           <CollapsibleSection label="Tools">
             <div className="flex flex-col gap-5 pt-1">
               <AutoHealToolCallsToggle />
@@ -2129,13 +1175,13 @@ export function ChatSettingsPanel({
               <ToolCallTimeoutSlider />
             </div>
           </CollapsibleSection>
-        ) : null}
+            )}
 
-        {!isExternalModel ? (
+            {isExternalModel ? null : (
           <CollapsibleSection label="Retrieval">
             <RetrievalSettingsSection />
           </CollapsibleSection>
-        ) : null}
+            )}
       </div>
       </div>
       </div>
@@ -2156,13 +1202,13 @@ export function ChatSettingsPanel({
           <div className="space-y-3">
             <div className="space-y-0.5 px-0.5">
               <div className="flex items-center justify-between gap-3">
-                <div className="text-[11px] font-medium">Prompt editor</div>
+                <div className="text-ui-11 font-medium">Prompt editor</div>
                 <Button
                   type="button"
                   variant="ghost"
                   size="sm"
                   onClick={() => setSystemVariablesOpen((open) => !open)}
-                  className="h-7 gap-1.5 rounded-full px-2.5 text-[11px] text-muted-foreground"
+                  className="h-7 gap-1.5 rounded-full px-2.5 text-ui-11 text-muted-foreground"
                   aria-expanded={systemVariablesOpen}
                 >
                   <Braces className="size-3.5" />
@@ -2175,7 +1221,7 @@ export function ChatSettingsPanel({
                   />
                 </Button>
               </div>
-              <p className="text-[11px] text-muted-foreground">
+              <p className="text-ui-11 text-muted-foreground">
                 Use this for longer edits. Save writes back to the active
                 configuration only. Insert variables with {"{{ env }}"}.
               </p>
@@ -2184,16 +1230,16 @@ export function ChatSettingsPanel({
               <div className="space-y-2 px-0.5">
                 <div className="flex flex-wrap items-start justify-between gap-2">
                   <div className="space-y-0.5">
-                    <div className="text-[11px] font-medium">
+                    <div className="text-ui-11 font-medium">
                       Prompt variables
                     </div>
-                    <p className="text-[11px] text-muted-foreground">
+                    <p className="text-ui-11 text-muted-foreground">
                       Define values as JSON below, then use each key in your
                       prompt, like {"{{ env }}"}.
                     </p>
                   </div>
                   <div className="flex flex-col items-end gap-1">
-                    <span className="text-[10px] text-muted-foreground">
+                    <span className="text-ui-10 text-muted-foreground">
                       Built-in, fill in automatically
                     </span>
                     <div className="flex flex-wrap justify-end gap-1">
@@ -2201,7 +1247,7 @@ export function ChatSettingsPanel({
                         <span
                           key={token}
                           title={`${token} is replaced automatically when you send`}
-                          className="rounded-full bg-muted px-2 py-0.5 font-mono text-[10px] text-muted-foreground"
+                          className="rounded-full bg-muted px-2 py-0.5 font-mono text-ui-10 text-muted-foreground"
                         >
                           {token}
                         </span>
@@ -2226,11 +1272,11 @@ export function ChatSettingsPanel({
                   aria-invalid={Boolean(systemVariablesError)}
                 />
                 {systemVariablesError ? (
-                  <p className="px-1 text-[11px] text-destructive">
+                  <p className="px-1 text-ui-11 text-destructive">
                     {systemVariablesError}
                   </p>
                 ) : (
-                  <p className="px-1 text-[11px] text-muted-foreground">
+                  <p className="px-1 text-ui-11 text-muted-foreground">
                     Names you don&apos;t define are left unchanged, so a stray
                     {" {{ typo }} "}stays visible in the prompt.
                   </p>
@@ -2380,7 +1426,7 @@ function AutoHealToolCallsToggle() {
   return (
     <div className="flex items-center justify-between gap-3">
       <div className="flex min-w-0 items-center gap-1.5">
-        <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+        <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
           Auto-Healing Tool Calls
         </span>
         <InfoHint>
@@ -2404,7 +1450,7 @@ function NudgeToolCallsToggle() {
   return (
     <div className="flex items-center justify-between gap-3">
       <div className="flex min-w-0 items-center gap-1.5">
-        <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+        <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
           Nudge Tool Calls
         </span>
         <InfoHint>
@@ -2429,7 +1475,7 @@ function ConfirmToolCallsToggle() {
     <div className="flex items-center justify-between gap-3">
       <div className="flex min-w-0 flex-col gap-0.5">
         <div className="flex min-w-0 items-center gap-1.5">
-          <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+          <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
             Confirm tool calls
           </span>
           <InfoHint>
@@ -2441,7 +1487,7 @@ function ConfirmToolCallsToggle() {
           </InfoHint>
         </div>
         {permissionMode === "full" ? (
-          <span className="text-[11px] text-muted-foreground">
+          <span className="text-ui-11 text-muted-foreground">
             Overridden by Full access
           </span>
         ) : null}
@@ -2462,7 +1508,7 @@ function BypassPermissionsToggle() {
   return (
     <div className="flex flex-col gap-2">
       <div className="flex min-w-0 items-center gap-1.5">
-        <span className="whitespace-nowrap text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+        <span className="whitespace-nowrap text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
           Tool permissions
         </span>
         <InfoHint>
@@ -2471,164 +1517,12 @@ function BypassPermissionsToggle() {
         </InfoHint>
       </div>
       {/* Full width, styled like the panel selects/preset input. */}
-      <PermissionModeDropdown triggerClassName="h-9 w-full justify-between rounded-full border-0 bg-[var(--panel-input-surface)] px-3.5 text-[13px] font-medium text-nav-fg shadow-none hover:bg-[var(--panel-input-surface)]" />
+      <PermissionModeDropdown triggerClassName="h-9 w-full justify-between rounded-full border-0 bg-[var(--panel-input-surface)] px-3.5 text-ui-13 font-medium text-nav-fg shadow-none hover:bg-[var(--panel-input-surface)]" />
       {permissionMode === "full" ? (
-        <span className="text-[11px] text-bypass">
+        <span className="text-ui-11 text-bypass">
           Tool calls run with no confirmation and no sandbox.
         </span>
       ) : null}
     </div>
   );
 }
-
-function ChatTemplateFields({ disabled = false }: { disabled?: boolean }) {
-  const defaultTemplate = useChatRuntimeStore((s) => s.defaultChatTemplate);
-  const override = useChatRuntimeStore((s) => s.chatTemplateOverride);
-  const setOverride = useChatRuntimeStore((s) => s.setChatTemplateOverride);
-  const [editorOpen, setEditorOpen] = useState(false);
-  const [draft, setDraft] = useState("");
-
-  if (!defaultTemplate) return null;
-
-  const displayValue = override ?? defaultTemplate;
-  const isModified = override !== null;
-  const draftDirty = draft !== displayValue;
-
-  const openEditor = () => {
-    setDraft(displayValue);
-    setEditorOpen(true);
-  };
-  const saveEditor = () => {
-    const cleared = draft.trim().length === 0 || draft === defaultTemplate;
-    setOverride(cleared ? null : draft);
-    setEditorOpen(false);
-    toast.success(
-      cleared
-        ? "Chat template reset to default. It applies on the next model reload."
-        : "Chat template saved. It applies on the next model reload.",
-    );
-  };
-
-  return (
-    <>
-      <div className="-mb-1.5 flex items-center justify-between gap-2">
-        <button
-          type="button"
-          onClick={openEditor}
-          disabled={disabled}
-          className="cursor-pointer text-left text-[13px] font-medium tracking-nav text-nav-fg disabled:pointer-events-none disabled:opacity-50"
-        >
-          Chat Template
-        </button>
-        <div className="flex items-center gap-1">
-          {isModified && (
-            <Tooltip>
-              <TooltipPrimitive.Trigger asChild>
-                <button
-                  type="button"
-                  onClick={() => setOverride(null)}
-                  disabled={disabled}
-                  className="nav-icon-btn text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white disabled:pointer-events-none disabled:opacity-50"
-                  aria-label="Revert chat template"
-                >
-                  <HugeiconsIcon
-                    icon={ArrowTurnBackwardIcon}
-                    strokeWidth={1.75}
-                    className="size-4"
-                  />
-                </button>
-              </TooltipPrimitive.Trigger>
-              <TooltipContent
-                side="top"
-                sideOffset={6}
-                className="tooltip-compact"
-              >
-                Revert changes
-              </TooltipContent>
-            </Tooltip>
-          )}
-          <Tooltip>
-            <TooltipPrimitive.Trigger asChild>
-              <button
-                type="button"
-                onClick={openEditor}
-                disabled={disabled}
-                className="nav-icon-btn text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white disabled:pointer-events-none disabled:opacity-50"
-                aria-label="Edit chat template"
-              >
-                <HugeiconsIcon
-                  icon={Edit03Icon}
-                  strokeWidth={1.75}
-                  className="size-3"
-                />
-              </button>
-            </TooltipPrimitive.Trigger>
-            <TooltipContent
-              side="top"
-              sideOffset={6}
-              className="tooltip-compact"
-            >
-              Edit template
-            </TooltipContent>
-          </Tooltip>
-        </div>
-      </div>
-      <Dialog open={editorOpen} onOpenChange={setEditorOpen}>
-        <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-3xl">
-          <DialogHeader>
-            <DialogTitle>Edit Chat Template</DialogTitle>
-            <DialogDescription>
-              Override the model's chat template. The change applies on the
-              next model reload.
-            </DialogDescription>
-          </DialogHeader>
-          <div className="space-y-2">
-            <div className="space-y-0.5 px-0.5">
-              <div className="text-[11px] font-medium">Template editor</div>
-              <p className="text-[11px] text-muted-foreground">
-                Jinja syntax. Save matching the default clears the override.
-              </p>
-            </div>
-            <Textarea
-              value={draft}
-              onChange={(event) => setDraft(event.target.value)}
-              fieldSizing="fixed"
-              className="min-h-[24rem] max-h-[50vh] overflow-y-auto border-0 font-mono text-xs leading-5 corner-squircle focus-visible:ring-0"
-              rows={14}
-              spellCheck={false}
-            />
-          </div>
-          <DialogFooter className="flex-wrap gap-2 sm:justify-between">
-            <Button
-              type="button"
-              variant="ghost"
-              onClick={() => setDraft(defaultTemplate)}
-              disabled={draft === defaultTemplate}
-              className="text-muted-foreground"
-            >
-              Reset
-            </Button>
-            <div className="flex flex-wrap gap-2">
-              <Button
-                type="button"
-                variant="ghost"
-                onClick={() => setEditorOpen(false)}
-              >
-                Cancel
-              </Button>
-              {/* Also locked mid-load: an autoLoad can start with this dialog
-                  already open, and a save then would be silently clobbered. */}
-              <Button
-                type="button"
-                onClick={saveEditor}
-                disabled={!draftDirty || disabled}
-              >
-                Save
-              </Button>
-            </div>
-          </DialogFooter>
-        </DialogContent>
-      </Dialog>
-    </>
-  );
-}
diff --git a/studio/frontend/src/features/chat/components/chat-search-dialog.tsx b/studio/frontend/src/features/chat/components/chat-search-dialog.tsx
index dc3e1aac29..7bf1b4b2aa 100644
--- a/studio/frontend/src/features/chat/components/chat-search-dialog.tsx
+++ b/studio/frontend/src/features/chat/components/chat-search-dialog.tsx
@@ -143,10 +143,10 @@ export function ChatSearchDialog() {
                   strokeWidth={2}
                   className="size-4 shrink-0 text-muted-foreground"
                 />
-                <span className="min-w-0 flex-1 truncate text-[13px] font-medium">
+                <span className="min-w-0 flex-1 truncate text-ui-13 font-medium">
                   {item.title || "Untitled chat"}
                 </span>
-                <span className="shrink-0 text-[11px] text-muted-foreground">
+                <span className="shrink-0 text-ui-11 text-muted-foreground">
                   {formatRelative(item.createdAt)}
                 </span>
               </CommandPrimitive.Item>
diff --git a/studio/frontend/src/features/chat/components/context-usage-bar.tsx b/studio/frontend/src/features/chat/components/context-usage-bar.tsx
index 80f502e222..9c80ce6b11 100644
--- a/studio/frontend/src/features/chat/components/context-usage-bar.tsx
+++ b/studio/frontend/src/features/chat/components/context-usage-bar.tsx
@@ -71,7 +71,7 @@ export const ContextUsageBar: FC<{
               : `Token usage: ${formatTokenCount(used)} tokens`
           }
           className={cn(
-            "flex items-center gap-2 rounded-[10px] px-2.5 py-1 font-mono text-chat-icon-fg text-[13px] tabular-nums transition-colors hover:bg-chat-icon-bg-hover hover:text-chat-icon-fg-hover",
+            "flex items-center gap-2 rounded-[10px] px-2.5 py-1 font-mono text-chat-icon-fg text-ui-13 tabular-nums transition-colors hover:bg-chat-icon-bg-hover hover:text-chat-icon-fg-hover",
             className,
           )}
         >
@@ -149,7 +149,7 @@ export const ContextUsageBar: FC<{
             </span>
           </div>
           {hasKnownLimit && percent !== null && percent > 85 ? (
-            <div className="mt-1 max-w-64 text-[11px] leading-snug text-muted-foreground/90">
+            <div className="mt-1 max-w-64 text-ui-11 leading-snug text-muted-foreground/90">
               Close to the context limit. Generation will stop at 100%.
               Increase <span className="font-medium">Context Length</span> in
               the chat Settings panel to keep going.
diff --git a/studio/frontend/src/features/chat/components/model-load-status.tsx b/studio/frontend/src/features/chat/components/model-load-status.tsx
index 292c7884fd..6e22c6de4b 100644
--- a/studio/frontend/src/features/chat/components/model-load-status.tsx
+++ b/studio/frontend/src/features/chat/components/model-load-status.tsx
@@ -54,14 +54,14 @@ export function ModelLoadDescription({
         {title ? <p className="text-foreground leading-tight font-semibold">{title}</p> : null}
         {hasProgress ? (
           <div className="w-full pt-1">
-            <div className="flex items-center justify-between gap-2 text-[10px] font-medium tracking-[0.08em] text-muted-foreground/80">
+            <div className="flex items-center justify-between gap-2 text-ui-10 font-medium tracking-[0.08em] text-muted-foreground/80">
               <span className="min-w-0 truncate">{labelPrimary}</span>
               <span className="shrink-0 tabular-nums">
                 {Math.round(clampProgress(progressPercent))}%
               </span>
             </div>
             {labelSecondary ? (
-              <div className="truncate pt-0.5 text-[10px] font-medium tracking-[0.08em] text-muted-foreground/60">
+              <div className="truncate pt-0.5 text-ui-10 font-medium tracking-[0.08em] text-muted-foreground/60">
                 {labelSecondary}
               </div>
             ) : null}
@@ -107,7 +107,7 @@ export function ModelLoadInlineStatus({
             <Progress value={clampProgress(progressPercent)} className="h-1 bg-foreground/[0.08]" />
           </div>
           <div
-            className="flex shrink-0 items-center gap-1 text-[10px] font-medium tracking-[0.08em] text-muted-foreground/80"
+            className="flex shrink-0 items-center gap-1 text-ui-10 font-medium tracking-[0.08em] text-muted-foreground/80"
             title={progressLabel ?? undefined}
           >
             {/* Tight inline layout: show only the primary (bytes) chunk;
@@ -124,7 +124,7 @@ export function ModelLoadInlineStatus({
           type="button"
           size="xs"
           variant="outline"
-          className="shrink-0 text-[11px]"
+          className="shrink-0 text-ui-11"
           onClick={onStop}
         >
           Stop
diff --git a/studio/frontend/src/features/chat/components/openai-code-exec-section.tsx b/studio/frontend/src/features/chat/components/openai-code-exec-section.tsx
index cb0234579b..4da9774192 100644
--- a/studio/frontend/src/features/chat/components/openai-code-exec-section.tsx
+++ b/studio/frontend/src/features/chat/components/openai-code-exec-section.tsx
@@ -435,7 +435,7 @@ export function OpenAICodeExecSection({
         <div className="flex min-w-0 items-center gap-1.5">
           <label
             htmlFor="openai-container-ttl"
-            className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg"
+            className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg"
           >
             Idle timeout
           </label>
@@ -459,7 +459,7 @@ export function OpenAICodeExecSection({
           ACTIVE pill marks which one (no separate picker). */}
       <div className="flex flex-col gap-1.5">
         <div className="flex items-center justify-between gap-2">
-          <span className="text-[11px] uppercase tracking-wider text-muted-foreground">
+          <span className="text-ui-11 uppercase tracking-wider text-muted-foreground">
             Containers
           </span>
           <Button
@@ -531,15 +531,15 @@ export function OpenAICodeExecSection({
                         {c.name ?? "(unnamed)"}
                       </span>
                       {isPending ? (
-                        <span className="shrink-0 rounded-sm bg-muted px-1 py-px text-[9px] font-medium uppercase tracking-wider text-muted-foreground">
+                        <span className="shrink-0 rounded-sm bg-muted px-1 py-px text-ui-9 font-medium uppercase tracking-wider text-muted-foreground">
                           Creating
                         </span>
                       ) : isActive ? (
-                        <span className="shrink-0 rounded-sm bg-primary/15 px-1 py-px text-[9px] font-medium uppercase tracking-wider text-primary">
+                        <span className="shrink-0 rounded-sm bg-primary/15 px-1 py-px text-ui-9 font-medium uppercase tracking-wider text-primary">
                           Active
                         </span>
                       ) : statusLabel ? (
-                        <span className="shrink-0 rounded-sm bg-muted px-1 py-px text-[9px] font-medium uppercase tracking-wider text-muted-foreground">
+                        <span className="shrink-0 rounded-sm bg-muted px-1 py-px text-ui-9 font-medium uppercase tracking-wider text-muted-foreground">
                           {statusLabel}
                         </span>
                       ) : null}
@@ -548,10 +548,10 @@ export function OpenAICodeExecSection({
                       className="flex min-w-0 items-center gap-1.5 text-muted-foreground"
                       title={c.id}
                     >
-                      <span className="min-w-0 truncate font-mono text-[11px]">
+                      <span className="min-w-0 truncate font-mono text-ui-11">
                         {shortContainerId(c.id)}
                       </span>
-                      <span className="shrink-0 text-[10px] uppercase tracking-wider">
+                      <span className="shrink-0 text-ui-10 uppercase tracking-wider">
                         · {ttlMinutes}m
                       </span>
                     </div>
diff --git a/studio/frontend/src/features/chat/components/project-switcher.tsx b/studio/frontend/src/features/chat/components/project-switcher.tsx
index 13360ccf7e..a37df882b4 100644
--- a/studio/frontend/src/features/chat/components/project-switcher.tsx
+++ b/studio/frontend/src/features/chat/components/project-switcher.tsx
@@ -57,7 +57,7 @@ export function ProjectSwitcher({
             className="size-icon shrink-0 text-foreground/70"
           />
           <span className="flex min-w-0 flex-1 items-baseline">
-            <span className="min-w-0 flex max-w-[150px] flex-1 items-baseline truncate font-heading text-[16px] font-medium leading-tight text-black dark:text-white">
+            <span className="min-w-0 flex max-w-[150px] flex-1 items-baseline truncate font-heading text-ui-16 font-medium leading-tight text-black dark:text-white">
               {label}
             </span>
           </span>
@@ -75,8 +75,11 @@ export function ProjectSwitcher({
         side="bottom"
         align="start"
         sideOffset={0}
-        className="unsloth-plus-menu ring-0 min-w-56 max-w-72 max-h-72 font-heading"
+        className="unsloth-plus-menu ring-0 min-w-56 max-w-72 font-heading"
       >
+        {/* Scroll the list here, not the container, so the rounded corners on
+            the scrollbar side are not squared off. */}
+        <div className="max-h-72 overflow-y-auto">
         {showLoadingRow ? (
           <DropdownMenuItem disabled={true} className="text-muted-foreground">
             Loading…
@@ -117,6 +120,7 @@ export function ProjectSwitcher({
         <DropdownMenuItem onSelect={onViewAllProjects}>
           View all projects
         </DropdownMenuItem>
+        </div>
       </DropdownMenuContent>
     </DropdownMenu>
   );
diff --git a/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts b/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
index 3003b52230..76a310ac33 100644
--- a/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
+++ b/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
@@ -32,14 +32,13 @@ import {
   GPU_LAYERS_AUTO,
   isLocalModelPath,
   loadedGpuMemoryFields,
-  loadedGpuMemoryFieldsUnlessStaged,
-  pendingSelectionMatches,
   persistGpuMemoryModeOnLoad,
   readPersistedSpeculativeType,
   reconcilePersistedGpuIds,
   resolveToolsEnabledOnLoad,
   saveSpeculativeType,
   useChatRuntimeStore,
+  type LoadingModelPick,
   type ReasoningEffort,
 } from "../stores/chat-runtime-store";
 import { clampReasoningEffortToLevels } from "../provider-capabilities";
@@ -61,7 +60,10 @@ import {
   isMultimodalResponse,
 } from "../types/api";
 import { isExternalModelId } from "../external-providers";
-import { cancelStagedModelDownload } from "@/features/hub";
+import {
+  applyPerModelConfigToRuntime,
+  type PerModelConfig,
+} from "@/features/model-picker";
 import type {
   ChatLoraSummary,
   ChatModelSummary,
@@ -81,14 +83,16 @@ export type SelectedModelInput = {
   expectedBytes?: number;
   forceReload?: boolean;
   nativePathToken?: string;
+  nativePathExpiresAtMs?: number | null;
   /** Direct local .gguf file (no HF variant / native token) — still a GGUF
    *  source, so the staging flow treats it as one. */
   isGguf?: boolean;
   throwOnError?: boolean;
   /** Keep the current speculative-decoding choice across the model switch
-   *  instead of resetting it to the standing preference. Set by the deferred
-   *  ("Load on selection") Load, where the user picked it for this model. */
+   *  instead of resetting it to the standing preference. */
   keepSpeculative?: boolean;
+  config?: PerModelConfig;
+  previousConfig?: PerModelConfig;
 };
 
 // Approved fingerprints by checkpoint, so a rollback after a failed switch can resend
@@ -107,7 +111,7 @@ const MODEL_LOAD_TOAST_CLASSNAMES = {
   title: "leading-5",
   description: "mt-0 w-full",
   cancelButton:
-    "!h-auto !rounded-none !border-0 !bg-transparent !px-1 !text-[11px] !font-normal !text-muted-foreground hover:!bg-transparent hover:!text-destructive focus-visible:!text-destructive",
+    "!h-auto !rounded-none !border-0 !bg-transparent !px-1 !text-ui-11 !font-normal !text-muted-foreground hover:!bg-transparent hover:!text-destructive focus-visible:!text-destructive",
 } as const;
 
 const MODEL_LOADED_TOAST_CLASSNAMES = {
@@ -347,6 +351,18 @@ export async function resyncInferenceStatusAfterServerModelChange(): Promise<voi
   await syncInferenceStatusToStore();
 }
 
+function pickOf(info: {
+  id: string;
+  ggufVariant?: string | null;
+  nativePathToken?: string | null;
+}): LoadingModelPick {
+  return {
+    id: info.id,
+    ggufVariant: info.ggufVariant ?? null,
+    nativePathToken: info.nativePathToken ?? null,
+  };
+}
+
 export function useChatModelRuntime() {
   const params = useChatRuntimeStore((state) => state.params);
   const models = useChatRuntimeStore((state) => state.models);
@@ -385,12 +401,16 @@ export function useChatModelRuntime() {
   }, []);
 
   const resetLoadingUi = useCallback(() => {
+    const inFlight = loadingModelRef.current;
     setLoadingModel(null);
     setLoadProgress(null);
     loadingModelRef.current = null;
     loadAbortRef.current = null;
     loadToastIdRef.current = null;
     setLoadToastDismissedState(false);
+    if (inFlight) {
+      useChatRuntimeStore.getState().clearLoadingModelPick(pickOf(inFlight));
+    }
     if (!cancelUnloadPendingRef.current) {
       useChatRuntimeStore.getState().setModelLoading(false);
     }
@@ -424,6 +444,7 @@ export function useChatModelRuntime() {
     loadAbortRef.current?.abort();
     loadAbortRef.current = null;
     loadingModelRef.current = null;
+    useChatRuntimeStore.getState().clearLoadingModelPick(pickOf(model));
     const tid = loadToastIdRef.current;
     loadToastIdRef.current = null;
     setLoadingModel(null);
@@ -460,45 +481,36 @@ export function useChatModelRuntime() {
         typeof selection === "string" ? false : selection.forceReload ?? false;
       const nativePathToken =
         typeof selection === "string" ? undefined : selection.nativePathToken;
+      const nativePathExpiresAtMs =
+        typeof selection === "string"
+          ? null
+          : selection.nativePathExpiresAtMs ?? null;
       const explicitIsGguf =
         typeof selection === "string" ? undefined : selection.isGguf;
       const throwOnError =
         typeof selection === "string" ? false : selection.throwOnError ?? false;
       const keepSpeculative =
         typeof selection === "string" ? false : selection.keepSpeculative ?? false;
-      // Picking/loading any model abandons a staged (deferred) selection.
-      // Before the early-returns below so even a no-op re-select clears the
-      // stage.
-      const staged = useChatRuntimeStore.getState().pendingSelection;
-      if (staged) {
-        // Loading a DIFFERENT model abandons this stage. Loading the staged pick
-        // ITSELF keeps it so the sidebar can show its load settings (context, KV
-        // cache, …) during the load. Cleared on success below; on failure it's
-        // left staged so the user can retry (see onLoadPendingModel's catch).
-        const loadingStagedPick = pendingSelectionMatches(staged, {
-          id: modelId,
-          ggufVariant,
-          nativePathToken,
-        });
-        if (!loadingStagedPick) {
-          cancelStagedModelDownload(staged);
-          useChatRuntimeStore.getState().setPendingSelection(null);
-        }
-      }
       const currentVariant = useChatRuntimeStore.getState().activeGgufVariant;
       if (!forceReload && (!modelId || (params.checkpoint === modelId && (ggufVariant ?? null) === (currentVariant ?? null)))) {
+        if (typeof selection !== "string" && selection.previousConfig) {
+          applyPerModelConfigToRuntime(selection.previousConfig);
+        }
         return;
       }
-      // A load is already in flight. If it's this exact pick (id + GGUF variant +
-      // native path token), ignore the duplicate click. If it's a DIFFERENT model
-      // -- crucially including a different GGUF variant of the same repo, which the
-      // old id+token-only guard wrongly treated as a duplicate and silently
-      // no-op'd -- don't start a second concurrent load (the load path has no clean
-      // supersession) and don't silently swallow the request: surface it so the
-      // user knows to wait for, or cancel, the in-flight load. Centralized here so
-      // every entry point is covered, not just the staged Load button.
-      const inFlightLoad = loadingModelRef.current;
+      // A load is already in flight. If it's this exact pick (id + variant + token),
+      // ignore the duplicate click. If it's a DIFFERENT model (including a different
+      // GGUF variant of the same repo, which the old id+token guard wrongly treated
+      // as a duplicate), don't start a second concurrent load and don't swallow the
+      // request: surface it so the user waits or cancels. Centralized here so every
+      // entry point is covered, not just the staged Load button.
+      const inFlightLoad =
+        loadingModelRef.current ??
+        useChatRuntimeStore.getState().loadingModelPick;
       if (inFlightLoad) {
+        if (typeof selection !== "string" && selection.previousConfig) {
+          applyPerModelConfigToRuntime(selection.previousConfig);
+        }
         const loadingSamePick =
           inFlightLoad.id === modelId &&
           (inFlightLoad.ggufVariant ?? null) === (ggufVariant ?? null) &&
@@ -526,7 +538,11 @@ export function useChatModelRuntime() {
       // native model intents only grant .gguf files), but its id is a display
       // label that need not end in ".gguf" -- without this, Manual + Auto
       // layers would pin the UI context instead of letting --fit size it.
-      const isGguf = explicitIsGguf ?? model?.isGguf ?? nativePathToken != null;
+      const isGguf =
+        explicitIsGguf ??
+        (ggufVariant != null ||
+          nativePathToken != null ||
+          model?.isGguf === true);
       const loraIsAdapter = lora?.exportType === "lora";
       const isLora =
         explicitIsLora ?? model?.isLora ?? loraIsAdapter ?? false;
@@ -575,6 +591,7 @@ export function useChatModelRuntime() {
       };
       setLoadingModel(loadInfo);
       useChatRuntimeStore.getState().setModelLoading(true);
+      useChatRuntimeStore.getState().setLoadingModelPick(pickOf(loadInfo));
       setLoadProgress(
         isDownloaded || isCachedLora
           ? { percent: null, label: null, phase: "starting" }
@@ -600,26 +617,33 @@ export function useChatModelRuntime() {
             || previousVariant != null
             || previousActiveNativePathToken != null
             || (previousCheckpoint?.toLowerCase().endsWith(".gguf") ?? false);
+          // Roll back to the previous model's own context. previousConfig was
+          // snapshotted before this load pre-applied the next model's config, so
+          // params.maxSeqLength may already be the next model's; use it only when
+          // no snapshot exists.
+          const previousMaxSeqLength =
+            (typeof selection !== "string"
+              ? selection.previousConfig?.maxSeqLength
+              : null) ?? maxSeqLength;
           // Respect the rolled-back model's auto-layers mode: a Manual+Auto model
-          // with an unpinned (auto) context must reload with 0 (so --fit
-          // re-auto-sizes), not the positive context it happened to pick (which
-          // the backend would treat as a pin).
+          // with an unpinned context must reload with 0 (so --fit re-auto-sizes),
+          // not the positive context it picked (which the backend treats as a pin).
           const rollbackMaxSeqLength = resolveFitMaxSeqLength(
             previousIsGguf,
             stateBeforeUnload.loadedGpuMemoryMode ?? "auto",
             stateBeforeUnload.loadedGpuLayers ?? GPU_LAYERS_AUTO,
             stateBeforeUnload.loadedCustomContextLength,
-            previousIsGguf ? (stateBeforeUnload.ggufContextLength ?? 0) : maxSeqLength,
+            previousIsGguf
+              ? (stateBeforeUnload.ggufContextLength ?? 0)
+              : previousMaxSeqLength,
           );
           const hfToken = stateBeforeUnload.hfToken || null;
           const previousModelRequiresTrustRemoteCode =
             stateBeforeUnload.modelRequiresTrustRemoteCode;
+          const previousActiveNativePathExpiresAtMs =
+            stateBeforeUnload.activeNativePathExpiresAtMs;
           // Snapshot the load settings at click time, before the awaits below
-          // (validation, the trust dialog, unload). For a staged Load these knobs
-          // stay editable and a sheet-close revert (abandonStagedModel) can fire
-          // mid-load; reading them live just before loadModel would let the load
-          // use post-click values. The model-switch speculative reset below
-          // updates this snapshot in lock-step so non-staged loads are unchanged.
+          // (validation, the trust dialog, unload).
           const loadChatTemplateOverride = stateBeforeUnload.chatTemplateOverride;
           const loadKvCacheDtype = stateBeforeUnload.kvCacheDtype;
           // gpuMemoryMode is a standing preference (kept across a model switch);
@@ -657,14 +681,11 @@ export function useChatModelRuntime() {
             // context can exceed maxSeqLength, so sizing on raw maxSeqLength could
             // pass, unload, then have /load refuse it. Uses the click-time
             // snapshot (same values loadModel uses below), so the two agree.
-            // Mirror what /load does on a cross-model switch: the reset below
-            // clears the per-model Auto-layers context pin + GPU pick, and
-            // Manual+Auto sizes context through resolveFitMaxSeqLength.
-            // gpuMemoryMode is a standing preference, kept across the switch.
-            // A same-repo quant switch (same checkpoint, different gguf_variant)
-            // is a different model for per-model knobs: the pinned context,
-            // gpuLayers, GPU pick, and MoE offload are scoped per variant, so
-            // treat a variant change like a model switch and re-baseline them.
+            // Mirror /load on a cross-model switch: the reset below clears the
+            // per-model Auto-layers context pin + GPU pick; gpuMemoryMode is a
+            // standing preference kept across the switch. A same-repo quant switch
+            // (different gguf_variant) is a different model for per-model knobs
+            // (context/gpuLayers/pick/MoE are per variant), so re-baseline them too.
             const switchingModelOrVariant =
               currentCheckpoint !== modelId ||
               (loadActiveGgufVariant ?? null) !== (ggufVariant ?? null);
@@ -867,7 +888,11 @@ export function useChatModelRuntime() {
             // The load applied this spec mode, so persist the user's standing
             // preference now (the requested intent, not the resolved echo;
             // saveSpeculativeType keeps only the universal auto/ngram/off).
-            saveSpeculativeType(loadSpeculativeType);
+            // Skip for a per-model config (keepSpeculative): that choice is
+            // model-specific and must not overwrite the global default.
+            if (!keepSpeculative) {
+              saveSpeculativeType(loadSpeculativeType);
+            }
             // Persist the GPU Memory mode only on a successful load (not on
             // dropdown change), so an abandoned selection doesn't stick.
             persistGpuMemoryModeOnLoad(loadResponse, loadGpuMemoryMode);
@@ -907,7 +932,9 @@ export function useChatModelRuntime() {
               ? (loadResponse.native_context_length ?? null)
               : null;
             // Keep an explicit Manual+Auto context pin (so a later Apply doesn't
-            // revert it to Auto); other cases baseline on ggufContextLength.
+            // revert it to Auto) and retain the user's requested context so
+            // re-open/re-save keeps the intended override, not the backend's
+            // auto-fit context; null stays null.
             const keepCustomCtx = resolveManualAutoCtxPin(
               loadGpuMemoryMode,
               loadGpuLayers,
@@ -978,6 +1005,9 @@ export function useChatModelRuntime() {
               loadedIsMultimodal: isMultimodalResponse(loadResponse),
               loadedIsDiffusion: loadResponse.is_diffusion ?? false,
               activeNativePathToken: nativePathToken ?? null,
+              activeNativePathExpiresAtMs: nativePathToken
+                ? nativePathExpiresAtMs
+                : null,
             });
             // Unlock attach menus for capabilities the catalog entry lacked.
             syncModelCapabilities(modelId, loadResponse);
@@ -1031,25 +1061,6 @@ export function useChatModelRuntime() {
                 recordLastLocalModelLoad({ id: modelId, kind: "model" });
               }
             }
-            // A successful load owns the shared (pick-unscoped) settings fields,
-            // so any surviving stage is stale: the just-loaded pick itself, or a
-            // pick queued for a different model mid-load whose knobs this load
-            // overwrote. Drop it. Only a DIFFERENT pick's download needs
-            // cancelling; the loaded pick's is already consumed, and cancelling
-            // it inside its post-complete linger window would flicker its card.
-            const staleStage = useChatRuntimeStore.getState().pendingSelection;
-            if (staleStage) {
-              if (
-                !pendingSelectionMatches(staleStage, {
-                  id: modelId,
-                  ggufVariant,
-                  nativePathToken,
-                })
-              ) {
-                cancelStagedModelDownload(staleStage);
-              }
-              useChatRuntimeStore.getState().setPendingSelection(null);
-            }
           } catch (error) {
             // Skip rollback if user cancelled -- model is already being unloaded.
             if (abortCtrl.signal.aborted) throw error;
@@ -1091,8 +1102,9 @@ export function useChatModelRuntime() {
                   // Restore the previous model in the split mode it was running,
                   // not the default layer split.
                   tensor_parallel: stateBeforeUnload.loadedTensorParallel ?? false,
+                  // Restore the previous model's GPU Memory placement, not backend defaults.
                   gpu_memory_mode: stateBeforeUnload.loadedGpuMemoryMode ?? "auto",
-                  gpu_layers: stateBeforeUnload.loadedGpuLayers ?? -1,
+                  gpu_layers: stateBeforeUnload.loadedGpuLayers ?? GPU_LAYERS_AUTO,
                   n_cpu_moe: stateBeforeUnload.loadedNCpuMoe ?? 0,
                   tensor_split: stateBeforeUnload.loadedSplitRatio ?? undefined,
                   gpu_ids: stateBeforeUnload.loadedGpuIds ?? undefined,
@@ -1102,28 +1114,27 @@ export function useChatModelRuntime() {
                 );
                 useChatRuntimeStore.setState({
                   activeNativePathToken: previousActiveNativePathToken ?? null,
+                  // Restore the previous token's lease together with the token so a
+                  // rollback never pairs restored token A with failed load B's expiry.
+                  activeNativePathExpiresAtMs: previousActiveNativePathToken
+                    ? (previousActiveNativePathExpiresAtMs ?? null)
+                    : null,
+                  // Restore the editable speculative knobs to the rolled-back
+                  // model's; the loaded baselines below come from its reload echo.
+                  speculativeType: stateBeforeUnload.loadedSpeculativeType ?? null,
+                  specDraftNMax: stateBeforeUnload.loadedSpecDraftNMax ?? null,
                   loadedSpeculativeType: rollbackSpeculativeType,
                   loadedSpecDraftNMax:
                     rollbackResponse.spec_draft_n_max ?? null,
                   loadedKvCacheDtype: rollbackResponse.cache_type_kv ?? null,
                   loadedChatTemplateOverride:
                     stateBeforeUnload.loadedChatTemplateOverride,
-                  // Re-baseline the GPU knobs from the rolled-back load's own
-                  // response (the shared seeding every load path uses): the
-                  // refresh() below can't do it, since the status reseed is
-                  // gated off while modelLoading is still true. A failed staged
-                  // Load stays staged for retry, so the staged hold applies.
-                  ...loadedGpuMemoryFieldsUnlessStaged(rollbackResponse, {
-                    tensorParallel: rollbackResponse.tensor_parallel ?? false,
-                    loadedTensorParallel:
-                      rollbackResponse.tensor_parallel ?? false,
-                    // refresh() is held while modelLoading remains true, so
-                    // restore the rolled-back model's context pin directly.
-                    customContextLength:
-                      stateBeforeUnload.loadedCustomContextLength,
-                  }),
+                  ...loadedGpuMemoryFields(rollbackResponse),
+                  tensorParallel: rollbackResponse.tensor_parallel ?? false,
                   loadedTensorParallel:
                     rollbackResponse.tensor_parallel ?? false,
+                  customContextLength:
+                    stateBeforeUnload.loadedCustomContextLength,
                   loadedCustomContextLength:
                     stateBeforeUnload.loadedCustomContextLength,
                 });
@@ -1444,6 +1455,9 @@ export function useChatModelRuntime() {
           resetLoadingUi();
         }
       } catch (error) {
+        if (typeof selection !== "string" && selection.previousConfig) {
+          applyPerModelConfigToRuntime(selection.previousConfig);
+        }
         if (abortCtrl.signal.aborted) return; // User cancelled, nothing to report
         resetLoadingUi();
         const message =
@@ -1474,6 +1488,13 @@ export function useChatModelRuntime() {
     if (!params.checkpoint) {
       return false;
     }
+    const runtime = useChatRuntimeStore.getState();
+    if (runtime.modelLoading || runtime.loadingModelPick) {
+      toast.info("A model is loading", {
+        description: "Wait for it to finish or cancel it first.",
+      });
+      return false;
+    }
     setModelsError(null);
     if (isExternalModelId(params.checkpoint)) {
       clearCheckpoint();
diff --git a/studio/frontend/src/features/chat/hooks/use-chat-projects.ts b/studio/frontend/src/features/chat/hooks/use-chat-projects.ts
index 3f0d46982d..86f540654d 100644
--- a/studio/frontend/src/features/chat/hooks/use-chat-projects.ts
+++ b/studio/frontend/src/features/chat/hooks/use-chat-projects.ts
@@ -1,8 +1,8 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { useEffect, useState } from "react";
-import { CHAT_HISTORY_UPDATED_EVENT } from "../api/chat-api";
+import { useEffect, useState, useSyncExternalStore } from "react";
+import { CHAT_PROJECTS_UPDATED_EVENT } from "../api/chat-api";
 import type { ProjectRecord } from "../types";
 import {
   createStoredChatProject,
@@ -15,32 +15,83 @@ import {
 import type { SidebarItem } from "./use-chat-sidebar-items";
 
 let cachedProjects: ProjectRecord[] = [];
+let projectsLoaded = false;
+let projectsRequest: Promise<ProjectRecord[]> | null = null;
+let projectsRefreshPending = false;
+let lastProjectsUpdateEvent: Event | null = null;
+const projectSubscribers = new Set<() => void>();
+
+function subscribeToProjects(onStoreChange: () => void): () => void {
+  projectSubscribers.add(onStoreChange);
+  return () => projectSubscribers.delete(onStoreChange);
+}
+
+function getProjectsSnapshot(): ProjectRecord[] {
+  return cachedProjects;
+}
+
+function publishProjects(projects: ProjectRecord[]): void {
+  cachedProjects = projects;
+  projectsLoaded = true;
+  for (const onStoreChange of projectSubscribers) onStoreChange();
+}
+
+function loadProjects(
+  force = false,
+  followUpIfPending = false,
+): Promise<ProjectRecord[]> {
+  if (projectsRequest) {
+    if (followUpIfPending) projectsRefreshPending = true;
+    return projectsRequest;
+  }
+  if (!force && projectsLoaded) {
+    return Promise.resolve(cachedProjects);
+  }
+
+  async function run(): Promise<ProjectRecord[]> {
+    let nextProjects: ProjectRecord[] | null = null;
+    do {
+      projectsRefreshPending = false;
+      try {
+        const next = await listStoredChatProjects({ includeArchived: false });
+        nextProjects = Array.isArray(next) ? next : [];
+      } catch (error) {
+        if (!isExpectedBackgroundChatStorageError(error)) throw error;
+        nextProjects = null;
+      }
+    } while (projectsRefreshPending);
+    if (nextProjects !== null) publishProjects(nextProjects);
+    return cachedProjects;
+  }
+
+  const request = run().finally(() => {
+    projectsRequest = null;
+  });
+  projectsRequest = request;
+  return request;
+}
 
 export function useChatProjects(): {
   projects: ProjectRecord[];
   isLoading: boolean;
   hasLoaded: boolean;
 } {
-  // Stay null-safe even if the cache was poisoned by a bad response.
-  const cached = Array.isArray(cachedProjects) ? cachedProjects : [];
-  const [projects, setProjects] = useState<ProjectRecord[]>(cached);
-  const [isLoading, setIsLoading] = useState(cached.length === 0);
-  const [hasLoaded, setHasLoaded] = useState(cached.length > 0);
+  const projects = useSyncExternalStore(
+    subscribeToProjects,
+    getProjectsSnapshot,
+    getProjectsSnapshot,
+  );
+  const [isLoading, setIsLoading] = useState(!projectsLoaded);
+  const [hasLoaded, setHasLoaded] = useState(projectsLoaded);
 
   useEffect(() => {
     let cancelled = false;
 
-    async function load() {
-      if (!cancelled) setIsLoading(true);
+    async function refresh(force = false, followUpIfPending = false) {
+      if (!force && projectsLoaded) return;
+      if (!cancelled && !projectsLoaded) setIsLoading(true);
       try {
-        const next = await listStoredChatProjects({ includeArchived: false });
-        cachedProjects = Array.isArray(next) ? next : [];
-        if (!cancelled) setProjects(cachedProjects);
-      } catch (error) {
-        if (isExpectedBackgroundChatStorageError(error)) {
-          return;
-        }
-        if (!cancelled) throw error;
+        await loadProjects(force, followUpIfPending);
       } finally {
         if (!cancelled) {
           setHasLoaded(true);
@@ -49,15 +100,18 @@ export function useChatProjects(): {
       }
     }
 
-    const onHistoryUpdated = () => {
-      void load();
+    const onProjectsUpdated = (event: Event) => {
+      const followUpIfPending = event !== lastProjectsUpdateEvent;
+      lastProjectsUpdateEvent = event;
+      void refresh(true, followUpIfPending);
     };
-
-    void load();
-    window.addEventListener(CHAT_HISTORY_UPDATED_EVENT, onHistoryUpdated);
+    // Cached rows render immediately, then one shared request reconciles
+    // changes made by another browser tab or API client.
+    void refresh(projectsLoaded);
+    window.addEventListener(CHAT_PROJECTS_UPDATED_EVENT, onProjectsUpdated);
     return () => {
       cancelled = true;
-      window.removeEventListener(CHAT_HISTORY_UPDATED_EVENT, onHistoryUpdated);
+      window.removeEventListener(CHAT_PROJECTS_UPDATED_EVENT, onProjectsUpdated);
     };
   }, []);
 
diff --git a/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts b/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
deleted file mode 100644
index a3e7a2d264..0000000000
--- a/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
+++ /dev/null
@@ -1,169 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { useCallback, useEffect } from "react";
-
-import { useRepoDownload } from "@/features/hub/download-manager/use-repo-download";
-import type { DownloadJob } from "@/features/hub/download-manager/use-repo-download";
-import { useLatestRef } from "@/features/hub/hooks/use-latest-ref";
-
-import { fetchGgufStagedMetadata } from "../api/chat-api";
-import {
-  isPendingGguf,
-  pendingSelectionMatches,
-  useChatRuntimeStore,
-} from "../stores/chat-runtime-store";
-import type { PendingModelSelection } from "../stores/chat-runtime-store";
-
-/**
- * Drives the deferred ("Load on selection" off) staging flow for a GGUF:
- * download the file if needed (HF repo) or read it in place (native drag-drop /
- * picked file), then read its header context length so the settings sheet can
- * show the real context slider before the single GPU load. The staged context
- * lands on `pendingSelection.contextLength` (scoped to the staged model, never
- * the loaded model's `ggufContextLength`). Returns the live download job so the
- * sheet can render progress / cancel. Mount once on the chat page.
- */
-export function useStagedModelPreparation(opts?: {
-  /** Load the cached file once an autoLoad pick's download completes. */
-  onAutoLoad?: (pending: PendingModelSelection) => void;
-}): DownloadJob {
-  const pendingId = useChatRuntimeStore((s) => s.pendingSelection?.id ?? null);
-  const pendingVariant = useChatRuntimeStore(
-    (s) => s.pendingSelection?.ggufVariant ?? null,
-  );
-  const pendingNativeToken = useChatRuntimeStore(
-    (s) => s.pendingSelection?.nativePathToken ?? null,
-  );
-  // Only GGUF picks (HF variant or native file) have a header worth reading.
-  const pendingIsGguf = useChatRuntimeStore((s) =>
-    isPendingGguf(s.pendingSelection),
-  );
-  // Non-GGUF HF repos download a full snapshot (variant null) but have no header.
-  const pendingIsHubRepo = useChatRuntimeStore(
-    (s) => s.pendingSelection?.isHubRepo ?? false,
-  );
-  const pendingDownloaded = useChatRuntimeStore(
-    (s) => s.pendingSelection?.isDownloaded ?? false,
-  );
-  // "Already probed" must key off layerCount / moeLayerCount, which only the
-  // full header probe fills (it sets all three together, so either is a
-  // reliable marker). contextLength alone can be list-seeded from
-  // /gguf-variants, which returns no layer/MoE counts -- treating it as
-  // complete would skip the probe and leave the GPU Layers slider at its 256
-  // fallback and the MoE slider hidden until the model loads.
-  const pendingHasMetadata = useChatRuntimeStore(
-    (s) =>
-      s.pendingSelection?.layerCount != null ||
-      s.pendingSelection?.moeLayerCount != null,
-  );
-  const setPendingSelection = useChatRuntimeStore((s) => s.setPendingSelection);
-  const onAutoLoadRef = useLatestRef(opts?.onAutoLoad);
-
-  // A failed or cancelled autoLoad download has no sheet to retry from, so drop
-  // the staged pick rather than leave it waiting on a load that won't come.
-  const handleAutoLoadAbort = useCallback((variant: string | null) => {
-    const latest = useChatRuntimeStore.getState().pendingSelection;
-    if (
-      latest?.autoLoad &&
-      (latest.ggufVariant ?? null) === (variant ?? null)
-    ) {
-      useChatRuntimeStore.getState().abandonStagedModel();
-    }
-  }, []);
-
-  const fetchContextMetadata = useCallback(async () => {
-    const current = useChatRuntimeStore.getState().pendingSelection;
-    if (!current?.id || !isPendingGguf(current)) return;
-    const { id, ggufVariant, nativePathToken } = current;
-    try {
-      const { contextLength, layerCount, moeLayerCount } =
-        await fetchGgufStagedMetadata({
-          model_path: id,
-          gguf_variant: ggufVariant,
-          hf_token: useChatRuntimeStore.getState().hfToken || null,
-          nativePathToken,
-        });
-      // Apply only if the same model is still staged (the user may have switched
-      // picks or loaded/cancelled while the request was in flight).
-      const latest = useChatRuntimeStore.getState().pendingSelection;
-      if (
-        latest &&
-        pendingSelectionMatches(latest, { id, ggufVariant, nativePathToken }) &&
-        (contextLength != null || layerCount != null || moeLayerCount != null)
-      ) {
-        setPendingSelection({
-          ...latest,
-          contextLength,
-          layerCount,
-          moeLayerCount,
-        });
-      }
-    } catch {
-      // Leave metadata null: the context/MoE sliders stay hidden and the user
-      // can still load (they fill in from the load response afterwards).
-    }
-  }, [setPendingSelection]);
-
-  const job = useRepoDownload({
-    kind: "model",
-    // useRepoDownload must be called unconditionally; an idle repo id keeps it
-    // inert until something is staged.
-    repoId: pendingId ?? "__staged_idle__",
-    activeVariant: pendingVariant,
-    onComplete: (variant) => {
-      // autoLoad picks load the cached file now; staged picks read the header so
-      // the sheet's context slider can show before a manual load.
-      const latest = useChatRuntimeStore.getState().pendingSelection;
-      if (
-        latest?.autoLoad &&
-        (latest.ggufVariant ?? null) === (variant ?? null)
-      ) {
-        onAutoLoadRef.current?.(latest);
-        return;
-      }
-      void fetchContextMetadata();
-    },
-    onError: handleAutoLoadAbort,
-    onCancelled: handleAutoLoadAbort,
-  });
-
-  // job.requestStartDownload's identity changes per render; hold it in a ref so
-  // the staging effect re-runs only when the staged model itself changes.
-  const startDownloadRef = useLatestRef(job.requestStartDownload);
-  const fetchMetadataRef = useLatestRef(fetchContextMetadata);
-
-  useEffect(() => {
-    // GGUF picks (header worth reading) and uncached non-GGUF hub repos (full
-    // snapshot, no header) both run here; everything else is loaded directly.
-    if (
-      !pendingId ||
-      (!pendingIsGguf && !pendingIsHubRepo) ||
-      pendingHasMetadata
-    ) {
-      return;
-    }
-    // Native files and already-downloaded HF files are local: read the header
-    // now. Otherwise download first (a GGUF variant, or a null-variant snapshot
-    // for a hub repo); onComplete then reads the header or auto-loads.
-    if (pendingNativeToken || pendingDownloaded) {
-      void fetchMetadataRef.current();
-    } else {
-      const expectedBytes =
-        useChatRuntimeStore.getState().pendingSelection?.expectedBytes ?? 0;
-      void startDownloadRef.current(pendingVariant, expectedBytes);
-    }
-  }, [
-    pendingId,
-    pendingVariant,
-    pendingNativeToken,
-    pendingIsGguf,
-    pendingIsHubRepo,
-    pendingDownloaded,
-    pendingHasMetadata,
-    startDownloadRef,
-    fetchMetadataRef,
-  ]);
-
-  return job;
-}
diff --git a/studio/frontend/src/features/chat/index.ts b/studio/frontend/src/features/chat/index.ts
index b0059b57b1..785212a2c4 100644
--- a/studio/frontend/src/features/chat/index.ts
+++ b/studio/frontend/src/features/chat/index.ts
@@ -3,20 +3,35 @@
 
 export { ChatPage, validateChatSearch, type ChatSearch } from "./chat-page";
 export {
+  addScanFolder,
+  browseFolders,
   deleteChatAttachment,
+  deleteFineTunedModel,
   fetchChatAttachmentBlob,
+  fetchGgufStagedMetadata,
+  getCachedModelPath,
   getInferenceStatus,
   listChatAttachments,
   listGgufVariants,
   listLocalModels,
+  listRecommendedFolders,
+  listScanFolders,
   loadModel,
+  notifyChatHistoryUpdated,
+  removeScanFolder,
+  revealCachedModel,
+  type BrowseFoldersResponse,
+  type CachedGgufRepo,
+  type CachedModelRepo,
   type ChatAttachmentPage,
   type ChatAttachmentRecord,
   type LocalModelInfo,
+  type ScanFolderInfo,
 } from "./api/chat-api";
 export type { GgufVariantDetail } from "./types/api";
 export {
   ChatSettingsPanel,
+  ParamSlider,
   defaultInferenceParams,
   type InferenceParams,
   type Preset,
@@ -25,6 +40,11 @@ export { useChatRuntimeStore } from "./stores/chat-runtime-store";
 export {
   CHAT_RAG_CAPTION_KEY,
   CHAT_RAG_OCR_KEY,
+  normalizeSpeculativeType,
+  readPersistedSpeculativeType,
+  readPersistedGpuMemoryMode,
+  reconcilePersistedGpuIds,
+  GPU_LAYERS_AUTO,
 } from "./stores/chat-runtime-store";
 export {
   preferFullToolOutput,
@@ -34,6 +54,7 @@ export {
 export { PermissionModeDropdown } from "./permission-mode-select";
 export { useChatSearchStore } from "./stores/chat-search-store";
 export { usePinnedChatsStore } from "./stores/pinned-chats-store";
+export { usePinnedProjectsStore } from "./stores/pinned-projects-store";
 export { useChatPreferencesStore } from "./stores/chat-preferences-store";
 export {
   PLUS_MENU_ORDER,
@@ -46,9 +67,11 @@ export {
 } from "./hooks/use-chat-model-runtime";
 export {
   customProviderDisplayName,
+  isCustomProviderType,
   isExternalModelId,
   parseExternalModelId,
 } from "./external-providers";
+export { ApiProviderLogo } from "./api-provider-logo";
 export { useExternalProvidersStore } from "./stores/external-providers-store";
 export { ChatSearchDialog } from "./components/chat-search-dialog";
 export { setTrainingCompareHandoff } from "./lib/training-compare-handoff";
@@ -62,8 +85,8 @@ export {
   useSelectedChatArtifact,
 } from "./artifacts/store";
 export {
-  downloadChatExport,
   downloadArchivedChatExport,
+  downloadChatExport,
 } from "./utils/export-chat-history";
 export {
   clearNewChatDraft,
@@ -96,3 +119,25 @@ export {
   updateChatProjectInstructions,
   useChatProjects,
 } from "./hooks/use-chat-projects";
+export { subscribeDictationLevel } from "./adapters/dictation-level";
+export {
+  StudioDictationAdapter,
+  cancelActiveStudioDictation,
+  isStudioDictationAvailable,
+  notifyStudioDictationUnavailable,
+} from "./adapters/studio-dictation-adapter";
+export {
+  StudioModelDictationAdapter,
+  fetchSttStatus,
+  loadSttModel,
+  startSttDownload,
+  unloadSttModel,
+  validateSttModel,
+  type SttDownloadStatus,
+} from "./adapters/studio-model-dictation-adapter";
+export {
+  StudioSpeechSynthesisAdapter,
+  createConfiguredUtterance,
+  curateSystemVoices,
+  generateStudioTtsAudio,
+} from "./adapters/studio-speech-synthesis-adapter";
diff --git a/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts b/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
index 69bb38bbbe..547c3f374e 100644
--- a/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
+++ b/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
@@ -280,12 +280,9 @@ export function applyActiveModelStatusToStore(
     ggufContextLength: currentGgufContextLength,
     ggufMaxContextLength,
     ggufNativeContextLength,
-    // A non-GGUF status must also drop a stale native-path token: without this the
-    // isGguf OR (activeGgufVariant || activeNativePathToken || ggufContextLength)
-    // stays true after switching from a native GGUF to a transformers model, so a
-    // Codex-only detection would auto-select for a model its preflight rejects. A real
-    // GGUF load reports is_gguf: true, so its token is preserved (the load path owns it).
-    ...(status.is_gguf ? {} : { activeNativePathToken: null }),
+    ...(status.is_gguf
+      ? {}
+      : { activeNativePathToken: null, activeNativePathExpiresAtMs: null }),
     modelRequiresTrustRemoteCode: status.requires_trust_remote_code ?? false,
     defaultChatTemplate: nextDefaultChatTemplate,
     loadedIsMultimodal: isMultimodalResponse(status),
@@ -299,13 +296,11 @@ export function applyActiveModelStatusToStore(
     // model changed underneath this tab (auto-switch, another client), the
     // old model's baselines are stale and must adopt the new status.
     ...(seedLoadParams &&
-      prevState.pendingSelection == null &&
       (prevState.loadedSpeculativeType === null || hydratingExistingModel) && {
         speculativeType: currentSpecType,
         loadedSpeculativeType: currentSpecType,
       }),
     ...(seedLoadParams &&
-      prevState.pendingSelection == null &&
       status.spec_draft_n_max !== undefined &&
       (hydratingExistingModel ||
         (prevState.loadedSpecDraftNMax === null &&
@@ -314,14 +309,12 @@ export function applyActiveModelStatusToStore(
         loadedSpecDraftNMax: status.spec_draft_n_max ?? null,
       }),
     ...(seedLoadParams &&
-      prevState.pendingSelection == null &&
       status.cache_type_kv !== undefined &&
       (prevState.loadedKvCacheDtype === null || hydratingExistingModel) && {
         kvCacheDtype: status.cache_type_kv,
         loadedKvCacheDtype: status.cache_type_kv,
       }),
     ...(seedLoadParams &&
-      prevState.pendingSelection == null &&
       status.tensor_parallel !== undefined &&
       (prevState.loadedTensorParallel === null || hydratingExistingModel) && {
         tensorParallel: status.tensor_parallel,
@@ -331,7 +324,6 @@ export function applyActiveModelStatusToStore(
     // placement change. gpuStatusFields preserves dirty local edits in the last
     // case while advancing their loaded baselines.
     ...(seedLoadParams &&
-      prevState.pendingSelection == null &&
       (prevState.loadedGpuMemoryMode === null ||
         hydratingExistingModel ||
         gpuStatusChanged) &&
diff --git a/studio/frontend/src/features/chat/permission-mode-select.tsx b/studio/frontend/src/features/chat/permission-mode-select.tsx
index e6c89cf54a..f3e1594795 100644
--- a/studio/frontend/src/features/chat/permission-mode-select.tsx
+++ b/studio/frontend/src/features/chat/permission-mode-select.tsx
@@ -120,7 +120,7 @@ export function PermissionModeMenuItems({
         >
           <option.icon className="mt-0.5 size-4 shrink-0" strokeWidth={2} />
           <span className="flex min-w-0 flex-1 flex-col gap-0.5">
-            <span className="text-[13px] leading-tight">{option.label}</span>
+            <span className="text-ui-13 leading-tight">{option.label}</span>
             <span className="text-xs font-normal leading-snug text-muted-foreground">
               {option.description}
             </span>
diff --git a/studio/frontend/src/features/chat/projects-page.tsx b/studio/frontend/src/features/chat/projects-page.tsx
index 5e0b37895b..e20e517787 100644
--- a/studio/frontend/src/features/chat/projects-page.tsx
+++ b/studio/frontend/src/features/chat/projects-page.tsx
@@ -30,6 +30,8 @@ import {
   SelectTrigger,
   SelectValue,
 } from "@/components/ui/select";
+import { isTauri } from "@/lib/api-base";
+import { isDownloadCancelled, pickNativeChatImport } from "@/lib/native-files";
 import { toast } from "@/lib/toast";
 import {
   createChatProject,
@@ -37,6 +39,7 @@ import {
   renameChatProject,
   useChatProjects,
   useChatRuntimeStore,
+  usePinnedProjectsStore,
   type ProjectRecord,
 } from "@/features/chat";
 import {
@@ -45,13 +48,15 @@ import {
   Edit03Icon,
   Folder02Icon,
   FolderAddIcon,
+  PinIcon,
+  PinOffIcon,
   Search01Icon,
   Upload01Icon,
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { MoreHorizontalIcon } from "lucide-react";
 import { useNavigate } from "@tanstack/react-router";
-import { useMemo, useRef, useState } from "react";
+import { useEffect, useMemo, useRef, useState } from "react";
 import {
   exportProjectConversations,
   exportBulkConversationsMerged,
@@ -66,21 +71,38 @@ import {
 
 type SortMode = "activity" | "name";
 
-function formatUpdatedAgo(ts: number): string {
-  const diff = Date.now() - ts;
-  if (!Number.isFinite(diff) || diff < 0) return "just now";
-  const s = Math.floor(diff / 1000);
-  if (s < 60) return "just now";
-  const m = Math.floor(s / 60);
-  if (m < 60) return `${m} minute${m === 1 ? "" : "s"} ago`;
-  const h = Math.floor(m / 60);
-  if (h < 24) return `${h} hour${h === 1 ? "" : "s"} ago`;
-  const d = Math.floor(h / 24);
-  if (d < 30) return `${d} day${d === 1 ? "" : "s"} ago`;
-  const mo = Math.floor(d / 30);
-  if (mo < 12) return `${mo} month${mo === 1 ? "" : "s"} ago`;
-  const y = Math.floor(mo / 12);
-  return `${y} year${y === 1 ? "" : "s"} ago`;
+// Reveal this many more projects each time the user scrolls near the bottom.
+const PROJECTS_PAGE_STEP = 12;
+// Visible count before the fit-to-height measurement runs.
+const PROJECTS_INITIAL_FALLBACK = 8;
+// Approx list row height in px, used to estimate how many rows fit the page.
+const PROJECTS_ROW_HEIGHT = 68;
+
+// Modified column, matching a file-list feel: Today / Yesterday / N days ago,
+// then a short date once it is over a week old.
+function formatModified(ts: number): string {
+  if (!Number.isFinite(ts)) return "";
+  const now = new Date();
+  const then = new Date(ts);
+  const startOfToday = new Date(
+    now.getFullYear(),
+    now.getMonth(),
+    now.getDate(),
+  ).getTime();
+  const startOfThen = new Date(
+    then.getFullYear(),
+    then.getMonth(),
+    then.getDate(),
+  ).getTime();
+  const dayDiff = Math.round((startOfToday - startOfThen) / 86_400_000);
+  if (dayDiff <= 0) return "Today";
+  if (dayDiff === 1) return "Yesterday";
+  if (dayDiff < 7) return `${dayDiff} days ago`;
+  return then.toLocaleDateString(undefined, {
+    month: "short",
+    day: "numeric",
+    year: then.getFullYear() === now.getFullYear() ? undefined : "numeric",
+  });
 }
 
 export function ProjectsPage() {
@@ -89,6 +111,17 @@ export function ProjectsPage() {
 
   const [query, setQuery] = useState("");
   const [sortMode, setSortMode] = useState<SortMode>("activity");
+  // Rows that fit the page height (measured), plus any revealed via Show more.
+  const [baseFit, setBaseFit] = useState(PROJECTS_INITIAL_FALLBACK);
+  const [extraCount, setExtraCount] = useState(0);
+  const listRef = useRef<HTMLDivElement>(null);
+  const sentinelRef = useRef<HTMLDivElement>(null);
+  const pinnedProjectIds = usePinnedProjectsStore((s) => s.pinnedIds);
+  const togglePinProject = usePinnedProjectsStore((s) => s.togglePin);
+  const pinnedProjectIdSet = useMemo(
+    () => new Set(pinnedProjectIds),
+    [pinnedProjectIds],
+  );
 
   const [creating, setCreating] = useState(false);
   const [nameDraft, setNameDraft] = useState("");
@@ -118,6 +151,40 @@ export function ProjectsPage() {
     }
   }
 
+
+  async function selectGlobalImportFile() {
+    if (!isTauri) {
+      globalImportRef.current?.click();
+      return;
+    }
+    try {
+      const selected = await pickNativeChatImport();
+      if (!selected) return;
+      setImportTargetId(projects[0]?.id ?? null);
+      setImportFile(new File([selected.content], selected.name));
+    } catch (error) {
+      toast.error("Import failed.", {
+        description: error instanceof Error ? error.message : String(error),
+      });
+    }
+  }
+
+  async function selectProjectImportFile(projectId: string) {
+    if (!isTauri) {
+      projectImportRefs.current.get(projectId)?.click();
+      return;
+    }
+    try {
+      const selected = await pickNativeChatImport();
+      if (!selected) return;
+      await handleImport(new File([selected.content], selected.name), projectId);
+    } catch (error) {
+      toast.error("Import failed.", {
+        description: error instanceof Error ? error.message : String(error),
+      });
+    }
+  }
+
   async function commitImport() {
     if (!importFile) return;
     const file = importFile;
@@ -126,7 +193,7 @@ export function ProjectsPage() {
     await handleImport(file, target);
   }
 
-  const visibleProjects = useMemo(() => {
+  const sortedProjects = useMemo(() => {
     const trimmed = query.trim().toLowerCase();
     const filtered = trimmed
       ? projects.filter((p) => p.name.toLowerCase().includes(trimmed))
@@ -138,6 +205,51 @@ export function ProjectsPage() {
     );
     return filtered;
   }, [projects, query, sortMode]);
+  // Default view shows as many rows as fit the page, then loads more as the
+  // user scrolls near the bottom. Search always spans every project.
+  const isSearching = query.trim() !== "";
+  const visibleCount = baseFit + extraCount;
+  const visibleProjects = isSearching
+    ? sortedProjects
+    : sortedProjects.slice(0, visibleCount);
+  const hasMore = !isSearching && sortedProjects.length > visibleCount;
+
+  // Estimate how many rows fit below the list's top so the first page fills the
+  // screen without loading everything up front.
+  useEffect(() => {
+    function measure() {
+      const el = listRef.current;
+      if (!el) return;
+      const top = el.getBoundingClientRect().top;
+      const reserve = 24; // bottom breathing room
+      const fits = Math.floor(
+        (window.innerHeight - top - reserve) / PROJECTS_ROW_HEIGHT,
+      );
+      setBaseFit(Math.max(PROJECTS_PAGE_STEP, fits));
+    }
+    measure();
+    window.addEventListener("resize", measure);
+    return () => window.removeEventListener("resize", measure);
+  }, [hasLoaded]);
+
+  // Infinite scroll: reveal another page-step whenever the sentinel near the
+  // list bottom scrolls into view.
+  useEffect(() => {
+    const el = sentinelRef.current;
+    if (!el || !hasMore) return;
+    const io = new IntersectionObserver(
+      (entries) => {
+        if (entries[0]?.isIntersecting) {
+          setExtraCount((n) => n + PROJECTS_PAGE_STEP);
+        }
+      },
+      { rootMargin: "300px" },
+    );
+    io.observe(el);
+    return () => io.disconnect();
+    // Re-observe after each load so it keeps filling while the sentinel stays
+    // in view (IntersectionObserver does not re-fire on a steady intersection).
+  }, [hasMore, visibleCount]);
 
   function openProject(projectId: string) {
     const runtime = useChatRuntimeStore.getState();
@@ -183,8 +295,10 @@ export function ProjectsPage() {
       const threads = await listStoredChatThreads({ projectId: project.id, includeArchived: false });
       const ids = [...new Set(threads.map((t) => t.id))];
       await exportProjectConversations(ids, fmt, project.name);
-    } catch {
-      toast.error("Export failed.");
+    } catch (error) {
+      if (!isDownloadCancelled(error)) {
+        toast.error("Export failed.");
+      }
     }
   }
 
@@ -215,8 +329,10 @@ export function ProjectsPage() {
       } else {
         await exportBulkConversationsSeparate(ids, fmt, basename);
       }
-    } catch {
-      toast.error("Export failed.");
+    } catch (error) {
+      if (!isDownloadCancelled(error)) {
+        toast.error("Export failed.");
+      }
     }
   }
 
@@ -234,7 +350,7 @@ export function ProjectsPage() {
   }
 
   return (
-    <main className="mx-auto w-full max-w-6xl px-6 py-10 font-heading sm:px-10">
+    <main className="mx-auto w-full max-w-5xl px-6 pb-10 pt-16 font-heading sm:px-10">
       {/* Global import file input */}
       <input
         ref={globalImportRef}
@@ -251,7 +367,7 @@ export function ProjectsPage() {
         }}
       />
       <div className="flex flex-wrap items-center justify-between gap-4">
-        <h1 className="text-[30px] font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-[34px]">
+        <h1 className="text-ui-30 font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-ui-34">
           Projects
         </h1>
         <div className="flex items-center gap-3">
@@ -294,7 +410,7 @@ export function ProjectsPage() {
               </Button>
             </DropdownMenuTrigger>
             <DropdownMenuContent align="end" className="w-56">
-              <DropdownMenuItem onSelect={() => globalImportRef.current?.click()}>
+              <DropdownMenuItem onSelect={() => void selectGlobalImportFile()}>
                 <HugeiconsIcon icon={Upload01Icon} strokeWidth={1.75} className="size-icon" />
                 Import chats…
               </DropdownMenuItem>
@@ -303,7 +419,7 @@ export function ProjectsPage() {
                 <DropdownMenuSubTrigger>Export All Projects</DropdownMenuSubTrigger>
                 <DropdownMenuSubContent className="w-52">
                   <DropdownMenuGroup>
-                    <DropdownMenuLabel className="pb-1 pt-2 text-[11px] font-medium">
+                    <DropdownMenuLabel className="pb-1 pt-2 text-ui-11 font-medium">
                       Combined
                     </DropdownMenuLabel>
                     {EXPORT_FORMATS_LIST.map(({ fmt, label }) => (
@@ -314,7 +430,7 @@ export function ProjectsPage() {
                   </DropdownMenuGroup>
                   <DropdownMenuSeparator />
                   <DropdownMenuGroup>
-                    <DropdownMenuLabel className="pb-1 pt-2 text-[11px] font-medium">
+                    <DropdownMenuLabel className="pb-1 pt-2 text-ui-11 font-medium">
                       Per chat
                     </DropdownMenuLabel>
                     {EXPORT_FORMATS_LIST.map(({ fmt, label }) => (
@@ -329,7 +445,7 @@ export function ProjectsPage() {
                 <DropdownMenuSubTrigger>Export Projects + Recents</DropdownMenuSubTrigger>
                 <DropdownMenuSubContent className="w-52">
                   <DropdownMenuGroup>
-                    <DropdownMenuLabel className="pb-1 pt-2 text-[11px] font-medium">
+                    <DropdownMenuLabel className="pb-1 pt-2 text-ui-11 font-medium">
                       Combined
                     </DropdownMenuLabel>
                     {EXPORT_FORMATS_LIST.map(({ fmt, label }) => (
@@ -340,7 +456,7 @@ export function ProjectsPage() {
                   </DropdownMenuGroup>
                   <DropdownMenuSeparator />
                   <DropdownMenuGroup>
-                    <DropdownMenuLabel className="pb-1 pt-2 text-[11px] font-medium">
+                    <DropdownMenuLabel className="pb-1 pt-2 text-ui-11 font-medium">
                       Per chat
                     </DropdownMenuLabel>
                     {EXPORT_FORMATS_LIST.map(({ fmt, label }) => (
@@ -365,16 +481,22 @@ export function ProjectsPage() {
       </div>
 
       {!hasLoaded ? (
-        <div className="mt-12 grid grid-cols-1 gap-5 sm:grid-cols-2 lg:grid-cols-3">
+        <div className="mt-16">
+          <div className="mb-1 flex items-center gap-3 px-5 pb-1 text-ui-13 font-medium text-muted-foreground">
+            <span className="flex-1">Name</span>
+            <span className="w-40 shrink-0">Modified</span>
+            <span className="w-8 shrink-0" />
+          </div>
           {Array.from({ length: 6 }).map((_, index) => (
             <div
               key={index}
-              className="min-h-[172px] rounded-[26px] bg-card p-6 shadow-[0_2px_12px_-4px_rgba(0,0,0,0.10)] dark:shadow-none"
+              className="flex items-center gap-3 rounded-xl px-5 py-4"
             >
-              <Skeleton className="size-10 rounded-[14px]" />
-              <Skeleton className="mt-4 h-5 w-2/3 rounded-[8px]" />
-              <Skeleton className="mt-2 h-4 w-4/5 rounded-[8px]" />
-              <Skeleton className="mt-8 h-3 w-24 rounded-[8px]" />
+              <Skeleton className="mr-1 size-9 shrink-0 rounded-[10px]" />
+              <Skeleton className="h-4 w-40 rounded-[8px]" />
+              <span className="flex-1" />
+              <Skeleton className="h-4 w-16 rounded-[8px]" />
+              <span className="w-8 shrink-0" />
             </div>
           ))}
         </div>
@@ -400,9 +522,20 @@ export function ProjectsPage() {
           )}
         </div>
       ) : (
-        <div className="mt-12 grid grid-cols-1 gap-5 sm:grid-cols-2 lg:grid-cols-3">
-          {visibleProjects.map((project) => (
-            <div key={`wrap-${project.id}`} className="contents">
+        <>
+        <div className="mt-16">
+          {/* Column header. Name starts at the folder icon's left edge; the
+              right-anchored columns keep Modified over its values. */}
+          <div className="mb-1 flex items-center gap-3 px-5 pb-1 text-ui-13 font-medium text-muted-foreground">
+            <span className="flex-1">Name</span>
+            <span className="w-40 shrink-0">Modified</span>
+            <span className="w-8 shrink-0" />
+          </div>
+          <div ref={listRef}>
+          {visibleProjects.map((project) => {
+            const pinned = pinnedProjectIdSet.has(project.id);
+            return (
+            <div key={`wrap-${project.id}`}>
             <input
               key={`import-${project.id}`}
               type="file"
@@ -429,23 +562,37 @@ export function ProjectsPage() {
                   openProject(project.id);
                 }
               }}
-              className="group/project-card relative flex min-h-[172px] cursor-pointer flex-col rounded-[26px] bg-card p-6 text-left shadow-[0_2px_12px_-4px_rgba(0,0,0,0.10)] transition-colors duration-150 hover:bg-[#f2f2f2] dark:shadow-none dark:hover:bg-accent/30 focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
+              className="group/project-row relative flex cursor-pointer items-center gap-3 rounded-xl px-5 py-4 text-left transition-colors duration-150 hover:bg-muted/70 dark:hover:bg-white/[0.055] focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
             >
-              <div className="flex items-start justify-between gap-2">
-                <span className="flex size-10 shrink-0 items-center justify-center rounded-[14px] bg-muted text-foreground/70 transition-colors group-hover/project-card:bg-primary/10 group-hover/project-card:text-primary">
-                  <HugeiconsIcon
-                    icon={Folder02Icon}
-                    strokeWidth={1.75}
-                    className="size-5"
-                  />
-                </span>
+              <span className="mr-1 flex size-9 shrink-0 items-center justify-center rounded-[10px] bg-muted text-foreground/70 transition-colors group-hover/project-row:bg-primary/10 group-hover/project-row:text-primary">
+                <HugeiconsIcon
+                  icon={Folder02Icon}
+                  strokeWidth={1.75}
+                  className="size-5"
+                />
+              </span>
+              <span className="min-w-0 flex-1 truncate text-ui-15 font-semibold text-foreground">
+                {project.name}
+              </span>
+              <span className="w-40 shrink-0 text-sm text-muted-foreground">
+                {formatModified(project.updatedAt)}
+              </span>
+              <div className="relative flex w-8 shrink-0 items-center justify-end">
+                {/* Pin fades out and the kebab fades in on hover, focus, or
+                    menu open. Absolute + opacity gating keeps them from
+                    overlapping while leaving the button keyboard-focusable. */}
+                {pinned && (
+                  <span className="text-muted-foreground transition-opacity group-hover/project-row:opacity-0 group-focus-within/project-row:opacity-0 group-has-[[data-state=open]]/project-row:opacity-0">
+                    <HugeiconsIcon icon={PinIcon} strokeWidth={1.75} className="size-4" />
+                  </span>
+                )}
                 <DropdownMenu>
                   <DropdownMenuTrigger asChild>
                     <button
                       type="button"
                       onClick={(e) => e.stopPropagation()}
                       aria-label="Project options"
-                      className="-mr-1 -mt-1 inline-flex size-7 shrink-0 items-center justify-center rounded-full text-muted-foreground opacity-0 transition-opacity hover:bg-black/5 hover:text-foreground dark:hover:bg-white/10 focus-visible:opacity-100 group-hover/project-card:opacity-100 data-[state=open]:bg-black/5 data-[state=open]:opacity-100 dark:data-[state=open]:bg-white/10"
+                      className="absolute right-0 flex size-7 shrink-0 items-center justify-center rounded-full text-muted-foreground opacity-0 transition hover:bg-black/5 hover:text-foreground focus-visible:opacity-100 group-hover/project-row:opacity-100 data-[state=open]:bg-black/5 data-[state=open]:opacity-100 dark:hover:bg-white/10 dark:data-[state=open]:bg-white/10"
                     >
                       <MoreHorizontalIcon strokeWidth={1.75} className="size-icon" />
                     </button>
@@ -458,6 +605,16 @@ export function ProjectsPage() {
                     onKeyDown={(e) => e.stopPropagation()}
                     className="app-user-menu menu-soft-surface menu-flat-destructive ring-0 w-44 py-2 font-heading rounded-[14px] border-0"
                   >
+                    <DropdownMenuItem
+                      onSelect={() => togglePinProject(project.id)}
+                    >
+                      <HugeiconsIcon
+                        icon={pinned ? PinOffIcon : PinIcon}
+                        strokeWidth={1.75}
+                        className="size-icon"
+                      />
+                      <span>{pinned ? "Unpin project" : "Pin project"}</span>
+                    </DropdownMenuItem>
                     <DropdownMenuItem
                       onSelect={() => {
                         setRenameDraft(project.name);
@@ -470,7 +627,7 @@ export function ProjectsPage() {
                     <DropdownMenuItem
                       onSelect={(e) => {
                         e.stopPropagation();
-                        projectImportRefs.current.get(project.id)?.click();
+                        void selectProjectImportFile(project.id);
                       }}
                     >
                       <HugeiconsIcon icon={Upload01Icon} strokeWidth={1.75} className="size-icon" />
@@ -506,21 +663,15 @@ export function ProjectsPage() {
                   </DropdownMenuContent>
                 </DropdownMenu>
               </div>
-              <h2 className="mt-4 truncate text-[16px] font-semibold text-foreground">
-                {project.name}
-              </h2>
-              {project.instructions ? (
-                <p className="mt-1.5 line-clamp-2 text-sm leading-relaxed text-muted-foreground">
-                  {project.instructions}
-                </p>
-              ) : null}
-              <span className="mt-auto pt-4 text-xs text-muted-foreground/80">
-                Updated {formatUpdatedAgo(project.updatedAt)}
-              </span>
             </div>
             </div>
-          ))}
+            );
+          })}
+          {/* Loads the next page-step when scrolled into view. */}
+          {hasMore && <div ref={sentinelRef} className="h-px w-full" />}
+          </div>
         </div>
+        </>
       )}
 
       {/* Create project */}
@@ -644,8 +795,8 @@ export function ProjectsPage() {
             <DialogTitle>Delete project</DialogTitle>
           </DialogHeader>
           <p className="text-sm text-muted-foreground">
-            Are you sure you want to delete <em>{deleting?.name}</em>? Chats in this
-            project will be moved back to Recents.
+            Are you sure you want to delete <em>{deleting?.name}</em>? Its chats will
+            be permanently deleted.
           </p>
           <DialogFooter className="flex-wrap gap-2 sm:justify-end">
             <Button type="button" variant="ghost" onClick={() => setDeleting(null)}>
diff --git a/studio/frontend/src/features/chat/prompt-storage/prompt-storage-dialog.tsx b/studio/frontend/src/features/chat/prompt-storage/prompt-storage-dialog.tsx
index 68f24a7b08..7295605553 100644
--- a/studio/frontend/src/features/chat/prompt-storage/prompt-storage-dialog.tsx
+++ b/studio/frontend/src/features/chat/prompt-storage/prompt-storage-dialog.tsx
@@ -10,6 +10,8 @@ import {
   DialogHeader,
   DialogTitle,
 } from "@/components/ui/dialog";
+import { downloadFile, isDownloadCancelled } from "@/lib/native-files";
+
 import { cn } from "@/lib/utils";
 import { Search01Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
@@ -70,77 +72,73 @@ function sanitizeFilename(name: string): string {
   return name.replace(/[\\/:*?"<>|]/g, "_").slice(0, 80) || "export";
 }
 
-function downloadBlob(content: string | Blob, filename: string, mimeType: string): void {
-  const blob = content instanceof Blob ? content : new Blob([content], { type: mimeType });
-  const url = URL.createObjectURL(blob);
-  const a = document.createElement("a");
-  a.href = url;
-  a.download = filename;
-  document.body.appendChild(a);
-  a.click();
-  document.body.removeChild(a);
-  URL.revokeObjectURL(url);
+async function downloadBlob(
+  content: string | Blob | Uint8Array,
+  filename: string,
+  mimeType: string,
+): Promise<void> {
+  return downloadFile(content, filename, mimeType);
 }
 
 function csvEscape(val: string): string {
   return `"${val.replace(/"/g, '""')}"`;
 }
 
-function exportPromptJsonl(entry: PromptEntry): void {
-  downloadBlob(
+function exportPromptJsonl(entry: PromptEntry): Promise<void> {
+  return downloadBlob(
     JSON.stringify({ name: entry.name, text: entry.text }),
     `${sanitizeFilename(entry.name)}.jsonl`,
     "application/x-ndjson",
   );
 }
 
-function exportPromptCsv(entry: PromptEntry): void {
-  downloadBlob(
+function exportPromptCsv(entry: PromptEntry): Promise<void> {
+  return downloadBlob(
     `name,text\n${csvEscape(entry.name)},${csvEscape(entry.text)}`,
     `${sanitizeFilename(entry.name)}.csv`,
     "text/csv",
   );
 }
 
-function exportAllPromptsJsonl(entries: PromptEntry[]): void {
+function exportAllPromptsJsonl(entries: PromptEntry[]): Promise<void> {
   const lines = entries.map((e) => JSON.stringify({ name: e.name, text: e.text })).join("\n");
-  downloadBlob(lines, "prompts.jsonl", "application/x-ndjson");
+  return downloadBlob(lines, "prompts.jsonl", "application/x-ndjson");
 }
 
-function exportAllPromptsCsv(entries: PromptEntry[]): void {
+function exportAllPromptsCsv(entries: PromptEntry[]): Promise<void> {
   const rows = entries.map((e) => `${csvEscape(e.name)},${csvEscape(e.text)}`).join("\n");
-  downloadBlob(`name,text\n${rows}`, "prompts.csv", "text/csv");
+  return downloadBlob(`name,text\n${rows}`, "prompts.csv", "text/csv");
 }
 
-function exportListJsonl(entry: PromptListEntry): void {
-  downloadBlob(
+function exportListJsonl(entry: PromptListEntry): Promise<void> {
+  return downloadBlob(
     JSON.stringify({ name: entry.name, items: entry.items }),
     `${sanitizeFilename(entry.name)}.jsonl`,
     "application/x-ndjson",
   );
 }
 
-function exportAllListsJsonl(entries: PromptListEntry[]): void {
+function exportAllListsJsonl(entries: PromptListEntry[]): Promise<void> {
   const lines = entries.map((e) => JSON.stringify({ name: e.name, items: e.items })).join("\n");
-  downloadBlob(lines, "prompt-lists.jsonl", "application/x-ndjson");
+  return downloadBlob(lines, "prompt-lists.jsonl", "application/x-ndjson");
 }
 
-function exportListCsv(entry: PromptListEntry): void {
+function exportListCsv(entry: PromptListEntry): Promise<void> {
   const rows = entry.items
     .map((text, i) => `${csvEscape(entry.name)},${i + 1},${csvEscape(text)}`)
     .join("\n");
-  downloadBlob(
+  return downloadBlob(
     `list_name,order,prompt_text\n${rows}`,
     `${sanitizeFilename(entry.name)}.csv`,
     "text/csv",
   );
 }
 
-function exportAllListsCsv(entries: PromptListEntry[]): void {
+function exportAllListsCsv(entries: PromptListEntry[]): Promise<void> {
   const rows = entries
     .flatMap((e) => e.items.map((text, i) => `${csvEscape(e.name)},${i + 1},${csvEscape(text)}`))
     .join("\n");
-  downloadBlob(`list_name,order,prompt_text\n${rows}`, "prompt-lists.csv", "text/csv");
+  return downloadBlob(`list_name,order,prompt_text\n${rows}`, "prompt-lists.csv", "text/csv");
 }
 
 function contentBlocksToText(content: unknown): string {
@@ -363,7 +361,7 @@ export async function exportConversationShareGPT(threadId: string): Promise<void
   }
 
   if (conversations.length === 0) { toast.info("No exportable content."); return; }
-  downloadBlob(
+  await downloadBlob(
     JSON.stringify({ conversations }),
     "conversation-" + exportTs() + ".jsonl",
     "application/x-ndjson",
@@ -378,7 +376,7 @@ export async function exportConversationRawJsonl(threadId: string): Promise<void
 
   const oaiMsgs: OAIMessage[] = messages.flatMap((msg) => messageToOpenAI(msg));
   if (oaiMsgs.length === 0) { toast.info("No exportable content."); return; }
-  downloadBlob(
+  await downloadBlob(
     JSON.stringify({ messages: oaiMsgs }),
     "conversation-" + exportTs() + ".jsonl",
     "application/x-ndjson",
@@ -397,7 +395,11 @@ export async function exportConversationCsv(threadId: string): Promise<void> {
   }
 
   if (rows.length <= 1) { toast.info("No exportable content."); return; }
-  downloadBlob(rows.join("\n"), "conversation-" + exportTs() + ".csv", "text/csv");
+  await downloadBlob(
+    rows.join("\n"),
+    "conversation-" + exportTs() + ".csv",
+    "text/csv",
+  );
 }
 
 export type ConvExportFormat = "jsonl-raw" | "csv" | "sharegpt";
@@ -479,7 +481,11 @@ export async function exportBulkConversationsMerged(
     ? header + "\n" + parts.join("\n")
     : parts.join("\n");
 
-  downloadBlob(body, `${basename}.${exportExt(format)}`, exportMime(format));
+  await downloadBlob(
+    body,
+    `${basename}.${exportExt(format)}`,
+    exportMime(format),
+  );
 }
 
 export async function exportBulkConversationsSeparate(
@@ -504,11 +510,7 @@ export async function exportBulkConversationsSeparate(
   if (Object.keys(files).length === 0) { toast.info("No exportable content."); return; }
 
   const zipped = zipSync(files);
-  downloadBlob(
-    new Blob([zipped], { type: "application/zip" }),
-    `${basename}.zip`,
-    "application/zip",
-  );
+  await downloadBlob(zipped, `${basename}.zip`, "application/zip");
 }
 
 // Scope-level bulk export shared by the sidebar Recents menu and
@@ -536,8 +538,10 @@ export async function bulkExportConversationsByScope(
     } else {
       await exportBulkConversationsSeparate(ids, format, basename);
     }
-  } catch {
-    toast.error("Export failed.");
+  } catch (error) {
+    if (!isDownloadCancelled(error)) {
+      toast.error("Export failed.");
+    }
   }
 }
 
@@ -749,7 +753,7 @@ export async function exportFineTuneJsonl(
     return 0;
   }
   const suffix = format === "openai" ? "" : `-${format}`;
-  downloadBlob(
+  await downloadBlob(
     lines.join("\n"),
     `chat-finetune${suffix}-${exportTs()}.jsonl`,
     "application/x-ndjson",
@@ -992,21 +996,21 @@ export async function importConversationsFromFile(
 
 // ShareGPT training exports: prompt → one record (human turn + empty gpt slot);
 // list → one multi-turn record, each item a human turn.
-function exportPromptTrainingJsonl(entry: PromptEntry): void {
+function exportPromptTrainingJsonl(entry: PromptEntry): Promise<void> {
   const record = {
     conversations: [
       { from: "human", value: entry.text },
       { from: "gpt", value: "" },
     ],
   };
-  downloadBlob(
+  return downloadBlob(
     JSON.stringify(record),
     `${sanitizeFilename(entry.name)}-training.jsonl`,
     "application/x-ndjson",
   );
 }
 
-function exportPromptsTrainingJsonl(entries: PromptEntry[]): void {
+function exportPromptsTrainingJsonl(entries: PromptEntry[]): Promise<void> {
   const lines = entries
     .map((e) =>
       JSON.stringify({
@@ -1017,22 +1021,22 @@ function exportPromptsTrainingJsonl(entries: PromptEntry[]): void {
       }),
     )
     .join("\n");
-  downloadBlob(lines, "prompts-training.jsonl", "application/x-ndjson");
+  return downloadBlob(lines, "prompts-training.jsonl", "application/x-ndjson");
 }
 
-function exportListTrainingJsonl(entry: PromptListEntry): void {
+function exportListTrainingJsonl(entry: PromptListEntry): Promise<void> {
   const conversations = entry.items.flatMap((text) => [
     { from: "human", value: text },
     { from: "gpt", value: "" },
   ]);
-  downloadBlob(
+  return downloadBlob(
     JSON.stringify({ conversations }),
     `${sanitizeFilename(entry.name)}-training.jsonl`,
     "application/x-ndjson",
   );
 }
 
-function exportListsTrainingJsonl(entries: PromptListEntry[]): void {
+function exportListsTrainingJsonl(entries: PromptListEntry[]): Promise<void> {
   const lines = entries
     .map((e) => {
       const conversations = e.items.flatMap((text) => [
@@ -1042,7 +1046,7 @@ function exportListsTrainingJsonl(entries: PromptListEntry[]): void {
       return JSON.stringify({ conversations });
     })
     .join("\n");
-  downloadBlob(lines, "prompt-lists-training.jsonl", "application/x-ndjson");
+  return downloadBlob(lines, "prompt-lists-training.jsonl", "application/x-ndjson");
 }
 
 // RFC 4180 CSV parser: handles quoted fields with embedded newlines/commas.
@@ -1268,38 +1272,44 @@ function ExportModal({
     if (!csvAvailable) setFormat("jsonl");
   }, [csvAvailable]);
 
-  const handleExport = useCallback(() => {
-    if (ctx.kind === "prompt") {
-      if (scope === "training") exportPromptTrainingJsonl(ctx.entry);
-      else if (format === "csv") exportPromptCsv(ctx.entry);
-      else exportPromptJsonl(ctx.entry);
-    } else if (ctx.kind === "list") {
-      if (scope === "training") exportListTrainingJsonl(ctx.entry);
-      else if (format === "csv") exportListCsv(ctx.entry);
-      else exportListJsonl(ctx.entry);
-    } else {
-      const { tab, prompts, lists } = ctx;
-      if (scope === "training") {
-        if (tab === "prompts") {
-          if (prompts.length === 0) { toast.info("No prompts to export"); return; }
-          exportPromptsTrainingJsonl(prompts);
-        } else {
-          if (lists.length === 0) { toast.info("No prompt lists to export"); return; }
-          exportListsTrainingJsonl(lists);
-        }
+  const handleExport = useCallback(async () => {
+    try {
+      if (ctx.kind === "prompt") {
+        if (scope === "training") await exportPromptTrainingJsonl(ctx.entry);
+        else if (format === "csv") await exportPromptCsv(ctx.entry);
+        else await exportPromptJsonl(ctx.entry);
+      } else if (ctx.kind === "list") {
+        if (scope === "training") await exportListTrainingJsonl(ctx.entry);
+        else if (format === "csv") await exportListCsv(ctx.entry);
+        else await exportListJsonl(ctx.entry);
       } else {
-        if (tab === "prompts") {
+        const { tab, prompts, lists } = ctx;
+        if (scope === "training") {
+          if (tab === "prompts") {
+            if (prompts.length === 0) { toast.info("No prompts to export"); return; }
+            await exportPromptsTrainingJsonl(prompts);
+          } else {
+            if (lists.length === 0) { toast.info("No prompt lists to export"); return; }
+            await exportListsTrainingJsonl(lists);
+          }
+        } else if (tab === "prompts") {
           if (prompts.length === 0) { toast.info("No prompts to export"); return; }
-          if (format === "csv") exportAllPromptsCsv(prompts);
-          else exportAllPromptsJsonl(prompts);
+          if (format === "csv") await exportAllPromptsCsv(prompts);
+          else await exportAllPromptsJsonl(prompts);
         } else {
           if (lists.length === 0) { toast.info("No prompt lists to export"); return; }
-          if (format === "csv") exportAllListsCsv(lists);
-          else exportAllListsJsonl(lists);
+          if (format === "csv") await exportAllListsCsv(lists);
+          else await exportAllListsJsonl(lists);
         }
       }
+      onClose();
+    } catch (error) {
+      if (!isDownloadCancelled(error)) {
+        toast.error("Could not save export.", {
+          description: error instanceof Error ? error.message : String(error),
+        });
+      }
     }
-    onClose();
   }, [ctx, scope, format, onClose]);
 
   const singleLabel =
@@ -1331,7 +1341,7 @@ function ExportModal({
 
           {/* */}
           <div className="flex flex-col gap-2">
-            <p className="text-[11px] font-semibold uppercase tracking-wider text-muted-foreground/60">
+            <p className="text-ui-11 font-semibold uppercase tracking-wider text-muted-foreground/60">
               Export as
             </p>
             <div className="flex flex-col gap-2">
@@ -1380,7 +1390,7 @@ function ExportModal({
                   <p className="mt-1 text-xs text-muted-foreground">
                     ShareGPT format for Unsloth fine-tuning
                   </p>
-                  <code className="mt-2 block w-full truncate rounded-md bg-muted px-2 py-1 font-mono text-[10px] text-muted-foreground/60">
+                  <code className="mt-2 block w-full truncate rounded-md bg-muted px-2 py-1 font-mono text-ui-10 text-muted-foreground/60">
                     {`{"conversations":[{"from":"human","value":"..."},{"from":"gpt","value":""}]}`}
                   </code>
                 </div>
@@ -1390,7 +1400,7 @@ function ExportModal({
 
           {/* */}
           <div className="flex flex-col gap-2">
-            <p className="text-[11px] font-semibold uppercase tracking-wider text-muted-foreground/60">
+            <p className="text-ui-11 font-semibold uppercase tracking-wider text-muted-foreground/60">
               Format
             </p>
             <div className="flex items-center gap-1 self-start rounded-lg bg-muted/60 p-1">
@@ -1720,7 +1730,7 @@ function PromptListCard({
     <div className="group rounded-xl border border-border/60 bg-card p-4 flex flex-col gap-2.5 hover:border-border hover:shadow-sm transition-all">
       <div className="flex items-center gap-2">
         <span className="font-semibold text-sm flex-1 truncate tracking-tight">{entry.name}</span>
-        <span className="shrink-0 rounded-full bg-muted px-2 py-0.5 text-[11px] font-medium text-muted-foreground">
+        <span className="shrink-0 rounded-full bg-muted px-2 py-0.5 text-ui-11 font-medium text-muted-foreground">
           {entry.items.length}
         </span>
         <div className="flex items-center gap-0.5 opacity-0 group-hover:opacity-100 transition-opacity">
@@ -1769,7 +1779,7 @@ function PromptListCard({
           </p>
         ))}
         {entry.items.length > 3 && (
-          <p className="text-[11px] text-muted-foreground/50 ml-5">
+          <p className="text-ui-11 text-muted-foreground/50 ml-5">
             +{entry.items.length - 3} more
           </p>
         )}
diff --git a/studio/frontend/src/features/chat/runtime-provider.tsx b/studio/frontend/src/features/chat/runtime-provider.tsx
index 4a8740ac9b..d9e407fd5e 100644
--- a/studio/frontend/src/features/chat/runtime-provider.tsx
+++ b/studio/frontend/src/features/chat/runtime-provider.tsx
@@ -33,8 +33,8 @@ import {
   useRef,
 } from "react";
 import { toast } from "sonner";
+import { StudioDictationAdapter } from "./adapters/studio-dictation-adapter";
 import { StudioSpeechSynthesisAdapter } from "./adapters/studio-speech-synthesis-adapter";
-import { StudioWebSpeechDictationAdapter } from "./adapters/studio-web-speech-dictation-adapter";
 import {
   ThreadAutosaveHandle,
   createOpenAIStreamAdapter,
@@ -1195,13 +1195,10 @@ function useStudioRuntimeAdapters(
     [aui, modelType, pairId],
   );
 
-  const dictation = useMemo(
-    () =>
-      StudioWebSpeechDictationAdapter.isSupported()
-        ? new StudioWebSpeechDictationAdapter()
-        : undefined,
-    [],
-  );
+  // Always register the adapter so the mic stays clickable for any engine. The
+  // engine is resolved at listen() time and the composer shows guidance when it
+  // cannot run, so engine switches also work on an already-mounted thread.
+  const dictation = useMemo(() => new StudioDictationAdapter(), []);
   const speech = useMemo(
     () =>
       StudioSpeechSynthesisAdapter.isSupported()
diff --git a/studio/frontend/src/features/chat/shared-composer.tsx b/studio/frontend/src/features/chat/shared-composer.tsx
index 461eef99b2..3f89f70ef1 100644
--- a/studio/frontend/src/features/chat/shared-composer.tsx
+++ b/studio/frontend/src/features/chat/shared-composer.tsx
@@ -24,18 +24,15 @@ import {
 } from "@/components/ui/dropdown-menu";
 import { applyQwenThinkingParams } from "@/features/chat/utils/qwen-params";
 import {
-  describeMediaError,
-  describeSpeechError,
-  isMissingDeviceError,
-} from "@/features/chat/adapters/studio-web-speech-dictation-adapter";
-import {
-  applyDictationDictionary,
-  recordRecentDictation,
-  resolveDictationLanguage,
-  useVoiceSettingsStore,
-} from "@/features/settings/stores/voice-settings-store";
+  StudioDictationAdapter,
+  isStudioDictationAvailable,
+  notifyStudioDictationUnavailable,
+} from "@/features/chat/adapters/studio-dictation-adapter";
+import type { StudioDictationSession } from "@/features/chat/adapters/studio-web-speech-dictation-adapter";
+import { useVoiceSettingsStore } from "@/features/settings/stores/voice-settings-store";
 import { AUDIO_ACCEPT, MAX_AUDIO_SIZE, fileToBase64 } from "@/lib/audio-utils";
 import { isTauri } from "@/lib/api-base";
+import { isDownloadCancelled } from "@/lib/native-files";
 import { isMultimodalResponse } from "./types/api";
 import { getImageInputUnavailableReason } from "./utils/image-input-support";
 import { useAui } from "@assistant-ui/react";
@@ -79,6 +76,12 @@ import { KnowledgeBaseComposerButton } from "@/features/rag/components/knowledge
 import { NewProjectDialog } from "./components/new-project-dialog";
 import { useChatProjects } from "./hooks/use-chat-projects";
 import { confirmRemoteCodeIfNeeded } from "@/features/security";
+import {
+  DEFAULT_MAX_SEQ_LENGTH,
+  normalizeMaxSeqLength,
+  resolveInitialConfig,
+  type PerModelConfig,
+} from "@/features/model-picker";
 import {
   confirmTransformersUpgradeIfNeeded,
   useTransformersUpgradeDialogStore,
@@ -91,13 +94,14 @@ import {
   providerTypeSupportsVision,
 } from "./external-providers";
 import { useExternalProvidersStore } from "./stores/external-providers-store";
+import { useIsMobile } from "@/hooks/use-mobile";
 import {
   PLUS_MENU_ORDER,
   type PlusMenuItemId,
   usePlusMenuPrefsStore,
 } from "./stores/plus-menu-prefs-store";
 import {
-  loadedGpuMemoryFieldsUnlessStaged,
+  loadedGpuMemoryFields,
   type ReasoningEffort,
   reconcilePersistedGpuIds,
   resolveLoadedSpeculativeSettings,
@@ -216,173 +220,95 @@ function formatReasoningDisabledLabel(
 function useDictation(
   setText: (value: string | ((prev: string) => string)) => void,
 ) {
+  // Re-render support state when the user switches recognition engines.
+  const dictationEngine = useVoiceSettingsStore((s) => s.dictationEngine);
   const [isDictating, setIsDictating] = useState(false);
-  const recognitionRef = useRef<SpeechRecognition | null>(null);
-
-  const streamRef = useRef<MediaStream | null>(null);
+  // True while a stopped recording's final audio is still transcribing; a
+  // second click then cancels the pending transcription instead of re-stopping.
+  const [isFinalizing, setIsFinalizing] = useState(false);
+  const sessionRef = useRef<StudioDictationSession | null>(null);
   const startingRef = useRef(false);
-  // Guards the getUserMedia await so a mic opened after unmount is released.
-  const disposedRef = useRef(false);
-
-  const releaseStream = useCallback(() => {
-    streamRef.current?.getTracks().forEach((track) => track.stop());
-    streamRef.current = null;
-  }, []);
+  const finalizingRef = useRef(false);
 
   const start = useCallback(async () => {
-    const SpeechRecognitionAPI =
-      typeof window !== "undefined" &&
-      (window.SpeechRecognition ??
-        (
-          window as unknown as {
-            webkitSpeechRecognition?: typeof SpeechRecognition;
-          }
-        ).webkitSpeechRecognition);
-    if (!SpeechRecognitionAPI) {
+    if (startingRef.current || sessionRef.current) return;
+    // Unsupported engine (e.g. Firefox): explain and steer to the local model.
+    if (!isStudioDictationAvailable()) {
+      notifyStudioDictationUnavailable();
       return;
     }
-    if (startingRef.current || recognitionRef.current) return;
     startingRef.current = true;
 
-    // Open the microphone chosen in Voice settings, matching the main chat
-    // adapter, so Compare dictation honors the same device selection.
-    let audioTrack: MediaStreamTrack | undefined;
-    const { micDeviceId } = useVoiceSettingsStore.getState();
-    if (navigator.mediaDevices?.getUserMedia) {
-      try {
-        let stream: MediaStream;
-        try {
-          stream = await navigator.mediaDevices.getUserMedia({
-            audio:
-              micDeviceId && micDeviceId !== "default"
-                ? { deviceId: { exact: micDeviceId } }
-                : true,
-          });
-        } catch (error) {
-          // Saved mic may be unplugged; fall back to the default device.
-          if (micDeviceId !== "default" && isMissingDeviceError(error)) {
-            stream = await navigator.mediaDevices.getUserMedia({
-              audio: true,
-            });
-          } else {
-            throw error;
-          }
-        }
-        streamRef.current = stream;
-        audioTrack = stream.getAudioTracks()[0];
-      } catch (error) {
-        // Permission/security failure: report it and stop instead of silently
-        // recording from a different default device, matching the main adapter.
-        startingRef.current = false;
-        releaseStream();
-        setIsDictating(false);
-        toast.error(describeMediaError(error));
-        return;
-      }
-    }
-
-    if (disposedRef.current) {
-      releaseStream();
-      startingRef.current = false;
-      return;
-    }
-
-    const recognition = new SpeechRecognitionAPI() as SpeechRecognition;
-    recognition.continuous = true;
-    recognition.interimResults = true;
-    recognition.lang = resolveDictationLanguage();
-    let sessionTranscript = "";
-    recognition.onresult = (event: SpeechRecognitionEvent) => {
-      // Iterate every result from resultIndex; a single event can carry more
-      // than one finalized phrase and dropping the rest loses dictated words.
-      for (let i = event.resultIndex; i < event.results.length; i++) {
-        const result = event.results[i];
-        if (!result?.isFinal) continue;
-        const transcript = applyDictationDictionary(
-          result[0]?.transcript?.trim() ?? "",
-        );
-        if (!transcript) continue;
-        sessionTranscript = sessionTranscript
-          ? `${sessionTranscript} ${transcript}`
-          : transcript;
-        setText((prev) => (prev ? `${prev} ${transcript}` : transcript));
-      }
-    };
-    recognition.onerror = (event) => {
-      // Report speech-service failures like the main adapter; aborted is a
-      // normal stop, not an error.
-      const errorEvent = event as SpeechRecognitionErrorEvent;
-      if (errorEvent.error !== "aborted") {
-        toast.error(describeSpeechError(errorEvent.error, errorEvent.message));
-      }
-      setIsDictating(false);
-    };
-    recognition.onend = () => {
-      // A stop()+immediate restart can install a new recognizer before this
-      // old one ends; only tear down shared refs when we are still current.
-      if (recognitionRef.current === recognition) {
-        releaseStream();
-        recognitionRef.current = null;
-        setIsDictating(false);
-      }
-      if (sessionTranscript) {
-        recordRecentDictation(sessionTranscript);
-        sessionTranscript = "";
-      }
-    };
+    let session: StudioDictationSession;
     try {
-      if (audioTrack) {
-        try {
-          recognition.start(audioTrack);
-        } catch {
-          // No start(track) overload: recognition captures from the default
-          // device, so release the selected-device stream.
-          releaseStream();
-          recognition.start();
-        }
-      } else {
-        recognition.start();
-      }
+      // Routes to the engine chosen in Voice settings (browser or STT model),
+      // honoring the selected microphone, language, and dictionary. Compare
+      // feeds two panes, so recent dictations must not link the unrelated
+      // single-chat active thread.
+      session = new StudioDictationAdapter({ chatId: null }).listen();
     } catch {
       startingRef.current = false;
-      releaseStream();
+      notifyStudioDictationUnavailable();
       return;
     }
-    recognitionRef.current = recognition;
-    startingRef.current = false;
+    sessionRef.current = session;
     setIsDictating(true);
-  }, [setText, releaseStream]);
+
+    // Append final transcripts; the adapter has already applied the dictionary
+    // and records the session in Recent dictations.
+    session.onSpeech((result) => {
+      if (!result.isFinal) return;
+      const transcript = result.transcript?.trim() ?? "";
+      if (transcript) {
+        setText((prev) => (prev ? `${prev} ${transcript}` : transcript));
+      }
+    });
+    session.onEnd?.(() => {
+      if (sessionRef.current === session) sessionRef.current = null;
+      finalizingRef.current = false;
+      setIsFinalizing(false);
+      setIsDictating(false);
+    });
+    startingRef.current = false;
+  }, [setText]);
 
   const stop = useCallback(() => {
-    if (recognitionRef.current) {
-      recognitionRef.current.stop();
-      recognitionRef.current = null;
+    const session = sessionRef.current;
+    if (!session) return;
+    // A second click while the final segment is transcribing discards the
+    // pending transcription instead of leaving the pane stuck until timeout.
+    if (finalizingRef.current) {
+      session.cancel();
+      if (sessionRef.current === session) sessionRef.current = null;
+      finalizingRef.current = false;
+      setIsFinalizing(false);
+      setIsDictating(false);
+      return;
     }
-    releaseStream();
-    setIsDictating(false);
-  }, [releaseStream]);
+    finalizingRef.current = true;
+    setIsFinalizing(true);
+    // Keep the session and dictation state alive while its final audio segment
+    // is transcribed. onEnd clears both after the transcript callbacks run.
+    void session.stop().catch((error) => {
+      console.error("Could not stop dictation:", error);
+      session.cancel();
+      if (sessionRef.current === session) sessionRef.current = null;
+      finalizingRef.current = false;
+      setIsFinalizing(false);
+      setIsDictating(false);
+    });
+  }, []);
 
   useEffect(() => {
-    disposedRef.current = false;
     return () => {
-      disposedRef.current = true;
-      if (recognitionRef.current) {
-        recognitionRef.current.abort();
-      }
-      streamRef.current?.getTracks().forEach((track) => track.stop());
-      streamRef.current = null;
+      sessionRef.current?.cancel();
+      sessionRef.current = null;
     };
   }, []);
 
-  const supported =
-    typeof window !== "undefined" &&
-    !!(
-      window.SpeechRecognition ??
-      (window as unknown as { webkitSpeechRecognition?: unknown })
-        .webkitSpeechRecognition
-    );
+  const supported = StudioDictationAdapter.isSupported(dictationEngine);
 
-  return { isDictating, start, stop, supported };
+  return { isDictating, isFinalizing, start, stop, supported };
 }
 
 export type CompareHandles = MutableRefObject<Record<string, CompareHandle>>;
@@ -495,8 +421,24 @@ type CompareModelSelection = {
   id: string;
   isLora: boolean;
   ggufVariant?: string;
+  config?: PerModelConfig;
 };
 
+function cleanCompareChatTemplate(
+  value: string | null | undefined,
+): string | null {
+  return value?.trim() ? value : null;
+}
+
+function resolveCompareSpecDraftNMax(
+  speculativeType: string | null,
+  value: number | null,
+): number | null {
+  return speculativeType === "mtp" || speculativeType === "mtp+ngram"
+    ? value
+    : null;
+}
+
 // Tool icon plus an X overlay CSS reveals on hover when the pill is active.
 function PillGlyph({ children }: { children: ReactNode }) {
   return (
@@ -790,15 +732,17 @@ export function SharedComposer({
   const ragDisabled = modelLoaded && (isExternalModel || !supportsTools);
   const showRagPill = !isExternalModel;
   // Above 4 pills, collapse to icons only. Compare, Search, Code, and
-  // permissions always show; the rest are conditional.
-  const pillsCompact =
+  // permissions always show; the rest are conditional. Narrow viewports
+  // collapse too: the labelled row is wider than a phone-width composer.
+  const isMobile = useIsMobile();
+  const pillCount =
     4 +
-      (showImagePill ? 1 : 0) +
-      (showRagPill && ragEnabled ? 1 : 0) +
-      (showWebFetchPill ? 1 : 0) +
-      (artifactsEnabled ? 1 : 0) +
-      (mcpEnabledForChat ? 1 : 0) >
-    4;
+    (showImagePill ? 1 : 0) +
+    (showRagPill && ragEnabled ? 1 : 0) +
+    (showWebFetchPill ? 1 : 0) +
+    (artifactsEnabled ? 1 : 0) +
+    (mcpEnabledForChat ? 1 : 0);
+  const pillsCompact = isMobile || pillCount > 4;
   // Backwards-compatible alias for call sites still referencing
   // `toolsDisabled` (rare; both pills used it before).
   const toolsDisabled = codeDisabled;
@@ -809,9 +753,9 @@ export function SharedComposer({
 
   const {
     isDictating,
+    isFinalizing: isDictationFinalizing,
     start: startDictation,
     stop: stopDictation,
-    supported: dictationSupported,
   } = useDictation(setText);
 
   useEffect(() => {
@@ -1023,15 +967,12 @@ export function SharedComposer({
     // Generalized compare: load each model before dispatching to its side
     if (isGeneralizedCompare) {
       const store = useChatRuntimeStore.getState();
-      const maxSeqLength = store.params.maxSeqLength;
       const trustRemoteCode = store.params.trustRemoteCode ?? false;
-      const chatTemplateOverride = store.chatTemplateOverride;
-      const effectiveChatTemplateOverride = chatTemplateOverride?.trim()
-        ? chatTemplateOverride
-        : null;
+      const fallbackTensorParallel = store.tensorParallel;
       const specSettings = resolveSpeculativeSettingsForLoad({
         usePersistedPreference: true,
       });
+      let loadedFromConfig = false;
 
       function modelDisplayName(id: string): string {
         const parts = id.split("/");
@@ -1058,7 +999,6 @@ export function SharedComposer({
         // path: an early remember-restore can hold a stale cross-host pick that
         // /load would reject (the device cache is populated by send time).
         selectedGpuIds: reconcilePersistedGpuIds(store.selectedGpuIds),
-        tensorParallel: store.tensorParallel,
         customContextLength: store.customContextLength,
       };
       // Set when an accepted transformers install unloaded the active model
@@ -1069,15 +1009,68 @@ export function SharedComposer({
         sel: CompareModelSelection,
       ): Promise<string> {
         const currentStore = useChatRuntimeStore.getState();
+        const config = sel.config ?? null;
+        // This pane's effective config: an explicit selection config, else the
+        // remembered store config for this model/quant (never the other pane's).
+        // No saved config resolves to all-null defaults, so settings below fall
+        // through to their session default.
+        const resolved = config
+          ? { config, remembered: true }
+          : resolveInitialConfig(sel.id, sel.ggufVariant ?? null);
+        const ownConfig = resolved.config;
+        const ownRemembered = resolved.remembered;
+        // Mirror single-view resolveLoadMaxSeqLength: a GGUF pane with no explicit
+        // context loads at native (0 -> n_ctx_train), not the session maxSeqLength,
+        // which would silently shrink the shown context.
+        const isGgufLoad =
+          (sel.ggufVariant ?? null) != null ||
+          sel.id.toLowerCase().endsWith(".gguf");
+        // A non-GGUF pane with no saved maxSeqLength falls back to the app default,
+        // not the active model's shared runtime snapshot: else comparing a saved
+        // 128K model against an unconfigured one loads the latter at 128K and OOMs.
+        const effectiveMaxSeqLength =
+          ownConfig.customContextLength ??
+          normalizeMaxSeqLength(ownConfig.maxSeqLength) ??
+          (isGgufLoad ? 0 : DEFAULT_MAX_SEQ_LENGTH);
+        const effectiveChatTemplateOverride = cleanCompareChatTemplate(
+          ownConfig.chatTemplateOverride,
+        );
+        const effectiveSpeculativeType =
+          ownConfig.speculativeType ?? specSettings.speculativeType;
+        const effectiveSpecDraftNMax = ownRemembered
+          ? resolveCompareSpecDraftNMax(
+              effectiveSpeculativeType,
+              ownConfig.specDraftNMax,
+            )
+          : specSettings.specDraftNMax;
+        const effectiveTensorParallel = ownRemembered
+          ? ownConfig.tensorParallel
+          : fallbackTensorParallel;
+        if (ownConfig.selectedGpuIds != null) {
+          await ensureGpuDeviceCache();
+        }
+        const effectiveGpuMemoryMode =
+          ownConfig.gpuMemoryMode ?? compareLoadKnobs.gpuMemoryMode;
+        const effectiveGpuLayers =
+          ownConfig.gpuLayers ?? compareLoadKnobs.gpuLayers;
+        const effectiveNCpuMoe =
+          ownConfig.nCpuMoe ?? compareLoadKnobs.nCpuMoe;
+        const effectiveSelectedGpuIds =
+          ownConfig.selectedGpuIds !== undefined
+            ? reconcilePersistedGpuIds(ownConfig.selectedGpuIds)
+            : compareLoadKnobs.selectedGpuIds;
+        // A pane's context comes from its own config only: a saved pin, or null
+        // (Auto/native). It must not inherit the active model's shared snapshot --
+        // resolveFitMaxSeqLength would treat that as a pin and load this pane at
+        // the other model's context (changing VRAM/results or OOMing).
+        const effectiveCustomContextLength = ownConfig.customContextLength;
         let loadTrustRemoteCode = trustRemoteCode;
         let approvedRemoteCodeFingerprint: string | null = null;
         const isAlreadyActive =
           currentStore.params.checkpoint === sel.id &&
           (currentStore.activeGgufVariant ?? null) ===
             (sel.ggufVariant ?? null);
-        // Already loaded (gate passed at first load): skip a redundant reload that would
-        // re-trigger the gate without the approval fingerprint and fail for HIGH custom code.
-        if (isAlreadyActive) {
+        if (isAlreadyActive && !config && !loadedFromConfig) {
           return "ready";
         }
         const targetIsGguf =
@@ -1087,10 +1080,13 @@ export function SharedComposer({
         // layers the load sends 0 / the pinned context, not raw maxSeqLength).
         const compareMaxSeqLength = resolveFitMaxSeqLength(
           targetIsGguf,
-          compareLoadKnobs.gpuMemoryMode,
-          compareLoadKnobs.gpuLayers,
-          compareLoadKnobs.customContextLength,
-          maxSeqLength,
+          effectiveGpuMemoryMode,
+          effectiveGpuLayers,
+          // Prefer this pane's own saved context pin over the shared snapshot,
+          // falling back to its per-pane effective context (GGUF with no saved
+          // context loads at native, not the session maxSeqLength).
+          effectiveCustomContextLength,
+          effectiveMaxSeqLength,
         );
         const validation = await validateModel({
           model_path: sel.id,
@@ -1105,8 +1101,8 @@ export function SharedComposer({
           // below: a non-GGUF target must not inherit a hidden GGUF GPU pick.
           ...(targetIsGguf
             ? {
-                gpu_ids: compareLoadKnobs.selectedGpuIds ?? undefined,
-                gpu_memory_mode: compareLoadKnobs.gpuMemoryMode,
+                gpu_ids: effectiveSelectedGpuIds ?? undefined,
+                gpu_memory_mode: effectiveGpuMemoryMode,
               }
             : {}),
         });
@@ -1164,27 +1160,28 @@ export function SharedComposer({
           trust_remote_code: loadTrustRemoteCode,
           approved_remote_code_fingerprint: approvedRemoteCodeFingerprint,
           chat_template_override: effectiveChatTemplateOverride,
-          speculative_type: specSettings.speculativeType,
-          spec_draft_n_max: specSettings.specDraftNMax,
-          // Honor the Tensor Parallelism + GPU Memory choices on compare loads.
-          // GGUF-only, like the auto-load path: the picker is a GGUF control,
-          // so a non-GGUF target loads via HF auto-placement instead of being
-          // pinned to a leftover GGUF pick it can't even show.
-          tensor_parallel: compareLoadKnobs.tensorParallel,
+          cache_type_kv: ownConfig.kvCacheDtype ?? null,
+          speculative_type: effectiveSpeculativeType,
+          spec_draft_n_max: effectiveSpecDraftNMax,
+          tensor_parallel: effectiveTensorParallel,
           ...(targetIsGguf
             ? {
-                gpu_memory_mode: compareLoadKnobs.gpuMemoryMode,
-                gpu_layers: compareLoadKnobs.gpuLayers,
-                n_cpu_moe: compareLoadKnobs.nCpuMoe,
+                gpu_memory_mode: effectiveGpuMemoryMode,
+                gpu_layers: effectiveGpuLayers,
+                n_cpu_moe: effectiveNCpuMoe,
                 tensor_split: compareLoadKnobs.splitRatio ?? undefined,
-                gpu_ids: compareLoadKnobs.selectedGpuIds ?? undefined,
+                gpu_ids: effectiveSelectedGpuIds ?? undefined,
               }
             : {}),
         });
-        saveSpeculativeType(specSettings.speculativeType);
+        // Keep a compare pane's per-model speculative choice load-local: persist
+        // the global preference only when it came from global settings.
+        if (ownConfig.speculativeType == null) {
+          saveSpeculativeType(effectiveSpeculativeType);
+        }
         // Persist the GPU Memory mode on a non-diffusion GGUF compare-load too,
         // so an applied manual choice survives a restart.
-        persistGpuMemoryModeOnLoad(resp, compareLoadKnobs.gpuMemoryMode);
+        persistGpuMemoryModeOnLoad(resp, effectiveGpuMemoryMode);
         upgradeUnloadedActive = false;
         const store = useChatRuntimeStore.getState();
         store.setCheckpoint(
@@ -1200,9 +1197,9 @@ export function SharedComposer({
         // compare loads don't send the pin, so their baseline clears.
         const keepCustomCtx = targetIsGguf
           ? resolveManualAutoCtxPin(
-              compareLoadKnobs.gpuMemoryMode,
-              compareLoadKnobs.gpuLayers,
-              compareLoadKnobs.customContextLength,
+              effectiveGpuMemoryMode,
+              effectiveGpuLayers,
+              effectiveCustomContextLength,
             )
           : null;
         useChatRuntimeStore.setState({
@@ -1211,37 +1208,52 @@ export function SharedComposer({
           ...reasoningCapsFromLoad(resp),
           supportsPreserveThinking: resp.supports_preserve_thinking ?? false,
           supportsTools: resp.supports_tools ?? false,
+          kvCacheDtype: resp.cache_type_kv ?? null,
+          loadedKvCacheDtype: resp.cache_type_kv ?? null,
           tensorParallel: resp.tensor_parallel ?? false,
           loadedTensorParallel: resp.tensor_parallel ?? false,
-          customContextLength: keepCustomCtx,
+          defaultChatTemplate: resp.chat_template ?? null,
+          chatTemplateOverride: effectiveChatTemplateOverride,
+          loadedChatTemplateOverride: effectiveChatTemplateOverride,
+          // The context baseline this pane loaded with (see keepCustomCtx above),
+          // so a later Apply/Reset can't silently revert a Manual+Auto pin.
           loadedCustomContextLength: keepCustomCtx,
-          // Seed the loaded GGUF context (interactive/auto-load parity): the
-          // settings sheet keys the GGUF GPU controls off it for a direct .gguf
-          // with no variant, and a later Apply reads it as the resolved context.
-          ...(targetIsGguf
-            ? {
-                ggufContextLength: resp.context_length ?? 131072,
-                ggufMaxContextLength:
-                  resp.max_context_length ?? resp.context_length ?? 131072,
-                ggufNativeContextLength: resp.native_context_length ?? null,
-              }
-            : { ggufContextLength: null }),
-          // Compare loads resolve by id (HF repo / local path), never through a
-          // native-path lease, so a token left by a previously loaded native
-          // GGUF is stale here -- isLoadedGguf keys off it, and a stale token
-          // would dress a non-GGUF compare load in GGUF controls. Mirror the
-          // interactive path, which writes it on every load success.
-          activeNativePathToken: null,
-          // Held under an open staged pick: setCheckpoint preserves a stage on
-          // the empty->active transition, so a compare load can complete with
-          // staged GPU edits still on screen.
-          ...loadedGpuMemoryFieldsUnlessStaged(resp),
+          // Adopt the load response's GPU-memory fields (mode/layers/MoE/split/pick
+          // plus loaded baselines) so the GPU controls round-trip. (gguf context,
+          // customContextLength and native-path token/expiry clear in the tail below.)
+          ...loadedGpuMemoryFields(resp),
           // Drives the GPU Memory controls' diffusion gate; set alongside the
           // GPU fields on every load path so the gate can't read stale.
           loadedIsDiffusion: resp.is_diffusion ?? false,
           loadedIsMultimodal: isMultimodalResponse(resp),
+          // Record the context this pane loaded with (like the single-model path)
+          // so when it becomes the active model, the UI and later reload/save use
+          // its context, not the previous/default one.
+          customContextLength: isGgufLoad
+            ? (ownConfig.customContextLength ?? keepCustomCtx)
+            : null,
+          ggufContextLength: resp.is_gguf ? (resp.context_length ?? null) : null,
+          ggufNativeContextLength: resp.is_gguf
+            ? (resp.native_context_length ?? null)
+            : null,
+          ggufMaxContextLength: resp.is_gguf
+            ? (resp.max_context_length ?? null)
+            : null,
+          // Compare selections load by repo/variant, never from the file picker,
+          // so they carry no native lease. Clear any prior picked file's
+          // token/expiry so the reload path never sends a stale lease.
+          activeNativePathToken: null,
+          activeNativePathExpiresAtMs: null,
           ...resolveLoadedSpeculativeSettings(resp),
         });
+        if (!isGgufLoad) {
+          // Non-GGUF panes carry their context in params.maxSeqLength.
+          store.setParams({
+            ...useChatRuntimeStore.getState().params,
+            maxSeqLength: effectiveMaxSeqLength,
+          });
+        }
+        loadedFromConfig = config != null;
         // Sync the models[] entry with the load response so attach/send gates
         // read fresh capabilities. /api/models/list can lag a model's actual
         // state (e.g. a GGUF whose mmproj arrived after the snapshot).
@@ -1389,7 +1401,7 @@ export function SharedComposer({
     }
     if (e.key === "Enter" && !e.shiftKey) {
       e.preventDefault();
-      if (!busy) {
+      if (!busy && !isDictating) {
         send();
       }
     }
@@ -1400,7 +1412,8 @@ export function SharedComposer({
       pendingImages.length > 0 ||
       pendingAudio !== null) &&
     !busy &&
-    !isComposing;
+    !isComposing &&
+    !isDictating;
 
   // Adjustable "+" menu items, keyed by id. Pinned ones render at the top
   // level; the rest fall into the "More" overflow submenu. Core items (photos,
@@ -1496,9 +1509,13 @@ export function SharedComposer({
                   toast.error("No conversation to export yet.");
                   return;
                 }
-                Promise.all(exportThreadIds.map((id) => fn(id))).catch(() =>
-                  toast.error("Export failed."),
-                );
+                (async () => {
+                  for (const id of exportThreadIds) {
+                    await fn(id);
+                  }
+                })().catch((error) => {
+                  if (!isDownloadCancelled(error)) toast.error("Export failed.");
+                });
               }}
             >
               {label}
@@ -1686,7 +1703,7 @@ export function SharedComposer({
       />
       <div className="composer-action-wrapper">
         <div
-          className="flex items-center gap-0.5"
+          className="flex min-w-0 flex-wrap items-center gap-0.5"
           data-pill-compact={pillsCompact ? "true" : undefined}
         >
           <input
@@ -2171,7 +2188,7 @@ export function SharedComposer({
               </button>
             )
           ) : null}
-          {dictationSupported && (
+          {
             <>
               {!isDictating ? (
                 <TooltipIconButton
@@ -2187,19 +2204,27 @@ export function SharedComposer({
                 </TooltipIconButton>
               ) : (
                 <TooltipIconButton
-                  tooltip="Stop dictation"
+                  tooltip={
+                    isDictationFinalizing
+                      ? "Cancel transcription"
+                      : "Stop dictation"
+                  }
                   side="bottom"
                   variant="ghost"
                   size="icon"
                   className="size-8 rounded-full text-destructive"
                   onClick={stopDictation}
-                  aria-label="Stop dictation"
+                  aria-label={
+                    isDictationFinalizing
+                      ? "Cancel transcription"
+                      : "Stop dictation"
+                  }
                 >
                   <SquareIcon className="size-3 animate-pulse fill-current" />
                 </TooltipIconButton>
               )}
             </>
-          )}
+          }
           {isQueueRunning ? (
             <button
               type="button"
diff --git a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
index 5786947118..89bc21ee18 100644
--- a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
+++ b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
@@ -1,16 +1,8 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import type { RememberedLoadSettings } from "@/components/assistant-ui/model-selector/remembered-load-settings";
-import {
-  cancelStagedModelDownload,
-  mirrorHfTokenInto,
-  useHfTokenStore,
-} from "@/features/hub";
-import {
-  cachedPinnableGpuIndices,
-  ensureGpuDeviceCache,
-} from "@/hooks/use-gpu-info";
+import { mirrorHfTokenInto, useHfTokenStore } from "@/features/hub";
+import { cachedPinnableGpuIndices } from "@/hooks/use-gpu-info";
 import { toast } from "@/lib/toast";
 import { create } from "zustand";
 import { isExternalModelId, parseExternalModelId } from "../external-providers";
@@ -46,7 +38,6 @@ export const CHAT_ALLOW_ARTIFACT_NETWORK_ACCESS_KEY =
   "unsloth_chat_allow_artifact_network_access";
 export const CHAT_MCP_ENABLED_KEY = "unsloth_chat_mcp_enabled";
 export const CHAT_CONFIRM_TOOL_CALLS_KEY = "unsloth_chat_confirm_tool_calls";
-export const CHAT_LOAD_ON_SELECTION_KEY = "unsloth_chat_load_on_selection";
 export const CHAT_EXPAND_QUANTIZATIONS_KEY =
   "unsloth_chat_expand_quantizations";
 export const CHAT_SHOW_ALL_QUANTIZATIONS_KEY =
@@ -229,6 +220,11 @@ export type PendingImageEditReference = {
   openaiResponseId?: string;
   openaiReasoningItem?: unknown;
 };
+export type LoadingModelPick = {
+  id: string;
+  ggufVariant: string | null;
+  nativePathToken: string | null;
+};
 export type ReasoningEffort =
   | "none"
   | "minimal"
@@ -680,70 +676,7 @@ export function loadedGpuMemoryFields(resp: {
   };
 }
 
-/** loadedGpuMemoryFields (plus any seedExtras), unless a staged pick is open.
- *
- * With a staged pick open (the load fired mid-staging), preserve its editable
- * GPU knobs and seedExtras, but still advance every loaded baseline. Otherwise
- * cancelling the stage restores its edits onto the newly loaded model. The
- * status reseed cannot repair that while pendingSelection holds it off.
- */
-export function loadedGpuMemoryFieldsUnlessStaged<T extends object>(
-  resp: Parameters<typeof loadedGpuMemoryFields>[0],
-  seedExtras?: T,
-) {
-  const fields = loadedGpuMemoryFields(resp);
-  if (useChatRuntimeStore.getState().pendingSelection != null) {
-    return {
-      loadedGpuMemoryMode: fields.loadedGpuMemoryMode,
-      loadedGpuLayers: fields.loadedGpuLayers,
-      loadedNCpuMoe: fields.loadedNCpuMoe,
-      loadedSplitRatio: fields.loadedSplitRatio,
-      loadedGpuIds: fields.loadedGpuIds,
-      // These are metadata ceilings for the model that actually loaded, not
-      // editable values from the open stage. Advance them with the baselines
-      // so abandoning the stage cannot expose the previous model's limits.
-      ggufLayerCount: fields.ggufLayerCount,
-      moeLayerCount: fields.moeLayerCount,
-    };
-  }
-  return { ...fields, ...seedExtras };
-}
-
-/** A local model staged for a deferred load (see `pendingSelection`). Shape is
- *  a subset of the load hook's `SelectedModelInput`, structurally assignable. */
-export type PendingModelSelection = {
-  id: string;
-  isLora?: boolean;
-  ggufVariant?: string;
-  isDownloaded?: boolean;
-  expectedBytes?: number;
-  /** Native (drag-drop / picked-from-disk) GGUF: the path token used to read
-   *  the header and to load. Absent for HF-repo models. */
-  nativePathToken?: string;
-  /** Direct local .gguf file (custom folder / LM Studio): a GGUF source even
-   *  though it carries neither an HF variant nor a native path token. */
-  isGguf?: boolean;
-  /** Native context length read from the GGUF header once the file is local.
-   *  Scoped here (not the shared `ggufContextLength`) so a staged model's
-   *  metadata never pollutes the currently-loaded model's context display. */
-  contextLength?: number | null;
-  /** Total layer count (GGUF block_count); the manual gpu-layers ceiling is
-   * this + 1 (llama.cpp counts the output layer as offloadable too);
-   *  scoped here like contextLength. */
-  layerCount?: number | null;
-  /** MoE expert-layer count from the GGUF header (manual --n-cpu-moe ceiling);
-   *  0 for dense models, scoped here like contextLength. */
-  moeLayerCount?: number | null;
-  /** "Load on selection" on + un-cached GGUF: download via the manager (global
-   *  indicator) without opening the sheet, then load once the download finishes. */
-  autoLoad?: boolean;
-  /** Uncached non-GGUF HF repo: download the full snapshot via the manager
-   *  (variant null) the same way GGUF picks download a variant. */
-  isHubRepo?: boolean;
-};
-
-/** A pick is a GGUF (HF variant, native file, or a direct local .gguf) and so
- *  has pre-load options worth staging. Works on a selection or a staged pick. */
+/** A pick is a GGUF: HF variant, native file, or a direct local .gguf. */
 export function hasGgufSource(x: {
   ggufVariant?: string;
   nativePathToken?: string;
@@ -781,30 +714,6 @@ export function isDownloadableHubRepo(x: {
   );
 }
 
-export function isPendingGguf(pending: PendingModelSelection | null): boolean {
-  return pending != null && hasGgufSource(pending);
-}
-
-/** Whether `pending` refers to the same model as `pick` (id + GGUF variant +
- *  native path token, optionals null-normalized). Native ids are display labels
- *  that can collide, so the token must match too — id alone can land on the
- *  wrong file. */
-export function pendingSelectionMatches(
-  pending: PendingModelSelection | null,
-  pick: {
-    id: string;
-    ggufVariant?: string | null;
-    nativePathToken?: string | null;
-  },
-): boolean {
-  return (
-    pending != null &&
-    pending.id === pick.id &&
-    (pending.ggufVariant ?? null) === (pick.ggufVariant ?? null) &&
-    (pending.nativePathToken ?? null) === (pick.nativePathToken ?? null)
-  );
-}
-
 type ChatRuntimeStore = {
   settingsHydrated: boolean;
   params: InferenceParams;
@@ -988,10 +897,6 @@ type ChatRuntimeStore = {
   /** Picked physical GPU indices (null = use all / automatic). */
   selectedGpuIds: number[] | null;
   loadedGpuIds: number[] | null;
-  /** Persisted: when false, picking a local model stages it as
-   *  `pendingSelection` (and opens settings) instead of loading immediately,
-   *  so load settings can be set before the single load. */
-  loadOnSelection: boolean;
   /** Persisted: expand every On Device GGUF repo's quantizations by default
    *  instead of waiting for a click. */
   expandQuantizations: boolean;
@@ -1000,9 +905,6 @@ type ChatRuntimeStore = {
   /** Persisted, shared by the chat model selector and the Hub page: list only
    *  models whose size fits this device's memory budget. */
   fitOnDeviceOnly: boolean;
-  /** A local model picked while `loadOnSelection` is off: staged, not loaded.
-   *  The settings sheet shows its load knobs and a Load button. */
-  pendingSelection: PendingModelSelection | null;
   loadedIsMultimodal: boolean;
   /** Active model is a block-diffusion model (DiffusionGemma): drives the
    *  denoising-canvas artifact auto-render. */
@@ -1041,9 +943,16 @@ type ChatRuntimeStore = {
     cacheWriteTokens?: number;
   } | null;
   modelLoading: boolean;
+  loadingModelPick: LoadingModelPick | null;
   activeNativePathToken: string | null;
+  // Wall-clock expiry (ms) of the active native path token. The desktop host
+  // prunes file leases after a TTL, so a reload checks this to prompt
+  // re-selection instead of reusing a dead token.
+  activeNativePathExpiresAtMs: number | null;
   hydratePersistedSettings: () => Promise<void>;
   setModelLoading: (loading: boolean) => void;
+  setLoadingModelPick: (pick: LoadingModelPick | null) => void;
+  clearLoadingModelPick: (expected: LoadingModelPick) => void;
   setModelRequiresTrustRemoteCode: (required: boolean) => void;
   setParams: (params: InferenceParams) => void;
   setCustomPresets: (presets: Preset[]) => void;
@@ -1119,38 +1028,14 @@ type ChatRuntimeStore = {
   setNudgeToolCalls: (enabled: boolean) => void;
   setMaxToolCallsPerMessage: (value: number) => void;
   setToolCallTimeout: (value: number) => void;
-  setKvCacheDtype: (dtype: string | null) => void;
-  setSpeculativeType: (type: string | null) => void;
-  setSpecDraftNMax: (value: number | null) => void;
-  /** Revert the editable load knobs to the loaded model's baseline (or defaults
-   *  when nothing is loaded). Used by the settings-sheet Reset button and to
-   *  start each deferred-staging session clean so one staged pick's settings
-   *  don't leak onto the next. */
-  resetModelSettingsToLoaded: () => void;
-  /** Seed the editable load knobs from a model's remembered settings. Shared by
-   *  the settings sheet's restore effect and the "Load on selection" paths,
-   *  which skip the sheet but must still honor a saved config. */
-  applyRememberedLoadSettings: (settings: RememberedLoadSettings) => void;
-  setTensorParallel: (value: boolean) => void;
   setGpuMemoryMode: (mode: "auto" | "manual") => void;
   setGpuLayers: (value: number) => void;
   setNCpuMoe: (value: number) => void;
   setSplitRatio: (value: number[] | null) => void;
   setSelectedGpuIds: (ids: number[] | null) => void;
-  setLoadOnSelection: (value: boolean) => void;
   setExpandQuantizations: (value: boolean) => void;
   setShowAllQuantizations: (value: boolean) => void;
   setFitOnDeviceOnly: (value: boolean) => void;
-  setPendingSelection: (selection: PendingModelSelection | null) => void;
-  /** Stage a pick for a deferred load: revert knobs to the loaded baseline,
-   *  record the selection, and open the settings sheet. */
-  stageModel: (selection: PendingModelSelection) => void;
-  /** Abandon a staged pick without loading: revert knobs to the loaded baseline
-   *  and clear the pending selection. Cancels its in-flight download too, unless
-   *  `keepDownload` is set (navigation keeps the transfer running, like Hub). */
-  abandonStagedModel: (opts?: { keepDownload?: boolean }) => void;
-  setCustomContextLength: (v: number | null) => void;
-  setChatTemplateOverride: (template: string | null) => void;
   setPendingAudio: (base64: string, name: string) => void;
   clearPendingAudio: () => void;
   setPendingImageEditReference: (
@@ -1352,38 +1237,6 @@ function setScalarSettingVersion<K extends ScalarSettingKey>(
   saveSettingsPatch({ [key]: value });
 }
 
-/** The "revert to the loaded model" baseline for the editable load knobs.
- *  Shared by resetModelSettingsToLoaded (full revert) and stageModel (which
- *  overrides speculative and the per-model GPU knobs to start a fresh pick). */
-function loadedBaselineSettings(s: ChatRuntimeStore) {
-  const hasLoadedModel = Boolean(s.params.checkpoint);
-  return {
-    // Revert to the loaded model's pin (null = Auto), not a blanket Auto.
-    customContextLength: s.loadedCustomContextLength,
-    kvCacheDtype: s.loadedKvCacheDtype,
-    tensorParallel: s.loadedTensorParallel ?? false,
-    speculativeType: hasLoadedModel
-      ? s.loadedSpeculativeType
-      : readPersistedSpeculativeType(),
-    specDraftNMax: hasLoadedModel ? s.loadedSpecDraftNMax : null,
-    chatTemplateOverride: s.loadedChatTemplateOverride,
-    // GPU memory mode is a standing preference; revert to the loaded model's
-    // mode (or the persisted default when nothing is loaded). Manual knobs and
-    // the GPU pick are per-model and revert to their loaded baseline. A loaded
-    // model with no applicable mode -- diffusion ("auto" baseline) or non-GGUF
-    // (null baseline) -- keeps the live preference so Reset can't drop it.
-    gpuMemoryMode: !hasLoadedModel
-      ? readPersistedGpuMemoryMode()
-      : s.loadedIsDiffusion
-        ? s.gpuMemoryMode
-        : (s.loadedGpuMemoryMode ?? s.gpuMemoryMode),
-    gpuLayers: s.loadedGpuLayers ?? GPU_LAYERS_AUTO,
-    nCpuMoe: s.loadedNCpuMoe ?? 0,
-    splitRatio: s.loadedSplitRatio ?? null,
-    selectedGpuIds: s.loadedGpuIds,
-  };
-}
-
 export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   settingsHydrated: false,
   // Hydrate the last external checkpoint so the external picker survives a
@@ -1493,11 +1346,9 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   moeLayerCount: null,
   selectedGpuIds: null,
   loadedGpuIds: null,
-  loadOnSelection: loadBool(CHAT_LOAD_ON_SELECTION_KEY, true),
   expandQuantizations: loadBool(CHAT_EXPAND_QUANTIZATIONS_KEY, false),
   showAllQuantizations: loadBool(CHAT_SHOW_ALL_QUANTIZATIONS_KEY, true),
   fitOnDeviceOnly: loadBool(MODELS_FIT_ON_DEVICE_ONLY_KEY, false),
-  pendingSelection: null,
   loadedIsMultimodal: false,
   loadedIsDiffusion: false,
   customContextLength: null,
@@ -1515,7 +1366,9 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   pendingImageEditReference: null,
   contextUsage: null,
   modelLoading: false,
+  loadingModelPick: null,
   activeNativePathToken: null,
+  activeNativePathExpiresAtMs: null,
   hydratePersistedSettings: async () => {
     if (get().settingsHydrated) {
       return;
@@ -1554,6 +1407,20 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     return settingsHydrationPromise;
   },
   setModelLoading: (loading) => set({ modelLoading: loading }),
+  setLoadingModelPick: (pick) => set({ loadingModelPick: pick }),
+  clearLoadingModelPick: (expected) =>
+    set((state) => {
+      const current = state.loadingModelPick;
+      if (
+        !current ||
+        current.id !== expected.id ||
+        current.ggufVariant !== expected.ggufVariant ||
+        current.nativePathToken !== expected.nativePathToken
+      ) {
+        return state;
+      }
+      return { loadingModelPick: null };
+    }),
   setModelRequiresTrustRemoteCode: (modelRequiresTrustRemoteCode) =>
     set({ modelRequiresTrustRemoteCode }),
   setParams: (params) =>
@@ -1634,13 +1501,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       // Clear stale per-turn usage on model change; the relaxed external-provider
       // render gate would otherwise show old counters until the next completion.
       const checkpointChanged = state.params.checkpoint !== modelId;
-      const pendingToClear =
-        checkpointChanged && state.params.checkpoint
-          ? state.pendingSelection
-          : null;
-      if (pendingToClear) {
-        cancelStagedModelDownload(pendingToClear);
-      }
       // Clamp maxTokens to the new model's cap when switching into an external
       // model so a value carried over from a local session doesn't exceed the
       // slider's max.
@@ -1668,14 +1528,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
         },
         activeGgufVariant: ggufVariant ?? null,
         ...(checkpointChanged ? { contextUsage: null } : {}),
-        // Switching away from a loaded model (e.g. picking an external provider)
-        // abandons any staged pick, so its Load button and edited knobs don't
-        // linger over the newly active model. Same revert as abandonStagedModel.
-        // Guarded on a non-empty current checkpoint: an establishing set from a
-        // background status sync (empty -> active) must not wipe a fresh stage.
-        ...(pendingToClear
-          ? { ...loadedBaselineSettings(state), pendingSelection: null }
-          : {}),
       };
     }),
   setActiveThreadId: (activeThreadId) =>
@@ -1689,7 +1541,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     // clear any stored external selection so the next refresh doesn't snap
     // back to a model the user intentionally cleared.
     saveLastExternalCheckpoint(null);
-    cancelStagedModelDownload(get().pendingSelection);
     return set((state) => ({
       params: {
         ...state.params,
@@ -1697,7 +1548,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       },
       activeGgufVariant: null,
       activeNativePathToken: null,
-      pendingSelection: null,
+      activeNativePathExpiresAtMs: null,
       ggufContextLength: null,
       ggufMaxContextLength: null,
       ggufNativeContextLength: null,
@@ -2044,10 +1895,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       );
       return { toolCallTimeout };
     }),
-  setKvCacheDtype: (kvCacheDtype) => set({ kvCacheDtype }),
-  setSpeculativeType: (speculativeType) => set({ speculativeType }),
-  setSpecDraftNMax: (specDraftNMax) => set({ specDraftNMax }),
-  setTensorParallel: (tensorParallel) => set({ tensorParallel }),
   // Standing preference, but persisted only on a successful load (see
   // use-chat-model-runtime), not on selection -- so an unapplied pick the user
   // resets/abandons doesn't stick to the next session.
@@ -2056,63 +1903,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   setNCpuMoe: (nCpuMoe) => set({ nCpuMoe }),
   setSplitRatio: (splitRatio) => set({ splitRatio }),
   setSelectedGpuIds: (selectedGpuIds) => set({ selectedGpuIds }),
-  resetModelSettingsToLoaded: () => set((s) => loadedBaselineSettings(s)),
-  applyRememberedLoadSettings: (settings) => {
-    const gpuCacheWasCold = cachedPinnableGpuIndices() === null;
-    const restoredGpuIds =
-      settings.selectedGpuIds !== undefined
-        ? reconcilePersistedGpuIds(settings.selectedGpuIds)
-        : undefined;
-    // Coalesce every field: a blob persisted by an older/newer build can omit
-    // keys, and a raw spread would push `undefined` into fields typed non-null.
-    // The GPU knobs are spread only when present, but first reset the per-model
-    // ones to defaults: this path (load-on-selection) starts from the loaded
-    // model's baseline and skips the model-switch reset, so a blob omitting
-    // gpuLayers/nCpuMoe/selectedGpuIds (older build) or splitRatio (never
-    // remembered) must not inherit the previous model's placement. gpuMemoryMode
-    // (standing preference) is NOT reset, only applied when the blob carries it;
-    // selectedGpuIds keeps a meaningful null (all GPUs), so it keys off undefined.
-    set({
-      gpuLayers: GPU_LAYERS_AUTO,
-      nCpuMoe: 0,
-      splitRatio: null,
-      selectedGpuIds: null,
-      customContextLength: settings.contextLength ?? null,
-      kvCacheDtype: settings.kvCacheDtype ?? null,
-      speculativeType: settings.speculativeType ?? "auto",
-      specDraftNMax: settings.specDraftNMax ?? null,
-      tensorParallel: settings.tensorParallel ?? false,
-      ...(settings.gpuMemoryMode != null && {
-        gpuMemoryMode: settings.gpuMemoryMode,
-      }),
-      ...(settings.gpuLayers != null && { gpuLayers: settings.gpuLayers }),
-      ...(settings.nCpuMoe != null && { nCpuMoe: settings.nCpuMoe }),
-      ...(restoredGpuIds !== undefined && {
-        // Reconcile against the GPUs present now (see reconcilePersistedGpuIds):
-        // a saved [1] on a 1-GPU host (or under relative/UUID visibility) would
-        // hide the picker yet still send gpu_ids, which the backend rejects.
-        selectedGpuIds: restoredGpuIds,
-      }),
-    });
-    // A cold cache makes the synchronous restore provisional. Reconcile again
-    // when the shared fetch completes, but only if this exact restored array is
-    // still current so a user edit, stage change, or load cannot be overwritten.
-    if (gpuCacheWasCold && restoredGpuIds != null) {
-      void ensureGpuDeviceCache().then(() => {
-        set((state) => {
-          if (state.selectedGpuIds !== restoredGpuIds) return state;
-          const reconciled = reconcilePersistedGpuIds(restoredGpuIds);
-          return reconciled === restoredGpuIds
-            ? state
-            : { selectedGpuIds: reconciled };
-        });
-      });
-    }
-  },
-  setLoadOnSelection: (loadOnSelection) => {
-    saveBool(CHAT_LOAD_ON_SELECTION_KEY, loadOnSelection);
-    set({ loadOnSelection });
-  },
   setExpandQuantizations: (expandQuantizations) => {
     saveBool(CHAT_EXPAND_QUANTIZATIONS_KEY, expandQuantizations);
     set({ expandQuantizations });
@@ -2125,55 +1915,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     saveBool(MODELS_FIT_ON_DEVICE_ONLY_KEY, fitOnDeviceOnly);
     set({ fitOnDeviceOnly });
   },
-  setPendingSelection: (pendingSelection) => set({ pendingSelection }),
-  stageModel: (selection) => {
-    // Refuse staging mid-load: post-load cleanup would silently drop the queued
-    // pick. stageOrLoad toasts first for callers that can.
-    if (get().modelLoading) return;
-    // Rebinding to a new pick keeps the prior pick's download running so the
-    // user can queue multiple downloads at once (Hub-style).
-    set((s) => {
-      return {
-        ...loadedBaselineSettings(s),
-        pendingSelection: selection,
-        // autoLoad downloads silently and loads on completion, so keep the sheet shut.
-        settingsPanelOpen: !selection.autoLoad,
-        // Speculative starts from the standing default, not the loaded model's
-        // mode, so a fresh pick doesn't inherit (and then carry, via the staged
-        // Load's keepSpeculative) a forced MTP mode onto a model that may lack it.
-        speculativeType: readPersistedSpeculativeType(),
-        specDraftNMax: null,
-        // Keep the on-screen GPU Memory selection (loadedBaselineSettings would
-        // otherwise revert it to the loaded model's mode, dropping a Manual choice
-        // just made). Use the live store value, not the persisted one, which can
-        // lag a mode hydrated from an out-of-band load.
-        gpuMemoryMode: s.gpuMemoryMode,
-        // Per-model GPU knobs start from defaults too so a fresh pick doesn't
-        // inherit the loaded model's layer/MoE/split/GPU choices, matching the
-        // immediate-switch reset.
-        gpuLayers: GPU_LAYERS_AUTO,
-        nCpuMoe: 0,
-        splitRatio: null,
-        selectedGpuIds: null,
-        // Fresh pick starts at Auto context (loadedBaselineSettings would
-        // otherwise restore the current model's pin). Leaves the baseline
-        // intact, like the GPU knobs, so abandoning restores the loaded pin.
-        customContextLength: null,
-      };
-    });
-  },
-  abandonStagedModel: (opts) => {
-    const { pendingSelection } = get();
-    if (!pendingSelection) return;
-    // Cancel the staged pick's in-flight download (centralized for every abandon
-    // path: sheet close, thread switch, route exit, new chat). `keepDownload`
-    // opts out so navigation leaves the transfer running, like a Hub download.
-    if (!opts?.keepDownload) cancelStagedModelDownload(pendingSelection);
-    set((s) => ({ ...loadedBaselineSettings(s), pendingSelection: null }));
-  },
-  setCustomContextLength: (customContextLength) => set({ customContextLength }),
-  setChatTemplateOverride: (chatTemplateOverride) =>
-    set({ chatTemplateOverride }),
   setPendingAudio: (base64, name) =>
     set({ pendingAudioBase64: base64, pendingAudioName: name }),
   clearPendingAudio: () =>
diff --git a/studio/frontend/src/features/chat/stores/pinned-projects-store.ts b/studio/frontend/src/features/chat/stores/pinned-projects-store.ts
new file mode 100644
index 0000000000..c6dbad5c79
--- /dev/null
+++ b/studio/frontend/src/features/chat/stores/pinned-projects-store.ts
@@ -0,0 +1,42 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { create } from "zustand";
+import { persist } from "zustand/middleware";
+
+// Client-side pin state for projects, keyed by project id. Kept in
+// localStorage. Pinned projects drive the sidebar "Projects" section; new pins
+// are prepended so the most recently pinned project sorts first.
+export interface PinnedProjectsState {
+  pinnedIds: string[];
+  togglePin: (id: string) => void;
+  unpin: (id: string) => void;
+}
+
+export const usePinnedProjectsStore = create<PinnedProjectsState>()(
+  persist(
+    (set) => ({
+      pinnedIds: [],
+      togglePin: (id) =>
+        set((state) => ({
+          pinnedIds: state.pinnedIds.includes(id)
+            ? state.pinnedIds.filter((x) => x !== id)
+            : [id, ...state.pinnedIds],
+        })),
+      unpin: (id) =>
+        set((state) => ({
+          pinnedIds: state.pinnedIds.filter((x) => x !== id),
+        })),
+    }),
+    {
+      name: "unsloth_pinned_projects",
+      merge: (persisted, current) => {
+        const saved = persisted as Partial<PinnedProjectsState> | undefined;
+        return {
+          ...current,
+          pinnedIds: Array.isArray(saved?.pinnedIds) ? saved.pinnedIds : [],
+        };
+      },
+    },
+  ),
+);
diff --git a/studio/frontend/src/features/chat/thread-sidebar.tsx b/studio/frontend/src/features/chat/thread-sidebar.tsx
index 9e65fc5749..bd1fb9d87c 100644
--- a/studio/frontend/src/features/chat/thread-sidebar.tsx
+++ b/studio/frontend/src/features/chat/thread-sidebar.tsx
@@ -42,6 +42,7 @@ import {
   PencilEdit02Icon,
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
+import { isDownloadCancelled } from "@/lib/native-files";
 import { toast } from "sonner";
 import { useChatRuntimeStore } from "./stores/chat-runtime-store";
 import type { ChatView } from "./types";
@@ -133,9 +134,13 @@ export function ThreadSidebar({
   ) {
     try {
       const ids = await getThreadIdsForItem(item);
-      await Promise.all(ids.map((id) => fn(id)));
-    } catch {
-      toast.error("Export failed.");
+      for (const id of ids) {
+        await fn(id);
+      }
+    } catch (error) {
+      if (!isDownloadCancelled(error)) {
+        toast.error("Export failed.");
+      }
     }
   }
 
@@ -162,8 +167,10 @@ export function ThreadSidebar({
       } else {
         await exportBulkConversationsSeparate(ids, fmt, basename);
       }
-    } catch {
-      toast.error("Export failed.");
+    } catch (error) {
+      if (!isDownloadCancelled(error)) {
+        toast.error("Export failed.");
+      }
     }
   }
 
@@ -259,7 +266,7 @@ export function ThreadSidebar({
                   >
                     {item.isFork ? (
                       <span
-                        className="mr-1 rounded-sm bg-primary/10 px-1.5 py-0.5 text-[10px] font-semibold uppercase tracking-wide text-primary"
+                        className="mr-1 rounded-sm bg-primary/10 px-1.5 py-0.5 text-ui-10 font-semibold uppercase tracking-wide text-primary"
                         title="Forked from another chat"
                       >
                         fork
diff --git a/studio/frontend/src/features/chat/types/api.ts b/studio/frontend/src/features/chat/types/api.ts
index c24ddde5f5..c9c06834c1 100644
--- a/studio/frontend/src/features/chat/types/api.ts
+++ b/studio/frontend/src/features/chat/types/api.ts
@@ -99,6 +99,9 @@ export interface ValidateModelResponse {
   /** MoE expert-layer count from the GGUF header (manual --n-cpu-moe ceiling);
    *  0 for dense models, null until downloaded. */
   moe_layer_count?: number | null;
+  /** Embedded GGUF chat template, returned when include_chat_template is set
+   *  (native lease-backed picks); null for non-GGUF, over-cap, or not read. */
+  chat_template?: string | null;
   /** Architecture only shipped by a newer transformers; UI pauses on the upgrade dialog. */
   requires_transformers_upgrade?: boolean;
   /** Set only when requires_transformers_upgrade. */
diff --git a/studio/frontend/src/features/chat/utils/export-chat-history.ts b/studio/frontend/src/features/chat/utils/export-chat-history.ts
index b4bc64d053..6f641a9fa9 100644
--- a/studio/frontend/src/features/chat/utils/export-chat-history.ts
+++ b/studio/frontend/src/features/chat/utils/export-chat-history.ts
@@ -1,9 +1,10 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import { downloadFile } from "@/lib/native-files";
+
 import { filterArchivedChatExport } from "./archived-chat-export";
 import { buildStoredChatExport } from "./chat-history-storage";
-import { triggerJsonDownload } from "./download-json";
 
 export const buildChatExport = buildStoredChatExport;
 
@@ -14,7 +15,11 @@ function dateStamp(): string {
 
 export async function downloadChatExport(): Promise<void> {
   const data = await buildChatExport();
-  triggerJsonDownload(data, `unsloth-chats-${dateStamp()}.json`);
+  await downloadFile(
+    JSON.stringify(data, null, 2),
+    `unsloth-chats-${dateStamp()}.json`,
+    "application/json",
+  );
 }
 
 // Full backup restricted to archived chats. Returns the archived thread count.
@@ -29,6 +34,10 @@ export async function downloadArchivedChatExport(): Promise<number> {
   if (archivedCount === 0) {
     return 0;
   }
-  triggerJsonDownload(data, `unsloth-archived-chats-${dateStamp()}.json`);
+  await downloadFile(
+    JSON.stringify(data, null, 2),
+    `unsloth-archived-chats-${dateStamp()}.json`,
+    "application/json",
+  );
   return archivedCount;
 }
diff --git a/studio/frontend/src/features/data-recipes/data/recipes-db.ts b/studio/frontend/src/features/data-recipes/data/recipes-db.ts
index f89707e159..3ffe09c2d2 100644
--- a/studio/frontend/src/features/data-recipes/data/recipes-db.ts
+++ b/studio/frontend/src/features/data-recipes/data/recipes-db.ts
@@ -16,11 +16,40 @@ db.version(1).stores({
 });
 
 const recentRecipeCache = new Map<string, RecipeRecord>();
+let cachedRecipeList: RecipeRecord[] = [];
+let recipeListReady = false;
+let recipeListRequest: Promise<RecipeRecord[]> | null = null;
 
 export function listRecipes(): Promise<RecipeRecord[]> {
   return db.recipes.orderBy("updatedAt").reverse().toArray();
 }
 
+function cacheRecipeList(recipes: RecipeRecord[]): RecipeRecord[] {
+  for (const recipe of recipes) {
+    writeRecipeCache(recipe);
+  }
+  cachedRecipeList = recipes;
+  recipeListReady = true;
+  return recipes;
+}
+
+export function preloadRecipes(): Promise<RecipeRecord[]> {
+  if (recipeListReady) {
+    return Promise.resolve(cachedRecipeList);
+  }
+  if (recipeListRequest) {
+    return recipeListRequest;
+  }
+
+  const request = listRecipes()
+    .then(cacheRecipeList)
+    .finally(() => {
+      recipeListRequest = null;
+    });
+  recipeListRequest = request;
+  return request;
+}
+
 export function getRecipe(id: string): Promise<RecipeRecord | undefined> {
   return db.recipes.get(id);
 }
@@ -55,12 +84,21 @@ export async function saveRecipe(
   };
   await db.recipes.put(record);
   writeRecipeCache(record);
+  if (recipeListReady) {
+    cachedRecipeList = [
+      record,
+      ...cachedRecipeList.filter((recipe) => recipe.id !== record.id),
+    ].sort((a, b) => b.updatedAt - a.updatedAt);
+  }
   return record;
 }
 
 export async function deleteRecipe(id: string): Promise<void> {
   await db.recipes.delete(id);
   recentRecipeCache.delete(id);
+  if (recipeListReady) {
+    cachedRecipeList = cachedRecipeList.filter((recipe) => recipe.id !== id);
+  }
 }
 
 export function createRecipeDraft(): Promise<RecipeRecord> {
@@ -87,15 +125,13 @@ export function useRecipes(): {
   recipes: RecipeRecord[];
   ready: boolean;
 } {
-  const [recipes, setRecipes] = useState<RecipeRecord[]>([]);
-  const [ready, setReady] = useState(false);
+  const [recipes, setRecipes] = useState<RecipeRecord[]>(cachedRecipeList);
+  const [ready, setReady] = useState(recipeListReady);
 
   useEffect(() => {
     const sub = liveQuery(() => listRecipes()).subscribe({
       next: (value) => {
-        for (const recipe of value) {
-          writeRecipeCache(recipe);
-        }
+        cacheRecipeList(value);
         setRecipes(value);
         setReady(true);
       },
diff --git a/studio/frontend/src/features/data-recipes/index.ts b/studio/frontend/src/features/data-recipes/index.ts
index d085096e0d..a75dd7075a 100644
--- a/studio/frontend/src/features/data-recipes/index.ts
+++ b/studio/frontend/src/features/data-recipes/index.ts
@@ -3,3 +3,4 @@
 
 export { DataRecipesPage } from "./pages/data-recipes-page";
 export { EditRecipePage } from "./pages/edit-recipe-page";
+export { preloadRecipes } from "./data/recipes-db";
diff --git a/studio/frontend/src/features/data-recipes/pages/data-recipes-page.tsx b/studio/frontend/src/features/data-recipes/pages/data-recipes-page.tsx
index 088d016894..7716671151 100644
--- a/studio/frontend/src/features/data-recipes/pages/data-recipes-page.tsx
+++ b/studio/frontend/src/features/data-recipes/pages/data-recipes-page.tsx
@@ -280,7 +280,7 @@ function LearningRecipeCards({
                       <Badge
                         key={`${template.title}-${badge}`}
                         variant="outline"
-                        className="h-5 shrink-0 px-1.5 text-[10px] dark:text-zinc-300"
+                        className="h-5 shrink-0 px-1.5 text-ui-10 dark:text-zinc-300"
                       >
                         {badge}
                       </Badge>
@@ -288,7 +288,7 @@ function LearningRecipeCards({
                     {extraLearningBadgeCount > 0 ? (
                       <Badge
                         variant="outline"
-                        className="h-5 shrink-0 px-1.5 text-[10px] dark:text-zinc-300"
+                        className="h-5 shrink-0 px-1.5 text-ui-10 dark:text-zinc-300"
                       >
                         +{extraLearningBadgeCount}
                       </Badge>
@@ -296,7 +296,7 @@ function LearningRecipeCards({
                     {isReady ? null : (
                       <Badge
                         variant="secondary"
-                        className="h-5 shrink-0 px-1.5 text-[10px] dark:text-zinc-300"
+                        className="h-5 shrink-0 px-1.5 text-ui-10 dark:text-zinc-300"
                       >
                         Soon
                       </Badge>
@@ -403,7 +403,7 @@ export function DataRecipesPage(): ReactElement {
       <main className="mx-auto w-full max-w-7xl px-5 py-8 sm:px-9">
         <div className="flex items-center justify-between gap-4">
           <div>
-            <h1 className="text-[30px] font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-[34px]">
+            <h1 className="text-ui-30 font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-ui-34">
               Data Recipes
             </h1>
             <p className="mt-1 text-sm text-muted-foreground">
diff --git a/studio/frontend/src/features/export/components/export-run-panel.tsx b/studio/frontend/src/features/export/components/export-run-panel.tsx
index 29ba5a703b..9d938a5ee3 100644
--- a/studio/frontend/src/features/export/components/export-run-panel.tsx
+++ b/studio/frontend/src/features/export/components/export-run-panel.tsx
@@ -2,7 +2,6 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { Button } from "@/components/ui/button";
-import { FolderBrowser } from "@/components/assistant-ui/model-selector/folder-browser";
 import { Input } from "@/components/ui/input";
 import {
   InputGroup,
@@ -17,6 +16,7 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import { FolderBrowser } from "@/features/model-picker";
 import {
   AlertCircleIcon,
   ArrowRight01Icon,
@@ -28,17 +28,17 @@ import {
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useEffect, useRef, useState } from "react";
 import { useShallow } from "zustand/react/shallow";
+import type { ExportLogEntry } from "../api/export-api";
 import {
   EXPORT_METHODS,
   type ExportMethod,
   findMergedFormat,
 } from "../constants";
-import type { ExportLogEntry } from "../api/export-api";
 import { getExportLogLineClass } from "../lib/log-style";
 import {
+  type ExportDestination,
   selectExportProgressPercent,
   useExportRuntimeStore,
-  type ExportDestination,
 } from "../stores/export-runtime-store";
 
 function useElapsedSeconds(startedAt: number | null, running: boolean): number {
@@ -165,7 +165,9 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
 
   const isExporting = run.isExporting;
   const isTerminal =
-    run.phase === "success" || run.phase === "error" || run.phase === "canceled";
+    run.phase === "success" ||
+    run.phase === "error" ||
+    run.phase === "canceled";
   const showConfig = run.phase === "idle";
   // Gate the log area on the active run's method (from the store) as well as the
   // local form selection, so it stays visible after navigating away and back
@@ -197,7 +199,9 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
     setFollowTail(nearBottom);
   };
 
-  const methodTitle = EXPORT_METHODS.find((m) => m.value === exportMethod)?.title;
+  const methodTitle = EXPORT_METHODS.find(
+    (m) => m.value === exportMethod,
+  )?.title;
   const summary = run.summary;
   const summaryBaseModel = summary?.baseModelName ?? baseModelName;
   const summaryCheckpoint = summary?.checkpointLabel ?? checkpoint;
@@ -274,7 +278,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
               </div>
               <div className="flex items-stretch gap-2">
                 <Input
-                  className="min-w-0 flex-1 font-mono text-[12px]"
+                  className="min-w-0 flex-1 font-mono text-ui-12"
                   value={saveDirectory}
                   onChange={(e) => onSaveDirectoryChange(e.target.value)}
                   spellCheck={false}
@@ -290,19 +294,22 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                       onClick={() => setFolderBrowserOpen(true)}
                       aria-label="Browse save folder"
                     >
-                      <HugeiconsIcon icon={FolderSearchIcon} className="size-4" />
+                      <HugeiconsIcon
+                        icon={FolderSearchIcon}
+                        className="size-4"
+                      />
                     </Button>
                   </TooltipTrigger>
                   <TooltipContent>Browse</TooltipContent>
                 </Tooltip>
               </div>
-              <p className="text-[11px] text-muted-foreground/70">
+              <p className="text-ui-11 text-muted-foreground/70">
                 {saveDirectory !== defaultSaveDirectory ? (
                   <>Default: {defaultSaveDirectory}</>
                 ) : (
                   <>
-                    Paste an absolute path if the folder browser cannot reach the
-                    drive.
+                    Paste an absolute path if the folder browser cannot reach
+                    the drive.
                   </>
                 )}
               </p>
@@ -343,7 +350,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                         href="https://huggingface.co/settings/tokens"
                         target="_blank"
                         rel="noopener noreferrer"
-                        className="flex items-center gap-1 text-[11px] text-emerald-600 hover:text-emerald-700 transition-colors"
+                        className="flex items-center gap-1 text-ui-11 text-emerald-600 hover:text-emerald-700 transition-colors"
                       >
                         Get token
                         <HugeiconsIcon icon={ArrowRight01Icon} className="size-3" />
@@ -362,7 +369,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                         onChange={(e) => onHfTokenChange(e.target.value)}
                       />
                     </InputGroup>
-                    <p className="text-[11px] text-muted-foreground/70">
+                    <p className="text-ui-11 text-muted-foreground/70">
                       Leave empty if already logged in via CLI.
                     </p>
                   </div>
@@ -410,14 +417,17 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                     : [];
               const showLabels = items.length > 1;
               return items.map((o, i) => (
-                <div key={`${o.path}-${i}`} className="flex min-w-0 flex-col gap-0.5">
+                <div
+                  key={`${o.path}-${i}`}
+                  className="flex min-w-0 flex-col gap-0.5"
+                >
                   {showLabels && o.label ? (
                     <span className="text-xs text-emerald-700/80 dark:text-emerald-300/80">
                       {o.label}
                     </span>
                   ) : null}
                   <code
-                    className="select-all break-all font-mono text-[12px] text-foreground/90"
+                    className="select-all break-all font-mono text-ui-12 text-foreground/90"
                     title={o.path}
                   >
                     {o.path}
@@ -431,14 +441,22 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
 
       {run.phase === "canceled" && (
         <div className="flex items-start gap-2 rounded-lg bg-amber-500/10 p-3 text-sm text-amber-700 dark:text-amber-300">
-          <HugeiconsIcon icon={CancelCircleIcon} className="mt-0.5 size-4 shrink-0" />
-          <span>Export canceled. Training and inference were not affected.</span>
+          <HugeiconsIcon
+            icon={CancelCircleIcon}
+            className="mt-0.5 size-4 shrink-0"
+          />
+          <span>
+            Export canceled. Training and inference were not affected.
+          </span>
         </div>
       )}
 
       {run.phase === "error" && run.error && (
         <div className="flex items-start gap-2 rounded-lg bg-destructive/10 p-3 text-sm text-destructive">
-          <HugeiconsIcon icon={AlertCircleIcon} className="size-4 mt-0.5 shrink-0" />
+          <HugeiconsIcon
+            icon={AlertCircleIcon}
+            className="size-4 mt-0.5 shrink-0"
+          />
           <span>{run.error}</span>
         </div>
       )}
@@ -447,15 +465,21 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
       <div className="rounded-xl bg-muted/50 p-3 text-xs text-muted-foreground flex flex-col gap-1">
         <div className="flex justify-between">
           <span>Base Model</span>
-          <span className="font-medium text-foreground">{summaryBaseModel}</span>
+          <span className="font-medium text-foreground">
+            {summaryBaseModel}
+          </span>
         </div>
         <div className="flex justify-between">
           <span>{isAdapter ? "Checkpoint" : "Model"}</span>
-          <span className="font-medium text-foreground">{summaryCheckpoint}</span>
+          <span className="font-medium text-foreground">
+            {summaryCheckpoint}
+          </span>
         </div>
         <div className="flex justify-between">
           <span>Export Method</span>
-          <span className="font-medium text-foreground">{summaryMethodLabel}</span>
+          <span className="font-medium text-foreground">
+            {summaryMethodLabel}
+          </span>
         </div>
         {summaryMethod === "merged" && summaryFormats.length > 0 && (
           <div className="flex justify-between gap-3">
@@ -479,18 +503,23 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
       {showProgress && (
         <div className="flex flex-col gap-2">
           <div className="flex flex-wrap items-center gap-2">
-            <span className="rounded-full bg-foreground/10 px-2.5 py-1 text-[10px] font-semibold">
+            <span className="rounded-full bg-foreground/10 px-2.5 py-1 text-ui-10 font-semibold">
               {PHASE_LABELS[run.phase] ?? run.phase}
             </span>
             {summaryMethod === "gguf" && run.quantTotal > 1 && (
-              <span className="text-[10px] tabular-nums text-muted-foreground">
-                Quant {Math.min(run.quantIndex + (isExporting ? 1 : 0), run.quantTotal)} of {run.quantTotal}
+              <span className="text-ui-10 tabular-nums text-muted-foreground">
+                Quant{" "}
+                {Math.min(
+                  run.quantIndex + (isExporting ? 1 : 0),
+                  run.quantTotal,
+                )}{" "}
+                of {run.quantTotal}
               </span>
             )}
-            <span className="rounded-full border border-border/60 px-2.5 py-1 text-[10px] font-medium tabular-nums text-muted-foreground">
+            <span className="rounded-full border border-border/60 px-2.5 py-1 text-ui-10 font-medium tabular-nums text-muted-foreground">
               {progress}%
             </span>
-            <span className="text-[10px] tabular-nums text-muted-foreground/70">
+            <span className="text-ui-10 tabular-nums text-muted-foreground/70">
               {formatElapsed(elapsedSeconds)}
             </span>
           </div>
@@ -506,7 +535,10 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
             }
           />
           {run.stage && (
-            <p className="truncate text-[11px] text-muted-foreground/80" title={run.stage}>
+            <p
+              className="truncate text-ui-11 text-muted-foreground/80"
+              title={run.stage}
+            >
               {run.stage}
             </p>
           )}
@@ -520,7 +552,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                 <label className="text-xs font-medium text-muted-foreground">
                   Export output
                 </label>
-                <div className="flex items-center gap-2 text-[11px] text-muted-foreground/80">
+                <div className="flex items-center gap-2 text-ui-11 text-muted-foreground/80">
                   <span
                     className={
                       run.reconnecting
@@ -544,7 +576,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
               <div
                 ref={logScrollRef}
                 onScroll={handleLogScroll}
-                className="h-56 w-full overflow-auto rounded-lg border border-border/40 bg-black/85 p-3 font-mono text-[11px] leading-[1.45] text-emerald-200/90"
+                className="h-56 w-full overflow-auto rounded-lg border border-border/40 bg-black/85 p-3 font-mono text-ui-11 leading-[1.45] text-emerald-200/90"
               >
                 {run.logLines.length === 0 ? (
                   <div className="flex h-full items-center justify-center text-muted-foreground/70">
@@ -556,10 +588,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                 ) : (
                   <div className="whitespace-pre-wrap break-words">
                     {run.logLines.map((entry, idx) => (
-                      <div
-                        key={idx}
-                        className={getExportLogLineClass(entry)}
-                      >
+                  <div key={idx} className={getExportLogLineClass(entry)}>
                         {formatLogLine(entry)}
                       </div>
                     ))}
diff --git a/studio/frontend/src/features/export/components/method-picker.tsx b/studio/frontend/src/features/export/components/method-picker.tsx
index 420a7f6146..0ab72b0b4a 100644
--- a/studio/frontend/src/features/export/components/method-picker.tsx
+++ b/studio/frontend/src/features/export/components/method-picker.tsx
@@ -123,7 +123,7 @@ export function MethodPicker({ value, onChange, disabledMethods = [], disabledRe
                   {m.badge && (
                     <Badge
                       variant="secondary"
-                      className="text-[10px] px-1.5 py-0"
+                      className="text-ui-10 px-1.5 py-0"
                     >
                       {m.badge}
                     </Badge>
diff --git a/studio/frontend/src/features/export/components/quant-picker.tsx b/studio/frontend/src/features/export/components/quant-picker.tsx
index 289f6498ce..b8c8e0fc77 100644
--- a/studio/frontend/src/features/export/components/quant-picker.tsx
+++ b/studio/frontend/src/features/export/components/quant-picker.tsx
@@ -61,7 +61,7 @@ export function QuantPicker({ value, onChange, sizes }: QuantPickerProps) {
             </a>
           </TooltipContent>
         </Tooltip>
-        <span className="text-[11px] text-muted-foreground/70">
+        <span className="text-ui-11 text-muted-foreground/70">
           — select one or more
         </span>
       </div>
@@ -90,10 +90,10 @@ export function QuantPicker({ value, onChange, sizes }: QuantPickerProps) {
               )}
               {q.label}
               {sizeLabel && (
-                <span className="text-[10px] opacity-60">{sizeLabel}</span>
+                <span className="text-ui-10 opacity-60">{sizeLabel}</span>
               )}
               {q.recommended && !active && (
-                <span className="rounded-full bg-emerald-100 px-1.5 py-0 text-[9px] font-semibold text-emerald-700 dark:bg-emerald-900 dark:text-emerald-300">
+                <span className="rounded-full bg-emerald-100 px-1.5 py-0 text-ui-9 font-semibold text-emerald-700 dark:bg-emerald-900 dark:text-emerald-300">
                   rec
                 </span>
               )}
@@ -103,13 +103,13 @@ export function QuantPicker({ value, onChange, sizes }: QuantPickerProps) {
       </div>
       {value.length > 0 && (
         <div className="flex items-center gap-3">
-          <span className="text-[11px] text-muted-foreground">
+          <span className="text-ui-11 text-muted-foreground">
             {value.length} selected
           </span>
           <button
             type="button"
             onClick={() => onChange([])}
-            className="text-[11px] text-muted-foreground/70 hover:text-foreground transition-colors"
+            className="text-ui-11 text-muted-foreground/70 hover:text-foreground transition-colors"
           >
             Clear all
           </button>
diff --git a/studio/frontend/src/features/export/export-navigation-cache.ts b/studio/frontend/src/features/export/export-navigation-cache.ts
new file mode 100644
index 0000000000..f026f64525
--- /dev/null
+++ b/studio/frontend/src/features/export/export-navigation-cache.ts
@@ -0,0 +1,61 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { type LocalModelInfo, listLocalModels } from "@/features/training";
+import { type ModelCheckpoints, fetchCheckpoints } from "./api/export-api";
+
+let cachedCheckpoints: ModelCheckpoints[] | null = null;
+let checkpointsRequest: Promise<ModelCheckpoints[]> | null = null;
+let cachedLocalModels: LocalModelInfo[] | null = null;
+let localModelsRequest: Promise<LocalModelInfo[]> | null = null;
+
+export function getCachedCheckpoints(): ModelCheckpoints[] | null {
+  return cachedCheckpoints;
+}
+
+export function getCachedLocalModels(): LocalModelInfo[] | null {
+  return cachedLocalModels;
+}
+
+export function refreshCheckpoints(): Promise<ModelCheckpoints[]> {
+  if (checkpointsRequest) {
+    return checkpointsRequest;
+  }
+  const request = fetchCheckpoints()
+    .then((data) => {
+      cachedCheckpoints = data.models;
+      return data.models;
+    })
+    .finally(() => {
+      checkpointsRequest = null;
+    });
+  checkpointsRequest = request;
+  return request;
+}
+
+export function refreshLocalModels(): Promise<LocalModelInfo[]> {
+  if (localModelsRequest) {
+    return localModelsRequest;
+  }
+  const request = listLocalModels()
+    .then((models) => {
+      cachedLocalModels = models;
+      return models;
+    })
+    .finally(() => {
+      localModelsRequest = null;
+    });
+  localModelsRequest = request;
+  return request;
+}
+
+export async function preloadExportData(): Promise<void> {
+  const requests: Promise<unknown>[] = [];
+  if (cachedCheckpoints === null) {
+    requests.push(refreshCheckpoints());
+  }
+  if (cachedLocalModels === null) {
+    requests.push(refreshLocalModels());
+  }
+  await Promise.allSettled(requests);
+}
diff --git a/studio/frontend/src/features/export/export-page.tsx b/studio/frontend/src/features/export/export-page.tsx
index 51e9f209dd..fc30555253 100644
--- a/studio/frontend/src/features/export/export-page.tsx
+++ b/studio/frontend/src/features/export/export-page.tsx
@@ -48,7 +48,6 @@ import { prepareHfTokenForUse } from "@/features/hf-auth";
 import { GuidedTour, useGuidedTourController } from "@/features/tour";
 import {
   type LocalModelInfo,
-  listLocalModels,
   useTrainingConfigStore,
 } from "@/features/training";
 import { useDebouncedValue, useHfTokenValidation } from "@/hooks";
@@ -67,7 +66,6 @@ import { useSearch } from "@tanstack/react-router";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { useShallow } from "zustand/react/shallow";
 import type { ModelCheckpoints } from "./api/export-api";
-import { fetchCheckpoints } from "./api/export-api";
 import { ExportRunPanel } from "./components/export-run-panel";
 import { MethodPicker } from "./components/method-picker";
 import { QuantPicker } from "./components/quant-picker";
@@ -83,6 +81,12 @@ import {
   mergedFormatPayload,
 } from "./constants";
 import { useExportSizeEstimate } from "./hooks/use-export-size-estimate";
+import {
+  getCachedCheckpoints,
+  getCachedLocalModels,
+  refreshCheckpoints,
+  refreshLocalModels,
+} from "./export-navigation-cache";
 import {
   isExportPanelActive,
   useExportRuntimeStore,
@@ -172,8 +176,12 @@ export function ExportPage() {
   );
 
   // ---- API-driven checkpoint state ----
-  const [models, setModels] = useState<ModelCheckpoints[]>([]);
-  const [loadingCheckpoints, setLoadingCheckpoints] = useState(true);
+  const [models, setModels] = useState<ModelCheckpoints[]>(
+    () => getCachedCheckpoints() ?? [],
+  );
+  const [loadingCheckpoints, setLoadingCheckpoints] = useState(
+    getCachedCheckpoints() === null,
+  );
   const [checkpointError, setCheckpointError] = useState<string | null>(null);
 
   const [selectedModelIdx, setSelectedModelIdx] = useState<string | null>(null);
@@ -185,8 +193,12 @@ export function ExportPage() {
     null,
   );
   const [localModelInput, setLocalModelInput] = useState("");
-  const [localModels, setLocalModels] = useState<LocalModelInfo[]>([]);
-  const [isLoadingLocalModels, setIsLoadingLocalModels] = useState(true);
+  const [localModels, setLocalModels] = useState<LocalModelInfo[]>(
+    () => getCachedLocalModels() ?? [],
+  );
+  const [isLoadingLocalModels, setIsLoadingLocalModels] = useState(
+    getCachedLocalModels() === null,
+  );
   const [localModelsError, setLocalModelsError] = useState<string | null>(null);
   const debouncedModelQuery = useDebouncedValue(modelInput);
   const debouncedHfToken = useDebouncedValue(hfToken, 500);
@@ -295,16 +307,15 @@ export function ExportPage() {
   // ---- Fetch checkpoints on mount ----
   useEffect(() => {
     let cancelled = false;
-    setLoadingCheckpoints(true);
-    setCheckpointError(null);
-    fetchCheckpoints()
-      .then((data) => {
+    const hadCache = getCachedCheckpoints() !== null;
+    refreshCheckpoints()
+      .then((models) => {
         if (!cancelled) {
-          setModels(data.models);
+          setModels(models);
         }
       })
       .catch((err) => {
-        if (!cancelled) {
+        if (!cancelled && !hadCache) {
           setCheckpointError(
             err instanceof Error ? err.message : "Failed to load checkpoints",
           );
@@ -343,14 +354,15 @@ export function ExportPage() {
 
   // ---- Fetch local models for direct export ----
   useEffect(() => {
-    const controller = new AbortController();
-    void listLocalModels(controller.signal)
+    let cancelled = false;
+    const hadCache = getCachedLocalModels() !== null;
+    void refreshLocalModels()
       .then((models) => {
-        if (controller.signal.aborted) return;
+        if (cancelled) return;
         setLocalModels(models);
       })
       .catch((error) => {
-        if (controller.signal.aborted) return;
+        if (cancelled || hadCache) return;
         setLocalModelsError(
           error instanceof Error
             ? error.message
@@ -358,10 +370,12 @@ export function ExportPage() {
         );
       })
       .finally(() => {
-        if (controller.signal.aborted) return;
+        if (cancelled) return;
         setIsLoadingLocalModels(false);
       });
-    return () => controller.abort();
+    return () => {
+      cancelled = true;
+    };
   }, []);
 
   // ---- Derived state ----
@@ -881,7 +895,7 @@ export function ExportPage() {
         <GuidedTour {...tour.tourProps} />
 
         <div className="mb-8 flex flex-col gap-0.5">
-          <h1 className="text-[30px] font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-[34px]">
+          <h1 className="text-ui-30 font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-ui-34">
             Export Model
           </h1>
           <p className="text-sm text-muted-foreground">
@@ -950,21 +964,21 @@ export function ExportPage() {
                         <TabsTrigger
                           value="local"
                           indicatorClassName="hub-tab-toggle-pill rounded-full"
-                          className="h-9 rounded-full border-0 px-3 text-[12.5px] text-muted-foreground hover:text-foreground data-active:text-foreground data-[state=active]:text-foreground"
+                          className="h-9 rounded-full border-0 px-3 text-ui-12p5 text-muted-foreground hover:text-foreground data-active:text-foreground data-[state=active]:text-foreground"
                         >
                           Local Model
                         </TabsTrigger>
                         <TabsTrigger
                           value="checkpoint"
                           indicatorClassName="hub-tab-toggle-pill rounded-full"
-                          className="h-9 rounded-full border-0 px-3 text-[12.5px] text-muted-foreground hover:text-foreground data-active:text-foreground data-[state=active]:text-foreground"
+                          className="h-9 rounded-full border-0 px-3 text-ui-12p5 text-muted-foreground hover:text-foreground data-active:text-foreground data-[state=active]:text-foreground"
                         >
                           Fine-tuned
                         </TabsTrigger>
                         <TabsTrigger
                           value="hf"
                           indicatorClassName="hub-tab-toggle-pill rounded-full"
-                          className="h-9 rounded-full border-0 px-3 text-[12.5px] text-muted-foreground hover:text-foreground data-active:text-foreground data-[state=active]:text-foreground"
+                          className="h-9 rounded-full border-0 px-3 text-ui-12p5 text-muted-foreground hover:text-foreground data-active:text-foreground data-[state=active]:text-foreground"
                         >
                           Hugging Face
                         </TabsTrigger>
@@ -1275,7 +1289,7 @@ export function ExportPage() {
                                         <span className="block min-w-0 flex-1 truncate">
                                           {model?.display_name ?? id}
                                         </span>
-                                        <span className="ml-auto shrink-0 text-[10px] text-muted-foreground">
+                                        <span className="ml-auto shrink-0 text-ui-10 text-muted-foreground">
                                           {source}
                                         </span>
                                       </ComboboxItem>
@@ -1286,15 +1300,15 @@ export function ExportPage() {
                             </Combobox>
                           </div>
                           {isLoadingLocalModels ? (
-                            <p className="text-[10px] text-muted-foreground">
+                            <p className="text-ui-10 text-muted-foreground">
                               Scanning local models...
                             </p>
                           ) : localModelsError ? (
-                            <p className="text-[10px] text-red-500">
+                            <p className="text-ui-10 text-red-500">
                               {localModelsError}
                             </p>
                           ) : (
-                            <p className="text-[10px] text-muted-foreground">
+                            <p className="text-ui-10 text-muted-foreground">
                               {exportableLocalModels.length > 0
                                 ? `${exportableLocalModels.length} local/cached models found`
                                 : "No local models found. Enter path manually."}
@@ -1304,7 +1318,7 @@ export function ExportPage() {
                       )}
 
                       <div className="rounded-xl bg-foreground/[0.04] p-3">
-                        <p className="text-[11px] text-muted-foreground">
+                        <p className="text-ui-11 text-muted-foreground">
                           Direct model exports currently support GGUF only.
                         </p>
                       </div>
@@ -1313,7 +1327,7 @@ export function ExportPage() {
 
                   {sourceMode === "checkpoint" && (
                     <div className="rounded-xl bg-foreground/[0.04] p-3 flex flex-col gap-2">
-                      <span className="text-[11px] font-medium text-muted-foreground uppercase tracking-wider">
+                      <span className="text-ui-11 font-medium text-muted-foreground uppercase tracking-wider">
                         Training Info
                       </span>
                       <div className="grid grid-cols-1 gap-x-6 gap-y-1.5 text-xs sm:grid-cols-2">
@@ -1360,7 +1374,7 @@ export function ExportPage() {
                         key={step}
                         className="flex items-start gap-2 text-xs text-muted-foreground"
                       >
-                        <span className="flex size-5 shrink-0 items-center justify-center rounded-full bg-foreground/10 text-[10px] font-semibold">
+                        <span className="flex size-5 shrink-0 items-center justify-center rounded-full bg-foreground/10 text-ui-10 font-semibold">
                           {i + 1}
                         </span>
                         {step}
@@ -1408,7 +1422,7 @@ export function ExportPage() {
                   <div className="space-y-2">
                     <div className="flex items-center justify-between">
                       <div className="text-sm font-medium">Precision</div>
-                      <span className="text-[11px] text-muted-foreground/70">
+                      <span className="text-ui-11 text-muted-foreground/70">
                         — select one or more
                       </span>
                     </div>
@@ -1465,7 +1479,7 @@ export function ExportPage() {
                                       {f.label}
                                       {f.needsCalibration ? " *" : ""}
                                     </span>
-                                    <span className="text-[10px] text-muted-foreground">
+                                    <span className="text-ui-10 text-muted-foreground">
                                       {f.hint}
                                     </span>
                                   </span>
@@ -1478,7 +1492,7 @@ export function ExportPage() {
 
                     {selectedFormats.length > 0 && (
                       <div className="flex flex-wrap items-center gap-x-3 gap-y-1">
-                        <span className="text-[11px] text-muted-foreground">
+                        <span className="text-ui-11 text-muted-foreground">
                           {selectedFormats.length} selected:{" "}
                           {selectedFormats
                             .map(
@@ -1492,7 +1506,7 @@ export function ExportPage() {
                           <button
                             type="button"
                             onClick={() => setSelectedFormats(["16-bit"])}
-                            className="text-[11px] text-muted-foreground/70 hover:text-foreground transition-colors"
+                            className="text-ui-11 text-muted-foreground/70 hover:text-foreground transition-colors"
                           >
                             Reset to 16-bit
                           </button>
@@ -1501,7 +1515,7 @@ export function ExportPage() {
                     )}
 
                     {hubMultiFormat && (
-                      <div className="text-[11px] text-amber-600 dark:text-amber-500">
+                      <div className="text-ui-11 text-amber-600 dark:text-amber-500">
                         Hub export supports one format at a time (each writes to
                         the repository root). Select a single format, or export
                         locally to produce several at once.
@@ -1513,13 +1527,13 @@ export function ExportPage() {
                         MERGED_FORMATS.find((f) => f.value === v)
                           ?.needsCalibration,
                     ) && (
-                      <div className="text-[11px] text-muted-foreground">
+                      <div className="text-ui-11 text-muted-foreground">
                         * calibrates on data (uses a small calibration set).
                       </div>
                     )}
 
                     {!hasNvidia && (
-                      <div className="text-[11px] text-muted-foreground">
+                      <div className="text-ui-11 text-muted-foreground">
                         No NVIDIA GPU detected: compressed-tensors formats are
                         hidden. 16-bit and portable FP8/INT8 (torchao) still
                         work here and load in vLLM.
diff --git a/studio/frontend/src/features/hub/catalog/catalog-states.tsx b/studio/frontend/src/features/hub/catalog/catalog-states.tsx
index 1d9eb63718..513f1c21c8 100644
--- a/studio/frontend/src/features/hub/catalog/catalog-states.tsx
+++ b/studio/frontend/src/features/hub/catalog/catalog-states.tsx
@@ -10,6 +10,7 @@ import {
 } from "@hugeicons/core-free-icons";
 import type { IconSvgElement } from "@hugeicons/react";
 import { HugeiconsIcon } from "@hugeicons/react";
+import type { ReactNode } from "react";
 import { useLayoutEffect, useRef, useState } from "react";
 
 export function NetworkErrorState({
@@ -37,20 +38,20 @@ export function NetworkErrorState({
         <HugeiconsIcon icon={icon} strokeWidth={1.6} className="size-5" />
       </div>
       <div className="space-y-1">
-        <p className="text-[14px] font-semibold tracking-tight text-foreground">
+        <p className="text-ui-14 font-semibold tracking-tight text-foreground">
           {title}
         </p>
-        <p className="max-w-md text-[12.5px] leading-5 text-muted-foreground">
+        <p className="max-w-md text-ui-12p5 leading-5 text-muted-foreground">
           {body}
         </p>
-        <p className="text-[11px] text-muted-foreground/70">{message}</p>
+        <p className="text-ui-11 text-muted-foreground/70">{message}</p>
       </div>
       <div className="flex flex-wrap items-center justify-center gap-2">
         {onSwitchDevice ? (
           <button
             type="button"
             onClick={onSwitchDevice}
-            className="inline-flex h-8 items-center gap-1.5 rounded-full bg-foreground/[0.06] px-3 text-[12px] font-medium text-foreground transition-colors hover:bg-foreground/[0.1] dark:bg-white/[0.06] dark:hover:bg-white/[0.1]"
+            className="inline-flex h-8 items-center gap-1.5 rounded-full bg-foreground/[0.06] px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.1] dark:bg-white/[0.06] dark:hover:bg-white/[0.1]"
           >
             On Device
           </button>
@@ -58,7 +59,7 @@ export function NetworkErrorState({
         <button
           type="button"
           onClick={onRetry}
-          className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-[12px] font-medium text-foreground transition-colors hover:bg-foreground/[0.04] dark:hover:bg-white/[0.05]"
+          className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.04] dark:hover:bg-white/[0.05]"
         >
           <HugeiconsIcon
             icon={Refresh01Icon}
@@ -91,10 +92,10 @@ export function DiscoverFetchMoreState({
         <HugeiconsIcon icon={FilterIcon} strokeWidth={1.5} className="size-5" />
       </div>
       <div className="space-y-1">
-        <p className="text-[14px] font-semibold tracking-tight text-foreground">
+        <p className="text-ui-14 font-semibold tracking-tight text-foreground">
           No matches yet
         </p>
-        <p className="max-w-md text-[12.5px] leading-5 text-muted-foreground">
+        <p className="max-w-md text-ui-12p5 leading-5 text-muted-foreground">
           Scanned {scannedCount.toLocaleString()} results. Load another page to
           keep searching Hugging Face.
         </p>
@@ -104,7 +105,7 @@ export function DiscoverFetchMoreState({
           <button
             type="button"
             onClick={onClearFilters}
-            className="inline-flex h-8 items-center gap-1.5 rounded-full bg-foreground/[0.06] px-3 text-[12px] font-medium text-foreground transition-colors hover:bg-foreground/[0.1] dark:bg-white/[0.06] dark:hover:bg-white/[0.1]"
+            className="inline-flex h-8 items-center gap-1.5 rounded-full bg-foreground/[0.06] px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.1] dark:bg-white/[0.06] dark:hover:bg-white/[0.1]"
           >
             Clear filters
           </button>
@@ -113,7 +114,7 @@ export function DiscoverFetchMoreState({
           type="button"
           onClick={onFetchMore}
           disabled={isLoadingMore}
-          className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-[12px] font-medium text-foreground transition-colors hover:bg-foreground/[0.04] disabled:cursor-not-allowed disabled:opacity-50 dark:hover:bg-white/[0.05]"
+          className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.04] disabled:cursor-not-allowed disabled:opacity-50 dark:hover:bg-white/[0.05]"
         >
           <HugeiconsIcon
             icon={Refresh01Icon}
@@ -140,7 +141,7 @@ export function DiscoverFetchMoreFooter({
     <div className="relative z-10 flex flex-col items-center gap-2 rounded-[16px] bg-card px-4 py-4 text-center">
       {/* Only warn about hidden results when a filter is actually narrowing them. */}
       {hasActiveFilters && (
-        <p className="text-[11.5px] leading-4 text-muted-foreground">
+        <p className="text-ui-11p5 leading-4 text-muted-foreground">
           Some results may be hidden by your filters.
         </p>
       )}
@@ -148,7 +149,7 @@ export function DiscoverFetchMoreFooter({
         type="button"
         onClick={onFetchMore}
         disabled={isLoadingMore}
-        className="inline-flex h-8 items-center gap-1.5 rounded-full bg-foreground/[0.06] px-3 text-[12px] font-medium text-foreground transition-colors hover:bg-foreground/[0.1] disabled:cursor-not-allowed disabled:opacity-50 dark:bg-white/[0.06] dark:hover:bg-white/[0.1]"
+        className="inline-flex h-8 items-center gap-1.5 rounded-full bg-foreground/[0.06] px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.1] disabled:cursor-not-allowed disabled:opacity-50 dark:bg-white/[0.06] dark:hover:bg-white/[0.1]"
       >
         <HugeiconsIcon
           icon={Refresh01Icon}
@@ -174,10 +175,10 @@ export function InventoryErrorState({
         <HugeiconsIcon icon={CloudOffIcon} strokeWidth={1.6} className="size-5" />
       </div>
       <div className="space-y-1">
-        <p className="text-[14px] font-semibold tracking-tight text-foreground">
+        <p className="text-ui-14 font-semibold tracking-tight text-foreground">
           Couldn't load your library
         </p>
-        <p className="max-w-md text-[12.5px] leading-5 text-muted-foreground">
+        <p className="max-w-md text-ui-12p5 leading-5 text-muted-foreground">
           Something went wrong reading your downloaded{" "}
           {isDataset ? "datasets" : "models"}. Check that the backend is running
           and try again.
@@ -186,7 +187,7 @@ export function InventoryErrorState({
       <button
         type="button"
         onClick={onRetry}
-        className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-[12px] font-medium text-foreground transition-colors hover:bg-foreground/[0.04] dark:hover:bg-white/[0.05]"
+        className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.04] dark:hover:bg-white/[0.05]"
       >
         <HugeiconsIcon icon={Refresh01Icon} strokeWidth={1.75} className="size-3.5" />
         Try again
@@ -199,10 +200,12 @@ export function EmptyState({
   title,
   body,
   icon = CubeIcon,
+  action,
 }: {
   title: string;
   body: string;
   icon?: IconSvgElement;
+  action?: ReactNode;
 }) {
   return (
     <div className="flex min-h-[220px] flex-col items-center justify-center gap-3 px-6 text-center">
@@ -210,13 +213,14 @@ export function EmptyState({
         <HugeiconsIcon icon={icon} strokeWidth={1.5} className="size-5" />
       </div>
       <div className="space-y-1">
-        <p className="text-[14px] font-semibold tracking-tight text-foreground">
+        <p className="text-ui-14 font-semibold tracking-tight text-foreground">
           {title}
         </p>
-        <p className="max-w-md text-[12.5px] leading-5 text-muted-foreground">
+        <p className="max-w-md text-ui-12p5 leading-5 text-muted-foreground">
           {body}
         </p>
       </div>
+      {action}
     </div>
   );
 }
diff --git a/studio/frontend/src/features/hub/catalog/dataset-download-section.tsx b/studio/frontend/src/features/hub/catalog/dataset-download-section.tsx
index d407517663..4a3e3f9ff6 100644
--- a/studio/frontend/src/features/hub/catalog/dataset-download-section.tsx
+++ b/studio/frontend/src/features/hub/catalog/dataset-download-section.tsx
@@ -50,7 +50,7 @@ export function DatasetDownloadSection({
   const hfToken = useHfTokenStore((s) => s.token);
   const [deleteOpen, setDeleteOpen] = useState(false);
   const { deleting, runDelete } = useCardDelete({
-    action: () => deleteCachedDataset(repoId),
+    action: () => deleteCachedDataset(repoId, cachePath ?? undefined),
     resourceName: "dataset",
     successMessage: () => `Deleted ${repoId}`,
     onSuccess: () => {
@@ -126,7 +126,7 @@ export function DatasetDownloadSection({
       }
     >
       <div className="relative flex h-9 min-w-0 flex-1 items-center pl-3 pr-2">
-        <span className="flex items-center gap-1.5 text-[12px] text-muted-foreground">
+        <span className="flex items-center gap-1.5 text-ui-12 text-muted-foreground">
           {isDownloaded && <DotTag tone="success" label="On device" />}
           {!isDownloaded && isPartial && !downloading && (
             <Tooltip>
@@ -152,11 +152,7 @@ export function DatasetDownloadSection({
             />
           )}
           {isDownloaded && cachePath && (
-            <PathInfoButton
-              path={cachePath}
-              title="On-device location"
-              description={`Where ${repoId} lives on disk.`}
-            />
+            <PathInfoButton path={cachePath} />
           )}
         </div>
       </div>
diff --git a/studio/frontend/src/features/hub/catalog/dot-tag.tsx b/studio/frontend/src/features/hub/catalog/dot-tag.tsx
index 9452a201d4..5c2a0c8d1a 100644
--- a/studio/frontend/src/features/hub/catalog/dot-tag.tsx
+++ b/studio/frontend/src/features/hub/catalog/dot-tag.tsx
@@ -36,7 +36,7 @@ export function DotTag({
   return (
     <span
       className={cn(
-        "inline-flex h-5 shrink-0 items-center gap-1.5 whitespace-nowrap rounded-full border border-border/60 bg-transparent px-2 text-[11px] font-medium leading-none text-muted-foreground",
+        "inline-flex h-5 shrink-0 items-center gap-1.5 whitespace-nowrap rounded-full border border-border/60 bg-transparent px-2 text-ui-11 font-medium leading-none text-muted-foreground",
         className,
       )}
     >
diff --git a/studio/frontend/src/features/hub/catalog/download-card.tsx b/studio/frontend/src/features/hub/catalog/download-card.tsx
index 9b4bc5fd01..8016a9406d 100644
--- a/studio/frontend/src/features/hub/catalog/download-card.tsx
+++ b/studio/frontend/src/features/hub/catalog/download-card.tsx
@@ -140,7 +140,7 @@ export function CardUpdateButton({
               e.stopPropagation();
               onClick();
             }}
-            className="inline-flex h-7 shrink-0 cursor-pointer items-center gap-1.5 rounded-full bg-amber-500/[0.07] pl-2 pr-2.5 text-[12px] font-medium text-amber-800/90 transition-colors duration-150 hover:bg-amber-500/[0.12] focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-amber-500/25 dark:bg-amber-400/[0.08] dark:text-amber-200/85 dark:hover:bg-amber-400/[0.16]"
+            className="inline-flex h-7 shrink-0 cursor-pointer items-center gap-1.5 rounded-full bg-amber-500/[0.07] pl-2 pr-2.5 text-ui-12 font-medium text-amber-800/90 transition-colors duration-150 hover:bg-amber-500/[0.12] focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-amber-500/25 dark:bg-amber-400/[0.08] dark:text-amber-200/85 dark:hover:bg-amber-400/[0.16]"
           >
             <HugeiconsIcon
               icon={ArrowReloadHorizontalIcon}
diff --git a/studio/frontend/src/features/hub/catalog/download-section.tsx b/studio/frontend/src/features/hub/catalog/download-section.tsx
index fb2921649b..b2dd4592a1 100644
--- a/studio/frontend/src/features/hub/catalog/download-section.tsx
+++ b/studio/frontend/src/features/hub/catalog/download-section.tsx
@@ -1,9 +1,9 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import type { ModelInventoryFormat } from "../inventory";
 import { GgufDownloadCard } from "./gguf-download-card";
 import { SafetensorsDownloadCard } from "./safetensors-download-card";
-import type { ModelInventoryFormat } from "../inventory";
 
 export function DownloadSection({
   repoId,
@@ -22,6 +22,7 @@ export function DownloadSection({
   knownBytes,
   onLoad,
   onUseInChat,
+  onEject,
   onTrain,
   onChange,
 }: {
@@ -41,6 +42,7 @@ export function DownloadSection({
   knownBytes?: number | null;
   onLoad: (opts: { ggufVariant?: string; expectedBytes?: number }) => void;
   onUseInChat?: () => void;
+  onEject?: () => void;
   onTrain?: () => void;
   onChange?: () => void;
 }) {
@@ -57,6 +59,7 @@ export function DownloadSection({
         isPartial={isPartial}
         onLoad={onLoad}
         onUseInChat={onUseInChat}
+        onEject={onEject}
         onChange={onChange}
       />
     );
@@ -75,6 +78,7 @@ export function DownloadSection({
       knownBytes={knownBytes}
       onLoad={onLoad}
       onUseInChat={onUseInChat}
+      onEject={onEject}
       onTrain={onTrain}
       onChange={onChange}
     />
diff --git a/studio/frontend/src/features/hub/catalog/external-link-confirm-dialog.tsx b/studio/frontend/src/features/hub/catalog/external-link-confirm-dialog.tsx
index 5a661467fc..b17898a8e0 100644
--- a/studio/frontend/src/features/hub/catalog/external-link-confirm-dialog.tsx
+++ b/studio/frontend/src/features/hub/catalog/external-link-confirm-dialog.tsx
@@ -54,10 +54,10 @@ export function ExternalLinkConfirmDialog() {
         </AlertDialogHeader>
         {pendingUrl && (
           <div className="min-w-0 rounded-[12px] bg-muted/50 px-3 py-2.5 text-left">
-            <p className="truncate text-[13px] font-medium text-foreground">
+            <p className="truncate text-ui-13 font-medium text-foreground">
               {hostOf(pendingUrl)}
             </p>
-            <p className="mt-0.5 break-all text-[11.5px] leading-[16px] text-muted-foreground">
+            <p className="mt-0.5 break-all text-ui-11p5 leading-ui-16 text-muted-foreground">
               {pendingUrl}
             </p>
           </div>
diff --git a/studio/frontend/src/features/hub/catalog/gguf-download-card.tsx b/studio/frontend/src/features/hub/catalog/gguf-download-card.tsx
index f31212e4fd..870adcde11 100644
--- a/studio/frontend/src/features/hub/catalog/gguf-download-card.tsx
+++ b/studio/frontend/src/features/hub/catalog/gguf-download-card.tsx
@@ -1,6 +1,13 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuSeparator,
+  DropdownMenuTrigger,
+} from "@/components/ui/dropdown-menu";
 import {
   Popover,
   PopoverContent,
@@ -12,49 +19,55 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
-import {
-  downloadManager,
-  useDownloadManagerStore,
-  useRepoDownload,
-} from "../download-manager";
-import {
-  type GgufVariantDetail,
-  deleteCachedModel,
-} from "../inventory";
-import { formatBytes } from "../lib/format";
-import { type GgufFitClass, classifyGgufFit } from "../lib/gguf-fit";
-import { HUB_GGUF_RUN_ACTIONS_VISIBLE } from "../lib/hub-feature-flags";
-import {
-  ggufVariantsMatch,
-  normalizeGgufVariantIdentity,
-} from "../lib/model-identity";
+import { usePlatformStore } from "@/config/env";
+import { getCachedModelPath, revealCachedModel } from "@/features/chat";
+import { pinKey, usePinnedModelsStore } from "@/features/model-picker";
+import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { copyToClipboard } from "@/lib/copy-to-clipboard";
+import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
-import { useHfTokenStore } from "../stores/hf-token-store";
-import { useOnlineStatus } from "../hooks/use-online-status";
 import {
   ArrowReloadHorizontalIcon,
+  Copy01Icon,
   Delete02Icon,
   Download01Icon,
+  Folder01Icon,
   InformationCircleIcon,
-  PencilEdit02Icon,
+  MoreVerticalIcon,
+  PinIcon,
+  PinOffIcon,
   PlayIcon,
+  RemoveCircleIcon,
 } from "@hugeicons/core-free-icons";
-import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import {
+  type KeyboardEventHandler,
   memo,
   useCallback,
   useEffect,
   useMemo,
   useState,
-  type KeyboardEventHandler,
-  type MouseEventHandler,
 } from "react";
+import {
+  downloadManager,
+  useDownloadManagerStore,
+  useRepoDownload,
+} from "../download-manager";
+import { useOnlineStatus } from "../hooks/use-online-status";
+import { type GgufVariantDetail, deleteCachedModel } from "../inventory";
+import { formatBytes } from "../lib/format";
+import { type GgufFitClass, classifyGgufFit } from "../lib/gguf-fit";
 import {
   ggufVariantDisplayLabel,
   ggufVariantDownloadSizeBytes,
   sortDownloadableGgufVariants,
 } from "../lib/gguf-variant-sort";
+import { HUB_GGUF_RUN_ACTIONS_VISIBLE } from "../lib/hub-feature-flags";
+import {
+  ggufVariantsMatch,
+  normalizeGgufVariantIdentity,
+} from "../lib/model-identity";
+import { useHfTokenStore } from "../stores/hf-token-store";
 import { DotTag } from "./dot-tag";
 import { DownloadCancelIndicator } from "./download-cancel-indicator";
 import {
@@ -72,7 +85,6 @@ import {
   GgufDownloadStatusCard,
   GgufDownloadingFallbackCard,
 } from "./gguf-status-cards";
-import { PathInfoButton } from "./path-info-button";
 import { useDeleteConfirmAction } from "./use-delete-confirm-action";
 import { useDownloadCardState } from "./use-download-card-state";
 import { useGgufVariantFetchState } from "./use-gguf-variant-fetch-state";
@@ -116,7 +128,7 @@ const FIT_BADGE: Record<GgufFitClass, FitBadgeMeta> = {
 
 /** Chip styling matching the on-device list's StatChip, no icon. */
 const CHIP_BASE =
-  "inline-flex h-5 shrink-0 items-center justify-center whitespace-nowrap rounded-full border px-2 text-[11.5px] font-medium tabular-nums leading-3 shadow-[inset_0_1px_0_rgba(255,255,255,0.04)]";
+  "inline-flex h-5 shrink-0 items-center justify-center whitespace-nowrap rounded-full border px-2 text-ui-11p5 font-medium tabular-nums leading-3 shadow-[inset_0_1px_0_rgba(255,255,255,0.04)]";
 const CHIP_DEFAULT =
   "border-foreground/15 bg-muted text-foreground/85 dark:border-border/60 dark:bg-white/[0.04] dark:text-foreground/85";
 const CHIP_ACTIVE =
@@ -172,7 +184,7 @@ function QuantBadge({
       // group's `overflow-hidden` sacrifices the trailing status tags instead.
       <span
         className={cn(
-          "inline-flex shrink-0 cursor-help items-center gap-1.5 whitespace-nowrap text-[12.5px] font-medium tracking-tight tabular-nums",
+          "inline-flex shrink-0 cursor-help items-center gap-1.5 whitespace-nowrap text-ui-12p5 font-medium tracking-tight tabular-nums",
           active ? "text-control-accent" : "text-foreground",
         )}
       >
@@ -204,7 +216,7 @@ function QuantBadge({
       onOpenChange={tooltipMode === "lazy" ? setTooltipOpen : undefined}
     >
       <TooltipTrigger
-        asChild
+        asChild={true}
         onFocusCapture={tooltipMode === "lazy" ? armTooltip : undefined}
         onPointerEnter={tooltipMode === "lazy" ? armTooltip : undefined}
       >
@@ -245,7 +257,181 @@ function createGgufVariantMenuItems(
   }));
 }
 
+// Shared options menu: used on every variant row, the run bar, and the
+// single-model (non-GGUF) run bar. Omit `quant` for a repo-level model. The
+// identifier uses llama.cpp's repo:quant syntax so it pastes into `-hf`.
+export function QuantOptionsMenu({
+  repoId,
+  quant,
+  label,
+  downloaded,
+  canDelete,
+  onDelete,
+  showPin = true,
+  buttonClassName,
+  iconClassName,
+}: {
+  repoId: string;
+  quant?: string;
+  label: string;
+  downloaded: boolean;
+  canDelete: boolean;
+  onDelete: (quant?: string) => void;
+  // Hidden in the run bar; pinning belongs to the On Device list.
+  showPin?: boolean;
+  buttonClassName?: string;
+  iconClassName?: string;
+}) {
+  const pinnedKeys = usePinnedModelsStore((s) => s.pinned);
+  const togglePinned = usePinnedModelsStore((s) => s.togglePinned);
+  const pinned = pinnedKeys.includes(pinKey(repoId, quant));
+  const deviceType = usePlatformStore((s) => s.deviceType);
+  const revealLabel =
+    deviceType === "mac"
+      ? "Reveal in Finder"
+      : deviceType === "windows"
+        ? "Reveal in File Explorer"
+        : "Reveal in File Manager";
+  const handleCopyPath = useCallback(async () => {
+    try {
+      const { path } = await getCachedModelPath(repoId, quant);
+      if (await copyToClipboard(path)) {
+        toast.success("Copied path");
+      } else {
+        toast.error("Failed to copy");
+      }
+    } catch (err) {
+      toast.error(
+        err instanceof Error ? err.message : "Failed to resolve model path",
+      );
+    }
+  }, [repoId, quant]);
+  const handleCopyId = useCallback(async () => {
+    const id = quant ? `${repoId}:${quant}` : repoId;
+    if (await copyToClipboard(id)) {
+      toast.success("Copied identifier");
+    } else {
+      toast.error("Failed to copy");
+    }
+  }, [repoId, quant]);
+
+  return (
+    <DropdownMenu>
+      <DropdownMenuTrigger asChild={true}>
+        <button
+          type="button"
+          onClick={(e) => e.stopPropagation()}
+          aria-label={`More options for ${label}`}
+          className={cn(
+            "inline-flex size-6 shrink-0 cursor-pointer items-center justify-center rounded-full",
+            "text-muted-foreground transition-colors hover:bg-muted hover:text-foreground",
+            "data-[state=open]:bg-muted data-[state=open]:text-foreground",
+            buttonClassName,
+          )}
+        >
+          <HugeiconsIcon
+            icon={MoreVerticalIcon}
+            strokeWidth={1.75}
+            className={cn("size-3.5", iconClassName)}
+          />
+        </button>
+      </DropdownMenuTrigger>
+      <DropdownMenuContent
+        side="bottom"
+        align="end"
+        sideOffset={2}
+        className="unsloth-plus-menu menu-flat-destructive w-48"
+      >
+        {showPin && downloaded && (
+          <DropdownMenuItem
+            onSelect={(e) => {
+              e.stopPropagation();
+              togglePinned(repoId, quant);
+            }}
+          >
+            <HugeiconsIcon
+              icon={pinned ? PinOffIcon : PinIcon}
+              strokeWidth={1.75}
+              className="size-icon"
+            />
+            <span>{pinned ? "Unpin" : "Pin to top"}</span>
+          </DropdownMenuItem>
+        )}
+        {downloaded && (
+          <DropdownMenuItem
+            onSelect={(e) => {
+              e.stopPropagation();
+              revealCachedModel(repoId, quant).catch((err) => {
+                toast.error(
+                  err instanceof Error
+                    ? err.message
+                    : "Failed to open file manager",
+                );
+              });
+            }}
+          >
+            <HugeiconsIcon
+              icon={Folder01Icon}
+              strokeWidth={1.75}
+              className="size-icon"
+            />
+            <span>{revealLabel}</span>
+          </DropdownMenuItem>
+        )}
+        <DropdownMenuItem
+          onSelect={(e) => {
+            e.stopPropagation();
+            void handleCopyId();
+          }}
+        >
+          <HugeiconsIcon
+            icon={Copy01Icon}
+            strokeWidth={1.75}
+            className="size-icon"
+          />
+          <span>Copy identifier</span>
+        </DropdownMenuItem>
+        {downloaded && (
+          <DropdownMenuItem
+            onSelect={(e) => {
+              e.stopPropagation();
+              void handleCopyPath();
+            }}
+          >
+            <HugeiconsIcon
+              icon={Copy01Icon}
+              strokeWidth={1.75}
+              className="size-icon"
+            />
+            <span>Copy path</span>
+          </DropdownMenuItem>
+        )}
+        {canDelete && (
+          <>
+            <DropdownMenuSeparator />
+            <DropdownMenuItem
+              variant="destructive"
+              onSelect={(e) => {
+                e.stopPropagation();
+                onDelete(quant);
+              }}
+            >
+              <HugeiconsIcon
+                icon={Delete02Icon}
+                strokeWidth={1.75}
+                className="size-icon"
+              />
+              <span>Delete</span>
+            </DropdownMenuItem>
+          </>
+        )}
+      </DropdownMenuContent>
+    </DropdownMenu>
+  );
+}
+
 const GgufVariantMenuRow = memo(function GgufVariantMenuRow({
+  repoId,
   item,
   selected,
   loaded,
@@ -254,6 +440,7 @@ const GgufVariantMenuRow = memo(function GgufVariantMenuRow({
   onSelect,
   onDelete,
 }: {
+  repoId: string;
   item: GgufVariantMenuItem;
   selected: boolean;
   loaded: boolean;
@@ -275,13 +462,6 @@ const GgufVariantMenuRow = memo(function GgufVariantMenuRow({
     },
     [selectVariant],
   );
-  const handleDelete = useCallback<MouseEventHandler<HTMLButtonElement>>(
-    (e) => {
-      e.stopPropagation();
-      onDelete(item.quant);
-    },
-    [item.quant, onDelete],
-  );
   const canDelete = (item.downloaded || item.partial) && !loaded && !liveActive;
 
   return (
@@ -317,7 +497,7 @@ const GgufVariantMenuRow = memo(function GgufVariantMenuRow({
         )}
         {!item.downloaded && item.partial && (
           <Tooltip>
-            <TooltipTrigger asChild>
+            <TooltipTrigger asChild={true}>
               <span className="inline-flex">
                 <DotTag
                   tone="warning"
@@ -334,30 +514,23 @@ const GgufVariantMenuRow = memo(function GgufVariantMenuRow({
         )}
       </span>
       <span className="ml-auto flex shrink-0 items-center gap-1.5">
-        <span className="relative">
-          <span className={cn(CHIP_BASE, CHIP_DEFAULT)}>
-            {item.downloadSizeLabel}
-          </span>
-          {canDelete && (
-            <button
-              type="button"
-              onClick={handleDelete}
-              aria-label={`Delete ${item.label}${item.partial && !item.downloaded ? " (partial)" : ""}`}
-              className={cn(
-                "absolute inset-0 inline-flex cursor-pointer items-center justify-center rounded-full",
-                "bg-popover text-foreground/70 ring-1 ring-border transition-colors",
-                "opacity-0 group-hover:opacity-100 focus-visible:opacity-100",
-                "hover:text-destructive hover:ring-destructive/40",
-              )}
-            >
-              <HugeiconsIcon
-                icon={Delete02Icon}
-                strokeWidth={1.75}
-                className="size-3"
-              />
-            </button>
-          )}
+        <span className={cn(CHIP_BASE, CHIP_DEFAULT)}>
+          {item.downloadSizeLabel}
         </span>
+        {/* Options only apply to files on disk; placeholder keeps the size
+            chips column-aligned across rows. */}
+        {item.downloaded || item.partial ? (
+          <QuantOptionsMenu
+            repoId={repoId}
+            quant={item.quant}
+            label={item.label}
+            downloaded={Boolean(item.downloaded)}
+            canDelete={canDelete}
+            onDelete={(q) => q && onDelete(q)}
+          />
+        ) : (
+          <span aria-hidden={true} className="size-6 shrink-0" />
+        )}
       </span>
     </div>
   );
@@ -374,7 +547,7 @@ export function GgufDownloadCard({
   preferLocalCache = false,
   isPartial = false,
   onLoad,
-  onUseInChat,
+  onEject,
   onChange,
 }: {
   repoId: string;
@@ -387,7 +560,9 @@ export function GgufDownloadCard({
   preferLocalCache?: boolean;
   isPartial?: boolean;
   onLoad: (opts: { ggufVariant?: string; expectedBytes?: number }) => void;
+  /** Accepted for API parity; the run bar ejects instead of opening chat. */
   onUseInChat?: () => void;
+  onEject?: () => void;
   onChange?: () => void;
 }) {
   const hfToken = useHfTokenStore((s) => s.token);
@@ -422,7 +597,9 @@ export function GgufDownloadCard({
     () => createLiveGgufVariantStatesSelector(repoId),
     [repoId],
   );
-  const liveVariantStates = useDownloadManagerStore(selectLiveGgufVariantStates);
+  const liveVariantStates = useDownloadManagerStore(
+    selectLiveGgufVariantStates,
+  );
   const sortedVariants = useMemo(() => {
     if (!rawSortedVariants) return null;
     const withLive = applyLiveGgufVariantStates(
@@ -499,12 +676,7 @@ export function GgufDownloadCard({
     if (expectedBytes > progress.expectedBytes) {
       setExpectedBytes(expectedBytes, progress.variant);
     }
-  }, [
-    variants,
-    progress?.variant,
-    progress?.expectedBytes,
-    setExpectedBytes,
-  ]);
+  }, [variants, progress?.variant, progress?.expectedBytes, setExpectedBytes]);
 
   useEffect(() => {
     setCompletedVariantKeys(new Set<string>());
@@ -593,9 +765,15 @@ export function GgufDownloadCard({
   const { deleting, runDelete } = useDeleteConfirmAction({
     action: async () => {
       if (!deleteTarget) return;
-      await deleteCachedModel(repoId, deleteTarget, hfToken || undefined);
+      await deleteCachedModel(
+        repoId,
+        deleteTarget,
+        hfToken || undefined,
+        cachePath ?? undefined,
+      );
     },
-    successMessage: () => `Deleted ${repoId} ${deleteTargetLabel ?? deleteTarget}`,
+    successMessage: () =>
+      `Deleted ${repoId} ${deleteTargetLabel ?? deleteTarget}`,
     errorToast: (err) => ({
       title: err instanceof Error ? err.message : "Failed to delete",
     }),
@@ -654,7 +832,7 @@ export function GgufDownloadCard({
     return (
       <GgufDownloadStatusCard
         job={job}
-        loading
+        loading={true}
         message="Loading available quantizations…"
       />
     );
@@ -666,7 +844,7 @@ export function GgufDownloadCard({
         <GgufDownloadStatusCard
           job={job}
           tone="muted"
-          partial
+          partial={true}
           message="Partial download present. Couldn't load quantizations."
           actionLabel="Reload"
           onAction={() => void refresh()}
@@ -729,7 +907,7 @@ export function GgufDownloadCard({
         }
       >
         <Popover open={open} onOpenChange={setOpen}>
-          <PopoverTrigger asChild>
+          <PopoverTrigger asChild={true}>
             <button
               type="button"
               onClick={(e) => {
@@ -741,7 +919,7 @@ export function GgufDownloadCard({
               {/* Quant label + status tags travel together as one left-aligned
                   group so the fit-info icon never floats orphaned from its tags;
                   only the chevron pins right, the standard select affordance. */}
-              <span className="flex min-w-0 flex-1 items-center gap-2 overflow-hidden text-[12px] text-muted-foreground">
+              <span className="flex min-w-0 flex-1 items-center gap-2 overflow-hidden text-ui-12 text-muted-foreground">
                 {selected ? (
                   <QuantBadge
                     quant={selectedLabel ?? selected.quant}
@@ -750,7 +928,7 @@ export function GgufDownloadCard({
                     active={Boolean(selectedIsActive)}
                   />
                 ) : (
-                  <span className="text-[12.5px] text-muted-foreground">
+                  <span className="text-ui-12p5 text-muted-foreground">
                     Select quantization
                   </span>
                 )}
@@ -762,7 +940,7 @@ export function GgufDownloadCard({
                 )}
                 {selected && !selected.downloaded && selected.partial && (
                   <Tooltip>
-                    <TooltipTrigger asChild>
+                    <TooltipTrigger asChild={true}>
                       <span className="inline-flex">
                         <DotTag
                           tone="warning"
@@ -806,6 +984,7 @@ export function GgufDownloadCard({
                 return (
                   <GgufVariantMenuRow
                     key={item.filename}
+                    repoId={repoId}
                     item={item}
                     selected={item.key === selectedVariantKey}
                     loaded={isActive && item.key === activeVariantKey}
@@ -820,14 +999,29 @@ export function GgufDownloadCard({
           </PopoverContent>
         </Popover>
 
-        {selected?.downloaded && cachePath && (
-          <PathInfoButton
-            path={cachePath}
-            title="On-device location"
-            description={`Where ${repoId} (${selectedLabel}) lives on disk.`}
-            className="ml-0.5"
-          />
-        )}
+        {/* TODO: inference settings gear hidden for now, work on it in a future PR. */}
+        {/* Options only resolve managed HF-cache repos, so skip local paths;
+            they also only apply to quants actually on disk. */}
+        {selected &&
+          Boolean(selected.downloaded || selected.partial) &&
+          !/^([/\\~.]|[A-Za-z]:)/.test(repoId) && (
+            <QuantOptionsMenu
+              repoId={repoId}
+              quant={selected.quant}
+              label={`${repoId} ${selectedLabel}`}
+              downloaded={Boolean(selected.downloaded)}
+              canDelete={
+                Boolean(selected.downloaded || selected.partial) &&
+                !selectedIsActive &&
+                !downloadingThisVariant &&
+                !isLoadingThisModel
+              }
+              onDelete={(q) => q && handleDeleteVariant(q)}
+              showPin={false}
+              buttonClassName="ml-0.5 size-7"
+              iconClassName="size-4"
+            />
+          )}
 
         {!isGgufRunCta && <CardDivider />}
 
@@ -859,7 +1053,7 @@ export function GgufDownloadCard({
               return;
             }
             if (selectedIsActive) {
-              onUseInChat?.();
+              onEject?.();
               return;
             }
             if (!selected) return;
@@ -874,7 +1068,7 @@ export function GgufDownloadCard({
           }}
           aria-label={downloadAction.ariaLabel}
           className={cn(
-            isGgufRunCta ? "hub-run-action-btn w-28" : "hub-action-btn w-28",
+            isGgufRunCta ? "hub-run-action-btn w-24" : "hub-action-btn w-24",
             isGgufRunCta && "ml-2",
             ctaDisabled &&
               !selectedIsActive &&
@@ -917,8 +1111,8 @@ export function GgufDownloadCard({
             </span>
           ) : selectedIsActive ? (
             <>
-              <HugeiconsIcon icon={PencilEdit02Icon} strokeWidth={1.75} />
-              New Chat
+              <HugeiconsIcon icon={RemoveCircleIcon} strokeWidth={1.75} />
+              Eject
             </>
           ) : selected?.downloaded ? (
             <>
@@ -937,7 +1131,7 @@ export function GgufDownloadCard({
         <button
           type="button"
           onClick={() => void refresh()}
-          className="self-start px-1 text-[11px] text-status-warning underline-offset-2 transition-colors hover:underline"
+          className="self-start px-1 text-ui-11 text-status-warning underline-offset-2 transition-colors hover:underline"
         >
           Couldn't refresh quantizations. Retry
         </button>
diff --git a/studio/frontend/src/features/hub/catalog/gguf-status-cards.tsx b/studio/frontend/src/features/hub/catalog/gguf-status-cards.tsx
index 6cc764b876..f4f4fb27d2 100644
--- a/studio/frontend/src/features/hub/catalog/gguf-status-cards.tsx
+++ b/studio/frontend/src/features/hub/catalog/gguf-status-cards.tsx
@@ -34,7 +34,7 @@ export function GgufDownloadStatusCard({
         <div className="relative flex h-9 min-w-0 flex-1 items-center pl-3 pr-2">
           <span
             className={cn(
-              "flex min-w-0 items-center gap-2 text-[12.5px]",
+              "flex min-w-0 items-center gap-2 text-ui-12p5",
               tone === "danger" ? "text-destructive" : "text-muted-foreground",
             )}
           >
@@ -91,7 +91,7 @@ export function GgufDownloadingFallbackCard({
     <div className="flex w-full flex-col gap-2">
       <DownloadCard job={job} progress={progress}>
         <div className="relative flex h-9 min-w-0 flex-1 items-center pl-3 pr-2">
-          <span className="flex min-w-0 items-center gap-2 text-[12.5px] text-muted-foreground">
+          <span className="flex min-w-0 items-center gap-2 text-ui-12p5 text-muted-foreground">
             {progress.variant && <DotTag tone="gguf" label={progress.variant} />}
             <span className="truncate">Downloading…</span>
           </span>
diff --git a/studio/frontend/src/features/hub/catalog/hub-detail-view.tsx b/studio/frontend/src/features/hub/catalog/hub-detail-view.tsx
index d733049ec3..78e1d0a420 100644
--- a/studio/frontend/src/features/hub/catalog/hub-detail-view.tsx
+++ b/studio/frontend/src/features/hub/catalog/hub-detail-view.tsx
@@ -69,7 +69,7 @@ export function HubDetailView({
             <button
               type="button"
               onClick={onBack}
-              className="-ml-1.5 inline-flex h-8 cursor-pointer select-none items-center gap-1.5 rounded-full pl-1.5 pr-2.5 text-[12.5px] font-medium text-muted-foreground transition-colors hover:bg-foreground/[0.05] hover:text-foreground dark:hover:bg-white/[0.06]"
+              className="-ml-1.5 inline-flex h-8 cursor-pointer select-none items-center gap-1.5 rounded-full pl-1.5 pr-2.5 text-ui-12p5 font-medium text-muted-foreground transition-colors hover:bg-foreground/[0.05] hover:text-foreground dark:hover:bg-white/[0.06]"
             >
               <HugeiconsIcon
                 icon={ArrowLeft01Icon}
diff --git a/studio/frontend/src/features/hub/catalog/hub-option-menu.tsx b/studio/frontend/src/features/hub/catalog/hub-option-menu.tsx
index 38464d36e4..5a11c474d4 100644
--- a/studio/frontend/src/features/hub/catalog/hub-option-menu.tsx
+++ b/studio/frontend/src/features/hub/catalog/hub-option-menu.tsx
@@ -6,9 +6,9 @@ import {
   PopoverContent,
   PopoverTrigger,
 } from "@/components/ui/popover";
-import { cn } from "@/lib/utils";
-import { Tick02Icon } from "@/lib/tick-icon";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { Tick02Icon } from "@/lib/tick-icon";
+import { cn } from "@/lib/utils";
 import { HugeiconsIcon } from "@hugeicons/react";
 import {
   type KeyboardEvent,
@@ -71,7 +71,9 @@ export function HubOptionMenu<T extends string>({
       ? -1
       : Math.min(activeIndex, options.length - 1);
   const activeOptionId =
-    resolvedActiveIndex >= 0 ? `${idBase}-option-${resolvedActiveIndex}` : undefined;
+    resolvedActiveIndex >= 0
+      ? `${idBase}-option-${resolvedActiveIndex}`
+      : undefined;
 
   const activateIndex = useCallback((index: number) => {
     setActiveIndex((current) => (current === index ? current : index));
@@ -161,7 +163,7 @@ export function HubOptionMenu<T extends string>({
 
   return (
     <Popover open={open} onOpenChange={handleOpenChange}>
-      <PopoverTrigger asChild>
+      <PopoverTrigger asChild={true}>
         <button
           ref={triggerRef}
           type="button"
@@ -171,7 +173,7 @@ export function HubOptionMenu<T extends string>({
           aria-label={ariaLabel}
           title={title}
           className={cn(
-            "field-trigger hub-menu-trigger field-soft field-filter inline-flex h-9 shrink-0 cursor-pointer items-center justify-between gap-0.5 rounded-full pl-3 pr-2 text-[12.5px] transition-colors",
+            "field-trigger hub-menu-trigger field-soft field-filter inline-flex h-9 shrink-0 cursor-pointer items-center justify-between gap-2.5 rounded-full pl-3 pr-2.5 text-ui-12p5 transition-colors",
             "focus-visible:border-border focus-visible:ring-0 focus-visible:ring-offset-0",
             className,
           )}
@@ -183,7 +185,10 @@ export function HubOptionMenu<T extends string>({
           }}
         >
           <span className="min-w-0 flex-1 truncate text-left">
-            {triggerContent ?? selected?.triggerLabel ?? selected?.label ?? value}
+            {triggerContent ??
+              selected?.triggerLabel ??
+              selected?.label ??
+              value}
           </span>
           {showChevron && (
             <HugeiconsIcon
diff --git a/studio/frontend/src/features/hub/catalog/hub-section-row.tsx b/studio/frontend/src/features/hub/catalog/hub-section-row.tsx
index b51a6cc257..e580c17a73 100644
--- a/studio/frontend/src/features/hub/catalog/hub-section-row.tsx
+++ b/studio/frontend/src/features/hub/catalog/hub-section-row.tsx
@@ -58,7 +58,7 @@ export const HubSectionRow = memo(function HubSectionRow({
           type="button"
           onClick={onOpenList}
           aria-label={`See all ${title}`}
-          className="hub-section-title group/section -mx-1 inline-flex cursor-pointer items-center gap-1.5 rounded-md px-1 text-[18px] font-semibold tracking-[-0.02em] text-foreground outline-none focus-visible:ring-1 focus-visible:ring-ring"
+          className="hub-section-title group/section -mx-1 inline-flex cursor-pointer items-center gap-1.5 rounded-md px-1 text-ui-18 font-semibold tracking-[-0.02em] text-foreground outline-none focus-visible:ring-1 focus-visible:ring-ring"
         >
           {title}
           <HugeiconsIcon
diff --git a/studio/frontend/src/features/hub/catalog/local-dataset-card.tsx b/studio/frontend/src/features/hub/catalog/local-dataset-card.tsx
index ddda124745..a4e6e5c9f5 100644
--- a/studio/frontend/src/features/hub/catalog/local-dataset-card.tsx
+++ b/studio/frontend/src/features/hub/catalog/local-dataset-card.tsx
@@ -25,7 +25,7 @@ export function LocalDatasetCard({
     <div className="hub-download-card">
       <div className="group/dl flex items-center">
         <div className="relative flex h-9 min-w-0 flex-1 items-center pl-3 pr-2">
-          <span className="flex min-w-0 items-center gap-1.5 text-[12px] text-muted-foreground">
+          <span className="flex min-w-0 items-center gap-1.5 text-ui-12 text-muted-foreground">
             <DotTag tone="success" label="On device" />
             {source !== "hf_cache" && (
               <span className="truncate text-muted-foreground/85">
@@ -34,11 +34,7 @@ export function LocalDatasetCard({
             )}
           </span>
           <div className="ml-auto flex items-center gap-0.5">
-            <PathInfoButton
-              path={path}
-              title={sourceLabel}
-              description="Where this dataset lives on disk."
-            />
+            <PathInfoButton path={path} />
           </div>
         </div>
         {HUB_POST_DOWNLOAD_ACTIONS_VISIBLE && (
diff --git a/studio/frontend/src/features/hub/catalog/local-on-device-card.tsx b/studio/frontend/src/features/hub/catalog/local-on-device-card.tsx
index 3c020a7199..9b508a5413 100644
--- a/studio/frontend/src/features/hub/catalog/local-on-device-card.tsx
+++ b/studio/frontend/src/features/hub/catalog/local-on-device-card.tsx
@@ -1,12 +1,6 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { TrainIcon } from "../components/train-icon";
-import {
-  HUB_GGUF_RUN_ACTIONS_VISIBLE,
-  HUB_NON_GGUF_RUN_ACTIONS_VISIBLE,
-  HUB_POST_DOWNLOAD_ACTIONS_VISIBLE,
-} from "../lib/hub-feature-flags";
 import {
   Popover,
   PopoverContent,
@@ -18,37 +12,44 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { cn } from "@/lib/utils";
 import {
-  type BaseModelSource,
-  type LocalModelInfo,
-  type ModelInventoryFormat,
-  deleteCachedModel,
-} from "../inventory";
+  Alert02Icon,
+  CubeIcon,
+  PlayIcon,
+  RemoveCircleIcon,
+  Share05Icon,
+} from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { useCallback, useMemo, useState } from "react";
+import { TrainIcon } from "../components/train-icon";
 import {
   downloadManager,
   jobKeyOf,
   selectActiveJob,
   useDownloadManagerStore,
 } from "../download-manager";
-import { formatBytes } from "../lib/format";
-import { ggufVariantsMatch } from "../lib/model-identity";
-import { cn } from "@/lib/utils";
-import { confirmExternalLink } from "../stores/external-link-confirm";
-import { useHfTokenStore } from "../stores/hf-token-store";
+import { useOnlineStatus } from "../hooks/use-online-status";
 import {
-  Alert02Icon,
-  CubeIcon,
-  PencilEdit02Icon,
-  PlayIcon,
-  Share05Icon,
-} from "@hugeicons/core-free-icons";
-import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
-import { HugeiconsIcon } from "@hugeicons/react";
-import { useCallback, useMemo, useState } from "react";
+  type BaseModelSource,
+  type LocalModelInfo,
+  type ModelInventoryFormat,
+  deleteCachedModel,
+} from "../inventory";
+import { formatBytes } from "../lib/format";
 import {
   ggufVariantDisplayLabel,
   sortLocalGgufVariants,
 } from "../lib/gguf-variant-sort";
+import {
+  HUB_GGUF_RUN_ACTIONS_VISIBLE,
+  HUB_NON_GGUF_RUN_ACTIONS_VISIBLE,
+  HUB_POST_DOWNLOAD_ACTIONS_VISIBLE,
+} from "../lib/hub-feature-flags";
+import { ggufVariantsMatch } from "../lib/model-identity";
+import { confirmExternalLink } from "../stores/external-link-confirm";
+import { useHfTokenStore } from "../stores/hf-token-store";
 import { DotTag } from "./dot-tag";
 import {
   CardDeleteButton,
@@ -60,7 +61,6 @@ import { PathInfoButton } from "./path-info-button";
 import { TransportConflictDialog } from "./transport-conflict-dialog";
 import { useCardDelete } from "./use-card-delete";
 import { useGgufVariantFetchState } from "./use-gguf-variant-fetch-state";
-import { useOnlineStatus } from "../hooks/use-online-status";
 
 type LocalLoadOptions = {
   ggufVariant?: string;
@@ -91,7 +91,9 @@ interface LocalOnDeviceCardProps {
   systemRamGb?: number;
   unsupportedReason?: string | null;
   onLoad: (opts?: LocalLoadOptions) => void;
+  /** Accepted for API parity; the run bar ejects instead of opening chat. */
   onUseInChat: () => void;
+  onEject?: () => void;
   onTrain?: () => void;
   onChange?: () => void;
 }
@@ -136,22 +138,22 @@ function BaseModelReference({
       </div>
       <div className="min-w-0 flex-1">
         <div className="flex min-w-0 items-center gap-1.5">
-          <span className="shrink-0 text-[11px] font-medium text-muted-foreground">
+          <span className="shrink-0 text-ui-11 font-medium text-muted-foreground">
             {baseModelSourceLabel(baseModelSource)}
           </span>
-          <span className="truncate text-[12px] font-medium text-foreground">
+          <span className="truncate text-ui-12 font-medium text-foreground">
             {baseModel}
           </span>
         </div>
         {baseModelSummary && (
-          <p className="mt-0.5 truncate text-[11px] text-muted-foreground">
+          <p className="mt-0.5 truncate text-ui-11 text-muted-foreground">
             {baseModelSummary}
           </p>
         )}
       </div>
       {canOpenHub && (
         <Tooltip>
-          <TooltipTrigger asChild>
+          <TooltipTrigger asChild={true}>
             <a
               href={`https://huggingface.co/${baseModelHubId}`}
               target="_blank"
@@ -160,7 +162,11 @@ function BaseModelReference({
               className="inline-flex size-7 shrink-0 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-background hover:text-foreground"
               onClick={(event) => {
                 event.stopPropagation();
-                if (confirmExternalLink(`https://huggingface.co/${baseModelHubId}`)) {
+                if (
+                  confirmExternalLink(
+                    `https://huggingface.co/${baseModelHubId}`,
+                  )
+                ) {
                   event.preventDefault();
                 }
               }}
@@ -205,7 +211,7 @@ export function LocalOnDeviceCard({
   systemRamGb,
   unsupportedReason,
   onLoad,
-  onUseInChat,
+  onEject,
   onTrain,
   onChange,
 }: LocalOnDeviceCardProps) {
@@ -241,7 +247,10 @@ export function LocalOnDeviceCard({
   const { deleting, runDelete } = useCardDelete({
     action: async () => {
       if (!repoId) return;
-      await deleteCachedModel(repoId, undefined, hfToken || undefined);
+      // Delete is only offered for hf_cache rows (see canDelete), so `path` is
+      // the cache snapshot path: pass it so the delete targets the cache this
+      // card shows instead of falling back to the active cache.
+      await deleteCachedModel(repoId, undefined, hfToken || undefined, path);
     },
     resourceName: "model",
     successMessage: () => `Deleted ${repoId}`,
@@ -371,18 +380,20 @@ export function LocalOnDeviceCard({
   const handleConfirmUpdate = () => {
     if (!repoId || !updateTargetVariant) return;
     setUpdateOpen(false);
-    void downloadManager.requestStart({
-      kind: "model",
-      repoId,
-      variant: updateTargetVariant,
-      expectedBytes: updateExpectedBytes,
-    }).then((outcome) => {
-      if (outcome === "conflict") {
-        setUpdateConflictKey(jobKeyOf("model", repoId, updateTargetVariant));
-      }
-      void currentVariantState.refresh();
-      void remoteVariantState.refresh();
-    });
+    void downloadManager
+      .requestStart({
+        kind: "model",
+        repoId,
+        variant: updateTargetVariant,
+        expectedBytes: updateExpectedBytes,
+      })
+      .then((outcome) => {
+        if (outcome === "conflict") {
+          setUpdateConflictKey(jobKeyOf("model", repoId, updateTargetVariant));
+        }
+        void currentVariantState.refresh();
+        void remoteVariantState.refresh();
+      });
   };
   const selectedVariantIsActive =
     needsVariantSelection && selectedQuant
@@ -416,7 +427,7 @@ export function LocalOnDeviceCard({
   return (
     <div className="flex w-full flex-col gap-2">
       {showOldCacheHint && (
-        <div className="flex items-start gap-2 rounded-[12px] border border-amber-500/20 bg-amber-500/8 px-3 py-2 text-[12px] leading-5 text-amber-700 dark:text-amber-300">
+        <div className="flex items-start gap-2 rounded-[12px] border border-amber-500/20 bg-amber-500/8 px-3 py-2 text-ui-12 leading-5 text-amber-700 dark:text-amber-300">
           <HugeiconsIcon
             icon={Alert02Icon}
             strokeWidth={1.75}
@@ -428,10 +439,11 @@ export function LocalOnDeviceCard({
             can still keep it on disk, or delete it to free space.
           </span>
         </div>
-      )}<div className="hub-download-card">
+      )}
+      <div className="hub-download-card">
         <div className="group/dl flex items-center">
           <div className="relative flex h-9 min-w-0 flex-1 items-center pl-3 pr-2">
-            <span className="flex min-w-0 items-center gap-1.5 text-[12px] text-muted-foreground">
+            <span className="flex min-w-0 items-center gap-1.5 text-ui-12 text-muted-foreground">
               <DotTag
                 tone="success"
                 label={selectedVariantIsActive ? "Loaded" : "On device"}
@@ -443,7 +455,7 @@ export function LocalOnDeviceCard({
                     <button
                       type="button"
                       disabled={currentVariantState.loading}
-                      className="inline-flex h-6 max-w-[170px] shrink-0 cursor-pointer items-center gap-1.5 rounded-[8px] border border-format-gguf/35 px-2 font-mono text-[10.5px] leading-none text-format-gguf transition-colors hover:bg-format-gguf/8 disabled:cursor-not-allowed disabled:opacity-60"
+                      className="inline-flex h-6 max-w-[170px] shrink-0 cursor-pointer items-center gap-1.5 rounded-[8px] border border-format-gguf/35 px-2 font-mono text-ui-10p5 leading-none text-format-gguf transition-colors hover:bg-format-gguf/8 disabled:cursor-not-allowed disabled:opacity-60"
                     >
                       <span className="truncate">
                         {currentVariantState.loading
@@ -455,7 +467,7 @@ export function LocalOnDeviceCard({
                               : "Select"}
                       </span>
                       {selectedVariant && (
-                        <span className="shrink-0 font-sans text-[10px] text-muted-foreground tabular-nums">
+                        <span className="shrink-0 font-sans text-ui-10 text-muted-foreground tabular-nums">
                           {formatBytes(selectedVariant.size_bytes)}
                         </span>
                       )}
@@ -500,14 +512,14 @@ export function LocalOnDeviceCard({
                                 : "hover:bg-foreground/[0.05] dark:hover:bg-foreground/[0.06]",
                             )}
                           >
-                            <span className="min-w-0 flex-1 truncate font-mono text-[12px] text-format-gguf">
+                            <span className="min-w-0 flex-1 truncate font-mono text-ui-12 text-format-gguf">
                               {label}
                             </span>
                             <span className="flex shrink-0 items-center gap-1.5">
                               {isLoaded && (
                                 <DotTag tone="success" label="Loaded" />
                               )}
-                              <span className="text-[10px] text-muted-foreground tabular-nums">
+                              <span className="text-ui-10 text-muted-foreground tabular-nums">
                                 {formatBytes(variant.size_bytes)}
                               </span>
                             </span>
@@ -540,7 +552,7 @@ export function LocalOnDeviceCard({
               {canUpdate && (
                 <CardUpdateButton
                   label={`Update ${repoId}`}
-                  emphasized
+                  emphasized={true}
                   onClick={() => setUpdateOpen(true)}
                 />
               )}
@@ -550,11 +562,7 @@ export function LocalOnDeviceCard({
                   onClick={() => setDeleteOpen(true)}
                 />
               )}
-              <PathInfoButton
-                path={path}
-                title={sourceLabel}
-                description="Where this model lives on disk."
-              />
+              <PathInfoButton path={path} />
             </div>
           </div>
           {onTrain && HUB_POST_DOWNLOAD_ACTIONS_VISIBLE && (
@@ -585,7 +593,7 @@ export function LocalOnDeviceCard({
               onClick={() => {
                 if (!canRun) return;
                 if (selectedVariantIsActive) {
-                  onUseInChat();
+                  onEject?.();
                   return;
                 }
                 if (needsVariantSelection) {
@@ -615,24 +623,24 @@ export function LocalOnDeviceCard({
                 </>
               ) : selectedVariantIsActive ? (
                 <>
-                  <HugeiconsIcon icon={PencilEdit02Icon} strokeWidth={1.75} />
-                  Chat
+                  <HugeiconsIcon icon={RemoveCircleIcon} strokeWidth={1.75} />
+                  Eject
                 </>
               ) : variantActionPending ? (
                 <>
                   <Spinner />
                   Loading…
                 </>
-              ) : !canRun ? (
-                <>
-                  <HugeiconsIcon icon={Alert02Icon} strokeWidth={1.75} />
-                  No run
-                </>
-              ) : (
+              ) : canRun ? (
                 <>
                   <HugeiconsIcon icon={PlayIcon} strokeWidth={1.75} />
                   Run
                 </>
+              ) : (
+                <>
+                  <HugeiconsIcon icon={Alert02Icon} strokeWidth={1.75} />
+                  No run
+                </>
               )}
             </button>
           </div>
diff --git a/studio/frontend/src/features/hub/catalog/model-card.tsx b/studio/frontend/src/features/hub/catalog/model-card.tsx
index 370e5071f4..b042eb1ad0 100644
--- a/studio/frontend/src/features/hub/catalog/model-card.tsx
+++ b/studio/frontend/src/features/hub/catalog/model-card.tsx
@@ -283,14 +283,14 @@ export const ModelCard = memo(function ModelCard({
         <OwnerAvatar
           owner={row.owner}
           repoName={row.repo}
-          className="size-11 shrink-0 rounded-[14px] text-[17px] ring-1 ring-white/10"
+          className="size-11 shrink-0 rounded-[14px] text-ui-17 ring-1 ring-white/10"
           remote={false}
         />
         <div className="min-w-0 flex-1 space-y-0.5">
-          <p className="hub-trending-title line-clamp-2 text-[13.5px] font-semibold leading-[16px] text-foreground">
+          <p className="hub-trending-title line-clamp-2 text-ui-13p5 font-semibold leading-ui-16 text-foreground">
             {row.repo}
           </p>
-          <span className="hub-trending-owner flex min-w-0 items-center gap-1 text-[11.5px] leading-[15px] text-muted-foreground/80">
+          <span className="hub-trending-owner flex min-w-0 items-center gap-1 text-ui-11p5 leading-ui-15 text-muted-foreground/80">
             <span className="truncate">{row.owner}</span>
             {row.owner.toLowerCase() === "unsloth" && (
               <span
diff --git a/studio/frontend/src/features/hub/catalog/model-inspector.tsx b/studio/frontend/src/features/hub/catalog/model-inspector.tsx
index 5a6ae1615a..c304738ab1 100644
--- a/studio/frontend/src/features/hub/catalog/model-inspector.tsx
+++ b/studio/frontend/src/features/hub/catalog/model-inspector.tsx
@@ -17,9 +17,9 @@ import {
   formatRelativeShort,
   formatShortDate,
 } from "@/features/hub/lib/format";
-import { cn, formatCompact } from "@/lib/utils";
-import { confirmExternalLink } from "../stores/external-link-confirm";
 import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
+import { Tick02Icon } from "@/lib/tick-icon";
+import { cn, formatCompact } from "@/lib/utils";
 import {
   Calendar03Icon,
   CalendarAdd01Icon,
@@ -37,10 +37,10 @@ import {
   RamMemoryIcon,
   Share05Icon,
 } from "@hugeicons/core-free-icons";
-import { Tick02Icon } from "@/lib/tick-icon";
 import type { IconSvgElement } from "@hugeicons/react";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { memo, useDeferredValue, useMemo } from "react";
+import { selectActiveJob, useDownloadManagerStore } from "../download-manager";
 import { useCopyFeedback } from "../hooks/use-copy-feedback";
 import { useDatasetSize } from "../hooks/use-dataset-size";
 import {
@@ -49,8 +49,8 @@ import {
   formatPipelineTag,
   parseLanguageTags,
 } from "../lib/view-models";
+import { confirmExternalLink } from "../stores/external-link-confirm";
 import type { SelectedModelView } from "../types";
-import { selectActiveJob, useDownloadManagerStore } from "../download-manager";
 import { DatasetDownloadSection } from "./dataset-download-section";
 import { DownloadSection } from "./download-section";
 import { LocalDatasetCard } from "./local-dataset-card";
@@ -166,7 +166,7 @@ function StatRow({
   return (
     <Tooltip>
       <TooltipTrigger asChild={true}>
-        <span className="hub-tag-meta inline-flex cursor-default items-center gap-1.5 px-2.5 py-1 text-[11.5px] text-muted-foreground transition-colors hover:text-foreground/80">
+        <span className="hub-tag-meta inline-flex cursor-default items-center gap-1.5 px-2.5 py-1 text-ui-11p5 text-muted-foreground transition-colors hover:text-foreground/80">
           <HugeiconsIcon
             icon={icon}
             strokeWidth={1.75}
@@ -208,7 +208,7 @@ function StatusChip({
   return (
     <span
       className={cn(
-        "inline-flex h-5 shrink-0 items-center whitespace-nowrap rounded-full border bg-transparent px-2 text-[11px] font-medium leading-none",
+        "inline-flex h-5 shrink-0 items-center whitespace-nowrap rounded-full border bg-transparent px-2 text-ui-11 font-medium leading-none",
         toneClass,
         className,
       )}
@@ -248,12 +248,12 @@ function BaseModelSearchChip({
           <button
             type="button"
             onClick={() => onSearchHub(searchTerm)}
-            className="inline-flex h-6 max-w-full cursor-pointer items-center gap-1.5 rounded-full bg-muted px-2.5 text-[11.5px] transition-colors hover:bg-muted/80 dark:bg-[rgba(255,255,255,0.04)]"
+            className="inline-flex h-6 max-w-full cursor-pointer items-center gap-1.5 rounded-full bg-muted px-2.5 text-ui-11p5 transition-colors hover:bg-muted/80 dark:bg-[rgba(255,255,255,0.04)]"
           >
             {content}
           </button>
         ) : (
-          <span className="inline-flex h-6 max-w-full items-center gap-1.5 rounded-full bg-muted px-2.5 text-[11.5px] dark:bg-[rgba(255,255,255,0.04)]">
+          <span className="inline-flex h-6 max-w-full items-center gap-1.5 rounded-full bg-muted px-2.5 text-ui-11p5 dark:bg-[rgba(255,255,255,0.04)]">
             {content}
           </span>
         )}
@@ -325,11 +325,11 @@ function ModelStatusChips({
           >
             This model may not be supported yet.
             {unslothSupport.reason && (
-              <span className="mt-1 block text-[10.5px] font-normal text-white/75">
+              <span className="mt-1 block text-ui-10p5 font-normal text-white/75">
                 {unslothSupport.reason}
               </span>
             )}
-            <span className="mt-1 block text-[10.5px] font-normal text-white/75">
+            <span className="mt-1 block text-ui-10p5 font-normal text-white/75">
               Still downloadable to your Hugging Face cache.
             </span>
           </TooltipContent>
@@ -349,7 +349,7 @@ function ModelStatusChips({
           >
             This device has no supported GPU or usable MLX, so only GGUF models
             can run here.
-            <span className="mt-1 block text-[10.5px] font-normal text-white/75">
+            <span className="mt-1 block text-ui-10p5 font-normal text-white/75">
               Still downloadable to your Hugging Face cache.
             </span>
           </TooltipContent>
@@ -368,7 +368,7 @@ function ModelStatusChips({
             className="tooltip-compact max-w-xs"
           >
             Estimated 4-bit memory load is around {vramInfo.est} GB.
-            <span className="mt-1 block text-[10.5px] font-normal text-white/75">
+            <span className="mt-1 block text-ui-10p5 font-normal text-white/75">
               {vramDetail}
             </span>
           </TooltipContent>
@@ -399,6 +399,7 @@ export type ModelInspectorActions = {
     expectedBytes?: number;
   }) => void;
   onUseInChat: () => void;
+  onEject?: () => void;
   onTrain?: () => void;
   onInventoryChange?: () => void;
   onSearchHub?: (query: string) => void;
@@ -433,6 +434,7 @@ export const ModelInspector = memo(function ModelInspector({
     onLoad,
     onLoadLocal,
     onUseInChat,
+    onEject,
     onTrain,
     onInventoryChange,
     onSearchHub,
@@ -500,10 +502,10 @@ export const ModelInspector = memo(function ModelInspector({
           <HugeiconsIcon icon={CubeIcon} strokeWidth={1.5} className="size-5" />
         </div>
         <div className="space-y-1">
-          <p className="text-[15px] font-semibold tracking-tight text-foreground">
+          <p className="text-ui-15 font-semibold tracking-tight text-foreground">
             Select a {isDataset ? "dataset" : "model"}
           </p>
-          <p className="max-w-sm text-[12.5px] leading-5 text-muted-foreground">
+          <p className="max-w-sm text-ui-12p5 leading-5 text-muted-foreground">
             {isDataset
               ? "Choose a dataset from the catalog to inspect its download state and details."
               : "Choose an item from the catalog to inspect its runtime fit, download state, and model card."}
@@ -517,14 +519,16 @@ export const ModelInspector = memo(function ModelInspector({
     ? formatRelativeShort(model.updatedAt)
     : formatLocalUpdated(model.localUpdatedAt);
   const updatedLabel = updatedRaw === "Unknown update" ? "N/A" : updatedRaw;
-  const createdLabel = model.createdAt ? formatShortDate(model.createdAt) : null;
+  const createdLabel = model.createdAt
+    ? formatShortDate(model.createdAt)
+    : null;
   const libraryLabel = isDataset ? null : formatLibrary(model.libraryName);
   const gatedAccess = model.gated !== false && model.gated !== undefined;
   const downloadsTooltip =
     model.downloadsAllTime != null ? (
       <>
         Downloads (30 days)
-        <span className="mt-1 block text-[10.5px] font-normal text-white/75">
+        <span className="mt-1 block text-ui-10p5 font-normal text-white/75">
           {formatCompact(model.downloadsAllTime)} all time
         </span>
       </>
@@ -578,11 +582,11 @@ export const ModelInspector = memo(function ModelInspector({
           <OwnerAvatar
             owner={model.owner}
             repoName={model.title}
-            className="size-[60px] rounded-[18px] text-[19px]"
+            className="size-[60px] rounded-[18px] text-ui-19"
           />
           <div className="min-w-0 flex-1">
             <div className="flex min-w-0 items-center gap-1.5">
-              <h2 className="truncate text-[25px] font-semibold leading-[31px] tracking-normal text-foreground">
+              <h2 className="truncate text-ui-25 font-semibold leading-ui-31 tracking-normal text-foreground">
                 {model.title}
               </h2>
               {model.hubRepoId && (
@@ -595,7 +599,7 @@ export const ModelInspector = memo(function ModelInspector({
                 </div>
               )}
             </div>
-            <div className="mt-0.5 flex min-w-0 items-center gap-1 text-[15px] leading-[24px] text-muted-foreground">
+            <div className="mt-0.5 flex min-w-0 items-center gap-1 text-ui-15 leading-ui-24 text-muted-foreground">
               <span className="truncate">{model.owner}</span>
               {model.owner.toLowerCase() === "unsloth" && (
                 <span
@@ -609,12 +613,12 @@ export const ModelInspector = memo(function ModelInspector({
 
         <div className="mt-4 flex flex-wrap items-center gap-1.5">
           {isDataset && (
-            <span className="inline-flex shrink-0 items-center rounded-full border border-violet-500/40 bg-transparent px-2 py-0.5 text-[11.5px] font-medium text-violet-600 dark:text-violet-400">
+            <span className="inline-flex shrink-0 items-center rounded-full border border-violet-500/40 bg-transparent px-2 py-0.5 text-ui-11p5 font-medium text-violet-600 dark:text-violet-400">
               Dataset
             </span>
           )}
           {!isDataset && (
-            <span className="inline-flex h-6 items-center gap-1.5 rounded-full bg-muted px-2.5 text-[11.5px] font-medium text-foreground dark:bg-[rgba(255,255,255,0.04)]">
+            <span className="inline-flex h-6 items-center gap-1.5 rounded-full bg-muted px-2.5 text-ui-11p5 font-medium text-foreground dark:bg-[rgba(255,255,255,0.04)]">
               <HugeiconsIcon
                 icon={CubeIcon}
                 strokeWidth={1.75}
@@ -696,6 +700,7 @@ export const ModelInspector = memo(function ModelInspector({
               }
               onLoad={onLoadLocal}
               onUseInChat={onUseInChat}
+              onEject={onEject}
               onTrain={
                 model.isDownloaded && canTrainModel ? onTrain : undefined
               }
@@ -719,6 +724,7 @@ export const ModelInspector = memo(function ModelInspector({
               knownBytes={model.cachedBytes}
               onLoad={model.isLocal ? onLoadLocal : onLoad}
               onUseInChat={onUseInChat}
+              onEject={onEject}
               onTrain={
                 model.isDownloaded && canTrainModel ? onTrain : undefined
               }
@@ -730,12 +736,12 @@ export const ModelInspector = memo(function ModelInspector({
 
       <div className="pb-5 pt-5">
         {selectionHiddenByFilters && (
-          <p className="mb-3 rounded-[8px] border border-amber-500/30 bg-amber-500/10 px-3 py-2 text-[11.5px] leading-snug text-muted-foreground">
+          <p className="mb-3 rounded-[8px] border border-amber-500/30 bg-amber-500/10 px-3 py-2 text-ui-11p5 leading-snug text-muted-foreground">
             Current selection is hidden by the active filters or search.
           </p>
         )}
         {metadataUnavailable && (
-          <p className="mb-3 text-[11.5px] leading-snug text-muted-foreground">
+          <p className="mb-3 text-ui-11p5 leading-snug text-muted-foreground">
             Couldn't load full details from Hugging Face. Some fields may be
             incomplete.
           </p>
diff --git a/studio/frontend/src/features/hub/catalog/model-readme.tsx b/studio/frontend/src/features/hub/catalog/model-readme.tsx
index 3d215473e2..889b011399 100644
--- a/studio/frontend/src/features/hub/catalog/model-readme.tsx
+++ b/studio/frontend/src/features/hub/catalog/model-readme.tsx
@@ -126,17 +126,17 @@ function prepareReadmeBody(markdown: string): string {
 }
 
 const PROSE = cn(
-  "max-w-none text-[13.5px] leading-[1.7] text-foreground/85",
-  "[&_h1]:text-[18px] [&_h1]:font-semibold [&_h1]:tracking-tight [&_h1]:mt-2 [&_h1]:mb-3",
-  "[&_h2]:text-[15.5px] [&_h2]:font-semibold [&_h2]:tracking-tight [&_h2]:mt-5 [&_h2]:mb-2",
-  "[&_h3]:text-[14px] [&_h3]:font-semibold [&_h3]:mt-4 [&_h3]:mb-1.5",
+  "max-w-none text-ui-13p5 leading-[1.7] text-foreground/85",
+  "[&_h1]:text-ui-18 [&_h1]:font-semibold [&_h1]:tracking-tight [&_h1]:mt-2 [&_h1]:mb-3",
+  "[&_h2]:text-ui-15p5 [&_h2]:font-semibold [&_h2]:tracking-tight [&_h2]:mt-5 [&_h2]:mb-2",
+  "[&_h3]:text-ui-14 [&_h3]:font-semibold [&_h3]:mt-4 [&_h3]:mb-1.5",
   "[&_p]:my-2.5 [&_ul]:my-2 [&_ol]:my-2 [&_li]:my-0.5",
   "[&_a]:text-primary [&_a:hover]:underline",
-  "[&_code]:rounded-md [&_code]:bg-muted/60 [&_code]:px-1 [&_code]:py-0.5 [&_code]:text-[12px] [&_code]:font-mono",
-  "[&_pre]:rounded-[12px] [&_pre]:border [&_pre]:border-border/60 [&_pre]:bg-muted/40 [&_pre]:p-3 [&_pre]:text-[12px] [&_pre]:overflow-x-auto",
+  "[&_code]:rounded-md [&_code]:bg-muted/60 [&_code]:px-1 [&_code]:py-0.5 [&_code]:text-ui-12 [&_code]:font-mono",
+  "[&_pre]:rounded-[12px] [&_pre]:border [&_pre]:border-border/60 [&_pre]:bg-muted/40 [&_pre]:p-3 [&_pre]:text-ui-12 [&_pre]:overflow-x-auto",
   "[&_pre_code]:bg-transparent [&_pre_code]:p-0",
   "[&_blockquote]:border-l-2 [&_blockquote]:border-border/60 [&_blockquote]:pl-3 [&_blockquote]:text-muted-foreground",
-  "[&_table]:my-3 [&_table]:text-[12.5px]",
+  "[&_table]:my-3 [&_table]:text-ui-12p5",
   "[&_th]:px-2 [&_th]:py-1.5 [&_th]:text-left [&_th]:font-semibold [&_th]:border-b [&_th]:border-border/60",
   "[&_td]:px-2 [&_td]:py-1.5 [&_td]:border-b [&_td]:border-border/40",
   "[&_img]:rounded-[10px] [&_img]:my-2 [&_img]:max-w-full",
@@ -300,7 +300,7 @@ function ReadmePlaceholder({
       aria-busy="true"
       aria-live="polite"
     >
-      <div className="flex items-center gap-2 text-[12.5px] text-muted-foreground">
+      <div className="flex items-center gap-2 text-ui-12p5 text-muted-foreground">
         <Spinner className="size-3.5" />
         {message ?? `Loading ${kind === "dataset" ? "dataset" : "model"} card…`}
       </div>
@@ -540,7 +540,7 @@ export function ModelReadme({
         ? current.error
         : readmeUnavailableMessage(subject);
     return (
-      <p className="min-h-[44px] text-[12.5px] text-muted-foreground">
+      <p className="min-h-[44px] text-ui-12p5 text-muted-foreground">
         {errorMessage}
       </p>
     );
@@ -548,7 +548,7 @@ export function ModelReadme({
 
   if (!current.body) {
     return (
-      <p className="min-h-[44px] text-[12.5px] text-muted-foreground">
+      <p className="min-h-[44px] text-ui-12p5 text-muted-foreground">
         {readmeMissingMessage(subject)}
       </p>
     );
diff --git a/studio/frontend/src/features/hub/catalog/models-catalog-lists.tsx b/studio/frontend/src/features/hub/catalog/models-catalog-lists.tsx
index 355c38a91e..cbae108006 100644
--- a/studio/frontend/src/features/hub/catalog/models-catalog-lists.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-catalog-lists.tsx
@@ -2,13 +2,20 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { Spinner } from "@/components/ui/spinner";
+import {
+  makePinRank,
+  pinKey,
+  usePinnedModelsStore,
+} from "@/features/model-picker";
 import {
   CubeIcon,
   DownloadCircle02Icon,
-  FolderSearchIcon,
+  PinIcon,
+  Search01Icon,
 } from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
 import type { RefObject } from "react";
-import { useMemo } from "react";
+import { useLayoutEffect, useMemo, useState } from "react";
 import {
   inventoryRowMatches,
   scoreInventoryRow,
@@ -61,7 +68,7 @@ export function InventoryWarningRow({
   onRetry: () => void;
 }) {
   return (
-    <div className="mx-5 mt-2 rounded-[8px] border border-amber-500/30 bg-amber-500/10 px-3 py-2 text-[12.5px] text-muted-foreground">
+    <div className="mx-5 mt-2 rounded-[8px] border border-amber-500/30 bg-amber-500/10 px-3 py-2 text-ui-12p5 text-muted-foreground">
       <div className="flex items-center justify-between gap-3">
         <span>
           Some on-device sources couldn't be scanned. Showing available{" "}
@@ -69,7 +76,7 @@ export function InventoryWarningRow({
         </span>
         <button
           type="button"
-          className="shrink-0 text-[12px] font-medium text-foreground transition-colors hover:text-primary"
+          className="shrink-0 text-ui-12 font-medium text-foreground transition-colors hover:text-primary"
           onClick={onRetry}
         >
           Retry
@@ -208,7 +215,7 @@ export function DiscoverList({
           <SkeletonList />
         ) : (
           <EmptyState
-            icon={query.trim() ? FolderSearchIcon : CubeIcon}
+            icon={query.trim() ? Search01Icon : CubeIcon}
             title={
               query.trim()
                 ? `No matching ${isDataset ? "datasets" : "models"}`
@@ -244,6 +251,8 @@ export function DownloadedList({
   downloadedReady,
   inventoryError,
   query,
+  typeFilterActive = false,
+  onClearFilters,
   scrollElement,
   columns = 1,
   activeCheckpoint,
@@ -262,6 +271,8 @@ export function DownloadedList({
   downloadedReady: boolean;
   inventoryError: boolean;
   query: string;
+  typeFilterActive?: boolean;
+  onClearFilters?: () => void;
   scrollElement: HTMLDivElement | null;
   columns?: number;
   activeCheckpoint: string | null;
@@ -274,11 +285,20 @@ export function DownloadedList({
   sort: InventorySort;
   onInventoryChange?: () => void;
 }) {
+  // Pinned repos surface first regardless of the active sort; the chosen sort
+  // still orders rows within the pinned and unpinned groups.
+  const pinnedIds = usePinnedModelsStore((s) => s.pinned);
+  const pinnedSet = useMemo(() => new Set(pinnedIds), [pinnedIds]);
   const inventoryItems = useMemo<InventoryItem[]>(() => {
     const merged: InventoryItem[] = [
       ...cachedRows.map((row) => ({ variant: "cached" as const, row })),
       ...localRows.map((row) => ({ variant: "local" as const, row })),
     ];
+    // Pinned rows order by pin recency (newest pin first), not the active
+    // sort, so "Pin to top" puts the row exactly where the user expects.
+    const rank = makePinRank(pinnedIds);
+    const pinRank = (item: InventoryItem) =>
+      item.row.repoId ? rank(pinKey(item.row.repoId)) : Number.MAX_SAFE_INTEGER;
     if (inventoryTokens.length > 0) {
       return merged
         .map((item, index) => ({
@@ -286,29 +306,89 @@ export function DownloadedList({
           index,
           score: scoreInventoryRow(item.row, inventoryTokens),
         }))
-        .sort((a, b) => b.score - a.score || a.index - b.index)
+        .sort(
+          (a, b) =>
+            pinRank(a.item) - pinRank(b.item) ||
+            b.score - a.score ||
+            a.index - b.index,
+        )
         .map((entry) => entry.item);
     }
     if (sort === "recent") {
-      return merged;
+      return merged
+        .map((item, index) => ({ item, index }))
+        .sort((a, b) => pinRank(a.item) - pinRank(b.item) || a.index - b.index)
+        .map((entry) => entry.item);
     }
     return merged
       .map((item, index) => ({ item, index }))
-      .sort((a, b) =>
-        sort === "name"
-          ? inventoryItemTitle(a.item).localeCompare(
-              inventoryItemTitle(b.item),
-            ) || a.index - b.index
-          : inventoryItemSize(b.item) - inventoryItemSize(a.item) ||
-            a.index - b.index,
+      .sort(
+        (a, b) =>
+          pinRank(a.item) - pinRank(b.item) ||
+          (sort === "name"
+            ? inventoryItemTitle(a.item).localeCompare(
+                inventoryItemTitle(b.item),
+              ) || a.index - b.index
+            : inventoryItemSize(b.item) - inventoryItemSize(a.item) ||
+              a.index - b.index),
       )
       .map((entry) => entry.item);
-  }, [cachedRows, localRows, inventoryTokens, sort]);
+  }, [cachedRows, localRows, inventoryTokens, sort, pinnedIds]);
   const hasInventoryRows = cachedRows.length > 0 || localRows.length > 0;
+  // Pinned repos get their own labelled section so it's clear why they lead
+  // the list; inventoryItems already sorts them first, so this is a prefix.
+  const pinnedCount = useMemo(
+    () =>
+      inventoryItems.filter(
+        (item) => item.row.repoId && pinnedSet.has(pinKey(item.row.repoId)),
+      ).length,
+    [inventoryItems, pinnedSet],
+  );
+  const pinnedItems = inventoryItems.slice(0, pinnedCount);
+  const unpinnedItems = inventoryItems.slice(pinnedCount);
+  const [virtualRowsWrapper, setVirtualRowsWrapper] =
+    useState<HTMLDivElement | null>(null);
+  const [scrollMargin, setScrollMargin] = useState(0);
+  useLayoutEffect(() => {
+    if (!virtualRowsWrapper || !scrollElement) return;
+    const measure = () => {
+      const margin = Math.max(
+        0,
+        Math.round(
+          virtualRowsWrapper.getBoundingClientRect().top -
+            scrollElement.getBoundingClientRect().top +
+            scrollElement.scrollTop,
+        ),
+      );
+      setScrollMargin((current) => (current === margin ? current : margin));
+    };
+    measure();
+    const observer = new ResizeObserver(measure);
+    observer.observe(virtualRowsWrapper.parentElement ?? scrollElement);
+    return () => observer.disconnect();
+  }, [virtualRowsWrapper, scrollElement]);
+  const rowHeightPx = compact
+    ? RESULT_SPLIT_ROW_HEIGHT_PX
+    : RESULT_GRID_ROW_HEIGHT_PX;
+  const cellHeightPx = compact ? RESULT_SPLIT_HEIGHT_PX : RESULT_GRID_HEIGHT_PX;
+  const renderInventoryRow = (item: InventoryItem) => (
+    <InventoryRow
+      row={item.row}
+      selected={selectedId === item.row.id}
+      activeCheckpoint={activeCheckpoint}
+      activeGgufVariant={activeGgufVariant}
+      isDataset={isDataset}
+      dimmed={!inventoryRowMatches(item.row, inventoryTokens)}
+      deviceType={deviceType}
+      compact={compact}
+      onSelect={onSelect}
+      onChange={onInventoryChange}
+    />
+  );
 
   if (!downloadedReady && !hasInventoryRows) {
     return (
-      <div className="flex min-h-[240px] items-center justify-center gap-3 text-[13px] text-muted-foreground">
+      <div className="flex min-h-[240px] items-center justify-center gap-3 text-ui-13 text-muted-foreground">
         <Spinner className="size-4" />
         Loading local inventory...
       </div>
@@ -325,9 +405,29 @@ export function DownloadedList({
   }
 
   if (cachedRows.length === 0 && localRows.length === 0) {
+    if (!query.trim() && typeFilterActive) {
+      return (
+        <EmptyState
+          icon={Search01Icon}
+          title="No matching models on device"
+          body="No downloaded or local model matches the selected type filter."
+          action={
+            onClearFilters && (
+              <button
+                type="button"
+                onClick={onClearFilters}
+                className="inline-flex h-8 items-center gap-1.5 rounded-full bg-transparent px-3 text-ui-12 font-medium text-foreground transition-colors hover:bg-foreground/[0.04] dark:hover:bg-white/[0.05]"
+              >
+                Show all types
+              </button>
+            )
+          }
+        />
+      );
+    }
     return (
       <EmptyState
-        icon={query.trim() ? FolderSearchIcon : DownloadCircle02Icon}
+        icon={query.trim() ? Search01Icon : DownloadCircle02Icon}
         title={query.trim() ? "No matches on device" : "Nothing on device yet"}
         body={
           query.trim()
@@ -341,27 +441,57 @@ export function DownloadedList({
   }
 
   return (
-    <VirtualRows
-      items={inventoryItems}
-      scrollElement={scrollElement}
-      columns={columns}
-      rowHeight={compact ? RESULT_SPLIT_ROW_HEIGHT_PX : RESULT_GRID_ROW_HEIGHT_PX}
-      cellHeight={compact ? RESULT_SPLIT_HEIGHT_PX : RESULT_GRID_HEIGHT_PX}
-      getKey={(item) => `${item.variant}-${item.row.id}`}
-      renderRow={(item) => (
-        <InventoryRow
-          row={item.row}
-          selected={selectedId === item.row.id}
-          activeCheckpoint={activeCheckpoint}
-          activeGgufVariant={activeGgufVariant}
-          isDataset={isDataset}
-          dimmed={!inventoryRowMatches(item.row, inventoryTokens)}
-          deviceType={deviceType}
-          compact={compact}
-          onSelect={onSelect}
-          onChange={onInventoryChange}
-        />
+    <>
+      {pinnedItems.length > 0 && (
+        <>
+          <div className="flex items-center gap-1.5 px-1 pb-2 pt-3 text-ui-11 font-semibold uppercase tracking-wider text-muted-foreground">
+            <HugeiconsIcon
+              icon={PinIcon}
+              strokeWidth={1.75}
+              className="size-3.5"
+            />
+            Pinned
+          </div>
+          {/* Pinned rows are few, so render them as a plain grid matching the
+              virtualized list's lane count and row spacing. */}
+          <div
+            style={{
+              display: "grid",
+              gridTemplateColumns: `repeat(${Math.max(1, columns)}, minmax(0, 1fr))`,
+              columnGap: 12,
+              rowGap: rowHeightPx - cellHeightPx,
+              paddingBottom: rowHeightPx - cellHeightPx,
+            }}
+          >
+            {pinnedItems.map((item) => (
+              <div
+                key={`${item.variant}-${item.row.id}`}
+                className="min-w-0"
+                style={{ height: cellHeightPx }}
+              >
+                {renderInventoryRow(item)}
+              </div>
+            ))}
+          </div>
+          {unpinnedItems.length > 0 && (
+            <div className="px-1 pb-2 pt-2 text-ui-11 font-semibold uppercase tracking-wider text-muted-foreground">
+              All {isDataset ? "datasets" : "models"}
+            </div>
+          )}
+        </>
       )}
-    />
+      <div ref={setVirtualRowsWrapper}>
+        <VirtualRows
+          items={unpinnedItems}
+          scrollElement={scrollElement}
+          scrollMargin={scrollMargin}
+          columns={columns}
+          rowHeight={rowHeightPx}
+          cellHeight={cellHeightPx}
+          getKey={(item) => `${item.variant}-${item.row.id}`}
+          renderRow={renderInventoryRow}
+        />
+      </div>
+    </>
   );
 }
diff --git a/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx b/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
index 111d78f00b..5236c0be74 100644
--- a/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { ModelDeleteAction } from "@/components/assistant-ui/model-selector/model-delete-action";
 import {
   Tooltip,
   TooltipContent,
@@ -9,18 +8,26 @@ import {
 } from "@/components/ui/tooltip";
 import {
   type GgufVariantDetail,
-  deleteCachedModel,
   deleteCachedDataset,
+  deleteCachedModel,
   formatLocalUpdated,
   listGgufVariants,
   useGgufVariantsCacheVersion,
-} from "@/features/hub/inventory";
-import { classifyUnslothSupport } from "@/features/hub/hooks/use-hub-model-search";
-import { formatBytes, formatRelativeShort } from "@/features/hub/lib/format";
-import { ggufVariantDisplayLabel } from "@/features/hub/lib/gguf-variant-sort";
-import { modelIdsMatch } from "@/features/hub/lib/model-identity";
+} from "../inventory";
+import {
+  classifyUnslothSupport,
+  formatBytes,
+  formatRelativeShort,
+  ggufVariantDisplayLabel,
+  useHfTokenStore,
+} from "@/features/hub";
+import { modelIdsMatch } from "../lib/model-identity";
+import {
+  ModelRowMenu,
+  pinKey,
+  usePinnedModelsStore,
+} from "@/features/model-picker";
 import { cn, formatCompact } from "@/lib/utils";
-import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
 import {
   Download01Icon,
   FavouriteIcon,
@@ -39,6 +46,7 @@ import {
   useRef,
   useState,
 } from "react";
+import { paramLabelFromId } from "../lib/view-models";
 import type {
   CachedInventoryRow,
   DiscoverRow,
@@ -46,7 +54,6 @@ import type {
 } from "../types";
 import { OwnerAvatar } from "./owner-avatar";
 import { AccessGlyphs } from "./shared";
-import { paramLabelFromId } from "../lib/view-models";
 
 const COARSE_POINTER =
   typeof window !== "undefined" &&
@@ -142,15 +149,15 @@ function CachedSizeChipLive({
   );
 
   const rows: Array<{ label: string; size_bytes: number }> | null =
-    !needsVariantFetch
-      ? [{ label: repoId, size_bytes: totalBytes }]
-      : currentVariantState.status === "loaded" &&
-          currentVariantState.variants.length > 0
+    needsVariantFetch
+      ? currentVariantState.status === "loaded" &&
+        currentVariantState.variants.length > 0
         ? currentVariantState.variants.map((variant) => ({
             label: ggufVariantDisplayLabel(variant),
             size_bytes: variant.size_bytes,
           }))
-        : null;
+        : null
+      : [{ label: repoId, size_bytes: totalBytes }];
   const variantMessage =
     currentVariantState.status === "loading"
       ? "Loading downloaded variants..."
@@ -181,14 +188,14 @@ function CachedSizeChipLive({
                   <StatChip
                     icon={PackageIcon}
                     value={formatBytes(row.size_bytes)}
-                    className="text-[11px] text-white/70"
+                    className="text-ui-11 text-white/70"
                   />
                 </span>
               </li>
             ))}
           </ul>
         ) : (
-          <span className="block max-w-52 text-[11px] leading-4 text-muted-foreground">
+          <span className="block max-w-52 text-ui-11 leading-4 text-muted-foreground">
             {variantMessage}
           </span>
         )}
@@ -218,7 +225,7 @@ export function StatChip({
   return (
     <span
       className={cn(
-        "inline-flex shrink-0 items-center gap-1 whitespace-nowrap text-[10px] font-medium leading-none tabular-nums text-muted-foreground/75",
+        "inline-flex shrink-0 items-center gap-1 whitespace-nowrap text-ui-10 font-medium leading-none tabular-nums text-muted-foreground/75",
         className,
       )}
     >
@@ -275,7 +282,9 @@ function CatalogRow({
         )}
       />
       <CatalogRowInteractiveContext.Provider value={interactive}>
-        <div className={cn("pointer-events-none relative", card && "z-[1] w-full")}>
+        <div
+          className={cn("pointer-events-none relative", card && "z-[1] w-full")}
+        >
           {children}
         </div>
       </CatalogRowInteractiveContext.Provider>
@@ -473,7 +482,7 @@ export const DiscoverModelRow = memo(function DiscoverModelRow({
         <div className="flex min-w-0 flex-1 flex-col gap-[3px]">
           <div className="flex h-[18px] min-w-0 items-center justify-between gap-2">
             <div className="flex min-w-0 items-center gap-2 pr-2">
-              <p className="truncate text-[12px] font-medium leading-[18px] tracking-[-0.005em] text-foreground">
+              <p className="truncate text-ui-12 font-medium leading-ui-18 tracking-[-0.005em] text-foreground">
                 {row.repo}
               </p>
               <AccessGlyphs
@@ -509,7 +518,7 @@ export const DiscoverModelRow = memo(function DiscoverModelRow({
               />
             </div>
           </div>
-          <div className="flex h-[16px] min-w-0 items-center justify-between gap-2 text-[11.5px] leading-[16px] text-muted-foreground/85">
+          <div className="flex h-[16px] min-w-0 items-center justify-between gap-2 text-ui-11p5 leading-ui-16 text-muted-foreground/85">
             <span className="flex min-w-0 items-center gap-1">
               <span className="truncate">{row.owner}</span>
               {row.owner.toLowerCase() === "unsloth" && (
@@ -519,7 +528,7 @@ export const DiscoverModelRow = memo(function DiscoverModelRow({
                 />
               )}
             </span>
-            <span className="shrink-0 text-[10.5px] tabular-nums">
+            <span className="shrink-0 text-ui-10p5 tabular-nums">
               {formatRelativeShort(row.result.updatedAt)}
             </span>
           </div>
@@ -653,9 +662,11 @@ export const InventoryRow = memo(function InventoryRow({
       <div className="hidden shrink-0 items-center gap-1.5 sm:flex">
         {/* Format already shows as the status dot, so the pill stays neutral. */}
         {formatLabel && <span className="hub-chip">{formatLabel}</span>}
-        {paramLabel && <span className="hub-chip tabular-nums">{paramLabel}</span>}
+        {paramLabel && (
+          <span className="hub-chip tabular-nums">{paramLabel}</span>
+        )}
         {quantLabel && (
-          <span className="hub-chip font-mono text-[10.5px] uppercase">
+          <span className="hub-chip font-mono text-ui-10p5 uppercase">
             {quantLabel}
           </span>
         )}
@@ -697,9 +708,7 @@ export const InventoryRow = memo(function InventoryRow({
   const compactMarkers =
     partialRepoId || unsupported ? (
       <span className="flex shrink-0 items-center gap-1">
-        {partialRepoId && (
-          <StatusDot tone="warning" label="Partial download" />
-        )}
+        {partialRepoId && <StatusDot tone="warning" label="Partial download" />}
         {unsupported && (
           <StatusDot tone="danger" label="May not be supported yet" />
         )}
@@ -707,7 +716,7 @@ export const InventoryRow = memo(function InventoryRow({
     ) : null;
 
   const ownerLine = (
-    <span className="mt-0.5 flex min-w-0 items-center gap-1 text-[11.5px] leading-[15px] text-muted-foreground/80">
+    <span className="mt-0.5 flex min-w-0 items-center gap-1 text-ui-11p5 leading-ui-15 text-muted-foreground/80">
       <span className="truncate">{subLabel}</span>
       {subLabel.toLowerCase() === "unsloth" && (
         <span
@@ -718,37 +727,81 @@ export const InventoryRow = memo(function InventoryRow({
     </span>
   );
 
+  const pinnedKeys = usePinnedModelsStore((s) => s.pinned);
+  const togglePinned = usePinnedModelsStore((s) => s.togglePinned);
+  const rowPinned =
+    cacheDeletableRepoId != null &&
+    pinnedKeys.includes(pinKey(cacheDeletableRepoId));
   const deleteAction =
     canDelete && cacheDeletableRepoId ? (
-      <ModelDeleteAction
-        ariaLabel={`Delete ${cacheDeletableRepoId}`}
-        title={isDataset ? "Delete cached dataset?" : "Delete cached model?"}
-        description={
-          <>
-            This will remove{" "}
-            <span className="font-medium text-foreground">
-              {cacheDeletableRepoId}
-            </span>{" "}
-            {isDataset
-              ? "and its downloaded files"
-              : row.isGguf
-                ? "and all of its downloaded quantizations"
-                : "and all of its downloaded files"}
-            {row.kind === "cache" ? ` (${formatBytes(row.bytes)})` : ""} from
-            disk. You can re-download it later.
-          </>
-        }
-        successMessage={`Deleted ${cacheDeletableRepoId}`}
+      <ModelRowMenu
+        ariaLabel={`More options for ${cacheDeletableRepoId}`}
         buttonClassName="pointer-events-auto hub-modal-pe-guard p-2 opacity-0 transition-opacity group-hover/row:opacity-100 focus-visible:opacity-100 data-[state=open]:opacity-100 [@media(pointer:coarse)]:opacity-100"
         iconClassName="size-4"
-        onConfirm={async () => {
-          if (isDataset) {
-            await deleteCachedDataset(cacheDeletableRepoId);
-          } else {
-            await deleteCachedModel(cacheDeletableRepoId);
-          }
+        pin={
+          isDataset
+            ? undefined
+            : {
+                pinned: rowPinned,
+                pinLabel: "Pin to top",
+                unpinLabel: "Unpin",
+                onToggle: () => togglePinned(cacheDeletableRepoId),
+              }
+        }
+        cachePath={isDataset ? undefined : { repoId: cacheDeletableRepoId }}
+        del={{
+          title: isDataset ? "Delete cached dataset?" : "Delete cached model?",
+          description: (
+            <>
+              This will remove{" "}
+              <span className="font-medium text-foreground">
+                {cacheDeletableRepoId}
+              </span>{" "}
+              {isDataset
+                ? "and its downloaded files"
+                : row.isGguf
+                  ? "and all of its downloaded quantizations"
+                  : "and all of its downloaded files"}
+              {row.kind === "cache" ? ` (${formatBytes(row.bytes)})` : ""} from
+              disk. You can re-download it later.
+            </>
+          ),
+          successMessage: `Deleted ${cacheDeletableRepoId}`,
+          onConfirm: async () => {
+            // Delete only the copy this row shows: cache rows carry the owning
+            // cache path, so pass it through and leave other caches untouched.
+            const rowCachePath =
+              row.kind === "cache" ? (row.cachePath ?? undefined) : undefined;
+            if (isDataset) {
+              await deleteCachedDataset(cacheDeletableRepoId, rowCachePath);
+            } else {
+              await deleteCachedModel(
+                cacheDeletableRepoId,
+                undefined,
+                undefined,
+                rowCachePath,
+              );
+              // Deleted repos can't stay pinned: drop the repo pin and any of
+              // its per-quant pins so stale rows don't linger up top.
+              const { pinned, togglePinned: toggle } =
+                usePinnedModelsStore.getState();
+              for (const key of pinned) {
+                if (
+                  key === pinKey(cacheDeletableRepoId) ||
+                  key.startsWith(`${cacheDeletableRepoId}::`)
+                ) {
+                  toggle(
+                    cacheDeletableRepoId,
+                    key.includes("::")
+                      ? key.slice(key.indexOf("::") + 2)
+                      : undefined,
+                  );
+                }
+              }
+            }
+          },
+          onDeleted: onChange,
         }}
-        onDeleted={onChange}
       />
     ) : null;
 
@@ -773,17 +826,17 @@ export const InventoryRow = memo(function InventoryRow({
           <OwnerAvatar
             owner={row.owner}
             repoName={title}
-            className="size-8 shrink-0 rounded-[9px] text-[12px]"
+            className="size-8 shrink-0 rounded-[9px] text-ui-12"
             remote={false}
           />
           <div className="min-w-0 flex-1">
             <div className="flex min-w-0 items-center gap-1.5">
-              <span className="truncate text-[12.5px] font-semibold leading-[16px] text-foreground">
+              <span className="truncate text-ui-12p5 font-semibold leading-ui-16 text-foreground">
                 {title}
               </span>
               {compactMarkers}
             </div>
-            <span className="mt-0.5 flex min-w-0 items-center gap-1.5 text-[10.5px] leading-[14px] text-muted-foreground/75">
+            <span className="mt-0.5 flex min-w-0 items-center gap-1.5 text-ui-10p5 leading-ui-14 text-muted-foreground/75">
               <span className="flex min-w-0 items-center gap-1">
                 <span className="truncate">{subLabel}</span>
                 {subLabel.toLowerCase() === "unsloth" && (
@@ -807,7 +860,7 @@ export const InventoryRow = memo(function InventoryRow({
               )}
             </span>
           </div>
-          <div className="flex shrink-0 items-center gap-2 text-[10.5px] tabular-nums text-muted-foreground/70">
+          <div className="flex shrink-0 items-center gap-2 text-ui-10p5 tabular-nums text-muted-foreground/70">
             {row.kind === "cache" ? (
               <CachedSizeChip
                 repoId={row.repoId}
@@ -850,7 +903,7 @@ export const InventoryRow = memo(function InventoryRow({
           />
           <div className="min-w-0 flex-1">
             <div className="flex min-w-0 items-center gap-1.5">
-              <span className="truncate text-[13.5px] font-semibold leading-[17px] text-foreground">
+              <span className="truncate text-ui-13p5 font-semibold leading-ui-17 text-foreground">
                 {title}
               </span>
               {statusMarkers}
@@ -871,11 +924,11 @@ export const InventoryRow = memo(function InventoryRow({
               cachePath={row.cachePath}
             />
           ) : trailing ? (
-            <span className="truncate text-[11.5px] tabular-nums text-muted-foreground/70">
+            <span className="truncate text-ui-11p5 tabular-nums text-muted-foreground/70">
               {trailing}
             </span>
           ) : sourceLabel ? (
-            <span className="truncate text-[11.5px] text-muted-foreground/55">
+            <span className="truncate text-ui-11p5 text-muted-foreground/55">
               {sourceLabel}
             </span>
           ) : null}
diff --git a/studio/frontend/src/features/hub/catalog/models-catalog.tsx b/studio/frontend/src/features/hub/catalog/models-catalog.tsx
index 344f5deb49..02b9b62fce 100644
--- a/studio/frontend/src/features/hub/catalog/models-catalog.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-catalog.tsx
@@ -54,6 +54,7 @@ export interface ModelsCatalogState {
   hasMore: boolean;
   manualFetchAvailable: boolean;
   hasActiveFilters: boolean;
+  typeFilterActive: boolean;
 }
 
 export interface ModelsCatalogPagination {
@@ -117,6 +118,7 @@ export const ModelsCatalog = memo(function ModelsCatalog({
     loadingIntentCount,
     hasMore,
     hasActiveFilters,
+    typeFilterActive,
   } = state;
   const { scrollRef, sentinelRef, isLoadingMore } = pagination;
   const {
@@ -469,6 +471,8 @@ export const ModelsCatalog = memo(function ModelsCatalog({
                 downloadedReady={downloadedReady}
                 inventoryError={inventoryError}
                 query={query}
+                typeFilterActive={typeFilterActive}
+                onClearFilters={onClearFilters}
                 scrollElement={downloadedScrollEl}
                 activeCheckpoint={activeCheckpoint}
                 activeGgufVariant={activeGgufVariant}
diff --git a/studio/frontend/src/features/hub/catalog/models-header.tsx b/studio/frontend/src/features/hub/catalog/models-header.tsx
index 10d5a80e5e..f0e0950871 100644
--- a/studio/frontend/src/features/hub/catalog/models-header.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-header.tsx
@@ -64,7 +64,7 @@ export function ModelsHeader({
   return (
     <header className="font-heading flex flex-col gap-3 sm:flex-row sm:flex-wrap sm:items-center sm:justify-between">
       <PageHeading
-        title="Hub"
+        title={isDataset ? "Datasets" : "Models"}
         onTitleClick={onTitleClick}
         subtitle={
           isDataset
@@ -91,7 +91,7 @@ export function ModelsHeader({
         <StatPill icon={CpuIcon} label="CPU" value={coreLabel} />
 
         {activeCheckpoint && (
-          <div className="hub-tag-soft ml-1 inline-flex items-center gap-1.5 px-2 py-1 text-[11.5px]">
+          <div className="hub-tag-soft ml-1 inline-flex items-center gap-1.5 px-2 py-1 text-ui-11p5">
             <span
               className="size-1.5 rounded-full bg-emerald-500"
               aria-hidden="true"
@@ -115,7 +115,7 @@ export function ModelsHeader({
             <button
               type="button"
               onClick={onEject}
-              className="-mr-0.5 ml-0.5 inline-flex cursor-pointer items-center gap-1 rounded-md px-1.5 text-[11px] text-muted-foreground transition-colors hover:text-foreground"
+              className="-mr-0.5 ml-0.5 inline-flex cursor-pointer items-center gap-1 rounded-md px-1.5 text-ui-11 text-muted-foreground transition-colors hover:text-foreground"
             >
               <HugeiconsIcon
                 icon={RemoveCircleIcon}
diff --git a/studio/frontend/src/features/hub/catalog/models-table.tsx b/studio/frontend/src/features/hub/catalog/models-table.tsx
index f3887fee28..e3cd77f781 100644
--- a/studio/frontend/src/features/hub/catalog/models-table.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-table.tsx
@@ -17,6 +17,10 @@ import {
   formatRelativeLong,
   formatRelativeShort,
 } from "@/features/hub/lib/format";
+import {
+  MODEL_TYPE_FILTER_OPTIONS,
+  type ModelTypeFilter,
+} from "@/features/hub/lib/model-type-filter";
 import {
   formatModelParamLabel,
   formatPipelineTag,
@@ -25,6 +29,7 @@ import { copyToClipboard } from "@/lib/copy-to-clipboard";
 import { cn, formatCompact } from "@/lib/utils";
 import {
   ArrowLeft01Icon,
+  ArrowUpDownIcon,
   Copy01Icon,
   Download01Icon,
   FavouriteIcon,
@@ -124,6 +129,7 @@ export function InventorySortControl({
   value: InventorySort;
   onChange: (value: InventorySort) => void;
 }) {
+  const selected = INVENTORY_SORTS.find((option) => option.value === value);
   return (
     <HubOptionMenu<InventorySort>
       value={value}
@@ -131,7 +137,46 @@ export function InventorySortControl({
       onValueChange={onChange}
       ariaLabel="Sort downloads"
       align="end"
-      className="h-8 text-[11.5px]"
+      title={selected?.label}
+      // Capped and shrinkable so a long label truncates instead of wrapping
+      // the "On device" heading beside these pills in the narrow split pane.
+      className="h-8 min-w-[72px] max-w-[124px] shrink text-ui-11p5"
+      triggerContent={
+        <span className="flex min-w-0 items-center gap-1">
+          <HugeiconsIcon
+            icon={ArrowUpDownIcon}
+            strokeWidth={1.75}
+            className="size-3.5 shrink-0 text-muted-foreground"
+          />
+          <span className="truncate">{selected?.label ?? value}</span>
+        </span>
+      }
+    />
+  );
+}
+
+// Model-type filter pill (Text / Vision / Embedding / …) beside the sort pill.
+export function InventoryTypeFilterControl({
+  value,
+  onChange,
+}: {
+  value: ModelTypeFilter;
+  onChange: (value: ModelTypeFilter) => void;
+}) {
+  const selected = MODEL_TYPE_FILTER_OPTIONS.find(
+    (option) => option.value === value,
+  );
+  return (
+    <HubOptionMenu<ModelTypeFilter>
+      value={value}
+      options={MODEL_TYPE_FILTER_OPTIONS}
+      onValueChange={onChange}
+      ariaLabel="Filter by model type"
+      align="end"
+      title={selected?.label}
+      // Capped and shrinkable so a long label ("Speech to text") truncates
+      // instead of wrapping the "On device" heading beside these pills.
+      className="h-8 min-w-[72px] max-w-[124px] shrink text-ui-11p5"
     />
   );
 }
@@ -183,11 +228,13 @@ export function HubListHeader({
           </button>
         )}
         <div className="min-w-0 space-y-0.5">
-          <h2 className="text-[18px] font-semibold tracking-[-0.02em] text-foreground">
+          {/* truncate keeps the heading on one line and clips a long search
+              query with an ellipsis instead of overflowing the pills. */}
+          <h2 className="truncate text-ui-18 font-semibold tracking-[-0.02em] text-foreground">
             {title}
           </h2>
           {subtitle && (
-            <p className="text-[12.5px] leading-tight text-muted-foreground">
+            <p className="text-ui-12p5 leading-tight text-muted-foreground">
               {subtitle}
             </p>
           )}
@@ -216,7 +263,9 @@ export function HubListHeader({
         )}
       </div>
       {(actions || onViewChange) && (
-        <div className="flex shrink-0 items-center gap-2">
+        // min-w-0 (not shrink-0) so shrinkable actions (the On-device filter
+        // pills) compress before the title is forced onto two lines.
+        <div className="flex min-w-0 items-center gap-2">
           {actions}
           {onViewChange && (
             <div
@@ -260,7 +309,7 @@ export function HubListHeader({
 
 export function ResultListHeader({ isDataset }: { isDataset: boolean }) {
   return (
-    <div className="flex w-full items-center gap-3 px-4 pb-2 text-[11px] font-medium text-muted-foreground/55">
+    <div className="flex w-full items-center gap-3 px-4 pb-2 text-ui-11 font-medium text-muted-foreground/55">
       <span className={LIST_COLS.model}>{isDataset ? "Dataset" : "Model"}</span>
       <span className={isDataset ? LIST_COLS.caps : LIST_COLS.capsModel}>
         {isDataset ? "Details" : "Capabilities"}
@@ -396,7 +445,7 @@ function CapabilitiesCell({
           ))}
           {extra > 0 && <span className="hub-chip shrink-0">+{extra}</span>}
           {shown.length === 0 && taskLabel && (
-            <span className="truncate text-[12px] text-muted-foreground/75">
+            <span className="truncate text-ui-12 text-muted-foreground/75">
               {taskLabel}
             </span>
           )}
@@ -405,7 +454,7 @@ function CapabilitiesCell({
       <TooltipContent side="top" align="start" className="tooltip-compact">
         <div className="flex flex-col items-start gap-1">
           {taskLabel && (
-            <span className="text-[11px] font-medium text-muted-foreground">
+            <span className="text-ui-11 font-medium text-muted-foreground">
               {taskLabel}
             </span>
           )}
@@ -524,7 +573,9 @@ function useResultRowModel(
     [isDataset, row.id, row.result, deviceType],
   );
   const sizeLabel = formatModelParamLabel(row.repo, row.result.totalParams);
-  const taskLabel = isDataset ? null : formatPipelineTag(row.result.pipelineTag);
+  const taskLabel = isDataset
+    ? null
+    : formatPipelineTag(row.result.pipelineTag);
   const unsupported = support?.status === "unsupported";
   return {
     support,
@@ -591,12 +642,12 @@ export const ResultCard = memo(function ResultCard({
       <OwnerAvatar
         owner={row.owner}
         repoName={row.repo}
-        className="size-[52px] shrink-0 rounded-[16px] text-[16px] ring-1 ring-black/5 dark:ring-white/10"
+        className="size-[52px] shrink-0 rounded-[16px] text-ui-16 ring-1 ring-black/5 dark:ring-white/10"
         remote={false}
       />
       <div className="flex min-w-0 flex-1 flex-col">
         <div className="flex min-w-0 items-center gap-2">
-          <span className="truncate text-[15px] font-semibold leading-[18px] text-foreground">
+          <span className="truncate text-ui-15 font-semibold leading-ui-18 text-foreground">
             {row.repo}
           </span>
           <TitleMarkers
@@ -608,10 +659,10 @@ export const ResultCard = memo(function ResultCard({
             onDevice={onDevice}
           />
         </div>
-        <span className="flex min-w-0 items-center gap-1 text-[12.5px] leading-[16px] text-muted-foreground/80">
+        <span className="flex min-w-0 items-center gap-1 text-ui-12p5 leading-ui-16 text-muted-foreground/80">
           <VerifiedOwner owner={row.owner} />
         </span>
-        <div className="flex min-w-0 items-center gap-2 overflow-hidden text-[11.5px] leading-[16px] tabular-nums text-muted-foreground/65">
+        <div className="flex min-w-0 items-center gap-2 overflow-hidden text-ui-11p5 leading-ui-16 tabular-nums text-muted-foreground/65">
           {textParts.map((part, index) => (
             <Fragment key={part.key}>
               {index > 0 && (
@@ -710,12 +761,12 @@ export const ResultGridRow = memo(function ResultGridRow({
           <OwnerAvatar
             owner={row.owner}
             repoName={row.repo}
-            className="size-9 shrink-0 rounded-[12px] text-[13px] ring-1 ring-black/5 dark:ring-white/10"
+            className="size-9 shrink-0 rounded-[12px] text-ui-13 ring-1 ring-black/5 dark:ring-white/10"
             remote={false}
           />
           <div className="min-w-0 flex-1">
             <div className="flex min-w-0 items-center gap-1.5">
-              <span className="truncate text-[13.5px] font-semibold leading-[17px] text-foreground">
+              <span className="truncate text-ui-13p5 font-semibold leading-ui-17 text-foreground">
                 {row.repo}
               </span>
               <TitleMarkers
@@ -727,7 +778,7 @@ export const ResultGridRow = memo(function ResultGridRow({
                 onDevice={onDevice}
               />
             </div>
-            <span className="mt-0.5 flex min-w-0 items-center gap-1 text-[11.5px] leading-[15px] text-muted-foreground/80">
+            <span className="mt-0.5 flex min-w-0 items-center gap-1 text-ui-11p5 leading-ui-15 text-muted-foreground/80">
               <VerifiedOwner owner={row.owner} />
             </span>
           </div>
@@ -735,7 +786,7 @@ export const ResultGridRow = memo(function ResultGridRow({
         <div className={isDataset ? LIST_COLS.caps : LIST_COLS.capsModel}>
           {isDataset ? (
             row.summary ? (
-              <span className="truncate text-[12px] text-muted-foreground/75">
+              <span className="truncate text-ui-12 text-muted-foreground/75">
                 {row.summary}
               </span>
             ) : null
@@ -750,7 +801,7 @@ export const ResultGridRow = memo(function ResultGridRow({
         <div
           className={cn(
             LIST_COLS.size,
-            "truncate text-[12px] tabular-nums text-muted-foreground",
+            "truncate text-ui-12 tabular-nums text-muted-foreground",
           )}
         >
           {sizeDisplay ?? "—"}
@@ -758,7 +809,7 @@ export const ResultGridRow = memo(function ResultGridRow({
         <div
           className={cn(
             LIST_COLS.updated,
-            "truncate text-[12px] tabular-nums text-muted-foreground",
+            "truncate text-ui-12 tabular-nums text-muted-foreground",
           )}
         >
           {formatRelativeShort(row.result.updatedAt)}
@@ -766,7 +817,7 @@ export const ResultGridRow = memo(function ResultGridRow({
         <div
           className={cn(
             LIST_COLS.downloads,
-            "text-[12px] tabular-nums text-muted-foreground",
+            "text-ui-12 tabular-nums text-muted-foreground",
           )}
         >
           <StatItem
@@ -777,7 +828,7 @@ export const ResultGridRow = memo(function ResultGridRow({
         <div
           className={cn(
             LIST_COLS.likes,
-            "text-[12px] tabular-nums text-muted-foreground",
+            "text-ui-12 tabular-nums text-muted-foreground",
           )}
         >
           <StatItem
@@ -832,12 +883,12 @@ export const ResultSplitRow = memo(function ResultSplitRow({
       <OwnerAvatar
         owner={row.owner}
         repoName={row.repo}
-        className="size-8 shrink-0 rounded-[9px] text-[12px]"
+        className="size-8 shrink-0 rounded-[9px] text-ui-12"
         remote={false}
       />
       <div className="flex min-w-0 flex-1 flex-col">
         <div className="flex min-w-0 items-center gap-1.5">
-          <span className="truncate text-[12.5px] font-semibold leading-[16px] text-foreground">
+          <span className="truncate text-ui-12p5 font-semibold leading-ui-16 text-foreground">
             {row.repo}
           </span>
           <TitleMarkers
@@ -849,11 +900,11 @@ export const ResultSplitRow = memo(function ResultSplitRow({
             onDevice={onDevice}
           />
         </div>
-        <span className="mt-0.5 flex min-w-0 items-center gap-1 text-[10.5px] leading-[14px] text-muted-foreground/80">
+        <span className="mt-0.5 flex min-w-0 items-center gap-1 text-ui-10p5 leading-ui-14 text-muted-foreground/80">
           <VerifiedOwner owner={row.owner} />
         </span>
       </div>
-      <div className="flex shrink-0 flex-col items-end gap-0.5 text-[10.5px] tabular-nums text-muted-foreground/70">
+      <div className="flex shrink-0 flex-col items-end gap-0.5 text-ui-10p5 tabular-nums text-muted-foreground/70">
         <div className="flex items-center gap-2">
           <span className="inline-flex items-center gap-1">
             <HugeiconsIcon
diff --git a/studio/frontend/src/features/hub/catalog/models-toolbar.tsx b/studio/frontend/src/features/hub/catalog/models-toolbar.tsx
index 7c08c9c486..a12b0b5571 100644
--- a/studio/frontend/src/features/hub/catalog/models-toolbar.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-toolbar.tsx
@@ -9,6 +9,7 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import type { HfSortKey } from "@/features/hub/hooks/use-hub-model-search";
 import { cn } from "@/lib/utils";
 import {
   AiChipIcon,
@@ -19,26 +20,25 @@ import {
   SlidersHorizontalIcon,
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
-import type { HfSortKey } from "@/features/hub/hooks/use-hub-model-search";
-import type {
-  CapabilityFilter,
-  ModelFormatFilter,
-  ModelsTab,
-  ResourceTypeFilter,
-} from "../types";
-import {
-  CAPABILITY_FILTER_OPTIONS,
-  FORMAT_FILTER_OPTIONS,
-} from "../lib/view-models";
-import { HubOptionMenu, type HubOption } from "./hub-option-menu";
+import { memo, useMemo, useState } from "react";
 import {
   clearRecentSearches,
   recordRecentSearch,
   removeRecentSearch,
   useRecentSearches,
 } from "../lib/recent-searches";
+import {
+  CAPABILITY_FILTER_OPTIONS,
+  FORMAT_FILTER_OPTIONS,
+} from "../lib/view-models";
+import type {
+  CapabilityFilter,
+  ModelFormatFilter,
+  ModelsTab,
+  ResourceTypeFilter,
+} from "../types";
+import { type HubOption, HubOptionMenu } from "./hub-option-menu";
 import { RecentSearches } from "./recent-searches";
-import { memo, useMemo, useState } from "react";
 
 // Widened so the format dropdown can carry the "Fine-tune ready" pseudo-option,
 // which opens the curated channel instead of becoming the active format filter.
@@ -175,7 +175,7 @@ export const ModelsToolbar = memo(function ModelsToolbar({
     <div className="flex min-w-0 flex-col gap-2 lg:flex-row lg:flex-nowrap lg:items-center">
       <div
         className={cn(
-          "hub-menu-trigger hub-tab-toggle relative inline-flex h-9 w-full shrink-0 items-center rounded-full lg:w-[240px]",
+          "hub-menu-trigger hub-tab-toggle relative inline-flex h-9 w-full shrink-0 items-center rounded-full lg:w-[280px]",
         )}
         role="radiogroup"
         aria-label="View"
@@ -194,7 +194,7 @@ export const ModelsToolbar = memo(function ModelsToolbar({
           aria-checked={tab === "discover"}
           onClick={() => onTabChange("discover")}
           className={cn(
-            "relative z-10 inline-flex h-9 flex-1 items-center justify-center rounded-full px-3 text-[12.5px] transition-colors",
+            "relative z-10 inline-flex h-9 flex-1 items-center justify-center rounded-full px-3 text-ui-12p5 transition-colors",
             tab === "discover"
               ? "text-foreground"
               : "text-muted-foreground hover:text-foreground",
@@ -208,7 +208,7 @@ export const ModelsToolbar = memo(function ModelsToolbar({
           aria-checked={tab === "downloaded"}
           onClick={() => onTabChange("downloaded")}
           className={cn(
-            "relative z-10 inline-flex h-9 flex-1 items-center justify-center rounded-full px-3 text-[12.5px] transition-colors",
+            "relative z-10 inline-flex h-9 flex-1 items-center justify-center rounded-full px-3 text-ui-12p5 transition-colors",
             tab === "downloaded"
               ? "text-foreground"
               : "text-muted-foreground hover:text-foreground",
@@ -219,94 +219,94 @@ export const ModelsToolbar = memo(function ModelsToolbar({
       </div>
 
       <div className="relative min-w-0 flex-1 lg:flex-[1_1_360px]">
-          <HugeiconsIcon
-            icon={Search01Icon}
-            strokeWidth={1.8}
-            className="pointer-events-none absolute left-3.5 top-1/2 size-4 -translate-y-1/2 text-muted-foreground"
-          />
-          <Input
-            // `type="search"` plus these flags stop password managers and noisy
-            // text assistance from acting on this field.
-            type="search"
-            name="hub-search"
-            autoComplete="off"
-            autoCorrect="off"
-            autoCapitalize="off"
-            spellCheck={false}
-            enterKeyHint="search"
-            data-1p-ignore={true}
-            data-lpignore={true}
-            data-form-type="other"
-            value={query}
-            onChange={(event) => onQueryChange(event.target.value)}
-            onFocus={() => setSearchFocused(true)}
-            onBlur={() => {
-              setSearchFocused(false);
-              if (isDiscover) {
-                recordRecentSearch(query);
-              }
-            }}
-            onKeyDown={(event) => {
-              if (event.key === "Enter" && isDiscover) {
-                recordRecentSearch(query);
-              } else if (event.key === "Escape" && showRecentSearches) {
-                event.currentTarget.blur();
-              }
-            }}
-            placeholder={
-              tab === "downloaded"
-                ? `Search on-device ${isDataset ? "datasets" : "models"}`
-                : isDataset
-                  ? "Search datasets"
-                  : "Search all models"
+        <HugeiconsIcon
+          icon={Search01Icon}
+          strokeWidth={1.8}
+          className="pointer-events-none absolute left-3.5 top-1/2 size-4 -translate-y-1/2 text-muted-foreground"
+        />
+        <Input
+          // `type="search"` plus these flags stop password managers and noisy
+          // text assistance from acting on this field.
+          type="search"
+          name="hub-search"
+          autoComplete="off"
+          autoCorrect="off"
+          autoCapitalize="off"
+          spellCheck={false}
+          enterKeyHint="search"
+          data-1p-ignore={true}
+          data-lpignore={true}
+          data-form-type="other"
+          value={query}
+          onChange={(event) => onQueryChange(event.target.value)}
+          onFocus={() => setSearchFocused(true)}
+          onBlur={() => {
+            setSearchFocused(false);
+            if (isDiscover) {
+              recordRecentSearch(query);
             }
-            className={cn(
-              "field-soft h-9 rounded-full !border-0 pl-10 text-[13px] placeholder:text-muted-foreground/80 focus-visible:!ring-0",
-              hasTrailing ? "pr-10" : "pr-4",
-            )}
-          />
-          {query ? (
-            <button
-              type="button"
-              aria-label="Clear search"
-              // Keep focus on the input so clearing reveals recent searches
-              // rather than dismissing the field.
-              onMouseDown={(event) => event.preventDefault()}
-              onClick={() => onQueryChange("")}
-              className="absolute right-2.5 top-1/2 inline-flex size-6 -translate-y-1/2 items-center justify-center rounded-full text-muted-foreground/70 transition-colors hover:text-foreground"
-            >
-              <HugeiconsIcon
-                icon={CancelCircleIcon}
-                strokeWidth={1.75}
-                className="size-[18px]"
-              />
-            </button>
-          ) : isDiscover && isLoading ? (
-            <Spinner className="pointer-events-none absolute right-3.5 top-1/2 size-4 -translate-y-1/2 text-muted-foreground" />
-          ) : null}
-          {showRecentSearches && (
-            <RecentSearches
-              searches={recentSearches}
-              onSelect={(value) => {
-                recordRecentSearch(value);
-                onQueryChange(value);
-              }}
-              onRemove={removeRecentSearch}
-              onClear={clearRecentSearches}
-            />
+          }}
+          onKeyDown={(event) => {
+            if (event.key === "Enter" && isDiscover) {
+              recordRecentSearch(query);
+            } else if (event.key === "Escape" && showRecentSearches) {
+              event.currentTarget.blur();
+            }
+          }}
+          placeholder={
+            tab === "downloaded"
+              ? `Search on-device ${isDataset ? "datasets" : "models"}`
+              : isDataset
+                ? "Search datasets"
+                : "Search all models"
+          }
+          className={cn(
+            "field-soft h-9 rounded-full !border-0 pl-10 text-ui-13 placeholder:text-muted-foreground/80 focus-visible:!ring-0",
+            hasTrailing ? "pr-10" : "pr-4",
           )}
-        </div>
+        />
+        {query ? (
+          <button
+            type="button"
+            aria-label="Clear search"
+            // Keep focus on the input so clearing reveals recent searches
+            // rather than dismissing the field.
+            onMouseDown={(event) => event.preventDefault()}
+            onClick={() => onQueryChange("")}
+            className="absolute right-2.5 top-1/2 inline-flex size-6 -translate-y-1/2 items-center justify-center rounded-full text-muted-foreground/70 transition-colors hover:text-foreground"
+          >
+            <HugeiconsIcon
+              icon={CancelCircleIcon}
+              strokeWidth={1.75}
+              className="size-[18px]"
+            />
+          </button>
+        ) : isDiscover && isLoading ? (
+          <Spinner className="pointer-events-none absolute right-3.5 top-1/2 size-4 -translate-y-1/2 text-muted-foreground" />
+        ) : null}
+        {showRecentSearches && (
+          <RecentSearches
+            searches={recentSearches}
+            onSelect={(value) => {
+              recordRecentSearch(value);
+              onQueryChange(value);
+            }}
+            onRemove={removeRecentSearch}
+            onClear={clearRecentSearches}
+          />
+        )}
+      </div>
 
       <div className="flex min-w-0 flex-wrap items-center gap-2 lg:flex-[0_0_auto] lg:flex-nowrap lg:justify-end">
         {tab === "downloaded" && !isDataset && (
           <Tooltip>
-            <TooltipTrigger asChild>
+            <TooltipTrigger asChild={true}>
               <button
                 type="button"
                 onClick={onManageLocalFolders}
                 className={cn(
                   triggerBase,
-                  "field-filter inline-flex h-9 shrink-0 items-center gap-1.5 rounded-full px-3 text-[12.5px]",
+                  "field-filter inline-flex h-9 shrink-0 items-center gap-1.5 rounded-full px-3 text-ui-12p5",
                 )}
               >
                 <HugeiconsIcon
@@ -359,18 +359,18 @@ export const ModelsToolbar = memo(function ModelsToolbar({
             footer={
               isDataset ? undefined : (
                 <Tooltip>
-                  <TooltipTrigger asChild>
+                  <TooltipTrigger asChild={true}>
                     <button
                       type="button"
                       role="checkbox"
                       aria-checked={fitOnDeviceOnly}
                       onClick={() => onFitOnDeviceOnlyChange(!fitOnDeviceOnly)}
-                      className="flex w-full cursor-pointer select-none items-center gap-2 rounded-[10px] px-3 py-2 text-left text-[12.5px] text-muted-foreground transition-colors hover:text-foreground"
+                      className="flex w-full cursor-pointer select-none items-center gap-2 rounded-[10px] px-3 py-2 text-left text-ui-12p5 text-muted-foreground transition-colors hover:text-foreground"
                     >
                       <Checkbox
                         checked={fitOnDeviceOnly}
                         tabIndex={-1}
-                        aria-hidden
+                        aria-hidden={true}
                         className="pointer-events-none size-3.5 rounded-full [&_svg]:!size-2.5"
                       />
                       Only show models that fit
@@ -402,7 +402,7 @@ export const ModelsToolbar = memo(function ModelsToolbar({
             )}
           />
           <Tooltip>
-            <TooltipTrigger asChild>
+            <TooltipTrigger asChild={true}>
               <button
                 type="button"
                 role="radio"
@@ -428,7 +428,7 @@ export const ModelsToolbar = memo(function ModelsToolbar({
             </TooltipContent>
           </Tooltip>
           <Tooltip>
-            <TooltipTrigger asChild>
+            <TooltipTrigger asChild={true}>
               <button
                 type="button"
                 role="radio"
diff --git a/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx b/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
index caa89db196..2b0f2c3a8d 100644
--- a/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
+++ b/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { FolderBrowser } from "@/components/assistant-ui/model-selector/folder-browser";
 import { Button } from "@/components/ui/button";
 import {
   Dialog,
@@ -22,9 +21,11 @@ import {
   addScanFolder,
   listScanFolders,
   removeScanFolder,
-} from "@/features/hub/inventory";
-import { openModelsDir } from "@/features/native-intents/api";
+} from "@/features/hub";
+import { FolderBrowser } from "@/features/model-picker";
+import { openModelsDir } from "@/features/native-intents";
 import { isTauri } from "@/lib/api-base";
+import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import {
   Delete02Icon,
@@ -38,7 +39,6 @@ import {
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "@/lib/toast";
 
 function pathTail(path: string): string {
   const parts = path.split(/[\\/]/).filter(Boolean);
@@ -123,7 +123,9 @@ export function OnDeviceFoldersDialog({
         setPath("");
         mutationVersionRef.current += 1;
         setFolders((current) => {
-          const withoutDuplicate = current.filter((row) => row.id !== folder.id);
+          const withoutDuplicate = current.filter(
+            (row) => row.id !== folder.id,
+          );
           return [...withoutDuplicate, folder];
         });
         toast.success("Location added", {
@@ -184,15 +186,18 @@ export function OnDeviceFoldersDialog({
           overlayClassName="bg-black/20 backdrop-blur-none"
         >
           <DialogHeader className="border-b border-border/60 px-5 py-4">
-            <DialogTitle className="text-[15px]">On-device locations</DialogTitle>
+            <DialogTitle className="text-ui-15">
+              On-device locations
+            </DialogTitle>
             <DialogDescription className="sr-only">
-              Hugging Face model folders, GGUF files, and adapters are indexed here.
+              Hugging Face model folders, GGUF files, and adapters are indexed
+              here.
             </DialogDescription>
           </DialogHeader>
 
           <div className="space-y-4 px-5 py-4">
             <div className="rounded-[14px] border border-border/70 bg-muted/20 p-3">
-              <div className="mb-2 flex items-center gap-2 text-[12px] font-medium text-foreground">
+              <div className="mb-2 flex items-center gap-2 text-ui-12 font-medium text-foreground">
                 <HugeiconsIcon
                   icon={FolderAddIcon}
                   strokeWidth={1.75}
@@ -217,7 +222,7 @@ export function OnDeviceFoldersDialog({
                       void handleAdd(path);
                     }}
                     placeholder="Paste model folder or file path"
-                    className="field-soft h-9 rounded-full pl-9 pr-3 font-mono text-[12px] placeholder:font-sans"
+                    className="field-soft h-9 rounded-full pl-9 pr-3 font-mono text-ui-12 placeholder:font-sans"
                   />
                 </div>
                 <div className="flex shrink-0 items-center gap-2">
@@ -247,7 +252,7 @@ export function OnDeviceFoldersDialog({
                     size="sm"
                     onClick={() => void handleAdd(path)}
                     disabled={!path.trim() || pending !== null}
-                    className="h-9 rounded-full px-3 text-[12.5px]"
+                    className="h-9 rounded-full px-3 text-ui-12p5"
                   >
                     {pending === "add" ? (
                       <Spinner className="size-3.5" />
@@ -266,14 +271,14 @@ export function OnDeviceFoldersDialog({
             </div>
 
             {error ? (
-              <div className="rounded-[10px] border border-destructive/20 bg-destructive/5 px-3 py-2 text-[12px] text-destructive">
+              <div className="rounded-[10px] border border-destructive/20 bg-destructive/5 px-3 py-2 text-ui-12 text-destructive">
                 {error}
               </div>
             ) : null}
 
             <div className="overflow-hidden rounded-[14px] border border-border/70">
               <div className="flex h-10 items-center justify-between border-b border-border/60 px-3">
-                <span className="text-[12px] font-medium text-foreground">
+                <span className="text-ui-12 font-medium text-foreground">
                   Indexed locations
                 </span>
                 <Tooltip>
@@ -300,12 +305,12 @@ export function OnDeviceFoldersDialog({
 
               <div className="max-h-64 overflow-y-auto">
                 {loading ? (
-                  <div className="flex h-24 items-center justify-center gap-2 text-[12px] text-muted-foreground">
+                  <div className="flex h-24 items-center justify-center gap-2 text-ui-12 text-muted-foreground">
                     <Spinner className="size-3.5" />
                     Loading locations...
                   </div>
                 ) : sortedFolders.length === 0 ? (
-                  <div className="flex h-28 flex-col items-center justify-center gap-2 px-4 text-center text-[12px] text-muted-foreground">
+                  <div className="flex h-28 flex-col items-center justify-center gap-2 px-4 text-center text-ui-12 text-muted-foreground">
                     <HugeiconsIcon
                       icon={FolderOpenIcon}
                       strokeWidth={1.75}
@@ -335,16 +340,14 @@ export function OnDeviceFoldersDialog({
                         </div>
                         <div className="min-w-0 overflow-hidden">
                           <p
-                            className="block w-full truncate text-[12.5px] font-medium text-foreground"
+                            className="block w-full truncate text-ui-12p5 font-medium text-foreground"
                             title={pathTail(folder.path)}
                           >
                             {pathTail(folder.path)}
                           </p>
                           <Tooltip>
                             <TooltipTrigger asChild={true}>
-                              <p
-                                className="block w-full truncate font-mono text-[10.5px] text-muted-foreground"
-                              >
+                              <p className="block w-full truncate font-mono text-ui-10p5 text-muted-foreground">
                                 {folder.path}
                               </p>
                             </TooltipTrigger>
@@ -372,7 +375,10 @@ export function OnDeviceFoldersDialog({
                                 />
                               </button>
                             </TooltipTrigger>
-                            <TooltipContent side="left" className="tooltip-compact">
+                            <TooltipContent
+                              side="left"
+                              className="tooltip-compact"
+                            >
                               Open in file manager
                             </TooltipContent>
                           </Tooltip>
@@ -397,7 +403,10 @@ export function OnDeviceFoldersDialog({
                               )}
                             </button>
                           </TooltipTrigger>
-                          <TooltipContent side="left" className="tooltip-compact">
+                          <TooltipContent
+                            side="left"
+                            className="tooltip-compact"
+                          >
                             Remove from list
                           </TooltipContent>
                         </Tooltip>
diff --git a/studio/frontend/src/features/hub/catalog/owner-avatar.tsx b/studio/frontend/src/features/hub/catalog/owner-avatar.tsx
index 852c09ab5f..ac8bee9ade 100644
--- a/studio/frontend/src/features/hub/catalog/owner-avatar.tsx
+++ b/studio/frontend/src/features/hub/catalog/owner-avatar.tsx
@@ -13,10 +13,10 @@ import {
 type AvatarSize = "xs" | "sm" | "md" | "lg";
 
 const SIZES: Record<AvatarSize, string> = {
-  xs: "size-5 rounded-[8px] text-[9px]",
-  sm: "size-7 rounded-[10px] text-[11px]",
-  md: "size-9 rounded-[12px] text-[13px]",
-  lg: "size-12 rounded-[15px] text-[16px]",
+  xs: "size-5 rounded-[8px] text-ui-9",
+  sm: "size-7 rounded-[10px] text-ui-11",
+  md: "size-9 rounded-[12px] text-ui-13",
+  lg: "size-12 rounded-[15px] text-ui-16",
 };
 
 const AVATAR_IMAGE_RETRY_BASE_MS = 60_000;
diff --git a/studio/frontend/src/features/hub/catalog/owner-scope-toggle.tsx b/studio/frontend/src/features/hub/catalog/owner-scope-toggle.tsx
index 5f36f5d031..d2870a09c4 100644
--- a/studio/frontend/src/features/hub/catalog/owner-scope-toggle.tsx
+++ b/studio/frontend/src/features/hub/catalog/owner-scope-toggle.tsx
@@ -29,7 +29,7 @@ export function OwnerScopeToggle({
       ariaLabel="Publisher scope"
       align="end"
       // Extra gap before the chevron; min-width keeps the pill readable.
-      className="h-8 min-w-[96px] gap-1.5 text-[11.5px]"
+      className="h-8 min-w-[96px] gap-1.5 text-ui-11p5"
     />
   );
 }
diff --git a/studio/frontend/src/features/hub/catalog/path-info-button.tsx b/studio/frontend/src/features/hub/catalog/path-info-button.tsx
index 0d5ca6e00e..403bb0148e 100644
--- a/studio/frontend/src/features/hub/catalog/path-info-button.tsx
+++ b/studio/frontend/src/features/hub/catalog/path-info-button.tsx
@@ -1,38 +1,83 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogHeader,
-  DialogTitle,
-} from "@/components/ui/dialog";
 import {
   Tooltip,
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import { usePlatformStore } from "@/config/env";
+import { revealCachedModel } from "@/features/chat";
+import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
-import { Copy01Icon, FolderSearchIcon } from "@hugeicons/core-free-icons";
+import { Copy01Icon, Folder01Icon } from "@hugeicons/core-free-icons";
 import { Tick02Icon } from "@/lib/tick-icon";
 import { HugeiconsIcon } from "@hugeicons/react";
 import type { MouseEvent } from "react";
-import { useState } from "react";
 import { useCopyFeedback } from "../hooks/use-copy-feedback";
 
+/** Reveal a cached repo (or one GGUF variant's file) in the OS file manager.
+ *  Resolved server-side from the HF cache, so only managed repos qualify. */
+export function RevealPathButton({
+  repoId,
+  variant,
+  className,
+}: {
+  repoId: string;
+  variant?: string | null;
+  className?: string;
+}) {
+  const deviceType = usePlatformStore((s) => s.deviceType);
+  const revealLabel =
+    deviceType === "mac"
+      ? "Reveal in Finder"
+      : deviceType === "windows"
+        ? "Reveal in File Explorer"
+        : "Reveal in File Manager";
+
+  return (
+    <Tooltip>
+      <TooltipTrigger asChild={true}>
+        <button
+          type="button"
+          aria-label={revealLabel}
+          onClick={(e) => {
+            e.stopPropagation();
+            revealCachedModel(repoId, variant ?? undefined).catch((err) => {
+              toast.error(
+                err instanceof Error
+                  ? err.message
+                  : "Failed to open file manager",
+              );
+            });
+          }}
+          className={cn(
+            "inline-flex size-7 shrink-0 cursor-pointer items-center justify-center rounded-full text-muted-foreground opacity-0 transition-[opacity,background-color,color] duration-150 hover:bg-muted hover:text-foreground focus-visible:opacity-100 group-hover/dl:opacity-100",
+            className,
+          )}
+        >
+          <HugeiconsIcon
+            icon={Folder01Icon}
+            strokeWidth={1.75}
+            className="size-4"
+          />
+        </button>
+      </TooltipTrigger>
+      <TooltipContent side="bottom" className="tooltip-compact">
+        {revealLabel}
+      </TooltipContent>
+    </Tooltip>
+  );
+}
+
+/** Copies the on-disk path straight to the clipboard, no dialog. */
 export function PathInfoButton({
   path,
-  title = "On-device location",
-  description = "Where this model lives on disk.",
   className,
 }: {
   path: string;
-  title?: string;
-  description?: string;
   className?: string;
 }) {
-  const [open, setOpen] = useState(false);
   const { copied, copy } = useCopyFeedback();
 
   const handleCopy = async (event: MouseEvent<HTMLButtonElement>) => {
@@ -42,67 +87,27 @@ export function PathInfoButton({
   };
 
   return (
-    <>
-      <Tooltip>
-        <TooltipTrigger asChild={true}>
-          <button
-            type="button"
-            aria-label="Show on-device path"
-            onClick={(e) => {
-              e.stopPropagation();
-              setOpen(true);
-            }}
-            className={cn(
-              "inline-flex size-7 shrink-0 cursor-pointer items-center justify-center rounded-full text-muted-foreground opacity-0 transition-[opacity,background-color,color] duration-150 hover:bg-muted hover:text-foreground focus-visible:opacity-100 group-hover/dl:opacity-100",
-              className,
-            )}
-          >
-            <HugeiconsIcon
-              icon={FolderSearchIcon}
-              strokeWidth={1.75}
-              className="size-4"
-            />
-          </button>
-        </TooltipTrigger>
-        <TooltipContent side="bottom" className="tooltip-compact">
-          Show path
-        </TooltipContent>
-      </Tooltip>
-      <Dialog open={open} onOpenChange={setOpen}>
-        <DialogContent
-          className="sm:max-w-[520px]"
-          onClick={(e) => e.stopPropagation()}
+    <Tooltip>
+      <TooltipTrigger asChild={true}>
+        <button
+          type="button"
+          aria-label="Copy on-device path"
+          onClick={handleCopy}
+          className={cn(
+            "inline-flex size-7 shrink-0 cursor-pointer items-center justify-center rounded-full text-muted-foreground opacity-0 transition-[opacity,background-color,color] duration-150 hover:bg-muted hover:text-foreground focus-visible:opacity-100 group-hover/dl:opacity-100",
+            className,
+          )}
         >
-          <DialogHeader>
-            <DialogTitle>{title}</DialogTitle>
-            <DialogDescription>{description}</DialogDescription>
-          </DialogHeader>
-          <div className="flex items-stretch gap-2">
-            <div className="flex-1 select-text rounded-[10px] border border-border bg-muted/30 px-3 py-2.5 text-[12px] leading-5 text-foreground/85 break-all">
-              {path}
-            </div>
-            <Tooltip>
-              <TooltipTrigger asChild={true}>
-                <button
-                  type="button"
-                  aria-label="Copy path"
-                  onClick={handleCopy}
-                  className="inline-flex shrink-0 cursor-pointer items-center justify-center rounded-[10px] border border-border bg-muted/30 px-3 text-muted-foreground transition-colors hover:bg-muted hover:text-foreground"
-                >
-                  <HugeiconsIcon
-                    icon={copied ? Tick02Icon : Copy01Icon}
-                    strokeWidth={1.75}
-                    className="size-4"
-                  />
-                </button>
-              </TooltipTrigger>
-              <TooltipContent side="bottom" className="tooltip-compact">
-                {copied ? "Copied" : "Copy path"}
-              </TooltipContent>
-            </Tooltip>
-          </div>
-        </DialogContent>
-      </Dialog>
-    </>
+          <HugeiconsIcon
+            icon={copied ? Tick02Icon : Copy01Icon}
+            strokeWidth={1.75}
+            className="size-4"
+          />
+        </button>
+      </TooltipTrigger>
+      <TooltipContent side="bottom" className="tooltip-compact">
+        {copied ? "Copied" : "Copy path"}
+      </TooltipContent>
+    </Tooltip>
   );
 }
diff --git a/studio/frontend/src/features/hub/catalog/recent-searches.tsx b/studio/frontend/src/features/hub/catalog/recent-searches.tsx
index 28f4d71510..a7fd10900f 100644
--- a/studio/frontend/src/features/hub/catalog/recent-searches.tsx
+++ b/studio/frontend/src/features/hub/catalog/recent-searches.tsx
@@ -30,13 +30,13 @@ export function RecentSearches({
       onMouseDown={(event) => event.preventDefault()}
     >
       <div className="flex items-center justify-between gap-2 px-2.5 pb-1.5 pt-1">
-        <span className="text-[11px] font-semibold uppercase tracking-[0.04em] text-muted-foreground/70">
+        <span className="text-ui-11 font-semibold uppercase tracking-[0.04em] text-muted-foreground/70">
           Recent searches
         </span>
         <button
           type="button"
           onClick={onClear}
-          className="hub-recent-clear rounded-full px-2 py-0.5 text-[11.5px] font-medium text-muted-foreground transition-colors hover:text-foreground"
+          className="hub-recent-clear rounded-full px-2 py-0.5 text-ui-11p5 font-medium text-muted-foreground transition-colors hover:text-foreground"
         >
           Clear all
         </button>
@@ -55,7 +55,7 @@ export function RecentSearches({
                   strokeWidth={1.75}
                   className="size-4 shrink-0 text-muted-foreground/70"
                 />
-                <span className="truncate text-[13px] text-foreground">
+                <span className="truncate text-ui-13 text-foreground">
                   {query}
                 </span>
               </button>
diff --git a/studio/frontend/src/features/hub/catalog/safetensors-download-card.tsx b/studio/frontend/src/features/hub/catalog/safetensors-download-card.tsx
index 424afa2e05..94c5175e8e 100644
--- a/studio/frontend/src/features/hub/catalog/safetensors-download-card.tsx
+++ b/studio/frontend/src/features/hub/catalog/safetensors-download-card.tsx
@@ -7,37 +7,36 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
-import { useRepoDownload } from "../download-manager";
-import { deleteCachedModel } from "../inventory";
 import { cn } from "@/lib/utils";
 import {
   Alert02Icon,
-  PencilEdit02Icon,
   PlayIcon,
+  RemoveCircleIcon,
 } from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { useEffect, useState } from "react";
 import { TrainIcon } from "../components/train-icon";
+import { useRepoDownload } from "../download-manager";
+import { useOnlineStatus } from "../hooks/use-online-status";
+import { deleteCachedModel } from "../inventory";
+import type { ModelInventoryFormat } from "../inventory";
+import { fetchModelSize } from "../lib/dataset-size";
+import { formatBytes } from "../lib/format";
 import {
   HUB_NON_GGUF_RUN_ACTIONS_VISIBLE,
   HUB_POST_DOWNLOAD_ACTIONS_VISIBLE,
 } from "../lib/hub-feature-flags";
-import { HugeiconsIcon } from "@hugeicons/react";
-import { useEffect, useState } from "react";
-import { useHfTokenStore } from "../stores/hf-token-store";
-import { fetchModelSize } from "../lib/dataset-size";
-import { formatBytes } from "../lib/format";
 import { fingerprintToken } from "../lib/token-fingerprint";
-import { useOnlineStatus } from "../hooks/use-online-status";
+import { useHfTokenStore } from "../stores/hf-token-store";
+import { DotTag } from "./dot-tag";
 import {
   CardDivider,
-  CardDeleteButton,
   DeleteConfirmDialog,
   DownloadActionButton,
   DownloadCard,
 } from "./download-card";
-import { DotTag } from "./dot-tag";
-import { PathInfoButton } from "./path-info-button";
+import { QuantOptionsMenu } from "./gguf-download-card";
 import { useCardDelete } from "./use-card-delete";
-import type { ModelInventoryFormat } from "../inventory";
 import { useDownloadCardState } from "./use-download-card-state";
 
 function formatModelLabel(modelFormat?: ModelInventoryFormat | null): string {
@@ -65,7 +64,7 @@ export function SafetensorsDownloadCard({
   cachePath,
   knownBytes,
   onLoad,
-  onUseInChat,
+  onEject,
   onTrain,
   onChange,
 }: {
@@ -77,10 +76,13 @@ export function SafetensorsDownloadCard({
   canRun?: boolean;
   isActive: boolean;
   isLoadingThisModel: boolean;
+  /** Owning cache dir, threaded into delete so it targets this copy. */
   cachePath?: string | null;
   knownBytes?: number | null;
   onLoad: (opts: { ggufVariant?: string; expectedBytes?: number }) => void;
+  /** Accepted for API parity; the run bar ejects instead of opening chat. */
   onUseInChat?: () => void;
+  onEject?: () => void;
   onTrain?: () => void;
   onChange?: () => void;
 }) {
@@ -95,11 +97,12 @@ export function SafetensorsDownloadCard({
     knownBytes && knownBytes > 0
       ? knownBytes
       : modelSize.key === sizeKey
-      ? modelSize.bytes
-      : null;
+        ? modelSize.bytes
+        : null;
   const [deleteRepoOpen, setDeleteRepoOpen] = useState(false);
   const { deleting, runDelete } = useCardDelete({
-    action: () => deleteCachedModel(repoId, undefined, hfToken || undefined),
+    action: () =>
+      deleteCachedModel(repoId, undefined, hfToken || undefined, cachePath ?? undefined),
     resourceName: "model",
     successMessage: () => `Deleted ${repoId}`,
     onSuccess: () => {
@@ -170,7 +173,8 @@ export function SafetensorsDownloadCard({
     !isLoadingThisModel;
 
   return (
-    <div className="flex w-full flex-col gap-2"><DownloadCard
+    <div className="flex w-full flex-col gap-2">
+      <DownloadCard
         job={job}
         progress={downloading ? progress : null}
         dialogs={
@@ -197,7 +201,7 @@ export function SafetensorsDownloadCard({
         }
       >
         <div className="relative flex h-9 min-w-0 flex-1 items-center pl-3 pr-2">
-          <span className="flex items-center gap-1.5 text-[12px] text-muted-foreground">
+          <span className="flex items-center gap-1.5 text-ui-12 text-muted-foreground">
             {(isActive || isDownloaded) && (
               <DotTag
                 tone="success"
@@ -206,7 +210,7 @@ export function SafetensorsDownloadCard({
             )}
             {!isDownloaded && !isActive && isPartial && !downloading && (
               <Tooltip>
-                <TooltipTrigger asChild>
+                <TooltipTrigger asChild={true}>
                   <span className="inline-flex">
                     <DotTag tone="warning" label="Partial" />
                   </span>
@@ -227,17 +231,20 @@ export function SafetensorsDownloadCard({
             )}
           </span>
           <div className="ml-auto flex items-center gap-0.5">
-            {canDelete && (
-              <CardDeleteButton
-                label={`Delete ${repoId}`}
-                onClick={() => setDeleteRepoOpen(true)}
-              />
-            )}
-            {isDownloaded && cachePath && (
-              <PathInfoButton
-                path={cachePath}
-                title="On-device location"
-                description={`Where ${repoId} lives on disk.`}
+            {/* TODO: inference settings gear hidden for now, work on it in a future PR. */}
+            {/* Same 3-dots menu as GGUF, at repo level (no quant); pinning is
+                omitted in the run bar. Managed HF-cache repos only. */}
+            {(isDownloaded || (isPartial && !downloading)) &&
+              !/^([/\\~.]|[A-Za-z]:)/.test(repoId) && (
+              <QuantOptionsMenu
+                repoId={repoId}
+                label={repoId}
+                downloaded={isDownloaded}
+                canDelete={canDelete}
+                onDelete={() => setDeleteRepoOpen(true)}
+                showPin={false}
+                buttonClassName="ml-0.5 size-7"
+                iconClassName="size-4"
               />
             )}
           </div>
@@ -268,7 +275,7 @@ export function SafetensorsDownloadCard({
               onClick={() => {
                 if (!canRun) return;
                 if (isActive) {
-                  onUseInChat?.();
+                  onEject?.();
                   return;
                 }
                 onLoad({});
@@ -287,26 +294,26 @@ export function SafetensorsDownloadCard({
                 </>
               ) : isActive ? (
                 <>
-                  <HugeiconsIcon icon={PencilEdit02Icon} strokeWidth={1.75} />
-                  Chat
+                  <HugeiconsIcon icon={RemoveCircleIcon} strokeWidth={1.75} />
+                  Eject
                 </>
-              ) : !canRun ? (
-                <>
-                  <HugeiconsIcon icon={Alert02Icon} strokeWidth={1.75} />
-                  No run
-                </>
-              ) : (
+              ) : canRun ? (
                 <>
                   <HugeiconsIcon icon={PlayIcon} strokeWidth={1.75} />
                   Run
                 </>
+              ) : (
+                <>
+                  <HugeiconsIcon icon={Alert02Icon} strokeWidth={1.75} />
+                  No run
+                </>
               )}
             </button>
           </div>
         ) : showUnavailableAction ? (
           <button
             type="button"
-            disabled
+            disabled={true}
             className="hub-action-btn w-28 opacity-70"
           >
             <HugeiconsIcon icon={Alert02Icon} strokeWidth={1.75} />
diff --git a/studio/frontend/src/features/hub/catalog/sampling-settings-dialog.tsx b/studio/frontend/src/features/hub/catalog/sampling-settings-dialog.tsx
new file mode 100644
index 0000000000..bc86a6302c
--- /dev/null
+++ b/studio/frontend/src/features/hub/catalog/sampling-settings-dialog.tsx
@@ -0,0 +1,435 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+// Gear button for the GGUF run bar: model config, system prompt, reasoning,
+// sampling, tools and retrieval, using the same controls as the chat page's
+// Run settings. Edits write to the chat runtime store's persisted state.
+
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import { InfoHint } from "@/components/ui/info-hint";
+import { Switch } from "@/components/ui/switch";
+import { Textarea } from "@/components/ui/textarea";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import {
+  ParamSlider,
+  useChatModelRuntime,
+  useChatRuntimeStore,
+} from "@/features/chat";
+import {
+  type PerModelConfig,
+  SidebarModelConfig,
+  applyPerModelConfigToRuntime,
+  currentRuntimePerModelConfig,
+  useActiveModelConfig,
+} from "@/features/model-picker";
+import { RetrievalSettingsSection } from "@/features/rag";
+import { toast } from "@/lib/toast";
+import { cn } from "@/lib/utils";
+import { Settings02Icon } from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { type ReactNode, useCallback, useState } from "react";
+import { HubOptionMenu } from "./hub-option-menu";
+
+function SettingsSection({
+  label,
+  labelClassName,
+  children,
+}: {
+  label: string;
+  labelClassName?: string;
+  children: ReactNode;
+}) {
+  return (
+    <div className="border-t border-border/50 pb-5 pt-5 first:border-t-0 first:pt-0">
+      <div
+        className={cn(
+          "pb-4 text-ui-11 font-semibold uppercase tracking-wider text-muted-foreground",
+          labelClassName,
+        )}
+      >
+        {label}
+      </div>
+      <div className="flex flex-col gap-5">{children}</div>
+    </div>
+  );
+}
+
+function ToggleRow({
+  label,
+  info,
+  checked,
+  disabled,
+  onCheckedChange,
+}: {
+  label: string;
+  info?: string;
+  checked: boolean;
+  disabled?: boolean;
+  onCheckedChange: (checked: boolean) => void;
+}) {
+  return (
+    <div className="flex items-center justify-between gap-3">
+      <div className="flex min-w-0 items-center gap-1.5">
+        <span className="text-ui-13 font-medium text-nav-fg">{label}</span>
+        {info && <InfoHint>{info}</InfoHint>}
+      </div>
+      <Switch
+        checked={checked}
+        disabled={disabled}
+        onCheckedChange={(value) => onCheckedChange(value === true)}
+        aria-label={label}
+      />
+    </div>
+  );
+}
+
+export function SamplingSettingsButton({ className }: { className?: string }) {
+  const [open, setOpen] = useState(false);
+  const params = useChatRuntimeStore((s) => s.params);
+  const setParams = useChatRuntimeStore((s) => s.setParams);
+
+  // Loaded model's per-model config (context length etc.), mirroring the chat
+  // page's Run settings Model section.
+  const { selectModel } = useChatModelRuntime();
+  const modelLoading = useChatRuntimeStore((s) => s.modelLoading);
+  const activeGgufVariant = useChatRuntimeStore((s) => s.activeGgufVariant);
+  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
+  const ggufNativeContextLength = useChatRuntimeStore(
+    (s) => s.ggufNativeContextLength,
+  );
+  const {
+    checkpoint,
+    isGguf: activeModelIsGguf,
+    config: activeModelConfig,
+  } = useActiveModelConfig();
+  const handleReloadActiveModel = useCallback(
+    (config: PerModelConfig) => {
+      const runtime = useChatRuntimeStore.getState();
+      const activeCheckpoint = runtime.params.checkpoint;
+      if (!activeCheckpoint) return;
+      const nativeToken = runtime.activeNativePathToken;
+      const nativeExpiry = runtime.activeNativePathExpiresAtMs;
+      // Mirrors the chat page: an expired native-path token can't reload.
+      if (nativeToken && nativeExpiry != null && Date.now() >= nativeExpiry) {
+        toast.error("This local model file's access has expired.", {
+          description: "Re-select the model file to reload it.",
+        });
+        return;
+      }
+      // selectModel reads config from the runtime store, not the selection, so
+      // apply it first (snapshotting the current one for rollback).
+      const previousConfig = currentRuntimePerModelConfig({
+        includeMaxSeqLength: true,
+      });
+      applyPerModelConfigToRuntime(config);
+      void selectModel({
+        id: activeCheckpoint,
+        source: "local",
+        ggufVariant: runtime.activeGgufVariant ?? undefined,
+        nativePathToken: nativeToken ?? undefined,
+        nativePathExpiresAtMs: nativeExpiry,
+        isGguf: activeModelIsGguf,
+        isDownloaded: true,
+        keepSpeculative: true,
+        previousConfig,
+        forceReload: true,
+      });
+    },
+    [selectModel, activeModelIsGguf],
+  );
+
+  // Reasoning + tools: same store bindings as the chat page.
+  const reasoningEnabled = useChatRuntimeStore((s) => s.reasoningEnabled);
+  const reasoningAlwaysOn = useChatRuntimeStore((s) => s.reasoningAlwaysOn);
+  const setReasoningEnabled = useChatRuntimeStore((s) => s.setReasoningEnabled);
+  const reasoningEffort = useChatRuntimeStore((s) => s.reasoningEffort);
+  const reasoningEffortLevels = useChatRuntimeStore(
+    (s) => s.reasoningEffortLevels,
+  );
+  const setReasoningEffort = useChatRuntimeStore((s) => s.setReasoningEffort);
+  const supportsPreserveThinking = useChatRuntimeStore(
+    (s) => s.supportsPreserveThinking,
+  );
+  const preserveThinking = useChatRuntimeStore((s) => s.preserveThinking);
+  const setPreserveThinking = useChatRuntimeStore((s) => s.setPreserveThinking);
+  const maxToolCalls = useChatRuntimeStore((s) => s.maxToolCallsPerMessage);
+  const setMaxToolCalls = useChatRuntimeStore(
+    (s) => s.setMaxToolCallsPerMessage,
+  );
+  const toolCallTimeout = useChatRuntimeStore((s) => s.toolCallTimeout);
+  const setToolCallTimeout = useChatRuntimeStore((s) => s.setToolCallTimeout);
+  const autoHealToolCalls = useChatRuntimeStore((s) => s.autoHealToolCalls);
+  const setAutoHealToolCalls = useChatRuntimeStore(
+    (s) => s.setAutoHealToolCalls,
+  );
+  const nudgeToolCalls = useChatRuntimeStore((s) => s.nudgeToolCalls);
+  const setNudgeToolCalls = useChatRuntimeStore((s) => s.setNudgeToolCalls);
+  const permissionMode = useChatRuntimeStore((s) => s.permissionMode);
+  const setConfirmToolCalls = useChatRuntimeStore((s) => s.setConfirmToolCalls);
+
+  const toolsEnabled = useChatRuntimeStore((s) => s.toolsEnabled);
+  const setToolsEnabled = useChatRuntimeStore((s) => s.setToolsEnabled);
+
+  const set = (key: keyof typeof params) => (value: number) =>
+    setParams({ ...params, [key]: value });
+
+  // Slider 0-41; 41 maps to 9999 ("Max"), mirroring the chat page.
+  const toolCallsSliderValue =
+    maxToolCalls >= 9999 ? 41 : Math.min(maxToolCalls, 40);
+  // Slider 1-31; 31 maps to 9999 ("Max").
+  const timeoutSliderValue =
+    toolCallTimeout >= 9999 ? 31 : Math.min(Math.max(toolCallTimeout, 1), 30);
+
+  return (
+    <>
+      <Tooltip>
+        <TooltipTrigger asChild={true}>
+          <button
+            type="button"
+            aria-label="Inference settings"
+            onClick={(e) => {
+              e.stopPropagation();
+              setOpen(true);
+            }}
+            className={cn(
+              "inline-flex size-7 shrink-0 cursor-pointer items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-muted hover:text-foreground",
+              className,
+            )}
+          >
+            <HugeiconsIcon
+              icon={Settings02Icon}
+              strokeWidth={1.75}
+              className="size-4"
+            />
+          </button>
+        </TooltipTrigger>
+        <TooltipContent side="bottom" className="tooltip-compact">
+          Inference settings
+        </TooltipContent>
+      </Tooltip>
+      <Dialog open={open} onOpenChange={setOpen}>
+        <DialogContent
+          className="flex max-h-[85vh] flex-col gap-5 sm:max-w-[580px]"
+          onClick={(e) => e.stopPropagation()}
+        >
+          <DialogHeader>
+            <DialogTitle>Inference settings</DialogTitle>
+            <DialogDescription>
+              Applies to chats with local models.
+            </DialogDescription>
+          </DialogHeader>
+          <div className="-mr-2 flex min-h-0 flex-col overflow-y-auto overflow-x-hidden pr-2 [scrollbar-width:thin]">
+            {checkpoint && activeModelConfig && !modelLoading && (
+              <SettingsSection label="Model">
+                <SidebarModelConfig
+                  modelId={checkpoint}
+                  ggufVariant={activeGgufVariant ?? null}
+                  isGguf={activeModelIsGguf}
+                  nativeContextLength={ggufNativeContextLength}
+                  loadedContextLength={ggufContextLength}
+                  loadedConfig={activeModelConfig}
+                  onReload={handleReloadActiveModel}
+                />
+              </SettingsSection>
+            )}
+
+            <SettingsSection label="System Prompt">
+              <Textarea
+                value={params.systemPrompt}
+                onChange={(e) =>
+                  setParams({ ...params, systemPrompt: e.target.value })
+                }
+                placeholder="Instructions sent before every conversation."
+                aria-label="System prompt"
+                className="min-h-[84px] resize-y text-ui-13"
+              />
+            </SettingsSection>
+
+            <SettingsSection label="Reasoning" labelClassName="pb-5">
+              <ToggleRow
+                label="Enable reasoning"
+                checked={reasoningAlwaysOn || reasoningEnabled}
+                disabled={reasoningAlwaysOn}
+                onCheckedChange={setReasoningEnabled}
+              />
+              {reasoningEffortLevels.length > 0 && (
+                <div className="flex items-center justify-between gap-3">
+                  <span className="text-ui-13 font-medium text-nav-fg">
+                    Reasoning effort
+                  </span>
+                  <HubOptionMenu
+                    value={reasoningEffort}
+                    options={reasoningEffortLevels.map((level) => ({
+                      value: level,
+                      label: level.charAt(0).toUpperCase() + level.slice(1),
+                    }))}
+                    onValueChange={setReasoningEffort}
+                    ariaLabel="Reasoning effort"
+                    align="end"
+                    className="h-8 text-ui-11p5"
+                  />
+                </div>
+              )}
+              {supportsPreserveThinking && (
+                <ToggleRow
+                  label="Preserve thinking"
+                  info="Keep earlier turns' reasoning in context so the model can build on it. Uses more context."
+                  checked={preserveThinking}
+                  onCheckedChange={setPreserveThinking}
+                />
+              )}
+            </SettingsSection>
+
+            <SettingsSection label="Sampling">
+              <ParamSlider
+                label="Temperature"
+                value={params.temperature}
+                min={0}
+                max={2}
+                step={0.01}
+                onChange={set("temperature")}
+                info="Controls randomness. Lower values make output focused and deterministic; higher values increase variety and creativity."
+              />
+              <ParamSlider
+                label="Top P"
+                value={params.topP}
+                min={0}
+                max={1}
+                step={0.05}
+                onChange={set("topP")}
+                displayValue={params.topP === 1 ? "Off" : undefined}
+                info="Nucleus sampling. Restricts choices to the smallest set of tokens whose cumulative probability reaches this threshold. 1.0 = off."
+              />
+              <ParamSlider
+                label="Top K"
+                value={params.topK}
+                min={0}
+                max={100}
+                step={1}
+                onChange={set("topK")}
+                displayValue={params.topK === 0 ? "Off" : undefined}
+                info="Limits sampling to the K most likely tokens at each step. 0 = off."
+              />
+              <ParamSlider
+                label="Min P"
+                value={params.minP}
+                min={0}
+                max={1}
+                step={0.01}
+                onChange={set("minP")}
+                info="Drops tokens whose probability is below this fraction of the top token's probability. Filters unlikely candidates."
+              />
+              <ParamSlider
+                label="Repetition Penalty"
+                value={params.repetitionPenalty}
+                min={1}
+                max={2}
+                step={0.05}
+                onChange={set("repetitionPenalty")}
+                displayValue={
+                  params.repetitionPenalty === 1 ? "Off" : undefined
+                }
+                info="Down-weights tokens that have already appeared, reducing repetition. 1.0 = off; higher values penalize more strongly."
+              />
+              <ParamSlider
+                label="Presence Penalty"
+                value={params.presencePenalty}
+                min={0}
+                max={2}
+                step={0.1}
+                onChange={set("presencePenalty")}
+                displayValue={params.presencePenalty === 0 ? "Off" : undefined}
+                info="Penalizes any token that has already appeared at least once, encouraging the model to introduce new topics. 0 = off."
+              />
+              <ParamSlider
+                label="Max Tokens"
+                value={params.maxTokens}
+                min={64}
+                max={131072}
+                step={64}
+                onChange={set("maxTokens")}
+                valueSize={6}
+                info="Maximum number of tokens to generate per response. Generation stops at this limit or when the model emits an end-of-sequence token."
+              />
+            </SettingsSection>
+
+            <SettingsSection label="Tools">
+              <ToggleRow
+                label="Enable tools"
+                info="Master switch for tool use in chat. When off, the model answers without calling any tools."
+                checked={toolsEnabled}
+                onCheckedChange={setToolsEnabled}
+              />
+              <ToggleRow
+                label="Auto-healing tool calls"
+                info="Unsloth auto-fixes broken tool calls so inference output is never broken."
+                checked={autoHealToolCalls}
+                onCheckedChange={setAutoHealToolCalls}
+              />
+              <ToggleRow
+                label="Nudge tool calls"
+                info="When a tool call cannot be repaired, re-ask the model once so the intended tool still runs."
+                checked={nudgeToolCalls}
+                onCheckedChange={setNudgeToolCalls}
+              />
+              <ToggleRow
+                label="Confirm tool calls"
+                info="Pause every local tool call for your approval before it runs. Overridden by Full access."
+                checked={permissionMode === "ask"}
+                disabled={permissionMode === "full"}
+                onCheckedChange={setConfirmToolCalls}
+              />
+              <ParamSlider
+                label="Max Tool Calls Per Message"
+                value={toolCallsSliderValue}
+                min={0}
+                max={41}
+                step={1}
+                onChange={(v) => setMaxToolCalls(v >= 41 ? 9999 : v)}
+                displayValue={
+                  toolCallsSliderValue >= 41
+                    ? "Max"
+                    : toolCallsSliderValue === 0
+                      ? "Off"
+                      : undefined
+                }
+                info="Cap on tool/function calls the model may invoke within a single response. 0 disables tool use; Max removes the cap."
+              />
+              <ParamSlider
+                label="Max Tool Call Duration"
+                value={timeoutSliderValue}
+                min={1}
+                max={31}
+                step={1}
+                onChange={(v) => setToolCallTimeout(v >= 31 ? 9999 : v)}
+                displayValue={
+                  timeoutSliderValue >= 31
+                    ? "Max"
+                    : timeoutSliderValue === 1
+                      ? "1 minute"
+                      : `${timeoutSliderValue} minutes`
+                }
+                valueSize={10}
+                info="Per-call wall-clock limit. Long-running tool executions are terminated when this elapses; the model continues with what completed."
+              />
+            </SettingsSection>
+
+            <SettingsSection label="Retrieval">
+              <RetrievalSettingsSection />
+            </SettingsSection>
+          </div>
+        </DialogContent>
+      </Dialog>
+    </>
+  );
+}
diff --git a/studio/frontend/src/features/hub/catalog/shared.tsx b/studio/frontend/src/features/hub/catalog/shared.tsx
index c435afcfe6..94040ad3e0 100644
--- a/studio/frontend/src/features/hub/catalog/shared.tsx
+++ b/studio/frontend/src/features/hub/catalog/shared.tsx
@@ -1,12 +1,19 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import { cn } from "@/lib/utils";
 import {
   BrainIcon,
   Chat01Icon,
   CodeIcon,
   GlobeIcon,
   HeadphonesIcon,
+  ImageIcon,
   LockIcon,
   LockKeyIcon,
   SparklesIcon,
@@ -15,12 +22,6 @@ import {
 } from "@hugeicons/core-free-icons";
 import type { IconSvgElement } from "@hugeicons/react";
 import { HugeiconsIcon } from "@hugeicons/react";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/ui/tooltip";
-import { cn } from "@/lib/utils";
 import type { Capability, CapabilityKey } from "../lib/model-capabilities";
 
 const CAPABILITY_ICON: Record<CapabilityKey, IconSvgElement> = {
@@ -30,6 +31,7 @@ const CAPABILITY_ICON: Record<CapabilityKey, IconSvgElement> = {
   reasoning: BrainIcon,
   code: CodeIcon,
   embedding: SparklesIcon,
+  diffusion: ImageIcon,
   multilingual: GlobeIcon,
   conversational: Chat01Icon,
 };
@@ -45,6 +47,8 @@ const CAPABILITY_TONE: Record<CapabilityKey, string> = {
   code: "bg-cyan-500/10 text-cyan-800 dark:bg-cyan-400/20 dark:text-cyan-300",
   embedding:
     "bg-emerald-500/10 text-emerald-700 dark:bg-emerald-400/20 dark:text-emerald-300",
+  diffusion:
+    "bg-pink-500/10 text-pink-700 dark:bg-pink-400/20 dark:text-pink-300",
   multilingual:
     "bg-sky-500/10 text-sky-700 dark:bg-sky-400/20 dark:text-sky-300",
   conversational:
@@ -53,15 +57,13 @@ const CAPABILITY_TONE: Record<CapabilityKey, string> = {
 
 export function AccessChip({ label }: { label: string }) {
   return (
-    <span className="inline-flex h-6 shrink-0 items-center rounded-full border border-amber-500/30 bg-amber-500/8 px-2 text-[11px] font-medium leading-none text-amber-700 dark:text-amber-300">
+    <span className="inline-flex h-6 shrink-0 items-center rounded-full border border-amber-500/30 bg-amber-500/8 px-2 text-ui-11 font-medium leading-none text-amber-700 dark:text-amber-300">
       {label}
     </span>
   );
 }
 
-function isGatedAccess(
-  gated: false | "auto" | "manual" | undefined,
-): boolean {
+function isGatedAccess(gated: false | "auto" | "manual" | undefined): boolean {
   return gated !== false && gated !== undefined;
 }
 
@@ -142,7 +144,7 @@ export function CapabilityPill({
     <span
       aria-label={iconOnly ? capability.label : undefined}
       className={cn(
-        "inline-flex h-6 shrink-0 items-center rounded-full text-[11.5px] font-medium",
+        "inline-flex h-6 shrink-0 items-center rounded-full text-ui-11p5 font-medium",
         iconOnly ? "w-6 justify-center px-0" : "gap-1.5 px-2.5",
         CAPABILITY_TONE[capability.key],
       )}
diff --git a/studio/frontend/src/features/hub/catalog/transport-toggle.tsx b/studio/frontend/src/features/hub/catalog/transport-toggle.tsx
index 9202b88f45..bd6222094a 100644
--- a/studio/frontend/src/features/hub/catalog/transport-toggle.tsx
+++ b/studio/frontend/src/features/hub/catalog/transport-toggle.tsx
@@ -40,7 +40,7 @@ export function TransportToggle() {
   return (
     <fieldset
       aria-label="Download transport"
-      className="hub-tag-soft m-0 inline-flex h-[26px] min-w-0 items-center gap-0.5 rounded-full border-0 p-0.5 text-[11px]"
+      className="hub-tag-soft m-0 inline-flex h-[26px] min-w-0 items-center gap-0.5 rounded-full border-0 p-0.5 text-ui-11"
     >
       {OPTIONS.map((opt) => {
         const active = mode === opt.value;
diff --git a/studio/frontend/src/features/hub/components/hf-token-indicator.tsx b/studio/frontend/src/features/hub/components/hf-token-indicator.tsx
index 1e143a805c..ef45c648f7 100644
--- a/studio/frontend/src/features/hub/components/hf-token-indicator.tsx
+++ b/studio/frontend/src/features/hub/components/hf-token-indicator.tsx
@@ -40,7 +40,7 @@ export function HfTokenIndicator({ showLabel = false }: HfTokenIndicatorProps =
             onClick={() => openDialog("general")}
             aria-label={ariaLabel}
             className={cn(
-              "hub-menu-trigger field-soft inline-flex h-9 w-full items-center justify-between gap-2 rounded-[12px] py-0 pl-1.5 pr-3 text-[12.5px] font-medium text-foreground transition-colors",
+              "hub-menu-trigger field-soft inline-flex h-9 w-full items-center justify-between gap-2 rounded-[12px] py-0 pl-1.5 pr-3 text-ui-12p5 font-medium text-foreground transition-colors",
               "focus-visible:outline-none focus-visible:ring-0 focus-visible:ring-offset-0",
             )}
           >
@@ -64,7 +64,7 @@ export function HfTokenIndicator({ showLabel = false }: HfTokenIndicatorProps =
             </span>
             <span
               className={cn(
-                "shrink-0 text-[11px] font-normal tabular-nums",
+                "shrink-0 text-ui-11 font-normal tabular-nums",
                 hasToken ? "text-verified" : "text-muted-foreground/70",
               )}
             >
@@ -89,7 +89,7 @@ export function HfTokenIndicator({ showLabel = false }: HfTokenIndicatorProps =
           className={cn(
             // Solid circle reads optically larger than the flat HTTP/Xet box, so
             // keep it 22px to sit within the row rather than bulging above it.
-            "inline-flex h-[22px] w-[22px] items-center justify-center rounded-full text-[11.5px] transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+            "inline-flex h-[22px] w-[22px] items-center justify-center rounded-full text-ui-11p5 transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
             hasToken
               ? "hub-tag-soft text-muted-foreground hover:text-foreground/80"
               : "bg-destructive text-destructive-foreground hover:bg-destructive/90",
diff --git a/studio/frontend/src/features/hub/components/page-heading.tsx b/studio/frontend/src/features/hub/components/page-heading.tsx
index e7c0f003f0..06dfcd922d 100644
--- a/studio/frontend/src/features/hub/components/page-heading.tsx
+++ b/studio/frontend/src/features/hub/components/page-heading.tsx
@@ -13,7 +13,7 @@ type PageHeadingProps = {
 };
 
 const TITLE_CLASS =
-  "text-[30px] font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-[34px]";
+  "text-ui-30 font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-ui-34";
 
 export function PageHeading({
   title,
@@ -38,7 +38,7 @@ export function PageHeading({
         <h1 className={TITLE_CLASS}>{title}</h1>
       )}
       {subtitle ? (
-        <p className="mt-2 text-[13px] leading-[19px] text-muted-foreground">
+        <p className="mt-2 text-ui-13 leading-ui-19 text-muted-foreground">
           {subtitle}
         </p>
       ) : null}
diff --git a/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts b/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
index da653ddeb7..2cea1d8304 100644
--- a/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
+++ b/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
@@ -1,14 +1,10 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { DOWNLOAD_KIND } from "./constants";
 import {
   createDownloadManagerInitialState,
-  jobKeyOf,
   removeJob,
-  selectActiveJob,
   setState,
-  useDownloadManagerStore,
 } from "./download-manager-state";
 import { resetDownloadApiAdapterState } from "./download-api-adapter";
 import {
@@ -69,25 +65,6 @@ export const downloadManager: DownloadManagerController = {
   dismiss: removeJob,
 };
 
-/** Cancel the in-flight download for a staged model pick. No-op when nothing is
- *  downloading (e.g. a native/local file that was never fetched). Lets non-React
- *  callers (the chat store's abandon paths) stop a staged transfer without the
- *  useRepoDownload hook. */
-export function cancelStagedModelDownload(
-  pending: { id: string; ggufVariant?: string | null } | null,
-): void {
-  if (!pending) return;
-  const variant = pending.ggufVariant ?? null;
-  const activeJob = selectActiveJob(
-    useDownloadManagerStore.getState(),
-    DOWNLOAD_KIND.MODEL,
-    pending.id,
-    variant,
-  );
-  void downloadManager.cancel(
-    activeJob?.key ?? jobKeyOf(DOWNLOAD_KIND.MODEL, pending.id, variant),
-  );
-}
 
 if (import.meta.hot) {
   import.meta.hot.dispose(() => {
diff --git a/studio/frontend/src/features/hub/download-manager/download-manager-panel.tsx b/studio/frontend/src/features/hub/download-manager/download-manager-panel.tsx
index d57da2137b..3e5a86a879 100644
--- a/studio/frontend/src/features/hub/download-manager/download-manager-panel.tsx
+++ b/studio/frontend/src/features/hub/download-manager/download-manager-panel.tsx
@@ -108,7 +108,7 @@ function DownloadRow({ jobKey }: { jobKey: string }) {
   return (
     <li className="flex flex-col gap-1.5 py-2.5 pl-4 pr-3">
       <div className="flex items-center gap-2">
-        <span className="min-w-0 flex-1 truncate text-[12.5px] font-medium text-foreground">
+        <span className="min-w-0 flex-1 truncate text-ui-12p5 font-medium text-foreground">
           {job.repoId}
           <span className="text-muted-foreground">{variantSuffix(job)}</span>
         </span>
@@ -165,7 +165,7 @@ function DownloadRow({ jobKey }: { jobKey: string }) {
         />
       ) : null}
       {terminal || job.state === "cancelling" || job.error ? (
-        <div className="px-0 text-[11px] text-muted-foreground tabular-nums">
+        <div className="px-0 text-ui-11 text-muted-foreground tabular-nums">
           <StatusLine job={job} />
         </div>
       ) : null}
@@ -231,7 +231,7 @@ export function DownloadManagerPanel({
       ) : (
         <div className="hub-download-panel pointer-events-auto w-[min(400px,calc(100vw-2rem))] overflow-hidden">
           <div className="flex items-center gap-2 border-b border-foreground/[0.07] py-2 pl-4 pr-3">
-            <span className="min-w-0 flex-1 truncate text-[12.5px] font-semibold text-foreground">
+            <span className="min-w-0 flex-1 truncate text-ui-12p5 font-semibold text-foreground">
               {headerLabel}
             </span>
             <button
diff --git a/studio/frontend/src/features/hub/download-manager/download-progress-bar.tsx b/studio/frontend/src/features/hub/download-manager/download-progress-bar.tsx
index f28fa0c525..9005435aa1 100644
--- a/studio/frontend/src/features/hub/download-manager/download-progress-bar.tsx
+++ b/studio/frontend/src/features/hub/download-manager/download-progress-bar.tsx
@@ -41,7 +41,7 @@ export function DownloadProgressBar({
           style={{ left: `${exactPercent}%` }}
         />
       </div>
-      <div className="flex items-center justify-between gap-2 text-[10.5px] text-muted-foreground tabular-nums">
+      <div className="flex items-center justify-between gap-2 text-ui-10p5 text-muted-foreground tabular-nums">
         <span>
           {formatBytes(progress.downloadedBytes)}
           {totalLabel && ` / ${totalLabel}`}
diff --git a/studio/frontend/src/features/hub/download-manager/index.ts b/studio/frontend/src/features/hub/download-manager/index.ts
index dd88aaf3f0..60ef3851f8 100644
--- a/studio/frontend/src/features/hub/download-manager/index.ts
+++ b/studio/frontend/src/features/hub/download-manager/index.ts
@@ -20,7 +20,6 @@ export {
 } from "./constants";
 export {
   __resetDownloadManagerForTests,
-  cancelStagedModelDownload,
   clearCompletedInventoryHint,
   downloadManager,
   hydrateDownloadManager,
diff --git a/studio/frontend/src/features/hub/hooks/use-hub-paginated-search.ts b/studio/frontend/src/features/hub/hooks/use-hub-paginated-search.ts
index 882c530782..d598065d17 100644
--- a/studio/frontend/src/features/hub/hooks/use-hub-paginated-search.ts
+++ b/studio/frontend/src/features/hub/hooks/use-hub-paginated-search.ts
@@ -1,7 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { useCallback, useEffect, useRef, useState } from "react";
+import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 
 interface HfPaginatedState<T> {
   results: T[];
@@ -12,6 +12,10 @@ interface HfPaginatedState<T> {
   error: string | null;
 }
 
+interface InternalPaginatedState<T> extends HfPaginatedState<T> {
+  queryKey: object | null;
+}
+
 const INITIAL: HfPaginatedState<never> = {
   results: [],
   scannedCount: 0,
@@ -74,10 +78,15 @@ export function useHubPaginatedSearch<T>(
   options?: { enabled?: boolean },
 ): HfPaginatedState<T> & { fetchMore: () => boolean; retry: () => void } {
   const enabled = options?.enabled ?? true;
-  const [state, setState] = useState<HfPaginatedState<T>>(
-    INITIAL as HfPaginatedState<T>,
-  );
   const [retryNonce, setRetryNonce] = useState(0);
+  const queryKey = useMemo(
+    () => ({ createIter, mapItem, retryNonce }),
+    [createIter, mapItem, retryNonce],
+  );
+  const [state, setState] = useState<InternalPaginatedState<T>>({
+    ...(INITIAL as HfPaginatedState<T>),
+    queryKey: null,
+  });
   const stateRef = useRef(state);
   useEffect(() => {
     stateRef.current = state;
@@ -187,6 +196,7 @@ export function useHubPaginatedSearch<T>(
     setState({
       ...(INITIAL as HfPaginatedState<T>),
       isLoading: true,
+      queryKey,
     });
 
     const iter = createIter(controller.signal);
@@ -203,6 +213,7 @@ export function useHubPaginatedSearch<T>(
           isLoadingMore: false,
           hasMore: !done,
           error: null,
+          queryKey,
         });
       })
       .catch((err) => {
@@ -214,6 +225,7 @@ export function useHubPaginatedSearch<T>(
           isLoadingMore: false,
           hasMore: false,
           error: err instanceof Error ? err.message : "Search failed",
+          queryKey,
         });
       })
       .finally(() => {
@@ -226,7 +238,14 @@ export function useHubPaginatedSearch<T>(
     return () => {
       clearDeferredFetch();
     };
-  }, [createIter, mapItem, enabled, retryNonce, clearDeferredFetch]);
+  }, [
+    createIter,
+    mapItem,
+    enabled,
+    retryNonce,
+    queryKey,
+    clearDeferredFetch,
+  ]);
 
   const retry = useCallback(() => {
     setRetryNonce((n) => n + 1);
@@ -358,5 +377,22 @@ export function useHubPaginatedSearch<T>(
     };
   }, [enabled, fetchMore]);
 
-  return { ...state, fetchMore, retry };
+  const visibleState: InternalPaginatedState<T> =
+    state.queryKey === queryKey
+      ? state
+      : {
+          ...(INITIAL as HfPaginatedState<T>),
+          isLoading: enabled,
+          queryKey,
+        };
+  return {
+    results: visibleState.results,
+    scannedCount: visibleState.scannedCount,
+    isLoading: visibleState.isLoading,
+    isLoadingMore: visibleState.isLoadingMore,
+    hasMore: visibleState.hasMore,
+    error: visibleState.error,
+    fetchMore,
+    retry,
+  };
 }
diff --git a/studio/frontend/src/features/hub/hooks/use-selected-model-view.ts b/studio/frontend/src/features/hub/hooks/use-selected-model-view.ts
index 171dd88d3c..cceac99753 100644
--- a/studio/frontend/src/features/hub/hooks/use-selected-model-view.ts
+++ b/studio/frontend/src/features/hub/hooks/use-selected-model-view.ts
@@ -48,7 +48,12 @@ function localResource(
       ? "cached"
       : "local";
   const id =
-    row.source === "hf_cache" && repoId && !row.partial ? repoId : row.loadId;
+    row.source === "hf_cache" &&
+    row.activeCache !== false &&
+    repoId &&
+    !row.partial
+      ? repoId
+      : row.loadId;
   return {
     repoId,
     localPath: row.path,
diff --git a/studio/frontend/src/features/hub/hub-page.tsx b/studio/frontend/src/features/hub/hub-page.tsx
index d57f9636fe..9fc452b4ed 100644
--- a/studio/frontend/src/features/hub/hub-page.tsx
+++ b/studio/frontend/src/features/hub/hub-page.tsx
@@ -1,34 +1,36 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import {
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
-import { hfModelFitsDevice } from "@/components/assistant-ui/model-selector/recommended-fit";
-import { useHubInventory } from "@/features/hub/inventory";
-import { useDebouncedValue } from "@/hooks/use-debounced-value";
-import { useGpuInfo } from "@/hooks/use-gpu-info";
-import {
-  type HfModelSearchChannel,
-  type HfSortDirection,
-  type HfSortKey,
-} from "@/features/hub/hooks/use-hub-model-search";
-import { useOnlineStatus } from "@/features/hub/hooks/use-online-status";
-import { useHubInfiniteScroll } from "@/features/hub/hooks/use-hub-infinite-scroll";
-import { ggufVariantsMatch, modelIdsMatch } from "@/features/hub/lib/model-identity";
-import { cn } from "@/lib/utils";
 import { usePlatformStore } from "@/config/env";
 import {
-  hfApiToken,
-  useHfTokenStore,
-} from "@/features/hub/stores/hf-token-store";
+  isChannelEntryFresh,
+  useHubFeedStore,
+} from "./stores/hub-feed-store";
 import {
   getInferenceStatus,
   isExternalModelId,
   useChatModelRuntime,
   useChatRuntimeStore,
 } from "@/features/chat";
+import { useHubInventory } from "./inventory";
+import type {
+  HfModelSearchChannel,
+  HfSortDirection,
+  HfSortKey,
+} from "./hooks/use-hub-model-search";
+import { useOnlineStatus } from "@/features/hub";
+import { useHubInfiniteScroll } from "@/features/hub";
+import { ggufVariantsMatch, modelIdsMatch } from "./lib/model-identity";
+import { hfApiToken, useHfTokenStore } from "./stores/hf-token-store";
+import {
+  applyModelLoadConfigToRuntime,
+  currentRuntimePerModelConfig,
+  hfModelFitsDevice,
+  resolveInitialConfig,
+} from "@/features/model-picker";
+import { useDebouncedValue } from "@/hooks/use-debounced-value";
+import { useGpuInfo } from "@/hooks/use-gpu-info";
+import { cn } from "@/lib/utils";
 import { useNavigate, useSearch } from "@tanstack/react-router";
 import {
   useCallback,
@@ -38,17 +40,10 @@ import {
   useRef,
   useState,
 } from "react";
+import { ExternalLinkConfirmDialog } from "./catalog/external-link-confirm-dialog";
 import { HubDetailView } from "./catalog/hub-detail-view";
-import { HubTopBar } from "./catalog/hub-top-bar";
 import { HubFeed } from "./catalog/hub-feed";
-import { OwnerScopeToggle } from "./catalog/owner-scope-toggle";
-import {
-  type AllModelsView,
-  HubListHeader,
-  type InventorySort,
-  InventorySortControl,
-  ResultListHeader,
-} from "./catalog/models-table";
+import { HubTopBar } from "./catalog/hub-top-bar";
 import {
   ModelsCatalog,
   type ModelsCatalogHandlers,
@@ -56,14 +51,22 @@ import {
   type ModelsCatalogState,
 } from "./catalog/models-catalog";
 import { ModelsHeader } from "./catalog/models-header";
+import {
+  type AllModelsView,
+  HubListHeader,
+  type InventorySort,
+  InventorySortControl,
+  InventoryTypeFilterControl,
+  ResultListHeader,
+} from "./catalog/models-table";
 import { ModelsToolbar } from "./catalog/models-toolbar";
-import { ExternalLinkConfirmDialog } from "./catalog/external-link-confirm-dialog";
 import { OnDeviceFoldersDialog } from "./catalog/on-device-folders-dialog";
+import { OwnerScopeToggle } from "./catalog/owner-scope-toggle";
 import { useDiscoverSearch } from "./hooks/use-discover-search";
 import { useFeedWriteBack } from "./hooks/use-feed-write-back";
+import { useHiddenEmbeddingModelIds } from "./hooks/use-hidden-embedding-models";
 import { useHubFeed } from "./hooks/use-hub-feed";
 import { useHubModelVram } from "./hooks/use-hub-model-vram";
-import { useHiddenEmbeddingModelIds } from "./hooks/use-hidden-embedding-models";
 import { useModelsSelection } from "./hooks/use-models-selection";
 import {
   CHANNEL_TO_SECTION,
@@ -79,7 +82,12 @@ import {
   isHiddenModelId,
 } from "./lib/hidden-models";
 import { inventoryRowMatches, tokenizeQuery } from "./lib/inventory-search";
+import {
+  type ModelTypeFilter,
+  matchesModelType,
+} from "./lib/model-type-filter";
 import { resolveOwnerProviderLogo } from "./lib/provider-logos";
+import { fingerprintToken } from "./lib/token-fingerprint";
 import {
   buildDiscoverRows,
   detectResultFormat,
@@ -103,6 +111,10 @@ const ALL_MODELS_VIEW_STORAGE_KEY = "unsloth.hub.allModelsView";
 const INVENTORY_SORT_STORAGE_KEY = "unsloth.hub.inventorySort";
 const OWNER_SCOPE_STORAGE_KEY = "unsloth.hub.ownerScope";
 
+// Iconless models (repo name matches no provider logo, e.g. Ornith, Inkling)
+// still show in the feed once they clear this many Hugging Face likes.
+const MIN_ICONLESS_MODEL_LIKES = 30;
+
 /** Discover browsing scope: the whole Hub (default) or only the unsloth org. */
 export type OwnerScope = "unsloth" | "all";
 
@@ -451,6 +463,8 @@ export function ModelsPage() {
     setInventorySortState(sort);
     writeInventorySortPreference(sort);
   }, []);
+  const [inventoryTypeFilter, setInventoryTypeFilter] =
+    useState<ModelTypeFilter>("all");
   const [foldersDialogOpen, setFoldersDialogOpen] = useState(false);
   const [discoverFetchIntent, setDiscoverFetchIntent] = useState(0);
   const [sortBrowseActive, setSortBrowseActive] = useState(false);
@@ -569,19 +583,23 @@ export function ModelsPage() {
   const hfToken = useHfTokenStore((s) => s.token);
   const debouncedHfToken = useDebouncedValue(hfToken, 500);
   const apiHfToken = hfApiToken(debouncedHfToken);
+  const tokenFingerprint = useMemo(
+    () => fingerprintToken(apiHfToken),
+    [apiHfToken],
+  );
   const deferredFormatFilter = useDeferredValue(formatFilter);
   const deferredCapabilityFilter = useDeferredValue(capabilityFilter);
 
   const hasQuery = deferredDebouncedQuery.trim() !== "";
-  const mode: DiscoverMode = !isModelDiscover
-    ? "search"
-    : hasQuery
+  const mode: DiscoverMode = isModelDiscover
+    ? hasQuery
       ? "search"
       : urlSection != null
         ? "channel-list"
         : sortBrowseActive
           ? "search"
-          : "feed";
+          : "feed"
+    : "search";
   const isFeedMode = mode === "feed";
   const isChannelListMode = mode === "channel-list";
   const isSortBrowseMode =
@@ -633,8 +651,22 @@ export function ModelsPage() {
     online,
   });
 
+  const cachedListEntry = useHubFeedStore((state) =>
+    liveListChannel ? state.channels[liveListChannel.id] : undefined,
+  );
+  const visibleResults =
+    results.length === 0 &&
+    liveListChannel &&
+    isChannelEntryFresh(
+      cachedListEntry,
+      liveListChannel.id,
+      tokenFingerprint,
+    )
+      ? (cachedListEntry?.results ?? results)
+      : results;
+
   useFeedWriteBack({
-    channelId: isChannelListMode ? activeChannelId : null,
+    channelId: liveListChannel?.id ?? null,
     results,
     isLoading,
     accessToken: apiHfToken,
@@ -656,8 +688,13 @@ export function ModelsPage() {
     [effectiveCachedRows, effectiveLocalRows],
   );
   const modelDiscoverRows = useMemo<DiscoverRow[]>(
-    () => buildDiscoverRows(results, effectiveCachedRows, effectiveLocalRows),
-    [results, modelDiscoveryInventorySignature],
+    () =>
+      buildDiscoverRows(
+        visibleResults,
+        effectiveCachedRows,
+        effectiveLocalRows,
+      ),
+    [visibleResults, modelDiscoveryInventorySignature],
   );
 
   const datasetDiscoverRows = useMemo<DiscoverRow[]>(() => {
@@ -706,10 +743,14 @@ export function ModelsPage() {
       (row) =>
         !isHiddenModelId(row.id) &&
         !isConfiguredHiddenModelId(hiddenEmbeddingModelIds, row.id) &&
-        // The default feed only shows models with a provider logo.
+        // Feed shows logo'd models, plus iconless ones above the likes threshold.
         (!isFeedMode ||
-          resolveOwnerProviderLogo(row.owner, row.repo) !== null) &&
-        matchesFormat(detectResultFormat(row.result), effectiveDiscoverFormat) &&
+          resolveOwnerProviderLogo(row.owner, row.repo) !== null ||
+          (row.result.likes ?? 0) >= MIN_ICONLESS_MODEL_LIKES) &&
+        matchesFormat(
+          detectResultFormat(row.result),
+          effectiveDiscoverFormat,
+        ) &&
         matchesCapability(row.capabilities, deferredCapabilityFilter) &&
         (!activeChannel?.finetunableOnly || isUnslothFinetunable(row.result)) &&
         // Models already on disk stay visible regardless of device fit,
@@ -779,12 +820,15 @@ export function ModelsPage() {
     }
     return merged;
   }, [isFeedMode, feedTrendingRows, filteredDiscoverRows]);
-  const feedResults = useMemo(() => feedRows.map((row) => row.result), [feedRows]);
+  const feedResults = useMemo(
+    () => feedRows.map((row) => row.result),
+    [feedRows],
+  );
   const selectionDiscoverRows = isFeedMode ? feedRows : discoverRows;
   const selectionFilteredDiscoverRows = isFeedMode
     ? feedRows
     : filteredDiscoverRows;
-  const selectionResults = isFeedMode ? feedResults : results;
+  const selectionResults = isFeedMode ? feedResults : visibleResults;
 
   const inventoryTokens = useMemo(
     () => (isDiscoverTab ? [] : tokenizeQuery(deferredDebouncedQuery)),
@@ -809,7 +853,8 @@ export function ModelsPage() {
       // Local rows may lack a repo id, so also check path and title.
       return (
         !isHiddenModelId(row.id, row.repoId, row.path, row.title) ||
-        (inventoryTokens.length > 0 && inventoryRowMatches(row, inventoryTokens))
+        (inventoryTokens.length > 0 &&
+          inventoryRowMatches(row, inventoryTokens))
       );
     },
     [hiddenEmbeddingModelIds, inventoryTokens],
@@ -827,6 +872,7 @@ export function ModelsPage() {
             // id/title/path happens to contain an infra needle is not dropped.
             isDatasetMode ||
             (matchesFormat(row.modelFormat, deferredFormatFilter) &&
+              matchesModelType(row, inventoryTypeFilter) &&
               isVisibleInventoryRow(row)),
         ),
         inventoryTokens,
@@ -835,6 +881,7 @@ export function ModelsPage() {
       effectiveCachedRows,
       isDatasetMode,
       deferredFormatFilter,
+      inventoryTypeFilter,
       inventoryTokens,
       isVisibleInventoryRow,
     ],
@@ -850,6 +897,7 @@ export function ModelsPage() {
             // id/title/path happens to contain an infra needle is not dropped.
             isDatasetMode ||
             (matchesFormat(row.modelFormat, deferredFormatFilter) &&
+              matchesModelType(row, inventoryTypeFilter) &&
               isVisibleInventoryRow(row)),
         ),
         inventoryTokens,
@@ -858,6 +906,7 @@ export function ModelsPage() {
       effectiveLocalRows,
       isDatasetMode,
       deferredFormatFilter,
+      inventoryTypeFilter,
       inventoryTokens,
       isVisibleInventoryRow,
     ],
@@ -890,6 +939,7 @@ export function ModelsPage() {
         resourceType,
         deferredFormatFilter,
         deferredCapabilityFilter,
+        inventoryTypeFilter,
         effectiveSort,
         effectiveDirection,
         activeChannelId,
@@ -900,6 +950,7 @@ export function ModelsPage() {
       resourceType,
       deferredFormatFilter,
       deferredCapabilityFilter,
+      inventoryTypeFilter,
       effectiveSort,
       effectiveDirection,
       activeChannelId,
@@ -918,6 +969,7 @@ export function ModelsPage() {
       }
     } else {
       setDownloadedFormat("all");
+      setInventoryTypeFilter("all");
     }
     setCapabilityFilter("all");
   }, [isDiscoverTab, urlSection, navigate]);
@@ -1127,50 +1179,22 @@ export function ModelsPage() {
     (opts: ModelLoadOptions, isDownloaded: boolean) => {
       if (!selectedModel) return;
       const runId = selectedModel.resource.runId;
-      // "Load on selection" off: stage GGUF picks instead of loading, so the
-      // chat page's staging flow can read the header and show the load options.
-      // Non-GGUF models have nothing to configure pre-load, so they load now.
-      if (
-        !useChatRuntimeStore.getState().loadOnSelection &&
-        (opts.ggufVariant != null || selectedModel.isGguf)
-      ) {
-        useChatRuntimeStore.getState().stageModel({
-          id: runId,
-          ggufVariant: opts.ggufVariant,
-          isGguf: selectedModel.isGguf,
-          isDownloaded,
-          expectedBytes: opts.expectedBytes,
-        });
-        openNewChat();
-        return;
-      }
-      // Detach any leftover staged pick first so its edited knobs (e.g. a custom
-      // context length) don't leak into this load -- mirrors the chat page's
-      // detachStaged(); keepDownload keeps any staged download running.
-      useChatRuntimeStore.getState().abandonStagedModel({ keepDownload: true });
-      // Load-on-selection skips the chat sheet, so seed this GGUF pick's saved
-      // load knobs here the way the sheet's restore effect would; otherwise the
-      // remembered config is silently ignored on the Hub run path. keepSpeculative
-      // then honors the restored speculative choice across the switch.
-      const remembered =
-        opts.ggufVariant != null || selectedModel.isGguf
-          ? loadRememberedLoadSettings(
-              rememberedLoadSettingsKey({
-                id: runId,
-                ggufVariant: opts.ggufVariant,
-              }),
-            )
-          : null;
-      if (remembered) {
-        useChatRuntimeStore.getState().applyRememberedLoadSettings(remembered);
-      }
+      const resolvedConfig = resolveInitialConfig(runId, opts.ggufVariant);
+      const rememberedConfig = resolvedConfig.remembered
+        ? resolvedConfig.config
+        : null;
+      const previousConfig = currentRuntimePerModelConfig({
+        includeMaxSeqLength: true,
+      });
+      const hasAppliedConfig = applyModelLoadConfigToRuntime(rememberedConfig);
       void selectModel({
         id: runId,
         ggufVariant: opts.ggufVariant,
         isDownloaded,
         expectedBytes: opts.expectedBytes,
-        keepSpeculative: remembered != null,
+        keepSpeculative: hasAppliedConfig,
         throwOnError: true,
+        previousConfig,
       })
         .then(() => {
           // Read fresh: the load is async, so the checkpoint may have changed.
@@ -1252,6 +1276,7 @@ export function ModelsPage() {
       onLoad: handleLoad,
       onLoadLocal: handleLoadLocal,
       onUseInChat: openNewChat,
+      onEject: () => void ejectModel(),
       onTrain: handleTrain,
       onInventoryChange: refreshInventory,
       onSearchHub: handleSearchHub,
@@ -1260,6 +1285,7 @@ export function ModelsPage() {
       handleLoad,
       handleLoadLocal,
       openNewChat,
+      ejectModel,
       handleTrain,
       handleSearchHub,
       refreshInventory,
@@ -1267,31 +1293,38 @@ export function ModelsPage() {
   );
 
   const catalogState = useMemo<ModelsCatalogState>(
-    () => ({
-      tab,
-      discoverRows: listRows,
-      cachedRows: filteredCachedRows,
-      localRows: filteredLocalRows,
-      selectedId,
-      isLoading,
-      downloadedReady,
-      inventoryError,
-      inventoryWarning,
-      query,
-      activeCheckpoint,
-      activeGgufVariant,
-      searchError,
-      online,
-      isDataset: isDatasetMode,
-      inventoryTokens,
-      scannedCount,
-      loadingIntentCount: discoverFetchIntent,
-      hasMore,
-      manualFetchAvailable: discoverManualFetchAvailable,
-      hasActiveFilters:
-        !isFeedMode &&
-        (deferredFormatFilter !== "all" || deferredCapabilityFilter !== "all"),
-    }),
+    () => {
+      const typeFilterActive =
+        !isDatasetMode && inventoryTypeFilter !== "all";
+      return {
+        tab,
+        discoverRows: listRows,
+        cachedRows: filteredCachedRows,
+        localRows: filteredLocalRows,
+        selectedId,
+        isLoading,
+        downloadedReady,
+        inventoryError,
+        inventoryWarning,
+        query,
+        activeCheckpoint,
+        activeGgufVariant,
+        searchError,
+        online,
+        isDataset: isDatasetMode,
+        inventoryTokens,
+        scannedCount,
+        loadingIntentCount: discoverFetchIntent,
+        hasMore,
+        manualFetchAvailable: discoverManualFetchAvailable,
+        hasActiveFilters:
+          !isFeedMode &&
+          (deferredFormatFilter !== "all" ||
+            deferredCapabilityFilter !== "all" ||
+            (tab === "downloaded" && typeFilterActive)),
+        typeFilterActive,
+      };
+    },
     [
       tab,
       isFeedMode,
@@ -1316,6 +1349,7 @@ export function ModelsPage() {
       discoverManualFetchAvailable,
       deferredFormatFilter,
       deferredCapabilityFilter,
+      inventoryTypeFilter,
     ],
   );
 
@@ -1394,16 +1428,18 @@ export function ModelsPage() {
         </div>
       );
     }
-    const ownerToggle = !isDatasetMode ? (
+    const ownerToggle = isDatasetMode ? undefined : (
       <OwnerScopeToggle value={ownerScope} onChange={setOwnerScope} />
-    ) : undefined;
+    );
     // Compact pill so it stays beside the view-mode tabs even in the narrow
     // split pane instead of dropping to its own row.
     return (
       <div className="flex flex-col gap-3 pt-6">
         {isChannelListMode ? (
           <HubListHeader
-            title={channelSection ? HUB_SECTION_TITLE[channelSection] : "Models"}
+            title={
+              channelSection ? HUB_SECTION_TITLE[channelSection] : "Models"
+            }
             count={listCount}
             view={allModelsView}
             onViewChange={setAllModelsView}
@@ -1446,27 +1482,40 @@ export function ModelsPage() {
   ]);
 
   const downloadedHeader = useMemo(() => {
-    const sortControl = (
-      <InventorySortControl value={inventorySort} onChange={setInventorySort} />
+    // Compact pills so they stay beside the view-mode tabs even in the narrow
+    // split pane instead of dropping to their own row.
+    const controls = (
+      <div className="flex min-w-0 items-center gap-1.5">
+        {!isDatasetMode && (
+          <InventoryTypeFilterControl
+            value={inventoryTypeFilter}
+            onChange={setInventoryTypeFilter}
+          />
+        )}
+        <InventorySortControl
+          value={inventorySort}
+          onChange={setInventorySort}
+        />
+      </div>
     );
-    // Compact pill so it stays beside the view-mode tabs even in the narrow
-    // split pane instead of dropping to its own row.
     return (
       <HubListHeader
         title="On device"
-        count={visibleCachedCount + visibleLocalCount}
+        count={filteredCachedRows.length + filteredLocalRows.length}
         view={allModelsView}
         onViewChange={setAllModelsView}
-        actions={sortControl}
+        actions={controls}
       />
     );
   }, [
-    visibleCachedCount,
-    visibleLocalCount,
+    filteredCachedRows,
+    filteredLocalRows,
     allModelsView,
     setAllModelsView,
     inventorySort,
     setInventorySort,
+    inventoryTypeFilter,
+    isDatasetMode,
   ]);
 
   const detailOpen = urlModel !== null;
@@ -1557,7 +1606,7 @@ export function ModelsPage() {
               />
             </div>
           ) : (
-            <div className="hidden min-h-0 flex-1 items-center justify-center px-6 text-center text-[13px] text-muted-foreground lg:flex">
+            <div className="hidden min-h-0 flex-1 items-center justify-center px-6 text-center text-ui-13 text-muted-foreground lg:flex">
               Select a model to preview its details.
             </div>
           )
diff --git a/studio/frontend/src/features/hub/hub.css b/studio/frontend/src/features/hub/hub.css
index 947dd8cb34..8dc6dac617 100644
--- a/studio/frontend/src/features/hub/hub.css
+++ b/studio/frontend/src/features/hub/hub.css
@@ -469,7 +469,7 @@
   }
 
   .hub-page .hub-focused-heading {
-    font-size: 18px;
+    font-size: calc(1.125rem * var(--ui-font-scale, 1));
     font-weight: 600;
     letter-spacing: 0;
     color: var(--foreground);
@@ -841,7 +841,7 @@
     padding-inline: 0;
     background-color: var(--status-success);
     color: var(--primary-foreground);
-    font-size: 10.5px;
+    font-size: calc(0.65625rem * var(--ui-font-scale, 1));
     font-weight: 600;
     line-height: 1;
     font-variant-numeric: tabular-nums;
@@ -1117,9 +1117,9 @@
     background-color: transparent;
     padding-left: 0.75rem;
     padding-right: 0.75rem;
-    font-size: 13px;
+    font-size: calc(0.8125rem * var(--ui-font-scale, 1));
     font-weight: 500;
-    line-height: 18px;
+    line-height: calc(1.125rem * var(--ui-font-scale, 1));
     letter-spacing: -0.025em;
     color: var(--foreground);
     transition: color 150ms, background-color 150ms;
@@ -1164,9 +1164,9 @@
     background-color: var(--status-success);
     padding-left: 1rem;
     padding-right: 1rem;
-    font-size: 13px;
+    font-size: calc(0.8125rem * var(--ui-font-scale, 1));
     font-weight: 600;
-    line-height: 18px;
+    line-height: calc(1.125rem * var(--ui-font-scale, 1));
     letter-spacing: -0.025em;
     color: var(--primary-foreground);
     transition: background-color 150ms, transform 150ms;
@@ -1273,7 +1273,7 @@
     font-weight: 400;
     padding-top: 0.25rem;
     padding-bottom: 0.25rem;
-    line-height: 1.25rem;
+    line-height: calc(1.25rem * var(--ui-font-scale, 1));
   }
 
   .hub-page .field-trigger.field-filter:hover {
@@ -1290,7 +1290,7 @@
     border-radius: 9999px;
     border: 1px solid color-mix(in srgb, var(--foreground) 8%, transparent);
     background-color: color-mix(in srgb, var(--foreground) 2.5%, transparent);
-    font-size: 12px;
+    font-size: calc(0.75rem * var(--ui-font-scale, 1));
     line-height: 1;
     color: var(--muted-foreground);
     white-space: nowrap;
@@ -1478,7 +1478,7 @@
 
 @layer utilities {
   .hub-chip {
-    @apply inline-flex items-center gap-1 rounded-full px-2 py-[3px] text-[11px] font-medium leading-none;
+    @apply inline-flex items-center gap-1 rounded-full px-2 py-[3px] text-ui-11 font-medium leading-none;
     background-color: color-mix(in srgb, var(--foreground) 5%, transparent);
     color: var(--muted-foreground);
   }
@@ -1488,7 +1488,7 @@
   }
 
   .hub-meta-tag {
-    @apply inline-flex h-[18px] shrink-0 items-center gap-1 rounded-full px-2 text-[11px] font-medium leading-none;
+    @apply inline-flex h-[18px] shrink-0 items-center gap-1 rounded-full px-2 text-ui-11 font-medium leading-none;
     background-color: color-mix(in srgb, var(--foreground) 5%, transparent);
     color: var(--muted-foreground);
   }
diff --git a/studio/frontend/src/features/hub/index.ts b/studio/frontend/src/features/hub/index.ts
index 5d4151e87d..7d9e5b74aa 100644
--- a/studio/frontend/src/features/hub/index.ts
+++ b/studio/frontend/src/features/hub/index.ts
@@ -1,10 +1,58 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-export { cancelStagedModelDownload } from "./download-manager";
+export {
+  DownloadProgressBar,
+  downloadManager,
+  jobKeyOf,
+  subscribeJobListeners,
+  useDownloadManagerStore,
+} from "./download-manager";
+export {
+  useHubInventory,
+  type CachedInventoryRow,
+  type GgufVariantDetail,
+  type LocalInventoryRow,
+  type LocalSource,
+  type ScanFolderInfo,
+  addScanFolder,
+  deleteCachedModel,
+  invalidateGgufVariantsCache,
+  listGgufVariants,
+  listScanFolders,
+  removeScanFolder,
+} from "./inventory";
+export {
+  type HfModelResult,
+  type HfSortKey,
+  useHubModelSearch,
+} from "./hooks/use-hub-model-search";
+export { useOnlineStatus } from "./hooks/use-online-status";
+export { useHubInfiniteScroll } from "./hooks/use-hub-infinite-scroll";
 export { bumpInventoryVersion } from "./stores/inventory-events";
 export {
   getHfToken,
+  hfApiToken,
   mirrorHfTokenInto,
   useHfTokenStore,
 } from "./stores/hf-token-store";
+export { useInventoryVersion } from "./stores/inventory-events";
+export { looksLikeLocalPath } from "./lib/local-path";
+export { hubTokenHeader } from "./lib/hub-token-header";
+export {
+  ggufVariantsMatch,
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "./lib/model-identity";
+export { formatBytes, formatRelativeShort } from "./lib/format";
+export { ggufVariantDisplayLabel } from "./lib/gguf-variant-sort";
+export {
+  DeleteConfirmDialog,
+  UpdateConfirmDialog,
+} from "./catalog/download-card";
+export { HubOptionMenu, type HubOption } from "./catalog/hub-option-menu";
+export { DotTag } from "./catalog/dot-tag";
+export { TransportConflictDialog } from "./catalog/transport-conflict-dialog";
+export { TrainIcon } from "./components/train-icon";
+export { isHiddenModelId } from "./lib/hidden-models";
+export { classifyUnslothSupport } from "./lib/unsloth-support";
diff --git a/studio/frontend/src/features/hub/inventory/api.ts b/studio/frontend/src/features/hub/inventory/api.ts
index 0e01c5c0cb..d3a1abb540 100644
--- a/studio/frontend/src/features/hub/inventory/api.ts
+++ b/studio/frontend/src/features/hub/inventory/api.ts
@@ -48,6 +48,7 @@ export interface CachedGgufRepo {
   capabilities?: BackendModelCapabilities | null;
   size_bytes: number;
   cache_path?: string;
+  last_modified?: number | null;
   partial?: boolean;
   partial_transport?: string | null;
   pipeline_tag?: string | null;
@@ -65,6 +66,7 @@ export interface CachedModelRepo {
   capabilities?: BackendModelCapabilities | null;
   size_bytes: number;
   cache_path?: string;
+  last_modified?: number | null;
   partial?: boolean;
   partial_transport?: string | null;
   pipeline_tag?: string | null;
@@ -86,6 +88,7 @@ export interface LocalModelInfo {
   capabilities?: BackendModelCapabilities | null;
   source: LocalSource;
   model_id?: string | null;
+  active_cache?: boolean | null;
   base_model?: string | null;
   base_model_source?: BaseModelSource | null;
   adapter_type?: string | null;
@@ -256,11 +259,18 @@ export async function listCachedDatasets(): Promise<CachedDatasetRepo[]> {
   return data.cached;
 }
 
-export async function deleteCachedDataset(repoId: string): Promise<void> {
+export async function deleteCachedDataset(
+  repoId: string,
+  cachePath?: string | null,
+): Promise<void> {
+  const payload: Record<string, string> = { repo_id: repoId };
+  if (cachePath) {
+    payload.cache_path = cachePath;
+  }
   const response = await authFetch("/api/hub/datasets/cached", {
     method: "DELETE",
     headers: { "Content-Type": "application/json" },
-    body: JSON.stringify({ repo_id: repoId }),
+    body: JSON.stringify(payload),
   });
   await throwIfNotOk(response, `Failed to delete dataset (${response.status})`);
   bumpInventoryVersion();
@@ -270,11 +280,17 @@ export async function deleteCachedModel(
   repoId: string,
   variant?: string,
   hfToken?: string | null,
+  cachePath?: string | null,
 ): Promise<void> {
   const payload: Record<string, string> = { repo_id: repoId };
   if (variant) {
     payload.variant = variant;
   }
+  // Scope the delete to the exact cache this row represents so copies in other,
+  // previously selected caches are not removed.
+  if (cachePath) {
+    payload.cache_path = cachePath;
+  }
   const response = await authFetch("/api/hub/delete-cached", {
     method: "DELETE",
     headers: { "Content-Type": "application/json", ...hubTokenHeader(hfToken) },
diff --git a/studio/frontend/src/features/hub/inventory/types.ts b/studio/frontend/src/features/hub/inventory/types.ts
index 6f65a56037..d1f2f993cd 100644
--- a/studio/frontend/src/features/hub/inventory/types.ts
+++ b/studio/frontend/src/features/hub/inventory/types.ts
@@ -47,6 +47,7 @@ export interface CachedInventoryRow {
   capabilities: ModelInventoryCapabilities;
   bytes: number;
   cachePath?: string | null;
+  lastModified?: number | null;
   partial?: boolean;
   partialTransport?: string | null;
   pipelineTag?: string | null;
@@ -66,6 +67,8 @@ export interface LocalInventoryRow {
   title: string;
   source: LocalSource;
   sourceLabel: string;
+  modelId?: string | null;
+  displayName?: string;
   path: string;
   isGguf: boolean;
   modelFormat: ModelInventoryFormat;
@@ -80,6 +83,7 @@ export interface LocalInventoryRow {
   updatedAt: number | null;
   partial?: boolean;
   partialTransport?: string | null;
+  activeCache?: boolean | null;
   pipelineTag?: string | null;
   tags?: string[];
   libraryName?: string | null;
diff --git a/studio/frontend/src/features/hub/inventory/use-device-inventory.ts b/studio/frontend/src/features/hub/inventory/use-device-inventory.ts
index 00eaa31a22..5ff57dfff4 100644
--- a/studio/frontend/src/features/hub/inventory/use-device-inventory.ts
+++ b/studio/frontend/src/features/hub/inventory/use-device-inventory.ts
@@ -14,6 +14,7 @@ import {
   listLocalModels,
 } from "./api";
 import { useDebouncedValue } from "@/hooks/use-debounced-value";
+import { ensureHiddenModelMatchers } from "../lib/hidden-models";
 import { fingerprintToken } from "@/features/hub/lib/token-fingerprint";
 import { useInventoryVersion } from "@/features/hub/stores/inventory-events";
 import { useCallback, useEffect, useMemo } from "react";
@@ -146,12 +147,15 @@ async function runSourceFetch<K extends DeviceInventorySource>(
 ): Promise<DeviceInventoryRows[K]> {
   switch (source) {
     case "cachedGguf":
+      await ensureHiddenModelMatchers();
       return (await listCachedGguf(hfToken)) as DeviceInventoryRows[K];
     case "cachedModels":
+      await ensureHiddenModelMatchers();
       return (await listCachedModels(hfToken)) as DeviceInventoryRows[K];
     case "cachedDatasets":
       return (await listCachedDatasets()) as DeviceInventoryRows[K];
     case "localModels":
+      await ensureHiddenModelMatchers();
       return (await listLocalModels()).models as DeviceInventoryRows[K];
     case "localDatasets":
       return (await listLocalDatasets()).datasets as DeviceInventoryRows[K];
diff --git a/studio/frontend/src/features/hub/inventory/view-models.ts b/studio/frontend/src/features/hub/inventory/view-models.ts
index 334050fab4..41b4733d19 100644
--- a/studio/frontend/src/features/hub/inventory/view-models.ts
+++ b/studio/frontend/src/features/hub/inventory/view-models.ts
@@ -176,6 +176,7 @@ export function buildCachedInventoryRow(
     runtime?: string | null;
     format_variant?: string | null;
     capabilities?: BackendModelCapabilities | null;
+    last_modified?: number | null;
     optimistic?: boolean;
   },
   fallbackFormat: ModelInventoryFormat,
@@ -215,6 +216,12 @@ export function buildCachedInventoryRow(
     capabilities,
     bytes: row.size_bytes,
     cachePath: row.cache_path ?? null,
+    lastModified:
+      typeof row.last_modified === "number" &&
+      Number.isFinite(row.last_modified) &&
+      row.last_modified > 0
+        ? row.last_modified
+        : null,
     partial: row.partial ?? false,
     partialTransport: row.partial_transport ?? null,
     pipelineTag: row.pipeline_tag ?? null,
@@ -278,6 +285,8 @@ export function buildLocalInventoryRows(
         title,
         source: model.source,
         sourceLabel: localSourceLabel(model.source),
+        modelId: model.model_id ?? null,
+        displayName: model.display_name,
         path: model.path,
         isGguf: modelFormat === "gguf",
         modelFormat,
@@ -292,6 +301,7 @@ export function buildLocalInventoryRows(
         updatedAt: normalizeTimestamp(model.updated_at),
         partial: model.partial ?? false,
         partialTransport: model.partial_transport ?? null,
+        activeCache: model.active_cache ?? null,
         pipelineTag: model.pipeline_tag ?? null,
         tags: model.tags,
         libraryName: model.library_name ?? null,
diff --git a/studio/frontend/src/features/hub/lib/hidden-models.ts b/studio/frontend/src/features/hub/lib/hidden-models.ts
index 634a061e0c..c5c72aea65 100644
--- a/studio/frontend/src/features/hub/lib/hidden-models.ts
+++ b/studio/frontend/src/features/hub/lib/hidden-models.ts
@@ -1,18 +1,94 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import { authFetch } from "@/features/auth";
+import { getInventoryVersion } from "../stores/inventory-events";
+
 // Infra models hidden from browse/preview lists (Hub Discover, the chat model
 // selector, and local on-device rows). Mirrors the backend
-// `utils.hidden_models`: the RAG embedding model and the llama.cpp validation
-// probe are not usable chat models. Server-confirmed cache rows are trusted
-// because the backend applies variant-aware filtering. Optimistic cache rows
-// still use these needles until the server confirms them. Per-repo views are
-// not filtered, so reinstall flows still show downloaded files.
+// `utils.hidden_models`: the RAG embedding model, STT dictation models, and the
+// llama.cpp validation probe are not usable chat models. Server-confirmed cache
+// rows are trusted because the backend applies variant-aware filtering.
+// Optimistic cache rows still use these needles until the server confirms them.
+// The dynamic matchers fetched from `/api/hub/hidden-models` add the user's
+// configured embedder as exact repo ids and exact resolved paths, never
+// substring needles. Per-repo views are not filtered, so reinstall flows still
+// show downloaded files.
 const HIDDEN_NEEDLES = [
   "bge-small-en-v1.5", // RAG embedder: unsloth/bge-small-en-v1.5[-GGUF]
   "ggml-org/models", // llama.cpp validation probe repo
   "stories260k.gguf", // probe filename (carries .gguf so it stays specific)
 ];
+const HIDDEN_STT_REPOS = new Set([
+  // Transformers safetensors repos and their whisper.cpp GGUF companions
+  // (unslothai/whisper-*-GGUF): STT-only, never chat models.
+  "unsloth/whisper-tiny",
+  "unsloth/whisper-base",
+  "unsloth/whisper-small",
+  "unsloth/whisper-large-v3-turbo",
+  "unsloth/whisper-large-v3",
+  "unslothai/whisper-tiny-gguf",
+  "unslothai/whisper-base-gguf",
+  "unslothai/whisper-small-gguf",
+  "unslothai/whisper-large-v3-turbo-gguf",
+  "unslothai/whisper-large-v3-gguf",
+]);
+const HIDDEN_STT_CACHE_NAMES = [...HIDDEN_STT_REPOS].map((repo) =>
+  repo.replace("/", "--"),
+);
+
+let dynamicNeedles: readonly string[] = [];
+let dynamicExactIds: readonly string[] = [];
+let dynamicExactPaths: readonly string[] = [];
+let matchersFetch: Promise<void> | null = null;
+let matchersFetchVersion = -1;
+
+function toLowerStrings(value: unknown): string[] {
+  if (!Array.isArray(value)) {
+    return [];
+  }
+  return value
+    .filter((v): v is string => typeof v === "string" && v.length > 0)
+    .map((v) => v.toLowerCase());
+}
+
+export function ensureHiddenModelMatchers(): Promise<void> {
+  const version = getInventoryVersion();
+  if (matchersFetch && matchersFetchVersion === version) {
+    return matchersFetch;
+  }
+  matchersFetchVersion = version;
+  matchersFetch = (async () => {
+    try {
+      const response = await authFetch("/api/hub/hidden-models");
+      if (!response.ok) {
+        throw new Error(`HTTP ${response.status}`);
+      }
+      const data = (await response.json()) as {
+        needles?: unknown;
+        exact_ids?: unknown;
+        exact_paths?: unknown;
+      };
+      if (
+        getInventoryVersion() !== version ||
+        matchersFetchVersion !== version
+      ) {
+        return;
+      }
+      dynamicNeedles = toLowerStrings(data.needles);
+      dynamicExactIds = toLowerStrings(data.exact_ids);
+      dynamicExactPaths = toLowerStrings(data.exact_paths);
+    } catch {
+      if (
+        getInventoryVersion() === version &&
+        matchersFetchVersion === version
+      ) {
+        matchersFetch = null;
+      }
+    }
+  })();
+  return matchersFetch;
+}
 
 /** True if any id/path is a hidden infra model. */
 export function isHiddenModelId(
@@ -23,7 +99,18 @@ export function isHiddenModelId(
       return false;
     }
     const lower = v.toLowerCase();
-    return HIDDEN_NEEDLES.some((needle) => lower.includes(needle));
+    const normalized = lower.trim().replace(/^\/+|\/+$/g, "");
+    const pathParts = lower.split(/[\\/]/);
+    return (
+      HIDDEN_STT_REPOS.has(normalized) ||
+      HIDDEN_STT_CACHE_NAMES.some((name) =>
+        pathParts.includes(`models--${name}`),
+      ) ||
+      HIDDEN_NEEDLES.some((needle) => lower.includes(needle)) ||
+      dynamicNeedles.some((needle) => lower.includes(needle)) ||
+      dynamicExactIds.includes(lower) ||
+      dynamicExactPaths.includes(lower)
+    );
   });
 }
 
diff --git a/studio/frontend/src/features/hub/lib/model-capabilities.ts b/studio/frontend/src/features/hub/lib/model-capabilities.ts
index 033a3b6f1f..1baa3fb8e0 100644
--- a/studio/frontend/src/features/hub/lib/model-capabilities.ts
+++ b/studio/frontend/src/features/hub/lib/model-capabilities.ts
@@ -10,6 +10,7 @@ export type CapabilityKey =
   | "reasoning"
   | "code"
   | "embedding"
+  | "diffusion"
   | "multilingual"
   | "conversational";
 
@@ -62,6 +63,20 @@ const REASONING_TAGS = new Set([
   "step-by-step",
 ]);
 
+// Image generation / diffusion (surfaced as "Image generation" in filters).
+const DIFFUSION_TAGS = new Set([
+  "diffusers",
+  "diffusion",
+  "stable-diffusion",
+  "latent-diffusion",
+  "flux",
+  "text-to-image",
+  "image-to-image",
+  "text-to-video",
+  "image-to-video",
+  "unconditional-image-generation",
+]);
+
 const CODE_TAGS = new Set([
   "code",
   "code-generation",
@@ -186,10 +201,7 @@ export function detectCapabilities(
   ) {
     out.push({ key: "code", label: "Code" });
   }
-  if (
-    hasAny(CONVERSATIONAL_TAGS) ||
-    CONVERSATIONAL_ID_RE.test(lowerId)
-  ) {
+  if (hasAny(CONVERSATIONAL_TAGS) || CONVERSATIONAL_ID_RE.test(lowerId)) {
     out.push({ key: "conversational", label: "Conversational" });
   }
   if (
@@ -200,6 +212,14 @@ export function detectCapabilities(
   ) {
     out.push({ key: "embedding", label: "Embeddings" });
   }
+  if (
+    hasAny(DIFFUSION_TAGS) ||
+    /stable[-_]?diffusion|\bsdxl\b|\bflux\b|qwen[-_]?image|hunyuan[-_]?(?:video|image)|wan2|latent[-_]?consistency|[-_]lcm\b|dreamshaper/.test(
+      lowerId,
+    )
+  ) {
+    out.push({ key: "diffusion", label: "Image generation" });
+  }
   const languageCodes = new Set<string>();
   for (const tag of tags ?? []) {
     const lower = tag.toLowerCase();
diff --git a/studio/frontend/src/features/hub/lib/model-type-filter.ts b/studio/frontend/src/features/hub/lib/model-type-filter.ts
new file mode 100644
index 0000000000..2a2e31437e
--- /dev/null
+++ b/studio/frontend/src/features/hub/lib/model-type-filter.ts
@@ -0,0 +1,52 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+// Type filter for the On Device list. Mirrors the hub Discover capability
+// options and shares its detection, so both dropdowns behave the same.
+
+import type {
+  CachedInventoryRow,
+  LocalInventoryRow,
+} from "@/features/hub/inventory/types";
+import { type CapabilityKey, detectCapabilities } from "./model-capabilities";
+
+export type ModelTypeFilter =
+  | "all"
+  | "reasoning"
+  | "vision"
+  | "audio"
+  | "embedding"
+  | "diffusion";
+
+export const MODEL_TYPE_FILTER_OPTIONS: ReadonlyArray<{
+  value: ModelTypeFilter;
+  label: string;
+}> = [
+  { value: "all", label: "All types" },
+  { value: "reasoning", label: "Reasoning" },
+  { value: "vision", label: "Vision" },
+  { value: "audio", label: "Audio" },
+  { value: "embedding", label: "Embeddings" },
+  { value: "diffusion", label: "Image generation" },
+];
+
+function rowName(row: CachedInventoryRow | LocalInventoryRow): string {
+  return row.kind === "local"
+    ? `${row.id} ${row.repoId ?? ""} ${row.title} ${row.modelId ?? ""}`
+    : `${row.id} ${row.repoId}`;
+}
+
+export function matchesModelType(
+  row: CachedInventoryRow | LocalInventoryRow,
+  filter: ModelTypeFilter,
+): boolean {
+  if (filter === "all") return true;
+  // Honor the row's own vision flag before falling back to tag detection.
+  if (filter === "vision" && row.capabilities.supportsVision) return true;
+  const caps = detectCapabilities(
+    row.tags ?? undefined,
+    row.pipelineTag ?? undefined,
+    rowName(row),
+  );
+  return caps.some((cap: { key: CapabilityKey }) => cap.key === filter);
+}
diff --git a/studio/frontend/src/features/hub/lib/view-models.ts b/studio/frontend/src/features/hub/lib/view-models.ts
index 9ee6c5de5d..d4efdb6a65 100644
--- a/studio/frontend/src/features/hub/lib/view-models.ts
+++ b/studio/frontend/src/features/hub/lib/view-models.ts
@@ -7,18 +7,18 @@ import type {
   CachedInventoryRow,
   LocalInventoryRow,
 } from "@/features/hub/inventory/types";
+import { ownerOf, repoOf } from "@/features/hub/lib/format";
 import type {
   CapabilityFilter,
   DiscoverRow,
   ModelFormatFilter,
 } from "../types";
+import { estimateSizeFromDtypes, isGgufLike } from "./hf-model-meta";
 import {
+  type CapabilityKey,
   detectBaseModel,
   detectCapabilities,
-  type CapabilityKey,
 } from "./model-capabilities";
-import { ownerOf, repoOf } from "@/features/hub/lib/format";
-import { estimateSizeFromDtypes, isGgufLike } from "./hf-model-meta";
 export {
   detectResultFormat,
   isUnslothFinetunable,
@@ -39,6 +39,7 @@ export const CAPABILITY_FILTER_OPTIONS: ReadonlyArray<{
   { value: "vision", label: "Vision" },
   { value: "audio", label: "Audio" },
   { value: "embedding", label: "Embeddings" },
+  { value: "diffusion", label: "Image generation" },
 ];
 
 export const FORMAT_FILTER_OPTIONS: ReadonlyArray<{
diff --git a/studio/frontend/src/features/model-picker/api/model-metadata.ts b/studio/frontend/src/features/model-picker/api/model-metadata.ts
new file mode 100644
index 0000000000..098ab51271
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/api/model-metadata.ts
@@ -0,0 +1,20 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { getModelConfig } from "@/features/training";
+
+export async function fetchModelMaxPositionEmbeddings(
+  modelName: string,
+  hfToken?: string | null,
+  signal?: AbortSignal,
+): Promise<number | null> {
+  const config = await getModelConfig(
+    modelName,
+    signal,
+    hfToken?.trim() || undefined,
+  );
+  const value = config.max_position_embeddings;
+  return typeof value === "number" && Number.isFinite(value) && value > 0
+    ? Math.floor(value)
+    : null;
+}
diff --git a/studio/frontend/src/features/model-picker/api/templates.ts b/studio/frontend/src/features/model-picker/api/templates.ts
new file mode 100644
index 0000000000..29f18cce29
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/api/templates.ts
@@ -0,0 +1,87 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { authFetch } from "@/features/auth";
+import { hubTokenHeader } from "@/features/hub";
+import { consumeNativePathToken } from "@/features/native-intents/api";
+import { readFastApiError } from "@/lib/format-fastapi-error";
+
+export interface ValidateChatTemplateResult {
+  valid: boolean;
+  error: string | null;
+}
+
+async function parseJsonOrThrow<T>(response: Response): Promise<T> {
+  if (!response.ok) {
+    throw new Error(await readFastApiError(response));
+  }
+  return response.json();
+}
+
+export async function validateChatTemplate(
+  template: string,
+  signal?: AbortSignal,
+): Promise<ValidateChatTemplateResult> {
+  const response = await authFetch("/api/picker/validate-chat-template", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ template }),
+    signal,
+  });
+  return parseJsonOrThrow<ValidateChatTemplateResult>(response);
+}
+
+export async function fetchDefaultChatTemplate(
+  modelName: string,
+  ggufVariant?: string | null,
+  hfToken?: string | null,
+  signal?: AbortSignal,
+  nativePathToken?: string | null,
+): Promise<string | null> {
+  // A native (picked / drag-drop) GGUF lives at a path only its signed lease
+  // knows, and the picker chat-template GET has no lease plumbing, so redeem a
+  // one-shot validate-model lease and read the embedded template through the
+  // lease-aware /api/inference/validate probe instead (mirrors the staged
+  // header-dims fetch). Non-native models keep the plain GET path.
+  if (nativePathToken) {
+    let nativePathLease: string | null = null;
+    try {
+      nativePathLease = (
+        await consumeNativePathToken(nativePathToken, "validate-model")
+      ).nativePathLease;
+    } catch {
+      // Lease expired / revoked: no readable path, so no default template (the
+      // subsequent load re-mints its own lease).
+      return null;
+    }
+    const response = await authFetch("/api/inference/validate", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({
+        model_path: modelName,
+        gguf_variant: ggufVariant ?? null,
+        hf_token: hfToken ?? null,
+        native_path_lease: nativePathLease,
+        include_chat_template: true,
+      }),
+      signal,
+    });
+    const data = await parseJsonOrThrow<{ chat_template?: string | null }>(
+      response,
+    );
+    return data.chat_template ?? null;
+  }
+
+  const query = ggufVariant
+    ? `?gguf_variant=${encodeURIComponent(ggufVariant)}`
+    : "";
+  const response = await authFetch(
+    `/api/picker/chat-template/${encodeURIComponent(modelName)}${query}`,
+    { headers: hubTokenHeader(hfToken), signal },
+  );
+  const data = await parseJsonOrThrow<{
+    model_name: string;
+    chat_template: string | null;
+  }>(response);
+  return data.chat_template ?? null;
+}
diff --git a/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx b/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
new file mode 100644
index 0000000000..5326bebac6
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
@@ -0,0 +1,191 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { Button } from "@/components/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import { Spinner } from "@/components/ui/spinner";
+import { Textarea } from "@/components/ui/textarea";
+import { useRef, useState } from "react";
+import { validateChatTemplate } from "../api/templates";
+import {
+  MAX_CHAT_TEMPLATE_BYTES,
+  chatTemplateByteLength,
+  isChatTemplateWithinLimit,
+} from "../model-config/per-model-config";
+
+interface ChatTemplateEditorDialogProps {
+  open: boolean;
+  onOpenChange: (open: boolean) => void;
+  value: string | null;
+  defaultTemplate: string | null;
+  defaultLoading: boolean;
+  onSave: (override: string | null) => void;
+  readOnly?: boolean;
+}
+
+export function ChatTemplateEditorDialog({
+  open,
+  onOpenChange,
+  value,
+  defaultTemplate,
+  defaultLoading,
+  onSave,
+  readOnly = false,
+}: ChatTemplateEditorDialogProps) {
+  const [draft, setDraft] = useState<string | null>(null);
+  const [error, setError] = useState<string | null>(null);
+  const [validating, setValidating] = useState(false);
+  // Bumped whenever the dialog closes so a validation still in flight cannot
+  // apply a template the user has already dismissed.
+  const validationToken = useRef(0);
+  const renderedDraft = draft ?? value ?? defaultTemplate ?? "";
+
+  const byteLength = chatTemplateByteLength(renderedDraft);
+  const overLimit = !isChatTemplateWithinLimit(renderedDraft);
+  const matchesDefault =
+    defaultTemplate != null && renderedDraft === defaultTemplate;
+
+  const handleClose = () => {
+    validationToken.current += 1;
+    setDraft(null);
+    setError(null);
+    setValidating(false);
+    onOpenChange(false);
+  };
+
+  const handleSave = async () => {
+    if (renderedDraft.trim().length === 0 || matchesDefault) {
+      onSave(null);
+      handleClose();
+      return;
+    }
+    if (overLimit) {
+      setError("Template exceeds the size limit.");
+      return;
+    }
+    setValidating(true);
+    const token = validationToken.current;
+    try {
+      const result = await validateChatTemplate(renderedDraft);
+      // Dialog was closed (or reopened) while validating; drop the result so a
+      // discarded template is never applied.
+      if (token !== validationToken.current) {
+        return;
+      }
+      if (!result.valid) {
+        setError(result.error ?? "Invalid Jinja template.");
+        return;
+      }
+      onSave(renderedDraft);
+      handleClose();
+    } catch {
+      if (token === validationToken.current) {
+        setError("Could not validate the template.");
+      }
+    } finally {
+      if (token === validationToken.current) {
+        setValidating(false);
+      }
+    }
+  };
+
+  return (
+    <Dialog
+      open={open}
+      onOpenChange={(nextOpen) => {
+        if (nextOpen) {
+          onOpenChange(true);
+          return;
+        }
+        handleClose();
+      }}
+    >
+      <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-3xl">
+        <DialogHeader>
+          <DialogTitle>
+            {readOnly ? "Chat Template" : "Edit Chat Template"}
+          </DialogTitle>
+          <DialogDescription>
+            {readOnly
+              ? "This is the model's chat template. Custom templates apply to GGUF models for now, so it is view only for safetensors models."
+              : "Override the model's chat template with custom Jinja. The change applies when the model loads. Saving an empty template or one that matches the default clears the override."}
+          </DialogDescription>
+        </DialogHeader>
+        <Textarea
+          value={renderedDraft}
+          onChange={(event) => {
+            if (readOnly) return;
+            setDraft(event.target.value);
+            setError(null);
+          }}
+          readOnly={readOnly}
+          className="min-h-[20rem] max-h-[50vh] overflow-y-auto border-0 font-mono text-xs leading-5 corner-squircle focus-visible:ring-0"
+          rows={14}
+          spellCheck={false}
+          placeholder={defaultLoading ? "Loading model default..." : ""}
+        />
+        {readOnly ? null : (
+          <div className="flex items-center justify-between gap-3 px-0.5 text-ui-11">
+            <span
+              className={overLimit ? "text-amber-500" : "text-muted-foreground"}
+            >
+              {byteLength.toLocaleString()} /{" "}
+              {MAX_CHAT_TEMPLATE_BYTES.toLocaleString()} bytes
+            </span>
+            {error ? (
+              <span className="truncate text-red-500" title={error}>
+                {error}
+              </span>
+            ) : null}
+          </div>
+        )}
+        <DialogFooter className="flex-wrap gap-2 sm:justify-between">
+          {readOnly ? (
+            <div className="flex w-full justify-end">
+              <Button type="button" onClick={handleClose}>
+                Close
+              </Button>
+            </div>
+          ) : (
+            <>
+              <Button
+                type="button"
+                variant="ghost"
+                onClick={() => setDraft(defaultTemplate ?? "")}
+                disabled={
+                  defaultLoading || renderedDraft === (defaultTemplate ?? "")
+                }
+                className="text-muted-foreground"
+              >
+                {defaultLoading ? (
+                  <Spinner className="size-3.5" />
+                ) : (
+                  "Reset to default"
+                )}
+              </Button>
+              <div className="flex gap-2">
+                <Button type="button" variant="ghost" onClick={handleClose}>
+                  Cancel
+                </Button>
+                <Button
+                  type="button"
+                  onClick={handleSave}
+                  disabled={validating || overLimit}
+                >
+                  {validating ? "Validating..." : "Save"}
+                </Button>
+              </div>
+            </>
+          )}
+        </DialogFooter>
+      </DialogContent>
+    </Dialog>
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/components/model-config-page.tsx b/studio/frontend/src/features/model-picker/components/model-config-page.tsx
new file mode 100644
index 0000000000..ee208dc0bc
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/model-config-page.tsx
@@ -0,0 +1,991 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { Button } from "@/components/ui/button";
+import { Checkbox } from "@/components/ui/checkbox";
+import { InfoHint } from "@/components/ui/info-hint";
+import {
+  Select,
+  SelectContent,
+  SelectItem,
+  SelectTrigger,
+  SelectValue,
+} from "@/components/ui/select";
+import { Slider } from "@/components/ui/slider";
+import { Switch } from "@/components/ui/switch";
+import {
+  GPU_LAYERS_AUTO,
+  fetchGgufStagedMetadata,
+  readPersistedSpeculativeType,
+  useChatRuntimeStore,
+} from "@/features/chat";
+import { useGpuDevices } from "@/hooks/use-gpu-info";
+import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { toast } from "@/lib/toast";
+import { ArrowLeft01Icon } from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { type ReactNode, useEffect, useId, useState } from "react";
+import {
+  useDefaultChatTemplate,
+  useModelMaxPositionEmbeddings,
+} from "../hooks/use-model-defaults";
+import { perModelConfigsEqual } from "../model-config/apply-per-model-config";
+import {
+  CONTEXT_LENGTH_MIN,
+  DEFAULT_MAX_SEQ_LENGTH,
+  DEFAULT_PER_MODEL_CONFIG,
+  KV_CACHE_DTYPES,
+  MAX_SEQ_LENGTH_MAX,
+  MAX_SEQ_LENGTH_MIN,
+  MAX_SEQ_LENGTH_STEP,
+  MTP_SPECULATIVE_TYPES,
+  type PerModelConfig,
+  SPECULATIVE_TYPES,
+  deletePerModelConfig,
+  floorMaxSeqLength,
+  isDefaultConfig,
+  normalizeMaxSeqLength,
+  resolveInitialConfig,
+  savePerModelConfig,
+} from "../model-config/per-model-config";
+import { ChatTemplateEditorDialog } from "./chat-template-editor-dialog";
+import type { ModelPickTarget } from "./model-selector/types";
+import { NumericValueInput } from "./numeric-value-input";
+
+const ROW_CLASS = "flex min-h-8 items-center justify-between gap-3";
+const LABEL_CLASS =
+  "min-w-0 truncate text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg";
+const LABEL_CLASS_WRAP =
+  "min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg";
+const CONTROL_SURFACE =
+  "rounded-full border-transparent bg-black/[0.04] dark:bg-white/[0.05] hover:bg-black/[0.06] dark:hover:bg-white/[0.1]";
+const SELECT_TRIGGER_CLASS = `grid h-8 min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 ${CONTROL_SURFACE} pl-3 pr-2 py-0 text-ui-13! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0`;
+const NUMBER_INPUT_CLASS = `h-8 w-[92px] ${CONTROL_SURFACE} pl-3 pr-2 py-0 text-right text-ui-13 font-medium text-nav-fg outline-none focus-visible:ring-0`;
+
+const KV_CACHE_DTYPE_DEFAULT = "f16";
+const SPECULATIVE_TYPE_LABELS: Record<(typeof SPECULATIVE_TYPES)[number], string> =
+  {
+    auto: "Auto",
+    mtp: "MTP",
+    ngram: "Ngram",
+    "mtp+ngram": "MTP+Ngram",
+    off: "Off",
+  };
+
+function hasNonDefaultAdvanced(config: PerModelConfig): boolean {
+  return (
+    config.kvCacheDtype != null ||
+    (config.speculativeType ?? "auto") !== "auto" ||
+    config.specDraftNMax != null ||
+    config.tensorParallel ||
+    config.chatTemplateOverride != null ||
+    (config.gpuMemoryMode ?? "auto") !== "auto" ||
+    (config.gpuLayers != null && config.gpuLayers >= 0) ||
+    (config.nCpuMoe ?? 0) > 0 ||
+    config.selectedGpuIds != null
+  );
+}
+
+function ChatTemplateSetting({
+  config,
+  onEditTemplate,
+  readOnly = false,
+}: {
+  config: PerModelConfig;
+  onEditTemplate: () => void;
+  readOnly?: boolean;
+}) {
+  return (
+    <div className={ROW_CLASS}>
+      <div className="flex min-w-0 items-center gap-1.5">
+        <span className={LABEL_CLASS}>Chat Template</span>
+        <InfoHint>
+          {readOnly
+            ? "Preview the model's chat template. Custom overrides apply to GGUF models for now."
+            : "Override the model's chat template with custom Jinja. Applies when the model loads."}
+        </InfoHint>
+      </div>
+      <div className="flex shrink-0 items-center gap-2">
+        {readOnly ? null : (
+          <span className="text-ui-12 text-muted-foreground">
+            {config.chatTemplateOverride ? "Custom" : "Default"}
+          </span>
+        )}
+        <Button
+          type="button"
+          size="sm"
+          variant="ghost"
+          className={`h-8 px-3 text-ui-13 ${CONTROL_SURFACE}`}
+          onClick={onEditTemplate}
+        >
+          {readOnly ? "View" : "Edit"}
+        </Button>
+      </div>
+    </div>
+  );
+}
+
+function MaxSeqLengthSetting({
+  value,
+  max,
+  inputMax,
+  onChange,
+}: {
+  value: number;
+  max: number;
+  inputMax: number;
+  onChange: (value: number) => void;
+}) {
+  return (
+    <div className="space-y-3">
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>Max Seq Length</span>
+          <InfoHint>
+            Maximum context window size in tokens. Applies when the model loads.
+          </InfoHint>
+        </div>
+        <NumericValueInput
+          value={value}
+          min={MAX_SEQ_LENGTH_MIN}
+          max={inputMax}
+          step={MAX_SEQ_LENGTH_STEP}
+          onChange={onChange}
+          ariaLabel="Max Seq Length"
+          className={NUMBER_INPUT_CLASS}
+          size={8}
+        />
+      </div>
+      <Slider
+        min={MAX_SEQ_LENGTH_MIN}
+        max={max}
+        step={MAX_SEQ_LENGTH_STEP}
+        value={[value]}
+        onValueChange={([next]) => onChange(next)}
+        className="panel-slider"
+        aria-label="Max Seq Length"
+      />
+    </div>
+  );
+}
+
+function clampMaxSeqLength(value: number, max: number): number {
+  const normalized = normalizeMaxSeqLength(value) ?? MAX_SEQ_LENGTH_MIN;
+  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(max, normalized));
+}
+
+function AdvancedGpuSlider({
+  label,
+  value,
+  min,
+  max,
+  onChange,
+  displayValue,
+  info,
+}: {
+  label: string;
+  value: number;
+  min: number;
+  max: number;
+  onChange: (value: number) => void;
+  displayValue?: string;
+  info?: ReactNode;
+}) {
+  return (
+    <div className="space-y-3">
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>{label}</span>
+          {info && <InfoHint>{info}</InfoHint>}
+        </div>
+        <NumericValueInput
+          value={value}
+          min={min}
+          max={max}
+          step={1}
+          onChange={onChange}
+          displayValue={displayValue}
+          ariaLabel={label}
+          className={NUMBER_INPUT_CLASS}
+          size={8}
+        />
+      </div>
+      <Slider
+        min={min}
+        max={max}
+        step={1}
+        value={[value]}
+        onValueChange={([next]) => onChange(next)}
+        className="panel-slider"
+        aria-label={label}
+      />
+    </div>
+  );
+}
+
+// GPU Memory placement controls (mode / GPU Layers / MoE offload / GPU picker),
+// GGUF only. Slider ceilings come from the GGUF header dims, the picker from the
+// live device list. --tensor-split is not persisted per model, so not exposed here.
+function GpuMemorySettings({
+  config,
+  update,
+  layerCount,
+  moeLayerCount,
+}: {
+  config: PerModelConfig;
+  update: (patch: Partial<PerModelConfig>) => void;
+  layerCount: number | null;
+  moeLayerCount: number | null;
+}) {
+  const gpuDevices = useGpuDevices();
+  const mode = config.gpuMemoryMode ?? "auto";
+  const isManual = mode === "manual";
+  const gpuLayers = config.gpuLayers ?? GPU_LAYERS_AUTO;
+  // Slider at Auto: llama.cpp --fit owns the layout, so MoE-offload doesn't apply.
+  const autoLayers = isManual && gpuLayers < 0;
+  // Ceiling = layer count + 1 (llama.cpp counts the output layer as offloadable),
+  // else a safe fallback.
+  const gpuLayersMax = layerCount != null ? layerCount + 1 : 256;
+  const nCpuMoe = config.nCpuMoe ?? 0;
+  const moeLayersMax = moeLayerCount ?? 0;
+  const showMoeSlider = isManual && !autoLayers && moeLayersMax > 0;
+  const selectedGpuIds = config.selectedGpuIds ?? null;
+  const singleGpuInUse =
+    (selectedGpuIds ?? gpuDevices.map((device) => device.index)).length <= 1;
+  // Multi-GPU only, and only with physical indices (relative ordinals from a
+  // CUDA_VISIBLE_DEVICES mask can't be mapped back to pin a device). null = all (auto).
+  const showGpuPicker =
+    gpuDevices.length > 1 && gpuDevices.every((d) => d.physicalIndex);
+  const isGpuChecked = (index: number) =>
+    selectedGpuIds === null || selectedGpuIds.includes(index);
+  const toggleGpu = (index: number) => {
+    const all = gpuDevices.map((d) => d.index);
+    const current = selectedGpuIds ?? all;
+    const next = current.includes(index)
+      ? current.filter((i) => i !== index)
+      : [...current, index].sort((a, b) => a - b);
+    if (next.length === 0) return; // keep at least one GPU selected
+    update({ selectedGpuIds: next.length === all.length ? null : next });
+  };
+  return (
+    <>
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>GPU Memory</span>
+          <InfoHint>
+            <div className="flex flex-col gap-1.5">
+              <div>
+                <span className="font-medium">Default:</span> Unsloth fits the
+                model and context to your GPUs.
+              </div>
+              <div>
+                <span className="font-medium">Manual:</span> set GPU Layers
+                yourself. Leave it on Auto to let llama.cpp size the context and
+                offload overflow (including MoE experts) to RAM.
+              </div>
+            </div>
+          </InfoHint>
+        </div>
+        <Select
+          value={mode}
+          onValueChange={(v) =>
+            // Returning to Default must clear the Manual-only knobs, else a
+            // remembered config keeps stale gpuLayers/nCpuMoe/GPU pick that a
+            // later load re-applies while the page shows Default.
+            update(
+              v === "manual"
+                ? { gpuMemoryMode: "manual" }
+                : {
+                    gpuMemoryMode: "auto",
+                    gpuLayers: undefined,
+                    nCpuMoe: undefined,
+                    selectedGpuIds: undefined,
+                  },
+            )
+          }
+        >
+          <SelectTrigger
+            animateRadius={false}
+            icon={ChevronDownStandardIcon}
+            iconClassName="size-3.5"
+            className={`w-[124px] shrink-0 ${SELECT_TRIGGER_CLASS}`}
+          >
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+            <SelectItem value="auto">Default</SelectItem>
+            <SelectItem value="manual">Manual</SelectItem>
+          </SelectContent>
+        </Select>
+      </div>
+      {isManual && (
+        <>
+          <AdvancedGpuSlider
+            label="GPU Layers"
+            value={Math.max(GPU_LAYERS_AUTO, Math.min(gpuLayers, gpuLayersMax))}
+            min={GPU_LAYERS_AUTO}
+            max={gpuLayersMax}
+            onChange={(v) => update({ gpuLayers: v })}
+            displayValue={autoLayers ? "Auto" : undefined}
+            info={
+              <>
+                Layers to keep on the GPU (--gpu-layers); the rest run on CPU.
+                Auto lets llama.cpp size the split (and the context) to fit VRAM.
+                At the maximum, the whole model is on the GPU.
+              </>
+            }
+          />
+          {showMoeSlider && (
+            <AdvancedGpuSlider
+              label="MoE Layers on CPU"
+              value={Math.min(nCpuMoe, moeLayersMax)}
+              min={0}
+              max={moeLayersMax}
+              onChange={(v) => update({ nCpuMoe: v })}
+              info={
+                <>
+                  Keep the experts of this many MoE layers on the CPU
+                  (--n-cpu-moe) to save VRAM. 0 = all experts on the GPU; at the
+                  maximum, all are on the CPU.
+                </>
+              }
+            />
+          )}
+        </>
+      )}
+      {showGpuPicker && (
+        <div className="space-y-2">
+          <div className="flex min-w-0 items-center gap-1.5">
+            <span className={LABEL_CLASS}>GPUs</span>
+            <InfoHint>
+              Which GPUs this model may use. Unchecked GPUs are hidden from
+              llama.cpp (CUDA_VISIBLE_DEVICES, or HIP_VISIBLE_DEVICES on ROCm).
+              Leave all checked to use every GPU. At least one GPU must stay
+              selected.
+            </InfoHint>
+          </div>
+          <div className="flex flex-col gap-2">
+            {gpuDevices.map((d) => (
+              <div
+                key={d.index}
+                className="flex items-center justify-between gap-3"
+              >
+                <span className="min-w-0 truncate text-ui-12 text-nav-fg/80">
+                  GPU {d.index}: {d.name}
+                  {d.memoryTotalGb
+                    ? ` · ${Math.round(d.memoryTotalGb)} GB`
+                    : ""}
+                </span>
+                <Switch
+                  className="panel-switch shrink-0"
+                  checked={isGpuChecked(d.index)}
+                  onCheckedChange={() => toggleGpu(d.index)}
+                  disabled={isGpuChecked(d.index) && singleGpuInUse}
+                />
+              </div>
+            ))}
+          </div>
+        </div>
+      )}
+    </>
+  );
+}
+
+function GgufAdvancedSettings({
+  config,
+  update,
+  isMtp,
+  speculativeFallback,
+  onEditTemplate,
+  layerCount,
+  moeLayerCount,
+}: {
+  config: PerModelConfig;
+  update: (patch: Partial<PerModelConfig>) => void;
+  isMtp: boolean;
+  speculativeFallback: string;
+  onEditTemplate: () => void;
+  layerCount: number | null;
+  moeLayerCount: number | null;
+}) {
+  return (
+    <>
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>KV Cache Dtype</span>
+          <InfoHint>
+            Lower KV cache precision to save VRAM at the cost of some quality.
+            f16/bf16 are full precision; q8_0/q5_1/q4_1 are quantized.
+          </InfoHint>
+        </div>
+        <Select
+          value={config.kvCacheDtype ?? KV_CACHE_DTYPE_DEFAULT}
+          onValueChange={(v) =>
+            update({ kvCacheDtype: v === KV_CACHE_DTYPE_DEFAULT ? null : v })
+          }
+        >
+          <SelectTrigger
+            animateRadius={false}
+            icon={ChevronDownStandardIcon}
+            iconClassName="size-3.5"
+            className={`w-[92px] ${SELECT_TRIGGER_CLASS}`}
+          >
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+            <SelectItem value={KV_CACHE_DTYPE_DEFAULT}>
+              {KV_CACHE_DTYPE_DEFAULT}
+            </SelectItem>
+            {KV_CACHE_DTYPES.map((dtype) => (
+              <SelectItem key={dtype} value={dtype}>
+                {dtype}
+              </SelectItem>
+            ))}
+          </SelectContent>
+        </Select>
+      </div>
+
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS_WRAP}>Speculative Decoding</span>
+          <InfoHint>
+            Faster generation with no accuracy hit. Auto picks MTP / ngram based
+            on the model and platform. Pick a strategy to force it.
+          </InfoHint>
+        </div>
+        <Select
+          value={config.speculativeType ?? speculativeFallback}
+          onValueChange={(v) =>
+            update({
+              speculativeType: v,
+              specDraftNMax:
+                v === "mtp" || v === "mtp+ngram" ? config.specDraftNMax : null,
+            })
+          }
+        >
+          <SelectTrigger
+            animateRadius={false}
+            icon={ChevronDownStandardIcon}
+            iconClassName="size-3.5"
+            className={`w-[124px] shrink-0 ${SELECT_TRIGGER_CLASS}`}
+          >
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+            {SPECULATIVE_TYPES.map((type) => (
+              <SelectItem key={type} value={type}>
+                {SPECULATIVE_TYPE_LABELS[type]}
+              </SelectItem>
+            ))}
+          </SelectContent>
+        </Select>
+      </div>
+
+      {isMtp && (
+        <div className={ROW_CLASS}>
+          <div className="flex min-w-0 items-center gap-1.5">
+            <span className={LABEL_CLASS}>Draft Tokens</span>
+            <InfoHint>
+              Max MTP draft tokens per step. Leave blank for the platform
+              default (2 on GPU, 3 on CPU/Mac).
+            </InfoHint>
+          </div>
+          <input
+            type="number"
+            min={1}
+            max={16}
+            step={1}
+            value={config.specDraftNMax ?? ""}
+            placeholder="auto"
+            onChange={(event) => {
+              const raw = event.target.value;
+              if (raw === "") {
+                update({ specDraftNMax: null });
+                return;
+              }
+              const parsed = Number.parseInt(raw, 10);
+              if (Number.isFinite(parsed)) {
+                update({ specDraftNMax: Math.max(1, Math.min(16, parsed)) });
+              }
+            }}
+            aria-label="Speculative decoding draft tokens"
+            className={NUMBER_INPUT_CLASS}
+          />
+        </div>
+      )}
+
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>Tensor Parallelism</span>
+          <InfoHint>
+            No effect on a single GPU. On multi-GPU setups, improves tokens/sec
+            for dense models. MoE models don't benefit.
+          </InfoHint>
+        </div>
+        <Switch
+          className="panel-switch shrink-0"
+          checked={config.tensorParallel}
+          onCheckedChange={(checked) => update({ tensorParallel: checked })}
+        />
+      </div>
+
+      <GpuMemorySettings
+        config={config}
+        update={update}
+        layerCount={layerCount}
+        moeLayerCount={moeLayerCount}
+      />
+
+      <ChatTemplateSetting config={config} onEditTemplate={onEditTemplate} />
+    </>
+  );
+}
+
+interface ModelConfigPageProps {
+  target: ModelPickTarget;
+  onBack?: () => void;
+  onRun: (config: PerModelConfig) => void;
+  loadedConfig?: PerModelConfig | null;
+  loadedContextLength?: number | null;
+  initialConfig?: PerModelConfig | null;
+  variant?: "page" | "sidebar";
+}
+
+export function ModelConfigPage({
+  target,
+  onBack,
+  onRun,
+  loadedConfig = null,
+  loadedContextLength = null,
+  initialConfig = null,
+  variant = "page",
+}: ModelConfigPageProps) {
+  const rememberId = useId();
+  const isActiveModel = loadedConfig != null;
+  const hfToken = useChatRuntimeStore((s) => s.hfToken);
+  const activeNativePathToken = useChatRuntimeStore(
+    (s) => s.activeNativePathToken,
+  );
+  const loadedDefaultChatTemplate = useChatRuntimeStore(
+    (s) => s.defaultChatTemplate,
+  );
+  const loadedMaxContextLength = useChatRuntimeStore(
+    (s) => s.ggufMaxContextLength,
+  );
+  const resolveInitial = () => {
+    const resolved = resolveInitialConfig(target.id, target.ggufVariant);
+    if (loadedConfig) {
+      return { config: loadedConfig, remembered: resolved.remembered };
+    }
+    if (initialConfig) {
+      return {
+        config: initialConfig,
+        remembered:
+          resolved.remembered &&
+          perModelConfigsEqual(initialConfig, resolved.config),
+      };
+    }
+    return resolved;
+  };
+  const [initial] = useState(resolveInitial);
+  const [config, setConfig] = useState<PerModelConfig>(() => initial.config);
+  const [remember, setRemember] = useState(() => initial.remembered);
+  const [savedRemember, setSavedRemember] = useState(() => initial.remembered);
+  const [speculativeFallback] = useState(readPersistedSpeculativeType);
+  const [templateOpen, setTemplateOpen] = useState(false);
+  const [showAdvanced, setShowAdvanced] = useState(() =>
+    hasNonDefaultAdvanced(config),
+  );
+  const nativePathToken =
+    target.meta.nativePathToken ??
+    (isActiveModel ? activeNativePathToken : null);
+  const templateDefaults = useDefaultChatTemplate(
+    target.id,
+    target.ggufVariant,
+    templateOpen,
+    nativePathToken,
+  );
+  const modelMaxPosition = useModelMaxPositionEmbeddings(
+    target.id,
+    !target.isGguf,
+  );
+  const hasLoadedDefaultTemplate =
+    isActiveModel && loadedDefaultChatTemplate != null;
+  const resolvedDefaultTemplate = hasLoadedDefaultTemplate
+    ? loadedDefaultChatTemplate
+    : templateDefaults.template;
+  const resolvedDefaultLoading = hasLoadedDefaultTemplate
+    ? false
+    : templateDefaults.loading;
+
+  const update = (patch: Partial<PerModelConfig>) =>
+    setConfig((current) => ({ ...current, ...patch }));
+
+  // Fetch GGUF header dims (context + layer/MoE counts) to size the GPU Memory
+  // sliders; the context also fills in below when target.meta lacks it.
+  const contextFetchKey = target.isGguf
+    ? `${target.id}\n${target.ggufVariant ?? ""}\n${hfToken || ""}\n${nativePathToken ?? ""}`
+    : null;
+  const [fetchedStagedDims, setFetchedStagedDims] = useState<{
+    key: string;
+    contextLength: number | null;
+    layerCount: number | null;
+    moeLayerCount: number | null;
+  } | null>(null);
+  useEffect(() => {
+    if (contextFetchKey == null) {
+      return;
+    }
+    let cancelled = false;
+    void fetchGgufStagedMetadata({
+      model_path: target.id,
+      gguf_variant: target.ggufVariant ?? null,
+      hf_token: hfToken || null,
+      nativePathToken,
+    })
+      .then((dims) => {
+        if (!cancelled) {
+          setFetchedStagedDims({ key: contextFetchKey, ...dims });
+        }
+      })
+      .catch(() => {
+        if (!cancelled) {
+          setFetchedStagedDims({
+            key: contextFetchKey,
+            contextLength: null,
+            layerCount: null,
+            moeLayerCount: null,
+          });
+        }
+      });
+    return () => {
+      cancelled = true;
+    };
+  }, [
+    contextFetchKey,
+    target.id,
+    target.ggufVariant,
+    hfToken,
+    nativePathToken,
+  ]);
+  const stagedDims =
+    fetchedStagedDims?.key === contextFetchKey ? fetchedStagedDims : null;
+
+  const isMtp =
+    config.speculativeType != null &&
+    MTP_SPECULATIVE_TYPES.has(config.speculativeType);
+  const nativeContextLength =
+    target.meta.contextLength ?? stagedDims?.contextLength ?? null;
+  const activeLoadedContext =
+    isActiveModel && target.isGguf ? loadedContextLength : null;
+  const minContext = CONTEXT_LENGTH_MIN;
+  const maxContext = Math.max(
+    minContext,
+    Math.max(
+      nativeContextLength ?? 0,
+      activeLoadedContext ?? 0,
+      config.customContextLength ?? 0,
+    ) || 32768,
+  );
+  const contextValue = Math.min(
+    Math.max(
+      config.customContextLength ??
+        activeLoadedContext ??
+        nativeContextLength ??
+        maxContext,
+      minContext,
+    ),
+    maxContext,
+  );
+  const setContextLength = (v: number) =>
+    update({ customContextLength: v });
+  const baseline = loadedConfig ?? DEFAULT_PER_MODEL_CONFIG;
+  const atBaseline = perModelConfigsEqual(config, baseline);
+  // An explicit customContextLength equal to the native ceiling is still an
+  // override (Reset stays enabled). "At default" means no override at all AND the
+  // shown context matches native (or no native context length is exposed).
+  const contextAtDefault =
+    !target.isGguf ||
+    (config.customContextLength == null &&
+      (nativeContextLength == null || contextValue === nativeContextLength));
+  const atDefault =
+    contextAtDefault &&
+    perModelConfigsEqual(
+      { ...config, customContextLength: null },
+      DEFAULT_PER_MODEL_CONFIG,
+    );
+  const nativeMaxSeqLength =
+    floorMaxSeqLength(modelMaxPosition.maxPositionEmbeddings) ??
+    MAX_SEQ_LENGTH_MAX;
+  // A non-GGUF active model seeds maxSeqLength from its loaded value. Once cleared
+  // (Reset sets null), fall back to the app default, not the loaded runtime value,
+  // else a remembered/active override can never be cleared.
+  const maxSeqLengthValue =
+    normalizeMaxSeqLength(config.maxSeqLength) ??
+    clampMaxSeqLength(DEFAULT_MAX_SEQ_LENGTH, nativeMaxSeqLength);
+  const maxSeqLengthMax = Math.max(nativeMaxSeqLength, maxSeqLengthValue);
+  // An auto-fit-below-native GGUF shows activeLoadedContext while
+  // customContextLength stays null. If the user fixes GPU Layers (Manual) and
+  // remembers, pin that shown context so a later fresh load keeps the fitted
+  // placement instead of sending native/0 for fixed layers and recreating the OOM.
+  const pinFixedLayerContext =
+    target.isGguf &&
+    config.gpuMemoryMode === "manual" &&
+    config.gpuLayers != null &&
+    config.gpuLayers >= 0 &&
+    config.customContextLength == null &&
+    activeLoadedContext != null;
+  // Persisted record: keep config as-is (non-GGUF keeps maxSeqLength null) so
+  // isDefaultConfig recognises it and clears a remembered override instead of
+  // pinning the app default.
+  const runtimeConfig = target.isGguf
+    ? pinFixedLayerContext
+      ? { ...config, customContextLength: activeLoadedContext }
+      : config
+    : config;
+  // Load request needs a concrete max length; substitute the fallback here only,
+  // never in the persisted runtimeConfig.
+  const loadConfig = target.isGguf
+    ? runtimeConfig
+    : { ...runtimeConfig, maxSeqLength: maxSeqLengthValue };
+  const rememberChanged = remember !== savedRemember;
+  const persistenceOnly = isActiveModel && atBaseline && rememberChanged;
+  const primaryActionLabel = persistenceOnly
+    ? remember
+      ? "Save settings"
+      : "Forget settings"
+    : isActiveModel
+      ? "Reload model"
+      : "Load model";
+
+  const handleRun = () => {
+    const defaultConfig = isDefaultConfig(runtimeConfig);
+    let saveFailed = false;
+    if (remember) {
+      saveFailed = !savePerModelConfig(
+        target.id,
+        target.ggufVariant,
+        runtimeConfig,
+      );
+    } else {
+      saveFailed = !deletePerModelConfig(target.id, target.ggufVariant);
+    }
+    if (persistenceOnly) {
+      if (saveFailed) {
+        toast.error("Couldn't save settings for this model.");
+        return;
+      }
+      const nextRemember = remember && !defaultConfig;
+      setSavedRemember(nextRemember);
+      setRemember(nextRemember);
+      toast.success(
+        nextRemember
+          ? "Settings saved."
+          : remember
+            ? "Default settings kept."
+            : "Settings forgotten.",
+      );
+      return;
+    }
+    if (saveFailed) {
+      toast.error("Couldn't save these settings, loading with them anyway.");
+    }
+    onRun(loadConfig);
+  };
+
+  return (
+    <div className="flex flex-col">
+      {variant === "page" && (
+        <div className="flex items-center gap-2.5 pb-4">
+          {onBack && (
+            <button
+              type="button"
+              onClick={onBack}
+              className="nav-icon-btn shrink-0 text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
+              aria-label="Back to model list"
+            >
+              <HugeiconsIcon
+                icon={ArrowLeft01Icon}
+                className="size-4"
+                strokeWidth={1.75}
+              />
+            </button>
+          )}
+          <div className="min-w-0 flex-1">
+            <div className="text-ui-10 font-semibold uppercase leading-none tracking-wider text-muted-foreground">
+              Run settings
+            </div>
+            <div className="mt-1.5 truncate text-ui-14 font-semibold leading-tight text-nav-fg">
+              {target.displayName}
+            </div>
+          </div>
+        </div>
+      )}
+
+      <div className="space-y-3.5">
+        {target.isGguf && (
+          <>
+            <div className="space-y-3">
+              <div className={ROW_CLASS}>
+                <div className="flex min-w-0 items-center gap-1.5">
+                  <span className={LABEL_CLASS}>Context Length</span>
+                  <InfoHint>
+                    Tokens of context to allocate. Higher uses more VRAM.
+                    {nativeContextLength != null
+                      ? ` This model's native context is ${nativeContextLength.toLocaleString()} tokens.`
+                      : ""}
+                  </InfoHint>
+                </div>
+                <NumericValueInput
+                  value={contextValue}
+                  min={minContext}
+                  max={maxContext}
+                  step={1}
+                  onChange={setContextLength}
+                  displayValue={
+                    config.customContextLength == null &&
+                    nativeContextLength == null &&
+                    activeLoadedContext == null
+                      ? "Auto"
+                      : undefined
+                  }
+                  ariaLabel="Context Length"
+                  className={NUMBER_INPUT_CLASS}
+                  size={8}
+                />
+              </div>
+              {nativeContextLength != null ? (
+                <Slider
+                  min={minContext}
+                  max={maxContext}
+                  step={128}
+                  value={[contextValue]}
+                  onValueChange={([v]) => setContextLength(v)}
+                  className="panel-slider"
+                  aria-label="Context Length"
+                />
+              ) : null}
+              {isActiveModel &&
+                loadedMaxContextLength != null &&
+                contextValue > loadedMaxContextLength && (
+                  <p className="text-ui-11 text-amber-500">
+                    Exceeds estimated VRAM capacity (
+                    {loadedMaxContextLength.toLocaleString()} tokens). The model
+                    may use system RAM.
+                  </p>
+                )}
+            </div>
+
+            {showAdvanced && (
+              <GgufAdvancedSettings
+                config={config}
+                update={update}
+                isMtp={isMtp}
+                speculativeFallback={speculativeFallback}
+                onEditTemplate={() => setTemplateOpen(true)}
+                layerCount={stagedDims?.layerCount ?? null}
+                moeLayerCount={stagedDims?.moeLayerCount ?? null}
+              />
+            )}
+
+            <div className={ROW_CLASS}>
+              <div className="flex min-w-0 items-center gap-1.5">
+                <span className="min-w-0 text-ui-13 font-medium leading-[1.25] tracking-nav text-muted-foreground">
+                  Advanced settings
+                </span>
+                <InfoHint>
+                  Extra options for how the model loads. Most setups don't need
+                  these.
+                </InfoHint>
+              </div>
+              <Switch
+                className="panel-switch shrink-0"
+                checked={showAdvanced}
+                onCheckedChange={setShowAdvanced}
+                aria-label="Show advanced settings"
+              />
+            </div>
+          </>
+        )}
+        {!target.isGguf && (
+          <>
+            <MaxSeqLengthSetting
+              value={maxSeqLengthValue}
+              max={maxSeqLengthMax}
+              inputMax={MAX_SEQ_LENGTH_MAX}
+              onChange={(value) =>
+                update({
+                  maxSeqLength: clampMaxSeqLength(value, MAX_SEQ_LENGTH_MAX),
+                })
+              }
+            />
+            <ChatTemplateSetting
+              config={config}
+              onEditTemplate={() => setTemplateOpen(true)}
+              readOnly={true}
+            />
+          </>
+        )}
+      </div>
+
+      <div
+        className={
+          variant === "sidebar"
+            ? "mt-4 flex flex-col gap-3 border-t border-border/60 pt-4"
+            : "mt-4 flex items-center justify-between gap-3 border-t border-border/60 pt-4"
+        }
+      >
+        <div className="flex min-w-0 items-center gap-2">
+          <Checkbox
+            id={rememberId}
+            checked={remember}
+            onCheckedChange={(checked) => setRemember(checked === true)}
+          />
+          <label
+            htmlFor={rememberId}
+            className="cursor-pointer select-none truncate text-ui-13 text-nav-fg"
+          >
+            Remember for this model
+          </label>
+        </div>
+        <div
+          className={
+            variant === "sidebar"
+              ? "flex items-center justify-end gap-2"
+              : "flex shrink-0 items-center gap-2"
+          }
+        >
+          <Button
+            type="button"
+            variant="ghost"
+            size="sm"
+            className="h-8"
+            disabled={atDefault}
+            onClick={() => setConfig({ ...DEFAULT_PER_MODEL_CONFIG })}
+          >
+            Reset
+          </Button>
+          <Button
+            type="button"
+            size="sm"
+            className="h-8"
+            disabled={isActiveModel && atBaseline && !rememberChanged}
+            onClick={handleRun}
+          >
+            {primaryActionLabel}
+          </Button>
+        </div>
+      </div>
+
+      <ChatTemplateEditorDialog
+        open={templateOpen}
+        onOpenChange={setTemplateOpen}
+        value={config.chatTemplateOverride}
+        defaultTemplate={resolvedDefaultTemplate}
+        defaultLoading={resolvedDefaultLoading}
+        readOnly={!target.isGguf}
+        onSave={(override) => update({ chatTemplateOverride: override })}
+      />
+    </div>
+  );
+}
diff --git a/studio/frontend/src/components/assistant-ui/model-selector.tsx b/studio/frontend/src/features/model-picker/components/model-selector.tsx
similarity index 83%
rename from studio/frontend/src/components/assistant-ui/model-selector.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector.tsx
index 6bfd1276ac..cda6e49e24 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector.tsx
@@ -3,6 +3,7 @@
 
 "use client";
 
+import { Input } from "@/components/ui/input";
 import {
   Popover,
   PopoverContent,
@@ -10,7 +11,7 @@ import {
 } from "@/components/ui/popover";
 import { TooltipProvider } from "@/components/ui/tooltip";
 import { usePlatformStore } from "@/config/env";
-import { isCustomProviderType } from "@/features/chat/external-providers";
+import { isCustomProviderType } from "@/features/chat";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { cn } from "@/lib/utils";
 import {
@@ -33,7 +34,11 @@ import {
   useRef,
   useState,
 } from "react";
-import { Input } from "../ui/input";
+import {
+  type PerModelConfig,
+  resolveInitialConfig,
+} from "../model-config/per-model-config";
+import { ModelConfigPage } from "./model-config-page";
 import { HubModelPicker, hasDownloadedModels } from "./model-selector/pickers";
 import { PillTabs } from "./model-selector/pill-tabs";
 import {
@@ -45,6 +50,7 @@ import type {
   ExternalModelOption,
   LoraModelOption,
   ModelOption,
+  ModelPickTarget,
   ModelSelectorChangeMeta,
 } from "./model-selector/types";
 
@@ -122,6 +128,10 @@ interface ModelSelectorProps {
   value?: string;
   defaultValue?: string;
   activeGgufVariant?: string | null;
+  activeModelConfig?: PerModelConfig | null;
+  activeGgufContextLength?: number | null;
+  selectedConfig?: PerModelConfig | null;
+  selectedGgufVariant?: string | null;
   onValueChange?: (value: string, meta: ModelSelectorChangeMeta) => void;
   onEject?: () => void;
   onFoldersChange?: () => void;
@@ -183,15 +193,12 @@ function ModelSelectorTrigger({
       >
         {isLoaded &&
           (onEject ? (
-            // Loaded status doubles as a mouse eject shortcut: green checkmark
-            // at rest, red eject icon on pill hover, click to eject. A plain
-            // span (no role/tabIndex) keeps it out of the trigger button's
-            // content model, which forbids focusable descendants. Keyboard and
-            // screen-reader users eject via the picker's "Eject model" button.
-            // aria-hidden marks it decorative; stopPropagation stops the
-            // popover from toggling. On touch (no hover) the eject icon and
-            // tooltip never reveal, so pointer-events-none disables the
-            // shortcut there and taps open the picker instead of ejecting.
+            // Loaded status doubles as a mouse eject shortcut (checkmark at rest,
+            // eject icon on hover). A plain span keeps it out of the trigger
+            // button's content model (no focusable descendants); keyboard/SR users
+            // eject via the "Eject model" button. aria-hidden marks it decorative;
+            // stopPropagation stops the popover toggling. On touch (no hover)
+            // pointer-events-none disables it so taps open the picker instead.
             <span
               aria-hidden={true}
               title="Eject model"
@@ -225,7 +232,7 @@ function ModelSelectorTrigger({
           </span>
         ) : null}
         <span className="flex min-w-0 flex-1 items-baseline">
-          <span className="min-w-0 flex flex-1 items-baseline truncate font-heading text-[16px] font-medium leading-tight text-black dark:text-white">
+          <span className="min-w-0 flex flex-1 items-baseline truncate font-heading text-ui-16 font-medium leading-tight text-black dark:text-white">
             {currentModel?.name ?? "Select model"}
             {showCloudIndicator ? (
               <HugeiconsIcon
@@ -285,7 +292,8 @@ function saveLastHubSection(section: HubSection): void {
 // when they have downloads, else Recommended.
 function defaultHubSection(): HubSection {
   return (
-    loadLastHubSection() ?? (hasDownloadedModels() ? "downloaded" : "recommended")
+    loadLastHubSection() ??
+    (hasDownloadedModels() ? "downloaded" : "recommended")
   );
 }
 
@@ -308,6 +316,11 @@ function ModelSelectorContent({
   loraModels,
   externalModels,
   value,
+  activeGgufVariant,
+  activeModelConfig,
+  activeGgufContextLength,
+  selectedConfig,
+  selectedGgufVariant,
   onSelect,
   onEject,
   onFoldersChange,
@@ -323,6 +336,11 @@ function ModelSelectorContent({
   loraModels: LoraModelOption[];
   externalModels: ExternalModelOption[];
   value?: string;
+  activeGgufVariant?: string | null;
+  activeModelConfig?: PerModelConfig | null;
+  activeGgufContextLength?: number | null;
+  selectedConfig?: PerModelConfig | null;
+  selectedGgufVariant?: string | null;
   onSelect: (id: string, meta: ModelSelectorChangeMeta) => void;
   onEject?: () => void;
   onFoldersChange?: () => void;
@@ -337,8 +355,7 @@ function ModelSelectorContent({
   const chatOnly = usePlatformStore((s) => s.isChatOnly());
   const hasExternal = externalModels.length > 0;
   // The Fine-tuned tab is for fine-tuned models only. Local models (LM Studio,
-  // Ollama, custom folders) carry source "local" and live in the Hub tab's
-  // Downloaded / Custom sections instead.
+  // Ollama, custom folders) carry source "local" and live in the Hub tab instead.
   const fineTunedModels = useMemo(
     () => loraModels.filter((model) => isFineTunedSource(model.source)),
     [loraModels],
@@ -391,9 +408,12 @@ function ModelSelectorContent({
   const effectiveHubSection: HubSection =
     hubSection === "connected" && !hasExternal ? "recommended" : hubSection;
 
-  // The picker below remounts on each open, but this tab state does not, so a
-  // persisted selection that lands in lora/external after async load would
-  // reopen on Hub. Re-derive the default tab on the open edge.
+  const [configTarget, setConfigTarget] = useState<ModelPickTarget | null>(
+    null,
+  );
+
+  // The picker remounts on each open but this tab state does not, so re-derive
+  // the default tab on the open edge (else a lora/external selection reopens on Hub).
   const wasOpen = useRef(open);
   useEffect(() => {
     if (open && !wasOpen.current) {
@@ -402,6 +422,9 @@ function ModelSelectorContent({
       // user has downloads, else their last section.
       setHubSection(wantsConnectedDefault ? "connected" : defaultHubSection());
     }
+    if (!open && wasOpen.current) {
+      setConfigTarget(null);
+    }
     wasOpen.current = open;
   }, [
     open,
@@ -452,6 +475,29 @@ function ModelSelectorContent({
     }
   }
 
+  const visibleConfigTarget = open ? configTarget : null;
+  const openConfigPage = (id: string, meta: ModelSelectorChangeMeta) => {
+    const leaf = id.includes("/") ? id.slice(id.lastIndexOf("/") + 1) : id;
+    setConfigTarget({
+      id,
+      displayName: meta.ggufVariant ? `${leaf} · ${meta.ggufVariant}` : leaf,
+      ggufVariant: meta.ggufVariant ?? null,
+      isGguf: meta.isGguf ?? Boolean(meta.ggufVariant),
+      meta,
+    });
+  };
+  const handlePick = (id: string, meta: ModelSelectorChangeMeta) => {
+    if (meta.source === "external") {
+      onSelect(id, meta);
+      return;
+    }
+    const resolved = resolveInitialConfig(id, meta.ggufVariant);
+    onSelect(id, {
+      ...meta,
+      ...(resolved.remembered ? { config: resolved.config } : {}),
+    });
+  };
+
   return (
     <PopoverContent
       align="start"
@@ -459,12 +505,17 @@ function ModelSelectorContent({
       data-tour={dataTour}
       onKeyDown={handlePickerEntryKeyDown}
       className={cn(
-        "unsloth-model-selector-menu menu-soft-surface ring-0 max-w-[calc(100vw-1rem)] min-w-0 gap-0 pt-4 pb-0 pl-4",
-        // Sized so the left-packed row keeps uniform gaps and the last dropdown's
-        // right gap matches the pill's left gap (pl-4 vs pr-4).
-        hasExternal
-          ? "w-[min(614px,calc(100vw-1rem))] pr-4"
-          : "w-[min(506px,calc(100vw-1rem))] pr-2",
+        "unsloth-model-selector-menu menu-soft-surface ring-0 max-w-[calc(100vw-1rem)] min-w-0 gap-0",
+        visibleConfigTarget
+          ? "w-[min(468px,calc(100vw-1rem))] px-4 pt-4 pb-4"
+          : cn(
+              "pt-4 pb-0 pl-4",
+              // Sized so the left-packed row keeps uniform gaps and the last
+              // dropdown's right gap matches the pill's left gap (pl-4 vs pr-4).
+              hasExternal
+                ? "w-[min(614px,calc(100vw-1rem))] pr-4"
+                : "w-[min(506px,calc(100vw-1rem))] pr-2",
+            ),
         className,
       )}
     >
@@ -477,6 +528,42 @@ function ModelSelectorContent({
         skipDelayDuration={0}
         disableHoverableContent={true}
       >
+        {visibleConfigTarget ? (
+          <ModelConfigPage
+            key={`${visibleConfigTarget.id}::${visibleConfigTarget.ggufVariant ?? ""}`}
+            target={visibleConfigTarget}
+            onBack={() => setConfigTarget(null)}
+            onRun={(config) =>
+              onSelect(visibleConfigTarget.id, {
+                ...visibleConfigTarget.meta,
+                config,
+                forceReload: true,
+              })
+            }
+            loadedConfig={
+              value === visibleConfigTarget.id &&
+              (activeGgufVariant ?? null) ===
+                (visibleConfigTarget.ggufVariant ?? null)
+                ? (activeModelConfig ?? null)
+                : null
+            }
+            loadedContextLength={
+              value === visibleConfigTarget.id &&
+              (activeGgufVariant ?? null) ===
+                (visibleConfigTarget.ggufVariant ?? null)
+                ? (activeGgufContextLength ?? null)
+                : null
+            }
+            initialConfig={
+              value === visibleConfigTarget.id &&
+              (selectedGgufVariant ?? null) ===
+                (visibleConfigTarget.ggufVariant ?? null)
+                ? (selectedConfig ?? null)
+                : null
+            }
+          />
+        ) : (
+          <>
         {tabs.length > 1 ? (
           <PillTabs
             ariaLabel="Model source"
@@ -494,13 +581,14 @@ function ModelSelectorContent({
             loraModels={fineTunedModels}
             externalModels={externalModels}
             value={value}
-            onSelect={onSelect}
+            onSelect={handlePick}
             onFoldersChange={onFoldersChange}
             onBrowseHub={onBrowseHub}
             onModelsChange={onModelsChange}
+            onConfigure={openConfigPage}
             deleteDisabled={deleteDisabled}
-            section={effectiveHubSection}
             onEject={hasSelection && onEject ? onEject : undefined}
+            section={effectiveHubSection}
             sectionToggle={
               <PillTabs
                 ariaLabel="Hub section"
@@ -538,10 +626,8 @@ function ModelSelectorContent({
             </button>
           </div>
         ) : null}
-        {/* Hub renders Eject inline as the last list row; other tabs keep the
-          footer button. */}
         {effectiveTab !== "hub" && hasSelection && onEject ? (
-          <div className="mt-1.5 pt-1.5">
+          <div className="mt-1.5 border-t border-border/70 pt-1.5 pb-2">
             <button
               type="button"
               onClick={onEject}
@@ -553,6 +639,8 @@ function ModelSelectorContent({
             </button>
           </div>
         ) : null}
+          </>
+        )}
       </TooltipProvider>
     </PopoverContent>
   );
@@ -565,6 +653,10 @@ export function ModelSelector({
   value,
   defaultValue,
   activeGgufVariant,
+  activeModelConfig,
+  activeGgufContextLength,
+  selectedConfig,
+  selectedGgufVariant,
   onValueChange,
   onEject,
   onFoldersChange,
@@ -693,6 +785,11 @@ export function ModelSelector({
         loraModels={loraModels}
         externalModels={externalModels}
         value={selected}
+        activeGgufVariant={activeGgufVariant}
+        activeModelConfig={activeModelConfig}
+        activeGgufContextLength={activeGgufContextLength}
+        selectedConfig={selectedConfig}
+        selectedGgufVariant={selectedGgufVariant}
         onSelect={handleSelect}
         onEject={onEject ? handleEject : undefined}
         onFoldersChange={onFoldersChange}
@@ -784,7 +881,7 @@ function ExternalModelPicker({
           ) : (
             grouped.map((group) => (
               <div key={group.providerId}>
-                <div className="flex items-center gap-2 px-2.5 py-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
+                <div className="flex items-center gap-2 px-2.5 py-1.5 text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
                   <ExternalProviderLogo
                     providerType={group.models[0]?.providerType}
                     className="size-3.5"
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx b/studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
similarity index 79%
rename from studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
index 16cc8a1956..bad6c27bb2 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
@@ -14,10 +14,7 @@ import {
   DialogTitle,
 } from "@/components/ui/dialog";
 import { Spinner } from "@/components/ui/spinner";
-import {
-  type BrowseFoldersResponse,
-  browseFolders,
-} from "@/features/chat/api/chat-api";
+import { type BrowseFoldersResponse, browseFolders } from "@/features/chat";
 import { ChevronUpStandardIcon } from "@/lib/chevron-icons";
 import { cn } from "@/lib/utils";
 import { Folder02Icon } from "@hugeicons/core-free-icons";
@@ -31,13 +28,16 @@ export interface FolderBrowserProps {
   onSelect: (path: string) => void;
   /** Optional initial directory. Defaults to the user's home on the server. */
   initialPath?: string;
+  title?: string;
+  confirmLabel?: string;
+  showModelHints?: boolean;
 }
 
 function splitBreadcrumb(path: string): { label: string; value: string }[] {
   if (!path) return [];
-  // Detect path style BEFORE normalizing: on POSIX, `\` is a valid filename
-  // char, so blindly rewriting `\` -> `/` mangles names like `my\backup` into
-  // 404ing breadcrumbs. Only Windows-style paths (drive letter, or UNC) convert.
+  // Detect path style BEFORE normalizing: on POSIX `\` is a valid filename char,
+  // so rewriting `\` -> `/` would mangle names like `my\backup`. Only Windows
+  // paths (drive letter or UNC) convert.
   const isWindowsDrive =
     /^[A-Za-z]:[\\/]/.test(path) || /^[A-Za-z]:$/.test(path);
   const isUnc = /^\\\\/.test(path);
@@ -58,9 +58,8 @@ function splitBreadcrumb(path: string): { label: string; value: string }[] {
     return parts;
   }
 
-  // Windows drive path (C:, D:): first segment is the drive. Use `C:/` as the
-  // crumb value so clicking the drive root navigates to the drive root, not the
-  // drive-relative CWD (`C:` alone resolves to CWD-on-C, not `C:\`).
+  // Windows drive path: use `C:/` as the crumb value so clicking the drive root
+  // goes to the drive root, not the drive-relative CWD (`C:` alone is CWD-on-C).
   if (/^[A-Za-z]:$/.test(segments[0])) {
     const driveRoot = `${segments[0]}/`;
     let cur = driveRoot;
@@ -82,6 +81,9 @@ export function FolderBrowser({
   onOpenChange,
   onSelect,
   initialPath,
+  title = "Select folder to detect models",
+  confirmLabel = "Use this folder",
+  showModelHints = true,
 }: FolderBrowserProps) {
   const [data, setData] = useState<BrowseFoldersResponse | null>(null);
   const [path, setPath] = useState<string | undefined>(initialPath);
@@ -90,47 +92,43 @@ export function FolderBrowser({
   const [error, setError] = useState<string | null>(null);
   const abortRef = useRef<AbortController | null>(null);
 
-  const navigate = useCallback(
-    (
-      target: string | undefined,
-      hidden: boolean,
-      opts?: { fallbackOnError?: boolean },
-    ) => {
-      abortRef.current?.abort();
-      const ctrl = new AbortController();
-      abortRef.current = ctrl;
-      setLoading(true);
-      setError(null);
-      // Forward the signal so cancelled navigation aborts the backend
-      // enumeration, not just the response.
-      browseFolders(target, hidden, ctrl.signal)
-        .then((res) => {
-          if (ctrl.signal.aborted) return;
-          setData(res);
-          setPath(res.current);
-        })
-        .catch((err) => {
-          if (ctrl.signal.aborted) return;
-          // Surface the error; if the first request (e.g. a bad initialPath)
-          // fails, fall back to HOME so the modal stays navigable.
-          const message = err instanceof Error ? err.message : String(err);
-          setError(message);
-          if (opts?.fallbackOnError && target !== undefined) {
-            // Re-issue without a target -> backend defaults to HOME.
-            // Don't recurse if HOME itself fails (allowlist always has HOME).
-            queueMicrotask(() => navigate(undefined, hidden));
-          }
-        })
-        .finally(() => {
-          if (!ctrl.signal.aborted) setLoading(false);
-        });
-    },
-    [],
-  );
+  function navigate(
+    target: string | undefined,
+    hidden: boolean,
+    opts?: { fallbackOnError?: boolean },
+  ) {
+    abortRef.current?.abort();
+    const ctrl = new AbortController();
+    abortRef.current = ctrl;
+    setLoading(true);
+    setError(null);
+    // Forward the signal so cancelled navigation aborts the backend
+    // enumeration, not just the response.
+    browseFolders(target, hidden, ctrl.signal)
+      .then((res) => {
+        if (ctrl.signal.aborted) return;
+        setData(res);
+        setPath(res.current);
+      })
+      .catch((err) => {
+        if (ctrl.signal.aborted) return;
+        // Surface the error; if the first request (e.g. a bad initialPath)
+        // fails, fall back to HOME so the modal stays navigable.
+        const message = err instanceof Error ? err.message : String(err);
+        setError(message);
+        if (opts?.fallbackOnError && target !== undefined) {
+          // Re-issue without a target -> backend defaults to HOME.
+          // Don't recurse if HOME itself fails (allowlist always has HOME).
+          queueMicrotask(() => navigate(undefined, hidden));
+        }
+      })
+      .finally(() => {
+        if (!ctrl.signal.aborted) setLoading(false);
+      });
+  }
 
   // Fetch only on closed -> open; later navigation is driven by `navigate()`,
   // so `path` is deliberately kept out of the dependency list.
-  // eslint-disable-next-line react-hooks/exhaustive-deps
   useEffect(() => {
     if (!open) return;
     // fallbackOnError: recover into HOME if initialPath is bad, rather than
@@ -147,7 +145,7 @@ export function FolderBrowser({
 
   const crumbs = useMemo(
     () => (data?.current ? splitBreadcrumb(data.current) : []),
-    [data?.current],
+    [data],
   );
 
   return (
@@ -158,11 +156,11 @@ export function FolderBrowser({
         data-testid="folder-browser-dialog"
       >
         <DialogHeader className="px-6 pt-6 pb-2">
-          <DialogTitle>Select folder to detect models</DialogTitle>
+          <DialogTitle>{title}</DialogTitle>
         </DialogHeader>
 
         {/* Breadcrumb */}
-        <div className="flex flex-wrap items-center gap-0.5 border-t border-border/50 px-6 py-2 font-mono text-[11px] text-muted-foreground">
+        <div className="flex flex-wrap items-center gap-0.5 border-t border-border/50 px-6 py-2 font-mono text-ui-11 text-muted-foreground">
           {crumbs.length === 0 ? (
             <span className="text-muted-foreground/60">(loading…)</span>
           ) : (
@@ -193,7 +191,7 @@ export function FolderBrowser({
                 type="button"
                 onClick={() => navigate(s, showHidden)}
                 disabled={loading}
-                className="rounded-full border border-border/50 px-2 py-0.5 font-mono text-[10px] text-muted-foreground transition-colors hover:bg-muted hover:text-foreground disabled:opacity-40"
+                className="rounded-full border border-border/50 px-2 py-0.5 font-mono text-ui-10 text-muted-foreground transition-colors hover:bg-muted hover:text-foreground disabled:opacity-40"
                 title={s}
               >
                 {s.length > 36 ? `…${s.slice(-33)}` : s}
@@ -238,21 +236,22 @@ export function FolderBrowser({
                 </button>
               )}
               {data.entries.length === 0 &&
-                !(data.model_files_here && data.model_files_here > 0) && (
+                (!showModelHints ||
+                  !(data.model_files_here && data.model_files_here > 0)) && (
                   <div className="px-6 py-3 text-xs text-muted-foreground/60">
                     (empty directory)
                   </div>
                 )}
-              {data.model_files_here !== undefined &&
+              {showModelHints && data.model_files_here !== undefined &&
                 data.model_files_here > 0 && (
-                  <div className="border-t border-border/30 px-6 py-1.5 text-[10px] text-foreground/70">
+                  <div className="border-t border-border/30 px-6 py-1.5 text-ui-10 text-foreground/70">
                     {data.model_files_here} model file
                     {data.model_files_here === 1 ? "" : "s"} in this folder.
                     Click "Use this folder" to scan it.
                   </div>
                 )}
               {data.truncated === true && (
-                <div className="border-t border-border/30 px-6 py-1.5 text-[10px] text-muted-foreground/70">
+                <div className="border-t border-border/30 px-6 py-1.5 text-ui-10 text-muted-foreground/70">
                   Showing first {data.entries.length} entries. Narrow the path
                   to see more.
                 </div>
@@ -280,8 +279,8 @@ export function FolderBrowser({
                     )}
                   />
                   <span className="truncate font-mono">{e.name}</span>
-                  {e.has_models && (
-                    <span className="ml-auto shrink-0 rounded-full border border-border/50 px-1.5 py-0 text-[9px] uppercase tracking-wider text-muted-foreground">
+                  {showModelHints && e.has_models && (
+                    <span className="ml-auto shrink-0 rounded-full border border-border/50 px-1.5 py-0 text-ui-9 uppercase tracking-wider text-muted-foreground">
                       models
                     </span>
                   )}
@@ -320,7 +319,7 @@ export function FolderBrowser({
               onClick={handleConfirm}
               disabled={!path || loading || !!error}
             >
-              Use this folder
+              {confirmLabel}
             </Button>
           </div>
         </DialogFooter>
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-capabilities.ts b/studio/frontend/src/features/model-picker/components/model-selector/model-capabilities.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-capabilities.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/model-capabilities.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
similarity index 90%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
index 4de96d3648..09bb43abdc 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
@@ -1,12 +1,12 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { DeleteConfirmDialog } from "@/features/hub/catalog/download-card";
+import { DeleteConfirmDialog } from "@/features/hub";
+import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import { Delete02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
-import { useCallback, useState, type ReactNode } from "react";
-import { toast } from "@/lib/toast";
+import { type ReactNode, useCallback, useState } from "react";
 
 interface ModelDeleteActionProps {
   ariaLabel: string;
@@ -63,7 +63,8 @@ export function ModelDeleteAction({
         disabled={disabled}
         className={cn(
           "shrink-0 rounded-md p-1.5 text-muted-foreground/60 transition-colors hover:bg-destructive/10 hover:text-destructive",
-          disabled && "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
+          disabled &&
+            "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
           buttonClassName,
         )}
       >
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
similarity index 63%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
index 58510762d4..bbef42063f 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
@@ -6,24 +6,18 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
-import { useChatRuntimeStore } from "@/features/chat/stores/chat-runtime-store";
 import { cn } from "@/lib/utils";
 import { Settings02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 
-/** Gear button on a downloaded quant row. Stages the model into the Run
- * settings sidebar (always, regardless of the Load-on-selection toggle) so the
- * user can set load options, then click Load model. */
 export function ModelLoadSettingsAction({
   ariaLabel,
-  repoId,
-  quant,
-  maxContext,
+  onConfigure,
+  className,
 }: {
   ariaLabel: string;
-  repoId: string;
-  quant: string;
-  maxContext?: number | null;
+  onConfigure: () => void;
+  className?: string;
 }) {
   return (
     <Tooltip delayDuration={0}>
@@ -32,16 +26,12 @@ export function ModelLoadSettingsAction({
           type="button"
           onClick={(e) => {
             e.stopPropagation();
-            useChatRuntimeStore.getState().stageModel({
-              id: repoId,
-              ggufVariant: quant,
-              isDownloaded: true,
-              contextLength: maxContext ?? null,
-            });
+            onConfigure();
           }}
           aria-label={ariaLabel}
           className={cn(
-            "shrink-0 rounded-md p-1 text-muted-foreground/60 transition-colors hover:bg-muted hover:text-foreground",
+            "shrink-0 rounded-md p-1 text-muted-foreground/60 transition-colors hover:bg-black/5 hover:text-foreground dark:hover:bg-white/10",
+            className,
           )}
         >
           <HugeiconsIcon
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/model-row-menu.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-row-menu.tsx
new file mode 100644
index 0000000000..ee149d802f
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-row-menu.tsx
@@ -0,0 +1,289 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+// Condensed row actions for model rows: everything except the run-settings
+// gear collapses into one dots menu (pin, update, delete) so rows don't grow
+// an icon strip. Mirrors the sidebar chat rows' MoreVertical menu pattern.
+
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuSeparator,
+  DropdownMenuTrigger,
+} from "@/components/ui/dropdown-menu";
+import { usePlatformStore } from "@/config/env";
+import { revealCachedModel } from "@/features/chat";
+import {
+  DeleteConfirmDialog,
+  UpdateConfirmDialog,
+  ggufVariantsMatch,
+  subscribeJobListeners,
+} from "@/features/hub";
+import { toast } from "@/lib/toast";
+import { cn } from "@/lib/utils";
+import {
+  Delete02Icon,
+  Folder01Icon,
+  MoreVerticalIcon,
+  PinIcon,
+  PinOffIcon,
+} from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { RefreshCw } from "lucide-react";
+import {
+  type ReactNode,
+  useCallback,
+  useEffect,
+  useRef,
+  useState,
+} from "react";
+
+interface ModelRowMenuPin {
+  pinned: boolean;
+  /** Menu item labels, e.g. "Pin quant to the top" / "Unpin quant". */
+  pinLabel: string;
+  unpinLabel: string;
+  onToggle: () => void;
+}
+
+interface ModelRowMenuUpdate {
+  title: string;
+  description: ReactNode;
+  /** Repo + variant the update targets (see ModelUpdateAction). */
+  repoId: string;
+  variant?: string | null;
+  disabled?: boolean;
+  onConfirm: () => Promise<void> | void;
+  onUpdated?: () => void;
+}
+
+interface ModelRowMenuDelete {
+  title: string;
+  description: ReactNode;
+  successMessage: string;
+  disabled?: boolean;
+  onConfirm: () => Promise<void> | void;
+  onDeleted?: () => void;
+}
+
+/** Managed-cache location for "Reveal in Finder" (resolved server-side). */
+interface ModelRowMenuCachePath {
+  repoId: string;
+  variant?: string;
+}
+
+export function ModelRowMenu({
+  ariaLabel,
+  buttonClassName,
+  iconClassName,
+  cachePath,
+  pin,
+  update,
+  del,
+}: {
+  ariaLabel: string;
+  buttonClassName?: string;
+  iconClassName?: string;
+  /** Enables "Reveal in Finder" for cached repos. */
+  cachePath?: ModelRowMenuCachePath;
+  pin?: ModelRowMenuPin;
+  update?: ModelRowMenuUpdate;
+  del?: ModelRowMenuDelete;
+}) {
+  const deviceType = usePlatformStore((s) => s.deviceType);
+  const revealLabel =
+    deviceType === "mac"
+      ? "Reveal in Finder"
+      : deviceType === "windows"
+        ? "Reveal in File Explorer"
+        : "Reveal in File Manager";
+  const [deleteOpen, setDeleteOpen] = useState(false);
+  const [deleting, setDeleting] = useState(false);
+  const [updateOpen, setUpdateOpen] = useState(false);
+
+  // Refresh the caller when this repo+variant's managed update completes
+  // (mirrors ModelUpdateAction).
+  const onUpdatedRef = useRef(update?.onUpdated);
+  useEffect(() => {
+    onUpdatedRef.current = update?.onUpdated;
+  }, [update?.onUpdated]);
+  const updateRepoId = update?.repoId;
+  const updateVariant = update?.variant ?? null;
+  useEffect(() => {
+    if (!updateRepoId) return;
+    return subscribeJobListeners("model", updateRepoId, {
+      onComplete: (completedVariant) => {
+        const matches = updateVariant
+          ? ggufVariantsMatch(completedVariant, updateVariant)
+          : !completedVariant;
+        if (matches) onUpdatedRef.current?.();
+      },
+    });
+  }, [updateRepoId, updateVariant]);
+
+  const onDeleteConfirm = del?.onConfirm;
+  const onDeleted = del?.onDeleted;
+  const deleteSuccessMessage = del?.successMessage;
+  const handleDeleteConfirm = useCallback(async () => {
+    if (!onDeleteConfirm) return;
+    setDeleting(true);
+    try {
+      await onDeleteConfirm();
+      if (deleteSuccessMessage) toast.success(deleteSuccessMessage);
+      onDeleted?.();
+      setDeleteOpen(false);
+    } catch (err) {
+      toast.error(
+        err instanceof Error ? err.message : "Failed to delete model",
+      );
+    } finally {
+      setDeleting(false);
+    }
+  }, [onDeleteConfirm, onDeleted, deleteSuccessMessage]);
+
+  const onUpdateConfirm = update?.onConfirm;
+  const handleUpdateConfirm = useCallback(() => {
+    // Start the re-download and close the dialog; the Downloads panel owns
+    // progress + cancel. Only a failure to START toasts.
+    void Promise.resolve()
+      .then(onUpdateConfirm)
+      .catch((err) => {
+        toast.error(
+          err instanceof Error ? err.message : "Failed to start update",
+        );
+      });
+    setUpdateOpen(false);
+  }, [onUpdateConfirm]);
+
+  const cachePathRepoId = cachePath?.repoId;
+  const cachePathVariant = cachePath?.variant;
+  const handleReveal = useCallback(() => {
+    if (!cachePathRepoId) return;
+    revealCachedModel(cachePathRepoId, cachePathVariant).catch((err) => {
+      toast.error(
+        err instanceof Error ? err.message : "Failed to open file manager",
+      );
+    });
+  }, [cachePathRepoId, cachePathVariant]);
+
+  if (!pin && !update && !del && !cachePath) return null;
+
+  return (
+    <>
+      <DropdownMenu>
+        <DropdownMenuTrigger asChild={true}>
+          <button
+            type="button"
+            onClick={(e) => e.stopPropagation()}
+            aria-label={ariaLabel}
+            className={cn(
+              "shrink-0 rounded-md p-1 text-muted-foreground/60 transition-colors hover:bg-black/5 hover:text-foreground dark:hover:bg-white/10",
+              buttonClassName,
+            )}
+          >
+            <HugeiconsIcon
+              icon={MoreVerticalIcon}
+              strokeWidth={1.75}
+              className={cn("size-3.5", iconClassName)}
+            />
+          </button>
+        </DropdownMenuTrigger>
+        <DropdownMenuContent
+          side="bottom"
+          align="end"
+          sideOffset={2}
+          className="unsloth-plus-menu menu-flat-destructive w-48"
+        >
+          {pin && (
+            <DropdownMenuItem
+              onSelect={(e) => {
+                e.stopPropagation();
+                pin.onToggle();
+              }}
+            >
+              <HugeiconsIcon
+                icon={pin.pinned ? PinOffIcon : PinIcon}
+                strokeWidth={1.75}
+                className="size-icon"
+              />
+              <span>{pin.pinned ? pin.unpinLabel : pin.pinLabel}</span>
+            </DropdownMenuItem>
+          )}
+          {cachePath && (
+            <DropdownMenuItem
+              onSelect={(e) => {
+                e.stopPropagation();
+                handleReveal();
+              }}
+            >
+              <HugeiconsIcon
+                icon={Folder01Icon}
+                strokeWidth={1.75}
+                className="size-icon"
+              />
+              <span>{revealLabel}</span>
+            </DropdownMenuItem>
+          )}
+          {update && (
+            <DropdownMenuItem
+              disabled={update.disabled}
+              onSelect={(e) => {
+                e.stopPropagation();
+                setUpdateOpen(true);
+              }}
+            >
+              <RefreshCw className="size-icon" />
+              <span>Update</span>
+            </DropdownMenuItem>
+          )}
+          {del && (
+            <>
+              {(cachePath || pin || update) && <DropdownMenuSeparator />}
+              <DropdownMenuItem
+                variant="destructive"
+                disabled={del.disabled}
+                onSelect={(e) => {
+                  e.stopPropagation();
+                  setDeleteOpen(true);
+                }}
+              >
+                <HugeiconsIcon
+                  icon={Delete02Icon}
+                  strokeWidth={1.75}
+                  className="size-icon"
+                />
+                <span>Delete</span>
+              </DropdownMenuItem>
+            </>
+          )}
+        </DropdownMenuContent>
+      </DropdownMenu>
+
+      {del && (
+        <DeleteConfirmDialog
+          open={deleteOpen}
+          onOpenChange={(nextOpen) => {
+            if (!nextOpen && deleting) return;
+            setDeleteOpen(nextOpen);
+          }}
+          title={del.title}
+          description={del.description}
+          deleting={deleting}
+          onConfirm={() => void handleDeleteConfirm()}
+        />
+      )}
+
+      {update && (
+        <UpdateConfirmDialog
+          open={updateOpen}
+          onOpenChange={setUpdateOpen}
+          title={update.title}
+          description={update.description}
+          updating={false}
+          onConfirm={handleUpdateConfirm}
+        />
+      )}
+    </>
+  );
+}
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
similarity index 82%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
index db7628777a..b13ed33d04 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
@@ -1,12 +1,20 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { subscribeJobListeners } from "@/features/hub/download-manager";
-import { UpdateConfirmDialog } from "@/features/hub/catalog/download-card";
-import { ggufVariantsMatch } from "@/features/hub/lib/model-identity";
+import {
+  UpdateConfirmDialog,
+  ggufVariantsMatch,
+  subscribeJobListeners,
+} from "@/features/hub";
 import { cn } from "@/lib/utils";
 import { RefreshCw } from "lucide-react";
-import { useCallback, useEffect, useRef, useState, type ReactNode } from "react";
+import {
+  type ReactNode,
+  useCallback,
+  useEffect,
+  useRef,
+  useState,
+} from "react";
 import { toast } from "sonner";
 
 interface ModelUpdateActionProps {
@@ -42,10 +50,10 @@ export function ModelUpdateAction({
 }: ModelUpdateActionProps) {
   const [open, setOpen] = useState(false);
 
-  // Refresh the caller when this repo+variant's download finishes so the "update available" cue
-  // clears. A ref keeps the subscription stable across renders.
   const onUpdatedRef = useRef(onUpdated);
-  onUpdatedRef.current = onUpdated;
+  useEffect(() => {
+    onUpdatedRef.current = onUpdated;
+  }, [onUpdated]);
   useEffect(() => {
     return subscribeJobListeners("model", repoId, {
       onComplete: (completedVariant) => {
@@ -83,7 +91,8 @@ export function ModelUpdateAction({
         disabled={disabled}
         className={cn(
           "shrink-0 rounded-md p-1.5 text-muted-foreground/60 transition-colors hover:bg-amber-500/10 hover:text-amber-700 dark:hover:bg-amber-500/15 dark:hover:text-amber-300",
-          disabled && "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
+          disabled &&
+            "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
           buttonClassName,
         )}
       >
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts b/studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
similarity index 93%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
index dbcd4b9a1b..c6665e7658 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
@@ -40,7 +40,8 @@ export function loadedAt(times: ModelLoadTimes, id: string): number {
 export function useModelLoadTimes(currentValue?: string): ModelLoadTimes {
   const [times, setTimes] = useState<ModelLoadTimes>(() => readLoadTimes());
   useEffect(() => {
-    if (currentValue) setTimes(recordModelLoaded(currentValue));
+    if (!currentValue) return;
+    queueMicrotask(() => setTimes(recordModelLoaded(currentValue)));
   }, [currentValue]);
   return times;
 }
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx b/studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
similarity index 57%
rename from studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
index 766139e2b4..20810b3f11 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
@@ -10,49 +10,48 @@ import {
   TooltipTrigger,
 } from "@/components/ui/tooltip";
 import { usePlatformStore } from "@/config/env";
-import { ApiProviderLogo } from "@/features/chat/api-provider-logo";
+import { ApiProviderLogo } from "@/features/chat";
 import {
   type ScanFolderInfo,
   addScanFolder,
-  deleteCachedModel,
   deleteFineTunedModel,
-  listCachedGguf,
-  listCachedModels,
   listGgufVariants,
-  listLocalModels,
   listRecommendedFolders,
   listScanFolders,
   removeScanFolder,
-} from "@/features/chat/api/chat-api";
-import { useChatRuntimeStore } from "@/features/chat/stores/chat-runtime-store";
+} from "@/features/chat";
+import { useChatRuntimeStore } from "@/features/chat";
 import type {
   CachedGgufRepo,
   CachedModelRepo,
+  GgufVariantDetail,
   LocalModelInfo,
-} from "@/features/chat/api/chat-api";
-import type { GgufVariantDetail } from "@/features/chat/types/api";
-import { DotTag } from "@/features/hub/catalog/dot-tag";
+} from "@/features/chat";
 import {
+  DotTag,
   type HubOption,
   HubOptionMenu,
-} from "@/features/hub/catalog/hub-option-menu";
-import { TransportConflictDialog } from "@/features/hub/catalog/transport-conflict-dialog";
-import { TrainIcon } from "@/features/hub/components/train-icon";
-import { useHubInfiniteScroll } from "@/features/hub/hooks/use-hub-infinite-scroll";
+  TrainIcon,
+  TransportConflictDialog,
+  deleteCachedModel,
+  listGgufVariants as listGgufVariantsCached,
+  useHubInfiniteScroll,
+} from "@/features/hub";
 import {
   type HfModelResult,
   type HfSortKey,
   useHubModelSearch,
-} from "@/features/hub/hooks/use-hub-model-search";
-import { useOnlineStatus } from "@/features/hub/hooks/use-online-status";
-import { isHiddenModelId } from "@/features/hub/lib/hidden-models";
-import { classifyUnslothSupport } from "@/features/hub/lib/unsloth-support";
-import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
+} from "@/features/hub";
 import {
+  classifyUnslothSupport,
   downloadManager,
+  hfApiToken,
+  isHiddenModelId,
   jobKeyOf,
   useDownloadManagerStore,
-} from "@/features/hub/download-manager";
+  useHfTokenStore,
+  useOnlineStatus,
+} from "@/features/hub";
 import { useDebouncedValue, useGpuInfo } from "@/hooks";
 import { extractParamLabel } from "@/lib/model-size";
 import { toast } from "@/lib/toast";
@@ -61,6 +60,7 @@ import type { VramFitStatus } from "@/lib/vram";
 import { checkVramFit, estimateLoadingVram } from "@/lib/vram";
 import {
   Add01Icon,
+  ArrowUpDownIcon,
   AudioWave01Icon,
   Cancel01Icon,
   DashboardCircleIcon,
@@ -68,7 +68,6 @@ import {
   Flag01Icon,
   Folder02Icon,
   PinIcon,
-  PinOffIcon,
   RemoveCircleIcon,
   Search01Icon,
   ViewIcon,
@@ -87,6 +86,7 @@ import {
   useRef,
   useState,
 } from "react";
+import { useChatPickerInventory } from "../../inventory/use-chat-picker-inventory";
 import { FolderBrowser } from "./folder-browser";
 import {
   type ModelCapabilities,
@@ -94,14 +94,15 @@ import {
   hasAnyCapability,
 } from "./model-capabilities";
 import { ModelDeleteAction } from "./model-delete-action";
-import { ModelUpdateAction } from "./model-update-action";
 import { ModelLoadSettingsAction } from "./model-load-settings-action";
+import { ModelRowMenu } from "./model-row-menu";
 import {
   type ModelLoadTimes,
   loadedAt,
   useModelLoadTimes,
 } from "./model-usage";
 import {
+  makePinRank,
   pinKey,
   pinnedQuantEntries,
   usePinnedModelsStore,
@@ -320,7 +321,7 @@ function ListLabel({
         divider ? "mt-3 border-t border-border/50 pt-3" : "pt-3",
       )}
     >
-      <span className="flex items-center gap-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
+      <span className="flex items-center gap-1.5 text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
         {icon}
         {children}
       </span>
@@ -349,15 +350,12 @@ function ListLabel({
 
 /** Format bytes to a human-readable size string. */
 function formatBytes(bytes: number): string {
-  // Guard non-positive / non-finite sizes (0, missing -> NaN, Infinity) so we
-  // never render "NaN undefined" or a negative unit index.
+  // Guard non-positive / non-finite sizes so we never render "NaN undefined".
   if (!Number.isFinite(bytes) || bytes <= 0) return "0 B";
-  // Decimal (base-1000) units to match what Hugging Face reports for a repo's
-  // file sizes -- e.g. 217 GB, not the 201.8 GiB a base-1024 divide would show.
-  // (GPU-fit math below stays base-1024 since VRAM is binary.)
-  // Divide iteratively rather than via Math.log, which has float error at exact
-  // powers of 1000 (log(1e12)/log(1000) = 3.9999... would mislabel 1 TB as
-  // "1000 GB"); the loop also can't run off the end of units.
+  // Decimal (base-1000) units to match Hugging Face's reported file sizes (GPU-fit
+  // math below stays base-1024 since VRAM is binary). Divide iteratively rather
+  // than via Math.log, which has float error at exact powers of 1000 (mislabeling
+  // 1 TB as "1000 GB") and could run off the end of units.
   const units = ["B", "KB", "MB", "GB", "TB"];
   let i = 0;
   let value = bytes;
@@ -422,8 +420,7 @@ function ggufVariantsMatchForPicker(
   right: string | null | undefined,
 ): boolean {
   return (
-    normalizeGgufVariantForPicker(left) ===
-    normalizeGgufVariantForPicker(right)
+    normalizeGgufVariantForPicker(left) === normalizeGgufVariantForPicker(right)
   );
 }
 
@@ -529,7 +526,7 @@ function ModelRow({
     >
       <span className="flex min-w-0 flex-1 items-baseline">
         {owner && !hideOwner ? (
-          <span className="inline-flex min-w-0 max-w-[45%] shrink items-baseline text-[13px] text-muted-foreground/90">
+          <span className="inline-flex min-w-0 max-w-[45%] shrink items-baseline text-ui-13 text-muted-foreground/90">
             <span className="truncate">{owner}</span>
             <span className="shrink-0 text-muted-foreground/45">/</span>
           </span>
@@ -579,25 +576,25 @@ function ModelRow({
           </span>
         )}
         {vramStatus === "exceeds" && (
-          <span className="text-[9px] font-medium !text-red-700 !bg-red-50 dark:!text-red-300 dark:!bg-red-500/15 px-1.5 py-0.5 rounded">
+          <span className="text-ui-9 font-medium !text-red-700 !bg-red-50 dark:!text-red-300 dark:!bg-red-500/15 px-1.5 py-0.5 rounded">
             OOM
           </span>
         )}
         {vramStatus === "tight" && (
-          <span className="text-[9px] font-medium !text-amber-400">TIGHT</span>
+          <span className="text-ui-9 font-medium !text-amber-400">TIGHT</span>
         )}
         {paramLabel ? (
-          <span className="rounded-md border border-border/60 px-1.5 py-px text-[10px] font-medium text-muted-foreground tabular-nums">
+          <span className="rounded-md border border-border/60 px-1.5 py-px text-ui-10 font-medium text-muted-foreground tabular-nums">
             {paramLabel}
           </span>
         ) : null}
         {parsed.texts.map((text) => (
-          <span key={text} className="text-[10px] text-muted-foreground">
+          <span key={text} className="text-ui-10 text-muted-foreground">
             {text}
           </span>
         ))}
         {parsed.size !== undefined ? (
-          <span className="text-[10px] text-muted-foreground tabular-nums">
+          <span className="text-ui-10 text-muted-foreground tabular-nums">
             {parsed.size}
           </span>
         ) : null}
@@ -617,7 +614,7 @@ function ModelRow({
   // Optional Hugging Face address line for online/Hub rows, rendered under
   // whichever tooltip shows so the repo id / URL is always visible on hover.
   const hubUrlLine = hubUrl ? (
-    <span className="block mt-1 text-[10px] text-muted-foreground break-all">
+    <span className="block mt-1 text-ui-10 text-muted-foreground break-all">
       {hubUrl}
     </span>
   ) : null;
@@ -625,7 +622,7 @@ function ModelRow({
   const tooltipBody = vramTooltipText ? (
     <>
       {label}
-      <span className="block text-[10px] mt-1">{vramTooltipText}</span>
+      <span className="block text-ui-10 mt-1">{vramTooltipText}</span>
       {hubUrlLine}
     </>
   ) : tooltipText ? (
@@ -674,12 +671,17 @@ function isValidGgufVariant(variant: unknown): variant is GgufVariantDetail {
   );
 }
 
-function normalizeGgufVariantsResponse(res: {
-  variants?: unknown;
-  default_variant?: unknown;
-  has_vision?: unknown;
-  context_length?: unknown;
-} | null | undefined): {
+function normalizeGgufVariantsResponse(
+  res:
+    | {
+        variants?: unknown;
+        default_variant?: unknown;
+        has_vision?: unknown;
+        context_length?: unknown;
+      }
+    | null
+    | undefined,
+): {
   variants: GgufVariantDetail[];
   defaultVariant: string | null;
   hasVision: boolean;
@@ -722,6 +724,7 @@ function GgufVariantExpander({
   parentOptionKey,
   onNavigatePastStart,
   onNavigatePastEnd,
+  onConfigure,
   sourceOverride,
   variantActions,
   onDevice = false,
@@ -738,6 +741,7 @@ function GgufVariantExpander({
   parentOptionKey?: string;
   onNavigatePastStart?: () => void;
   onNavigatePastEnd?: () => void;
+  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   sourceOverride?: ModelSelectorChangeMeta["source"];
   /** Update/delete actions for cached variant rows. Omitted by browse-only
    *  expanders (Recommended, etc.) that don't manage on-disk variants. */
@@ -765,13 +769,18 @@ function GgufVariantExpander({
   const pinnedKeys = usePinnedModelsStore((s) => s.pinned);
   const togglePinnedQuant = usePinnedModelsStore((s) => s.togglePinned);
   const onUpdateVariant = variantActions?.onUpdate;
-  const updateVariantTitle = variantActions?.updateTitle ?? "Update cached model?";
-  const renderUpdateVariantDescription = variantActions?.renderUpdateDescription;
+  const updateVariantTitle =
+    variantActions?.updateTitle ?? "Update cached model?";
+  const renderUpdateVariantDescription =
+    variantActions?.renderUpdateDescription;
   const updateDisabled = variantActions?.updateDisabled ?? false;
   const onDeleteVariant = variantActions?.onDelete;
-  const deleteVariantTitle = variantActions?.deleteTitle ?? "Delete cached model?";
-  const renderDeleteVariantDescription = variantActions?.renderDeleteDescription;
-  const getDeleteVariantSuccessMessage = variantActions?.getDeleteSuccessMessage;
+  const deleteVariantTitle =
+    variantActions?.deleteTitle ?? "Delete cached model?";
+  const renderDeleteVariantDescription =
+    variantActions?.renderDeleteDescription;
+  const getDeleteVariantSuccessMessage =
+    variantActions?.getDeleteSuccessMessage;
   const deleteDisabled = variantActions?.deleteDisabled ?? false;
   const [variants, setVariants] = useState<GgufVariantDetail[] | null>(null);
   const [defaultVariant, setDefaultVariant] = useState<string | null>(null);
@@ -784,8 +793,11 @@ function GgufVariantExpander({
 
   useEffect(() => {
     let canceled = false;
-    setLoading(true);
-    setError(null);
+    queueMicrotask(() => {
+      if (canceled) return;
+      setLoading(true);
+      setError(null);
+    });
 
     listGgufVariants(repoId, hfToken)
       .then((res) => {
@@ -813,17 +825,12 @@ function GgufVariantExpander({
   }, [repoId, refreshKey, hfToken]);
 
   // Covers Unix absolute (/), Windows drive (C:\, D:/), UNC (\\server), relative (./, ../), tilde (~/)
-  const isLocalPath = /^(\/|\.{1,2}[\\\/]|~[\\\/]|[A-Za-z]:[\\\/]|\\\\)/.test(
+  const isLocalPath = /^(\/|\.{1,2}[\\/]|~[\\/]|[A-Za-z]:[\\/]|\\\\)/.test(
     repoId,
   );
 
   const handleVariantClick = useCallback(
     (quant: string, downloaded?: boolean, sizeBytes?: number) => {
-      // Only seed the staged context for picks whose weights are already on
-      // disk. The staging effect short-circuits on a known contextLength
-      // (pendingHasContext) before starting the download, so attaching it to an
-      // undownloaded quant from a partially cached repo would skip the download
-      // entirely (and, with Load on selection, never load).
       const isAvailable = isLocalPath || downloaded === true;
       onSelect(repoId, {
         source: sourceOverride ?? (isLocalPath ? "local" : "hub"),
@@ -832,6 +839,7 @@ function GgufVariantExpander({
         isDownloaded: isLocalPath ? true : downloaded,
         expectedBytes: sizeBytes,
         contextLength: isAvailable ? nativeContext : undefined,
+        isGguf: true,
       });
     },
     [repoId, isLocalPath, onSelect, sourceOverride, nativeContext],
@@ -846,13 +854,12 @@ function GgufVariantExpander({
 
   const getGgufFit = useCallback(
     (sizeBytes: number): "fits" | "tight" | "oom" => {
-      // No device budget at all (no GPU and no known system RAM): can't
-      // classify, so don't scare the user with OOM badges.
+      // No device budget at all: can't classify, so don't show OOM badges.
       if (totalBudgetGb <= 0) return "fits";
       const gb = sizeBytes / 1024 ** 3;
       if (gb <= 0 || gb <= gpuBudgetGb) return "fits";
-      // No-GPU / unified-memory hosts (Mac) have only the RAM budget, so the
-      // tier collapses to fit-or-oom against system RAM rather than GPU+offload.
+      // No-GPU / unified-memory hosts (Mac) have only the RAM budget, so the tier
+      // collapses to fit-or-oom against system RAM.
       if (gpuBudgetGb <= 0) return gb <= totalBudgetGb ? "fits" : "oom";
       if (gb <= totalBudgetGb) return "tight";
       return "oom";
@@ -870,17 +877,13 @@ function GgufVariantExpander({
     if (defaultV && getGgufFit(defaultV.size_bytes) !== "oom")
       return defaultVariant;
     // Largest non-OOM variant (best quality that fits)
-    const fitting = variants.filter(
-      (v) => getGgufFit(v.size_bytes) !== "oom",
-    );
+    const fitting = variants.filter((v) => getGgufFit(v.size_bytes) !== "oom");
     if (fitting.length > 0) {
       fitting.sort((a, b) => b.size_bytes - a.size_bytes);
       return fitting[0].quant;
     }
     // All OOM -- recommend smallest (most likely to partially run)
-    const sorted = [...variants].sort(
-      (a, b) => a.size_bytes - b.size_bytes,
-    );
+    const sorted = [...variants].sort((a, b) => a.size_bytes - b.size_bytes);
     return sorted[0]?.quant ?? defaultVariant;
   }, [variants, defaultVariant, totalBudgetGb, getGgufFit]);
 
@@ -973,11 +976,11 @@ function GgufVariantExpander({
           redundant; its Vision badge is relayed to the name instead. */}
       {!onDevice && (
         <div className="px-2 py-1 flex items-center gap-1.5">
-          <span className="text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
+          <span className="text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
             Quantizations
           </span>
           {hasVision && (
-            <span className="flex items-center gap-0.5 text-[9px] font-medium text-indigo-700 dark:text-indigo-300">
+            <span className="flex items-center gap-0.5 text-ui-9 font-medium text-indigo-700 dark:text-indigo-300">
               <HugeiconsIcon
                 icon={ViewIcon}
                 className="size-3"
@@ -996,7 +999,7 @@ function GgufVariantExpander({
         const keyBase = `${repoId}:${v.filename}`;
         const variantOptionKey = makeModelOptionKey("gguf-variant", keyBase);
         return (
-          <div key={v.filename} className="flex items-center gap-0.5">
+          <div key={v.filename} className="flex items-center">
             <button
               type="button"
               {...variantList.getOptionProps(variantOptionKey, false)}
@@ -1004,7 +1007,7 @@ function GgufVariantExpander({
                 handleVariantClick(v.quant, v.downloaded, expectedBytes)
               }
               className={cn(
-                "flex min-w-0 flex-1 items-center justify-between gap-2 rounded-full px-2 py-1 text-left text-sm transition-colors hover:bg-[#ececec] focus-visible:bg-[#ececec] focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring dark:hover:bg-[var(--sidebar-accent)] dark:focus-visible:bg-[var(--sidebar-accent)]",
+                "flex min-w-0 flex-1 items-center justify-between gap-2 rounded-full py-1 pl-2 pr-1.5 text-left text-sm transition-colors hover:bg-[#ececec] focus-visible:bg-[#ececec] focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring dark:hover:bg-[var(--sidebar-accent)] dark:focus-visible:bg-[var(--sidebar-accent)]",
               )}
             >
               <span className="min-w-0 flex-1 truncate font-mono text-xs">
@@ -1015,137 +1018,135 @@ function GgufVariantExpander({
                 </span>
                 {v.downloaded ? (
                   <>
-                    <span className="ml-1.5 text-[9px] font-sans font-medium text-green-600/90 dark:text-green-400/80">
+                    <span className="ml-1.5 text-ui-9 font-sans font-medium text-green-600/90 dark:text-green-400/80">
                       downloaded
                     </span>
                     {v.update_available ? (
-                      <span className="ml-1.5 text-[9px] font-sans font-medium text-amber-700 dark:text-amber-300">
+                      <span className="ml-1.5 text-ui-9 font-sans font-medium text-amber-700 dark:text-amber-300">
                         update available
                       </span>
-                    ): null}
+                    ) : null}
                   </>
                 ) : v.quant === effectiveRecommended ? (
-                  <span className="ml-1.5 text-[9px] font-sans font-medium text-primary/70">
+                  <span className="ml-1.5 text-ui-9 font-sans font-medium text-primary/70">
                     recommended
                   </span>
                 ) : null}
               </span>
               <span className="flex items-center gap-1.5 shrink-0">
                 {oom && (
-                  <span className="text-[9px] font-medium !text-red-700 !bg-red-50 dark:!text-red-300 dark:!bg-red-500/15 px-1.5 py-0.5 rounded">
+                  <span className="text-ui-9 font-medium !text-red-700 !bg-red-50 dark:!text-red-300 dark:!bg-red-500/15 px-1.5 py-0.5 rounded">
                     OOM
                   </span>
                 )}
                 {tight && (
-                  <span className="text-[9px] font-medium !text-amber-400">
+                  <span className="text-ui-9 font-medium !text-amber-400">
                     TIGHT
                   </span>
                 )}
-                <span className="text-[10px] text-muted-foreground">
+                <span className="text-ui-10 text-muted-foreground">
                   {formatBytes(v.size_bytes)}
                 </span>
               </span>
             </button>
-            {v.downloaded && v.update_available && onUpdateVariant && (
-              <ModelUpdateAction
-                ariaLabel={`Update ${repoId} ${v.quant}`}
-                title={updateVariantTitle}
-                description={
-                  renderUpdateVariantDescription?.(v.quant) ?? (
-                    <>
-                      This will update{" "}
-                      <span className="font-medium text-foreground">
-                        {repoId} ({v.quant})
-                      </span>{"."}
-                    </>
-                  )
-                }
-                repoId={repoId}
-                variant={v.quant}
-                buttonClassName="p-1"
-                iconClassName="size-3"
-                disabled={updateDisabled}
-                onConfirm={() => onUpdateVariant(v.quant, expectedBytes)}
-                onUpdated={() => setRefreshKey((key) => key + 1)}
-              />
-            )}
-            {v.downloaded && allowPin && (
-              <Tooltip delayDuration={0}>
-                <TooltipTrigger asChild={true}>
-                  <button
-                    type="button"
-                    onClick={() => togglePinnedQuant(repoId, v.quant)}
-                    aria-label={
-                      pinnedKeys.includes(pinKey(repoId, v.quant))
-                        ? `Unpin ${repoId} ${v.quant}`
-                        : `Pin ${repoId} ${v.quant}`
-                    }
-                    aria-pressed={pinnedKeys.includes(pinKey(repoId, v.quant))}
-                    className={cn(
-                      "shrink-0 rounded-md p-1 transition-colors hover:bg-black/5 hover:text-foreground dark:hover:bg-white/10",
-                      pinnedKeys.includes(pinKey(repoId, v.quant))
-                        ? "text-foreground/80"
-                        : "text-muted-foreground/60",
-                    )}
-                  >
-                    <HugeiconsIcon
-                      icon={
-                        pinnedKeys.includes(pinKey(repoId, v.quant))
-                          ? PinOffIcon
-                          : PinIcon
-                      }
-                      strokeWidth={1.75}
-                      className="size-3"
-                    />
-                  </button>
-                </TooltipTrigger>
-                <TooltipContent side="bottom" className="tooltip-compact">
-                  {pinnedKeys.includes(pinKey(repoId, v.quant))
-                    ? "Unpin quant"
-                    : "Pin quant to the top"}
-                </TooltipContent>
-              </Tooltip>
-            )}
-            {v.downloaded && (
+            {v.downloaded && onConfigure && (
               <ModelLoadSettingsAction
                 ariaLabel={`Inference settings for ${repoId} ${v.quant}`}
-                repoId={repoId}
-                quant={v.quant}
-                maxContext={nativeContext}
+                className="relative left-0.5"
+                onConfigure={() =>
+                  onConfigure(repoId, {
+                    source: sourceOverride ?? (isLocalPath ? "local" : "hub"),
+                    isLora: false,
+                    ggufVariant: v.quant,
+                    isDownloaded: true,
+                    expectedBytes,
+                    contextLength: nativeContext,
+                    isGguf: true,
+                  })
+                }
               />
             )}
-            {v.downloaded && onDeleteVariant && (
-              <ModelDeleteAction
-                ariaLabel={`Delete ${repoId} ${v.quant}`}
-                title={deleteVariantTitle}
-                description={
-                  renderDeleteVariantDescription?.(v.quant) ?? (
-                    <>
-                      This will remove{" "}
-                      <span className="font-medium text-foreground">
-                        {repoId} ({v.quant})
-                      </span>{" "}
-                      from disk. You can re-download it later.
-                    </>
-                  )
-                }
-                successMessage={
-                  getDeleteVariantSuccessMessage?.(v.quant) ??
-                  `Deleted ${repoId} ${v.quant}`
-                }
-                buttonClassName="p-1"
-                iconClassName="size-3"
-                disabled={deleteDisabled}
-                onConfirm={async () => {
-                  await onDeleteVariant(v.quant);
-                  // Drop the pin too: a pinned row for a deleted file
-                  // would try to load something that no longer exists.
-                  if (pinnedKeys.includes(pinKey(repoId, v.quant))) {
-                    togglePinnedQuant(repoId, v.quant);
+            {v.downloaded &&
+              (allowPin ||
+                (v.update_available && onUpdateVariant) ||
+                onDeleteVariant ||
+                !isLocalPath) && (
+                <ModelRowMenu
+                  ariaLabel={`More options for ${repoId} ${v.quant}`}
+                  iconClassName="size-3"
+                  cachePath={
+                    isLocalPath ? undefined : { repoId, variant: v.quant }
                   }
-                }}
-              />
-            )}
+                  pin={
+                    allowPin
+                      ? {
+                          pinned: pinnedKeys.includes(pinKey(repoId, v.quant)),
+                          pinLabel: "Pin to top",
+                          unpinLabel: "Unpin",
+                          onToggle: () => togglePinnedQuant(repoId, v.quant),
+                        }
+                      : undefined
+                  }
+                  update={
+                    v.update_available && onUpdateVariant
+                      ? {
+                          title: updateVariantTitle,
+                          description: renderUpdateVariantDescription?.(
+                            v.quant,
+                          ) ?? (
+                            <>
+                              This will update{" "}
+                              <span className="font-medium text-foreground">
+                                {repoId} ({v.quant})
+                              </span>
+                              {"."}
+                            </>
+                          ),
+                          repoId,
+                          variant: v.quant,
+                          disabled: updateDisabled,
+                          onConfirm: () =>
+                            onUpdateVariant(v.quant, expectedBytes),
+                          onUpdated: () => setRefreshKey((key) => key + 1),
+                        }
+                      : undefined
+                  }
+                  del={
+                    onDeleteVariant
+                      ? {
+                          title: deleteVariantTitle,
+                          description: renderDeleteVariantDescription?.(
+                            v.quant,
+                          ) ?? (
+                            <>
+                              This will remove{" "}
+                              <span className="font-medium text-foreground">
+                                {repoId} ({v.quant})
+                              </span>{" "}
+                              from disk. You can re-download it later.
+                            </>
+                          ),
+                          successMessage:
+                            getDeleteVariantSuccessMessage?.(v.quant) ??
+                            `Deleted ${repoId} ${v.quant}`,
+                          disabled: deleteDisabled,
+                          onConfirm: async () => {
+                            await onDeleteVariant(v.quant);
+                            // Drop the pin too: a pinned row for a deleted file
+                            // would try to load something that no longer exists.
+                            if (pinnedKeys.includes(pinKey(repoId, v.quant))) {
+                              togglePinnedQuant(repoId, v.quant);
+                            }
+                            // Re-fetch this expander's variants so the deleted
+                            // quant stops showing as downloaded (and clickable to
+                            // reload) while the repo still has other cached quants.
+                            setRefreshKey((key) => key + 1);
+                          },
+                        }
+                      : undefined
+                  }
+                />
+              )}
           </div>
         );
       })}
@@ -1170,17 +1171,6 @@ let _lmStudioCache: LocalModelInfo[] = [];
 let _localDirCache: LocalModelInfo[] = [];
 let _customFolderCache: LocalModelInfo[] = [];
 let _scanFoldersCache: ScanFolderInfo[] = [];
-let _onDeviceCachesReady = false;
-let _cachedGgufRequestVersion = 0;
-let _cachedModelsRequestVersion = 0;
-let _localModelsRequestVersion = 0;
-const _onDeviceCacheListeners = new Set<(settled?: boolean) => void>();
-
-const ON_DEVICE_CACHE_TIMEOUT_MS = 30_000;
-
-function notifyOnDeviceCachesChanged(settled = false): void {
-  for (const listener of _onDeviceCacheListeners) listener(settled);
-}
 
 /** True when any on-device model (downloaded GGUF, cached repo, LM Studio, or
  * custom-folder model) is known. Reads the module caches, which persist across
@@ -1326,13 +1316,26 @@ function localPathTooltip(name: string, path: string): ReactNode {
   return (
     <>
       <span className="block break-words">{name}</span>
-      <span className="block mt-1 text-[10px] text-muted-foreground break-all">
+      <span className="block mt-1 text-ui-10 text-muted-foreground break-all">
         {path}
       </span>
     </>
   );
 }
 
+function localModelMeta(isGguf = false): ModelSelectorChangeMeta {
+  return {
+    source: "local",
+    isLora: false,
+    isDownloaded: true,
+    ...(isGguf ? { isGguf: true } : {}),
+  };
+}
+
+function localDirectGgufMeta(): ModelSelectorChangeMeta {
+  return localModelMeta(true);
+}
+
 /** Hugging Face address for an online/Hub row, or undefined when the repo id is
  * missing so the row shows no (empty) address line on hover. */
 function hubRepoUrl(id: string | null | undefined): string | undefined {
@@ -1343,9 +1346,7 @@ function hubRepoUrl(id: string | null | undefined): string | undefined {
 /** Whether a local model is an MLX build (name hint). MLX runs on Mac only, so
  * callers gate visibility on the host being a Mac. */
 function localModelIsMlx(m: LocalModelInfo): boolean {
-  return (
-    isMlxId(m.id) || isMlxId(m.display_name) || isMlxId(m.model_id ?? "")
-  );
+  return isMlxId(m.id) || isMlxId(m.display_name) || isMlxId(m.model_id ?? "");
 }
 
 /** Whether a local model matches the format toggle (GGUF detected by name/path). */
@@ -1369,6 +1370,7 @@ export function HubModelPicker({
   onFoldersChange,
   onBrowseHub,
   onModelsChange,
+  onConfigure,
   deleteDisabled = false,
   section = "downloaded",
   sectionToggle,
@@ -1385,12 +1387,12 @@ export function HubModelPicker({
   /** Open the full Hub page to browse more models. */
   onBrowseHub?: () => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
+  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   deleteDisabled?: boolean;
   /** Section shown when not searching. Search spans all sections. */
   section?: "downloaded" | "recommended" | "custom" | "connected";
   /** Section toggle rendered under the search bar. */
   sectionToggle?: ReactNode;
-  /** Eject the loaded model. Rendered as the last list row when set. */
   onEject?: () => void;
 }) {
   const gpu = useGpuInfo();
@@ -1411,7 +1413,8 @@ export function HubModelPicker({
   // Shared Hub search stack (the same hooks the Hub page uses) so the picker
   // and Hub run one implementation. Scoped to unsloth like the old listing.
   const online = useOnlineStatus();
-  const accessToken = hfToken || undefined;
+  // Sanitize to anonymous on a malformed token, matching the Hub page.
+  const accessToken = hfApiToken(hfToken);
   // Recommended section: a live unsloth listing sorted by the dropdown. The
   // same sort drives the search results so the dropdown works while searching.
   const [recommendedSort, setRecommendedSort] =
@@ -1433,9 +1436,8 @@ export function HubModelPicker({
     pinUnslothFirst: true,
     keepUnsupportedTags: true,
     accessToken,
-    // Only the Recommended section renders Hub results (On Device / Connected
-    // use local data), so keep the Hub hooks idle on the other tabs to avoid
-    // needless requests/spinner and to preserve offline-local behavior.
+    // Only Recommended renders Hub results, so keep the Hub hooks idle on other
+    // tabs to avoid needless requests and preserve offline-local behavior.
     enabled: online && section === "recommended",
   });
   const recommendedSearch = useHubModelSearch("", {
@@ -1448,10 +1450,9 @@ export function HubModelPicker({
     enabled: online && section === "recommended",
   });
 
-  // Lowercased repo ids confirmed GGUF by the store or HF search.
-  // Absence means "no hint" -> hasGgufSuffix is the fallback (don't
-  // conflate unknown with known-not-GGUF). Lowercased so store and HF
-  // IDs differing only by casing match the same hint.
+  // Lowercased repo ids confirmed GGUF by the store or HF search. Absence means
+  // "no hint" -> hasGgufSuffix is the fallback (don't conflate unknown with
+  // known-not-GGUF). Lowercased so store and HF IDs match regardless of casing.
   const modelGgufIds = useMemo(() => {
     const ids = new Set<string>();
     for (const model of models) {
@@ -1493,12 +1494,14 @@ export function HubModelPicker({
   const setFitOnDeviceOnly = useChatRuntimeStore((s) => s.setFitOnDeviceOnly);
   // Repos the user clicked to collapse while expand-by-default is on. Kept in
   // memory only, so it resets on reload (and when the setting is toggled).
-  const [collapsedGguf, setCollapsedGguf] = useState<Set<string>>(
-    () => new Set(),
-  );
-  useEffect(() => {
-    setCollapsedGguf(new Set());
-  }, [expandQuantizations]);
+  const [collapsedGgufState, setCollapsedGgufState] = useState<{
+    expandQuantizations: boolean;
+    value: Set<string>;
+  }>(() => ({ expandQuantizations, value: new Set() }));
+  const collapsedGguf =
+    collapsedGgufState.expandQuantizations === expandQuantizations
+      ? collapsedGgufState.value
+      : new Set<string>();
   const isGgufExpanded = useCallback(
     (id: string) =>
       expandQuantizations ? !collapsedGguf.has(id) : expandedGguf === id,
@@ -1509,11 +1512,15 @@ export function HubModelPicker({
   const toggleGgufExpanded = useCallback(
     (id: string) => {
       if (expandQuantizations) {
-        setCollapsedGguf((prev) => {
-          const next = new Set(prev);
+        setCollapsedGgufState((prev) => {
+          const current =
+            prev.expandQuantizations === expandQuantizations
+              ? prev.value
+              : new Set<string>();
+          const next = new Set(current);
           if (next.has(id)) next.delete(id);
           else next.add(id);
-          return next;
+          return { expandQuantizations, value: next };
         });
       } else {
         setExpandedGguf((prev) => (prev === id ? null : id));
@@ -1574,14 +1581,37 @@ export function HubModelPicker({
     });
   }, []);
 
-  // Cached (downloaded) repos -- module-level cache avoids flashing an
-  // empty "Downloaded" section when the popover re-mounts.
-  const [cachedGguf, setCachedGguf] =
-    useState<CachedGgufRepo[]>(_cachedGgufCache);
-  const [cachedModels, setCachedModels] =
-    useState<CachedModelRepo[]>(_cachedModelsCache);
-  const alreadyCached = _onDeviceCachesReady || hasDownloadedModels();
-  const [cachedReady, setCachedReady] = useState(alreadyCached);
+  const pickerInventory = useChatPickerInventory({ enabled: true });
+  const { cachedGguf, cachedModels, cachedReady, refreshInventory } =
+    pickerInventory;
+  const lmStudioModels = useMemo(
+    () =>
+      sortLmStudio(
+        pickerInventory.localModels.filter((m) => m.source === "lmstudio"),
+      ),
+    [pickerInventory.localModels],
+  );
+  const localDirModels = useMemo(
+    () => pickerInventory.localModels.filter((m) => m.source === "models_dir"),
+    [pickerInventory.localModels],
+  );
+  const customFolderModels = useMemo(
+    () => pickerInventory.localModels.filter((m) => m.source === "custom"),
+    [pickerInventory.localModels],
+  );
+  useEffect(() => {
+    _cachedGgufCache = cachedGguf;
+    _cachedModelsCache = cachedModels;
+    _lmStudioCache = lmStudioModels;
+    _localDirCache = localDirModels;
+    _customFolderCache = customFolderModels;
+  }, [
+    cachedGguf,
+    cachedModels,
+    lmStudioModels,
+    localDirModels,
+    customFolderModels,
+  ]);
   const [updateConflictKey, setUpdateConflictKey] = useState<string | null>(
     null,
   );
@@ -1605,35 +1635,6 @@ export function HubModelPicker({
     setUpdateConflictKey(null);
   }, [updateConflictKey]);
 
-  // LM Studio local models -- module-level cache, same pattern as above.
-  const [lmStudioModels, setLmStudioModels] =
-    useState<LocalModelInfo[]>(_lmStudioCache);
-  // Models found under the local models directory (./models), so they stay
-  // selectable on the On Device tab after leaving the Fine-tuned tab.
-  const [localDirModels, setLocalDirModels] =
-    useState<LocalModelInfo[]>(_localDirCache);
-  const [customFolderModels, setCustomFolderModels] =
-    useState<LocalModelInfo[]>(_customFolderCache);
-
-  useEffect(() => {
-    const syncModuleCaches = (settled = false) => {
-      setCachedGguf(_cachedGgufCache);
-      setCachedModels(_cachedModelsCache);
-      setLmStudioModels(_lmStudioCache);
-      setLocalDirModels(_localDirCache);
-      setCustomFolderModels(_customFolderCache);
-      setCachedReady(
-        (ready) =>
-          ready || settled || _onDeviceCachesReady || hasDownloadedModels(),
-      );
-    };
-    _onDeviceCacheListeners.add(syncModuleCaches);
-    syncModuleCaches();
-    return () => {
-      _onDeviceCacheListeners.delete(syncModuleCaches);
-    };
-  }, []);
-
   // Custom scan folders management
   const [scanFolders, setScanFolders] =
     useState<ScanFolderInfo[]>(_scanFoldersCache);
@@ -1644,94 +1645,9 @@ export function HubModelPicker({
   const [showFolderBrowser, setShowFolderBrowser] = useState(false);
   const [recommendedFolders, setRecommendedFolders] = useState<string[]>([]);
 
-  const applyLocalModels = useCallback(
-    (res: Awaited<ReturnType<typeof listLocalModels>>) => {
-      const lm = sortLmStudio(
-        res.models.filter((m) => m.source === "lmstudio"),
-      );
-      _lmStudioCache = lm;
-      setLmStudioModels(lm);
-      const ld = res.models.filter((m) => m.source === "models_dir");
-      _localDirCache = ld;
-      setLocalDirModels(ld);
-      const cf = res.models.filter((m) => m.source === "custom");
-      _customFolderCache = cf;
-      setCustomFolderModels(cf);
-      notifyOnDeviceCachesChanged();
-    },
-    [],
-  );
-
-  const refreshColdOnDeviceCaches = useCallback(() => {
-    const ggufRequestVersion = ++_cachedGgufRequestVersion;
-    const modelsRequestVersion = ++_cachedModelsRequestVersion;
-    const localRequestVersion = ++_localModelsRequestVersion;
-    let ggufResult: Awaited<ReturnType<typeof listCachedGguf>> | undefined;
-    let modelsResult: Awaited<ReturnType<typeof listCachedModels>> | undefined;
-    let localResult: Awaited<ReturnType<typeof listLocalModels>> | undefined;
-    let released = false;
-
-    const ggufRequest = listCachedGguf().then(
-      (value) => { if (!released) ggufResult = value; },
-      () => {},
-    );
-    const modelsRequest = listCachedModels(hfToken || undefined).then(
-      (value) => { if (!released) modelsResult = value; },
-      () => {},
-    );
-    const localRequest = listLocalModels().then(
-      (value) => {
-        localResult = value;
-        if (released && localRequestVersion === _localModelsRequestVersion) {
-          if (ggufResult !== undefined && modelsResult !== undefined) _onDeviceCachesReady = true;
-          applyLocalModels(value);
-        }
-      },
-      () => {},
-    );
-    const isCurrent = () =>
-      ggufRequestVersion === _cachedGgufRequestVersion &&
-      modelsRequestVersion === _cachedModelsRequestVersion &&
-      localRequestVersion === _localModelsRequestVersion;
-    const publish = (invalidate = false) => {
-      if (!isCurrent()) return;
-      if (invalidate) {
-        released = true;
-        ++_cachedGgufRequestVersion;
-        ++_cachedModelsRequestVersion;
-      }
-      if (ggufResult !== undefined) {
-        _cachedGgufCache = ggufResult;
-        setCachedGguf(ggufResult);
-      }
-      if (modelsResult !== undefined) {
-        _cachedModelsCache = modelsResult;
-        setCachedModels(modelsResult);
-      }
-      if (localResult !== undefined) applyLocalModels(localResult);
-      if (ggufResult !== undefined && modelsResult !== undefined && localResult !== undefined) {
-        _onDeviceCachesReady = true;
-      }
-      notifyOnDeviceCachesChanged(true);
-    };
-    const timeout = window.setTimeout(() => publish(true), ON_DEVICE_CACHE_TIMEOUT_MS);
-    void Promise.all([ggufRequest, modelsRequest, localRequest]).then(() => {
-      window.clearTimeout(timeout);
-      publish();
-    });
-  }, [applyLocalModels, hfToken]);
-
   const refreshLocalModelsList = useCallback(() => {
-    if (!_onDeviceCachesReady && !hasDownloadedModels()) return refreshColdOnDeviceCaches();
-    const requestVersion = ++_localModelsRequestVersion;
-    listLocalModels()
-      .then((res) => {
-        if (requestVersion === _localModelsRequestVersion) {
-          applyLocalModels(res);
-        }
-      })
-      .catch(() => {});
-  }, [applyLocalModels, refreshColdOnDeviceCaches]);
+    void pickerInventory.refreshInventory();
+  }, [pickerInventory.refreshInventory]);
 
   const refreshScanFolders = useCallback(() => {
     listScanFolders()
@@ -1751,9 +1667,8 @@ export function HubModelPicker({
       if (!trimmed || folderLoading) return;
       setFolderError(null);
       setFolderLoading(true);
-      // From the folder browser's one-click "Use this folder": the typed-
-      // input panel is closed, so the inline folderError is invisible.
-      // Surface failures (denylisted path, sandbox 403, etc.) via toast.
+      // From the folder browser's "Use this folder": the typed-input panel is
+      // closed, so surface failures (denylisted path, sandbox 403) via toast.
       const fromBrowser = overridePath !== undefined;
       try {
         const created = await addScanFolder(trimmed);
@@ -1810,46 +1725,37 @@ export function HubModelPicker({
   );
 
   const refreshCachedLists = useCallback(() => {
-    if (!_onDeviceCachesReady && !hasDownloadedModels()) return refreshColdOnDeviceCaches();
-    const ggufRequestVersion = ++_cachedGgufRequestVersion;
-    listCachedGguf()
-      .then((v) => {
-        if (ggufRequestVersion !== _cachedGgufRequestVersion) return;
-        _cachedGgufCache = v;
-        setCachedGguf(v);
-        notifyOnDeviceCachesChanged();
-      })
-      .catch(() => {});
-    const modelsRequestVersion = ++_cachedModelsRequestVersion;
-    listCachedModels(hfToken || undefined)
-      .then((v) => {
-        if (modelsRequestVersion !== _cachedModelsRequestVersion) return;
-        _cachedModelsCache = v;
-        setCachedModels(v);
-        notifyOnDeviceCachesChanged();
-      })
-      .catch(() => {});
-    refreshLocalModelsList();
-  }, [hfToken, refreshColdOnDeviceCaches, refreshLocalModelsList]);
+    void pickerInventory.refreshInventory();
+  }, [pickerInventory.refreshInventory]);
 
   // Updates run as managed downloads (Downloads panel: progress + Cancel), not a blocking
   // call. The worker pulls only changed blobs, so the cached copy stays usable until done.
-  const startManagedUpdate = useCallback((repoId: string, variant: string, expectedBytes: number) => {
-    return downloadManager
-      .requestStart({
-        kind: "model",
-        repoId,
-        variant,
-        expectedBytes,
-      })
-      .then((outcome) => {
-        if (outcome === "conflict") {
-          setUpdateConflictKey(jobKeyOf("model", repoId, variant));
-        } else if (outcome === "error") {
-          throw new Error("Failed to start update");
-        }
-      });
-  }, []);
+  const startManagedUpdate = useCallback(
+    (repoId: string, variant: string, expectedBytes: number) => {
+      return downloadManager
+        .requestStart({
+          kind: "model",
+          repoId,
+          variant,
+          expectedBytes,
+        })
+        .then((outcome) => {
+          if (outcome === "conflict") {
+            setUpdateConflictKey(jobKeyOf("model", repoId, variant));
+          } else if (outcome === "busy") {
+            // A sibling variant/snapshot for this repo is already downloading,
+            // so this update did not start. Say so instead of closing the
+            // dialog as if it began and leaving the cached copy stale.
+            toast.info("A download for this model is already in progress", {
+              description: "Try updating again once it finishes.",
+            });
+          } else if (outcome === "error") {
+            throw new Error("Failed to start update");
+          }
+        });
+    },
+    [],
+  );
 
   const updateGgufVariant = useCallback(
     (repoId: string, quant: string, expectedBytes: number) =>
@@ -1862,96 +1768,11 @@ export function HubModelPicker({
     listRecommendedFolders()
       .then(setRecommendedFolders)
       .catch(() => {});
+  }, [refreshScanFolders]);
 
-    // Publish downloaded and local rows as one bounded snapshot. Existing data
-    // stays visible during background refreshes, and a failed source keeps its
-    // last successful cache instead of clearing or durably marking it ready.
-    const controller = new AbortController();
-    const timeout = window.setTimeout(
-      () => controller.abort(),
-      ON_DEVICE_CACHE_TIMEOUT_MS,
-    );
-    const aborted = new Promise<never>((_, reject) => {
-      controller.signal.addEventListener(
-        "abort",
-        () => reject(controller.signal.reason),
-        { once: true },
-      );
-    });
-    const bounded = <T,>(request: Promise<T>) =>
-      Promise.race([request, aborted]);
-    let cancelled = false;
-    const ggufRequestVersion = ++_cachedGgufRequestVersion;
-    const modelsRequestVersion = ++_cachedModelsRequestVersion;
-    const localRequestVersion = ++_localModelsRequestVersion;
-    const localRequest = listLocalModels();
-
-    void Promise.allSettled([
-      bounded(listCachedGguf(controller.signal)),
-      bounded(listCachedModels(hfToken || undefined, controller.signal)),
-      bounded(localRequest),
-    ]).then(([ggufResult, modelsResult, localResult]) => {
-      window.clearTimeout(timeout);
-      if (cancelled) return;
-
-      const ggufIsCurrent =
-        ggufRequestVersion === _cachedGgufRequestVersion;
-      const modelsAreCurrent =
-        modelsRequestVersion === _cachedModelsRequestVersion;
-      const localIsCurrent =
-        localRequestVersion === _localModelsRequestVersion;
-
-      if (ggufResult.status === "fulfilled" && ggufIsCurrent) {
-        _cachedGgufCache = ggufResult.value;
-        setCachedGguf(ggufResult.value);
-        notifyOnDeviceCachesChanged();
-      }
-      if (modelsResult.status === "fulfilled" && modelsAreCurrent) {
-        _cachedModelsCache = modelsResult.value;
-        setCachedModels(modelsResult.value);
-        notifyOnDeviceCachesChanged();
-      }
-      if (localResult.status === "fulfilled" && localIsCurrent) {
-        applyLocalModels(localResult.value);
-      }
-      if (localResult.status === "rejected" && controller.signal.aborted) {
-        void localRequest.then((value) => {
-          if (cancelled || localRequestVersion !== _localModelsRequestVersion) return;
-          if (ggufResult.status === "fulfilled" && modelsResult.status === "fulfilled") _onDeviceCachesReady = true;
-          applyLocalModels(value);
-        }).catch(() => {});
-      }
-      const snapshotIsCurrent =
-        ggufIsCurrent && modelsAreCurrent && localIsCurrent;
-      if (
-        ggufResult.status === "fulfilled" &&
-        modelsResult.status === "fulfilled" &&
-        localResult.status === "fulfilled" &&
-        snapshotIsCurrent
-      ) {
-        _onDeviceCachesReady = true;
-      }
-      notifyOnDeviceCachesChanged(snapshotIsCurrent);
-    });
-
-    return () => {
-      cancelled = true;
-      window.clearTimeout(timeout);
-      controller.abort();
-      queueMicrotask(() => {
-        if (
-          ggufRequestVersion === _cachedGgufRequestVersion &&
-          modelsRequestVersion === _cachedModelsRequestVersion &&
-          localRequestVersion === _localModelsRequestVersion
-        ) {
-          ++_cachedGgufRequestVersion;
-          ++_cachedModelsRequestVersion;
-          ++_localModelsRequestVersion;
-          notifyOnDeviceCachesChanged(true);
-        }
-      });
-    };
-  }, [applyLocalModels, hfToken, refreshScanFolders]);
+  useEffect(() => {
+    void refreshInventory();
+  }, [refreshInventory]);
 
   // Hide downloaded models from the recommended list. Case-insensitive
   // since the HF cache lowercases repo IDs.
@@ -1988,7 +1809,8 @@ export function HubModelPicker({
       // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
       // on Mac (matches the empty Recommended view so search stays consistent).
       .filter(
-        (id) => !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
+        (id) =>
+          !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
       )
       .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id));
     // Sort: GGUFs first, then hub models
@@ -2258,14 +2080,12 @@ export function HubModelPicker({
   const togglePinned = usePinnedModelsStore((s) => s.togglePinned);
   const pinnedSet = useMemo(() => new Set(pinnedIds), [pinnedIds]);
 
-  // Candidate pins whose repo still exists in the managed cache. Per-quant
-  // validation below is required because deleting one variant can leave a
-  // sibling quant (and therefore the repo row) cached.
+  // Candidate pins whose repo still exists in the cache. Per-quant validation
+  // below is needed because deleting one variant can leave a sibling cached.
   const pinnedQuantCandidates = useMemo(() => {
-    // The existence check ignores the text query (but keeps the format filter)
-    // so a pinned quant stays findable by its quant name even when the repo id
-    // does not match the query; querying visibleCachedGguf here would drop the
-    // repo before the later `${repoId} ${quant}` predicate could surface it.
+    // The existence check ignores the text query (keeps the format filter) so a
+    // pinned quant stays findable by quant name; querying visibleCachedGguf would
+    // drop the repo before the `${repoId} ${quant}` predicate could surface it.
     const cached = new Set(
       sortedCachedGguf
         .filter((c) => matchesFormatFilter(c.repo_id, true, formatFilter))
@@ -2275,21 +2095,22 @@ export function HubModelPicker({
       cached.has(entry.repoId),
     );
   }, [pinnedIds, sortedCachedGguf, formatFilter]);
-  const pinnedQuantValidationKey = useMemo(() => {
-    const cacheByRepo = new Map(
-      sortedCachedGguf.map((repo) => [repo.repo_id, repo]),
-    );
-    return pinnedQuantCandidates
-      .map((entry) => {
-        const cached = cacheByRepo.get(entry.repoId);
-        return `${pinKey(entry.repoId, entry.quant)}@${cached?.size_bytes ?? 0}:${cached?.last_modified ?? 0}`;
-      })
-      .join("\u0000");
-  }, [pinnedQuantCandidates, sortedCachedGguf]);
   const [pinnedQuantValidation, setPinnedQuantValidation] = useState<{
-    key: string;
+    validated: boolean;
     downloaded: ReadonlySet<string>;
-  }>({ key: "", downloaded: new Set() });
+  }>({ validated: false, downloaded: new Set() });
+  const prunePinnedQuantValidation = useCallback(
+    (repoId: string, quant: string) => {
+      const key = pinKey(repoId, quant);
+      setPinnedQuantValidation((prev) => {
+        if (!prev.downloaded.has(key)) return prev;
+        const downloaded = new Set(prev.downloaded);
+        downloaded.delete(key);
+        return { ...prev, downloaded };
+      });
+    },
+    [],
+  );
 
   useEffect(() => {
     let cancelled = false;
@@ -2301,12 +2122,13 @@ export function HubModelPicker({
     void Promise.all(
       repoIds.map(async (repoId) => {
         try {
-          const response = await listGgufVariants(
+          const response = await listGgufVariantsCached(
             repoId,
             hfToken || undefined,
+            { preferLocalCache: true },
           );
-          return normalizeGgufVariantsResponse(response).variants
-            .filter((variant) => variant.downloaded === true)
+          return normalizeGgufVariantsResponse(response)
+            .variants.filter((variant) => variant.downloaded === true)
             .map((variant) => pinKey(repoId, variant.quant));
         } catch {
           // If the backend cannot verify a quant, hiding the direct-load row
@@ -2317,7 +2139,7 @@ export function HubModelPicker({
     ).then((groups) => {
       if (!cancelled) {
         setPinnedQuantValidation({
-          key: pinnedQuantValidationKey,
+          validated: true,
           downloaded: new Set(groups.flat()),
         });
       }
@@ -2326,13 +2148,13 @@ export function HubModelPicker({
     return () => {
       cancelled = true;
     };
-  }, [hfToken, pinnedQuantCandidates, pinnedQuantValidationKey]);
+  }, [hfToken, pinnedQuantCandidates]);
   const downloadedPinnedQuantKeys = useMemo<ReadonlySet<string>>(
     () =>
-      pinnedQuantValidation.key === pinnedQuantValidationKey
+      pinnedQuantValidation.validated
         ? pinnedQuantValidation.downloaded
         : new Set(),
-    [pinnedQuantValidation, pinnedQuantValidationKey],
+    [pinnedQuantValidation],
   );
 
   // Verified downloaded quants, in pin order and filtered by repo id or quant.
@@ -2344,17 +2166,32 @@ export function HubModelPicker({
         (!q ||
           normalizeForSearch(`${entry.repoId} ${entry.quant}`).includes(q)),
     );
-  }, [
-    debouncedQuery,
-    downloadedPinnedQuantKeys,
-    pinnedQuantCandidates,
-  ]);
+  }, [debouncedQuery, downloadedPinnedQuantKeys, pinnedQuantCandidates]);
 
   const pinnedCachedModelRows = useMemo(
-    () => visibleCachedModelRows.filter((c) => pinnedSet.has(pinKey(c.repo_id))),
+    () =>
+      visibleCachedModelRows.filter((c) => pinnedSet.has(pinKey(c.repo_id))),
     [visibleCachedModelRows, pinnedSet],
   );
 
+  const pinnedRows = useMemo(() => {
+    const rank = makePinRank(pinnedIds);
+    const rows = [
+      ...pinnedQuants.map((entry) => ({
+        key: pinKey(entry.repoId, entry.quant),
+        entry,
+        model: null,
+      })),
+      ...pinnedCachedModelRows.map((model) => ({
+        key: pinKey(model.repo_id),
+        entry: null,
+        model,
+      })),
+    ];
+    rows.sort((a, b) => rank(a.key) - rank(b.key));
+    return rows;
+  }, [pinnedIds, pinnedQuants, pinnedCachedModelRows]);
+
   // Split downloaded models so non-Unsloth repos get their own "Other models"
   // section above Fine-tuned.
   const unslothCachedGguf = useMemo(
@@ -2394,26 +2231,28 @@ export function HubModelPicker({
   const filteredRecommendedIds = useMemo(() => {
     if (!showHfSection) return [];
     const q = normalizeForSearch(debouncedQuery.trim());
-    return recommendedIds
-      .filter((id) => normalizeForSearch(id).includes(q))
-      .filter((id) =>
-        matchesFormatFilter(id, isKnownGgufRepo(id), formatFilter),
-      )
-      // Curated defaults obey the fit toggle like the live HF rows, else large
-      // defaults resurface in search results with the filter on.
-      .filter(
-        (id) =>
-          !fitOnDeviceOnly ||
-          downloadedSet.has(id.toLowerCase()) ||
-          hfModelFitsDevice(
-            {
-              id,
-              totalParams: recommendedParamCountById.get(id),
-              isGguf: isKnownGgufRepo(id),
-            },
-            gpu,
-          ),
-      );
+    return (
+      recommendedIds
+        .filter((id) => normalizeForSearch(id).includes(q))
+        .filter((id) =>
+          matchesFormatFilter(id, isKnownGgufRepo(id), formatFilter),
+        )
+        // Curated defaults obey the fit toggle like the live HF rows, else large
+        // defaults resurface in search results with the filter on.
+        .filter(
+          (id) =>
+            !fitOnDeviceOnly ||
+            downloadedSet.has(id.toLowerCase()) ||
+            hfModelFitsDevice(
+              {
+                id,
+                totalParams: recommendedParamCountById.get(id),
+                isGguf: isKnownGgufRepo(id),
+              },
+              gpu,
+            ),
+        )
+    );
   }, [
     showHfSection,
     debouncedQuery,
@@ -2434,27 +2273,30 @@ export function HubModelPicker({
   const hfIds = useMemo(() => {
     // Only the Unsloth tab searches the HF listing, and only Unsloth models.
     if (!showHfSection || section !== "recommended") return [];
-    return results
-      .filter(isChatSupported)
-      .filter(
-        (r) =>
-          !fitOnDeviceOnly ||
-          downloadedSet.has(r.id.toLowerCase()) ||
-          hfModelFitsDevice(r, gpu),
-      )
-      .map((result) => result.id)
-      .filter((id) => !isHiddenModelId(id))
-      .filter((id) => id.toLowerCase().startsWith("unsloth/"))
-      .filter((id) => !recommendedSet.has(id))
-      // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
-      // on Mac (matches the empty Recommended view so search stays consistent).
-      .filter(
-        (id) => !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
-      )
-      .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id))
-      .filter((id) =>
-        matchesFormatFilter(id, isKnownGgufRepo(id), formatFilter),
-      );
+    return (
+      results
+        .filter(isChatSupported)
+        .filter(
+          (r) =>
+            !fitOnDeviceOnly ||
+            downloadedSet.has(r.id.toLowerCase()) ||
+            hfModelFitsDevice(r, gpu),
+        )
+        .map((result) => result.id)
+        .filter((id) => !isHiddenModelId(id))
+        .filter((id) => id.toLowerCase().startsWith("unsloth/"))
+        .filter((id) => !recommendedSet.has(id))
+        // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
+        // on Mac (matches the empty Recommended view so search stays consistent).
+        .filter(
+          (id) =>
+            !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
+        )
+        .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id))
+        .filter((id) =>
+          matchesFormatFilter(id, isKnownGgufRepo(id), formatFilter),
+        )
+    );
   }, [
     recommendedSet,
     results,
@@ -2478,16 +2320,13 @@ export function HubModelPicker({
       section === "downloaded" &&
       cachedReady &&
       !pinnedCollapsed &&
-      (pinnedQuants.length > 0 || pinnedCachedModelRows.length > 0)
+      pinnedRows.length > 0
     ) {
       keys.push(
-        ...pinnedQuants.map((entry) =>
-          makeModelOptionKey("pinned-quant", pinKey(entry.repoId, entry.quant)),
-        ),
-      );
-      keys.push(
-        ...pinnedCachedModelRows.map((model) =>
-          makeModelOptionKey("downloaded-model", model.repo_id),
+        ...pinnedRows.map((row) =>
+          row.entry
+            ? makeModelOptionKey("pinned-quant", row.key)
+            : makeModelOptionKey("downloaded-model", row.model.repo_id),
         ),
       );
     }
@@ -2542,12 +2381,12 @@ export function HubModelPicker({
     }
 
     // Fine-tuned models sit below downloaded, above custom folders.
-    if (section === "downloaded" && cachedReady && !fineTunedCollapsed) {
+    if (section === "downloaded" && !fineTunedCollapsed) {
       keys.push(...fineTunedRows.map((m) => makeModelOptionKey("lora", m.id)));
     }
 
     // Custom folders sit right below the downloaded models on On Device.
-    if (section === "downloaded" && cachedReady && !customFoldersCollapsed) {
+    if (section === "downloaded" && !customFoldersCollapsed) {
       keys.push(
         ...sortedCustomFolderModels.map((model) =>
           makeModelOptionKey("custom-folder", model.id),
@@ -2555,7 +2394,7 @@ export function HubModelPicker({
       );
     }
 
-    if (section === "downloaded" && cachedReady && !lmStudioCollapsed) {
+    if (section === "downloaded" && !lmStudioCollapsed) {
       keys.push(
         ...sortedLmStudio.map((model) =>
           makeModelOptionKey("lm-studio", model.id),
@@ -2563,7 +2402,7 @@ export function HubModelPicker({
       );
     }
 
-    if (section === "downloaded" && cachedReady && !localDirCollapsed) {
+    if (section === "downloaded" && !localDirCollapsed) {
       keys.push(
         ...sortedLocalDir.map((model) =>
           makeModelOptionKey("local-dir", model.id),
@@ -2583,8 +2422,7 @@ export function HubModelPicker({
     chatOnly,
     sortedCustomFolderModels,
     customFoldersCollapsed,
-    pinnedQuants,
-    pinnedCachedModelRows,
+    pinnedRows,
     pinnedCollapsed,
     downloadedCollapsed,
     fineTunedRows,
@@ -2705,9 +2543,8 @@ export function HubModelPicker({
   }, [scrollRef, updateListFades]);
 
   // Sentinel + IntersectionObserver for recommended infinite scroll. Re-running
-  // on each loaded page (results length) re-attaches the observer so a heavily
-  // filtered list keeps paging until the viewport fills or the listing ends;
-  // fetchMore is a no-op while a page is in flight. Callback ref tracks mount.
+  // per loaded page re-attaches the observer so a heavily filtered list keeps
+  // paging until the viewport fills; fetchMore is a no-op while a page is in flight.
   const [recommendedSentinel, setRecommendedSentinel] =
     useState<HTMLDivElement | null>(null);
   const recommendedSentinelRef = useCallback((node: HTMLDivElement | null) => {
@@ -2756,8 +2593,8 @@ export function HubModelPicker({
   const showDownloaded = section === "downloaded";
   const showCustom = section === "downloaded";
   const showRecommendedSection = !showHfSection && section === "recommended";
-  const onDeviceCacheLoading = showDownloaded && !cachedReady;
   const downloadedEmpty =
+    pinnedRows.length === 0 &&
     visibleCachedGguf.length === 0 &&
     visibleCachedModelRows.length === 0 &&
     sortedLmStudio.length === 0 &&
@@ -2766,25 +2603,21 @@ export function HubModelPicker({
     // non-empty Fine-tuned section.
     fineTunedRows.length === 0;
 
-  // Sort dropdown shown inline to the right of the section toggle. Options
-  // depend on the tab and stay visible while searching so results can be
-  // sorted. Fixed width matching the Search Hub button so it and the format
-  // dropdown always line up; text-xs matches that button too. The trigger label
-  // clips (no ellipsis) when long; the open menu expands to show it in full.
+  // Sort dropdown inline right of the section toggle; options depend on the tab
+  // and stay visible while searching. Fixed width matches the Search Hub button
+  // so it and the format dropdown line up. Trigger label clips; the menu shows full.
   const sortTriggerClassName =
     "w-[110px] shrink-0 justify-between pr-2.5 !border-0 text-xs [&>span]:!text-clip";
-  // Tighter menu like the Projects activity Select: less left/top padding and
-  // text-xs to match the trigger. Keep the option's right padding so the
-  // selected-item checkmark never overlaps the label.
+  // Tighter menu (less padding, text-xs) matching the trigger. Keep the option's
+  // right padding so the selected-item checkmark never overlaps the label.
   const sortMenuContentClassName =
     "!p-1 !rounded-[14px] [&_[role=option]]:!pl-2 [&_[role=option]]:!py-1.5 [&_[role=option]]:!text-xs [&_[role=option]]:!rounded-[10px]";
-  // Device-fit toggle lives inside the sort menu (shared with the Hub page).
-  // The whole row is the click target (a button): a Checkbox renders as a
-  // <button>, and label-click forwarding to a button is unreliable, so the row
-  // owns the toggle and the Checkbox is presentational (pointer-events-none).
+  // Device-fit toggle inside the sort menu (shared with the Hub page). The whole
+  // row is the button: a Checkbox renders as a <button> and label-click forwarding
+  // to it is unreliable, so the row owns the toggle and the Checkbox is presentational.
   const fitOnDeviceFooter = (
     <Tooltip>
-      <TooltipTrigger asChild>
+      <TooltipTrigger asChild={true}>
         <button
           type="button"
           role="checkbox"
@@ -2795,7 +2628,7 @@ export function HubModelPicker({
           <Checkbox
             checked={fitOnDeviceOnly}
             tabIndex={-1}
-            aria-hidden
+            aria-hidden={true}
             className="pointer-events-none size-3.5 rounded-full [&_svg]:!size-2.5"
           />
           Only show models that fit
@@ -2807,6 +2640,19 @@ export function HubModelPicker({
       </TooltipContent>
     </Tooltip>
   );
+  // Sort icon + selected label inside the trigger pill.
+  const sortTriggerContent = (label: ReactNode) => (
+    <span className="flex items-center gap-1">
+      <HugeiconsIcon
+        icon={ArrowUpDownIcon}
+        strokeWidth={1.75}
+        className="size-3.5 shrink-0 text-muted-foreground"
+      />
+      <span className="truncate">{label}</span>
+    </span>
+  );
+  // On Device / Custom rows are already on disk, so the device-fit filter
+  // only applies to the Unsloth listing.
   const sectionSortDropdown =
     section === "recommended" ? (
       <HubOptionMenu
@@ -2817,6 +2663,10 @@ export function HubModelPicker({
         align="end"
         className={sortTriggerClassName}
         contentClassName={sortMenuContentClassName}
+        triggerContent={sortTriggerContent(
+          RECOMMENDED_SORT_OPTIONS.find((o) => o.value === recommendedSort)
+            ?.label ?? recommendedSort,
+        )}
         footer={fitOnDeviceFooter}
       />
     ) : section === "downloaded" ? (
@@ -2828,7 +2678,10 @@ export function HubModelPicker({
         align="end"
         className={sortTriggerClassName}
         contentClassName={sortMenuContentClassName}
-        footer={fitOnDeviceFooter}
+        triggerContent={sortTriggerContent(
+          LOCAL_SORT_OPTIONS.find((o) => o.value === downloadedSort)?.label ??
+            downloadedSort,
+        )}
       />
     ) : (
       <HubOptionMenu
@@ -2839,7 +2692,10 @@ export function HubModelPicker({
         align="end"
         className={sortTriggerClassName}
         contentClassName={sortMenuContentClassName}
-        footer={fitOnDeviceFooter}
+        triggerContent={sortTriggerContent(
+          LOCAL_SORT_OPTIONS.find((o) => o.value === customSort)?.label ??
+            customSort,
+        )}
       />
     );
 
@@ -2895,60 +2751,6 @@ export function HubModelPicker({
       selected && "bg-[#ececec] dark:bg-[var(--sidebar-accent)]",
     );
 
-  // Pin toggle at a row's right edge: hidden until the row is hovered (or the
-  // button is focused), always visible while pinned so pinned rows read as such.
-  // `small` matches the compact quant-row action sizing; it also skips the
-  // hide-until-hover classes since small pins render inside a hover-gated group.
-  const renderPinAction = (
-    repoId: string,
-    quant?: string,
-    opts?: { className?: string; small?: boolean },
-  ) => {
-    const pinned = pinnedSet.has(pinKey(repoId, quant));
-    const target = quant ? `${repoId} ${quant}` : repoId;
-    return (
-      <Tooltip delayDuration={0}>
-        <TooltipTrigger asChild={true}>
-          <button
-            type="button"
-            onClick={(e) => {
-              e.stopPropagation();
-              togglePinned(repoId, quant);
-            }}
-            aria-label={pinned ? `Unpin ${target}` : `Pin ${target}`}
-            aria-pressed={pinned}
-            className={cn(
-              "shrink-0 rounded-md transition-colors hover:bg-black/5 dark:hover:bg-white/10",
-              opts?.small ? "p-1" : "p-1.5",
-              pinned
-                ? "text-foreground/80 hover:text-foreground"
-                : "text-muted-foreground/60 hover:text-foreground",
-              !pinned &&
-                !opts?.small &&
-                "opacity-0 focus-visible:opacity-100 group-hover:opacity-100 group-focus-within:opacity-100",
-              opts?.className,
-            )}
-          >
-            <HugeiconsIcon
-              icon={pinned ? PinOffIcon : PinIcon}
-              strokeWidth={1.75}
-              className={opts?.small ? "size-3" : "size-3.5"}
-            />
-          </button>
-        </TooltipTrigger>
-        <TooltipContent side="bottom" className="tooltip-compact">
-          {pinned
-            ? quant
-              ? "Unpin quant"
-              : "Unpin model"
-            : quant
-              ? "Pin quant to the top"
-              : "Pin model to the top"}
-        </TooltipContent>
-      </Tooltip>
-    );
-  };
-
   // A pinned quant: repo name with the quant as a grey chip. One click loads
   // that quant directly, no expansion needed.
   const renderPinnedQuantRow = (entry: { repoId: string; quant: string }) => {
@@ -2957,16 +2759,14 @@ export function HubModelPicker({
       pinKey(entry.repoId, entry.quant),
     );
     const { owner, name } = splitRepoLabel(entry.repoId);
-    const isSelected = value === entry.repoId && activeGgufVariant === entry.quant;
+    const isSelected =
+      value === entry.repoId && activeGgufVariant === entry.quant;
     const isLoaded =
       modelIdsMatchForPicker(loadedModelId, entry.repoId) &&
       !ggufVariantsMatchForPicker(activeGgufVariant, null) &&
       ggufVariantsMatchForPicker(activeGgufVariant, entry.quant);
     return (
-      <div
-        key={optionKey}
-        className={downloadedRowShellClassName(isSelected)}
-      >
+      <div key={optionKey} className={downloadedRowShellClassName(isSelected)}>
         <button
           type="button"
           {...hubModelList.getOptionProps(optionKey, isSelected)}
@@ -2986,14 +2786,14 @@ export function HubModelPicker({
         >
           <span className="flex min-w-0 items-baseline">
             {owner ? (
-              <span className="inline-flex min-w-0 max-w-[45%] shrink items-baseline text-[13px] text-muted-foreground/90">
+              <span className="inline-flex min-w-0 max-w-[45%] shrink items-baseline text-ui-13 text-muted-foreground/90">
                 <span className="truncate">{owner}</span>
                 <span className="shrink-0 text-muted-foreground/45">/</span>
               </span>
             ) : null}
             <span className="min-w-0 truncate">{name}</span>
           </span>
-          <span className="shrink-0 rounded-md bg-black/[0.06] px-1.5 py-px font-mono text-[10px] text-muted-foreground dark:bg-white/[0.1]">
+          <span className="shrink-0 rounded-md bg-black/[0.06] px-1.5 py-px font-mono text-ui-10 text-muted-foreground dark:bg-white/[0.1]">
             {entry.quant}
           </span>
           {isLoaded && (
@@ -3005,34 +2805,54 @@ export function HubModelPicker({
             />
           )}
         </button>
-        <span className="mr-1 flex shrink-0 items-center gap-0.5 opacity-0 transition-opacity focus-within:opacity-100 group-hover:opacity-100 group-focus-within:opacity-100">
-          {renderPinAction(entry.repoId, entry.quant, { small: true })}
-          <ModelLoadSettingsAction
-            ariaLabel={`Inference settings for ${entry.repoId} ${entry.quant}`}
-            repoId={entry.repoId}
-            quant={entry.quant}
-          />
-          <ModelDeleteAction
-            ariaLabel={`Delete ${entry.repoId} ${entry.quant}`}
-            title="Delete cached model?"
-            description={
-              <>
-                This will remove{" "}
-                <span className="font-medium text-foreground">
-                  {entry.repoId} ({entry.quant})
-                </span>{" "}
-                from disk. You can re-download it later.
-              </>
-            }
-            successMessage={`Deleted ${entry.repoId} ${entry.quant}`}
-            buttonClassName="p-1"
+        <span className="mr-1 flex shrink-0 items-center opacity-0 transition-opacity focus-within:opacity-100 group-hover:opacity-100 group-focus-within:opacity-100">
+          {onConfigure && (
+            <ModelLoadSettingsAction
+              ariaLabel={`Inference settings for ${entry.repoId} ${entry.quant}`}
+              onConfigure={() =>
+                onConfigure(entry.repoId, {
+                  source: "hub",
+                  isLora: false,
+                  ggufVariant: entry.quant,
+                  isDownloaded: true,
+                  isGguf: true,
+                })
+              }
+            />
+          )}
+          <ModelRowMenu
+            ariaLabel={`More options for ${entry.repoId} ${entry.quant}`}
             iconClassName="size-3"
-            disabled={deleteDisabled}
-            onConfirm={async () => {
-              await deleteCachedModel(entry.repoId, entry.quant);
-              refreshCachedLists();
-              // The file is gone, so drop its pin too.
-              togglePinned(entry.repoId, entry.quant);
+            cachePath={{ repoId: entry.repoId, variant: entry.quant }}
+            pin={{
+              pinned: true,
+              pinLabel: "Pin to top",
+              unpinLabel: "Unpin",
+              onToggle: () => togglePinned(entry.repoId, entry.quant),
+            }}
+            del={{
+              title: "Delete cached model?",
+              description: (
+                <>
+                  This will remove{" "}
+                  <span className="font-medium text-foreground">
+                    {entry.repoId} ({entry.quant})
+                  </span>{" "}
+                  from disk. You can re-download it later.
+                </>
+              ),
+              successMessage: `Deleted ${entry.repoId} ${entry.quant}`,
+              disabled: deleteDisabled,
+              onConfirm: async () => {
+                await deleteCachedModel(
+                  entry.repoId,
+                  entry.quant,
+                  hfToken || undefined,
+                );
+                refreshCachedLists();
+                // The file is gone, so drop its pin too.
+                togglePinned(entry.repoId, entry.quant);
+              },
             }}
           />
         </span>
@@ -3080,6 +2900,7 @@ export function HubModelPicker({
             allowPin={true}
             onHasVision={(v) => reportVision(c.repo_id, v)}
             onSelect={onSelect}
+            onConfigure={onConfigure}
             hfToken={hfToken || undefined}
             parentOptionKey={optionKey}
             onNavigatePastStart={() => hubModelList.focusOption(optionKey)}
@@ -3089,13 +2910,17 @@ export function HubModelPicker({
             variantActions={{
               onUpdate: (quant, expectedBytes) =>
                 updateGgufVariant(c.repo_id, quant, expectedBytes),
-              // Can't update the model that's live in memory under itself.
               updateDisabled: loadedModelId === c.repo_id,
               onDelete: async (quant) => {
-                await deleteCachedModel(c.repo_id, quant);
+                await deleteCachedModel(
+                  c.repo_id,
+                  quant,
+                  hfToken || undefined,
+                  c.cache_path || undefined,
+                );
+                prunePinnedQuantValidation(c.repo_id, quant);
                 refreshCachedLists();
               },
-              deleteDisabled,
             }}
           />
         )}
@@ -3108,10 +2933,7 @@ export function HubModelPicker({
     const optionKey = makeModelOptionKey("downloaded-model", c.repo_id);
     const isSelected = value === c.repo_id;
     return (
-      <div
-        key={c.repo_id}
-        className={downloadedRowShellClassName(isSelected)}
-      >
+      <div key={c.repo_id} className={downloadedRowShellClassName(isSelected)}>
         <div className="min-w-0 flex-1">
           <ModelRow
             label={c.repo_id}
@@ -3126,10 +2948,7 @@ export function HubModelPicker({
               c.repo_id,
               "none",
             )}
-            optionProps={hubModelList.getOptionProps(
-              optionKey,
-              isSelected,
-            )}
+            optionProps={hubModelList.getOptionProps(optionKey, isSelected)}
             onClick={() =>
               onSelect(c.repo_id, {
                 source: "hub",
@@ -3141,27 +2960,53 @@ export function HubModelPicker({
             className={downloadedRowButtonClassName}
           />
         </div>
-        {renderPinAction(c.repo_id)}
-        <ModelDeleteAction
-          ariaLabel={`Delete ${c.repo_id}`}
-          title="Delete cached model?"
-          description={
-            <>
-              This will remove{" "}
-              <span className="font-medium text-foreground">{c.repo_id}</span>{" "}
-              from disk. You can re-download it later.
-            </>
-          }
-          successMessage={`Deleted ${c.repo_id}`}
-          buttonClassName="mr-1"
-          disabled={deleteDisabled}
-          onConfirm={async () => {
-            await deleteCachedModel(c.repo_id);
-            if (pinnedSet.has(pinKey(c.repo_id))) {
-              togglePinned(c.repo_id);
+        {onConfigure && (
+          <ModelLoadSettingsAction
+            ariaLabel={`Inference settings for ${c.repo_id}`}
+            onConfigure={() =>
+              onConfigure(c.repo_id, {
+                source: "hub",
+                isLora: false,
+                isDownloaded: true,
+                isGguf: false,
+              })
             }
+          />
+        )}
+        <ModelRowMenu
+          ariaLabel={`More options for ${c.repo_id}`}
+          buttonClassName="mr-1"
+          cachePath={{ repoId: c.repo_id }}
+          pin={{
+            pinned: pinnedSet.has(pinKey(c.repo_id)),
+            pinLabel: "Pin to top",
+            unpinLabel: "Unpin",
+            onToggle: () => togglePinned(c.repo_id),
+          }}
+          del={{
+            title: "Delete cached model?",
+            description: (
+              <>
+                This will remove{" "}
+                <span className="font-medium text-foreground">{c.repo_id}</span>{" "}
+                from disk. You can re-download it later.
+              </>
+            ),
+            successMessage: `Deleted ${c.repo_id}`,
+            disabled: deleteDisabled,
+            onConfirm: async () => {
+              await deleteCachedModel(
+                c.repo_id,
+                undefined,
+                hfToken || undefined,
+                c.cache_path || undefined,
+              );
+              if (pinnedSet.has(pinKey(c.repo_id))) {
+                togglePinned(c.repo_id);
+              }
+            },
+            onDeleted: refreshCachedLists,
           }}
-          onDeleted={refreshCachedLists}
         />
       </div>
     );
@@ -3170,214 +3015,237 @@ export function HubModelPicker({
   return (
     <>
       <div className="relative space-y-2">
-      {/* A small right inset shortens the search bar so Search Hub lands on the
+        {/* A small right inset shortens the search bar so Search Hub lands on the
           last dropdown's right edge (none on the wider Connected box). */}
-      <div
-        className={cn(
-          "flex items-center gap-2 pb-1",
-          hasConnected ? "pr-0" : "pr-2",
-        )}
-      >
-        <div className="relative flex-1">
-          <HugeiconsIcon
-            icon={Search01Icon}
-            className="pointer-events-none absolute left-2.5 top-2.5 size-4 text-muted-foreground"
-          />
-          <Input
-            value={query}
-            onChange={(event) => setQuery(event.target.value)}
-            placeholder={
-              section === "downloaded"
-                ? "Search local models"
-                : "Search Unsloth models"
-            }
-            data-model-picker-search-input={true}
-            className="field-soft h-9 border-0 pl-8 pr-8"
-          />
-          {isLoading && (
-            <Spinner className="pointer-events-none absolute right-2.5 top-2.5 size-4 text-muted-foreground" />
-          )}
-        </div>
-        {onBrowseHub ? (
-          <Tooltip>
-            <TooltipTrigger asChild>
-              <button
-                type="button"
-                onClick={onBrowseHub}
-                aria-label="Search more models on the Hub"
-                className="hub-tab-toggle-pill flex h-9 w-[110px] shrink-0 items-center justify-center gap-[5px] rounded-full border-0 text-xs text-foreground transition-colors"
-              >
-                <HugeiconsIcon icon={DashboardCircleIcon} className="size-4" />
-                Search Hub
-              </button>
-            </TooltipTrigger>
-            <TooltipContent>Search all models</TooltipContent>
-          </Tooltip>
-        ) : null}
-      </div>
-
-      {/* Section tabs then the format and sort dropdowns, packed left with one
-          uniform gap between every control. The box is sized so the last
-          dropdown still lands on Search Hub's edge. Dropdowns hide on Connected. */}
-      <div className="flex items-center gap-2">
-        {sectionToggle}
-        {showConnected ? null : (
-          <div className="flex items-center gap-2">
-            <HubOptionMenu
-              value={formatFilter}
-              options={FORMAT_FILTER_OPTIONS}
-              onValueChange={setFormatFilter}
-              ariaLabel="Filter by format"
-              align="end"
-              className={sortTriggerClassName}
-              contentClassName={sortMenuContentClassName}
-            />
-            {sectionSortDropdown}
-          </div>
-        )}
-      </div>
-
-      <div
-        ref={scrollRef}
-        onScroll={(e) => updateListFades(e.currentTarget)}
-        className={cn(
-          // List sits within the menu padding so left and right gaps match.
-          // Height tracks the content up to the cap, so short lists do not
-          // leave white space. scroll-py + symmetric px keep the focus ring off
-          // the overflow clip edges during keyboard nav.
-          "model-list-scroll max-h-[335px] overflow-y-auto scroll-py-1.5 px-0.5 mr-1",
-          listScrolled && "is-scrolled",
-          listMoreBelow && "is-bottom-faded",
-        )}
-        {...hubModelList.listboxProps}
-      >
-        {/* Clear space for the floating Eject pill when scrolled to the end, so
-            its gap above the last row matches its gap below (applies to every
-            section, including Recommended). */}
         <div
           className={cn(
-            "pr-0",
-            // On Device pulls the heading block tight to the controls; Recommended
-            // keeps a little more top room above its first row.
-            showDownloaded ? "pt-0" : "pt-[4px]",
-            onEject ? "pb-[60px]" : "pb-4",
+            "flex items-center gap-2 pb-1",
+            hasConnected ? "pr-0" : "pr-2",
           )}
         >
-          {showConnected ? (
-            connectedGroups.length === 0 ? (
-              <div className="px-2.5 py-2 text-xs leading-relaxed text-muted-foreground">
-                {externalModels.length === 0
-                  ? "No models from your connections. Set up in Settings then Connections."
-                  : "No models match your search."}
-              </div>
+          <div className="relative flex-1">
+            <HugeiconsIcon
+              icon={Search01Icon}
+              className="pointer-events-none absolute left-2.5 top-2.5 size-4 text-muted-foreground"
+            />
+            <Input
+              value={query}
+              onChange={(event) => setQuery(event.target.value)}
+              placeholder={
+                section === "downloaded"
+                  ? "Search local models"
+                  : "Search Unsloth models"
+              }
+              data-model-picker-search-input={true}
+              className="field-soft h-9 border-0 pl-8 pr-8"
+            />
+            {isLoading && (
+              <Spinner className="pointer-events-none absolute right-2.5 top-2.5 size-4 text-muted-foreground" />
+            )}
+          </div>
+          {onBrowseHub ? (
+            <Tooltip>
+              <TooltipTrigger asChild={true}>
+                <button
+                  type="button"
+                  onClick={onBrowseHub}
+                  aria-label="Search more models on the Hub"
+                  className="hub-tab-toggle-pill flex h-9 w-[110px] shrink-0 items-center justify-center gap-[5px] rounded-full border-0 text-xs text-foreground transition-colors"
+                >
+                  <HugeiconsIcon
+                    icon={DashboardCircleIcon}
+                    className="size-4"
+                  />
+                  Search Hub
+                </button>
+              </TooltipTrigger>
+              <TooltipContent>Search all models</TooltipContent>
+            </Tooltip>
+          ) : null}
+        </div>
+
+        {/* Section tabs then the format and sort dropdowns, packed left with one
+          uniform gap between every control. The box is sized so the last
+          dropdown still lands on Search Hub's edge. Dropdowns hide on Connected. */}
+        <div className="flex items-center gap-2">
+          {sectionToggle}
+          {showConnected ? null : (
+            <div className="flex items-center gap-2">
+              <HubOptionMenu
+                value={formatFilter}
+                options={FORMAT_FILTER_OPTIONS}
+                onValueChange={setFormatFilter}
+                ariaLabel="Filter by format"
+                align="end"
+                className={sortTriggerClassName}
+                contentClassName={sortMenuContentClassName}
+              />
+              {sectionSortDropdown}
+            </div>
+          )}
+        </div>
+
+        <div
+          ref={scrollRef}
+          onScroll={(e) => updateListFades(e.currentTarget)}
+          className={cn(
+            // List sits within the menu padding so gaps match; height tracks content
+            // up to the cap. scroll-py + symmetric px keep the focus ring off the
+            // overflow clip edges during keyboard nav.
+            "model-list-scroll max-h-[335px] overflow-y-auto scroll-py-1.5 px-0.5 mr-1",
+            listScrolled && "is-scrolled",
+            listMoreBelow && "is-bottom-faded",
+          )}
+          {...hubModelList.listboxProps}
+        >
+          <div
+            className={cn(
+              "pr-0",
+              // On Device pulls the heading block tight to the controls; Recommended
+              // keeps a little more top room above its first row.
+              showDownloaded ? "pt-0" : "pt-[4px]",
+              onEject ? "pb-[60px]" : "pb-4",
+            )}
+          >
+            {showConnected ? (
+              connectedGroups.length === 0 ? (
+                <div className="px-2.5 py-2 text-xs leading-relaxed text-muted-foreground">
+                  {externalModels.length === 0
+                    ? "No models from your connections. Set up in Settings then Connections."
+                    : "No models match your search."}
+                </div>
+              ) : (
+                connectedGroups.map((group) => (
+                  <div key={group.providerId}>
+                    <div className="flex items-center gap-2 px-2.5 py-1.5 text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
+                      <ApiProviderLogo
+                        providerType={group.providerType}
+                        className="size-3.5"
+                        title={group.providerName}
+                      />
+                      <span className="min-w-0 truncate">
+                        {group.providerName}
+                      </span>
+                    </div>
+                    {group.models.map((model) => (
+                      <button
+                        key={model.id}
+                        type="button"
+                        onClick={() =>
+                          onSelect(model.id, {
+                            source: "external",
+                            isLora: false,
+                          })
+                        }
+                        className={cn(
+                          "flex w-full items-center rounded-md px-2.5 py-1.5 text-left text-sm transition-colors hover:bg-[#ececec] dark:hover:bg-[var(--sidebar-accent)]",
+                          value === model.id &&
+                            "bg-[#ececec] dark:bg-[var(--sidebar-accent)]",
+                        )}
+                      >
+                        <span className="min-w-0 truncate">{model.name}</span>
+                      </button>
+                    ))}
+                  </div>
+                ))
+              )
             ) : (
-              connectedGroups.map((group) => (
-                <div key={group.providerId}>
-                  <div className="flex items-center gap-2 px-2.5 py-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
-                    <ApiProviderLogo
-                      providerType={group.providerType}
-                      className="size-3.5"
-                      title={group.providerName}
-                    />
-                    <span className="min-w-0 truncate">
-                      {group.providerName}
+              <>
+                {/* First-load spinner only when nothing cached is shown yet. */}
+                {showDownloaded &&
+                !cachedReady &&
+                !showHfSection &&
+                downloadedEmpty ? (
+                  <div className="flex items-center gap-2 px-5 py-3">
+                    <Spinner className="size-3 text-muted-foreground" />
+                    <span className="text-xs text-muted-foreground">
+                      Loading models…
                     </span>
                   </div>
-                  {group.models.map((model) => (
-                    <button
-                      key={model.id}
-                      type="button"
-                      onClick={() =>
-                        onSelect(model.id, {
-                          source: "external",
-                          isLora: false,
-                        })
-                      }
-                      className={cn(
-                        "flex w-full items-center rounded-md px-2.5 py-1.5 text-left text-sm transition-colors hover:bg-[#ececec] dark:hover:bg-[var(--sidebar-accent)]",
-                        value === model.id &&
-                          "bg-[#ececec] dark:bg-[var(--sidebar-accent)]",
-                      )}
-                    >
-                      <span className="min-w-0 truncate">{model.name}</span>
-                    </button>
-                  ))}
-                </div>
-              ))
-            )
-          ) : (
-            <>
-              {/* First-load spinner while downloaded/local scans are resolving. */}
-              {onDeviceCacheLoading ? (
-                <div className="flex items-center gap-2 px-5 py-3">
-                  <Spinner className="size-3 text-muted-foreground" />
-                  <span className="text-xs text-muted-foreground">
-                    Loading models…
-                  </span>
-                </div>
-              ) : null}
+                ) : null}
 
-              {/* Empty On Device: a search miss vs nothing downloaded yet. Hidden
+                {/* Empty On Device: a search miss vs nothing downloaded yet. Hidden
               when custom folders below still have matches. */}
-              {showDownloaded &&
-              cachedReady &&
-              downloadedEmpty &&
-              sortedCustomFolderModels.length === 0 ? (
-                <div className="px-2.5 py-2 text-xs text-muted-foreground">
-                  {showHfSection
-                    ? "No matching models on device."
-                    : formatFilter === "all"
-                      ? "No downloaded models yet. Search above or pick Recommended."
-                      : `No downloaded ${FORMAT_FILTER_LABELS[formatFilter]} models yet.`}
-                </div>
-              ) : null}
+                {showDownloaded &&
+                cachedReady &&
+                downloadedEmpty &&
+                sortedCustomFolderModels.length === 0 ? (
+                  <div className="px-2.5 py-2 text-xs text-muted-foreground">
+                    {showHfSection
+                      ? "No matching models on device."
+                      : formatFilter === "all"
+                        ? "No downloaded models yet. Search above or pick Recommended."
+                        : `No downloaded ${FORMAT_FILTER_LABELS[formatFilter]} models yet.`}
+                  </div>
+                ) : null}
 
-              {/* Pinned quants and models sit above the Unsloth heading so
+                {/* Pinned quants and models sit above the Unsloth heading so
               favorites are always first. Filtered by the query like the
               sections below. */}
-              {showDownloaded &&
-              (pinnedQuants.length > 0 ||
-                pinnedCachedModelRows.length > 0) ? (
-                <>
-                  <ListLabel
-                    icon={<HugeiconsIcon icon={PinIcon} className="size-3.5" />}
-                    collapsed={pinnedCollapsed}
-                    onToggle={() => setPinnedCollapsed((v) => !v)}
-                  >
-                    Pinned
-                  </ListLabel>
-                  {!pinnedCollapsed && pinnedQuants.map(renderPinnedQuantRow)}
-                  {!pinnedCollapsed &&
-                    pinnedCachedModelRows.map(renderDownloadedModelRow)}
-                </>
-              ) : null}
+                {showDownloaded && pinnedRows.length > 0 ? (
+                  <>
+                    <ListLabel
+                      icon={
+                        <HugeiconsIcon icon={PinIcon} className="size-3.5" />
+                      }
+                      collapsed={pinnedCollapsed}
+                      onToggle={() => setPinnedCollapsed((v) => !v)}
+                    >
+                      Pinned
+                    </ListLabel>
+                    {!pinnedCollapsed &&
+                      pinnedRows.map((row) =>
+                        row.entry
+                          ? renderPinnedQuantRow(row.entry)
+                          : renderDownloadedModelRow(row.model),
+                      )}
+                  </>
+                ) : null}
 
-              {/* Downloaded (Unsloth) stays visible (filtered) while searching. */}
-              {showDownloaded &&
-              cachedReady &&
-              (unslothCachedGguf.length > 0 ||
-                unslothCachedModelRows.length > 0) ? (
-                <>
-                  <ListLabel
-                    divider={
-                      pinnedQuants.length > 0 ||
-                      pinnedCachedModelRows.length > 0
-                    }
-                    collapsed={downloadedCollapsed}
-                    onToggle={() => setDownloadedCollapsed((v) => !v)}
-                    action={
-                      <>
-                        {hasOtherModels ? (
+                {/* Downloaded (Unsloth) stays visible (filtered) while searching. */}
+                {showDownloaded &&
+                (unslothCachedGguf.length > 0 ||
+                  unslothCachedModelRows.length > 0) ? (
+                  <>
+                    <ListLabel
+                      divider={pinnedRows.length > 0}
+                      collapsed={downloadedCollapsed}
+                      onToggle={() => setDownloadedCollapsed((v) => !v)}
+                      action={
+                        <>
+                          {hasOtherModels ? (
+                            <Tooltip delayDuration={0}>
+                              <TooltipTrigger asChild={true}>
+                                <button
+                                  type="button"
+                                  onClick={scrollToOtherModels}
+                                  aria-label="Go to other models"
+                                  className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
+                                >
+                                  <HugeiconsIcon
+                                    icon={Flag01Icon}
+                                    className="size-3"
+                                  />
+                                </button>
+                              </TooltipTrigger>
+                              <TooltipContent
+                                side="bottom"
+                                className="tooltip-compact"
+                              >
+                                Other non-Unsloth models
+                              </TooltipContent>
+                            </Tooltip>
+                          ) : null}
                           <Tooltip delayDuration={0}>
                             <TooltipTrigger asChild={true}>
                               <button
                                 type="button"
-                                onClick={scrollToOtherModels}
-                                aria-label="Go to other models"
+                                onClick={scrollToFineTuned}
+                                aria-label="Go to fine-tuned models"
                                 className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
                               >
                                 <HugeiconsIcon
-                                  icon={Flag01Icon}
+                                  icon={TrainIcon}
                                   className="size-3"
                                 />
                               </button>
@@ -3386,845 +3254,809 @@ export function HubModelPicker({
                               side="bottom"
                               className="tooltip-compact"
                             >
-                              Other non-Unsloth models
+                              Go to fine-tuned models
                             </TooltipContent>
                           </Tooltip>
-                        ) : null}
-                        <Tooltip delayDuration={0}>
-                          <TooltipTrigger asChild={true}>
-                            <button
-                              type="button"
-                              onClick={scrollToFineTuned}
-                              aria-label="Go to fine-tuned models"
-                              className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
+                          <Tooltip delayDuration={0}>
+                            <TooltipTrigger asChild={true}>
+                              <button
+                                type="button"
+                                onClick={scrollToCustomFolders}
+                                aria-label="Go to custom folders"
+                                className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
+                              >
+                                <HugeiconsIcon
+                                  icon={Folder02Icon}
+                                  className="size-3"
+                                />
+                              </button>
+                            </TooltipTrigger>
+                            <TooltipContent
+                              side="bottom"
+                              className="tooltip-compact"
                             >
-                              <HugeiconsIcon
-                                icon={TrainIcon}
-                                className="size-3"
-                              />
-                            </button>
-                          </TooltipTrigger>
-                          <TooltipContent
-                            side="bottom"
-                            className="tooltip-compact"
-                          >
-                            Go to fine-tuned models
-                          </TooltipContent>
-                        </Tooltip>
-                        <Tooltip delayDuration={0}>
-                          <TooltipTrigger asChild={true}>
-                            <button
-                              type="button"
-                              onClick={scrollToCustomFolders}
-                              aria-label="Go to custom folders"
-                              className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
-                            >
-                              <HugeiconsIcon
-                                icon={Folder02Icon}
-                                className="size-3"
-                              />
-                            </button>
-                          </TooltipTrigger>
-                          <TooltipContent
-                            side="bottom"
-                            className="tooltip-compact"
-                          >
-                            Go to custom folders
-                          </TooltipContent>
-                        </Tooltip>
-                      </>
-                    }
-                  >
-                    {/* When other providers (LM Studio/Ollama) also show here, name
-                    this group "Unsloth" so the two are easy to tell apart. */}
-                    {sortedLmStudio.length > 0 ? "Unsloth" : "Downloaded"}
-                  </ListLabel>
-                  {!downloadedCollapsed &&
-                    unslothCachedGguf.map(renderDownloadedGgufRow)}
-                  {!downloadedCollapsed &&
-                    unslothCachedModelRows.map(renderDownloadedModelRow)}
-                </>
-              ) : null}
-
-              {/* Other models: non-Unsloth downloads, grouped just above
-              Fine-tuned. Shown only when such models exist. */}
-              {showDownloaded && cachedReady && hasOtherModels ? (
-                <div ref={otherModelsSectionRef}>
-                  <ListLabel
-                    divider={true}
-                    icon={
-                      <HugeiconsIcon icon={Flag01Icon} className="size-3.5" />
-                    }
-                    collapsed={otherModelsCollapsed}
-                    onToggle={() => setOtherModelsCollapsed((v) => !v)}
-                  >
-                    Other models
-                  </ListLabel>
-                  {!otherModelsCollapsed &&
-                    otherCachedGguf.map(renderDownloadedGgufRow)}
-                  {!otherModelsCollapsed &&
-                    otherCachedModelRows.map(renderDownloadedModelRow)}
-                </div>
-              ) : null}
-
-              {/* Fine-tuned models: shown after the On Device scans resolve so
-              downloaded sections do not reorder during startup. */}
-              {section === "downloaded" && cachedReady ? (
-                <>
-                  <div
-                    ref={fineTunedSectionRef}
-                    className="mt-3 flex items-center gap-1 border-t border-border/50 px-2.5 pb-1 pt-3"
-                  >
-                    <span className="flex items-center gap-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
-                      <HugeiconsIcon icon={TrainIcon} className="size-3.5" />
-                      Fine-tuned
-                    </span>
-                    <div className="ml-auto">
-                      <button
-                        type="button"
-                        aria-label={
-                          fineTunedCollapsed
-                            ? "Expand fine-tuned models"
-                            : "Collapse fine-tuned models"
-                        }
-                        title={fineTunedCollapsed ? "Expand" : "Collapse"}
-                        onClick={() => setFineTunedCollapsed((v) => !v)}
-                        className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
-                      >
-                        {fineTunedCollapsed ? (
-                          <ChevronRightIcon className="size-3" />
-                        ) : (
-                          <ChevronDownIcon className="size-3" />
-                        )}
-                      </button>
-                    </div>
-                  </div>
-                  {!fineTunedCollapsed && fineTunedRows.length > 0 && (
-                    <FineTunedRows
-                      adapters={fineTunedRows}
-                      value={value}
-                      loadedModelId={loadedModelId}
-                      activeGgufVariant={activeGgufVariant}
-                      onSelect={onSelect}
-                      onModelsChange={onModelsChange}
-                      deleteDisabled={deleteDisabled}
-                      loraModelList={hubModelList}
-                      expandedGguf={expandedGguf}
-                      setExpandedGguf={setExpandedGguf}
-                      gpu={gpu}
-                    />
-                  )}
-                </>
-              ) : null}
-
-              {showCustom && cachedReady ? (
-                <>
-                  <div
-                    ref={customFolderSectionRef}
-                    className="mt-3 flex items-center gap-1 border-t border-border/50 px-2.5 pb-1 pt-3"
-                  >
-                    <button
-                      type="button"
-                      onClick={() => setShowFolderBrowser(true)}
-                      title="Browse folders on the server"
-                      className="flex items-center gap-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground transition-colors hover:text-foreground"
+                              Go to custom folders
+                            </TooltipContent>
+                          </Tooltip>
+                        </>
+                      }
                     >
-                      <HugeiconsIcon icon={Folder02Icon} className="size-3.5" />
-                      Custom Folders
-                    </button>
-                    <div className="flex items-center gap-0.5">
-                      <button
-                        type="button"
-                        aria-label={
-                          showFolderInput
-                            ? "Cancel adding folder"
-                            : "Add scan folder by path"
-                        }
-                        title={
-                          showFolderInput ? "Cancel" : "Add by typing a path"
-                        }
-                        onClick={() => {
-                          setShowFolderInput((open) => {
-                            if (open) {
-                              setFolderInput("");
-                              setFolderError(null);
-                            }
-                            return !open;
-                          });
-                        }}
-                        className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
-                      >
-                        <HugeiconsIcon
-                          icon={showFolderInput ? Cancel01Icon : Add01Icon}
-                          className="size-3"
-                        />
-                      </button>
-                      <button
-                        type="button"
-                        aria-label="Browse for a folder on the server"
-                        title="Browse folders on the server"
-                        onClick={() => setShowFolderBrowser(true)}
-                        className="shrink-0 rounded p-0.5 text-muted-foreground/60 transition-colors hover:text-foreground"
-                      >
-                        <HugeiconsIcon
-                          icon={Search01Icon}
-                          className="size-2.5"
-                        />
-                      </button>
-                    </div>
-                    <div className="ml-auto">
-                      <button
-                        type="button"
-                        aria-label={
-                          customFoldersCollapsed
-                            ? "Expand custom folders"
-                            : "Collapse custom folders"
-                        }
-                        title={customFoldersCollapsed ? "Expand" : "Collapse"}
-                        onClick={() => setCustomFoldersCollapsed((v) => !v)}
-                        className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
-                      >
-                        {customFoldersCollapsed ? (
-                          <ChevronRightIcon className="size-3" />
-                        ) : (
-                          <ChevronDownIcon className="size-3" />
-                        )}
-                      </button>
-                    </div>
-                  </div>
+                      {/* When other providers (LM Studio/Ollama) also show here, name
+                    this group "Unsloth" so the two are easy to tell apart. */}
+                      {sortedLmStudio.length > 0 ? "Unsloth" : "Downloaded"}
+                    </ListLabel>
+                    {!downloadedCollapsed &&
+                      unslothCachedGguf.map(renderDownloadedGgufRow)}
+                    {!downloadedCollapsed &&
+                      unslothCachedModelRows.map(renderDownloadedModelRow)}
+                  </>
+                ) : null}
 
-                  {/* Folder paths */}
-                  {!customFoldersCollapsed &&
-                    scanFolders.map((f) => (
-                      <div
-                        key={f.id}
-                        className="group flex items-center gap-1.5 px-2.5 py-0.5"
+                {/* Other models: non-Unsloth downloads, grouped just above
+              Fine-tuned. Shown only when such models exist. */}
+                {showDownloaded && hasOtherModels ? (
+                  <div ref={otherModelsSectionRef}>
+                    <ListLabel
+                      divider={true}
+                      icon={
+                        <HugeiconsIcon icon={Flag01Icon} className="size-3.5" />
+                      }
+                      collapsed={otherModelsCollapsed}
+                      onToggle={() => setOtherModelsCollapsed((v) => !v)}
+                    >
+                      Other models
+                    </ListLabel>
+                    {!otherModelsCollapsed &&
+                      otherCachedGguf.map(renderDownloadedGgufRow)}
+                    {!otherModelsCollapsed &&
+                      otherCachedModelRows.map(renderDownloadedModelRow)}
+                  </div>
+                ) : null}
+
+                {/* Fine-tuned models: a section above Custom Folders. Always shown on
+              On Device so the train shortcut always has a target, with an empty
+              state when none exist. */}
+                {section === "downloaded" ? (
+                  <>
+                    <div
+                      ref={fineTunedSectionRef}
+                      className="mt-3 flex items-center gap-1 border-t border-border/50 px-2.5 pb-1 pt-3"
+                    >
+                      <span className="flex items-center gap-1.5 text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
+                        <HugeiconsIcon icon={TrainIcon} className="size-3.5" />
+                        Fine-tuned
+                      </span>
+                      <div className="ml-auto">
+                        <button
+                          type="button"
+                          aria-label={
+                            fineTunedCollapsed
+                              ? "Expand fine-tuned models"
+                              : "Collapse fine-tuned models"
+                          }
+                          title={fineTunedCollapsed ? "Expand" : "Collapse"}
+                          onClick={() => setFineTunedCollapsed((v) => !v)}
+                          className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
+                        >
+                          {fineTunedCollapsed ? (
+                            <ChevronRightIcon className="size-3" />
+                          ) : (
+                            <ChevronDownIcon className="size-3" />
+                          )}
+                        </button>
+                      </div>
+                    </div>
+                    {!fineTunedCollapsed && fineTunedRows.length > 0 && (
+                      <FineTunedRows
+                        adapters={fineTunedRows}
+                        value={value}
+                        loadedModelId={loadedModelId}
+                        activeGgufVariant={activeGgufVariant}
+                        onSelect={onSelect}
+                        onConfigure={onConfigure}
+                        onModelsChange={onModelsChange}
+                        deleteDisabled={deleteDisabled}
+                        loraModelList={hubModelList}
+                        expandedGguf={expandedGguf}
+                        setExpandedGguf={setExpandedGguf}
+                        gpu={gpu}
+                      />
+                    )}
+                  </>
+                ) : null}
+
+                {showCustom ? (
+                  <>
+                    <div
+                      ref={customFolderSectionRef}
+                      className="mt-3 flex items-center gap-1 border-t border-border/50 px-2.5 pb-1 pt-3"
+                    >
+                      <button
+                        type="button"
+                        onClick={() => setShowFolderBrowser(true)}
+                        title="Browse folders on the server"
+                        className="flex items-center gap-1.5 text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground transition-colors hover:text-foreground"
                       >
                         <HugeiconsIcon
                           icon={Folder02Icon}
-                          className="size-3 shrink-0 text-muted-foreground/40"
+                          className="size-3.5"
                         />
-                        <span
-                          className="min-w-0 flex-1 truncate font-mono text-[10px] text-muted-foreground/70"
-                          title={f.path}
-                        >
-                          {f.path}
-                        </span>
+                        Custom Folders
+                      </button>
+                      <div className="flex items-center gap-0.5">
                         <button
                           type="button"
-                          onClick={() => handleRemoveFolder(f.id)}
-                          aria-label={`Remove folder ${f.path}`}
-                          className="shrink-0 rounded p-1 text-foreground/70 transition-colors hover:bg-destructive/10 hover:text-destructive focus-visible:bg-destructive/10 focus-visible:text-destructive"
+                          aria-label={
+                            showFolderInput
+                              ? "Cancel adding folder"
+                              : "Add scan folder by path"
+                          }
+                          title={
+                            showFolderInput ? "Cancel" : "Add by typing a path"
+                          }
+                          onClick={() => {
+                            setShowFolderInput((open) => {
+                              if (open) {
+                                setFolderInput("");
+                                setFolderError(null);
+                              }
+                              return !open;
+                            });
+                          }}
+                          className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
                         >
                           <HugeiconsIcon
-                            icon={Cancel01Icon}
+                            icon={showFolderInput ? Cancel01Icon : Add01Icon}
                             className="size-3"
                           />
                         </button>
-                      </div>
-                    ))}
-
-                  {/* Recommended folders */}
-                  {!customFoldersCollapsed &&
-                    (() => {
-                      const registered = new Set(
-                        scanFolders.map((f) => f.path),
-                      );
-                      const unregistered = recommendedFolders.filter(
-                        (p) => !registered.has(p),
-                      );
-                      if (unregistered.length === 0) return null;
-                      return (
-                        <div className="flex flex-wrap gap-1 px-2.5 pb-0.5">
-                          {unregistered.map((p) => (
-                            <button
-                              key={p}
-                              type="button"
-                              onClick={() => void handleAddFolder(p)}
-                              disabled={folderLoading}
-                              title={`Add ${p}`}
-                              className="rounded-full border border-dashed border-border/50 px-2 py-0.5 font-mono text-[10px] text-muted-foreground/70 transition-colors hover:border-foreground/30 hover:bg-accent hover:text-foreground disabled:opacity-40"
-                            >
-                              <span className="text-[11px] font-semibold">
-                                +
-                              </span>{" "}
-                              {p.length > 30 ? `...${p.slice(-27)}` : p}
-                            </button>
-                          ))}
-                        </div>
-                      );
-                    })()}
-
-                  {/* Add folder input */}
-                  {!customFoldersCollapsed && showFolderInput && (
-                    <div className="px-2.5 pb-1 pt-0.5">
-                      <div className="flex items-center gap-1">
-                        <HugeiconsIcon
-                          icon={Folder02Icon}
-                          className="size-3 shrink-0 text-muted-foreground/40"
-                        />
-                        <input
-                          value={folderInput}
-                          onChange={(e) => {
-                            setFolderInput(e.target.value);
-                            setFolderError(null);
-                          }}
-                          onKeyDown={(e) => {
-                            if (e.key === "Enter") {
-                              e.preventDefault();
-                              handleAddFolder();
-                            }
-                            if (e.key === "Escape") {
-                              e.preventDefault();
-                              e.stopPropagation();
-                              setShowFolderInput(false);
-                              setFolderInput("");
-                              setFolderError(null);
-                            }
-                          }}
-                          placeholder="/path/to/models"
-                          className="h-6 min-w-0 flex-1 rounded border border-border/50 bg-transparent px-1.5 font-mono text-[10px] text-foreground outline-none placeholder:text-muted-foreground/40 focus:border-foreground/20"
-                          disabled={folderLoading}
-                          autoFocus={true}
-                        />
                         <button
                           type="button"
-                          onClick={() => setShowFolderBrowser(true)}
-                          disabled={folderLoading}
-                          aria-label="Browse for folder"
+                          aria-label="Browse for a folder on the server"
                           title="Browse folders on the server"
-                          className="flex h-6 shrink-0 items-center justify-center rounded border border-border/50 px-1.5 text-muted-foreground transition-colors hover:bg-accent hover:text-foreground disabled:opacity-40"
+                          onClick={() => setShowFolderBrowser(true)}
+                          className="shrink-0 rounded p-0.5 text-muted-foreground/60 transition-colors hover:text-foreground"
                         >
                           <HugeiconsIcon
                             icon={Search01Icon}
-                            className="size-3"
+                            className="size-2.5"
                           />
                         </button>
+                      </div>
+                      <div className="ml-auto">
                         <button
                           type="button"
-                          onClick={() => {
-                            void handleAddFolder();
-                          }}
-                          disabled={folderLoading || !folderInput.trim()}
-                          className="h-6 shrink-0 rounded border border-border/50 px-1.5 text-[10px] text-muted-foreground transition-colors hover:bg-accent disabled:opacity-40"
+                          aria-label={
+                            customFoldersCollapsed
+                              ? "Expand custom folders"
+                              : "Collapse custom folders"
+                          }
+                          title={customFoldersCollapsed ? "Expand" : "Collapse"}
+                          onClick={() => setCustomFoldersCollapsed((v) => !v)}
+                          className="shrink-0 rounded p-1 text-muted-foreground/60 transition-colors hover:text-foreground"
                         >
-                          Add
+                          {customFoldersCollapsed ? (
+                            <ChevronRightIcon className="size-3" />
+                          ) : (
+                            <ChevronDownIcon className="size-3" />
+                          )}
                         </button>
                       </div>
-                      {folderError && (
-                        <p className="px-0.5 pt-0.5 text-[10px] text-destructive">
-                          {folderError}
-                        </p>
-                      )}
                     </div>
-                  )}
 
-                  <FolderBrowser
-                    open={showFolderBrowser}
-                    onOpenChange={setShowFolderBrowser}
-                    initialPath={folderInput.trim() || undefined}
-                    onSelect={(picked) => {
-                      setFolderInput(picked);
-                      setFolderError(null);
-                      // Pass the path explicitly: `folderInput` state hasn't
-                      // flushed yet when "Use this folder" submits.
-                      void handleAddFolder(picked);
-                    }}
-                  />
-
-                  {/* Models from custom folders */}
-                  {!customFoldersCollapsed &&
-                    sortedCustomFolderModels.map((m) => {
-                      const isGgufFile = m.path.toLowerCase().endsWith(".gguf");
-                      // Honor the backend model_format hint (suffixless GGUF
-                      // folders) in addition to name/path so the row classifies
-                      // and loads through the same GGUF path as the filter.
-                      const isGguf = localModelIsGguf(m);
-                      // Single .gguf files (e.g. Ollama blobs) load directly;
-                      // GGUF repos/directories expand to pick a variant.
-                      const isDirectGguf = isGgufFile;
-                      const optionKey = makeModelOptionKey(
-                        "custom-folder",
-                        m.id,
-                      );
-                      return (
-                        <div key={m.id}>
-                          <ModelRow
-                            label={m.model_id ?? m.display_name}
-                            meta={isGguf ? "GGUF" : "Local"}
-                            tooltipText={localPathTooltip(
-                              m.model_id ?? m.display_name,
-                              m.path,
-                            )}
-                            selected={value === m.id}
-                            loaded={isRuntimeLoadedModel(
-                              loadedModelId,
-                              activeGgufVariant,
-                              m.id,
-                              isGgufFile
-                                ? "ignore"
-                                : isGguf
-                                  ? "required"
-                                  : "none",
-                            )}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === m.id,
-                            )}
-                            onClick={() => {
-                              if (isDirectGguf) {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                  // Mark GGUF so "Load on selection = off" stages
-                                  // through Run settings (matches LM Studio path).
-                                  isGguf: true,
-                                });
-                              } else if (isGguf) {
-                                toggleGgufExpanded(m.id);
-                              } else {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                });
-                              }
-                            }}
-                            onArrowDownIntoChildren={
-                              isGguf && !isDirectGguf && isGgufExpanded(m.id)
-                                ? () => {
-                                    const focused =
-                                      focusFirstChildOption(optionKey);
-                                    return focused;
-                                  }
-                                : undefined
-                            }
-                            vramStatus={null}
+                    {/* Folder paths */}
+                    {!customFoldersCollapsed &&
+                      scanFolders.map((f) => (
+                        <div
+                          key={f.id}
+                          className="group flex items-center gap-1.5 px-2.5 py-0.5"
+                        >
+                          <HugeiconsIcon
+                            icon={Folder02Icon}
+                            className="size-3 shrink-0 text-muted-foreground/40"
                           />
-                          {isGguf && !isDirectGguf && isGgufExpanded(m.id) && (
-                            <GgufVariantExpander
-                              repoId={m.id}
-                              onDevice={true}
-                              onSelect={onSelect}
-                              parentOptionKey={optionKey}
-                              onNavigatePastStart={() =>
-                                hubModelList.focusOption(optionKey)
-                              }
-                              onNavigatePastEnd={() =>
-                                hubModelList.moveFocus(optionKey, "next")
-                              }
-                              gpuGb={
-                                gpu.available ? gpu.memoryTotalGb : undefined
-                              }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                          <span
+                            className="min-w-0 flex-1 truncate font-mono text-ui-10 text-muted-foreground/70"
+                            title={f.path}
+                          >
+                            {f.path}
+                          </span>
+                          <button
+                            type="button"
+                            onClick={() => handleRemoveFolder(f.id)}
+                            aria-label={`Remove folder ${f.path}`}
+                            className="shrink-0 rounded p-1 text-foreground/70 transition-colors hover:bg-destructive/10 hover:text-destructive focus-visible:bg-destructive/10 focus-visible:text-destructive"
+                          >
+                            <HugeiconsIcon
+                              icon={Cancel01Icon}
+                              className="size-3"
                             />
-                          )}
+                          </button>
                         </div>
-                      );
-                    })}
-                  {!customFoldersCollapsed &&
-                  showHfSection &&
-                  sortedCustomFolderModels.length === 0 ? (
-                    <div className="px-2.5 py-2 text-xs text-muted-foreground">
-                      No matching models in custom folders.
-                    </div>
-                  ) : null}
-                </>
-              ) : null}
+                      ))}
 
-              {section === "downloaded" &&
-              cachedReady &&
-              sortedLmStudio.length > 0 ? (
-                <>
-                  <ListLabel
-                    divider={true}
-                    collapsed={lmStudioCollapsed}
-                    onToggle={() => setLmStudioCollapsed((v) => !v)}
-                  >
-                    LM Studio
-                  </ListLabel>
-                  {!lmStudioCollapsed &&
-                    sortedLmStudio.map((m) => {
-                      const isGgufFile = m.path.toLowerCase().endsWith(".gguf");
-                      // LM Studio dirs are GGUF but rarely carry a -GGUF suffix;
-                      // use the shared helper (model_format hint) so the row,
-                      // filter, and load path agree.
-                      const isGguf = localModelIsGguf(m);
-                      const optionKey = makeModelOptionKey("lm-studio", m.id);
-                      return (
-                        <div key={m.id}>
-                          <ModelRow
-                            label={m.model_id ?? m.display_name}
-                            meta={isGguf ? "GGUF" : "Local"}
-                            tooltipText={localPathTooltip(
-                              m.model_id ?? m.display_name,
-                              m.path,
-                            )}
-                            selected={value === m.id}
-                            loaded={isRuntimeLoadedModel(
-                              loadedModelId,
-                              activeGgufVariant,
-                              m.id,
-                              isGgufFile
-                                ? "ignore"
-                                : isGguf
-                                  ? "required"
-                                  : "none",
-                            )}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === m.id,
-                            )}
-                            onClick={() => {
-                              if (isGgufFile) {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                  isGguf: true,
-                                });
-                              } else if (isGguf) {
-                                toggleGgufExpanded(m.id);
-                              } else {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                });
+                    {/* Recommended folders */}
+                    {!customFoldersCollapsed &&
+                      (() => {
+                        const registered = new Set(
+                          scanFolders.map((f) => f.path),
+                        );
+                        const unregistered = recommendedFolders.filter(
+                          (p) => !registered.has(p),
+                        );
+                        if (unregistered.length === 0) return null;
+                        return (
+                          <div className="flex flex-wrap gap-1 px-2.5 pb-0.5">
+                            {unregistered.map((p) => (
+                              <button
+                                key={p}
+                                type="button"
+                                onClick={() => void handleAddFolder(p)}
+                                disabled={folderLoading}
+                                title={`Add ${p}`}
+                                className="rounded-full border border-dashed border-border/50 px-2 py-0.5 font-mono text-ui-10 text-muted-foreground/70 transition-colors hover:border-foreground/30 hover:bg-accent hover:text-foreground disabled:opacity-40"
+                              >
+                                <span className="text-ui-11 font-semibold">
+                                  +
+                                </span>{" "}
+                                {p.length > 30 ? `...${p.slice(-27)}` : p}
+                              </button>
+                            ))}
+                          </div>
+                        );
+                      })()}
+
+                    {/* Add folder input */}
+                    {!customFoldersCollapsed && showFolderInput && (
+                      <div className="px-2.5 pb-1 pt-0.5">
+                        <div className="flex items-center gap-1">
+                          <HugeiconsIcon
+                            icon={Folder02Icon}
+                            className="size-3 shrink-0 text-muted-foreground/40"
+                          />
+                          <input
+                            value={folderInput}
+                            onChange={(e) => {
+                              setFolderInput(e.target.value);
+                              setFolderError(null);
+                            }}
+                            onKeyDown={(e) => {
+                              if (e.key === "Enter") {
+                                e.preventDefault();
+                                handleAddFolder();
+                              }
+                              if (e.key === "Escape") {
+                                e.preventDefault();
+                                e.stopPropagation();
+                                setShowFolderInput(false);
+                                setFolderInput("");
+                                setFolderError(null);
                               }
                             }}
-                            onArrowDownIntoChildren={
-                              isGguf && !isGgufFile && isGgufExpanded(m.id)
-                                ? () => {
-                                    const focused =
-                                      focusFirstChildOption(optionKey);
-                                    return focused;
-                                  }
-                                : undefined
-                            }
-                            vramStatus={null}
+                            placeholder="/path/to/models"
+                            className="h-6 min-w-0 flex-1 rounded border border-border/50 bg-transparent px-1.5 font-mono text-ui-10 text-foreground outline-none placeholder:text-muted-foreground/40 focus:border-foreground/20"
+                            disabled={folderLoading}
+                            autoFocus={true}
                           />
-                          {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
-                            <GgufVariantExpander
-                              repoId={m.id}
-                              onDevice={true}
-                              onSelect={onSelect}
-                              parentOptionKey={optionKey}
-                              onNavigatePastStart={() =>
-                                hubModelList.focusOption(optionKey)
-                              }
-                              onNavigatePastEnd={() =>
-                                hubModelList.moveFocus(optionKey, "next")
-                              }
-                              gpuGb={
-                                gpu.available ? gpu.memoryTotalGb : undefined
-                              }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                          <button
+                            type="button"
+                            onClick={() => setShowFolderBrowser(true)}
+                            disabled={folderLoading}
+                            aria-label="Browse for folder"
+                            title="Browse folders on the server"
+                            className="flex h-6 shrink-0 items-center justify-center rounded border border-border/50 px-1.5 text-muted-foreground transition-colors hover:bg-accent hover:text-foreground disabled:opacity-40"
+                          >
+                            <HugeiconsIcon
+                              icon={Search01Icon}
+                              className="size-3"
                             />
-                          )}
-                        </div>
-                      );
-                    })}
-                </>
-              ) : null}
-
-              {section === "downloaded" &&
-              cachedReady &&
-              sortedLocalDir.length > 0 ? (
-                <>
-                  <ListLabel
-                    divider={true}
-                    collapsed={localDirCollapsed}
-                    onToggle={() => setLocalDirCollapsed((v) => !v)}
-                  >
-                    Local models
-                  </ListLabel>
-                  {!localDirCollapsed &&
-                    sortedLocalDir.map((m) => {
-                      // A loose ./models/*.gguf file loads directly; a GGUF repo
-                      // directory expands to pick a variant. The backend's local
-                      // variant scanner returns nothing for a config-less loose
-                      // file, so expanding it would dead-end at "No GGUF variants".
-                      const isGgufFile = m.path.toLowerCase().endsWith(".gguf");
-                      const isGguf = localModelIsGguf(m);
-                      const optionKey = makeModelOptionKey("local-dir", m.id);
-                      return (
-                        <div key={m.id}>
-                          <ModelRow
-                            label={m.model_id ?? m.display_name}
-                            meta={isGguf ? "GGUF" : "Local"}
-                            tooltipText={localPathTooltip(
-                              m.model_id ?? m.display_name,
-                              m.path,
-                            )}
-                            selected={value === m.id}
-                            loaded={isRuntimeLoadedModel(
-                              loadedModelId,
-                              activeGgufVariant,
-                              m.id,
-                              isGgufFile
-                                ? "ignore"
-                                : isGguf
-                                  ? "required"
-                                  : "none",
-                            )}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === m.id,
-                            )}
+                          </button>
+                          <button
+                            type="button"
                             onClick={() => {
-                              if (isGgufFile) {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                  isGguf: true,
-                                });
-                              } else if (isGguf) {
-                                toggleGgufExpanded(m.id);
-                              } else {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                });
-                              }
+                              void handleAddFolder();
                             }}
-                            onArrowDownIntoChildren={
-                              isGguf && !isGgufFile && isGgufExpanded(m.id)
-                                ? () => focusFirstChildOption(optionKey)
-                                : undefined
-                            }
-                            vramStatus={null}
-                          />
-                          {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
-                            <GgufVariantExpander
-                              repoId={m.id}
-                              onDevice={true}
-                              onSelect={onSelect}
-                              parentOptionKey={optionKey}
-                              onNavigatePastStart={() =>
-                                hubModelList.focusOption(optionKey)
-                              }
-                              onNavigatePastEnd={() =>
-                                hubModelList.moveFocus(optionKey, "next")
-                              }
-                              gpuGb={
-                                gpu.available ? gpu.memoryTotalGb : undefined
-                              }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
-                            />
-                          )}
+                            disabled={folderLoading || !folderInput.trim()}
+                            className="h-6 shrink-0 rounded border border-border/50 px-1.5 text-ui-10 text-muted-foreground transition-colors hover:bg-accent disabled:opacity-40"
+                          >
+                            Add
+                          </button>
                         </div>
-                      );
-                    })}
-                </>
-              ) : null}
-
-              {showRecommendedSection ? (
-                <>
-                  {recommendedSearch.isLoading &&
-                  recommendedRows.length === 0 ? (
-                    <div className="flex items-center gap-2 px-5 py-3">
-                      <Spinner className="size-3 text-muted-foreground" />
-                      <span className="text-xs text-muted-foreground">
-                        Loading models…
-                      </span>
-                    </div>
-                  ) : recommendedRows.length === 0 ? (
-                    <div className="px-2.5 py-2 text-xs text-muted-foreground">
-                      No models found.
-                    </div>
-                  ) : (
-                    recommendedRows.map((r) => {
-                      const id = r.id;
-                      const info = recommendedMeta.get(id);
-                      const isG = isKnownGgufRepo(id);
-                      const optionKey = makeModelOptionKey("recommended", id);
-                      return (
-                        <div key={id}>
-                          <ModelRow
-                            label={id}
-                            hubUrl={hubRepoUrl(id)}
-                            hideOwner={true}
-                            downloaded={downloadedSet.has(id.toLowerCase())}
-                            capabilities={capsById.get(id)}
-                            meta={
-                              info?.meta ??
-                              (isG ? "GGUF" : extractParamLabel(id))
-                            }
-                            selected={value === id}
-                            loaded={isRuntimeLoadedModel(
-                              loadedModelId,
-                              activeGgufVariant,
-                              id,
-                              isG ? "required" : "none",
-                            )}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === id,
-                            )}
-                            onClick={() => {
-                              if (isG) {
-                                setExpandedGguf((prev) =>
-                                  prev === id ? null : id,
-                                );
-                              } else {
-                                handleModelClick(id);
-                              }
-                            }}
-                            vramStatus={info?.status ?? null}
-                            vramEst={info?.est}
-                            gpuGb={
-                              gpu.available ? gpu.memoryTotalGb : undefined
-                            }
-                            onArrowDownIntoChildren={
-                              expandedGguf === id
-                                ? () => focusFirstChildOption(optionKey)
-                                : undefined
-                            }
-                          />
-                          {expandedGguf === id && (
-                            <GgufVariantExpander
-                              repoId={id}
-                              onSelect={onSelect}
-                              hfToken={hfToken || undefined}
-                              parentOptionKey={optionKey}
-                              onNavigatePastStart={() =>
-                                hubModelList.focusOption(optionKey)
-                              }
-                              onNavigatePastEnd={() =>
-                                hubModelList.moveFocus(optionKey, "next")
-                              }
-                              gpuGb={
-                                gpu.available ? gpu.memoryTotalGb : undefined
-                              }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
-                              variantActions={{
-                                onDelete: async (quant) => {
-                                  await deleteCachedModel(id, quant);
-                                  refreshCachedLists();
-                                },
-                                deleteDisabled,
-                              }}
-                            />
-                          )}
-                        </div>
-                      );
-                    })
-                  )}
-                  {recommendedSearch.hasMore && (
-                    <>
-                      <div ref={recommendedSentinelRef} className="h-px" />
-                      <div className="flex items-center justify-center py-2">
-                        <Spinner className="size-3.5 text-muted-foreground" />
-                      </div>
-                    </>
-                  )}
-                </>
-              ) : null}
-
-              {showHfSection &&
-              section === "recommended" &&
-              filteredRecommendedIds.length > 0 ? (
-                <>
-                  {filteredRecommendedIds.map((id) => {
-                    const vram = recommendedVramMap.get(id);
-                    const optionKey = makeModelOptionKey(
-                      "search-recommended",
-                      id,
-                    );
-                    return (
-                      <div key={id}>
-                        <ModelRow
-                          label={id}
-                          hubUrl={hubRepoUrl(id)}
-                          capabilities={capsById.get(id)}
-                          meta={
-                            isKnownGgufRepo(id)
-                              ? "GGUF"
-                              : (vram?.detail ?? extractParamLabel(id))
-                          }
-                          selected={value === id}
-                          loaded={isRuntimeLoadedModel(
-                            loadedModelId,
-                            activeGgufVariant,
-                            id,
-                            isKnownGgufRepo(id) ? "required" : "none",
-                          )}
-                          optionProps={hubModelList.getOptionProps(
-                            optionKey,
-                            value === id,
-                          )}
-                          onClick={() => {
-                            if (isKnownGgufRepo(id)) {
-                              setExpandedGguf((prev) =>
-                                prev === id ? null : id,
-                              );
-                            } else {
-                              handleModelClick(id);
-                            }
-                          }}
-                          vramStatus={
-                            isKnownGgufRepo(id) ? null : (vram?.status ?? null)
-                          }
-                          vramEst={isKnownGgufRepo(id) ? undefined : vram?.est}
-                          gpuGb={gpu.available ? gpu.memoryTotalGb : undefined}
-                          onArrowDownIntoChildren={
-                            expandedGguf === id
-                              ? () => {
-                                  const focused =
-                                    focusFirstChildOption(optionKey);
-                                  return focused;
-                                }
-                              : undefined
-                          }
-                        />
-                        {expandedGguf === id && (
-                          <GgufVariantExpander
-                            repoId={id}
-                            onSelect={onSelect}
-                            hfToken={hfToken || undefined}
-                            parentOptionKey={optionKey}
-                            onNavigatePastStart={() =>
-                              hubModelList.focusOption(optionKey)
-                            }
-                            onNavigatePastEnd={() =>
-                              hubModelList.moveFocus(optionKey, "next")
-                            }
-                            gpuGb={
-                              gpu.available ? gpu.memoryTotalGb : undefined
-                            }
-                            systemRamGb={gpu.systemRamAvailableGb || undefined}
-                            variantActions={{
-                              onDelete: async (quant) => {
-                                await deleteCachedModel(id, quant);
-                                refreshCachedLists();
-                              },
-                              deleteDisabled,
-                            }}
-                          />
+                        {folderError && (
+                          <p className="px-0.5 pt-0.5 text-ui-10 text-destructive">
+                            {folderError}
+                          </p>
                         )}
                       </div>
-                    );
-                  })}
-                </>
-              ) : null}
+                    )}
 
-              {showHfSection && section === "recommended" ? (
-                <>
-                  {hfIds.length === 0 && !isLoading ? (
-                    filteredRecommendedIds.length === 0 ? (
+                    <FolderBrowser
+                      open={showFolderBrowser}
+                      onOpenChange={setShowFolderBrowser}
+                      initialPath={folderInput.trim() || undefined}
+                      onSelect={(picked) => {
+                        setFolderInput(picked);
+                        setFolderError(null);
+                        // Pass the path explicitly: `folderInput` state hasn't
+                        // flushed yet when "Use this folder" submits.
+                        void handleAddFolder(picked);
+                      }}
+                    />
+
+                    {/* Models from custom folders */}
+                    {!customFoldersCollapsed &&
+                      sortedCustomFolderModels.map((m) => {
+                        const isGgufFile = m.path
+                          .toLowerCase()
+                          .endsWith(".gguf");
+                        // Honor the backend model_format hint (suffixless GGUF
+                        // folders) in addition to name/path so the row classifies
+                        // and loads through the same GGUF path as the filter.
+                        const isGguf = localModelIsGguf(m);
+                        // Single .gguf files (e.g. Ollama blobs) load directly;
+                        // GGUF repos/directories expand to pick a variant.
+                        const isDirectGguf = isGgufFile;
+                        const optionKey = makeModelOptionKey(
+                          "custom-folder",
+                          m.id,
+                        );
+                        return (
+                          <div key={m.id}>
+                            <div className="flex items-center gap-0.5">
+                              <div className="min-w-0 flex-1">
+                                <ModelRow
+                                  label={m.model_id ?? m.display_name}
+                                  meta={isGguf ? "GGUF" : "Local"}
+                                  tooltipText={localPathTooltip(
+                                    m.model_id ?? m.display_name,
+                                    m.path,
+                                  )}
+                                  selected={value === m.id}
+                                  loaded={isRuntimeLoadedModel(
+                                    loadedModelId,
+                                    activeGgufVariant,
+                                    m.id,
+                                    isGgufFile
+                                      ? "ignore"
+                                      : isGguf
+                                        ? "required"
+                                        : "none",
+                                  )}
+                                  optionProps={hubModelList.getOptionProps(
+                                    optionKey,
+                                    value === m.id,
+                                  )}
+                                  onClick={() => {
+                                    if (isDirectGguf) {
+                                      onSelect(m.id, localDirectGgufMeta());
+                                    } else if (isGguf) {
+                                      toggleGgufExpanded(m.id);
+                                    } else {
+                                      onSelect(m.id, localModelMeta());
+                                    }
+                                  }}
+                                  onArrowDownIntoChildren={
+                                    isGguf &&
+                                    !isDirectGguf &&
+                                    isGgufExpanded(m.id)
+                                      ? () => {
+                                          const focused =
+                                            focusFirstChildOption(optionKey);
+                                          return focused;
+                                        }
+                                      : undefined
+                                  }
+                                  vramStatus={null}
+                                />
+                              </div>
+                              {isDirectGguf && onConfigure && (
+                                <ModelLoadSettingsAction
+                                  ariaLabel={`Inference settings for ${
+                                    m.model_id ?? m.display_name
+                                  }`}
+                                  onConfigure={() =>
+                                    onConfigure(m.id, localDirectGgufMeta())
+                                  }
+                                />
+                              )}
+                              {!isGguf && onConfigure && (
+                                <ModelLoadSettingsAction
+                                  ariaLabel={`Inference settings for ${
+                                    m.model_id ?? m.display_name
+                                  }`}
+                                  onConfigure={() =>
+                                    onConfigure(m.id, localModelMeta())
+                                  }
+                                />
+                              )}
+                            </div>
+                            {isGguf &&
+                              !isDirectGguf &&
+                              isGgufExpanded(m.id) && (
+                                <GgufVariantExpander
+                                  repoId={m.id}
+                                  onDevice={true}
+                                  onSelect={onSelect}
+                                  onConfigure={onConfigure}
+                                  parentOptionKey={optionKey}
+                                  onNavigatePastStart={() =>
+                                    hubModelList.focusOption(optionKey)
+                                  }
+                                  onNavigatePastEnd={() =>
+                                    hubModelList.moveFocus(optionKey, "next")
+                                  }
+                                  gpuGb={
+                                    gpu.available
+                                      ? gpu.memoryTotalGb
+                                      : undefined
+                                  }
+                                  systemRamGb={
+                                    gpu.systemRamAvailableGb || undefined
+                                  }
+                                />
+                              )}
+                          </div>
+                        );
+                      })}
+                    {!customFoldersCollapsed &&
+                    showHfSection &&
+                    sortedCustomFolderModels.length === 0 ? (
                       <div className="px-2.5 py-2 text-xs text-muted-foreground">
-                        No matching Unsloth models.
+                        No matching models in custom folders.
                       </div>
-                    ) : null
-                  ) : (
-                    hfIds.map((id) => {
-                      const vram = vramMap.get(id);
-                      const isSearchGguf = isKnownGgufRepo(id);
-                      const optionKey = makeModelOptionKey("search-hf", id);
+                    ) : null}
+                  </>
+                ) : null}
+
+                {section === "downloaded" && sortedLmStudio.length > 0 ? (
+                  <>
+                    <ListLabel
+                      divider={true}
+                      collapsed={lmStudioCollapsed}
+                      onToggle={() => setLmStudioCollapsed((v) => !v)}
+                    >
+                      LM Studio
+                    </ListLabel>
+                    {!lmStudioCollapsed &&
+                      sortedLmStudio.map((m) => {
+                        const isGgufFile = m.path
+                          .toLowerCase()
+                          .endsWith(".gguf");
+                        // LM Studio dirs are GGUF but rarely carry a -GGUF suffix;
+                        // use the shared helper (model_format hint) so the row,
+                        // filter, and load path agree.
+                        const isGguf = localModelIsGguf(m);
+                        const optionKey = makeModelOptionKey("lm-studio", m.id);
+                        return (
+                          <div key={m.id}>
+                            <div className="flex items-center gap-0.5">
+                              <div className="min-w-0 flex-1">
+                                <ModelRow
+                                  label={m.model_id ?? m.display_name}
+                                  meta={isGguf ? "GGUF" : "Local"}
+                                  tooltipText={localPathTooltip(
+                                    m.model_id ?? m.display_name,
+                                    m.path,
+                                  )}
+                                  selected={value === m.id}
+                                  loaded={isRuntimeLoadedModel(
+                                    loadedModelId,
+                                    activeGgufVariant,
+                                    m.id,
+                                    isGgufFile
+                                      ? "ignore"
+                                      : isGguf
+                                        ? "required"
+                                        : "none",
+                                  )}
+                                  optionProps={hubModelList.getOptionProps(
+                                    optionKey,
+                                    value === m.id,
+                                  )}
+                                  onClick={() => {
+                                    if (isGgufFile) {
+                                      onSelect(m.id, localDirectGgufMeta());
+                                    } else if (isGguf) {
+                                      toggleGgufExpanded(m.id);
+                                    } else {
+                                      onSelect(m.id, localModelMeta());
+                                    }
+                                  }}
+                                  onArrowDownIntoChildren={
+                                    isGguf &&
+                                    !isGgufFile &&
+                                    isGgufExpanded(m.id)
+                                      ? () => {
+                                          const focused =
+                                            focusFirstChildOption(optionKey);
+                                          return focused;
+                                        }
+                                      : undefined
+                                  }
+                                  vramStatus={null}
+                                />
+                              </div>
+                              {isGgufFile && onConfigure && (
+                                <ModelLoadSettingsAction
+                                  ariaLabel={`Inference settings for ${
+                                    m.model_id ?? m.display_name
+                                  }`}
+                                  onConfigure={() =>
+                                    onConfigure(m.id, localDirectGgufMeta())
+                                  }
+                                />
+                              )}
+                              {!isGguf && onConfigure && (
+                                <ModelLoadSettingsAction
+                                  ariaLabel={`Inference settings for ${
+                                    m.model_id ?? m.display_name
+                                  }`}
+                                  onConfigure={() =>
+                                    onConfigure(m.id, localModelMeta())
+                                  }
+                                />
+                              )}
+                            </div>
+                            {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
+                              <GgufVariantExpander
+                                repoId={m.id}
+                                onDevice={true}
+                                onSelect={onSelect}
+                                onConfigure={onConfigure}
+                                parentOptionKey={optionKey}
+                                onNavigatePastStart={() =>
+                                  hubModelList.focusOption(optionKey)
+                                }
+                                onNavigatePastEnd={() =>
+                                  hubModelList.moveFocus(optionKey, "next")
+                                }
+                                gpuGb={
+                                  gpu.available ? gpu.memoryTotalGb : undefined
+                                }
+                                systemRamGb={
+                                  gpu.systemRamAvailableGb || undefined
+                                }
+                              />
+                            )}
+                          </div>
+                        );
+                      })}
+                  </>
+                ) : null}
+
+                {section === "downloaded" && sortedLocalDir.length > 0 ? (
+                  <>
+                    <ListLabel
+                      divider={true}
+                      collapsed={localDirCollapsed}
+                      onToggle={() => setLocalDirCollapsed((v) => !v)}
+                    >
+                      Local models
+                    </ListLabel>
+                    {!localDirCollapsed &&
+                      sortedLocalDir.map((m) => {
+                        // A loose ./models/*.gguf loads directly; a GGUF repo dir
+                        // expands to pick a variant. The variant scanner returns
+                        // nothing for a config-less loose file, so expanding it would
+                        // dead-end at "No GGUF variants".
+                        const isGgufFile = m.path
+                          .toLowerCase()
+                          .endsWith(".gguf");
+                        const isGguf = localModelIsGguf(m);
+                        const optionKey = makeModelOptionKey("local-dir", m.id);
+                        return (
+                          <div key={m.id}>
+                            <div className="flex items-center gap-0.5">
+                              <div className="min-w-0 flex-1">
+                                <ModelRow
+                                  label={m.model_id ?? m.display_name}
+                                  meta={isGguf ? "GGUF" : "Local"}
+                                  tooltipText={localPathTooltip(
+                                    m.model_id ?? m.display_name,
+                                    m.path,
+                                  )}
+                                  selected={value === m.id}
+                                  loaded={isRuntimeLoadedModel(
+                                    loadedModelId,
+                                    activeGgufVariant,
+                                    m.id,
+                                    isGgufFile
+                                      ? "ignore"
+                                      : isGguf
+                                        ? "required"
+                                        : "none",
+                                  )}
+                                  optionProps={hubModelList.getOptionProps(
+                                    optionKey,
+                                    value === m.id,
+                                  )}
+                                  onClick={() => {
+                                    if (isGgufFile) {
+                                      onSelect(m.id, localDirectGgufMeta());
+                                    } else if (isGguf) {
+                                      toggleGgufExpanded(m.id);
+                                    } else {
+                                      onSelect(m.id, localModelMeta());
+                                    }
+                                  }}
+                                  onArrowDownIntoChildren={
+                                    isGguf &&
+                                    !isGgufFile &&
+                                    isGgufExpanded(m.id)
+                                      ? () => focusFirstChildOption(optionKey)
+                                      : undefined
+                                  }
+                                  vramStatus={null}
+                                />
+                              </div>
+                              {isGgufFile && onConfigure && (
+                                <ModelLoadSettingsAction
+                                  ariaLabel={`Inference settings for ${
+                                    m.model_id ?? m.display_name
+                                  }`}
+                                  onConfigure={() =>
+                                    onConfigure(m.id, localDirectGgufMeta())
+                                  }
+                                />
+                              )}
+                              {!isGguf && onConfigure && (
+                                <ModelLoadSettingsAction
+                                  ariaLabel={`Inference settings for ${
+                                    m.model_id ?? m.display_name
+                                  }`}
+                                  onConfigure={() =>
+                                    onConfigure(m.id, localModelMeta())
+                                  }
+                                />
+                              )}
+                            </div>
+                            {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
+                              <GgufVariantExpander
+                                repoId={m.id}
+                                onDevice={true}
+                                onSelect={onSelect}
+                                onConfigure={onConfigure}
+                                parentOptionKey={optionKey}
+                                onNavigatePastStart={() =>
+                                  hubModelList.focusOption(optionKey)
+                                }
+                                onNavigatePastEnd={() =>
+                                  hubModelList.moveFocus(optionKey, "next")
+                                }
+                                gpuGb={
+                                  gpu.available ? gpu.memoryTotalGb : undefined
+                                }
+                                systemRamGb={
+                                  gpu.systemRamAvailableGb || undefined
+                                }
+                              />
+                            )}
+                          </div>
+                        );
+                      })}
+                  </>
+                ) : null}
+
+                {showRecommendedSection ? (
+                  <>
+                    {recommendedSearch.isLoading &&
+                    recommendedRows.length === 0 ? (
+                      <div className="flex items-center gap-2 px-5 py-3">
+                        <Spinner className="size-3 text-muted-foreground" />
+                        <span className="text-xs text-muted-foreground">
+                          Loading models…
+                        </span>
+                      </div>
+                    ) : recommendedRows.length === 0 ? (
+                      <div className="px-2.5 py-2 text-xs text-muted-foreground">
+                        No models found.
+                      </div>
+                    ) : (
+                      recommendedRows.map((r) => {
+                        const id = r.id;
+                        const info = recommendedMeta.get(id);
+                        const isG = isKnownGgufRepo(id);
+                        const optionKey = makeModelOptionKey("recommended", id);
+                        return (
+                          <div key={id}>
+                            <ModelRow
+                              label={id}
+                              hubUrl={hubRepoUrl(id)}
+                              hideOwner={true}
+                              downloaded={downloadedSet.has(id.toLowerCase())}
+                              capabilities={capsById.get(id)}
+                              meta={
+                                info?.meta ??
+                                (isG ? "GGUF" : extractParamLabel(id))
+                              }
+                              selected={value === id}
+                              loaded={isRuntimeLoadedModel(
+                                loadedModelId,
+                                activeGgufVariant,
+                                id,
+                                isG ? "required" : "none",
+                              )}
+                              optionProps={hubModelList.getOptionProps(
+                                optionKey,
+                                value === id,
+                              )}
+                              onClick={() => {
+                                if (isG) {
+                                  setExpandedGguf((prev) =>
+                                    prev === id ? null : id,
+                                  );
+                                } else {
+                                  handleModelClick(id);
+                                }
+                              }}
+                              vramStatus={info?.status ?? null}
+                              vramEst={info?.est}
+                              gpuGb={
+                                gpu.available ? gpu.memoryTotalGb : undefined
+                              }
+                              onArrowDownIntoChildren={
+                                expandedGguf === id
+                                  ? () => focusFirstChildOption(optionKey)
+                                  : undefined
+                              }
+                            />
+                            {expandedGguf === id && (
+                              <GgufVariantExpander
+                                repoId={id}
+                                onSelect={onSelect}
+                                onConfigure={onConfigure}
+                                hfToken={hfToken || undefined}
+                                parentOptionKey={optionKey}
+                                onNavigatePastStart={() =>
+                                  hubModelList.focusOption(optionKey)
+                                }
+                                onNavigatePastEnd={() =>
+                                  hubModelList.moveFocus(optionKey, "next")
+                                }
+                                gpuGb={
+                                  gpu.available ? gpu.memoryTotalGb : undefined
+                                }
+                                systemRamGb={
+                                  gpu.systemRamAvailableGb || undefined
+                                }
+                                variantActions={{
+                                  onDelete: async (quant) => {
+                                    await deleteCachedModel(
+                                      id,
+                                      quant,
+                                      hfToken || undefined,
+                                    );
+                                    prunePinnedQuantValidation(id, quant);
+                                    refreshCachedLists();
+                                  },
+                                }}
+                              />
+                            )}
+                          </div>
+                        );
+                      })
+                    )}
+                    {recommendedSearch.hasMore && (
+                      <>
+                        <div ref={recommendedSentinelRef} className="h-px" />
+                        <div className="flex items-center justify-center py-2">
+                          <Spinner className="size-3.5 text-muted-foreground" />
+                        </div>
+                      </>
+                    )}
+                  </>
+                ) : null}
+
+                {showHfSection &&
+                section === "recommended" &&
+                filteredRecommendedIds.length > 0 ? (
+                  <>
+                    {filteredRecommendedIds.map((id) => {
+                      const vram = recommendedVramMap.get(id);
+                      const optionKey = makeModelOptionKey(
+                        "search-recommended",
+                        id,
+                      );
                       return (
                         <div key={id}>
                           <ModelRow
@@ -4232,29 +4064,23 @@ export function HubModelPicker({
                             hubUrl={hubRepoUrl(id)}
                             capabilities={capsById.get(id)}
                             meta={
-                              isSearchGguf
+                              isKnownGgufRepo(id)
                                 ? "GGUF"
-                                : [
-                                    metricsById.get(id) ??
-                                      extractParamLabel(id),
-                                    isMlxId(id) ? "MLX" : "Safetensors",
-                                  ]
-                                    .filter(Boolean)
-                                    .join(" · ")
+                                : (vram?.detail ?? extractParamLabel(id))
                             }
                             selected={value === id}
                             loaded={isRuntimeLoadedModel(
                               loadedModelId,
                               activeGgufVariant,
                               id,
-                              isSearchGguf ? "required" : "none",
+                              isKnownGgufRepo(id) ? "required" : "none",
                             )}
                             optionProps={hubModelList.getOptionProps(
                               optionKey,
                               value === id,
                             )}
                             onClick={() => {
-                              if (isSearchGguf) {
+                              if (isKnownGgufRepo(id)) {
                                 setExpandedGguf((prev) =>
                                   prev === id ? null : id,
                                 );
@@ -4263,9 +4089,13 @@ export function HubModelPicker({
                               }
                             }}
                             vramStatus={
-                              isSearchGguf ? null : (vram?.status ?? null)
+                              isKnownGgufRepo(id)
+                                ? null
+                                : (vram?.status ?? null)
+                            }
+                            vramEst={
+                              isKnownGgufRepo(id) ? undefined : vram?.est
                             }
-                            vramEst={isSearchGguf ? undefined : vram?.est}
                             gpuGb={
                               gpu.available ? gpu.memoryTotalGb : undefined
                             }
@@ -4283,6 +4113,7 @@ export function HubModelPicker({
                             <GgufVariantExpander
                               repoId={id}
                               onSelect={onSelect}
+                              onConfigure={onConfigure}
                               hfToken={hfToken || undefined}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
@@ -4294,47 +4125,156 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                              systemRamGb={
+                                gpu.systemRamAvailableGb || undefined
+                              }
                               variantActions={{
                                 onDelete: async (quant) => {
-                                  await deleteCachedModel(id, quant);
+                                  await deleteCachedModel(
+                                    id,
+                                    quant,
+                                    hfToken || undefined,
+                                  );
+                                  prunePinnedQuantValidation(id, quant);
                                   refreshCachedLists();
                                 },
-                                deleteDisabled,
                               }}
                             />
                           )}
                         </div>
                       );
-                    })
-                  )}
-                  <div ref={sentinelRef} className="h-px" />
-                  {isLoadingMore ? (
-                    <div className="flex items-center justify-center py-2">
-                      <Spinner className="size-3.5 text-muted-foreground" />
-                    </div>
-                  ) : null}
-                </>
-              ) : null}
-            </>
-          )}
+                    })}
+                  </>
+                ) : null}
+
+                {showHfSection && section === "recommended" ? (
+                  <>
+                    {hfIds.length === 0 && !isLoading ? (
+                      filteredRecommendedIds.length === 0 ? (
+                        <div className="px-2.5 py-2 text-xs text-muted-foreground">
+                          No matching Unsloth models.
+                        </div>
+                      ) : null
+                    ) : (
+                      hfIds.map((id) => {
+                        const vram = vramMap.get(id);
+                        const isSearchGguf = isKnownGgufRepo(id);
+                        const optionKey = makeModelOptionKey("search-hf", id);
+                        return (
+                          <div key={id}>
+                            <ModelRow
+                              label={id}
+                              hubUrl={hubRepoUrl(id)}
+                              capabilities={capsById.get(id)}
+                              meta={
+                                isSearchGguf
+                                  ? "GGUF"
+                                  : [
+                                      metricsById.get(id) ??
+                                        extractParamLabel(id),
+                                      isMlxId(id) ? "MLX" : "Safetensors",
+                                    ]
+                                      .filter(Boolean)
+                                      .join(" · ")
+                              }
+                              selected={value === id}
+                              loaded={isRuntimeLoadedModel(
+                                loadedModelId,
+                                activeGgufVariant,
+                                id,
+                                isSearchGguf ? "required" : "none",
+                              )}
+                              optionProps={hubModelList.getOptionProps(
+                                optionKey,
+                                value === id,
+                              )}
+                              onClick={() => {
+                                if (isSearchGguf) {
+                                  setExpandedGguf((prev) =>
+                                    prev === id ? null : id,
+                                  );
+                                } else {
+                                  handleModelClick(id);
+                                }
+                              }}
+                              vramStatus={
+                                isSearchGguf ? null : (vram?.status ?? null)
+                              }
+                              vramEst={isSearchGguf ? undefined : vram?.est}
+                              gpuGb={
+                                gpu.available ? gpu.memoryTotalGb : undefined
+                              }
+                              onArrowDownIntoChildren={
+                                expandedGguf === id
+                                  ? () => {
+                                      const focused =
+                                        focusFirstChildOption(optionKey);
+                                      return focused;
+                                    }
+                                  : undefined
+                              }
+                            />
+                            {expandedGguf === id && (
+                              <GgufVariantExpander
+                                repoId={id}
+                                onSelect={onSelect}
+                                onConfigure={onConfigure}
+                                hfToken={hfToken || undefined}
+                                parentOptionKey={optionKey}
+                                onNavigatePastStart={() =>
+                                  hubModelList.focusOption(optionKey)
+                                }
+                                onNavigatePastEnd={() =>
+                                  hubModelList.moveFocus(optionKey, "next")
+                                }
+                                gpuGb={
+                                  gpu.available ? gpu.memoryTotalGb : undefined
+                                }
+                                systemRamGb={
+                                  gpu.systemRamAvailableGb || undefined
+                                }
+                                variantActions={{
+                                  onDelete: async (quant) => {
+                                    await deleteCachedModel(
+                                      id,
+                                      quant,
+                                      hfToken || undefined,
+                                    );
+                                    prunePinnedQuantValidation(id, quant);
+                                    refreshCachedLists();
+                                  },
+                                }}
+                              />
+                            )}
+                          </div>
+                        );
+                      })
+                    )}
+                    <div ref={sentinelRef} className="h-px" />
+                    {isLoadingMore ? (
+                      <div className="flex items-center justify-center py-2">
+                        <Spinner className="size-3.5 text-muted-foreground" />
+                      </div>
+                    ) : null}
+                  </>
+                ) : null}
+              </>
+            )}
+          </div>
         </div>
-      </div>
-      {/* Floating eject pill: overlaid on the list bottom, outside the scroll
-          so the edge fade never touches it. Only the pill catches clicks. */}
-      {onEject ? (
-        <div className="pointer-events-none absolute inset-x-0 bottom-0 flex justify-end pr-3.5 pb-[19px]">
-          <button
-            type="button"
-            onClick={onEject}
-            className="pointer-events-auto inline-flex items-center justify-center gap-2 rounded-md bg-popover px-3 py-2 text-[13px] font-medium text-destructive shadow-[0_2px_8px_-2px_rgba(0,0,0,0.16)] transition-colors hover:bg-[color-mix(in_srgb,var(--destructive)_12%,var(--popover))] dark:bg-[color-mix(in_srgb,var(--foreground)_10%,var(--sidebar))] dark:shadow-none dark:hover:bg-[color-mix(in_srgb,var(--destructive)_22%,var(--sidebar))]"
-            title="Eject model"
-          >
-            <HugeiconsIcon icon={RemoveCircleIcon} className="size-3.5" />
-            Eject model
-          </button>
-        </div>
-      ) : null}
+        {onEject ? (
+          <div className="pointer-events-none absolute inset-x-0 bottom-0 flex justify-end pr-3.5 pb-[19px]">
+            <button
+              type="button"
+              onClick={onEject}
+              className="pointer-events-auto inline-flex items-center justify-center gap-2 rounded-md bg-popover px-3 py-2 text-ui-13 font-medium text-destructive shadow-[0_2px_8px_-2px_rgba(0,0,0,0.16)] transition-colors hover:bg-[color-mix(in_srgb,var(--destructive)_12%,var(--popover))] dark:bg-[color-mix(in_srgb,var(--foreground)_10%,var(--sidebar))] dark:shadow-none dark:hover:bg-[color-mix(in_srgb,var(--destructive)_22%,var(--sidebar))]"
+              title="Eject model"
+            >
+              <HugeiconsIcon icon={RemoveCircleIcon} className="size-3.5" />
+              Eject model
+            </button>
+          </div>
+        ) : null}
       </div>
       <TransportConflictDialog
         conflict={updateTransportConflict}
@@ -4354,6 +4294,7 @@ function FineTunedRows({
   loadedModelId,
   activeGgufVariant,
   onSelect,
+  onConfigure,
   onModelsChange,
   deleteDisabled = false,
   loraModelList,
@@ -4366,6 +4307,7 @@ function FineTunedRows({
   loadedModelId?: string;
   activeGgufVariant?: string | null;
   onSelect: (id: string, meta: ModelSelectorChangeMeta) => void;
+  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
   deleteDisabled?: boolean;
   loraModelList: ReturnType<typeof useRovingModelList>;
@@ -4390,6 +4332,13 @@ function FineTunedRows({
         const isTrainingFull = isTraining && isMerged;
         const isLocalGgufDir =
           isLocal && (isGgufRepo(adapter.id) || isGgufRepo(adapter.name));
+        const selectionMeta: ModelSelectorChangeMeta = {
+          source: isLocal ? "local" : isExported ? "exported" : "lora",
+          isLora: !isLocal && !isMerged && !isGguf,
+          isDownloaded: true,
+          isGguf: false,
+        };
+        const canConfigure = !(isLocalGgufDir || isExportedGguf);
         const optionKey = makeModelOptionKey("lora", adapter.id);
         const tag = isLocal
           ? isLocalGgufDir
@@ -4437,21 +4386,13 @@ function FineTunedRows({
                         prev === adapter.id ? null : adapter.id,
                       );
                     } else {
-                      onSelect(adapter.id, {
-                        source: isLocal
-                          ? "local"
-                          : isExported
-                            ? "exported"
-                            : "lora",
-                        isLora: !isLocal && !isMerged && !isGguf,
-                        isDownloaded: true,
-                      });
+                      onSelect(adapter.id, selectionMeta);
                     }
                   }}
                   tooltipText={
                     <>
                       <span className="block break-words">{adapter.name}</span>
-                      <span className="block mt-1 text-[10px] text-muted-foreground break-all">
+                      <span className="block mt-1 text-ui-10 text-muted-foreground break-all">
                         {adapter.id}
                       </span>
                     </>
@@ -4466,6 +4407,12 @@ function FineTunedRows({
                   }
                 />
               </div>
+              {canConfigure && onConfigure && (
+                <ModelLoadSettingsAction
+                  ariaLabel={`Inference settings for ${adapter.name}`}
+                  onConfigure={() => onConfigure(adapter.id, selectionMeta)}
+                />
+              )}
               {canDelete && (
                 <ModelDeleteAction
                   ariaLabel={`Delete ${adapter.name}`}
@@ -4496,6 +4443,7 @@ function FineTunedRows({
               <GgufVariantExpander
                 repoId={adapter.id}
                 onSelect={onSelect}
+                onConfigure={onConfigure}
                 parentOptionKey={optionKey}
                 onNavigatePastStart={() => loraModelList.focusOption(optionKey)}
                 onNavigatePastEnd={() =>
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx b/studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
similarity index 96%
rename from studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
index e6da8a7b74..5dd5ca055a 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
@@ -78,13 +78,14 @@ export function PillTabs({
             onValueChange(tabs[next].value);
             e.currentTarget.parentElement
               ?.querySelectorAll<HTMLElement>('button[role="tab"]')
-              [next]?.focus();
+              .item(next)
+              ?.focus();
           }}
           onClick={() => onValueChange(tab.value)}
           className={cn(
             "relative z-10 inline-flex items-center justify-center gap-1.5 rounded-full transition-colors",
             fit ? "shrink-0" : "min-w-0 flex-1",
-            compact ? "h-7 px-2.5 text-[11px]" : "h-9 px-3 text-[12.5px]",
+            compact ? "h-7 px-2.5 text-ui-11" : "h-9 px-3 text-ui-12p5",
             value === tab.value
               ? "text-foreground"
               : "text-muted-foreground hover:text-foreground",
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/pinned-models.ts b/studio/frontend/src/features/model-picker/components/model-selector/pinned-models.ts
similarity index 78%
rename from studio/frontend/src/components/assistant-ui/model-selector/pinned-models.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/pinned-models.ts
index 4835c4c0cf..0444b9f3cc 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/pinned-models.ts
+++ b/studio/frontend/src/features/model-picker/components/model-selector/pinned-models.ts
@@ -21,6 +21,13 @@ export interface PinnedQuantEntry {
   quant: string;
 }
 
+export function makePinRank(
+  pinned: readonly string[],
+): (key: string) => number {
+  const pinIndex = new Map(pinned.map((key, index) => [key, index]));
+  return (key) => pinIndex.get(key) ?? Number.MAX_SAFE_INTEGER;
+}
+
 /** The pinned GGUF quants, in pin order. Plain repo pins are excluded. */
 export function pinnedQuantEntries(pinned: string[]): PinnedQuantEntry[] {
   const out: PinnedQuantEntry[] = [];
@@ -63,10 +70,20 @@ export const usePinnedModelsStore = create<PinnedModelsState>((set) => ({
   togglePinned: (repoId, quant) =>
     set((state) => {
       const key = pinKey(repoId, quant);
+      // Newest pin first, so "Pin to top" literally lands on top of the
+      // pinned group rather than under earlier pins.
       const next = state.pinned.includes(key)
         ? state.pinned.filter((id) => id !== key)
-        : [...state.pinned, key];
+        : [key, ...state.pinned];
       writePinned(next);
       return { pinned: next };
     }),
 }));
+
+if (typeof window !== "undefined") {
+  window.addEventListener("storage", (event) => {
+    if (event.key === KEY || event.key === null) {
+      usePinnedModelsStore.setState({ pinned: readPinned() });
+    }
+  });
+}
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts b/studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts
similarity index 91%
rename from studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts
index 7c2ed266c0..b8fe47c706 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts
+++ b/studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts
@@ -64,9 +64,8 @@ export function matchesFormatFilter(
   }
 }
 
-// First "<n>B" token in a repo id, e.g. "Qwen3-4B-GGUF" -> 4, "gpt-oss-20b" ->
-// 20, "Qwen3-30B-A3B" -> 30 (MoE total), "gemma-4-E4B" -> 4 (effective-param
-// "E" series). The digits must be bounded by a separator so we never read "16"
+// First "<n>B" token in a repo id, e.g. "Qwen3-30B-A3B" -> 30 (MoE total),
+// "gemma-4-E4B" -> 4. Digits must be separator-bounded so we never read "16"
 // from "bf16" or the "2" in "Kimi-K2".
 const PARAM_RE = /(?:^|[-_/. ])[eE]?(\d+(?:\.\d+)?)\s*[bB](?=$|[-_./ ])/;
 
@@ -79,9 +78,8 @@ export function paramsFromId(id: string): number | undefined {
   return Number.isFinite(billions) && billions > 0 ? billions * 1e9 : undefined;
 }
 
-// Smallest practical GGUF/MLX quant (~Q2_K, low-bit). The fit check asks whether
-// a model can run at all, so it uses this rather than a default 4-bit size; a
-// user with a smaller device can still pick a low-bit variant.
+// Smallest practical GGUF/MLX quant (~Q2_K). The fit check asks whether a model
+// can run at all, so it uses this rather than a default 4-bit size.
 const MIN_QUANT_BYTES_PER_PARAM = 0.4;
 
 /** Rough on-disk bytes for the smallest practical quant of `params` weights. */
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/row-meta.ts b/studio/frontend/src/features/model-picker/components/model-selector/row-meta.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/row-meta.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/row-meta.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/source-tabs.ts b/studio/frontend/src/features/model-picker/components/model-selector/source-tabs.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/source-tabs.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/source-tabs.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/types.ts b/studio/frontend/src/features/model-picker/components/model-selector/types.ts
similarity index 74%
rename from studio/frontend/src/components/assistant-ui/model-selector/types.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/types.ts
index 6a86515267..9adf2d899e 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/types.ts
+++ b/studio/frontend/src/features/model-picker/components/model-selector/types.ts
@@ -2,6 +2,7 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import type { ReactNode } from "react";
+import type { PerModelConfig } from "../../model-config/per-model-config";
 
 export interface ModelOption {
   id: string;
@@ -36,6 +37,19 @@ export interface ModelSelectorChangeMeta {
   /** Direct local .gguf file picked without a variant (custom folder / LM
    *  Studio). Marks it as a GGUF source for the deferred-load staging flow. */
   isGguf?: boolean;
+  config?: PerModelConfig;
+  forceReload?: boolean;
+  /** Native path token so an active-model reload can reopen a file-picked GGUF. */
+  nativePathToken?: string;
+  nativePathExpiresAtMs?: number | null;
+}
+
+export interface ModelPickTarget {
+  id: string;
+  displayName: string;
+  ggufVariant?: string | null;
+  isGguf: boolean;
+  meta: ModelSelectorChangeMeta;
 }
 
 export interface DeletedModelRef {
diff --git a/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx b/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
new file mode 100644
index 0000000000..2489927fc2
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
@@ -0,0 +1,113 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { cn } from "@/lib/utils";
+import { useRef, useState } from "react";
+
+export function snapToStep(
+  value: number,
+  step: number,
+  min?: number,
+  max?: number,
+): number {
+  const lo = min ?? Number.NEGATIVE_INFINITY;
+  const hi = max ?? Number.POSITIVE_INFINITY;
+  const clamped = Math.min(Math.max(value, lo), hi);
+  const stepStr = String(step);
+  const decimals = stepStr.includes(".") ? stepStr.split(".")[1].length : 0;
+  const base = Number.isFinite(lo) ? lo : 0;
+  const snapped = base + Math.round((clamped - base) / step) * step;
+  const reclamped = Math.min(Math.max(snapped, lo), hi);
+  return Number(reclamped.toFixed(decimals));
+}
+
+function sanitizeNumeric(raw: string, allowNegative: boolean): string {
+  const sign = allowNegative && raw.startsWith("-") ? "-" : "";
+  const [head, ...rest] = raw.replace(/[^\d.]/g, "").split(".");
+  const tail = rest.length > 0 ? `.${rest.join("")}` : "";
+  return `${sign}${head}${tail}`;
+}
+
+export function NumericValueInput({
+  value,
+  min,
+  max,
+  step,
+  onChange,
+  displayValue,
+  className,
+  ariaLabel,
+  size: sizeAttr,
+  disabled = false,
+}: {
+  value: number;
+  min?: number;
+  max?: number;
+  step: number;
+  onChange: (v: number) => void;
+  displayValue?: string;
+  className?: string;
+  ariaLabel?: string;
+  size?: number;
+  disabled?: boolean;
+}) {
+  const [focused, setFocused] = useState(false);
+  const [draft, setDraft] = useState("");
+  const cancelBlurCommitRef = useRef(false);
+
+  const commit = (raw: string) => {
+    const parsed = Number.parseFloat(raw);
+    if (!Number.isFinite(parsed)) {
+      return;
+    }
+    const final = snapToStep(parsed, step, min, max);
+    if (final !== value) {
+      onChange(final);
+    }
+  };
+
+  const displayed = focused ? draft : (displayValue ?? String(value));
+
+  return (
+    <input
+      type="text"
+      inputMode="decimal"
+      disabled={disabled}
+      size={sizeAttr}
+      style={{
+        boxSizing: "content-box",
+        width: `calc(${Math.max(displayed.length, 4)}ch + 2px)`,
+      }}
+      value={displayed}
+      aria-label={ariaLabel}
+      onFocus={(e) => {
+        cancelBlurCommitRef.current = false;
+        setDraft(String(value));
+        setFocused(true);
+        const target = e.currentTarget;
+        requestAnimationFrame(() => target.select());
+      }}
+      onBlur={() => {
+        if (cancelBlurCommitRef.current) {
+          cancelBlurCommitRef.current = false;
+        } else {
+          commit(draft);
+        }
+        setFocused(false);
+      }}
+      onChange={(e) =>
+        setDraft(sanitizeNumeric(e.target.value, (min ?? 0) < 0))
+      }
+      onKeyDown={(e) => {
+        if (e.key === "Enter") {
+          e.currentTarget.blur();
+        } else if (e.key === "Escape") {
+          cancelBlurCommitRef.current = true;
+          setDraft(String(value));
+          e.currentTarget.blur();
+        }
+      }}
+      className={cn(className)}
+    />
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx b/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
new file mode 100644
index 0000000000..2d12c503a4
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
@@ -0,0 +1,91 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useMemo } from "react";
+import { gpuFieldsSignature } from "../model-config/apply-per-model-config";
+import type { PerModelConfig } from "../model-config/per-model-config";
+import { ModelConfigPage } from "./model-config-page";
+import type { ModelPickTarget } from "./model-selector/types";
+
+interface SidebarModelConfigProps {
+  modelId: string;
+  ggufVariant: string | null;
+  isGguf: boolean;
+  nativeContextLength: number | null;
+  loadedContextLength: number | null;
+  loadedConfig: PerModelConfig;
+  onReload: (config: PerModelConfig) => void;
+}
+
+const TRAILING_SEPARATORS = /[\\/]+$/;
+
+function leafName(id: string): string {
+  const trimmed = id.replace(TRAILING_SEPARATORS, "");
+  const separator = Math.max(
+    trimmed.lastIndexOf("/"),
+    trimmed.lastIndexOf("\\"),
+  );
+  return separator >= 0 ? trimmed.slice(separator + 1) : trimmed;
+}
+
+function hashString(value: string): number {
+  let hash = 5381;
+  for (let i = 0; i < value.length; i += 1) {
+    hash = (Math.imul(hash, 33) ^ value.charCodeAt(i)) >>> 0;
+  }
+  return hash;
+}
+
+function configSignature(config: PerModelConfig): string {
+  return [
+    config.customContextLength ?? "",
+    config.maxSeqLength ?? "",
+    config.kvCacheDtype ?? "",
+    config.speculativeType ?? "",
+    config.specDraftNMax ?? "",
+    config.tensorParallel ? "1" : "0",
+    config.chatTemplateOverride == null
+      ? ""
+      : `${config.chatTemplateOverride.length}:${hashString(config.chatTemplateOverride)}`,
+    gpuFieldsSignature(config),
+  ].join("|");
+}
+
+export function SidebarModelConfig({
+  modelId,
+  ggufVariant,
+  isGguf,
+  nativeContextLength,
+  loadedContextLength,
+  loadedConfig,
+  onReload,
+}: SidebarModelConfigProps) {
+  const target = useMemo<ModelPickTarget>(() => {
+    const leaf = leafName(modelId);
+    return {
+      id: modelId,
+      displayName: ggufVariant ? `${leaf} · ${ggufVariant}` : leaf,
+      ggufVariant,
+      isGguf,
+      meta: {
+        source: "local",
+        isLora: false,
+        ggufVariant: ggufVariant ?? undefined,
+        isGguf,
+        isDownloaded: true,
+        contextLength: nativeContextLength,
+      },
+    };
+  }, [modelId, ggufVariant, isGguf, nativeContextLength]);
+
+  return (
+    <ModelConfigPage
+      key={`${modelId}::${ggufVariant ?? ""}::${configSignature(loadedConfig)}`}
+      target={target}
+      onRun={onReload}
+      loadedConfig={loadedConfig}
+      loadedContextLength={loadedContextLength}
+      variant="sidebar"
+    />
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/hooks/use-active-model-config.ts b/studio/frontend/src/features/model-picker/hooks/use-active-model-config.ts
new file mode 100644
index 0000000000..9d09ee6897
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/hooks/use-active-model-config.ts
@@ -0,0 +1,77 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { isExternalModelId, useChatRuntimeStore } from "@/features/chat";
+import { useMemo } from "react";
+import type { PerModelConfig } from "../model-config/per-model-config";
+
+export interface ActiveModelConfigState {
+  checkpoint: string | null;
+  isGguf: boolean;
+  config: PerModelConfig | null;
+}
+
+export function useActiveModelConfig(): ActiveModelConfigState {
+  const checkpoint = useChatRuntimeStore((s) => s.params.checkpoint) || null;
+  const maxSeqLength = useChatRuntimeStore((s) => s.params.maxSeqLength);
+  const activeGgufVariant = useChatRuntimeStore((s) => s.activeGgufVariant);
+  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
+  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
+  const kvCacheDtype = useChatRuntimeStore((s) => s.kvCacheDtype);
+  const speculativeType = useChatRuntimeStore((s) => s.speculativeType);
+  const specDraftNMax = useChatRuntimeStore((s) => s.specDraftNMax);
+  const tensorParallel = useChatRuntimeStore((s) => s.tensorParallel);
+  const chatTemplateOverride = useChatRuntimeStore(
+    (s) => s.chatTemplateOverride,
+  );
+  const gpuMemoryMode = useChatRuntimeStore((s) => s.gpuMemoryMode);
+  const gpuLayers = useChatRuntimeStore((s) => s.gpuLayers);
+  const nCpuMoe = useChatRuntimeStore((s) => s.nCpuMoe);
+  const selectedGpuIds = useChatRuntimeStore((s) => s.selectedGpuIds);
+
+  const isGguf =
+    activeGgufVariant != null ||
+    ggufContextLength != null ||
+    (checkpoint?.toLowerCase().endsWith(".gguf") ?? false);
+
+  const config = useMemo<PerModelConfig | null>(() => {
+    if (!checkpoint || isExternalModelId(checkpoint)) {
+      return null;
+    }
+    const base: PerModelConfig = {
+      customContextLength: customContextLength ?? null,
+      maxSeqLength: isGguf ? null : maxSeqLength,
+      kvCacheDtype: kvCacheDtype ?? null,
+      speculativeType: speculativeType ?? "auto",
+      specDraftNMax: specDraftNMax ?? null,
+      tensorParallel: tensorParallel ?? false,
+      chatTemplateOverride: chatTemplateOverride ?? null,
+    };
+    if (!isGguf) {
+      return base;
+    }
+    return {
+      ...base,
+      gpuMemoryMode,
+      gpuLayers,
+      nCpuMoe,
+      selectedGpuIds,
+    };
+  }, [
+    checkpoint,
+    isGguf,
+    maxSeqLength,
+    customContextLength,
+    kvCacheDtype,
+    speculativeType,
+    specDraftNMax,
+    tensorParallel,
+    chatTemplateOverride,
+    gpuMemoryMode,
+    gpuLayers,
+    nCpuMoe,
+    selectedGpuIds,
+  ]);
+
+  return { checkpoint, isGguf, config };
+}
diff --git a/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts b/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
new file mode 100644
index 0000000000..530e6e06d8
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
@@ -0,0 +1,191 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useHfTokenStore, useInventoryVersion } from "@/features/hub";
+import { useEffect, useState } from "react";
+import { fetchModelMaxPositionEmbeddings } from "../api/model-metadata";
+import { fetchDefaultChatTemplate } from "../api/templates";
+
+export interface DefaultChatTemplateState {
+  template: string | null;
+  loading: boolean;
+  error: string | null;
+}
+
+export interface ModelMaxPositionState {
+  maxPositionEmbeddings: number | null;
+  loading: boolean;
+  error: string | null;
+}
+
+const TEMPLATE_CACHE_MAX_ENTRIES = 50;
+const templateCache = new Map<string, string | null>();
+const maxPositionCache = new Map<string, number | null>();
+
+function cacheTemplate(key: string, template: string | null): void {
+  templateCache.delete(key);
+  templateCache.set(key, template);
+  while (templateCache.size > TEMPLATE_CACHE_MAX_ENTRIES) {
+    const oldest = templateCache.keys().next().value;
+    if (oldest === undefined) {
+      break;
+    }
+    templateCache.delete(oldest);
+  }
+}
+
+function cacheMaxPosition(key: string, value: number | null): void {
+  maxPositionCache.delete(key);
+  maxPositionCache.set(key, value);
+  while (maxPositionCache.size > TEMPLATE_CACHE_MAX_ENTRIES) {
+    const oldest = maxPositionCache.keys().next().value;
+    if (oldest === undefined) {
+      break;
+    }
+    maxPositionCache.delete(oldest);
+  }
+}
+
+export function useDefaultChatTemplate(
+  modelId: string | null,
+  ggufVariant: string | null | undefined,
+  enabled: boolean,
+  nativePathToken?: string | null,
+): DefaultChatTemplateState {
+  const token = useHfTokenStore((s) => s.token);
+  const inventoryVersion = useInventoryVersion();
+  // The native token is part of the identity: a picked GGUF resolves its
+  // template through the lease, not the model id, so two picks of the same
+  // basename must not share a cache entry.
+  const cacheKey =
+    enabled && modelId
+      ? `${modelId}::${ggufVariant ?? ""}::${token}::${inventoryVersion}::${nativePathToken ?? ""}`
+      : null;
+  const [fetched, setFetched] = useState<{
+    key: string;
+    state: DefaultChatTemplateState;
+  } | null>(null);
+
+  useEffect(() => {
+    if (cacheKey == null || !modelId || templateCache.has(cacheKey)) {
+      return;
+    }
+    const controller = new AbortController();
+    fetchDefaultChatTemplate(
+      modelId,
+      ggufVariant,
+      token,
+      controller.signal,
+      nativePathToken,
+    )
+      .then((template) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        // Cache the terminal result, including a null "no default template",
+        // so reopening the viewer for such a model reuses it instead of
+        // re-running the backend/Hugging Face lookup every time.
+        cacheTemplate(cacheKey, template);
+        setFetched({
+          key: cacheKey,
+          state: { template, loading: false, error: null },
+        });
+      })
+      .catch((err: unknown) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        setFetched({
+          key: cacheKey,
+          state: {
+            template: null,
+            loading: false,
+            error:
+              err instanceof Error ? err.message : "Failed to load template",
+          },
+        });
+      });
+
+    return () => controller.abort();
+  }, [cacheKey, modelId, ggufVariant, token, nativePathToken]);
+
+  if (cacheKey == null) {
+    return { template: null, loading: false, error: null };
+  }
+  if (templateCache.has(cacheKey)) {
+    return {
+      template: templateCache.get(cacheKey) ?? null,
+      loading: false,
+      error: null,
+    };
+  }
+  if (fetched?.key === cacheKey) {
+    return fetched.state;
+  }
+  return { template: null, loading: true, error: null };
+}
+
+export function useModelMaxPositionEmbeddings(
+  modelId: string | null,
+  enabled: boolean,
+): ModelMaxPositionState {
+  const token = useHfTokenStore((s) => s.token);
+  const inventoryVersion = useInventoryVersion();
+  const cacheKey =
+    enabled && modelId ? `${modelId}::${token}::${inventoryVersion}` : null;
+  const [fetched, setFetched] = useState<{
+    key: string;
+    state: ModelMaxPositionState;
+  } | null>(null);
+
+  useEffect(() => {
+    if (cacheKey == null || !modelId || maxPositionCache.has(cacheKey)) {
+      return;
+    }
+    const controller = new AbortController();
+    fetchModelMaxPositionEmbeddings(modelId, token, controller.signal)
+      .then((maxPositionEmbeddings) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        cacheMaxPosition(cacheKey, maxPositionEmbeddings);
+        setFetched({
+          key: cacheKey,
+          state: { maxPositionEmbeddings, loading: false, error: null },
+        });
+      })
+      .catch((err: unknown) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        setFetched({
+          key: cacheKey,
+          state: {
+            maxPositionEmbeddings: null,
+            loading: false,
+            error:
+              err instanceof Error
+                ? err.message
+                : "Failed to load model metadata",
+          },
+        });
+      });
+
+    return () => controller.abort();
+  }, [cacheKey, modelId, token]);
+
+  if (cacheKey == null) {
+    return { maxPositionEmbeddings: null, loading: false, error: null };
+  }
+  if (maxPositionCache.has(cacheKey)) {
+    return {
+      maxPositionEmbeddings: maxPositionCache.get(cacheKey) ?? null,
+      loading: false,
+      error: null,
+    };
+  }
+  if (fetched?.key === cacheKey) {
+    return fetched.state;
+  }
+  return { maxPositionEmbeddings: null, loading: true, error: null };
+}
diff --git a/studio/frontend/src/features/model-picker/index.ts b/studio/frontend/src/features/model-picker/index.ts
new file mode 100644
index 0000000000..d2b4785ec3
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/index.ts
@@ -0,0 +1,39 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+export { ModelSelector } from "./components/model-selector";
+export { FolderBrowser } from "./components/model-selector/folder-browser";
+export { ModelRowMenu } from "./components/model-selector/model-row-menu";
+export {
+  makePinRank,
+  pinKey,
+  usePinnedModelsStore,
+} from "./components/model-selector/pinned-models";
+export { hfModelFitsDevice } from "./components/model-selector/recommended-fit";
+export {
+  NumericValueInput,
+  snapToStep,
+} from "./components/numeric-value-input";
+export { SidebarModelConfig } from "./components/sidebar-model-config";
+export {
+  useActiveModelConfig,
+} from "./hooks/use-active-model-config";
+export type {
+  DeletedModelRef,
+  ExternalModelOption,
+  LoraModelOption,
+  ModelOption,
+  ModelSelectorChangeMeta,
+} from "./components/model-selector";
+export {
+  applyModelLoadConfigToRuntime,
+  applyPerModelConfigToRuntime,
+  currentRuntimePerModelConfig,
+  perModelConfigsEqual,
+} from "./model-config/apply-per-model-config";
+export {
+  DEFAULT_MAX_SEQ_LENGTH,
+  normalizeMaxSeqLength,
+  type PerModelConfig,
+  resolveInitialConfig,
+} from "./model-config/per-model-config";
diff --git a/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts b/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
new file mode 100644
index 0000000000..b46e83819c
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
@@ -0,0 +1,123 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import type {
+  CachedGgufRepo,
+  CachedModelRepo,
+  LocalModelInfo,
+} from "@/features/chat";
+import {
+  type CachedInventoryRow,
+  type LocalInventoryRow,
+  type LocalSource,
+  isHiddenModelId,
+  useHubInventory,
+} from "@/features/hub";
+import { useMemo } from "react";
+
+const PICKER_LOCAL_SOURCES: ReadonlySet<LocalSource> = new Set([
+  "lmstudio",
+  "models_dir",
+  "custom",
+]);
+
+function isCompleteCachedRow(row: CachedInventoryRow): boolean {
+  return !row.partial && !row.liveDownload;
+}
+
+function toCachedGgufRepo(row: CachedInventoryRow): CachedGgufRepo {
+  return {
+    repo_id: row.repoId,
+    size_bytes: row.bytes,
+    cache_path: row.cachePath ?? "",
+    last_modified: row.lastModified ?? undefined,
+    has_vision: row.capabilities.supportsVision,
+  };
+}
+
+function toCachedModelRepo(row: CachedInventoryRow): CachedModelRepo {
+  return {
+    repo_id: row.repoId,
+    size_bytes: row.bytes,
+    last_modified: row.lastModified ?? undefined,
+  };
+}
+
+function toLocalModelInfo(row: LocalInventoryRow): LocalModelInfo {
+  return {
+    id: row.loadId,
+    display_name: row.displayName ?? row.title,
+    path: row.path,
+    source: row.source as LocalModelInfo["source"],
+    model_id: row.modelId ?? row.repoId,
+    model_format: row.modelFormat,
+    updated_at: row.updatedAt,
+  };
+}
+
+export interface ChatPickerInventory {
+  cachedGguf: CachedGgufRepo[];
+  cachedModels: CachedModelRepo[];
+  cachedReady: boolean;
+  localModels: LocalModelInfo[];
+  refreshInventory: () => Promise<void>;
+}
+
+export function useChatPickerInventory(
+  options: { enabled?: boolean } = {},
+): ChatPickerInventory {
+  const inventory = useHubInventory({
+    kind: "models",
+    enabled: options.enabled,
+    includeLocal: true,
+  });
+
+  const cachedGguf = useMemo(
+    () =>
+      inventory.cachedRows
+        .filter(
+          (row) =>
+            row.modelFormat === "gguf" &&
+            isCompleteCachedRow(row) &&
+            !isHiddenModelId(row.repoId),
+        )
+        .map(toCachedGgufRepo),
+    [inventory.cachedRows],
+  );
+  const cachedModels = useMemo(
+    () =>
+      inventory.cachedRows
+        .filter(
+          (row) =>
+            row.modelFormat !== "gguf" &&
+            isCompleteCachedRow(row) &&
+            !isHiddenModelId(row.repoId),
+        )
+        .map(toCachedModelRepo),
+    [inventory.cachedRows],
+  );
+  const localModels = useMemo(
+    () =>
+      inventory.localRows
+        .filter(
+          (row) =>
+            PICKER_LOCAL_SOURCES.has(row.source) &&
+            // Skip non-chat rows (e.g. a folder with only config.json is
+            // classified "unknown" -> canChat false); selecting one would try to
+            // load a weightless path. toLocalModelInfo drops capabilities, so
+            // this is the only place the guard can live.
+            row.capabilities.canChat &&
+            !isHiddenModelId(row.modelId, row.repoId, row.path),
+        )
+        .map(toLocalModelInfo),
+    [inventory.localRows],
+  );
+
+  return {
+    cachedGguf,
+    cachedModels,
+    cachedReady: inventory.downloadedReady,
+    localModels,
+    refreshInventory: inventory.refreshInventory,
+  };
+}
diff --git a/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts b/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
new file mode 100644
index 0000000000..c21d3e164a
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
@@ -0,0 +1,127 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  GPU_LAYERS_AUTO,
+  defaultInferenceParams,
+  normalizeSpeculativeType,
+  readPersistedGpuMemoryMode,
+  readPersistedSpeculativeType,
+  reconcilePersistedGpuIds,
+  useChatRuntimeStore,
+} from "@/features/chat";
+import {
+  DEFAULT_PER_MODEL_CONFIG,
+  type PerModelConfig,
+  normalizeMaxSeqLength,
+} from "./per-model-config";
+
+function cleanTemplate(value: string | null | undefined): string | null {
+  return value?.trim() ? value : null;
+}
+
+export function applyPerModelConfigToRuntime(config: PerModelConfig): void {
+  // Fall back to the standing default when the model has no saved
+  // maxSeqLength. maxSeqLength is the only per-model field carried on
+  // params (the rest are reset below), so without this a model with no
+  // remembered config would inherit the previously loaded model's value.
+  const maxSeqLength =
+    normalizeMaxSeqLength(config.maxSeqLength) ??
+    defaultInferenceParams.maxSeqLength;
+  const store = useChatRuntimeStore.getState();
+  if (maxSeqLength !== store.params.maxSeqLength) {
+    store.setParams({ ...store.params, maxSeqLength });
+  }
+  useChatRuntimeStore.setState({
+    customContextLength: config.customContextLength ?? null,
+    kvCacheDtype: config.kvCacheDtype ?? null,
+    speculativeType:
+      normalizeSpeculativeType(config.speculativeType) ??
+      readPersistedSpeculativeType(),
+    specDraftNMax: config.specDraftNMax ?? null,
+    tensorParallel: config.tensorParallel ?? false,
+    chatTemplateOverride: cleanTemplate(config.chatTemplateOverride),
+    // GPU Memory knobs are per-model (GGUF-only). Absent = defaults; the mode is
+    // a standing preference so an absent mode falls back to the persisted one.
+    // The per-GPU split ratio is never remembered, so it always resets. The GPU
+    // pick is reconciled against the GPUs present now (a saved [1] on a 1-GPU
+    // host would otherwise be sent and rejected).
+    gpuMemoryMode: config.gpuMemoryMode ?? readPersistedGpuMemoryMode(),
+    gpuLayers: config.gpuLayers ?? GPU_LAYERS_AUTO,
+    nCpuMoe: config.nCpuMoe ?? 0,
+    splitRatio: null,
+    selectedGpuIds:
+      config.selectedGpuIds !== undefined
+        ? reconcilePersistedGpuIds(config.selectedGpuIds)
+        : null,
+  });
+}
+
+export function applyModelLoadConfigToRuntime(
+  config: PerModelConfig | null | undefined,
+): boolean {
+  const hasConfig = config != null;
+  applyPerModelConfigToRuntime(config ?? DEFAULT_PER_MODEL_CONFIG);
+  return hasConfig;
+}
+
+export function currentRuntimePerModelConfig(
+  options: { includeMaxSeqLength?: boolean } = {},
+): PerModelConfig {
+  const s = useChatRuntimeStore.getState();
+  return {
+    customContextLength: s.customContextLength ?? null,
+    maxSeqLength: options.includeMaxSeqLength
+      ? normalizeMaxSeqLength(s.params.maxSeqLength)
+      : null,
+    kvCacheDtype: s.kvCacheDtype ?? null,
+    speculativeType: normalizeSpeculativeType(s.speculativeType),
+    specDraftNMax: s.specDraftNMax ?? null,
+    tensorParallel: s.tensorParallel ?? false,
+    chatTemplateOverride: cleanTemplate(s.chatTemplateOverride),
+    // Snapshot the live GPU knobs too so a failed switch rolls the previous
+    // model's GPU Memory settings back (see applyPerModelConfigToRuntime). The
+    // split ratio is intentionally never remembered.
+    gpuMemoryMode: s.gpuMemoryMode,
+    gpuLayers: s.gpuLayers,
+    nCpuMoe: s.nCpuMoe,
+    selectedGpuIds: s.selectedGpuIds,
+  };
+}
+
+export function perModelConfigsEqual(
+  a: PerModelConfig,
+  b: PerModelConfig,
+): boolean {
+  return (
+    (a.customContextLength ?? null) === (b.customContextLength ?? null) &&
+    normalizeMaxSeqLength(a.maxSeqLength) ===
+      normalizeMaxSeqLength(b.maxSeqLength) &&
+    (a.kvCacheDtype ?? null) === (b.kvCacheDtype ?? null) &&
+    normalizeSpeculativeType(a.speculativeType) ===
+      normalizeSpeculativeType(b.speculativeType) &&
+    (a.specDraftNMax ?? null) === (b.specDraftNMax ?? null) &&
+    Boolean(a.tensorParallel) === Boolean(b.tensorParallel) &&
+    cleanTemplate(a.chatTemplateOverride) ===
+      cleanTemplate(b.chatTemplateOverride) &&
+    gpuFieldsEqual(a, b)
+  );
+}
+
+// Serialize the per-model GPU knobs with the same "absent == default"
+// coalescing the store applies: mode auto/absent, gpuLayers Auto (< 0) /
+// absent, nCpuMoe 0 / absent, and the GPU pick (null / absent = all GPUs).
+export function gpuFieldsSignature(config: PerModelConfig): string {
+  return [
+    config.gpuMemoryMode ?? "auto",
+    config.gpuLayers == null || config.gpuLayers < 0 ? -1 : config.gpuLayers,
+    config.nCpuMoe ?? 0,
+    config.selectedGpuIds == null
+      ? "all"
+      : [...config.selectedGpuIds].sort((a, b) => a - b).join(","),
+  ].join("|");
+}
+
+function gpuFieldsEqual(a: PerModelConfig, b: PerModelConfig): boolean {
+  return gpuFieldsSignature(a) === gpuFieldsSignature(b);
+}
diff --git a/studio/frontend/src/features/model-picker/model-config/model-identity.ts b/studio/frontend/src/features/model-picker/model-config/model-identity.ts
new file mode 100644
index 0000000000..0caa7c1312
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/model-config/model-identity.ts
@@ -0,0 +1,69 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "@/features/hub";
+
+export {
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "@/features/hub";
+
+const MODEL_STORAGE_KEY_PREFIX = "v2:";
+
+type ParsedModelStorageKey = {
+  modelId: string;
+  ggufVariant: string;
+};
+
+function parseVersionedModelStorageKey(
+  key: string,
+): ParsedModelStorageKey | null {
+  if (!key.startsWith(MODEL_STORAGE_KEY_PREFIX)) {
+    return null;
+  }
+  try {
+    const parsed = JSON.parse(key.slice(MODEL_STORAGE_KEY_PREFIX.length));
+    if (
+      !Array.isArray(parsed) ||
+      parsed.length !== 2 ||
+      typeof parsed[0] !== "string" ||
+      typeof parsed[1] !== "string"
+    ) {
+      return null;
+    }
+    return { modelId: parsed[0], ggufVariant: parsed[1] };
+  } catch {
+    return null;
+  }
+}
+
+export function modelStorageKey(
+  modelId: string,
+  ggufVariant?: string | null,
+): string {
+  return `${MODEL_STORAGE_KEY_PREFIX}${JSON.stringify([
+    normalizeModelIdentity(modelId),
+    normalizeGgufVariantIdentity(ggufVariant),
+  ])}`;
+}
+
+export function modelIdFromStorageKey(key: string): string | null {
+  const parsed = parseVersionedModelStorageKey(key);
+  if (parsed) {
+    return parsed.modelId;
+  }
+  const separator = key.lastIndexOf("::");
+  return separator >= 0 ? key.slice(0, separator) : null;
+}
+
+export function ggufVariantFromStorageKey(key: string): string | null {
+  const parsed = parseVersionedModelStorageKey(key);
+  if (parsed) {
+    return parsed.ggufVariant;
+  }
+  const separator = key.lastIndexOf("::");
+  return separator >= 0 ? key.slice(separator + 2) : null;
+}
diff --git a/studio/frontend/src/features/model-picker/model-config/per-model-config.ts b/studio/frontend/src/features/model-picker/model-config/per-model-config.ts
new file mode 100644
index 0000000000..0b03423736
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/model-config/per-model-config.ts
@@ -0,0 +1,665 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  ggufVariantFromStorageKey,
+  modelIdFromStorageKey,
+  modelStorageKey,
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "./model-identity";
+
+export interface PerModelConfig {
+  customContextLength: number | null;
+  maxSeqLength: number | null;
+  kvCacheDtype: string | null;
+  speculativeType: string | null;
+  specDraftNMax: number | null;
+  tensorParallel: boolean;
+  chatTemplateOverride: string | null;
+  // GPU Memory controls (per-model, GGUF-only), optional so older blobs still
+  // parse. null selectedGpuIds (all GPUs) is distinct from absent. The --tensor-split
+  // ratio is deliberately not remembered: it is positionally bound to the exact
+  // GPU set/order and unvalidated.
+  gpuMemoryMode?: "auto" | "manual";
+  gpuLayers?: number;
+  nCpuMoe?: number;
+  selectedGpuIds?: number[] | null;
+}
+
+export const DEFAULT_PER_MODEL_CONFIG: PerModelConfig = {
+  customContextLength: null,
+  maxSeqLength: null,
+  kvCacheDtype: null,
+  speculativeType: null,
+  specDraftNMax: null,
+  tensorParallel: false,
+  chatTemplateOverride: null,
+};
+
+export const MAX_SEQ_LENGTH_MIN = 128;
+export const MAX_SEQ_LENGTH_MAX = 1048576;
+export const MAX_SEQ_LENGTH_STEP = 128;
+// App-default max sequence length when a non-GGUF model has no override. Both
+// paths fall back to this rather than an active model's runtime value, so an
+// unconfigured pane never inherits another model's larger context and OOMs.
+export const DEFAULT_MAX_SEQ_LENGTH = 4096;
+export const CONTEXT_LENGTH_MIN = 128;
+
+export const KV_CACHE_DTYPES = ["bf16", "q8_0", "q5_1", "q4_1"] as const;
+const VALID_KV_CACHE_DTYPES = new Set<string>(KV_CACHE_DTYPES);
+
+export const SPECULATIVE_TYPES = [
+  "auto",
+  "mtp",
+  "ngram",
+  "mtp+ngram",
+  "off",
+] as const;
+export const MTP_SPECULATIVE_TYPES: ReadonlySet<string> = new Set([
+  "mtp",
+  "mtp+ngram",
+]);
+
+const STORAGE_KEY = "unsloth_model_configs";
+const LEGACY_STORAGE_KEY = "unsloth_load_settings";
+const LEGACY_MIGRATION_FLAG = "unsloth_model_configs_migrated";
+const STORAGE_SCHEMA_VERSION = 1;
+const MAX_ENTRIES = 500;
+const MAX_PER_MODEL_CONFIG_STORAGE_BYTES = 1024 * 1024;
+export const MAX_CHAT_TEMPLATE_BYTES = 65_536;
+
+type StoredPerModelConfig = PerModelConfig & {
+  version: typeof STORAGE_SCHEMA_VERSION;
+};
+type StoredMap = Record<string, PerModelConfig | StoredPerModelConfig>;
+type RawConfig = Partial<PerModelConfig> & { version?: unknown };
+
+const STORED_CONFIG_FIELDS = new Set([
+  "version",
+  "customContextLength",
+  "maxSeqLength",
+  "kvCacheDtype",
+  "speculativeType",
+  "specDraftNMax",
+  "tensorParallel",
+  "chatTemplateOverride",
+  "gpuMemoryMode",
+  "gpuLayers",
+  "nCpuMoe",
+  "selectedGpuIds",
+]);
+
+function normalizeGpuFields(partial: RawConfig): {
+  gpuMemoryMode?: "auto" | "manual";
+  gpuLayers?: number;
+  nCpuMoe?: number;
+  selectedGpuIds?: number[] | null;
+} {
+  const out: {
+    gpuMemoryMode?: "auto" | "manual";
+    gpuLayers?: number;
+    nCpuMoe?: number;
+    selectedGpuIds?: number[] | null;
+  } = {};
+  // Only "manual" is a real override; persisting "auto" would pin the model and
+  // stop it following later changes to the global GPU Memory preference.
+  if (partial.gpuMemoryMode === "manual") {
+    out.gpuMemoryMode = "manual";
+  }
+  if (
+    typeof partial.gpuLayers === "number" &&
+    Number.isFinite(partial.gpuLayers)
+  ) {
+    out.gpuLayers = Math.trunc(partial.gpuLayers);
+  }
+  if (
+    typeof partial.nCpuMoe === "number" &&
+    Number.isFinite(partial.nCpuMoe) &&
+    partial.nCpuMoe >= 0
+  ) {
+    out.nCpuMoe = Math.trunc(partial.nCpuMoe);
+  }
+  if (partial.selectedGpuIds === null) {
+    out.selectedGpuIds = null;
+  } else if (
+    Array.isArray(partial.selectedGpuIds) &&
+    partial.selectedGpuIds.every(
+      (n) => typeof n === "number" && Number.isFinite(n),
+    )
+  ) {
+    out.selectedGpuIds = partial.selectedGpuIds.map((n) => Math.trunc(n));
+  }
+  return out;
+}
+
+function canonicalizeSpeculativeType(value: string): string | null {
+  const s = value.trim().toLowerCase();
+  if (!s) {
+    return null;
+  }
+  // "auto"/"default" is the follow-global sentinel; store as null so it is never
+  // persisted as an override and global speculative-decoding changes keep applying.
+  if (s === "auto" || s === "default") {
+    return null;
+  }
+  if (s === "off") {
+    return "off";
+  }
+  if (s === "mtp" || s === "draft-mtp") {
+    return "mtp";
+  }
+  if (s === "ngram" || s === "ngram-mod" || s === "ngram-simple") {
+    return "ngram";
+  }
+  if (s === "mtp+ngram") {
+    return "mtp+ngram";
+  }
+  return null;
+}
+
+export function normalizeMaxSeqLength(value: unknown): number | null {
+  if (typeof value !== "number" || !Number.isFinite(value) || value <= 0) {
+    return null;
+  }
+  const snapped = Math.round(value / MAX_SEQ_LENGTH_STEP) * MAX_SEQ_LENGTH_STEP;
+  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(MAX_SEQ_LENGTH_MAX, snapped));
+}
+
+export function floorMaxSeqLength(value: unknown): number | null {
+  if (typeof value !== "number" || !Number.isFinite(value) || value <= 0) {
+    return null;
+  }
+  const snapped = Math.floor(value / MAX_SEQ_LENGTH_STEP) * MAX_SEQ_LENGTH_STEP;
+  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(MAX_SEQ_LENGTH_MAX, snapped));
+}
+
+function canUseStorage(): boolean {
+  return typeof window !== "undefined";
+}
+
+function serializedByteLength(value: string): number {
+  return typeof TextEncoder !== "undefined"
+    ? new TextEncoder().encode(value).byteLength
+    : value.length;
+}
+
+export function chatTemplateByteLength(value: string): number {
+  return serializedByteLength(value);
+}
+
+export function isChatTemplateWithinLimit(value: string): boolean {
+  return chatTemplateByteLength(value) <= MAX_CHAT_TEMPLATE_BYTES;
+}
+
+function serializedMapSize(map: StoredMap): number {
+  return serializedByteLength(JSON.stringify(map));
+}
+
+function serializedMapEntrySize(key: string, value: StoredMap[string]): number {
+  return (
+    serializedByteLength(JSON.stringify(key)) +
+    1 +
+    serializedByteLength(JSON.stringify(value))
+  );
+}
+
+function deleteOldestEvictableEntry(
+  map: StoredMap,
+  protectedKeys?: ReadonlySet<string>,
+): { key: string; value: StoredMap[string] } | null {
+  for (const key of Object.keys(map)) {
+    // Never evict a future-schema entry an older client cannot interpret.
+    if (
+      protectedKeys?.has(key) ||
+      storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION
+    ) {
+      continue;
+    }
+    const value = map[key];
+    delete map[key];
+    return { key, value };
+  }
+  return null;
+}
+
+function enforceStorageBudget(
+  map: StoredMap,
+  protectedKeys?: ReadonlySet<string>,
+): boolean {
+  let entryCount = Object.keys(map).length;
+  while (entryCount > MAX_ENTRIES) {
+    if (!deleteOldestEvictableEntry(map, protectedKeys)) {
+      return false;
+    }
+    entryCount -= 1;
+  }
+  let bytes = serializedMapSize(map);
+  while (bytes > MAX_PER_MODEL_CONFIG_STORAGE_BYTES) {
+    const removed = deleteOldestEvictableEntry(map, protectedKeys);
+    if (!removed) {
+      return false;
+    }
+    bytes -=
+      serializedMapEntrySize(removed.key, removed.value) +
+      (entryCount > 1 ? 1 : 0);
+    entryCount -= 1;
+  }
+  return true;
+}
+
+function storedConfigVersion(raw: unknown): number {
+  if (!raw || typeof raw !== "object" || Array.isArray(raw)) {
+    return 0;
+  }
+  const version = (raw as RawConfig).version;
+  return typeof version === "number" && Number.isFinite(version) ? version : 0;
+}
+
+let legacyMigrationChecked = false;
+
+function parseLegacyModelKey(
+  key: string,
+): { modelId: string; ggufVariant: string | null } | null {
+  const separator = key.lastIndexOf("::");
+  if (separator >= 0) {
+    const modelId = key.slice(0, separator);
+    return modelId
+      ? { modelId, ggufVariant: key.slice(separator + 2) || null }
+      : null;
+  }
+  return key ? { modelId: key, ggufVariant: null } : null;
+}
+
+function legacyEntryToConfig(raw: Record<string, unknown>): PerModelConfig {
+  return normalizeV1({
+    customContextLength:
+      typeof raw.contextLength === "number" ? raw.contextLength : null,
+    maxSeqLength: null,
+    kvCacheDtype:
+      typeof raw.kvCacheDtype === "string" ? raw.kvCacheDtype : null,
+    speculativeType:
+      typeof raw.speculativeType === "string" ? raw.speculativeType : null,
+    specDraftNMax:
+      typeof raw.specDraftNMax === "number" ? raw.specDraftNMax : null,
+    tensorParallel:
+      typeof raw.tensorParallel === "boolean" ? raw.tensorParallel : false,
+    chatTemplateOverride: null,
+    // Carry legacy GPU Memory knobs; normalizeGpuFields drops anything malformed.
+    gpuMemoryMode:
+      raw.gpuMemoryMode === "auto" || raw.gpuMemoryMode === "manual"
+        ? raw.gpuMemoryMode
+        : undefined,
+    gpuLayers: typeof raw.gpuLayers === "number" ? raw.gpuLayers : undefined,
+    nCpuMoe: typeof raw.nCpuMoe === "number" ? raw.nCpuMoe : undefined,
+    selectedGpuIds:
+      raw.selectedGpuIds === null
+        ? null
+        : Array.isArray(raw.selectedGpuIds)
+          ? (raw.selectedGpuIds as number[])
+          : undefined,
+  });
+}
+
+function mergeLegacyEntries(
+  map: StoredMap,
+  legacy: Record<string, unknown>,
+): string[] {
+  const addedKeys: string[] = [];
+  for (const [legacyKey, value] of Object.entries(legacy)) {
+    if (!value || typeof value !== "object") {
+      continue;
+    }
+    const parsedKey = parseLegacyModelKey(legacyKey);
+    if (!parsedKey) {
+      continue;
+    }
+    const migrated = legacyEntryToConfig(value as Record<string, unknown>);
+    const key = modelStorageKey(parsedKey.modelId, parsedKey.ggufVariant);
+    if (isDefaultConfig(migrated) || Object.hasOwn(map, key)) {
+      continue;
+    }
+    map[key] = toStoredConfig(migrated);
+    addedKeys.push(key);
+  }
+  return addedKeys;
+}
+
+function migrateLegacyLoadSettingsOnce(): void {
+  if (legacyMigrationChecked || !canUseStorage()) {
+    return;
+  }
+  legacyMigrationChecked = true;
+  try {
+    if (localStorage.getItem(LEGACY_MIGRATION_FLAG)) {
+      return;
+    }
+    let legacy: unknown = null;
+    try {
+      legacy = JSON.parse(localStorage.getItem(LEGACY_STORAGE_KEY) ?? "null");
+    } catch {
+      legacy = null;
+    }
+    if (!legacy || typeof legacy !== "object" || Array.isArray(legacy)) {
+      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
+      return;
+    }
+    const map = readMapRaw();
+    // Snapshot existing entries so eviction can protect them: importing old load
+    // settings must never discard a newer per-model config the user already has.
+    const existingKeys = new Set(Object.keys(map));
+    const migratedKeys = mergeLegacyEntries(
+      map,
+      legacy as Record<string, unknown>,
+    );
+    if (migratedKeys.length === 0) {
+      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
+      return;
+    }
+    // Protect pre-existing entries so only just-migrated legacy entries are
+    // dropped when over budget.
+    if (!enforceStorageBudget(map, existingKeys)) {
+      return;
+    }
+    if (writeMap(map)) {
+      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
+    }
+  } catch (err) {
+    console.warn("Failed to migrate legacy load settings:", err);
+  }
+}
+
+function readMapRaw(): StoredMap {
+  if (!canUseStorage()) {
+    return {};
+  }
+  try {
+    const raw = localStorage.getItem(STORAGE_KEY);
+    if (!raw) {
+      return {};
+    }
+    const parsed = JSON.parse(raw);
+    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) {
+      return {};
+    }
+    return parsed as StoredMap;
+  } catch {
+    return {};
+  }
+}
+
+function readMap(): StoredMap {
+  migrateLegacyLoadSettingsOnce();
+  return readMapRaw();
+}
+
+function writeMap(map: StoredMap): boolean {
+  if (!canUseStorage()) {
+    return false;
+  }
+  try {
+    localStorage.setItem(STORAGE_KEY, JSON.stringify(map));
+    return true;
+  } catch (err) {
+    console.warn("Failed to persist per-model config:", err);
+    return false;
+  }
+}
+
+function warnDroppedFields(raw: Record<string, unknown>, version: number): void {
+  if (!import.meta.env?.DEV) {
+    return;
+  }
+  const dropped = Object.keys(raw).filter(
+    (key) => !STORED_CONFIG_FIELDS.has(key),
+  );
+  if (dropped.length > 0) {
+    console.warn("Dropped unknown per-model config fields:", dropped);
+  }
+  if (version > STORAGE_SCHEMA_VERSION) {
+    console.warn("Per-model config schema is newer than this app:", version);
+  }
+}
+
+function normalizeV1(partial: RawConfig): PerModelConfig {
+  const rawSpecType =
+    typeof partial.speculativeType === "string"
+      ? canonicalizeSpeculativeType(partial.speculativeType)
+      : null;
+  const speculativeType = rawSpecType ?? DEFAULT_PER_MODEL_CONFIG.speculativeType;
+  const specDraftNMax =
+    speculativeType != null &&
+    MTP_SPECULATIVE_TYPES.has(speculativeType) &&
+    typeof partial.specDraftNMax === "number" &&
+    Number.isFinite(partial.specDraftNMax)
+      ? Math.max(1, Math.min(16, Math.round(partial.specDraftNMax)))
+      : null;
+  return {
+    customContextLength:
+      typeof partial.customContextLength === "number" &&
+      Number.isFinite(partial.customContextLength) &&
+      partial.customContextLength > 0
+        ? Math.max(CONTEXT_LENGTH_MIN, Math.floor(partial.customContextLength))
+        : null,
+    maxSeqLength: normalizeMaxSeqLength(partial.maxSeqLength),
+    kvCacheDtype:
+      typeof partial.kvCacheDtype === "string" &&
+      VALID_KV_CACHE_DTYPES.has(partial.kvCacheDtype)
+        ? partial.kvCacheDtype
+        : null,
+    speculativeType,
+    specDraftNMax,
+    tensorParallel:
+      typeof partial.tensorParallel === "boolean"
+        ? partial.tensorParallel
+        : DEFAULT_PER_MODEL_CONFIG.tensorParallel,
+    chatTemplateOverride:
+      typeof partial.chatTemplateOverride === "string" &&
+      isChatTemplateWithinLimit(partial.chatTemplateOverride)
+        ? partial.chatTemplateOverride
+        : null,
+    ...normalizeGpuFields(partial),
+  };
+}
+
+function normalize(raw: unknown): PerModelConfig {
+  if (!raw || typeof raw !== "object" || Array.isArray(raw)) {
+    return normalizeV1({});
+  }
+  const partial = raw as RawConfig;
+  const version =
+    typeof partial.version === "number" && Number.isFinite(partial.version)
+      ? partial.version
+      : 0;
+  warnDroppedFields(raw as Record<string, unknown>, version);
+  return normalizeV1(partial);
+}
+
+function toStoredConfig(config: PerModelConfig): StoredPerModelConfig {
+  return {
+    version: STORAGE_SCHEMA_VERSION,
+    ...normalize(config),
+  };
+}
+
+function legacyModelStorageKey(
+  modelId: string,
+  ggufVariant?: string | null,
+): string {
+  return `${modelId}::${ggufVariant ?? ""}`;
+}
+
+function storageKeysForModelVariant(
+  modelId: string,
+  ggufVariant?: string | null,
+): string[] {
+  const key = modelStorageKey(modelId, ggufVariant);
+  const legacyKey = legacyModelStorageKey(modelId, ggufVariant);
+  return key === legacyKey ? [key] : [key, legacyKey];
+}
+
+function configKeyMatchesModelVariant(
+  key: string,
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  const storedModelId = modelIdFromStorageKey(key);
+  if (!storedModelId) {
+    return false;
+  }
+  return (
+    normalizeModelIdentity(storedModelId) === normalizeModelIdentity(modelId) &&
+    normalizeGgufVariantIdentity(ggufVariantFromStorageKey(key)) ===
+      normalizeGgufVariantIdentity(ggufVariant)
+  );
+}
+
+function findConfigKeyForModelVariant(
+  map: StoredMap,
+  modelId: string,
+  ggufVariant?: string | null,
+): string | null {
+  for (const key of storageKeysForModelVariant(modelId, ggufVariant)) {
+    if (Object.hasOwn(map, key)) {
+      return key;
+    }
+  }
+  for (const key of Object.keys(map)) {
+    if (configKeyMatchesModelVariant(key, modelId, ggufVariant)) {
+      return key;
+    }
+  }
+  return null;
+}
+
+function hasFutureConfigForModelVariant(
+  map: StoredMap,
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  for (const key of Object.keys(map)) {
+    if (
+      configKeyMatchesModelVariant(key, modelId, ggufVariant) &&
+      storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION
+    ) {
+      return true;
+    }
+  }
+  return false;
+}
+
+function deleteConfigEntriesForModelVariant(
+  map: StoredMap,
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  let changed = false;
+  for (const key of Object.keys(map)) {
+    if (!configKeyMatchesModelVariant(key, modelId, ggufVariant)) {
+      continue;
+    }
+    delete map[key];
+    changed = true;
+  }
+  return changed;
+}
+
+function loadPerModelConfig(
+  modelId: string,
+  ggufVariant?: string | null,
+): PerModelConfig | null {
+  const map = readMap();
+  const key = findConfigKeyForModelVariant(map, modelId, ggufVariant);
+  if (!key) {
+    return null;
+  }
+  // Never apply a future-schema record an older client cannot interpret.
+  if (storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION) {
+    return null;
+  }
+  return normalize(map[key]);
+}
+
+export function isDefaultConfig(config: PerModelConfig): boolean {
+  return (
+    config.customContextLength == null &&
+    config.maxSeqLength == null &&
+    (config.kvCacheDtype ?? null) === DEFAULT_PER_MODEL_CONFIG.kvCacheDtype &&
+    config.speculativeType === DEFAULT_PER_MODEL_CONFIG.speculativeType &&
+    config.specDraftNMax == null &&
+    Boolean(config.tensorParallel) ===
+      Boolean(DEFAULT_PER_MODEL_CONFIG.tensorParallel) &&
+    (config.chatTemplateOverride ?? null) === null &&
+    gpuFieldsAtDefault(config)
+  );
+}
+
+// GPU knobs are "default" when mode is Auto with no explicit choice: mode
+// auto/absent, gpuLayers < 0/absent, nCpuMoe 0/absent, selectedGpuIds null/absent.
+function gpuFieldsAtDefault(config: PerModelConfig): boolean {
+  return (
+    (config.gpuMemoryMode ?? "auto") === "auto" &&
+    (config.gpuLayers == null || config.gpuLayers < 0) &&
+    (config.nCpuMoe == null || config.nCpuMoe === 0) &&
+    config.selectedGpuIds == null
+  );
+}
+
+export function savePerModelConfig(
+  modelId: string,
+  ggufVariant: string | null | undefined,
+  config: PerModelConfig,
+): boolean {
+  if (
+    typeof config.chatTemplateOverride === "string" &&
+    !isChatTemplateWithinLimit(config.chatTemplateOverride)
+  ) {
+    return false;
+  }
+  const normalized = normalize(config);
+  const map = readMap();
+  if (hasFutureConfigForModelVariant(map, modelId, ggufVariant)) {
+    return false;
+  }
+  if (isDefaultConfig(normalized)) {
+    const changed = deleteConfigEntriesForModelVariant(
+      map,
+      modelId,
+      ggufVariant,
+    );
+    return changed ? writeMap(map) : true;
+  }
+  const [key] = storageKeysForModelVariant(modelId, ggufVariant);
+  deleteConfigEntriesForModelVariant(map, modelId, ggufVariant);
+  map[key] = toStoredConfig(normalized);
+  if (!enforceStorageBudget(map, new Set([key]))) {
+    return false;
+  }
+  return writeMap(map);
+}
+
+export function deletePerModelConfig(
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  const map = readMap();
+  // Mirror savePerModelConfig: never let an older client destroy a future-schema entry.
+  if (hasFutureConfigForModelVariant(map, modelId, ggufVariant)) {
+    return false;
+  }
+  if (!deleteConfigEntriesForModelVariant(map, modelId, ggufVariant)) {
+    return true;
+  }
+  return writeMap(map);
+}
+
+export function resolveInitialConfig(
+  modelId: string,
+  ggufVariant?: string | null,
+): { config: PerModelConfig; remembered: boolean } {
+  const saved = loadPerModelConfig(modelId, ggufVariant);
+  if (saved) {
+    return { config: saved, remembered: true };
+  }
+  return { config: { ...DEFAULT_PER_MODEL_CONFIG }, remembered: false };
+}
diff --git a/studio/frontend/src/features/native-intents/api.ts b/studio/frontend/src/features/native-intents/api.ts
index b5c7e33b3a..98caa709b9 100644
--- a/studio/frontend/src/features/native-intents/api.ts
+++ b/studio/frontend/src/features/native-intents/api.ts
@@ -23,6 +23,11 @@ export async function pickNativeModel(): Promise<NativeIntent | null> {
   return invokeNative<NativeIntent | null>("pick_native_model");
 }
 
+export async function pickHuggingFaceCacheDir(): Promise<string | null> {
+  if (!isTauri) return null;
+  return invokeNative<string | null>("pick_hugging_face_cache_dir");
+}
+
 export async function registerNativeModelPath(path: string): Promise<NativeIntent> {
   return invokeNative<NativeIntent>("register_native_model_path", { path });
 }
diff --git a/studio/frontend/src/features/native-intents/components/native-model-drop-overlay.tsx b/studio/frontend/src/features/native-intents/components/native-model-drop-overlay.tsx
index 725fb14259..33b8934756 100644
--- a/studio/frontend/src/features/native-intents/components/native-model-drop-overlay.tsx
+++ b/studio/frontend/src/features/native-intents/components/native-model-drop-overlay.tsx
@@ -60,7 +60,7 @@ export function NativeModelDropOverlay({ state }: { state: NativeModelDropState
           <div className="truncate text-xs font-medium text-foreground">
             {title}
           </div>
-          <div className="mt-0.5 truncate text-[11px] leading-4 text-muted-foreground">
+          <div className="mt-0.5 truncate text-ui-11 leading-4 text-muted-foreground">
             {description}
           </div>
         </div>
diff --git a/studio/frontend/src/features/native-intents/index.ts b/studio/frontend/src/features/native-intents/index.ts
index a82c39a9ec..98b89f08f3 100644
--- a/studio/frontend/src/features/native-intents/index.ts
+++ b/studio/frontend/src/features/native-intents/index.ts
@@ -3,7 +3,7 @@
 
 export { NativeModelChip } from "./components/native-model-chip";
 export { NativeModelDropOverlay } from "./components/native-model-drop-overlay";
-export { openModelsDir } from "./api";
+export { openModelsDir, pickHuggingFaceCacheDir } from "./api";
 export { useNativeIntentStore } from "./store";
 export type { NativeIntent } from "./types";
 export { useChooseNativeModel } from "./use-native-dialogs";
diff --git a/studio/frontend/src/features/onboarding/components/steps/model-selection-step.tsx b/studio/frontend/src/features/onboarding/components/steps/model-selection-step.tsx
index e60786decb..b22e91eaf0 100644
--- a/studio/frontend/src/features/onboarding/components/steps/model-selection-step.tsx
+++ b/studio/frontend/src/features/onboarding/components/steps/model-selection-step.tsx
@@ -286,12 +286,12 @@ export function ModelSelectionStep() {
                         </Tooltip>
                         <span className="flex items-center gap-1.5 shrink-0">
                           {fitStatus === "exceeds" && (
-                            <span className="text-[9px] font-medium !text-red-700 !bg-red-50 dark:!text-red-400 dark:!bg-red-950 px-1.5 py-0.5 rounded">
+                            <span className="text-ui-9 font-medium !text-red-700 !bg-red-50 dark:!text-red-400 dark:!bg-red-950 px-1.5 py-0.5 rounded">
                               OOM
                             </span>
                           )}
                           {fitStatus === "tight" && (
-                            <span className="text-[9px] font-medium !text-amber-400">
+                            <span className="text-ui-9 font-medium !text-amber-400">
                               TIGHT
                             </span>
                           )}
diff --git a/studio/frontend/src/features/onboarding/components/steps/model-type-step.tsx b/studio/frontend/src/features/onboarding/components/steps/model-type-step.tsx
index 4f9f1ffea9..038b19cdc9 100644
--- a/studio/frontend/src/features/onboarding/components/steps/model-type-step.tsx
+++ b/studio/frontend/src/features/onboarding/components/steps/model-type-step.tsx
@@ -106,7 +106,7 @@ export function ModelTypeStep(): ReactElement {
                 {isDisabled && (
                   <Badge
                     variant="secondary"
-                    className="absolute top-2 right-2 text-[10px]"
+                    className="absolute top-2 right-2 text-ui-10"
                   >
                     Coming Soon
                   </Badge>
diff --git a/studio/frontend/src/features/onboarding/components/wizard-sidebar.tsx b/studio/frontend/src/features/onboarding/components/wizard-sidebar.tsx
index 4637336c6c..d5e11110ab 100644
--- a/studio/frontend/src/features/onboarding/components/wizard-sidebar.tsx
+++ b/studio/frontend/src/features/onboarding/components/wizard-sidebar.tsx
@@ -17,14 +17,16 @@ export function WizardSidebar({ returnTo }: { returnTo: string }) {
   return (
     <aside className="w-full shrink-0 bg-muted/70 p-4 md:w-64 md:p-6">
       <div className="flex items-center gap-3 py-1 md:py-2">
+        {/* Logo lockup follows the UI font size at half rate:
+            base + (root scale - 1) * 8px. Exact base sizes at 16px. */}
         <img
           src={`${import.meta.env.BASE_URL}sticker.png`}
           alt="Unsloth"
-          className="size-12"
+          className="size-[calc(40px+0.5rem*var(--ui-font-scale,1))]"
         />
         <div className="flex flex-col">
-          <span className="font-semibold text-lg leading-tight">Unsloth</span>
-          <span className="text-xs text-muted-foreground">Studio</span>
+          <span className="font-semibold text-[calc(10px+0.5rem*var(--ui-font-scale,1))] leading-tight">Unsloth</span>
+          <span className="text-[calc(4px+0.5rem*var(--ui-font-scale,1))] text-muted-foreground">Studio</span>
         </div>
       </div>
       <div className="mt-3 md:mt-0">
diff --git a/studio/frontend/src/features/profile/components/profile-personalization-panel.tsx b/studio/frontend/src/features/profile/components/profile-personalization-panel.tsx
index 5fc6d090db..d403f7fe66 100644
--- a/studio/frontend/src/features/profile/components/profile-personalization-panel.tsx
+++ b/studio/frontend/src/features/profile/components/profile-personalization-panel.tsx
@@ -191,7 +191,7 @@ export function ProfilePersonalizationPanel() {
           name={previewName}
           imageUrl={shownAvatar}
           size="lg"
-          className="size-[124px] text-[3.15rem]"
+          className="size-[124px] text-[calc(3.15rem*var(--ui-font-scale,1))]"
         />
         <input
           ref={fileInputRef}
@@ -288,7 +288,7 @@ export function ProfilePersonalizationPanel() {
               onClick={() => setAvatarShape(shape)}
               aria-pressed={avatarShape === shape}
               className={cn(
-                "inline-flex h-8 items-center rounded-full px-4 text-[13px] font-medium transition-colors",
+                "inline-flex h-8 items-center rounded-full px-4 text-ui-13 font-medium transition-colors",
                 avatarShape === shape
                   ? "hub-tab-toggle-pill text-foreground"
                   : "text-muted-foreground hover:text-foreground",
@@ -366,7 +366,7 @@ export function ProfilePersonalizationPanel() {
               shownAvatar === null && "ring-ring-strong hover:ring-ring-strong",
             )}
           >
-            <span className="text-[11px] font-medium">
+            <span className="text-ui-11 font-medium">
               {t("settings.profile.noneLabel")}
             </span>
           </button>
diff --git a/studio/frontend/src/features/profile/components/user-avatar.tsx b/studio/frontend/src/features/profile/components/user-avatar.tsx
index 2db103c1d4..e883fc5fad 100644
--- a/studio/frontend/src/features/profile/components/user-avatar.tsx
+++ b/studio/frontend/src/features/profile/components/user-avatar.tsx
@@ -21,7 +21,7 @@ const SIZE: Record<"sm" | "md" | "lg", string> = {
   sm: "size-9 text-xs",
   md: "size-11 text-sm",
   /** ~10% larger than `size-24` / `text-2xl` for the edit-profile dialog. */
-  lg: "size-[106px] text-[1.65rem]",
+  lg: "size-[106px] text-[calc(1.65rem*var(--ui-font-scale,1))]",
 };
 
 // Percentage radius keeps the rounded-rectangle proportional across sizes.
diff --git a/studio/frontend/src/features/rag/components/project-sources-panel.tsx b/studio/frontend/src/features/rag/components/project-sources-panel.tsx
index 941e385563..1bbbc58c0c 100644
--- a/studio/frontend/src/features/rag/components/project-sources-panel.tsx
+++ b/studio/frontend/src/features/rag/components/project-sources-panel.tsx
@@ -77,7 +77,7 @@ export function ProjectSourcesPanel({ projectId }: { projectId: string }) {
             />
           </span>
           <div className="space-y-1">
-            <p className="text-[15px] font-semibold text-foreground">
+            <p className="text-ui-15 font-semibold text-foreground">
               Give this project context
             </p>
             <p className="max-w-sm text-sm text-muted-foreground">
@@ -94,7 +94,7 @@ export function ProjectSourcesPanel({ projectId }: { projectId: string }) {
           >
             Add sources
           </Button>
-          <p className="text-[11px] text-muted-foreground">Or drop files here</p>
+          <p className="text-ui-11 text-muted-foreground">Or drop files here</p>
         </div>
       ) : (
         <div className="flex flex-col gap-4 rounded-[26px] bg-muted/30 px-6 py-5">
diff --git a/studio/frontend/src/features/rag/components/retrieval-settings-section.tsx b/studio/frontend/src/features/rag/components/retrieval-settings-section.tsx
index be791b8e6d..9c91360d44 100644
--- a/studio/frontend/src/features/rag/components/retrieval-settings-section.tsx
+++ b/studio/frontend/src/features/rag/components/retrieval-settings-section.tsx
@@ -75,10 +75,10 @@ function SliderRow({
       )}
     >
       <div className="flex items-center justify-between">
-        <span className="text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+        <span className="text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
           {label}
         </span>
-        <span className="text-[13px] tabular-nums text-muted-foreground">
+        <span className="text-ui-13 tabular-nums text-muted-foreground">
           {format(value)}
         </span>
       </div>
@@ -120,7 +120,7 @@ export function RetrievalSettingsSection() {
   return (
     <div className="flex flex-col gap-5 pt-1">
       <div className="flex flex-col gap-2">
-        <span className="text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+        <span className="text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
           Search mode
         </span>
         <Select
@@ -143,10 +143,10 @@ export function RetrievalSettingsSection() {
 
       <div className="flex flex-col gap-2">
         <div className="flex items-center justify-between">
-          <span className="text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+          <span className="text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
             Passages (top K)
           </span>
-          <span className="text-[13px] tabular-nums text-muted-foreground">
+          <span className="text-ui-13 tabular-nums text-muted-foreground">
             {ragTopK}
           </span>
         </div>
@@ -163,7 +163,7 @@ export function RetrievalSettingsSection() {
 
       <div className="flex flex-col gap-3">
         <div className="flex flex-col">
-          <span className="flex items-center gap-1.5 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+          <span className="flex items-center gap-1.5 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
             Auto-retrieve documents
             <InfoHint>
               Auto turns retrieval on for smaller models (9B and below), which
@@ -171,7 +171,7 @@ export function RetrievalSettingsSection() {
               larger ones. On and Off force it either way.
             </InfoHint>
           </span>
-          <span className="text-[12px] leading-[1.3] text-muted-foreground">
+          <span className="text-ui-12 leading-[1.3] text-muted-foreground">
             Search attached documents before answering.
           </span>
         </div>
@@ -212,7 +212,7 @@ export function RetrievalSettingsSection() {
 
       <div className="flex items-start justify-between gap-3">
         <div className="flex flex-col">
-          <span className="flex items-center gap-1.5 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+          <span className="flex items-center gap-1.5 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
             OCR scanned pages
             <InfoHint>
               Read text off scanned or image-only PDF pages with the loaded
@@ -221,7 +221,7 @@ export function RetrievalSettingsSection() {
               unaffected.
             </InfoHint>
           </span>
-          <span className="text-[12px] leading-[1.3] text-muted-foreground">
+          <span className="text-ui-12 leading-[1.3] text-muted-foreground">
             Transcribe image-only PDF pages when attaching.
           </span>
         </div>
@@ -235,7 +235,7 @@ export function RetrievalSettingsSection() {
 
       <div className="flex items-start justify-between gap-3">
         <div className="flex flex-col">
-          <span className="flex items-center gap-1.5 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+          <span className="flex items-center gap-1.5 text-ui-13 font-medium leading-[1.25] tracking-nav text-nav-fg">
             Describe figures &amp; charts
             <InfoHint>
               Caption PDF figures, charts, tables and diagrams at upload with the
@@ -243,7 +243,7 @@ export function RetrievalSettingsSection() {
               vision model; adds vision calls for detected figures.
             </InfoHint>
           </span>
-          <span className="text-[12px] leading-[1.3] text-muted-foreground">
+          <span className="text-ui-12 leading-[1.3] text-muted-foreground">
             Read charts and diagrams when attaching.
           </span>
         </div>
diff --git a/studio/frontend/src/features/recipe-studio/components/block-sheet.tsx b/studio/frontend/src/features/recipe-studio/components/block-sheet.tsx
index 1b38f91d64..6aebac66df 100644
--- a/studio/frontend/src/features/recipe-studio/components/block-sheet.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/block-sheet.tsx
@@ -205,12 +205,12 @@ function BlockSheetButton({
             {title}
           </p>
           {badge ? (
-            <Badge variant="outline" className="rounded-full text-[10px]">
+            <Badge variant="outline" className="rounded-full text-ui-10">
               {badge}
             </Badge>
           ) : null}
         </div>
-        <p className="break-words text-[11px] text-muted-foreground">
+        <p className="break-words text-ui-11 text-muted-foreground">
           {description}
         </p>
       </div>
diff --git a/studio/frontend/src/features/recipe-studio/components/executions/execution-sidebar.tsx b/studio/frontend/src/features/recipe-studio/components/executions/execution-sidebar.tsx
index a8ae8ff188..f613c775b3 100644
--- a/studio/frontend/src/features/recipe-studio/components/executions/execution-sidebar.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/executions/execution-sidebar.tsx
@@ -66,7 +66,7 @@ export function ExecutionSidebar({
                   </p>
                   <Badge
                     variant="outline"
-                    className={cn("capitalize text-[11px]", statusTone(execution.status))}
+                    className={cn("capitalize text-ui-11", statusTone(execution.status))}
                   >
                     {formatStatus(execution.status)}
                   </Badge>
diff --git a/studio/frontend/src/features/recipe-studio/components/inline/inline-category-badges.tsx b/studio/frontend/src/features/recipe-studio/components/inline/inline-category-badges.tsx
index a2e352a8f7..8db276eca3 100644
--- a/studio/frontend/src/features/recipe-studio/components/inline/inline-category-badges.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/inline/inline-category-badges.tsx
@@ -64,7 +64,7 @@ export function InlineCategoryBadges({
           <Badge
             key={`m-${v}-${i}`}
             variant="secondary"
-            className="corner-squircle h-4 shrink-0 px-1.5 text-[10px]"
+            className="corner-squircle h-4 shrink-0 px-1.5 text-ui-10"
           >
             {v}
           </Badge>
@@ -76,13 +76,13 @@ export function InlineCategoryBadges({
           <Badge
             key={`${v}-${i}`}
             variant="secondary"
-            className="corner-squircle h-4 px-1.5 text-[10px]"
+            className="corner-squircle h-4 px-1.5 text-ui-10"
           >
             {v}
           </Badge>
         ))}
         {overflow > 0 && (
-          <Badge variant="outline" className="corner-squircle h-4 px-1.5 text-[10px]">
+          <Badge variant="outline" className="corner-squircle h-4 px-1.5 text-ui-10">
             +{overflow}
           </Badge>
         )}
diff --git a/studio/frontend/src/features/recipe-studio/components/inline/inline-field.tsx b/studio/frontend/src/features/recipe-studio/components/inline/inline-field.tsx
index e52ee00425..76eddd2c9e 100644
--- a/studio/frontend/src/features/recipe-studio/components/inline/inline-field.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/inline/inline-field.tsx
@@ -17,7 +17,7 @@ export function InlineField({
 }: InlineFieldProps): ReactElement {
   return (
     <div className={cn("grid gap-1.5", className)}>
-      <p className="text-[11px] font-semibold uppercase tracking-wide text-muted-foreground">
+      <p className="text-ui-11 font-semibold uppercase tracking-wide text-muted-foreground">
         {label}
       </p>
       {children}
diff --git a/studio/frontend/src/features/recipe-studio/components/inline/inline-llm.tsx b/studio/frontend/src/features/recipe-studio/components/inline/inline-llm.tsx
index 45fb1b52a0..36479d2b58 100644
--- a/studio/frontend/src/features/recipe-studio/components/inline/inline-llm.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/inline/inline-llm.tsx
@@ -184,7 +184,7 @@ export function InlineLlm({ config, onUpdate }: InlineLlmProps): ReactElement {
           </Select>
         </InlineField>
       )}
-      <p className="text-[11px] text-muted-foreground">
+      <p className="text-ui-11 text-muted-foreground">
         Prompt/system edited on aux nodes.
       </p>
     </div>
diff --git a/studio/frontend/src/features/recipe-studio/components/inline/inline-seed.tsx b/studio/frontend/src/features/recipe-studio/components/inline/inline-seed.tsx
index 82ec2f1de8..c4ca2d1834 100644
--- a/studio/frontend/src/features/recipe-studio/components/inline/inline-seed.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/inline/inline-seed.tsx
@@ -74,7 +74,7 @@ export function InlineSeed({
         </div>
         <div className="min-w-0">
           <p className="truncate text-xs font-medium">{summary}</p>
-          <p className="truncate text-[11px] text-muted-foreground">
+          <p className="truncate text-ui-11 text-muted-foreground">
             {warning ??
               `${itemsLabel} · limit ${limit} · ${commentsLabel} · ${tokenLabel}`}
           </p>
@@ -106,7 +106,7 @@ export function InlineSeed({
             placeholder="org/repo"
           />
         </InlineField>
-        <p className="text-[11px] text-muted-foreground">
+        <p className="text-ui-11 text-muted-foreground">
           Load columns in dialog.
         </p>
       </div>
@@ -132,7 +132,7 @@ export function InlineSeed({
         <p className="truncate text-xs font-medium">
           {fileName || "No file selected"}
         </p>
-        <p className="text-[11px] text-muted-foreground">
+        <p className="text-ui-11 text-muted-foreground">
           {isLocal ? "Structured file" : "Unstructured document"} · configure in
           dialog
         </p>
diff --git a/studio/frontend/src/features/recipe-studio/components/recipe-graph-node.tsx b/studio/frontend/src/features/recipe-studio/components/recipe-graph-node.tsx
index a13c651149..9ad483d738 100644
--- a/studio/frontend/src/features/recipe-studio/components/recipe-graph-node.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/recipe-graph-node.tsx
@@ -338,7 +338,7 @@ function renderNodeBody(
               <Badge
                 key={providerName}
                 variant="secondary"
-                className="corner-squircle font-mono text-[11px]"
+                className="corner-squircle font-mono text-ui-11"
               >
                 {providerName}
               </Badge>
@@ -505,7 +505,7 @@ function RecipeGraphNodeBase({
             <BaseNodeHeaderTitle className="truncate text-sm">
               {data.name}
             </BaseNodeHeaderTitle>
-            <p className="truncate text-[11px] text-muted-foreground">
+            <p className="truncate text-ui-11 text-muted-foreground">
               {data.subtype} · {data.title}
             </p>
           </div>
diff --git a/studio/frontend/src/features/recipe-studio/components/recipe-studio-header.tsx b/studio/frontend/src/features/recipe-studio/components/recipe-studio-header.tsx
index 385bef2b77..af22778ce5 100644
--- a/studio/frontend/src/features/recipe-studio/components/recipe-studio-header.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/recipe-studio-header.tsx
@@ -118,7 +118,7 @@ export function RecipeStudioHeader({
               {workflowName}
             </button>
           )}
-          <Badge variant="secondary" className="h-6 shrink-0 text-[10px]">
+          <Badge variant="secondary" className="h-6 shrink-0 text-ui-10">
             {STATUS_MESSAGE_CLASS[saveTone]}
           </Badge>
           <span
@@ -148,7 +148,7 @@ export function RecipeStudioHeader({
             <PopoverTrigger asChild={true}>
               <button
                 type="button"
-                className={`inline-flex h-6 shrink-0 items-center gap-1 rounded-md border px-2 text-[10px] font-medium ${RECIPE_STUDIO_WARNING_BADGE_TONE}`}
+                className={`inline-flex h-6 shrink-0 items-center gap-1 rounded-md border px-2 text-ui-10 font-medium ${RECIPE_STUDIO_WARNING_BADGE_TONE}`}
               >
                 <HugeiconsIcon icon={Alert02Icon} className="size-3" />
                 {warnings.length}
diff --git a/studio/frontend/src/features/recipe-studio/components/runtime/execution-progress-island.tsx b/studio/frontend/src/features/recipe-studio/components/runtime/execution-progress-island.tsx
index 587fd6c262..f67019498e 100644
--- a/studio/frontend/src/features/recipe-studio/components/runtime/execution-progress-island.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/runtime/execution-progress-island.tsx
@@ -156,7 +156,7 @@ export function ExecutionProgressIsland({
           {showLoadingSpinner && (
             <Spinner className="size-3.5 text-muted-foreground" />
           )}
-          <span className="shrink-0 text-[11px] text-muted-foreground">
+          <span className="shrink-0 text-ui-11 text-muted-foreground">
             {formatPercent(progressPercent)}
           </span>
           <button
@@ -180,7 +180,7 @@ export function ExecutionProgressIsland({
 
       {!minimized && (
         <>
-          <div className="grid grid-cols-2 gap-2 px-3 pt-2 text-[11px] text-muted-foreground sm:grid-cols-4">
+          <div className="grid grid-cols-2 gap-2 px-3 pt-2 text-ui-11 text-muted-foreground sm:grid-cols-4">
             <p
               className="truncate"
               title={`Done: ${formatMetricValue(execution.progress?.done)}`}
@@ -207,7 +207,7 @@ export function ExecutionProgressIsland({
             </p>
           </div>
           {showSourceProgress ? (
-            <div className="mt-1 flex items-center gap-1.5 px-3 text-[11px] text-muted-foreground">
+            <div className="mt-1 flex items-center gap-1.5 px-3 text-ui-11 text-muted-foreground">
               <HugeiconsIcon
                 icon={Flag02Icon}
                 className="size-3.5 shrink-0 text-amber-700 dark:text-amber-300"
@@ -217,7 +217,7 @@ export function ExecutionProgressIsland({
               </p>
             </div>
           ) : (
-            <div className="mt-1 flex items-center gap-1.5 px-3 text-[11px] text-muted-foreground">
+            <div className="mt-1 flex items-center gap-1.5 px-3 text-ui-11 text-muted-foreground">
               <HugeiconsIcon
                 icon={currentColumnIcon}
                 className="size-3.5 shrink-0"
@@ -229,7 +229,7 @@ export function ExecutionProgressIsland({
           )}
           {showBatch && (
             <div
-              className="mt-1 truncate px-3 text-[11px] text-muted-foreground"
+              className="mt-1 truncate px-3 text-ui-11 text-muted-foreground"
               title={`Batch: ${execution.batch?.idx ?? "--"}/${execution.batch?.total ?? "--"}`}
             >
               Batch: {execution.batch?.idx ?? "--"}/
@@ -241,7 +241,7 @@ export function ExecutionProgressIsland({
               type="button"
               variant="outline"
               size="sm"
-              className="h-7 w-full text-[11px]"
+              className="h-7 w-full text-ui-11"
               onClick={onViewExecutions}
             >
               View run details
diff --git a/studio/frontend/src/features/recipe-studio/components/shared/available-references-inline.tsx b/studio/frontend/src/features/recipe-studio/components/shared/available-references-inline.tsx
index fad7985ae1..ec75f59c05 100644
--- a/studio/frontend/src/features/recipe-studio/components/shared/available-references-inline.tsx
+++ b/studio/frontend/src/features/recipe-studio/components/shared/available-references-inline.tsx
@@ -66,7 +66,7 @@ export function AvailableReferencesInline({
 
   return (
     <div className="space-y-1">
-      <p className="text-[10px] font-medium text-muted-foreground">
+      <p className="text-ui-10 font-medium text-muted-foreground">
         Available references
       </p>
       <div ref={wrapperRef} className="relative">
@@ -83,8 +83,8 @@ export function AvailableReferencesInline({
                   variant="secondary"
                   className={
                     entry.source === "seed"
-                      ? "corner-squircle h-4 border-blue-500/25 bg-blue-500/10 px-1.5 font-mono text-[10px] text-blue-700 dark:text-blue-300"
-                      : "corner-squircle h-4 px-1.5 font-mono text-[10px]"
+                      ? "corner-squircle h-4 border-blue-500/25 bg-blue-500/10 px-1.5 font-mono text-ui-10 text-blue-700 dark:text-blue-300"
+                      : "corner-squircle h-4 px-1.5 font-mono text-ui-10"
                   }
                 >
                   {entry.name}
@@ -100,8 +100,8 @@ export function AvailableReferencesInline({
               variant="secondary"
               className={
                 entry.source === "seed"
-                  ? "corner-squircle h-4 border-blue-500/25 bg-blue-500/10 px-1.5 font-mono text-[10px] text-blue-700 dark:text-blue-300"
-                  : "corner-squircle h-4 px-1.5 font-mono text-[10px]"
+                  ? "corner-squircle h-4 border-blue-500/25 bg-blue-500/10 px-1.5 font-mono text-ui-10 text-blue-700 dark:text-blue-300"
+                  : "corner-squircle h-4 px-1.5 font-mono text-ui-10"
               }
             >
               {entry.name}
@@ -110,7 +110,7 @@ export function AvailableReferencesInline({
           {!expanded && hiddenCount > 0 && (
             <button
               type="button"
-              className="corner-squircle h-4 px-1.5 text-[10px] text-muted-foreground hover:text-foreground"
+              className="corner-squircle h-4 px-1.5 text-ui-10 text-muted-foreground hover:text-foreground"
               onClick={() => setExpanded(true)}
             >
               +{hiddenCount} more
@@ -119,7 +119,7 @@ export function AvailableReferencesInline({
           {expanded && collapsedCount < entries.length && (
             <button
               type="button"
-              className="corner-squircle h-4 px-1.5 text-[10px] text-muted-foreground hover:text-foreground"
+              className="corner-squircle h-4 px-1.5 text-ui-10 text-muted-foreground hover:text-foreground"
               onClick={() => setExpanded(false)}
             >
               Show less
diff --git a/studio/frontend/src/features/recipe-studio/dialogs/models/local-recipe-model-selector.tsx b/studio/frontend/src/features/recipe-studio/dialogs/models/local-recipe-model-selector.tsx
index c857b88a91..48229ecdcc 100644
--- a/studio/frontend/src/features/recipe-studio/dialogs/models/local-recipe-model-selector.tsx
+++ b/studio/frontend/src/features/recipe-studio/dialogs/models/local-recipe-model-selector.tsx
@@ -190,7 +190,7 @@ function LocalGgufVariantList({
 
   return (
     <div className="ml-6 mt-1 rounded-lg bg-muted/25 p-1.5">
-      <div className="mb-1 px-2 text-[10px] font-medium uppercase tracking-wide text-muted-foreground">
+      <div className="mb-1 px-2 text-ui-10 font-medium uppercase tracking-wide text-muted-foreground">
         Quantization
       </div>
       <div className="space-y-0.5">
@@ -210,12 +210,12 @@ function LocalGgufVariantList({
                 {variant.quant}
               </span>
               {variant.quant === defaultVariant ? (
-                <Badge variant="secondary" className="h-4 px-1.5 text-[10px]">
+                <Badge variant="secondary" className="h-4 px-1.5 text-ui-10">
                   recommended
                 </Badge>
               ) : null}
               {variant.downloaded ? (
-                <Badge variant="outline" className="h-4 px-1.5 text-[10px]">
+                <Badge variant="outline" className="h-4 px-1.5 text-ui-10">
                   ready
                 </Badge>
               ) : null}
@@ -276,7 +276,7 @@ const SelectorTrigger = forwardRef<HTMLButtonElement, SelectorTriggerProps>(
             {selected.label || "Choose a local model"}
           </span>
           {compact ? null : (
-            <span className="mt-0.5 flex min-w-0 items-center gap-1.5 text-[11px] text-muted-foreground">
+            <span className="mt-0.5 flex min-w-0 items-center gap-1.5 text-ui-11 text-muted-foreground">
               <span className="truncate">
                 {selected.label
                   ? selected.source
@@ -292,7 +292,7 @@ const SelectorTrigger = forwardRef<HTMLButtonElement, SelectorTriggerProps>(
         {compact && ggufVariant ? (
           <Badge
             variant="secondary"
-            className="h-4 px-1.5 font-mono text-[10px]"
+            className="h-4 px-1.5 font-mono text-ui-10"
           >
             {ggufVariant}
           </Badge>
@@ -347,7 +347,7 @@ function LocalModelRow({
           <span className="block truncate font-medium">
             {getModelLabel(model)}
           </span>
-          <span className="mt-0.5 block truncate text-[11px] text-muted-foreground">
+          <span className="mt-0.5 block truncate text-ui-11 text-muted-foreground">
             {model.id}
           </span>
         </span>
@@ -356,11 +356,11 @@ function LocalModelRow({
             <Spinner className="size-3 text-muted-foreground" />
           ) : null}
           {expandable || directGguf ? (
-            <Badge variant="secondary" className="h-4 px-1.5 text-[10px]">
+            <Badge variant="secondary" className="h-4 px-1.5 text-ui-10">
               GGUF
             </Badge>
           ) : null}
-          <Badge variant="outline" className="h-4 px-1.5 text-[10px]">
+          <Badge variant="outline" className="h-4 px-1.5 text-ui-10">
             {sourceLabel(model)}
           </Badge>
         </span>
diff --git a/studio/frontend/src/features/recipe-studio/dialogs/preview-dialog.tsx b/studio/frontend/src/features/recipe-studio/dialogs/preview-dialog.tsx
index 3181d9fe67..f2ef34df8c 100644
--- a/studio/frontend/src/features/recipe-studio/dialogs/preview-dialog.tsx
+++ b/studio/frontend/src/features/recipe-studio/dialogs/preview-dialog.tsx
@@ -653,7 +653,7 @@ function RunDialogBody({
             />
             <Badge
               variant="outline"
-              className="rounded-full text-[10px] text-destructive"
+              className="rounded-full text-ui-10 text-destructive"
             >
               Before you run
             </Badge>
diff --git a/studio/frontend/src/features/recipe-studio/dialogs/seed/seed-dialog.tsx b/studio/frontend/src/features/recipe-studio/dialogs/seed/seed-dialog.tsx
index 53f8566090..fedd603a9d 100644
--- a/studio/frontend/src/features/recipe-studio/dialogs/seed/seed-dialog.tsx
+++ b/studio/frontend/src/features/recipe-studio/dialogs/seed/seed-dialog.tsx
@@ -319,7 +319,7 @@ export function GithubRepoSeedForm({
             hint="Prefer the server GH_TOKEN / GITHUB_TOKEN env var. Use public_repo for public repos or repo for private repos."
           />
           {usingEnvToken && (
-            <span className="shrink-0 rounded-md border border-emerald-500/40 bg-emerald-500/10 px-1.5 py-0.5 text-[10px] font-medium text-emerald-700 dark:text-emerald-300">
+            <span className="shrink-0 rounded-md border border-emerald-500/40 bg-emerald-500/10 px-1.5 py-0.5 text-ui-10 font-medium text-emerald-700 dark:text-emerald-300">
               Using server env var
             </span>
           )}
diff --git a/studio/frontend/src/features/recipe-studio/dialogs/tool-profile/tool-profile-dialog.tsx b/studio/frontend/src/features/recipe-studio/dialogs/tool-profile/tool-profile-dialog.tsx
index bf5a61ac00..802729fcd8 100644
--- a/studio/frontend/src/features/recipe-studio/dialogs/tool-profile/tool-profile-dialog.tsx
+++ b/studio/frontend/src/features/recipe-studio/dialogs/tool-profile/tool-profile-dialog.tsx
@@ -135,11 +135,11 @@ function McpServerCard({
                   <p className="truncate text-sm font-semibold text-foreground">
                     {summaryTitle}
                   </p>
-                  <Badge variant="outline" className="rounded-full text-[10px] uppercase">
+                  <Badge variant="outline" className="rounded-full text-ui-10 uppercase">
                     {transportLabel}
                   </Badge>
                   {toolsLabel ? (
-                    <Badge variant="secondary" className="rounded-full text-[10px]">
+                    <Badge variant="secondary" className="rounded-full text-ui-10">
                       {toolsLabel}
                     </Badge>
                   ) : null}
@@ -680,7 +680,7 @@ export function ToolProfileDialog({
                     <p className="text-xs font-semibold uppercase text-muted-foreground">
                       {providerName}
                     </p>
-                    <Badge variant="outline" className="rounded-full text-[10px]">
+                    <Badge variant="outline" className="rounded-full text-ui-10">
                       {toolNames.length}
                     </Badge>
                   </div>
diff --git a/studio/frontend/src/features/recipe-studio/recipe-studio-page.tsx b/studio/frontend/src/features/recipe-studio/recipe-studio-page.tsx
index ec9358ee0f..30302b86a7 100644
--- a/studio/frontend/src/features/recipe-studio/recipe-studio-page.tsx
+++ b/studio/frontend/src/features/recipe-studio/recipe-studio-page.tsx
@@ -670,7 +670,7 @@ export function RecipeStudioPage({
                 />
               </div>
               <div className="mt-4 space-y-2">
-                <p className="text-[11px] font-semibold uppercase tracking-wide text-primary">
+                <p className="text-ui-11 font-semibold uppercase tracking-wide text-primary">
                   Best place to start
                 </p>
                 <p className="text-sm font-semibold text-foreground">
diff --git a/studio/frontend/src/features/recipe-studio/utils/ui-tones.ts b/studio/frontend/src/features/recipe-studio/utils/ui-tones.ts
index 3d9ecff15a..1dc3666687 100644
--- a/studio/frontend/src/features/recipe-studio/utils/ui-tones.ts
+++ b/studio/frontend/src/features/recipe-studio/utils/ui-tones.ts
@@ -27,10 +27,10 @@ export const RECIPE_STUDIO_USER_NODE_TONE =
 
 export const RECIPE_STUDIO_REFERENCE_BADGE_TONES = {
   user:
-    "corner-squircle border-amber-500/25 bg-amber-500/10 font-mono text-[11px] text-amber-700 dark:text-amber-300",
+    "corner-squircle border-amber-500/25 bg-amber-500/10 font-mono text-ui-11 text-amber-700 dark:text-amber-300",
   seed:
-    "corner-squircle border-blue-500/25 bg-blue-500/10 font-mono text-[11px] text-blue-700 dark:text-blue-300",
-  default: "corner-squircle font-mono text-[11px]",
+    "corner-squircle border-blue-500/25 bg-blue-500/10 font-mono text-ui-11 text-blue-700 dark:text-blue-300",
+  default: "corner-squircle font-mono text-ui-11",
 } as const;
 
 export const RECIPE_STUDIO_WARNING_BADGE_TONE =
diff --git a/studio/frontend/src/features/security/components/remote-code-consent-dialog.tsx b/studio/frontend/src/features/security/components/remote-code-consent-dialog.tsx
index 6426225e7f..69bab2156e 100644
--- a/studio/frontend/src/features/security/components/remote-code-consent-dialog.tsx
+++ b/studio/frontend/src/features/security/components/remote-code-consent-dialog.tsx
@@ -111,7 +111,7 @@ function UnsafeFileCard({ file }: { file: UnsafeFile }) {
       <Badge
         variant="outline"
         className={cn(
-          "shrink-0 text-[10px] font-semibold uppercase tracking-wide",
+          "shrink-0 text-ui-10 font-semibold uppercase tracking-wide",
           severityTone("CRITICAL"),
         )}
       >
@@ -134,7 +134,7 @@ function FindingCard({ finding }: { finding: RemoteCodeFinding }) {
         <Badge
           variant="outline"
           className={cn(
-            "shrink-0 text-[10px] font-semibold tracking-wide",
+            "shrink-0 text-ui-10 font-semibold tracking-wide",
             severityTone(finding.severity),
           )}
         >
diff --git a/studio/frontend/src/features/settings/api/hugging-face-cache.ts b/studio/frontend/src/features/settings/api/hugging-face-cache.ts
new file mode 100644
index 0000000000..3ca0f31053
--- /dev/null
+++ b/studio/frontend/src/features/settings/api/hugging-face-cache.ts
@@ -0,0 +1,90 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { authFetch } from "@/features/auth";
+import {
+  bumpInventoryVersion,
+  invalidateGgufVariantsCache,
+} from "@/features/hub";
+import { readFastApiError } from "@/lib/format-fastapi-error";
+
+export type HuggingFaceCacheSettings = {
+  cacheHome: string;
+  hubCache: string;
+  xetCache: string;
+  source: "default" | "studio" | "environment";
+  editable: boolean;
+  isCustom: boolean;
+  available: boolean;
+  writable: boolean;
+  freeBytes: number | null;
+  environmentVariable: string | null;
+};
+
+type ApiHuggingFaceCacheSettings = {
+  // biome-ignore lint/style/useNamingConvention: API schema
+  cache_home: string;
+  // biome-ignore lint/style/useNamingConvention: API schema
+  hub_cache: string;
+  // biome-ignore lint/style/useNamingConvention: API schema
+  xet_cache: string;
+  source: HuggingFaceCacheSettings["source"];
+  editable: boolean;
+  // biome-ignore lint/style/useNamingConvention: API schema
+  is_custom: boolean;
+  available: boolean;
+  writable: boolean;
+  // biome-ignore lint/style/useNamingConvention: API schema
+  free_bytes: number | null;
+  // biome-ignore lint/style/useNamingConvention: API schema
+  environment_variable: string | null;
+};
+
+function fromApi(value: ApiHuggingFaceCacheSettings): HuggingFaceCacheSettings {
+  return {
+    cacheHome: value.cache_home,
+    hubCache: value.hub_cache,
+    xetCache: value.xet_cache,
+    source: value.source,
+    editable: value.editable,
+    isCustom: value.is_custom,
+    available: value.available,
+    writable: value.writable,
+    freeBytes: value.free_bytes,
+    environmentVariable: value.environment_variable,
+  };
+}
+
+export async function loadHuggingFaceCacheSettings() {
+  const response = await authFetch("/api/settings/hugging-face-cache");
+  if (!response.ok) {
+    throw new Error(
+      await readFastApiError(
+        response,
+        "Failed to load the model cache location",
+      ),
+    );
+  }
+  return fromApi(await response.json());
+}
+
+export async function updateHuggingFaceCacheSettings(cacheHome: string | null) {
+  const response = await authFetch("/api/settings/hugging-face-cache", {
+    method: "PUT",
+    headers: { "Content-Type": "application/json" },
+    // biome-ignore lint/style/useNamingConvention: API schema
+    body: JSON.stringify({ cache_home: cacheHome }),
+  });
+  if (!response.ok) {
+    throw new Error(
+      await readFastApiError(
+        response,
+        "Failed to update the model cache location",
+      ),
+    );
+  }
+  const settings = fromApi(await response.json());
+  bumpInventoryVersion();
+  invalidateGgufVariantsCache();
+  return settings;
+}
diff --git a/studio/frontend/src/features/settings/api/models-folder.ts b/studio/frontend/src/features/settings/api/models-folder.ts
deleted file mode 100644
index 13e8c065c3..0000000000
--- a/studio/frontend/src/features/settings/api/models-folder.ts
+++ /dev/null
@@ -1,40 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { authFetch } from "@/features/auth";
-import { readFastApiError } from "@/lib/format-fastapi-error";
-
-export type ModelsFolder = {
-  path: string;
-};
-
-// The path is resolved once at backend startup and never changes, so cache it
-// and dedupe concurrent loads (same shape as the sibling settings loaders).
-let cachedModelsFolder: ModelsFolder | null = null;
-let inFlightModelsFolder: Promise<ModelsFolder> | null = null;
-
-async function fetchModelsFolder(): Promise<ModelsFolder> {
-  const res = await authFetch("/api/hub/models-folder");
-  if (!res.ok) {
-    throw new Error(
-      await readFastApiError(res, "Failed to load models folder"),
-    );
-  }
-  const data = (await res.json()) as { path: string };
-  return { path: data.path };
-}
-
-export async function loadModelsFolder(): Promise<ModelsFolder> {
-  if (cachedModelsFolder) {
-    return cachedModelsFolder;
-  }
-  inFlightModelsFolder ??= fetchModelsFolder()
-    .then((folder) => {
-      cachedModelsFolder = folder;
-      return folder;
-    })
-    .finally(() => {
-      inFlightModelsFolder = null;
-    });
-  return inFlightModelsFolder;
-}
diff --git a/studio/frontend/src/features/settings/components/api-key-row.tsx b/studio/frontend/src/features/settings/components/api-key-row.tsx
index 9a6e1ee207..7100634942 100644
--- a/studio/frontend/src/features/settings/components/api-key-row.tsx
+++ b/studio/frontend/src/features/settings/components/api-key-row.tsx
@@ -69,11 +69,11 @@ export function ApiKeyRow({
           <span className="truncate text-sm font-medium text-foreground" title={apiKey.name}>
             {apiKey.name}
           </span>
-          <code className="shrink-0 font-mono text-[11px] text-muted-foreground">
+          <code className="shrink-0 font-mono text-ui-11 text-muted-foreground">
             {prefix}
           </code>
         </div>
-        <div className="flex flex-wrap gap-x-1.5 text-[11px] text-muted-foreground">
+        <div className="flex flex-wrap gap-x-1.5 text-ui-11 text-muted-foreground">
           <span>
             {t("settings.apiKeys.created", {
               value: relative(apiKey.created_at, t),
diff --git a/studio/frontend/src/features/settings/components/api-monitor-console.tsx b/studio/frontend/src/features/settings/components/api-monitor-console.tsx
index ef4daa1349..0f931ff4da 100644
--- a/studio/frontend/src/features/settings/components/api-monitor-console.tsx
+++ b/studio/frontend/src/features/settings/components/api-monitor-console.tsx
@@ -127,7 +127,7 @@ function MonitorEntry({
               {compactEndpoint(entry.endpoint)}
             </span>
           </div>
-          <div className="mt-1 truncate text-[11px] text-muted-foreground">
+          <div className="mt-1 truncate text-ui-11 text-muted-foreground">
             {entry.model}
           </div>
           <div className="mt-2 line-clamp-2 whitespace-pre-wrap break-words text-xs text-muted-foreground">
@@ -137,7 +137,7 @@ function MonitorEntry({
               (entry.status === "running" ? "Waiting..." : "No preview")}
           </div>
         </div>
-        <div className="flex shrink-0 items-start gap-2 text-right text-[11px] text-muted-foreground">
+        <div className="flex shrink-0 items-start gap-2 text-right text-ui-11 text-muted-foreground">
           <div>
             <div>{formatTime(entry.started_at)}</div>
             <div>{formatDuration(entry.duration_ms)}</div>
@@ -155,7 +155,7 @@ function MonitorEntry({
         <div className="border-t border-border/60 p-3 pt-2">
           <div className="grid gap-2">
             <div>
-              <div className="mb-1 flex items-center justify-between gap-2 text-[10px] font-semibold uppercase text-muted-foreground">
+              <div className="mb-1 flex items-center justify-between gap-2 text-ui-10 font-semibold uppercase text-muted-foreground">
                 <span>Prompt</span>
                 {entry.prompt_truncated && !detail ? <span>Preview</span> : null}
               </div>
@@ -164,7 +164,7 @@ function MonitorEntry({
               </pre>
             </div>
             <div>
-              <div className="mb-1 flex items-center justify-between gap-2 text-[10px] font-semibold uppercase text-muted-foreground">
+              <div className="mb-1 flex items-center justify-between gap-2 text-ui-10 font-semibold uppercase text-muted-foreground">
                 <span>Reply</span>
                 {entry.reply_truncated && !detail ? <span>Preview</span> : null}
               </div>
@@ -174,7 +174,7 @@ function MonitorEntry({
             </div>
           </div>
 
-          <div className="mt-3 text-[11px] text-muted-foreground">
+          <div className="mt-3 text-ui-11 text-muted-foreground">
             {formatTokens(entry)}
             {entry.context_length ? (
               <> / {entry.context_length.toLocaleString()} context</>
diff --git a/studio/frontend/src/features/settings/components/archived-chats-dialog.tsx b/studio/frontend/src/features/settings/components/archived-chats-dialog.tsx
index c4932ccc5b..43b2900fbe 100644
--- a/studio/frontend/src/features/settings/components/archived-chats-dialog.tsx
+++ b/studio/frontend/src/features/settings/components/archived-chats-dialog.tsx
@@ -22,10 +22,14 @@ import {
 import { toast } from "@/lib/toast";
 import { ArchiveRestoreIcon, Delete02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
+import { Button } from "@/components/ui/button";
 import { useNavigate, useRouterState } from "@tanstack/react-router";
 import { useState } from "react";
 import { useSettingsDialogStore } from "../stores/settings-dialog-store";
 
+/** Archived chats shown per page; "Show more" reveals the next page. */
+const ARCHIVED_PAGE_SIZE = 20;
+
 function formatCreatedAt(ms: number): string {
   return new Date(ms).toLocaleDateString(undefined, {
     year: "numeric",
@@ -54,6 +58,9 @@ export function ArchivedChatsView() {
   const [confirmingDelete, setConfirmingDelete] = useState<SidebarItem | null>(
     null,
   );
+  // Pagination: the view remounts with its settings tab, so plain state
+  // restarts from the first page on each visit.
+  const [visibleCount, setVisibleCount] = useState(ARCHIVED_PAGE_SIZE);
 
   // Open an archived chat: leave it archived, just navigate to it.
   function openChat(item: SidebarItem) {
@@ -113,7 +120,7 @@ export function ArchivedChatsView() {
             <span className="w-32 shrink-0">Date created</span>
             <span className="w-16 shrink-0" />
           </div>
-          {archivedItems.map((item) => (
+          {archivedItems.slice(0, visibleCount).map((item) => (
             <div
               key={item.id}
               className="group flex items-center gap-4 border-b border-border/40 px-1 py-2.5 text-sm last:border-0"
@@ -159,6 +166,19 @@ export function ArchivedChatsView() {
               </span>
             </div>
           ))}
+          {archivedItems.length > visibleCount ? (
+            <div className="flex justify-center pt-3">
+              <Button
+                variant="outline"
+                size="sm"
+                onClick={() =>
+                  setVisibleCount(visibleCount + ARCHIVED_PAGE_SIZE)
+                }
+              >
+                Show more ({archivedItems.length - visibleCount})
+              </Button>
+            </div>
+          ) : null}
         </div>
       )}
 
diff --git a/studio/frontend/src/features/settings/components/change-password-dialog.tsx b/studio/frontend/src/features/settings/components/change-password-dialog.tsx
index cd30d37d5d..c88fc48cac 100644
--- a/studio/frontend/src/features/settings/components/change-password-dialog.tsx
+++ b/studio/frontend/src/features/settings/components/change-password-dialog.tsx
@@ -78,6 +78,9 @@ function passwordValidationMessage(
       minLength: MIN_PASSWORD_LENGTH,
     });
   }
+  if (/\s/.test(nextPassword)) {
+    return t("settings.general.passwordDialog.newHasSpaces");
+  }
   if (nextPassword !== confirmPassword) {
     return t("settings.general.passwordDialog.mismatch");
   }
@@ -160,6 +163,7 @@ export function ChangePasswordDialog() {
 
   const currentTooShort = hasStartedTooShortPassword(current);
   const nextTooShort = hasStartedTooShortPassword(next);
+  const nextHasSpaces = /\s/.test(next);
   const mismatch = confirm.length > 0 && next !== confirm;
   const samePassword = hasReusablePassword(current, next);
   const validationMessage = passwordValidationMessage(
@@ -279,13 +283,15 @@ export function ChangePasswordDialog() {
                 minLength={MIN_PASSWORD_LENGTH}
                 disabled={submitting}
               />
-              {nextTooShort || samePassword ? (
+              {nextTooShort || nextHasSpaces || samePassword ? (
                 <p className="text-xs text-destructive" aria-live="polite">
                   {nextTooShort
                     ? t("settings.general.passwordDialog.newTooShort", {
                         minLength: MIN_PASSWORD_LENGTH,
                       })
-                    : t("settings.general.passwordDialog.samePassword")}
+                    : nextHasSpaces
+                      ? t("settings.general.passwordDialog.newHasSpaces")
+                      : t("settings.general.passwordDialog.samePassword")}
                 </p>
               ) : null}
             </div>
diff --git a/studio/frontend/src/features/settings/components/color-picker.tsx b/studio/frontend/src/features/settings/components/color-picker.tsx
index d42e439349..77ff8b1b7f 100644
--- a/studio/frontend/src/features/settings/components/color-picker.tsx
+++ b/studio/frontend/src/features/settings/components/color-picker.tsx
@@ -156,7 +156,7 @@ export function ColorPickerSwatch({
           type="button"
           aria-label={label}
           className={cn(
-            "flex h-8 w-24 cursor-pointer items-center gap-1.5 rounded-full border px-2.5 font-mono text-xs uppercase transition-colors",
+            "flex h-8 min-w-24 cursor-pointer items-center gap-1.5 rounded-full border px-2.5 font-mono text-xs uppercase transition-colors",
             light
               ? "border-black/10 text-black/80"
               : "border-white/15 text-white",
diff --git a/studio/frontend/src/features/settings/components/create-key-form.tsx b/studio/frontend/src/features/settings/components/create-key-form.tsx
index 642d9ad320..a16f67f1c1 100644
--- a/studio/frontend/src/features/settings/components/create-key-form.tsx
+++ b/studio/frontend/src/features/settings/components/create-key-form.tsx
@@ -64,7 +64,7 @@ export function CreateKeyForm({
                 onClick={() => setExpiry(p.value)}
                 aria-pressed={active}
                 className={cn(
-                  "inline-flex h-8 items-center rounded-full px-3.5 text-[12px] font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+                  "inline-flex h-8 items-center rounded-full px-3.5 text-ui-12 font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
                   active
                     ? "hub-tab-toggle-pill text-foreground"
                     : "text-muted-foreground hover:text-foreground",
diff --git a/studio/frontend/src/features/settings/components/dictation-dictionary-view.tsx b/studio/frontend/src/features/settings/components/dictation-dictionary-view.tsx
new file mode 100644
index 0000000000..41b8b21156
--- /dev/null
+++ b/studio/frontend/src/features/settings/components/dictation-dictionary-view.tsx
@@ -0,0 +1,132 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { Button } from "@/components/ui/button";
+import { Input } from "@/components/ui/input";
+import { useT } from "@/i18n";
+import {
+  ArrowLeft01Icon,
+  Delete02Icon,
+  PlusSignIcon,
+} from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { useState } from "react";
+import { useVoiceSettingsStore } from "../stores/voice-settings-store";
+
+// Full-page editor for the dictation dictionary. Kept on its own subpage so a
+// long list of entries does not crowd the main Voice settings.
+export function DictationDictionaryView({ onBack }: { onBack: () => void }) {
+  const t = useT();
+  const dictionary = useVoiceSettingsStore((s) => s.dictionary);
+  const addDictionaryEntry = useVoiceSettingsStore((s) => s.addDictionaryEntry);
+  const updateDictionaryEntry = useVoiceSettingsStore(
+    (s) => s.updateDictionaryEntry,
+  );
+  const commitDictionaryEntry = useVoiceSettingsStore(
+    (s) => s.commitDictionaryEntry,
+  );
+  const removeDictionaryEntry = useVoiceSettingsStore(
+    (s) => s.removeDictionaryEntry,
+  );
+  const [newEntry, setNewEntry] = useState("");
+
+  const handleAddEntry = () => {
+    const trimmed = newEntry.trim();
+    if (!trimmed) return;
+    addDictionaryEntry(trimmed);
+    setNewEntry("");
+  };
+
+  return (
+    <div className="flex flex-col gap-6">
+      <header className="flex items-center gap-2">
+        <button
+          type="button"
+          onClick={onBack}
+          aria-label={t("settings.voice.dictionary.backToVoice")}
+          className="inline-flex size-7 shrink-0 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-muted hover:text-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring"
+        >
+          <HugeiconsIcon icon={ArrowLeft01Icon} className="size-4" />
+        </button>
+        <h1 className="font-heading text-xl font-semibold">
+          {t("settings.voice.title")}
+        </h1>
+      </header>
+
+      <div className="flex flex-col gap-1">
+        <h2 className="text-sm font-semibold">
+          {t("settings.voice.dictionary.sectionTitle")}
+        </h2>
+        <p className="text-xs text-muted-foreground">
+          {t("settings.voice.dictionary.sectionDescription")}
+        </p>
+      </div>
+
+      <div className="flex flex-col">
+        {dictionary.map((entry, index) => (
+          <div
+            // biome-ignore lint/suspicious/noArrayIndexKey: entries are editable in place
+            key={index}
+            className="flex items-center gap-2 py-1.5"
+          >
+            <Input
+              value={entry}
+              onChange={(e) => updateDictionaryEntry(index, e.target.value)}
+              // Tabbing to this row's remove button must not commit-splice the
+              // row first, which shifts indices and deletes the wrong entry.
+              onBlur={(e) => {
+                if (
+                  e.relatedTarget instanceof HTMLElement &&
+                  e.relatedTarget.dataset.removeIndex === String(index)
+                ) {
+                  return;
+                }
+                commitDictionaryEntry(index);
+              }}
+              className="h-8 flex-1 text-sm"
+              aria-label={`Dictionary entry ${index + 1}`}
+            />
+            <Button
+              variant="ghost"
+              size="icon"
+              className="size-8 shrink-0 text-muted-foreground hover:text-destructive"
+              data-remove-index={index}
+              // Keep the click from blurring an empty input first, which would
+              // commit-splice this row and make onClick delete the next one.
+              onMouseDown={(e) => e.preventDefault()}
+              onClick={() => removeDictionaryEntry(index)}
+              aria-label={`Remove dictionary entry ${index + 1}`}
+            >
+              <HugeiconsIcon icon={Delete02Icon} className="size-3.5" />
+            </Button>
+          </div>
+        ))}
+        <div className="flex items-center gap-2 py-1.5">
+          <Input
+            value={newEntry}
+            onChange={(e) => setNewEntry(e.target.value)}
+            onKeyDown={(e) => {
+              if (e.key === "Enter") {
+                e.preventDefault();
+                handleAddEntry();
+              }
+            }}
+            placeholder="Jane Doe"
+            className="h-8 flex-1 text-sm"
+            aria-label="New dictionary entry"
+          />
+          <Button
+            variant="outline"
+            size="sm"
+            className="shrink-0"
+            onClick={handleAddEntry}
+            disabled={!newEntry.trim()}
+          >
+            <HugeiconsIcon icon={PlusSignIcon} className="mr-1.5 size-3.5" />
+            {t("settings.voice.dictionary.addEntry")}
+          </Button>
+        </div>
+      </div>
+    </div>
+  );
+}
diff --git a/studio/frontend/src/features/settings/components/embedding-model-combobox.tsx b/studio/frontend/src/features/settings/components/embedding-model-combobox.tsx
index b0e9a41b7d..28df663ec7 100644
--- a/studio/frontend/src/features/settings/components/embedding-model-combobox.tsx
+++ b/studio/frontend/src/features/settings/components/embedding-model-combobox.tsx
@@ -100,7 +100,7 @@ export function EmbeddingModelCombobox({
         autoHighlight={true}
       >
         <ComboboxInput
-          className="h-8 w-full font-mono [&_input]:text-[11px]"
+          className="h-8 w-full font-mono [&_input]:text-ui-11"
           placeholder={placeholder}
           aria-label={ariaLabel}
           disabled={disabled}
@@ -123,7 +123,7 @@ export function EmbeddingModelCombobox({
                   selectingRef.current = true;
                 }}
               >
-                <span className="truncate font-mono text-[11px]">{id}</span>
+                <span className="truncate font-mono text-ui-11">{id}</span>
               </ComboboxItem>
             )}
           </ComboboxList>
diff --git a/studio/frontend/src/features/settings/components/key-reveal-card.tsx b/studio/frontend/src/features/settings/components/key-reveal-card.tsx
index 34517cf3bd..80c93d7770 100644
--- a/studio/frontend/src/features/settings/components/key-reveal-card.tsx
+++ b/studio/frontend/src/features/settings/components/key-reveal-card.tsx
@@ -61,7 +61,7 @@ export function KeyRevealCard({
         />
       </button>
       <div className="flex items-center justify-between gap-3 pt-0.5">
-        <p className="text-[11px] text-muted-foreground">
+        <p className="text-ui-11 text-muted-foreground">
           {t("settings.apiKeys.copyNow")}
         </p>
         <Button
diff --git a/studio/frontend/src/features/settings/components/recent-dictations-view.tsx b/studio/frontend/src/features/settings/components/recent-dictations-view.tsx
new file mode 100644
index 0000000000..f4c58818bd
--- /dev/null
+++ b/studio/frontend/src/features/settings/components/recent-dictations-view.tsx
@@ -0,0 +1,515 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  AlertDialog,
+  AlertDialogAction,
+  AlertDialogCancel,
+  AlertDialogContent,
+  AlertDialogDescription,
+  AlertDialogFooter,
+  AlertDialogHeader,
+  AlertDialogTitle,
+} from "@/components/ui/alert-dialog";
+import { Button } from "@/components/ui/button";
+import {
+  InputGroup,
+  InputGroupAddon,
+  InputGroupInput,
+} from "@/components/ui/input-group";
+import {
+  Select,
+  SelectContent,
+  SelectItem,
+  SelectTrigger,
+  SelectValue,
+} from "@/components/ui/select";
+import {
+  deleteChatItem,
+  useChatRuntimeStore,
+  type SidebarItem,
+} from "@/features/chat";
+import { useT } from "@/i18n";
+import { copyToClipboard } from "@/lib/copy-to-clipboard";
+import { toast } from "@/lib/toast";
+import {
+  ArrowLeft01Icon,
+  Copy01Icon,
+  Delete02Icon,
+  Message01Icon,
+  Search01Icon,
+  ViewIcon,
+} from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { useNavigate } from "@tanstack/react-router";
+import { useMemo, useState } from "react";
+import {
+  type RecentDictation,
+  useVoiceSettingsStore,
+} from "../stores/voice-settings-store";
+import { useSettingsDialogStore } from "../stores/settings-dialog-store";
+
+/** Dictations shown per page; "Show more" reveals the next page. */
+const PAGE_SIZE = 20;
+
+type PendingDelete =
+  | { kind: "one"; dictation: RecentDictation }
+  | { kind: "all" }
+  | null;
+
+type SortOrder = "newest" | "oldest" | "az";
+
+function formatDictationDate(ms: number): string {
+  return new Date(ms).toLocaleString(undefined, {
+    year: "numeric",
+    month: "short",
+    day: "numeric",
+    hour: "numeric",
+    minute: "2-digit",
+  });
+}
+
+export function RecentDictationsView({
+  selectedId,
+  onSelect,
+  onBack,
+}: {
+  selectedId: string | null;
+  onSelect: (id: string | null) => void;
+  onBack: () => void;
+}) {
+  const t = useT();
+  const recentDictations = useVoiceSettingsStore((s) => s.recentDictations);
+  const removeRecentDictation = useVoiceSettingsStore(
+    (s) => s.removeRecentDictation,
+  );
+  const clearRecentDictations = useVoiceSettingsStore(
+    (s) => s.clearRecentDictations,
+  );
+  const [pendingDelete, setPendingDelete] = useState<PendingDelete>(null);
+  const [search, setSearch] = useState("");
+  const [sortOrder, setSortOrder] = useState<SortOrder>("newest");
+  // Pagination is keyed to the search/sort inputs so changing either restarts
+  // from the first page without an effect.
+  const pageKey = `${sortOrder}::${search}`;
+  const [page, setPage] = useState({ key: pageKey, count: PAGE_SIZE });
+  const visibleCount = page.key === pageKey ? page.count : PAGE_SIZE;
+  const navigate = useNavigate();
+  const closeSettings = useSettingsDialogStore((s) => s.closeDialog);
+  const selected =
+    recentDictations.find((dictation) => dictation.id === selectedId) ?? null;
+
+  function openChat(chatId: string) {
+    closeSettings();
+    void navigate({ to: "/chat", search: { thread: chatId } });
+  }
+
+  const visible = useMemo(() => {
+    const query = search.trim().toLowerCase();
+    const filtered = query
+      ? recentDictations.filter((d) => d.text.toLowerCase().includes(query))
+      : recentDictations;
+    const sorted = [...filtered];
+    if (sortOrder === "oldest") {
+      sorted.sort((a, b) => a.at - b.at);
+    } else if (sortOrder === "az") {
+      sorted.sort((a, b) => a.text.localeCompare(b.text));
+    } else {
+      sorted.sort((a, b) => b.at - a.at);
+    }
+    return sorted;
+  }, [recentDictations, search, sortOrder]);
+
+  async function handleCopy(text: string) {
+    if (await copyToClipboard(text)) {
+      toast.success(t("settings.voice.recents.copied"));
+    } else {
+      toast.error(t("settings.voice.recents.copyFailed"));
+    }
+  }
+
+  function confirmDelete() {
+    try {
+      if (pendingDelete?.kind === "one") {
+        removeRecentDictation(pendingDelete.dictation.id);
+        if (pendingDelete.dictation.id === selectedId) {
+          onSelect(null);
+        }
+      } else if (pendingDelete?.kind === "all") {
+        clearRecentDictations();
+        onSelect(null);
+      }
+    } finally {
+      setPendingDelete(null);
+    }
+  }
+
+  // Delete a linked dictation together with the chat it was used in.
+  async function confirmDeleteWithChat() {
+    if (pendingDelete?.kind !== "one") {
+      return;
+    }
+    const dictation = pendingDelete.dictation;
+    setPendingDelete(null);
+    if (dictation.chatId) {
+      const item: SidebarItem = {
+        type: "single",
+        id: dictation.chatId,
+        title: "",
+        createdAt: 0,
+        updatedAt: 0,
+      };
+      try {
+        await deleteChatItem(
+          item,
+          useChatRuntimeStore.getState().activeThreadId ?? undefined,
+          () => {
+            // The deleted chat was open; leave the user on a fresh chat.
+            void navigate({
+              to: "/chat",
+              search: { new: crypto.randomUUID() },
+            });
+          },
+        );
+      } catch (error) {
+        toast.error(t("settings.voice.recents.deleteWithChatFailed"), {
+          description: error instanceof Error ? error.message : undefined,
+        });
+        return;
+      }
+    }
+    removeRecentDictation(dictation.id);
+    if (dictation.id === selectedId) {
+      onSelect(null);
+    }
+  }
+
+  return (
+    <div className="flex flex-col gap-6">
+      <header className="flex items-center gap-2">
+        <button
+          type="button"
+          onClick={() => (selected ? onSelect(null) : onBack())}
+          aria-label={
+            selected
+              ? t("settings.voice.recents.backToRecents")
+              : t("settings.voice.recents.backToVoice")
+          }
+          className="inline-flex size-7 shrink-0 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-muted hover:text-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring"
+        >
+          <HugeiconsIcon icon={ArrowLeft01Icon} className="size-4" />
+        </button>
+        <h1 className="font-heading text-xl font-semibold">
+          {t("settings.voice.title")}
+        </h1>
+      </header>
+
+      <div className="flex flex-col gap-1">
+        <h2 className="text-sm font-semibold">
+          {selected
+            ? t("settings.voice.recents.detailTitle")
+            : t("settings.voice.recents.sectionTitle")}
+        </h2>
+        <p className="text-xs text-muted-foreground">
+          {selected
+            ? formatDictationDate(selected.at)
+            : t("settings.voice.recents.pageDescription")}
+        </p>
+      </div>
+
+      {selected ? (
+        <div className="flex min-h-0 flex-col gap-4">
+          <article className="rounded-lg border border-border/60 bg-muted/20 p-4">
+            <p className="whitespace-pre-wrap break-words text-sm leading-relaxed text-foreground select-text">
+              {selected.text}
+            </p>
+          </article>
+          <div className="flex justify-end gap-2">
+            {selected.chatId ? (
+              <Button
+                variant="outline"
+                size="sm"
+                onClick={() => openChat(selected.chatId as string)}
+              >
+                <HugeiconsIcon
+                  icon={Message01Icon}
+                  className="mr-1.5 size-3.5"
+                />
+                {t("settings.voice.recents.openChat")}
+              </Button>
+            ) : null}
+            <Button
+              variant="outline"
+              size="sm"
+              onClick={async () => {
+                await handleCopy(selected.text);
+              }}
+            >
+              <HugeiconsIcon icon={Copy01Icon} className="mr-1.5 size-3.5" />
+              {t("settings.voice.recents.copy")}
+            </Button>
+            <Button
+              variant="outline"
+              size="sm"
+              onClick={() =>
+                setPendingDelete({ kind: "one", dictation: selected })
+              }
+              className="text-destructive hover:border-destructive/60 hover:text-destructive"
+            >
+              <HugeiconsIcon icon={Delete02Icon} className="mr-1.5 size-3.5" />
+              {t("settings.voice.recents.delete")}
+            </Button>
+          </div>
+        </div>
+      ) : recentDictations.length === 0 ? (
+        <p className="py-8 text-center text-sm text-muted-foreground">
+          {t("settings.voice.recents.empty")}
+        </p>
+      ) : (
+        <div className="flex flex-col gap-3">
+          <div className="flex items-center gap-2">
+            <InputGroup className="h-8 flex-1">
+              <InputGroupAddon align="inline-start">
+                <HugeiconsIcon
+                  icon={Search01Icon}
+                  strokeWidth={2}
+                  className="size-3.5 text-muted-foreground"
+                />
+              </InputGroupAddon>
+              <InputGroupInput
+                value={search}
+                onChange={(e) => setSearch(e.target.value)}
+                placeholder={t("settings.voice.recents.searchPlaceholder")}
+                aria-label={t("settings.voice.recents.searchPlaceholder")}
+                className="text-sm"
+              />
+            </InputGroup>
+            <Select
+              value={sortOrder}
+              onValueChange={(value) => setSortOrder(value as SortOrder)}
+            >
+              <SelectTrigger
+                size="sm"
+                className="w-36 shrink-0"
+                aria-label={t("settings.voice.recents.sortLabel")}
+              >
+                <SelectValue />
+              </SelectTrigger>
+              <SelectContent>
+                <SelectItem value="newest">
+                  {t("settings.voice.recents.sortNewest")}
+                </SelectItem>
+                <SelectItem value="oldest">
+                  {t("settings.voice.recents.sortOldest")}
+                </SelectItem>
+                <SelectItem value="az">
+                  {t("settings.voice.recents.sortAlpha")}
+                </SelectItem>
+              </SelectContent>
+            </Select>
+            <Button
+              variant="outline"
+              size="sm"
+              onClick={() => setPendingDelete({ kind: "all" })}
+              className="shrink-0 text-destructive hover:border-destructive/60 hover:text-destructive"
+            >
+              <HugeiconsIcon icon={Delete02Icon} className="mr-1.5 size-3.5" />
+              {t("settings.voice.recents.clear")}
+            </Button>
+          </div>
+
+          {visible.length === 0 ? (
+            <p className="py-8 text-center text-sm text-muted-foreground">
+              {t("settings.voice.recents.noMatches")}
+            </p>
+          ) : (
+            <div className="flex flex-col">
+              <div className="flex items-center gap-4 border-b border-border/60 px-1 pb-2 text-xs font-semibold text-foreground">
+                <span className="min-w-0 flex-1">
+                  {t("settings.voice.recents.dictationColumn")}
+                </span>
+                <span className="hidden w-40 shrink-0 items-center gap-1.5 sm:flex">
+                  {/* Spacer matching the row's chat-link icon slot so the
+                      header starts exactly where the dates start. */}
+                  <span className="size-3.5 shrink-0" />
+                  {t("settings.voice.recents.dateColumn")}
+                </span>
+                <span className="w-24 shrink-0" />
+              </div>
+              {visible.slice(0, visibleCount).map((dictation) => (
+                <div
+                  key={dictation.id}
+                  className="group flex items-stretch gap-2 border-b border-border/40 last:border-0"
+                >
+                  <button
+                    type="button"
+                    onClick={() =>
+                      dictation.chatId
+                        ? openChat(dictation.chatId)
+                        : onSelect(dictation.id)
+                    }
+                    aria-label={
+                      dictation.chatId
+                        ? t("settings.voice.recents.openChat")
+                        : t("settings.voice.recents.view")
+                    }
+                    className="flex min-w-0 flex-1 items-start gap-4 rounded-md px-1 py-3 text-left transition-colors hover:bg-muted/50 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring"
+                  >
+                    <span className="min-w-0 flex-1">
+                      <span className="line-clamp-3 whitespace-pre-wrap break-words text-sm text-foreground">
+                        {dictation.text}
+                      </span>
+                      <span className="mt-1 flex items-center gap-1.5 text-xs text-muted-foreground sm:hidden">
+                        {dictation.chatId ? (
+                          <HugeiconsIcon
+                            icon={Message01Icon}
+                            className="size-3"
+                          />
+                        ) : null}
+                        {formatDictationDate(dictation.at)}
+                      </span>
+                    </span>
+                    <span className="hidden w-40 shrink-0 items-center gap-1.5 text-left text-xs text-muted-foreground tabular-nums sm:flex">
+                      {/* Fixed icon slot keeps every date starting at the
+                          same column whether or not a chat is linked. */}
+                      <span className="flex size-3.5 shrink-0 items-center justify-center">
+                        {dictation.chatId ? (
+                          <HugeiconsIcon
+                            icon={Message01Icon}
+                            className="size-3.5"
+                            aria-label={t("settings.voice.recents.openChat")}
+                          />
+                        ) : null}
+                      </span>
+                      <span className="whitespace-nowrap">
+                        {formatDictationDate(dictation.at)}
+                      </span>
+                    </span>
+                  </button>
+                  <span className="flex w-24 shrink-0 items-center justify-end gap-1">
+                    {dictation.chatId ? (
+                      <button
+                        type="button"
+                        onClick={() => onSelect(dictation.id)}
+                        aria-label={t("settings.voice.recents.view")}
+                        title={t("settings.voice.recents.view")}
+                        className="inline-flex size-7 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-muted hover:text-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring"
+                      >
+                        <HugeiconsIcon
+                          icon={ViewIcon}
+                          strokeWidth={1.75}
+                          className="size-4"
+                        />
+                      </button>
+                    ) : null}
+                    <button
+                      type="button"
+                      onClick={async () => {
+                        await handleCopy(dictation.text);
+                      }}
+                      aria-label={t("settings.voice.recents.copy")}
+                      title={t("settings.voice.recents.copy")}
+                      className="inline-flex size-7 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-muted hover:text-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring"
+                    >
+                      <HugeiconsIcon
+                        icon={Copy01Icon}
+                        strokeWidth={1.75}
+                        className="size-4"
+                      />
+                    </button>
+                    <button
+                      type="button"
+                      onClick={() =>
+                        setPendingDelete({ kind: "one", dictation })
+                      }
+                      aria-label={t("settings.voice.recents.delete")}
+                      title={t("settings.voice.recents.delete")}
+                      className="inline-flex size-7 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-destructive/10 hover:text-destructive focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring"
+                    >
+                      <HugeiconsIcon
+                        icon={Delete02Icon}
+                        strokeWidth={1.75}
+                        className="size-4"
+                      />
+                    </button>
+                  </span>
+                </div>
+              ))}
+            </div>
+          )}
+
+          {visible.length > visibleCount ? (
+            <div className="flex justify-center pt-1">
+              <Button
+                variant="outline"
+                size="sm"
+                onClick={() =>
+                  setPage({ key: pageKey, count: visibleCount + PAGE_SIZE })
+                }
+              >
+                {t("settings.voice.recents.showMore", {
+                  count: visible.length - visibleCount,
+                })}
+              </Button>
+            </div>
+          ) : null}
+        </div>
+      )}
+
+      <AlertDialog
+        open={pendingDelete !== null}
+        onOpenChange={(open) => {
+          if (!open) {
+            setPendingDelete(null);
+          }
+        }}
+      >
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>
+              {pendingDelete?.kind === "all"
+                ? t("settings.voice.recents.clearTitle")
+                : t("settings.voice.recents.deleteTitle")}
+            </AlertDialogTitle>
+            <AlertDialogDescription>
+              {pendingDelete?.kind === "all"
+                ? t("settings.voice.recents.clearDescription")
+                : pendingDelete?.kind === "one" &&
+                    pendingDelete.dictation.chatId
+                  ? t("settings.voice.recents.deleteLinkedDescription")
+                  : t("settings.voice.recents.deleteDescription")}
+            </AlertDialogDescription>
+          </AlertDialogHeader>
+          <AlertDialogFooter>
+            <AlertDialogCancel>{t("common.cancel")}</AlertDialogCancel>
+            {pendingDelete?.kind === "one" && pendingDelete.dictation.chatId ? (
+              <AlertDialogAction
+                variant="outline"
+                className="text-destructive hover:border-destructive/60 hover:text-destructive"
+                onClick={(event) => {
+                  // Close only through state so the dismissal can't race a
+                  // click on whatever ends up under the pointer.
+                  event.preventDefault();
+                  void confirmDeleteWithChat();
+                }}
+              >
+                {t("settings.voice.recents.deleteWithChat")}
+              </AlertDialogAction>
+            ) : null}
+            <AlertDialogAction
+              variant="destructive"
+              onClick={(event) => {
+                event.preventDefault();
+                confirmDelete();
+              }}
+            >
+              {pendingDelete?.kind === "all"
+                ? t("settings.voice.recents.clearConfirm")
+                : t("common.delete")}
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
+    </div>
+  );
+}
diff --git a/studio/frontend/src/features/settings/components/sidebar-menu-customizer.tsx b/studio/frontend/src/features/settings/components/sidebar-menu-customizer.tsx
index e7e6576eef..bd8ca69b66 100644
--- a/studio/frontend/src/features/settings/components/sidebar-menu-customizer.tsx
+++ b/studio/frontend/src/features/settings/components/sidebar-menu-customizer.tsx
@@ -45,7 +45,7 @@ function FixedRow({ icon, label }: { icon: IconSvgElement; label: string }) {
       {/* Spacer where the drag handle sits on movable rows. */}
       <span className="size-4" aria-hidden="true" />
       <HugeiconsIcon icon={icon} strokeWidth={1.75} className="size-4" />
-      <span className="text-[13px]">{label}</span>
+      <span className="text-ui-13">{label}</span>
     </div>
   );
 }
@@ -93,7 +93,7 @@ function MovableRow({ item }: { item: SidebarMenuItemPref }) {
         strokeWidth={1.75}
         className="size-4 text-foreground/80"
       />
-      <span className="text-[13px] text-foreground">{t(meta.labelKey)}</span>
+      <span className="text-ui-13 text-foreground">{t(meta.labelKey)}</span>
       <Switch
         className="ml-auto"
         checked={item.visible}
diff --git a/studio/frontend/src/features/settings/components/update-studio-instructions.tsx b/studio/frontend/src/features/settings/components/update-studio-instructions.tsx
index e7ec970cc0..9854fa54e4 100644
--- a/studio/frontend/src/features/settings/components/update-studio-instructions.tsx
+++ b/studio/frontend/src/features/settings/components/update-studio-instructions.tsx
@@ -91,7 +91,7 @@ function CopyableCommand({
         type="text"
         readOnly={true}
         value={command}
-        className="min-w-0 flex-1 bg-transparent px-2 py-1.5 font-mono text-[11px] text-foreground outline-none"
+        className="min-w-0 flex-1 bg-transparent px-2 py-1.5 font-mono text-ui-11 text-foreground outline-none"
         title={command}
         aria-label={t("settings.about.update.commandText", {
           label: copyLabel,
@@ -187,7 +187,7 @@ function ShellToggleButton({
       onClick={onClick}
       aria-pressed={active}
       className={cn(
-        "inline-flex h-8 items-center justify-center rounded-full px-3.5 text-[12px] font-medium transition-colors",
+        "inline-flex h-8 items-center justify-center rounded-full px-3.5 text-ui-12 font-medium transition-colors",
         active
           ? "hub-tab-toggle-pill text-foreground"
           : "cursor-pointer text-muted-foreground hover:text-foreground",
diff --git a/studio/frontend/src/features/settings/components/uploaded-files-dialog.tsx b/studio/frontend/src/features/settings/components/uploaded-files-dialog.tsx
index 3368f07ff2..cb5ed0ad34 100644
--- a/studio/frontend/src/features/settings/components/uploaded-files-dialog.tsx
+++ b/studio/frontend/src/features/settings/components/uploaded-files-dialog.tsx
@@ -526,7 +526,7 @@ export function UploadedFilesView() {
                       {row.name}
                     </span>
                     {row.typeLabel ? (
-                      <span className="shrink-0 rounded-md bg-black/[0.06] px-1.5 py-px text-[9px] font-medium uppercase tracking-wide text-muted-foreground dark:bg-white/[0.1]">
+                      <span className="shrink-0 rounded-md bg-black/[0.06] px-1.5 py-px text-ui-9 font-medium uppercase tracking-wide text-muted-foreground dark:bg-white/[0.1]">
                         {row.typeLabel}
                       </span>
                     ) : null}
diff --git a/studio/frontend/src/features/settings/components/usage-examples.tsx b/studio/frontend/src/features/settings/components/usage-examples.tsx
index 4ccc43d16c..ade181f632 100644
--- a/studio/frontend/src/features/settings/components/usage-examples.tsx
+++ b/studio/frontend/src/features/settings/components/usage-examples.tsx
@@ -454,7 +454,7 @@ function HighlightedCode({
     [code, language],
   );
   return (
-    <div className="max-w-full overflow-x-auto p-3 pr-16 text-[11px] leading-relaxed [&_pre]:!m-0 [&_pre]:!whitespace-pre-wrap [&_pre]:!break-words [&_pre]:!border-0 [&_pre]:!bg-transparent [&_pre]:!p-0 [&_pre]:!text-[11px] [&_pre]:!leading-relaxed [&_code]:!text-[11px] [&_[data-streamdown=code-block]]:!my-0 [&_[data-streamdown=code-block]]:!border-0 [&_[data-streamdown=code-block]]:!bg-transparent [&_[data-streamdown=code-block]]:!p-0 [&_[data-streamdown=code-block]]:!text-[11px]">
+    <div className="max-w-full overflow-x-auto p-3 pr-16 text-ui-11 leading-relaxed [&_pre]:!m-0 [&_pre]:!whitespace-pre-wrap [&_pre]:!break-words [&_pre]:!border-0 [&_pre]:!bg-transparent [&_pre]:!p-0 [&_pre]:!text-ui-11 [&_pre]:!leading-relaxed [&_code]:!text-ui-11 [&_[data-streamdown=code-block]]:!my-0 [&_[data-streamdown=code-block]]:!border-0 [&_[data-streamdown=code-block]]:!bg-transparent [&_[data-streamdown=code-block]]:!p-0 [&_[data-streamdown=code-block]]:!text-ui-11">
       <Streamdown
         mode="static"
         plugins={{ code: codePlugin }}
@@ -668,7 +668,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
               onCheckedChange={handleToggleAutoSwitch}
               aria-label={t("settings.general.modelAutoSwitch.enable")}
             />
-            <span className="text-[11px] font-medium text-foreground">
+            <span className="text-ui-11 font-medium text-foreground">
               {t("settings.general.modelAutoSwitch.enable")}
             </span>
             <Tooltip>
@@ -686,7 +686,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
                   />
                 </button>
               </TooltipTrigger>
-              <TooltipContent className="max-w-[260px] text-[11px] leading-snug">
+              <TooltipContent className="max-w-[260px] text-ui-11 leading-snug">
                 {t("settings.general.modelAutoSwitch.enableDescription")}
               </TooltipContent>
             </Tooltip>
@@ -701,7 +701,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
                 onCheckedChange={handleToggleTunnel}
                 aria-label={t("settings.apiKeys.secureHttps")}
               />
-              <span className="text-[11px] font-medium text-foreground">
+              <span className="text-ui-11 font-medium text-foreground">
                 {t("settings.apiKeys.secureHttps")}
               </span>
               {/* Only when not launched with --secure: the raw 0.0.0.0 port is
@@ -720,7 +720,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
                       />
                     </button>
                   </TooltipTrigger>
-                  <TooltipContent className="max-w-[260px] text-[11px] leading-snug">
+                  <TooltipContent className="max-w-[260px] text-ui-11 leading-snug">
                     {t("settings.apiKeys.secureHttpsHint")}
                   </TooltipContent>
                 </Tooltip>
@@ -730,7 +730,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
               type="button"
               onClick={handleCopyUrl}
               className={cn(
-                "flex min-w-0 items-center gap-1 rounded px-1.5 py-1 text-[11px] text-muted-foreground transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+                "flex min-w-0 items-center gap-1 rounded px-1.5 py-1 text-ui-11 text-muted-foreground transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
                 !useTunnel && "opacity-50",
               )}
               title={cloudflareUrl}
@@ -759,7 +759,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
                   onClick={() => setLang(tab.id)}
                   aria-pressed={active}
                   className={cn(
-                    "rounded-full px-2.5 py-1 text-[11px] font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+                    "rounded-full px-2.5 py-1 text-ui-11 font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
                     active
                       ? "hub-tab-toggle-pill text-foreground"
                       : "text-muted-foreground hover:text-foreground",
@@ -778,7 +778,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
               onClick={() => setOs("unix")}
               aria-pressed={os === "unix"}
               className={cn(
-                "rounded-full px-2.5 py-1 text-[11px] font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+                "rounded-full px-2.5 py-1 text-ui-11 font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
                 os === "unix"
                   ? "hub-tab-toggle-pill text-foreground"
                   : "text-muted-foreground hover:text-foreground",
@@ -791,7 +791,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
               onClick={() => setOs("windows")}
               aria-pressed={os === "windows"}
               className={cn(
-                "rounded-full px-2.5 py-1 text-[11px] font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+                "rounded-full px-2.5 py-1 text-ui-11 font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
                 os === "windows"
                   ? "hub-tab-toggle-pill text-foreground"
                   : "text-muted-foreground hover:text-foreground",
@@ -805,7 +805,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
           <button
             type="button"
             onClick={handleCopy}
-            className="absolute right-2 top-2 z-10 flex items-center gap-1 rounded border border-border bg-background/80 px-1.5 py-1 text-[11px] text-muted-foreground backdrop-blur transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
+            className="absolute right-2 top-2 z-10 flex items-center gap-1 rounded border border-border bg-background/80 px-1.5 py-1 text-ui-11 text-muted-foreground backdrop-blur transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
             aria-label={t("settings.apiKeys.copySnippet")}
           >
             <HugeiconsIcon
@@ -821,10 +821,10 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
           />
         </div>
         <div className="flex min-w-0 flex-col gap-1.5 border-t border-border px-3 py-2.5">
-          <span className="text-[11px] font-semibold text-foreground">
+          <span className="text-ui-11 font-semibold text-foreground">
             {t("settings.apiKeys.codingAgents")}
           </span>
-          <span className="text-[11px] leading-snug text-muted-foreground">
+          <span className="text-ui-11 leading-snug text-muted-foreground">
             {t("settings.apiKeys.codingAgentsHint")}
           </span>
           <div className="flex min-w-0 flex-wrap items-center gap-1">
@@ -846,7 +846,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
                       : undefined
                   }
                   className={cn(
-                    "flex items-center gap-1 rounded-full px-2.5 py-1 text-[11px] font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
+                    "flex items-center gap-1 rounded-full px-2.5 py-1 text-ui-11 font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring",
                     active
                       ? "hub-tab-toggle-pill text-foreground"
                       : "text-muted-foreground hover:text-foreground",
@@ -864,13 +864,13 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
             })}
           </div>
           <div className="relative mt-0.5 min-w-0">
-            <code className="block min-w-0 overflow-x-auto rounded border border-border bg-muted/30 px-2 py-1.5 pr-14 font-mono text-[11px] text-foreground">
+            <code className="block min-w-0 overflow-x-auto rounded border border-border bg-muted/30 px-2 py-1.5 pr-14 font-mono text-ui-11 text-foreground">
               {agentCommand}
             </code>
             <button
               type="button"
               onClick={handleCopyAgent}
-              className="absolute right-1.5 top-1/2 flex -translate-y-1/2 items-center gap-1 rounded border border-border bg-background/80 px-1.5 py-0.5 text-[11px] text-muted-foreground backdrop-blur transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
+              className="absolute right-1.5 top-1/2 flex -translate-y-1/2 items-center gap-1 rounded border border-border bg-background/80 px-1.5 py-0.5 text-ui-11 text-muted-foreground backdrop-blur transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
               aria-label={t("settings.apiKeys.copySnippet")}
             >
               <HugeiconsIcon
@@ -879,7 +879,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
               />
             </button>
           </div>
-          <span className="text-[11px] leading-snug text-muted-foreground">
+          <span className="text-ui-11 leading-snug text-muted-foreground">
             {detectedAgents.length > 0
               ? t("settings.apiKeys.codingAgentsDetectedHint", {
                   agents: detectedAgents
@@ -889,7 +889,7 @@ export function UsageExamples({ apiKey }: { apiKey?: string | null }) {
               : t("settings.apiKeys.codingAgentsSwap")}
           </span>
         </div>
-        <div className="flex flex-wrap items-center gap-x-2 gap-y-1 border-t border-border px-3 py-2 text-[11px] text-muted-foreground">
+        <div className="flex flex-wrap items-center gap-x-2 gap-y-1 border-t border-border px-3 py-2 text-ui-11 text-muted-foreground">
           <span>{t("settings.apiKeys.setupDocs")}</span>
           {DOC_LINKS.map((link) => (
             <a
diff --git a/studio/frontend/src/features/settings/settings-dialog.tsx b/studio/frontend/src/features/settings/settings-dialog.tsx
index d98d1b8ac0..7a3a3c58f7 100644
--- a/studio/frontend/src/features/settings/settings-dialog.tsx
+++ b/studio/frontend/src/features/settings/settings-dialog.tsx
@@ -309,7 +309,7 @@ export function SettingsDialog() {
                         <button
                           type="button"
                           onClick={() => openResult(tab.id)}
-                          className="flex h-[30px] items-center gap-2.5 rounded-full pl-3 pr-2.5 text-[13.5px] font-medium text-muted-foreground transition-colors hover:bg-accent hover:text-accent-foreground"
+                          className="flex h-[30px] items-center gap-2.5 rounded-full pl-3 pr-2.5 text-ui-13p5 font-medium text-muted-foreground transition-colors hover:bg-accent hover:text-accent-foreground"
                         >
                           {tab.iconComponent ? (
                             <tab.iconComponent className="size-icon shrink-0" />
@@ -327,7 +327,7 @@ export function SettingsDialog() {
                             key={entry}
                             type="button"
                             onClick={() => openResult(tab.id, entry)}
-                            className="flex h-[30px] items-center rounded-full pl-10 pr-2.5 text-left text-[14px] text-foreground transition-colors hover:bg-accent hover:text-accent-foreground"
+                            className="flex h-[30px] items-center rounded-full pl-10 pr-2.5 text-left text-ui-14 text-foreground transition-colors hover:bg-accent hover:text-accent-foreground"
                           >
                             <span className="min-w-0 truncate">{entry}</span>
                           </button>
@@ -339,7 +339,7 @@ export function SettingsDialog() {
               ) : null}
               <p
                 className={cn(
-                  "pl-4 pt-3 pb-2.5 text-[13px] font-medium text-muted-foreground max-sm:hidden",
+                  "pl-4 pt-3 pb-2.5 text-ui-13 font-medium text-muted-foreground max-sm:hidden",
                   results !== null && "hidden",
                 )}
               >
@@ -362,7 +362,7 @@ export function SettingsDialog() {
                       type="button"
                       onClick={() => setActiveTab(tab.id)}
                       className={cn(
-                        "relative flex h-[32px] items-center gap-2.5 rounded-full pl-3 pr-2.5 text-[14.5px] leading-[19px] tracking-nav font-medium transition-colors",
+                        "relative flex h-[32px] items-center gap-2.5 rounded-full pl-3 pr-2.5 text-ui-14p5 leading-ui-19 tracking-nav font-medium transition-colors",
                         "max-sm:shrink-0",
                         "focus-visible:outline-none",
                         // The active pill already marks the current tab, so
@@ -401,7 +401,7 @@ export function SettingsDialog() {
                         {t(tab.labelKey)}
                       </span>
                       {tab.badgeKey ? (
-                        <span className="relative z-10 ml-auto rounded-full bg-control-accent/10 px-2 py-1 text-[10px] leading-none font-semibold text-control-accent">
+                        <span className="relative z-10 ml-auto rounded-full bg-control-accent/10 px-2 py-1 text-ui-10 leading-none font-semibold text-control-accent">
                           {t(tab.badgeKey)}
                         </span>
                       ) : null}
diff --git a/studio/frontend/src/features/settings/settings-search.ts b/studio/frontend/src/features/settings/settings-search.ts
index c19b27c732..63b492878f 100644
--- a/studio/frontend/src/features/settings/settings-search.ts
+++ b/studio/frontend/src/features/settings/settings-search.ts
@@ -16,8 +16,6 @@ export const SETTINGS_SEARCH_INDEX: Record<SettingsTab, TranslationKey[]> = {
     "settings.general.huggingFaceToken",
     "settings.general.gettingStarted",
     "settings.general.startOnboarding",
-    "settings.general.storage.sectionTitle",
-    "settings.general.storage.modelsFolder",
     "settings.appearance.language.title",
     "settings.appearance.language.label",
     "settings.general.notifications.sectionTitle",
@@ -71,6 +69,7 @@ export const SETTINGS_SEARCH_INDEX: Record<SettingsTab, TranslationKey[]> = {
     "settings.resources.gpu.title",
     "settings.resources.storage.title",
     "settings.resources.storage.modelsFolder",
+    "settings.resources.storage.futureDownloads",
     "settings.resources.storage.systemDisk",
     "settings.resources.environment.title",
     "settings.resources.environment.backend",
@@ -109,7 +108,6 @@ export const SETTINGS_SEARCH_INDEX: Record<SettingsTab, TranslationKey[]> = {
     "settings.voice.dictation.sectionTitle",
     "settings.voice.dictation.microphoneLabel",
     "settings.voice.dictation.languageLabel",
-    "settings.voice.dictation.testLabel",
     "settings.voice.dictionary.sectionTitle",
     "settings.voice.recents.sectionTitle",
     "settings.voice.readAloud.sectionTitle",
diff --git a/studio/frontend/src/features/settings/stores/appearance-custom-store.ts b/studio/frontend/src/features/settings/stores/appearance-custom-store.ts
index b8c8d96f5a..0e449092e5 100644
--- a/studio/frontend/src/features/settings/stores/appearance-custom-store.ts
+++ b/studio/frontend/src/features/settings/stores/appearance-custom-store.ts
@@ -479,6 +479,8 @@ export function applyCustomizationToDocument(
     "--font-sans",
     c.uiFont ? `"${c.uiFont}", ${DEFAULT_SANS_STACK}` : null,
   );
+  // Custom interface fonts cascade into chat and opt out of its Inter tuning.
+  el.toggleAttribute("data-ui-font", Boolean(c.uiFont));
   setVar(
     "--font-heading",
     c.headingFont ? `"${c.headingFont}", ${DEFAULT_HEADING_STACK}` : null,
@@ -508,11 +510,20 @@ export function applyCustomizationToDocument(
     setVar("--custom-chat-font", null);
   }
 
+  // The UI font size drives a typography scale factor, never the root font
+  // size: rem-based layout geometry must not move with the preference. The
+  // scale reaches text through the --text-* / --text-ui-* / --leading-*
+  // tokens in index.css.
   if (c.uiFontSize !== null && c.uiFontSize !== UI_FONT_SIZE_RANGE.default) {
-    style.fontSize = `${c.uiFontSize}px`;
+    setVar("--ui-font-scale", String(c.uiFontSize / UI_FONT_SIZE_RANGE.default));
+    el.setAttribute("data-ui-font-size", String(c.uiFontSize));
   } else {
-    style.removeProperty("font-size");
+    setVar("--ui-font-scale", null);
+    el.removeAttribute("data-ui-font-size");
   }
+  // Older builds scaled the root font size directly; clear any stale inline
+  // value so layout never scales with the preference again.
+  style.removeProperty("font-size");
 
   if (c.codeFontSize !== null) {
     el.setAttribute("data-code-font-size", "");
diff --git a/studio/frontend/src/features/settings/stores/voice-settings-store.ts b/studio/frontend/src/features/settings/stores/voice-settings-store.ts
index 9e38f4c6ce..5f71085981 100644
--- a/studio/frontend/src/features/settings/stores/voice-settings-store.ts
+++ b/studio/frontend/src/features/settings/stores/voice-settings-store.ts
@@ -2,28 +2,118 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { create } from "zustand";
-import { persist } from "zustand/middleware";
+import { createJSONStorage, persist } from "zustand/middleware";
 
 // Voice preferences in localStorage. Adapters read them at call time so
 // changes apply without reloading the chat runtime.
 
 export interface RecentDictation {
+  id: string;
   text: string;
   at: number;
+  /** Chat the dictation was spoken into, when one was open at the time. */
+  chatId?: string;
 }
 
-const MAX_RECENT_DICTATIONS = 20;
+// Dictation history is kept in full; the list view paginates. QUOTA_TRIM_KEEP is
+// the emergency floor if localStorage runs out of room (see persist wrapper).
+const QUOTA_TRIM_KEEP = 200;
 // Cap stored transcript length so a few long dictations cannot bloat the
 // persisted blob and trip a synchronous localStorage quota error on save.
 const MAX_RECENT_DICTATION_LENGTH = 2000;
 const MAX_DICTIONARY_ENTRIES = 100;
 const MAX_DICTIONARY_ENTRY_LENGTH = 120;
 
+/** Five curated Whisper choices, mirrored by the backend (stt_sidecar.py). */
+export const STT_MODELS = [
+  "tiny",
+  "base",
+  "small",
+  "large-v3-turbo",
+  "large-v3",
+] as const;
+export type DefaultSttModel = (typeof STT_MODELS)[number];
+/** A curated id or a user-selected Hugging Face `owner/model` repository. */
+export type SttModel = string;
+/** Whisper repos downloaded through Studio's existing Model Hub manager. */
+export const STT_MODEL_REPOS: Record<DefaultSttModel, string> = {
+  tiny: "unsloth/whisper-tiny",
+  base: "unsloth/whisper-base",
+  small: "unsloth/whisper-small",
+  "large-v3-turbo": "unsloth/whisper-large-v3-turbo",
+  "large-v3": "unsloth/whisper-large-v3",
+};
+export const DEFAULT_STT_MODEL: DefaultSttModel = "small";
+const HF_REPO_ID =
+  /^[A-Za-z0-9][A-Za-z0-9._-]{0,95}\/[A-Za-z0-9][A-Za-z0-9._-]{0,95}$/;
+
+export function isSttModelId(value: string): boolean {
+  const normalized = value.trim();
+  return (
+    (STT_MODELS as readonly string[]).includes(normalized) ||
+    HF_REPO_ID.test(normalized)
+  );
+}
+
+export function normalizeSttModel(value: unknown): SttModel {
+  if (typeof value !== "string") {
+    return DEFAULT_STT_MODEL;
+  }
+  const normalized = value.trim();
+  return isSttModelId(normalized) ? normalized : DEFAULT_STT_MODEL;
+}
+
+export function getSttModelRepo(model: SttModel): string {
+  return STT_MODEL_REPOS[model as DefaultSttModel] ?? normalizeSttModel(model);
+}
+
+// All curated models are multilingual. Custom `.en` checkpoints are treated as
+// English-only so a later language change falls back safely.
+export const ENGLISH_ONLY_STT_MODELS: ReadonlySet<SttModel> = new Set([]);
+
+/** Whether a model can honor the selected dictation language. */
+export function isSttModelLanguageCompatible(
+  model: SttModel,
+  language: string,
+): boolean {
+  const isEnglishOnly =
+    ENGLISH_ONLY_STT_MODELS.has(model) ||
+    getSttModelRepo(model).toLowerCase().endsWith(".en");
+  if (!isEnglishOnly) {
+    return true;
+  }
+  const normalized = language.trim().replaceAll("_", "-").toLowerCase();
+  // Auto sends no forced language, which English-only checkpoints accept.
+  return normalized === "auto" || normalized.split("-", 1)[0] === "en";
+}
+
+export type DictationEngine = "browser" | "model";
+
+/**
+ * Whether a model id is one of the five curated Whisper choices. Curated models
+ * run GGML through whisper.cpp; custom repos are safetensors and run through
+ * Transformers.
+ */
+export function isCuratedSttModel(model: SttModel): boolean {
+  return (STT_MODELS as readonly string[]).includes(model.trim());
+}
+
 export interface VoiceSettingsState {
   /** Input device for dictation. "default" = system default microphone. */
   micDeviceId: string;
   setMicDeviceId: (value: string) => void;
 
+  /**
+   * "browser": Web Speech API. "model": local transcription; the model decides
+   * the backend (whisper.cpp for curated GGML, Transformers for custom repos).
+   */
+  dictationEngine: DictationEngine;
+  setDictationEngine: (value: DictationEngine) => void;
+
+  /** STT model to use when dictationEngine is "model". */
+  sttModel: SttModel;
+  setSttModel: (value: SttModel) => void;
+
   /** BCP 47 tag for speech recognition, or "auto" for the browser locale. */
   dictationLanguage: string;
   setDictationLanguage: (value: string) => void;
@@ -38,7 +128,8 @@ export interface VoiceSettingsState {
 
   /** Final transcripts, newest first, so text can be recovered. */
   recentDictations: RecentDictation[];
-  addRecentDictation: (text: string) => void;
+  addRecentDictation: (text: string, chatId?: string) => void;
+  removeRecentDictation: (id: string) => void;
   clearRecentDictations: () => void;
 
   /** Show the read-aloud button on assistant responses. */
@@ -61,14 +152,81 @@ export interface VoiceSettingsState {
   setTtsVolume: (value: number) => void;
 }
 
+/**
+ * localStorage wrapper that keeps the full dictation history until the browser's
+ * quota is hit, then drops the oldest entries instead of losing the whole save.
+ */
+const quotaSafeLocalStorage = {
+  getItem: (key: string) => localStorage.getItem(key),
+  removeItem: (key: string) => localStorage.removeItem(key),
+  setItem: (key: string, value: string) => {
+    try {
+      localStorage.setItem(key, value);
+      return;
+    } catch {
+      // Quota exceeded: trim dictation history, oldest first, and retry.
+    }
+    let parsed: { state?: { recentDictations?: RecentDictation[] } };
+    try {
+      parsed = JSON.parse(value) as typeof parsed;
+    } catch {
+      return;
+    }
+    const state = parsed.state;
+    const recents = state?.recentDictations;
+    if (!state || !Array.isArray(recents)) return;
+    // Halve the history until the save fits, down to an empty history, so even
+    // a small history shrinks when another store already consumed the quota.
+    let keep = Math.min(QUOTA_TRIM_KEEP, recents.length);
+    for (;;) {
+      keep = keep >= recents.length ? Math.floor(recents.length / 2) : keep;
+      try {
+        state.recentDictations = recents.slice(0, keep);
+        localStorage.setItem(key, JSON.stringify(parsed));
+        return;
+      } catch {
+        // Still over quota: trim harder.
+      }
+      if (keep === 0) return;
+      keep = Math.floor(keep / 2);
+    }
+  },
+};
+
 export const useVoiceSettingsStore = create<VoiceSettingsState>()(
   persist(
     (set) => ({
       micDeviceId: "default",
       setMicDeviceId: (micDeviceId) => set({ micDeviceId }),
 
+      dictationEngine: "browser",
+      setDictationEngine: (dictationEngine) => set({ dictationEngine }),
+
+      sttModel: DEFAULT_STT_MODEL,
+      setSttModel: (value) =>
+        set((state) => {
+          const sttModel = normalizeSttModel(value);
+          return {
+            sttModel: isSttModelLanguageCompatible(
+              sttModel,
+              state.dictationLanguage,
+            )
+              ? sttModel
+              : DEFAULT_STT_MODEL,
+          };
+        }),
+
       dictationLanguage: "auto",
-      setDictationLanguage: (dictationLanguage) => set({ dictationLanguage }),
+      setDictationLanguage: (dictationLanguage) =>
+        set((state) => ({
+          dictationLanguage,
+          sttModel: isSttModelLanguageCompatible(
+            state.sttModel,
+            dictationLanguage,
+          )
+            ? state.sttModel
+            : DEFAULT_STT_MODEL,
+        })),
 
       dictionary: [],
       addDictionaryEntry: (value) =>
@@ -111,17 +269,31 @@ export const useVoiceSettingsStore = create<VoiceSettingsState>()(
         })),
 
       recentDictations: [],
-      addRecentDictation: (text) =>
+      addRecentDictation: (text, chatId) =>
         set((state) => {
           const trimmed = text.trim().slice(0, MAX_RECENT_DICTATION_LENGTH);
-          if (!trimmed) return state;
+          if (!trimmed) {
+            return state;
+          }
+          const at = Date.now();
           return {
             recentDictations: [
-              { text: trimmed, at: Date.now() },
+              {
+                id: `${at}-${Math.random().toString(36).slice(2, 10)}`,
+                text: trimmed,
+                at,
+                ...(chatId ? { chatId } : {}),
+              },
               ...state.recentDictations,
-            ].slice(0, MAX_RECENT_DICTATIONS),
+            ],
           };
         }),
+      removeRecentDictation: (id) =>
+        set((state) => ({
+          recentDictations: state.recentDictations.filter(
+            (dictation) => dictation.id !== id,
+          ),
+        })),
       clearRecentDictations: () => set({ recentDictations: [] }),
 
       ttsEnabled: true,
@@ -142,30 +314,37 @@ export const useVoiceSettingsStore = create<VoiceSettingsState>()(
     }),
     {
       name: "unsloth_voice_settings",
+      storage: createJSONStorage(() => quotaSafeLocalStorage),
       merge: (persisted, current) => {
         const saved = persisted as Partial<VoiceSettingsState> | undefined;
+        const dictationLanguage = asString(saved?.dictationLanguage, "auto");
+        // "gguf" was a short-lived separate engine choice; both local
+        // backends now live under "model".
+        const savedEngine = saved?.dictationEngine as string | undefined;
+        const dictationEngine: DictationEngine =
+          savedEngine === "model" || savedEngine === "gguf"
+            ? "model"
+            : "browser";
+        const savedSttModel = normalizeSttModel(saved?.sttModel);
+        const sttModel = isSttModelLanguageCompatible(
+          savedSttModel,
+          dictationLanguage,
+        )
+          ? savedSttModel
+          : DEFAULT_STT_MODEL;
         return {
           ...current,
           micDeviceId: asString(saved?.micDeviceId, "default"),
-          dictationLanguage: asString(saved?.dictationLanguage, "auto"),
+          dictationEngine,
+          sttModel,
+          dictationLanguage,
           dictionary: Array.isArray(saved?.dictionary)
             ? saved.dictionary
                 .filter((v): v is string => typeof v === "string" && !!v.trim())
                 .map((v) => v.trim().slice(0, MAX_DICTIONARY_ENTRY_LENGTH))
                 .slice(0, MAX_DICTIONARY_ENTRIES)
             : [],
-          recentDictations: Array.isArray(saved?.recentDictations)
-            ? saved.recentDictations
-                .filter(
-                  (v): v is RecentDictation =>
-                    typeof v?.text === "string" && typeof v?.at === "number",
-                )
-                .slice(0, MAX_RECENT_DICTATIONS)
-                .map((v) => ({
-                  text: v.text.slice(0, MAX_RECENT_DICTATION_LENGTH),
-                  at: v.at,
-                }))
-            : [],
+          recentDictations: normalizeRecentDictations(saved?.recentDictations),
           ttsEnabled:
             typeof saved?.ttsEnabled === "boolean" ? saved.ttsEnabled : true,
           ttsEngine: saved?.ttsEngine === "studio" ? "studio" : "system",
@@ -183,6 +362,40 @@ function asString(value: unknown, fallback: string): string {
   return typeof value === "string" && value ? value : fallback;
 }
 
+function normalizeRecentDictations(value: unknown): RecentDictation[] {
+  if (!Array.isArray(value)) {
+    return [];
+  }
+
+  const normalized: RecentDictation[] = [];
+  for (const [index, entry] of value.entries()) {
+    if (!entry || typeof entry !== "object") {
+      continue;
+    }
+    const candidate = entry as Partial<RecentDictation>;
+    if (
+      typeof candidate.text !== "string" ||
+      !candidate.text.trim() ||
+      typeof candidate.at !== "number" ||
+      !Number.isFinite(candidate.at)
+    ) {
+      continue;
+    }
+    normalized.push({
+      id:
+        typeof candidate.id === "string" && candidate.id
+          ? candidate.id
+          : `legacy-${candidate.at}-${index}`,
+      text: candidate.text.trim().slice(0, MAX_RECENT_DICTATION_LENGTH),
+      at: candidate.at,
+      ...(typeof candidate.chatId === "string" && candidate.chatId
+        ? { chatId: candidate.chatId }
+        : {}),
+    });
+  }
+  return normalized;
+}
+
 function clampNumber(
   value: unknown,
   min: number,
@@ -202,6 +415,47 @@ export function resolveDictationLanguage(setting?: string): string {
     : "en-US";
 }
 
+// Whisper's language codes: transformers `LANGUAGES` keys plus the backend's
+// BCP-47 aliases (stt_sidecar.py `_WHISPER_LANGUAGE_ALIASES`). Keep in sync with
+// `_known_whisper_languages()`; Auto only resolves to a code in this set, so a
+// UI locale Whisper cannot honor stays on auto-detect.
+const WHISPER_DICTATION_LANGUAGES = new Set([
+  "af", "am", "ar", "as", "az", "ba", "be", "bg", "bn", "bo", "br", "bs",
+  "ca", "cmn", "cs", "cy", "da", "de", "el", "en", "es", "et", "eu", "fa",
+  "fi", "fil", "fo", "fr", "gl", "gu", "ha", "haw", "he", "hi", "hr", "ht",
+  "hu", "hy", "id", "in", "is", "it", "iw", "ja", "ji", "jw", "ka", "kk",
+  "km", "kn", "ko", "la", "lb", "ln", "lo", "lt", "lv", "mg", "mi", "mk",
+  "ml", "mn", "mr", "ms", "mt", "my", "nb", "ne", "nl", "nn", "no", "oc",
+  "pa", "pl", "ps", "pt", "ro", "ru", "sa", "sd", "si", "sk", "sl", "sn",
+  "so", "sq", "sr", "su", "sv", "sw", "ta", "te", "tg", "th", "tk", "tl",
+  "tr", "tt", "uk", "ur", "uz", "vi", "yi", "yo", "yue", "zh",
+]);
+
+/**
+ * Resolve Auto for the model STT engine (the browser engine resolves it via
+ * `resolveDictationLanguage`). Only the literal "auto" resolves to a concrete
+ * locale; an explicit or malformed setting passes through unchanged. Gated so
+ * Auto only becomes a language the model AND Whisper can honor, else it stays
+ * auto-detect rather than forcing a locale Whisper cannot handle (e.g. Irish)
+ * or 422ing every dictation.
+ */
+export function resolveModelDictationLanguage(
+  model: SttModel,
+  requested: string,
+): string {
+  if (requested !== "auto") return requested;
+  const resolved = resolveDictationLanguage(requested);
+  const primary = resolved
+    .trim()
+    .replaceAll("_", "-")
+    .toLowerCase()
+    .split("-", 1)[0];
+  return isSttModelLanguageCompatible(model, resolved) &&
+    WHISPER_DICTATION_LANGUAGES.has(primary)
+    ? resolved
+    : requested;
+}
+
 function escapeRegExp(value: string): string {
   return value.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
 }
@@ -240,6 +494,6 @@ export function applyDictationDictionary(
 }
 
 /** Record a finished dictation so it can be recovered from settings. */
-export function recordRecentDictation(text: string): void {
-  useVoiceSettingsStore.getState().addRecentDictation(text);
+export function recordRecentDictation(text: string, chatId?: string): void {
+  useVoiceSettingsStore.getState().addRecentDictation(text, chatId);
 }
diff --git a/studio/frontend/src/features/settings/tabs/chat-tab.tsx b/studio/frontend/src/features/settings/tabs/chat-tab.tsx
index f7f3bccad6..a6fcf87c57 100644
--- a/studio/frontend/src/features/settings/tabs/chat-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/chat-tab.tsx
@@ -16,7 +16,6 @@ import {
   Folder01Icon,
   McpServerIcon,
   PencilRulerIcon,
-  Settings02Icon,
   ShieldBanIcon,
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
@@ -148,10 +147,6 @@ export function ChatTab() {
   const hydratePersistedSettings = useChatRuntimeStore(
     (state) => state.hydratePersistedSettings,
   );
-  const loadOnSelection = useChatRuntimeStore((state) => state.loadOnSelection);
-  const setLoadOnSelection = useChatRuntimeStore(
-    (state) => state.setLoadOnSelection,
-  );
   const expandQuantizations = useChatRuntimeStore(
     (state) => state.expandQuantizations,
   );
@@ -193,40 +188,6 @@ export function ChatTab() {
       </header>
 
       <SettingsSection title="Select model settings">
-        <SettingsRow
-          label="Load on selection"
-          alignTop={true}
-          description={
-            <span>
-              On: Unsloth auto-picks the best settings and loads it.
-              <br />
-              Off: opens Run settings to customize, then load.
-              <br />
-              The gear always opens Run settings:{" "}
-              <span className="ml-2 inline-flex items-center gap-3 align-middle">
-                <span className="font-mono text-xs text-foreground">
-                  Q4_K_M
-                </span>
-                <span className="text-[9px] font-medium text-green-600/90 dark:text-green-400/80">
-                  downloaded
-                </span>
-                <span className="text-[10px] text-muted-foreground">16 GB</span>
-                <span className="inline-flex size-4 items-center justify-center rounded bg-black/[0.06] dark:bg-white/[0.08]">
-                  <HugeiconsIcon
-                    icon={Settings02Icon}
-                    strokeWidth={1.75}
-                    className="size-2.5 text-muted-foreground/80"
-                  />
-                </span>
-              </span>
-            </span>
-          }
-        >
-          <Switch
-            checked={loadOnSelection}
-            onCheckedChange={setLoadOnSelection}
-          />
-        </SettingsRow>
         <SettingsRow
           label="Expand quantizations"
           description={
diff --git a/studio/frontend/src/features/settings/tabs/data-tab.tsx b/studio/frontend/src/features/settings/tabs/data-tab.tsx
index dc9e707ea0..e2b524f46e 100644
--- a/studio/frontend/src/features/settings/tabs/data-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/data-tab.tsx
@@ -39,6 +39,9 @@ import {
   useChatSidebarItems,
 } from "@/features/chat";
 import { useT } from "@/i18n";
+
+import { isTauri } from "@/lib/api-base";
+import { isDownloadCancelled, pickNativeChatImport } from "@/lib/native-files";
 import {
   ChevronDownStandardIcon,
   ChevronRightStandardIcon,
@@ -147,6 +150,12 @@ export function DataTab() {
     setExporting(true);
     try {
       await downloadChatExport();
+    } catch (error) {
+      if (!isDownloadCancelled(error)) {
+        toast.error("Could not export chats", {
+          description: error instanceof Error ? error.message : String(error),
+        });
+      }
     } finally {
       setExporting(false);
     }
@@ -164,9 +173,11 @@ export function DataTab() {
             : t("settings.data.exportedArchivedChatCount", { count: exported }),
       );
     } catch (error) {
-      toast.error(t("settings.data.failedToExportArchivedChats"), {
-        description: error instanceof Error ? error.message : undefined,
-      });
+      if (!isDownloadCancelled(error)) {
+        toast.error(t("settings.data.failedToExportArchivedChats"), {
+          description: error instanceof Error ? error.message : undefined,
+        });
+      }
     } finally {
       setArchivedExporting(false);
     }
@@ -191,6 +202,24 @@ export function DataTab() {
     }
   };
 
+  const handleImportClick = async () => {
+    if (!isTauri) {
+      importInputRef.current?.click();
+      return;
+    }
+    try {
+      const selected = await pickNativeChatImport();
+      if (!selected) {
+        return;
+      }
+      await handleImport(new File([selected.content], selected.name));
+    } catch (error) {
+      toast.error(t("settings.chat.importFailed"), {
+        description: error instanceof Error ? error.message : String(error),
+      });
+    }
+  };
+
   const handleArchiveAll = async () => {
     setArchiving(true);
     try {
@@ -219,9 +248,11 @@ export function DataTab() {
     try {
       await exportFineTuneJsonl(fineTuneFormat);
     } catch (error) {
-      toast.error(t("settings.data.fineTuneExportFailed"), {
-        description: error instanceof Error ? error.message : undefined,
-      });
+      if (!isDownloadCancelled(error)) {
+        toast.error(t("settings.data.fineTuneExportFailed"), {
+          description: error instanceof Error ? error.message : undefined,
+        });
+      }
     } finally {
       setFineTuneExporting(false);
     }
@@ -632,7 +663,7 @@ export function DataTab() {
           <Button
             variant="outline"
             size="sm"
-            onClick={() => importInputRef.current?.click()}
+            onClick={() => void handleImportClick()}
           >
             <HugeiconsIcon icon={Upload01Icon} className="size-3.5 mr-1.5" />
             {t("settings.chat.importChatsAction")}
diff --git a/studio/frontend/src/features/settings/tabs/general-tab.tsx b/studio/frontend/src/features/settings/tabs/general-tab.tsx
index d5a85c01c6..1d5c533a25 100644
--- a/studio/frontend/src/features/settings/tabs/general-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/general-tab.tsx
@@ -15,7 +15,6 @@ import { Switch } from "@/components/ui/switch";
 import { usePlatformStore } from "@/config/env";
 import { resetOnboardingDone } from "@/features/auth";
 import { PermissionModeDropdown, useChatRuntimeStore } from "@/features/chat";
-import { openModelsDir } from "@/features/native-intents";
 import { emitTrainingRunsChanged } from "@/features/training";
 import {
   setShowLlamaUpdateBanner,
@@ -24,7 +23,6 @@ import {
 import { useHfTokenValidation } from "@/hooks";
 import { LOCALE_STORAGE_KEY, useT } from "@/i18n";
 import { isTauri } from "@/lib/api-base";
-import { copyToClipboard } from "@/lib/copy-to-clipboard";
 import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import { useNavigate, useRouterState } from "@tanstack/react-router";
@@ -43,7 +41,6 @@ import {
   loadHelperPrecacheSettings,
   updateHelperPrecacheSettings,
 } from "../api/helper-precache";
-import { type ModelsFolder, loadModelsFolder } from "../api/models-folder";
 import {
   type PreviewSharingSettings,
   loadPreviewSharing,
@@ -93,9 +90,11 @@ const PREFS_KEYS: string[] = [
   "unsloth_chat_inference_params",
   "unsloth_chat_collapsible_state",
   "unsloth_chat_preferences",
+  "unsloth_model_configs",
+  "unsloth_model_configs_migrated",
   "unsloth_load_settings",
-  // Model selector settings ("Select model settings" group)
   "unsloth_chat_load_on_selection",
+  // Model selector settings ("Select model settings" group)
   "unsloth_chat_expand_quantizations",
   "unsloth_chat_show_all_quantizations",
   "unsloth_models_fit_on_device_only",
@@ -181,7 +180,6 @@ export function GeneralTab() {
   const [isSavingPreviewSharing, setIsSavingPreviewSharing] = useState(false);
   const [revokePreviewOpen, setRevokePreviewOpen] = useState(false);
   const [isRevokingPreview, setIsRevokingPreview] = useState(false);
-  const [modelsFolder, setModelsFolder] = useState<ModelsFolder | null>(null);
   const [embeddingModel, setEmbeddingModel] =
     useState<EmbeddingModelSettings | null>(null);
   const [draftEmbeddingModel, setDraftEmbeddingModel] = useState("");
@@ -223,12 +221,13 @@ export function GeneralTab() {
     setHfToken("");
   };
 
-  // Show an "accepted" tick once a non-empty token has been committed to the
-  // store and the field still matches it (i.e. not mid-edit). Gives the user
-  // feedback that a pasted token was saved.
-  const tokenSaved =
+  // Only show the success tick for the currently displayed token after the
+  // authenticated validation endpoint has confirmed it. A saved token alone
+  // may still be malformed, expired, or revoked.
+  const tokenIsCurrent =
     draftToken.trim().length > 0 && draftToken.trim() === (hfToken ?? "");
   const tokenValidation = useHfTokenValidation(hfToken ?? "");
+  const tokenValidated = tokenIsCurrent && tokenValidation.isValid === true;
 
   useEffect(() => {
     let cancelled = false;
@@ -314,43 +313,6 @@ export function GeneralTab() {
     };
   }, [t]);
 
-  useEffect(() => {
-    let cancelled = false;
-    void loadModelsFolder()
-      .then((folder) => {
-        if (cancelled) return;
-        setModelsFolder(folder);
-      })
-      .catch(() => {
-        // Non-critical: leave the row hidden if the path can't be resolved.
-      });
-    return () => {
-      cancelled = true;
-    };
-  }, []);
-
-  // Desktop opens the folder in the OS file manager; the browser can't, so it
-  // falls back to copying the path (which is the info users actually want).
-  const handleModelsFolder = async () => {
-    const folder = modelsFolder;
-    if (!folder) return;
-    if (isTauri) {
-      try {
-        await openModelsDir(folder.path);
-      } catch (error) {
-        toast.error(t("settings.general.storage.openError"), {
-          description: error instanceof Error ? error.message : undefined,
-        });
-      }
-      return;
-    }
-    if (await copyToClipboard(folder.path)) {
-      toast.success(t("settings.general.storage.copied"));
-    } else {
-      toast.error(t("settings.general.storage.copyError"));
-    }
-  };
-
   const saveHelperPrecache = async (enabled: boolean) => {
     setIsSavingHelperPrecache(true);
     setHelperPrecacheError(null);
@@ -520,16 +482,16 @@ export function GeneralTab() {
                   onBlur={commitToken}
                   className={cn(
                     "h-8 w-full font-mono text-xs",
-                    tokenSaved ? "pr-14" : "pr-8",
+                    tokenValidated ? "pr-14" : "pr-8",
                   )}
                 />
-                {tokenSaved ? (
+                {tokenValidated ? (
                   // Decorative: pointer-events-none lets clicks reach the input
                   // underneath so the field still focuses anywhere.
                   <span
                     className="pointer-events-none absolute right-7 top-1/2 flex size-5 -translate-y-1/2 items-center justify-center text-emerald-600 duration-150 animate-in fade-in zoom-in dark:text-emerald-500"
                     role="img"
-                    aria-label={t("settings.general.tokenSaved")}
+                    aria-label={t("settings.general.tokenValidated")}
                   >
                     <Check className="size-4" strokeWidth={2.5} />
                   </span>
@@ -585,33 +547,6 @@ export function GeneralTab() {
         )}
       </SettingsSection>
 
-      {modelsFolder ? (
-        <SettingsSection title={t("settings.general.storage.sectionTitle")}>
-          <SettingsRow
-            label={t("settings.general.storage.modelsFolder")}
-            description={t("settings.general.storage.modelsFolderDescription")}
-          >
-            <div className="flex items-center gap-2">
-              <span
-                title={modelsFolder.path}
-                className="max-w-[280px] truncate font-mono text-xs text-muted-foreground"
-              >
-                {modelsFolder.path}
-              </span>
-              <Button
-                variant="outline"
-                size="sm"
-                onClick={() => void handleModelsFolder()}
-              >
-                {isTauri
-                  ? t("settings.general.storage.openAction")
-                  : t("settings.general.storage.copyAction")}
-              </Button>
-            </div>
-          </SettingsRow>
-        </SettingsSection>
-      ) : null}
-
       <SettingsSection title={t("settings.appearance.language.title")}>
         <SettingsRow
           label={t("settings.appearance.language.label")}
diff --git a/studio/frontend/src/features/settings/tabs/resources-tab.tsx b/studio/frontend/src/features/settings/tabs/resources-tab.tsx
index eb7fa03cf9..b22a54cb0b 100644
--- a/studio/frontend/src/features/settings/tabs/resources-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/resources-tab.tsx
@@ -2,9 +2,14 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { Button } from "@/components/ui/button";
+import { Input } from "@/components/ui/input";
 import { Progress } from "@/components/ui/progress";
 import { Switch } from "@/components/ui/switch";
-import { openModelsDir } from "@/features/native-intents";
+import { FolderBrowser } from "@/features/model-picker";
+import {
+  openModelsDir,
+  pickHuggingFaceCacheDir,
+} from "@/features/native-intents";
 import { useSystemInfo, type GpuDevice } from "@/hooks/use-system";
 import { isTauri } from "@/lib/api-base";
 import { copyToClipboard } from "@/lib/copy-to-clipboard";
@@ -12,11 +17,15 @@ import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import { useT } from "@/i18n";
 import { useEffect, useMemo, useState } from "react";
-import { loadModelsFolder, type ModelsFolder } from "../api/models-folder";
+import {
+  type HuggingFaceCacheSettings,
+  loadHuggingFaceCacheSettings,
+  updateHuggingFaceCacheSettings,
+} from "../api/hugging-face-cache";
 import { SettingsRow } from "../components/settings-row";
 import { SettingsSection } from "../components/settings-section";
 import { useMonitorOverlayStore } from "../stores/monitor-overlay-store";
-import { LayersIcon } from "lucide-react";
+import { CopyIcon, FolderOpenIcon, LayersIcon } from "lucide-react";
 
 const POLL_MS = 3000;
 
@@ -47,6 +56,12 @@ function formatGb(value: number | null | undefined): string {
   return `${safe.toFixed(digits)} GB`;
 }
 
+function formatBytes(value: number | null): string | null {
+  if (value === null || !Number.isFinite(value)) return null;
+  const gib = value / 1024 ** 3;
+  return `${gib >= 10 ? gib.toFixed(1) : gib.toFixed(2)} GiB`;
+}
+
 // RAM/VRAM come from the backend in binary units (bytes / 1024**3), matching
 // nvidia-smi and PyTorch, so label those readouts GiB. Disk stays on formatGb
 // because the backend reports disk in decimal GB (bytes / 1e9).
@@ -99,7 +114,7 @@ function MetricTile({
   return (
     <div className="flex min-w-0 flex-col gap-2 rounded-md border border-border/60 bg-muted/20 p-3">
       <div className="flex items-center justify-between gap-3">
-        <span className="truncate text-[11px] font-semibold uppercase tracking-[0.08em] text-muted-foreground">
+        <span className="truncate text-ui-11 font-semibold uppercase tracking-[0.08em] text-muted-foreground">
           {label}
         </span>
         <span
@@ -165,20 +180,22 @@ export function ResourcesTab() {
     enabled: liveUpdates,
     pollMs: liveUpdates ? POLL_MS : undefined,
   });
-  const [modelsFolder, setModelsFolder] = useState<ModelsFolder | null>(null);
-  const [modelsFolderLoaded, setModelsFolderLoaded] = useState(false);
+  const [hfCache, setHfCache] = useState<HuggingFaceCacheSettings | null>(null);
+  const [hfCacheLoaded, setHfCacheLoaded] = useState(false);
+  const [cacheBrowserOpen, setCacheBrowserOpen] = useState(false);
+  const [cacheSaving, setCacheSaving] = useState(false);
 
   useEffect(() => {
     let cancelled = false;
-    void loadModelsFolder()
-      .then((folder) => {
+    void loadHuggingFaceCacheSettings()
+      .then((settings) => {
         if (cancelled) return;
-        setModelsFolder(folder);
-        setModelsFolderLoaded(true);
+        setHfCache(settings);
+        setHfCacheLoaded(true);
       })
       .catch(() => {
         if (cancelled) return;
-        setModelsFolderLoaded(true);
+        setHfCacheLoaded(true);
       });
     return () => {
       cancelled = true;
@@ -237,12 +254,11 @@ export function ResourcesTab() {
     };
   }, [systemInfo]);
 
-  const handleModelsFolder = async () => {
-    const folder = modelsFolder;
-    if (!folder) return;
+  const handleCacheFolder = async () => {
+    if (!hfCache) return;
     if (isTauri) {
       try {
-        await openModelsDir(folder.path);
+        await openModelsDir(hfCache.cacheHome);
       } catch (error) {
         toast.error(t("settings.resources.storage.openError"), {
           description: error instanceof Error ? error.message : undefined,
@@ -250,13 +266,43 @@ export function ResourcesTab() {
       }
       return;
     }
-    if (await copyToClipboard(folder.path)) {
+    if (await copyToClipboard(hfCache.cacheHome)) {
       toast.success(t("settings.resources.storage.copied"));
     } else {
       toast.error(t("settings.resources.storage.copyError"));
     }
   };
 
+  const saveCacheFolder = async (path: string | null) => {
+    setCacheSaving(true);
+    try {
+      const settings = await updateHuggingFaceCacheSettings(path);
+      setHfCache(settings);
+      toast.success(t("settings.resources.storage.cacheSaved"));
+    } catch (error) {
+      toast.error(t("settings.resources.storage.cacheSaveError"), {
+        description: error instanceof Error ? error.message : undefined,
+      });
+    } finally {
+      setCacheSaving(false);
+    }
+  };
+
+  const changeCacheFolder = async () => {
+    if (!isTauri) {
+      setCacheBrowserOpen(true);
+      return;
+    }
+    try {
+      const path = await pickHuggingFaceCacheDir();
+      if (path) await saveCacheFolder(path);
+    } catch (error) {
+      toast.error(t("settings.resources.storage.cachePickerError"), {
+        description: error instanceof Error ? error.message : undefined,
+      });
+    }
+  };
+
   const cpuCoresLabel =
     systemInfo.cpu?.logical_count && systemInfo.cpu?.physical_count
       ? t("settings.resources.liveMonitor.cpuCores", {
@@ -270,11 +316,27 @@ export function ResourcesTab() {
   const backendLabel = (
     systemInfo.gpu?.backend ?? systemInfo.device_backend ?? "cpu"
   ).toUpperCase();
-  const modelsFolderPath = modelsFolder
-    ? modelsFolder.path
-    : modelsFolderLoaded
+  const modelsFolderPath = hfCache
+    ? hfCache.cacheHome
+    : hfCacheLoaded
       ? t("settings.resources.environment.unknown")
       : t("common.loading");
+  const cacheLocationDetail = hfCache
+    ? hfCache.source === "environment"
+      ? t("settings.resources.storage.environmentManaged", {
+          variable: hfCache.environmentVariable ?? "HF_HOME",
+        })
+      : [
+          t("settings.resources.storage.futureDownloads"),
+          hfCache.freeBytes !== null
+            ? t("settings.resources.storage.locationFree", {
+                free: formatBytes(hfCache.freeBytes) ?? "",
+              })
+            : null,
+        ]
+          .filter(Boolean)
+          .join(" · ")
+    : null;
   const unknownLabel = t("settings.resources.environment.unknown");
 
   return (
@@ -467,29 +529,86 @@ export function ResourcesTab() {
         <SettingsRow
           label={t("settings.resources.storage.modelsFolder")}
           description={t("settings.resources.storage.modelsFolderDescription")}
-          className="max-sm:flex-col max-sm:items-start max-sm:gap-2"
+          className="max-[840px]:flex-col max-[840px]:items-stretch max-[840px]:gap-2"
         >
-          <div className="flex min-w-0 items-center gap-2 max-sm:max-w-[calc(100vw-5rem)]">
-            <span
-              title={modelsFolder?.path}
-              className="min-w-0 max-w-[280px] truncate font-mono text-xs text-muted-foreground max-sm:max-w-[180px]"
-            >
-              {modelsFolderPath}
-            </span>
+          <div className="grid w-[392px] min-w-0 grid-cols-[minmax(0,1fr)_auto] gap-x-2 gap-y-1.5 max-[840px]:w-full">
+            <div className="relative min-w-0">
+              <Input
+                readOnly
+                aria-label={t("settings.resources.storage.modelsFolder")}
+                value={modelsFolderPath}
+                title={hfCache?.cacheHome}
+                className="h-8 w-full pr-7 font-mono text-xs"
+              />
+              <button
+                type="button"
+                disabled={!hfCache}
+                onClick={() => void handleCacheFolder()}
+                aria-label={
+                  isTauri
+                    ? t("settings.resources.storage.openAction")
+                    : t("settings.resources.storage.copyAction")
+                }
+                title={
+                  isTauri
+                    ? t("settings.resources.storage.openAction")
+                    : t("settings.resources.storage.copyAction")
+                }
+                className="absolute right-1.5 top-1/2 flex size-5 -translate-y-1/2 items-center justify-center rounded text-muted-foreground transition-colors hover:text-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring disabled:pointer-events-none disabled:opacity-50"
+              >
+                {isTauri ? (
+                  <FolderOpenIcon className="size-3.5" />
+                ) : (
+                  <CopyIcon className="size-3.5" />
+                )}
+              </button>
+            </div>
             <Button
               variant="outline"
               size="sm"
-              disabled={!modelsFolder}
-              onClick={() => void handleModelsFolder()}
+              className="h-8"
+              disabled={!hfCache?.editable || cacheSaving}
+              onClick={() => void changeCacheFolder()}
             >
-              {isTauri
-                ? t("settings.resources.storage.openAction")
-                : t("settings.resources.storage.copyAction")}
+              {t("settings.resources.storage.changeAction")}
             </Button>
+            {cacheLocationDetail || hfCache?.isCustom ? (
+              <div className="col-span-2 flex min-w-0 items-center justify-between gap-2 pl-3.5 pr-1 text-xs text-muted-foreground">
+                {cacheLocationDetail ? (
+                  <span
+                    title={cacheLocationDetail}
+                    className="min-w-0 truncate"
+                  >
+                    {cacheLocationDetail}
+                  </span>
+                ) : null}
+                {hfCache?.isCustom ? (
+                  <Button
+                    variant="link"
+                    size="xs"
+                    className="h-auto px-0 text-xs"
+                    disabled={cacheSaving}
+                    onClick={() => void saveCacheFolder(null)}
+                  >
+                    {t("settings.resources.storage.resetAction")}
+                  </Button>
+                ) : null}
+              </div>
+            ) : null}
           </div>
         </SettingsRow>
       </SettingsSection>
 
+      <FolderBrowser
+        open={!isTauri && cacheBrowserOpen}
+        onOpenChange={setCacheBrowserOpen}
+        onSelect={(path) => void saveCacheFolder(path)}
+        initialPath={hfCache?.cacheHome}
+        title={t("settings.resources.storage.chooseTitle")}
+        confirmLabel={t("settings.resources.storage.chooseAction")}
+        showModelHints={false}
+      />
+
       <SettingsSection title={t("settings.resources.environment.title")}>
         <InfoRow
           label={t("settings.resources.environment.backend")}
diff --git a/studio/frontend/src/features/settings/tabs/voice-tab.tsx b/studio/frontend/src/features/settings/tabs/voice-tab.tsx
index 4b86105926..59c03bdf14 100644
--- a/studio/frontend/src/features/settings/tabs/voice-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/voice-tab.tsx
@@ -3,6 +3,11 @@
 
 import { Button } from "@/components/ui/button";
 import { Input } from "@/components/ui/input";
+import {
+  Popover,
+  PopoverContent,
+  PopoverTrigger,
+} from "@/components/ui/popover";
 import {
   Select,
   SelectContent,
@@ -11,41 +16,52 @@ import {
   SelectValue,
 } from "@/components/ui/select";
 import { Slider } from "@/components/ui/slider";
+import { Spinner } from "@/components/ui/spinner";
 import { Switch } from "@/components/ui/switch";
 import {
+  StudioModelDictationAdapter,
+  type SttDownloadStatus,
+  fetchSttStatus,
+  loadSttModel,
+  startSttDownload,
+  unloadSttModel,
+  validateSttModel,
   StudioSpeechSynthesisAdapter,
   createConfiguredUtterance,
   curateSystemVoices,
   generateStudioTtsAudio,
-} from "@/features/chat/adapters/studio-speech-synthesis-adapter";
+} from "@/features/chat";
 import {
-  StudioWebSpeechDictationAdapter,
-  describeSpeechError,
-  isMissingDeviceError,
-} from "@/features/chat/adapters/studio-web-speech-dictation-adapter";
+  DownloadProgressBar,
+  hfApiToken,
+  useHfTokenStore,
+  useHubModelSearch,
+} from "@/features/hub";
+import { useDebouncedValue, useWheelScrollRef } from "@/hooks";
 import { useT } from "@/i18n";
-import { toast } from "@/lib/toast";
+import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { MicIcon } from "@/lib/mic-icon";
-import { copyToClipboard } from "@/lib/copy-to-clipboard";
-import {
-  Copy01Icon,
-  Delete02Icon,
-  PlusSignIcon,
-  VolumeHighIcon,
-} from "@hugeicons/core-free-icons";
+import { toast } from "@/lib/toast";
+import { Search01Icon, VolumeHighIcon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { SquareIcon } from "lucide-react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { DictationDictionaryView } from "../components/dictation-dictionary-view";
+import { RecentDictationsView } from "../components/recent-dictations-view";
 import { SettingsRow } from "../components/settings-row";
 import { SettingsSection } from "../components/settings-section";
 import {
-  applyDictationDictionary,
-  recordRecentDictation,
-  resolveDictationLanguage,
+  type DefaultSttModel,
+  STT_MODELS,
+  type SttModel,
+  getSttModelRepo,
+  isCuratedSttModel,
+  isSttModelId,
+  isSttModelLanguageCompatible,
   useVoiceSettingsStore,
 } from "../stores/voice-settings-store";
 
-// Languages offered for browser speech recognition.
+// Languages shared by browser speech recognition and local STT.
 const DICTATION_LANGUAGES: { value: string; label: string }[] = [
   { value: "auto", label: "" }, // label rendered via i18n
   { value: "en-US", label: "English (US)" },
@@ -63,6 +79,225 @@ const DICTATION_LANGUAGES: { value: string; label: string }[] = [
   { value: "ar-SA", label: "العربية" },
 ];
 
+// Speech-recognition models, not voices. Name and size are separate so the list
+// can right-align the size; the speed/accuracy note lives in the row description.
+const STT_MODEL_NAMES: Record<DefaultSttModel, string> = {
+  tiny: "Whisper Tiny",
+  base: "Whisper Base",
+  small: "Whisper Small",
+  "large-v3-turbo": "Whisper Large v3 Turbo",
+  "large-v3": "Whisper Large v3",
+};
+// Curated models run as f16 GGML files through whisper.cpp.
+const STT_MODEL_SIZES: Record<DefaultSttModel, string> = {
+  tiny: "78 MB",
+  base: "148 MB",
+  small: "488 MB",
+  "large-v3-turbo": "1.6 GB",
+  "large-v3": "3.1 GB",
+};
+
+function sttModelName(model: SttModel): string {
+  return STT_MODEL_NAMES[model as DefaultSttModel] ?? model;
+}
+
+function sttModelSize(model: SttModel): string {
+  return STT_MODEL_SIZES[model as DefaultSttModel] ?? "";
+}
+
+/** Source repository shown under a model row. Curated models download from
+ * the Unsloth GGUF repos, mirrored by the backend (stt_ggml_sidecar.py). */
+function sttModelSource(model: SttModel): string {
+  return isCuratedSttModel(model)
+    ? `unslothai/whisper-${model}-GGUF`
+    : getSttModelRepo(model);
+}
+
+/**
+ * Model picker for local transcription. Lists the curated whisper.cpp
+ * checkpoints and searches Hugging Face for other Whisper repos (safetensors via
+ * Transformers). The trigger is a plain button so the selection never renders
+ * inside a text input.
+ */
+function SttModelPicker({
+  value,
+  language,
+  onChange,
+}: {
+  value: SttModel;
+  language: string;
+  onChange: (model: SttModel) => void;
+}) {
+  const t = useT();
+  const hfToken = useHfTokenStore((state) => state.token);
+  const [open, setOpen] = useState(false);
+  const [query, setQuery] = useState("");
+  const [validating, setValidating] = useState(false);
+  const resultsRef = useWheelScrollRef<HTMLDivElement>();
+  const debouncedQuery = useDebouncedValue(query.trim());
+
+  const { results, isLoading } = useHubModelSearch(debouncedQuery, {
+    task: "automatic-speech-recognition",
+    accessToken: hfApiToken(hfToken),
+    excludeGguf: true,
+    enabled: debouncedQuery.length >= 2,
+    keepUnsupportedTags: true,
+    ownerScope: "all",
+  });
+
+  const items = useMemo(() => {
+    if (!debouncedQuery) {
+      const defaults: string[] = STT_MODELS.filter((model) =>
+        isSttModelLanguageCompatible(model, language),
+      );
+      if (!defaults.includes(value)) {
+        defaults.push(value);
+      }
+      return defaults;
+    }
+    const ids: string[] = [];
+    for (const result of results) {
+      const tags = result.tags?.map((tag) => tag.toLowerCase()) ?? [];
+      const isWhisper =
+        result.id.toLowerCase().includes("whisper") || tags.includes("whisper");
+      const isExactMatch =
+        result.id.toLowerCase() === debouncedQuery.toLowerCase();
+      if (
+        (isExactMatch ||
+          (isWhisper &&
+            result.pipelineTag === "automatic-speech-recognition")) &&
+        isSttModelLanguageCompatible(result.id, language) &&
+        !ids.includes(result.id)
+      ) {
+        ids.push(result.id);
+      }
+    }
+    return ids;
+  }, [debouncedQuery, language, results, value]);
+
+  const selectModel = async (model: string) => {
+    if (!isSttModelId(model) || validating) {
+      return;
+    }
+    if (!isCuratedSttModel(model)) {
+      setValidating(true);
+      try {
+        await validateSttModel(model, hfApiToken(hfToken));
+      } catch (error) {
+        toast.error(t("settings.voice.dictation.sttModelInvalid"), {
+          description: error instanceof Error ? error.message : undefined,
+        });
+        return;
+      } finally {
+        setValidating(false);
+      }
+    }
+    onChange(model);
+    setOpen(false);
+    setQuery("");
+  };
+
+  return (
+    <Popover
+      open={open}
+      onOpenChange={(next) => {
+        setOpen(next);
+        if (!next) setQuery("");
+      }}
+    >
+      <PopoverTrigger asChild={true}>
+        <button
+          type="button"
+          aria-label="Speech recognition model"
+          className="border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.06] dark:hover:bg-white/10 focus-visible:border-ring flex h-8 w-full cursor-pointer items-center justify-between gap-1.5 rounded-full border px-3.5 text-sm outline-none transition-colors"
+        >
+          <span className="truncate">{sttModelName(value)}</span>
+          <HugeiconsIcon
+            icon={ChevronDownStandardIcon}
+            strokeWidth={2}
+            className="text-muted-foreground pointer-events-none size-4 shrink-0"
+          />
+        </button>
+      </PopoverTrigger>
+      <PopoverContent align="start" sideOffset={4} className="w-72 gap-0 p-0">
+        <div className="relative p-1.5 pb-0.5">
+          <HugeiconsIcon
+            icon={Search01Icon}
+            strokeWidth={2}
+            className="text-muted-foreground pointer-events-none absolute top-[calc(50%+2px)] left-4 size-3.5 -translate-y-1/2"
+          />
+          <Input
+            value={query}
+            onChange={(event) => setQuery(event.target.value)}
+            placeholder={t(
+              "settings.voice.dictation.sttModelSearchPlaceholder",
+            )}
+            className="h-8 pl-8 text-sm"
+            autoFocus={true}
+            onKeyDown={(event) => {
+              if (event.key === "Enter" && items.length > 0) {
+                event.preventDefault();
+                void selectModel(items[0]);
+              }
+            }}
+          />
+        </div>
+        <div
+          ref={resultsRef}
+          data-testid="stt-model-results"
+          className="max-h-64 overflow-y-auto p-1"
+        >
+          {(isLoading && debouncedQuery) || validating ? (
+            <div className="flex items-center gap-2 px-3 py-3 text-xs text-muted-foreground">
+              <Spinner className="size-3.5" />
+              {validating
+                ? t("settings.voice.dictation.sttModelValidating")
+                : t("settings.voice.dictation.sttModelSearching")}
+            </div>
+          ) : items.length === 0 ? (
+            <div className="px-3 py-3 text-xs text-muted-foreground">
+              {t("settings.voice.dictation.sttModelNoResults")}
+            </div>
+          ) : (
+            items.map((model) => {
+              // A custom repo's name is its id: one-line rows keep a pill shape,
+              // two-line rows use a subtler radius.
+              const twoLines = sttModelSource(model) !== sttModelName(model);
+              return (
+                <button
+                  key={model}
+                  type="button"
+                  onClick={() => void selectModel(model)}
+                  aria-selected={model === value}
+                  className={`flex w-full items-center justify-between gap-3 px-2.5 py-1.5 text-left transition-colors hover:bg-muted ${
+                    twoLines ? "rounded-sm" : "rounded-full"
+                  } ${model === value ? "bg-accent font-medium" : ""}`}
+                >
+                  <span className="min-w-0 flex-1 truncate">
+                    <span className="block truncate text-xs">
+                      {sttModelName(model)}
+                    </span>
+                    {twoLines ? (
+                      <span className="mt-0.5 block truncate font-mono text-[9px] leading-tight text-muted-foreground">
+                        {sttModelSource(model)}
+                      </span>
+                    ) : null}
+                  </span>
+                  {sttModelSize(model) ? (
+                    <span className="shrink-0 text-[10px] tabular-nums text-muted-foreground">
+                      {sttModelSize(model)}
+                    </span>
+                  ) : null}
+                </button>
+              );
+            })
+          )}
+        </div>
+      </PopoverContent>
+    </Popover>
+  );
+}
+
 const TTS_PREVIEW_TEXT =
   "Hello from Unsloth Studio! This is a preview of the selected voice.";
 
@@ -84,11 +319,29 @@ function useAudioInputDevices() {
   }, []);
 
   useEffect(() => {
-    void refresh();
     const media = navigator.mediaDevices;
-    if (!media?.addEventListener) return;
+    if (!media?.addEventListener) {
+      return;
+    }
+    let cancelled = false;
+    media
+      .enumerateDevices()
+      .then((all) => {
+        if (cancelled) {
+          return;
+        }
+        const inputs = all.filter((device) => device.kind === "audioinput");
+        setDevices(inputs);
+        setHasLabels(inputs.some((device) => device.label));
+      })
+      .catch(() => {
+        // Enumeration can fail in insecure contexts; leave the list empty.
+      });
     media.addEventListener("devicechange", refresh);
-    return () => media.removeEventListener("devicechange", refresh);
+    return () => {
+      cancelled = true;
+      media.removeEventListener("devicechange", refresh);
+    };
   }, [refresh]);
 
   // Labels are hidden until mic permission; open a short stream to get them.
@@ -102,7 +355,9 @@ function useAudioInputDevices() {
       const stream = await navigator.mediaDevices.getUserMedia({
         audio: true,
       });
-      stream.getTracks().forEach((track) => track.stop());
+      for (const track of stream.getTracks()) {
+        track.stop();
+      }
       await refresh();
     } catch {
       toast.error(t("settings.voice.dictation.micAccessBlocked"));
@@ -127,234 +382,18 @@ function useSystemVoices() {
   return voices;
 }
 
-/** Inline mic test: runs speech recognition and shows the live transcript. */
-function DictationTest() {
-  const t = useT();
-  const [testing, setTesting] = useState(false);
-  const [transcript, setTranscript] = useState("");
-  const [interim, setInterim] = useState("");
-  const recognitionRef = useRef<SpeechRecognition | null>(null);
-  const streamRef = useRef<MediaStream | null>(null);
-  // Guards the getUserMedia await so a mic opened after unmount is released.
-  const disposedRef = useRef(false);
-  // Mirrors the transcript state so onend can record it without stale closures.
-  const transcriptRef = useRef("");
-
-  // Single cleanup path: the browser can end recognition on its own (silence
-  // timeout, service disconnect), so onend must release the mic and save the
-  // transcript, not just the Stop button.
-  const finalize = useCallback(() => {
-    streamRef.current?.getTracks().forEach((track) => track.stop());
-    streamRef.current = null;
-    recognitionRef.current = null;
-    if (transcriptRef.current) {
-      recordRecentDictation(transcriptRef.current);
-      transcriptRef.current = "";
-    }
-    setTesting(false);
-    setInterim("");
-  }, []);
-
-  const stop = useCallback(() => {
-    const recognition = recognitionRef.current;
-    if (recognition) {
-      // onend fires next and runs finalize()
-      recognition.stop();
-    } else {
-      finalize();
-    }
-  }, [finalize]);
-
-  useEffect(() => {
-    disposedRef.current = false;
-    return () => {
-      disposedRef.current = true;
-      recognitionRef.current?.abort();
-      streamRef.current?.getTracks().forEach((track) => track.stop());
-      streamRef.current = null;
-    };
-  }, []);
-
-  // Set before the getUserMedia await so a double click or a slow
-  // permission prompt cannot start a second recognizer over the first.
-  const startingRef = useRef(false);
-
-  const start = useCallback(async () => {
-    const SpeechRecognitionAPI =
-      window.SpeechRecognition ?? window.webkitSpeechRecognition;
-    if (!SpeechRecognitionAPI) return;
-    if (startingRef.current || recognitionRef.current) return;
-    startingRef.current = true;
-    setTranscript("");
-    setInterim("");
-    transcriptRef.current = "";
-
-    const { micDeviceId } = useVoiceSettingsStore.getState();
-    let audioTrack: MediaStreamTrack | undefined;
-    try {
-      let stream: MediaStream;
-      try {
-        stream = await navigator.mediaDevices.getUserMedia({
-          audio:
-            micDeviceId && micDeviceId !== "default"
-              ? { deviceId: { exact: micDeviceId } }
-              : true,
-        });
-      } catch (error) {
-        // Saved mic may be unplugged; fall back to the default device.
-        if (micDeviceId !== "default" && isMissingDeviceError(error)) {
-          stream = await navigator.mediaDevices.getUserMedia({ audio: true });
-        } else {
-          throw error;
-        }
-      }
-      if (disposedRef.current) {
-        stream.getTracks().forEach((track) => track.stop());
-        startingRef.current = false;
-        return;
-      }
-      streamRef.current = stream;
-      audioTrack = stream.getAudioTracks()[0];
-    } catch {
-      startingRef.current = false;
-      toast.error(t("settings.voice.dictation.micOpenFailed"));
-      return;
-    }
-
-    const recognition = new SpeechRecognitionAPI();
-    recognition.lang = resolveDictationLanguage();
-    recognition.continuous = true;
-    recognition.interimResults = true;
-    recognition.onresult = (event: SpeechRecognitionEvent) => {
-      let interimText = "";
-      for (let i = event.resultIndex; i < event.results.length; i++) {
-        const result = event.results[i];
-        const text = result?.[0]?.transcript ?? "";
-        if (result?.isFinal) {
-          const corrected = applyDictationDictionary(text.trim());
-          setTranscript((prev) => {
-            const next = prev ? `${prev} ${corrected}` : corrected;
-            transcriptRef.current = next;
-            return next;
-          });
-        } else {
-          interimText += text;
-        }
-      }
-      setInterim(interimText);
-    };
-    recognition.onerror = (event) => {
-      // onend follows and runs finalize(); surface non-abort failures here.
-      const errorEvent = event as SpeechRecognitionErrorEvent;
-      if (errorEvent.error !== "aborted") {
-        toast.error(describeSpeechError(errorEvent.error, errorEvent.message));
-      }
-    };
-    recognition.onend = () => finalize();
-    try {
-      if (audioTrack) {
-        try {
-          recognition.start(audioTrack);
-        } catch {
-          // Engine has no start(track) overload: it will capture from the
-          // default device, so release the selected-device stream.
-          streamRef.current?.getTracks().forEach((track) => track.stop());
-          streamRef.current = null;
-          recognition.start();
-        }
-      } else {
-        recognition.start();
-      }
-    } catch {
-      startingRef.current = false;
-      finalize();
-      return;
-    }
-    recognitionRef.current = recognition;
-    startingRef.current = false;
-    setTesting(true);
-  }, [finalize, t]);
-
-  const finishedTest = !testing && transcript;
-
-  return (
-    <div className="flex flex-col gap-2">
-      <SettingsRow
-        label={t("settings.voice.dictation.testLabel")}
-        description={t("settings.voice.dictation.testDescription")}
-      >
-        <Button
-          variant="outline"
-          size="sm"
-          onClick={() => {
-            if (testing) {
-              stop();
-            } else {
-              void start();
-            }
-          }}
-        >
-          {testing ? (
-            <>
-              <SquareIcon className="mr-1.5 size-3 animate-pulse fill-current text-destructive" />
-              {t("settings.voice.dictation.stopTest")}
-            </>
-          ) : (
-            <>
-              <MicIcon className="mr-1.5 size-3.5" />
-              {t("settings.voice.dictation.startTest")}
-            </>
-          )}
-        </Button>
-      </SettingsRow>
-      {(testing || transcript) && (
-        <div className="rounded-lg border border-border/60 bg-muted/30 px-3 py-2 text-sm">
-          {transcript || interim ? (
-            <>
-              <span className="text-foreground">{transcript}</span>
-              {interim ? (
-                <span className="text-muted-foreground"> {interim}</span>
-              ) : null}
-            </>
-          ) : (
-            <span className="text-muted-foreground">
-              {testing ? t("settings.voice.dictation.listening") : ""}
-            </span>
-          )}
-          {finishedTest ? (
-            <div className="mt-1 text-xs text-muted-foreground">
-              {t("settings.voice.dictation.testSaved")}
-            </div>
-          ) : null}
-        </div>
-      )}
-    </div>
-  );
-}
-
 export function VoiceTab() {
   const t = useT();
   const micDeviceId = useVoiceSettingsStore((s) => s.micDeviceId);
   const setMicDeviceId = useVoiceSettingsStore((s) => s.setMicDeviceId);
+  const dictationEngine = useVoiceSettingsStore((s) => s.dictationEngine);
+  const setDictationEngine = useVoiceSettingsStore((s) => s.setDictationEngine);
+  const sttModel = useVoiceSettingsStore((s) => s.sttModel);
+  const setSttModel = useVoiceSettingsStore((s) => s.setSttModel);
   const dictationLanguage = useVoiceSettingsStore((s) => s.dictationLanguage);
   const setDictationLanguage = useVoiceSettingsStore(
     (s) => s.setDictationLanguage,
   );
-  const dictionary = useVoiceSettingsStore((s) => s.dictionary);
-  const addDictionaryEntry = useVoiceSettingsStore((s) => s.addDictionaryEntry);
-  const updateDictionaryEntry = useVoiceSettingsStore(
-    (s) => s.updateDictionaryEntry,
-  );
-  const commitDictionaryEntry = useVoiceSettingsStore(
-    (s) => s.commitDictionaryEntry,
-  );
-  const removeDictionaryEntry = useVoiceSettingsStore(
-    (s) => s.removeDictionaryEntry,
-  );
-  const recentDictations = useVoiceSettingsStore((s) => s.recentDictations);
-  const clearRecentDictations = useVoiceSettingsStore(
-    (s) => s.clearRecentDictations,
-  );
   const ttsEnabled = useVoiceSettingsStore((s) => s.ttsEnabled);
   const setTtsEnabled = useVoiceSettingsStore((s) => s.setTtsEnabled);
   const ttsEngine = useVoiceSettingsStore((s) => s.ttsEngine);
@@ -371,29 +410,288 @@ export function VoiceTab() {
   const { devices, hasLabels, requestAccess } = useAudioInputDevices();
   const rawVoices = useSystemVoices();
   const voices = useMemo(
-    () => curateSystemVoices(rawVoices, ttsVoiceURI),
-    // dictationLanguage feeds the curation language filter.
+    () => curateSystemVoices(rawVoices, ttsVoiceURI, dictationLanguage),
     [rawVoices, ttsVoiceURI, dictationLanguage],
   );
-  const [newEntry, setNewEntry] = useState("");
   const [previewing, setPreviewing] = useState(false);
+  const [subpage, setSubpage] = useState<"main" | "recents" | "dictionary">(
+    "main",
+  );
+  const [selectedDictationId, setSelectedDictationId] = useState<string | null>(
+    null,
+  );
 
-  const dictationSupported = StudioWebSpeechDictationAdapter.isSupported();
+  const modelSttSupported = StudioModelDictationAdapter.isSupported();
   const ttsSupported = StudioSpeechSynthesisAdapter.isSupported();
   const systemTtsSupported =
     StudioSpeechSynthesisAdapter.systemVoicesSupported();
   const effectiveTtsEngine = systemTtsSupported ? ttsEngine : "studio";
 
+  // Local STT stays on-demand. Track its phase without fetching model weights.
+  type SttPhase =
+    | "idle"
+    | "checking"
+    | "on-demand"
+    | "unavailable"
+    | "loading"
+    | "ready"
+    | "error";
+  type SttDownloadAvailability =
+    | "checking"
+    | "missing"
+    | "downloaded"
+    | "error";
+  const [sttPhase, setSttPhase] = useState<SttPhase>("idle");
+  const [sttDevice, setSttDevice] = useState<string | null>(null);
+  const [statusNonce, setStatusNonce] = useState(0);
+  const [sttDownloadStarting, setSttDownloadStarting] = useState(false);
+  const [sttUnloading, setSttUnloading] = useState(false);
+  const isLocalEngine = dictationEngine === "model";
+  // The model decides the backend: curated ids run GGML through whisper.cpp,
+  // custom repos run through Transformers.
+  const isGgufModel = isCuratedSttModel(sttModel);
+  // Progress of the selected engine's model download, from /stt/status.
+  const [sttDownload, setSttDownload] = useState<SttDownloadStatus | null>(
+    null,
+  );
+  const [downloadBytesPerSec, setDownloadBytesPerSec] = useState(0);
+  // Last observed (bytes, time) so successive polls yield a transfer rate.
+  const downloadRateSampleRef = useRef<{ bytes: number; at: number } | null>(
+    null,
+  );
+  // Model whose download this tab watched; completion auto-loads it.
+  const watchedDownloadRef = useRef<string | null>(null);
+
+  // Selecting a model (or finishing its download) loads it without a Load
+  // click. A model that is not downloaded fails quietly and stays on demand.
+  const autoLoadSttModel = useCallback(async (model: string) => {
+    setSttPhase("loading");
+    try {
+      await loadSttModel(model);
+    } catch {
+      // Not downloaded (or the engine is busy): the status poll resets the phase
+      // and the user still sees the Download button.
+    } finally {
+      setStatusNonce((nonce) => nonce + 1);
+    }
+  }, []);
+  const sttRepoId = getSttModelRepo(sttModel);
+  const hfToken = useHfTokenStore((state) => state.token);
+  const [sttDownloadAvailability, setSttDownloadAvailability] = useState<{
+    repoId: string;
+    state: SttDownloadAvailability;
+  }>({ repoId: "", state: "checking" });
+  const effectiveSttDownloadAvailability =
+    sttDownloadAvailability.repoId === sttRepoId
+      ? sttDownloadAvailability.state
+      : "checking";
+  useEffect(() => {
+    if (!isLocalEngine || !modelSttSupported) {
+      return;
+    }
+    let cancelled = false;
+    void (async () => {
+      // Only surface "checking" on the first poll; background refreshes keep
+      // the last phase so the status line doesn't flicker while polling.
+      setSttPhase((phase) => (phase === "idle" ? "checking" : phase));
+      try {
+        const status = await fetchSttStatus(statusNonce, sttModel);
+        if (cancelled) return;
+        // A curated model prefers the GGUF (whisper.cpp) engine, but without
+        // whisper-server the backend serves it through Transformers instead of
+        // failing. Fall back to the Transformers status here too, or the model
+        // shows as unavailable and download is blocked even though it works.
+        const engineStatus =
+          isGgufModel && status.gguf?.available
+            ? status.gguf
+            : status.transformers;
+        if (!engineStatus?.available) {
+          setSttPhase("unavailable");
+          return;
+        }
+        const download = engineStatus.download;
+        setSttDownload(download);
+        setSttDownloadAvailability({
+          repoId: sttRepoId,
+          state: engineStatus.downloaded_models.includes(sttModel)
+            ? "downloaded"
+            : download.error
+              ? "error"
+              : "missing",
+        });
+        if (download.downloading) {
+          watchedDownloadRef.current = download.model;
+          const bytes = download.bytes_done ?? 0;
+          const sample = downloadRateSampleRef.current;
+          const now = Date.now();
+          if (sample && bytes > sample.bytes && now > sample.at) {
+            setDownloadBytesPerSec(
+              ((bytes - sample.bytes) * 1000) / (now - sample.at),
+            );
+          }
+          downloadRateSampleRef.current = { bytes, at: now };
+          // Keep the download progress fresh.
+          window.setTimeout(() => {
+            if (!cancelled) setStatusNonce((n) => n + 1);
+          }, 800);
+        } else {
+          const finished = watchedDownloadRef.current;
+          watchedDownloadRef.current = null;
+          downloadRateSampleRef.current = null;
+          setDownloadBytesPerSec(0);
+          if (
+            finished === sttModel &&
+            engineStatus.downloaded_models.includes(sttModel) &&
+            engineStatus.loaded_model !== sttModel
+          ) {
+            // The download this tab watched just finished; load the model.
+            void autoLoadSttModel(sttModel);
+            return;
+          }
+        }
+        if (engineStatus.loading) {
+          setSttPhase("loading");
+          window.setTimeout(() => {
+            if (!cancelled) setStatusNonce((n) => n + 1);
+          }, 600);
+          return;
+        }
+        if (engineStatus.loaded_model === sttModel && !engineStatus.loading) {
+          setSttDevice(engineStatus.device);
+          setSttPhase("ready");
+          window.setTimeout(
+            () => {
+              if (!cancelled) setStatusNonce((n) => n + 1);
+            },
+            Math.max(
+              1000,
+              Math.min(engineStatus.keep_alive_seconds * 1000, 15_000),
+            ),
+          );
+          return;
+        }
+        // Merely opening settings or selecting local STT never downloads or
+        // loads a model. Loading begins from Load or when recording starts.
+        setSttDevice(null);
+        setSttPhase("on-demand");
+      } catch {
+        if (!cancelled) setSttPhase("error");
+      }
+    })();
+    return () => {
+      cancelled = true;
+    };
+  }, [
+    isLocalEngine,
+    isGgufModel,
+    sttModel,
+    sttRepoId,
+    modelSttSupported,
+    statusNonce,
+    autoLoadSttModel,
+  ]);
+
+  const sttStatusText = (() => {
+    switch (sttPhase) {
+      case "checking":
+        return t("settings.voice.dictation.sttChecking");
+      case "loading":
+        return t("settings.voice.dictation.sttLoadingModel");
+      case "on-demand":
+        return t("settings.voice.dictation.sttOnDemand");
+      case "ready":
+        // The GGML backend reports its runtime name, not a device; show a plain
+        // "Loaded" rather than surfacing it.
+        return sttDevice && sttDevice !== "whisper.cpp"
+          ? t("settings.voice.dictation.sttReady", {
+              device: sttDevice.toUpperCase(),
+            })
+          : t("settings.voice.dictation.sttLoaded");
+      case "unavailable":
+        return t("settings.voice.dictation.sttUnavailable");
+      case "error":
+        return t("settings.voice.dictation.sttModelFailed");
+      default:
+        return "";
+    }
+  })();
+
+  const downloadingThisModel =
+    isLocalEngine &&
+    sttDownload?.downloading === true &&
+    sttDownload.model === sttModel;
+
+  const sttModelStatusText = (() => {
+    if (downloadingThisModel) {
+      const total = sttDownload?.bytes_total ?? 0;
+      const done = sttDownload?.bytes_done ?? 0;
+      return t("settings.voice.dictation.sttDownloading", {
+        progress:
+          total > 0 ? Math.min(99, Math.round((done / total) * 100)) : 0,
+      });
+    }
+    if (sttPhase === "unavailable") {
+      return sttStatusText;
+    }
+    switch (effectiveSttDownloadAvailability) {
+      case "checking":
+        return t("settings.voice.dictation.sttDownloadChecking");
+      case "missing":
+        return t("settings.voice.dictation.sttNotDownloaded");
+      case "error":
+        return t("settings.voice.dictation.sttDownloadStatusFailed");
+      case "downloaded":
+        return sttStatusText;
+      default:
+        return "";
+    }
+  })();
+
+  const beginSttDownload = async () => {
+    setSttDownloadStarting(true);
+    try {
+      // Engine-managed download; progress arrives via /stt/status.
+      await startSttDownload(sttModel, hfApiToken(hfToken));
+      setStatusNonce((nonce) => nonce + 1);
+    } catch (error) {
+      toast.error(t("settings.voice.dictation.sttDownloadFailed"), {
+        description: error instanceof Error ? error.message : undefined,
+      });
+    } finally {
+      setSttDownloadStarting(false);
+    }
+  };
+
+  const warmSttModel = async () => {
+    setSttPhase("loading");
+    try {
+      await loadSttModel(sttModel);
+      setStatusNonce((nonce) => nonce + 1);
+    } catch (error) {
+      setSttPhase("error");
+      toast.error(t("settings.voice.dictation.sttModelFailed"), {
+        description: error instanceof Error ? error.message : undefined,
+      });
+    }
+  };
+
+  const releaseSttModel = async () => {
+    setSttUnloading(true);
+    try {
+      await unloadSttModel();
+      setStatusNonce((nonce) => nonce + 1);
+    } catch (error) {
+      toast.error(t("settings.voice.dictation.sttModelFailed"), {
+        description: error instanceof Error ? error.message : undefined,
+      });
+    } finally {
+      setSttUnloading(false);
+    }
+  };
+
   // Keep an item for an unplugged saved mic so the value stays visible.
   const knownMic = devices.some((d) => d.deviceId === micDeviceId);
 
-  const handleAddEntry = () => {
-    const trimmed = newEntry.trim();
-    if (!trimmed) return;
-    addDictionaryEntry(trimmed);
-    setNewEntry("");
-  };
-
   const previewAudioRef = useRef<HTMLAudioElement | null>(null);
   const previewAbortRef = useRef<AbortController | null>(null);
   // Mirrors `previewing` so unmount cleanup can tell whether this tab owns
@@ -450,8 +748,7 @@ export function VoiceTab() {
         const audio = new Audio(url);
         audio.playbackRate = ttsRate;
         audio.volume = ttsVolume;
-        // Some browsers reset playbackRate to 1 once the source loads; reapply
-        // it on loadedmetadata so the speed setting reliably takes effect.
+        // Some browsers reset playbackRate once metadata loads.
         audio.addEventListener("loadedmetadata", () => {
           audio.playbackRate = ttsRate;
         });
@@ -462,8 +759,6 @@ export function VoiceTab() {
         audio.addEventListener("error", () => {
           releasePreviewAudio();
           markPreviewing(false);
-          // Surface playback failures like the catch below, instead of just
-          // resetting the button with no explanation.
           toast.error("TTS preview failed");
         });
         previewAudioRef.current = audio;
@@ -501,6 +796,23 @@ export function VoiceTab() {
   // Stop any preview playback when the tab unmounts.
   useEffect(() => stopPreview, [stopPreview]);
 
+  if (subpage === "recents") {
+    return (
+      <RecentDictationsView
+        selectedId={selectedDictationId}
+        onSelect={setSelectedDictationId}
+        onBack={() => {
+          setSelectedDictationId(null);
+          setSubpage("main");
+        }}
+      />
+    );
+  }
+
+  if (subpage === "dictionary") {
+    return <DictationDictionaryView onBack={() => setSubpage("main")} />;
+  }
+
   return (
     <div className="flex flex-col gap-6">
       <header className="flex flex-col gap-1">
@@ -513,6 +825,191 @@ export function VoiceTab() {
       </header>
 
       <SettingsSection title={t("settings.voice.dictation.sectionTitle")}>
+        <SettingsRow
+          label={t("settings.voice.dictation.engineLabel")}
+          description={
+            dictationEngine === "model"
+              ? t("settings.voice.dictation.engineModelDescription")
+              : t("settings.voice.dictation.engineBrowserDescription")
+          }
+        >
+          <Select
+            value={dictationEngine}
+            onValueChange={(value) => {
+              const next = value === "model" ? "model" : "browser";
+              if (next !== dictationEngine) {
+                // Unload whichever backend was resident for the old engine.
+                void unloadSttModel().catch(() => {});
+                if (next === "model") {
+                  setSttPhase("checking");
+                  setSttDevice(null);
+                  setSttDownload(null);
+                }
+              }
+              setDictationEngine(next);
+            }}
+          >
+            <SelectTrigger
+              aria-label="Dictation engine"
+              className="w-56"
+              size="sm"
+            >
+              <SelectValue />
+            </SelectTrigger>
+            <SelectContent>
+              <SelectItem value="browser">
+                {t("settings.voice.dictation.engineBrowser")}
+              </SelectItem>
+              <SelectItem value="model">
+                {t("settings.voice.dictation.engineModel")}
+              </SelectItem>
+            </SelectContent>
+          </Select>
+        </SettingsRow>
+
+        {isLocalEngine ? (
+          modelSttSupported ? (
+            <SettingsRow
+              label={t("settings.voice.dictation.sttModelLabel")}
+              description={t("settings.voice.dictation.sttModelDescription")}
+            >
+              <div className="flex w-56 flex-col items-stretch gap-2">
+                <SttModelPicker
+                  value={sttModel}
+                  language={dictationLanguage}
+                  onChange={(next) => {
+                    if (next !== sttModel) {
+                      void unloadSttModel().catch(() => {});
+                      void autoLoadSttModel(next);
+                    }
+                    setSttModel(next);
+                  }}
+                />
+                {downloadingThisModel ? (
+                  <div className="rounded-md border border-border/60 bg-muted/20 px-2.5 pt-2">
+                    <div className="mb-1.5 flex items-center justify-between gap-3">
+                      <span className="text-xs text-muted-foreground">
+                        {sttModelStatusText}
+                      </span>
+                    </div>
+                    <DownloadProgressBar
+                      progress={{
+                        expectedBytes: sttDownload?.bytes_total ?? 0,
+                        downloadedBytes: sttDownload?.bytes_done ?? 0,
+                        fraction:
+                          sttDownload?.bytes_total &&
+                          sttDownload.bytes_total > 0
+                            ? (sttDownload.bytes_done ?? 0) /
+                              sttDownload.bytes_total
+                            : 0,
+                      }}
+                      bytesPerSec={downloadBytesPerSec}
+                    />
+                  </div>
+                ) : (
+                  <div className="flex min-h-7 items-center justify-between gap-3">
+                    <span className="flex min-w-0 items-center gap-2 text-xs text-muted-foreground">
+                      {effectiveSttDownloadAvailability === "checking" ||
+                      sttPhase === "loading" ||
+                      sttPhase === "checking" ? (
+                        <span className="size-1.5 shrink-0 animate-pulse rounded-full bg-current" />
+                      ) : sttPhase === "ready" ||
+                        (effectiveSttDownloadAvailability === "downloaded" &&
+                          sttPhase === "on-demand") ? (
+                        <span className="size-1.5 shrink-0 rounded-full bg-emerald-500" />
+                      ) : effectiveSttDownloadAvailability === "error" ||
+                        sttPhase === "error" ? (
+                        <span className="size-1.5 shrink-0 rounded-full bg-destructive" />
+                      ) : null}
+                      <span>{sttModelStatusText}</span>
+                    </span>
+                    {sttPhase === "unavailable" ? (
+                      <Button
+                        variant="ghost"
+                        size="sm"
+                        className="h-7 px-2 text-xs"
+                        onClick={() => setStatusNonce((nonce) => nonce + 1)}
+                      >
+                        {t("settings.voice.dictation.sttRetry")}
+                      </Button>
+                    ) : effectiveSttDownloadAvailability === "error" ? (
+                      <Button
+                        variant="ghost"
+                        size="sm"
+                        className="h-7 px-2 text-xs"
+                        disabled={sttDownloadStarting || downloadingThisModel}
+                        // Restart the download; the sidecar error is sticky until
+                        // a new start(), so re-polling alone never clears it.
+                        onClick={beginSttDownload}
+                      >
+                        {t("settings.voice.dictation.sttRetry")}
+                      </Button>
+                    ) : effectiveSttDownloadAvailability === "missing" ? (
+                      <Button
+                        variant="outline"
+                        size="sm"
+                        className="h-7 px-2.5 text-xs"
+                        disabled={sttDownloadStarting || downloadingThisModel}
+                        onClick={beginSttDownload}
+                      >
+                        {sttDownloadStarting || downloadingThisModel ? (
+                          <Spinner className="mr-1.5" />
+                        ) : null}
+                        {t("settings.voice.dictation.sttDownload")}
+                      </Button>
+                    ) : effectiveSttDownloadAvailability === "downloaded" ? (
+                      sttPhase === "ready" ? (
+                        <Button
+                          variant="outline"
+                          size="sm"
+                          className="h-7 px-2.5 text-xs"
+                          disabled={sttUnloading}
+                          onClick={releaseSttModel}
+                        >
+                          {sttUnloading ? <Spinner className="mr-1.5" /> : null}
+                          {sttUnloading
+                            ? t("settings.voice.dictation.sttUnloading")
+                            : t("settings.voice.dictation.sttUnload")}
+                        </Button>
+                      ) : sttPhase === "loading" || sttPhase === "checking" ? (
+                        // The status line already says "Loading model…"; the
+                        // button only needs the spinner.
+                        <Button
+                          variant="outline"
+                          size="sm"
+                          className="h-7 px-2.5 text-xs"
+                          disabled={true}
+                          aria-label={t(
+                            "settings.voice.dictation.sttLoadingModel",
+                          )}
+                        >
+                          <Spinner />
+                        </Button>
+                      ) : (
+                        <Button
+                          variant="outline"
+                          size="sm"
+                          className="h-7 px-2.5 text-xs"
+                          onClick={warmSttModel}
+                        >
+                          {sttPhase === "error"
+                            ? t("settings.voice.dictation.sttRetry")
+                            : t("settings.voice.dictation.sttLoad")}
+                        </Button>
+                      )
+                    ) : null}
+                  </div>
+                )}
+              </div>
+            </SettingsRow>
+          ) : (
+            <SettingsRow
+              label={t("settings.voice.dictation.sttModelLabel")}
+              description={t("settings.voice.dictation.sttModelUnsupported")}
+            />
+          )
+        ) : null}
+
         <SettingsRow
           label={t("settings.voice.dictation.microphoneLabel")}
           description={
@@ -525,7 +1022,7 @@ export function VoiceTab() {
         >
           {hasLabels ? (
             <Select value={micDeviceId} onValueChange={setMicDeviceId}>
-              <SelectTrigger aria-label="Microphone" className="w-56" size="sm">
+              <SelectTrigger aria-label="Microphone" className="min-w-56 max-w-72" size="sm">
                 <SelectValue />
               </SelectTrigger>
               <SelectContent>
@@ -564,7 +1061,7 @@ export function VoiceTab() {
           >
             <SelectTrigger
               aria-label="Dictation language"
-              className="w-56"
+              className="min-w-56 max-w-72"
               size="sm"
             >
               <SelectValue />
@@ -581,144 +1078,34 @@ export function VoiceTab() {
           </Select>
         </SettingsRow>
 
-        {dictationSupported ? (
-          <DictationTest />
-        ) : (
-          <SettingsRow
-            label={t("settings.voice.dictation.testLabel")}
-            description={t("settings.voice.dictation.notSupported")}
-          />
-        )}
-      </SettingsSection>
-
-      <SettingsSection
-        title={t("settings.voice.dictionary.sectionTitle")}
-        description={t("settings.voice.dictionary.sectionDescription")}
-      >
-        {dictionary.map((entry, index) => (
-          <div
-            // biome-ignore lint/suspicious/noArrayIndexKey: entries are editable in place
-            key={index}
-            className="flex items-center gap-2 py-1.5"
-          >
-            <Input
-              value={entry}
-              onChange={(e) => updateDictionaryEntry(index, e.target.value)}
-              // Skip the empty-row commit-splice when focus moves to this row's
-              // Remove button (keyboard Tab), so its index stays valid and its
-              // activation deletes this row instead of the next one.
-              onBlur={(e) => {
-                if (
-                  (e.relatedTarget as HTMLElement | null)?.dataset.dictRemove ===
-                  String(index)
-                ) {
-                  return;
-                }
-                commitDictionaryEntry(index);
-              }}
-              className="h-8 flex-1 text-sm"
-              aria-label={`Dictionary entry ${index + 1}`}
-            />
-            <Button
-              variant="ghost"
-              size="icon"
-              className="size-8 shrink-0 text-muted-foreground hover:text-destructive"
-              data-dict-remove={index}
-              // Mouse: keep the click from blurring an empty input first, which
-              // would commit-splice this row and make onClick delete the next.
-              onMouseDown={(e) => e.preventDefault()}
-              onClick={() => removeDictionaryEntry(index)}
-              aria-label={`Remove dictionary entry ${index + 1}`}
-            >
-              <HugeiconsIcon icon={Delete02Icon} className="size-3.5" />
-            </Button>
-          </div>
-        ))}
-        <div className="flex items-center gap-2 py-1.5">
-          <Input
-            value={newEntry}
-            onChange={(e) => setNewEntry(e.target.value)}
-            onKeyDown={(e) => {
-              if (e.key === "Enter") {
-                e.preventDefault();
-                handleAddEntry();
-              }
-            }}
-            placeholder="Jane Doe"
-            className="h-8 flex-1 text-sm"
-            aria-label="New dictionary entry"
-          />
+        <SettingsRow
+          label={t("settings.voice.dictionary.manageLabel")}
+          description={t("settings.voice.dictionary.sectionDescription")}
+        >
           <Button
             variant="outline"
             size="sm"
-            className="shrink-0"
-            onClick={handleAddEntry}
-            disabled={!newEntry.trim()}
+            onClick={() => setSubpage("dictionary")}
           >
-            <HugeiconsIcon icon={PlusSignIcon} className="mr-1.5 size-3.5" />
-            {t("settings.voice.dictionary.addEntry")}
+            {t("settings.voice.dictionary.manage")}
           </Button>
-        </div>
-      </SettingsSection>
+        </SettingsRow>
 
-      <SettingsSection
-        title={t("settings.voice.recents.sectionTitle")}
-        description={t("settings.voice.recents.sectionDescription")}
-      >
-        {recentDictations.length === 0 ? (
-          <p className="py-3 text-sm text-muted-foreground">
-            {t("settings.voice.recents.empty")}
-          </p>
-        ) : (
-          <>
-            {recentDictations.map((item) => (
-              <div
-                key={`${item.at}-${item.text.slice(0, 24)}`}
-                className="flex items-start justify-between gap-3 py-2.5"
-              >
-                <div className="min-w-0 flex-1">
-                  <p className="whitespace-pre-wrap break-words text-sm text-foreground">
-                    {item.text}
-                  </p>
-                  <p className="mt-0.5 text-xs text-muted-foreground">
-                    {new Date(item.at).toLocaleString()}
-                  </p>
-                </div>
-                <Button
-                  variant="ghost"
-                  size="icon"
-                  className="size-8 shrink-0 text-muted-foreground"
-                  aria-label="Copy dictation"
-                  onClick={async () => {
-                    // Helper falls back to execCommand where navigator.clipboard
-                    // is unavailable (Safari, insecure http LAN contexts).
-                    if (await copyToClipboard(item.text)) {
-                      toast.success(t("settings.voice.recents.copied"));
-                    } else {
-                      toast.error(t("settings.voice.recents.copyFailed"));
-                    }
-                  }}
-                >
-                  <HugeiconsIcon icon={Copy01Icon} className="size-3.5" />
-                </Button>
-              </div>
-            ))}
-            <div className="flex justify-end py-2">
-              <Button
-                variant="outline"
-                size="sm"
-                onClick={clearRecentDictations}
-                className="text-destructive hover:text-destructive hover:border-destructive/60"
-              >
-                <HugeiconsIcon
-                  icon={Delete02Icon}
-                  className="mr-1.5 size-3.5"
-                />
-                {t("settings.voice.recents.clear")}
-              </Button>
-            </div>
-          </>
-        )}
+        <SettingsRow
+          label={t("settings.voice.recents.manageLabel")}
+          description={t("settings.voice.recents.sectionDescription")}
+        >
+          <Button
+            variant="outline"
+            size="sm"
+            onClick={() => {
+              setSelectedDictationId(null);
+              setSubpage("recents");
+            }}
+          >
+            {t("settings.voice.recents.manage")}
+          </Button>
+        </SettingsRow>
       </SettingsSection>
 
       <SettingsSection title={t("settings.voice.readAloud.sectionTitle")}>
@@ -747,7 +1134,7 @@ export function VoiceTab() {
               >
                 <SelectTrigger
                   aria-label="TTS engine"
-                  className="w-56"
+                  className="min-w-56 max-w-72"
                   size="sm"
                 >
                   <SelectValue />
@@ -778,7 +1165,7 @@ export function VoiceTab() {
                 <Select value={ttsVoiceURI} onValueChange={setTtsVoiceURI}>
                   <SelectTrigger
                     aria-label="Text to speech voice"
-                    className="w-56"
+                    className="min-w-56 max-w-72"
                     size="sm"
                   >
                     <SelectValue />
diff --git a/studio/frontend/src/features/studio/historical-training-view.tsx b/studio/frontend/src/features/studio/historical-training-view.tsx
index b6ec06b06a..4a123875a8 100644
--- a/studio/frontend/src/features/studio/historical-training-view.tsx
+++ b/studio/frontend/src/features/studio/historical-training-view.tsx
@@ -2,19 +2,29 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import type { TrainingViewData } from "@/features/training";
-import { getTrainingRun, onTrainingRunUpdated } from "@/features/training";
+import {
+  getTrainingRun,
+  onTrainingRunUpdated,
+  useTrainingActions,
+  useTrainingRuntimeStore,
+} from "@/features/training";
 import type { TrainingRunDetailResponse } from "@/features/training";
 import { parseBackendTrainingMethod } from "@/features/training/lib/training-methods";
 import { type ReactElement, useEffect, useState } from "react";
 import { ChartsSection } from "./sections/charts-section";
 import { ProgressSection } from "./sections/progress-section";
 import { mapRunConfigToOverride } from "./sections/run-config-override";
+import { Button } from "@/components/ui/button";
+import { Spinner } from "@/components/ui/spinner";
+import { PlayIcon } from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
 import { translate, useT } from "@/i18n";
 
 type StudioT = ReturnType<typeof useT>;
 
 interface HistoricalTrainingViewProps {
   runId: string;
+  onResumeStarted?: () => void;
 }
 
 function mapToViewData(
@@ -93,10 +103,27 @@ function mapToViewData(
 
 export function HistoricalTrainingView({
   runId,
+  onResumeStarted,
 }: HistoricalTrainingViewProps): ReactElement {
   const t = useT();
   const [detail, setDetail] = useState<TrainingRunDetailResponse | null>(null);
   const [error, setError] = useState<string | null>(null);
+  const [resuming, setResuming] = useState(false);
+  const { resumeTrainingRunFromHistory } = useTrainingActions();
+  const isStarting = useTrainingRuntimeStore((state) => state.isStarting);
+  const isTrainingRunning = useTrainingRuntimeStore(
+    (state) => state.isTrainingRunning,
+  );
+
+  const handleResume = async () => {
+    setResuming(true);
+    try {
+      const ok = await resumeTrainingRunFromHistory(runId);
+      if (ok) onResumeStarted?.();
+    } finally {
+      setResuming(false);
+    }
+  };
 
   // Derive loading from detail/error; no separate state.
   const loading = detail === null && error === null;
@@ -152,6 +179,27 @@ export function HistoricalTrainingView({
 
   return (
     <div className="flex flex-col gap-6">
+      {detail.run.can_resume && (
+        <div className="flex justify-end">
+          <Button
+            type="button"
+            size="sm"
+            variant="outline"
+            className="gap-1.5"
+            disabled={isStarting || resuming || isTrainingRunning}
+            onClick={() => void handleResume()}
+          >
+            {resuming ? (
+              <Spinner className="size-3.5" />
+            ) : (
+              <HugeiconsIcon icon={PlayIcon} className="size-3.5" />
+            )}
+            {resuming
+              ? t("studio.history.resuming")
+              : t("studio.history.resumeTraining")}
+          </Button>
+        </div>
+      )}
       <ProgressSection
         data={viewData}
         isHistorical
diff --git a/studio/frontend/src/features/studio/history-card-grid.tsx b/studio/frontend/src/features/studio/history-card-grid.tsx
index bd76171ce2..21dc786e34 100644
--- a/studio/frontend/src/features/studio/history-card-grid.tsx
+++ b/studio/frontend/src/features/studio/history-card-grid.tsx
@@ -78,13 +78,17 @@ function wasContinuedInVisibleRuns(
   run: TrainingRunSummary,
   runs: TrainingRunSummary[],
 ): boolean {
-  if (run.status !== "stopped" || !run.output_dir) return false;
+  if ((run.status !== "stopped" && run.status !== "error") || !run.output_dir)
+    return false;
   const startedAt = new Date(run.started_at).getTime();
   return runs.some(
     (other) =>
       other.id !== run.id &&
       other.output_dir === run.output_dir &&
-      (other.status === "stopped" || other.status === "completed") &&
+      (other.status === "stopped" ||
+        other.status === "completed" ||
+        other.status === "error" ||
+        other.status === "running") &&
       new Date(other.started_at).getTime() > startedAt,
   );
 }
@@ -421,14 +425,14 @@ export function HistoryCardGrid({
               <div className="flex items-center justify-between pr-6">
                 <span
                   className={cn(
-                    "inline-flex items-center gap-1.5 rounded-full px-2 py-0.5 text-[10px] font-semibold",
+                    "inline-flex items-center gap-1.5 rounded-full px-2 py-0.5 text-ui-10 font-semibold",
                     badge.className,
                   )}
                 >
                   {isRunning && <Spinner className="size-2.5" />}
                   {formatStatusLabel(wasContinued ? "resumed_later" : run.status, t)}
                 </span>
-                <span className="text-[10px] text-muted-foreground">
+                <span className="text-ui-10 text-muted-foreground">
                   {formatRelativeTime(run.started_at, t)}
                 </span>
               </div>
@@ -437,7 +441,7 @@ export function HistoryCardGrid({
                   type="button"
                   size="xs"
                   variant="outline"
-                  className="absolute bottom-3 left-4 h-6 rounded-full px-2.5 text-[11px] leading-none shadow-sm"
+                  className="absolute bottom-3 left-4 h-6 rounded-full px-2.5 text-ui-11 leading-none shadow-sm"
                   disabled={isStarting || isResuming}
                   onClick={(e) => {
                     e.stopPropagation();
@@ -452,7 +456,7 @@ export function HistoryCardGrid({
                   type="button"
                   size="xs"
                   variant="outline"
-                  className="absolute bottom-3 right-4 h-6 rounded-full px-2.5 text-[11px] leading-none shadow-sm"
+                  className="absolute bottom-3 right-4 h-6 rounded-full px-2.5 text-ui-11 leading-none shadow-sm"
                   onClick={async (e) => {
                     e.stopPropagation();
                     // Encode each segment but keep "/" so the /p route matches.
@@ -520,7 +524,7 @@ export function HistoryCardGrid({
                   />
                 </div>
               )}
-              <div className="flex flex-wrap gap-x-4 gap-y-1 text-[11px] text-muted-foreground">
+              <div className="flex flex-wrap gap-x-4 gap-y-1 text-ui-11 text-muted-foreground">
                 <span>
                   {t("studio.history.loss")}:{" "}
                   {run.final_loss != null ? run.final_loss.toFixed(4) : "--"}
diff --git a/studio/frontend/src/features/studio/recent-trainings-section.tsx b/studio/frontend/src/features/studio/recent-trainings-section.tsx
index ba65d7f736..092732b486 100644
--- a/studio/frontend/src/features/studio/recent-trainings-section.tsx
+++ b/studio/frontend/src/features/studio/recent-trainings-section.tsx
@@ -22,7 +22,7 @@ export function RecentTrainingsSection() {
 
   return (
     <section className="mt-10">
-      <h2 className="mb-4 text-[18px] font-semibold tracking-[-0.02em] text-foreground">
+      <h2 className="mb-4 text-ui-18 font-semibold tracking-[-0.02em] text-foreground">
         Recent trainings
       </h2>
       <HistoryCardGrid
diff --git a/studio/frontend/src/features/studio/sections/charts/chart-settings-sheet.tsx b/studio/frontend/src/features/studio/sections/charts/chart-settings-sheet.tsx
index baa66e8b83..f0f030dace 100644
--- a/studio/frontend/src/features/studio/sections/charts/chart-settings-sheet.tsx
+++ b/studio/frontend/src/features/studio/sections/charts/chart-settings-sheet.tsx
@@ -251,7 +251,7 @@ export function ChartSettingsSheet(): ReactElement {
                   max={0.9}
                   step={0.01}
                 />
-                <p className="text-[11px] text-muted-foreground">
+                <p className="text-ui-11 text-muted-foreground">
                   {t("studio.charts.smoothingDescription")}
                 </p>
               </div>
diff --git a/studio/frontend/src/features/studio/sections/charts/training-loss-chart-card.tsx b/studio/frontend/src/features/studio/sections/charts/training-loss-chart-card.tsx
index 16113f3219..738305eaca 100644
--- a/studio/frontend/src/features/studio/sections/charts/training-loss-chart-card.tsx
+++ b/studio/frontend/src/features/studio/sections/charts/training-loss-chart-card.tsx
@@ -152,7 +152,7 @@ export function TrainingLossChartCard({
                     value: formatMetric(avgRaw),
                   }),
                   position: "insideTopRight",
-                  fontSize: 10,
+                  fontSize: "calc(0.625rem * var(--ui-font-scale, 1))",
                   fill: "#3b82f6",
                 }}
               />
diff --git a/studio/frontend/src/features/studio/sections/dataset-preview-dialog-mapping.tsx b/studio/frontend/src/features/studio/sections/dataset-preview-dialog-mapping.tsx
index 5be1c32f69..d20cc0b63d 100644
--- a/studio/frontend/src/features/studio/sections/dataset-preview-dialog-mapping.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-preview-dialog-mapping.tsx
@@ -74,15 +74,15 @@ export function HeaderRolePicker({
       value={currentRole ?? "_none"}
       onValueChange={(v) => onRoleChange(v === "_none" ? undefined : v)}
     >
-      <SelectTrigger className="h-6 w-[90px] text-[10px] px-2 py-0 border-dashed cursor-pointer">
+      <SelectTrigger className="h-6 w-[90px] text-ui-10 px-2 py-0 border-dashed cursor-pointer">
         <SelectValue placeholder="Role..." />
       </SelectTrigger>
       <SelectContent>
-        <SelectItem value="_none" className="text-[11px]">
+        <SelectItem value="_none" className="text-ui-11">
           None
         </SelectItem>
         {availableRoles.map((role) => (
-          <SelectItem key={role} value={role} className="text-[11px]">
+          <SelectItem key={role} value={role} className="text-ui-11">
             {ROLE_LABELS[role] ?? role}
           </SelectItem>
         ))}
@@ -179,7 +179,7 @@ export function DatasetMappingCard({
                 <Badge
                   key={col}
                   variant="outline"
-                  className="h-6 text-[11px] bg-white/60 dark:bg-transparent"
+                  className="h-6 text-ui-11 bg-white/60 dark:bg-transparent"
                 >
                   <span className="font-mono">{col}</span>
                   <span className="mx-1 text-muted-foreground/60">&rarr;</span>
@@ -211,7 +211,7 @@ export function DatasetMappingCard({
                   <>
                     <Sparkles className="mr-1.5 h-3.5 w-3.5" />
                     AI Assist
-                    <Badge variant="outline" className="ml-1.5 text-[9px] px-1 py-0 h-4 font-medium">Beta</Badge>
+                    <Badge variant="outline" className="ml-1.5 text-ui-9 px-1 py-0 h-4 font-medium">Beta</Badge>
                   </>
                 )}
               </Button>
@@ -227,7 +227,7 @@ export function DatasetMappingCard({
                 <span>{advisorNotification}</span>
               </div>
               {advisorSystemPrompt && (
-                <div className="pl-5.5 text-[11px] font-mono text-indigo-600/80 dark:text-indigo-400/80">
+                <div className="pl-5.5 text-ui-11 font-mono text-indigo-600/80 dark:text-indigo-400/80">
                   <span className="font-sans font-medium text-indigo-500 dark:text-indigo-400">System:</span>{" "}
                   <span className="break-words">{advisorSystemPrompt}</span>
                 </div>
@@ -256,7 +256,7 @@ export function DatasetMappingFooter({
   return (
     <div className="mt-3 flex flex-col gap-2">
       <div className="flex items-center justify-between gap-3">
-        <p className="text-[11px] text-muted-foreground/70 leading-relaxed">
+        <p className="text-ui-11 text-muted-foreground/70 leading-relaxed">
           Tip: use the role dropdowns in the column headers to assign roles.
         </p>
         <div className="flex items-center gap-2">
diff --git a/studio/frontend/src/features/studio/sections/dataset-preview-dialog.tsx b/studio/frontend/src/features/studio/sections/dataset-preview-dialog.tsx
index c467880b6b..71939aaee2 100644
--- a/studio/frontend/src/features/studio/sections/dataset-preview-dialog.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-preview-dialog.tsx
@@ -261,7 +261,7 @@ export function DatasetPreviewDialog({
       accessorKey: colName,
       header: () => (
         <div className="flex flex-col gap-2">
-          <span className="font-heading text-[13px] font-semibold tracking-tight text-foreground">
+          <span className="font-heading text-ui-13 font-semibold tracking-tight text-foreground">
             {colName}
           </span>
           {mappingEnabled && (
@@ -308,7 +308,7 @@ export function DatasetPreviewDialog({
         const text = formatCell(value);
         if (!text) {
           return (
-            <span className="text-muted-foreground/40 italic text-[13px]">
+            <span className="text-muted-foreground/40 italic text-ui-13">
               --
             </span>
           );
@@ -316,7 +316,7 @@ export function DatasetPreviewDialog({
         const full = typeof value === "string" ? value : JSON.stringify(value);
         return (
           <p
-            className="text-[13px] leading-relaxed line-clamp-6"
+            className="text-ui-13 leading-relaxed line-clamp-6"
             title={full}
           >
             {text}
@@ -331,11 +331,11 @@ export function DatasetPreviewDialog({
         id: "__system_generated",
         header: () => (
           <div className="flex flex-col gap-2">
-            <span className="font-heading text-[13px] font-semibold tracking-tight text-foreground">
+            <span className="font-heading text-ui-13 font-semibold tracking-tight text-foreground">
               System <span className="text-muted-foreground font-normal">(generated)</span>
             </span>
             {mappingEnabled && (
-              <Badge variant="outline" className="h-6 w-fit text-[10px] px-2 py-0 border-dashed text-muted-foreground">
+              <Badge variant="outline" className="h-6 w-fit text-ui-10 px-2 py-0 border-dashed text-muted-foreground">
                 System
               </Badge>
             )}
@@ -343,7 +343,7 @@ export function DatasetPreviewDialog({
         ),
         cell: () => (
           <p
-            className="text-[13px] leading-relaxed line-clamp-6 text-muted-foreground italic"
+            className="text-ui-13 leading-relaxed line-clamp-6 text-muted-foreground italic"
             title={datasetSystemPrompt}
           >
             {datasetSystemPrompt}
@@ -443,7 +443,7 @@ export function DatasetPreviewDialog({
                         <Badge
                           key={col}
                           variant="outline"
-                          className="text-[11px] font-mono h-5"
+                          className="text-ui-11 font-mono h-5"
                         >
                           {col}
                         </Badge>
@@ -493,7 +493,7 @@ export function DatasetPreviewDialog({
 
               {/* Footer */}
               <div className="mt-3">
-                <p className="text-[11px] text-muted-foreground/60 text-center tabular-nums">
+                <p className="text-ui-11 text-muted-foreground/60 text-center tabular-nums">
                   Showing {rows.length}
                   {data.total_rows != null &&
                     ` of ${data.total_rows.toLocaleString()}`}{" "}
@@ -501,7 +501,7 @@ export function DatasetPreviewDialog({
                 </p>
 
                 {mode === "preview" && mappingEnabled && (
-                  <p className="mt-2 text-[11px] text-muted-foreground/70 text-center">
+                  <p className="mt-2 text-ui-11 text-muted-foreground/70 text-center">
                     Mapping is saved automatically. You can start training anytime.
                   </p>
                 )}
@@ -540,7 +540,7 @@ function MetaRow({
       <span className="text-muted-foreground font-medium text-xs w-24 shrink-0">
         {label}:
       </span>
-      <span className="text-foreground text-[13px] min-w-0">{value}</span>
+      <span className="text-foreground text-ui-13 min-w-0">{value}</span>
     </div>
   );
 }
diff --git a/studio/frontend/src/features/studio/sections/dataset-section.tsx b/studio/frontend/src/features/studio/sections/dataset-section.tsx
index 6aa9329609..6a3cc8129a 100644
--- a/studio/frontend/src/features/studio/sections/dataset-section.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-section.tsx
@@ -728,7 +728,7 @@ export function DatasetSection() {
                       }
                     }}
                     className={cn(
-                      "relative inline-flex h-9 flex-auto cursor-pointer items-center justify-center rounded-full px-3 text-[12.5px] font-medium transition-colors",
+                      "relative inline-flex h-9 flex-auto cursor-pointer items-center justify-center rounded-full px-3 text-ui-12p5 font-medium transition-colors",
                       datasetSource === item.value
                         ? "text-foreground"
                         : "text-muted-foreground hover:text-foreground",
@@ -764,7 +764,7 @@ export function DatasetSection() {
             <div className="flex min-w-0 flex-col gap-2">
               <span className="flex items-center gap-1.5 text-xs font-medium text-muted-foreground">
                 {t("studio.dataset.chooseDataset")}
-                <span className="rounded-full border border-border/70 bg-muted/40 px-2 py-0.5 text-[10px] font-medium text-foreground/80">
+                <span className="rounded-full border border-border/70 bg-muted/40 px-2 py-0.5 text-ui-10 font-medium text-foreground/80">
                   {datasetSource === "upload"
                     ? t("studio.dataset.localTab")
                     : "Hugging Face"}
@@ -1030,7 +1030,7 @@ export function DatasetSection() {
                 </p>
               )}
               {pickerTab !== activeSourceTab && (
-                <p className="text-[11px] text-muted-foreground">
+                <p className="text-ui-11 text-muted-foreground">
                   {t("studio.dataset.browsingSource", {
                     browsing:
                       pickerTab === "local"
@@ -1068,7 +1068,7 @@ export function DatasetSection() {
                       <p className="text-xs font-medium text-muted-foreground">
                         {t("studio.dataset.localDatasetMetadata")}
                       </p>
-                      <p className="text-[10px] text-muted-foreground/80">
+                      <p className="text-ui-10 text-muted-foreground/80">
                         {t("studio.dataset.dataRecipeOutput")}
                       </p>
                     </div>
@@ -1172,7 +1172,7 @@ export function DatasetSection() {
                       ? t("studio.dataset.uploading")
                       : t("studio.dataset.uploadEvalFile")}
                   </Button>
-                  <p className="text-[10px] text-muted-foreground/80">
+                  <p className="text-ui-10 text-muted-foreground/80">
                     {t("studio.dataset.evalDatasetDescription")}
                   </p>
                 </div>
@@ -1379,7 +1379,7 @@ export function DatasetSection() {
                           deriveLocalDatasetName(selectedDatasetName))
                         : selectedDatasetName}
                     </p>
-                    <p className="text-[10px] text-muted-foreground">
+                    <p className="text-ui-10 text-muted-foreground">
                       {datasetSource === "upload" ? (
                         uploadedFile ? (
                           <>
@@ -1433,7 +1433,7 @@ export function DatasetSection() {
                     <span className="block text-xs font-medium text-foreground">
                       {t("studio.dataset.dropFileOrClick")}
                     </span>
-                    <span className="mt-0.5 block truncate text-[10px] text-muted-foreground">
+                    <span className="mt-0.5 block truncate text-ui-10 text-muted-foreground">
                       {TRAINING_DATASET_UPLOAD_LABEL} · up to {uploadLimitLabel}
                       ; {DOCUMENT_REDIRECT_LABEL}
                     </span>
diff --git a/studio/frontend/src/features/studio/sections/model-section.tsx b/studio/frontend/src/features/studio/sections/model-section.tsx
index c8f36b397c..0589fde350 100644
--- a/studio/frontend/src/features/studio/sections/model-section.tsx
+++ b/studio/frontend/src/features/studio/sections/model-section.tsx
@@ -374,7 +374,7 @@ export function ModelSection() {
                               {model?.path ?? id}
                             </TooltipContent>
                           </Tooltip>
-                          <span className="ml-auto shrink-0 text-[10px] text-muted-foreground">
+                          <span className="ml-auto shrink-0 text-ui-10 text-muted-foreground">
                             {source}
                           </span>
                         </ComboboxItem>
@@ -385,13 +385,13 @@ export function ModelSection() {
               </Combobox>
             </div>
             {isLoadingLocalModels ? (
-              <p className="text-[10px] text-muted-foreground">
+              <p className="text-ui-10 text-muted-foreground">
                 {t("studio.model.scanningLocalModels")}
               </p>
             ) : localModelsError ? (
-              <p className="text-[10px] text-red-500">{localModelsError}</p>
+              <p className="text-ui-10 text-red-500">{localModelsError}</p>
             ) : (
-              <p className="text-[10px] text-muted-foreground">
+              <p className="text-ui-10 text-muted-foreground">
                 {trainableLocalModels.length > 0
                   ? t("studio.model.localModelsFound", {
                       count: trainableLocalModels.length,
@@ -507,7 +507,7 @@ export function ModelSection() {
                                 {vramEst != null &&
                                   vramEst > 0 &&
                                   gpu.available && (
-                                    <span className="block text-[10px] mt-1">
+                                    <span className="block text-ui-10 mt-1">
                                       {exceeds
                                         ? t("studio.model.needsVram", {
                                             vram: vramEst,
@@ -527,17 +527,17 @@ export function ModelSection() {
                             </Tooltip>
                             <span className="ml-auto flex items-center gap-1.5 shrink-0">
                               {fitStatus === "exceeds" && (
-                                <span className="text-[9px] font-medium !text-red-700 !bg-red-50 dark:!text-red-400 dark:!bg-red-950 px-1.5 py-0.5 rounded">
+                                <span className="text-ui-9 font-medium !text-red-700 !bg-red-50 dark:!text-red-400 dark:!bg-red-950 px-1.5 py-0.5 rounded">
                                   OOM
                                 </span>
                               )}
                               {fitStatus === "tight" && (
-                                <span className="text-[9px] font-medium !text-amber-400">
+                                <span className="text-ui-9 font-medium !text-amber-400">
                                   TIGHT
                                 </span>
                               )}
                               {detail && (
-                                <span className="text-[10px] text-muted-foreground">
+                                <span className="text-ui-10 text-muted-foreground">
                                   {detail}
                                 </span>
                               )}
diff --git a/studio/frontend/src/features/studio/sections/params-section.tsx b/studio/frontend/src/features/studio/sections/params-section.tsx
index ad438f63f1..3270eb4e3d 100644
--- a/studio/frontend/src/features/studio/sections/params-section.tsx
+++ b/studio/frontend/src/features/studio/sections/params-section.tsx
@@ -36,6 +36,7 @@ import {
   CONTEXT_LENGTHS,
   CPT_TARGET_MODULES,
   LR_SCHEDULER_OPTIONS,
+  MLX_OPTIMIZER_OPTIONS,
   OPTIMIZER_OPTIONS,
   TARGET_MODULES,
 } from "@/config/training";
@@ -204,6 +205,42 @@ export function ParamsSection(): ReactElement {
     setCtxInput(String(store.contextLength));
   }, [store.contextLength]);
 
+  // On Apple Silicon the MLX trainer supports a different optimizer set than
+  // the CUDA/bitsandbytes list, so offer the MLX names there.
+  const isMac = platformDeviceType === "mac";
+  const optimizerOptions = isMac ? MLX_OPTIMIZER_OPTIONS : OPTIMIZER_OPTIONS;
+
+  // On Mac, the MLX backend normalizes every CUDA/bitsandbytes optimizer in
+  // OPTIMIZER_OPTIONS (including the shared default) to plain AdamW, so show
+  // AdamW for those to keep the control truthful and non-blank. Any other
+  // value -- an MLX optimizer the user picked, or an unrecognized/non-canonical
+  // imported one -- is shown as-is rather than mislabeled as AdamW, since the
+  // backend would run or reject it on its own terms. Non-Mac display unchanged.
+  const isCudaAliasOptimizer = OPTIMIZER_OPTIONS.some(
+    (o) => o.value === store.optimizerType,
+  );
+  const selectedOptimizer =
+    isMac && isCudaAliasOptimizer ? "adamw" : store.optimizerType;
+
+  // LoftQ is not supported on MLX (the backend rejects it), so clear a stale
+  // selection to lora on Apple Silicon -- whether persisted, applied from a
+  // model default, or imported -- so the backend never receives it.
+  const setLoraVariant = store.setLoraVariant;
+  useEffect(() => {
+    if (isMac && store.loraVariant === "loftq") {
+      setLoraVariant("lora");
+    }
+  }, [isMac, store.loraVariant, setLoraVariant]);
+
+  // Packing is not supported on MLX (the backend forces it off), so clear it on
+  // Apple Silicon -- the checkbox is disabled and the flag is never sent.
+  const setPacking = store.setPacking;
+  useEffect(() => {
+    if (isMac && store.packing) {
+      setPacking(false);
+    }
+  }, [isMac, store.packing, setPacking]);
+
   const trySetContextLength = (input: string): number | null => {
     const n = Number(input);
     if (Number.isInteger(n) && n > 0) {
@@ -238,7 +275,7 @@ export function ParamsSection(): ReactElement {
           <div className="flex flex-col gap-2">
             <span className="flex items-center gap-1.5 text-xs font-medium text-muted-foreground">
               {t("studio.params.projectName")}
-              <span className="text-[10px] font-normal text-muted-foreground/70">
+              <span className="text-ui-10 font-normal text-muted-foreground/70">
                 {t("studio.params.optional")}
               </span>
             </span>
@@ -248,7 +285,7 @@ export function ParamsSection(): ReactElement {
               placeholder="customer-support-lora"
               maxLength={80}
             />
-            <p className="text-[10px] text-muted-foreground">
+            <p className="text-ui-10 text-muted-foreground">
               {t("studio.params.projectNameDescription")}
             </p>
           </div>
@@ -337,7 +374,7 @@ export function ParamsSection(): ReactElement {
                 max={useEpochs ? epochsSliderMax : maxStepsSliderMax}
                 step={1}
               />
-              <p className="text-[10px] text-muted-foreground">
+              <p className="text-ui-10 text-muted-foreground">
                 {useEpochs
                   ? t("studio.params.epochsDescription")
                   : t("studio.params.maxStepsDescription")}
@@ -425,7 +462,7 @@ export function ParamsSection(): ReactElement {
                 </ComboboxContent>
               </Combobox>
             </div>
-            <p className="text-[10px] text-muted-foreground">
+            <p className="text-ui-10 text-muted-foreground">
               {t("studio.params.contextLengthDescription")}
             </p>
           </div>
@@ -466,7 +503,7 @@ export function ParamsSection(): ReactElement {
               onChange={(e) => store.setLearningRate(Number(e.target.value))}
               className="w-full font-mono"
             />
-            <p className="text-[10px] text-muted-foreground">
+            <p className="text-ui-10 text-muted-foreground">
               {t("studio.params.learningRateDescription")}
             </p>
           </div>
@@ -511,7 +548,7 @@ export function ParamsSection(): ReactElement {
                 }}
                 className="w-full font-mono"
               />
-              <p className="text-[10px] text-muted-foreground">
+              <p className="text-ui-10 text-muted-foreground">
                 {t("studio.params.embeddingLearningRateDescription")}
               </p>
             </div>
@@ -667,7 +704,7 @@ export function ParamsSection(): ReactElement {
                                       : [...store.targetModules, mod],
                                   );
                                 }}
-                                className={`cursor-pointer rounded-full border px-2.5 py-0.5 text-[11px] font-mono transition-colors ${
+                                className={`cursor-pointer rounded-full border px-2.5 py-0.5 text-ui-11 font-mono transition-colors ${
                                   active
                                     ? "border-orange-300 bg-orange-50 text-orange-700 dark:border-orange-700 dark:bg-orange-950 dark:text-orange-300"
                                     : "text-muted-foreground hover:bg-muted/50"
@@ -706,16 +743,19 @@ export function ParamsSection(): ReactElement {
                       <button
                         key={opt.value}
                         type="button"
+                        disabled={isMac && opt.value === "loftq"}
                         onClick={() => store.setLoraVariant(opt.value)}
-                        className={`flex-1 corner-squircle rounded-xl border px-3 py-2 text-left transition-colors cursor-pointer ${
+                        className={`flex-1 corner-squircle rounded-xl border px-3 py-2 text-left transition-colors cursor-pointer disabled:cursor-not-allowed disabled:opacity-60 ${
                           store.loraVariant === opt.value
                             ? "border-ring-strong bg-primary/5"
                             : "border-border hover:border-foreground/20"
                         }`}
                       >
                         <p className="text-xs font-medium">{opt.label}</p>
-                        <p className="text-[10px] text-muted-foreground">
-                          {opt.desc}
+                        <p className="text-ui-10 text-muted-foreground">
+                          {isMac && opt.value === "loftq"
+                            ? "Not supported on Apple Silicon"
+                            : opt.desc}
                         </p>
                       </button>
                     ))}
@@ -765,7 +805,11 @@ export function ParamsSection(): ReactElement {
                     label={t("studio.params.optimizer")}
                     tooltip={
                       <>
-                        {t("studio.params.optimizerTooltip")}{" "}
+                        {t(
+                          isMac
+                            ? "studio.params.optimizerTooltipMlx"
+                            : "studio.params.optimizerTooltip",
+                        )}{" "}
                         <a
                           href="https://unsloth.ai/docs/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide"
                           target="_blank"
@@ -778,14 +822,14 @@ export function ParamsSection(): ReactElement {
                     }
                   >
                     <Select
-                      value={store.optimizerType}
+                      value={selectedOptimizer}
                       onValueChange={(v) => store.setOptimizerType(v)}
                     >
                       <SelectTrigger className="w-48">
                         <SelectValue />
                       </SelectTrigger>
                       <SelectContent>
-                        {OPTIMIZER_OPTIONS.map((opt) => (
+                        {optimizerOptions.map((opt) => (
                           <SelectItem key={opt.value} value={opt.value}>
                             {formatOptimizerLabel(opt.value, opt.label, t)}
                           </SelectItem>
@@ -1105,14 +1149,37 @@ export function ParamsSection(): ReactElement {
                       <Checkbox
                         id="packing"
                         checked={store.packing}
+                        disabled={isMac}
                         onCheckedChange={(v) => store.setPacking(!!v)}
                       />
                       <label
                         htmlFor="packing"
-                        className="text-xs cursor-pointer text-muted-foreground"
+                        className={`text-xs text-muted-foreground ${
+                          isMac
+                            ? "cursor-not-allowed opacity-60"
+                            : "cursor-pointer"
+                        }`}
                       >
                         {t("studio.params.enablePacking")}
                       </label>
+                      {isMac && (
+                        <Tooltip>
+                          <TooltipTrigger asChild={true}>
+                            <button
+                              type="button"
+                              className="text-foreground/70 hover:text-foreground"
+                            >
+                              <HugeiconsIcon
+                                icon={InformationCircleIcon}
+                                className="size-3"
+                              />
+                            </button>
+                          </TooltipTrigger>
+                          <TooltipContent>
+                            Packing is not supported on Apple Silicon (MLX).
+                          </TooltipContent>
+                        </Tooltip>
+                      )}
                     </div>
                   )}
                   {!store.isEmbeddingModel && !isCpt && !isRawText && (
diff --git a/studio/frontend/src/features/studio/sections/progress-section.tsx b/studio/frontend/src/features/studio/sections/progress-section.tsx
index 37bec84a48..ad813e888e 100644
--- a/studio/frontend/src/features/studio/sections/progress-section.tsx
+++ b/studio/frontend/src/features/studio/sections/progress-section.tsx
@@ -19,7 +19,8 @@ import {
   PopoverTrigger,
 } from "@/components/ui/popover";
 import { Progress } from "@/components/ui/progress";
-import { OPTIMIZER_OPTIONS } from "@/config/training";
+import { usePlatformStore } from "@/config/env";
+import { MLX_OPTIMIZER_OPTIONS, OPTIMIZER_OPTIONS } from "@/config/training";
 import { setTrainingCompareHandoff } from "@/features/chat";
 import {
   useTrainingActions,
@@ -92,6 +93,7 @@ export function ProgressSection({
 }: ProgressSectionProps): ReactElement {
   const t = useT();
   const navigate = useNavigate();
+  const platformDeviceType = usePlatformStore((s) => s.deviceType);
   const trainingMethodLabel = getTrainingMethodLabel(data.trainingMethod);
 
   const config = useTrainingConfigStore(
@@ -187,9 +189,18 @@ export function ProgressSection({
   const cfgLoraDropout = cfg?.loraDropout;
   const cfgLoraVariant = cfg?.loraVariant;
 
+  // Mirror the training form: on Mac the CUDA/bitsandbytes optimizer names run
+  // as plain AdamW (the MLX backend normalizes them), so label them AdamW here
+  // too rather than by the requested, unnormalized name.
+  const effectiveOptimizer =
+    platformDeviceType === "mac" &&
+    OPTIMIZER_OPTIONS.some((o) => o.value === cfgOptimizerType)
+      ? "adamw"
+      : cfgOptimizerType;
   const optimizerLabel =
-    OPTIMIZER_OPTIONS.find((o) => o.value === cfgOptimizerType)?.label ??
-    cfgOptimizerType;
+    [...OPTIMIZER_OPTIONS, ...MLX_OPTIMIZER_OPTIONS].find(
+      (o) => o.value === effectiveOptimizer,
+    )?.label ?? effectiveOptimizer;
 
   const configItems: ConfigGroup[] = [
     {
@@ -258,21 +269,21 @@ export function ProgressSection({
         <div className="flex flex-col gap-4">
           <div className="flex flex-wrap items-center gap-2">
             <span
-              className={`rounded-full px-2.5 py-1 text-[10px] font-semibold ${phaseColors[data.phase]}`}
+              className={`rounded-full px-2.5 py-1 text-ui-10 font-semibold ${phaseColors[data.phase]}`}
             >
               {t(phaseLabelKeys[data.phase])}
             </span>
             {data.projectName && (
-              <span className="rounded-full border border-border/60 px-2.5 py-1 text-[10px] font-medium text-foreground/80">
+              <span className="rounded-full border border-border/60 px-2.5 py-1 text-ui-10 font-medium text-foreground/80">
                 {data.projectName}
               </span>
             )}
-            <span className="text-[10px] tabular-nums text-muted-foreground">
+            <span className="text-ui-10 tabular-nums text-muted-foreground">
               {t("studio.progress.epoch", {
                 value: formatNumber(data.currentEpoch, 2),
               })}
             </span>
-            <span className="rounded-full border border-border/60 px-2.5 py-1 text-[10px] font-medium tabular-nums text-muted-foreground">
+            <span className="rounded-full border border-border/60 px-2.5 py-1 text-ui-10 font-medium tabular-nums text-muted-foreground">
               {t("studio.progress.percentComplete", { percent: pct })}
             </span>
           </div>
@@ -394,7 +405,7 @@ function LiveGpuPanel({
             <select
               value={selectedGpu}
               onChange={(e) => setSelectedGpu(Number(e.target.value))}
-              className="h-6 cursor-pointer rounded-md border border-border bg-popover px-1.5 py-0.5 text-[11px] text-popover-foreground outline-none hover:bg-muted focus:border-ring transition-colors font-medium appearance-none"
+              className="h-6 cursor-pointer rounded-md border border-border bg-popover px-1.5 py-0.5 text-ui-11 text-popover-foreground outline-none hover:bg-muted focus:border-ring transition-colors font-medium appearance-none"
               title="Select GPU"
             >
               {gpus.map((device, index) => (
@@ -409,7 +420,7 @@ function LiveGpuPanel({
             </select>
           )}
         </div>
-        <span className="text-[11px] text-muted-foreground">
+        <span className="text-ui-11 text-muted-foreground">
           {t("studio.progress.live")}
         </span>
       </div>
@@ -527,7 +538,7 @@ function ConfigPopoverButton({
           <p className="text-xs font-semibold">{t("studio.progress.configLabel")}</p>
           {configItems.map((group) => (
             <div key={group.section} className="flex flex-col gap-1">
-              <p className="text-[10px] font-semibold uppercase tracking-wider text-muted-foreground">
+              <p className="text-ui-10 font-semibold uppercase tracking-wider text-muted-foreground">
                 {group.section}
               </p>
               {group.rows.map(([label, value]) => (
@@ -628,7 +639,7 @@ function MilestoneCallout({
       <div className="flex items-start justify-between gap-3">
         <div className="min-w-0">
           {!showCompletedHint && (
-            <p className="text-[10px] font-medium uppercase tracking-[0.12em] text-muted-foreground">
+            <p className="text-ui-10 font-medium uppercase tracking-[0.12em] text-muted-foreground">
               {t("studio.training.milestone")}
             </p>
           )}
@@ -644,7 +655,7 @@ function MilestoneCallout({
           </p>
         </div>
         {!showCompletedHint && (
-          <span className="rounded-full border border-border/60 bg-background/80 px-2 py-0.5 text-[10px] font-medium text-muted-foreground">
+          <span className="rounded-full border border-border/60 bg-background/80 px-2 py-0.5 text-ui-10 font-medium text-muted-foreground">
             50%+
           </span>
         )}
@@ -674,7 +685,7 @@ function MetricStat({
 }): ReactElement {
   return (
     <div className="min-w-0">
-      <p className="text-[11px] text-muted-foreground">{label}</p>
+      <p className="text-ui-11 text-muted-foreground">{label}</p>
       <p
         className={`mt-1 text-base font-semibold tabular-nums ${valueClassName ?? ""}`}
       >
diff --git a/studio/frontend/src/features/studio/sections/s3-config-form.tsx b/studio/frontend/src/features/studio/sections/s3-config-form.tsx
index 8126027cf9..e7daffb750 100644
--- a/studio/frontend/src/features/studio/sections/s3-config-form.tsx
+++ b/studio/frontend/src/features/studio/sections/s3-config-form.tsx
@@ -51,7 +51,7 @@ export function S3ConfigForm() {
         <p className="text-xs font-medium text-foreground">
           {t("studio.dataset.s3.title")}
         </p>
-        <p className="text-[10px] text-muted-foreground/80">
+        <p className="text-ui-10 text-muted-foreground/80">
           {t("studio.dataset.s3.description")}
         </p>
       </div>
diff --git a/studio/frontend/src/features/studio/studio-page.tsx b/studio/frontend/src/features/studio/studio-page.tsx
index 4d3a32fab3..f50dcf5155 100644
--- a/studio/frontend/src/features/studio/studio-page.tsx
+++ b/studio/frontend/src/features/studio/studio-page.tsx
@@ -165,7 +165,7 @@ export function StudioPage(): ReactElement {
         />
 
         <div className="mb-6 flex flex-col gap-0.5 sm:mb-8">
-          <h1 className="text-[30px] font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-[34px]">
+          <h1 className="text-ui-30 font-semibold leading-[1.04] tracking-[-0.028em] text-foreground sm:text-ui-34">
             {t("studio.title")}
           </h1>
           <p className="text-sm text-muted-foreground">{subtitle}</p>
@@ -217,7 +217,13 @@ export function StudioPage(): ReactElement {
 
             <TabsContent value="history">
               {selectedHistoryRunId ? (
-                <HistoricalTrainingView runId={selectedHistoryRunId} />
+                <HistoricalTrainingView
+                  runId={selectedHistoryRunId}
+                  onResumeStarted={() => {
+                    setSelectedHistoryRunId(null);
+                    handleTabChange("current-run");
+                  }}
+                />
               ) : (
                 <HistoryCardGrid onSelectRun={(runId) => {
                   if (runId === currentJobId && isTrainingRunning) {
diff --git a/studio/frontend/src/features/studio/training-start-overlay.tsx b/studio/frontend/src/features/studio/training-start-overlay.tsx
index db2ca91313..c836b61ce4 100644
--- a/studio/frontend/src/features/studio/training-start-overlay.tsx
+++ b/studio/frontend/src/features/studio/training-start-overlay.tsx
@@ -210,7 +210,7 @@ function DownloadRow({ label, state }: DownloadRowProps): ReactElement | null {
           <span className="text-xs text-foreground/90">{label}</span>
           {statusLabel ? (
             <span
-              className={`rounded-full px-1.5 py-0.5 text-[10px] font-medium ${isComplete ? "bg-emerald-100 text-emerald-700 ring-1 ring-emerald-200/80 dark:bg-emerald-500/15 dark:text-emerald-300 dark:ring-emerald-500/30" : "bg-muted text-muted-foreground"}`}
+              className={`rounded-full px-1.5 py-0.5 text-ui-10 font-medium ${isComplete ? "bg-emerald-100 text-emerald-700 ring-1 ring-emerald-200/80 dark:bg-emerald-500/15 dark:text-emerald-300 dark:ring-emerald-500/30" : "bg-muted text-muted-foreground"}`}
             >
               {statusLabel}
             </span>
@@ -221,7 +221,7 @@ function DownloadRow({ label, state }: DownloadRowProps): ReactElement | null {
         </span>
       </div>
       {sizeLabel ? (
-        <div className="text-[11px] tabular-nums text-muted-foreground">
+        <div className="text-ui-11 tabular-nums text-muted-foreground">
           {sizeLabel}
         </div>
       ) : null}
@@ -233,7 +233,7 @@ function DownloadRow({ label, state }: DownloadRowProps): ReactElement | null {
       ) : null}
       {state.cachePath ? (
         <div
-          className="truncate rounded bg-muted/50 px-2 py-1 text-[10px] text-muted-foreground/70"
+          className="truncate rounded bg-muted/50 px-2 py-1 text-ui-10 text-muted-foreground/70"
           title={state.cachePath}
         >
           {formatCachePath(state.cachePath)}
diff --git a/studio/frontend/src/features/tour/components/guided-tour.tsx b/studio/frontend/src/features/tour/components/guided-tour.tsx
index a0ed6be98c..c0730d0389 100644
--- a/studio/frontend/src/features/tour/components/guided-tour.tsx
+++ b/studio/frontend/src/features/tour/components/guided-tour.tsx
@@ -313,13 +313,13 @@ export function GuidedTour({
                   <div className="relative p-5">
                     <div className="flex items-start justify-between gap-3">
                       <div className="min-w-0">
-                        <div className="inline-flex items-center gap-2 rounded-full bg-black/[0.04] px-2.5 py-1 text-[10px] font-mono text-foreground/60 ring-1 ring-black/10 dark:bg-white/[0.04] dark:text-zinc-200/75 dark:ring-white/14">
+                        <div className="inline-flex items-center gap-2 rounded-full bg-black/[0.04] px-2.5 py-1 text-ui-10 font-mono text-foreground/60 ring-1 ring-black/10 dark:bg-white/[0.04] dark:text-zinc-200/75 dark:ring-white/14">
                           {idx + 1}/{total}
                           <span className="size-1 rounded-full bg-control-accent/70" />
                           guided tour
                         </div>
                         <DialogPrimitive.Title
-                          className="mt-2 text-[18px] leading-tight"
+                          className="mt-2 text-ui-18 leading-tight"
                           style={{ fontFamily: "var(--font-serif)" }}
                         >
                           {step?.title ?? "Quick tour"}
@@ -383,7 +383,7 @@ export function GuidedTour({
                   </div>
 
                   <div className="h-px bg-gradient-to-r from-transparent via-black/10 to-transparent dark:via-white/14" />
-                  <div className="px-5 py-3 text-[11px] text-foreground/55 dark:text-zinc-300/65">
+                  <div className="px-5 py-3 text-ui-11 text-foreground/55 dark:text-zinc-300/65">
                     Tip: `Esc` skips. Tour blocks clicks so you can read.
                   </div>
                 </motion.div>
diff --git a/studio/frontend/src/features/training/api/models-api.ts b/studio/frontend/src/features/training/api/models-api.ts
index e5fd8b043d..adda7d0a77 100644
--- a/studio/frontend/src/features/training/api/models-api.ts
+++ b/studio/frontend/src/features/training/api/models-api.ts
@@ -2,6 +2,7 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { authFetch } from "@/features/auth";
+import { hubTokenHeader } from "@/features/hub";
 
 interface VisionCheckResponse {
   model_name: string;
@@ -98,8 +99,9 @@ export async function checkVisionModel(
   hfToken?: string | null,
 ): Promise<boolean> {
   const encoded = encodeURIComponent(modelName);
-  const query = hfToken?.trim() ? `?hf_token=${encodeURIComponent(hfToken.trim())}` : "";
-  const response = await authFetch(`/api/models/check-vision/${encoded}${query}`);
+  const response = await authFetch(`/api/models/check-vision/${encoded}`, {
+    headers: hubTokenHeader(hfToken?.trim() || null),
+  });
   if (!response.ok) {
     // If the check fails (e.g. network error), default to non-vision
     return false;
@@ -114,8 +116,9 @@ export async function checkEmbeddingModel(
   hfToken?: string | null,
 ): Promise<boolean> {
   const encoded = encodeURIComponent(modelName);
-  const query = hfToken?.trim() ? `?hf_token=${encodeURIComponent(hfToken.trim())}` : "";
-  const response = await authFetch(`/api/models/check-embedding/${encoded}${query}`);
+  const response = await authFetch(`/api/models/check-embedding/${encoded}`, {
+    headers: hubTokenHeader(hfToken?.trim() || null),
+  });
   if (!response.ok) {
     // If the check fails (e.g. network error), default to non-embedding
     return false;
@@ -130,8 +133,10 @@ export async function getModelConfig(
   hfToken?: string,
 ): Promise<ModelConfigResponse> {
   const encoded = encodeURIComponent(modelName);
-  const params = hfToken ? `?hf_token=${encodeURIComponent(hfToken)}` : "";
-  const response = await authFetch(`/api/models/config/${encoded}${params}`, { signal });
+  const response = await authFetch(`/api/models/config/${encoded}`, {
+    headers: hubTokenHeader(hfToken?.trim() || null),
+    signal,
+  });
   if (!response.ok) {
     throw new Error(`Failed to fetch model config (${response.status})`);
   }
diff --git a/studio/frontend/src/features/training/hooks/use-training-actions.ts b/studio/frontend/src/features/training/hooks/use-training-actions.ts
index 0d32e066d5..9bb8206f28 100644
--- a/studio/frontend/src/features/training/hooks/use-training-actions.ts
+++ b/studio/frontend/src/features/training/hooks/use-training-actions.ts
@@ -217,7 +217,7 @@ export function useTrainingActions() {
       const detail = await getTrainingRun(runId);
       const outputDir = detail.run.output_dir;
       if (!detail.run.can_resume || !outputDir) {
-        throw new Error("Only stopped runs with a saved checkpoint can be resumed.");
+        throw new Error("Only stopped or errored runs with a saved checkpoint can be resumed.");
       }
 
       primeNativeNotificationPermission().catch(() => undefined);
diff --git a/studio/frontend/src/features/training/index.ts b/studio/frontend/src/features/training/index.ts
index a0d249ff1b..81514b4415 100644
--- a/studio/frontend/src/features/training/index.ts
+++ b/studio/frontend/src/features/training/index.ts
@@ -25,8 +25,8 @@ export { HfDatasetSubsetSplitSelectors } from "./components/hf-dataset-subset-sp
 export { useDatasetPreviewDialogStore } from "./stores/dataset-preview-dialog-store";
 export { listLocalDatasets, uploadTrainingDataset } from "./api/datasets-api";
 export type { LocalDatasetInfo } from "./types/datasets";
-export { listLocalModels } from "./api/models-api";
-export type { LocalModelInfo } from "./api/models-api";
+export { getModelConfig, listLocalModels } from "./api/models-api";
+export type { LocalModelInfo, ModelConfigResponse } from "./api/models-api";
 export type {
   TrainingPhase,
   TrainingViewData,
diff --git a/studio/frontend/src/features/training/stores/training-runtime-store.ts b/studio/frontend/src/features/training/stores/training-runtime-store.ts
index acc80a3be2..131ea30d30 100644
--- a/studio/frontend/src/features/training/stores/training-runtime-store.ts
+++ b/studio/frontend/src/features/training/stores/training-runtime-store.ts
@@ -223,7 +223,10 @@ export const useTrainingRuntimeStore = create<TrainingRuntimeStore>()((set) => (
           typeof detailLr === "number" ? detailLr : state.currentLearningRate,
         currentEpoch:
           typeof detailEpoch === "number" ? detailEpoch : state.currentEpoch,
-        outputDir: payload.details?.output_dir ?? state.outputDir,
+        outputDir:
+          payload.details?.output_dir !== undefined
+            ? payload.details.output_dir
+            : state.outputDir,
         lossHistory: metricHistory.lossHistory ?? state.lossHistory,
         lrHistory: metricHistory.lrHistory ?? state.lrHistory,
         gradNormHistory: metricHistory.gradNormHistory ?? state.gradNormHistory,
diff --git a/studio/frontend/src/features/training/types/runtime.ts b/studio/frontend/src/features/training/types/runtime.ts
index 8ed0ce0037..373e876653 100644
--- a/studio/frontend/src/features/training/types/runtime.ts
+++ b/studio/frontend/src/features/training/types/runtime.ts
@@ -26,7 +26,8 @@ export interface TrainingStatusResponse {
     total_steps?: number;
     loss?: number;
     learning_rate?: number;
-    output_dir?: string;
+    // null = explicit clear (run stopped without saving); absent = unchanged.
+    output_dir?: string | null;
   } | null;
   metric_history?: {
     steps?: number[];
diff --git a/studio/frontend/src/hooks/index.ts b/studio/frontend/src/hooks/index.ts
index 5b2fa43ae7..33289ffe9e 100644
--- a/studio/frontend/src/hooks/index.ts
+++ b/studio/frontend/src/hooks/index.ts
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-
 export { useDebouncedValue } from "./use-debounced-value";
 export { useGpuInfo } from "./use-gpu-info";
 export { useGpuUtilization } from "./use-gpu-utilization";
@@ -11,3 +10,4 @@ export { useHfTokenValidation } from "./use-hf-token-validation";
 export { useTauriBackend } from "./use-tauri-backend";
 export { useCollapseScrollLock } from "./use-collapse-scroll-lock";
 export { useSystemInfo } from "./use-system";
+export { useWheelScrollRef } from "./use-wheel-scroll-ref";
diff --git a/studio/frontend/src/hooks/use-hf-token-validation.ts b/studio/frontend/src/hooks/use-hf-token-validation.ts
index e0ed02cca2..64e8a869b4 100644
--- a/studio/frontend/src/hooks/use-hf-token-validation.ts
+++ b/studio/frontend/src/hooks/use-hf-token-validation.ts
@@ -36,10 +36,8 @@ const COMPLETE_HF_TOKEN = /^hf_[A-Za-z0-9]{34}$/;
  * requests while typing. isValid is null until checked.
  */
 export function useHfTokenValidation(token: string): HfTokenValidationState {
-  const debouncedToken = useDebouncedValue(
-    token.trim().replace(/^["']+|["']+$/g, ""),
-    500,
-  );
+  const normalizedToken = token.trim().replace(/^["']+|["']+$/g, "");
+  const debouncedToken = useDebouncedValue(normalizedToken, 500);
   const [completed, setCompleted] = useState<CompletedValidation>(
     NO_COMPLETED_VALIDATION,
   );
@@ -83,7 +81,8 @@ export function useHfTokenValidation(token: string): HfTokenValidationState {
           setCompleted({
             token: debouncedToken,
             isValid: null,
-            error: "Could not verify the token. Check your connection and try again.",
+            error:
+              "Could not verify the token. Check your connection and try again.",
             isChecking: false,
           });
         }
@@ -93,15 +92,16 @@ export function useHfTokenValidation(token: string): HfTokenValidationState {
         setCompleted({
           token: debouncedToken,
           isValid: null,
-          error: "Could not verify the token. Check your connection and try again.",
+          error:
+            "Could not verify the token. Check your connection and try again.",
           isChecking: false,
         });
       },
     );
   }, [debouncedToken, shouldValidate]);
 
-  if (!shouldValidate) return INITIAL;
-  if (completed.token !== debouncedToken) {
+  if (!COMPLETE_HF_TOKEN.test(normalizedToken)) return INITIAL;
+  if (completed.token !== normalizedToken) {
     return { isValid: null, error: null, isChecking: true };
   }
   return {
diff --git a/studio/frontend/src/hooks/use-llama-update-check.ts b/studio/frontend/src/hooks/use-llama-update-check.ts
index e3a735ffde..999700ae1f 100644
--- a/studio/frontend/src/hooks/use-llama-update-check.ts
+++ b/studio/frontend/src/hooks/use-llama-update-check.ts
@@ -30,6 +30,7 @@ export interface LlamaUpdateJob {
 export interface LlamaUpdateStatus {
   supported: boolean;
   update_available: boolean;
+  component: "llama.cpp" | "whisper.cpp";
   installed_tag: string | null;
   latest_tag: string | null;
   // Prebuilt download size in bytes, if known.
@@ -55,13 +56,30 @@ function parseJob(value: unknown): LlamaUpdateJob {
 function parseStatus(value: unknown): LlamaUpdateStatus | null {
   if (!value || typeof value !== "object") return null;
   const s = value as Record<string, unknown>;
+  const component =
+    s.update_component === "whisper" ? "whisper.cpp" : "llama.cpp";
+  const whisper =
+    s.whisper && typeof s.whisper === "object"
+      ? (s.whisper as Record<string, unknown>)
+      : null;
+  // Legacy top-level version fields intentionally retain their llama meaning.
+  // A whisper-only update must display the nested whisper release instead of
+  // presenting equal llama tags as a new llama update.
+  const details = component === "whisper.cpp" && whisper ? whisper : s;
   return {
     supported: s.supported === true,
     update_available: s.update_available === true,
-    installed_tag: typeof s.installed_tag === "string" ? s.installed_tag : null,
-    latest_tag: typeof s.latest_tag === "string" ? s.latest_tag : null,
+    component,
+    installed_tag:
+      typeof details.installed_tag === "string"
+        ? details.installed_tag
+        : null,
+    latest_tag:
+      typeof details.latest_tag === "string" ? details.latest_tag : null,
     update_size_bytes:
-      typeof s.update_size_bytes === "number" ? s.update_size_bytes : null,
+      typeof details.update_size_bytes === "number"
+        ? details.update_size_bytes
+        : null,
     job: parseJob(s.job),
   };
 }
@@ -163,8 +181,12 @@ export function useLlamaUpdateCheck({
   // can drop or double-fire the notification.
   const notifyReloadIfNeeded = useCallback(
     (job: Pick<LlamaUpdateJob, "state" | "reload_required" | "finished_at">) => {
+      // "error" is included for partial chained updates: the llama phase can
+      // land (and unload the server) before a later phase fails, and the
+      // backend keeps reload_required set in exactly that case. Without the
+      // resync the chat UI would keep pointing at the unloaded model.
       if (
-        job.state === "success" &&
+        (job.state === "success" || job.state === "error") &&
         job.reload_required &&
         job.finished_at !== reloadNotifiedForRef.current
       ) {
@@ -202,7 +224,9 @@ export function useLlamaUpdateCheck({
             reloadRequired: s.job.reload_required,
           });
         } else if (s.job.state === "error") {
-          // Keep the banner visible so retry is available.
+          // Keep the banner visible so retry is available. A partial chained
+          // update can still have unloaded the llama server before failing.
+          notifyReloadIfNeeded(s.job);
           onDone?.({ ok: false, error: s.job.error });
         } else {
           onDone?.({ ok: false, error: "update did not complete" });
diff --git a/studio/frontend/src/hooks/use-wheel-scroll-ref.ts b/studio/frontend/src/hooks/use-wheel-scroll-ref.ts
new file mode 100644
index 0000000000..09d0ea5a97
--- /dev/null
+++ b/studio/frontend/src/hooks/use-wheel-scroll-ref.ts
@@ -0,0 +1,43 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useCallback, useRef } from "react";
+
+/**
+ * Callback ref for scroll containers inside modal scroll locks. The lock may
+ * cancel native wheel scrolling, so apply the delta before it reaches the
+ * portaled dialog boundary.
+ */
+export function useWheelScrollRef<T extends HTMLElement>() {
+  const detachRef = useRef<(() => void) | null>(null);
+
+  return useCallback((node: T | null) => {
+    detachRef.current?.();
+    detachRef.current = null;
+    if (!node) {
+      return;
+    }
+
+    const onWheel = (event: WheelEvent) => {
+      if (event.ctrlKey || node.scrollHeight <= node.clientHeight) {
+        return;
+      }
+      const multiplier =
+        event.deltaMode === WheelEvent.DOM_DELTA_LINE
+          ? 16
+          : event.deltaMode === WheelEvent.DOM_DELTA_PAGE
+            ? node.clientHeight
+            : 1;
+      const delta = event.deltaY * multiplier;
+      if (delta === 0) {
+        return;
+      }
+      node.scrollTop += delta;
+      event.preventDefault();
+      event.stopPropagation();
+    };
+
+    node.addEventListener("wheel", onWheel, { passive: false });
+    detachRef.current = () => node.removeEventListener("wheel", onWheel);
+  }, []);
+}
diff --git a/studio/frontend/src/i18n/locales/ar.ts b/studio/frontend/src/i18n/locales/ar.ts
index 4bd4328cce..be641781df 100644
--- a/studio/frontend/src/i18n/locales/ar.ts
+++ b/studio/frontend/src/i18n/locales/ar.ts
@@ -39,7 +39,7 @@ export const ar = {
       returnToChat: "العودة إلى المحادثة",
       compare: "مقارنة",
       search: "بحث",
-      hub: "Hub",
+      hub: "النماذج",
       train: "تدريب",
       recipes: "الوصفات",
       export: "تصدير",
@@ -111,7 +111,7 @@ export const ar = {
         "يُستخدم لتحميل النماذج المقيّدة ورفع المخرجات.",
       hideToken: "إخفاء التوكن",
       showToken: "إظهار التوكن",
-      tokenSaved: "تم حفظ التوكن",
+      tokenValidated: "تم التحقق من الرمز",
       password: "كلمة المرور",
       passwordDescription: "تغيير كلمة المرور لحساب Unsloth هذا.",
       passwordDialog: {
diff --git a/studio/frontend/src/i18n/locales/de.ts b/studio/frontend/src/i18n/locales/de.ts
index c28d07790f..42df1d5cd3 100644
--- a/studio/frontend/src/i18n/locales/de.ts
+++ b/studio/frontend/src/i18n/locales/de.ts
@@ -39,7 +39,7 @@ export const de = {
       returnToChat: "Zurück zum Chat",
       compare: "Vergleichen",
       search: "Suchen",
-      hub: "Hub",
+      hub: "Modelle",
       train: "Trainieren",
       recipes: "Rezepte",
       export: "Exportieren",
@@ -112,7 +112,7 @@ export const de = {
         "Wird verwendet, um gated Modelle zu laden und Artefakte zu pushen.",
       hideToken: "Token verbergen",
       showToken: "Token anzeigen",
-      tokenSaved: "Token gespeichert",
+      tokenValidated: "Token validiert",
       password: "Passwort",
       passwordDescription:
         "Ändern Sie das Passwort für dieses Unsloth-Konto.",
diff --git a/studio/frontend/src/i18n/locales/en.ts b/studio/frontend/src/i18n/locales/en.ts
index 3e1c1e5a76..a0f9bfc1cd 100644
--- a/studio/frontend/src/i18n/locales/en.ts
+++ b/studio/frontend/src/i18n/locales/en.ts
@@ -32,11 +32,11 @@ export const en = {
       runOptions: "Run options",
     },
     navigation: {
-      newChat: "New Chat",
+      newChat: "New chat",
       returnToChat: "Return to Chat",
       compare: "Compare",
       search: "Search",
-      hub: "Hub",
+      hub: "Models",
       train: "Train",
       recipes: "Recipes",
       export: "Export",
@@ -105,9 +105,45 @@ export const en = {
     },
     voice: {
       title: "Voice",
-      description: "Microphone, dictation, and read-aloud",
+      description: "Microphone, dictation, speech-to-text and read-aloud",
       dictation: {
         sectionTitle: "Dictation",
+        engineLabel: "Dictation engine",
+        engineBrowser: "Browser",
+        engineBrowserDescription:
+          "Transcribes audio using your browser speech service. Select 'Local transcription' to use a STT model.",
+        engineModel: "Local transcription",
+        engineModelDescription:
+          "Runs a speech-to-text (STT) model locally and works offline. Download, load, then unloads after inactivity.",
+        sttModelLabel: "Speech recognition model",
+        sttModelDescription: "Choose or search a STT model to run locally.",
+        sttModelSearchPlaceholder: "Search model",
+        sttModelSearching: "Searching Hugging Face…",
+        sttModelValidating: "Checking Whisper compatibility…",
+        sttModelNoResults: "No Whisper models found",
+        sttModelInvalid: "This repository cannot be used for dictation",
+        sttModelFailed: "Could not load the STT model",
+        sttModelUnsupported: "Recording is not supported in this browser",
+        sttChecking: "Checking…",
+        sttOnDemand: "Downloaded",
+        sttLoadingModel: "Loading model…",
+        sttReady: "Loaded on {device}",
+        sttLoaded: "Loaded",
+        sttUnavailable:
+          "Not installed on this server. Run `unsloth studio update` to enable local dictation.",
+        sttRetry: "Retry",
+        sttDownloadChecking: "Checking download status…",
+        sttNotDownloaded: "Not downloaded",
+        sttDownloadStatusFailed: "Could not check download status",
+        sttDownload: "Download",
+        sttDownloading: "Downloading… {progress}%",
+        sttCancelDownload: "Cancel",
+        sttCancellingDownload: "Cancelling…",
+        sttDownloadComplete: "Speech recognition model downloaded",
+        sttDownloadFailed: "Could not download the speech recognition model",
+        sttLoad: "Load",
+        sttUnload: "Unload",
+        sttUnloading: "Unloading…",
         microphoneLabel: "Microphone",
         microphoneDescription: "Used for dictation",
         microphoneFallbackHint:
@@ -118,35 +154,58 @@ export const en = {
           "Microphone access was blocked. Allow microphone access for this Unsloth page, then try again.",
         micAccessUnsupported:
           "Microphone access is not supported in this browser or context.",
-        micOpenFailed:
-          "Could not open the selected microphone. Check permissions or pick another device.",
         systemDefault: "System default",
         savedMicDisconnected: "Saved microphone (not connected)",
         languageLabel: "Dictation language",
         languageDescription: "Language to recognize",
         languageAuto: "Auto (browser language)",
-        testLabel: "Test dictation",
-        testDescription: "Speak to check your mic and settings",
-        startTest: "Start test",
-        stopTest: "Stop test",
-        listening: "Listening…",
-        testSaved: "Saved to recent dictations",
-        notSupported: "Not supported in this browser",
       },
       dictionary: {
         sectionTitle: "Dictation dictionary",
-        sectionDescription:
-          "Apply the spelling entered here when dictation recognizes the same words or phrase",
+        sectionDescription: "Set how dictation spells specific words or phrases",
+        manageLabel: "Custom spellings",
+        manage: "Manage",
+        backToVoice: "Back to Voice",
         addEntry: "Add entry",
       },
       recents: {
-        sectionTitle: "Recent dictations",
+        sectionTitle: "Dictation history",
         sectionDescription:
-          "Your recent dictations will appear here so you can recover text",
+          "Every dictation is saved here so you can recover text",
+        manageLabel: "Dictation history",
+        manage: "Manage",
+        pageDescription:
+          "Every dictation is saved. View, copy, or delete them, or open the chat a dictation was used in.",
+        searchPlaceholder: "Search dictations",
+        sortLabel: "Sort dictations",
+        sortNewest: "Newest",
+        sortOldest: "Oldest",
+        sortAlpha: "A to Z",
+        noMatches: "No dictations match your search",
+        detailTitle: "Saved dictation",
+        backToVoice: "Back to Voice",
+        backToRecents: "Back to recent dictations",
+        view: "View full dictation",
         empty: "No dictations yet",
+        dictationColumn: "Dictation",
+        dateColumn: "Date created",
+        copy: "Copy dictation",
         copied: "Copied to clipboard",
         copyFailed: "Could not copy to clipboard",
-        clear: "Clear recent dictations",
+        delete: "Delete dictation",
+        deleteTitle: "Delete dictation",
+        deleteDescription:
+          "Delete this saved dictation? This cannot be undone.",
+        deleteLinkedDescription:
+          "Delete this saved dictation? You can also delete the chat it was used in. This cannot be undone.",
+        deleteWithChat: "Delete chat and dictation",
+        deleteWithChatFailed: "Could not delete the chat",
+        clear: "Clear history",
+        clearTitle: "Clear dictation history",
+        clearDescription: "Delete all saved dictations? This cannot be undone.",
+        clearConfirm: "Clear all",
+        showMore: "Show more ({count})",
+        openChat: "Open chat",
       },
       readAloud: {
         sectionTitle: "Read aloud",
@@ -182,7 +241,7 @@ export const en = {
         "Used to load gated models and push artifacts.",
       hideToken: "Hide token",
       showToken: "Show token",
-      tokenSaved: "Token saved",
+      tokenValidated: "Token validated",
       password: "Password",
       passwordDescription: "Change the password for this Unsloth account.",
       passwordDialog: {
@@ -196,6 +255,7 @@ export const en = {
         currentTooShort:
           "Current password must be at least {minLength} characters.",
         newTooShort: "New password must be at least {minLength} characters.",
+        newHasSpaces: "New password cannot contain spaces.",
         mismatch: "Passwords do not match.",
         samePassword:
           "New password must be different from your current password.",
@@ -490,10 +550,20 @@ export const en = {
         systemDisk: "System disk",
         diskUsage: "{used} used / {total}",
         diskFree: "{free} free",
-        modelsFolder: "Models folder",
-        modelsFolderDescription: "Where downloaded models are stored.",
+        modelsFolder: "Model downloads",
+        modelsFolderDescription: "Hugging Face cache used for model downloads.",
+        futureDownloads: "New downloads only",
+        environmentManaged: "Managed by the {variable} environment variable.",
+        locationFree: "{free} free",
         openAction: "Open",
         copyAction: "Copy path",
+        changeAction: "Change",
+        resetAction: "Use default",
+        chooseTitle: "Choose model download location",
+        chooseAction: "Use for future downloads",
+        cacheSaved: "Model download location updated",
+        cacheSaveError: "Couldn't update the model download location",
+        cachePickerError: "Couldn't open the folder picker",
         copied: "Path copied",
         openError: "Couldn't open the folder",
         copyError: "Couldn't copy the path",
@@ -981,6 +1051,8 @@ export const en = {
       optimizer: "Optimizer",
       optimizerTooltip:
         "Optimization algorithm. 8-bit variants reduce memory usage. Fused is recommended for vision models.",
+      optimizerTooltipMlx:
+        "Optimization algorithm. AdamW is the default. Lion uses less memory but usually needs a lower learning rate.",
       lrScheduler: "LR scheduler",
       lrSchedulerTooltip:
         "How the learning rate changes over training. Linear decays steadily; cosine decays in a curve.",
@@ -1053,7 +1125,8 @@ export const en = {
       continueAction: "Continue Training",
       cancelAction: "Cancel Training",
       stopTitle: "Stop Training",
-      stopDescription: "Choose how you want to stop the current training run.",
+      stopDescription:
+        "Choose how you want to stop the current training run. Stop and Save writes a checkpoint you can resume from later; Stop cannot be resumed.",
       stopAction: "Stop",
       stopping: "Stopping...",
       stopAndSave: "Stop and Save",
diff --git a/studio/frontend/src/i18n/locales/es.ts b/studio/frontend/src/i18n/locales/es.ts
index b7dfee10b8..dfbd98aca6 100644
--- a/studio/frontend/src/i18n/locales/es.ts
+++ b/studio/frontend/src/i18n/locales/es.ts
@@ -39,7 +39,7 @@ export const es = {
       returnToChat: "Volver al chat",
       compare: "Comparar",
       search: "Buscar",
-      hub: "Hub",
+      hub: "Modelos",
       train: "Entrenar",
       recipes: "Recetas",
       export: "Exportar",
@@ -112,7 +112,7 @@ export const es = {
         "Se usa para cargar modelos restringidos y subir artefactos.",
       hideToken: "Ocultar token",
       showToken: "Mostrar token",
-      tokenSaved: "Token guardado",
+      tokenValidated: "Token validado",
       password: "Contraseña",
       passwordDescription:
         "Cambia la contraseña de esta cuenta de Unsloth.",
diff --git a/studio/frontend/src/i18n/locales/fr.ts b/studio/frontend/src/i18n/locales/fr.ts
index 6105cd8ccf..59d01c7dae 100644
--- a/studio/frontend/src/i18n/locales/fr.ts
+++ b/studio/frontend/src/i18n/locales/fr.ts
@@ -39,7 +39,7 @@ export const fr = {
       returnToChat: "Retour à la discussion",
       compare: "Comparer",
       search: "Rechercher",
-      hub: "Hub",
+      hub: "Modèles",
       train: "Entraîner",
       recipes: "Recettes",
       export: "Exporter",
@@ -112,7 +112,7 @@ export const fr = {
         "Utilisé pour charger des modèles restreints et publier des artefacts.",
       hideToken: "Masquer le token",
       showToken: "Afficher le token",
-      tokenSaved: "Token enregistré",
+      tokenValidated: "Jeton validé",
       password: "Mot de passe",
       passwordDescription:
         "Changez le mot de passe de ce compte Unsloth.",
diff --git a/studio/frontend/src/i18n/locales/hi.ts b/studio/frontend/src/i18n/locales/hi.ts
index 732ae1d7fa..bb8cb70fea 100644
--- a/studio/frontend/src/i18n/locales/hi.ts
+++ b/studio/frontend/src/i18n/locales/hi.ts
@@ -39,7 +39,7 @@ export const hi = {
       returnToChat: "चैट पर लौटें",
       compare: "तुलना करें",
       search: "खोजें",
-      hub: "Hub",
+      hub: "मॉडल",
       train: "ट्रेनिंग",
       recipes: "रेसिपी",
       export: "एक्सपोर्ट",
@@ -111,7 +111,7 @@ export const hi = {
         "गेटेड मॉडल लोड करने और आर्टिफैक्ट पुश करने के लिए उपयोग किया जाता है।",
       hideToken: "token छिपाएं",
       showToken: "token दिखाएं",
-      tokenSaved: "Token सहेजा गया",
+      tokenValidated: "Token सत्यापित",
       password: "पासवर्ड",
       passwordDescription: "इस Unsloth खाते के लिए पासवर्ड बदलें।",
       passwordDialog: {
diff --git a/studio/frontend/src/i18n/locales/ja.ts b/studio/frontend/src/i18n/locales/ja.ts
index de5e93c672..c0a8c62734 100644
--- a/studio/frontend/src/i18n/locales/ja.ts
+++ b/studio/frontend/src/i18n/locales/ja.ts
@@ -40,7 +40,7 @@ export const ja = {
       returnToChat: "チャットに戻る",
       compare: "比較",
       search: "検索",
-      hub: "ハブ",
+      hub: "モデル",
       train: "トレーニング",
       recipes: "レシピ",
       export: "エクスポート",
@@ -114,7 +114,7 @@ export const ja = {
       huggingFaceTokenDescription: "ゲート付きモデルの読み込みや、アーティファクトのプッシュに使用されます。",
       hideToken: "トークンを非表示",
       showToken: "トークンを表示",
-      tokenSaved: "トークンを保存しました",
+      tokenValidated: "トークンは検証済みです",
       password: "パスワード",
       passwordDescription: "この Unsloth アカウントのパスワードを変更します。",
       passwordDialog: {
diff --git a/studio/frontend/src/i18n/locales/ko.ts b/studio/frontend/src/i18n/locales/ko.ts
index 6ff9cdbb5e..16e27b50cd 100644
--- a/studio/frontend/src/i18n/locales/ko.ts
+++ b/studio/frontend/src/i18n/locales/ko.ts
@@ -39,7 +39,7 @@ export const ko = {
       returnToChat: "채팅으로 돌아가기",
       compare: "비교",
       search: "검색",
-      hub: "Hub",
+      hub: "모델",
       train: "학습",
       recipes: "레시피",
       export: "내보내기",
@@ -111,7 +111,7 @@ export const ko = {
         "게이트된 모델을 불러오고 아티팩트를 푸시하는 데 사용됩니다.",
       hideToken: "토큰 숨기기",
       showToken: "토큰 표시",
-      tokenSaved: "토큰이 저장되었습니다",
+      tokenValidated: "토큰이 확인되었습니다",
       password: "비밀번호",
       passwordDescription: "이 Unsloth 계정의 비밀번호를 변경합니다.",
       passwordDialog: {
diff --git a/studio/frontend/src/i18n/locales/pt-br.ts b/studio/frontend/src/i18n/locales/pt-br.ts
index e6d2347c10..b46aea6321 100644
--- a/studio/frontend/src/i18n/locales/pt-br.ts
+++ b/studio/frontend/src/i18n/locales/pt-br.ts
@@ -39,7 +39,7 @@ export const ptBR = {
       returnToChat: "Retornar ao Chat",
       compare: "Comparar",
       search: "Buscar",
-      hub: "Hub",
+      hub: "Modelos",
       train: "Treinar",
       recipes: "Receitas",
       export: "Exportar",
@@ -112,7 +112,7 @@ export const ptBR = {
       huggingFaceToken: "Token do Hugging Face",
       huggingFaceTokenDescription:
         "Usado para carregar modelos restritos e enviar artefatos.",
-      tokenSaved: "Token salvo",
+      tokenValidated: "Token validado",
       hideToken: "Ocultar token",
       showToken: "Mostrar token",
       password: "Senha",
diff --git a/studio/frontend/src/i18n/locales/ru.ts b/studio/frontend/src/i18n/locales/ru.ts
index 60e939bb0d..1c0ac6f95e 100644
--- a/studio/frontend/src/i18n/locales/ru.ts
+++ b/studio/frontend/src/i18n/locales/ru.ts
@@ -39,7 +39,7 @@ export const ru = {
       returnToChat: "Вернуться к чату",
       compare: "Сравнить",
       search: "Поиск",
-      hub: "Hub",
+      hub: "Модели",
       train: "Обучение",
       recipes: "Рецепты",
       export: "Экспорт",
@@ -111,7 +111,7 @@ export const ru = {
         "Используется для загрузки закрытых моделей и публикации артефактов.",
       hideToken: "Скрыть токен",
       showToken: "Показать токен",
-      tokenSaved: "Токен сохранён",
+      tokenValidated: "Токен проверен",
       password: "Пароль",
       passwordDescription: "Изменить пароль для этого аккаунта Unsloth.",
       passwordDialog: {
diff --git a/studio/frontend/src/i18n/locales/zh-CN.ts b/studio/frontend/src/i18n/locales/zh-CN.ts
index 37c73086cf..eb962cc8d4 100644
--- a/studio/frontend/src/i18n/locales/zh-CN.ts
+++ b/studio/frontend/src/i18n/locales/zh-CN.ts
@@ -39,7 +39,7 @@ export const zhCN = {
       returnToChat: "返回聊天",
       compare: "对比",
       search: "搜索",
-      hub: "Hub",
+      hub: "模型",
       train: "训练",
       recipes: "配方",
       export: "导出",
@@ -113,7 +113,7 @@ export const zhCN = {
       huggingFaceTokenDescription: "用于加载受限模型和推送产物。",
       hideToken: "隐藏 token",
       showToken: "显示 token",
-      tokenSaved: "Token 已保存",
+      tokenValidated: "Token 已验证",
       password: "密码",
       passwordDescription: "更改此 Unsloth 账号的密码。",
       passwordDialog: {
@@ -901,7 +901,8 @@ export const zhCN = {
       continueAction: "继续训练",
       cancelAction: "取消训练",
       stopTitle: "停止训练",
-      stopDescription: "选择如何停止当前训练运行。",
+      stopDescription:
+        "选择如何停止当前训练运行。“停止并保存”会写入检查点，之后可从该处恢复；“停止”则无法恢复。",
       stopAction: "停止",
       stopping: "停止中...",
       stopAndSave: "停止并保存",
diff --git a/studio/frontend/src/index.css b/studio/frontend/src/index.css
index b06dc03fba..0cba3407fe 100644
--- a/studio/frontend/src/index.css
+++ b/studio/frontend/src/index.css
@@ -633,6 +633,22 @@ html.no-font-smoothing body {
 	-moz-osx-font-smoothing: auto;
 }
 
+/* Match Inter's lighter macOS rendering. Dark surfaces need a stronger
+   correction than light surfaces. Keep 410 when smoothing is off or a custom
+   font reaches chat. */
+html.render-linux:not(.no-font-smoothing):not([data-chat-font]):not([data-ui-font])
+	:is(.aui-assistant-message-root, .aui-user-message-root) {
+	font-weight: 390;
+}
+
+html.dark.render-linux:not(.no-font-smoothing):not([data-chat-font]):not([data-ui-font])
+	:is(.aui-assistant-message-root, .aui-user-message-root) {
+	font-weight: 350;
+	/* The lighter variable-font instance has narrower advances. Reduce
+	   dark-mode line-wrap drift without changing custom-font paths. */
+	letter-spacing: 0.023em;
+}
+
 /* Chat font: only applies while a custom chat font is set. Elements with
    explicit font utilities (headings, code) keep their own families. */
 html[data-chat-font] .aui-root {
@@ -669,6 +685,59 @@ html[data-chat-font] .aui-root {
 }
 
 @theme inline {
+	/* UI typography scale (Settings > Appearance). Every token multiplies
+	   its default size by --ui-font-scale, so text follows the preference
+	   while rem-based layout stays put. Identity at the 16px default. */
+	--text-xs: calc(0.75rem * var(--ui-font-scale, 1));
+	--text-sm: calc(0.875rem * var(--ui-font-scale, 1));
+	--text-base: calc(1rem * var(--ui-font-scale, 1));
+	--text-lg: calc(1.125rem * var(--ui-font-scale, 1));
+	--text-xl: calc(1.25rem * var(--ui-font-scale, 1));
+	--text-2xl: calc(1.5rem * var(--ui-font-scale, 1));
+	--text-3xl: calc(1.875rem * var(--ui-font-scale, 1));
+	--text-4xl: calc(2.25rem * var(--ui-font-scale, 1));
+	/* Arbitrary px sizes from the design, one token per size. */
+	--text-ui-8: calc(0.5rem * var(--ui-font-scale, 1));
+	--text-ui-9: calc(0.5625rem * var(--ui-font-scale, 1));
+	--text-ui-10: calc(0.625rem * var(--ui-font-scale, 1));
+	--text-ui-10p5: calc(0.65625rem * var(--ui-font-scale, 1));
+	--text-ui-11: calc(0.6875rem * var(--ui-font-scale, 1));
+	--text-ui-11p5: calc(0.71875rem * var(--ui-font-scale, 1));
+	--text-ui-12: calc(0.75rem * var(--ui-font-scale, 1));
+	--text-ui-12p5: calc(0.78125rem * var(--ui-font-scale, 1));
+	--text-ui-13: calc(0.8125rem * var(--ui-font-scale, 1));
+	--text-ui-13p5: calc(0.84375rem * var(--ui-font-scale, 1));
+	--text-ui-14: calc(0.875rem * var(--ui-font-scale, 1));
+	--text-ui-14p5: calc(0.90625rem * var(--ui-font-scale, 1));
+	--text-ui-15: calc(0.9375rem * var(--ui-font-scale, 1));
+	--text-ui-15p5: calc(0.96875rem * var(--ui-font-scale, 1));
+	--text-ui-16: calc(1rem * var(--ui-font-scale, 1));
+	--text-ui-17: calc(1.0625rem * var(--ui-font-scale, 1));
+	--text-ui-18: calc(1.125rem * var(--ui-font-scale, 1));
+	--text-ui-19: calc(1.1875rem * var(--ui-font-scale, 1));
+	--text-ui-21: calc(1.3125rem * var(--ui-font-scale, 1));
+	--text-ui-25: calc(1.5625rem * var(--ui-font-scale, 1));
+	--text-ui-30: calc(1.875rem * var(--ui-font-scale, 1));
+	--text-ui-34: calc(2.125rem * var(--ui-font-scale, 1));
+	/* Exact line-heights paired with the sizes above. */
+	--leading-ui-14: calc(0.875rem * var(--ui-font-scale, 1));
+	--leading-ui-15: calc(0.9375rem * var(--ui-font-scale, 1));
+	--leading-ui-16: calc(1rem * var(--ui-font-scale, 1));
+	--leading-ui-17: calc(1.0625rem * var(--ui-font-scale, 1));
+	--leading-ui-18: calc(1.125rem * var(--ui-font-scale, 1));
+	--leading-ui-19: calc(1.1875rem * var(--ui-font-scale, 1));
+	--leading-ui-24: calc(1.5rem * var(--ui-font-scale, 1));
+	--leading-ui-31: calc(1.9375rem * var(--ui-font-scale, 1));
+	/* Numeric leading is typographic: scale it too (it would
+	   otherwise pin through --spacing). Same values at 16px. */
+	--leading-3: calc(0.75rem * var(--ui-font-scale, 1));
+	--leading-4: calc(1rem * var(--ui-font-scale, 1));
+	--leading-5: calc(1.25rem * var(--ui-font-scale, 1));
+	--leading-6: calc(1.5rem * var(--ui-font-scale, 1));
+	--leading-7: calc(1.75rem * var(--ui-font-scale, 1));
+	--leading-8: calc(2rem * var(--ui-font-scale, 1));
+	--leading-9: calc(2.25rem * var(--ui-font-scale, 1));
+	--leading-10: calc(2.5rem * var(--ui-font-scale, 1));
 	/* Reference the :root tokens instead of literal stacks so the runtime
 	   font overrides (Settings > Appearance) reach every font-* utility. */
 	--font-sans: var(--font-sans);
@@ -980,7 +1049,7 @@ html[data-chat-font] .aui-root {
 	}
 
 	.sidebar-sticky-label {
-		@apply rounded-none bg-sidebar pt-0 pb-[8px] pl-[16px] pr-4 text-[14px]! leading-[17px] font-medium normal-case focus-visible:ring-0! focus-visible:outline-none transition-shadow duration-150;
+		@apply rounded-none bg-sidebar pt-0 pb-[8px] pl-[16px] pr-4 text-ui-14! leading-ui-17 font-medium normal-case focus-visible:ring-0! focus-visible:outline-none transition-shadow duration-150;
 		/* Muted section-header gray, matching Gemini's "Notebooks"/"Recents".
 		   Lightened from #5f6368 so the label reads as a header, clearly
 		   lighter than the near-black nav items. */
@@ -1119,7 +1188,7 @@ html[data-chat-font] .aui-root {
 	   fade-in, just enough to read as interactive without competing
 	   with the slider row's quiet aesthetic. */
 	.panel-number-input {
-		@apply h-7 min-w-8 shrink-0 rounded-full border-0 bg-transparent px-2 text-right text-[13px]! font-medium tabular-nums text-nav-fg shadow-none transition-colors hover:bg-black/[0.04] focus:bg-black/[0.05] focus-visible:ring-0! focus-visible:outline-none md:text-[13px]!;
+		@apply h-7 min-w-8 shrink-0 rounded-full border-0 bg-transparent px-2 text-right text-ui-13! font-medium tabular-nums text-nav-fg shadow-none transition-colors hover:bg-black/[0.04] focus:bg-black/[0.05] focus-visible:ring-0! focus-visible:outline-none md:text-ui-13!;
 	}
 	.dark .panel-number-input {
 		@apply hover:bg-white/[0.04] focus:bg-white/[0.06];
@@ -1142,7 +1211,7 @@ html[data-chat-font] .aui-root {
 	}
 
 	.tooltip-compact {
-		@apply rounded-[11px] border-transparent bg-black px-2.5 py-1.5 text-[11px] font-medium leading-snug text-white shadow-md;
+		@apply rounded-[11px] border-transparent bg-black px-2.5 py-1.5 text-ui-11 font-medium leading-snug text-white shadow-md;
 	}
 
 	/* Dialog popups: borderless; chatbox shadow in light, flat card
@@ -1179,8 +1248,8 @@ html[data-chat-font] .aui-root {
 		gap: 9.5px !important;
 		border-radius: 12px;
 		font-weight: 500;
-		font-size: 15px;
-		line-height: 20px;
+		font-size: calc(0.9375rem * var(--ui-font-scale, 1));
+		line-height: calc(1.25rem * var(--ui-font-scale, 1));
 		letter-spacing: 0;
 		color: var(--nav-fg);
 	}
@@ -1424,7 +1493,7 @@ html[data-chat-font] .aui-root {
 	}
 
 	.composer-pill-btn {
-		@apply flex cursor-pointer items-center gap-1.5 rounded-full py-1.5 pl-2 pr-2.5 text-[14px] font-medium text-muted-foreground/70 transition-colors hover:bg-primary/10 dark:hover:bg-white/[0.1] disabled:cursor-not-allowed disabled:opacity-40;
+		@apply flex cursor-pointer items-center gap-1.5 rounded-full py-1.5 pl-2 pr-2.5 text-ui-14 font-medium text-muted-foreground/70 transition-colors hover:bg-primary/10 dark:hover:bg-white/[0.1] disabled:cursor-not-allowed disabled:opacity-40;
 	}
 
 	/* Caret pills (RAG, MCP): the chevron carries its own whitespace, so the
@@ -1512,7 +1581,7 @@ html[data-chat-font] .aui-root {
 		.composer-pill-btn:not([data-keep-label])[data-pill-label]:hover::after {
 		content: attr(data-pill-label);
 		/* Always one nowrap line, so always a full pill. */
-		@apply pointer-events-none absolute bottom-[calc(100%+6px)] left-1/2 z-50 -translate-x-1/2 rounded-full bg-black px-2.5 py-1.5 text-[11px] font-medium leading-snug whitespace-nowrap text-white shadow-md;
+		@apply pointer-events-none absolute bottom-[calc(100%+6px)] left-1/2 z-50 -translate-x-1/2 rounded-full bg-black px-2.5 py-1.5 text-ui-11 font-medium leading-snug whitespace-nowrap text-white shadow-md;
 	}
 
 	/* Compact caret pills (RAG, MCP) open their menu on click instead of
@@ -1565,7 +1634,7 @@ html[data-chat-font] .aui-root {
 	}
 
 	.composer-footer-note {
-		@apply mt-1.5 text-center text-[11px] tracking-[0em] text-muted-foreground;
+		@apply mt-1.5 text-center text-ui-11 tracking-[0em] text-muted-foreground;
 		font-family: var(--font-sans);
 	}
 
@@ -1605,8 +1674,14 @@ html[data-chat-font] .aui-root {
 		@apply flex w-full flex-wrap items-center gap-0.5 px-1;
 	}
 
+	/* Recording is a dedicated one-line mode. Active tool pills must not force
+	   the composer back into the normal two-row layout. */
+	.unsloth-composer-line[data-dictating="true"] {
+		@apply flex-nowrap;
+	}
+
 	.unsloth-composer-left {
-		@apply flex shrink-0 items-center gap-0.5;
+		@apply flex min-w-0 flex-wrap items-center gap-0.5;
 		order: 1;
 		/* Pull the plus button closer to the composer edge. */
 		margin-left: -0.25rem;
@@ -1652,7 +1727,7 @@ html[data-chat-font] .aui-root {
 	}
 
 	.unsloth-composer-input {
-		@apply min-h-[40px] min-w-0 flex-1 resize-none overflow-y-auto bg-transparent pl-0.5 pr-2 py-2 text-[15px] font-[450] leading-6 outline-none placeholder:text-muted-foreground focus-visible:ring-0;
+		@apply min-h-[40px] min-w-0 flex-1 resize-none overflow-y-auto bg-transparent pl-0.5 pr-2 py-2 text-ui-15 font-[450] leading-6 outline-none placeholder:text-muted-foreground focus-visible:ring-0;
 	}
 
 	.unsloth-composer-plus {
@@ -1731,7 +1806,7 @@ html[data-chat-font] .aui-root {
 	/* Right-side Thinking pill (toggle or dropdown). pl-2 matches the left
 	   pills so the hover X is not pushed in too far. */
 	.unsloth-thinking-pill {
-		@apply inline-flex shrink-0 cursor-pointer items-center gap-1 rounded-full py-1.5 pl-2 pr-2.5 text-[14px] font-medium text-muted-foreground transition-colors hover:bg-primary/10 dark:hover:bg-white/[0.1] disabled:cursor-not-allowed disabled:opacity-40;
+		@apply inline-flex shrink-0 cursor-pointer items-center gap-1 rounded-full py-1.5 pl-2 pr-2.5 text-ui-14 font-medium text-muted-foreground transition-colors hover:bg-primary/10 dark:hover:bg-white/[0.1] disabled:cursor-not-allowed disabled:opacity-40;
 		/* Reserve a text line so the icon-only (inactive) pill matches the
 		   text pills' height instead of collapsing to the icon. */
 		min-height: calc(1lh + 0.75rem);
@@ -1766,7 +1841,7 @@ html[data-chat-font] .aui-root {
 
 		.unsloth-thinking-pill[data-pill-label]:not([data-state="open"]):hover::after {
 			content: attr(data-pill-label);
-			@apply pointer-events-none absolute bottom-[calc(100%+6px)] left-1/2 z-50 -translate-x-1/2 rounded-full bg-black px-2.5 py-1.5 text-[11px] font-medium leading-snug whitespace-nowrap text-white shadow-md;
+			@apply pointer-events-none absolute bottom-[calc(100%+6px)] left-1/2 z-50 -translate-x-1/2 rounded-full bg-black px-2.5 py-1.5 text-ui-11 font-medium leading-snug whitespace-nowrap text-white shadow-md;
 		}
 	}
 
@@ -1811,7 +1886,7 @@ html[data-chat-font] .aui-root {
 			[data-slot="dropdown-menu-item"],
 			[data-slot="dropdown-menu-sub-trigger"]
 		) {
-		@apply gap-3 pl-3 pr-3 py-2 text-[14px];
+		@apply gap-3 pl-3 pr-3 py-2 text-ui-14;
 		cursor: pointer;
 		/* Pin hover-box radius so dark matches light (container radius minus the
 		   side gutter keeps the curves concentric). */
@@ -1819,7 +1894,7 @@ html[data-chat-font] .aui-root {
 	}
 
 	.unsloth-plus-menu [data-slot="dropdown-menu-label"] {
-		@apply pl-3 pr-3 py-1.5 text-[12px];
+		@apply pl-3 pr-3 py-1.5 text-ui-12;
 	}
 
 	/* Active (green) items keep their primary text and icon color on hover. */
@@ -2109,21 +2184,21 @@ html[data-chat-font] .aui-root {
 
 	/* Chat thread: code slightly smaller by default; step up when the thread column is wide. */
 	.aui-thread-root [data-streamdown="code-block"] {
-		font-size: 0.8125rem;
+		font-size: calc(0.8125rem * var(--ui-font-scale, 1));
 		line-height: 1.55;
 	}
 
 	.aui-thread-root [data-streamdown="code-block-header"] {
-		font-size: 0.6875rem;
+		font-size: calc(0.6875rem * var(--ui-font-scale, 1));
 	}
 
 	@container (min-width: 36rem) {
 		.aui-thread-root [data-streamdown="code-block"] {
-			font-size: 0.875rem;
+			font-size: calc(0.875rem * var(--ui-font-scale, 1));
 		}
 
 		.aui-thread-root [data-streamdown="code-block-header"] {
-			font-size: 0.75rem;
+			font-size: calc(0.75rem * var(--ui-font-scale, 1));
 		}
 	}
 
@@ -2655,3 +2730,37 @@ html[data-chat-font] .aui-root {
 .aui-tool-group-root .aui-tool-fallback-trigger:focus-visible .aui-tool-fallback-trigger-chevron {
   opacity: 1;
 }
+
+/* Third-party UI text follows the typography scale. Values equal the
+   library defaults at the 16px setting. KaTeX's internal font-size:1px
+   sizing trick is layout, not text, and stays untouched. */
+.before\:text-\[13px\]::before {
+	/* streamdown citation chip utility (class scanned from node_modules). */
+	font-size: calc(0.8125rem * var(--ui-font-scale, 1));
+}
+.recharts-text {
+	/* Chart axis/label text; beats the fontSize presentation attribute. */
+	font-size: calc(0.625rem * var(--ui-font-scale, 1));
+}
+.react-flow__edge-text.react-flow__edge-text {
+	/* Doubled class: react-flow's stylesheet loads after this file, so win
+	   on specificity, not order. */
+	font-size: calc(0.625rem * var(--ui-font-scale, 1));
+}
+.react-flow__attribution.react-flow__attribution {
+	font-size: calc(0.625rem * var(--ui-font-scale, 1));
+}
+.react-flow__node-input.react-flow__node-input,
+.react-flow__node-default.react-flow__node-default,
+.react-flow__node-output.react-flow__node-output,
+.react-flow__node-group.react-flow__node-group {
+	font-size: calc(0.75rem * var(--ui-font-scale, 1));
+}
+
+/* Radix hides the select viewport scrollbar (the viewport is the scroller
+   so menu corners stay rounded); restore the app's thin one. The inline
+   scrollbar-width on the viewport handles Firefox. */
+[data-slot="select-content"] [data-radix-select-viewport]::-webkit-scrollbar {
+	display: block !important;
+	width: 8px;
+}
diff --git a/studio/frontend/src/lib/native-files.ts b/studio/frontend/src/lib/native-files.ts
new file mode 100644
index 0000000000..48a6bd4ab7
--- /dev/null
+++ b/studio/frontend/src/lib/native-files.ts
@@ -0,0 +1,86 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { isTauri } from "@/lib/api-base";
+
+const NATIVE_FILE_NAME_HEADER = "x-unsloth-default-name";
+export class DownloadCancelledError extends Error {
+  constructor() {
+    super("Save cancelled.");
+    this.name = "DownloadCancelledError";
+  }
+}
+
+export function isDownloadCancelled(error: unknown): boolean {
+  return error instanceof DownloadCancelledError;
+}
+
+function encodeNativeFilename(filename: string): string {
+  const bytes = new TextEncoder().encode(filename);
+  let binary = "";
+  for (const byte of bytes) {
+    binary += String.fromCharCode(byte);
+  }
+  return btoa(binary);
+}
+
+export interface NativeChatImport {
+  name: string;
+  content: string;
+}
+
+function browserDownload(blob: Blob, filename: string): void {
+  const url = URL.createObjectURL(blob);
+  const anchor = document.createElement("a");
+  anchor.href = url;
+  anchor.download = filename;
+  document.body.appendChild(anchor);
+  anchor.click();
+  anchor.remove();
+  URL.revokeObjectURL(url);
+}
+
+/** Save through a native chooser in Tauri and retain normal downloads on web. */
+export async function downloadFile(
+  content: string | Blob | Uint8Array,
+  filename: string,
+  mimeType = "application/octet-stream",
+): Promise<void> {
+  if (isTauri) {
+    const { invoke } = await import("@tauri-apps/api/core");
+    const bytes =
+      typeof content === "string"
+        ? new TextEncoder().encode(content)
+        : content instanceof Blob
+          ? new Uint8Array(await content.arrayBuffer())
+          : content;
+    const savedPath = await invoke<string | null>("save_native_file", bytes, {
+      headers: {
+        [NATIVE_FILE_NAME_HEADER]: encodeNativeFilename(filename),
+      },
+    });
+    if (savedPath === null) {
+      throw new DownloadCancelledError();
+    }
+    return;
+  }
+
+  const browserContent =
+    content instanceof Uint8Array ? Uint8Array.from(content).buffer : content;
+  const blob =
+    browserContent instanceof Blob
+      ? browserContent
+      : new Blob([browserContent], { type: mimeType });
+
+  browserDownload(blob, filename);
+  return;
+}
+
+/** Open the bounded native chat-import picker. Cancellation returns null. */
+export async function pickNativeChatImport(): Promise<NativeChatImport | null> {
+  if (!isTauri) {
+    return null;
+  }
+  const { invoke } = await import("@tauri-apps/api/core");
+  return invoke<NativeChatImport | null>("pick_native_chat_import");
+}
diff --git a/studio/frontend/src/main.tsx b/studio/frontend/src/main.tsx
index d0ddf2fc6e..e3b2bceccf 100644
--- a/studio/frontend/src/main.tsx
+++ b/studio/frontend/src/main.tsx
@@ -36,6 +36,13 @@ if (!rootElement) {
 
 initializeLocale();
 
+// Rasterization follows the browser OS, not the potentially remote server.
+// This adjustment is calibrated for desktop Linux, so exclude Android.
+const uaLower = navigator.userAgent.toLowerCase();
+if (uaLower.includes("linux") && !uaLower.includes("android")) {
+  document.documentElement.classList.add("render-linux");
+}
+
 createRoot(rootElement).render(
   <StrictMode>
     <App />
diff --git a/studio/install_llama_prebuilt.py b/studio/install_llama_prebuilt.py
index b8182a534b..6026962478 100644
--- a/studio/install_llama_prebuilt.py
+++ b/studio/install_llama_prebuilt.py
@@ -43,6 +43,21 @@ except ImportError:
 from pathlib import Path
 from typing import Any, Iterable, Iterator
 
+# Shared component-agnostic machinery lives in prebuilt_core (same directory);
+# put studio/ on sys.path so it resolves whether this file is run as a script
+# (from any cwd) or loaded via an importlib spec by the tests.
+_STUDIO_DIR = os.path.dirname(os.path.abspath(__file__))
+if _STUDIO_DIR not in sys.path:
+    sys.path.insert(0, _STUDIO_DIR)
+
+import prebuilt_core as _core  # noqa: E402
+
+# Late-binding seam: core functions resolve collaborators (download_file,
+# fetch_json, ...) through this module's globals at call time, so tests that
+# monkeypatch names on this module keep working.
+_OPS = _core.ModuleOps(globals())
+USER_AGENT = "unsloth-studio-llama-prebuilt"
+
 
 EXIT_SUCCESS = 0
 EXIT_FALLBACK = 2
@@ -121,26 +136,7 @@ def _amd_smi_allowed() -> bool:
     return False
 
 
-def windows_hidden_subprocess_kwargs() -> dict[str, object]:
-    """Return Windows-only subprocess kwargs that suppress console windows."""
-    if sys.platform != "win32":
-        return {}
-
-    kwargs: dict[str, object] = {}
-    create_no_window = getattr(subprocess, "CREATE_NO_WINDOW", 0)
-    if create_no_window:
-        kwargs["creationflags"] = create_no_window
-
-    startupinfo_factory = getattr(subprocess, "STARTUPINFO", None)
-    startf_use_showwindow = getattr(subprocess, "STARTF_USESHOWWINDOW", 0)
-    sw_hide = getattr(subprocess, "SW_HIDE", 0)
-    if startupinfo_factory is not None and startf_use_showwindow:
-        startupinfo = startupinfo_factory()
-        startupinfo.dwFlags |= startf_use_showwindow
-        startupinfo.wShowWindow = sw_hide
-        kwargs["startupinfo"] = startupinfo
-
-    return kwargs
+windows_hidden_subprocess_kwargs = _core.windows_hidden_subprocess_kwargs
 
 
 def env_int(
@@ -347,10 +343,7 @@ class LinuxCudaSelection:
         return self.attempts[0]
 
 
-@dataclass
-class CudaRuntimePreference:
-    runtime_line: str | None
-    selection_log: list[str]
+CudaRuntimePreference = _core.CudaRuntimePreference
 
 
 @dataclass(frozen = True)
@@ -404,12 +397,8 @@ class InstallReleasePlan:
     approved_checksums: ApprovedReleaseChecksums
 
 
-class PrebuiltFallback(RuntimeError):
-    pass
-
-
-class BusyInstallConflict(RuntimeError):
-    pass
+PrebuiltFallback = _core.PrebuiltFallback
+BusyInstallConflict = _core.BusyInstallConflict
 
 
 class ExistingInstallSatisfied(RuntimeError):
@@ -419,51 +408,8 @@ class ExistingInstallSatisfied(RuntimeError):
         self.used_fallback = used_fallback
 
 
-def _os_error_messages(exc: BaseException) -> list[str]:
-    messages: list[str] = []
-    if isinstance(exc, OSError):
-        for value in (
-            getattr(exc, "strerror", None),
-            getattr(exc, "filename", None),
-            getattr(exc, "filename2", None),
-        ):
-            if isinstance(value, str) and value:
-                messages.append(value)
-    text = str(exc)
-    if text:
-        messages.append(text)
-    return [message.lower() for message in messages if message]
-
-
-def is_busy_lock_error(exc: BaseException) -> bool:
-    if isinstance(exc, BusyInstallConflict):
-        return True
-    if isinstance(exc, OSError):
-        if exc.errno in {
-            errno.EACCES,
-            errno.EBUSY,
-            errno.EPERM,
-            errno.ETXTBSY,
-        }:
-            return True
-        if getattr(exc, "winerror", None) in {5, 32, 145}:
-            return True
-    for message in _os_error_messages(exc):
-        if any(
-            needle in message
-            for needle in (
-                "access is denied",
-                "being used by another process",
-                "device or resource busy",
-                "permission denied",
-                "text file busy",
-                "file is in use",
-                "process cannot access the file",
-                "cannot create a file when that file already exists",
-            )
-        ):
-            return True
-    return False
+_os_error_messages = _core._os_error_messages
+is_busy_lock_error = _core.is_busy_lock_error
 
 
 # Status logs default to stderr so resolver modes keep stdout machine-readable
@@ -481,153 +427,30 @@ def log_lines(lines: Iterable[str]) -> None:
         log(line)
 
 
-def parsed_hostname(url: str | None) -> str | None:
-    if not url:
-        return None
-    try:
-        hostname = urllib.parse.urlparse(url).hostname
-    except Exception:
-        return None
-    if not hostname:
-        return None
-    return hostname.lower()
-
-
-def should_send_github_auth(url: str | None) -> bool:
-    return parsed_hostname(url) in GITHUB_AUTH_HOSTS
-
-
-def should_send_hf_auth(url: str | None) -> bool:
-    return parsed_hostname(url) in HF_AUTH_HOSTS
+parsed_hostname = _core.parsed_hostname
+should_send_github_auth = _core.should_send_github_auth
+should_send_hf_auth = _core.should_send_hf_auth
 
 
 def auth_headers(url: str | None = None) -> dict[str, str]:
-    headers = {
-        "User-Agent": "unsloth-studio-llama-prebuilt",
-    }
-    token = os.environ.get("GH_TOKEN") or os.environ.get("GITHUB_TOKEN")
-    if token and should_send_github_auth(url):
-        headers["Authorization"] = f"Bearer {token}"
-        return headers
-    # Anonymous huggingface.co fetches share a per-IP rate limit that CI
-    # fleets exhaust (HTTP 429), sinking the prebuilt path into a source
-    # build. Authenticate when a token is available.
-    hf_token = os.environ.get("HF_TOKEN") or os.environ.get("HUGGING_FACE_HUB_TOKEN")
-    if hf_token and should_send_hf_auth(url):
-        headers["Authorization"] = f"Bearer {hf_token}"
-    return headers
+    return _core.auth_headers(_OPS, url)
 
 
-class _CrossHostAuthStrippingRedirectHandler(urllib.request.HTTPRedirectHandler):
-    """Drop Authorization when a redirect leaves the original host.
-
-    huggingface.co redirects file downloads to CDN hosts whose signed URLs
-    can reject foreign Authorization headers; urllib forwards headers to
-    redirect targets by default (requests/huggingface_hub strip them).
-    """
-
-    def redirect_request(self, req, fp, code, msg, headers, newurl):
-        new_request = super().redirect_request(req, fp, code, msg, headers, newurl)
-        if new_request is not None and parsed_hostname(newurl) != parsed_hostname(req.full_url):
-            new_request.headers.pop("Authorization", None)
-            new_request.unredirected_hdrs.pop("Authorization", None)
-        return new_request
-
-
-_URL_OPENER = urllib.request.build_opener(_CrossHostAuthStrippingRedirectHandler())
+_CrossHostAuthStrippingRedirectHandler = _core._CrossHostAuthStrippingRedirectHandler
+_URL_OPENER = _core._URL_OPENER
 
 
 def github_api_headers(url: str | None = None) -> dict[str, str]:
-    return {
-        "Accept": "application/vnd.github+json",
-        **auth_headers(url),
-    }
-
-
-def is_github_api_url(url: str | None) -> bool:
-    return parsed_hostname(url) == "api.github.com"
-
-
-def is_retryable_url_error(exc: Exception) -> bool:
-    if isinstance(exc, urllib.error.HTTPError):
-        # GitHub returns 403 (not the standard 429) when the API rate
-        # limit is hit. Anonymous calls share a 60-req/hour bucket per
-        # runner IP, which CI fleets can exhaust trivially. Treat 403
-        # against api.github.com as retryable so we get one or two
-        # backoff cycles before the source-build fallback fires; honour
-        # Retry-After / X-RateLimit-Reset in sleep_backoff for accurate
-        # waits. Real 403s on other hosts (private artefact downloads,
-        # auth failures) stay non-retryable.
-        if exc.code == 403:
-            return is_github_api_url(getattr(exc, "url", None))
-        return exc.code in RETRYABLE_HTTP_STATUS
-    if isinstance(exc, urllib.error.URLError):
-        return True
-    if isinstance(exc, TimeoutError):
-        return True
-    if isinstance(exc, socket.timeout):
-        return True
-    return False
+    return _core.github_api_headers(_OPS, url)
 
 
+is_github_api_url = _core.is_github_api_url
+is_retryable_url_error = _core.is_retryable_url_error
 _RATE_LIMIT_WAIT_CAP_SECONDS = 60.0
-
-
-def _http_error_retry_delay(exc: Exception) -> float | None:
-    """Extract a recommended wait from rate-limit headers on a 403/429.
-
-    Returns None when no header is present or the indicated wait is
-    longer than _RATE_LIMIT_WAIT_CAP_SECONDS (in which case the caller
-    should not block on it -- the source-build fallback is faster).
-    """
-    if not isinstance(exc, urllib.error.HTTPError):
-        return None
-    headers = getattr(exc, "headers", None)
-    if headers is None:
-        return None
-    retry_after = headers.get("Retry-After")
-    if retry_after and retry_after.strip().isdigit():
-        wait = float(retry_after.strip())
-        return wait if wait <= _RATE_LIMIT_WAIT_CAP_SECONDS else None
-    rate_reset = headers.get("X-RateLimit-Reset")
-    if rate_reset and rate_reset.strip().isdigit():
-        wait = float(rate_reset.strip()) - time.time()
-        if 0.0 < wait <= _RATE_LIMIT_WAIT_CAP_SECONDS:
-            return wait + 1.0  # +1s of slack so the bucket is fresh
-    return None
-
-
-def sleep_backoff(
-    attempt: int,
-    *,
-    base_delay: float = HTTP_FETCH_BASE_DELAY_SECONDS,
-    exc: Exception | None = None,
-) -> None:
-    delay = base_delay * (2 ** max(attempt - 1, 0))
-    header_delay = _http_error_retry_delay(exc) if exc is not None else None
-    if header_delay is not None:
-        delay = max(delay, header_delay)
-    delay += random.uniform(0.0, 0.2)
-    time.sleep(delay)
-
-
-def atomic_write_bytes(destination: Path, data: bytes) -> None:
-    destination.parent.mkdir(parents = True, exist_ok = True)
-    with tempfile.NamedTemporaryFile(
-        prefix = destination.name + ".tmp-",
-        dir = destination.parent,
-        delete = False,
-    ) as handle:
-        tmp_path = Path(handle.name)
-        handle.write(data)
-        handle.flush()
-        os.fsync(handle.fileno())
-    os.replace(tmp_path, destination)
-
-
-def atomic_replace_from_tempfile(tmp_path: Path, destination: Path) -> None:
-    destination.parent.mkdir(parents = True, exist_ok = True)
-    os.replace(tmp_path, destination)
+_http_error_retry_delay = _core._http_error_retry_delay
+sleep_backoff = _core.sleep_backoff
+atomic_write_bytes = _core.atomic_write_bytes
+atomic_replace_from_tempfile = _core.atomic_replace_from_tempfile
 
 
 def source_archive_logical_name(upstream_tag: str) -> str:
@@ -638,27 +461,9 @@ def exact_source_archive_logical_name(source_commit: str) -> str:
     return f"llama.cpp-source-commit-{source_commit}.tar.gz"
 
 
-def sha256_file(path: Path) -> str:
-    digest = hashlib.sha256()
-    with path.open("rb") as handle:
-        for chunk in iter(lambda: handle.read(1024 * 1024), b""):
-            digest.update(chunk)
-    return digest.hexdigest()
-
-
-def sha256_bytes(data: bytes) -> str:
-    return hashlib.sha256(data).hexdigest()
-
-
-def normalize_sha256_digest(value: str | None) -> str | None:
-    if not isinstance(value, str) or not value:
-        return None
-    lowered = value.lower()
-    if lowered.startswith("sha256:"):
-        lowered = lowered.split(":", 1)[1]
-    if len(lowered) != 64 or any(ch not in "0123456789abcdef" for ch in lowered):
-        return None
-    return lowered
+sha256_file = _core.sha256_file
+sha256_bytes = _core.sha256_bytes
+normalize_sha256_digest = _core.normalize_sha256_digest
 
 
 def normalize_source_ref_kind(value: str | None) -> str | None:
@@ -682,15 +487,7 @@ def normalize_source_commit(value: str | None) -> str | None:
 
 
 def validate_schema_version(payload: dict[str, Any], *, label: str) -> None:
-    schema_version = payload.get("schema_version")
-    if schema_version is None:
-        return
-    try:
-        normalized = int(schema_version)
-    except (TypeError, ValueError) as exc:
-        raise RuntimeError(f"{label} schema_version was not an integer") from exc
-    if normalized != 1:
-        raise RuntimeError(f"{label} schema_version={normalized} is unsupported")
+    _core.validate_schema_version(payload, label = label)
 
 
 def repo_slug_from_source(value: str | None) -> str | None:
@@ -856,127 +653,10 @@ def _published_windows_cuda_runtime(
     return f"{major}.{best}" if best is not None else None
 
 
-def format_byte_count(num_bytes: float) -> str:
-    units = ["B", "KiB", "MiB", "GiB", "TiB"]
-    value = float(num_bytes)
-    for unit in units:
-        if abs(value) < 1024.0 or unit == units[-1]:
-            if unit == "B":
-                return f"{int(value)} {unit}"
-            return f"{value:.1f} {unit}"
-        value /= 1024.0
-    return f"{num_bytes:.1f} B"
-
-
-def _progress_percent_step() -> int:
-    """Non-tty milestone granularity. The in-app updater sets
-    UNSLOTH_PROGRESS_PERCENT_STEP=5 to stream finer progress lines."""
-    try:
-        step = int(os.environ.get("UNSLOTH_PROGRESS_PERCENT_STEP", "25"))
-    except ValueError:
-        return 25
-    return min(max(step, 1), 50)
-
-
-class DownloadProgress:
-    def __init__(self, label: str, total_bytes: int | None) -> None:
-        self.label = label
-        self.total_bytes = total_bytes if total_bytes and total_bytes > 0 else None
-        self.start_time = time.monotonic()
-        self.last_emit = 0.0
-        term_ok = os.environ.get("TERM", "").lower() != "dumb"
-        self.stream = (
-            sys.stderr if sys.stderr.isatty() else sys.stdout if sys.stdout.isatty() else sys.stderr
-        )
-        self.is_tty = term_ok and self.stream.isatty()
-        self.completed = False
-        self.milestone_step = _progress_percent_step()
-        self.last_milestone_percent = -1
-        self.last_milestone_bytes = 0
-        self.has_rendered_tty_progress = False
-
-    def _render(
-        self,
-        downloaded_bytes: int,
-        *,
-        final: bool = False,
-    ) -> str:
-        elapsed = max(time.monotonic() - self.start_time, 1e-6)
-        speed = downloaded_bytes / elapsed
-        speed_text = f"{format_byte_count(speed)}/s"
-        if self.total_bytes is not None:
-            percent = min(100.0, (downloaded_bytes / self.total_bytes) * 100.0)
-            return (
-                f"{self.label}: {percent:5.1f}% "
-                f"({format_byte_count(downloaded_bytes)}/{format_byte_count(self.total_bytes)}) "
-                f"at {speed_text}"
-            )
-        if final:
-            return f"{self.label}: {format_byte_count(downloaded_bytes)} downloaded at {speed_text}"
-        return f"{self.label}: {format_byte_count(downloaded_bytes)} downloaded at {speed_text}"
-
-    def update(self, downloaded_bytes: int) -> None:
-        now = time.monotonic()
-        if self.is_tty:
-            elapsed = now - self.start_time
-            if not self.has_rendered_tty_progress:
-                if self.total_bytes is not None and downloaded_bytes >= self.total_bytes:
-                    return
-                if elapsed < TTY_PROGRESS_START_DELAY_SECONDS:
-                    return
-            min_interval = 0.2
-            if (
-                self.has_rendered_tty_progress
-                and not self.completed
-                and (now - self.last_emit) < min_interval
-            ):
-                return
-            self.last_emit = now
-            line = self._render(downloaded_bytes)
-            self.stream.write("\r\033[K" + line)
-            self.stream.flush()
-            self.has_rendered_tty_progress = True
-            return
-
-        should_emit = False
-        if self.total_bytes is not None:
-            percent = int((downloaded_bytes * 100) / max(self.total_bytes, 1))
-            step = self.milestone_step
-            milestone_percent = min((percent // step) * step, 100)
-            if milestone_percent > self.last_milestone_percent and milestone_percent < 100:
-                self.last_milestone_percent = milestone_percent
-                should_emit = True
-        else:
-            byte_step = 25 * 1024 * 1024
-            if (
-                downloaded_bytes - self.last_milestone_bytes >= byte_step
-                and (now - self.last_emit) >= 5.0
-            ):
-                self.last_milestone_bytes = downloaded_bytes
-                should_emit = True
-
-        if not should_emit:
-            return
-
-        self.last_emit = now
-        self.stream.write(self._render(downloaded_bytes) + "\n")
-        self.stream.flush()
-
-    def finish(self, downloaded_bytes: int) -> None:
-        self.completed = True
-        line = self._render(downloaded_bytes, final = True)
-        if self.is_tty:
-            if not self.has_rendered_tty_progress:
-                return
-            self.stream.write("\r\033[K")
-        else:
-            self.stream.write(line + "\n")
-        self.stream.flush()
-
-
-def download_label_from_url(url: str) -> str:
-    name = Path(urllib.parse.urlparse(url).path).name
-    return name or url
+format_byte_count = _core.format_byte_count
+_progress_percent_step = _core._progress_percent_step
+DownloadProgress = _core.DownloadProgress
+download_label_from_url = _core.download_label_from_url
 
 
 def download_bytes(
@@ -987,151 +667,30 @@ def download_bytes(
     headers: dict[str, str] | None = None,
     progress_label: str | None = None,
 ) -> bytes:
-    last_exc: Exception | None = None
-    for attempt in range(1, attempts + 1):
-        try:
-            request = urllib.request.Request(url, headers = headers or auth_headers(url))
-            with _URL_OPENER.open(request, timeout = timeout) as response:
-                total_bytes: int | None = None
-                content_length = response.headers.get("Content-Length")
-                if content_length and content_length.isdigit():
-                    total_bytes = int(content_length)
-                progress = DownloadProgress(progress_label, total_bytes) if progress_label else None
-                data = bytearray()
-                while True:
-                    chunk = response.read(1024 * 1024)
-                    if not chunk:
-                        break
-                    data.extend(chunk)
-                    if progress is not None:
-                        progress.update(len(data))
-                if progress is not None:
-                    progress.finish(len(data))
-                return bytes(data)
-        except Exception as exc:
-            last_exc = exc
-            if attempt >= attempts or not is_retryable_url_error(exc):
-                raise
-            log(f"fetch failed ({attempt}/{attempts}) for {url}: {exc}; retrying")
-            sleep_backoff(attempt, exc = exc)
-    assert last_exc is not None
-    raise last_exc
+    return _core.download_bytes(
+        _OPS,
+        url,
+        timeout = timeout,
+        attempts = attempts,
+        headers = headers,
+        progress_label = progress_label,
+    )
 
 
 def fetch_json(url: str) -> Any:
-    attempts = JSON_FETCH_ATTEMPTS if is_github_api_url(url) else 1
-    last_decode_exc: Exception | None = None
-    for attempt in range(1, attempts + 1):
-        try:
-            data = download_bytes(
-                url,
-                timeout = 30,
-                headers = github_api_headers(url) if is_github_api_url(url) else auth_headers(url),
-            )
-        except urllib.error.HTTPError as exc:
-            if exc.code == 403 and is_github_api_url(url):
-                hint = ""
-                if not (os.environ.get("GH_TOKEN") or os.environ.get("GITHUB_TOKEN")):
-                    hint = "; set GH_TOKEN or GITHUB_TOKEN to avoid GitHub API rate limits"
-                raise RuntimeError(f"GitHub API returned 403 for {url}{hint}") from exc
-            raise
-        if not data:
-            last_decode_exc = RuntimeError(f"downloaded empty JSON payload from {url}")
-        else:
-            try:
-                payload = json.loads(data.decode("utf-8"))
-            except (UnicodeDecodeError, json.JSONDecodeError) as exc:
-                last_decode_exc = RuntimeError(f"downloaded invalid JSON from {url}: {exc}")
-            else:
-                if not isinstance(payload, dict) and not isinstance(payload, list):
-                    raise RuntimeError(
-                        f"downloaded unexpected JSON type from {url}: {type(payload).__name__}"
-                    )
-                return payload
-        if attempt >= attempts:
-            assert last_decode_exc is not None
-            raise last_decode_exc
-        log(f"json fetch failed ({attempt}/{attempts}) for {url}; retrying")
-        sleep_backoff(attempt)
-    assert last_decode_exc is not None
-    raise last_decode_exc
+    return _core.fetch_json(_OPS, url)
 
 
 def download_file(url: str, destination: Path) -> None:
-    destination.parent.mkdir(parents = True, exist_ok = True)
-    last_exc: Exception | None = None
-    for attempt in range(1, HTTP_FETCH_ATTEMPTS + 1):
-        tmp_path: Path | None = None
-        try:
-            request = urllib.request.Request(url, headers = auth_headers(url))
-            with tempfile.NamedTemporaryFile(
-                prefix = destination.name + ".tmp-",
-                dir = destination.parent,
-                delete = False,
-            ) as handle:
-                tmp_path = Path(handle.name)
-                with _URL_OPENER.open(request, timeout = 120) as response:
-                    total_bytes: int | None = None
-                    content_length = response.headers.get("Content-Length")
-                    if content_length and content_length.isdigit():
-                        total_bytes = int(content_length)
-                    progress = DownloadProgress(f"Downloading {destination.name}", total_bytes)
-                    downloaded_bytes = 0
-                    while True:
-                        chunk = response.read(1024 * 1024)
-                        if not chunk:
-                            break
-                        handle.write(chunk)
-                        downloaded_bytes += len(chunk)
-                        progress.update(downloaded_bytes)
-                    progress.finish(downloaded_bytes)
-                handle.flush()
-                os.fsync(handle.fileno())
-            if not tmp_path.exists() or tmp_path.stat().st_size == 0:
-                raise RuntimeError(f"downloaded empty file from {url}")
-            atomic_replace_from_tempfile(tmp_path, destination)
-            return
-        except Exception as exc:
-            last_exc = exc
-            if tmp_path is not None:
-                try:
-                    tmp_path.unlink(missing_ok = True)
-                except Exception:
-                    pass
-            if attempt >= HTTP_FETCH_ATTEMPTS or not is_retryable_url_error(exc):
-                raise
-            log(f"download failed ({attempt}/{HTTP_FETCH_ATTEMPTS}) for {url}: {exc}; retrying")
-            sleep_backoff(attempt, exc = exc)
-    assert last_exc is not None
-    raise last_exc
+    _core.download_file(_OPS, url, destination)
 
 
 def download_file_verified(
     url: str, destination: Path, *, expected_sha256: str | None, label: str
 ) -> None:
-    normalized_expected = normalize_sha256_digest(expected_sha256)
-    if not normalized_expected:
-        download_file(url, destination)
-        log(f"downloaded {label} without a published sha256; relying on install validation")
-        return
-
-    for attempt in range(1, 3):
-        download_file(url, destination)
-        actual_sha256 = sha256_file(destination)
-        if actual_sha256 == normalized_expected:
-            log(f"verified {label} sha256={actual_sha256}")
-            return
-
-        log(
-            f"{label} checksum mismatch on attempt {attempt}/2: "
-            f"expected={normalized_expected} actual={actual_sha256}"
-        )
-        destination.unlink(missing_ok = True)
-        if attempt == 2:
-            raise PrebuiltFallback(
-                f"{label} checksum mismatch after retry: expected={normalized_expected} actual={actual_sha256}"
-            )
-        log(f"retrying {label} download after checksum mismatch")
+    _core.download_file_verified(
+        _OPS, url, destination, expected_sha256 = expected_sha256, label = label
+    )
 
 
 def upstream_source_archive_urls(tag: str) -> list[str]:
@@ -1165,21 +724,11 @@ def release_asset_download_url(
 
 
 def github_release_assets(repo: str, tag: str) -> dict[str, str]:
-    payload = fetch_json(
-        f"https://api.github.com/repos/{repo}/releases/tags/{urllib.parse.quote(tag, safe = '')}"
-    )
-    if not isinstance(payload, dict):
-        raise RuntimeError(f"unexpected release payload for {repo}@{tag}")
-    return release_asset_map(payload)
+    return _core.github_release_assets(_OPS, repo, tag)
 
 
 def github_release(repo: str, tag: str) -> dict[str, Any]:
-    payload = fetch_json(
-        f"https://api.github.com/repos/{repo}/releases/tags/{urllib.parse.quote(tag, safe = '')}"
-    )
-    if not isinstance(payload, dict):
-        raise RuntimeError(f"unexpected release payload for {repo}@{tag}")
-    return payload
+    return _core.github_release(_OPS, repo, tag)
 
 
 def github_releases(
@@ -1542,10 +1091,7 @@ def resolve_simple_install_release_plans(
                 if not allow_older_release_fallback:
                     raise
                 release_tag = release.get("tag_name") or "unknown"
-                log(
-                    "published release skipped for install planning: "
-                    f"{repo}@{release_tag} ({exc})"
-                )
+                log(f"published release skipped for install planning: {repo}@{release_tag} ({exc})")
                 continue
 
             plans.append(plan)
@@ -1571,198 +1117,23 @@ def normalized_requested_llama_tag(requested_tag: str | None) -> str:
     return "latest"
 
 
-def normalize_compute_cap(value: Any) -> str | None:
-    raw = str(value).strip()
-    if not raw:
-        return None
-    if "." in raw:
-        parts = raw.split(".", 1)
-        if len(parts) != 2:
-            return None
-        major, minor = parts
-        if not major.isdigit() or not minor.isdigit():
-            return None
-        return f"{int(major)}{int(minor)}"
-    if raw.isdigit():
-        return str(int(raw))
-    return None
-
-
-def normalize_compute_caps(compute_caps: Iterable[str]) -> list[str]:
-    normalized: list[str] = []
-    seen: set[str] = set()
-    for raw in compute_caps:
-        normalized_value = normalize_compute_cap(raw)
-        if normalized_value is None:
-            continue
-        if normalized_value in seen:
-            continue
-        seen.add(normalized_value)
-        normalized.append(normalized_value)
-    normalized.sort(key = int)
-    return normalized
-
-
-def parse_cuda_visible_devices(value: str | None) -> list[str] | None:
-    if value is None:
-        return None
-    raw = value.strip()
-    if not raw or raw == "-1":
-        return []
-    return [token.strip() for token in raw.split(",") if token.strip()]
-
-
-def supports_explicit_visible_device_matching(visible_devices: list[str] | None) -> bool:
-    if not visible_devices:
-        return False
-    for token in visible_devices:
-        lowered = token.lower()
-        if token.isdigit() or lowered.startswith("gpu-"):
-            continue
-        return False
-    return True
-
-
-def select_visible_gpu_rows(
-    gpu_rows: Iterable[tuple[str, str, str]], visible_devices: list[str] | None
-) -> list[tuple[str, str, str]]:
-    rows = list(gpu_rows)
-    if visible_devices is None:
-        return rows
-    if not visible_devices:
-        return []
-
-    by_index = {index: (index, uuid, cap) for index, uuid, cap in rows}
-    by_uuid = {uuid.lower(): (index, uuid, cap) for index, uuid, cap in rows}
-    selected: list[tuple[str, str, str]] = []
-    seen_indices: set[str] = set()
-    for token in visible_devices:
-        row = by_index.get(token)
-        if row is None:
-            normalized_token = token.lower()
-            row = by_uuid.get(normalized_token)
-            if row is None and normalized_token.startswith("gpu-"):
-                row = by_uuid.get(normalized_token)
-            if row is None and not normalized_token.startswith("gpu-"):
-                row = by_uuid.get("gpu-" + normalized_token)
-        if row is None:
-            continue
-        index = row[0]
-        if index in seen_indices:
-            continue
-        seen_indices.add(index)
-        selected.append(row)
-    return selected
-
-
-def dir_provides_exact_library(directory: str | Path, library: str) -> bool:
-    if not library:
-        return False
-    candidate = Path(directory) / library
-    return candidate.exists() and (candidate.is_file() or candidate.is_symlink())
+normalize_compute_cap = _core.normalize_compute_cap
+normalize_compute_caps = _core.normalize_compute_caps
+parse_cuda_visible_devices = _core.parse_cuda_visible_devices
+supports_explicit_visible_device_matching = _core.supports_explicit_visible_device_matching
+select_visible_gpu_rows = _core.select_visible_gpu_rows
+dir_provides_exact_library = _core.dir_provides_exact_library
 
 
 def linux_runtime_dirs_for_required_libraries(required_libraries: Iterable[str]) -> list[str]:
-    required = [library for library in required_libraries if library]
-    candidates: list[str | Path] = []
-
-    env_dirs = os.environ.get("CUDA_RUNTIME_LIB_DIR", "")
-    if env_dirs:
-        candidates.extend(part for part in env_dirs.split(os.pathsep) if part)
-    ld_library_path = os.environ.get("LD_LIBRARY_PATH", "")
-    if ld_library_path:
-        candidates.extend(part for part in ld_library_path.split(os.pathsep) if part)
-
-    cuda_roots: list[Path] = []
-    for name in ("CUDA_HOME", "CUDA_PATH", "CUDA_ROOT"):
-        value = os.environ.get(name)
-        if value:
-            cuda_roots.append(Path(value))
-    cuda_roots.extend(Path(path) for path in glob_paths("/usr/local/cuda", "/usr/local/cuda-*"))
-
-    for root in cuda_roots:
-        candidates.extend(
-            [
-                root / "lib",
-                root / "lib64",
-                root / "targets" / "x86_64-linux" / "lib",
-            ]
-        )
-
-    candidates.extend(
-        Path(path)
-        for path in glob_paths(
-            "/lib",
-            "/lib64",
-            "/usr/lib",
-            "/usr/lib64",
-            "/usr/local/lib",
-            "/usr/local/lib64",
-            "/lib/x86_64-linux-gnu",
-            "/usr/lib/x86_64-linux-gnu",
-        )
-    )
-    candidates.extend(
-        Path(path) for path in glob_paths("/usr/local/lib/ollama/cuda_v*", "/usr/lib/wsl/lib")
-    )
-    candidates.extend(Path(path) for path in python_runtime_dirs())
-    candidates.extend(Path(path) for path in ldconfig_runtime_dirs(required))
-
-    resolved = dedupe_existing_dirs(candidates)
-    if not required:
-        return resolved
-
-    matched: list[tuple[int, str]] = []
-    for directory in resolved:
-        base = Path(directory)
-        provided = sum(1 for library in required if dir_provides_exact_library(directory, library))
-        if provided:
-            matched.append((provided, directory))
-
-    matched.sort(key = lambda item: item[0], reverse = True)
-    return [directory for _, directory in matched]
+    return _core.linux_runtime_dirs_for_required_libraries(_OPS, required_libraries)
 
 
 def detected_linux_runtime_lines() -> tuple[list[str], dict[str, list[str]]]:
-    line_requirements = {
-        f"cuda{m}": [f"libcudart.so.{m}", f"libcublas.so.{m}"]
-        for m in range(_MAX_PROBE_CUDA_MAJOR, _MIN_CUDA_MAJOR - 1, -1)
-    }
-    detected: list[str] = []
-    runtime_dirs: dict[str, list[str]] = {}
-    for line, required in line_requirements.items():
-        dirs = linux_runtime_dirs_for_required_libraries(required)
-        library_matches: dict[str, list[str]] = {}
-        matching_dirs: list[str] = []
-        for library in required:
-            matched_dirs = [
-                directory for directory in dirs if any(Path(directory).glob(f"{library}*"))
-            ]
-            if not matched_dirs:
-                library_matches = {}
-                matching_dirs = []
-                break
-            library_matches[library] = matched_dirs
-            for directory in matched_dirs:
-                if directory not in matching_dirs:
-                    matching_dirs.append(directory)
-        if library_matches:
-            detected.append(line)
-            runtime_dirs[line] = matching_dirs
-    return detected, runtime_dirs
+    return _core.detected_linux_runtime_lines(_OPS)
 
 
-def release_asset_map(release: dict[str, Any]) -> dict[str, str]:
-    assets = release.get("assets")
-    if not isinstance(assets, list):
-        return {}
-    return {
-        asset["name"]: asset.get("browser_download_url", "")
-        for asset in assets
-        if isinstance(asset, dict)
-        and isinstance(asset.get("name"), str)
-        and isinstance(asset.get("browser_download_url"), str)
-    }
+release_asset_map = _core.release_asset_map
 
 
 def parse_published_artifact(raw: Any) -> PublishedLlamaArtifact | None:
@@ -2067,47 +1438,9 @@ def iter_published_release_bundles(
         yield bundle
 
 
-def _artifact_covers_sms(artifact: PublishedLlamaArtifact, host_sms: Iterable[str]) -> bool:
-    """True when every host SM is listed in the artifact's supported_sms and
-    falls within its [min_sm, max_sm] range."""
-    if not artifact.supported_sms or artifact.min_sm is None or artifact.max_sm is None:
-        return False
-    supported = {str(value) for value in artifact.supported_sms}
-    return all(sm in supported and artifact.min_sm <= int(sm) <= artifact.max_sm for sm in host_sms)
-
-
-def _sm_range(artifact: PublishedLlamaArtifact) -> int:
-    """SM-coverage span used as a sort key, where a tighter (smaller) range wins.
-    A bundle with no SM metadata (legacy/upstream-named) gets a max range so it
-    sorts last and can't outrank a real targeted bundle whose tight range would
-    otherwise sort first."""
-    if artifact.min_sm is not None and artifact.max_sm is not None:
-        return artifact.max_sm - artifact.min_sm
-    return 9999
-
-
-def _blackwell_capable_linux_runtime_lines(
-    host_sms: list[str], artifacts: list[PublishedLlamaArtifact]
-) -> list[str]:
-    """CUDA runtime lines (highest major first) shipping a bundle that covers every
-    visible host SM. Lets a Blackwell host prefer a native sm_120 line over torch's
-    reported line, mirroring the Windows Blackwell preference."""
-    lines: set[str] = set()
-    for artifact in artifacts:
-        line = artifact.runtime_line
-        # Only rank "cuda<major>" lines; ignore malformed/future-format values
-        # (e.g. "cuda13.1") so they are skipped, as pre-existing code does, rather
-        # than crashing the major sort.
-        if not (line and line.startswith("cuda") and line[len("cuda") :].isdigit()):
-            continue
-        if not artifact.supported_sms or artifact.min_sm is None or artifact.max_sm is None:
-            continue
-        supported = {str(value) for value in artifact.supported_sms}
-        if all(
-            sm in supported and artifact.min_sm <= int(sm) <= artifact.max_sm for sm in host_sms
-        ):
-            lines.add(line)
-    return sorted(lines, key = lambda line: int(line[len("cuda") :]), reverse = True)
+_artifact_covers_sms = _core.artifact_covers_sms
+_sm_range = _core.sm_range
+_blackwell_capable_linux_runtime_lines = _core.blackwell_capable_linux_runtime_lines
 
 
 def linux_cuda_choice_from_release(
@@ -2398,50 +1731,15 @@ def _download_host_resolve_enabled() -> bool:
 
 
 def _release_asset_download_url(repo: str, tag: str, asset_name: str) -> str:
-    """Tag-pinned asset URL on the release-assets CDN (not api.github.com, so no
-    rate limit)."""
-    return (
-        f"https://github.com/{urllib.parse.quote(repo, safe = '/')}/releases/download/"
-        f"{urllib.parse.quote(tag, safe = '')}/"
-        f"{urllib.parse.quote(asset_name, safe = '')}"
-    )
+    return _core.release_asset_download_url(repo, tag, asset_name)
 
 
 def _download_host_latest_release_tag(repo: str) -> str | None:
-    """Authoritative latest tag from GitHub's /releases/latest redirect target
-    (github.com, no api.github.com rate limit); the fast path pins URLs to it rather
-    than the checksum asset's self-reported release_tag. /releases/latest resolves by
-    created_at/make_latest, which can lag the published_at newest the freshness
-    detection uses. None on 404 so the caller falls back to the API."""
-    url = f"https://github.com/{urllib.parse.quote(repo, safe = '/')}/releases/latest"
-    request = urllib.request.Request(
-        url,
-        method = "HEAD",
-        headers = {"User-Agent": "unsloth-studio-llama-prebuilt"},
-    )
-    try:
-        with _URL_OPENER.open(request, timeout = 30) as response:
-            final_url = response.geturl()
-    except urllib.error.HTTPError as exc:
-        if exc.code == 404:
-            return None
-        raise
-    marker = "/releases/tag/"
-    index = final_url.find(marker)
-    if index == -1:
-        return None
-    tag = urllib.parse.unquote(final_url[index + len(marker) :]).strip("/")
-    return tag or None
+    return _core.download_host_latest_release_tag(_OPS, repo)
 
 
 def _fetch_download_host_json(url: str) -> Any:
-    # Public CDN asset: plain unauthenticated GET, not the rate-limited API.
-    data = download_bytes(
-        url,
-        timeout = 30,
-        headers = {"User-Agent": "unsloth-studio-llama-prebuilt"},
-    )
-    return json.loads(data.decode("utf-8"))
+    return _core.fetch_download_host_json(_OPS, url)
 
 
 def _download_host_resolved_release(repo: str) -> ResolvedPublishedRelease | None:
@@ -3292,38 +2590,14 @@ def pick_windows_cuda_runtime(host: HostInfo) -> str | None:
     return None
 
 
-def compatible_linux_runtime_lines(host: HostInfo) -> list[str]:
-    if not host.driver_cuda_version:
-        return []
-    major, _minor = host.driver_cuda_version
-    if major < _MIN_CUDA_MAJOR:
-        return []
-    return _cuda_runtime_lines_for_major(major)
+compatible_linux_runtime_lines = _core.compatible_linux_runtime_lines
 
 
-def windows_runtime_line_info() -> dict[str, tuple[str, ...]]:
-    # Generated per CUDA major (newest first) so a new toolkit is detected
-    # without a code change while the cudart64_<major>.dll naming holds.
-    return {
-        f"cuda{m}": (
-            f"cudart64_{m}*.dll",
-            f"cublas64_{m}*.dll",
-            f"cublasLt64_{m}*.dll",
-        )
-        for m in range(_MAX_PROBE_CUDA_MAJOR, _MIN_CUDA_MAJOR - 1, -1)
-    }
+windows_runtime_line_info = _core.windows_runtime_line_info
 
 
 def detected_windows_runtime_lines() -> tuple[list[str], dict[str, list[str]]]:
-    dirs = windows_runtime_dirs()
-    detected: list[str] = []
-    runtime_dirs: dict[str, list[str]] = {}
-    for runtime_line, required_patterns in windows_runtime_line_info().items():
-        matching_dirs = windows_runtime_dirs_for_patterns(required_patterns, dirs)
-        if matching_dirs:
-            detected.append(runtime_line)
-            runtime_dirs[runtime_line] = matching_dirs
-    return detected, runtime_dirs
+    return _core.detected_windows_runtime_lines(_OPS)
 
 
 def compatible_windows_runtime_lines(host: HostInfo) -> list[str]:
@@ -3337,68 +2611,8 @@ def compatible_windows_runtime_lines(host: HostInfo) -> list[str]:
     return _cuda_runtime_lines_for_major(major)
 
 
-def runtime_line_from_cuda_version(cuda_version: str | None) -> str | None:
-    if not cuda_version:
-        return None
-    raw = str(cuda_version).strip()
-    if not raw:
-        return None
-    major, _, _ = raw.partition(".")
-    if major == "12":
-        return "cuda12"
-    if major == "13":
-        return "cuda13"
-    return None
-
-
-def detect_torch_cuda_runtime_preference(host: HostInfo) -> CudaRuntimePreference:
-    selection_log: list[str] = []
-    if host.is_macos:
-        selection_log.append("torch_cuda_preference: skipped on macOS")
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-    if not (host.has_usable_nvidia and (host.is_linux or host.is_windows)):
-        selection_log.append(
-            "torch_cuda_preference: skipped because CUDA host prerequisites were not met"
-        )
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-
-    try:
-        import torch
-    except Exception as exc:
-        selection_log.append(f"torch_cuda_preference: import failed: {exc}")
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-
-    cuda_version = getattr(getattr(torch, "version", None), "cuda", None)
-    if not isinstance(cuda_version, str) or not cuda_version.strip():
-        selection_log.append(
-            "torch_cuda_preference: torch.version.cuda missing; skipping Torch shortcut"
-        )
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-
-    try:
-        cuda_available = bool(torch.cuda.is_available())
-    except Exception as exc:
-        selection_log.append(f"torch_cuda_preference: torch.cuda.is_available() failed: {exc}")
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-
-    if not cuda_available:
-        selection_log.append(
-            "torch_cuda_preference: torch.cuda.is_available() returned False; falling back to normal selection"
-        )
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-
-    runtime_line = runtime_line_from_cuda_version(cuda_version)
-    if runtime_line is None:
-        selection_log.append(
-            f"torch_cuda_preference: unsupported torch.version.cuda={cuda_version}; falling back to normal selection"
-        )
-        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
-
-    selection_log.append(
-        "torch_cuda_preference: selected runtime_line="
-        f"{runtime_line} from torch.version.cuda={cuda_version}"
-    )
-    return CudaRuntimePreference(runtime_line = runtime_line, selection_log = selection_log)
+runtime_line_from_cuda_version = _core.runtime_line_from_cuda_version
+detect_torch_cuda_runtime_preference = _core.detect_torch_cuda_runtime_preference
 
 
 def windows_cuda_attempts(
@@ -3569,18 +2783,8 @@ def _windows_cuda_attempt_covers_blackwell(
     return attempt.max_sm is not None and attempt.max_sm >= _BLACKWELL_MIN_SM
 
 
-def _host_is_blackwell(host: HostInfo) -> bool:
-    caps = normalize_compute_caps(host.compute_caps)
-    return bool(caps) and int(caps[-1]) >= _BLACKWELL_MIN_SM
-
-
-def _blackwell_min_toolkit_for_host(host: HostInfo) -> tuple[int, int]:
-    """Minimum CUDA toolkit this Blackwell host needs: 12.8 for the family,
-    12.9 if any of its SMs is sm_103/sm_121 (no native target before 12.9)."""
-    req = _BLACKWELL_MIN_TOOLKIT
-    for sm in normalize_compute_caps(host.compute_caps):
-        req = max(req, _BLACKWELL_SM_MIN_TOOLKIT.get(int(sm), _BLACKWELL_MIN_TOOLKIT))
-    return req
+_host_is_blackwell = _core.host_is_blackwell
+_blackwell_min_toolkit_for_host = _core.blackwell_min_toolkit_for_host
 
 
 def _drop_blackwell_incapable_windows_cuda(
@@ -4204,169 +3408,7 @@ def resolve_release_asset_choice(
     )
 
 
-def extract_archive(archive_path: Path, destination: Path) -> None:
-    def safe_extract_path(base: Path, member_name: str) -> Path:
-        normalized = member_name.replace("\\", "/")
-        member_path = Path(normalized)
-        if member_path.is_absolute():
-            raise PrebuiltFallback(f"archive member used an absolute path: {member_name}")
-
-        target = (base / member_path).resolve()
-        base_resolved = base.resolve()
-        try:
-            target.relative_to(base_resolved)
-        except ValueError as exc:
-            raise PrebuiltFallback(f"archive member escaped destination: {member_name}") from exc
-        return target
-
-    def _try_repair_missing_slash(
-        member_name: str, link_name: str, archive_names: set[str]
-    ) -> str | None:
-        """Some upstream llama.cpp Mac releases (e.g. b9165, b9169) ship
-        symlinks whose linkname is missing the directory separator AND
-        the leading character of the file basename between the
-        top-level dir and the rest of the path:
-
-            llama-b9165/libggml-rpc.0.dylib -> llama-b9165ibggml-rpc.0.11.1.dylib
-
-        That cannot be resolved as written. Detect the pattern
-        (linkname starts with the top-level dir name but no following
-        slash) and search archive entries under that dir for a real
-        file whose basename ends with the mangled suffix. Only accept
-        when the suffix uniquely identifies a real archive entry.
-        Returns the corrected linkname expressed relative to the
-        member's parent directory -- callers join it with
-        `target.parent`, so a full `top/file` path would double the
-        prefix into `top/top/file`."""
-        if "/" not in member_name or "/" in link_name:
-            return None
-        top, _, _ = member_name.partition("/")
-        if not link_name.startswith(top) or len(link_name) <= len(top):
-            return None
-        bad_suffix = link_name[len(top) :]
-        if not bad_suffix or bad_suffix.startswith("/"):
-            return None
-        prefix = f"{top}/"
-        candidates = [
-            name
-            for name in archive_names
-            if name.startswith(prefix)
-            and "/" not in name[len(prefix) :]
-            and name[len(prefix) :].endswith(bad_suffix)
-        ]
-        if len(candidates) != 1:
-            return None
-        # Strip the top-level dir so the caller's `target.parent / Path(...)`
-        # composition resolves inside the staging dir, not into a duplicate
-        # `top/top/...` path.
-        return candidates[0][len(prefix) :]
-
-    def safe_link_target(
-        base: Path, member_name: str, link_name: str, target: Path, archive_names: set[str]
-    ) -> tuple[str, Path]:
-        normalized = link_name.replace("\\", "/")
-        repaired = _try_repair_missing_slash(member_name, normalized, archive_names)
-        if repaired is not None:
-            normalized = repaired
-        link_path = Path(normalized)
-        if link_path.is_absolute():
-            raise PrebuiltFallback(
-                f"archive link used an absolute target: {member_name} -> {link_name}"
-            )
-        if not normalized:
-            raise PrebuiltFallback(f"archive link used an empty target: {member_name}")
-
-        resolved = (target.parent / link_path).resolve()
-        base_resolved = base.resolve()
-        try:
-            resolved.relative_to(base_resolved)
-        except ValueError as exc:
-            raise PrebuiltFallback(
-                f"archive link escaped destination: {member_name} -> {link_name}"
-            ) from exc
-        return normalized, resolved
-
-    def extract_zip_safely(source: Path, base: Path) -> None:
-        with zipfile.ZipFile(source) as archive:
-            for member in archive.infolist():
-                target = safe_extract_path(base, member.filename)
-                mode = (member.external_attr >> 16) & 0o170000
-                if mode == 0o120000:
-                    raise PrebuiltFallback(
-                        f"zip archive contained a symlink entry: {member.filename}"
-                    )
-                if member.is_dir():
-                    target.mkdir(parents = True, exist_ok = True)
-                    continue
-                target.parent.mkdir(parents = True, exist_ok = True)
-                with archive.open(member, "r") as src, target.open("wb") as dst:
-                    shutil.copyfileobj(src, dst)
-
-    def extract_tar_safely(source: Path, base: Path) -> None:
-        pending_links: list[tuple[tarfile.TarInfo, Path]] = []
-        archive_names: set[str] = set()
-        with tarfile.open(source, "r:gz") as archive:
-            for member in archive.getmembers():
-                archive_names.add(member.name)
-                target = safe_extract_path(base, member.name)
-                if member.isdir():
-                    target.mkdir(parents = True, exist_ok = True)
-                    continue
-                if member.islnk() or member.issym():
-                    pending_links.append((member, target))
-                    continue
-                if not member.isfile():
-                    raise PrebuiltFallback(
-                        f"tar archive contained an unsupported entry: {member.name}"
-                    )
-                target.parent.mkdir(parents = True, exist_ok = True)
-                extracted = archive.extractfile(member)
-                if extracted is None:
-                    raise PrebuiltFallback(f"tar archive entry could not be read: {member.name}")
-                with extracted, target.open("wb") as dst:
-                    shutil.copyfileobj(extracted, dst)
-
-        unresolved = list(pending_links)
-        while unresolved:
-            next_round: list[tuple[tarfile.TarInfo, Path]] = []
-            progressed = False
-            for member, target in unresolved:
-                normalized_link, resolved_target = safe_link_target(
-                    base, member.name, member.linkname, target, archive_names
-                )
-                if not resolved_target.exists() and not resolved_target.is_symlink():
-                    next_round.append((member, target))
-                    continue
-                if resolved_target.is_dir():
-                    raise PrebuiltFallback(
-                        f"archive link targeted a directory: {member.name} -> {member.linkname}"
-                    )
-
-                target.parent.mkdir(parents = True, exist_ok = True)
-                if target.exists() or target.is_symlink():
-                    target.unlink()
-
-                if member.issym():
-                    target.symlink_to(normalized_link)
-                else:
-                    shutil.copy2(resolved_target, target)
-                progressed = True
-
-            if not progressed:
-                details = ", ".join(
-                    f"{member.name} -> {member.linkname}" for member, _ in next_round
-                )
-                raise PrebuiltFallback(f"tar archive contained unresolved link entries: {details}")
-            unresolved = next_round
-
-    destination.mkdir(parents = True, exist_ok = True)
-    if archive_path.name.endswith(".zip"):
-        extract_zip_safely(archive_path, destination)
-        return
-    if archive_path.name.endswith(".tar.gz"):
-        extract_tar_safely(archive_path, destination)
-        return
-    raise PrebuiltFallback(f"unsupported archive format: {archive_path.name}")
+extract_archive = _core.extract_archive
 
 
 def copy_globs(
@@ -4778,83 +3820,8 @@ def metadata_patterns_for_choice(choice: AssetChoice) -> list[str]:
     return patterns
 
 
-@contextmanager
-def install_lock(lock_path: Path) -> Iterator[None]:
-    lock_path.parent.mkdir(parents = True, exist_ok = True)
-
-    if FileLock is None:
-        # Fallback: exclusive file creation as a simple lock.
-        # Write our PID so stale locks from crashed processes can be detected.
-        fd: int | None = None
-        deadline = time.monotonic() + INSTALL_LOCK_TIMEOUT_SECONDS
-        while True:
-            try:
-                fd = os.open(str(lock_path), os.O_CREAT | os.O_EXCL | os.O_RDWR)
-                try:
-                    os.write(fd, f"{os.getpid()}\n".encode())
-                    os.fsync(fd)
-                except Exception:
-                    os.close(fd)
-                    fd = None
-                    lock_path.unlink(missing_ok = True)
-                    raise
-                break
-            except FileExistsError:
-                # Check if the holder process is still alive
-                stale = False
-                try:
-                    raw = lock_path.read_text().strip()
-                except FileNotFoundError:
-                    # Lock vanished between our open attempt and read -- retry
-                    continue
-                if not raw:
-                    # File exists but PID not yet written -- another process
-                    # just created it. Wait briefly for the write to land.
-                    if time.monotonic() >= deadline:
-                        raise BusyInstallConflict(
-                            f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
-                        )
-                    time.sleep(0.1)
-                    continue
-                try:
-                    holder_pid = int(raw)
-                    os.kill(holder_pid, 0)  # signal 0 = existence check
-                except ValueError:
-                    # PID unreadable (corrupted file)
-                    stale = True
-                except ProcessLookupError:
-                    # Process is dead
-                    stale = True
-                except PermissionError:
-                    # Process is alive but owned by another user -- not stale
-                    pass
-                if stale:
-                    lock_path.unlink(missing_ok = True)
-                    continue
-                if time.monotonic() >= deadline:
-                    raise BusyInstallConflict(
-                        f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
-                    )
-                time.sleep(0.5)
-        try:
-            yield
-        finally:
-            if fd is not None:
-                os.close(fd)
-            lock_path.unlink(missing_ok = True)
-        return
-
-    try:
-        with FileLock(lock_path, timeout = INSTALL_LOCK_TIMEOUT_SECONDS):
-            yield
-    except FileLockTimeout as exc:
-        raise BusyInstallConflict(
-            f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
-        ) from exc
-
-
-def install_lock_path(install_dir: Path) -> Path:
-    return install_dir.parent / f".{install_dir.name}.install.lock"
+install_lock = _core.install_lock
+install_lock_path = _core.install_lock_path
 
 
 def install_staging_root(install_dir: Path) -> Path:
@@ -5441,18 +4408,7 @@ _CPU_TYPE_X86_64 = 0x01000007
 _CPU_TYPE_ARM64 = 0x0100000C
 
 
-def parse_macos_version(value: str | None) -> tuple[int, int] | None:
-    """Parse a macOS product version string into (major, minor).
-
-    Handles "14.7.1", "15.5", "26.0" and bare "26". Returns None when the
-    value is empty or cannot be parsed (callers then defer to runtime
-    validation rather than rejecting every prebuilt)."""
-    if not value:
-        return None
-    match = re.match(r"\s*(\d+)(?:\.(\d+))?", str(value))
-    if not match:
-        return None
-    return int(match.group(1)), int(match.group(2) or 0)
+parse_macos_version = _core.parse_macos_version
 
 
 def host_supports_macos_minos(host: HostInfo, minos: tuple[int, int] | None) -> bool:
@@ -5717,6 +4673,50 @@ def _wsl_system_rocm_lib_dirs() -> list[str]:
     return out
 
 
+def _bundled_hip_present(binary_dir: str) -> bool:
+    if not binary_dir:
+        return False
+    try:
+        # Glob the version suffix (libggml-hip.so, .so.0, .so.0.11.1) the same
+        # way the installer's runtime health check matches libggml-hip.so*.
+        return any(Path(str(binary_dir)).glob("libggml-hip.so*"))
+    except OSError:
+        return False
+
+
+def _native_linux_system_rocm_lib_dirs(binary_dir: str = "") -> list[str]:
+    # UNSLOTH_LLAMA_NO_SYSTEM_ROCM=1 keeps the bundled runtime (opt-out).
+    if os.environ.get("UNSLOTH_LLAMA_NO_SYSTEM_ROCM") == "1":
+        return []
+    if sys.platform != "linux" or os.path.exists("/dev/dxg"):
+        return []
+    if not os.path.exists("/dev/kfd"):
+        return []
+    if not _bundled_hip_present(binary_dir):
+        return []
+    # Env-configured ROCm root first; /opt/rocm only as a fallback so a stale
+    # /opt/rocm doesn't shadow the driver-matching install these vars point at.
+    candidates = []
+    for var in ("HIP_PATH", "HIP_PATH_57", "ROCM_PATH"):
+        val = os.environ.get(var)
+        if val:
+            candidates.append(val)
+    candidates.append("/opt/rocm")
+    out: list[str] = []
+    seen: set[str] = set()
+    for base in candidates:
+        for lib_sub in ("lib", "lib64"):
+            d = os.path.join(base, lib_sub)
+            if d in seen:
+                continue
+            seen.add(d)
+            if os.path.exists(os.path.join(d, "libhsa-runtime64.so")) or os.path.exists(
+                os.path.join(d, "libhsa-runtime64.so.1")
+            ):
+                out.append(d)
+    return out
+
+
 # Secrets a downloaded llama.cpp binary never needs; keep them out of binary_env().
 # The installer's own API calls read os.environ directly, so auth is unaffected.
 _SECRET_ENV_EXACT_NAMES = frozenset(
@@ -5877,6 +4877,11 @@ def binary_env(
         if _wsl_rocm:
             ld_dirs = [*_wsl_rocm, *ld_dirs]
             env.setdefault("HSA_ENABLE_DXG_DETECTION", "1")
+        # Native Linux AMD: system ROCm libs before the bundle's bundled HIP
+        # runtime, which can be incompatible with the host amdkfd driver.
+        _native_rocm = _native_linux_system_rocm_lib_dirs(str(binary_path.parent))
+        if _native_rocm:
+            ld_dirs = [*_native_rocm, *ld_dirs]
         existing = [part for part in env.get("LD_LIBRARY_PATH", "").split(os.pathsep) if part]
         env["LD_LIBRARY_PATH"] = os.pathsep.join(dedupe_existing_dirs([*ld_dirs, *existing]))
     elif host.is_macos:
@@ -6574,6 +5579,52 @@ def load_prebuilt_metadata(install_dir: Path) -> dict[str, Any] | None:
     return payload
 
 
+def default_managed_llama_dir() -> Path:
+    """The managed llama.cpp install root, mirroring setup.sh and the updater:
+    the UNSLOTH_LLAMA_CPP_PATH override, else <custom studio home>/llama.cpp,
+    else the legacy ~/.unsloth/llama.cpp."""
+    override = (os.environ.get("UNSLOTH_LLAMA_CPP_PATH") or "").strip()
+    if override:
+        return Path(override).expanduser()
+    home = (os.environ.get("UNSLOTH_STUDIO_HOME") or os.environ.get("STUDIO_HOME") or "").strip()
+    if home:
+        root = Path(home).expanduser()
+        legacy_studio = Path.home() / ".unsloth" / "studio"
+        try:
+            is_legacy = root.resolve() == legacy_studio.resolve()
+        except (OSError, ValueError):
+            is_legacy = root == legacy_studio
+        if not is_legacy:
+            return root / "llama.cpp"
+    return Path.home() / ".unsloth" / "llama.cpp"
+
+
+def installed_llama_runtime(install_dir: Path | None = None) -> tuple[Path, str, str] | None:
+    """The completed managed llama.cpp prebuilt install, or None.
+
+    Returns (runtime bin dir holding the ggml libraries, installed release tag,
+    bundle profile). install_whisper_prebuilt.py reads this to pair slim whisper
+    bundles with the ggml runtime the llama install already provides; tests pass
+    an explicit ``install_dir``.
+    """
+    root = install_dir if install_dir is not None else default_managed_llama_dir()
+    metadata = load_prebuilt_metadata(root)
+    if metadata is None:
+        return None
+    release_tag = metadata.get("release_tag")
+    if not isinstance(release_tag, str) or not release_tag:
+        return None
+    # Same layout install_runtime_dir() derives; a marker on disk always
+    # belongs to this host, so the running OS picks the variant.
+    bin_dir = root / "build" / "bin"
+    if os.name == "nt":
+        bin_dir = bin_dir / "Release"
+    if not bin_dir.is_dir():
+        return None
+    profile = metadata.get("bundle_profile")
+    return bin_dir, release_tag, profile if isinstance(profile, str) else ""
+
+
 def runtime_payload_health_groups(choice: AssetChoice) -> list[list[str]]:
     if choice.install_kind in {"linux-cpu", "linux-arm64"}:
         return [
diff --git a/studio/install_python_stack.py b/studio/install_python_stack.py
index 9921b83543..a29ba0d7e5 100644
--- a/studio/install_python_stack.py
+++ b/studio/install_python_stack.py
@@ -73,6 +73,27 @@ _ROCM_TORCH_INDEX: dict[tuple[int, int], str] = {
     (6, 0): "rocm6.0",
 }
 
+
+def _generic_pytorch_rocm_tag(ver: tuple[int, int]) -> str | None:
+    """Newest download.pytorch.org rocmX.Y tag for a host ROCm version."""
+    return next(
+        (t for (maj, mn), t in sorted(_ROCM_TORCH_INDEX.items(), reverse = True) if ver >= (maj, mn)),
+        None,
+    )
+
+
+_ROCM_ARCH_INDEX_FLOOR = (7, 13)  # AMD per-arch index ships torch 2.11+rocm7.13
+
+
+def _strix_needs_amd_arch_index(ver: tuple[int, int]) -> bool:
+    """True when Strix's generic pytorch.org index sits below the AMD arch floor
+    (7.13), so gfx1150/1151 must use repo.amd.com's per-arch wheels. Mirrors
+    install.sh _rocm_leaf_below: reroute any generic rocm index (6.x/7.0/7.2 and a
+    future 7.3+), never one at/above the floor."""
+    key = next((k for k in sorted(_ROCM_TORCH_INDEX, reverse = True) if ver >= k), None)
+    return key is not None and key < _ROCM_ARCH_INDEX_FLOOR
+
+
 # AMD per-arch leaves needing the torch 2.11 floor (the _grouped_mm <2.11 bug).
 # Mirrors *FloorMap in install.ps1 / setup.ps1; other arches ship <2.11 and stay bare.
 _ROCM_GFX_TORCH211_LEAVES: frozenset[str] = frozenset({"gfx120x-all", "gfx1151", "gfx1150"})
@@ -352,6 +373,13 @@ _GFX_TO_AMD_INDEX_ARCH: dict[str, str] = {
     "gfx1102": "gfx110X-all",  # RDNA 3
     "gfx1101": "gfx110X-all",
     "gfx1100": "gfx110X-all",
+    "gfx1036": "gfx103X-all",
+    "gfx1035": "gfx103X-all",  # RDNA 2 (RX 6000)
+    "gfx1034": "gfx103X-all",
+    "gfx1033": "gfx103X-all",
+    "gfx1032": "gfx103X-all",
+    "gfx1031": "gfx103X-all",
+    "gfx1030": "gfx103X-all",
     "gfx90a": "gfx90a",
     "gfx908": "gfx908",  # MI200/MI100
 }
@@ -712,8 +740,8 @@ def _detect_windows_gfx_arch() -> str | None:
 _WIN_GPU_NAME_ARCH_TABLE: "list[tuple[str, str]]" = [
     (r"9070 XT|9080", "gfx1201"),  # RDNA 4 (Radeon RX 9070 XT / 9080)
     (r"9070|9060", "gfx1200"),  # RDNA 4 (Radeon RX 9070 / 9060)
-    # RDNA 3.5 (Strix Halo: Radeon 8060S/8050S/8040S iGPU, Ryzen AI Max+)
-    (r"8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max", "gfx1151"),
+    # RDNA 3.5 (Strix Halo + Gorgon Halo: Radeon 8065S/8060S/8050S/8040S iGPU, Ryzen AI Max / Max+)
+    (r"8065S|8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max", "gfx1151"),
     # RDNA 3.5 (Strix/Krackan Point: Radeon 890M/880M iGPU, Ryzen AI 9 HX 370/375)
     (
         r"890M|880M|860M|840M|Strix Point|Krackan|HX 37[05]|AI 9 HX|AI 9 36[05]"
@@ -741,6 +769,142 @@ def _gfx_arch_from_gpu_name(name: str) -> "str | None":
     return None
 
 
+def _linux_amd_gfx_from_cpuinfo() -> "str | None":
+    """Infer gfx arch from /proc/cpuinfo on integrated AMD APUs (Strix Halo/Point)."""
+    try:
+        text = Path("/proc/cpuinfo").read_text(encoding = "utf-8", errors = "replace")
+    except OSError:
+        return None
+    if re.search(r"Ryzen AI Max|Radeon 80[0-9][05]S|Strix Halo", text, re.IGNORECASE):
+        return "gfx1151"
+    if re.search(
+        r"890M|880M|860M|840M|Strix Point|Krackan|HX 37[05]|AI 9 HX|AI 9 36[05]"
+        r"|AI 7 35[05]|AI 5 34[05]|AI 7 PRO 35|AI 5 33",
+        text,
+        re.IGNORECASE,
+    ):
+        return "gfx1150"
+    return None
+
+
+def _linux_amd_gfx_from_lspci() -> "str | None":
+    """First AMD display-class lspci line mapping to a known gfx arch. A non-AMD
+    controller can enumerate first (Intel/ASPEED before an AMD dGPU), so scan
+    them all. The vendor guard is case-SENSITIVE: a -i "ATI" would match
+    "CorporATIon" on every Intel/NVIDIA line. Whole-line matching also survives
+    the 0000: PCI domain prefix."""
+    lspci = shutil.which("lspci")
+    if not lspci:
+        return None
+    try:
+        result = subprocess.run(
+            [lspci, "-nn"],
+            stdout = subprocess.PIPE,
+            stderr = subprocess.DEVNULL,
+            text = True,
+            timeout = 10,
+        )
+    except Exception:
+        return None
+    if result.returncode != 0:
+        return None
+    for line in result.stdout.splitlines():
+        if not re.search(r"VGA compatible controller|3D controller|Display controller", line, re.I):
+            continue
+        if not re.search(r"AMD|ATI", line):
+            continue
+        arch = _gfx_arch_from_gpu_name(line)
+        if arch:
+            return arch
+    return None
+
+
+def _is_wsl() -> bool:
+    """True on WSL, where the AMD GPU is reached via /dev/dxg (not /dev/kfd)."""
+    if os.path.exists("/dev/dxg"):
+        return True
+    try:
+        with open("/proc/version", encoding = "utf-8", errors = "replace") as fh:
+            return "microsoft" in fh.read().lower()
+    except OSError:
+        return False
+
+
+def _wsl_rocm_runtime_present() -> bool:
+    """librocdxg (the WSL ROCDXG bridge that lets HIP reach the GPU over /dev/dxg)
+    under a ROCm lib dir. Its absence marks a WSL box whose ROCm was never set up."""
+    dirs = ["/opt/rocm/lib", "/opt/rocm/lib64"]
+    dirs += glob.glob("/opt/rocm-*/lib") + glob.glob("/opt/rocm-*/lib64")
+    return any(
+        os.path.exists(os.path.join(d, so))
+        for d in dirs
+        for so in ("librocdxg.so", "librocdxg.so.1")
+    )
+
+
+def _linux_amd_display_device_present() -> bool:
+    """Any AMD (vendor 0x1002) PCI display-class (0x03*) device in sysfs.
+    /proc/cpuinfo leaks the HOST CPU model into VMs/containers that received no
+    AMD GPU, so the CPU-model text alone is not GPU evidence; this is the
+    device-level check (mirrors install.sh _amd_gpu_present_via_pci)."""
+    try:
+        for dev in Path("/sys/bus/pci/devices").iterdir():
+            try:
+                if (dev / "vendor").read_text().strip() != "0x1002":
+                    continue
+                if (dev / "class").read_text().strip().startswith("0x03"):
+                    return True
+            except OSError:
+                continue
+    except OSError:
+        pass
+    return False
+
+
+def _infer_linux_amd_gfx_arch() -> "str | None":
+    """Infer gfx when ROCm runtime is absent but the host is a known AMD arch (unslothai#7301)."""
+    override = (os.environ.get("UNSLOTH_ROCM_GFX_ARCH") or "").strip().lower()
+    if override:
+        return override
+    if _is_wsl():
+        # cpuinfo/lspci see the host APU even on a WSL box whose ROCDXG runtime
+        # was never bootstrapped; inferring there would install per-arch ROCm
+        # wheels into an env that still can't expose the GPU. Skip unless that
+        # runtime is present -- WSL enumerates no PCI display device, so
+        # /dev/dxg + librocdxg IS the GPU evidence there.
+        if not _wsl_rocm_runtime_present():
+            return None
+    elif not _linux_amd_display_device_present():
+        # Native Linux: a VM/container on a Strix host still shows the host CPU
+        # model in /proc/cpuinfo while receiving no AMD GPU, so require an AMD
+        # display device before trusting the CPU-model inference. The lspci
+        # fallback reads the same PCI space and would find nothing here either.
+        return None
+    cpu_gfx = _linux_amd_gfx_from_cpuinfo()
+    if cpu_gfx:
+        return cpu_gfx
+    return _linux_amd_gfx_from_lspci()
+
+
+def _amd_arch_index_url(gfx_arch: str | None) -> str | None:
+    """Return the AMD per-arch pip index URL for a gfx arch (Linux + Windows).
+
+    Windows honors UNSLOTH_ROCM_WINDOWS_MIRROR (via _windows_rocm_index_url);
+    Linux honors UNSLOTH_AMD_ROCM_MIRROR -- the same var install.sh uses -- so a
+    mirrored/air-gapped Linux repair reaches the index install.sh chose rather
+    than falling back to repo.amd.com. Both default to repo.amd.com when unset.
+    """
+    if IS_WINDOWS:
+        return _windows_rocm_index_url(gfx_arch)
+    arch_family = _GFX_TO_AMD_INDEX_ARCH.get(gfx_arch or "")
+    if arch_family is None:
+        return None
+    base = (os.environ.get("UNSLOTH_AMD_ROCM_MIRROR") or "https://repo.amd.com/rocm/whl").rstrip(
+        "/"
+    )
+    return f"{base}/{arch_family}/"
+
+
 def _windows_rocm_index_url(gfx_arch: str | None) -> str | None:
     """Return the AMD pip index URL for the given GPU arch, or None if unsupported."""
     arch_family = _GFX_TO_AMD_INDEX_ARCH.get(gfx_arch or "")
@@ -1619,22 +1783,24 @@ def _ensure_rocm_torch() -> None:
     # An explicit ROCm pin commits to ROCm wheels regardless of the visible GPU (headless / CI).
     # Mirror _ensure_cuda_torch: skip the NVIDIA/no-AMD/unreadable gates.
     _rocm_pin = _explicit_rocm_torch_index_url()
+    _inferred_linux_gfx = (
+        _infer_linux_amd_gfx_arch() if (_rocm_pin is None and not IS_WINDOWS) else None
+    )
     if _rocm_pin is None:
         # NVIDIA takes precedence on mixed hosts (only if a GPU is usable).
         if _has_usable_nvidia_gpu():
             return
         # _has_rocm_gpu() (rocminfo / amd-smi rows) is the authoritative AMD-host signal;
         # the old /opt/rocm-or-hipcc gate broke runtime-only ROCm installs.
-        if not _has_rocm_gpu():
+        if not _has_rocm_gpu() and not _inferred_linux_gfx:
             return  # no AMD GPU visible
 
     ver = _detect_rocm_version()
     if ver is None:
-        if _rocm_pin is None:
+        if _rocm_pin is None and not _inferred_linux_gfx:
             print("   ROCm detected but version unreadable -- skipping torch reinstall")
             return
-        # Explicit pin: the pinned leaf drives the install, so an unreadable host version
-        # is fine (sentinel keeps ver comparisons defined).
+        # Explicit pin or inferred gfx: the index drives the install.
         ver = (0, 0)
 
     # Probe whether torch links against HIP, capturing the installed ROCm tag for pin-mismatch
@@ -1684,13 +1850,51 @@ def _ensure_rocm_torch() -> None:
 
     rocm_torch_ready = has_hip_torch and not _rocm_pin_mismatch
 
-    # Strix Halo / Point (gfx1151 / gfx1150) segfault under ROCm 7.1 in torch._grouped_mm;
-    # AMD's per-gfx repo ships 2.11.0+rocm7.13.0 with the fix, so route those hosts there
-    # (mirrors install.sh). On mixed hosts, reroute only when HIP's runtime GPU is the Strix one.
+    # Inferred-gfx path: ROCm runtime missing but install.sh would route to AMD wheels.
+    # Gated on the runtime NOT enumerating a GPU: when it can, the runtime-visible
+    # arch (Strix override / generic below) decides, not cpuinfo -- a mixed Strix
+    # APU + dGPU box with HIP_VISIBLE_DEVICES on the dGPU must not get APU wheels.
+    # An explicit UNSLOTH_ROCM_GFX_ARCH is exempt from that runtime gate (mirrors
+    # install.sh): a visible GPU with an unreadable/unsupported ROCm version must
+    # not silently discard the user's named arch and leave CPU torch in place.
+    _gfx_override_env = (os.environ.get("UNSLOTH_ROCM_GFX_ARCH") or "").strip().lower()
+    if (
+        _inferred_linux_gfx
+        and not has_hip_torch
+        and _rocm_pin is None
+        and (_gfx_override_env or not _has_rocm_gpu())
+    ):
+        index_url = _amd_arch_index_url(_inferred_linux_gfx)
+        if index_url is not None:
+            _torch_pkg, _vision_pkg, _audio_pkg = _WINDOWS_ROCM_TORCH_PKG_SPECS.get(
+                _inferred_linux_gfx, ("torch", "torchvision", "torchaudio")
+            )
+            print(
+                f"\n   {_inferred_linux_gfx} inferred (ROCm runtime not visible) -- "
+                f"installing torch from {_strip_index_url_credentials(index_url)}\n"
+                f"   AMD wheels bundle their own ROCm runtime; install the kernel stack "
+                f"for native GPU compute.\n"
+            )
+            pip_install(
+                f"ROCm torch (inferred {_inferred_linux_gfx})",
+                "--force-reinstall",
+                "--no-cache-dir",
+                _torch_pkg,
+                _vision_pkg,
+                _audio_pkg,
+                "--index-url",
+                index_url,
+                constrain = False,
+            )
+            rocm_torch_ready = True
+
+    # Strix Halo / Point (gfx1151 / gfx1150) need torch from AMD's per-gfx index
+    # (2.11+rocm7.13); any generic pytorch.org rocm index lacks the fixes (ROCm 7.1
+    # segfaults in _grouped_mm). See _strix_needs_amd_arch_index for the floor gate.
     _strix_override_url: "str | None" = None
     _strix_override_pkgs: "tuple[str, str, str] | None" = None
     # An explicit ROCm pin is authoritative: never auto-reroute it.
-    if ver < (7, 2) and _explicit_rocm_torch_index_url() is None:
+    if _strix_needs_amd_arch_index(ver) and _explicit_rocm_torch_index_url() is None:
         gfx_codes = _detect_amd_gfx_codes()
         _strix_gfx = {"gfx1151", "gfx1150"}
         _detected_strix = _strix_gfx.intersection(gfx_codes)
@@ -1714,10 +1918,10 @@ def _ensure_rocm_torch() -> None:
                 print(
                     f"\n   {_selected_gfx} (AMD Strix) is the runtime target with ROCm "
                     f"{ver[0]}.{ver[1]}.\n"
-                    f"   ROCm 7.1 has a known _grouped_mm segfault on this GPU;\n"
-                    f"   routing torch install to AMD's arch-specific index\n"
+                    f"   Routing torch install to AMD's arch-specific index\n"
                     f"   ({_strix_override_url}) which serves torch 2.11.0+rocm7.13.0\n"
-                    f"   with the upstream fix.\n"
+                    f"   with AMD's gfx1150/gfx1151 fixes (more reliable than the generic\n"
+                    f"   pytorch.org rocm7.2 index on ROCm 7.3+ hosts).\n"
                 )
             else:
                 _gfx_str = ", ".join(sorted(_detected_strix))
@@ -1733,7 +1937,7 @@ def _ensure_rocm_torch() -> None:
         index_url = _strix_override_url
         _torch_pkg, _vision_pkg, _audio_pkg = _strix_override_pkgs
         print(
-            f"   Strix ROCm 7.1 override -- installing torch from "
+            f"   Strix arch-specific override -- installing torch from "
             f"{_strip_index_url_credentials(index_url)}"
         )
         pip_install(
@@ -1748,8 +1952,11 @@ def _ensure_rocm_torch() -> None:
             constrain = False,
         )
         rocm_torch_ready = True
-    elif not has_hip_torch or _rocm_pin_mismatch:
+    elif not rocm_torch_ready:
         # Reinstall when torch is not ROCm yet, OR a ROCm build's family differs from a pin.
+        # Gate on rocm_torch_ready (not has_hip_torch alone) so a successful inferred-gfx
+        # install above is not overwritten by the generic pytorch.org/rocmX.Y path -- that
+        # would undo the fresh-ROCm/no-/dev/kfd repair this path exists for (Codex P1 #7305).
         # Honour a ROCm pin verbatim; else pick the newest wheel tag <= host.
         _override_idx = _explicit_rocm_torch_index_url()
         if _override_idx is not None:
diff --git a/studio/install_whisper_prebuilt.py b/studio/install_whisper_prebuilt.py
new file mode 100644
index 0000000000..1c81ad6105
--- /dev/null
+++ b/studio/install_whisper_prebuilt.py
@@ -0,0 +1,1377 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Cross-platform whisper.cpp (whisper-server) prebuilt installer for Unsloth Studio.
+
+Downloads a per-platform whisper.cpp bundle published by the Unsloth fork
+(``unslothai/whisper.cpp``) into an isolated ``<UNSLOTH_HOME>/whisper.cpp``,
+never a system whisper.cpp. The canonical install target matches the
+sidecar/build-script contract in ``stt_ggml_sidecar.py``:
+
+    <install-dir>/build/bin/whisper-server              (Unix)
+    <install-dir>/build/bin/Release/whisper-server.exe  (Windows)
+
+Bundles are dynamically linked: ``whisper-server`` needs ``libwhisper``,
+``libggml*`` and any GPU backend libraries. The binaries carry ``RUNPATH=$ORIGIN``
+so the installer co-locates every shared library from the archive into the same
+``build/bin`` directory and marks the server executable on Unix.
+
+Archives are verified against the release's own ``whisper-prebuilt-sha256.json``
+checksum index (same model as ``install_llama_prebuilt.py``). An asset absent
+from the index, or a release without it, fails closed (setup reports the prebuilt
+unavailable and local dictation uses Transformers STT). Being a same-origin
+checksum it proves integrity, not authenticity; pair the release with GitHub
+artifact attestations for provenance.
+
+Release resolution prefers the download host (``github.com/<repo>/releases/...``),
+fetching the manifest + checksum index with zero ``api.github.com`` calls (that
+API is rate-limited to 60 req/hour unauthenticated); the GitHub API is only a
+fallback on a 404 / malformed asset.
+
+The whole component-agnostic flow (verified downloads, safe extraction, the
+install lock, release resolution, checksum-index handling, the install driver,
+the resolve probe) lives in ``prebuilt_core.py`` and is shared with
+``install_llama_prebuilt.py``. This module keeps only the whisper specifics: the
+host mapping, install-tree layout, slim pairing with the installed llama.cpp ggml
+runtime, the pinned-release CPU escape hatch, the marker filename, and the CLI.
+Every retained public name is a thin wrapper tests can monkeypatch so the core
+observes the patch.
+
+Selection is slim-only for current releases (v1.9.1-unsloth.2+): every published
+bundle is a slim (ggml-less) whisper paired to the llama.cpp prebuilt, which
+provides all ggml backends. The per-accelerator fat selection chain was deleted
+with the fat bundles; the one legacy shape still honored is the published fat CPU
+bundle of an explicitly pinned pre-slim release.
+
+Mirrors ``install_node_prebuilt.py`` / ``install_llama_prebuilt.py``. Exit codes:
+0 success (or already current), 1 error, 2 incompatible paired release, 3 busy. A re-run
+that already matches logs "already matches" and returns 0 without downloading
+(the scripts grep it).
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import re
+import shutil
+import subprocess
+import sys
+from dataclasses import dataclass, replace
+from pathlib import Path
+from typing import Any
+
+# Put studio/ on sys.path so install_llama_prebuilt / prebuilt_core resolve
+# whether run as a script (from any cwd) or imported by the tests.
+_STUDIO_DIR = os.path.dirname(os.path.abspath(__file__))
+if _STUDIO_DIR not in sys.path:
+    sys.path.insert(0, _STUDIO_DIR)
+
+import install_llama_prebuilt as llama  # noqa: E402
+import prebuilt_core as core  # noqa: E402
+
+# Shared machinery re-exported as module globals; the wrappers below resolve
+# these by bare name at call time so tests can monkeypatch them here.
+PrebuiltFallback = core.PrebuiltFallback
+BusyInstallConflict = core.BusyInstallConflict
+auth_headers = llama.auth_headers
+download_bytes = llama.download_bytes
+download_file = llama.download_file
+fetch_json = llama.fetch_json
+sha256_file = core.sha256_file
+_URL_OPENER = core._URL_OPENER
+install_lock = core.install_lock
+install_lock_path = core.install_lock_path
+parse_macos_version = core.parse_macos_version
+release_asset_map = core.release_asset_map
+release_asset_download_url = core.release_asset_download_url
+compute_install_fingerprint = core.compute_install_fingerprint
+artifact_coverage = core.artifact_coverage
+emit_resolver_output = core.emit_resolver_output
+_valid_sha256 = core.valid_sha256
+_swap_into_place = core.swap_into_place
+InstallSelection = core.InstallSelection
+ReleaseBundle = core.ReleaseBundle
+llama_detect_host = llama.detect_host
+installed_llama_runtime = llama.installed_llama_runtime
+
+# Late-binding seam for prebuilt_core: name lookups hit this module's globals
+# first (so monkeypatches apply), then the core defaults.
+_OPS = core.ModuleOps(globals())
+
+
+# Resolver mode keeps stdout to the JSON payload only (setup.sh parses it);
+# main() flips this on for the install path so setup surfaces progress.
+_LOG_TO_STDOUT = False
+
+
+class ReleaseCompatibilityError(PrebuiltFallback):
+    """A valid slim release cannot pair with this host's installed runtime."""
+
+
+def log(message: str) -> None:
+    print(f"[whisper-prebuilt] {message}", file = sys.stdout if _LOG_TO_STDOUT else sys.stderr)
+
+
+EXIT_SUCCESS = 0
+EXIT_ERROR = 1
+EXIT_INCOMPATIBLE = 2
+EXIT_BUSY = 3
+
+COMPONENT = "whisper.cpp"
+SCHEMA_VERSION = 1
+USER_AGENT = "unsloth-studio-whisper-prebuilt"
+
+DEFAULT_PUBLISHED_REPO = "unslothai/whisper.cpp"
+# Release assets published by the fork's prebuilt CI.
+MANIFEST_ASSET_NAME = "whisper-prebuilt-manifest.json"
+SHA256_ASSET_NAME = "whisper-prebuilt-sha256.json"
+
+METADATA_FILENAME = "UNSLOTH_WHISPER_PREBUILT_INFO.json"
+
+# Backends the installer can select: accelerator identities for the slim pairing
+# (which llama ggml module must exist) and the marker. Only "cpu" can match a fat
+# artifact (the pinned pre-slim escape hatch).
+SUPPORTED_BACKENDS = ("cpu", "cuda", "metal", "vulkan", "rocm")
+
+# Fallback the core applies on a GPU-selection miss: retry with cpu so the slim
+# bundle can pair via the llama cpu modules, or -- on a pinned pre-slim release --
+# the published fat CPU bundle installs. A miss is an install error unless the
+# valid slim release specifically requires a different paired llama release.
+FALLBACK_BACKEND = "cpu"
+
+# Backends whose slim (ggml-less) whisper bundle can ride the installed llama.cpp
+# prebuilt's ggml runtime. All are eligible: the next whisper release ships only
+# slim bundles, so cpu and metal pair like the GPUs do.
+SLIM_ELIGIBLE_BACKENDS = ("cpu", "cuda", "metal", "rocm", "vulkan")
+
+# ggml backend module the llama bin dir must provide per accelerator, keyed by
+# asset os token, following llama's bundle layout / health globs. A backend with
+# no glob for the host os (metal off macOS) is never slim there. llama's x64 cpu
+# bundles ship per-arch libggml-cpu-<variant> modules, macOS a single
+# libggml-cpu; the cpu globs cover both.
+SLIM_BACKEND_MODULE_GLOBS = {
+    "cpu": {
+        "linux": "libggml-cpu*.so*",
+        "windows": "ggml-cpu*.dll",
+        "macos": "libggml-cpu*.dylib",
+    },
+    "cuda": {"linux": "libggml-cuda.so*", "windows": "ggml-cuda.dll"},
+    "metal": {"macos": "libggml-metal*.dylib"},
+    "rocm": {"linux": "libggml-hip.so*", "windows": "*hip*.dll"},
+    "vulkan": {"linux": "libggml-vulkan.so*", "windows": "ggml-vulkan.dll"},
+}
+
+# Everything the slim wiring mirrors from the llama bin dir: the core ggml
+# sonames plus every dlopen'd backend module (CPU variants included). libggml*
+# matches .so and .dylib alike; ggml*.dll covers Windows. libomp*.dll rides along
+# because llama's clang-built windows-arm64 ggml-base.dll imports
+# libomp140.aarch64.dll, shipped in the llama bundle but never a system DLL, so
+# the loader needs it next to whisper-server.exe (MSVC x64 uses System32
+# vcomp140.dll; Linux ggml needs system libgomp.so.1, which llama already requires).
+SLIM_GGML_LIBRARY_GLOBS = ("libggml*", "ggml*.dll", "libomp*.dll")
+SLIM_ROCM_LIBRARY_GLOBS = (
+    "libamd*.so*",
+    "libhip*.so*",
+    "libhsa*.so*",
+    "libroc*.so*",
+)
+SLIM_ROCM_RUNTIME_DIRS = ("hipblaslt", "rocblas")
+SLIM_RUNTIME_WIRING_VERSION = 2
+
+INSTALL_STAGING_ROOT_NAME = ".staging"
+
+# Master switch for the staged runtime smoke test (start whisper-server + a tiny
+# transcription) before the atomic activate. Off by default so a bundle whose GPU
+# forward pass JIT-compiles kernels does not stall every install; the check and
+# its CPU-asset retry stay intact -- set True to re-enable.
+_RUN_STAGED_PREBUILT_VALIDATION = False
+
+
+# ── Host detection (probes shared with install_llama_prebuilt) ──
+@dataclass(frozen = True)
+class HostInfo:
+    system: str  # platform.system()
+    machine: str  # lowered platform.machine()
+    whisper_os: str  # asset token: linux | macos | windows
+    whisper_arch: str  # asset token: x64 | arm64
+    archive_ext: str  # .tar.gz | .zip
+    is_windows: bool
+    is_macos: bool
+    is_apple_silicon: bool
+    has_usable_nvidia: bool = False
+    has_rocm: bool = False
+    rocm_gfx: str | None = None
+    # (major, minor) from platform.mac_ver(); None off macOS or if unparseable.
+    # Enforces a macOS artifact's min_os so we never pick a bundle that cannot
+    # load on this OS version.
+    macos_version: tuple[int, int] | None = None
+
+
+def host_from_llama(base: Any) -> HostInfo:
+    """Map install_llama_prebuilt's detected host onto the whisper asset tokens.
+    Raises PrebuiltFallback on an unsupported OS/arch."""
+    system = base.system
+    machine = base.machine.lower()
+    if system == "Linux":
+        whisper_os = "linux"
+    elif system == "Darwin":
+        whisper_os = "macos"
+    elif system == "Windows":
+        whisper_os = "windows"
+    else:
+        raise PrebuiltFallback(f"unsupported operating system for whisper.cpp prebuilt: {system}")
+
+    if machine in {"x86_64", "amd64", "x64"}:
+        whisper_arch = "x64"
+    elif machine in {"arm64", "aarch64"}:
+        whisper_arch = "arm64"
+    else:
+        raise PrebuiltFallback(f"unsupported CPU architecture for whisper.cpp prebuilt: {machine}")
+
+    return HostInfo(
+        system = system,
+        machine = machine,
+        whisper_os = whisper_os,
+        whisper_arch = whisper_arch,
+        archive_ext = ".zip" if base.is_windows else ".tar.gz",
+        is_windows = base.is_windows,
+        is_macos = base.is_macos,
+        is_apple_silicon = base.is_macos and whisper_arch == "arm64",
+        has_usable_nvidia = base.has_usable_nvidia,
+        has_rocm = base.has_rocm,
+        rocm_gfx = base.rocm_gfx_target,
+        macos_version = base.macos_version,
+    )
+
+
+def detect_host() -> HostInfo:
+    return host_from_llama(llama_detect_host())
+
+
+def apply_host_overrides(
+    host: HostInfo,
+    *,
+    has_rocm: bool = False,
+    rocm_gfx: str | None = None,
+    force_cpu: bool = False,
+) -> HostInfo:
+    """Apply CLI overrides (setup forwards hardware hints) onto a detected host."""
+    if force_cpu:
+        return replace(
+            host,
+            has_usable_nvidia = False,
+            has_rocm = False,
+            rocm_gfx = None,
+            is_apple_silicon = False,
+        )
+    updates: dict[str, Any] = {}
+    if has_rocm or rocm_gfx:
+        # --rocm-gfx implies --has-rocm (llama parity); otherwise the host stays on
+        # its CUDA/CPU path and never picks the ROCm bundle. Drop CUDA detection too.
+        updates["has_rocm"] = True
+        updates["has_usable_nvidia"] = False
+    if rocm_gfx:
+        updates["rocm_gfx"] = rocm_gfx
+    return replace(host, **updates) if updates else host
+
+
+def host_platform_tokens(host: HostInfo) -> tuple[str, str]:
+    """Canonical (os, arch) asset tokens the core uses for matching/reporting."""
+    return host.whisper_os, host.whisper_arch
+
+
+# ── Backend selection ──
+def auto_detect_backend(host: HostInfo) -> str:
+    return core.auto_detect_backend(_OPS, host)
+
+
+def resolve_backend(host: HostInfo, requested: str | None, *, cpu_fallback: bool) -> str:
+    return core.resolve_backend(_OPS, host, requested, cpu_fallback = cpu_fallback)
+
+
+# ── Asset naming (pure, unit tested) ──
+def whisper_asset_name(release_tag: str, host: HostInfo, accel: str) -> str:
+    """e.g. whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz.
+
+    `accel` is the asset-filename accelerator token (cpu, metal, cuda12, ...),
+    finer-grained than the coarse backend. An install's authoritative asset name
+    comes from the release manifest; this constructor is for defaults/diagnostics.
+    """
+    tag = release_tag if release_tag.startswith("v") else f"v{release_tag}"
+    return f"whisper-{tag}-{host.whisper_os}-{host.whisper_arch}-{accel}{host.archive_ext}"
+
+
+# ── Manifest (release-side artifact catalogue; generic parser in the core) ──
+def validate_schema_version(payload: dict[str, Any], *, label: str) -> None:
+    core.validate_schema_version(
+        payload, label = label, schema_version = SCHEMA_VERSION, error = PrebuiltFallback
+    )
+
+
+def parse_manifest(payload: Any, *, label: str = MANIFEST_ASSET_NAME) -> dict[str, Any]:
+    return core.parse_manifest(_OPS, payload, label = label)
+
+
+def _macos_min_os_ok(host: HostInfo, min_os: Any) -> bool:
+    return core.macos_min_os_ok(_OPS, host, min_os)
+
+
+def macos_min_os_ok(host: HostInfo, min_os: Any) -> bool:
+    return _macos_min_os_ok(host, min_os)
+
+
+def _artifacts_for_host(
+    manifest: dict[str, Any], host: HostInfo, backend: str
+) -> list[dict[str, Any]]:
+    return core.artifacts_for_host(_OPS, manifest, host, backend)
+
+
+def artifacts_for_host(
+    manifest: dict[str, Any], host: HostInfo, backend: str
+) -> list[dict[str, Any]]:
+    return _artifacts_for_host(manifest, host, backend)
+
+
+# ── Slim selection (paired with the installed llama.cpp ggml runtime) ──
+def slim_pairing_for_artifact(
+    artifact: dict[str, Any], host: HostInfo, backend: str
+) -> tuple[Path, str] | None:
+    """(llama bin dir, llama release tag) when the installed llama runtime can
+    back this slim artifact, else None. Each failed gate logs why; the caller
+    then retries via CPU or reports the prebuilt unavailable."""
+    asset = artifact.get("asset")
+    runtime = installed_llama_runtime()
+    if runtime is None:
+        log(f"slim_selection: {asset} skipped: no managed llama.cpp prebuilt install")
+        return None
+    llama_bin_dir, llama_tag, _profile = runtime
+    requires_tag = artifact.get("requires_llama_tag")
+    if not isinstance(requires_tag, str) or requires_tag != llama_tag:
+        log(
+            f"slim_selection: {asset} skipped: installed llama tag {llama_tag!r} "
+            f"!= required {requires_tag!r}"
+        )
+        return None
+    sonames = artifact.get("requires_ggml_sonames")
+    if not isinstance(sonames, list) or not sonames:
+        log(f"slim_selection: {asset} skipped: manifest lists no requires_ggml_sonames")
+        return None
+    missing = [str(name) for name in sonames if not (llama_bin_dir / str(name)).is_file()]
+    if missing:
+        log(f"slim_selection: {asset} skipped: llama runtime missing {', '.join(missing)}")
+        return None
+    module_glob = SLIM_BACKEND_MODULE_GLOBS.get(backend, {}).get(host.whisper_os)
+    if module_glob is None:
+        log(f"slim_selection: {asset} skipped: no {backend} ggml module on {host.whisper_os}")
+        return None
+    if not any(path.is_file() for path in llama_bin_dir.glob(module_glob)):
+        log(f"slim_selection: {asset} skipped: llama runtime has no {module_glob} module")
+        return None
+    log(f"slim_selection: selected {asset} paired with llama {llama_tag} at {llama_bin_dir}")
+    return llama_bin_dir, llama_tag
+
+
+def select_slim_artifact(
+    manifest: dict[str, Any], host: HostInfo, backend: str
+) -> dict[str, Any] | None:
+    """The paired slim artifact for any backend (cpu and metal included), or None.
+    Slim assets carry backend "slim" so the CPU escape hatch's fat os/arch/backend
+    matching never sees them. When the release ships slim candidates but none
+    pair, log the actionable reason: on a slim-only release nothing else selects,
+    setup reports the prebuilt unavailable, and local dictation stays on
+    Transformers STT."""
+    if backend not in SLIM_ELIGIBLE_BACKENDS:
+        return None
+    os_token, arch_token = host_platform_tokens(host)
+    candidates = [
+        artifact
+        for artifact in manifest.get("artifacts", [])
+        if artifact.get("os") == os_token
+        and artifact.get("arch") == arch_token
+        and artifact.get("backend") == "slim"
+        and artifact.get("install_kind") == "slim"
+        and (not host.is_macos or _macos_min_os_ok(host, artifact.get("min_os")))
+    ]
+    for artifact in candidates:
+        if slim_pairing_for_artifact(artifact, host, backend) is not None:
+            return artifact
+    if candidates:
+        required_tag = candidates[0].get("requires_llama_tag")
+        log(f"slim bundle requires llama.cpp {required_tag}; install or update llama.cpp first")
+    return None
+
+
+def select_artifact(
+    manifest: dict[str, Any], host: HostInfo, backend: str
+) -> dict[str, Any] | None:
+    """Slim-only: every backend resolves to the paired slim artifact. The one
+    legacy shape still honored is the published fat CPU bundle of a pinned pre-slim
+    release, reached by a GPU-backend miss through the core's CPU fallback retry.
+    No other fat artifact is ever selected."""
+    slim = select_slim_artifact(manifest, host, backend)
+    if slim is not None:
+        return slim
+    if backend != "cpu":
+        return None
+    candidates = _artifacts_for_host(manifest, host, "cpu")
+    return candidates[0] if candidates else None
+
+
+def select_artifact_with_cpu_fallback(
+    manifest: dict[str, Any], host: HostInfo, backend: str
+) -> tuple[dict[str, Any], str, bool]:
+    try:
+        return core.select_artifact_with_fallback(_OPS, manifest, host, backend)
+    except PrebuiltFallback as exc:
+        reason = _slim_release_incompatibility(manifest, host)
+        if reason is not None:
+            raise ReleaseCompatibilityError(reason) from exc
+        raise
+
+
+def _slim_release_incompatibility(manifest: dict[str, Any], host: HostInfo) -> str | None:
+    """Explain a valid platform slim release that this runtime cannot pair.
+
+    This intentionally excludes missing files, malformed manifests, checksum
+    failures, and unsupported platforms. Those are operational errors and must
+    never be converted into the update path's kept-existing-runtime success.
+    """
+    os_token, arch_token = host_platform_tokens(host)
+    candidates = [
+        artifact
+        for artifact in manifest.get("artifacts", [])
+        if artifact.get("os") == os_token
+        and artifact.get("arch") == arch_token
+        and artifact.get("backend") == "slim"
+        and artifact.get("install_kind") == "slim"
+    ]
+    if not candidates:
+        return None
+    os_compatible = [
+        artifact
+        for artifact in candidates
+        if not host.is_macos or _macos_min_os_ok(host, artifact.get("min_os"))
+    ]
+    if not os_compatible:
+        required = candidates[0].get("min_os")
+        return f"slim bundle requires macOS {required}; this host is older"
+    runtime = installed_llama_runtime()
+    if runtime is None:
+        return None
+    installed_tag = runtime[1]
+    required_tags = {
+        artifact.get("requires_llama_tag")
+        for artifact in os_compatible
+        if isinstance(artifact.get("requires_llama_tag"), str)
+    }
+    if required_tags and installed_tag not in required_tags:
+        required_tag = sorted(required_tags)[0]
+        return (
+            f"slim bundle requires llama.cpp {required_tag}; "
+            f"installed llama.cpp is {installed_tag}"
+        )
+    return None
+
+
+def select_artifact_with_fallback(
+    manifest: dict[str, Any], host: HostInfo, backend: str
+) -> tuple[dict[str, Any], str, bool]:
+    return select_artifact_with_cpu_fallback(manifest, host, backend)
+
+
+# ── Release checksum index (trust anchor: the release's own sha256 asset) ──
+def parse_release_checksums(repo: str, release_tag: str, payload: Any) -> dict[str, str]:
+    return core.parse_release_checksums(_OPS, repo, release_tag, payload)
+
+
+def fetch_release_checksums(bundle: ReleaseBundle) -> dict[str, str]:
+    return core.fetch_release_checksums(_OPS, bundle)
+
+
+def expected_sha256_for(
+    checksums: dict[str, str],
+    asset_name: str,
+    *,
+    manifest_sha256: str | None = None,
+) -> str:
+    return core.expected_sha256_for(_OPS, checksums, asset_name, manifest_sha256 = manifest_sha256)
+
+
+# ── Verified download (retries once on checksum mismatch) ──
+def download_file_verified(
+    url: str, destination: Path, *, expected_sha256: str, label: str
+) -> None:
+    core.download_file_verified_strict(
+        _OPS, url, destination, expected_sha256 = expected_sha256, label = label
+    )
+
+
+# ── GitHub release resolution ──
+def github_release(repo: str, tag: str) -> dict[str, Any]:
+    return core.github_release(_OPS, repo, tag, error = PrebuiltFallback)
+
+
+def fetch_release_bundle(repo: str, release_tag: str) -> ReleaseBundle:
+    return core.fetch_release_bundle(_OPS, repo, release_tag)
+
+
+def asset_download_url(bundle: ReleaseBundle, asset_name: str) -> str:
+    return core.asset_download_url(_OPS, bundle, asset_name)
+
+
+# ── Download-host fast path (resolve + fetch the JSON assets with no GitHub API) ──
+def _download_host_latest_release_tag(repo: str) -> str | None:
+    return core.download_host_latest_release_tag(_OPS, repo)
+
+
+def _download_host_json(url: str) -> Any:
+    return core.fetch_download_host_json(_OPS, url)
+
+
+def _resolve_release_via_download_host(
+    repo: str, published_release_tag: str | None
+) -> tuple[ReleaseBundle, dict[str, str]] | None:
+    return core.resolve_release_via_download_host(_OPS, repo, published_release_tag)
+
+
+# ── Archive extraction (core's guarded extractor + tar exec-bit restore) ──
+def extract_archive(archive_path: Path, destination: Path) -> None:
+    """Shared guarded extraction, then restore tar exec bits (the extractor writes
+    plain files; whisper-server must stay executable)."""
+    core.extract_archive(archive_path, destination)
+    core.restore_tar_exec_bits(archive_path, destination)
+
+
+# ── Install layout ──
+def server_binary_name(host: HostInfo) -> str:
+    return "whisper-server.exe" if host.is_windows else "whisper-server"
+
+
+def runtime_bin_dir(install_dir: Path, host: HostInfo) -> Path:
+    """Canonical directory holding whisper-server + its co-located libs."""
+    if host.is_windows:
+        return install_dir / "build" / "bin" / "Release"
+    return install_dir / "build" / "bin"
+
+
+def whisper_server_path(install_dir: Path, host: HostInfo) -> Path:
+    return runtime_bin_dir(install_dir, host) / server_binary_name(host)
+
+
+def installed_server_path(install_dir: Path, host: HostInfo) -> Path:
+    return whisper_server_path(install_dir, host)
+
+
+def _locate_server_in_tree(root: Path, host: HostInfo) -> Path:
+    return core.locate_server_in_tree(_OPS, root, host)
+
+
+def locate_server_in_tree(root: Path, host: HostInfo) -> Path:
+    return _locate_server_in_tree(root, host)
+
+
+def _assemble_install_tree(bundle_root: Path, staged_root: Path, host: HostInfo) -> Path:
+    """Lay out staged_root as a full install: build/bin/<server + libs>.
+
+    Everything beside the server in the archive (shared libs, backend kernel
+    subdirs, license/build-info) is co-located into the canonical bin dir so the
+    server's RUNPATH=$ORIGIN resolves its libs.
+    """
+    bin_dir = runtime_bin_dir(staged_root, host)
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    for entry in sorted(bundle_root.iterdir()):
+        if entry.name == METADATA_FILENAME:
+            continue
+        dest = bin_dir / entry.name
+        if entry.is_dir() and not entry.is_symlink():
+            shutil.copytree(entry, dest, symlinks = True)
+        else:
+            shutil.copy2(entry, dest, follow_symlinks = False)
+    server = bin_dir / server_binary_name(host)
+    if not server.exists():
+        raise PrebuiltFallback("staged install is missing the whisper-server binary")
+    if not host.is_windows:
+        os.chmod(server, server.stat().st_mode | 0o111)
+    return server
+
+
+def assemble_install_tree(bundle_root: Path, staged_root: Path, host: HostInfo) -> Path:
+    return _assemble_install_tree(bundle_root, staged_root, host)
+
+
+def _validate_staged_server(staged_root: Path, host: HostInfo) -> None:
+    """Optional pre-activate smoke test. Gated off by default (see the switch)."""
+    if not _RUN_STAGED_PREBUILT_VALIDATION:
+        return
+    server = whisper_server_path(staged_root, host)
+    env = os.environ.copy()
+    bin_dir = str(runtime_bin_dir(staged_root, host))
+    for var in ("LD_LIBRARY_PATH", "DYLD_LIBRARY_PATH"):
+        env[var] = bin_dir + (os.pathsep + env[var] if env.get(var) else "")
+    try:
+        result = subprocess.run(
+            [str(server), "--help"],
+            capture_output = True,
+            text = True,
+            timeout = 60,
+            env = env,
+            **llama.windows_hidden_subprocess_kwargs(),
+        )
+    except (OSError, subprocess.SubprocessError) as exc:
+        raise PrebuiltFallback(f"staged whisper-server failed to launch: {exc}") from exc
+    if result.returncode != 0:
+        raise PrebuiltFallback(
+            f"staged whisper-server --help exited {result.returncode}: {result.stderr.strip()}"
+        )
+
+
+def validate_staged_server(staged_root: Path, host: HostInfo) -> None:
+    _validate_staged_server(staged_root, host)
+
+
+# ── Slim install wiring (llama ggml runtime into the whisper bin dir) ──
+def _elf_needed(path: Path) -> set[str] | None:
+    """Read ELF DT_NEEDED names when a standard inspection tool is available."""
+    commands = (("readelf", "-d"), ("objdump", "-p"))
+    for command in commands:
+        try:
+            result = subprocess.run(
+                [*command, str(path)], capture_output = True, text = True, timeout = 10
+            )
+        except (OSError, subprocess.SubprocessError):
+            continue
+        if result.returncode != 0:
+            continue
+        needed: set[str] = set()
+        for line in result.stdout.splitlines():
+            match = re.search(r"\(NEEDED\).*\[([^]]+)\]", line)
+            if match:
+                needed.add(match.group(1))
+                continue
+            match = re.match(r"\s*NEEDED\s+(\S+)", line)
+            if match:
+                needed.add(match.group(1))
+        return needed
+    return None
+
+
+def _runtime_library_sources(llama_bin_dir: Path, backend: str | None) -> list[Path]:
+    patterns = list(SLIM_GGML_LIBRARY_GLOBS)
+    sources = {
+        path for pattern in patterns for path in llama_bin_dir.glob(pattern) if path.is_file()
+    }
+    if backend == "rocm":
+        # Windows llama HIP/ROCm prebuilts use a flat *.dll runtime overlay.
+        # Mirror that complete no-SDK closure, not only filenames containing
+        # ggml, hip, or roc: transitive runtime DLLs can have unrelated names.
+        windows_dlls = {path for path in llama_bin_dir.glob("*.dll") if path.is_file()}
+        if windows_dlls:
+            sources.update(windows_dlls)
+            return sorted(sources)
+
+        # Linux can inspect DT_NEEDED and copy the exact packaged closure. Fall
+        # back to the ROCm globs only when standard ELF tools are unavailable.
+        by_name = {path.name: path for path in llama_bin_dir.iterdir() if path.is_file()}
+        pending = list(sources)
+        inspected_hip = False
+        system_libraries = {
+            "libc.so.6",
+            "libdl.so.2",
+            "libgcc_s.so.1",
+            "libm.so.6",
+            "libpthread.so.0",
+            "librt.so.1",
+            "libstdc++.so.6",
+        }
+        while pending:
+            source = pending.pop()
+            needed = _elf_needed(source)
+            if needed is None:
+                continue
+            if source.name.startswith("libggml-hip"):
+                inspected_hip = True
+            for name in needed - system_libraries:
+                dependency = by_name.get(name)
+                if dependency is not None and dependency not in sources:
+                    sources.add(dependency)
+                    pending.append(dependency)
+        if not inspected_hip:
+            sources.update(
+                path
+                for pattern in SLIM_ROCM_LIBRARY_GLOBS
+                for path in llama_bin_dir.glob(pattern)
+                if path.is_file()
+            )
+    return sorted(sources)
+
+
+def _link_or_copy(source: Path, destination: Path) -> None:
+    destination.parent.mkdir(parents = True, exist_ok = True)
+    if destination.exists() or destination.is_symlink():
+        destination.unlink()
+    try:
+        os.link(source, destination)
+    except OSError:
+        shutil.copy2(source, destination)
+
+
+def link_ggml_runtime(
+    llama_bin_dir: Path,
+    whisper_bin_dir: Path,
+    *,
+    backend: str | None = None,
+) -> list[str]:
+    """Hardlink every ggml library from the llama runtime into the whisper bin
+    dir; returns the wired filenames (sorted) for the marker / sidecar launch guard.
+
+    Hardlinks (not symlinks) on purpose: when the llama updater atomically swaps
+    its install dir, the old inodes stay alive under these links, so a
+    not-yet-updated whisper keeps running the exact ggml build it was installed
+    against. Falls back to a copy where linking is unsupported or crosses devices.
+    Re-run on every install/update so the links track the current pairing.
+    """
+    sources = _runtime_library_sources(llama_bin_dir, backend)
+    if not any(source.name.startswith(("libggml", "ggml")) for source in sources):
+        raise PrebuiltFallback(
+            f"no ggml libraries found in {llama_bin_dir} to pair the slim whisper install"
+        )
+    whisper_bin_dir.mkdir(parents = True, exist_ok = True)
+    for source in sources:
+        # Follows a libggml.so.0 -> libggml.so.0.x symlink to its inode, so every
+        # created name is a real hardlink surviving a dir swap.
+        _link_or_copy(source, whisper_bin_dir / source.name)
+    return [source.name for source in sources]
+
+
+def link_runtime_directories(
+    llama_bin_dir: Path, whisper_bin_dir: Path, *, backend: str, host: HostInfo
+) -> list[str]:
+    """Mirror GPU kernel catalogs that packaged ROCm libraries load at runtime."""
+    # Windows ROCm prebuilts are a flat DLL overlay. The hipblaslt/rocblas
+    # catalog directories are part of the Linux ROCm bundle layout only.
+    if backend != "rocm" or host.is_windows:
+        return []
+    linked: list[str] = []
+    for name in SLIM_ROCM_RUNTIME_DIRS:
+        source_root = llama_bin_dir / name
+        if not source_root.is_dir():
+            raise PrebuiltFallback(f"paired ROCm runtime is missing its {name} kernel catalog")
+        files = [path for path in source_root.rglob("*") if path.is_file()]
+        if not files:
+            raise PrebuiltFallback(f"paired ROCm runtime has an empty {name} kernel catalog")
+        for source in files:
+            _link_or_copy(source, whisper_bin_dir / name / source.relative_to(source_root))
+        linked.append(name)
+    return linked
+
+
+def prepare_runtime_payload(staged_root: Path, host: HostInfo, selection: Any) -> Any:
+    """Slim installs wire the paired llama ggml runtime into the staged bin dir
+    before validation so the activated tree is self-contained; the returned
+    selection carries the wired filenames for the marker. Fat installs need
+    nothing (the archive carries its ggml) and return None."""
+    if getattr(selection, "install_kind", None) != "slim" or not selection.linked_from:
+        return None
+    source = Path(selection.linked_from)
+    destination = runtime_bin_dir(staged_root, host)
+    linked = link_ggml_runtime(source, destination, backend = selection.backend)
+    linked_dirs = link_runtime_directories(
+        source,
+        destination,
+        backend = selection.backend,
+        host = host,
+    )
+    log(f"slim install: hardlinked {len(linked)} ggml libraries from {selection.linked_from}")
+    return replace(
+        selection,
+        linked_libraries = tuple(linked),
+        runtime_wiring_version = SLIM_RUNTIME_WIRING_VERSION,
+        linked_runtime_directories = tuple(linked_dirs),
+    )
+
+
+# ── Metadata / marker ──
+def metadata_path(install_dir: Path) -> Path:
+    return install_dir / METADATA_FILENAME
+
+
+def selection_from_artifact(
+    *,
+    published_repo: str,
+    release_tag: str,
+    manifest: dict[str, Any],
+    artifact: dict[str, Any],
+    backend: str,
+    asset_sha256: str,
+) -> InstallSelection:
+    selection = core.selection_from_artifact(
+        _OPS,
+        published_repo = published_repo,
+        release_tag = release_tag,
+        manifest = manifest,
+        artifact = artifact,
+        backend = backend,
+        asset_sha256 = asset_sha256,
+    )
+    if artifact.get("install_kind") != "slim":
+        return selection
+    # A slim selection carries its pairing so the install wiring and marker know
+    # which llama runtime provides the ggml libraries.
+    runtime = installed_llama_runtime()
+    if runtime is None or runtime[1] != artifact.get("requires_llama_tag"):
+        raise PrebuiltFallback(
+            "the paired llama.cpp runtime changed underneath the slim whisper selection"
+        )
+    llama_bin_dir, llama_tag, _profile = runtime
+    return replace(
+        selection,
+        install_kind = "slim",
+        paired_llama_tag = llama_tag,
+        linked_from = str(llama_bin_dir),
+    )
+
+
+def write_prebuilt_metadata(install_dir: Path, selection: InstallSelection) -> None:
+    core.write_prebuilt_metadata(_OPS, install_dir, selection)
+
+
+def load_whisper_prebuilt_metadata(install_dir: Path) -> dict[str, Any] | None:
+    return core.load_prebuilt_metadata(_OPS, install_dir)
+
+
+def load_prebuilt_metadata(install_dir: Path) -> dict[str, Any] | None:
+    return load_whisper_prebuilt_metadata(install_dir)
+
+
+def existing_install_matches(
+    install_dir: Path, host: HostInfo, selection: InstallSelection
+) -> bool:
+    """Core fingerprint match, hardened for repairability: a marker-matching
+    install is only "current" when the server is executable (the sidecar refuses
+    non-executable binaries, so setup must repair not skip) and, for slim
+    installs, every wired ggml library is still present (else a deleted/moved
+    llama dir leaves dictation broken while update reports up to date)."""
+    if not core.existing_install_matches(_OPS, install_dir, host, selection):
+        return False
+    server = installed_server_path(install_dir, host)
+    if not host.is_windows and not os.access(server, os.X_OK):
+        log(f"existing install at {install_dir} has a non-executable server; reinstalling")
+        return False
+    marker = load_prebuilt_metadata(install_dir) or {}
+    if marker.get("install_kind") == "slim":
+        bin_dir = server.parent
+        if marker.get("runtime_wiring_version") != SLIM_RUNTIME_WIRING_VERSION:
+            log(f"existing slim install at {install_dir} has stale runtime wiring; reinstalling")
+            return False
+        linked_libraries = marker.get("linked_libraries")
+        if (
+            not isinstance(linked_libraries, list)
+            or not linked_libraries
+            or not all(
+                isinstance(name, str) and name and Path(name).name == name
+                for name in linked_libraries
+            )
+        ):
+            log(f"existing slim install at {install_dir} has invalid runtime wiring; reinstalling")
+            return False
+        missing = [name for name in linked_libraries if not (bin_dir / name).is_file()]
+        if missing:
+            log(
+                f"existing slim install at {install_dir} is missing wired ggml "
+                f"libraries ({', '.join(missing[:4])}); reinstalling"
+            )
+            return False
+        runtime_dirs = marker.get("linked_runtime_directories")
+        if (
+            marker.get("backend") == "rocm"
+            and not host.is_windows
+            and (
+                not isinstance(runtime_dirs, list)
+                or set(runtime_dirs) != set(SLIM_ROCM_RUNTIME_DIRS)
+            )
+        ):
+            log(f"existing ROCm install at {install_dir} lacks kernel catalogs; reinstalling")
+            return False
+        missing_dirs = [
+            name
+            for name in runtime_dirs or []
+            if not isinstance(name, str)
+            or not (bin_dir / name).is_dir()
+            or not any(path.is_file() for path in (bin_dir / name).rglob("*"))
+        ]
+        if missing_dirs:
+            log(
+                f"existing slim install at {install_dir} is missing runtime directories "
+                f"({', '.join(str(name) for name in missing_dirs[:4])}); reinstalling"
+            )
+            return False
+    return True
+
+
+# ── Orchestration ──
+def resolve_newest_release_tag(repo: str) -> str:
+    return core.resolve_newest_release_tag(_OPS, repo)
+
+
+def resolve_release_tag(published_repo: str, *, published_release_tag: str | None) -> str:
+    return core.resolve_release_tag(
+        _OPS, published_repo, published_release_tag = published_release_tag
+    )
+
+
+def fetch_release_for_install(
+    repo: str, *, published_release_tag: str | None
+) -> tuple[ReleaseBundle, dict[str, str]]:
+    return core.fetch_release_for_install(_OPS, repo, published_release_tag = published_release_tag)
+
+
+@dataclass(frozen = True)
+class WhisperReleasePlan:
+    bundle: ReleaseBundle
+    selection: InstallSelection | None
+    artifact: dict[str, Any]
+    resolved_backend: str
+    used_fallback: bool
+
+
+def _normalized_upstream_tag(value: str) -> str:
+    value = value.strip()
+    return value[1:] if value[:1].lower() == "v" else value
+
+
+def _bundle_matches_whisper_tag(bundle: ReleaseBundle, whisper_tag: str) -> bool:
+    requested = whisper_tag.strip()
+    if not requested or requested.lower() == "latest":
+        return True
+    upstream = bundle.manifest.get("upstream_tag")
+    return isinstance(upstream, str) and _normalized_upstream_tag(
+        upstream
+    ) == _normalized_upstream_tag(requested)
+
+
+def _published_release_tags(repo: str) -> list[str]:
+    """Published release tags in newest-first order for compatibility search."""
+    payload = fetch_json(f"https://api.github.com/repos/{repo}/releases?per_page=100")
+    if not isinstance(payload, list):
+        raise PrebuiltFallback(f"unexpected releases payload for {repo}")
+    releases = [
+        release
+        for release in payload
+        if isinstance(release, dict)
+        and not release.get("draft")
+        and not release.get("prerelease")
+        and isinstance(release.get("tag_name"), str)
+        and release.get("tag_name")
+    ]
+    releases.sort(key = lambda release: release.get("published_at") or "", reverse = True)
+    return [str(release["tag_name"]) for release in releases]
+
+
+def _fetch_release_candidate(repo: str, release_tag: str) -> ReleaseBundle:
+    """Fetch one candidate manifest by its deterministic download-host URL."""
+    manifest_url = release_asset_download_url(repo, release_tag, MANIFEST_ASSET_NAME)
+    try:
+        payload = _download_host_json(manifest_url)
+        manifest = parse_manifest(payload, label = f"{MANIFEST_ASSET_NAME} in {repo}@{release_tag}")
+    except Exception as exc:
+        raise PrebuiltFallback(
+            f"could not read {MANIFEST_ASSET_NAME} from {repo}@{release_tag}: {exc}"
+        ) from exc
+    asset_names = {MANIFEST_ASSET_NAME, SHA256_ASSET_NAME}
+    asset_names.update(
+        str(artifact["asset"])
+        for artifact in manifest.get("artifacts", [])
+        if isinstance(artifact, dict) and artifact.get("asset")
+    )
+    asset_urls = {name: release_asset_download_url(repo, release_tag, name) for name in asset_names}
+    return ReleaseBundle(
+        repo = repo,
+        release_tag = release_tag,
+        manifest = manifest,
+        asset_urls = asset_urls,
+    )
+
+
+def _plan_bundle(
+    host: HostInfo,
+    bundle: ReleaseBundle,
+    checksums: dict[str, str],
+    *,
+    published_repo: str,
+    requested_backend: str,
+    verify_checksums: bool,
+) -> WhisperReleasePlan:
+    artifact, resolved_backend, used_fallback = select_artifact_with_cpu_fallback(
+        bundle.manifest, host, requested_backend
+    )
+    selection = (
+        plan_selection(
+            host,
+            bundle,
+            published_repo = published_repo,
+            backend = requested_backend,
+            checksums = checksums,
+        )
+        if verify_checksums
+        else None
+    )
+    return WhisperReleasePlan(
+        bundle = bundle,
+        selection = selection,
+        artifact = artifact,
+        resolved_backend = resolved_backend,
+        used_fallback = used_fallback,
+    )
+
+
+def _release_plan_for_host(
+    host: HostInfo,
+    *,
+    published_repo: str,
+    published_release_tag: str | None,
+    whisper_tag: str,
+    requested_backend: str,
+    verify_checksums: bool = True,
+) -> WhisperReleasePlan:
+    """Select the requested or newest host-compatible published release.
+
+    Explicit published release pins never walk. An upstream ``whisper_tag``
+    searches published manifests for that exact upstream version. An unpinned
+    macOS install may walk older published releases only when the newest
+    manifest has no host-compatible artifact. Checksum and archive failures are
+    outside this search and remain hard failures.
+    """
+    requested_specific_tag = whisper_tag.strip().lower() not in ("", "latest")
+    first_bundle: ReleaseBundle | None = None
+    first_error: PrebuiltFallback | None = None
+    # An upstream version pin searches manifests directly. It must not depend
+    # on the unrelated newest release or its checksum index being healthy.
+    if not requested_specific_tag or published_release_tag:
+        first_bundle, first_checksums = fetch_release_for_install(
+            published_repo, published_release_tag = published_release_tag
+        )
+        if not _bundle_matches_whisper_tag(first_bundle, whisper_tag):
+            first_error = PrebuiltFallback(
+                f"{published_repo}@{first_bundle.release_tag} targets whisper.cpp "
+                f"{first_bundle.manifest.get('upstream_tag')}, not requested {whisper_tag}"
+            )
+        else:
+            try:
+                select_artifact_with_cpu_fallback(first_bundle.manifest, host, requested_backend)
+            except PrebuiltFallback as exc:
+                first_error = exc
+            else:
+                # Integrity validation happens only after compatibility succeeds.
+                # Its failures are never eligible for release walkback.
+                return _plan_bundle(
+                    host,
+                    first_bundle,
+                    first_checksums,
+                    published_repo = published_repo,
+                    requested_backend = requested_backend,
+                    verify_checksums = verify_checksums,
+                )
+
+    if published_release_tag:
+        assert first_error is not None
+        raise first_error
+
+    if not requested_specific_tag and not host.is_macos:
+        assert first_error is not None
+        raise first_error
+
+    for release_tag in _published_release_tags(published_repo):
+        if first_bundle is not None and release_tag == first_bundle.release_tag:
+            continue
+        try:
+            bundle = _fetch_release_candidate(published_repo, release_tag)
+        except PrebuiltFallback:
+            continue
+        if not _bundle_matches_whisper_tag(bundle, whisper_tag):
+            continue
+        try:
+            # Establish host compatibility before fetching or trusting this
+            # candidate's checksum index. Once selected, integrity failures must
+            # stop the install rather than silently downgrade again.
+            select_artifact_with_cpu_fallback(bundle.manifest, host, requested_backend)
+        except PrebuiltFallback:
+            continue
+        checksums = fetch_release_checksums(bundle) if verify_checksums else {}
+        plan = _plan_bundle(
+            host,
+            bundle,
+            checksums,
+            published_repo = published_repo,
+            requested_backend = requested_backend,
+            verify_checksums = verify_checksums,
+        )
+        log(
+            f"selected compatible published release {bundle.release_tag} "
+            f"(upstream {bundle.manifest.get('upstream_tag')})"
+        )
+        return plan
+
+    if requested_specific_tag:
+        raise PrebuiltFallback(
+            f"no published {COMPONENT} release for upstream tag {whisper_tag} supports this host"
+        )
+    assert first_error is not None
+    raise first_error
+
+
+def _install_from_bundle(
+    install_dir: Path, host: HostInfo, bundle: ReleaseBundle, selection: InstallSelection
+) -> None:
+    core.install_from_bundle(_OPS, install_dir, host, bundle, selection)
+
+
+def plan_selection(
+    host: HostInfo,
+    bundle: ReleaseBundle,
+    *,
+    published_repo: str,
+    backend: str,
+    checksums: dict[str, str],
+) -> InstallSelection:
+    return core.plan_selection(
+        _OPS,
+        host,
+        bundle,
+        published_repo = published_repo,
+        backend = backend,
+        checksums = checksums,
+    )
+
+
+def install_prebuilt(
+    install_dir: Path,
+    *,
+    whisper_tag: str = "latest",
+    published_repo: str = DEFAULT_PUBLISHED_REPO,
+    published_release_tag: str | None = None,
+    backend: str | None = "auto",
+    has_rocm: bool = False,
+    rocm_gfx: str | None = None,
+    cpu_fallback: bool = False,
+    force: bool = False,
+) -> int:
+    host = apply_host_overrides(
+        detect_host(), has_rocm = has_rocm, rocm_gfx = rocm_gfx, force_cpu = cpu_fallback
+    )
+    requested_backend = resolve_backend(host, backend, cpu_fallback = cpu_fallback)
+    os_token, arch_token = host_platform_tokens(host)
+    log(
+        f"target {COMPONENT} from {published_repo} "
+        f"({os_token}-{arch_token}, backend {requested_backend})"
+    )
+    plan = _release_plan_for_host(
+        host,
+        published_repo = published_repo,
+        published_release_tag = published_release_tag,
+        whisper_tag = whisper_tag,
+        requested_backend = requested_backend,
+    )
+    if plan.selection is None:  # pragma: no cover - install plans always verify
+        raise PrebuiltFallback("install plan did not validate its checksum entry")
+    return core.install_selected_prebuilt(
+        _OPS,
+        install_dir,
+        host = host,
+        bundle = plan.bundle,
+        selection = plan.selection,
+        force = force,
+    )
+
+
+def resolver_payload_extra(artifact: dict[str, Any]) -> dict[str, Any]:
+    """Additive --resolve-prebuilt field: whether the selected asset installs
+    slim (paired with the llama ggml runtime) or fat (self-contained)."""
+    return {"install_kind": "slim" if artifact.get("install_kind") == "slim" else "fat"}
+
+
+def resolve_prebuilt(
+    host: HostInfo,
+    *,
+    published_repo: str,
+    published_release_tag: str | None,
+    whisper_tag: str = "latest",
+    backend: str | None,
+    cpu_fallback: bool,
+) -> dict[str, Any]:
+    requested_backend = resolve_backend(host, backend, cpu_fallback = cpu_fallback)
+    try:
+        plan = _release_plan_for_host(
+            host,
+            published_repo = published_repo,
+            published_release_tag = published_release_tag,
+            whisper_tag = whisper_tag,
+            requested_backend = requested_backend,
+            verify_checksums = False,
+        )
+    except PrebuiltFallback:
+        return {"prebuilt_available": False, "repo": published_repo}
+    os_token, arch_token = host_platform_tokens(host)
+    payload = {
+        "prebuilt_available": True,
+        "repo": published_repo,
+        "release_tag": plan.bundle.release_tag,
+        "upstream_tag": plan.bundle.manifest.get("upstream_tag"),
+        "backend": plan.resolved_backend,
+        "requested_backend": requested_backend,
+        "cpu_fallback": plan.used_fallback,
+        "asset": str(plan.artifact.get("asset")),
+        "os": os_token,
+        "arch": arch_token,
+        "runtime_line": plan.artifact.get("runtime_line"),
+    }
+    payload.update(resolver_payload_extra(plan.artifact))
+    return payload
+
+
+# The whisper component descriptor: the declarative form of everything above,
+# for descriptor-driven consumers (shared tests, future tooling). The shipped CLI
+# runs through this module's wrappers so monkeypatch seams stay intact.
+DESCRIPTOR = core.ComponentDescriptor(
+    component = COMPONENT,
+    log_prefix = "whisper-prebuilt",
+    published_repo = DEFAULT_PUBLISHED_REPO,
+    manifest_asset_name = MANIFEST_ASSET_NAME,
+    sha256_asset_name = SHA256_ASSET_NAME,
+    metadata_filename = METADATA_FILENAME,
+    user_agent = USER_AGENT,
+    supported_backends = SUPPORTED_BACKENDS,
+    schema_version = SCHEMA_VERSION,
+    fallback_backend = FALLBACK_BACKEND,
+    detect_host = detect_host,
+    host_platform_tokens = host_platform_tokens,
+    server_binary_name = server_binary_name,
+    runtime_bin_dir = runtime_bin_dir,
+)
+
+
+def build_arg_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description = "Install a prebuilt whisper.cpp (whisper-server) for Unsloth Studio"
+    )
+    parser.add_argument(
+        "--install-dir",
+        default = None,
+        help = (
+            "managed whisper.cpp directory, e.g. <UNSLOTH_HOME>/whisper.cpp. Required for an "
+            "install; omit it only with --resolve-prebuilt (a read-only probe)."
+        ),
+    )
+    parser.add_argument(
+        "--whisper-tag",
+        default = os.environ.get("UNSLOTH_WHISPER_TAG", "latest"),
+        help = "upstream whisper.cpp tag hint (default 'latest' or $UNSLOTH_WHISPER_TAG)",
+    )
+    parser.add_argument(
+        "--published-repo",
+        default = DEFAULT_PUBLISHED_REPO,
+        help = f"GitHub repo publishing the prebuilt releases (default {DEFAULT_PUBLISHED_REPO})",
+    )
+    parser.add_argument(
+        "--published-release-tag",
+        default = os.environ.get("UNSLOTH_WHISPER_RELEASE_TAG") or None,
+        help = "explicit release tag to install (default: the newest published release)",
+    )
+    parser.add_argument(
+        "--backend",
+        default = os.environ.get("UNSLOTH_WHISPER_BACKEND", "auto"),
+        choices = ("auto", *SUPPORTED_BACKENDS),
+        help = "accelerator backend; 'auto' detects from hardware",
+    )
+    parser.add_argument("--has-rocm", action = "store_true", help = "treat this host as ROCm-capable")
+    parser.add_argument("--rocm-gfx", default = None, help = "ROCm gfx target override, e.g. gfx1100")
+    parser.add_argument(
+        "--cpu-fallback", action = "store_true", help = "force the CPU asset regardless of hardware"
+    )
+    parser.add_argument(
+        "--resolve-prebuilt",
+        nargs = "?",
+        const = "latest",
+        default = None,
+        help = "report whether a prebuilt exists for this host without downloading",
+    )
+    parser.add_argument(
+        "--output-format",
+        choices = ("plain", "json"),
+        default = "plain",
+        help = "resolver output format (default plain)",
+    )
+    parser.add_argument(
+        "--force", action = "store_true", help = "reinstall even if the install already matches"
+    )
+    return parser
+
+
+def main(argv: list[str] | None = None) -> int:
+    global _LOG_TO_STDOUT
+    parser = build_arg_parser()
+    args = parser.parse_args(argv)
+
+    if args.resolve_prebuilt is not None:
+        # Read-only probe: stdout is only the JSON/asset line (setup.sh and
+        # whisper_cpp_update.py parse it), so force diagnostics to stderr and map
+        # any failure to "not available" rather than a traceback.
+        _LOG_TO_STDOUT = False
+        try:
+            host = apply_host_overrides(
+                detect_host(),
+                has_rocm = args.has_rocm,
+                rocm_gfx = args.rocm_gfx,
+                force_cpu = args.cpu_fallback,
+            )
+            payload = resolve_prebuilt(
+                host,
+                published_repo = args.published_repo,
+                published_release_tag = args.published_release_tag,
+                whisper_tag = args.resolve_prebuilt,
+                backend = args.backend,
+                cpu_fallback = args.cpu_fallback,
+            )
+        except PrebuiltFallback:
+            payload = {"prebuilt_available": False, "repo": args.published_repo}
+        except Exception as exc:  # noqa: BLE001 - probe must never crash the caller
+            log(f"resolve failed: {exc}")
+            payload = {"prebuilt_available": False, "repo": args.published_repo}
+        emit_resolver_output(payload, output_format = args.output_format)
+        return EXIT_SUCCESS
+
+    # Install path: progress logs go to stdout so setup surfaces them.
+    _LOG_TO_STDOUT = True
+
+    if not args.install_dir:
+        parser.error("--install-dir is required unless --resolve-prebuilt is used")
+    install_dir = Path(args.install_dir).expanduser().resolve()
+    try:
+        return install_prebuilt(
+            install_dir,
+            whisper_tag = args.whisper_tag,
+            published_repo = args.published_repo,
+            published_release_tag = args.published_release_tag,
+            backend = args.backend,
+            has_rocm = args.has_rocm,
+            rocm_gfx = args.rocm_gfx,
+            cpu_fallback = args.cpu_fallback,
+            force = args.force,
+        )
+    except BusyInstallConflict as exc:
+        log(str(exc))
+        return EXIT_BUSY
+    except ReleaseCompatibilityError as exc:
+        log(f"incompatible release: {exc}")
+        return EXIT_INCOMPATIBLE
+    except PrebuiltFallback as exc:
+        log(f"prebuilt install failed: {exc}")
+        return EXIT_ERROR
+    except Exception as exc:  # noqa: BLE001
+        log(f"unexpected error: {exc}")
+        return EXIT_ERROR
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/studio/prebuilt_core.py b/studio/prebuilt_core.py
new file mode 100644
index 0000000000..5dc85af1c2
--- /dev/null
+++ b/studio/prebuilt_core.py
@@ -0,0 +1,2427 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Component-agnostic machinery shared by the ggml-family prebuilt installers.
+
+``install_llama_prebuilt.py`` and ``install_whisper_prebuilt.py`` both run on
+this module, which owns two layers:
+
+1. Primitives: HTTP fetches with retries and token-safe redirects, verified
+   downloads, safe archive extraction, the install lock, sha256 helpers, and
+   CUDA runtime-line / compute-capability selection. Moved verbatim out of
+   ``install_llama_prebuilt.py``, which re-exports them under their old names.
+
+2. The generic descriptor-driven install flow: release resolution (download
+   host fast path, GitHub API fallback), checksum-index parsing, coverage-aware
+   artifact selection, verified download + extraction + staged atomic
+   activation, marker/fingerprint handling, and the resolve probe. Whisper runs
+   entirely on this flow; a third component plugs in with a ``ComponentDescriptor``.
+
+Seam rule: every function calling a collaborator tests monkeypatch takes an
+``ops`` handle first. ``ops`` resolves names in the calling installer module's
+globals first (so a ``monkeypatch.setattr`` still wins) and falls back to this
+module's defaults, letting a descriptor-only component work with no installer
+module behind it.
+"""
+
+from __future__ import annotations
+
+import errno
+import functools
+import hashlib
+import json
+import os
+import random
+import re
+import shutil
+import socket
+import subprocess
+import sys
+import tarfile
+import tempfile
+import time
+import urllib.error
+import urllib.parse
+import urllib.request
+import zipfile
+from contextlib import contextmanager
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Callable, Iterable, Iterator
+
+try:
+    from filelock import FileLock, Timeout as FileLockTimeout
+except ImportError:
+    FileLock = None
+    FileLockTimeout = None
+
+
+class PrebuiltFallback(RuntimeError):
+    pass
+
+
+class BusyInstallConflict(RuntimeError):
+    pass
+
+
+# ── Defaults a component module may override via its own globals ──
+USER_AGENT = "unsloth-studio-prebuilt"
+GITHUB_AUTH_HOSTS = {"api.github.com", "github.com"}
+HF_AUTH_HOSTS = {"huggingface.co", "www.huggingface.co"}
+RETRYABLE_HTTP_STATUS = {408, 429, 500, 502, 503, 504}
+HTTP_FETCH_ATTEMPTS = 4
+HTTP_FETCH_BASE_DELAY_SECONDS = 0.75
+JSON_FETCH_ATTEMPTS = 3
+TTY_PROGRESS_START_DELAY_SECONDS = 0.5
+INSTALL_LOCK_TIMEOUT_SECONDS = 300
+INSTALL_STAGING_ROOT_NAME = ".staging"
+SCHEMA_VERSION = 1
+# Backend to retry when the preferred one has no covering asset; None disables it.
+FALLBACK_BACKEND: str | None = "cpu"
+_RATE_LIMIT_WAIT_CAP_SECONDS = 60.0
+
+# Lowest CUDA major we ship prebuilts for, and highest we probe for installed
+# runtime libraries. Detection and runtime-line derivation are generated per
+# major, so a new toolkit (cuda14, ...) needs no code change while ggml keeps
+# the cudart64_<major>.dll / libcudart.so.<major> naming.
+_MIN_CUDA_MAJOR = 12
+_MAX_PROBE_CUDA_MAJOR = 19
+
+# Blackwell floor is sm_100 (B100/B200 sm_100, B300/GB300 sm_103 below consumer
+# RTX 50 sm_120); the family needs toolkit >= 12.8, sm_103/sm_121 need 12.9.
+_BLACKWELL_MIN_SM = 100
+_BLACKWELL_MIN_TOOLKIT = (12, 8)
+_BLACKWELL_SM_MIN_TOOLKIT = {103: (12, 9), 121: (12, 9)}
+
+
+def log(message: str) -> None:
+    print(f"[prebuilt-core] {message}", file = sys.stderr)
+
+
+def _cuda_runtime_lines_for_major(major: int) -> list[str]:
+    """Runtime lines a driver of this CUDA major can use (its own major and any
+    older one, newest first down to the minimum we ship)."""
+    return [f"cuda{m}" for m in range(major, _MIN_CUDA_MAJOR - 1, -1)]
+
+
+# ── The ops seam ──
+_MISSING = object()
+
+# Core functions expecting an ``ops`` first argument. ModuleOps binds itself when
+# a lookup falls back to the core default, so a descriptor-only component gets
+# working defaults while an installer wrapper (or a test monkeypatch) always wins.
+_OPS_FIRST_NAMES = {
+    "auth_headers",
+    "github_api_headers",
+    "download_bytes",
+    "fetch_json",
+    "download_file",
+    "download_file_verified",
+    "download_file_verified_strict",
+    "github_release",
+    "github_release_assets",
+    "download_host_latest_release_tag",
+    "fetch_download_host_json",
+    "linux_runtime_dirs_for_required_libraries",
+    "detected_linux_runtime_lines",
+    "detected_windows_runtime_lines",
+    "parse_manifest",
+    "parse_release_checksums",
+    "fetch_release_checksums",
+    "expected_sha256_for",
+    "macos_min_os_ok",
+    "artifacts_for_host",
+    "select_artifact",
+    "select_artifact_with_fallback",
+    "auto_detect_backend",
+    "resolve_backend",
+    "fetch_release_bundle",
+    "asset_download_url",
+    "resolve_newest_release_tag",
+    "resolve_release_tag",
+    "resolve_release_via_download_host",
+    "fetch_release_for_install",
+    "write_prebuilt_metadata",
+    "load_prebuilt_metadata",
+    "existing_install_matches",
+    "metadata_path",
+    "selection_from_artifact",
+    "plan_selection",
+    "install_from_bundle",
+    "install_prebuilt",
+    "resolve_prebuilt",
+    "installed_server_path",
+    "assemble_install_tree",
+    "validate_staged_server",
+    "locate_server_in_tree",
+    # Underscored aliases the installer modules expose for their tests.
+    "_download_host_latest_release_tag",
+    "_download_host_json",
+    "_resolve_release_via_download_host",
+    "_install_from_bundle",
+}
+
+
+class ModuleOps:
+    """Late-binding name resolver over an installer module's globals.
+
+    Lookup hits the wrapped globals first (so a ``monkeypatch.setattr`` is always
+    observed), then this module's defaults (ops-first defaults come back bound).
+    """
+
+    def __init__(self, module_globals: dict[str, Any]) -> None:
+        self._globals = module_globals
+
+    def __getattr__(self, name: str) -> Any:
+        value = self._globals.get(name, _MISSING)
+        if value is _MISSING:
+            value = globals().get(name, _MISSING)
+            if value is _MISSING:
+                raise AttributeError(f"prebuilt component namespace has no attribute {name!r}")
+            if name in _OPS_FIRST_NAMES:
+                return functools.partial(value, self)
+        return value
+
+
+@dataclass(frozen = True)
+class ComponentDescriptor:
+    """Everything the generic flow needs about one ggml-family component.
+
+    Hooks mirror the module-level names an installer defines; a descriptor-only
+    component supplies them here and ``component_ops`` builds a namespace with
+    core defaults behind them.
+    """
+
+    component: str  # manifest "component" value, e.g. "whisper.cpp"
+    log_prefix: str  # stderr prefix, e.g. "whisper-prebuilt"
+    published_repo: str  # fork publishing the prebuilt releases
+    manifest_asset_name: str
+    sha256_asset_name: str
+    metadata_filename: str  # marker written into the install dir
+    user_agent: str
+    supported_backends: tuple[str, ...] = ("cpu", "cuda", "metal", "vulkan", "rocm")
+    schema_version: int = SCHEMA_VERSION
+    # Backend to retry when the preferred one has no covering asset: "cpu"
+    # (whisper) ships a CPU bundle in every release; None (llama) reports "no
+    # prebuilt" so the caller falls back to a source build.
+    fallback_backend: str | None = "cpu"
+    staging_root_name: str = INSTALL_STAGING_ROOT_NAME
+    run_staged_validation: bool = False
+    # Hooks. Each mirrors the module-level function it replaces; None keeps the
+    # core default (which raises if truly required).
+    detect_host: Callable[[], Any] | None = None
+    host_platform_tokens: Callable[[Any], tuple[str, str]] | None = None
+    server_binary_name: Callable[[Any], str] | None = None
+    runtime_bin_dir: Callable[[Path, Any], Path] | None = None
+    auto_detect_backend: Callable[[Any], str] | None = None
+
+
+def component_namespace(descriptor: ComponentDescriptor) -> dict[str, Any]:
+    """Materialize a descriptor into the module-like namespace ``ModuleOps``
+    resolves against; core defaults cover anything not listed here."""
+    prefix = descriptor.log_prefix
+
+    def component_log(message: str) -> None:
+        print(f"[{prefix}] {message}", file = sys.stderr)
+
+    namespace: dict[str, Any] = {
+        "COMPONENT": descriptor.component,
+        "SCHEMA_VERSION": descriptor.schema_version,
+        "DEFAULT_PUBLISHED_REPO": descriptor.published_repo,
+        "MANIFEST_ASSET_NAME": descriptor.manifest_asset_name,
+        "SHA256_ASSET_NAME": descriptor.sha256_asset_name,
+        "METADATA_FILENAME": descriptor.metadata_filename,
+        "SUPPORTED_BACKENDS": descriptor.supported_backends,
+        "USER_AGENT": descriptor.user_agent,
+        "FALLBACK_BACKEND": descriptor.fallback_backend,
+        "INSTALL_STAGING_ROOT_NAME": descriptor.staging_root_name,
+        "_RUN_STAGED_PREBUILT_VALIDATION": descriptor.run_staged_validation,
+        "log": component_log,
+    }
+    for hook in (
+        "detect_host",
+        "host_platform_tokens",
+        "server_binary_name",
+        "runtime_bin_dir",
+        "auto_detect_backend",
+    ):
+        value = getattr(descriptor, hook)
+        if value is not None:
+            namespace[hook] = value
+    return namespace
+
+
+def component_ops(descriptor: ComponentDescriptor) -> ModuleOps:
+    return ModuleOps(component_namespace(descriptor))
+
+
+# ── Lock/busy classification ──
+def _os_error_messages(exc: BaseException) -> list[str]:
+    messages: list[str] = []
+    if isinstance(exc, OSError):
+        for value in (
+            getattr(exc, "strerror", None),
+            getattr(exc, "filename", None),
+            getattr(exc, "filename2", None),
+        ):
+            if isinstance(value, str) and value:
+                messages.append(value)
+    text = str(exc)
+    if text:
+        messages.append(text)
+    return [message.lower() for message in messages if message]
+
+
+def is_busy_lock_error(exc: BaseException) -> bool:
+    if isinstance(exc, BusyInstallConflict):
+        return True
+    if isinstance(exc, OSError):
+        if exc.errno in {
+            errno.EACCES,
+            errno.EBUSY,
+            errno.EPERM,
+            errno.ETXTBSY,
+        }:
+            return True
+        if getattr(exc, "winerror", None) in {5, 32, 145}:
+            return True
+    for message in _os_error_messages(exc):
+        if any(
+            needle in message
+            for needle in (
+                "access is denied",
+                "being used by another process",
+                "device or resource busy",
+                "permission denied",
+                "text file busy",
+                "file is in use",
+                "process cannot access the file",
+                "cannot create a file when that file already exists",
+            )
+        ):
+            return True
+    return False
+
+
+# ── HTTP: auth, redirects, retries ──
+def parsed_hostname(url: str | None) -> str | None:
+    if not url:
+        return None
+    try:
+        hostname = urllib.parse.urlparse(url).hostname
+    except Exception:
+        return None
+    if not hostname:
+        return None
+    return hostname.lower()
+
+
+def should_send_github_auth(url: str | None) -> bool:
+    return parsed_hostname(url) in GITHUB_AUTH_HOSTS
+
+
+def should_send_hf_auth(url: str | None) -> bool:
+    return parsed_hostname(url) in HF_AUTH_HOSTS
+
+
+def auth_headers(ops: ModuleOps, url: str | None = None) -> dict[str, str]:
+    headers = {
+        "User-Agent": ops.USER_AGENT,
+    }
+    token = os.environ.get("GH_TOKEN") or os.environ.get("GITHUB_TOKEN")
+    if token and should_send_github_auth(url):
+        headers["Authorization"] = f"Bearer {token}"
+        return headers
+    # Anonymous huggingface.co fetches share a per-IP rate limit CI fleets
+    # exhaust (HTTP 429); authenticate when a token is available.
+    hf_token = os.environ.get("HF_TOKEN") or os.environ.get("HUGGING_FACE_HUB_TOKEN")
+    if hf_token and should_send_hf_auth(url):
+        headers["Authorization"] = f"Bearer {hf_token}"
+    return headers
+
+
+class _CrossHostAuthStrippingRedirectHandler(urllib.request.HTTPRedirectHandler):
+    """Drop Authorization when a redirect leaves the original host.
+
+    huggingface.co redirects downloads to CDN hosts whose signed URLs can reject
+    a foreign Authorization header; urllib forwards headers across redirects by
+    default (requests/huggingface_hub strip them).
+    """
+
+    def redirect_request(self, req, fp, code, msg, headers, newurl):
+        new_request = super().redirect_request(req, fp, code, msg, headers, newurl)
+        if new_request is not None and parsed_hostname(newurl) != parsed_hostname(req.full_url):
+            new_request.headers.pop("Authorization", None)
+            new_request.unredirected_hdrs.pop("Authorization", None)
+        return new_request
+
+
+_URL_OPENER = urllib.request.build_opener(_CrossHostAuthStrippingRedirectHandler())
+
+
+def github_api_headers(ops: ModuleOps, url: str | None = None) -> dict[str, str]:
+    return {
+        "Accept": "application/vnd.github+json",
+        **ops.auth_headers(url),
+    }
+
+
+def is_github_api_url(url: str | None) -> bool:
+    return parsed_hostname(url) == "api.github.com"
+
+
+def is_retryable_url_error(exc: Exception) -> bool:
+    if isinstance(exc, urllib.error.HTTPError):
+        # GitHub returns 403 (not 429) on API rate-limit; anonymous calls share a
+        # 60-req/hour bucket per runner IP that CI fleets exhaust. Treat 403
+        # against api.github.com as retryable so we get a backoff cycle or two
+        # (honouring Retry-After / X-RateLimit-Reset) before the source-build
+        # fallback fires. 403s on other hosts (private downloads, auth) stay non-retryable.
+        if exc.code == 403:
+            return is_github_api_url(getattr(exc, "url", None))
+        return exc.code in RETRYABLE_HTTP_STATUS
+    if isinstance(exc, urllib.error.URLError):
+        return True
+    if isinstance(exc, TimeoutError):
+        return True
+    if isinstance(exc, socket.timeout):
+        return True
+    return False
+
+
+def _http_error_retry_delay(exc: Exception) -> float | None:
+    """Recommended wait from rate-limit headers on a 403/429.
+
+    None when no header is present or the wait exceeds
+    _RATE_LIMIT_WAIT_CAP_SECONDS (the source-build fallback is faster).
+    """
+    if not isinstance(exc, urllib.error.HTTPError):
+        return None
+    headers = getattr(exc, "headers", None)
+    if headers is None:
+        return None
+    retry_after = headers.get("Retry-After")
+    if retry_after and retry_after.strip().isdigit():
+        wait = float(retry_after.strip())
+        return wait if wait <= _RATE_LIMIT_WAIT_CAP_SECONDS else None
+    rate_reset = headers.get("X-RateLimit-Reset")
+    if rate_reset and rate_reset.strip().isdigit():
+        wait = float(rate_reset.strip()) - time.time()
+        if 0.0 < wait <= _RATE_LIMIT_WAIT_CAP_SECONDS:
+            return wait + 1.0  # +1s of slack so the bucket is fresh
+    return None
+
+
+def sleep_backoff(
+    attempt: int,
+    *,
+    base_delay: float = HTTP_FETCH_BASE_DELAY_SECONDS,
+    exc: Exception | None = None,
+) -> None:
+    delay = base_delay * (2 ** max(attempt - 1, 0))
+    header_delay = _http_error_retry_delay(exc) if exc is not None else None
+    if header_delay is not None:
+        delay = max(delay, header_delay)
+    delay += random.uniform(0.0, 0.2)
+    time.sleep(delay)
+
+
+# ── Atomic writes and hashing ──
+def atomic_write_bytes(destination: Path, data: bytes) -> None:
+    destination.parent.mkdir(parents = True, exist_ok = True)
+    with tempfile.NamedTemporaryFile(
+        prefix = destination.name + ".tmp-",
+        dir = destination.parent,
+        delete = False,
+    ) as handle:
+        tmp_path = Path(handle.name)
+        handle.write(data)
+        handle.flush()
+        os.fsync(handle.fileno())
+    os.replace(tmp_path, destination)
+
+
+def atomic_replace_from_tempfile(tmp_path: Path, destination: Path) -> None:
+    destination.parent.mkdir(parents = True, exist_ok = True)
+    os.replace(tmp_path, destination)
+
+
+def sha256_file(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as handle:
+        for chunk in iter(lambda: handle.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def sha256_bytes(data: bytes) -> str:
+    return hashlib.sha256(data).hexdigest()
+
+
+def normalize_sha256_digest(value: str | None) -> str | None:
+    if not isinstance(value, str) or not value:
+        return None
+    lowered = value.lower()
+    if lowered.startswith("sha256:"):
+        lowered = lowered.split(":", 1)[1]
+    if len(lowered) != 64 or any(ch not in "0123456789abcdef" for ch in lowered):
+        return None
+    return lowered
+
+
+def validate_schema_version(
+    payload: dict[str, Any],
+    *,
+    label: str,
+    schema_version: int = SCHEMA_VERSION,
+    error: type[Exception] = RuntimeError,
+) -> None:
+    value = payload.get("schema_version")
+    if value is None:
+        return
+    try:
+        normalized = int(value)
+    except (TypeError, ValueError) as exc:
+        raise error(f"{label} schema_version was not an integer") from exc
+    if normalized != schema_version:
+        raise error(f"{label} schema_version={normalized} is unsupported")
+
+
+# ── Download progress ──
+def format_byte_count(num_bytes: float) -> str:
+    units = ["B", "KiB", "MiB", "GiB", "TiB"]
+    value = float(num_bytes)
+    for unit in units:
+        if abs(value) < 1024.0 or unit == units[-1]:
+            if unit == "B":
+                return f"{int(value)} {unit}"
+            return f"{value:.1f} {unit}"
+        value /= 1024.0
+    return f"{num_bytes:.1f} B"
+
+
+def _progress_percent_step() -> int:
+    """Non-tty milestone granularity. The in-app updater sets
+    UNSLOTH_PROGRESS_PERCENT_STEP=5 for finer progress lines."""
+    try:
+        step = int(os.environ.get("UNSLOTH_PROGRESS_PERCENT_STEP", "25"))
+    except ValueError:
+        return 25
+    return min(max(step, 1), 50)
+
+
+class DownloadProgress:
+    def __init__(self, label: str, total_bytes: int | None) -> None:
+        self.label = label
+        self.total_bytes = total_bytes if total_bytes and total_bytes > 0 else None
+        self.start_time = time.monotonic()
+        self.last_emit = 0.0
+        term_ok = os.environ.get("TERM", "").lower() != "dumb"
+        self.stream = (
+            sys.stderr if sys.stderr.isatty() else sys.stdout if sys.stdout.isatty() else sys.stderr
+        )
+        self.is_tty = term_ok and self.stream.isatty()
+        self.completed = False
+        self.milestone_step = _progress_percent_step()
+        self.last_milestone_percent = -1
+        self.last_milestone_bytes = 0
+        self.has_rendered_tty_progress = False
+
+    def _render(
+        self,
+        downloaded_bytes: int,
+        *,
+        final: bool = False,
+    ) -> str:
+        elapsed = max(time.monotonic() - self.start_time, 1e-6)
+        speed = downloaded_bytes / elapsed
+        speed_text = f"{format_byte_count(speed)}/s"
+        if self.total_bytes is not None:
+            percent = min(100.0, (downloaded_bytes / self.total_bytes) * 100.0)
+            return (
+                f"{self.label}: {percent:5.1f}% "
+                f"({format_byte_count(downloaded_bytes)}/{format_byte_count(self.total_bytes)}) "
+                f"at {speed_text}"
+            )
+        if final:
+            return f"{self.label}: {format_byte_count(downloaded_bytes)} downloaded at {speed_text}"
+        return f"{self.label}: {format_byte_count(downloaded_bytes)} downloaded at {speed_text}"
+
+    def update(self, downloaded_bytes: int) -> None:
+        now = time.monotonic()
+        if self.is_tty:
+            elapsed = now - self.start_time
+            if not self.has_rendered_tty_progress:
+                if self.total_bytes is not None and downloaded_bytes >= self.total_bytes:
+                    return
+                if elapsed < TTY_PROGRESS_START_DELAY_SECONDS:
+                    return
+            min_interval = 0.2
+            if (
+                self.has_rendered_tty_progress
+                and not self.completed
+                and (now - self.last_emit) < min_interval
+            ):
+                return
+            self.last_emit = now
+            line = self._render(downloaded_bytes)
+            self.stream.write("\r\033[K" + line)
+            self.stream.flush()
+            self.has_rendered_tty_progress = True
+            return
+
+        should_emit = False
+        if self.total_bytes is not None:
+            percent = int((downloaded_bytes * 100) / max(self.total_bytes, 1))
+            step = self.milestone_step
+            milestone_percent = min((percent // step) * step, 100)
+            if milestone_percent > self.last_milestone_percent and milestone_percent < 100:
+                self.last_milestone_percent = milestone_percent
+                should_emit = True
+        else:
+            byte_step = 25 * 1024 * 1024
+            if (
+                downloaded_bytes - self.last_milestone_bytes >= byte_step
+                and (now - self.last_emit) >= 5.0
+            ):
+                self.last_milestone_bytes = downloaded_bytes
+                should_emit = True
+
+        if not should_emit:
+            return
+
+        self.last_emit = now
+        self.stream.write(self._render(downloaded_bytes) + "\n")
+        self.stream.flush()
+
+    def finish(self, downloaded_bytes: int) -> None:
+        self.completed = True
+        line = self._render(downloaded_bytes, final = True)
+        if self.is_tty:
+            if not self.has_rendered_tty_progress:
+                return
+            self.stream.write("\r\033[K")
+        else:
+            self.stream.write(line + "\n")
+        self.stream.flush()
+
+
+def download_label_from_url(url: str) -> str:
+    name = Path(urllib.parse.urlparse(url).path).name
+    return name or url
+
+
+# ── Downloads ──
+def download_bytes(
+    ops: ModuleOps,
+    url: str,
+    *,
+    timeout: int = 120,
+    attempts: int | None = None,
+    headers: dict[str, str] | None = None,
+    progress_label: str | None = None,
+) -> bytes:
+    if attempts is None:
+        attempts = ops.HTTP_FETCH_ATTEMPTS
+    last_exc: Exception | None = None
+    for attempt in range(1, attempts + 1):
+        try:
+            request = urllib.request.Request(url, headers = headers or ops.auth_headers(url))
+            with ops._URL_OPENER.open(request, timeout = timeout) as response:
+                total_bytes: int | None = None
+                content_length = response.headers.get("Content-Length")
+                if content_length and content_length.isdigit():
+                    total_bytes = int(content_length)
+                progress = DownloadProgress(progress_label, total_bytes) if progress_label else None
+                data = bytearray()
+                while True:
+                    chunk = response.read(1024 * 1024)
+                    if not chunk:
+                        break
+                    data.extend(chunk)
+                    if progress is not None:
+                        progress.update(len(data))
+                if progress is not None:
+                    progress.finish(len(data))
+                return bytes(data)
+        except Exception as exc:
+            last_exc = exc
+            if attempt >= attempts or not is_retryable_url_error(exc):
+                raise
+            ops.log(f"fetch failed ({attempt}/{attempts}) for {url}: {exc}; retrying")
+            sleep_backoff(attempt, exc = exc)
+    assert last_exc is not None
+    raise last_exc
+
+
+def fetch_json(ops: ModuleOps, url: str) -> Any:
+    attempts = ops.JSON_FETCH_ATTEMPTS if is_github_api_url(url) else 1
+    last_decode_exc: Exception | None = None
+    for attempt in range(1, attempts + 1):
+        try:
+            data = ops.download_bytes(
+                url,
+                timeout = 30,
+                headers = ops.github_api_headers(url)
+                if is_github_api_url(url)
+                else ops.auth_headers(url),
+            )
+        except urllib.error.HTTPError as exc:
+            if exc.code == 403 and is_github_api_url(url):
+                hint = ""
+                if not (os.environ.get("GH_TOKEN") or os.environ.get("GITHUB_TOKEN")):
+                    hint = "; set GH_TOKEN or GITHUB_TOKEN to avoid GitHub API rate limits"
+                raise RuntimeError(f"GitHub API returned 403 for {url}{hint}") from exc
+            raise
+        if not data:
+            last_decode_exc = RuntimeError(f"downloaded empty JSON payload from {url}")
+        else:
+            try:
+                payload = json.loads(data.decode("utf-8"))
+            except (UnicodeDecodeError, json.JSONDecodeError) as exc:
+                last_decode_exc = RuntimeError(f"downloaded invalid JSON from {url}: {exc}")
+            else:
+                if not isinstance(payload, dict) and not isinstance(payload, list):
+                    raise RuntimeError(
+                        f"downloaded unexpected JSON type from {url}: {type(payload).__name__}"
+                    )
+                return payload
+        if attempt >= attempts:
+            assert last_decode_exc is not None
+            raise last_decode_exc
+        ops.log(f"json fetch failed ({attempt}/{attempts}) for {url}; retrying")
+        sleep_backoff(attempt)
+    assert last_decode_exc is not None
+    raise last_decode_exc
+
+
+def download_file(ops: ModuleOps, url: str, destination: Path) -> None:
+    destination.parent.mkdir(parents = True, exist_ok = True)
+    attempts = ops.HTTP_FETCH_ATTEMPTS
+    last_exc: Exception | None = None
+    for attempt in range(1, attempts + 1):
+        tmp_path: Path | None = None
+        try:
+            request = urllib.request.Request(url, headers = ops.auth_headers(url))
+            with tempfile.NamedTemporaryFile(
+                prefix = destination.name + ".tmp-",
+                dir = destination.parent,
+                delete = False,
+            ) as handle:
+                tmp_path = Path(handle.name)
+                with ops._URL_OPENER.open(request, timeout = 120) as response:
+                    total_bytes: int | None = None
+                    content_length = response.headers.get("Content-Length")
+                    if content_length and content_length.isdigit():
+                        total_bytes = int(content_length)
+                    progress = DownloadProgress(f"Downloading {destination.name}", total_bytes)
+                    downloaded_bytes = 0
+                    while True:
+                        chunk = response.read(1024 * 1024)
+                        if not chunk:
+                            break
+                        handle.write(chunk)
+                        downloaded_bytes += len(chunk)
+                        progress.update(downloaded_bytes)
+                    progress.finish(downloaded_bytes)
+                handle.flush()
+                os.fsync(handle.fileno())
+            if not tmp_path.exists() or tmp_path.stat().st_size == 0:
+                raise RuntimeError(f"downloaded empty file from {url}")
+            atomic_replace_from_tempfile(tmp_path, destination)
+            return
+        except Exception as exc:
+            last_exc = exc
+            if tmp_path is not None:
+                try:
+                    tmp_path.unlink(missing_ok = True)
+                except Exception:
+                    pass
+            if attempt >= attempts or not is_retryable_url_error(exc):
+                raise
+            ops.log(f"download failed ({attempt}/{attempts}) for {url}: {exc}; retrying")
+            sleep_backoff(attempt, exc = exc)
+    assert last_exc is not None
+    raise last_exc
+
+
+def download_file_verified(
+    ops: ModuleOps, url: str, destination: Path, *, expected_sha256: str | None, label: str
+) -> None:
+    normalized_expected = normalize_sha256_digest(expected_sha256)
+    if not normalized_expected:
+        ops.download_file(url, destination)
+        ops.log(f"downloaded {label} without a published sha256; relying on install validation")
+        return
+
+    for attempt in range(1, 3):
+        ops.download_file(url, destination)
+        actual_sha256 = ops.sha256_file(destination)
+        if actual_sha256 == normalized_expected:
+            ops.log(f"verified {label} sha256={actual_sha256}")
+            return
+
+        ops.log(
+            f"{label} checksum mismatch on attempt {attempt}/2: "
+            f"expected={normalized_expected} actual={actual_sha256}"
+        )
+        destination.unlink(missing_ok = True)
+        if attempt == 2:
+            raise PrebuiltFallback(
+                f"{label} checksum mismatch after retry: expected={normalized_expected} actual={actual_sha256}"
+            )
+        ops.log(f"retrying {label} download after checksum mismatch")
+
+
+def download_file_verified_strict(
+    ops: ModuleOps, url: str, destination: Path, *, expected_sha256: str, label: str
+) -> None:
+    """Verified download with a required digest (the generic flow fails closed on
+    a missing checksum, so None never reaches here)."""
+    for attempt in range(1, 3):
+        ops.download_file(url, destination)
+        actual = ops.sha256_file(destination)
+        if actual == expected_sha256:
+            ops.log(f"verified {label} sha256={actual}")
+            return
+        ops.log(
+            f"{label} checksum mismatch {attempt}/2: expected={expected_sha256} actual={actual}"
+        )
+        destination.unlink(missing_ok = True)
+        if attempt == 2:
+            raise PrebuiltFallback(f"{label} checksum mismatch after retry")
+
+
+# ── GitHub release primitives ──
+def release_asset_map(release: dict[str, Any]) -> dict[str, str]:
+    assets = release.get("assets")
+    if not isinstance(assets, list):
+        return {}
+    return {
+        asset["name"]: asset.get("browser_download_url", "")
+        for asset in assets
+        if isinstance(asset, dict)
+        and isinstance(asset.get("name"), str)
+        and isinstance(asset.get("browser_download_url"), str)
+    }
+
+
+def github_release(
+    ops: ModuleOps,
+    repo: str,
+    tag: str,
+    *,
+    error: type[Exception] = RuntimeError,
+) -> dict[str, Any]:
+    payload = ops.fetch_json(
+        f"https://api.github.com/repos/{repo}/releases/tags/{urllib.parse.quote(tag, safe = '')}"
+    )
+    if not isinstance(payload, dict):
+        raise error(f"unexpected release payload for {repo}@{tag}")
+    return payload
+
+
+def github_release_assets(ops: ModuleOps, repo: str, tag: str) -> dict[str, str]:
+    payload = ops.fetch_json(
+        f"https://api.github.com/repos/{repo}/releases/tags/{urllib.parse.quote(tag, safe = '')}"
+    )
+    if not isinstance(payload, dict):
+        raise RuntimeError(f"unexpected release payload for {repo}@{tag}")
+    return release_asset_map(payload)
+
+
+def release_asset_download_url(repo: str, release_tag: str, asset_name: str) -> str:
+    """Tag-pinned asset URL on the release-assets CDN (github.com redirect, NOT
+    api.github.com, so no 60-req/hour unauthenticated limit)."""
+    return (
+        f"https://github.com/{urllib.parse.quote(repo, safe = '/')}/releases/download/"
+        f"{urllib.parse.quote(release_tag, safe = '')}/"
+        f"{urllib.parse.quote(asset_name, safe = '')}"
+    )
+
+
+def download_host_latest_release_tag(ops: ModuleOps, repo: str) -> str | None:
+    """Latest release tag from github.com/<repo>/releases/latest via its redirect
+    target (no api.github.com call). None on 404 so the caller falls back to the
+    API. /releases/latest resolves by created_at/make_latest, which can lag the
+    published_at newest the freshness check uses -- acceptable for install."""
+    url = f"https://github.com/{urllib.parse.quote(repo, safe = '/')}/releases/latest"
+    request = urllib.request.Request(
+        url,
+        method = "HEAD",
+        headers = {"User-Agent": ops.USER_AGENT},
+    )
+    try:
+        with ops._URL_OPENER.open(request, timeout = 30) as response:
+            final_url = response.geturl()
+    except urllib.error.HTTPError as exc:
+        if exc.code == 404:
+            return None
+        raise
+    marker = "/releases/tag/"
+    index = final_url.find(marker)
+    if index == -1:
+        return None
+    tag = urllib.parse.unquote(final_url[index + len(marker) :]).strip("/")
+    return tag or None
+
+
+def fetch_download_host_json(ops: ModuleOps, url: str) -> Any:
+    # Public CDN asset: plain unauthenticated GET, not the rate-limited API.
+    data = ops.download_bytes(
+        url,
+        timeout = 30,
+        headers = {"User-Agent": ops.USER_AGENT},
+    )
+    return json.loads(data.decode("utf-8"))
+
+
+# ── Archive extraction (traversal/symlink guarded) ──
+def extract_archive(archive_path: Path, destination: Path) -> None:
+    def safe_extract_path(base: Path, member_name: str) -> Path:
+        normalized = member_name.replace("\\", "/")
+        member_path = Path(normalized)
+        if member_path.is_absolute():
+            raise PrebuiltFallback(f"archive member used an absolute path: {member_name}")
+
+        target = (base / member_path).resolve()
+        base_resolved = base.resolve()
+        try:
+            target.relative_to(base_resolved)
+        except ValueError as exc:
+            raise PrebuiltFallback(f"archive member escaped destination: {member_name}") from exc
+        return target
+
+    def _try_repair_missing_slash(
+        member_name: str, link_name: str, archive_names: set[str]
+    ) -> str | None:
+        """Repair a mangled symlink from some upstream llama.cpp Mac releases
+        (e.g. b9165, b9169) whose linkname drops the separator AND the file
+        basename's leading char between the top-level dir and the rest:
+
+            llama-b9165/libggml-rpc.0.dylib -> llama-b9165ibggml-rpc.0.11.1.dylib
+
+        Detect the pattern (linkname starts with the top-level dir but no
+        following slash), then find the archive entry under that dir whose
+        basename ends with the mangled suffix; only accept a unique match.
+        Returns the corrected linkname relative to the member's parent dir --
+        callers join it with `target.parent`, so a full `top/file` path would
+        double the prefix into `top/top/file`."""
+        if "/" not in member_name or "/" in link_name:
+            return None
+        top, _, _ = member_name.partition("/")
+        if not link_name.startswith(top) or len(link_name) <= len(top):
+            return None
+        bad_suffix = link_name[len(top) :]
+        if not bad_suffix or bad_suffix.startswith("/"):
+            return None
+        prefix = f"{top}/"
+        candidates = [
+            name
+            for name in archive_names
+            if name.startswith(prefix)
+            and "/" not in name[len(prefix) :]
+            and name[len(prefix) :].endswith(bad_suffix)
+        ]
+        if len(candidates) != 1:
+            return None
+        # Strip the top-level dir so the caller's `target.parent / Path(...)`
+        # resolves inside the staging dir, not a duplicate `top/top/...` path.
+        return candidates[0][len(prefix) :]
+
+    def safe_link_target(
+        base: Path, member_name: str, link_name: str, target: Path, archive_names: set[str]
+    ) -> tuple[str, Path]:
+        normalized = link_name.replace("\\", "/")
+        repaired = _try_repair_missing_slash(member_name, normalized, archive_names)
+        if repaired is not None:
+            normalized = repaired
+        link_path = Path(normalized)
+        if link_path.is_absolute():
+            raise PrebuiltFallback(
+                f"archive link used an absolute target: {member_name} -> {link_name}"
+            )
+        if not normalized:
+            raise PrebuiltFallback(f"archive link used an empty target: {member_name}")
+
+        resolved = (target.parent / link_path).resolve()
+        base_resolved = base.resolve()
+        try:
+            resolved.relative_to(base_resolved)
+        except ValueError as exc:
+            raise PrebuiltFallback(
+                f"archive link escaped destination: {member_name} -> {link_name}"
+            ) from exc
+        return normalized, resolved
+
+    def extract_zip_safely(source: Path, base: Path) -> None:
+        with zipfile.ZipFile(source) as archive:
+            for member in archive.infolist():
+                target = safe_extract_path(base, member.filename)
+                mode = (member.external_attr >> 16) & 0o170000
+                if mode == 0o120000:
+                    raise PrebuiltFallback(
+                        f"zip archive contained a symlink entry: {member.filename}"
+                    )
+                if member.is_dir():
+                    target.mkdir(parents = True, exist_ok = True)
+                    continue
+                target.parent.mkdir(parents = True, exist_ok = True)
+                with archive.open(member, "r") as src, target.open("wb") as dst:
+                    shutil.copyfileobj(src, dst)
+
+    def extract_tar_safely(source: Path, base: Path) -> None:
+        pending_links: list[tuple[tarfile.TarInfo, Path]] = []
+        archive_names: set[str] = set()
+        with tarfile.open(source, "r:gz") as archive:
+            for member in archive.getmembers():
+                archive_names.add(member.name)
+                target = safe_extract_path(base, member.name)
+                if member.isdir():
+                    target.mkdir(parents = True, exist_ok = True)
+                    continue
+                if member.islnk() or member.issym():
+                    pending_links.append((member, target))
+                    continue
+                if not member.isfile():
+                    raise PrebuiltFallback(
+                        f"tar archive contained an unsupported entry: {member.name}"
+                    )
+                target.parent.mkdir(parents = True, exist_ok = True)
+                extracted = archive.extractfile(member)
+                if extracted is None:
+                    raise PrebuiltFallback(f"tar archive entry could not be read: {member.name}")
+                with extracted, target.open("wb") as dst:
+                    shutil.copyfileobj(extracted, dst)
+
+        unresolved = list(pending_links)
+        while unresolved:
+            next_round: list[tuple[tarfile.TarInfo, Path]] = []
+            progressed = False
+            for member, target in unresolved:
+                normalized_link, resolved_target = safe_link_target(
+                    base, member.name, member.linkname, target, archive_names
+                )
+                if not resolved_target.exists() and not resolved_target.is_symlink():
+                    next_round.append((member, target))
+                    continue
+                if resolved_target.is_dir():
+                    raise PrebuiltFallback(
+                        f"archive link targeted a directory: {member.name} -> {member.linkname}"
+                    )
+
+                target.parent.mkdir(parents = True, exist_ok = True)
+                if target.exists() or target.is_symlink():
+                    target.unlink()
+
+                if member.issym():
+                    target.symlink_to(normalized_link)
+                else:
+                    shutil.copy2(resolved_target, target)
+                progressed = True
+
+            if not progressed:
+                details = ", ".join(
+                    f"{member.name} -> {member.linkname}" for member, _ in next_round
+                )
+                raise PrebuiltFallback(f"tar archive contained unresolved link entries: {details}")
+            unresolved = next_round
+
+    destination.mkdir(parents = True, exist_ok = True)
+    if archive_path.name.endswith(".zip"):
+        extract_zip_safely(archive_path, destination)
+        return
+    if archive_path.name.endswith(".tar.gz"):
+        extract_tar_safely(archive_path, destination)
+        return
+    raise PrebuiltFallback(f"unsupported archive format: {archive_path.name}")
+
+
+def restore_tar_exec_bits(archive_path: Path, destination: Path) -> None:
+    """Re-apply tar exec bits after the guarded extraction writes plain files;
+    server binaries must stay executable on Unix."""
+    if os.name == "nt" or not archive_path.name.endswith(".tar.gz"):
+        return
+    with tarfile.open(archive_path, "r:gz") as archive:
+        for member in archive.getmembers():
+            if not (member.isfile() and member.mode & 0o111):
+                continue
+            # Paths were already traversal-validated by the extractor above.
+            target = destination / Path(member.name.replace("\\", "/"))
+            if target.is_file():
+                os.chmod(target, target.stat().st_mode | 0o111)
+
+
+# ── Install lock ──
+@contextmanager
+def install_lock(lock_path: Path) -> Iterator[None]:
+    lock_path.parent.mkdir(parents = True, exist_ok = True)
+
+    if FileLock is None:
+        # Fallback lock: exclusive file creation, writing our PID so stale locks
+        # from crashed processes can be detected.
+        fd: int | None = None
+        deadline = time.monotonic() + INSTALL_LOCK_TIMEOUT_SECONDS
+        while True:
+            try:
+                fd = os.open(str(lock_path), os.O_CREAT | os.O_EXCL | os.O_RDWR)
+                try:
+                    os.write(fd, f"{os.getpid()}\n".encode())
+                    os.fsync(fd)
+                except Exception:
+                    os.close(fd)
+                    fd = None
+                    lock_path.unlink(missing_ok = True)
+                    raise
+                break
+            except FileExistsError:
+                stale = False
+                try:
+                    raw = lock_path.read_text().strip()
+                except FileNotFoundError:
+                    # Lock vanished between our open and read -- retry
+                    continue
+                if not raw:
+                    # Exists but PID not yet written; wait for the write to land.
+                    if time.monotonic() >= deadline:
+                        raise BusyInstallConflict(
+                            f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
+                        )
+                    time.sleep(0.1)
+                    continue
+                try:
+                    holder_pid = int(raw)
+                    os.kill(holder_pid, 0)  # signal 0 = existence check
+                except ValueError:
+                    stale = True  # PID unreadable (corrupted file)
+                except ProcessLookupError:
+                    stale = True  # holder is dead
+                except PermissionError:
+                    pass  # alive but owned by another user -- not stale
+                if stale:
+                    lock_path.unlink(missing_ok = True)
+                    continue
+                if time.monotonic() >= deadline:
+                    raise BusyInstallConflict(
+                        f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
+                    )
+                time.sleep(0.5)
+        try:
+            yield
+        finally:
+            if fd is not None:
+                os.close(fd)
+            lock_path.unlink(missing_ok = True)
+        return
+
+    try:
+        with FileLock(lock_path, timeout = INSTALL_LOCK_TIMEOUT_SECONDS):
+            yield
+    except FileLockTimeout as exc:
+        raise BusyInstallConflict(
+            f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
+        ) from exc
+
+
+def install_lock_path(install_dir: Path) -> Path:
+    return install_dir.parent / f".{install_dir.name}.install.lock"
+
+
+# ── macOS version parsing ──
+def parse_macos_version(value: str | None) -> tuple[int, int] | None:
+    """Parse a macOS product version into (major, minor).
+
+    Handles "14.7.1", "15.5", "26.0", bare "26". None when empty/unparseable
+    (callers then defer to runtime validation rather than reject every prebuilt)."""
+    if not value:
+        return None
+    match = re.match(r"\s*(\d+)(?:\.(\d+))?", str(value))
+    if not match:
+        return None
+    return int(match.group(1)), int(match.group(2) or 0)
+
+
+# ── GPU and CUDA runtime-line selection primitives ──
+def normalize_compute_cap(value: Any) -> str | None:
+    raw = str(value).strip()
+    if not raw:
+        return None
+    if "." in raw:
+        parts = raw.split(".", 1)
+        if len(parts) != 2:
+            return None
+        major, minor = parts
+        if not major.isdigit() or not minor.isdigit():
+            return None
+        return f"{int(major)}{int(minor)}"
+    if raw.isdigit():
+        return str(int(raw))
+    return None
+
+
+def normalize_compute_caps(compute_caps: Iterable[str]) -> list[str]:
+    normalized: list[str] = []
+    seen: set[str] = set()
+    for raw in compute_caps:
+        normalized_value = normalize_compute_cap(raw)
+        if normalized_value is None:
+            continue
+        if normalized_value in seen:
+            continue
+        seen.add(normalized_value)
+        normalized.append(normalized_value)
+    normalized.sort(key = int)
+    return normalized
+
+
+def parse_cuda_visible_devices(value: str | None) -> list[str] | None:
+    if value is None:
+        return None
+    raw = value.strip()
+    if not raw or raw == "-1":
+        return []
+    return [token.strip() for token in raw.split(",") if token.strip()]
+
+
+def supports_explicit_visible_device_matching(visible_devices: list[str] | None) -> bool:
+    if not visible_devices:
+        return False
+    for token in visible_devices:
+        lowered = token.lower()
+        if token.isdigit() or lowered.startswith("gpu-"):
+            continue
+        return False
+    return True
+
+
+def select_visible_gpu_rows(
+    gpu_rows: Iterable[tuple[str, str, str]], visible_devices: list[str] | None
+) -> list[tuple[str, str, str]]:
+    rows = list(gpu_rows)
+    if visible_devices is None:
+        return rows
+    if not visible_devices:
+        return []
+
+    by_index = {index: (index, uuid, cap) for index, uuid, cap in rows}
+    by_uuid = {uuid.lower(): (index, uuid, cap) for index, uuid, cap in rows}
+    selected: list[tuple[str, str, str]] = []
+    seen_indices: set[str] = set()
+    for token in visible_devices:
+        row = by_index.get(token)
+        if row is None:
+            normalized_token = token.lower()
+            row = by_uuid.get(normalized_token)
+            if row is None and normalized_token.startswith("gpu-"):
+                row = by_uuid.get(normalized_token)
+            if row is None and not normalized_token.startswith("gpu-"):
+                row = by_uuid.get("gpu-" + normalized_token)
+        if row is None:
+            continue
+        index = row[0]
+        if index in seen_indices:
+            continue
+        seen_indices.add(index)
+        selected.append(row)
+    return selected
+
+
+def dir_provides_exact_library(directory: str | Path, library: str) -> bool:
+    if not library:
+        return False
+    candidate = Path(directory) / library
+    return candidate.exists() and (candidate.is_file() or candidate.is_symlink())
+
+
+def linux_runtime_dirs_for_required_libraries(
+    ops: ModuleOps, required_libraries: Iterable[str]
+) -> list[str]:
+    required = [library for library in required_libraries if library]
+    candidates: list[str | Path] = []
+
+    env_dirs = os.environ.get("CUDA_RUNTIME_LIB_DIR", "")
+    if env_dirs:
+        candidates.extend(part for part in env_dirs.split(os.pathsep) if part)
+    ld_library_path = os.environ.get("LD_LIBRARY_PATH", "")
+    if ld_library_path:
+        candidates.extend(part for part in ld_library_path.split(os.pathsep) if part)
+
+    cuda_roots: list[Path] = []
+    for name in ("CUDA_HOME", "CUDA_PATH", "CUDA_ROOT"):
+        value = os.environ.get(name)
+        if value:
+            cuda_roots.append(Path(value))
+    cuda_roots.extend(Path(path) for path in ops.glob_paths("/usr/local/cuda", "/usr/local/cuda-*"))
+
+    for root in cuda_roots:
+        candidates.extend(
+            [
+                root / "lib",
+                root / "lib64",
+                root / "targets" / "x86_64-linux" / "lib",
+            ]
+        )
+
+    candidates.extend(
+        Path(path)
+        for path in ops.glob_paths(
+            "/lib",
+            "/lib64",
+            "/usr/lib",
+            "/usr/lib64",
+            "/usr/local/lib",
+            "/usr/local/lib64",
+            "/lib/x86_64-linux-gnu",
+            "/usr/lib/x86_64-linux-gnu",
+        )
+    )
+    candidates.extend(
+        Path(path) for path in ops.glob_paths("/usr/local/lib/ollama/cuda_v*", "/usr/lib/wsl/lib")
+    )
+    candidates.extend(Path(path) for path in ops.python_runtime_dirs())
+    candidates.extend(Path(path) for path in ops.ldconfig_runtime_dirs(required))
+
+    resolved = ops.dedupe_existing_dirs(candidates)
+    if not required:
+        return resolved
+
+    matched: list[tuple[int, str]] = []
+    for directory in resolved:
+        provided = sum(1 for library in required if dir_provides_exact_library(directory, library))
+        if provided:
+            matched.append((provided, directory))
+
+    matched.sort(key = lambda item: item[0], reverse = True)
+    return [directory for _, directory in matched]
+
+
+def detected_linux_runtime_lines(ops: ModuleOps) -> tuple[list[str], dict[str, list[str]]]:
+    """`cuda<major>` lines with a matching libcudart/libcublas file on disk (glob
+    match, so a versioned-only file counts), plus the dirs that matched."""
+    line_requirements = {
+        f"cuda{m}": [f"libcudart.so.{m}", f"libcublas.so.{m}"]
+        for m in range(_MAX_PROBE_CUDA_MAJOR, _MIN_CUDA_MAJOR - 1, -1)
+    }
+    detected: list[str] = []
+    runtime_dirs: dict[str, list[str]] = {}
+    for line, required in line_requirements.items():
+        dirs = ops.linux_runtime_dirs_for_required_libraries(required)
+        library_matches: dict[str, list[str]] = {}
+        matching_dirs: list[str] = []
+        for library in required:
+            matched_dirs = [
+                directory for directory in dirs if any(Path(directory).glob(f"{library}*"))
+            ]
+            if not matched_dirs:
+                library_matches = {}
+                matching_dirs = []
+                break
+            library_matches[library] = matched_dirs
+            for directory in matched_dirs:
+                if directory not in matching_dirs:
+                    matching_dirs.append(directory)
+        if library_matches:
+            detected.append(line)
+            runtime_dirs[line] = matching_dirs
+    return detected, runtime_dirs
+
+
+def windows_runtime_line_info() -> dict[str, tuple[str, ...]]:
+    # Generated per CUDA major (newest first) so a new toolkit is detected without
+    # a code change while the cudart64_<major>.dll naming holds.
+    return {
+        f"cuda{m}": (
+            f"cudart64_{m}*.dll",
+            f"cublas64_{m}*.dll",
+            f"cublasLt64_{m}*.dll",
+        )
+        for m in range(_MAX_PROBE_CUDA_MAJOR, _MIN_CUDA_MAJOR - 1, -1)
+    }
+
+
+def detected_windows_runtime_lines(ops: ModuleOps) -> tuple[list[str], dict[str, list[str]]]:
+    dirs = ops.windows_runtime_dirs()
+    detected: list[str] = []
+    runtime_dirs: dict[str, list[str]] = {}
+    for runtime_line, required_patterns in windows_runtime_line_info().items():
+        matching_dirs = ops.windows_runtime_dirs_for_patterns(required_patterns, dirs)
+        if matching_dirs:
+            detected.append(runtime_line)
+            runtime_dirs[runtime_line] = matching_dirs
+    return detected, runtime_dirs
+
+
+def compatible_linux_runtime_lines(host: Any) -> list[str]:
+    if not host.driver_cuda_version:
+        return []
+    major, _minor = host.driver_cuda_version
+    if major < _MIN_CUDA_MAJOR:
+        return []
+    return _cuda_runtime_lines_for_major(major)
+
+
+def runtime_line_from_cuda_version(cuda_version: str | None) -> str | None:
+    if not cuda_version:
+        return None
+    raw = str(cuda_version).strip()
+    if not raw:
+        return None
+    major, _, _ = raw.partition(".")
+    if major == "12":
+        return "cuda12"
+    if major == "13":
+        return "cuda13"
+    return None
+
+
+@dataclass
+class CudaRuntimePreference:
+    runtime_line: str | None
+    selection_log: list[str]
+
+
+def detect_torch_cuda_runtime_preference(host: Any) -> CudaRuntimePreference:
+    selection_log: list[str] = []
+    if host.is_macos:
+        selection_log.append("torch_cuda_preference: skipped on macOS")
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+    if not (host.has_usable_nvidia and (host.is_linux or host.is_windows)):
+        selection_log.append(
+            "torch_cuda_preference: skipped because CUDA host prerequisites were not met"
+        )
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+
+    try:
+        import torch
+    except Exception as exc:
+        selection_log.append(f"torch_cuda_preference: import failed: {exc}")
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+
+    cuda_version = getattr(getattr(torch, "version", None), "cuda", None)
+    if not isinstance(cuda_version, str) or not cuda_version.strip():
+        selection_log.append(
+            "torch_cuda_preference: torch.version.cuda missing; skipping Torch shortcut"
+        )
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+
+    try:
+        cuda_available = bool(torch.cuda.is_available())
+    except Exception as exc:
+        selection_log.append(f"torch_cuda_preference: torch.cuda.is_available() failed: {exc}")
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+
+    if not cuda_available:
+        selection_log.append(
+            "torch_cuda_preference: torch.cuda.is_available() returned False; falling back to normal selection"
+        )
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+
+    runtime_line = runtime_line_from_cuda_version(cuda_version)
+    if runtime_line is None:
+        selection_log.append(
+            f"torch_cuda_preference: unsupported torch.version.cuda={cuda_version}; falling back to normal selection"
+        )
+        return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
+
+    selection_log.append(
+        "torch_cuda_preference: selected runtime_line="
+        f"{runtime_line} from torch.version.cuda={cuda_version}"
+    )
+    return CudaRuntimePreference(runtime_line = runtime_line, selection_log = selection_log)
+
+
+def artifact_covers_sms(artifact: Any, host_sms: Iterable[str]) -> bool:
+    """True when every host SM is in the artifact's supported_sms and within its
+    [min_sm, max_sm] range."""
+    if not artifact.supported_sms or artifact.min_sm is None or artifact.max_sm is None:
+        return False
+    supported = {str(value) for value in artifact.supported_sms}
+    return all(sm in supported and artifact.min_sm <= int(sm) <= artifact.max_sm for sm in host_sms)
+
+
+def sm_range(artifact: Any) -> int:
+    """SM-coverage span as a sort key (tighter range wins). A bundle with no SM
+    metadata gets a max range so it sorts last, never outranking a targeted bundle."""
+    if artifact.min_sm is not None and artifact.max_sm is not None:
+        return artifact.max_sm - artifact.min_sm
+    return 9999
+
+
+def blackwell_capable_linux_runtime_lines(host_sms: list[str], artifacts: list[Any]) -> list[str]:
+    """CUDA runtime lines (highest major first) shipping a bundle covering every
+    visible host SM. Lets a Blackwell host prefer a native sm_120 line over torch's
+    reported line, mirroring the Windows Blackwell preference."""
+    lines: set[str] = set()
+    for artifact in artifacts:
+        line = artifact.runtime_line
+        # Only rank "cuda<major>" lines; skip malformed/future-format values
+        # (e.g. "cuda13.1") rather than crash the major sort.
+        if not (line and line.startswith("cuda") and line[len("cuda") :].isdigit()):
+            continue
+        if not artifact.supported_sms or artifact.min_sm is None or artifact.max_sm is None:
+            continue
+        supported = {str(value) for value in artifact.supported_sms}
+        if all(
+            sm in supported and artifact.min_sm <= int(sm) <= artifact.max_sm for sm in host_sms
+        ):
+            lines.add(line)
+    return sorted(lines, key = lambda line: int(line[len("cuda") :]), reverse = True)
+
+
+def host_is_blackwell(host: Any) -> bool:
+    caps = normalize_compute_caps(host.compute_caps)
+    return bool(caps) and int(caps[-1]) >= _BLACKWELL_MIN_SM
+
+
+def blackwell_min_toolkit_for_host(host: Any) -> tuple[int, int]:
+    """Minimum CUDA toolkit this Blackwell host needs: 12.8 for the family, 12.9
+    if any SM is sm_103/sm_121 (no native target before 12.9)."""
+    req = _BLACKWELL_MIN_TOOLKIT
+    for sm in normalize_compute_caps(host.compute_caps):
+        req = max(req, _BLACKWELL_SM_MIN_TOOLKIT.get(int(sm), _BLACKWELL_MIN_TOOLKIT))
+    return req
+
+
+# ════════════════════════════════════════════════════════════════════════════
+# Generic descriptor-driven install flow (whisper dialect: one release carries
+# a manifest of os/arch/backend artifacts plus a same-origin checksum index).
+# ════════════════════════════════════════════════════════════════════════════
+def host_platform_tokens(host: Any) -> tuple[str, str]:
+    """Default (os, arch) asset tokens; components with their own HostInfo field
+    names override this hook."""
+    return host.os_token, host.arch_token
+
+
+# ── Manifest parsing ──
+def parse_manifest(ops: ModuleOps, payload: Any, *, label: str) -> dict[str, Any]:
+    """Validate a component prebuilt manifest and return it normalized.
+
+    Rejects an unknown schema_version or wrong component. Returns keys:
+    schema_version, component, studio_protocol, upstream_tag, source_commit,
+    artifacts (list of dicts).
+    """
+    component = ops.COMPONENT
+    if not isinstance(payload, dict):
+        raise PrebuiltFallback(f"{label} was not a JSON object")
+    validate_schema_version(
+        payload, label = label, schema_version = ops.SCHEMA_VERSION, error = PrebuiltFallback
+    )
+    manifest_component = payload.get("component")
+    if manifest_component != component:
+        raise PrebuiltFallback(
+            f"{label} describes component {manifest_component!r}, expected {component!r}"
+        )
+
+    artifacts_raw = payload.get("artifacts")
+    if not isinstance(artifacts_raw, list):
+        raise PrebuiltFallback(f"{label} omitted an 'artifacts' list")
+    artifacts: list[dict[str, Any]] = []
+    for index, raw in enumerate(artifacts_raw):
+        if not isinstance(raw, dict):
+            ops.log(f"{label} artifact[{index}] ignored: not an object")
+            continue
+        asset = raw.get("asset")
+        if not isinstance(asset, str) or not asset:
+            ops.log(f"{label} artifact[{index}] ignored: missing asset name")
+            continue
+        artifacts.append(raw)
+
+    studio_protocol = payload.get("studio_protocol")
+    return {
+        "schema_version": ops.SCHEMA_VERSION,
+        "component": component,
+        "studio_protocol": studio_protocol if isinstance(studio_protocol, str) else None,
+        "upstream_tag": payload.get("upstream_tag")
+        if isinstance(payload.get("upstream_tag"), str)
+        else None,
+        "source_commit": payload.get("source_commit")
+        if isinstance(payload.get("source_commit"), str)
+        else None,
+        "artifacts": artifacts,
+    }
+
+
+def macos_min_os_ok(ops: ModuleOps, host: Any, min_os: Any) -> bool:
+    """True if a macOS artifact requiring `min_os` can load here. The manifest
+    labels it `macos-<version>` (e.g. `macos-14.0`); strip that prefix before
+    parsing or every entry parses as None and the guard no-ops. Unknown host or
+    min_os -> True (defer to runtime validation)."""
+    if not isinstance(min_os, str) or not min_os.strip():
+        return True
+    raw = min_os.strip()
+    if raw.lower().startswith("macos-"):
+        raw = raw[len("macos-") :]
+    required = ops.parse_macos_version(raw)
+    if required is None or host.macos_version is None:
+        return True
+    return host.macos_version >= required
+
+
+def artifacts_for_host(
+    ops: ModuleOps, manifest: dict[str, Any], host: Any, backend: str
+) -> list[dict[str, Any]]:
+    """Manifest artifacts matching this host os/arch/backend. On macOS, drop any
+    whose `min_os` exceeds the host version."""
+    os_token, arch_token = ops.host_platform_tokens(host)
+    return [
+        artifact
+        for artifact in manifest.get("artifacts", [])
+        if artifact.get("os") == os_token
+        and artifact.get("arch") == arch_token
+        and artifact.get("backend") == backend
+        and (not host.is_macos or ops.macos_min_os_ok(host, artifact.get("min_os")))
+    ]
+
+
+def select_artifact(
+    ops: ModuleOps, manifest: dict[str, Any], host: Any, backend: str
+) -> dict[str, Any] | None:
+    """First manifest artifact matching this host os/arch and backend, or None
+    (caller then applies the component's fallback policy). No accelerator
+    capability matching here: whisper bundles are slim per os/arch (the paired
+    llama.cpp installer already picked SM/gfx-appropriate ggml backends), and
+    llama keeps its own selection chain in install_llama_prebuilt.py."""
+    candidates = ops.artifacts_for_host(manifest, host, backend)
+    return candidates[0] if candidates else None
+
+
+def select_artifact_with_fallback(
+    ops: ModuleOps, manifest: dict[str, Any], host: Any, backend: str
+) -> tuple[dict[str, Any], str, bool]:
+    """Select the backend artifact, else the descriptor's fallback-backend
+    artifact of the same release (whisper: CPU; llama: none, so a GPU miss
+    surfaces as "no prebuilt" and the caller does a source build).
+
+    Returns (artifact, effective_backend, used_fallback). Raises PrebuiltFallback
+    when neither the requested backend nor the fallback has an asset."""
+    os_token, arch_token = ops.host_platform_tokens(host)
+    artifact = ops.select_artifact(manifest, host, backend)
+    if artifact is not None:
+        return artifact, backend, False
+    fallback_backend = ops.FALLBACK_BACKEND
+    if fallback_backend and backend != fallback_backend:
+        fallback_artifact = ops.select_artifact(manifest, host, fallback_backend)
+        if fallback_artifact is not None:
+            ops.log(
+                f"no '{backend}' asset for {os_token}-{arch_token}; "
+                f"falling back to the {fallback_backend.upper()} asset of the same release"
+            )
+            return fallback_artifact, fallback_backend, True
+    raise PrebuiltFallback(
+        f"no {ops.COMPONENT} prebuilt asset for {os_token}-{arch_token} (backend '{backend}')"
+    )
+
+
+def artifact_coverage(artifact: dict[str, Any]) -> dict[str, Any]:
+    """The sm/gfx/min_os coverage recorded for an artifact (marker/fingerprint)."""
+    coverage: dict[str, Any] = {}
+    for key in ("sm_coverage", "gfx_coverage", "min_os", "sm", "gfx"):
+        if key in artifact and artifact.get(key) is not None:
+            coverage[key] = artifact.get(key)
+    return coverage
+
+
+# ── Backend resolution ──
+def auto_detect_backend(ops: ModuleOps, host: Any) -> str:
+    """Host-preferred backend: Apple Silicon -> metal, usable NVIDIA -> cuda,
+    AMD gfx -> rocm, otherwise cpu."""
+    if host.is_apple_silicon:
+        return "metal"
+    if host.has_usable_nvidia:
+        return "cuda"
+    if host.has_rocm:
+        return "rocm"
+    return "cpu"
+
+
+def resolve_backend(ops: ModuleOps, host: Any, requested: str | None, *, cpu_fallback: bool) -> str:
+    """Resolve the effective backend from --backend / --cpu-fallback and detection."""
+    if cpu_fallback:
+        return "cpu"
+    value = (requested or "auto").strip().lower()
+    if value in {"", "auto"}:
+        return ops.auto_detect_backend(host)
+    if value in ops.SUPPORTED_BACKENDS:
+        return value
+    raise PrebuiltFallback(
+        f"unsupported --backend '{requested}'; choose from auto,{','.join(ops.SUPPORTED_BACKENDS)}"
+    )
+
+
+# ── Release checksum index (trust anchor: the release's own sha256 asset) ──
+def valid_sha256(value: Any) -> str | None:
+    if not isinstance(value, str):
+        return None
+    digest = value.strip().lower()
+    if digest.startswith("sha256:"):
+        digest = digest[len("sha256:") :]
+    if len(digest) == 64 and all(c in "0123456789abcdef" for c in digest):
+        return digest
+    return None
+
+
+def parse_release_checksums(
+    ops: ModuleOps, repo: str, release_tag: str, payload: Any
+) -> dict[str, str]:
+    """Asset name -> sha256 from a release's checksum-index asset.
+
+    That index is the authority for each asset's sha256. It is validated for
+    schema/component and that its ``release_tag`` matches the resolved release,
+    so a redirected or mismatched index is rejected; malformed fails closed."""
+    label = f"{ops.SHA256_ASSET_NAME} in {repo}@{release_tag}"
+    if not isinstance(payload, dict):
+        raise PrebuiltFallback(f"{label} was not a JSON object")
+    if payload.get("schema_version") != ops.SCHEMA_VERSION:
+        raise PrebuiltFallback(f"{label} has an unexpected schema_version")
+    if payload.get("component") != ops.COMPONENT:
+        raise PrebuiltFallback(f"{label} did not describe {ops.COMPONENT}")
+    payload_tag = payload.get("release_tag")
+    if not isinstance(payload_tag, str) or not payload_tag:
+        raise PrebuiltFallback(f"{label} omitted release_tag")
+    if payload_tag != release_tag:
+        raise PrebuiltFallback(
+            f"{label} release_tag={payload_tag} did not match the resolved release {release_tag}"
+        )
+    artifacts = payload.get("artifacts")
+    if not isinstance(artifacts, dict):
+        raise PrebuiltFallback(f"{label} omitted an 'artifacts' map")
+    checksums: dict[str, str] = {}
+    for asset_name, entry in artifacts.items():
+        if not isinstance(asset_name, str) or not asset_name or not isinstance(entry, dict):
+            continue
+        digest = valid_sha256(entry.get("sha256"))
+        if digest is not None:
+            checksums[asset_name] = digest
+    if not checksums:
+        raise PrebuiltFallback(f"{label} carried no usable sha256 entries")
+    return checksums
+
+
+def fetch_release_checksums(ops: ModuleOps, bundle: "ReleaseBundle") -> dict[str, str]:
+    """Download + parse the release's checksum-index asset; fails closed if the
+    release does not publish it."""
+    sha_asset = ops.SHA256_ASSET_NAME
+    url = bundle.asset_urls.get(sha_asset)
+    if not url:
+        raise PrebuiltFallback(
+            f"release {bundle.repo}@{bundle.release_tag} has no {sha_asset}; "
+            f"cannot verify a download"
+        )
+    try:
+        raw = ops.download_bytes(url, timeout = 30, headers = ops.auth_headers(url))
+        payload = json.loads(raw.decode("utf-8"))
+    except (urllib.error.URLError, OSError, socket.timeout) as exc:
+        raise PrebuiltFallback(
+            f"could not fetch {sha_asset} from {bundle.repo}@{bundle.release_tag}: {exc}"
+        ) from exc
+    except (UnicodeDecodeError, json.JSONDecodeError) as exc:
+        raise PrebuiltFallback(
+            f"{sha_asset} in {bundle.repo}@{bundle.release_tag} was not valid JSON"
+        ) from exc
+    return ops.parse_release_checksums(bundle.repo, bundle.release_tag, payload)
+
+
+def expected_sha256_for(
+    ops: ModuleOps,
+    checksums: dict[str, str],
+    asset_name: str,
+    *,
+    manifest_sha256: str | None = None,
+) -> str:
+    """The sha256 the archive must match, from the release checksum-index entry.
+    An asset absent from the index fails closed. Any sha256 the manifest embeds
+    for the asset must agree with the index (a mismatch means a tampered manifest)."""
+    digest = checksums.get(asset_name)
+    if digest is None:
+        raise PrebuiltFallback(
+            f"{asset_name} is not covered by {ops.SHA256_ASSET_NAME}; "
+            f"refusing an unverifiable download"
+        )
+    embedded = valid_sha256(manifest_sha256)
+    if embedded is not None and embedded != digest:
+        raise PrebuiltFallback(
+            f"manifest sha256 for {asset_name} disagrees with {ops.SHA256_ASSET_NAME}; "
+            f"refusing a possibly tampered release"
+        )
+    ops.log(f"verifying {asset_name} against {ops.SHA256_ASSET_NAME} sha256={digest}")
+    return digest
+
+
+# ── Release resolution ──
+@dataclass
+class ReleaseBundle:
+    repo: str
+    release_tag: str
+    manifest: dict[str, Any]
+    asset_urls: dict[str, str]
+
+
+def fetch_release_bundle(ops: ModuleOps, repo: str, release_tag: str) -> ReleaseBundle:
+    """Fetch a fork release, download+validate its manifest, return the bundle.
+
+    The single network seam for API-path release resolution; tests inject a fake
+    to exercise selection/install offline. A missing or unreachable release (404,
+    rate limit, no network) surfaces as PrebuiltFallback so the caller does a
+    source build rather than error out.
+    """
+    manifest_asset = ops.MANIFEST_ASSET_NAME
+    try:
+        release = ops.github_release(repo, release_tag)
+    except PrebuiltFallback:
+        raise
+    except (urllib.error.URLError, OSError, socket.timeout) as exc:
+        raise PrebuiltFallback(f"could not fetch release {repo}@{release_tag}: {exc}") from exc
+    resolved_tag = release.get("tag_name")
+    resolved_tag = resolved_tag if isinstance(resolved_tag, str) and resolved_tag else release_tag
+    asset_urls = ops.release_asset_map(release)
+    manifest_url = asset_urls.get(manifest_asset)
+    if not manifest_url:
+        raise PrebuiltFallback(
+            f"release {repo}@{resolved_tag} has no {manifest_asset}; cannot select a prebuilt"
+        )
+    try:
+        manifest_bytes = ops.download_bytes(
+            manifest_url, timeout = 30, headers = ops.auth_headers(manifest_url)
+        )
+    except (urllib.error.URLError, OSError, socket.timeout) as exc:
+        raise PrebuiltFallback(
+            f"could not fetch {manifest_asset} from {repo}@{resolved_tag}: {exc}"
+        ) from exc
+    try:
+        manifest_payload = json.loads(manifest_bytes.decode("utf-8"))
+    except (UnicodeDecodeError, json.JSONDecodeError) as exc:
+        raise PrebuiltFallback(
+            f"{manifest_asset} in {repo}@{resolved_tag} was not valid JSON"
+        ) from exc
+    manifest = ops.parse_manifest(
+        manifest_payload, label = f"{manifest_asset} in {repo}@{resolved_tag}"
+    )
+    return ReleaseBundle(
+        repo = repo, release_tag = resolved_tag, manifest = manifest, asset_urls = asset_urls
+    )
+
+
+def asset_download_url(ops: ModuleOps, bundle: ReleaseBundle, asset_name: str) -> str:
+    url = bundle.asset_urls.get(asset_name)
+    if url:
+        return url
+    # A manifest can list an asset the release JSON omitted; fall back to the
+    # deterministic release-download URL.
+    return ops.release_asset_download_url(bundle.repo, bundle.release_tag, asset_name)
+
+
+def resolve_newest_release_tag(ops: ModuleOps, repo: str) -> str:
+    """Newest published (non-draft/non-prerelease) release tag for `repo` by
+    ``published_at`` -- what the freshness checks use, NOT GitHub's
+    ``/releases/latest`` pointer (sorts by commit date, can lag the newest build)."""
+    payload = ops.fetch_json(f"https://api.github.com/repos/{repo}/releases?per_page=30")
+    if not isinstance(payload, list):
+        raise PrebuiltFallback(f"unexpected releases payload for {repo}")
+    published = [
+        r
+        for r in payload
+        if isinstance(r, dict)
+        and not r.get("draft")
+        and not r.get("prerelease")
+        and isinstance(r.get("tag_name"), str)
+        and r.get("tag_name")
+    ]
+    if not published:
+        raise PrebuiltFallback(f"{repo} has no published prebuilt release yet")
+    newest = max(published, key = lambda r: r.get("published_at") or "")
+    return newest["tag_name"]
+
+
+def resolve_release_tag(
+    ops: ModuleOps, published_repo: str, *, published_release_tag: str | None
+) -> str:
+    """The release tag to install: an explicit override, else the newest
+    published release resolved at runtime."""
+    override = (published_release_tag or "").strip()
+    if override:
+        return override
+    return ops.resolve_newest_release_tag(published_repo)
+
+
+def resolve_release_via_download_host(
+    ops: ModuleOps, repo: str, published_release_tag: str | None
+) -> tuple[ReleaseBundle, dict[str, str]] | None:
+    """Resolve the release + manifest + checksum index entirely from the download
+    host, with zero api.github.com calls. None (caller falls back to the API) on a
+    missing/renamed asset, a 404, or a tag mismatch. Fetches the checksum index
+    first (an in-progress release can publish it before the manifest)."""
+    manifest_asset = ops.MANIFEST_ASSET_NAME
+    sha_asset = ops.SHA256_ASSET_NAME
+    release_tag = (published_release_tag or "").strip() or ops._download_host_latest_release_tag(
+        repo
+    )
+    if not release_tag:
+        return None
+    sha_url = ops.release_asset_download_url(repo, release_tag, sha_asset)
+    try:
+        sha_payload = ops._download_host_json(sha_url)
+    except urllib.error.HTTPError as exc:
+        if exc.code == 404:
+            return None
+        raise
+    except (
+        urllib.error.URLError,
+        OSError,
+        socket.timeout,
+        UnicodeDecodeError,
+        json.JSONDecodeError,
+    ):
+        return None
+    try:
+        checksums = ops.parse_release_checksums(repo, release_tag, sha_payload)
+    except PrebuiltFallback:
+        return None  # schema/component/tag mismatch -> let the API path decide
+    manifest_url = ops.release_asset_download_url(repo, release_tag, manifest_asset)
+    try:
+        manifest_payload = ops._download_host_json(manifest_url)
+    except urllib.error.HTTPError as exc:
+        if exc.code == 404:
+            return None
+        raise
+    except (
+        urllib.error.URLError,
+        OSError,
+        socket.timeout,
+        UnicodeDecodeError,
+        json.JSONDecodeError,
+    ):
+        return None
+    try:
+        manifest = ops.parse_manifest(
+            manifest_payload, label = f"{manifest_asset} in {repo}@{release_tag}"
+        )
+    except PrebuiltFallback:
+        return None
+    # Tag-pinned CDN URLs for every asset the install may fetch (asset_download_url
+    # reconstructs any missing one), keeping this a pure download-host path.
+    names = {
+        str(a.get("asset"))
+        for a in manifest.get("artifacts", [])
+        if isinstance(a, dict) and a.get("asset")
+    }
+    names |= {manifest_asset, sha_asset}
+    asset_urls = {name: ops.release_asset_download_url(repo, release_tag, name) for name in names}
+    bundle = ReleaseBundle(
+        repo = repo, release_tag = release_tag, manifest = manifest, asset_urls = asset_urls
+    )
+    return bundle, checksums
+
+
+def fetch_release_for_install(
+    ops: ModuleOps, repo: str, *, published_release_tag: str | None
+) -> tuple[ReleaseBundle, dict[str, str]]:
+    """Resolve the release + manifest + checksum index, preferring the download
+    host (no api.github.com rate limit) and falling back to the GitHub API. The
+    single network seam the install/probe paths use."""
+    fast = ops._resolve_release_via_download_host(repo, published_release_tag)
+    if fast is not None:
+        bundle, checksums = fast
+        ops.log(f"resolved {repo}@{bundle.release_tag} via the download host (no GitHub API)")
+        return bundle, checksums
+    release_tag = ops.resolve_release_tag(repo, published_release_tag = published_release_tag)
+    bundle = ops.fetch_release_bundle(repo, release_tag)
+    checksums = ops.fetch_release_checksums(bundle)
+    return bundle, checksums
+
+
+# ── Marker and fingerprint ──
+def compute_install_fingerprint(
+    *,
+    published_repo: str,
+    release_tag: str,
+    upstream_tag: str | None,
+    source_commit: str | None,
+    asset: str,
+    asset_sha256: str,
+    backend: str,
+    runtime_line: str | None,
+    coverage: dict[str, Any],
+) -> str:
+    payload = {
+        "published_repo": published_repo,
+        "release_tag": release_tag,
+        "upstream_tag": upstream_tag,
+        "source_commit": source_commit,
+        "asset": asset,
+        "asset_sha256": asset_sha256,
+        "backend": backend,
+        "runtime_line": runtime_line,
+        "coverage": coverage,
+    }
+    return hashlib.sha256(
+        json.dumps(payload, sort_keys = True, separators = (",", ":")).encode("utf-8")
+    ).hexdigest()
+
+
+@dataclass(frozen = True)
+class InstallSelection:
+    """The identity of a chosen prebuilt: everything the marker/fingerprint record."""
+
+    published_repo: str
+    release_tag: str
+    upstream_tag: str | None
+    source_commit: str | None
+    asset: str
+    asset_sha256: str
+    backend: str
+    runtime_line: str | None
+    coverage: dict[str, Any]
+    studio_protocol: str | None
+    # Slim pairing identity (whisper slim bundles ride the llama ggml runtime);
+    # all None for fat installs, never part of the fingerprint.
+    install_kind: str | None = None
+    paired_llama_tag: str | None = None
+    linked_from: str | None = None
+    # Filenames the slim wiring hardlinked beside the server; the sidecar launch
+    # guard verifies exactly these instead of hardcoded per-OS names.
+    linked_libraries: tuple[str, ...] | None = None
+    runtime_wiring_version: int | None = None
+    linked_runtime_directories: tuple[str, ...] | None = None
+
+    def fingerprint(self) -> str:
+        return compute_install_fingerprint(
+            published_repo = self.published_repo,
+            release_tag = self.release_tag,
+            upstream_tag = self.upstream_tag,
+            source_commit = self.source_commit,
+            asset = self.asset,
+            asset_sha256 = self.asset_sha256,
+            backend = self.backend,
+            runtime_line = self.runtime_line,
+            coverage = self.coverage,
+        )
+
+
+def selection_from_artifact(
+    ops: ModuleOps,
+    *,
+    published_repo: str,
+    release_tag: str,
+    manifest: dict[str, Any],
+    artifact: dict[str, Any],
+    backend: str,
+    asset_sha256: str,
+) -> InstallSelection:
+    return InstallSelection(
+        published_repo = published_repo,
+        release_tag = release_tag,
+        upstream_tag = manifest.get("upstream_tag"),
+        source_commit = manifest.get("source_commit"),
+        asset = str(artifact.get("asset")),
+        asset_sha256 = asset_sha256,
+        backend = backend,
+        runtime_line = artifact.get("runtime_line")
+        if isinstance(artifact.get("runtime_line"), str)
+        else None,
+        coverage = ops.artifact_coverage(artifact),
+        studio_protocol = manifest.get("studio_protocol"),
+    )
+
+
+def metadata_path(ops: ModuleOps, install_dir: Path) -> Path:
+    return install_dir / ops.METADATA_FILENAME
+
+
+def write_prebuilt_metadata(ops: ModuleOps, install_dir: Path, selection: InstallSelection) -> None:
+    coverage = selection.coverage
+    payload = {
+        "schema_version": ops.SCHEMA_VERSION,
+        "component": ops.COMPONENT,
+        "published_repo": selection.published_repo,
+        "release_tag": selection.release_tag,
+        "upstream_tag": selection.upstream_tag,
+        "source_commit": selection.source_commit,
+        "asset": selection.asset,
+        "asset_sha256": selection.asset_sha256,
+        "backend": selection.backend,
+        "runtime_line": selection.runtime_line,
+        "sm_coverage": coverage.get("sm_coverage") or coverage.get("sm"),
+        "gfx_coverage": coverage.get("gfx_coverage") or coverage.get("gfx"),
+        "min_os": coverage.get("min_os"),
+        "studio_protocol": selection.studio_protocol,
+        "install_fingerprint": selection.fingerprint(),
+        "installed_at_utc": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+    }
+    if selection.install_kind == "slim":
+        # Additive slim fields; fat markers keep the legacy payload exactly.
+        payload["install_kind"] = "slim"
+        payload["paired_llama_tag"] = selection.paired_llama_tag
+        payload["linked_from"] = selection.linked_from
+        if selection.linked_libraries is not None:
+            payload["linked_libraries"] = list(selection.linked_libraries)
+        if selection.runtime_wiring_version is not None:
+            payload["runtime_wiring_version"] = selection.runtime_wiring_version
+        if selection.linked_runtime_directories is not None:
+            payload["linked_runtime_directories"] = list(selection.linked_runtime_directories)
+    ops.metadata_path(install_dir).write_text(
+        json.dumps(payload, indent = 2) + "\n", encoding = "utf-8"
+    )
+
+
+def load_prebuilt_metadata(ops: ModuleOps, install_dir: Path) -> dict[str, Any] | None:
+    path = ops.metadata_path(install_dir)
+    if not path.is_file():
+        return None
+    try:
+        payload = json.loads(path.read_text(encoding = "utf-8"))
+    except (json.JSONDecodeError, OSError):
+        return None
+    return payload if isinstance(payload, dict) else None
+
+
+def existing_install_matches(
+    ops: ModuleOps, install_dir: Path, host: Any, selection: InstallSelection
+) -> bool:
+    """True iff the marker records this exact selection and the server binary is on disk."""
+    metadata = ops.load_prebuilt_metadata(install_dir)
+    if metadata is None:
+        return False
+    if not ops.installed_server_path(install_dir, host).is_file():
+        return False
+    recorded = metadata.get("install_fingerprint")
+    if not isinstance(recorded, str) or recorded != selection.fingerprint():
+        return False
+    ops.log(
+        f"existing {ops.COMPONENT} install already matches {selection.release_tag} "
+        f"({selection.backend}); nothing to do"
+    )
+    return True
+
+
+# ── Install tree assembly and staged activation ──
+def locate_server_in_tree(ops: ModuleOps, root: Path, host: Any) -> Path:
+    name = ops.server_binary_name(host)
+    matches = sorted(root.rglob(name))
+    if not matches:
+        raise PrebuiltFallback(f"archive did not contain a {name} binary")
+    return matches[0]
+
+
+def assemble_install_tree(ops: ModuleOps, bundle_root: Path, staged_root: Path, host: Any) -> Path:
+    """Lay out staged_root as a full install: <runtime bin dir>/<server + libs>.
+
+    Everything beside the server in the archive (shared libs, backend kernel
+    subdirs, license/build-info) is co-located into the canonical bin dir so the
+    server's RUNPATH=$ORIGIN resolves its libs.
+    """
+    bin_dir = ops.runtime_bin_dir(staged_root, host)
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    for entry in sorted(bundle_root.iterdir()):
+        dest = bin_dir / entry.name
+        if entry.is_dir() and not entry.is_symlink():
+            shutil.copytree(entry, dest, symlinks = True)
+        else:
+            shutil.copy2(entry, dest, follow_symlinks = False)
+    server = bin_dir / ops.server_binary_name(host)
+    if not server.exists():
+        raise PrebuiltFallback(f"staged install is missing the {ops.COMPONENT} server binary")
+    if not host.is_windows:
+        os.chmod(server, server.stat().st_mode | 0o111)
+    return server
+
+
+def swap_into_place(staged_root: Path, install_dir: Path) -> None:
+    """Atomically replace install_dir with staged_root (same filesystem), with rollback."""
+    install_dir.parent.mkdir(parents = True, exist_ok = True)
+    backup: Path | None = None
+    try:
+        if install_dir.exists():
+            backup = install_dir.parent / f".{install_dir.name}.old-{os.getpid()}"
+            os.replace(install_dir, backup)
+        os.replace(staged_root, install_dir)
+    except OSError as exc:
+        restored = False
+        if backup is not None and backup.exists() and not install_dir.exists():
+            try:
+                os.replace(backup, install_dir)
+                restored = True
+            except OSError as rollback_exc:
+                raise PrebuiltFallback(
+                    "prebuilt activation failed and the previous install could not be restored "
+                    f"({exc}; rollback: {rollback_exc})"
+                ) from rollback_exc
+        if is_busy_lock_error(exc):
+            detail = "; restored the previous install" if restored else ""
+            raise BusyInstallConflict(
+                f"the existing install appears to still be in use{detail} ({exc})"
+            ) from exc
+        raise
+    if backup is not None:
+        shutil.rmtree(backup, ignore_errors = True)
+
+
+def validate_staged_server(ops: ModuleOps, staged_root: Path, host: Any) -> None:
+    """Optional pre-activate smoke test, gated off by default (the component's
+    _RUN_STAGED_PREBUILT_VALIDATION switch)."""
+    if not ops._RUN_STAGED_PREBUILT_VALIDATION:
+        return
+    server = ops.installed_server_path(staged_root, host)
+    env = os.environ.copy()
+    bin_dir = str(ops.runtime_bin_dir(staged_root, host))
+    for var in ("LD_LIBRARY_PATH", "DYLD_LIBRARY_PATH"):
+        env[var] = bin_dir + (os.pathsep + env[var] if env.get(var) else "")
+    try:
+        result = subprocess.run(
+            [str(server), "--help"],
+            capture_output = True,
+            text = True,
+            timeout = 60,
+            env = env,
+            **ops.windows_hidden_subprocess_kwargs(),
+        )
+    except (OSError, subprocess.SubprocessError) as exc:
+        raise PrebuiltFallback(f"staged {ops.COMPONENT} server failed to launch: {exc}") from exc
+    if result.returncode != 0:
+        raise PrebuiltFallback(
+            f"staged {ops.COMPONENT} server --help exited {result.returncode}: "
+            f"{result.stderr.strip()}"
+        )
+
+
+def windows_hidden_subprocess_kwargs() -> dict[str, object]:
+    """Return Windows-only subprocess kwargs that suppress console windows."""
+    if sys.platform != "win32":
+        return {}
+
+    kwargs: dict[str, object] = {}
+    create_no_window = getattr(subprocess, "CREATE_NO_WINDOW", 0)
+    if create_no_window:
+        kwargs["creationflags"] = create_no_window
+
+    startupinfo_factory = getattr(subprocess, "STARTUPINFO", None)
+    startf_use_showwindow = getattr(subprocess, "STARTF_USESHOWWINDOW", 0)
+    sw_hide = getattr(subprocess, "SW_HIDE", 0)
+    if startupinfo_factory is not None and startf_use_showwindow:
+        startupinfo = startupinfo_factory()
+        startupinfo.dwFlags |= startf_use_showwindow
+        startupinfo.wShowWindow = sw_hide
+        kwargs["startupinfo"] = startupinfo
+
+    return kwargs
+
+
+def install_from_bundle(
+    ops: ModuleOps, install_dir: Path, host: Any, bundle: ReleaseBundle, selection: InstallSelection
+) -> None:
+    staging_root = install_dir.parent / ops.INSTALL_STAGING_ROOT_NAME
+    staging_root.mkdir(parents = True, exist_ok = True)
+    staging = Path(tempfile.mkdtemp(prefix = f"{install_dir.name}.staging-", dir = staging_root))
+    try:
+        archive_path = staging / selection.asset
+        url = ops.asset_download_url(bundle, selection.asset)
+        ops.log(f"downloading {url}")
+        ops.download_file_verified(
+            url, archive_path, expected_sha256 = selection.asset_sha256, label = selection.asset
+        )
+        extract_dir = staging / "extracted"
+        ops.extract_archive(archive_path, extract_dir)
+
+        server = ops.locate_server_in_tree(extract_dir, host)
+        bundle_root = server.parent
+
+        staged_root = staging / "staged"
+        ops.assemble_install_tree(bundle_root, staged_root, host)
+        # Component hook (default no-op): slim whisper wires the llama ggml
+        # runtime here so staged validation sees the final linked tree; a returned
+        # selection (with the wired filenames) supersedes the input so the marker
+        # records what was actually linked.
+        updated = ops.prepare_runtime_payload(staged_root, host, selection)
+        if updated is not None:
+            selection = updated
+        ops.validate_staged_server(staged_root, host)
+        ops.write_prebuilt_metadata(staged_root, selection)
+        ops._swap_into_place(staged_root, install_dir)
+    finally:
+        shutil.rmtree(staging, ignore_errors = True)
+        try:
+            staging_root.rmdir()
+        except OSError:
+            pass
+
+
+def plan_selection(
+    ops: ModuleOps,
+    host: Any,
+    bundle: ReleaseBundle,
+    *,
+    published_repo: str,
+    backend: str,
+    checksums: dict[str, str],
+) -> InstallSelection:
+    """Choose an artifact (with the component's fallback policy) and resolve its
+    trusted sha256 from the release checksum index."""
+    artifact, effective_backend, _used_fallback = ops.select_artifact_with_fallback(
+        bundle.manifest, host, backend
+    )
+    asset = str(artifact.get("asset"))
+    manifest_sha256 = artifact.get("sha256") if isinstance(artifact.get("sha256"), str) else None
+    expected_sha = ops.expected_sha256_for(
+        checksums,
+        asset,
+        manifest_sha256 = manifest_sha256,
+    )
+    return ops.selection_from_artifact(
+        published_repo = published_repo,
+        release_tag = bundle.release_tag,
+        manifest = bundle.manifest,
+        artifact = artifact,
+        backend = effective_backend,
+        asset_sha256 = expected_sha,
+    )
+
+
+def install_prebuilt(
+    ops: ModuleOps,
+    install_dir: Path,
+    *,
+    published_repo: str,
+    published_release_tag: str | None = None,
+    backend: str | None = "auto",
+    cpu_fallback: bool = False,
+    force: bool = False,
+    host: Any = None,
+) -> int:
+    if host is None:
+        host = ops.detect_host()
+    effective_backend = ops.resolve_backend(host, backend, cpu_fallback = cpu_fallback)
+    os_token, arch_token = ops.host_platform_tokens(host)
+    ops.log(
+        f"target {ops.COMPONENT} from {published_repo} "
+        f"({os_token}-{arch_token}, backend {effective_backend})"
+    )
+
+    bundle, checksums = ops.fetch_release_for_install(
+        published_repo, published_release_tag = published_release_tag
+    )
+    selection = ops.plan_selection(
+        host,
+        bundle,
+        published_repo = published_repo,
+        backend = effective_backend,
+        checksums = checksums,
+    )
+
+    return install_selected_prebuilt(
+        ops,
+        install_dir,
+        host = host,
+        bundle = bundle,
+        selection = selection,
+        force = force,
+    )
+
+
+def install_selected_prebuilt(
+    ops: ModuleOps,
+    install_dir: Path,
+    *,
+    host: Any,
+    bundle: ReleaseBundle,
+    selection: InstallSelection,
+    force: bool,
+) -> int:
+    """Validate and activate an already selected release plan.
+
+    Components that need to examine more than one published release can keep
+    release selection component-specific while sharing the lock, idempotency,
+    atomic activation, and post-install verification path.
+    """
+
+    if not force and ops.existing_install_matches(install_dir, host, selection):
+        return 0
+
+    with ops.install_lock(ops.install_lock_path(install_dir)):
+        # Re-check under the lock: a concurrent run may have just finished.
+        if not force and ops.existing_install_matches(install_dir, host, selection):
+            return 0
+        ops._install_from_bundle(install_dir, host, bundle, selection)
+
+    server = ops.installed_server_path(install_dir, host)
+    if not server.is_file():
+        raise PrebuiltFallback(f"post-install verification failed: {server} is missing")
+    ops.log(
+        f"installed {ops.COMPONENT} {bundle.release_tag} " f"({selection.backend}) at {install_dir}"
+    )
+    return 0
+
+
+def resolve_prebuilt(
+    ops: ModuleOps,
+    host: Any,
+    *,
+    published_repo: str,
+    published_release_tag: str | None,
+    backend: str | None,
+    cpu_fallback: bool,
+) -> dict[str, Any]:
+    """Host-aware "is a prebuilt available" probe. No archive download."""
+    effective_backend = ops.resolve_backend(host, backend, cpu_fallback = cpu_fallback)
+    try:
+        bundle, _checksums = ops.fetch_release_for_install(
+            published_repo, published_release_tag = published_release_tag
+        )
+        artifact, resolved_backend, used_fallback = ops.select_artifact_with_fallback(
+            bundle.manifest, host, effective_backend
+        )
+    except PrebuiltFallback:
+        return {"prebuilt_available": False, "repo": published_repo}
+    os_token, arch_token = ops.host_platform_tokens(host)
+    payload = {
+        "prebuilt_available": True,
+        "repo": published_repo,
+        "release_tag": bundle.release_tag,
+        "upstream_tag": bundle.manifest.get("upstream_tag"),
+        "backend": resolved_backend,
+        "requested_backend": effective_backend,
+        "cpu_fallback": used_fallback,
+        "asset": str(artifact.get("asset")),
+        "os": os_token,
+        "arch": arch_token,
+        "runtime_line": artifact.get("runtime_line"),
+    }
+    # Component hook (default none): whisper adds install_kind slim|fat. The JSON
+    # emitter sorts keys, so an appended field can't perturb the legacy key order.
+    payload.update(ops.resolver_payload_extra(artifact))
+    return payload
+
+
+def prepare_runtime_payload(staged_root: Path, host: Any, selection: InstallSelection) -> Any:
+    """Post-assemble hook; the core stages nothing extra. Components override it
+    to wire external runtime files into the staged bin dir (whisper slim hardlinks
+    the llama install's ggml libraries) before validation, and may return an
+    updated InstallSelection for the marker to record instead."""
+    return None
+
+
+def resolver_payload_extra(artifact: dict[str, Any]) -> dict[str, Any]:
+    """Additive --resolve-prebuilt payload fields; the core adds none."""
+    return {}
+
+
+def installed_server_path(ops: ModuleOps, install_dir: Path, host: Any) -> Path:
+    return ops.runtime_bin_dir(install_dir, host) / ops.server_binary_name(host)
+
+
+# Underscored aliases so ops lookups that mirror the installer modules' private
+# names still resolve for a descriptor-only component.
+_download_host_latest_release_tag = download_host_latest_release_tag
+_download_host_json = fetch_download_host_json
+_resolve_release_via_download_host = resolve_release_via_download_host
+_install_from_bundle = install_from_bundle
+_swap_into_place = swap_into_place
+
+
+def emit_resolver_output(payload: dict[str, Any], *, output_format: str) -> None:
+    if output_format == "json":
+        print(json.dumps(payload, sort_keys = True))
+        return
+    if "asset" in payload and payload.get("prebuilt_available"):
+        print(payload["asset"])
+        return
+    print(json.dumps(payload, sort_keys = True))
diff --git a/studio/setup.ps1 b/studio/setup.ps1
index f523b9ff14..c6932121c9 100644
--- a/studio/setup.ps1
+++ b/studio/setup.ps1
@@ -1498,7 +1498,7 @@ if (-not $HasNvidiaSmi) {
             $nameArchTable = @(
                 @{ P = "9070 XT|9080";                                        A = "gfx1201" }  # RDNA 4 (Radeon RX 9070 XT / 9080)
                 @{ P = "9070|9060";                                           A = "gfx1200" }  # RDNA 4 (Radeon RX 9070 / 9060)
-                @{ P = "8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max"; A = "gfx1151" }  # RDNA 3.5 (Strix Halo: Radeon 8060S/8050S/8040S iGPU, Ryzen AI Max+)
+                @{ P = "8065S|8060S|8050S|8040S|Strix Halo|Ryzen AI Max|AI Max"; A = "gfx1151" }  # RDNA 3.5 (Strix Halo + Gorgon Halo: Radeon 8065S/8060S/8050S/8040S iGPU, Ryzen AI Max / Max+)
                 @{ P = "890M|880M|860M|840M|Strix Point|Krackan|HX 37[05]|AI 9 HX|AI 9 36[05]|AI 7 35[05]|AI 5 34[05]|AI 7 PRO 35|AI 5 33"; A = "gfx1150" }  # RDNA 3.5 (Strix/Krackan Point: Radeon 890M/880M iGPU, Ryzen AI 9 HX 370/375)
                 @{ P = "RX 7900|RX 7800|RX 7700(?!S)|PRO W7900|PRO W7800|PRO W7700"; A = "gfx1100" }  # RDNA 3 desktop / workstation (Navi 31)
                 @{ P = "RX 7600|RX 7700S|RX 7650|PRO W7600|PRO W7500|PRO V710"; A = "gfx1102" }  # RDNA 3 (Navi 33)
@@ -2655,12 +2655,13 @@ if (Test-Path -LiteralPath $LegacyStudioHome -PathType Container) {
 }
 $StudioHomeIsCustom = ($_studioHomeCanon -ne $LegacyStudioHome)
 # Directory-local evidence that Unsloth created $Path, used to adopt a custom-home
-# llama.cpp predating the .unsloth-studio-owned marker (see setup.sh). Only the
-# prebuilt UNSLOTH_PREBUILT_INFO.json counts; source builds are indistinguishable
-# from a user clone on Windows and stay under the strict guard.
+# llama.cpp or whisper.cpp predating the .unsloth-studio-owned marker (see
+# setup.sh). Only Unsloth prebuilt markers count; source builds are
+# indistinguishable from a user clone on Windows and stay under the strict guard.
 function Test-StudioOwnedAdoptable {
     param([Parameter(Mandatory = $true)][string]$Path)
     if (Test-Path -LiteralPath (Join-Path $Path "UNSLOTH_PREBUILT_INFO.json") -PathType Leaf) { return $true }
+    if (Test-Path -LiteralPath (Join-Path $Path "UNSLOTH_WHISPER_PREBUILT_INFO.json") -PathType Leaf) { return $true }
     return $false
 }
 function Assert-StudioOwnedOrAbsent {
@@ -2774,6 +2775,7 @@ if ((Test-Path -LiteralPath $VenvDir -PathType Container) -and -not $NoTorchMode
                 "gfx1201", "gfx1200",           # RDNA 4
                 "gfx1151", "gfx1150",           # RDNA 3.5 (Strix Halo/Point)
                 "gfx1103", "gfx1102", "gfx1101", "gfx1100",  # RDNA 3
+                "gfx1036", "gfx1035", "gfx1034", "gfx1033", "gfx1032", "gfx1031", "gfx1030",  # RDNA 2 (RX 6000)
                 "gfx90a", "gfx908"              # MI200 / MI100
             )
             if ($script:ROCmGfxArch -and ($_rocmWheelArches -contains $script:ROCmGfxArch)) {
@@ -3064,6 +3066,10 @@ if (-not $TorchIndexPinned -and ($HasROCm -or $ROCmGfxArch) -and $CuTag -eq "cpu
         "gfx1151" = "gfx1151";     "gfx1150" = "gfx1150"      # RDNA 3.5 (Strix Halo/Point)
         "gfx1103" = "gfx110X-all"; "gfx1102" = "gfx110X-all"  # RDNA 3
         "gfx1101" = "gfx110X-all"; "gfx1100" = "gfx110X-all"
+        "gfx1036" = "gfx103X-all"; "gfx1035" = "gfx103X-all"  # RDNA 2 (RX 6000)
+        "gfx1034" = "gfx103X-all"; "gfx1033" = "gfx103X-all"
+        "gfx1032" = "gfx103X-all"; "gfx1031" = "gfx103X-all"
+        "gfx1030" = "gfx103X-all"
         "gfx90a"  = "gfx90a";      "gfx908"  = "gfx908"       # MI200/MI100
     }
     # gfx120X and Strix have a null _grouped_mm kernel on torch <2.11.0.
@@ -3098,7 +3104,7 @@ if (-not $TorchIndexPinned -and ($HasROCm -or $ROCmGfxArch) -and $CuTag -eq "cpu
         # GPU arch detected but not in the supported wheel map — warn explicitly
         # so the user knows why they are getting CPU PyTorch instead of ROCm.
         substep "[WARN] AMD GPU ($ROCmGfxArch) not in supported arch list -- falling back to CPU-only PyTorch" "Yellow"
-        substep "       Supported: gfx1200/1201 (RDNA 4), gfx1150/1151 (RDNA 3.5), gfx1100-1103 (RDNA 3), gfx90a, gfx908" "Yellow"
+        substep "       Supported: gfx1200/1201 (RDNA 4), gfx1150/1151 (RDNA 3.5), gfx1100-1103 (RDNA 3), gfx1030-1036 (RDNA 2), gfx90a, gfx908" "Yellow"
     } else {
         # HIP SDK present ($HasROCm=true via amd-smi) but gcnArchName was not
         # readable — warn rather than silently falling back to CPU PyTorch.
@@ -3762,6 +3768,83 @@ if ($LocalLlamaCppLinked) {
         }
 }
 
+# ==========================================================================
+#  PHASE 3.4: Install the whisper.cpp prebuilt (dictation runtime)
+# ==========================================================================
+# Mirrors the llama.cpp prebuilt install above; current whisper releases are
+# slim bundles that reuse the llama install's ggml runtime, so this runs after
+# llama. Failure is never fatal: local dictation falls back to Transformers STT.
+$WhisperCppDir = Join-Path $UnslothHome "whisper.cpp"
+$WhisperInstaller = Join-Path $PSScriptRoot "install_whisper_prebuilt.py"
+# Same opt-outs as setup.sh: a user-configured binary/dir or an explicit skip
+# disables the managed install entirely.
+if ($env:WHISPER_SERVER_PATH -or $env:UNSLOTH_WHISPER_CPP_PATH) {
+    substep "whisper.cpp: using a user-configured binary/dir; skipping managed install"
+} elseif ($env:UNSLOTH_SKIP_WHISPER_INSTALL -eq "1") {
+    substep "whisper.cpp: install skipped (UNSLOTH_SKIP_WHISPER_INSTALL=1)"
+} elseif (Test-Path -LiteralPath $WhisperInstaller) {
+    # The installer's atomic activation replaces the whole directory, so the
+    # custom-home ownership guard must run first (mirrors the llama block).
+    if ($StudioHomeIsCustom) {
+        Assert-StudioOwnedOrAbsent -Path $WhisperCppDir -Label "whisper.cpp install"
+    }
+    $whisperArgs = @($WhisperInstaller, "--install-dir", $WhisperCppDir)
+    if ($env:UNSLOTH_WHISPER_RELEASE_TAG) {
+        $whisperArgs += @("--published-release-tag", $env:UNSLOTH_WHISPER_RELEASE_TAG)
+    }
+    if ($script:ROCmGfxArch) {
+        $whisperArgs += @("--rocm-gfx", $script:ROCmGfxArch)
+    } elseif ($HasROCm) {
+        $whisperArgs += "--has-rocm"
+    }
+    $prevEAPWhisper = $ErrorActionPreference
+    $ErrorActionPreference = "Continue"
+    $previousNativeErrorPreferenceW = $null
+    $restoreNativeErrorPreferenceW = $false
+    if ($PSVersionTable.PSVersion.Major -ge 7) {
+        $previousNativeErrorPreferenceW = $PSNativeCommandUseErrorActionPreference
+        $PSNativeCommandUseErrorActionPreference = $false
+        $restoreNativeErrorPreferenceW = $true
+    }
+    try {
+        $whisperOutput = & python @whisperArgs 2>&1 | Out-String
+        $whisperExit = $LASTEXITCODE
+    } finally {
+        if ($restoreNativeErrorPreferenceW) {
+            $PSNativeCommandUseErrorActionPreference = $previousNativeErrorPreferenceW
+        }
+    }
+    $ErrorActionPreference = $prevEAPWhisper
+    if ($whisperExit -eq 0) {
+        if ($whisperOutput -match "already matches") {
+            step "whisper.cpp" "prebuilt up to date"
+        } else {
+            step "whisper.cpp" "prebuilt installed"
+        }
+        if ($StudioHomeIsCustom -and (Test-Path -LiteralPath $WhisperCppDir -PathType Container)) {
+            Mark-StudioOwned -Path $WhisperCppDir
+        }
+    } elseif ($whisperExit -eq 3) {
+        step "whisper.cpp" "install busy; keeping existing runtime" "Yellow"
+    } elseif ($whisperExit -eq 2) {
+        $requiredWhisperLlamaTag = "unknown"
+        if ($whisperOutput -match "slim bundle requires llama\.cpp ([^;\s]+)") {
+            $requiredWhisperLlamaTag = $Matches[1]
+        }
+        $installedWhisperLlamaTag = "unknown"
+        $llamaMarker = Join-Path $LlamaCppDir "UNSLOTH_PREBUILT_INFO.json"
+        if (Test-Path -LiteralPath $llamaMarker -PathType Leaf) {
+            try {
+                $markerPayload = Get-Content -LiteralPath $llamaMarker -Raw | ConvertFrom-Json
+                if ($markerPayload.release_tag) { $installedWhisperLlamaTag = $markerPayload.release_tag }
+            } catch {}
+        }
+        step "whisper.cpp" "no compatible prebuilt (installed llama.cpp $installedWhisperLlamaTag; whisper requires $requiredWhisperLlamaTag); curated whisper.cpp dictation is unavailable; publish paired releases in llama.cpp then whisper.cpp order; browser and Transformers dictation remain available" "Yellow"
+    } else {
+        step "whisper.cpp" "prebuilt install failed; curated whisper.cpp dictation is unavailable; retry setup or inspect verbose output; browser and Transformers dictation remain available" "Yellow"
+    }
+}
+
 # ==========================================================================
 #  PHASE 3.5: Install OpenSSL dev (for HTTPS support in llama-server)
 # ==========================================================================
diff --git a/studio/setup.sh b/studio/setup.sh
index df7178c662..3c97f77065 100755
--- a/studio/setup.sh
+++ b/studio/setup.sh
@@ -537,11 +537,13 @@ if [ "$_studio_home_canon" != "$_LEGACY_STUDIO_HOME" ]; then
 fi
 # Directory-local evidence Unsloth created "$1": only prebuilt-installer metadata
 # counts (UNSLOTH_PREBUILT_INFO.json for llama.cpp, UNSLOTH_NODE_PREBUILT_INFO.json
-# for Node), both written only by our installers. Mirrors the setup.ps1 Node guard.
-# A markerless source build stays strict since this runs right before an rm -rf.
+# for Node, UNSLOTH_WHISPER_PREBUILT_INFO.json for whisper.cpp), all written only
+# by our installers. Mirrors the setup.ps1 Node guard. A markerless source build
+# stays strict since this runs right before an rm -rf.
 _studio_owned_adoptable() {
     [ -f "$1/UNSLOTH_PREBUILT_INFO.json" ] && return 0
     [ -f "$1/UNSLOTH_NODE_PREBUILT_INFO.json" ] && return 0
+    [ -f "$1/UNSLOTH_WHISPER_PREBUILT_INFO.json" ] && return 0
     return 1
 }
 _assert_studio_owned_or_absent() {
@@ -1101,8 +1103,7 @@ if [ "$_setup_nvidia_usable" != true ]; then
         _setup_mkt=$(_setup_run_smi amd-smi static --asic 2>/dev/null | awk -F'[:|]' \
             '/[Mm]arket.?[Nn]ame/{gsub(/^[[:space:]]+|[[:space:]]+$/,"", $2); if($2){print $2; exit}}' || true)
     elif [ -e /dev/kfd ] && \
-         awk 'FNR==1{ gpu=0; amd=0 } /gpu_id/{ gpu=($2+0>0) } /vendor_id/{ amd=($2==4098) } \
-              gpu && amd { found=1 } END{ exit !found }' \
+         awk '/vendor_id/ && $2 == 4098 { found = 1 } END { exit !found }' \
              /sys/class/kfd/kfd/topology/nodes/*/properties 2>/dev/null; then
         # KFD sysfs fallback, AMD vendor_id 4098 only (mirrors install.sh
         # _has_amd_rocm_gpu): covers AMD hosts where rocminfo/amd-smi are
@@ -1136,7 +1137,7 @@ elif [ "$_setup_amd_detected" = true ]; then
         case "$_setup_mkt" in
             *"9070 XT"*|*9080*)                                                                            _setup_gfx="gfx1201" ;;  # RDNA 4
             *9070*|*9060*)                                                                                 _setup_gfx="gfx1200" ;;  # RDNA 4
-            *"8060S"*|*"8050S"*|*"8040S"*|*"Strix Halo"*|*"Ryzen AI Max"*|*"AI Max"*) _setup_gfx="gfx1151" ;;  # RDNA 3.5 (Strix Halo: Radeon 8060S/8050S/8040S iGPU, Ryzen AI Max+)
+            *"8065S"*|*"8060S"*|*"8050S"*|*"8040S"*|*"Strix Halo"*|*"Ryzen AI Max"*|*"AI Max"*) _setup_gfx="gfx1151" ;;  # RDNA 3.5 (Strix Halo + Gorgon Halo: Radeon 8065S/8060S/8050S/8040S iGPU, Ryzen AI Max / Max+)
             *"890M"*|*"880M"*|*"860M"*|*"840M"*|*"Strix Point"*|*"Krackan"*|*"HX 37"*|*"AI 9 HX"*|*"AI 9 36"*|*"AI 7 35"*|*"AI 5 34"*|*"AI 7 PRO 35"*|*"AI 5 33"*) _setup_gfx="gfx1150" ;;  # RDNA 3.5 (Strix/Krackan Point: Radeon 890M/880M iGPU, Ryzen AI 9 HX 370/375)
             *"RX 7600"*|*"RX 7700S"*|*"RX 7650"*|*"PRO W7600"*|*"PRO W7500"*|*"PRO V710"*)                  _setup_gfx="gfx1102" ;;  # RDNA 3 (Navi 33)
             *"RX 7900"*|*"RX 7800"*|*"RX 7700"*|*"PRO W7900"*|*"PRO W7800"*|*"PRO W7700"*)                  _setup_gfx="gfx1100" ;;  # RDNA 3 desktop / workstation (Navi 31)
@@ -1358,9 +1359,14 @@ else
     # name-inferred arch). Implies --has-rocm on the installer side.
     if [ -n "${_setup_gfx:-}" ]; then
         _PREBUILT_CMD+=(--rocm-gfx "$_setup_gfx")
-    elif [ "$_setup_amd_detected" = true ]; then
-        # AMD was detected but gfx resolution failed; tell the installer ROCm is
-        # present so it can still attempt a prebuilt. Mirrors setup.ps1 behaviour.
+    elif [ "$_setup_amd_detected" = true ] && \
+         { command -v hipcc >/dev/null 2>&1 || [ -x /opt/rocm/bin/hipcc ] || \
+           ls /opt/rocm-*/bin/hipcc >/dev/null 2>&1; }; then
+        # AMD detected but gfx unknown (KFD-only host): forward --has-rocm only when
+        # hipcc can actually build llama.cpp (incl. a versioned /opt/rocm-*/bin, the
+        # same paths the source build uses). With no gfx the prebuilt resolver finds
+        # no ROCm bundle and the source build would fail, so without hipcc fall
+        # through to the CPU prebuilt instead of breaking the install.
         _PREBUILT_CMD+=(--has-rocm)
     fi
     # UNSLOTH_LLAMA_CPP_BACKEND=cpu (case-insensitive, trimmed) forces the CPU-only
@@ -1961,6 +1967,99 @@ if [ ! -L "$LLAMA_CPP_DIR" ] && {
     _remove_agent_instruction_files "$LLAMA_CPP_DIR"
 fi
 
+# ── whisper.cpp (local speech-to-text dictation engine) ──
+# Optional runtime for local dictation. Fail-open: any failure leaves the
+# Transformers STT engine and browser dictation working, so it never aborts
+# setup (unlike llama.cpp). Runs in 'unsloth studio update' too so the runtime
+# installs/refreshes without a compiler. Installs beside llama.cpp under the
+# same managed home the sidecar's _managed_whisper_cpp_dir() resolves.
+WHISPER_CPP_DIR="$UNSLOTH_HOME/whisper.cpp"
+if [ -n "${WHISPER_SERVER_PATH:-}" ] || [ -n "${UNSLOTH_WHISPER_CPP_PATH:-}" ]; then
+    verbose_substep "whisper.cpp: using a user-configured binary/dir; skipping managed install"
+elif [ "${UNSLOTH_SKIP_WHISPER_INSTALL:-0}" = "1" ]; then
+    verbose_substep "whisper.cpp: install skipped (UNSLOTH_SKIP_WHISPER_INSTALL=1)"
+else
+    if [ "$_STUDIO_HOME_IS_CUSTOM" = true ]; then
+        _assert_studio_owned_or_absent "$WHISPER_CPP_DIR" "whisper.cpp install"
+    fi
+    _WHISPER_CMD=(python "$SCRIPT_DIR/install_whisper_prebuilt.py" --install-dir "$WHISPER_CPP_DIR")
+    if [ -n "${UNSLOTH_WHISPER_RELEASE_TAG:-}" ]; then
+        _WHISPER_CMD+=(--published-release-tag "$UNSLOTH_WHISPER_RELEASE_TAG")
+    fi
+    if [ -n "${_setup_gfx:-}" ]; then
+        _WHISPER_CMD+=(--rocm-gfx "$_setup_gfx")
+    elif [ "$_setup_amd_detected" = true ]; then
+        _WHISPER_CMD+=(--has-rocm)
+    fi
+    _WHISPER_LOG="$(mktemp)"
+    set +e
+    if _is_verbose; then
+        "${_WHISPER_CMD[@]}" 2>&1 | tee "$_WHISPER_LOG"
+        _WHISPER_STATUS=${PIPESTATUS[0]}
+    else
+        "${_WHISPER_CMD[@]}" >"$_WHISPER_LOG" 2>&1
+        _WHISPER_STATUS=$?
+    fi
+    set -e
+    if [ "$_WHISPER_STATUS" -eq 0 ]; then
+        if grep -Fq "already matches" "$_WHISPER_LOG"; then
+            step "whisper.cpp" "prebuilt up to date"
+        else
+            step "whisper.cpp" "prebuilt installed"
+        fi
+        if [ "$_STUDIO_HOME_IS_CUSTOM" = true ] && [ -d "$WHISPER_CPP_DIR" ]; then
+            : > "$WHISPER_CPP_DIR/$_STUDIO_OWNED_MARKER" 2>/dev/null || true
+        fi
+        rm -f "$_WHISPER_LOG"
+    elif [ "$_WHISPER_STATUS" -eq 3 ]; then
+        # A warm dictation server holds the binary; keep the old install.
+        step "whisper.cpp" "install busy; keeping existing runtime" "$C_WARN"
+        rm -f "$_WHISPER_LOG"
+    else
+        # A source build is opt-in. Keep the installer log until fallback has
+        # finished so setup can distinguish release skew from an operational
+        # installer failure and report the exact pairing when available.
+        _WHISPER_RECOVERED=false
+        _WHISPER_BUILD="$SCRIPT_DIR/../scripts/build_whisper_cpp.sh"
+        if [ "${UNSLOTH_WHISPER_FORCE_COMPILE:-0}" = "1" ] && [ -f "$_WHISPER_BUILD" ] \
+                && command -v cmake >/dev/null 2>&1 && command -v git >/dev/null 2>&1; then
+            substep "whisper.cpp prebuilt unavailable; building from source (UNSLOTH_WHISPER_FORCE_COMPILE=1)..."
+            # The source build overwrites whisper-server in the managed dir but
+            # knows nothing about the prebuilt marker; a stale marker would make
+            # a later setup run report "already matches" and skip repairing the
+            # prebuilt over the source binary. Drop it before building.
+            rm -f "$WHISPER_CPP_DIR/UNSLOTH_WHISPER_PREBUILT_INFO.json" 2>/dev/null || true
+            if run_quiet_no_exit "whisper.cpp source build" sh "$_WHISPER_BUILD"; then
+                _WHISPER_RECOVERED=true
+                step "whisper.cpp" "source build installed"
+                if [ "$_STUDIO_HOME_IS_CUSTOM" = true ] && [ -d "$WHISPER_CPP_DIR" ]; then
+                    : > "$WHISPER_CPP_DIR/$_STUDIO_OWNED_MARKER" 2>/dev/null || true
+                fi
+            else
+                :
+            fi
+        fi
+        if [ "$_WHISPER_RECOVERED" != true ]; then
+            if [ "$_WHISPER_STATUS" -eq 2 ]; then
+                _WHISPER_REQUIRED_TAG="$(sed -n 's/.*slim bundle requires llama\.cpp \([^; ]*\).*/\1/p' "$_WHISPER_LOG" | tail -n 1)"
+                _WHISPER_INSTALLED_TAG="$(python - "$UNSLOTH_HOME/llama.cpp/UNSLOTH_PREBUILT_INFO.json" <<'PY' 2>/dev/null || true
+import json, sys
+try:
+    print(json.load(open(sys.argv[1], encoding="utf-8")).get("release_tag", ""))
+except Exception:
+    pass
+PY
+)"
+                _WHISPER_PAIRING="installed llama.cpp ${_WHISPER_INSTALLED_TAG:-unknown}; whisper requires ${_WHISPER_REQUIRED_TAG:-unknown}"
+                step "whisper.cpp" "no compatible prebuilt ($_WHISPER_PAIRING); curated whisper.cpp dictation is unavailable; publish the paired releases in llama.cpp then whisper.cpp order; browser and Transformers dictation remain available" "$C_WARN"
+            else
+                step "whisper.cpp" "prebuilt install failed; curated whisper.cpp dictation is unavailable; retry setup or inspect verbose output; browser and Transformers dictation remain available" "$C_WARN"
+            fi
+        fi
+        rm -f "$_WHISPER_LOG"
+    fi
+fi
+
 # ── Footer ──
 if [ "$_LLAMA_ONLY" = "1" ]; then
     echo ""
diff --git a/studio/src-tauri/Cargo.lock b/studio/src-tauri/Cargo.lock
index 183cfc1cc8..604bb01525 100644
--- a/studio/src-tauri/Cargo.lock
+++ b/studio/src-tauri/Cargo.lock
@@ -5592,6 +5592,7 @@ dependencies = [
  "tauri-plugin-single-instance",
  "tauri-plugin-updater",
  "tauri-plugin-window-state",
+ "tempfile",
  "tokio",
  "windows 0.62.2",
  "windows-sys 0.61.2",
diff --git a/studio/src-tauri/Cargo.toml b/studio/src-tauri/Cargo.toml
index 438558fe77..826509ce9a 100644
--- a/studio/src-tauri/Cargo.toml
+++ b/studio/src-tauri/Cargo.toml
@@ -29,6 +29,7 @@ tauri-plugin-clipboard-manager = "2"
 tauri-plugin-dialog = "2"
 rand = "0.10.0"
 tauri-plugin-notification = "2.3.3"
+tempfile = "3"
 tauri-plugin-window-state = "2"
 
 [target.'cfg(unix)'.dependencies]
diff --git a/studio/src-tauri/Entitlements.plist b/studio/src-tauri/Entitlements.plist
index 10e6df3427..71b1d2c0f4 100644
--- a/studio/src-tauri/Entitlements.plist
+++ b/studio/src-tauri/Entitlements.plist
@@ -8,6 +8,9 @@
     <!-- Network access for backend health checks and HuggingFace API -->
     <key>com.apple.security.network.client</key>
     <true/>
+    <!-- Permit microphone capture for local dictation -->
+    <key>com.apple.security.device.audio-input</key>
+    <true/>
     <!-- Allow loading Python/venv libraries not signed by us -->
     <key>com.apple.security.cs.disable-library-validation</key>
     <true/>
diff --git a/studio/src-tauri/Info.plist b/studio/src-tauri/Info.plist
new file mode 100644
index 0000000000..e7a280647b
--- /dev/null
+++ b/studio/src-tauri/Info.plist
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+    <key>NSMicrophoneUsageDescription</key>
+    <string>Unsloth Studio uses the microphone you select for local voice dictation.</string>
+</dict>
+</plist>
diff --git a/studio/src-tauri/src/app_layout.rs b/studio/src-tauri/src/app_layout.rs
new file mode 100644
index 0000000000..9b9277b48d
--- /dev/null
+++ b/studio/src-tauri/src/app_layout.rs
@@ -0,0 +1,274 @@
+use std::fs;
+use std::path::{Path, PathBuf};
+use tauri::{Manager, WebviewWindow};
+
+use tauri_plugin_window_state::AppHandleExt;
+
+const APP_LAYOUT_MARKER_FILE: &str = "app-layout-initialized-v1";
+const INITIALIZED_MARKER: &[u8] = b"initialized\n";
+const RESET_MARKER: &[u8] = b"reset\n";
+
+const SETUP_WINDOW_WIDTH: f64 = 760.0;
+const SETUP_WINDOW_HEIGHT: f64 = 560.0;
+const MIN_REASONABLE_WINDOW_WIDTH: u64 = 320;
+const MIN_REASONABLE_WINDOW_HEIGHT: u64 = 240;
+
+const SETUP_SIZE_TOLERANCE_PX: f64 = 2.0;
+
+#[derive(serde::Deserialize)]
+struct PersistedWindowState {
+    width: u32,
+    height: u32,
+    #[serde(rename = "x")]
+    _x: i32,
+    #[serde(rename = "y")]
+    _y: i32,
+    #[serde(rename = "prev_x")]
+    _prev_x: i32,
+    #[serde(rename = "prev_y")]
+    _prev_y: i32,
+    #[serde(rename = "maximized")]
+    _maximized: bool,
+    #[serde(rename = "visible")]
+    _visible: bool,
+    #[serde(rename = "decorated")]
+    _decorated: bool,
+    #[serde(rename = "fullscreen")]
+    _fullscreen: bool,
+}
+
+fn marker_path(config_dir: &Path) -> PathBuf {
+    config_dir.join(APP_LAYOUT_MARKER_FILE)
+}
+
+fn marker_matches(config_dir: &Path, expected: &[u8]) -> bool {
+    fs::read(marker_path(config_dir))
+        .map(|contents| contents == expected)
+        .unwrap_or(false)
+}
+
+fn is_initialized(config_dir: &Path) -> bool {
+    marker_matches(config_dir, INITIALIZED_MARKER)
+}
+
+fn is_reset_pending(config_dir: &Path) -> bool {
+    marker_matches(config_dir, RESET_MARKER)
+}
+
+fn write_marker(config_dir: &Path, contents: &[u8]) -> Result<(), String> {
+    fs::create_dir_all(config_dir).map_err(|error| {
+        format!(
+            "Failed to create app configuration directory {}: {error}",
+            config_dir.display()
+        )
+    })?;
+    let path = marker_path(config_dir);
+    fs::write(&path, contents).map_err(|error| {
+        format!(
+            "Failed to write app layout marker {}: {error}",
+            path.display()
+        )
+    })
+}
+
+fn reset_initialized(config_dir: &Path) -> Result<(), String> {
+    write_marker(config_dir, RESET_MARKER)
+}
+
+fn is_setup_window_size(width: u64, height: u64) -> bool {
+    // Window-state persists physical dimensions but not their source scale.
+    let width_scale = width as f64 / SETUP_WINDOW_WIDTH;
+    let height_scale = height as f64 / SETUP_WINDOW_HEIGHT;
+    let scale_tolerance = SETUP_SIZE_TOLERANCE_PX / SETUP_WINDOW_WIDTH
+        + SETUP_SIZE_TOLERANCE_PX / SETUP_WINDOW_HEIGHT;
+    (width_scale - height_scale).abs() <= scale_tolerance
+}
+
+fn saved_main_window_size(config_dir: &Path, state_file_name: &str) -> Option<(u64, u64)> {
+    let contents = fs::read(config_dir.join(state_file_name)).ok()?;
+    let states = serde_json::from_slice::<std::collections::HashMap<String, PersistedWindowState>>(
+        &contents,
+    )
+    .ok()?;
+    let main = states.get("main")?;
+    let width = u64::from(main.width);
+    let height = u64::from(main.height);
+    if width < MIN_REASONABLE_WINDOW_WIDTH || height < MIN_REASONABLE_WINDOW_HEIGHT {
+        return None;
+    }
+    Some((width, height))
+}
+
+fn should_restore_saved_layout(config_dir: &Path, state_file_name: &str) -> bool {
+    if is_reset_pending(config_dir) {
+        return false;
+    }
+    let Some((width, height)) = saved_main_window_size(config_dir, state_file_name) else {
+        return false;
+    };
+    is_initialized(config_dir) || !is_setup_window_size(width, height)
+}
+
+fn mark_initialized(config_dir: &Path) -> Result<(), String> {
+    write_marker(config_dir, INITIALIZED_MARKER)
+}
+
+fn app_config_dir(app: &tauri::AppHandle) -> Result<PathBuf, String> {
+    app.path()
+        .app_config_dir()
+        .map_err(|error| format!("Could not determine app configuration directory: {error}"))
+}
+
+/// Returns whether a full-app layout has previously completed. Legacy state is
+/// migrated unless it matches the fixed setup-window size at any display scale.
+#[tauri::command]
+pub fn has_initialized_app_window_layout(
+    window: WebviewWindow,
+    app: tauri::AppHandle,
+) -> Result<bool, String> {
+    crate::native_intents::ensure_main_window(&window)?;
+    let config_dir = app_config_dir(&app)?;
+    Ok(should_restore_saved_layout(&config_dir, &app.filename()))
+}
+
+/// Persist only after the caller has successfully sized/centered or restored,
+/// shown, constrained, and minimum-sized the full application window.
+#[tauri::command]
+pub fn mark_app_window_layout_initialized(
+    window: WebviewWindow,
+    app: tauri::AppHandle,
+) -> Result<(), String> {
+    crate::native_intents::ensure_main_window(&window)?;
+    mark_initialized(&app_config_dir(&app)?)
+}
+
+/// Force the next full-app transition to use a monitor-safe layout. Setup can
+/// overwrite the plugin's saved full-app dimensions before the process exits.
+#[tauri::command]
+pub fn reset_app_window_layout_initialized(
+    window: WebviewWindow,
+    app: tauri::AppHandle,
+) -> Result<(), String> {
+    crate::native_intents::ensure_main_window(&window)?;
+    reset_initialized(&app_config_dir(&app)?)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use std::time::{SystemTime, UNIX_EPOCH};
+
+    fn temp_dir(name: &str) -> PathBuf {
+        let nanos = SystemTime::now()
+            .duration_since(UNIX_EPOCH)
+            .unwrap()
+            .as_nanos();
+        std::env::temp_dir().join(format!(
+            "unsloth-app-layout-{name}-{}-{nanos}",
+            std::process::id()
+        ))
+    }
+
+    fn window_state(width: u32, height: u32, maximized: bool) -> String {
+        serde_json::json!({
+            "main": {
+                "width": width,
+                "height": height,
+                "x": 0,
+                "y": 0,
+                "prev_x": 0,
+                "prev_y": 0,
+                "maximized": maximized,
+                "visible": true,
+                "decorated": true,
+                "fullscreen": false
+            }
+        })
+        .to_string()
+    }
+
+    #[test]
+    fn marker_is_absent_until_full_layout_is_marked() {
+        let dir = temp_dir("transition");
+        assert!(!is_initialized(&dir));
+        mark_initialized(&dir).unwrap();
+        assert!(is_initialized(&dir));
+        assert_eq!(fs::read(marker_path(&dir)).unwrap(), b"initialized\n");
+        let _ = fs::remove_dir_all(dir);
+    }
+
+    #[test]
+    fn marker_write_and_reset_are_idempotent() {
+        let dir = temp_dir("idempotent");
+        mark_initialized(&dir).unwrap();
+        mark_initialized(&dir).unwrap();
+        assert!(is_initialized(&dir));
+        assert!(!is_reset_pending(&dir));
+
+        reset_initialized(&dir).unwrap();
+        reset_initialized(&dir).unwrap();
+        assert!(!is_initialized(&dir));
+        assert!(is_reset_pending(&dir));
+
+        mark_initialized(&dir).unwrap();
+        assert!(is_initialized(&dir));
+        assert!(!is_reset_pending(&dir));
+        let _ = fs::remove_dir_all(dir);
+    }
+
+    #[test]
+    fn legacy_full_app_state_is_migrated_but_setup_state_at_any_scale_is_not() {
+        let dir = temp_dir("legacy-plugin-state");
+        fs::create_dir_all(&dir).unwrap();
+        let state_file = ".window-state.json";
+        let state_path = dir.join(state_file);
+
+        fs::write(&state_path, window_state(1200, 800, false)).unwrap();
+        assert!(should_restore_saved_layout(&dir, state_file));
+
+        fs::write(&state_path, window_state(760, 560, false)).unwrap();
+        assert!(!should_restore_saved_layout(&dir, state_file));
+
+        fs::write(&state_path, window_state(950, 700, false)).unwrap();
+        assert!(!should_restore_saved_layout(&dir, state_file));
+
+        fs::write(&state_path, window_state(1520, 1120, false)).unwrap();
+        assert!(!should_restore_saved_layout(&dir, state_file));
+
+        fs::write(&state_path, window_state(1520, 1120, true)).unwrap();
+        assert!(!should_restore_saved_layout(&dir, state_file));
+        let _ = fs::remove_dir_all(dir);
+    }
+
+    #[test]
+    fn explicit_reset_blocks_legacy_migration_until_app_layout_completes() {
+        let dir = temp_dir("reset-migration");
+        fs::create_dir_all(&dir).unwrap();
+        let state_file = ".window-state.json";
+        fs::write(dir.join(state_file), window_state(1200, 800, false)).unwrap();
+
+        mark_initialized(&dir).unwrap();
+        assert!(should_restore_saved_layout(&dir, state_file));
+        reset_initialized(&dir).unwrap();
+        assert!(!should_restore_saved_layout(&dir, state_file));
+        mark_initialized(&dir).unwrap();
+        assert!(should_restore_saved_layout(&dir, state_file));
+        let _ = fs::remove_dir_all(dir);
+    }
+
+    #[test]
+    fn corrupt_plugin_state_does_not_restore_even_with_initialized_marker() {
+        let dir = temp_dir("plugin-state");
+        fs::create_dir_all(&dir).unwrap();
+        let state_file = ".window-state.json";
+        fs::write(
+            dir.join(state_file),
+            r#"{"main":{"width":1200,"height":800}}"#,
+        )
+        .unwrap();
+        mark_initialized(&dir).unwrap();
+        assert!(is_initialized(&dir));
+        assert!(!should_restore_saved_layout(&dir, state_file));
+        let _ = fs::remove_dir_all(dir);
+    }
+}
diff --git a/studio/src-tauri/src/commands.rs b/studio/src-tauri/src/commands.rs
index 5d41cb9217..72ea9d6985 100644
--- a/studio/src-tauri/src/commands.rs
+++ b/studio/src-tauri/src/commands.rs
@@ -339,11 +339,21 @@ pub fn get_server_logs(state: tauri::State<'_, BackendState>) -> Vec<String> {
 
 /// Open an existing directory in the system file manager. Validates the path
 /// up front so callers get a clean error instead of a raw OS failure.
-fn open_existing_dir(dir: &std::path::Path) -> Result<(), String> {
+fn open_existing_dir_with<E>(
+    dir: &std::path::Path,
+    opener: impl FnOnce(&std::path::Path) -> Result<(), E>,
+) -> Result<(), String>
+where
+    E: std::fmt::Display,
+{
     if !dir.is_dir() {
         return Err(format!("Directory does not exist: {}", dir.display()));
     }
-    open::that(dir).map_err(|e| format!("Failed to open directory: {}", e))
+    opener(dir).map_err(|error| format!("Failed to open directory: {error}"))
+}
+
+fn open_existing_dir(dir: &std::path::Path) -> Result<(), String> {
+    open_existing_dir_with(dir, |path| open::that_detached(path))
 }
 
 /// Open the Unsloth Studio directory in the system file manager.
@@ -641,7 +651,8 @@ pub async fn start_managed_repair(
 
 #[cfg(test)]
 mod tests {
-    use std::time::Duration;
+    use std::fs;
+    use std::time::{Duration, SystemTime, UNIX_EPOCH};
     use tokio::io::{AsyncReadExt, AsyncWriteExt};
     use tokio::net::TcpListener;
 
@@ -699,6 +710,40 @@ mod tests {
         port
     }
 
+    #[test]
+    fn existing_directory_helper_invokes_opener_and_surfaces_errors() {
+        let nanos = SystemTime::now()
+            .duration_since(UNIX_EPOCH)
+            .unwrap()
+            .as_nanos();
+        let dir =
+            std::env::temp_dir().join(format!("unsloth-open-dir-{}-{nanos}", std::process::id()));
+        fs::create_dir_all(&dir).unwrap();
+        let mut opened = false;
+        super::open_existing_dir_with(&dir, |path| {
+            opened = true;
+            assert_eq!(path, dir);
+            Ok::<_, &str>(())
+        })
+        .unwrap();
+        assert!(opened);
+
+        let error = super::open_existing_dir_with(&dir, |_| Err("opener failed")).unwrap_err();
+        assert!(error.contains("opener failed"));
+        let _ = fs::remove_dir_all(dir);
+    }
+
+    #[test]
+    fn existing_directory_helper_rejects_missing_path_without_opening() {
+        let missing = std::env::temp_dir().join("unsloth-definitely-missing-open-dir");
+        let error = super::open_existing_dir_with(&missing, |_| {
+            panic!("opener must not run for an invalid directory");
+            #[allow(unreachable_code)]
+            Ok::<_, &str>(())
+        })
+        .unwrap_err();
+        assert!(error.contains("Directory does not exist"));
+    }
     #[test]
     fn repair_elevation_is_not_a_terminal_repair_failure() {
         assert!(!super::should_emit_repair_failed("NEEDS_ELEVATION"));
diff --git a/studio/src-tauri/src/main.rs b/studio/src-tauri/src/main.rs
index 4724317601..405b390177 100644
--- a/studio/src-tauri/src/main.rs
+++ b/studio/src-tauri/src/main.rs
@@ -1,5 +1,6 @@
 #![cfg_attr(not(debug_assertions), windows_subsystem = "windows")]
 
+mod app_layout;
 mod commands;
 mod desktop_auth;
 mod desktop_backend_owner;
@@ -7,6 +8,7 @@ mod desktop_update_policy;
 mod diagnostics;
 mod install;
 mod native_backend_lease;
+mod native_file_dialogs;
 mod native_intents;
 mod native_path_policy;
 mod preflight;
@@ -195,6 +197,9 @@ fn main() {
         .manage(process::new_shutdown_flag())
         .manage(update::new_update_state())
         .invoke_handler(tauri::generate_handler![
+            app_layout::has_initialized_app_window_layout,
+            app_layout::mark_app_window_layout_initialized,
+            app_layout::reset_app_window_layout_initialized,
             commands::check_install_status,
             commands::desktop_preflight,
             commands::start_install,
@@ -213,9 +218,12 @@ fn main() {
             desktop_update_policy::check_desktop_manual_update,
             desktop_update_policy::desktop_update_policy,
             diagnostics::collect_support_diagnostics,
+            native_file_dialogs::save_native_file,
+            native_file_dialogs::pick_native_chat_import,
             native_intents::drain_native_intents,
             native_intents::register_native_model_path,
             native_intents::pick_native_model,
+            native_intents::pick_hugging_face_cache_dir,
             native_intents::consume_native_path_token,
             native_intents::register_artifact_path,
             native_intents::reveal_path_token,
diff --git a/studio/src-tauri/src/native_file_dialogs.rs b/studio/src-tauri/src/native_file_dialogs.rs
new file mode 100644
index 0000000000..d795eb020c
--- /dev/null
+++ b/studio/src-tauri/src/native_file_dialogs.rs
@@ -0,0 +1,320 @@
+use base64::{engine::general_purpose::STANDARD as BASE64, Engine as _};
+
+use serde::Serialize;
+use std::fs::{self, File};
+use std::io::{Read, Write};
+use std::path::{Path, PathBuf};
+use tauri::{AppHandle, WebviewWindow};
+use tauri_plugin_dialog::DialogExt;
+
+const MAX_CHAT_IMPORT_BYTES: u64 = 64 * 1024 * 1024;
+const NATIVE_FILE_NAME_HEADER: &str = "x-unsloth-default-name";
+const CHAT_IMPORT_EXTENSIONS: &[&str] = &["jsonl", "ndjson", "csv"];
+
+#[derive(Debug, Serialize)]
+#[serde(rename_all = "camelCase")]
+pub struct NativeImportedFile {
+    name: String,
+    content: String,
+}
+
+fn default_file_name(suggested_name: &str) -> String {
+    Path::new(suggested_name)
+        .file_name()
+        .and_then(|name| name.to_str())
+        .filter(|name| !name.is_empty() && *name != "." && *name != "..")
+        .unwrap_or("unsloth-export.json")
+        .to_string()
+}
+fn decode_default_file_name(encoded_name: &str) -> Result<String, String> {
+    let bytes = BASE64
+        .decode(encoded_name)
+        .map_err(|_| "Invalid native export filename.".to_string())?;
+    let name =
+        String::from_utf8(bytes).map_err(|_| "Invalid native export filename.".to_string())?;
+    Ok(default_file_name(&name))
+}
+
+fn save_filter(file_name: &str) -> (&'static str, Vec<&'static str>) {
+    match Path::new(file_name)
+        .extension()
+        .and_then(|extension| extension.to_str())
+        .map(str::to_ascii_lowercase)
+        .as_deref()
+    {
+        Some("json") => ("JSON", vec!["json"]),
+        Some("jsonl") | Some("ndjson") => ("JSON Lines", vec!["jsonl", "ndjson"]),
+        Some("csv") => ("CSV", vec!["csv"]),
+        Some("md") | Some("markdown") => ("Markdown", vec!["md", "markdown"]),
+        Some("zip") => ("ZIP archive", vec!["zip"]),
+        _ => (
+            "Export files",
+            vec!["json", "jsonl", "ndjson", "csv", "md", "markdown", "zip"],
+        ),
+    }
+}
+
+fn local_dialog_path(path: tauri_plugin_dialog::FilePath) -> Result<PathBuf, String> {
+    path.into_path()
+        .map_err(|_| "Only local filesystem paths are supported.".to_string())
+}
+
+fn save_selected_file(
+    selected_path: Option<PathBuf>,
+    content: &[u8],
+) -> Result<Option<String>, String> {
+    let Some(path) = selected_path else {
+        return Ok(None);
+    };
+    let parent = path
+        .parent()
+        .filter(|parent| !parent.as_os_str().is_empty())
+        .unwrap_or_else(|| Path::new("."));
+    let mut builder = tempfile::Builder::new();
+    #[cfg(unix)]
+    {
+        use std::os::unix::fs::PermissionsExt;
+        let permissions = fs::metadata(&path)
+            .map(|metadata| metadata.permissions())
+            .unwrap_or_else(|_| fs::Permissions::from_mode(0o666));
+        builder.permissions(permissions);
+    }
+    let mut temporary = builder
+        .prefix(".unsloth-export-")
+        .tempfile_in(parent)
+        .map_err(|error| format!("Failed to prepare {}: {error}", path.display()))?;
+    temporary
+        .write_all(content)
+        .and_then(|()| temporary.as_file().sync_all())
+        .map_err(|error| format!("Failed to save {}: {error}", path.display()))?;
+    temporary
+        .persist(&path)
+        .map_err(|error| format!("Failed to save {}: {}", path.display(), error.error))?;
+    let file_name = path
+        .file_name()
+        .and_then(|name| name.to_str())
+        .unwrap_or("export")
+        .to_string();
+    Ok(Some(file_name))
+}
+
+fn read_selected_import(
+    selected_path: Option<PathBuf>,
+) -> Result<Option<NativeImportedFile>, String> {
+    let Some(path) = selected_path else {
+        return Ok(None);
+    };
+    let extension = path
+        .extension()
+        .and_then(|extension| extension.to_str())
+        .map(str::to_ascii_lowercase)
+        .ok_or_else(|| "Chat import must be a .jsonl, .ndjson, or .csv file.".to_string())?;
+    if !CHAT_IMPORT_EXTENSIONS.contains(&extension.as_str()) {
+        return Err("Chat import must be a .jsonl, .ndjson, or .csv file.".to_string());
+    }
+
+    let metadata = fs::metadata(&path)
+        .map_err(|error| format!("Failed to inspect {}: {error}", path.display()))?;
+    if !metadata.is_file() {
+        return Err(format!("Selected import is not a file: {}", path.display()));
+    }
+    if metadata.len() > MAX_CHAT_IMPORT_BYTES {
+        return Err(format!(
+            "Chat import is too large (maximum {} MiB).",
+            MAX_CHAT_IMPORT_BYTES / 1024 / 1024
+        ));
+    }
+
+    // Limit the read too, so a file that grows after metadata inspection cannot
+    // make the command allocate without bound.
+    let file =
+        File::open(&path).map_err(|error| format!("Failed to open {}: {error}", path.display()))?;
+    let mut bytes = Vec::with_capacity(metadata.len() as usize);
+    file.take(MAX_CHAT_IMPORT_BYTES + 1)
+        .read_to_end(&mut bytes)
+        .map_err(|error| format!("Failed to read {}: {error}", path.display()))?;
+    if bytes.len() as u64 > MAX_CHAT_IMPORT_BYTES {
+        return Err(format!(
+            "Chat import is too large (maximum {} MiB).",
+            MAX_CHAT_IMPORT_BYTES / 1024 / 1024
+        ));
+    }
+    let content = String::from_utf8(bytes)
+        .map_err(|_| format!("Chat import is not valid UTF-8: {}", path.display()))?;
+    let name = path
+        .file_name()
+        .and_then(|name| name.to_str())
+        .map(str::to_string)
+        .unwrap_or_else(|| format!("chat-import.{extension}"));
+    Ok(Some(NativeImportedFile { name, content }))
+}
+
+#[tauri::command]
+pub async fn save_native_file(
+    window: WebviewWindow,
+    app: AppHandle,
+    request: tauri::ipc::Request<'_>,
+) -> Result<Option<String>, String> {
+    crate::native_intents::ensure_main_window(&window)?;
+    let encoded_name = request
+        .headers()
+        .get(NATIVE_FILE_NAME_HEADER)
+        .ok_or_else(|| "Native export filename is missing.".to_string())?
+        .to_str()
+        .map_err(|_| "Invalid native export filename.".to_string())?;
+    let file_name = decode_default_file_name(encoded_name)?;
+    let content = match request.body() {
+        tauri::ipc::InvokeBody::Raw(content) => content,
+        _ => return Err("Native export content must be binary.".to_string()),
+    };
+    let (filter_name, extensions) = save_filter(&file_name);
+    let (tx, rx) = tokio::sync::oneshot::channel();
+    app.dialog()
+        .file()
+        .set_title("Save Unsloth export")
+        .set_file_name(file_name)
+        .add_filter(filter_name, &extensions)
+        .save_file(move |path| {
+            let _ = tx.send(path);
+        });
+    let selected_path = rx
+        .await
+        .map_err(|_| "Save dialog closed unexpectedly.".to_string())?
+        .map(local_dialog_path)
+        .transpose()?;
+    save_selected_file(selected_path, content)
+}
+
+#[tauri::command]
+pub async fn pick_native_chat_import(
+    window: WebviewWindow,
+    app: AppHandle,
+) -> Result<Option<NativeImportedFile>, String> {
+    crate::native_intents::ensure_main_window(&window)?;
+    let (tx, rx) = tokio::sync::oneshot::channel();
+    app.dialog()
+        .file()
+        .set_title("Import chats")
+        .add_filter("Chat exports", CHAT_IMPORT_EXTENSIONS)
+        .pick_file(move |path| {
+            let _ = tx.send(path);
+        });
+    let selected_path = rx
+        .await
+        .map_err(|_| "Import dialog closed unexpectedly.".to_string())?
+        .map(local_dialog_path)
+        .transpose()?;
+    read_selected_import(selected_path)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use std::time::{SystemTime, UNIX_EPOCH};
+
+    fn temp_path(name: &str) -> PathBuf {
+        let nanos = SystemTime::now()
+            .duration_since(UNIX_EPOCH)
+            .unwrap()
+            .as_nanos();
+        std::env::temp_dir().join(format!(
+            "unsloth-native-files-{name}-{}-{nanos}",
+            std::process::id()
+        ))
+    }
+
+    #[test]
+    fn cancellation_is_quiet_for_save_and_import() {
+        assert!(save_selected_file(None, b"x").unwrap().is_none());
+        assert!(read_selected_import(None).unwrap().is_none());
+    }
+
+    #[test]
+    fn writes_text_and_binary_exactly() {
+        // Overwriting must stage the new content before replacing the destination.
+        let text_path = temp_path("text").with_extension("json");
+        let binary_path = temp_path("binary").with_extension("zip");
+
+        fs::write(&text_path, b"previous export").unwrap();
+        save_selected_file(Some(text_path.clone()), b"{\"ok\":true}").unwrap();
+        save_selected_file(Some(binary_path.clone()), &[0, 1, 2, 255]).unwrap();
+        assert_eq!(fs::read(&text_path).unwrap(), b"{\"ok\":true}");
+        assert_eq!(fs::read(&binary_path).unwrap(), [0, 1, 2, 255]);
+        let _ = fs::remove_file(text_path);
+        let _ = fs::remove_file(binary_path);
+    }
+
+    #[test]
+    fn markdown_exports_use_a_markdown_save_filter() {
+        assert_eq!(
+            save_filter("message.md"),
+            ("Markdown", vec!["md", "markdown"])
+        );
+    }
+
+    #[test]
+    fn reads_supported_import_and_rejects_other_extensions() {
+        let jsonl_path = temp_path("allowed").with_extension("JSONL");
+        fs::write(&jsonl_path, "{\"messages\":[]}").unwrap();
+        let imported = read_selected_import(Some(jsonl_path.clone()))
+            .unwrap()
+            .unwrap();
+        assert_eq!(imported.content, "{\"messages\":[]}");
+
+        let json_path = temp_path("unsupported").with_extension("json");
+        fs::write(&json_path, "{}").unwrap();
+        assert!(read_selected_import(Some(json_path.clone())).is_err());
+        let txt_path = temp_path("denied").with_extension("txt");
+        fs::write(&txt_path, "no").unwrap();
+        assert!(read_selected_import(Some(txt_path.clone()))
+            .unwrap_err()
+            .contains(".json"));
+        let _ = fs::remove_file(jsonl_path);
+        let _ = fs::remove_file(json_path);
+        let _ = fs::remove_file(txt_path);
+    }
+
+    #[test]
+    fn read_limit_and_utf8_errors_are_concrete() {
+        let oversized = temp_path("oversized").with_extension("csv");
+        let file = File::create(&oversized).unwrap();
+        file.set_len(MAX_CHAT_IMPORT_BYTES + 1).unwrap();
+        assert!(read_selected_import(Some(oversized.clone()))
+            .unwrap_err()
+            .contains("too large"));
+
+        let invalid = temp_path("invalid-utf8").with_extension("jsonl");
+        fs::write(&invalid, [0xff]).unwrap();
+        assert!(read_selected_import(Some(invalid.clone()))
+            .unwrap_err()
+            .contains("UTF-8"));
+        let _ = fs::remove_file(oversized);
+        let _ = fs::remove_file(invalid);
+    }
+
+    #[cfg(unix)]
+    #[test]
+    fn non_utf8_import_name_preserves_csv_extension() {
+        use std::ffi::OsString;
+        use std::os::unix::ffi::OsStringExt;
+
+        let path = std::env::temp_dir().join(OsString::from_vec(vec![
+            b'u', b'n', b's', b'l', b'o', b't', b'h', 0xff, b'.', b'c', b's', b'v',
+        ]));
+        fs::write(&path, "role,content\nuser,hello\n").unwrap();
+        let imported = read_selected_import(Some(path.clone())).unwrap().unwrap();
+        assert_eq!(imported.name, "chat-import.csv");
+        let _ = fs::remove_file(path);
+    }
+
+    #[test]
+    fn strips_directories_from_suggested_default_name() {
+        assert_eq!(default_file_name("../../chat.jsonl"), "chat.jsonl");
+        assert_eq!(default_file_name(""), "unsloth-export.json");
+
+        assert_eq!(
+            decode_default_file_name("Y2hhdC5qc29ubA==").unwrap(),
+            "chat.jsonl"
+        );
+    }
+}
diff --git a/studio/src-tauri/src/native_intents.rs b/studio/src-tauri/src/native_intents.rs
index dccbba7083..006babfaa7 100644
--- a/studio/src-tauri/src/native_intents.rs
+++ b/studio/src-tauri/src/native_intents.rs
@@ -16,6 +16,25 @@ use tauri_plugin_dialog::DialogExt;
 
 const TOKEN_TTL: Duration = Duration::from_secs(15 * 60);
 
+fn normalize_windows_verbatim_path(path: String) -> String {
+    if let Some(rest) = path.strip_prefix(r"\\?\UNC\") {
+        return format!(r"\\{rest}");
+    }
+    path.strip_prefix(r"\\?\").unwrap_or(&path).to_string()
+}
+
+fn portable_path_string(path: &Path) -> String {
+    let value = path.to_string_lossy().to_string();
+    #[cfg(windows)]
+    {
+        return normalize_windows_verbatim_path(value);
+    }
+    #[cfg(not(windows))]
+    {
+        value
+    }
+}
+
 #[derive(Clone, Debug)]
 struct NativePathEntry {
     token: String,
@@ -311,6 +330,34 @@ pub async fn pick_native_model(
         .map(Some)
 }
 
+#[tauri::command]
+pub async fn pick_hugging_face_cache_dir(
+    window: WebviewWindow,
+    app: AppHandle,
+) -> Result<Option<String>, String> {
+    ensure_main_window(&window)?;
+    let (tx, rx) = tokio::sync::oneshot::channel();
+    app.dialog()
+        .file()
+        .set_title("Choose model download location")
+        .pick_folder(move |path| {
+            let _ = tx.send(path);
+        });
+    let Some(folder_path) = rx.await.map_err(|_| "Dialog closed".to_string())? else {
+        return Ok(None);
+    };
+    let path = folder_path
+        .into_path()
+        .map_err(|_| "Only local filesystem folders are supported.".to_string())?;
+    let canonical = path
+        .canonicalize()
+        .map_err(|e| format!("Could not use the selected folder: {e}"))?;
+    if !canonical.is_dir() {
+        return Err("The selected location is not a folder.".to_string());
+    }
+    Ok(Some(portable_path_string(&canonical)))
+}
+
 #[tauri::command]
 pub fn consume_native_path_token(
     window: WebviewWindow,
@@ -451,6 +498,18 @@ mod tests {
         let _ = fs::remove_file(path);
     }
 
+    #[test]
+    fn windows_verbatim_paths_are_portable() {
+        assert_eq!(
+            normalize_windows_verbatim_path(r"\\?\C:\models\cache".to_string()),
+            r"C:\models\cache"
+        );
+        assert_eq!(
+            normalize_windows_verbatim_path(r"\\?\UNC\server\share\cache".to_string()),
+            r"\\server\share\cache"
+        );
+    }
+
     #[cfg(unix)]
     #[test]
     fn reveal_rejects_symlink_replacement() {
diff --git a/studio/src-tauri/src/native_path_policy.rs b/studio/src-tauri/src/native_path_policy.rs
index b82e516e7a..26d4cdb61a 100644
--- a/studio/src-tauri/src/native_path_policy.rs
+++ b/studio/src-tauri/src/native_path_policy.rs
@@ -130,8 +130,8 @@ fn classify_existing_path(path: &Path) -> Result<ClassifiedPath, String> {
         .canonicalize()
         .map_err(|e| format!("Path could not be resolved: {e}"))?;
     reject_network_or_device_path(&canonical_path)?;
-    let canonical_symlink_metadata = fs::symlink_metadata(&canonical_path)
-        .map_err(|e| format!("Path is not available: {e}"))?;
+    let canonical_symlink_metadata =
+        fs::symlink_metadata(&canonical_path).map_err(|e| format!("Path is not available: {e}"))?;
     if canonical_symlink_metadata.file_type().is_symlink() {
         return Err("Symlink paths are not supported for native intake.".to_string());
     }
diff --git a/studio/src-tauri/tauri.macos.conf.json b/studio/src-tauri/tauri.macos.conf.json
index 202c9fb505..b1517a6234 100644
--- a/studio/src-tauri/tauri.macos.conf.json
+++ b/studio/src-tauri/tauri.macos.conf.json
@@ -2,6 +2,7 @@
   "bundle": {
     "macOS": {
       "entitlements": "./Entitlements.plist",
+      "infoPlist": "./Info.plist",
       "dmg": {
         "appPosition": { "x": 180, "y": 220 },
         "applicationFolderPosition": { "x": 480, "y": 220 }
diff --git a/tests/run_all.sh b/tests/run_all.sh
index a31103a85b..eaa726f73c 100755
--- a/tests/run_all.sh
+++ b/tests/run_all.sh
@@ -17,6 +17,7 @@ sh "$TESTS_DIR/sh/test_uninstall_shared_icon.sh"
 sh "$TESTS_DIR/sh/test_torch_flavor.sh"
 sh "$TESTS_DIR/sh/test_redact_install_output.sh"
 sh "$TESTS_DIR/sh/test_install_uv_override_space.sh"
+sh "$TESTS_DIR/sh/test_install_rollback_lifecycle.sh"
 
 echo ""
 echo "=== Python tests ==="
diff --git a/tests/sh/test_install_rollback_lifecycle.sh b/tests/sh/test_install_rollback_lifecycle.sh
new file mode 100644
index 0000000000..d1ccae8e19
--- /dev/null
+++ b/tests/sh/test_install_rollback_lifecycle.sh
@@ -0,0 +1,202 @@
+#!/bin/bash
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+# Exercises install.sh's real rollback helpers without downloading the Studio stack.
+set -e
+
+SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
+INSTALL_SH="$SCRIPT_DIR/../../install.sh"
+INSTALL_PS1="$SCRIPT_DIR/../../install.ps1"
+PASS=0
+FAIL=0
+
+ok()  { echo "  PASS: $1"; PASS=$((PASS + 1)); }
+bad() { echo "  FAIL: $1"; FAIL=$((FAIL + 1)); }
+
+ROLLBACK_BLOCK=$(sed -n '/^_VENV_ROLLBACK_DIR=""/,/^trap '\''_on_install_signal 143'\'' TERM$/p' "$INSTALL_SH")
+if ! printf '%s\n' "$ROLLBACK_BLOCK" | grep -q '^_on_install_signal() {'; then
+    echo "  FAIL: could not extract rollback lifecycle block from install.sh"
+    exit 1
+fi
+
+WORK=$(mktemp -d)
+trap 'rm -rf "$WORK"' EXIT
+
+run_signal_case() {
+    _signal="$1"
+    _expected_status="$2"
+    _case_dir="$WORK/signal-$_signal"
+    mkdir -p "$_case_dir/unsloth_studio"
+    printf 'old\n' > "$_case_dir/unsloth_studio/generation"
+    _harness="$_case_dir/harness.sh"
+    {
+        printf '%s\n' 'set -e'
+        printf '%s\n' 'substep() { :; }'
+        printf '%s\n' 'C_WARN=""'
+        printf "STUDIO_HOME='%s'\n" "$_case_dir"
+        printf "VENV_DIR='%s/unsloth_studio'\n" "$_case_dir"
+        printf '%s\n' "$ROLLBACK_BLOCK"
+        printf '%s\n' '_start_studio_venv_replacement "$VENV_DIR"'
+        printf '%s\n' 'mkdir -p "$VENV_DIR"'
+        printf '%s\n' 'printf "partial\n" > "$VENV_DIR/generation"'
+        printf 'kill -%s $$\n' "$_signal"
+        printf '%s\n' 'exit 99'
+    } > "$_harness"
+
+    set +e
+    dash "$_harness" >/dev/null 2>&1
+    _status=$?
+    set -e
+    if [ "$_status" = "$_expected_status" ]; then
+        ok "dash $_signal exits with $_expected_status"
+    else
+        bad "dash $_signal exits with $_expected_status (got $_status)"
+    fi
+    if [ "$(cat "$_case_dir/unsloth_studio/generation" 2>/dev/null)" = "old" ]; then
+        ok "dash $_signal restores the previous environment"
+    else
+        bad "dash $_signal did not restore the previous environment"
+    fi
+    if ! find "$_case_dir" -maxdepth 1 -name 'unsloth_studio.rollback.*' -print -quit | grep -q .; then
+        ok "dash $_signal leaves no rollback copy"
+    else
+        bad "dash $_signal left a rollback copy"
+    fi
+}
+
+echo "=== install.sh signal rollback ==="
+run_signal_case INT 130
+run_signal_case TERM 143
+run_signal_case HUP 129
+
+echo "=== install.sh transition boundaries ==="
+START_BOUNDARY_DIR="$WORK/start-boundary"
+mkdir -p "$START_BOUNDARY_DIR/unsloth_studio"
+printf 'old\n' > "$START_BOUNDARY_DIR/unsloth_studio/generation"
+START_BOUNDARY_HARNESS="$START_BOUNDARY_DIR/harness.sh"
+{
+    printf '%s\n' 'set -e'
+    printf '%s\n' 'substep() { :; }'
+    printf '%s\n' 'C_WARN=""'
+    printf "STUDIO_HOME='%s'\n" "$START_BOUNDARY_DIR"
+    printf "VENV_DIR='%s/unsloth_studio'\n" "$START_BOUNDARY_DIR"
+    printf '%s\n' "$ROLLBACK_BLOCK"
+    printf '%s\n' 'mv() { command mv "$@"; kill -TERM $$; }'
+    printf '%s\n' '_start_studio_venv_replacement "$VENV_DIR"'
+} > "$START_BOUNDARY_HARNESS"
+set +e
+dash "$START_BOUNDARY_HARNESS" >/dev/null 2>&1
+_start_boundary_status=$?
+set -e
+if [ "$_start_boundary_status" -eq 143 ] \
+   && [ "$(cat "$START_BOUNDARY_DIR/unsloth_studio/generation" 2>/dev/null)" = "old" ]; then
+    ok "signal immediately after rollback rename restores the old environment"
+else
+    bad "rollback state was not published before rename"
+fi
+
+COMMIT_BOUNDARY_DIR="$WORK/commit-boundary"
+mkdir -p "$COMMIT_BOUNDARY_DIR/unsloth_studio"
+printf 'old\n' > "$COMMIT_BOUNDARY_DIR/unsloth_studio/generation"
+COMMIT_BOUNDARY_HARNESS="$COMMIT_BOUNDARY_DIR/harness.sh"
+{
+    printf '%s\n' 'set -e'
+    printf '%s\n' 'substep() { :; }'
+    printf '%s\n' 'C_WARN=""'
+    printf "STUDIO_HOME='%s'\n" "$COMMIT_BOUNDARY_DIR"
+    printf "VENV_DIR='%s/unsloth_studio'\n" "$COMMIT_BOUNDARY_DIR"
+    printf '%s\n' "$ROLLBACK_BLOCK"
+    printf '%s\n' '_start_studio_venv_replacement "$VENV_DIR"'
+    printf '%s\n' 'mkdir -p "$VENV_DIR"'
+    printf '%s\n' 'printf "new\n" > "$VENV_DIR/generation"'
+    printf '%s\n' 'rm() { kill -TERM $$; }'
+    printf '%s\n' '_commit_studio_venv_replacement'
+} > "$COMMIT_BOUNDARY_HARNESS"
+set +e
+dash "$COMMIT_BOUNDARY_HARNESS" >/dev/null 2>&1
+_commit_boundary_status=$?
+set -e
+if [ "$_commit_boundary_status" -eq 143 ] \
+   && [ "$(cat "$COMMIT_BOUNDARY_DIR/unsloth_studio/generation" 2>/dev/null)" = "new" ]; then
+    ok "signal during committed-backup deletion keeps the new environment"
+else
+    bad "signal during committed-backup deletion restored a partial backup"
+fi
+
+echo "=== install.sh successful cleanup ==="
+PRUNE_DIR="$WORK/prune"
+mkdir -p "$PRUNE_DIR/unsloth_studio"
+printf 'old\n' > "$PRUNE_DIR/unsloth_studio/generation"
+PRUNE_HARNESS="$PRUNE_DIR/harness.sh"
+{
+    printf '%s\n' 'set -e'
+    printf '%s\n' 'substep() { :; }'
+    printf '%s\n' 'C_WARN=""'
+    printf "STUDIO_HOME='%s'\n" "$PRUNE_DIR"
+    printf "VENV_DIR='%s/unsloth_studio'\n" "$PRUNE_DIR"
+    printf '%s\n' "$ROLLBACK_BLOCK"
+    printf '%s\n' '_start_studio_venv_replacement "$VENV_DIR"'
+    printf '%s\n' 'mkdir -p "$VENV_DIR"'
+    printf '%s\n' 'printf "new\n" > "$VENV_DIR/generation"'
+    printf '%s\n' 'mkdir "$STUDIO_HOME/unsloth_studio.rollback.20000101000000.999999999"'
+    printf '%s\n' 'mkdir "$STUDIO_HOME/unsloth_studio.rollback.20000101000001.$$"'
+    printf '%s\n' 'mkdir "$STUDIO_HOME/unsloth_studio.rollback.user-data"'
+    printf '%s\n' 'mkdir "$STUDIO_HOME/outside"'
+    printf '%s\n' 'ln -s "$STUDIO_HOME/outside" "$STUDIO_HOME/unsloth_studio.rollback.20000101000002.999999998"'
+    printf '%s\n' '_commit_studio_venv_replacement'
+} > "$PRUNE_HARNESS"
+
+sh "$PRUNE_HARNESS" >/dev/null 2>&1
+if [ "$(cat "$PRUNE_DIR/unsloth_studio/generation" 2>/dev/null)" = "new" ]; then
+    ok "successful replacement keeps the new environment"
+else
+    bad "successful replacement lost the new environment"
+fi
+if [ ! -d "$PRUNE_DIR/unsloth_studio.rollback.20000101000000.999999999" ]; then
+    ok "successful install removes an orphan from a dead PID"
+else
+    bad "successful install left an orphan from a dead PID"
+fi
+_active_count=$(find "$PRUNE_DIR" -maxdepth 1 -type d -name 'unsloth_studio.rollback.20000101000001.*' | wc -l)
+if [ "$_active_count" -eq 1 ]; then
+    ok "successful install preserves a concurrent installer's rollback"
+else
+    bad "successful install removed a concurrent installer's rollback"
+fi
+if [ -d "$PRUNE_DIR/unsloth_studio.rollback.user-data" ]; then
+    ok "stale cleanup preserves names outside the generated format"
+else
+    bad "stale cleanup removed a non-generated rollback name"
+fi
+if [ -L "$PRUNE_DIR/unsloth_studio.rollback.20000101000002.999999998" ] \
+   && [ -d "$PRUNE_DIR/outside" ]; then
+    ok "stale cleanup does not follow rollback symlinks"
+else
+    bad "stale cleanup mutated a rollback symlink target"
+fi
+
+echo "=== install.ps1 rollback wiring ==="
+if grep -q '^    function Remove-StaleStudioVenvRollbacks {' "$INSTALL_PS1" \
+   && grep -q '^    Remove-StaleStudioVenvRollbacks$' "$INSTALL_PS1"; then
+    ok "Windows installer prunes stale rollbacks after success"
+else
+    bad "Windows installer does not wire stale rollback cleanup"
+fi
+if grep -q '^    } finally {$' "$INSTALL_PS1" \
+   && grep -A3 '^    } finally {$' "$INSTALL_PS1" | grep -q 'Restore-StudioVenvRollback'; then
+    ok "Windows replacement is protected by finally"
+else
+    bad "Windows replacement lacks finally rollback"
+fi
+if grep -A18 '^    function Remove-StudioVenvTreeWithRetry {' "$INSTALL_PS1" \
+   | grep -q 'ErrorAction Stop'; then
+    ok "Windows rollback deletion failures are observable and retried"
+else
+    bad "Windows rollback deletion still hides failures"
+fi
+
+echo ""
+echo "  PASS: $PASS"
+echo "  FAIL: $FAIL"
+[ "$FAIL" -eq 0 ] || exit 1
+echo "ALL PASSED"
diff --git a/tests/sh/test_previous_torch_pin.sh b/tests/sh/test_previous_torch_pin.sh
index 1bc0d1f27f..f910affc2f 100644
--- a/tests/sh/test_previous_torch_pin.sh
+++ b/tests/sh/test_previous_torch_pin.sh
@@ -98,7 +98,7 @@ assert_eq "probe before venv replacement" "yes" "$([ -n "$_probe_line" ] && [ -n
 # The pin must be evaluated AFTER the last index/constraint decision (the Strix
 # reroute raises the floor), so a raised floor rejects an older kept release.
 _pin_line=$(grep -n '_prev_pin=\$(_previous_torch_pin' "$INSTALL_SH" | head -1 | cut -d: -f1)
-_strix_line=$(grep -n 'Strix Halo / Strix Point: force rocm7.2 wheels' "$INSTALL_SH" | head -1 | cut -d: -f1)
+_strix_line=$(grep -n 'Strix Halo / Strix Point:' "$INSTALL_SH" | head -1 | cut -d: -f1)
 assert_eq "pin evaluated after the Strix reroute" "yes" "$([ -n "$_pin_line" ] && [ -n "$_strix_line" ] && [ "$_pin_line" -gt "$_strix_line" ] && echo yes)"
 # A kept release that vanished from the index must fall back to the supported range.
 assert_eq "resolve-failure fallback wired" "yes" "$(grep -q 'TORCH_CONSTRAINT="\$_PREV_FALLBACK_CONSTRAINT"' "$INSTALL_SH" && echo yes)"
diff --git a/tests/sh/test_unsloth_torch_override.sh b/tests/sh/test_unsloth_torch_override.sh
index 7e8e3f5b5b..84e52ca287 100644
--- a/tests/sh/test_unsloth_torch_override.sh
+++ b/tests/sh/test_unsloth_torch_override.sh
@@ -75,11 +75,22 @@ assert_true "overrides temp file is removed after the unsloth installs" "$?"
 grep -q 'for _ov_file in \${UV_OVERRIDE:-}' "$INSTALL_SH"
 assert_true "UV_OVERRIDE env files are merged into the overrides file" "$?"
 
-# 6. The EXIT trap also removes the overrides file, so a failed Step 2 (set -e
-#    fires before the normal-path rm) cannot leak it.
-sed -n '/_on_install_exit() {/,/^}/p' "$INSTALL_SH" \
+# 6. Exit and signal traps share cleanup, so a failed or interrupted Step 2
+#    cannot leak the overrides file.
+sed -n '/_on_install_exit() {/,/^}/p' "$INSTALL_SH" | grep -q '_cleanup_install_temporaries'
+_exit_cleanup_rc=$?
+sed -n '/_on_install_signal() {/,/^}/p' "$INSTALL_SH" | grep -q '_cleanup_install_temporaries'
+_signal_cleanup_rc=$?
+sed -n '/_cleanup_install_temporaries() {/,/^}/p' "$INSTALL_SH" \
     | grep -q 'rm -f "\$_UNSLOTH_TORCH_OVERRIDES"'
-assert_true "EXIT trap removes the overrides temp file on failure" "$?"
+_cleanup_body_rc=$?
+if [ "$_exit_cleanup_rc" -eq 0 ] && [ "$_signal_cleanup_rc" -eq 0 ] \
+   && [ "$_cleanup_body_rc" -eq 0 ]; then
+    _rc=0
+else
+    _rc=1
+fi
+assert_true "exit and signal traps remove the overrides temp file" "$_rc"
 
 # 7. The UV_OVERRIDE fold filters inherited files instead of cat-ing them (run
 #    the extracted awk program on sample files): (a) inherited torch-trio lines
diff --git a/tests/studio/install/test_install_llama_prebuilt_logic.py b/tests/studio/install/test_install_llama_prebuilt_logic.py
index 9a094ddc0e..0964c047d5 100644
--- a/tests/studio/install/test_install_llama_prebuilt_logic.py
+++ b/tests/studio/install/test_install_llama_prebuilt_logic.py
@@ -22,7 +22,6 @@ sys.modules[SPEC.name] = INSTALL_LLAMA_PREBUILT
 SPEC.loader.exec_module(INSTALL_LLAMA_PREBUILT)
 
 PrebuiltFallback = INSTALL_LLAMA_PREBUILT.PrebuiltFallback
-extract_archive = INSTALL_LLAMA_PREBUILT.extract_archive
 binary_env = INSTALL_LLAMA_PREBUILT.binary_env
 is_secret_env_name = INSTALL_LLAMA_PREBUILT.is_secret_env_name
 scrub_env = INSTALL_LLAMA_PREBUILT.scrub_env
@@ -105,105 +104,10 @@ def approved_checksums_for(
     )
 
 
-def test_extract_archive_allows_safe_tar_symlink_chain(tmp_path: Path):
-    archive_path = tmp_path / "bundle.tar.gz"
-    payload = b"shared-object"
-
-    with tarfile.open(archive_path, "w:gz") as archive:
-        versioned = tarfile.TarInfo("libllama.so.0.0.1")
-        versioned.size = len(payload)
-        archive.addfile(versioned, io_bytes(payload))
-
-        soname = tarfile.TarInfo("libllama.so.0")
-        soname.type = tarfile.SYMTYPE
-        soname.linkname = "libllama.so.0.0.1"
-        archive.addfile(soname)
-
-        linker_name = tarfile.TarInfo("libllama.so")
-        linker_name.type = tarfile.SYMTYPE
-        linker_name.linkname = "libllama.so.0"
-        archive.addfile(linker_name)
-
-    destination = tmp_path / "extract"
-    extract_archive(archive_path, destination)
-
-    assert (destination / "libllama.so.0.0.1").read_bytes() == payload
-    assert (destination / "libllama.so.0").is_symlink()
-    assert (destination / "libllama.so").is_symlink()
-    assert (destination / "libllama.so").resolve().read_bytes() == payload
-
-
-def test_extract_archive_allows_safe_tar_hardlink(tmp_path: Path):
-    archive_path = tmp_path / "bundle.tar.gz"
-    payload = b"quantize"
-
-    with tarfile.open(archive_path, "w:gz") as archive:
-        target = tarfile.TarInfo("llama-quantize")
-        target.size = len(payload)
-        archive.addfile(target, io_bytes(payload))
-
-        hardlink = tarfile.TarInfo("llama-quantize-copy")
-        hardlink.type = tarfile.LNKTYPE
-        hardlink.linkname = "llama-quantize"
-        archive.addfile(hardlink)
-
-    destination = tmp_path / "extract"
-    extract_archive(archive_path, destination)
-
-    assert (destination / "llama-quantize-copy").read_bytes() == payload
-    assert not (destination / "llama-quantize-copy").is_symlink()
-
-
-def test_extract_archive_rejects_absolute_tar_symlink_target(tmp_path: Path):
-    archive_path = tmp_path / "bundle.tar.gz"
-
-    with tarfile.open(archive_path, "w:gz") as archive:
-        entry = tarfile.TarInfo("libllama.so")
-        entry.type = tarfile.SYMTYPE
-        entry.linkname = "/tmp/libllama.so.0"
-        archive.addfile(entry)
-
-    with pytest.raises(PrebuiltFallback, match = "archive link used an absolute target"):
-        extract_archive(archive_path, tmp_path / "extract")
-
-
-def test_extract_archive_rejects_escaping_tar_symlink_target(tmp_path: Path):
-    archive_path = tmp_path / "bundle.tar.gz"
-
-    with tarfile.open(archive_path, "w:gz") as archive:
-        entry = tarfile.TarInfo("libllama.so")
-        entry.type = tarfile.SYMTYPE
-        entry.linkname = "../outside/libllama.so.0"
-        archive.addfile(entry)
-
-    with pytest.raises(PrebuiltFallback, match = "archive link escaped destination"):
-        extract_archive(archive_path, tmp_path / "extract")
-
-
-def test_extract_archive_rejects_unresolved_tar_symlink_target(tmp_path: Path):
-    archive_path = tmp_path / "bundle.tar.gz"
-
-    with tarfile.open(archive_path, "w:gz") as archive:
-        entry = tarfile.TarInfo("libllama.so")
-        entry.type = tarfile.SYMTYPE
-        entry.linkname = "libllama.so.0"
-        archive.addfile(entry)
-
-    with pytest.raises(PrebuiltFallback, match = "unresolved link entries"):
-        extract_archive(archive_path, tmp_path / "extract")
-
-
-def test_extract_archive_rejects_zip_symlink_entry(tmp_path: Path):
-    archive_path = tmp_path / "bundle.zip"
-
-    with zipfile.ZipFile(archive_path, "w") as archive:
-        info = zipfile.ZipInfo("libllama.so")
-        info.create_system = 3
-        info.external_attr = 0o120777 << 16
-        archive.writestr(info, "libllama.so.0")
-
-    with pytest.raises(PrebuiltFallback, match = "zip archive contained a symlink entry"):
-        extract_archive(archive_path, tmp_path / "extract")
+# The extract_archive guard tests (safe symlink chain / hardlink, absolute or
+# escaping or unresolved symlink targets, zip symlink entries) moved verbatim
+# to tests/studio/install/test_prebuilt_core.py: extract_archive is the shared
+# prebuilt_core implementation, re-exported by this installer.
 
 
 def test_remove_agent_instruction_files_does_not_follow_links(tmp_path: Path):
diff --git a/tests/studio/install/test_install_whisper_prebuilt_logic.py b/tests/studio/install/test_install_whisper_prebuilt_logic.py
new file mode 100644
index 0000000000..7364ea454d
--- /dev/null
+++ b/tests/studio/install/test_install_whisper_prebuilt_logic.py
@@ -0,0 +1,1357 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Logic tests for studio/install_whisper_prebuilt.py -- the prebuilt whisper-server installer.
+# No network/GPU: release resolution is injected and archives are built on disk in a tmp dir.
+
+import importlib.util
+import io
+import json
+import sys
+import tarfile
+import zipfile
+from pathlib import Path
+
+import pytest
+
+
+PACKAGE_ROOT = Path(__file__).resolve().parents[3]
+MODULE_PATH = PACKAGE_ROOT / "studio" / "install_whisper_prebuilt.py"
+# The installer imports install_llama_prebuilt (same directory); make studio/
+# importable so that resolves under spec-based loading.
+_STUDIO_DIR = str(MODULE_PATH.parent)
+if _STUDIO_DIR not in sys.path:
+    sys.path.insert(0, _STUDIO_DIR)
+SPEC = importlib.util.spec_from_file_location("studio_install_whisper_prebuilt", MODULE_PATH)
+assert SPEC is not None and SPEC.loader is not None
+M = importlib.util.module_from_spec(SPEC)
+sys.modules[SPEC.name] = M
+SPEC.loader.exec_module(M)
+
+HostInfo = M.HostInfo
+PrebuiltFallback = M.PrebuiltFallback
+ReleaseCompatibilityError = M.ReleaseCompatibilityError
+BusyInstallConflict = M.BusyInstallConflict
+
+RELEASE_TAG = "v1.9.1-unsloth.1"
+UPSTREAM_TAG = "v1.9.1"
+SOURCE_COMMIT = "0" * 40
+STUDIO_PROTOCOL = "inference/multipart-v1"
+
+
+def _host(
+    whisper_os: str,
+    whisper_arch: str,
+    *,
+    has_usable_nvidia: bool = False,
+    has_rocm: bool = False,
+    rocm_gfx: str | None = None,
+    macos_version: tuple[int, int] | None = None,
+) -> HostInfo:
+    ext = ".zip" if whisper_os == "windows" else ".tar.gz"
+    return HostInfo(
+        system = {"linux": "Linux", "macos": "Darwin", "windows": "Windows"}[whisper_os],
+        machine = whisper_arch,
+        whisper_os = whisper_os,
+        whisper_arch = whisper_arch,
+        archive_ext = ext,
+        is_windows = whisper_os == "windows",
+        is_macos = whisper_os == "macos",
+        is_apple_silicon = whisper_os == "macos" and whisper_arch == "arm64",
+        has_usable_nvidia = has_usable_nvidia,
+        has_rocm = has_rocm,
+        rocm_gfx = rocm_gfx,
+        macos_version = macos_version,
+    )
+
+
+def _artifact(os_: str, arch: str, backend: str, asset: str, sha256: str, **extra) -> dict:
+    art = {
+        "os": os_,
+        "arch": arch,
+        "backend": backend,
+        "asset": asset,
+        "sha256": sha256,
+        "runtime_line": extra.get("runtime_line"),
+    }
+    art.update(extra)
+    return art
+
+
+def _manifest(
+    artifacts: list[dict],
+    *,
+    component: str = "whisper.cpp",
+    schema_version: int = 1,
+) -> dict:
+    return {
+        "schema_version": schema_version,
+        "component": component,
+        "studio_protocol": STUDIO_PROTOCOL,
+        "upstream_tag": UPSTREAM_TAG,
+        "source_commit": SOURCE_COMMIT,
+        "artifacts": artifacts,
+    }
+
+
+# ── Host detection (probes come from install_llama_prebuilt.detect_host) ──
+def _llama_host(
+    system: str,
+    machine: str,
+    *,
+    has_usable_nvidia: bool = False,
+    compute_caps: list[str] | None = None,
+    driver_cuda_version: tuple[int, int] | None = None,
+    has_rocm: bool = False,
+    rocm_gfx: str | None = None,
+    macos_version: tuple[int, int] | None = None,
+):
+    """A fake install_llama_prebuilt HostInfo, as llama_detect_host would return."""
+    lowered = machine.lower()
+    return M.llama.HostInfo(
+        system = system,
+        machine = machine,
+        is_windows = system == "Windows",
+        is_linux = system == "Linux",
+        is_macos = system == "Darwin",
+        is_x86_64 = lowered in {"x86_64", "amd64"},
+        is_arm64 = lowered in {"arm64", "aarch64"},
+        nvidia_smi = None,
+        driver_cuda_version = driver_cuda_version,
+        compute_caps = list(compute_caps or []),
+        visible_cuda_devices = None,
+        has_physical_nvidia = has_usable_nvidia,
+        has_usable_nvidia = has_usable_nvidia,
+        has_rocm = has_rocm,
+        rocm_gfx_target = rocm_gfx,
+        macos_version = macos_version,
+    )
+
+
+@pytest.mark.parametrize(
+    "system,machine,exp_os,exp_arch,exp_ext",
+    [
+        ("Linux", "x86_64", "linux", "x64", ".tar.gz"),
+        ("Linux", "aarch64", "linux", "arm64", ".tar.gz"),
+        ("Darwin", "x86_64", "macos", "x64", ".tar.gz"),
+        ("Darwin", "arm64", "macos", "arm64", ".tar.gz"),
+        ("Windows", "AMD64", "windows", "x64", ".zip"),
+        ("Windows", "ARM64", "windows", "arm64", ".zip"),
+    ],
+)
+def test_detect_host(monkeypatch, system, machine, exp_os, exp_arch, exp_ext):
+    monkeypatch.setattr(M, "llama_detect_host", lambda: _llama_host(system, machine))
+    host = M.detect_host()
+    assert (host.whisper_os, host.whisper_arch, host.archive_ext) == (exp_os, exp_arch, exp_ext)
+    assert host.is_windows == (exp_os == "windows")
+    assert host.is_apple_silicon == (exp_os == "macos" and exp_arch == "arm64")
+
+
+def test_detect_host_maps_rocm_fields(monkeypatch):
+    monkeypatch.setattr(
+        M,
+        "llama_detect_host",
+        lambda: _llama_host("Linux", "x86_64", has_rocm = True, rocm_gfx = "gfx1100"),
+    )
+    host = M.detect_host()
+    assert host.has_rocm is True
+    assert host.rocm_gfx == "gfx1100"
+    assert host.has_usable_nvidia is False
+
+
+@pytest.mark.parametrize(
+    "system,machine",
+    [("Plan9", "x86_64"), ("Linux", "sparc64"), ("Linux", "armv7l")],
+)
+def test_detect_host_unsupported(monkeypatch, system, machine):
+    monkeypatch.setattr(M, "llama_detect_host", lambda: _llama_host(system, machine))
+    with pytest.raises(PrebuiltFallback):
+        M.detect_host()
+
+
+# ── Asset naming (pure) ──
+def test_whisper_asset_name():
+    assert (
+        M.whisper_asset_name(RELEASE_TAG, _host("linux", "x64"), "cpu")
+        == "whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz"
+    )
+    assert (
+        M.whisper_asset_name(RELEASE_TAG, _host("macos", "arm64"), "metal")
+        == "whisper-v1.9.1-unsloth.1-macos-arm64-metal.tar.gz"
+    )
+    assert (
+        M.whisper_asset_name(RELEASE_TAG, _host("windows", "x64"), "cuda12")
+        == "whisper-v1.9.1-unsloth.1-windows-x64-cuda12.zip"
+    )
+
+
+# ── Install layout ──
+def test_whisper_server_path_layout():
+    nix = _host("linux", "x64")
+    win = _host("windows", "x64")
+    assert M.whisper_server_path(Path("/w"), nix) == Path("/w/build/bin/whisper-server")
+    assert M.whisper_server_path(Path("/w"), win) == Path("/w/build/bin/Release/whisper-server.exe")
+
+
+# ── Manifest parse + basic selection (wiring pin; the rejection matrix,
+# extraction guards, resolver payload shape and macOS min_os gating are
+# asserted against the real whisper descriptor in
+# tests/studio/install/test_prebuilt_core.py) ──
+def test_parse_manifest_ok_and_basic_selection():
+    cpu_asset = "whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz"
+    manifest = M.parse_manifest(_manifest([_artifact("linux", "x64", "cpu", cpu_asset, "a" * 64)]))
+    assert manifest["component"] == "whisper.cpp"
+    assert manifest["studio_protocol"] == STUDIO_PROTOCOL
+    host = _host("linux", "x64")
+    # The pinned pre-slim escape hatch: only the fat CPU bundle ever matches.
+    assert M.select_artifact(manifest, host, "cpu")["asset"] == cpu_asset
+    assert M.select_artifact(manifest, host, "metal") is None
+
+
+def test_select_artifact_never_picks_fat_gpu_bundles():
+    # A pinned pre-slim release's fat GPU bundles are dead shapes: a cuda/rocm
+    # backend selects nothing (the core then retries with cpu), never the fat
+    # per-accelerator artifact.
+    manifest = M.parse_manifest(
+        _manifest(
+            [
+                _artifact("linux", "x64", "cpu", "whisper-linux-x64-cpu.tar.gz", "a" * 64),
+                _artifact("linux", "x64", "cuda", "whisper-linux-x64-cuda13.tar.gz", "b" * 64),
+                _artifact("linux", "x64", "rocm", "whisper-linux-x64-rocm.tar.gz", "c" * 64),
+            ]
+        )
+    )
+    cuda_host = _host("linux", "x64", has_usable_nvidia = True)
+    assert M.select_artifact(manifest, cuda_host, "cuda") is None
+    rocm_host = _host("linux", "x64", has_rocm = True, rocm_gfx = "gfx1100")
+    assert M.select_artifact(manifest, rocm_host, "rocm") is None
+    artifact, backend, used_fallback = M.select_artifact_with_fallback(manifest, cuda_host, "cuda")
+    assert artifact["asset"] == "whisper-linux-x64-cpu.tar.gz"
+    assert backend == "cpu" and used_fallback is True
+
+
+# ── Traversal-safe extraction ──
+def _add_file(
+    tar: tarfile.TarFile,
+    name: str,
+    data: bytes,
+    mode: int = 0o644,
+):
+    info = tarfile.TarInfo(name)
+    info.size = len(data)
+    info.mode = mode
+    tar.addfile(info, io.BytesIO(data))
+
+
+# ── Fixture archive + full staging/activate install ──
+def _build_cpu_bundle(tmp_path: Path, host: HostInfo) -> tuple[Path, str, str]:
+    """Build a fake CPU bundle archive with a dummy server + lib; return (path, name, sha256)."""
+    asset = M.whisper_asset_name(RELEASE_TAG, host, "cpu")
+    archive = tmp_path / asset
+    server_name = M.server_binary_name(host)
+    with tarfile.open(archive, "w:gz") as tar:
+        _add_file(tar, server_name, b"#!/bin/sh\necho whisper\n", mode = 0o755)
+        _add_file(tar, "libwhisper.so", b"dummy-libwhisper")
+        _add_file(tar, "libggml-base.so", b"dummy-libggml")
+    return archive, asset, M.sha256_file(archive)
+
+
+def _install_env(
+    monkeypatch,
+    tmp_path,
+    host,
+    *,
+    asset,
+    sha256,
+    backend_in_manifest = "cpu",
+):
+    """Wire monkeypatches so install_prebuilt runs fully offline against a local
+    archive, injecting the release bundle + checksum index (the checksum trust
+    model) via the single fetch_release_for_install seam."""
+    manifest = M.parse_manifest(
+        _manifest(
+            [_artifact(host.whisper_os, host.whisper_arch, backend_in_manifest, asset, sha256)]
+        )
+    )
+    bundle = M.ReleaseBundle(
+        repo = "unslothai/whisper.cpp",
+        release_tag = RELEASE_TAG,
+        manifest = manifest,
+        asset_urls = {asset: f"https://example.invalid/{asset}"},
+    )
+    checksums = {asset: sha256}
+    monkeypatch.setattr(
+        M,
+        "fetch_release_for_install",
+        lambda repo, *, published_release_tag = None: (bundle, checksums),
+    )
+    return bundle
+
+
+def test_install_produces_colocated_layout_and_marker(tmp_path, monkeypatch):
+    host = _host("linux", "x64")
+    archive, asset, sha256 = _build_cpu_bundle(tmp_path, host)
+
+    def fake_download(url, destination):
+        destination.parent.mkdir(parents = True, exist_ok = True)
+        destination.write_bytes(archive.read_bytes())
+
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(M, "download_file", fake_download)
+    _install_env(monkeypatch, tmp_path, host, asset = asset, sha256 = sha256)
+
+    install_dir = tmp_path / "whisper.cpp"
+    rc = M.install_prebuilt(install_dir, backend = "cpu")
+    assert rc == M.EXIT_SUCCESS
+
+    server = install_dir / "build" / "bin" / "whisper-server"
+    assert server.is_file()
+    assert server.stat().st_mode & 0o111  # +x set on unix
+    # every shared lib from the archive is co-located next to the server
+    assert (install_dir / "build" / "bin" / "libwhisper.so").is_file()
+    assert (install_dir / "build" / "bin" / "libggml-base.so").is_file()
+    # marker written at the component root
+    marker = json.loads((install_dir / M.METADATA_FILENAME).read_text())
+    assert marker["component"] == "whisper.cpp"
+    assert marker["release_tag"] == RELEASE_TAG
+    assert marker["backend"] == "cpu"
+    assert marker["studio_protocol"] == STUDIO_PROTOCOL
+    assert marker["install_fingerprint"]
+
+
+def test_install_is_idempotent(tmp_path, monkeypatch):
+    host = _host("linux", "x64")
+    archive, asset, sha256 = _build_cpu_bundle(tmp_path, host)
+
+    calls = {"n": 0}
+
+    def fake_download(url, destination):
+        calls["n"] += 1
+        destination.parent.mkdir(parents = True, exist_ok = True)
+        destination.write_bytes(archive.read_bytes())
+
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(M, "download_file", fake_download)
+    _install_env(monkeypatch, tmp_path, host, asset = asset, sha256 = sha256)
+
+    install_dir = tmp_path / "whisper.cpp"
+    assert M.install_prebuilt(install_dir, backend = "cpu") == M.EXIT_SUCCESS
+    assert calls["n"] == 1
+    # Second run: marker + binary already match -> "already matches", no download.
+    assert M.install_prebuilt(install_dir, backend = "cpu") == M.EXIT_SUCCESS
+    assert calls["n"] == 1
+
+
+def test_install_sha_mismatch_then_retry_fails_closed(tmp_path, monkeypatch):
+    host = _host("linux", "x64")
+    archive, asset, _real_sha = _build_cpu_bundle(tmp_path, host)
+    wrong_sha = "f" * 64  # the checksum index claims a different sha than the archive
+
+    def fake_download(url, destination):
+        destination.parent.mkdir(parents = True, exist_ok = True)
+        destination.write_bytes(archive.read_bytes())
+
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(M, "download_file", fake_download)
+    _install_env(monkeypatch, tmp_path, host, asset = asset, sha256 = wrong_sha)
+
+    install_dir = tmp_path / "whisper.cpp"
+    with pytest.raises(PrebuiltFallback):
+        M.install_prebuilt(install_dir, backend = "cpu")
+    # A failed verify never activates a binary.
+    assert not (install_dir / "build" / "bin" / "whisper-server").exists()
+
+
+# ── Busy lock -> exit 3 ──
+def test_busy_lock_maps_to_exit_busy(tmp_path, monkeypatch):
+    host = _host("linux", "x64")
+    archive, asset, sha256 = _build_cpu_bundle(tmp_path, host)
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(M, "download_file", lambda u, d: None)
+    _install_env(monkeypatch, tmp_path, host, asset = asset, sha256 = sha256)
+
+    from contextlib import contextmanager
+
+    @contextmanager
+    def busy_lock(_path):
+        raise BusyInstallConflict("held by another process")
+        yield  # pragma: no cover
+
+    monkeypatch.setattr(M, "install_lock", busy_lock)
+    rc = M.main(["--install-dir", str(tmp_path / "whisper.cpp"), "--backend", "cpu"])
+    assert rc == M.EXIT_BUSY
+
+
+# ── Resolver JSON shape ──
+def test_resolve_mode_keeps_stdout_json_only(tmp_path, monkeypatch, capsys):
+    # Even when the slim pairing emits diagnostics, --resolve-prebuilt must keep
+    # stdout to exactly the JSON line (setup.sh / whisper_cpp_update.py parse
+    # it); the slim_selection log noise belongs on stderr.
+    host = _cuda_host()
+    bin_dir = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer")
+    )
+    manifest = _slim_manifest()
+    bundle = M.ReleaseBundle(
+        repo = "unslothai/whisper.cpp",
+        release_tag = RELEASE_TAG,
+        manifest = manifest,
+        asset_urls = {
+            a["asset"]: f"https://example.invalid/{a['asset']}" for a in manifest["artifacts"]
+        },
+    )
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(
+        M, "fetch_release_for_install", lambda repo, *, published_release_tag = None: (bundle, {})
+    )
+    # A prior install test may have left the module flag True; the resolver must
+    # force it back to stderr regardless.
+    monkeypatch.setattr(M, "_LOG_TO_STDOUT", True, raising = False)
+
+    rc = M.main(["--resolve-prebuilt", "--output-format", "json"])
+    assert rc == M.EXIT_SUCCESS
+    captured = capsys.readouterr()
+    payload = json.loads(captured.out.strip())  # exactly one JSON line, parseable
+    assert payload["asset"] == SLIM_ASSET
+    assert "[whisper-prebuilt]" not in captured.out  # no log noise on stdout
+    assert "slim_selection:" in captured.err  # diagnostics routed to stderr
+
+
+def test_main_maps_prebuilt_fallback_to_exit_error(tmp_path, monkeypatch):
+    def boom(*a, **kw):
+        raise PrebuiltFallback("no prebuilt")
+
+    monkeypatch.setattr(M, "install_prebuilt", boom)
+    rc = M.main(["--install-dir", str(tmp_path / "whisper.cpp"), "--backend", "cpu"])
+    assert rc == M.EXIT_ERROR
+
+
+def test_main_forwards_requested_whisper_tags(tmp_path, monkeypatch):
+    seen = {}
+
+    def install(*args, **kwargs):
+        seen.update(kwargs)
+        return M.EXIT_SUCCESS
+
+    monkeypatch.setattr(M, "install_prebuilt", install)
+    rc = M.main(["--install-dir", str(tmp_path / "whisper.cpp"), "--whisper-tag", "v1.9.0"])
+    assert rc == M.EXIT_SUCCESS
+    assert seen["whisper_tag"] == "v1.9.0"
+
+    monkeypatch.setattr(M, "detect_host", lambda: _host("linux", "x64"))
+    monkeypatch.setattr(
+        M,
+        "resolve_prebuilt",
+        lambda host, **kwargs: seen.update(kwargs)
+        or {"prebuilt_available": False, "repo": "unslothai/whisper.cpp"},
+    )
+    assert M.main(["--resolve-prebuilt", "v1.8.0", "--output-format", "json"]) == 0
+    assert seen["whisper_tag"] == "v1.8.0"
+
+
+def test_main_reserves_exit_2_for_release_incompatibility(tmp_path, monkeypatch):
+    def boom(*a, **kw):
+        raise ReleaseCompatibilityError("slim bundle requires llama.cpp b2; installed b1")
+
+    monkeypatch.setattr(M, "install_prebuilt", boom)
+    rc = M.main(["--install-dir", str(tmp_path / "whisper.cpp"), "--backend", "cpu"])
+    assert rc == M.EXIT_INCOMPATIBLE
+
+
+def test_main_maps_unexpected_error_to_exit_error(tmp_path, monkeypatch):
+    def boom(*a, **kw):
+        raise RuntimeError("kaboom")
+
+    monkeypatch.setattr(M, "install_prebuilt", boom)
+    rc = M.main(["--install-dir", str(tmp_path / "whisper.cpp"), "--backend", "cpu"])
+    assert rc == M.EXIT_ERROR
+
+
+def test_resolve_mode_unexpected_error_reports_unavailable(monkeypatch, capsys):
+    # An unexpected failure inside the probe maps to prebuilt_available=False, not
+    # a traceback, so the caller falls back cleanly.
+    host = _host("linux", "x64")
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+
+    def boom(repo, *, published_release_tag = None):
+        raise RuntimeError("network down")
+
+    monkeypatch.setattr(M, "fetch_release_for_install", boom)
+    rc = M.main(["--resolve-prebuilt", "--output-format", "json"])
+    assert rc == M.EXIT_SUCCESS
+    payload = json.loads(capsys.readouterr().out.strip())
+    assert payload == {"prebuilt_available": False, "repo": "unslothai/whisper.cpp"}
+
+
+# ── --rocm-gfx / --has-rocm overrides (llama parity) ──
+def test_rocm_gfx_override_implies_has_rocm():
+    # --rocm-gfx alone (no --has-rocm) must enable ROCm and clear NVIDIA, else the
+    # host stays on its CUDA/CPU path and never picks the ROCm bundle.
+    base = _host("linux", "x64", has_usable_nvidia = True)
+    out = M.apply_host_overrides(base, rocm_gfx = "gfx1100")
+    assert out.has_rocm is True
+    assert out.rocm_gfx == "gfx1100"
+    assert out.has_usable_nvidia is False
+    assert M.auto_detect_backend(out) == "rocm"
+
+
+# ── Slim bundles paired with the installed llama.cpp ggml runtime ──
+SLIM_LLAMA_TAG = "b10069-mix-fb3d4ca"
+SLIM_ASSET = "whisper-v1.9.1-unsloth.1-linux-x64-slim.tar.gz"
+CPU_ASSET = "whisper-v1.9.1-unsloth.1-linux-x64-cpu.tar.gz"
+
+
+def _fake_llama_bin(
+    tmp_path: Path,
+    *,
+    backend_module: str | None = "libggml-cuda.so",
+    sonames: tuple[str, ...] = ("libggml.so.0", "libggml-base.so.0"),
+) -> Path:
+    bin_dir = tmp_path / "llama.cpp" / "build" / "bin"
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    for name in sonames:
+        (bin_dir / name).write_bytes(b"ggml-old-" + name.encode())
+    if backend_module:
+        (bin_dir / backend_module).write_bytes(b"ggml-backend-old")
+    (bin_dir / "libggml-cpu-x64.so").write_bytes(b"ggml-cpu-old")
+    (bin_dir / "libllama.so").write_bytes(b"not-ggml")  # must never be linked
+    return bin_dir
+
+
+def _slim_artifact(**extra) -> dict:
+    art = {
+        "os": "linux",
+        "arch": "x64",
+        "backend": "slim",
+        "asset": SLIM_ASSET,
+        "sha256": "c" * 64,
+        "install_kind": "slim",
+        "requires_llama_tag": SLIM_LLAMA_TAG,
+        "requires_ggml_version": "0.17.0",
+        "requires_ggml_sonames": ["libggml.so.0", "libggml-base.so.0"],
+        "min_os": None,
+    }
+    art.update(extra)
+    return art
+
+
+def _slim_manifest(slim_extra: dict | None = None) -> dict:
+    """The transition-release shape: a slim bundle beside the published fat CPU
+    bundle (the pinned pre-slim escape hatch)."""
+    artifacts = [
+        _artifact("linux", "x64", "cpu", CPU_ASSET, "a" * 64),
+        _slim_artifact(**(slim_extra or {})),
+    ]
+    return M.parse_manifest(_manifest(artifacts))
+
+
+def _cuda_host() -> HostInfo:
+    return _host("linux", "x64", has_usable_nvidia = True)
+
+
+def test_installed_llama_runtime_reads_marker(tmp_path):
+    root = tmp_path / "llama.cpp"
+    bin_dir = root / "build" / "bin"
+    bin_dir.mkdir(parents = True)
+    (root / "UNSLOTH_PREBUILT_INFO.json").write_text(
+        json.dumps({"release_tag": SLIM_LLAMA_TAG, "bundle_profile": "cuda13-newer"})
+    )
+    assert M.llama.installed_llama_runtime(root) == (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer")
+
+
+@pytest.mark.parametrize(
+    "prepare",
+    [
+        lambda root: None,  # no marker at all
+        lambda root: (root / "UNSLOTH_PREBUILT_INFO.json").write_text("{}"),  # no release_tag
+        lambda root: (root / "UNSLOTH_PREBUILT_INFO.json").write_text("not json"),
+    ],
+)
+def test_installed_llama_runtime_rejects_incomplete_installs(tmp_path, prepare):
+    root = tmp_path / "llama.cpp"
+    (root / "build" / "bin").mkdir(parents = True)
+    prepare(root)
+    assert M.llama.installed_llama_runtime(root) is None
+
+
+def test_installed_llama_runtime_requires_bin_dir(tmp_path):
+    root = tmp_path / "llama.cpp"
+    root.mkdir()
+    (root / "UNSLOTH_PREBUILT_INFO.json").write_text(json.dumps({"release_tag": SLIM_LLAMA_TAG}))
+    assert M.llama.installed_llama_runtime(root) is None  # marker but no build/bin
+
+
+def test_slim_selected_when_all_pairing_checks_pass(tmp_path, monkeypatch):
+    bin_dir = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer")
+    )
+    artifact, backend, used_fallback = M.select_artifact_with_fallback(
+        _slim_manifest(), _cuda_host(), "cuda"
+    )
+    assert artifact["asset"] == SLIM_ASSET
+    assert backend == "cuda" and used_fallback is False
+
+
+@pytest.mark.parametrize(
+    "runtime,slim_extra",
+    [
+        # No llama install at all.
+        (lambda bin_dir: None, None),
+        # Installed llama tag does not match requires_llama_tag.
+        (lambda bin_dir: (bin_dir, "b99999-mix-0000000", "cuda13-newer"), None),
+        # A required soname is missing from the llama bin dir.
+        (
+            lambda bin_dir: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer"),
+            {"requires_ggml_sonames": ["libggml.so.0", "libggml-base.so.0", "libggml-extra.so.9"]},
+        ),
+        # Manifest omits the soname contract entirely.
+        (lambda bin_dir: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer"), {"requires_ggml_sonames": []}),
+    ],
+)
+def test_slim_pairing_failure_falls_back_to_pinned_cpu(tmp_path, monkeypatch, runtime, slim_extra):
+    # With the fat per-accelerator chain gone, a failed pairing degrades to the
+    # one legacy shape: the release's published fat CPU bundle.
+    bin_dir = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(M, "installed_llama_runtime", lambda: runtime(bin_dir))
+    artifact, backend, used_fallback = M.select_artifact_with_fallback(
+        _slim_manifest(slim_extra), _cuda_host(), "cuda"
+    )
+    assert artifact["asset"] == CPU_ASSET
+    assert backend == "cpu" and used_fallback is True
+
+
+def test_slim_missing_accel_module_rides_the_cpu_module(tmp_path, monkeypatch):
+    # Sonames present but no libggml-cuda.so in the llama bin dir: the cuda
+    # pairing fails, and the cpu retry still serves the same slim bundle via
+    # the llama cpu modules.
+    bin_dir = _fake_llama_bin(tmp_path, backend_module = None)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer")
+    )
+    artifact, backend, used_fallback = M.select_artifact_with_fallback(
+        _slim_manifest(), _cuda_host(), "cuda"
+    )
+    assert artifact["asset"] == SLIM_ASSET
+    assert backend == "cpu" and used_fallback is True
+
+
+def test_slim_selected_for_cpu_backend_on_linux(tmp_path, monkeypatch):
+    # Slim-only releases must serve cpu too: with the llama cpu modules present
+    # the cpu backend rides the same slim bundle as the GPUs.
+    bin_dir = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer")
+    )
+    artifact, backend, _fb = M.select_artifact_with_fallback(
+        _slim_manifest(), _host("linux", "x64"), "cpu"
+    )
+    assert artifact["asset"] == SLIM_ASSET and backend == "cpu"
+
+
+def test_slim_cpu_requires_a_cpu_module(tmp_path, monkeypatch):
+    # Sonames present but no libggml-cpu* variant in the llama bin dir -> fat cpu.
+    bin_dir = tmp_path / "llama.cpp" / "build" / "bin"
+    bin_dir.mkdir(parents = True)
+    for name in ("libggml.so.0", "libggml-base.so.0"):
+        (bin_dir / name).write_bytes(b"ggml")
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "linux-cpu")
+    )
+    artifact, backend, _fb = M.select_artifact_with_fallback(
+        _slim_manifest(), _host("linux", "x64"), "cpu"
+    )
+    assert artifact["asset"] == CPU_ASSET and backend == "cpu"
+
+
+WIN_SLIM_ASSET = "whisper-v1.9.1-unsloth.1-windows-x64-slim.zip"
+
+
+def test_slim_selected_for_cpu_backend_on_windows(tmp_path, monkeypatch):
+    bin_dir = tmp_path / "llama.cpp" / "build" / "bin" / "Release"
+    bin_dir.mkdir(parents = True)
+    for name in ("ggml.dll", "ggml-base.dll", "ggml-cpu-haswell.dll"):
+        (bin_dir / name).write_bytes(b"ggml")
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "windows-cpu")
+    )
+    manifest = M.parse_manifest(
+        _manifest(
+            [
+                _slim_artifact(
+                    os = "windows",
+                    arch = "x64",
+                    asset = WIN_SLIM_ASSET,
+                    requires_ggml_sonames = ["ggml.dll", "ggml-base.dll"],
+                )
+            ]
+        )
+    )
+    artifact, backend, _fb = M.select_artifact_with_fallback(
+        manifest, _host("windows", "x64"), "cpu"
+    )
+    assert artifact["asset"] == WIN_SLIM_ASSET and backend == "cpu"
+
+
+MAC_SLIM_ASSET = "whisper-v1.9.1-unsloth.1-macos-arm64-slim.tar.gz"
+
+
+def _fake_llama_bin_macos(tmp_path: Path) -> Path:
+    """The dylib names the live llama macos bundle ships (core + cpu + metal)."""
+    bin_dir = tmp_path / "llama.cpp" / "build" / "bin"
+    bin_dir.mkdir(parents = True, exist_ok = True)
+    for name in (
+        "libggml.dylib",
+        "libggml-base.dylib",
+        "libggml-cpu.dylib",
+        "libggml-metal.dylib",
+        "libggml-blas.dylib",
+    ):
+        (bin_dir / name).write_bytes(b"ggml-" + name.encode())
+    (bin_dir / "libllama.dylib").write_bytes(b"not-ggml")
+    return bin_dir
+
+
+def _macos_slim_manifest(arch: str = "arm64") -> dict:
+    return M.parse_manifest(
+        _manifest(
+            [
+                _slim_artifact(
+                    os = "macos",
+                    arch = arch,
+                    asset = MAC_SLIM_ASSET,
+                    requires_ggml_sonames = ["libggml.dylib", "libggml-base.dylib"],
+                )
+            ]
+        )
+    )
+
+
+@pytest.mark.parametrize("backend", ["metal", "cpu"])
+def test_slim_selected_for_metal_and_cpu_on_macos(tmp_path, monkeypatch, backend):
+    bin_dir = _fake_llama_bin_macos(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "macos-metal-arm64")
+    )
+    host = _host("macos", "arm64", macos_version = (14, 0))
+    artifact, effective, _fb = M.select_artifact_with_fallback(
+        _macos_slim_manifest(), host, backend
+    )
+    assert artifact["asset"] == MAC_SLIM_ASSET
+    assert effective == backend  # the accel identity, never "slim"
+
+
+def test_macos_auto_backends_route_to_slim(tmp_path, monkeypatch):
+    # auto -> metal on Apple Silicon, cpu on Intel macs; both must pick slim.
+    bin_dir = _fake_llama_bin_macos(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "macos-metal-arm64")
+    )
+    silicon = _host("macos", "arm64", macos_version = (14, 0))
+    assert M.resolve_backend(silicon, "auto", cpu_fallback = False) == "metal"
+    artifact, backend, _fb = M.select_artifact_with_fallback(
+        _macos_slim_manifest(), silicon, "metal"
+    )
+    assert artifact["asset"] == MAC_SLIM_ASSET and backend == "metal"
+
+    intel = _host("macos", "x64", macos_version = (14, 0))
+    assert M.resolve_backend(intel, "auto", cpu_fallback = False) == "cpu"
+    artifact, backend, _fb = M.select_artifact_with_fallback(
+        _macos_slim_manifest(arch = "x64"), intel, "cpu"
+    )
+    assert artifact["asset"] == MAC_SLIM_ASSET and backend == "cpu"
+
+
+def test_slim_metal_requires_the_metal_module(tmp_path, monkeypatch):
+    # A macos llama runtime without libggml-metal*.dylib cannot back metal; the
+    # cpu fallback still rides the same slim bundle via the cpu module.
+    bin_dir = tmp_path / "llama.cpp" / "build" / "bin"
+    bin_dir.mkdir(parents = True)
+    for name in ("libggml.dylib", "libggml-base.dylib", "libggml-cpu.dylib"):
+        (bin_dir / name).write_bytes(b"ggml")
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "macos-cpu-x64")
+    )
+    host = _host("macos", "arm64", macos_version = (14, 0))
+    artifact, backend, used_fallback = M.select_artifact_with_fallback(
+        _macos_slim_manifest(), host, "metal"
+    )
+    assert artifact["asset"] == MAC_SLIM_ASSET
+    assert backend == "cpu" and used_fallback is True
+
+
+def test_slim_only_release_pairing_failure_is_actionable(tmp_path, monkeypatch):
+    # A slim-only release with no llama install is an operational failure, not
+    # the narrowly handled installed-version skew.
+    lines: list[str] = []
+    monkeypatch.setattr(M, "log", lines.append)
+    monkeypatch.setattr(M, "installed_llama_runtime", lambda: None)
+    manifest = M.parse_manifest(_manifest([_slim_artifact()]))
+    with pytest.raises(PrebuiltFallback):
+        M.select_artifact_with_fallback(manifest, _cuda_host(), "cuda")
+    assert any(
+        f"slim bundle requires llama.cpp {SLIM_LLAMA_TAG}; "
+        "install or update llama.cpp first" in line
+        for line in lines
+    )
+
+
+def test_slim_release_tag_skew_has_distinct_compatibility_error(tmp_path, monkeypatch):
+    bin_dir = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(
+        M,
+        "installed_llama_runtime",
+        lambda: (bin_dir, "b10068-mix-old", "cuda13-newer"),
+    )
+    manifest = M.parse_manifest(_manifest([_slim_artifact()]))
+    with pytest.raises(ReleaseCompatibilityError, match = SLIM_LLAMA_TAG):
+        M.select_artifact_with_fallback(manifest, _cuda_host(), "cuda")
+
+
+def test_link_ggml_runtime_hardlinks_every_ggml_library(tmp_path):
+    bin_dir = _fake_llama_bin(tmp_path)
+    whisper_bin = tmp_path / "whisper.cpp" / "build" / "bin"
+    linked = M.link_ggml_runtime(bin_dir, whisper_bin)
+    assert linked == [
+        "libggml-base.so.0",
+        "libggml-cpu-x64.so",
+        "libggml-cuda.so",
+        "libggml.so.0",
+    ]
+    for name in ("libggml.so.0", "libggml-base.so.0", "libggml-cuda.so", "libggml-cpu-x64.so"):
+        source, dest = bin_dir / name, whisper_bin / name
+        assert dest.is_file() and not dest.is_symlink()
+        assert dest.stat().st_ino == source.stat().st_ino  # a true hardlink
+    assert not (whisper_bin / "libllama.so").exists()  # only ggml libraries wire over
+
+
+def test_link_ggml_runtime_copy_fallback(tmp_path, monkeypatch):
+    def no_link(src, dst, **kwargs):
+        raise OSError("cross-device link")
+
+    monkeypatch.setattr(M.os, "link", no_link)
+    bin_dir = _fake_llama_bin(tmp_path)
+    whisper_bin = tmp_path / "whisper.cpp" / "build" / "bin"
+    assert len(M.link_ggml_runtime(bin_dir, whisper_bin)) == 4
+    dest = whisper_bin / "libggml.so.0"
+    assert dest.read_bytes() == (bin_dir / "libggml.so.0").read_bytes()
+    assert dest.stat().st_nlink == 1  # a copy, not a link
+
+
+def test_link_ggml_runtime_hardlinks_dylibs(tmp_path):
+    # macOS wiring: the libggml* glob must take the .dylib names too.
+    bin_dir = _fake_llama_bin_macos(tmp_path)
+    whisper_bin = tmp_path / "whisper.cpp" / "build" / "bin"
+    linked = M.link_ggml_runtime(bin_dir, whisper_bin)
+    assert linked == [
+        "libggml-base.dylib",
+        "libggml-blas.dylib",
+        "libggml-cpu.dylib",
+        "libggml-metal.dylib",
+        "libggml.dylib",
+    ]
+    for name in linked:
+        source, dest = bin_dir / name, whisper_bin / name
+        assert dest.is_file() and not dest.is_symlink()
+        assert dest.stat().st_ino == source.stat().st_ino  # a true hardlink
+    assert not (whisper_bin / "libllama.dylib").exists()
+
+
+def test_link_ggml_runtime_fails_closed_on_empty_runtime(tmp_path):
+    empty = tmp_path / "empty"
+    empty.mkdir()
+    with pytest.raises(PrebuiltFallback):
+        M.link_ggml_runtime(empty, tmp_path / "whisper_bin")
+
+
+def test_link_ggml_runtime_wires_windows_libomp(tmp_path):
+    # llama's clang-built windows-arm64 ggml-base.dll imports
+    # libomp140.aarch64.dll (bundled, not a system DLL): the wiring must place
+    # it next to whisper-server.exe or the loader dies with DLL_NOT_FOUND.
+    bin_dir = tmp_path / "llama_bin"
+    bin_dir.mkdir()
+    for name in ("ggml.dll", "ggml-base.dll", "ggml-cpu.dll", "libomp140.aarch64.dll"):
+        (bin_dir / name).write_bytes(b"x")
+    (bin_dir / "llama.dll").write_bytes(b"x")  # never wired
+    whisper_bin = tmp_path / "whisper_bin"
+    linked = M.link_ggml_runtime(bin_dir, whisper_bin)
+    assert linked == ["ggml-base.dll", "ggml-cpu.dll", "ggml.dll", "libomp140.aarch64.dll"]
+    assert not (whisper_bin / "llama.dll").exists()
+
+
+def test_rocm_runtime_wires_complete_windows_dll_overlay(tmp_path):
+    bin_dir = tmp_path / "llama_bin"
+    bin_dir.mkdir()
+    dlls = {
+        "ggml.dll",
+        "ggml-base.dll",
+        "ggml-hip.dll",
+        "amdhip64.dll",
+        "rocblas.dll",
+        "hipblaslt.dll",
+        "hsa-runtime64.dll",
+        # The llama Windows ROCm archive can carry transitive DLLs whose names
+        # do not contain hip/roc/amd. Its installer overlays every DLL.
+        "runtime-support.dll",
+    }
+    for name in dlls:
+        (bin_dir / name).write_bytes(name.encode())
+    (bin_dir / "not-a-runtime.txt").write_text("ignored")
+
+    whisper_bin = tmp_path / "whisper_bin"
+    linked = M.link_ggml_runtime(bin_dir, whisper_bin, backend = "rocm")
+    linked_dirs = M.link_runtime_directories(
+        bin_dir,
+        whisper_bin,
+        backend = "rocm",
+        host = _host("windows", "x64"),
+    )
+
+    assert set(linked) == dlls
+    assert linked_dirs == []
+    assert all((whisper_bin / name).is_file() for name in dlls)
+    assert not (whisper_bin / "not-a-runtime.txt").exists()
+
+
+def test_assemble_does_not_copy_packaging_marker_beside_server(tmp_path):
+    host = _host("linux", "x64")
+    bundle = tmp_path / "bundle"
+    bundle.mkdir()
+    (bundle / "whisper-server").write_text("server")
+    (bundle / M.METADATA_FILENAME).write_text('{"backend":"slim"}')
+    staged = tmp_path / "staged"
+    M.assemble_install_tree(bundle, staged, host)
+    assert not (staged / "build" / "bin" / M.METADATA_FILENAME).exists()
+
+
+def test_rocm_runtime_wires_packaged_dependency_closure_and_catalogs(tmp_path, monkeypatch):
+    llama_bin = _fake_llama_bin(tmp_path, backend_module = "libggml-hip.so")
+    for name in ("libamdhip64.so.6", "libhipblas.so.2", "libcustomrocm.so.1"):
+        (llama_bin / name).write_bytes(name.encode())
+    for directory in M.SLIM_ROCM_RUNTIME_DIRS:
+        catalog = llama_bin / directory / "library" / "gfx1100"
+        catalog.mkdir(parents = True)
+        (catalog / "kernel.dat").write_bytes(directory.encode())
+
+    dependencies = {
+        "libggml-hip.so": {"libamdhip64.so.6", "libcustomrocm.so.1"},
+        "libamdhip64.so.6": {"libhipblas.so.2"},
+    }
+    monkeypatch.setattr(M, "_elf_needed", lambda path: dependencies.get(path.name, set()))
+    whisper_bin = tmp_path / "whisper-bin"
+    linked = M.link_ggml_runtime(llama_bin, whisper_bin, backend = "rocm")
+    linked_dirs = M.link_runtime_directories(
+        llama_bin,
+        whisper_bin,
+        backend = "rocm",
+        host = _host("linux", "x64"),
+    )
+
+    assert "libcustomrocm.so.1" in linked
+    assert "libhipblas.so.2" in linked
+    assert linked_dirs == ["hipblaslt", "rocblas"]
+    for directory in linked_dirs:
+        linked_catalog = whisper_bin / directory / "library" / "gfx1100" / "kernel.dat"
+        source_catalog = llama_bin / directory / "library" / "gfx1100" / "kernel.dat"
+        assert linked_catalog.stat().st_ino == source_catalog.stat().st_ino
+
+
+def test_rocm_runtime_requires_both_kernel_catalogs(tmp_path):
+    llama_bin = _fake_llama_bin(tmp_path, backend_module = "libggml-hip.so")
+    (llama_bin / "hipblaslt").mkdir()
+    (llama_bin / "hipblaslt" / "kernel.dat").write_bytes(b"kernel")
+    with pytest.raises(PrebuiltFallback, match = "rocblas"):
+        M.link_runtime_directories(
+            llama_bin,
+            tmp_path / "whisper-bin",
+            backend = "rocm",
+            host = _host("linux", "x64"),
+        )
+
+
+def test_rocm_runtime_catalog_copy_fallback(tmp_path, monkeypatch):
+    llama_bin = _fake_llama_bin(tmp_path, backend_module = "libggml-hip.so")
+    for directory in M.SLIM_ROCM_RUNTIME_DIRS:
+        catalog = llama_bin / directory
+        catalog.mkdir()
+        (catalog / "kernel.dat").write_bytes(directory.encode())
+    monkeypatch.setattr(M.os, "link", lambda *args: (_ for _ in ()).throw(OSError("xdev")))
+    whisper_bin = tmp_path / "whisper-bin"
+    M.link_runtime_directories(
+        llama_bin,
+        whisper_bin,
+        backend = "rocm",
+        host = _host("linux", "x64"),
+    )
+    for directory in M.SLIM_ROCM_RUNTIME_DIRS:
+        assert (whisper_bin / directory / "kernel.dat").read_bytes() == directory.encode()
+
+
+def test_existing_install_requires_executable_server(tmp_path, monkeypatch):
+    # A marker-matching install with a non-executable server must reinstall:
+    # the sidecar refuses it via os.access(X_OK), so "already matches" would
+    # otherwise leave dictation permanently broken.
+    host = _host("linux", "x64")
+    selection = object()
+    monkeypatch.setattr(M.core, "existing_install_matches", lambda *a: True)
+    server = tmp_path / "build" / "bin" / "whisper-server"
+    server.parent.mkdir(parents = True)
+    server.write_text("bin")
+    monkeypatch.setattr(M, "installed_server_path", lambda d, h: server)
+    monkeypatch.setattr(M, "load_prebuilt_metadata", lambda d: {})
+    server.chmod(0o644)
+    assert M.existing_install_matches(tmp_path, host, selection) is False
+    server.chmod(0o755)
+    assert M.existing_install_matches(tmp_path, host, selection) is True
+
+
+def test_existing_slim_install_requires_wired_libraries(tmp_path, monkeypatch):
+    # A slim install whose hardlinked ggml files vanished (llama dir deleted)
+    # must reinstall so update re-wires instead of reporting up to date.
+    host = _host("linux", "x64")
+    monkeypatch.setattr(M.core, "existing_install_matches", lambda *a: True)
+    server = tmp_path / "build" / "bin" / "whisper-server"
+    server.parent.mkdir(parents = True)
+    server.write_text("bin")
+    server.chmod(0o755)
+    monkeypatch.setattr(M, "installed_server_path", lambda d, h: server)
+    marker = {
+        "install_kind": "slim",
+        "runtime_wiring_version": M.SLIM_RUNTIME_WIRING_VERSION,
+        "linked_libraries": ["libggml.so.0"],
+    }
+    monkeypatch.setattr(M, "load_prebuilt_metadata", lambda d: marker)
+    marker.pop("runtime_wiring_version")
+    assert M.existing_install_matches(tmp_path, host, object()) is False
+    marker["runtime_wiring_version"] = M.SLIM_RUNTIME_WIRING_VERSION
+    assert M.existing_install_matches(tmp_path, host, object()) is False
+    (server.parent / "libggml.so.0").write_text("lib")
+    assert M.existing_install_matches(tmp_path, host, object()) is True
+    marker.update(backend = "rocm", linked_runtime_directories = [])
+    assert M.existing_install_matches(tmp_path, _host("windows", "x64"), object()) is True
+
+
+def test_link_ggml_runtime_libomp_alone_is_not_a_pairing(tmp_path):
+    # A libomp without any ggml library is not a usable llama runtime.
+    bin_dir = tmp_path / "llama_bin"
+    bin_dir.mkdir()
+    (bin_dir / "libomp140.aarch64.dll").write_bytes(b"x")
+    with pytest.raises(PrebuiltFallback):
+        M.link_ggml_runtime(bin_dir, tmp_path / "whisper_bin")
+
+
+def _build_slim_bundle(tmp_path: Path, host: HostInfo) -> tuple[Path, str]:
+    """Slim archive per the CI contract: whisper-server + libwhisper only."""
+    archive = tmp_path / SLIM_ASSET
+    with tarfile.open(archive, "w:gz") as tar:
+        _add_file(tar, M.server_binary_name(host), b"#!/bin/sh\necho whisper\n", mode = 0o755)
+        _add_file(tar, "libwhisper.so.1", b"dummy-libwhisper")
+    return archive, M.sha256_file(archive)
+
+
+def _slim_install_env(monkeypatch, tmp_path, host, *, sha256: str) -> Path:
+    llama_bin = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(
+        M,
+        "installed_llama_runtime",
+        lambda install_dir = None: (llama_bin, SLIM_LLAMA_TAG, "cuda13-newer"),
+    )
+    manifest = M.parse_manifest(
+        _manifest(
+            [
+                _artifact("linux", "x64", "cpu", CPU_ASSET, "a" * 64),
+                _slim_artifact(sha256 = sha256),
+            ]
+        )
+    )
+    bundle = M.ReleaseBundle(
+        repo = "unslothai/whisper.cpp",
+        release_tag = RELEASE_TAG,
+        manifest = manifest,
+        asset_urls = {SLIM_ASSET: f"https://example.invalid/{SLIM_ASSET}"},
+    )
+    checksums = {SLIM_ASSET: sha256, CPU_ASSET: "a" * 64}
+    monkeypatch.setattr(
+        M,
+        "fetch_release_for_install",
+        lambda repo, *, published_release_tag = None: (bundle, checksums),
+    )
+    return llama_bin
+
+
+def test_slim_install_wires_links_and_marker(tmp_path, monkeypatch):
+    host = _cuda_host()
+    archive, sha256 = _build_slim_bundle(tmp_path, host)
+
+    def fake_download(url, destination):
+        destination.parent.mkdir(parents = True, exist_ok = True)
+        destination.write_bytes(archive.read_bytes())
+
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(M, "download_file", fake_download)
+    llama_bin = _slim_install_env(monkeypatch, tmp_path, host, sha256 = sha256)
+
+    install_dir = tmp_path / "whisper.cpp"
+    assert M.install_prebuilt(install_dir, backend = "cuda") == M.EXIT_SUCCESS
+
+    whisper_bin = install_dir / "build" / "bin"
+    assert (whisper_bin / "whisper-server").is_file()
+    assert (whisper_bin / "libwhisper.so.1").is_file()
+    for name in ("libggml.so.0", "libggml-base.so.0", "libggml-cuda.so", "libggml-cpu-x64.so"):
+        dest = whisper_bin / name
+        assert dest.is_file() and not dest.is_symlink()
+        assert dest.stat().st_ino == (llama_bin / name).stat().st_ino
+
+    marker = json.loads((install_dir / M.METADATA_FILENAME).read_text())
+    assert marker["backend"] == "cuda"  # the accel identity, not "slim"
+    assert marker["asset"] == SLIM_ASSET
+    assert marker["install_kind"] == "slim"
+    assert marker["paired_llama_tag"] == SLIM_LLAMA_TAG
+    assert marker["linked_from"] == str(llama_bin)
+    # The wired filenames land in the marker; the sidecar launch guard
+    # verifies exactly these names instead of hardcoded per-OS globs.
+    assert marker["linked_libraries"] == [
+        "libggml-base.so.0",
+        "libggml-cpu-x64.so",
+        "libggml-cuda.so",
+        "libggml.so.0",
+    ]
+    assert marker["runtime_wiring_version"] == M.SLIM_RUNTIME_WIRING_VERSION
+    assert marker["linked_runtime_directories"] == []
+
+
+def test_slim_links_survive_a_llama_dir_swap(tmp_path, monkeypatch):
+    # The whole point of hardlinks: replace the llama dir contents after wiring
+    # and whisper's links must still hold the OLD inodes/content.
+    host = _cuda_host()
+    archive, sha256 = _build_slim_bundle(tmp_path, host)
+
+    def fake_download(url, destination):
+        destination.parent.mkdir(parents = True, exist_ok = True)
+        destination.write_bytes(archive.read_bytes())
+
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(M, "download_file", fake_download)
+    llama_bin = _slim_install_env(monkeypatch, tmp_path, host, sha256 = sha256)
+
+    install_dir = tmp_path / "whisper.cpp"
+    assert M.install_prebuilt(install_dir, backend = "cuda") == M.EXIT_SUCCESS
+    whisper_lib = install_dir / "build" / "bin" / "libggml.so.0"
+    old_inode = whisper_lib.stat().st_ino
+    old_content = whisper_lib.read_bytes()
+
+    # Simulate the llama updater swapping in a new release's libraries.
+    for path in llama_bin.iterdir():
+        path.unlink()
+    (llama_bin / "libggml.so.0").write_bytes(b"ggml-NEW")
+
+    assert whisper_lib.stat().st_ino == old_inode  # old inode survives the swap
+    assert whisper_lib.read_bytes() == old_content
+    assert whisper_lib.stat().st_nlink == 1  # the llama side is gone; ours remains
+
+
+# The exact resolver key set shipped before slim existed; install_kind is the
+# one additive field and must stay the only difference.
+_LEGACY_RESOLVER_KEYS = {
+    "prebuilt_available",
+    "repo",
+    "release_tag",
+    "upstream_tag",
+    "backend",
+    "requested_backend",
+    "cpu_fallback",
+    "asset",
+    "os",
+    "arch",
+    "runtime_line",
+}
+
+
+def _resolver_payload(monkeypatch, capsys, manifest, host) -> dict:
+    bundle = M.ReleaseBundle(
+        repo = "unslothai/whisper.cpp",
+        release_tag = RELEASE_TAG,
+        manifest = manifest,
+        asset_urls = {},
+    )
+    monkeypatch.setattr(M, "detect_host", lambda: host)
+    monkeypatch.setattr(
+        M, "fetch_release_for_install", lambda repo, *, published_release_tag = None: (bundle, {})
+    )
+    assert M.main(["--resolve-prebuilt", "--output-format", "json"]) == M.EXIT_SUCCESS
+    return json.loads(capsys.readouterr().out.strip())
+
+
+def test_resolver_reports_install_kind_fat_additively(monkeypatch, capsys):
+    # The pinned pre-slim escape hatch resolves the published fat CPU bundle.
+    manifest = M.parse_manifest(_manifest([_artifact("linux", "x64", "cpu", CPU_ASSET, "a" * 64)]))
+    payload = _resolver_payload(monkeypatch, capsys, manifest, _host("linux", "x64"))
+    assert set(payload) == _LEGACY_RESOLVER_KEYS | {"install_kind"}
+    assert payload["install_kind"] == "fat"
+    assert payload["asset"] == CPU_ASSET
+
+
+def _release_for_selection(release_tag: str, upstream_tag: str, artifact: dict) -> M.ReleaseBundle:
+    payload = _manifest([artifact])
+    payload["upstream_tag"] = upstream_tag
+    return M.ReleaseBundle(
+        repo = "unslothai/whisper.cpp",
+        release_tag = release_tag,
+        manifest = M.parse_manifest(payload),
+        asset_urls = {},
+    )
+
+
+def test_whisper_tag_selects_matching_published_upstream(monkeypatch):
+    latest_asset = "latest-linux-x64-cpu.tar.gz"
+    pinned_asset = "pinned-linux-x64-cpu.tar.gz"
+    latest = _release_for_selection(
+        "v1.9.2-unsloth.1",
+        "v1.9.2",
+        _artifact("linux", "x64", "cpu", latest_asset, "a" * 64),
+    )
+    pinned = _release_for_selection(
+        "v1.9.0-unsloth.3",
+        "v1.9.0",
+        _artifact("linux", "x64", "cpu", pinned_asset, "b" * 64),
+    )
+    monkeypatch.setattr(
+        M,
+        "fetch_release_for_install",
+        lambda *args, **kwargs: (_ for _ in ()).throw(
+            AssertionError("an upstream pin consulted the unrelated newest release")
+        ),
+    )
+    monkeypatch.setattr(
+        M,
+        "_published_release_tags",
+        lambda repo: [latest.release_tag, pinned.release_tag],
+    )
+    monkeypatch.setattr(
+        M,
+        "_fetch_release_candidate",
+        lambda repo, tag: latest if tag == latest.release_tag else pinned,
+    )
+    monkeypatch.setattr(M, "fetch_release_checksums", lambda bundle: {pinned_asset: "b" * 64})
+
+    payload = M.resolve_prebuilt(
+        _host("linux", "x64"),
+        published_repo = "unslothai/whisper.cpp",
+        published_release_tag = None,
+        whisper_tag = "v1.9.0",
+        backend = "cpu",
+        cpu_fallback = False,
+    )
+    assert payload["prebuilt_available"] is True
+    assert payload["release_tag"] == pinned.release_tag
+    assert payload["upstream_tag"] == "v1.9.0"
+
+
+def test_macos_walks_back_to_newest_compatible_release(monkeypatch):
+    latest_asset = "latest-macos-arm64-cpu.tar.gz"
+    compatible_asset = "compatible-macos-arm64-cpu.tar.gz"
+    latest = _release_for_selection(
+        "v1.9.2-unsloth.1",
+        "v1.9.2",
+        _artifact(
+            "macos",
+            "arm64",
+            "cpu",
+            latest_asset,
+            "a" * 64,
+            min_os = "macos-15.0",
+        ),
+    )
+    compatible = _release_for_selection(
+        "v1.9.1-unsloth.1",
+        "v1.9.1",
+        _artifact(
+            "macos",
+            "arm64",
+            "cpu",
+            compatible_asset,
+            "b" * 64,
+            min_os = "macos-13.0",
+        ),
+    )
+    monkeypatch.setattr(
+        M,
+        "fetch_release_for_install",
+        lambda repo, *, published_release_tag = None: (latest, {latest_asset: "a" * 64}),
+    )
+    monkeypatch.setattr(
+        M,
+        "_published_release_tags",
+        lambda repo: [latest.release_tag, compatible.release_tag],
+    )
+    monkeypatch.setattr(M, "_fetch_release_candidate", lambda repo, tag: compatible)
+    monkeypatch.setattr(
+        M,
+        "fetch_release_checksums",
+        lambda bundle: {compatible_asset: "b" * 64},
+    )
+
+    payload = M.resolve_prebuilt(
+        _host("macos", "arm64", macos_version = (14, 7)),
+        published_repo = "unslothai/whisper.cpp",
+        published_release_tag = None,
+        backend = "cpu",
+        cpu_fallback = False,
+    )
+    assert payload["prebuilt_available"] is True
+    assert payload["release_tag"] == compatible.release_tag
+
+
+def test_macos_walkback_never_masks_checksum_failure(monkeypatch):
+    asset = "latest-macos-arm64-cpu.tar.gz"
+    latest = _release_for_selection(
+        "v1.9.2-unsloth.1",
+        "v1.9.2",
+        _artifact("macos", "arm64", "cpu", asset, "a" * 64, min_os = "macos-13.0"),
+    )
+    monkeypatch.setattr(
+        M,
+        "fetch_release_for_install",
+        lambda repo, *, published_release_tag = None: (latest, {asset: "b" * 64}),
+    )
+    monkeypatch.setattr(
+        M,
+        "_published_release_tags",
+        lambda repo: (_ for _ in ()).throw(AssertionError("integrity failure walked back")),
+    )
+
+    with pytest.raises(PrebuiltFallback, match = "disagrees"):
+        M._release_plan_for_host(
+            _host("macos", "arm64", macos_version = (14, 7)),
+            published_repo = "unslothai/whisper.cpp",
+            published_release_tag = None,
+            whisper_tag = "latest",
+            requested_backend = "cpu",
+        )
+
+
+def test_resolver_reports_install_kind_slim_when_paired(tmp_path, monkeypatch, capsys):
+    bin_dir = _fake_llama_bin(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "cuda13-newer")
+    )
+    payload = _resolver_payload(monkeypatch, capsys, _slim_manifest(), _cuda_host())
+    assert set(payload) == _LEGACY_RESOLVER_KEYS | {"install_kind"}
+    assert payload["install_kind"] == "slim"
+    assert payload["asset"] == SLIM_ASSET
+    assert payload["backend"] == "cuda"
+
+
+def test_resolver_reports_metal_slim_on_macos(tmp_path, monkeypatch, capsys):
+    # Same contract shape on macs: backend stays the accel (metal), the one
+    # additive field says the asset installs slim.
+    bin_dir = _fake_llama_bin_macos(tmp_path)
+    monkeypatch.setattr(
+        M, "installed_llama_runtime", lambda: (bin_dir, SLIM_LLAMA_TAG, "macos-metal-arm64")
+    )
+    host = _host("macos", "arm64", macos_version = (14, 0))
+    payload = _resolver_payload(monkeypatch, capsys, _macos_slim_manifest(), host)
+    assert set(payload) == _LEGACY_RESOLVER_KEYS | {"install_kind"}
+    assert payload["install_kind"] == "slim"
+    assert payload["asset"] == MAC_SLIM_ASSET
+    assert payload["backend"] == "metal"
+    assert payload["requested_backend"] == "metal"
diff --git a/tests/studio/install/test_prebuilt_core.py b/tests/studio/install/test_prebuilt_core.py
new file mode 100644
index 0000000000..4d1c37b8da
--- /dev/null
+++ b/tests/studio/install/test_prebuilt_core.py
@@ -0,0 +1,918 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Shared descriptor-parameterized tests for studio/prebuilt_core.py.
+
+Runs the component-agnostic core against BOTH shipped descriptors -- the real
+whisper descriptor exported by install_whisper_prebuilt and a llama-flavored
+descriptor built here the way a hypothetical third ggml-family component would
+plug in (descriptor only, no installer module). Covers os/arch selection,
+checksum fail-closed behavior, extraction guards, the resolver payload, and the
+ops monkeypatch seam, so a new component gets this coverage for free.
+
+The llama installer's shipped release-plan machinery is intentionally NOT
+routed through the generic flow (its characterization suites pin it); the
+llama descriptor here exercises the canonical dialect a future migration
+would use, including the "no fallback backend -> report no prebuilt" policy.
+"""
+
+import importlib.util
+import io
+import json
+import sys
+import tarfile
+import zipfile
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+PACKAGE_ROOT = Path(__file__).resolve().parents[3]
+STUDIO_DIR = PACKAGE_ROOT / "studio"
+if str(STUDIO_DIR) not in sys.path:
+    sys.path.insert(0, str(STUDIO_DIR))
+
+SPEC = importlib.util.spec_from_file_location(
+    "studio_prebuilt_core", STUDIO_DIR / "prebuilt_core.py"
+)
+assert SPEC is not None and SPEC.loader is not None
+core = importlib.util.module_from_spec(SPEC)
+sys.modules[SPEC.name] = core
+SPEC.loader.exec_module(core)
+
+WSPEC = importlib.util.spec_from_file_location(
+    "studio_install_whisper_prebuilt_for_core", STUDIO_DIR / "install_whisper_prebuilt.py"
+)
+assert WSPEC is not None and WSPEC.loader is not None
+iwp = importlib.util.module_from_spec(WSPEC)
+sys.modules[WSPEC.name] = iwp
+WSPEC.loader.exec_module(iwp)
+
+
+LLAMA_DESCRIPTOR = core.ComponentDescriptor(
+    component = "llama.cpp",
+    log_prefix = "llama-prebuilt",
+    published_repo = "unslothai/llama.cpp",
+    manifest_asset_name = "llama-prebuilt-manifest.json",
+    sha256_asset_name = "llama-prebuilt-sha256.json",
+    metadata_filename = "UNSLOTH_LLAMA_PREBUILT_INFO.json",
+    user_agent = "unsloth-studio-llama-prebuilt",
+    # A GPU-selection miss reports "no prebuilt" so the caller can fall back to
+    # a source build instead of silently degrading to CPU.
+    fallback_backend = None,
+    server_binary_name = lambda host: "llama-server",
+    runtime_bin_dir = lambda install_dir, host: install_dir / "build" / "bin",
+)
+
+
+class Component:
+    """One descriptor under test plus the mutable namespace behind its ops."""
+
+    def __init__(self, descriptor):
+        self.descriptor = descriptor
+        self.namespace = core.component_namespace(descriptor)
+        self.namespace["log"] = lambda message: None  # keep test output quiet
+        self.ops = core.ModuleOps(self.namespace)
+
+    @property
+    def falls_back_to_cpu(self):
+        return self.descriptor.fallback_backend == "cpu"
+
+
+@pytest.fixture(params = ["whisper", "llama"])
+def component(request):
+    if request.param == "whisper":
+        return Component(iwp.DESCRIPTOR)
+    return Component(LLAMA_DESCRIPTOR)
+
+
+def make_host(
+    component,
+    *,
+    os_token = "linux",
+    arch_token = "x64",
+    is_windows = False,
+    is_macos = False,
+    is_apple_silicon = False,
+    has_usable_nvidia = False,
+    has_rocm = False,
+    rocm_gfx = None,
+    macos_version = None,
+):
+    if component.descriptor is iwp.DESCRIPTOR:
+        return iwp.HostInfo(
+            system = {"linux": "Linux", "macos": "Darwin", "windows": "Windows"}[os_token],
+            machine = "x86_64" if arch_token == "x64" else "arm64",
+            whisper_os = os_token,
+            whisper_arch = arch_token,
+            archive_ext = ".zip" if is_windows else ".tar.gz",
+            is_windows = is_windows,
+            is_macos = is_macos,
+            is_apple_silicon = is_apple_silicon,
+            has_usable_nvidia = has_usable_nvidia,
+            has_rocm = has_rocm,
+            rocm_gfx = rocm_gfx,
+            macos_version = macos_version,
+        )
+    # Descriptor-only component: the core default host_platform_tokens hook
+    # reads .os_token/.arch_token off a plain host object.
+    return SimpleNamespace(
+        os_token = os_token,
+        arch_token = arch_token,
+        is_windows = is_windows,
+        is_macos = is_macos,
+        is_apple_silicon = is_apple_silicon,
+        has_usable_nvidia = has_usable_nvidia,
+        has_rocm = has_rocm,
+        rocm_gfx = rocm_gfx,
+        macos_version = macos_version,
+    )
+
+
+def artifact(
+    os_ = "linux",
+    arch = "x64",
+    backend = "cpu",
+    asset = "bundle.tar.gz",
+    **extra,
+):
+    payload = {"os": os_, "arch": arch, "backend": backend, "asset": asset}
+    payload.update(extra)
+    return payload
+
+
+def manifest_for(component, artifacts, **extra):
+    payload = {
+        "schema_version": 1,
+        "component": extra.pop("component_name", component.descriptor.component),
+        "upstream_tag": "v1.0.0",
+        "source_commit": "a" * 40,
+        "artifacts": artifacts,
+    }
+    payload.update(extra)
+    return payload
+
+
+# ── Manifest parsing ──
+def test_parse_manifest_normalizes(component):
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [artifact(), "not-a-dict", {"os": "linux"}]), label = "m"
+    )
+    assert manifest["component"] == component.descriptor.component
+    assert manifest["upstream_tag"] == "v1.0.0"
+    # Non-dict entries and entries without an asset name are dropped.
+    assert [a["asset"] for a in manifest["artifacts"]] == ["bundle.tar.gz"]
+
+
+def test_parse_manifest_rejects_wrong_component(component):
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.parse_manifest(
+            manifest_for(component, [artifact()], component_name = "other.cpp"), label = "m"
+        )
+
+
+def test_parse_manifest_rejects_unknown_schema(component):
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.parse_manifest(
+            manifest_for(component, [artifact()], schema_version = 99), label = "m"
+        )
+
+
+def test_parse_manifest_rejects_non_object(component):
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.parse_manifest(["nope"], label = "m")
+    # An object without an 'artifacts' list is rejected too.
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.parse_manifest(
+            {"schema_version": 1, "component": component.descriptor.component}, label = "m"
+        )
+
+
+# ── Selection matrix ──
+def test_select_cpu_first_match(component):
+    manifest = component.ops.parse_manifest(
+        manifest_for(
+            component,
+            [
+                artifact(backend = "cpu", asset = "first-cpu.tar.gz"),
+                artifact(backend = "cpu", asset = "second-cpu.tar.gz"),
+            ],
+        ),
+        label = "m",
+    )
+    host = make_host(component)
+    chosen = component.ops.select_artifact(manifest, host, "cpu")
+    assert chosen["asset"] == "first-cpu.tar.gz"
+
+
+def test_select_respects_os_arch(component):
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [artifact(os_ = "windows", backend = "cpu")]), label = "m"
+    )
+    host = make_host(component)
+    assert component.ops.select_artifact(manifest, host, "cpu") is None
+
+
+def test_fallback_policy_differs_per_descriptor(component):
+    # No asset for the requested backend: whisper degrades to the CPU asset of
+    # the same release, the llama-flavored descriptor reports no prebuilt
+    # (source-build fallback).
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [artifact(backend = "cpu", asset = "cpu.tar.gz")]), label = "m"
+    )
+    host = make_host(component, has_usable_nvidia = True)
+    assert component.ops.select_artifact(manifest, host, "cuda") is None
+    if component.falls_back_to_cpu:
+        chosen, backend, used_fallback = component.ops.select_artifact_with_fallback(
+            manifest, host, "cuda"
+        )
+        assert (chosen["asset"], backend, used_fallback) == ("cpu.tar.gz", "cpu", True)
+    else:
+        with pytest.raises(core.PrebuiltFallback):
+            component.ops.select_artifact_with_fallback(manifest, host, "cuda")
+
+
+def test_macos_min_os_gate(component):
+    manifest = component.ops.parse_manifest(
+        manifest_for(
+            component,
+            [
+                artifact(
+                    os_ = "macos",
+                    arch = "arm64",
+                    backend = "metal",
+                    asset = "metal-new.tar.gz",
+                    min_os = "macos-15.0",
+                )
+            ],
+        ),
+        label = "m",
+    )
+    old_host = make_host(
+        component,
+        os_token = "macos",
+        arch_token = "arm64",
+        is_macos = True,
+        is_apple_silicon = True,
+        macos_version = (14, 7),
+    )
+    new_host = make_host(
+        component,
+        os_token = "macos",
+        arch_token = "arm64",
+        is_macos = True,
+        is_apple_silicon = True,
+        macos_version = (15, 1),
+    )
+    assert component.ops.select_artifact(manifest, old_host, "metal") is None
+    chosen = component.ops.select_artifact(manifest, new_host, "metal")
+    assert chosen["asset"] == "metal-new.tar.gz"
+
+
+def _metal_artifact(asset, min_os):
+    return artifact(
+        os_ = "macos",
+        arch = "arm64",
+        backend = "metal",
+        asset = asset,
+        min_os = min_os,
+    )
+
+
+def _arm_mac_host(component, macos_version):
+    return make_host(
+        component,
+        os_token = "macos",
+        arch_token = "arm64",
+        is_macos = True,
+        is_apple_silicon = True,
+        macos_version = macos_version,
+    )
+
+
+def test_macos_min_os_filters_to_compatible_bundle(component):
+    # host 14.0 can't load the 15.0 bundle; the 13.0 bundle is picked instead.
+    manifest = component.ops.parse_manifest(
+        manifest_for(
+            component,
+            [
+                _metal_artifact("metal-new.tar.gz", "macos-15.0"),
+                _metal_artifact("metal.tar.gz", "macos-13.0"),
+            ],
+        ),
+        label = "m",
+    )
+    host = _arm_mac_host(component, (14, 0))
+    assert component.ops.select_artifact(manifest, host, "metal")["asset"] == "metal.tar.gz"
+
+
+def test_macos_min_os_unknown_host_version_keeps_artifact(component):
+    # Unknown host macOS version -> defer to runtime validation, don't reject.
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [_metal_artifact("metal-new.tar.gz", "macos-15.0")]), label = "m"
+    )
+    host = _arm_mac_host(component, None)
+    assert component.ops.select_artifact(manifest, host, "metal")["asset"] == "metal-new.tar.gz"
+
+
+def test_macos_min_os_accepts_bare_version_format(component):
+    # A bare "14.0" (no 'macos-' prefix) must still parse, for forward-compat.
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [_metal_artifact("metal.tar.gz", "14.0")]), label = "m"
+    )
+    host = _arm_mac_host(component, (13, 0))
+    assert component.ops.select_artifact(manifest, host, "metal") is None  # 13.0 < 14.0
+
+
+def test_macos_min_os_ok_helper_handles_prefix_and_bare(component):
+    host14 = _arm_mac_host(component, (14, 0))
+    # The live manifest format is 'macos-<ver>'; the prefix must be stripped.
+    assert component.ops.macos_min_os_ok(host14, "macos-14.0") is True
+    assert component.ops.macos_min_os_ok(host14, "macos-15.0") is False
+    assert component.ops.macos_min_os_ok(host14, "13.3") is True  # bare also parses
+    assert component.ops.macos_min_os_ok(host14, None) is True  # unknown -> defer
+    host_unknown = _arm_mac_host(component, None)
+    assert component.ops.macos_min_os_ok(host_unknown, "macos-15.0") is True
+
+
+# ── Backend resolution ──
+def test_resolve_backend_auto_and_validation(component):
+    gpu_host = make_host(component, has_usable_nvidia = True)
+    assert component.ops.resolve_backend(gpu_host, "auto", cpu_fallback = False) == "cuda"
+    assert component.ops.resolve_backend(gpu_host, "auto", cpu_fallback = True) == "cpu"
+    # --cpu-fallback wins over an explicit backend too.
+    assert component.ops.resolve_backend(gpu_host, "cuda", cpu_fallback = True) == "cpu"
+    # An explicit supported backend passes through untouched.
+    assert component.ops.resolve_backend(gpu_host, "vulkan", cpu_fallback = False) == "vulkan"
+    mac_host = make_host(
+        component, os_token = "macos", arch_token = "arm64", is_macos = True, is_apple_silicon = True
+    )
+    assert component.ops.resolve_backend(mac_host, None, cpu_fallback = False) == "metal"
+    # Intel mac has no Metal bundle in the P0 matrix -> cpu.
+    intel_mac = make_host(component, os_token = "macos", arch_token = "x64", is_macos = True)
+    assert component.ops.resolve_backend(intel_mac, "auto", cpu_fallback = False) == "cpu"
+    rocm_host = make_host(component, has_rocm = True, rocm_gfx = "gfx1100")
+    assert component.ops.resolve_backend(rocm_host, "auto", cpu_fallback = False) == "rocm"
+    bare_host = make_host(component)
+    assert component.ops.resolve_backend(bare_host, None, cpu_fallback = False) == "cpu"
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.resolve_backend(gpu_host, "tpu", cpu_fallback = False)
+
+
+# ── Checksum index: fail closed ──
+def _index_for(
+    component,
+    tag = "v1",
+    artifacts = None,
+):
+    return {
+        "schema_version": 1,
+        "component": component.descriptor.component,
+        "release_tag": tag,
+        "artifacts": artifacts
+        if artifacts is not None
+        else {"bundle.tar.gz": {"sha256": "0" * 64}},
+    }
+
+
+def test_parse_release_checksums_valid(component):
+    out = component.ops.parse_release_checksums("r", "v1", _index_for(component))
+    assert out == {"bundle.tar.gz": "0" * 64}
+
+
+@pytest.mark.parametrize(
+    "mutation",
+    [
+        {"component": "other.cpp"},
+        {"schema_version": 99},
+        {"release_tag": "v2"},
+        {"artifacts": {"bundle.tar.gz": {"sha256": "nope"}}},
+        {"artifacts": "not-a-map"},
+    ],
+)
+def test_parse_release_checksums_fails_closed(component, mutation):
+    payload = _index_for(component)
+    payload.update(mutation)
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.parse_release_checksums("r", "v1", payload)
+
+
+def test_parse_release_checksums_rejects_non_object(component):
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.parse_release_checksums("r", "v1", ["not", "a", "dict"])
+
+
+def test_expected_sha256_covered_asset_plain_lookup(component):
+    assert component.ops.expected_sha256_for({"a.tar.gz": "0" * 64}, "a.tar.gz") == "0" * 64
+
+
+def test_expected_sha256_missing_asset_fails_closed(component):
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.expected_sha256_for({"a.tar.gz": "0" * 64}, "b.tar.gz")
+
+
+def test_expected_sha256_manifest_disagreement_fails_closed(component):
+    with pytest.raises(core.PrebuiltFallback):
+        component.ops.expected_sha256_for(
+            {"a.tar.gz": "0" * 64}, "a.tar.gz", manifest_sha256 = "1" * 64
+        )
+    assert (
+        component.ops.expected_sha256_for(
+            {"a.tar.gz": "0" * 64}, "a.tar.gz", manifest_sha256 = "0" * 64
+        )
+        == "0" * 64
+    )
+
+
+# ── Extraction guards ──
+def test_extract_archive_rejects_traversal(tmp_path):
+    archive = tmp_path / "evil.tar.gz"
+    with tarfile.open(archive, "w:gz") as tar:
+        data = b"x"
+        info = tarfile.TarInfo("../escape.txt")
+        info.size = len(data)
+        tar.addfile(info, io.BytesIO(data))
+    with pytest.raises(core.PrebuiltFallback):
+        core.extract_archive(archive, tmp_path / "out")
+
+
+def test_extract_archive_rejects_absolute_member(tmp_path):
+    archive = tmp_path / "abs.tar.gz"
+    with tarfile.open(archive, "w:gz") as tar:
+        data = b"x"
+        info = tarfile.TarInfo("/abs.txt")
+        info.size = len(data)
+        tar.addfile(info, io.BytesIO(data))
+    with pytest.raises(core.PrebuiltFallback):
+        core.extract_archive(archive, tmp_path / "out")
+
+
+def test_extract_archive_rejects_zip_symlink(tmp_path):
+    archive = tmp_path / "link.zip"
+    with zipfile.ZipFile(archive, "w") as zf:
+        info = zipfile.ZipInfo("link")
+        info.create_system = 3
+        info.external_attr = 0o120777 << 16
+        zf.writestr(info, "target")
+    with pytest.raises(core.PrebuiltFallback, match = "zip archive contained a symlink entry"):
+        core.extract_archive(archive, tmp_path / "out")
+
+
+def test_extract_archive_rejects_absolute_zip_member(tmp_path):
+    archive = tmp_path / "abs.zip"
+    with zipfile.ZipFile(archive, "w") as zf:
+        zf.writestr("/etc/passwd", b"pwn")
+    with pytest.raises(core.PrebuiltFallback):
+        core.extract_archive(archive, tmp_path / "out")
+
+
+def test_extract_archive_allows_safe_tar_symlink_chain(tmp_path):
+    archive = tmp_path / "bundle.tar.gz"
+    payload = b"shared-object"
+    with tarfile.open(archive, "w:gz") as tar:
+        versioned = tarfile.TarInfo("libllama.so.0.0.1")
+        versioned.size = len(payload)
+        tar.addfile(versioned, io.BytesIO(payload))
+        soname = tarfile.TarInfo("libllama.so.0")
+        soname.type = tarfile.SYMTYPE
+        soname.linkname = "libllama.so.0.0.1"
+        tar.addfile(soname)
+        linker_name = tarfile.TarInfo("libllama.so")
+        linker_name.type = tarfile.SYMTYPE
+        linker_name.linkname = "libllama.so.0"
+        tar.addfile(linker_name)
+    destination = tmp_path / "extract"
+    core.extract_archive(archive, destination)
+    assert (destination / "libllama.so.0.0.1").read_bytes() == payload
+    assert (destination / "libllama.so.0").is_symlink()
+    assert (destination / "libllama.so").is_symlink()
+    assert (destination / "libllama.so").resolve().read_bytes() == payload
+
+
+def test_extract_archive_allows_safe_tar_hardlink(tmp_path):
+    archive = tmp_path / "bundle.tar.gz"
+    payload = b"quantize"
+    with tarfile.open(archive, "w:gz") as tar:
+        target = tarfile.TarInfo("llama-quantize")
+        target.size = len(payload)
+        tar.addfile(target, io.BytesIO(payload))
+        hardlink = tarfile.TarInfo("llama-quantize-copy")
+        hardlink.type = tarfile.LNKTYPE
+        hardlink.linkname = "llama-quantize"
+        tar.addfile(hardlink)
+    destination = tmp_path / "extract"
+    core.extract_archive(archive, destination)
+    assert (destination / "llama-quantize-copy").read_bytes() == payload
+    assert not (destination / "llama-quantize-copy").is_symlink()
+
+
+def test_extract_archive_rejects_absolute_tar_symlink_target(tmp_path):
+    archive = tmp_path / "bundle.tar.gz"
+    with tarfile.open(archive, "w:gz") as tar:
+        entry = tarfile.TarInfo("libllama.so")
+        entry.type = tarfile.SYMTYPE
+        entry.linkname = "/tmp/libllama.so.0"
+        tar.addfile(entry)
+    with pytest.raises(core.PrebuiltFallback, match = "archive link used an absolute target"):
+        core.extract_archive(archive, tmp_path / "extract")
+
+
+def test_extract_archive_rejects_escaping_tar_symlink_target(tmp_path):
+    archive = tmp_path / "bundle.tar.gz"
+    with tarfile.open(archive, "w:gz") as tar:
+        entry = tarfile.TarInfo("libllama.so")
+        entry.type = tarfile.SYMTYPE
+        entry.linkname = "../outside/libllama.so.0"
+        tar.addfile(entry)
+    with pytest.raises(core.PrebuiltFallback, match = "archive link escaped destination"):
+        core.extract_archive(archive, tmp_path / "extract")
+
+
+def test_extract_archive_rejects_unresolved_tar_symlink_target(tmp_path):
+    archive = tmp_path / "bundle.tar.gz"
+    with tarfile.open(archive, "w:gz") as tar:
+        entry = tarfile.TarInfo("libllama.so")
+        entry.type = tarfile.SYMTYPE
+        entry.linkname = "libllama.so.0"
+        tar.addfile(entry)
+    with pytest.raises(core.PrebuiltFallback, match = "unresolved link entries"):
+        core.extract_archive(archive, tmp_path / "extract")
+
+
+def test_extract_archive_rejects_unknown_format(tmp_path):
+    archive = tmp_path / "blob.xz"
+    archive.write_bytes(b"data")
+    with pytest.raises(core.PrebuiltFallback):
+        core.extract_archive(archive, tmp_path / "out")
+
+
+def test_restore_tar_exec_bits(tmp_path):
+    payload = tmp_path / "server"
+    payload.write_bytes(b"#!/bin/sh\n")
+    payload.chmod(0o755)
+    archive = tmp_path / "bundle.tar.gz"
+    with tarfile.open(archive, "w:gz") as tar:
+        tar.add(payload, arcname = "bundle/server")
+    out = tmp_path / "out"
+    core.extract_archive(archive, out)
+    extracted = out / "bundle" / "server"
+    assert extracted.is_file()
+    core.restore_tar_exec_bits(archive, out)
+    assert extracted.stat().st_mode & 0o111
+
+
+# ── Resolver payload ──
+def _fake_release(component, artifacts):
+    ns = component.namespace
+    manifest = component.ops.parse_manifest(manifest_for(component, artifacts), label = "m")
+    bundle = core.ReleaseBundle(
+        repo = component.descriptor.published_repo,
+        release_tag = "v1",
+        manifest = manifest,
+        asset_urls = {},
+    )
+    checksums = {str(a["asset"]): "0" * 64 for a in artifacts}
+    ns["fetch_release_for_install"] = lambda repo, *, published_release_tag: (bundle, checksums)
+    return bundle
+
+
+def test_resolve_prebuilt_payload_keys(component):
+    _fake_release(component, [artifact(backend = "cpu", asset = "cpu.tar.gz")])
+    host = make_host(component)
+    payload = component.ops.resolve_prebuilt(
+        host,
+        published_repo = component.descriptor.published_repo,
+        published_release_tag = None,
+        backend = "cpu",
+        cpu_fallback = True,
+    )
+    assert payload == {
+        "prebuilt_available": True,
+        "repo": component.descriptor.published_repo,
+        "release_tag": "v1",
+        "upstream_tag": "v1.0.0",
+        "backend": "cpu",
+        "requested_backend": "cpu",
+        "cpu_fallback": False,
+        "asset": "cpu.tar.gz",
+        "os": "linux",
+        "arch": "x64",
+        "runtime_line": None,
+    }
+
+
+def test_resolve_prebuilt_unavailable_payload(component):
+    ns = component.namespace
+
+    def boom(repo, *, published_release_tag):
+        raise core.PrebuiltFallback("no release")
+
+    ns["fetch_release_for_install"] = boom
+    host = make_host(component)
+    payload = component.ops.resolve_prebuilt(
+        host,
+        published_repo = component.descriptor.published_repo,
+        published_release_tag = None,
+        backend = "cpu",
+        cpu_fallback = True,
+    )
+    assert payload == {"prebuilt_available": False, "repo": component.descriptor.published_repo}
+
+
+def test_emit_resolver_output_formats(capsys):
+    payload = {"prebuilt_available": True, "asset": "a.tar.gz"}
+    core.emit_resolver_output(payload, output_format = "json")
+    assert json.loads(capsys.readouterr().out) == payload
+    core.emit_resolver_output(payload, output_format = "plain")
+    assert capsys.readouterr().out.strip() == "a.tar.gz"
+    core.emit_resolver_output({"prebuilt_available": False}, output_format = "plain")
+    assert json.loads(capsys.readouterr().out) == {"prebuilt_available": False}
+
+
+# ── Marker / fingerprint ──
+def test_install_fingerprint_is_stable_and_sensitive(component):
+    kwargs = dict(
+        published_repo = component.descriptor.published_repo,
+        release_tag = "v1",
+        upstream_tag = "v1.0.0",
+        source_commit = "a" * 40,
+        asset = "cpu.tar.gz",
+        asset_sha256 = "0" * 64,
+        backend = "cpu",
+        runtime_line = None,
+        coverage = {},
+    )
+    first = core.compute_install_fingerprint(**kwargs)
+    assert first == core.compute_install_fingerprint(**kwargs)
+    changed = core.compute_install_fingerprint(**{**kwargs, "asset_sha256": "1" * 64})
+    assert changed != first
+
+
+def test_write_and_match_marker(component, tmp_path):
+    host = make_host(component)
+    install_dir = tmp_path / "install"
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [artifact(backend = "cpu", asset = "cpu.tar.gz")]), label = "m"
+    )
+    selection = component.ops.selection_from_artifact(
+        published_repo = component.descriptor.published_repo,
+        release_tag = "v1",
+        manifest = manifest,
+        artifact = manifest["artifacts"][0],
+        backend = "cpu",
+        asset_sha256 = "0" * 64,
+    )
+    # No marker on disk yet -> not a match.
+    assert not component.ops.existing_install_matches(install_dir, host, selection)
+    bin_dir = component.ops.runtime_bin_dir(install_dir, host)
+    bin_dir.mkdir(parents = True)
+    component.ops.write_prebuilt_metadata(install_dir, selection)
+    # Marker alone is not enough: the server binary must exist too.
+    assert not component.ops.existing_install_matches(install_dir, host, selection)
+    (bin_dir / component.ops.server_binary_name(host)).write_bytes(b"bin")
+    marker = json.loads((install_dir / component.descriptor.metadata_filename).read_text())
+    assert marker["component"] == component.descriptor.component
+    assert marker["install_fingerprint"] == selection.fingerprint()
+    assert component.ops.existing_install_matches(install_dir, host, selection)
+    # A different selection (new sha) must force a reinstall.
+    other = core.InstallSelection(
+        **{
+            **selection.__dict__,
+            "asset_sha256": "1" * 64,
+        }
+    )
+    assert not component.ops.existing_install_matches(install_dir, host, other)
+
+
+def test_slim_selection_fields_are_additive(component, tmp_path):
+    """The slim pairing identity rides InstallSelection additively: it never
+    enters the fingerprint, and only a slim selection writes marker fields."""
+    manifest = component.ops.parse_manifest(
+        manifest_for(component, [artifact(backend = "cpu", asset = "cpu.tar.gz")]), label = "m"
+    )
+    selection = component.ops.selection_from_artifact(
+        published_repo = component.descriptor.published_repo,
+        release_tag = "v1",
+        manifest = manifest,
+        artifact = manifest["artifacts"][0],
+        backend = "cpu",
+        asset_sha256 = "0" * 64,
+    )
+    import dataclasses
+
+    slim = dataclasses.replace(
+        selection,
+        install_kind = "slim",
+        paired_llama_tag = "b10069-mix-fb3d4ca",
+        linked_from = "/llama/build/bin",
+        linked_libraries = ("libggml.so.0", "libggml-base.so.0"),
+    )
+    assert slim.fingerprint() == selection.fingerprint()  # no change to the computation
+
+    fat_dir, slim_dir = tmp_path / "fat", tmp_path / "slim"
+    fat_dir.mkdir(), slim_dir.mkdir()
+    component.ops.write_prebuilt_metadata(fat_dir, selection)
+    fat_marker = json.loads((fat_dir / component.descriptor.metadata_filename).read_text())
+    for key in ("install_kind", "paired_llama_tag", "linked_from", "linked_libraries"):
+        assert key not in fat_marker
+    component.ops.write_prebuilt_metadata(slim_dir, slim)
+    slim_marker = json.loads((slim_dir / component.descriptor.metadata_filename).read_text())
+    assert slim_marker["install_kind"] == "slim"
+    assert slim_marker["paired_llama_tag"] == "b10069-mix-fb3d4ca"
+    assert slim_marker["linked_from"] == "/llama/build/bin"
+    assert slim_marker["linked_libraries"] == ["libggml.so.0", "libggml-base.so.0"]
+    assert set(slim_marker) == set(fat_marker) | {
+        "install_kind",
+        "paired_llama_tag",
+        "linked_from",
+        "linked_libraries",
+    }
+
+
+def test_core_slim_hooks_default_inert(component, tmp_path):
+    # A component without its own hooks stages nothing extra and adds no
+    # resolver fields (llama's probe output must stay byte-identical).
+    assert component.ops.resolver_payload_extra({"install_kind": "slim"}) == {}
+    host = make_host(component)
+    selection = object()
+    assert component.ops.prepare_runtime_payload(tmp_path, host, selection) is None
+
+
+def test_busy_activation_restores_previous_install(monkeypatch, tmp_path):
+    install_dir = tmp_path / "whisper.cpp"
+    staged_root = tmp_path / "staged"
+    install_dir.mkdir()
+    staged_root.mkdir()
+    (install_dir / "version").write_text("old")
+    (staged_root / "version").write_text("new")
+    real_replace = core.os.replace
+
+    def locked_activation(source, destination):
+        if Path(source) == staged_root:
+            raise PermissionError(13, "Permission denied")
+        return real_replace(source, destination)
+
+    monkeypatch.setattr(core.os, "replace", locked_activation)
+    with pytest.raises(core.BusyInstallConflict):
+        core.swap_into_place(staged_root, install_dir)
+
+    assert (install_dir / "version").read_text() == "old"
+    assert staged_root.is_dir()
+    assert not list(tmp_path.glob(".whisper.cpp.old-*"))
+
+
+# ── Host/GPU token helpers (component-independent core functions) ──
+# Value tables moved verbatim from the llama characterization suite; these are
+# pure functions with no descriptor sensitivity, so they run unparameterized.
+@pytest.mark.parametrize(
+    "value,expected",
+    [
+        ("8.6", "86"),
+        ("07.05", "75"),
+        ("75", "75"),
+        (86, "86"),
+        ("", None),
+        ("  ", None),
+        ("x.y", None),
+        ("8.6.0", None),
+        ("9.0", "90"),
+    ],
+)
+def test_normalize_compute_cap(value, expected):
+    assert core.normalize_compute_cap(value) == expected
+
+
+@pytest.mark.parametrize(
+    "values,expected",
+    [
+        (["8.6", "86", "8.6"], ["86"]),  # deduplication
+        (["9.0", "7.5", "8.6"], ["75", "86", "90"]),  # numeric sort
+        (["8.6", "bad", "", "7.5"], ["75", "86"]),  # drops invalid
+        ([], []),
+    ],
+)
+def test_normalize_compute_caps(values, expected):
+    assert core.normalize_compute_caps(values) == expected
+
+
+@pytest.mark.parametrize(
+    "value,expected",
+    [
+        (None, None),
+        ("", []),
+        ("-1", []),
+        ("0", ["0"]),
+        ("0,1,2", ["0", "1", "2"]),
+        (" 0 , 1 ", ["0", "1"]),
+    ],
+)
+def test_parse_cuda_visible_devices(value, expected):
+    assert core.parse_cuda_visible_devices(value) == expected
+
+
+@pytest.mark.parametrize(
+    "visible,expected",
+    [
+        (["0", "1", "2"], True),
+        (["GPU-abc123"], True),
+        (None, False),
+        ([], False),
+        (["0", "MIG-device"], False),
+    ],
+)
+def test_supports_explicit_visible_device_matching(visible, expected):
+    assert core.supports_explicit_visible_device_matching(visible) is expected
+
+
+_GPU_ROWS = [
+    ("0", "GPU-aaa", "8.6"),
+    ("1", "GPU-bbb", "7.5"),
+    ("2", "GPU-ccc", "8.9"),
+]
+
+
+@pytest.mark.parametrize(
+    "visible,expected_indices",
+    [
+        (None, [0, 1, 2]),  # no filter returns all
+        ([], []),
+        (["0", "2"], [0, 2]),  # filter by index
+        (["gpu-bbb"], [1]),  # UUID match is case insensitive
+        (["0", "0"], [0]),  # same device requested twice is deduplicated
+        (["99"], []),  # unknown token matches nothing
+    ],
+)
+def test_select_visible_gpu_rows(visible, expected_indices):
+    expected = [_GPU_ROWS[i] for i in expected_indices]
+    assert core.select_visible_gpu_rows(_GPU_ROWS, visible) == expected
+
+
+@pytest.mark.parametrize(
+    "driver,expected",
+    [
+        (None, []),
+        ((11, 8), []),
+        ((12, 4), ["cuda12"]),
+        ((13, 0), ["cuda13", "cuda12"]),
+        ((14, 0), ["cuda14", "cuda13", "cuda12"]),  # future major derives lines
+    ],
+)
+def test_compatible_linux_runtime_lines(driver, expected):
+    host = SimpleNamespace(driver_cuda_version = driver)
+    assert core.compatible_linux_runtime_lines(host) == expected
+
+
+@pytest.mark.parametrize(
+    "value,expected",
+    [
+        ("12.6", "cuda12"),
+        ("13.0", "cuda13"),
+        ("11.8", None),
+        (None, None),
+        ("", None),
+    ],
+)
+def test_runtime_line_from_cuda_version(value, expected):
+    assert core.runtime_line_from_cuda_version(value) == expected
+
+
+def _caps_host(caps):
+    return SimpleNamespace(compute_caps = list(caps))
+
+
+def test_host_is_blackwell_includes_datacenter_parts():
+    assert core.host_is_blackwell(_caps_host(["10.0"])) is True  # B200 sm_100
+    assert core.host_is_blackwell(_caps_host(["10.3"])) is True  # B300 sm_103
+    assert core.host_is_blackwell(_caps_host(["12.0"])) is True  # RTX 50 sm_120
+    assert core.host_is_blackwell(_caps_host(["12.1"])) is True  # DGX Spark sm_121
+    assert core.host_is_blackwell(_caps_host(["9.0"])) is False  # Hopper
+    assert core.host_is_blackwell(_caps_host(["8.0"])) is False  # Ampere
+    assert core.host_is_blackwell(_caps_host(["9.0", "10.0"])) is True  # highest cap wins
+
+
+def test_blackwell_min_toolkit_is_sm_aware():
+    # Family floor is 12.8; sm_103/sm_121 (no native target before 12.9) lift it.
+    f = core.blackwell_min_toolkit_for_host
+    assert f(_caps_host(["10.0"])) == (12, 8)  # B200
+    assert f(_caps_host(["12.0"])) == (12, 8)  # RTX 50
+    assert f(_caps_host(["10.3"])) == (12, 9)  # B300
+    assert f(_caps_host(["12.1"])) == (12, 9)  # DGX Spark
+    assert f(_caps_host(["10.0", "10.3"])) == (12, 9)  # max across SMs wins
+
+
+# ── The ops seam ──
+def test_module_ops_prefers_module_globals_over_core_defaults(component):
+    ns = dict(component.namespace)
+    calls = []
+
+    def fake_download_file(url, destination):
+        calls.append(url)
+        destination.write_bytes(b"data")
+
+    ns["download_file"] = fake_download_file
+    ops = core.ModuleOps(ns)
+    assert ops.download_file is fake_download_file
+    # Core defaults still resolve (and come back bound) for everything else.
+    assert callable(ops.fetch_json)
+    with pytest.raises(AttributeError):
+        _ = ops.does_not_exist_anywhere
diff --git a/tests/studio/install/test_rocm_support.py b/tests/studio/install/test_rocm_support.py
index b94578369d..b919206120 100644
--- a/tests/studio/install/test_rocm_support.py
+++ b/tests/studio/install/test_rocm_support.py
@@ -3,9 +3,13 @@
 import importlib.util
 import json
 import os
+import re
+import shutil
 import subprocess
 import sys
+import tempfile
 from pathlib import Path
+from types import SimpleNamespace
 from unittest.mock import MagicMock, mock_open, patch, PropertyMock
 
 import pytest
@@ -228,6 +232,10 @@ UPSTREAM_ASSETS = {
 class TestResolveUpstreamAssetChoice:
     """Verify that the asset selection logic picks the right binary for each platform."""
 
+    # The plain cpu-linux / windows-cpu / macos-arm64 routing cases live in
+    # test_selection_logic.py::TestResolveUpstreamAssetChoice (exact-name pins);
+    # this class keeps the ROCm/NVIDIA-precedence dialect only.
+
     @patch.object(prebuilt_mod, "github_release_assets", return_value = UPSTREAM_ASSETS)
     def test_nvidia_linux_gets_cpu_asset(self, mock_assets):
         """NVIDIA host should NOT hit the ROCm path -- gets CPU asset (CUDA handled elsewhere)."""
@@ -245,30 +253,6 @@ class TestResolveUpstreamAssetChoice:
         assert choice.install_kind == "linux-rocm"
         assert "rocm" in choice.name
 
-    @patch.object(prebuilt_mod, "github_release_assets", return_value = UPSTREAM_ASSETS)
-    def test_cpu_linux_gets_cpu_asset(self, mock_assets):
-        """CPU-only Linux host should get CPU asset."""
-        host = cpu_host()
-        choice = resolve_upstream_asset_choice(host, LLAMA_TAG)
-        assert choice.install_kind == "linux-cpu"
-        assert "ubuntu-x64" in choice.name
-
-    @patch.object(prebuilt_mod, "github_release_assets", return_value = UPSTREAM_ASSETS)
-    def test_macos_arm64_gets_macos_asset(self, mock_assets):
-        """macOS arm64 host should get macOS asset."""
-        host = macos_host()
-        choice = resolve_upstream_asset_choice(host, LLAMA_TAG)
-        assert choice.install_kind == "macos-arm64"
-        assert "macos-arm64" in choice.name
-
-    @patch.object(prebuilt_mod, "github_release_assets", return_value = UPSTREAM_ASSETS)
-    def test_windows_cpu_gets_cpu_asset(self, mock_assets):
-        """Windows CPU-only host should get Windows CPU asset."""
-        host = windows_host()
-        choice = resolve_upstream_asset_choice(host, LLAMA_TAG)
-        assert choice.install_kind == "windows-cpu"
-        assert "win-cpu" in choice.name
-
     @patch.object(prebuilt_mod, "github_release_assets", return_value = UPSTREAM_ASSETS)
     def test_windows_rocm_gets_hip_asset(self, mock_assets):
         """Windows ROCm host should get Windows HIP asset."""
@@ -557,9 +541,13 @@ class TestDetectRocmVersion:
 class TestEnsureRocmTorch:
     """Verify ROCm torch reinstall logic."""
 
+    # _infer_linux_amd_gfx_arch mocked to None: on a real Strix host the live
+    # /proc/cpuinfo would otherwise take the inferred-install path and break
+    # these "must not install" hosts (environment leak, not the code under test).
     @patch.object(stack_mod, "pip_install")
     @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
-    def test_no_rocm_skips(self, mock_nvidia, mock_pip):
+    @patch.object(stack_mod, "_infer_linux_amd_gfx_arch", return_value = None)
+    def test_no_rocm_skips(self, mock_infer, mock_nvidia, mock_pip):
         """No ROCm toolchain should skip entirely."""
         # Pin _detect_windows_gfx_arch to None so a real AMD test host's WMI
         # fallback can't defeat the "no ROCm anywhere" premise.
@@ -569,6 +557,105 @@ class TestEnsureRocmTorch:
                     _ensure_rocm_torch()
         mock_pip.assert_not_called()
 
+    @patch.object(stack_mod, "IS_WINDOWS", False)
+    @patch.object(stack_mod, "pip_install_try", return_value = True)
+    @patch.object(stack_mod, "pip_install")
+    @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
+    @patch.object(stack_mod, "_has_rocm_gpu", return_value = False)
+    @patch.object(stack_mod, "_infer_linux_amd_gfx_arch", return_value = "gfx1151")
+    @patch.object(stack_mod, "_detect_rocm_version", return_value = None)
+    def test_inferred_gfx_without_rocm_runtime_installs_amd_index(
+        self, mock_ver, mock_infer, mock_gpu, mock_nvidia, mock_pip, mock_pip_try
+    ):
+        """Strix Halo without /dev/kfd must still get AMD gfx1151 wheels (unslothai#7301)."""
+        mock_probe = MagicMock()
+        mock_probe.returncode = 0
+        mock_probe.stdout = b"|2.10.0+cpu\n"
+        with patch("os.path.isdir", return_value = True):
+            with patch("subprocess.run", return_value = mock_probe):
+                _ensure_rocm_torch()
+        torch_call = str(mock_pip.call_args_list[0])
+        assert "gfx1151" in torch_call
+        assert "torch>=2.11.0,<2.12.0" in torch_call
+
+    @patch.object(stack_mod, "IS_WINDOWS", False)
+    @patch.object(stack_mod, "pip_install_try", return_value = True)
+    @patch.object(stack_mod, "pip_install")
+    @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
+    @patch.object(stack_mod, "_has_rocm_gpu", return_value = False)
+    @patch.object(stack_mod, "_infer_linux_amd_gfx_arch", return_value = "gfx1151")
+    @patch.object(stack_mod, "_detect_amd_gfx_codes", return_value = [])
+    @patch.object(stack_mod, "_detect_rocm_version", return_value = (7, 1))
+    def test_inferred_gfx_not_overwritten_when_rocm_userland_readable(
+        self, mock_ver, mock_gfx, mock_infer, mock_gpu, mock_nvidia, mock_pip, mock_pip_try
+    ):
+        """Codex P1 #7305: after an inferred per-arch install, do not fall through to the
+        generic pytorch.org/rocmX.Y reinstall just because has_hip_torch is still False.
+        Readable ROCm userland without /dev/kfd is exactly the case that used to overwrite
+        the AMD gfx wheels."""
+        mock_probe = MagicMock()
+        mock_probe.returncode = 0
+        mock_probe.stdout = b"|2.10.0+cpu\n"
+        with patch("os.path.isdir", return_value = True):
+            with patch("subprocess.run", return_value = mock_probe):
+                _ensure_rocm_torch()
+        assert mock_pip.call_count == 1, mock_pip.call_args_list
+        torch_call = str(mock_pip.call_args_list[0])
+        assert "gfx1151" in torch_call
+        assert "rocm7.1" not in torch_call
+        assert "download.pytorch.org" not in torch_call
+
+    @patch.object(stack_mod, "IS_WINDOWS", False)
+    @patch.object(stack_mod, "pip_install_try", return_value = True)
+    @patch.object(stack_mod, "pip_install")
+    @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
+    @patch.object(stack_mod, "_has_rocm_gpu", return_value = True)
+    @patch.object(stack_mod, "_infer_linux_amd_gfx_arch", return_value = "gfx1151")
+    @patch.object(stack_mod, "_detect_amd_gfx_codes", return_value = ["gfx1100"])
+    @patch.object(stack_mod, "_detect_rocm_version", return_value = (7, 1))
+    def test_inference_yields_to_runtime_visible_gpu(
+        self, mock_ver, mock_gfx, mock_infer, mock_gpu, mock_nvidia, mock_pip, mock_pip_try
+    ):
+        """When the runtime CAN enumerate a GPU, the cpuinfo inference must not
+        install wheels: a mixed Strix APU + dGPU box with the dGPU selected would
+        otherwise get gfx1151 wheels for a gfx1100 GPU. The runtime-visible arch
+        (Strix override / generic branch) decides instead."""
+        mock_probe = MagicMock()
+        mock_probe.returncode = 0
+        mock_probe.stdout = b"|2.10.0+cpu\n"
+        with patch("os.path.isdir", return_value = True):
+            with patch("subprocess.run", return_value = mock_probe):
+                _ensure_rocm_torch()
+        all_calls = str(mock_pip.call_args_list) + str(mock_pip_try.call_args_list)
+        assert "gfx1151" not in all_calls, all_calls
+        assert "rocm7.1" in all_calls, all_calls
+
+    @patch.object(stack_mod, "IS_WINDOWS", False)
+    @patch.object(stack_mod, "pip_install_try", return_value = True)
+    @patch.object(stack_mod, "pip_install")
+    @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
+    @patch.object(stack_mod, "_has_rocm_gpu", return_value = True)
+    @patch.object(stack_mod, "_detect_amd_gfx_codes", return_value = [])
+    @patch.object(stack_mod, "_detect_rocm_version", return_value = None)
+    def test_gfx_override_installs_despite_visible_rocm(
+        self, mock_ver, mock_gfx, mock_gpu, mock_nvidia, mock_pip, mock_pip_try
+    ):
+        """#7305 review: an explicit UNSLOTH_ROCM_GFX_ARCH is exempt from the
+        not-_has_rocm_gpu() gate (mirrors install.sh). A visible GPU with an
+        unreadable ROCm version must not silently discard the user's named arch
+        and leave CPU torch in place -- the per-arch install runs."""
+        mock_probe = MagicMock()
+        mock_probe.returncode = 0
+        mock_probe.stdout = b"|2.10.0+cpu\n"
+        with patch.dict(os.environ, {"UNSLOTH_ROCM_GFX_ARCH": "gfx1151"}):
+            with patch("os.path.isdir", return_value = True):
+                with patch("subprocess.run", return_value = mock_probe):
+                    _ensure_rocm_torch()
+        assert mock_pip.call_count == 1, mock_pip.call_args_list
+        torch_call = str(mock_pip.call_args_list[0])
+        assert "gfx1151" in torch_call
+        assert "download.pytorch.org" not in torch_call
+
     @patch.object(stack_mod, "IS_WINDOWS", False)
     @patch.object(stack_mod, "pip_install_try", return_value = True)
     @patch.object(stack_mod, "pip_install")
@@ -680,9 +767,10 @@ class TestEnsureRocmTorch:
     @patch.object(stack_mod, "pip_install")
     @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
     @patch.object(stack_mod, "_has_rocm_gpu", return_value = True)
+    @patch.object(stack_mod, "_infer_linux_amd_gfx_arch", return_value = None)
     @patch.object(stack_mod, "_detect_rocm_version", return_value = None)
     def test_version_unreadable_prints_warning(
-        self, mock_ver, mock_gpu, mock_nvidia, mock_pip, capsys
+        self, mock_ver, mock_infer, mock_gpu, mock_nvidia, mock_pip, capsys
     ):
         """ROCm detected but version unreadable should print warning and skip."""
         with patch("os.path.isdir", return_value = True):
@@ -707,6 +795,27 @@ class TestEnsureRocmTorch:
         torch_call = mock_pip.call_args_list[0]
         assert "rocm7.2" in str(torch_call)
 
+    @patch.object(stack_mod, "IS_WINDOWS", False)
+    @patch.object(stack_mod, "pip_install_try", return_value = True)
+    @patch.object(stack_mod, "pip_install")
+    @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
+    @patch.object(stack_mod, "_has_rocm_gpu", return_value = True)
+    @patch.object(stack_mod, "_detect_rocm_version", return_value = (7, 14))
+    @patch.object(stack_mod, "_detect_amd_gfx_codes", return_value = ["gfx1150"])
+    def test_rocm_714_strix_routes_to_amd_arch_index(
+        self, mock_gfx, mock_ver, mock_gpu, mock_nvidia, mock_pip, mock_pip_try
+    ):
+        """ROCm 7.14 caps to rocm7.2 on pytorch.org; Strix must use AMD gfx index."""
+        mock_probe = MagicMock()
+        mock_probe.returncode = 0
+        mock_probe.stdout = b"7.14.60850|2.11.0+rocm7.2\n"
+        with patch("os.path.isdir", return_value = True):
+            with patch("subprocess.run", return_value = mock_probe):
+                _ensure_rocm_torch()
+        torch_call = str(mock_pip.call_args_list[0])
+        assert "gfx1150" in torch_call
+        assert "torch>=2.11.0,<2.12.0" in torch_call
+
     @patch.object(stack_mod, "IS_WINDOWS", False)
     @patch.object(stack_mod, "pip_install_try", return_value = True)
     @patch.object(stack_mod, "pip_install")
@@ -1018,7 +1127,8 @@ class TestEnsureRocmTorch:
     @patch.object(stack_mod, "pip_install")
     @patch.object(stack_mod, "_has_usable_nvidia_gpu", return_value = False)
     @patch.object(stack_mod, "_has_rocm_gpu", return_value = False)
-    def test_no_gpu_with_rocm_tools_skips(self, mock_gpu, mock_nvidia, mock_pip):
+    @patch.object(stack_mod, "_infer_linux_amd_gfx_arch", return_value = None)
+    def test_no_gpu_with_rocm_tools_skips(self, mock_infer, mock_gpu, mock_nvidia, mock_pip):
         """ROCm tools present but no actual AMD GPU should skip entirely."""
         # Pin the Windows arch probe to None so a real AMD host's WMI fallback
         # can't defeat the "no actual GPU" premise.
@@ -1329,6 +1439,59 @@ class TestInstallShStructure:
         sh_path = PACKAGE_ROOT / "install.sh"
         source = sh_path.read_text(encoding = "utf-8")
         assert "amd-smi" in source
+
+    def test_cpu_index_note_respects_explicit_pin(self):
+        """An explicit UNSLOTH_TORCH_INDEX_URL/_FAMILY CPU pin is a request, not
+        a detection failure: the */cpu wheel note must report the pin instead of
+        claiming ROCm/HIP is unusable, the WSL setup guidance must be skipped,
+        and the gpu summary must not label a pinned AMD host "no usable ROCm"."""
+        sh_path = PACKAGE_ROOT / "install.sh"
+        source = sh_path.read_text(encoding = "utf-8")
+        note = source.find('substep "AMD GPU detected, but no usable ROCm/HIP install')
+        assert note != -1
+        assert (
+            '[ "$_torch_index_pinned" = true ]' in source[note - 400 : note]
+        ), "the */cpu note must check the explicit pin before diagnosing ROCm"
+        assert (
+            '[ "$OS" = "wsl" ] && [ "$_torch_index_pinned" = false ]' in source
+        ), "ROCm-on-WSL guidance is detection advice; skip it for pinned installs"
+        summary = source.find('step "gpu" "AMD GPU (no usable ROCm -- CPU fallback)"')
+        assert summary != -1
+        assert (
+            '[ "$_torch_index_pinned" = true ]' in source[summary - 700 : summary]
+        ), "the gpu summary must not claim no usable ROCm for a pinned index"
+
+    def test_rocm_version_chain_survives_no_source_under_set_e(self):
+        """When every ROCm version source is missing (e.g. rocminfo present but
+        rocm-core not installed, so dpkg-query/rpm exit 1), the _rocm_tag ||
+        chain fails as a whole; without the || guard set -e kills the installer
+        BEFORE the actionable no-version WARN it feeds. Executed, not text."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the version chain")
+        sh_path = PACKAGE_ROOT / "install.sh"
+        source = sh_path.read_text(encoding = "utf-8")
+        chain = re.search(
+            r'^        _rocm_tag=\$\(\{ command -v amd-smi.*?\|\| _rocm_tag=""\n',
+            source,
+            re.S | re.M,
+        )
+        assert chain, "could not extract the guarded _rocm_tag chain"
+        with tempfile.TemporaryDirectory() as d:
+            # Tools exist on PATH but yield nothing usable, like a box with the
+            # probe tools installed and no rocm-core package.
+            for name in ("amd-smi", "hipconfig", "dpkg-query", "rpm"):
+                p = os.path.join(d, name)
+                with open(p, "w", encoding = "utf-8") as f:
+                    f.write("#!/bin/sh\nexit 1\n")
+                os.chmod(p, 0o755)
+            script = (
+                "set -euo pipefail\n" + chain.group(0) + '\nprintf "SURVIVED:%s\\n" "$_rocm_tag"\n'
+            )
+            env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""))
+            r = subprocess.run([shell, "-c", script], env = env, capture_output = True, text = True)
+            assert r.returncode == 0, f"version chain aborted under set -e: {r.stderr}"
+            assert r.stdout.startswith("SURVIVED:"), r.stdout
         assert "rocm" in source.lower()
 
     def test_cuda_precedence(self):
@@ -1460,17 +1623,446 @@ class TestInstallShStructure:
             "4098" in func_body
         ), "_has_amd_rocm_gpu sysfs fallback must require AMD vendor_id 4098 (0x1002)"
 
-    def test_kfd_awk_resets_state_per_file(self):
-        """KFD sysfs awk must reset gpu/amd state per file (FNR==1) to avoid Ryzen+NVIDIA false positives."""
+    def test_kfd_awk_vendor_check_is_per_line(self):
+        """KFD sysfs awk must decide on a single vendor_id line, with no cross-node state.
+
+        The old awk paired two per-node flags (gpu_id + vendor_id) and needed an FNR==1
+        reset so flags from different KFD nodes could not combine into a Ryzen+NVIDIA
+        false positive. gpu_id is a sibling sysfs file and never appears inside
+        properties, so that pairing also never matched at all (every ROCm-less AMD host
+        was reported as no-GPU). The replacement keys on one atomic line: only an AMD
+        GPU node reports `vendor_id 4098` (KFD CPU nodes report 0, NVIDIA's open kernel
+        module registers 4318), so there is no cross-file state left to reset.
+        """
         sh_path = PACKAGE_ROOT / "install.sh"
         source = sh_path.read_text(encoding = "utf-8")
         func_start = source.find("_has_amd_rocm_gpu()")
         func_end = source.find("\n}", func_start)
         func_body = source[func_start:func_end]
-        assert "FNR==1" in func_body, (
-            "_has_amd_rocm_gpu KFD awk must reset state per file with FNR==1 "
-            "to avoid false positives on Ryzen+NVIDIA hosts with multiple KFD nodes"
+        assert "$2 == 4098" in func_body, (
+            "_has_amd_rocm_gpu KFD awk must match `vendor_id 4098` as a single-line "
+            "condition so no per-node state can leak across KFD nodes"
         )
+        assert "/gpu_id/" not in func_body, (
+            "_has_amd_rocm_gpu KFD awk must not key on a gpu_id line: gpu_id is a "
+            "sibling sysfs file, not a line in properties, so it never matches there"
+        )
+
+    def test_setup_sh_kfd_awk_matches_install_sh(self):
+        """setup.sh's KFD fallback must use the same per-line vendor_id check as install.sh.
+
+        setup.sh re-probes AMD detection independently of install.sh; if its copy keeps
+        the dead gpu_id-inside-properties pairing, a host that install.sh routes to ROCm
+        still gets a CPU llama.cpp from the setup step (_setup_amd_detected stays false).
+        """
+        source = (PACKAGE_ROOT / "studio" / "setup.sh").read_text(encoding = "utf-8")
+        assert (
+            "$2 == 4098" in source
+        ), "setup.sh KFD awk must match `vendor_id 4098` as a single-line condition"
+        assert (
+            "/gpu_id/" not in source
+        ), "setup.sh KFD awk must not key on a gpu_id line inside properties"
+
+    def test_kfd_only_torch_falls_back_to_cpu(self):
+        """An AMD host whose gfx arch can't be read (rocminfo/amd-smi missing, or
+        present but not enumerating the GPU) must route torch to CPU, not a generic
+        rocm index: a Strix box (gfx1150/1151) would otherwise get the broken
+        _grouped_mm wheels because the reroute has no gfx to correct it."""
+        source = (PACKAGE_ROOT / "install.sh").read_text(encoding = "utf-8")
+        body = _extract_sh_function_body(source, "get_torch_index_url")
+        probe = body.find("_amd_gfx_probe=$(_probe_amd_gfx_arch)")
+        assert probe >= 0, "get_torch_index_url must probe the gfx arch before picking a rocm index"
+        # The shared probe reads gfx (not just tests binary presence), from rocminfo
+        # AND amd-smi, so an installed-but-not-enumerating probe still falls to CPU.
+        helper = _extract_sh_function_body(source, "_probe_amd_gfx_arch")
+        assert helper, "install.sh must define the shared _probe_amd_gfx_arch helper"
+        assert (
+            "rocminfo 2>/dev/null) | grep -oE 'gfx" in helper
+        ), "probe must read gfx from rocminfo"
+        assert (
+            "amd-smi list 2>/dev/null) | grep -oE 'gfx" in helper
+        ), "probe must read gfx from amd-smi"
+        # The probe clears ROCR/HIP_VISIBLE_DEVICES so a container mask
+        # (ROCR_VISIBLE_DEVICES=-1) can't blind the env-independent KFD detection.
+        assert (
+            "unset ROCR_VISIBLE_DEVICES HIP_VISIBLE_DEVICES" in helper
+        ), "the gfx probe must clear the visibility masks so a mask can't force CPU"
+        cpu_guard = body.find('if [ -z "$_amd_gfx_probe" ]')
+        assert cpu_guard >= 0, "unreadable gfx must fall back to CPU"
+        assert cpu_guard < body.find(
+            "_rocm_tag="
+        ), "the gfx gate must run before the ROCm version/index selection"
+
+    def test_kfd_only_llama_requires_hipcc(self):
+        """setup.sh must forward --has-rocm for a gfx-unknown (KFD-only) host only when
+        hipcc is present. With no gfx the prebuilt resolver finds no ROCm bundle and the
+        source build would fail, so without a HIP toolchain the host keeps the CPU
+        prebuilt rather than breaking the llama.cpp install."""
+        source = (PACKAGE_ROOT / "studio" / "setup.sh").read_text(encoding = "utf-8")
+        idx = source.find("_PREBUILT_CMD+=(--has-rocm)")
+        assert idx >= 0, "setup.sh must still be able to forward --has-rocm"
+        window = source[max(0, idx - 900) : idx]
+        assert (
+            "hipcc" in window
+        ), "the gfx-unknown --has-rocm branch must gate on hipcc (a usable HIP toolchain)"
+        assert (
+            "command -v hipcc" in window or "/opt/rocm/bin/hipcc" in window
+        ), "hipcc presence must be checked via command -v or the rocm bin path"
+        assert (
+            "/opt/rocm-*/bin/hipcc" in window
+        ), "the hipcc gate must also accept a versioned /opt/rocm-*/bin/hipcc toolchain"
+
+    def test_gfx_unknown_guard_honors_override(self):
+        """A user-set UNSLOTH_ROCM_GFX_ARCH must seed the gfx probe before the CPU
+        fallback: an air-gapped/rocminfo-less Strix host that names its arch should
+        still reach a rocm index instead of being forced to CPU."""
+        source = (PACKAGE_ROOT / "install.sh").read_text(encoding = "utf-8")
+        helper = _extract_sh_function_body(source, "_probe_amd_gfx_arch")
+        assert helper, "install.sh must define the shared _probe_amd_gfx_arch helper"
+        seed = helper.find("$(printf")
+        assert seed >= 0, "the gfx probe must seed from UNSLOTH_ROCM_GFX_ARCH"
+        assert "UNSLOTH_ROCM_GFX_ARCH" in helper[seed : seed + 80]
+        assert seed < helper.find(
+            "rocminfo 2>/dev/null) | grep -oE 'gfx"
+        ), "the override must be read before probing rocminfo"
+        body = _extract_sh_function_body(source, "get_torch_index_url")
+        call = body.find("_amd_gfx_probe=$(_probe_amd_gfx_arch)")
+        assert call >= 0, "get_torch_index_url must call the shared probe"
+        assert call < body.find(
+            'if [ -z "$_amd_gfx_probe" ]; then'
+        ), "the probe must run before the CPU fallback guard"
+
+    def test_gfx_override_seeds_reroute_without_tools(self):
+        """The Strix reroute must honour UNSLOTH_ROCM_GFX_ARCH even when rocminfo and
+        amd-smi are absent, so a manual override reaches the arch index; with no
+        override and no tools it must stay empty (no false Strix routing)."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the probe block")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        block = re.search(
+            r'^        _gfx_all=\$\(printf[^\n]*\n.*?(?=^        _strix_gfx="")',
+            source,
+            re.S | re.M,
+        )
+        assert block, "could not extract the gfx-detection block"
+        with tempfile.TemporaryDirectory() as d:
+            # Shim rocminfo/amd-smi to enumerate nothing, so only the override can
+            # supply a gfx (keeps coreutils on PATH for tr/grep/printf).
+            for name in ("rocminfo", "amd-smi"):
+                p = os.path.join(d, name)
+                with open(p, "w", encoding = "utf-8") as f:
+                    f.write("#!/bin/sh\nexit 0\n")
+                os.chmod(p, 0o755)
+            script = (
+                'set -euo pipefail\nHIP_VISIBLE_DEVICES=""\nROCR_VISIBLE_DEVICES=""\n'
+                + block.group(0)
+                + '\nprintf "OK:%s\\n" "$_gfx_all"\n'
+            )
+
+            def run(**extra):
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""), **extra)
+                return subprocess.run(
+                    [shell, "-c", script], env = env, capture_output = True, text = True
+                )
+
+            r = run(UNSLOTH_ROCM_GFX_ARCH = "GFX1151")
+            assert r.returncode == 0, f"override probe aborted: {r.stderr}"
+            assert "OK:gfx1151" in r.stdout, f"override not honoured/lowercased: {r.stdout!r}"
+            r2 = run()
+            assert r2.returncode == 0, f"empty probe aborted: {r2.stderr}"
+            assert (
+                "OK:\n" in r2.stdout or r2.stdout.strip() == "OK:"
+            ), f"no override + no tools must leave gfx empty: {r2.stdout!r}"
+
+    def test_gfx_probe_ignores_visibility_mask(self):
+        """A container visibility mask (ROCR_VISIBLE_DEVICES=-1) must not blind the
+        gfx probe: rocminfo honours the mask and would enumerate nothing, but KFD
+        detection is env-independent, so the probe clears the mask and still reads
+        the arch (else a masked host is wrongly forced to CPU)."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the probe block")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        probe_fn = _extract_sh_function_body(source, "_probe_amd_gfx_arch")
+        assert probe_fn, "could not extract _probe_amd_gfx_arch"
+        with tempfile.TemporaryDirectory() as d:
+            # rocminfo that mimics ROCR_VISIBLE_DEVICES=-1 hiding all agents.
+            with open(os.path.join(d, "rocminfo"), "w", encoding = "utf-8") as f:
+                f.write(
+                    "#!/bin/sh\n"
+                    'if [ "${ROCR_VISIBLE_DEVICES:-}" = "-1" ]; then echo "no agents"; exit 0; fi\n'
+                    'echo "  Name:  gfx1151"\n'
+                )
+            os.chmod(os.path.join(d, "rocminfo"), 0o755)
+            script = (
+                "set -euo pipefail\n"
+                "_ensure_rocm_probe_env() { :; }\n"
+                + probe_fn
+                + '\n_amd_gfx_probe=$(_probe_amd_gfx_arch)\nprintf "OK:%s\\n" "$_amd_gfx_probe"\n'
+            )
+
+            def run(**extra):
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""), **extra)
+                return subprocess.run(
+                    [shell, "-c", script], env = env, capture_output = True, text = True
+                )
+
+            r = run(ROCR_VISIBLE_DEVICES = "-1")
+            assert r.returncode == 0, f"masked probe aborted: {r.stderr}"
+            assert (
+                "OK:gfx1151" in r.stdout
+            ), f"a visibility mask must not blind the gfx probe: {r.stdout!r}"
+
+    def test_kfd_only_inferable_gfx_defers_to_reroute(self):
+        """A KFD-only host (GPU detected, gfx unreadable) whose arch IS inferable
+        from hardware IDs must not print the 'installing CPU-only PyTorch' warning:
+        get_torch_index_url returns the cpu index quietly and the runtime-less
+        reroute upgrades it to AMD per-arch wheels. Only when inference also fails
+        (or maps to no supported family) is CPU final, with the actionable hint."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute get_torch_index_url")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        fn = _extract_sh_function_body(source, "get_torch_index_url")
+        probe_fn = _extract_sh_function_body(source, "_probe_amd_gfx_arch")
+        family_fn = _extract_sh_function_body(source, "_amd_arch_index_family_for_gfx")
+        assert fn and probe_fn and family_fn
+        with tempfile.TemporaryDirectory() as d:
+            # uname -> Linux/x86_64 so the AMD branch runs on any dev host; the
+            # rocminfo/amd-smi shims enumerate nothing (KFD-only host).
+            with open(os.path.join(d, "uname"), "w", encoding = "utf-8", newline = "\n") as f:
+                f.write('#!/bin/sh\ncase "${1:-}" in -m) echo x86_64 ;; *) echo Linux ;; esac\n')
+            for name in ("rocminfo", "amd-smi"):
+                with open(os.path.join(d, name), "w", encoding = "utf-8", newline = "\n") as f:
+                    f.write("#!/bin/sh\nexit 0\n")
+            for name in ("uname", "rocminfo", "amd-smi"):
+                os.chmod(os.path.join(d, name), 0o755)
+
+            def run(infer_stub):
+                script = (
+                    "set -euo pipefail\n"
+                    "_ensure_rocm_probe_env() { :; }\n"
+                    "_trim_index_path_slashes() { printf '%s\\n' \"$1\"; }\n"
+                    "_has_usable_nvidia_gpu() { return 1; }\n"
+                    "_has_amd_rocm_gpu() { return 0; }\n"
+                    + infer_stub
+                    + "\n"
+                    + probe_fn
+                    + "\n"
+                    + family_fn
+                    + "\n"
+                    + fn
+                    + "\n"
+                    "get_torch_index_url\n"
+                )
+                # Run from a file, not -c: Windows bash mangles multi-KB -c strings.
+                sp = os.path.join(d, "gtiu.sh")
+                with open(sp, "w", encoding = "utf-8", newline = "\n") as f:
+                    f.write(script)
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""))
+                for var in (
+                    "UNSLOTH_ROCM_GFX_ARCH",
+                    "UNSLOTH_TORCH_INDEX_URL",
+                    "UNSLOTH_TORCH_INDEX_FAMILY",
+                    "UNSLOTH_PYTORCH_MIRROR",
+                    "ROCR_VISIBLE_DEVICES",
+                    "HIP_VISIBLE_DEVICES",
+                ):
+                    env.pop(var, None)
+                return subprocess.run(
+                    [shell, sp.replace("\\", "/")], env = env, capture_output = True, text = True
+                )
+
+            r = run("_infer_linux_amd_gfx_arch() { echo gfx1100; }")
+            assert r.returncode == 0, f"inferable case aborted: {r.stderr}"
+            assert r.stdout.strip().endswith(
+                "/cpu"
+            ), f"must hand */cpu to the reroute: {r.stdout!r}"
+            assert (
+                "inferring gfx1100" in r.stderr
+            ), f"must announce the inference handoff: {r.stderr!r}"
+            assert (
+                "installing CPU-only PyTorch" not in r.stderr
+            ), f"must not promise a CPU-only install the reroute will override: {r.stderr!r}"
+            r2 = run("_infer_linux_amd_gfx_arch() { return 1; }")
+            assert r2.returncode == 0, f"uninferable case aborted: {r2.stderr}"
+            assert r2.stdout.strip().endswith("/cpu")
+            assert (
+                "installing CPU-only PyTorch" in r2.stderr
+            ), f"uninferable gfx must keep the actionable CPU warning: {r2.stderr!r}"
+            r3 = run("_infer_linux_amd_gfx_arch() { echo gfx906; }")
+            assert r3.returncode == 0, f"unsupported-family case aborted: {r3.stderr}"
+            assert r3.stdout.strip().endswith("/cpu")
+            assert (
+                "installing CPU-only PyTorch" in r3.stderr
+            ), f"an inferred arch with no wheel family must keep the CPU warning: {r3.stderr!r}"
+
+    def test_no_version_cpu_warning_respects_gfx_override(self):
+        """With UNSLOTH_ROCM_GFX_ARCH set on a KFD-only host that has no ROCm
+        version sources, the gfx probe is seeded by the override, so the
+        no-version endpoint used to print 'falling back to CPU-only PyTorch'
+        even though the reroute then installs the per-arch wheels (Codex P3).
+        A supported override must defer; an unsupported override, or a
+        readable-gfx host without an override, keeps the CPU warning."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute get_torch_index_url")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        fn = _extract_sh_function_body(source, "get_torch_index_url")
+        probe_fn = _extract_sh_function_body(source, "_probe_amd_gfx_arch")
+        family_fn = _extract_sh_function_body(source, "_amd_arch_index_family_for_gfx")
+        assert fn and probe_fn and family_fn
+        with tempfile.TemporaryDirectory() as d:
+            with open(os.path.join(d, "uname"), "w", encoding = "utf-8", newline = "\n") as f:
+                f.write('#!/bin/sh\ncase "${1:-}" in -m) echo x86_64 ;; *) echo Linux ;; esac\n')
+            # Silence every ROCm version source, not just amd-smi: a dev box with
+            # a real hipconfig/dpkg would otherwise resolve a version and skip
+            # the no-version endpoint this test exercises.
+            with open(os.path.join(d, "amd-smi"), "w", encoding = "utf-8", newline = "\n") as f:
+                f.write("#!/bin/sh\nexit 0\n")
+            for name in ("hipconfig", "dpkg-query", "rpm"):
+                with open(os.path.join(d, name), "w", encoding = "utf-8", newline = "\n") as f:
+                    f.write("#!/bin/sh\nexit 1\n")
+            for name in ("uname", "amd-smi", "hipconfig", "dpkg-query", "rpm"):
+                os.chmod(os.path.join(d, name), 0o755)
+            script = (
+                "set -euo pipefail\n"
+                "_ensure_rocm_probe_env() { :; }\n"
+                "_trim_index_path_slashes() { printf '%s\\n' \"$1\"; }\n"
+                "_has_usable_nvidia_gpu() { return 1; }\n"
+                "_has_amd_rocm_gpu() { return 0; }\n"
+                "_infer_linux_amd_gfx_arch() { return 1; }\n"
+                + probe_fn
+                + "\n"
+                + family_fn
+                + "\n"
+                + fn
+                + "\n"
+                "get_torch_index_url\n"
+            )
+            sp = os.path.join(d, "gtiu.sh")
+            with open(sp, "w", encoding = "utf-8", newline = "\n") as f:
+                f.write(script)
+
+            def run(rocminfo_body, **extra):
+                with open(os.path.join(d, "rocminfo"), "w", encoding = "utf-8", newline = "\n") as f:
+                    f.write("#!/bin/sh\n" + rocminfo_body)
+                os.chmod(os.path.join(d, "rocminfo"), 0o755)
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""), **extra)
+                for var in (
+                    "UNSLOTH_TORCH_INDEX_URL",
+                    "UNSLOTH_TORCH_INDEX_FAMILY",
+                    "UNSLOTH_PYTORCH_MIRROR",
+                    "ROCR_VISIBLE_DEVICES",
+                    "HIP_VISIBLE_DEVICES",
+                ):
+                    env.pop(var, None)
+                if "UNSLOTH_ROCM_GFX_ARCH" not in extra:
+                    env.pop("UNSLOTH_ROCM_GFX_ARCH", None)
+                return subprocess.run(
+                    [shell, sp.replace("\\", "/")], env = env, capture_output = True, text = True
+                )
+
+            # Supported override on a tool-blind host: defer to the reroute.
+            r = run("exit 0\n", UNSLOTH_ROCM_GFX_ARCH = "gfx1151")
+            assert r.returncode == 0, f"override case aborted: {r.stderr}"
+            assert r.stdout.strip().endswith("/cpu")
+            assert (
+                "falling back to CPU-only PyTorch" not in r.stderr
+            ), f"a supported override must not get the false CPU warning: {r.stderr!r}"
+            assert (
+                "UNSLOTH_ROCM_GFX_ARCH=gfx1151 is set" in r.stderr
+            ), f"the override deferral must be announced: {r.stderr!r}"
+            # Unsupported override: the reroute can't map it -> CPU warning stays.
+            r2 = run("exit 0\n", UNSLOTH_ROCM_GFX_ARCH = "gfx906")
+            assert r2.returncode == 0, f"unsupported-override case aborted: {r2.stderr}"
+            assert (
+                "falling back to CPU-only PyTorch" in r2.stderr
+            ), f"an unmappable override must keep the CPU warning: {r2.stderr!r}"
+            # Readable gfx, no override, no version: deliberate CPU fallback.
+            r3 = run('echo "  Name:  gfx1151"\n')
+            assert r3.returncode == 0, f"readable-gfx case aborted: {r3.stderr}"
+            assert (
+                "falling back to CPU-only PyTorch" in r3.stderr
+            ), f"a readable-gfx host without a version keeps the CPU warning: {r3.stderr!r}"
+
+    def test_reroute_gate_covers_kfd_only(self):
+        """The runtime-less reroute must fire for a KFD-only host: _has_amd_rocm_gpu
+        is now true via the KFD topology, so the gate also accepts a detected GPU
+        whose gfx probe is empty (unslothai#7314 P2). A */cpu index chosen with a
+        READABLE gfx (deliberate ROCm-version fallback) must stay un-rerouted."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the reroute block")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        block = re.search(
+            r'^if \[ "\$_torch_index_pinned" = false \] && \[ "\$SKIP_TORCH" = false \] && \\\n'
+            r".*?^fi\n",
+            source,
+            re.S | re.M,
+        )
+        assert block, "could not extract the runtime-less reroute block"
+        family_fn = _extract_sh_function_body(source, "_amd_arch_index_family_for_gfx")
+        assert family_fn
+        with tempfile.TemporaryDirectory() as d:
+            with open(os.path.join(d, "uname"), "w", encoding = "utf-8", newline = "\n") as f:
+                f.write('#!/bin/sh\ncase "${1:-}" in -m) echo x86_64 ;; *) echo Linux ;; esac\n')
+            os.chmod(os.path.join(d, "uname"), 0o755)
+
+            def run(gpu_stub, probe_stub):
+                script = (
+                    "set -euo pipefail\n"
+                    "_has_usable_nvidia_gpu() { return 1; }\n"
+                    f"_has_amd_rocm_gpu() {{ {gpu_stub}; }}\n"
+                    f"_probe_amd_gfx_arch() {{ {probe_stub}; }}\n"
+                    "_infer_linux_amd_gfx_arch() { echo gfx1100; }\n"
+                    "_strip_index_url_credentials() { printf '%s\\n' \"$1\"; }\n" + family_fn + "\n"
+                    "_torch_index_pinned=false\nSKIP_TORCH=false\n_ARCH=x86_64\n"
+                    "TORCH_INDEX_URL=https://download.pytorch.org/whl/cpu\n"
+                    + block.group(0)
+                    + 'printf "URL:%s GFX:%s\\n" "$TORCH_INDEX_URL" "${UNSLOTH_ROCM_GFX_ARCH:-}"\n'
+                )
+                # Run from a file, not -c: Windows bash mangles multi-KB -c strings.
+                sp = os.path.join(d, "reroute.sh")
+                with open(sp, "w", encoding = "utf-8", newline = "\n") as f:
+                    f.write(script)
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""))
+                for var in ("UNSLOTH_ROCM_GFX_ARCH", "UNSLOTH_AMD_ROCM_MIRROR"):
+                    env.pop(var, None)
+                return subprocess.run(
+                    [shell, sp.replace("\\", "/")], env = env, capture_output = True, text = True
+                )
+
+            # KFD-only: GPU detected, probe empty -> reroute to per-arch wheels.
+            r = run("return 0", "printf '\\n'")
+            assert r.returncode == 0, f"kfd-only reroute aborted: {r.stderr}"
+            assert (
+                "URL:https://repo.amd.com/rocm/whl/gfx110X-all/ GFX:gfx1100" in r.stdout
+            ), f"KFD-only host must reach the AMD arch index: {r.stdout!r}"
+            # The diagnostic must not claim /dev/kfd is missing: KFD visibility is
+            # exactly what detected this host (Codex P3).
+            assert (
+                "ROCm runtime not visible" not in r.stderr
+            ), f"KFD-only reroute must not claim /dev/kfd is missing: {r.stderr!r}"
+            assert (
+                "visible via the kernel driver (KFD)" in r.stderr
+            ), f"KFD-only reroute must name the tooling gap: {r.stderr!r}"
+            # Readable gfx: the */cpu index is a deliberate fallback -> untouched.
+            r2 = run("return 0", "echo gfx1151")
+            assert r2.returncode == 0, f"readable-gfx case aborted: {r2.stderr}"
+            assert (
+                "URL:https://download.pytorch.org/whl/cpu GFX:" in r2.stdout
+            ), f"a deliberate CPU fallback must not be rerouted: {r2.stdout!r}"
+            # No AMD GPU detected at all: the pre-KFD-fix path still reroutes.
+            r3 = run("return 1", "printf '\\n'")
+            assert r3.returncode == 0, f"undetected-GPU case aborted: {r3.stderr}"
+            assert (
+                "URL:https://repo.amd.com/rocm/whl/gfx110X-all/ GFX:gfx1100" in r3.stdout
+            ), f"the original undetected-GPU reroute must keep working: {r3.stdout!r}"
+            assert (
+                "ROCm runtime not visible" in r3.stderr
+            ), f"a truly runtime-invisible host keeps the original diagnostic: {r3.stderr!r}"
 
     def test_get_torch_index_url_uses_nvidia_detected_flag(self):
         """get_torch_index_url must track NVIDIA via _nvidia_detected (proc-only NVIDIA still picks CUDA)."""
@@ -1557,7 +2149,7 @@ class TestWorkerRocmMambaSsm:
         assert "getattr(torch.version, 'hip', None)" in source
 
     def test_direct_wheel_url_returns_none_without_cuda_major(self, monkeypatch):
-        """_direct_wheel_url should return None when cuda_major is empty (ROCm)."""
+        """direct_wheel_url should return None when cuda_major is empty (ROCm)."""
         _worker_spec = importlib.util.spec_from_file_location("test_worker", _WORKER_PATH)
         assert _worker_spec is not None and _worker_spec.loader is not None
         worker_mod = importlib.util.module_from_spec(_worker_spec)
@@ -1583,7 +2175,7 @@ class TestWorkerRocmMambaSsm:
             "hip_version": "7.1.12345",
             "cxx11abi": "TRUE",
         }
-        result = worker_mod._direct_wheel_url(
+        result = worker_mod.direct_wheel_url(
             filename_prefix = "causal_conv1d",
             package_version = "1.6.1",
             release_tag = "v1.6.1.post4",
@@ -2098,6 +2690,7 @@ class TestGfxArchNameFallback:
         "name, expected",
         [
             ("AMD Radeon(TM) 8060S Graphics", "gfx1151"),
+            ("AMD Radeon(TM) 8065S Graphics", "gfx1151"),
             ("AMD Ryzen AI MAX+ 395 w/ Radeon 8060S", "gfx1151"),
             ("AMD Radeon(TM) 890M", "gfx1150"),
             ("AMD Ryzen AI 9 HX 370 w/ Radeon 890M", "gfx1150"),
@@ -3165,6 +3758,286 @@ _SETUP_SH_PATH = PACKAGE_ROOT / "studio" / "setup.sh"
 class TestStrixRocm71Override:
     """install.sh routes gfx1151/gfx1150 to AMD's arch index instead of ROCm 7.1 (_grouped_mm segfault)."""
 
+    def test_linux_gfx_inference_helpers_present(self):
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        assert "_infer_linux_amd_gfx_arch" in source
+        assert "_amd_arch_index_family_for_gfx" in source
+        assert "_amd_gpu_present_via_pci" in source
+        assert "unslothai#7301" in source
+
+    def test_infer_linux_amd_gfx_from_cpuinfo(self):
+        assert stack_mod._linux_amd_gfx_from_cpuinfo is not None
+        with patch.object(
+            Path,
+            "read_text",
+            return_value = "model name : AMD Ryzen AI Max+ 395 w/ Radeon 8060S\n",
+        ):
+            assert stack_mod._linux_amd_gfx_from_cpuinfo() == "gfx1151"
+        # 8065S (Gorgon Halo) must match on the Radeon name alone, even without the
+        # "Ryzen AI Max" branding (mirrors setup.sh / setup.ps1 which list 8065S).
+        with patch.object(Path, "read_text", return_value = "model name : AMD Radeon 8065S\n"):
+            assert stack_mod._linux_amd_gfx_from_cpuinfo() == "gfx1151"
+
+    def test_infer_gfx_gated_out_of_wsl_without_runtime(self):
+        """On WSL the cpuinfo/lspci inference must be skipped unless the WSL ROCDXG
+        runtime (librocdxg) is present: a bare `unsloth studio update` must not
+        install per-arch ROCm wheels into an env that still can't expose the GPU.
+        An explicit UNSLOTH_ROCM_GFX_ARCH override stays authoritative regardless."""
+        m = stack_mod
+        with (
+            patch.object(m, "_linux_amd_gfx_from_cpuinfo", return_value = "gfx1151"),
+            patch.object(m, "_linux_amd_gfx_from_lspci", return_value = None),
+            # PCI evidence present (the WSL branch never consults it anyway).
+            patch.object(m, "_linux_amd_display_device_present", return_value = True),
+            patch.dict(os.environ, {"UNSLOTH_ROCM_GFX_ARCH": ""}),
+        ):
+            # WSL + no runtime -> inference suppressed (CPU torch stays).
+            with (
+                patch.object(m, "_is_wsl", return_value = True),
+                patch.object(m, "_wsl_rocm_runtime_present", return_value = False),
+            ):
+                assert m._infer_linux_amd_gfx_arch() is None
+            # WSL + runtime present (this dev box) -> inference still runs.
+            with (
+                patch.object(m, "_is_wsl", return_value = True),
+                patch.object(m, "_wsl_rocm_runtime_present", return_value = True),
+            ):
+                assert m._infer_linux_amd_gfx_arch() == "gfx1151"
+            # Native Linux (not WSL) -> the gate never applies.
+            with (
+                patch.object(m, "_is_wsl", return_value = False),
+                patch.object(m, "_wsl_rocm_runtime_present", return_value = False),
+            ):
+                assert m._infer_linux_amd_gfx_arch() == "gfx1151"
+        # Explicit override wins even on a bare WSL box (no runtime).
+        with (
+            patch.object(m, "_is_wsl", return_value = True),
+            patch.object(m, "_wsl_rocm_runtime_present", return_value = False),
+            patch.dict(os.environ, {"UNSLOTH_ROCM_GFX_ARCH": "gfx1151"}),
+        ):
+            assert m._infer_linux_amd_gfx_arch() == "gfx1151"
+
+    def test_infer_gfx_requires_amd_display_device_on_native_linux(self):
+        """A VM/container on a Strix host still shows the host CPU model in
+        /proc/cpuinfo while receiving no AMD GPU, so on native Linux the
+        CPU-model inference must require an AMD PCI display device (#7305
+        review). WSL is exempt (no PCI enumeration there; the librocdxg gate is
+        the evidence) and the explicit override stays authoritative."""
+        m = stack_mod
+        with (
+            patch.object(m, "_linux_amd_gfx_from_cpuinfo", return_value = "gfx1151"),
+            patch.object(m, "_linux_amd_gfx_from_lspci", return_value = None),
+            patch.object(m, "_is_wsl", return_value = False),
+            patch.dict(os.environ, {"UNSLOTH_ROCM_GFX_ARCH": ""}),
+        ):
+            # No AMD display device -> the CPU-model text alone must not infer.
+            with patch.object(m, "_linux_amd_display_device_present", return_value = False):
+                assert m._infer_linux_amd_gfx_arch() is None
+            # Device present -> inference unchanged.
+            with patch.object(m, "_linux_amd_display_device_present", return_value = True):
+                assert m._infer_linux_amd_gfx_arch() == "gfx1151"
+        # Explicit override needs no device evidence (headless/cross-install).
+        with (
+            patch.object(m, "_is_wsl", return_value = False),
+            patch.object(m, "_linux_amd_display_device_present", return_value = False),
+            patch.dict(os.environ, {"UNSLOTH_ROCM_GFX_ARCH": "GFX1151"}),
+        ):
+            assert m._infer_linux_amd_gfx_arch() == "gfx1151"
+
+    def test_install_sh_cpuinfo_inference_requires_pci_evidence(self):
+        """install.sh mirror of the VM/container guard: both cpuinfo greps must be
+        gated on _gpu_evidence (AMD PCI display device via _amd_gpu_present_via_pci,
+        or the WSL librocdxg gate), and the gate must sit before the first grep."""
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        body = _extract_sh_function_body(source, "_infer_linux_amd_gfx_arch")
+        assert body, "could not extract _infer_linux_amd_gfx_arch"
+        pci = body.find("_amd_gpu_present_via_pci")
+        infer = body.find("grep -qiE 'Ryzen AI Max")
+        assert pci >= 0 and infer >= 0
+        assert pci < infer, "the PCI evidence check must run before the cpuinfo inference"
+        assert (
+            body.count('[ -n "$_gpu_evidence" ] && grep -qiE') == 2
+        ), "both cpuinfo greps (gfx1151 and gfx1150) must be gated on _gpu_evidence"
+
+    def test_lspci_scan_covers_all_display_controllers(self):
+        """The lspci fallback must scan every display-class line, not just the
+        first: a non-AMD controller (Intel iGPU, ASPEED BMC) often enumerates
+        before the AMD dGPU. Non-AMD vendors must never map (an NVIDIA GeForce
+        GTX 860M would otherwise hit the AMD 860M pattern), and a 0000: PCI
+        domain prefix must not break matching."""
+        m = stack_mod
+
+        def fake_lspci(stdout):
+            result = SimpleNamespace(returncode = 0, stdout = stdout)
+            return (
+                patch.object(m.shutil, "which", return_value = "/usr/bin/lspci"),
+                patch.object(m.subprocess, "run", return_value = result),
+            )
+
+        intel_then_amd = (
+            "00:02.0 VGA compatible controller [0300]: Intel Corporation Raptor Lake-S GT1 [8086:a780]\n"
+            "03:00.0 VGA compatible controller [0300]: Advanced Micro Devices, Inc. [AMD/ATI]"
+            " Navi 31 [Radeon RX 7900 XT] [1002:744c]\n"
+        )
+        nvidia_only = "01:00.0 3D controller [0302]: NVIDIA Corporation GM107M [GeForce GTX 860M] [10de:1392]\n"
+        domain_prefixed = (
+            "0000:c5:00.0 VGA compatible controller [0300]: Advanced Micro Devices, Inc. [AMD/ATI]"
+            " Strix Halo [Radeon Graphics / Radeon 8060S] [1002:150e]\n"
+        )
+        unmapped_then_mapped = (
+            "03:00.0 Display controller [0380]: Advanced Micro Devices, Inc. [AMD/ATI]"
+            " Cape Verde [FirePro W600] [1002:6821]\n"
+            "04:00.0 VGA compatible controller [0300]: Advanced Micro Devices, Inc. [AMD/ATI]"
+            " Navi 33 [Radeon RX 7600] [1002:7480]\n"
+        )
+        for stdout, expected in (
+            (intel_then_amd, "gfx1100"),
+            (nvidia_only, None),
+            (domain_prefixed, "gfx1151"),
+            (unmapped_then_mapped, "gfx1102"),
+        ):
+            w, r = fake_lspci(stdout)
+            with w, r:
+                assert m._linux_amd_gfx_from_lspci() == expected, stdout
+
+    def test_install_sh_lspci_scan_covers_all_display_controllers(self):
+        """install.sh mirror of the scan-all behaviour, executed with a shimmed
+        lspci: Intel-first still finds the AMD dGPU, NVIDIA-only maps nothing
+        (860M collision), a domain-prefixed AMD line still maps."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the probe block")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        name_fn = re.search(
+            r"^_infer_amd_gfx_arch_from_gpu_name\(\) \{\n.*?\n\}\n", source, re.S | re.M
+        )
+        scan = re.search(
+            r"^    if command -v lspci[^\n]*\n.*?\nEOF\n    fi\n    return 1\n", source, re.S | re.M
+        )
+        assert name_fn and scan, "could not extract the lspci scan block"
+        cases = (
+            (
+                "00:02.0 VGA compatible controller [0300]: Intel Corporation UHD [8086:a780]\n"
+                "03:00.0 VGA compatible controller [0300]: Advanced Micro Devices, Inc. [AMD/ATI]"
+                " Navi 31 [Radeon RX 7900 XT] [1002:744c]",
+                "OK:gfx1100",
+            ),
+            (
+                "01:00.0 3D controller [0302]: NVIDIA Corporation GM107M [GeForce GTX 860M] [10de:1392]",
+                "OK:",
+            ),
+            (
+                "0000:c5:00.0 VGA compatible controller [0300]: Advanced Micro Devices, Inc."
+                " [AMD/ATI] Strix Halo [Radeon 8060S] [1002:150e]",
+                "OK:gfx1151",
+            ),
+        )
+        for lspci_out, expected in cases:
+            with tempfile.TemporaryDirectory() as d:
+                p = os.path.join(d, "lspci")
+                with open(p, "w", encoding = "utf-8") as f:
+                    f.write(f'#!/bin/sh\ncat <<"EOT"\n{lspci_out}\nEOT\n')
+                os.chmod(p, 0o755)
+                script = (
+                    "set -euo pipefail\n"
+                    + name_fn.group(0)
+                    + "probe() {\n"
+                    + scan.group(0)
+                    + "}\nprintf 'OK:%s\\n' \"$(probe || true)\"\n"
+                )
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""))
+                r = subprocess.run([shell, "-c", script], env = env, capture_output = True, text = True)
+                assert r.returncode == 0, f"scan aborted: {r.stderr}"
+                assert (
+                    r.stdout.splitlines()[-1] == expected
+                ), f"lspci scan wrong for {lspci_out!r}: {r.stdout!r}"
+
+    def test_install_sh_infer_gfx_gated_on_wsl_runtime(self):
+        """install.sh's _infer_linux_amd_gfx_arch must, like the Python side, skip
+        the cpuinfo/lspci inference on WSL unless librocdxg is present -- the
+        override still returns first, so it stays authoritative."""
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        body = _extract_sh_function_body(source, "_infer_linux_amd_gfx_arch")
+        assert body, "could not extract _infer_linux_amd_gfx_arch"
+        override = body.find("UNSLOTH_ROCM_GFX_ARCH")
+        dxg = body.find("/dev/dxg")
+        rocdxg = body.find("librocdxg")
+        # Anchor on the first cpuinfo *inference* (the grep), not a comment mention.
+        infer = body.find("grep -qiE 'Ryzen AI Max")
+        assert override >= 0 and dxg >= 0 and rocdxg >= 0 and infer >= 0
+        assert "microsoft" in body, "WSL gate must also detect WSL via /proc/version"
+        assert override < dxg, "the explicit override must return before the WSL gate"
+        assert (
+            dxg < infer and rocdxg < infer
+        ), "the WSL/librocdxg gate must run before the cpuinfo/lspci inference"
+
+    def test_install_sh_reroute_is_x86_64_only(self):
+        """The Linux inferred-gfx reroute must be x86_64-only: ROCm torch wheels are
+        not published for arm64, so an inferred/overridden gfx must not push an
+        arm64 host to the AMD arch index (get_torch_index_url returns CPU there)."""
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        idx = source.find("_linux_inferred_gfx=$(_infer_linux_amd_gfx_arch")
+        assert idx >= 0, "reroute consumer not found"
+        window = source[max(0, idx - 400) : idx]
+        assert (
+            'case "$_ARCH" in x86_64|amd64)' in window
+        ), "the inferred-gfx reroute must guard on x86_64|amd64 arch"
+
+    def test_install_sh_reroute_skips_visible_rocm_gpu(self):
+        """A */cpu index on a host whose AMD GPU IS visible to the ROCm probes is a
+        deliberate fallback (unsupported/unreadable ROCm version, warned about in
+        get_torch_index_url), not a missing runtime: the reroute must not override
+        it with inferred per-arch wheels. The explicit UNSLOTH_ROCM_GFX_ARCH
+        override must still win either way."""
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        idx = source.find("_linux_inferred_gfx=$(_infer_linux_amd_gfx_arch")
+        assert idx >= 0, "reroute consumer not found"
+        window = source[max(0, idx - 700) : idx]
+        assert (
+            "! _has_amd_rocm_gpu" in window
+        ), "the reroute must be gated on _has_amd_rocm_gpu being false"
+        assert (
+            '[ -n "${UNSLOTH_ROCM_GFX_ARCH:-}" ] || ! _has_amd_rocm_gpu' in window
+        ), "an explicit UNSLOTH_ROCM_GFX_ARCH override must bypass the visible-GPU gate"
+
+    def test_install_sh_reroute_exports_gfx_for_setup_sh(self):
+        """The inferred arch must be exported as UNSLOTH_ROCM_GFX_ARCH so the
+        downstream setup.sh run (which re-probes ROCm independently and finds
+        nothing on these runtime-less hosts) routes llama.cpp to the matching
+        ROCm prebuilt instead of the CPU one -- setup.sh and
+        install_llama_prebuilt.py both read that env var."""
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        assign = source.find('TORCH_INDEX_URL="${_amd_mirror}/${_amd_family}/"')
+        assert assign >= 0, "inferred-gfx index assignment not found"
+        block_end = source.find("esac", assign)
+        assert (
+            'export UNSLOTH_ROCM_GFX_ARCH="$_linux_inferred_gfx"' in source[assign:block_end]
+        ), "the reroute must export the inferred gfx for the setup.sh handoff"
+        # setup.sh's side of the handoff must still exist.
+        setup_source = (PACKAGE_ROOT / "studio" / "setup.sh").read_text(encoding = "utf-8")
+        assert "UNSLOTH_ROCM_GFX_ARCH" in setup_source
+
+    def test_amd_arch_index_url_linux_honors_amd_mirror(self):
+        """On Linux the inferred-gfx repair must honour UNSLOTH_AMD_ROCM_MIRROR (the
+        var install.sh uses), not the Windows mirror var, so a mirrored/air-gapped
+        Linux install does not silently fall back to repo.amd.com. Windows still
+        delegates to the Windows mirror path."""
+        m = stack_mod
+        with (
+            patch.object(m, "IS_WINDOWS", False),
+            patch.dict(os.environ, {"UNSLOTH_AMD_ROCM_MIRROR": "https://mirror.local/rocm"}),
+        ):
+            assert m._amd_arch_index_url("gfx1151") == "https://mirror.local/rocm/gfx1151/"
+        with (
+            patch.object(m, "IS_WINDOWS", False),
+            patch.dict(os.environ, {"UNSLOTH_AMD_ROCM_MIRROR": ""}),
+        ):
+            assert m._amd_arch_index_url("gfx1151") == "https://repo.amd.com/rocm/whl/gfx1151/"
+            assert m._amd_arch_index_url("gfx9999") is None
+        # Windows path is unchanged: delegate to the Windows mirror helper.
+        with patch.object(m, "IS_WINDOWS", True):
+            assert m._amd_arch_index_url("gfx1151") == m._windows_rocm_index_url("gfx1151")
+
     def test_strix_gfx_detection_in_install_sh(self):
         """install.sh must detect gfx1151 and gfx1150 for the override."""
         source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
@@ -3191,13 +4064,136 @@ class TestStrixRocm71Override:
         source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
         assert "moe_utils" in source or "_grouped_mm" in source
 
-    def test_strix_override_only_fires_on_rocm71(self):
-        """install.sh must scope the Strix override to rocm7.1 only (not rocm7.2+)."""
+    def test_strix_override_scoped_below_arch_floor(self):
+        """Strix reroute must fire for rocm leaves BELOW the arch floor (7.13) and
+        NOT at/above it. Executed via _rocm_leaf_below so it verifies the actual
+        version comparison, not a text match that a comment could satisfy."""
         source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
-        strix_idx = source.find("_strix_gfx")
-        assert strix_idx != -1
-        context_before = source[max(0, strix_idx - 2400) : strix_idx]
-        assert "rocm7.1" in context_before
+        # Selector + gate must switch on the index LEAF, not the whole URL (a mirror
+        # base path with its own rocm token would false-positive otherwise).
+        assert 'case "$_torch_index_leaf" in' in source
+        assert '_rocm_leaf_below "$_torch_index_leaf" 7 13' in source
+        shell = shutil.which("sh") or shutil.which("bash")
+        if not shell:
+            pytest.skip("no POSIX shell to execute _rocm_leaf_below")
+        match = re.search(r"^_rocm_leaf_below\(\) \{.*?^\}", source, re.S | re.M)
+        assert match, "could not extract _rocm_leaf_below from install.sh"
+        fn = match.group(0)
+
+        def below(leaf):
+            return (
+                subprocess.run(
+                    [shell, "-c", f'{fn}\n_rocm_leaf_below "$1" 7 13', "_", leaf]
+                ).returncode
+                == 0
+            )
+
+        for leaf in ("rocm6.0", "rocm7.0", "rocm7.1", "rocm7.2", "rocm7.12"):
+            assert below(leaf), f"{leaf} must reroute (below arch floor 7.13)"
+        for leaf in ("rocm7.13", "rocm7.14", "rocm8.0", "gfx1151", "cu128", "cpu"):
+            assert not below(leaf), f"{leaf} must NOT reroute (>= floor or non-rocm)"
+
+    def test_gfx_probe_survives_no_match_under_set_e(self):
+        """A gfx probe whose grep finds no match must not abort install.sh under
+        set -euo pipefail before the amd-smi fallback runs. The reroute case now
+        matches every rocm* index, so this would break ordinary 6.x/7.2 installs
+        with a flaky rocminfo. Executed with shimmed tools, not a text match."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the probe block")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        block = re.search(
+            r'^        _gfx_all=\$\(printf[^\n]*\n.*?(?=^        _strix_gfx="")',
+            source,
+            re.S | re.M,
+        )
+        assert block, "could not extract the gfx-detection block"
+        with tempfile.TemporaryDirectory() as d:
+            # rocminfo emits no gfx token; amd-smi supplies gfx1151 (the fallback)
+            for name, out in (("rocminfo", "no gpu here"), ("amd-smi", "GPU: gfx1151")):
+                p = os.path.join(d, name)
+                with open(p, "w", encoding = "utf-8") as f:
+                    f.write(f'#!/bin/sh\ncat <<"EOT"\n{out}\nEOT\n')
+                os.chmod(p, 0o755)
+            script = (
+                'set -euo pipefail\nHIP_VISIBLE_DEVICES=""\nROCR_VISIBLE_DEVICES=""\n'
+                + block.group(0)
+                + '\nprintf "OK:%s\\n" "$_gfx_all"\n'
+            )
+            env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""))
+            r = subprocess.run([shell, "-c", script], env = env, capture_output = True, text = True)
+            assert r.returncode == 0, f"probe aborted under set -e: {r.stderr}"
+            assert "OK:gfx1151" in r.stdout, f"amd-smi fallback not reached: {r.stdout!r}"
+
+    def test_strix_reroute_reprobes_when_mask_hides_all(self):
+        """A visibility mask hiding every agent (ROCR_VISIBLE_DEVICES=-1) must not
+        skip the Strix reroute: get_torch_index_url reads the arch unmasked, so
+        the reroute must re-probe unmasked too or a masked Strix box gets the
+        broken generic wheels. A partial mask must keep its per-GPU selection.
+        Executed with mask-honouring shims, not a text match."""
+        shell = shutil.which("bash")
+        if not shell:
+            pytest.skip("bash needed to execute the probe block")
+        source = _INSTALL_SH_PATH.read_text(encoding = "utf-8")
+        block = re.search(
+            r'^        _gfx_all=\$\(printf[^\n]*\n.*?(?=^        _strix_gfx="")',
+            source,
+            re.S | re.M,
+        )
+        assert block, "could not extract the gfx-detection block"
+        with tempfile.TemporaryDirectory() as d:
+            # rocminfo honours ROCR_VISIBLE_DEVICES like the real tool: -1 and
+            # set-but-empty hide both agents, 1 renumbers to the dGPU only,
+            # unset shows both.
+            rocminfo = (
+                "#!/bin/sh\n"
+                'case "${ROCR_VISIBLE_DEVICES-__unset__}" in\n'
+                '  __unset__) printf "Name: gfx1151\\nName: gfx1201\\n" ;;\n'
+                '  ""|-1) echo "no visible agents" ;;\n'
+                '  1) printf "Name: gfx1201\\n" ;;\n'
+                '  *) printf "Name: gfx1151\\nName: gfx1201\\n" ;;\n'
+                "esac\n"
+            )
+            for name, body in (("rocminfo", rocminfo), ("amd-smi", "#!/bin/sh\nexit 0\n")):
+                p = os.path.join(d, name)
+                with open(p, "w", encoding = "utf-8") as f:
+                    f.write(body)
+                os.chmod(p, 0o755)
+            script = (
+                "set -euo pipefail\n" + block.group(0) + '\nprintf "OK:%s\\n" "$_runtime_gfx"\n'
+            )
+
+            def run(**extra):
+                env = dict(os.environ, PATH = d + os.pathsep + os.environ.get("PATH", ""), **extra)
+                env.pop("UNSLOTH_ROCM_GFX_ARCH", None)
+                env.pop("HIP_VISIBLE_DEVICES", None)
+                return subprocess.run(
+                    [shell, "-c", script], env = env, capture_output = True, text = True
+                )
+
+            # Mask hides everything: re-probe must recover the first GPU (Strix).
+            r = run(ROCR_VISIBLE_DEVICES = "-1")
+            assert r.returncode == 0, f"masked probe aborted: {r.stderr}"
+            assert "OK:gfx1151" in r.stdout, f"reroute blinded by full mask: {r.stdout!r}"
+            # A SET-but-empty mask also hides every agent and must re-probe too
+            # (the ${VAR+x} guard, not ${VAR:-}).
+            r0 = run(ROCR_VISIBLE_DEVICES = "")
+            assert r0.returncode == 0, f"empty-mask probe aborted: {r0.stderr}"
+            assert "OK:gfx1151" in r0.stdout, f"reroute blinded by empty mask: {r0.stdout!r}"
+            # Partial mask: enumeration already reflects it; the dGPU selection
+            # must survive (no unmasked re-probe overriding the user's pick).
+            r2 = run(ROCR_VISIBLE_DEVICES = "1")
+            assert r2.returncode == 0, f"partial-mask probe aborted: {r2.stderr}"
+            assert "OK:gfx1201" in r2.stdout, f"partial mask selection lost: {r2.stdout!r}"
+
+    def test_strix_routing_helpers_cover_rocm714(self):
+        # Reroute for any generic pytorch.org index below the 7.13 arch floor (7.0,
+        # 7.2, a future 7.3+), never at/above it -- mirrors install.sh _rocm_leaf_below.
+        assert stack_mod._generic_pytorch_rocm_tag((7, 14)) == "rocm7.2"
+        assert stack_mod._strix_needs_amd_arch_index((7, 14)) is True
+        assert stack_mod._strix_needs_amd_arch_index((7, 0)) is True
+        assert stack_mod._strix_needs_amd_arch_index((6, 0)) is True
+        assert stack_mod._strix_needs_amd_arch_index((5, 0)) is False
 
     def test_torch_constraint_updated_for_strix_amd_index(self):
         """install.sh must set TORCH_CONSTRAINT>=2.11 when routing Strix to AMD index."""
diff --git a/tests/studio/install/test_selection_logic.py b/tests/studio/install/test_selection_logic.py
index e372a3bbeb..8ebcd6cc86 100644
--- a/tests/studio/install/test_selection_logic.py
+++ b/tests/studio/install/test_selection_logic.py
@@ -31,17 +31,8 @@ PrebuiltFallback = INSTALL_LLAMA_PREBUILT.PrebuiltFallback
 LinuxCudaSelection = INSTALL_LLAMA_PREBUILT.LinuxCudaSelection
 UPSTREAM_REPO = INSTALL_LLAMA_PREBUILT.UPSTREAM_REPO
 
-normalize_compute_cap = INSTALL_LLAMA_PREBUILT.normalize_compute_cap
-normalize_compute_caps = INSTALL_LLAMA_PREBUILT.normalize_compute_caps
-parse_cuda_visible_devices = INSTALL_LLAMA_PREBUILT.parse_cuda_visible_devices
-supports_explicit_visible_device_matching = (
-    INSTALL_LLAMA_PREBUILT.supports_explicit_visible_device_matching
-)
-select_visible_gpu_rows = INSTALL_LLAMA_PREBUILT.select_visible_gpu_rows
-compatible_linux_runtime_lines = INSTALL_LLAMA_PREBUILT.compatible_linux_runtime_lines
 pick_windows_cuda_runtime = INSTALL_LLAMA_PREBUILT.pick_windows_cuda_runtime
 compatible_windows_runtime_lines = INSTALL_LLAMA_PREBUILT.compatible_windows_runtime_lines
-runtime_line_from_cuda_version = INSTALL_LLAMA_PREBUILT.runtime_line_from_cuda_version
 apply_approved_hashes = INSTALL_LLAMA_PREBUILT.apply_approved_hashes
 linux_cuda_choice_from_release = INSTALL_LLAMA_PREBUILT.linux_cuda_choice_from_release
 windows_cuda_attempts = INSTALL_LLAMA_PREBUILT.windows_cuda_attempts
@@ -452,165 +443,25 @@ class TestStudioLocalhostIpv6Warning:
 
 
 # ===========================================================================
-# A. normalize_compute_cap
+# A-F, H. Component-independent GPU/token helpers: the behavior tables live in
+# tests/studio/install/test_prebuilt_core.py (they are pure prebuilt_core
+# functions). This pin proves the installer still re-exports them from core, so
+# the master tables keep covering the names this module and its callers use.
 # ===========================================================================
 
 
-class TestNormalizeComputeCap:
-    def test_dotted_86(self):
-        assert normalize_compute_cap("8.6") == "86"
-
-    def test_dotted_leading_zero(self):
-        assert normalize_compute_cap("07.05") == "75"
-
-    def test_already_normalized(self):
-        assert normalize_compute_cap("75") == "75"
-
-    def test_int_input(self):
-        assert normalize_compute_cap(86) == "86"
-
-    def test_empty_string(self):
-        assert normalize_compute_cap("") is None
-
-    def test_whitespace(self):
-        assert normalize_compute_cap("  ") is None
-
-    def test_non_numeric(self):
-        assert normalize_compute_cap("x.y") is None
-
-    def test_triple_part(self):
-        assert normalize_compute_cap("8.6.0") is None
-
-    def test_zero_minor(self):
-        assert normalize_compute_cap("9.0") == "90"
-
-
-# ===========================================================================
-# B. normalize_compute_caps
-# ===========================================================================
-
-
-class TestNormalizeComputeCaps:
-    def test_deduplication(self):
-        assert normalize_compute_caps(["8.6", "86", "8.6"]) == ["86"]
-
-    def test_numeric_sort(self):
-        assert normalize_compute_caps(["9.0", "7.5", "8.6"]) == ["75", "86", "90"]
-
-    def test_drops_invalid(self):
-        assert normalize_compute_caps(["8.6", "bad", "", "7.5"]) == ["75", "86"]
-
-    def test_empty_input(self):
-        assert normalize_compute_caps([]) == []
-
-
-# ===========================================================================
-# C. parse_cuda_visible_devices
-# ===========================================================================
-
-
-class TestParseCudaVisibleDevices:
-    def test_none(self):
-        assert parse_cuda_visible_devices(None) is None
-
-    def test_empty(self):
-        assert parse_cuda_visible_devices("") == []
-
-    def test_minus_one(self):
-        assert parse_cuda_visible_devices("-1") == []
-
-    def test_single(self):
-        assert parse_cuda_visible_devices("0") == ["0"]
-
-    def test_multi(self):
-        assert parse_cuda_visible_devices("0,1,2") == ["0", "1", "2"]
-
-    def test_whitespace_stripped(self):
-        assert parse_cuda_visible_devices(" 0 , 1 ") == ["0", "1"]
-
-
-# ===========================================================================
-# D. supports_explicit_visible_device_matching
-# ===========================================================================
-
-
-class TestSupportsExplicitVisibleDeviceMatching:
-    def test_all_digits(self):
-        assert supports_explicit_visible_device_matching(["0", "1", "2"]) is True
-
-    def test_gpu_prefix(self):
-        assert supports_explicit_visible_device_matching(["GPU-abc123"]) is True
-
-    def test_none(self):
-        assert supports_explicit_visible_device_matching(None) is False
-
-    def test_empty(self):
-        assert supports_explicit_visible_device_matching([]) is False
-
-    def test_mixed_invalid(self):
-        assert supports_explicit_visible_device_matching(["0", "MIG-device"]) is False
-
-
-# ===========================================================================
-# E. select_visible_gpu_rows
-# ===========================================================================
-
-
-class TestSelectVisibleGpuRows:
-    ROWS = [
-        ("0", "GPU-aaa", "8.6"),
-        ("1", "GPU-bbb", "7.5"),
-        ("2", "GPU-ccc", "8.9"),
-    ]
-
-    def test_none_returns_all(self):
-        assert select_visible_gpu_rows(self.ROWS, None) == list(self.ROWS)
-
-    def test_empty_returns_empty(self):
-        assert select_visible_gpu_rows(self.ROWS, []) == []
-
-    def test_filter_by_index(self):
-        result = select_visible_gpu_rows(self.ROWS, ["0", "2"])
-        assert result == [("0", "GPU-aaa", "8.6"), ("2", "GPU-ccc", "8.9")]
-
-    def test_filter_by_uuid_case_insensitive(self):
-        result = select_visible_gpu_rows(self.ROWS, ["gpu-bbb"])
-        assert result == [("1", "GPU-bbb", "7.5")]
-
-    def test_dedup_same_device(self):
-        result = select_visible_gpu_rows(self.ROWS, ["0", "0"])
-        assert result == [("0", "GPU-aaa", "8.6")]
-
-    def test_missing_token(self):
-        result = select_visible_gpu_rows(self.ROWS, ["99"])
-        assert result == []
-
-
-# ===========================================================================
-# F. compatible_linux_runtime_lines
-# ===========================================================================
-
-
-class TestCompatibleLinuxRuntimeLines:
-    def test_no_driver(self):
-        host = make_host(driver_cuda_version = None)
-        assert compatible_linux_runtime_lines(host) == []
-
-    def test_driver_11_8(self):
-        host = make_host(driver_cuda_version = (11, 8))
-        assert compatible_linux_runtime_lines(host) == []
-
-    def test_driver_12_4(self):
-        host = make_host(driver_cuda_version = (12, 4))
-        assert compatible_linux_runtime_lines(host) == ["cuda12"]
-
-    def test_driver_13_0(self):
-        host = make_host(driver_cuda_version = (13, 0))
-        assert compatible_linux_runtime_lines(host) == ["cuda13", "cuda12"]
-
-    def test_future_major_derives_lines(self):
-        host = make_host(driver_cuda_version = (14, 0))
-        assert compatible_linux_runtime_lines(host) == ["cuda14", "cuda13", "cuda12"]
+def test_core_helper_aliases_bound_to_prebuilt_core():
+    import prebuilt_core as _core
+    for name in (
+        "normalize_compute_cap",
+        "normalize_compute_caps",
+        "parse_cuda_visible_devices",
+        "supports_explicit_visible_device_matching",
+        "select_visible_gpu_rows",
+        "compatible_linux_runtime_lines",
+        "runtime_line_from_cuda_version",
+    ):
+        assert getattr(INSTALL_LLAMA_PREBUILT, name) is getattr(_core, name), name
 
 
 # ===========================================================================
@@ -669,28 +520,6 @@ class TestCompatibleWindowsRuntimeLines:
         assert compatible_windows_runtime_lines(host) == ["cuda14", "cuda13", "cuda12"]
 
 
-# ===========================================================================
-# H. runtime_line_from_cuda_version
-# ===========================================================================
-
-
-class TestRuntimeLineFromCudaVersion:
-    def test_cuda_12(self):
-        assert runtime_line_from_cuda_version("12.6") == "cuda12"
-
-    def test_cuda_13(self):
-        assert runtime_line_from_cuda_version("13.0") == "cuda13"
-
-    def test_cuda_11(self):
-        assert runtime_line_from_cuda_version("11.8") is None
-
-    def test_none(self):
-        assert runtime_line_from_cuda_version(None) is None
-
-    def test_empty(self):
-        assert runtime_line_from_cuda_version("") is None
-
-
 # ===========================================================================
 # I. apply_approved_hashes
 # ===========================================================================
diff --git a/tests/studio/install/test_setup_whisper_status.py b/tests/studio/install/test_setup_whisper_status.py
new file mode 100644
index 0000000000..fd3bd82507
--- /dev/null
+++ b/tests/studio/install/test_setup_whisper_status.py
@@ -0,0 +1,29 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+"""Contract checks for actionable whisper prebuilt setup outcomes."""
+
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parents[3]
+
+
+def test_shell_setup_distinguishes_release_skew_from_install_failure():
+    script = (ROOT / "studio" / "setup.sh").read_text(encoding = "utf-8")
+    assert 'if [ "$_WHISPER_STATUS" -eq 2 ]' in script
+    assert "installed llama.cpp ${_WHISPER_INSTALLED_TAG:-unknown}" in script
+    assert "whisper requires ${_WHISPER_REQUIRED_TAG:-unknown}" in script
+    assert "prebuilt install failed" in script
+    assert "retry setup or inspect verbose output" in script
+    assert "curated whisper.cpp dictation is unavailable" in script
+    assert "browser and Transformers dictation remain available" in script
+
+
+def test_powershell_setup_distinguishes_release_skew_from_install_failure():
+    script = (ROOT / "studio" / "setup.ps1").read_text(encoding = "utf-8")
+    assert "elseif ($whisperExit -eq 2)" in script
+    assert "installed llama.cpp $installedWhisperLlamaTag" in script
+    assert "whisper requires $requiredWhisperLlamaTag" in script
+    assert "prebuilt install failed" in script
+    assert "retry setup or inspect verbose output" in script
+    assert "curated whisper.cpp dictation is unavailable" in script
+    assert "browser and Transformers dictation remain available" in script
diff --git a/tests/studio/playwright_chat_ui.py b/tests/studio/playwright_chat_ui.py
index b00b45f97a..a06e559100 100644
--- a/tests/studio/playwright_chat_ui.py
+++ b/tests/studio/playwright_chat_ui.py
@@ -821,10 +821,16 @@ with sync_playwright() as p:
     last_assistant = page.locator('[data-role="assistant"]').last
     last_assistant.hover()
     page.wait_for_timeout(400)
-    regen_btn = page.get_by_role(
-        "button",
-        name = re.compile(r"(reload|regenerate)", re.I),
-    ).first
+    # Exclude disabled controls: the picker's new disabled "Reload model"
+    # button also matches and sorts first, so .first would target it.
+    regen_btn = (
+        page.get_by_role(
+            "button",
+            name = re.compile(r"(reload|regenerate)", re.I),
+        )
+        .and_(page.locator("button:not([disabled])"))
+        .first
+    )
     if regen_btn.count() > 0:
         regen_btn.click()
         try:
@@ -930,6 +936,70 @@ with sync_playwright() as p:
             page.keyboard.press("Escape")
         page.wait_for_timeout(300)
 
+    def read_chat_typography():
+        """Read message typography after a user-driven theme transition."""
+        return robust_evaluate(
+            page,
+            """() => {
+                const root = document.documentElement;
+                const assistant = Array.from(
+                    document.querySelectorAll('.aui-assistant-message-root')
+                );
+                const user = Array.from(
+                    document.querySelectorAll('.aui-user-message-root')
+                );
+                if (assistant.length === 0 || user.length === 0) {
+                    return { error: 'chat message roots are missing' };
+                }
+                const ua = navigator.userAgent.toLowerCase();
+                const role = (nodes) => {
+                    const styles = nodes.map((node) => getComputedStyle(node));
+                    return {
+                        fontWeight: [...new Set(styles.map((style) => style.fontWeight))],
+                        letterSpacing: [...new Set(styles.map((style) => style.letterSpacing))],
+                    };
+                };
+                return {
+                    actualRenderLinux: root.classList.contains('render-linux'),
+                    isDesktopLinux: ua.includes('linux') && !ua.includes('android'),
+                    isDark: root.classList.contains('dark'),
+                    usesBaselineTypography: (
+                        root.classList.contains('no-font-smoothing') ||
+                        root.hasAttribute('data-chat-font') ||
+                        root.hasAttribute('data-ui-font')
+                    ),
+                    assistant: role(assistant),
+                    user: role(user),
+                };
+            }""",
+        )
+
+    def assert_chat_typography(label, typography):
+        if typography.get("error"):
+            fail(typography["error"])
+        if typography["actualRenderLinux"] != typography["isDesktopLinux"]:
+            fail(f"desktop Linux detection mismatch: {typography!r}")
+        is_dark = typography["isDark"]
+        expected_spacing = "0.31px" if is_dark else "0.155px"
+        if typography["isDesktopLinux"] and not typography["usesBaselineTypography"]:
+            expected_weight = "350" if is_dark else "390"
+            if is_dark:
+                expected_spacing = "0.3565px"
+        else:
+            expected_weight = "410"
+        for role in ("assistant", "user"):
+            actual = typography[role]
+            if actual["fontWeight"] != [expected_weight]:
+                fail(
+                    f"chat font weight {label}/{role}: expected {expected_weight}, "
+                    f"got {actual['fontWeight']!r}"
+                )
+            if actual["letterSpacing"] != [expected_spacing]:
+                fail(
+                    f"chat letter spacing {label}/{role}: expected {expected_spacing}, "
+                    f"got {actual['letterSpacing']!r}"
+                )
+
     # ─────────────────────────────────────────────────────
     # 9. Theme toggle -- multiple cycles + computed-bg-color check
     # (light is near-white >240; dark is near-black <40).
@@ -938,6 +1008,7 @@ with sync_playwright() as p:
     if acct.count() > 0:
         step("theme toggle x3 with computed-color assertion")
         observed = []
+        typography_states = []
         for cycle in range(3):
             # Wait for any prior dropdown to fully detach: clicking while
             # the view-transition is still open no-ops silently. The
@@ -1026,6 +1097,9 @@ with sync_playwright() as p:
             }""",
             )
             observed.append(bg)
+            typography = read_chat_typography()
+            assert_chat_typography(f"theme-cycle-{cycle + 1}", typography)
+            typography_states.append(typography)
             shoot(f"10-theme-cycle-{cycle + 1}")
             info(f"  cycle {cycle + 1}: dark={bg['isDark']} body bg={bg['bg']!r}")
         # Across cycles we should see both a near-white (light) and a
@@ -1048,6 +1122,20 @@ with sync_playwright() as p:
                 "(toggle may not flip on this runner's color-scheme)"
             )
 
+        # These are user-driven theme transitions, not synthetic class
+        # changes. A completed three-cycle toggle must expose both typography
+        # states before we check the Linux selector.
+        if len(typography_states) != 3:
+            soft_fail(
+                f"chat typography observed {len(typography_states)} theme state(s), expected 3"
+            )
+        elif {state["isDark"] for state in typography_states} != {False, True}:
+            soft_fail(f"chat typography did not observe both themes: {typography_states!r}")
+        else:
+            info("OK chat typography platform and theme behavior")
+    else:
+        soft_fail("chat typography requires the account-menu theme control")
+
     # ─────────────────────────────────────────────────────
     # 10. Sidebar nav: New Chat, Compare, Search, Recipes.
     # ─────────────────────────────────────────────────────
diff --git a/tests/studio/playwright_extra_ui.py b/tests/studio/playwright_extra_ui.py
index dde6c5d635..0da028a28c 100644
--- a/tests/studio/playwright_extra_ui.py
+++ b/tests/studio/playwright_extra_ui.py
@@ -482,6 +482,14 @@ with sync_playwright() as p:
     step("Settings dialog: cycle through tabs")
     page.goto(f"{BASE}/chat")
     composer.wait_for(state = "visible", timeout = 60_000)
+    dictate = page.get_by_role("button", name = "Dictate").first
+    if dictate.count() == 0:
+        fail("Chat Dictate button not found")
+    elif dictate.get_attribute("type") != "button":
+        fail("Chat Dictate control must use type=button, not submit the composer")
+    else:
+        info("OK Chat Dictate control is type=button")
+
     page.keyboard.press("Control+,")
     page.wait_for_timeout(800)
     settings = page.get_by_role("dialog").first
@@ -501,6 +509,7 @@ with sync_playwright() as p:
             "Appearance",
             "Chat",
             "Developer",
+            "Voice",
             "About",
         )
         seen_tabs = []
@@ -528,6 +537,39 @@ with sync_playwright() as p:
                     soft_fail(f"Settings tab '{tab_name}' body suspiciously short: {body_text}")
             except Exception as exc:
                 soft_fail(f"Settings tab '{tab_name}' click failed: {exc!r}")
+        step("Voice model picker: real mouse-wheel scrolling")
+        voice_tab = page.get_by_role(
+            "button", name = re.compile(r"^\s*Voice(?:\s+New)?\s*$", re.I)
+        ).first
+        if voice_tab.count() == 0:
+            fail("Voice settings tab not found")
+        else:
+            voice_tab.click()
+            page.get_by_label("Dictation engine").click()
+            page.get_by_role("option", name = "Local transcription").click()
+            page.get_by_label("Speech recognition model").click()
+            page.get_by_placeholder("Search model").fill("whisper")
+            results = page.get_by_test_id("stt-model-results")
+            try:
+                page.wait_for_function(
+                    """() => {
+                        const node = document.querySelector('[data-testid="stt-model-results"]');
+                        return !!node && node.scrollHeight > node.clientHeight;
+                    }""",
+                    timeout = 30_000,
+                )
+                results.hover()
+                page.mouse.wheel(0, 700)
+                page.wait_for_function(
+                    """() => {
+                        const node = document.querySelector('[data-testid="stt-model-results"]');
+                        return !!node && node.scrollTop > 0;
+                    }""",
+                    timeout = 5_000,
+                )
+                info("OK Voice model picker mouse wheel changed scrollTop")
+            except Exception as exc:
+                fail(f"Voice model picker did not wheel-scroll: {exc!r}")
         shoot("10-settings-tabs-visited")
         page.keyboard.press("Escape")
         page.wait_for_timeout(300)
diff --git a/tests/studio/playwright_model_config.py b/tests/studio/playwright_model_config.py
new file mode 100644
index 0000000000..a8d143a253
--- /dev/null
+++ b/tests/studio/playwright_model_config.py
@@ -0,0 +1,740 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Model-picker per-model-config Playwright regression test (GPU-free, CPU gemma).
+
+Guards, end to end against the real frontend, the exact regressions that got the
+predecessor PR reverted:
+
+  - Context Length persists: set a distinctive per-model Context Length + tick
+    "Remember for this model" + Load; the value reaches the /api/inference/load
+    request (max_seq_length) AND lands in localStorage (unsloth_model_configs),
+    and survives a full browser reload (HARD).
+  - Reset clears: after customizing, Reset must clear the stored override, never
+    pin the context to a fixed number (the "Reset pins context" regression) (HARD).
+  - Hidden infra models absent: the RAG embedder (bge-small-en-v1.5) and the
+    llama.cpp validation probe (stories260K) never appear in the picker. The
+    probe GGUF is primed into the HF cache by the CI job, so "absent" proves
+    "hidden", not "not downloaded" (HARD).
+  - Legacy migration is idempotent: a pre-feature unsloth_load_settings store
+    migrates once into the versioned unsloth_model_configs map with the value
+    preserved, and a second reload with a fresh legacy seed present does not
+    re-migrate, duplicate, or clobber (gates under STUDIO_UI_STRICT via soft_fail).
+  - Advanced settings persist: KV cache dtype / tensor-parallel toggled under
+    Advanced + Remember land in unsloth_model_configs (best-effort).
+
+Runs as a plain script (not via pytest), mirroring tests/studio/playwright_extra_ui.py:
+accumulate failures in `_failed`, exit non-zero if any HARD gate failed. With
+STUDIO_UI_STRICT=1 (as CI sets), soft_fail also gates; genuinely-optional checks
+use runtime_warn so they never flake the merge gate.
+"""
+
+import json
+import re
+import sys
+import os
+import time
+from pathlib import Path
+
+from playwright.sync_api import sync_playwright
+
+# Run as a plain script (not via pytest), so prepend the dir to sys.path.
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from _playwright_robust import (  # noqa: E402
+    chromium_launch_args,
+    click_and_wait_for_response,
+    evaluate_fetch,
+    install_view_transition_killer,
+    install_wall_clock_watchdog,
+    is_benign_page_error,
+    recover_or_replace_page,
+    robust_evaluate,
+    wait_for_health,
+)
+
+BASE = os.environ["BASE_URL"]
+NEW = os.environ.get("STUDIO_NEW_PW", "ModelCfg-NEW-2026!")
+# Attach mode: log into an already-provisioned Studio with an existing password
+# instead of the first-boot change-password dance. CI leaves STUDIO_LOGIN_PW unset
+# to exercise the real change-password flow; local runs can set it to skip re-provisioning.
+LOGIN_PW = os.environ.get("STUDIO_LOGIN_PW")
+LOGIN_USER = os.environ.get("STUDIO_LOGIN_USER", "unsloth")
+GGUF_REPO = os.environ.get("GGUF_REPO", "unsloth/gemma-3-270m-it-GGUF")
+GGUF_VARIANT = os.environ.get("GGUF_VARIANT", "UD-Q4_K_XL")
+# Substring of the On Device picker row for the loaded model.
+MODEL_HINT = os.environ.get("STUDIO_MODEL_HINT", "gemma-3-270m")
+# A distinctive valid (>=128, multiple of 128, below the model's 32768 ceiling)
+# Context Length, clearly not a default, so persistence is unambiguous.
+DISTINCT_CTX = int(os.environ.get("STUDIO_DISTINCT_CTX", "4096"))
+ART_DIR = os.environ.get("PW_ART_DIR", "logs/playwright_modelcfg")
+ART = Path(ART_DIR)
+ART.mkdir(parents = True, exist_ok = True)
+STRICT = os.environ.get("STUDIO_UI_STRICT", "0") == "1"
+TURN_TIMEOUT_MS = int(os.environ.get("STUDIO_UI_TURN_TIMEOUT_MS", "180000"))
+WALL_TIMEOUT_S = float(os.environ.get("STUDIO_UI_WALL_TIMEOUT_S", "720"))
+FETCH_TIMEOUT_MS = int(os.environ.get("STUDIO_UI_FETCH_TIMEOUT_MS", "30000"))
+LOAD_FETCH_TIMEOUT_MS = int(os.environ.get("STUDIO_UI_LOAD_TIMEOUT_MS", "180000"))
+
+_n = [0]
+_failed: list[str] = []
+
+
+def step(s: str) -> None:
+    print(f"[ui-modelcfg] STEP {s}", flush = True)
+
+
+def info(s: str) -> None:
+    print(f"[ui-modelcfg] {s}", flush = True)
+
+
+def fail(m: str) -> None:
+    print(f"[ui-modelcfg] FAIL: {m}", flush = True)
+    _failed.append(m)
+
+
+def soft_fail(m: str) -> None:
+    if STRICT:
+        fail(m)
+    else:
+        info(f"WARN (strict-off): {m}")
+
+
+def runtime_warn(m: str) -> None:
+    """Warn about a genuinely-optional check that STRICT does not gate."""
+    info(f"WARN (runtime): {m}")
+
+
+def _count(loc) -> int:
+    try:
+        return loc.count()
+    except Exception:
+        return 0
+
+
+def _as_int(value) -> int | None:
+    """Parse an input value to int, tolerating commas/whitespace. Comparisons
+    must be numeric, never substring: '40960' (a model's native default) would
+    spuriously "contain" '4096'."""
+    if value is None:
+        return None
+    try:
+        return int(str(value).replace(",", "").strip())
+    except Exception:
+        return None
+
+
+def _login_token_via_api(base: str, user: str, pw: str) -> str:
+    """POST /api/auth/login -> access_token (attach-mode helper, stdlib only)."""
+    import urllib.request
+
+    req = urllib.request.Request(
+        f"{base}/api/auth/login",
+        data = json.dumps({"username": user, "password": pw}).encode(),
+        headers = {"Content-Type": "application/json"},
+        method = "POST",
+    )
+    with urllib.request.urlopen(req, timeout = 15) as r:
+        return json.loads(r.read().decode())["access_token"]
+
+
+with sync_playwright() as p:
+    _watchdog = install_wall_clock_watchdog(
+        WALL_TIMEOUT_S,
+        label = "ui-modelcfg",
+        info = info,
+    )
+    # Health pre-flight: bash-side health wait can pass before the auth DB migrates.
+    wait_for_health(BASE, timeout = 30.0, info = info)
+    browser = p.chromium.launch(
+        headless = True,
+        args = chromium_launch_args(),
+    )
+    ctx = browser.new_context(
+        viewport = {"width": 1280, "height": 900},
+        reduced_motion = "reduce",
+    )
+    install_view_transition_killer(ctx)
+    page = ctx.new_page()
+    page.set_default_timeout(60_000)
+    page_errors = []
+
+    def _on_pageerror(e):
+        msg = str(e)
+        if is_benign_page_error(msg):
+            info(f"WARN ignoring benign pageerror: {msg!r}")
+            return
+        page_errors.append(msg)
+
+    page.on("pageerror", _on_pageerror)
+
+    # Record every /api/inference/load POST payload so the persistence gate can
+    # assert max_seq_length.
+    load_posts: list[str] = []
+
+    def _on_request(req):
+        try:
+            if req.method == "POST" and "/api/inference/load" in req.url:
+                load_posts.append(req.post_data or "")
+        except Exception:
+            pass
+
+    page.on("request", _on_request)
+
+    def shoot(name: str) -> None:
+        _n[0] += 1
+        try:
+            page.screenshot(
+                path = str(ART / f"{_n[0]:02d}-{name}.png"),
+                full_page = True,
+                timeout = 90_000,
+                animations = "disabled",
+            )
+        except Exception as _shoot_err:
+            info(f"WARN: screenshot {name} failed: {_shoot_err}")
+
+    def read_configs() -> dict:
+        """Return the parsed unsloth_model_configs map (or {} if absent/invalid)."""
+        raw = robust_evaluate(page, "() => localStorage.getItem('unsloth_model_configs')")
+        if not raw:
+            return {}
+        try:
+            data = json.loads(raw)
+            return data if isinstance(data, dict) else {}
+        except Exception:
+            return {}
+
+    def config_entries(cfg: dict) -> list[dict]:
+        """The per-model entries (dict values) of the stored map, schema-tolerant."""
+        return [v for v in cfg.values() if isinstance(v, dict)]
+
+    # ─────────────────────────────────────────────────────
+    # Setup: authenticate + model load.
+    # ─────────────────────────────────────────────────────
+    if LOGIN_PW:
+        # Attach mode: log in via the API and seed the token before navigation,
+        # skipping the first-boot change-password dance.
+        step("setup: API login + token seed (attach to running Studio)")
+        _tok = _login_token_via_api(BASE, LOGIN_USER, LOGIN_PW)
+        ctx.add_init_script(
+            f"try{{localStorage.setItem('unsloth_auth_token', {json.dumps(_tok)});}}"
+            f"catch(e){{}}"
+        )
+        page.goto(BASE, wait_until = "domcontentloaded", timeout = 60_000)
+    else:
+        step("setup: change-password")
+        # 3-attempt retry: the form can re-render mid-fill on slow runners and
+        # detach the password fields; each retry re-navigates with a fresh page.
+        form_err: Exception | None = None
+        for _form_attempt in range(3):
+            try:
+                page.goto(f"{BASE}/change-password", wait_until = "domcontentloaded", timeout = 60_000)
+                try:
+                    page.wait_for_load_state("networkidle", timeout = 30_000)
+                except Exception:
+                    pass
+                pw_field = page.locator("#new-password")
+                pw_field.wait_for(state = "visible", timeout = 60_000)
+                pw_field.fill(NEW, timeout = 60_000)
+                page.fill("#confirm-password", NEW, timeout = 60_000)
+                status, _ = click_and_wait_for_response(
+                    page,
+                    url_substr = "/api/auth/change-password",
+                    method = "POST",
+                    do_click = lambda: page.locator('button[type="submit"]').click(),
+                    timeout_ms = 30_000,
+                    info = lambda m: print(f"[ui-modelcfg]   {m}", flush = True),
+                )
+                if status is not None and status >= 400:
+                    raise AssertionError(
+                        f"change-password POST returned {status}; page_errors={page_errors[:1]!r}"
+                    )
+                form_err = None
+                break
+            except Exception as e:
+                form_err = e
+                try:
+                    cur_url = page.url
+                except Exception:
+                    cur_url = "<page closed>"
+                print(
+                    f"[ui-modelcfg]   change-password attempt {_form_attempt + 1} failed: "
+                    f"{type(e).__name__}: {str(e)[:200]}; page.url={cur_url}; "
+                    f"page_errors={len(page_errors)}",
+                    flush = True,
+                )
+                if _form_attempt < 2:
+                    if "ERR_NO_BUFFER_SPACE" in str(e):
+                        backoff_s = 5 if _form_attempt == 0 else 15
+                        time.sleep(backoff_s)
+                    page = recover_or_replace_page(
+                        page,
+                        ctx,
+                        default_timeout_ms = 60_000,
+                        info = lambda m: print(f"[ui-modelcfg]   recovery: {m}", flush = True),
+                    )
+                    page.on("request", _on_request)
+        if form_err is not None:
+            raise form_err
+
+    try:
+        page.wait_for_load_state("networkidle", timeout = 30_000)
+    except Exception:
+        pass
+    composer = page.locator('textarea[aria-label="Message input"]')
+    last_err: Exception | None = None
+    for _attempt in range(2):
+        try:
+            composer.wait_for(state = "visible", timeout = 60_000)
+            last_err = None
+            break
+        except Exception as e:
+            last_err = e
+            try:
+                shoot(f"00-composer-wait-attempt-{_attempt + 1}-fail")
+            except Exception:
+                pass
+            if _attempt == 0:
+                page = recover_or_replace_page(
+                    page,
+                    ctx,
+                    default_timeout_ms = 60_000,
+                    goto_url = BASE,
+                    settle_networkidle = True,
+                    info = lambda m: print(f"[ui-modelcfg]   recovery: {m}", flush = True),
+                )
+                page.on("request", _on_request)
+                composer = page.locator('textarea[aria-label="Message input"]')
+    if last_err is not None:
+        raise last_err
+    shoot("01-chat-loaded")
+
+    token = robust_evaluate(page, "() => localStorage.getItem('unsloth_auth_token')")
+    if not token:
+        fail("no access token after auth setup")
+        sys.exit(1)
+
+    # Load the tiny GGUF so it is a live "On Device" model in the picker.
+    load_resp = evaluate_fetch(
+        page,
+        f"{BASE}/api/inference/load",
+        method = "POST",
+        headers = {
+            "Authorization": f"Bearer {token}",
+            "Content-Type": "application/json",
+        },
+        body = {
+            "model_path": GGUF_REPO,
+            "gguf_variant": GGUF_VARIANT,
+            "is_lora": False,
+            "max_seq_length": 2048,
+        },
+        timeout_ms = LOAD_FETCH_TIMEOUT_MS,
+    )
+    if load_resp.get("error"):
+        fail(f"/api/inference/load wedged: {load_resp['error']!r}")
+        sys.exit(1)
+    if load_resp["status"] != 200:
+        fail(f"/api/inference/load -> {load_resp['status']}: {load_resp.get('body')!r}")
+        sys.exit(1)
+    info(f"loaded model: {(load_resp['body'] or {}).get('display_name')}")
+    page.reload()
+    composer = page.locator('textarea[aria-label="Message input"]')
+    composer.wait_for(state = "visible", timeout = 60_000)
+    load_posts.clear()  # drop the setup load; keep only UI-driven loads below.
+
+    # ─────────────────────────────────────────────────────
+    # Picker helpers (proven selectors).
+    # ─────────────────────────────────────────────────────
+    POPOVER = '[data-tour="chat-model-selector-popover"]'
+    TRIGGER = '[data-tour="chat-model-selector"]'
+
+    def open_picker():
+        popover = page.locator(POPOVER).first
+        if _count(popover) == 0 or not popover.is_visible():
+            page.locator(TRIGGER).first.click()
+            page.wait_for_timeout(900)
+            popover = page.locator(POPOVER).first
+        popover.wait_for(state = "visible", timeout = 30_000)
+        return popover
+
+    def close_picker():
+        try:
+            page.keyboard.press("Escape")
+            page.wait_for_timeout(400)
+        except Exception:
+            pass
+
+    def select_on_device_row(popover, hint):
+        od = page.get_by_role("tab", name = "On Device").first
+        if _count(od):
+            od.click()
+            page.wait_for_timeout(700)
+        row = popover.locator("[data-model-picker-option]", has_text = hint).first
+        if _count(row) == 0:
+            # Fall back to search filtering.
+            search = popover.locator("[data-model-picker-search-input]").first
+            if _count(search):
+                search.click()
+                search.fill(hint)
+                page.wait_for_timeout(700)
+                row = popover.locator("[data-model-picker-option]", has_text = hint).first
+        if _count(row) == 0:
+            return None
+        row.click()
+        page.wait_for_timeout(800)
+        return row
+
+    def open_config(popover, hint):
+        if select_on_device_row(popover, hint) is None:
+            return None
+        gear = popover.locator('button[aria-label^="Inference settings for"]').first
+        if _count(gear) == 0:
+            return None
+        gear.click()
+        page.wait_for_timeout(800)
+        return popover
+
+    def context_input(popover):
+        for role in ("textbox", "spinbutton"):
+            loc = popover.get_by_role(role, name = "Context Length").first
+            if _count(loc):
+                return loc
+        loc = popover.locator('input[aria-label="Context Length"]').first
+        return loc if _count(loc) else None
+
+    def primary_button(popover):
+        for name in ("Load model", "Reload model", "Save settings", "Forget settings"):
+            b = popover.get_by_role("button", name = name).first
+            if _count(b):
+                return b
+        return None
+
+    # ─────────────────────────────────────────────────────
+    # 1. Hidden infra models absent from the picker (HARD).
+    # ─────────────────────────────────────────────────────
+    step("hidden infra models absent from picker")
+    popover = open_picker()
+    shoot("02-picker-open")
+    needles = ["bge-small-en-v1.5", "stories260"]
+    tabs = ["Recommended", "On Device", "Connected"]
+    hidden_ok = True
+    for needle in needles:
+        for tab_name in tabs:
+            tab = page.get_by_role("tab", name = tab_name).first
+            if _count(tab) == 0:
+                continue
+            try:
+                tab.click()
+                page.wait_for_timeout(400)
+            except Exception:
+                continue
+            search = popover.locator("[data-model-picker-search-input]").first
+            if _count(search):
+                search.click()
+                search.fill(needle)
+                page.wait_for_timeout(600)
+            hit = popover.locator(
+                "[data-model-picker-option]",
+                has_text = re.compile(re.escape(needle), re.I),
+            )
+            c = _count(hit)
+            if c > 0:
+                hidden_ok = False
+                fail(f"infra model {needle!r} visible in picker '{tab_name}' tab ({c} rows)")
+            if _count(search):
+                search.fill("")
+                page.wait_for_timeout(300)
+    if hidden_ok:
+        info("OK hidden: bge-small-en-v1.5 + stories260K absent from every picker tab")
+    shoot("03-hidden-check")
+    close_picker()
+
+    # ─────────────────────────────────────────────────────
+    # 2. Context Length persists (load + request + reload) (HARD).
+    # ─────────────────────────────────────────────────────
+    step(f"context length {DISTINCT_CTX} persists")
+    popover = open_picker()
+    if open_config(popover, MODEL_HINT) is None:
+        fail(f"could not open run-settings for a model matching {MODEL_HINT!r}")
+    else:
+        shoot("04-config-open")
+        ctx_in = context_input(popover)
+        if ctx_in is None:
+            fail("Context Length input not found in run-settings")
+        else:
+            default_ctx = ctx_in.input_value()
+            info(f"default Context Length shown: {default_ctx!r}")
+            ctx_in.click()
+            ctx_in.fill(str(DISTINCT_CTX))
+            page.wait_for_timeout(300)
+            page.keyboard.press("Tab")  # blur to commit
+            page.wait_for_timeout(300)
+            remember = popover.get_by_label("Remember for this model").first
+            if _count(remember):
+                try:
+                    remember.check()
+                except Exception:
+                    remember.click()
+            else:
+                fail("'Remember for this model' checkbox not found")
+            page.wait_for_timeout(300)
+            shoot("05-ctx-set")
+            btn = primary_button(popover)
+            if btn is None:
+                fail("primary Load/Save button not found in run-settings")
+            else:
+                btn.click()
+                page.wait_for_timeout(2500)
+                shoot("06-after-load")
+
+                # (a) localStorage stored the distinctive context.
+                cfg = read_configs()
+                entries = config_entries(cfg)
+                got_ls = any(e.get("customContextLength") == DISTINCT_CTX for e in entries)
+                if got_ls:
+                    info(f"OK persist(localStorage): customContextLength={DISTINCT_CTX} stored")
+                else:
+                    fail(
+                        "context not stored in unsloth_model_configs "
+                        f"(entries={json.dumps(entries)[:400]})"
+                    )
+
+                # (b) the load request carried max_seq_length == distinctive value.
+                got_req = False
+                for body in load_posts:
+                    try:
+                        payload = json.loads(body) if body else {}
+                    except Exception:
+                        payload = {}
+                    if payload.get("max_seq_length") == DISTINCT_CTX:
+                        got_req = True
+                        break
+                if got_req:
+                    info(f"OK persist(request): /api/inference/load max_seq_length={DISTINCT_CTX}")
+                else:
+                    # The UI may debounce the load; localStorage is the primary
+                    # proof, so only warn if the request was missed.
+                    runtime_warn(
+                        "no /api/inference/load carried "
+                        f"max_seq_length={DISTINCT_CTX}; posts={load_posts!r}"
+                    )
+
+    # (c) survives a full browser reload.
+    close_picker()
+    page.reload()
+    composer = page.locator('textarea[aria-label="Message input"]')
+    composer.wait_for(state = "visible", timeout = 60_000)
+    popover = open_picker()
+    if open_config(popover, MODEL_HINT) is None:
+        fail("could not reopen run-settings after reload")
+    else:
+        ctx_in = context_input(popover)
+        val = ctx_in.input_value() if ctx_in else None
+        if _as_int(val) == DISTINCT_CTX:
+            info(f"OK persist(reload): Context Length still {val!r} after reload")
+        else:
+            fail(f"Context Length did not persist across reload (got {val!r})")
+        shoot("07-after-reload")
+
+    # ─────────────────────────────────────────────────────
+    # 3. Reset clears the override (never pins context) (HARD).
+    # ─────────────────────────────────────────────────────
+    step("reset clears the per-model override")
+    # (popover + config still open from the reload check.)
+    reset_btn = popover.get_by_role("button", name = "Reset").first
+    if _count(reset_btn) == 0:
+        fail("Reset button not found in run-settings")
+    else:
+        try:
+            reset_btn.click()
+            page.wait_for_timeout(500)
+        except Exception as e:
+            fail(f"Reset click failed: {e}")
+        # The input after Reset is informational only: a live-loaded model can still
+        # echo its context even with the stored override gone. The regression we
+        # guard ("Reset PINS the override") lives in localStorage, asserted below.
+        ctx_in = context_input(popover)
+        after_reset = ctx_in.input_value() if ctx_in else None
+        info(f"reset: Context Length input now shows {after_reset!r}")
+        # Commit the reset so the stored override is dropped, then assert storage.
+        btn = primary_button(popover)
+        if btn is not None and btn.is_enabled():
+            btn.click()
+            page.wait_for_timeout(1500)
+        cfg = read_configs()
+        pinned = any(
+            _as_int(e.get("customContextLength")) == DISTINCT_CTX for e in config_entries(cfg)
+        )
+        if pinned:
+            fail("Reset left the distinctive context pinned in unsloth_model_configs")
+        else:
+            info("OK reset: distinctive context cleared from unsloth_model_configs")
+        shoot("08-after-reset")
+    close_picker()
+
+    # ─────────────────────────────────────────────────────
+    # 4. Advanced settings persist (best-effort, never gates).
+    # ─────────────────────────────────────────────────────
+    step("advanced (KV cache dtype / tensor parallel) persists")
+    try:
+        popover = open_picker()
+        if open_config(popover, MODEL_HINT) is not None:
+            adv = popover.get_by_role("switch", name = re.compile("advanced settings", re.I)).first
+            if _count(adv):
+                try:
+                    adv.check()
+                except Exception:
+                    adv.click()
+                page.wait_for_timeout(500)
+            # The Tensor Parallelism Radix Switch has no aria-label, so target the
+            # first switch after the "Tensor Parallelism" text.
+            tp = popover.locator(
+                'xpath=.//span[contains(text(),"Tensor Parallelism")]'
+                '/following::*[@role="switch"][1]'
+            ).first
+            toggled = False
+            if _count(tp):
+                try:
+                    tp.click()
+                    toggled = True
+                except Exception:
+                    pass
+            remember = popover.get_by_label("Remember for this model").first
+            if _count(remember):
+                try:
+                    remember.check()
+                except Exception:
+                    remember.click()
+            btn = primary_button(popover)
+            if btn is not None and btn.is_enabled():
+                btn.click()
+                page.wait_for_timeout(1500)
+            cfg = read_configs()
+            has_adv = any(
+                e.get("tensorParallel") or e.get("kvCacheDtype") for e in config_entries(cfg)
+            )
+            if toggled and has_adv:
+                info("OK advanced: tensorParallel/kvCacheDtype persisted")
+            else:
+                runtime_warn(
+                    f"advanced persistence not observed (toggled={toggled}, "
+                    f"entries={json.dumps(config_entries(cfg))[:300]})"
+                )
+        else:
+            runtime_warn("could not open run-settings for the advanced-persist check")
+        close_picker()
+    except Exception as e:
+        runtime_warn(f"advanced-persist check errored: {e}")
+
+    # ─────────────────────────────────────────────────────
+    # 5. Legacy migration is idempotent (gates in CI via soft_fail).
+    #    Seed a pre-feature unsloth_load_settings store, confirm it migrates once
+    #    with the value preserved, then reload with a fresh legacy seed and confirm
+    #    the migration does not re-run, duplicate, or clobber. Re-running on every
+    #    reload was the regression that reverted the predecessor PR.
+    # ─────────────────────────────────────────────────────
+    step("legacy unsloth_load_settings migrates once and stays idempotent")
+    try:
+        legacy_key = f"{GGUF_REPO}::{GGUF_VARIANT}"
+        legacy = {
+            legacy_key: {
+                "contextLength": DISTINCT_CTX,
+                "kvCacheDtype": "q8_0",
+                "tensorParallel": True,
+            }
+        }
+        robust_evaluate(
+            page,
+            "(seed) => {"
+            "  localStorage.setItem('unsloth_load_settings', JSON.stringify(seed));"
+            "  localStorage.removeItem('unsloth_model_configs');"
+            "  localStorage.removeItem('unsloth_model_configs_migrated');"
+            "  return true;"
+            "}",
+            arg = legacy,
+        )
+        page.reload()
+        composer = page.locator('textarea[aria-label="Message input"]')
+        composer.wait_for(state = "visible", timeout = 60_000)
+        # Opening the picker config forces the store to read (which migrates).
+        popover = open_picker()
+        open_config(popover, MODEL_HINT)
+        page.wait_for_timeout(800)
+        cfg_first = read_configs()
+        migrated_ctx = any(
+            e.get("customContextLength") == DISTINCT_CTX for e in config_entries(cfg_first)
+        )
+        if migrated_ctx:
+            info(f"OK migration: legacy context {DISTINCT_CTX} preserved after migrating")
+        else:
+            soft_fail(
+                f"legacy context {DISTINCT_CTX} not migrated into unsloth_model_configs "
+                f"(got {json.dumps(cfg_first)[:400]})"
+            )
+        flag_first = robust_evaluate(
+            page, "() => localStorage.getItem('unsloth_model_configs_migrated')"
+        )
+        if flag_first != "1":
+            soft_fail(f"migration flag not set after migrating (got {flag_first!r})")
+        shoot("09-after-migration")
+        close_picker()
+
+        # Idempotency: a second reload with a DIFFERENT legacy entry must not re-run
+        # the migration (the persistent flag blocks it), so the new key must not leak
+        # in, nothing duplicates, and the migrated value is untouched.
+        if migrated_ctx:
+            probe_key = "unsloth/__idem_probe__::Q4_K_M"
+            robust_evaluate(
+                page,
+                "(seed) => {"
+                "  localStorage.setItem('unsloth_load_settings', JSON.stringify(seed));"
+                "  return true;"
+                "}",
+                arg = {probe_key: {"contextLength": DISTINCT_CTX + 2048, "tensorParallel": True}},
+            )
+            page.reload()
+            composer.wait_for(state = "visible", timeout = 60_000)
+            popover = open_picker()
+            open_config(popover, MODEL_HINT)
+            page.wait_for_timeout(800)
+            cfg_second = read_configs()
+            keys_first = set(cfg_first.keys())
+            keys_second = set(cfg_second.keys())
+            new_keys = keys_second - keys_first
+            still_has_ctx = any(
+                e.get("customContextLength") == DISTINCT_CTX for e in config_entries(cfg_second)
+            )
+            if new_keys:
+                soft_fail(
+                    "legacy migration re-ran on a second reload (persistent flag "
+                    f"ignored): new keys {sorted(new_keys)}"
+                )
+            elif keys_second != keys_first:
+                soft_fail(
+                    "legacy migration dropped entries on a second reload: "
+                    f"{sorted(keys_first)} -> {sorted(keys_second)}"
+                )
+            elif not still_has_ctx:
+                soft_fail("legacy migration clobbered the migrated context on a second reload")
+            else:
+                info(
+                    "OK migration idempotent: second reload did not re-migrate, duplicate, or clobber"
+                )
+            shoot("10-after-second-reload")
+            close_picker()
+    except Exception as e:
+        soft_fail(f"migration idempotency check errored: {e}")
+
+    # ─────────────────────────────────────────────────────
+    if page_errors:
+        fail(f"page errors during run: {page_errors[:3]!r}")
+
+    browser.close()
+
+if _failed:
+    print(f"[ui-modelcfg] RESULT: FAIL ({len(_failed)} issue(s))", flush = True)
+    for m in _failed:
+        print(f"[ui-modelcfg]   - {m}", flush = True)
+    sys.exit(1)
+print("[ui-modelcfg] RESULT: PASS", flush = True)
+sys.exit(0)
diff --git a/tests/studio/playwright_ui_font_scale.py b/tests/studio/playwright_ui_font_scale.py
new file mode 100644
index 0000000000..89c7894929
--- /dev/null
+++ b/tests/studio/playwright_ui_font_scale.py
@@ -0,0 +1,213 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""UI font size scaling regression (Settings > Appearance).
+
+Drives the real appearance controls and asserts the typography-scale
+contract: text and line heights scale by size/16, the root font size and
+layout geometry never move, an explicit Code font size stays fixed, and an
+overflowing Radix select scrolls its viewport by keyboard and wheel.
+
+Runs against an already-booted, already-bootstrapped Unsloth:
+    BASE_URL=http://127.0.0.1:18894 STUDIO_PW=... python tests/studio/playwright_ui_font_scale.py
+"""
+
+import os
+import sys
+from pathlib import Path
+
+from playwright.sync_api import sync_playwright
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from _playwright_robust import wait_for_health  # noqa: E402
+
+BASE = os.environ["BASE_URL"]
+PW = os.environ["STUDIO_PW"]
+ART = Path(os.environ.get("PW_ART_DIR", "logs/playwright_fontscale"))
+ART.mkdir(parents = True, exist_ok = True)
+
+SIZES = (12, 20)
+DEFAULT = 16
+
+
+def step(s):
+    print(f"[font-scale] STEP {s}", flush = True)
+
+
+def fail(m):
+    raise AssertionError(f"[font-scale] FAIL: {m}")
+
+
+def near(
+    a,
+    b,
+    tol = 0.35,
+):
+    return a is not None and b is not None and abs(a - b) <= tol
+
+
+MEASURE_JS = """
+() => {
+  const fs = (el) => (el ? parseFloat(getComputedStyle(el).fontSize) : null);
+  const lh = (el) => (el ? parseFloat(getComputedStyle(el).lineHeight) : null);
+  const byText = (txt) =>
+    [...document.querySelectorAll("span, h2, label, p")].find(
+      (e) => e.textContent.trim() === txt,
+    );
+  const nav = byText("New chat");
+  const sidebar =
+    document.querySelector("[data-slot='sidebar-container']") ??
+    document.querySelector("aside") ??
+    document.querySelector("nav");
+  return {
+    root: parseFloat(getComputedStyle(document.documentElement).fontSize),
+    uiAttr: document.documentElement.getAttribute("data-ui-font-size"),
+    navFont: fs(nav),
+    navLine: lh(nav),
+    sidebarW: sidebar ? sidebar.getBoundingClientRect().width : null,
+  };
+}
+"""
+
+
+def measure(page):
+    return page.evaluate(MEASURE_JS)
+
+
+def set_input(page, label, value):
+    field = page.locator(f"input[aria-label='{label}']")
+    field.scroll_into_view_if_needed()
+    field.fill(str(value))
+    page.keyboard.press("Enter")
+    page.wait_for_timeout(600)
+
+
+def open_appearance(page):
+    page.keyboard.press("Control+,")
+    page.wait_for_timeout(700)
+    if page.get_by_role("dialog").count() == 0:
+        page.keyboard.press("Meta+,")
+        page.wait_for_timeout(700)
+    if page.get_by_role("dialog").count() == 0:
+        fail("settings dialog did not open")
+    page.get_by_role("dialog").get_by_role("button").filter(has_text = "Appearance").first.click()
+    page.wait_for_timeout(600)
+
+
+def main():
+    wait_for_health(BASE)
+    with sync_playwright() as p:
+        browser = p.chromium.launch()
+        page = browser.new_page(viewport = {"width": 1440, "height": 900})
+        page.goto(BASE, wait_until = "networkidle")
+        pw_field = page.locator("input[type='password']")
+        if pw_field.count():
+            pw_field.first.fill(PW)
+            page.keyboard.press("Enter")
+            page.wait_for_load_state("networkidle")
+            page.wait_for_timeout(1500)
+
+        step("baseline at the default size")
+        open_appearance(page)
+        set_input(page, "UI font size", DEFAULT)
+        base = measure(page)
+        if base["root"] != 16:
+            fail(f"root font size not 16 at default: {base['root']}")
+        if base["navFont"] is None or base["sidebarW"] is None:
+            fail(f"baseline samples missing: {base}")
+
+        for size in SIZES:
+            step(f"UI font size {size}")
+            set_input(page, "UI font size", size)
+            m = measure(page)
+            ratio = size / DEFAULT
+            if m["root"] != 16:
+                fail(f"root font size moved at {size}: {m['root']}")
+            if m["uiAttr"] != str(size):
+                fail(f"data-ui-font-size wrong at {size}: {m['uiAttr']}")
+            if not near(m["navFont"], base["navFont"] * ratio):
+                fail(f"nav font at {size}: {base['navFont']} -> {m['navFont']}")
+            if not near(m["navLine"], base["navLine"] * ratio):
+                fail(f"nav line-height at {size}: {base['navLine']} -> {m['navLine']}")
+            if not near(m["sidebarW"], base["sidebarW"], 0.75):
+                fail(f"sidebar width moved at {size}: {base['sidebarW']} -> {m['sidebarW']}")
+            page.screenshot(path = str(ART / f"scale-{size}.png"))
+
+        step("explicit Code font size stays fixed under UI 20")
+        set_input(page, "Code font size", 13)
+        res = page.evaluate(
+            """
+            () => {
+              const pre = document.createElement("pre");
+              pre.textContent = "sample";
+              document.body.appendChild(pre);
+              const size = getComputedStyle(pre).fontSize;
+              pre.remove();
+              return size;
+            }
+            """
+        )
+        if res != "13px":
+            fail(f"explicit code font size scaled: {res}")
+        code_field = page.locator("input[aria-label='Code font size']")
+        code_field.fill("")
+        page.keyboard.press("Enter")
+        page.wait_for_timeout(400)
+
+        step("overflowing select scrolls its Radix viewport")
+        page.get_by_role("dialog").get_by_role("button").filter(has_text = "Voice").first.click()
+        page.wait_for_timeout(600)
+        page.set_viewport_size({"width": 1440, "height": 480})
+        page.locator("[aria-label='Dictation language']").click()
+        page.wait_for_timeout(700)
+        state = page.evaluate(
+            """
+            () => {
+              const vp = document.querySelector("[data-radix-select-viewport]");
+              return vp
+                ? { scrollable: vp.scrollHeight > vp.clientHeight, top: vp.scrollTop }
+                : null;
+            }
+            """
+        )
+        if not state or not state["scrollable"]:
+            fail(f"select viewport not scrollable: {state}")
+        for _ in range(6):
+            page.keyboard.press("ArrowDown")
+            page.wait_for_timeout(100)
+        kb_top = page.evaluate(
+            "() => document.querySelector('[data-radix-select-viewport]').scrollTop"
+        )
+        if not kb_top > 0:
+            fail(f"keyboard did not scroll the select viewport: {kb_top}")
+        vp_box = page.locator("[data-radix-select-viewport]").bounding_box()
+        page.mouse.move(vp_box["x"] + vp_box["width"] / 2, vp_box["y"] + 40)
+        page.mouse.wheel(0, -400)
+        page.wait_for_timeout(300)
+        wheel_top = page.evaluate(
+            "() => document.querySelector('[data-radix-select-viewport]').scrollTop"
+        )
+        if not wheel_top < kb_top:
+            fail(f"wheel did not scroll the select viewport: {kb_top} -> {wheel_top}")
+        page.keyboard.press("Escape")
+        page.set_viewport_size({"width": 1440, "height": 900})
+        page.wait_for_timeout(400)
+
+        step("default restores exactly")
+        page.get_by_role("dialog").get_by_role("button").filter(has_text = "Appearance").first.click()
+        page.wait_for_timeout(500)
+        set_input(page, "UI font size", DEFAULT)
+        final = measure(page)
+        for key in ("root", "navFont", "navLine", "sidebarW"):
+            if not near(final[key], base[key], 0.35):
+                fail(f"default drifted for {key}: {base[key]} -> {final[key]}")
+        if final["uiAttr"] is not None:
+            fail(f"data-ui-font-size present at default: {final['uiAttr']}")
+
+        page.screenshot(path = str(ART / "restored-default.png"))
+        browser.close()
+    print("[font-scale] PASS", flush = True)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/studio/test_cached_model_path_selection.py b/tests/studio/test_cached_model_path_selection.py
new file mode 100644
index 0000000000..2b6b9c7829
--- /dev/null
+++ b/tests/studio/test_cached_model_path_selection.py
@@ -0,0 +1,241 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Variant-file selection guards for the cached-model-path endpoint.
+
+The Copy path / Reveal endpoint must resolve a quant label to the same file
+the variant menus offer: MTP drafters, mmproj vision adapters, and big-endian
+builds are excluded, and directory layouts (``BF16/model-00001-of-....gguf``)
+resolve their label from the snapshot-relative path, not the basename.
+"""
+
+from __future__ import annotations
+
+import os
+import sys
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+
+def _find_repo_root() -> Path | None:
+    env = os.environ.get("UNSLOTH_REPO_ROOT")
+    if env:
+        p = Path(env).resolve()
+        if (p / "studio" / "backend").is_dir():
+            return p
+    here = Path(__file__).resolve()
+    for parent in (here, *here.parents):
+        if (parent / "studio" / "backend").is_dir():
+            return parent
+    return None
+
+
+_REPO_ROOT = _find_repo_root()
+if _REPO_ROOT is None:
+    pytest.skip(
+        "Could not locate studio/backend. Set UNSLOTH_REPO_ROOT or run from "
+        "the repository checkout.",
+        allow_module_level = True,
+    )
+
+_STUDIO_BACKEND = _REPO_ROOT / "studio" / "backend"
+if str(_STUDIO_BACKEND) not in sys.path:
+    sys.path.insert(0, str(_STUDIO_BACKEND))
+
+pytest.importorskip("fastapi")
+pytest.importorskip("huggingface_hub")
+
+try:
+    from routes import models as routes_models
+except Exception as exc:
+    pytest.skip(f"studio backend import unavailable: {exc}", allow_module_level = True)
+
+from fastapi import HTTPException
+
+
+def test_plain_quant_label_resolves():
+    assert routes_models._main_variant_gguf_label("Model-Q8_0.gguf") == "Q8_0"
+
+
+def test_mtp_drafter_in_subdir_is_excluded():
+    assert routes_models._main_variant_gguf_label("MTP/Model-Q8_0-MTP.gguf") is None
+
+
+def test_mtp_drafter_root_prefix_is_excluded():
+    assert routes_models._main_variant_gguf_label("mtp-Model-Q8_0.gguf") is None
+
+
+def test_mmproj_adapter_is_excluded():
+    assert routes_models._main_variant_gguf_label("mmproj-Model-F16.gguf") is None
+
+
+def test_directory_layout_quant_resolves_from_parent_dir():
+    assert routes_models._main_variant_gguf_label("BF16/Model-00001-of-00002.gguf") == "BF16"
+
+
+def test_big_endian_build_is_excluded():
+    assert routes_models._main_variant_gguf_label("Model-Q8_0-BE.gguf") is None
+
+
+def test_non_gguf_file_is_excluded():
+    assert routes_models._main_variant_gguf_label("config.json") is None
+
+
+def test_normalized_quant_label_ignores_separators():
+    assert routes_models._normalized_quant_label("UD-Q4_K_XL") == "udq4kxl"
+    assert routes_models._normalized_quant_label("Q8-0") == routes_models._normalized_quant_label(
+        "Q8_0"
+    )
+
+
+def _revision(
+    snapshot: Path,
+    last_modified: float,
+    names: list[str],
+    size_on_disk: int = 4,
+) -> SimpleNamespace:
+    files = []
+    for name in names:
+        path = snapshot / name
+        path.parent.mkdir(parents = True, exist_ok = True)
+        path.write_bytes(b"x" * size_on_disk)
+        files.append(
+            SimpleNamespace(
+                file_name = name,
+                file_path = path,
+                blob_path = path,
+                size_on_disk = size_on_disk,
+            )
+        )
+    return SimpleNamespace(snapshot_path = snapshot, last_modified = last_modified, files = files)
+
+
+def _patch_cache(monkeypatch, tmp_path: Path, revisions: list[SimpleNamespace]) -> None:
+    repo = SimpleNamespace(
+        repo_id = "Org/Repo",
+        repo_type = "model",
+        repo_path = tmp_path,
+        revisions = revisions,
+    )
+    monkeypatch.setattr(
+        routes_models, "_all_hf_cache_scans", lambda: [SimpleNamespace(repos = [repo])]
+    )
+
+
+def _repo(root: Path, revisions: list[SimpleNamespace]) -> SimpleNamespace:
+    return SimpleNamespace(
+        repo_id = "Org/Repo",
+        repo_type = "model",
+        repo_path = root,
+        revisions = revisions,
+    )
+
+
+def _patch_caches(monkeypatch, repos: list[SimpleNamespace]) -> None:
+    monkeypatch.setattr(
+        routes_models,
+        "_all_hf_cache_scans",
+        lambda: [SimpleNamespace(repos = [repo]) for repo in repos],
+    )
+
+
+@pytest.mark.parametrize("newest_first", [True, False])
+def test_variant_resolves_from_newest_revision(monkeypatch, tmp_path, newest_first):
+    old = _revision(tmp_path / "snapshots" / "aaa", 1_000.0, ["Model-Q4_K_M.gguf"])
+    new = _revision(tmp_path / "snapshots" / "bbb", 2_000.0, ["Model-Q4_K_M.gguf"])
+    _patch_cache(monkeypatch, tmp_path, [new, old] if newest_first else [old, new])
+    resolved = routes_models._resolve_cached_model_path("Org/Repo", "Q4_K_M")
+    assert resolved == tmp_path / "snapshots" / "bbb" / "Model-Q4_K_M.gguf"
+
+
+def test_sharded_variant_resolves_first_split(monkeypatch, tmp_path):
+    rev = _revision(
+        tmp_path / "snapshots" / "aaa",
+        1_000.0,
+        ["Model-Q4_K_M-00002-of-00002.gguf", "Model-Q4_K_M-00001-of-00002.gguf"],
+    )
+    _patch_cache(monkeypatch, tmp_path, [rev])
+    resolved = routes_models._resolve_cached_model_path("Org/Repo", "Q4_K_M")
+    assert resolved.name == "Model-Q4_K_M-00001-of-00002.gguf"
+
+
+def test_variant_only_in_older_revision_resolves(monkeypatch, tmp_path):
+    old = _revision(tmp_path / "snapshots" / "aaa", 1_000.0, ["Model-Q4_K_M.gguf"])
+    new = _revision(tmp_path / "snapshots" / "bbb", 2_000.0, ["Model-Q8_0.gguf"])
+    _patch_cache(monkeypatch, tmp_path, [new, old])
+    resolved = routes_models._resolve_cached_model_path("Org/Repo", "Q4_K_M")
+    assert resolved == tmp_path / "snapshots" / "aaa" / "Model-Q4_K_M.gguf"
+
+
+def test_missing_newest_file_falls_back_to_older_revision(monkeypatch, tmp_path):
+    old = _revision(tmp_path / "snapshots" / "aaa", 1_000.0, ["Model-Q4_K_M.gguf"])
+    new_snapshot = tmp_path / "snapshots" / "bbb"
+    new_snapshot.mkdir(parents = True)
+    new = SimpleNamespace(
+        snapshot_path = new_snapshot,
+        last_modified = 2_000.0,
+        files = [
+            SimpleNamespace(
+                file_name = "Model-Q4_K_M.gguf",
+                file_path = new_snapshot / "Model-Q4_K_M.gguf",
+            )
+        ],
+    )
+    _patch_cache(monkeypatch, tmp_path, [new, old])
+    resolved = routes_models._resolve_cached_model_path("Org/Repo", "Q4_K_M")
+    assert resolved == tmp_path / "snapshots" / "aaa" / "Model-Q4_K_M.gguf"
+
+
+def test_variant_resolves_across_all_cache_roots(monkeypatch, tmp_path):
+    first_root = tmp_path / "active"
+    second_root = tmp_path / "default"
+    old = _revision(
+        first_root / "snapshots" / "aaa",
+        1_000.0,
+        ["Model-Q4_K_M.gguf"],
+    )
+    new = _revision(
+        second_root / "snapshots" / "bbb",
+        2_000.0,
+        ["Model-Q4_K_M.gguf"],
+    )
+    _patch_caches(
+        monkeypatch,
+        [_repo(first_root, [old]), _repo(second_root, [new])],
+    )
+    resolved = routes_models._resolve_cached_model_path("Org/Repo", "Q4_K_M")
+    assert resolved == second_root / "snapshots" / "bbb" / "Model-Q4_K_M.gguf"
+
+
+def test_repo_path_matches_largest_visible_cache_entry(monkeypatch, tmp_path):
+    first_root = tmp_path / "active"
+    second_root = tmp_path / "default"
+    small = _revision(
+        first_root / "snapshots" / "aaa",
+        2_000.0,
+        ["Model-Q8_0.gguf"],
+        size_on_disk = 4,
+    )
+    large = _revision(
+        second_root / "snapshots" / "bbb",
+        1_000.0,
+        ["Model-Q8_0.gguf"],
+        size_on_disk = 8,
+    )
+    _patch_caches(
+        monkeypatch,
+        [_repo(first_root, [small]), _repo(second_root, [large])],
+    )
+    resolved = routes_models._resolve_cached_model_path("Org/Repo", None)
+    assert resolved == second_root / "snapshots" / "bbb"
+
+
+def test_unknown_variant_raises_404(monkeypatch, tmp_path):
+    rev = _revision(tmp_path / "snapshots" / "aaa", 1_000.0, ["Model-Q8_0.gguf"])
+    _patch_cache(monkeypatch, tmp_path, [rev])
+    with pytest.raises(HTTPException) as excinfo:
+        routes_models._resolve_cached_model_path("Org/Repo", "Q4_K_M")
+    assert excinfo.value.status_code == 404
+    assert "Q4_K_M" in excinfo.value.detail
diff --git a/tests/studio/test_compact_dropdown_submenus.py b/tests/studio/test_compact_dropdown_submenus.py
index c82b1e4751..a02b0d8254 100644
--- a/tests/studio/test_compact_dropdown_submenus.py
+++ b/tests/studio/test_compact_dropdown_submenus.py
@@ -22,7 +22,7 @@ def test_shared_submenu_uses_its_layout_width_on_mobile():
 
 def test_shared_submenu_never_exceeds_the_compact_viewport():
     source = DROPDOWN_MENU.read_text(encoding = "utf-8")
-    assert "max-w-[calc(100vw-2rem)]" in source
+    assert "max-w-[calc(100vw-32px)]" in source
 
 
 def test_consumers_do_not_duplicate_compact_offset_logic():
diff --git a/tests/studio/test_desktop_reliability_frontend_contract.py b/tests/studio/test_desktop_reliability_frontend_contract.py
new file mode 100644
index 0000000000..868895b8f0
--- /dev/null
+++ b/tests/studio/test_desktop_reliability_frontend_contract.py
@@ -0,0 +1,131 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Static contracts for focused packaged-desktop reliability behavior."""
+
+from pathlib import Path
+
+
+REPO = Path(__file__).resolve().parents[2]
+FRONTEND = REPO / "studio/frontend/src"
+NATIVE_FILES = FRONTEND / "lib/native-files.ts"
+CHAT_EXPORT = FRONTEND / "features/chat/utils/export-chat-history.ts"
+DATA_TAB = FRONTEND / "features/settings/tabs/data-tab.tsx"
+PROMPT_STORAGE = FRONTEND / "features/chat/prompt-storage/prompt-storage-dialog.tsx"
+
+APP_SIDEBAR = FRONTEND / "components/app-sidebar.tsx"
+THREAD = FRONTEND / "components/assistant-ui/thread.tsx"
+THREAD_SIDEBAR = FRONTEND / "features/chat/thread-sidebar.tsx"
+SHARED_COMPOSER = FRONTEND / "features/chat/shared-composer.tsx"
+TITLEBAR = FRONTEND / "components/tauri/window-titlebar.tsx"
+NATIVE_DIALOGS = REPO / "studio/src-tauri/src/native_file_dialogs.rs"
+
+
+APP_PROVIDER = FRONTEND / "app/provider.tsx"
+
+
+def test_file_actions_route_through_native_commands_only_in_tauri():
+    helper = NATIVE_FILES.read_text(encoding = "utf-8")
+    history = CHAT_EXPORT.read_text(encoding = "utf-8")
+    data_tab = DATA_TAB.read_text(encoding = "utf-8")
+    prompt_storage = PROMPT_STORAGE.read_text(encoding = "utf-8")
+
+    projects = (FRONTEND / "features/chat/projects-page.tsx").read_text(encoding = "utf-8")
+
+    assert 'invoke<string | null>("save_native_file", bytes, {' in helper
+    assert '"x-unsloth-default-name"' in helper
+    assert "Array.from(new Uint8Array" not in helper
+    assert 'invoke<NativeChatImport | null>("pick_native_chat_import")' in helper
+    assert "if (isTauri)" in helper
+    assert 'document.createElement("a")' in helper
+    assert "DownloadCancelledError" in helper
+    assert "throw new DownloadCancelledError()" in helper
+    assert "return savedPath !== null" not in helper
+
+    assert helper.index("if (isTauri)") < helper.index("  const blob =")
+    assert "downloadFile(" in history
+    assert "downloadFile(" in prompt_storage
+    assert "pickNativeChatImport" in data_tab
+    assert "if (!isTauri)" in data_tab
+
+    assert "pickNativeChatImport" in projects
+    assert "if (!isTauri)" in projects
+    # Browser builds retain the existing hidden-input route.
+    assert 'type="file"' in data_tab
+    assert 'accept=".jsonl,.ndjson,.csv"' in data_tab
+
+    native_dialogs = NATIVE_DIALOGS.read_text(encoding = "utf-8")
+    assert 'CHAT_IMPORT_EXTENSIONS: &[&str] = &["jsonl", "ndjson", "csv"]' in native_dialogs
+    assert "InvokeBody::Raw" in native_dialogs
+
+    assert ".tempfile_in(parent)" in native_dialogs
+    assert ".persist(&path)" in native_dialogs
+    assert "fs::write(&path, content)" not in native_dialogs
+
+
+def test_chat_exports_await_native_saves_and_markdown_uses_shared_helper():
+    app_sidebar = APP_SIDEBAR.read_text(encoding = "utf-8")
+    prompt_storage = PROMPT_STORAGE.read_text(encoding = "utf-8")
+    thread = THREAD.read_text(encoding = "utf-8")
+    thread_sidebar = THREAD_SIDEBAR.read_text(encoding = "utf-8")
+    shared_composer = SHARED_COMPOSER.read_text(encoding = "utf-8")
+
+    data_tab = DATA_TAB.read_text(encoding = "utf-8")
+    projects = (FRONTEND / "features/chat/projects-page.tsx").read_text(encoding = "utf-8")
+    assert "async function downloadBlob(" in prompt_storage
+    download_blob = prompt_storage.split("async function downloadBlob(", 1)[1].split("\n}\n", 1)[0]
+    assert "return downloadFile(" in download_blob
+    assert "catch (error)" not in download_blob
+    assert "isDownloadCancelled(error)" in prompt_storage
+
+    for source in (app_sidebar, thread, thread_sidebar, shared_composer, data_tab, projects):
+        assert "isDownloadCancelled(error)" in source
+    assert "const handleExport = useCallback(async () =>" in prompt_storage
+    assert prompt_storage.count("await export") >= 12
+    assert "await Promise.all(" not in app_sidebar
+    assert "for (const id of ids)" in app_sidebar
+    assert prompt_storage.count("await downloadBlob(") >= 5
+
+    assert "await downloadBlob(zipped," in prompt_storage
+    assert "new Blob([zipped]" not in prompt_storage
+    assert "Promise.all(ids.map((id) => fn(id)))" not in thread_sidebar
+    assert "for (const id of ids)" in thread_sidebar
+    assert "Promise.all(exportThreadIds.map((id) => fn(id)))" not in shared_composer
+    assert "for (const id of exportThreadIds)" in shared_composer
+    assert "onExport={exportMessageMarkdown}" in thread
+    assert '"text/markdown"' in thread
+    assert "downloadFile(" in thread
+
+
+def test_full_app_layout_uses_its_own_initialized_marker():
+    source = APP_PROVIDER.read_text(encoding = "utf-8")
+
+    assert 'invoke<boolean>("has_initialized_app_window_layout")' in source
+    setup_layout = source.split("async function showSetupWindow", 1)[1].split(
+        "async function enforceMinimumWindowSize", 1
+    )[0]
+    reset_call = 'invoke("reset_app_window_layout_initialized")'
+    assert reset_call in setup_layout
+    assert setup_layout.index(reset_call) < setup_layout.index("win.setSize")
+    assert 'invoke("mark_app_window_layout_initialized")' in source
+    assert "hasInitializedAppLayout && hasSavedState" in source
+
+
+def test_expanded_titlebar_button_and_corner_match_sidebar_edge():
+    source = TITLEBAR.read_text(encoding = "utf-8")
+
+    assert 'pinned ? "gap-2 pl-3" : "justify-center"' in source
+    assert "gap-2 px-3" not in source
+    assert "const contentBorderLeft = pinned" in source
+    assert ': "0px";' in source
+    # The curved transition and sidebar-colored backing are expanded-only;
+    # collapsed content is square and its divider spans the sidebar too.
+    assert source.count("{showSidebarSurface && pinned && (") == 2
+    assert (
+        'className="pointer-events-none absolute top-full size-3 -translate-x-px bg-sidebar"'
+        in source
+    )
+    assert (
+        'className="pointer-events-none absolute top-full size-3 -translate-x-px rounded-tl-[12px] border-l border-t border-sidebar-border bg-background"'
+        in source
+    )
diff --git a/tests/studio/test_gpu_inference_smoke.py b/tests/studio/test_gpu_inference_smoke.py
new file mode 100644
index 0000000000..a28166e1e0
--- /dev/null
+++ b/tests/studio/test_gpu_inference_smoke.py
@@ -0,0 +1,65 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Fast, GPU-gated real-inference smoke.
+
+GitHub-hosted CI runners have no GPU, so this AUTO-SKIPS there; the full picker
+-> load -> chat flow is covered on CPU by tests/studio/playwright_model_config.py
+and studio-ui-smoke.yml. This test adds a quick real-generation check for local
+dev and self-hosted GPU runners: it loads the smallest model (gemma-3-270m-it)
+on the GPU and does a single short greedy generation, asserting a non-empty
+reply. Kept deliberately short (a handful of new tokens) so it is a confidence
+check, not a benchmark. Select/deselect it by name, e.g. `-k gpu_generation`.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+torch = pytest.importorskip("torch")
+
+# Smallest instruct model in the CI fixture family; ~270M params loads and
+# generates a few tokens in seconds on any GPU.
+MODEL_ID = "unsloth/gemma-3-270m-it"
+# A handful of forced real tokens: enough to prove GPU decode produced content,
+# short enough to stay a few seconds.
+MIN_NEW_TOKENS = 4
+MAX_NEW_TOKENS = 16
+
+
+@pytest.mark.skipif(not torch.cuda.is_available(), reason = "requires a CUDA GPU")
+def test_gpu_generation_smoke():
+    try:
+        from transformers import AutoModelForCausalLM, AutoTokenizer
+    except Exception as exc:  # pragma: no cover - env without transformers
+        pytest.skip(f"transformers unavailable: {exc}")
+
+    # Gemma is numerically unstable in fp16 (it emits only <pad>); use bf16 where
+    # supported, else fp32. The model is tiny, so fp32 is still fast.
+    dtype = torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float32
+    try:
+        tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+        model = AutoModelForCausalLM.from_pretrained(MODEL_ID, dtype = dtype).to("cuda")
+    except Exception as exc:  # offline / gated / download failure is not a code defect
+        pytest.skip(f"could not fetch/load {MODEL_ID}: {exc}")
+
+    model.eval()
+    messages = [{"role": "user", "content": "Say hello in one word."}]
+    inputs = tokenizer.apply_chat_template(
+        messages, add_generation_prompt = True, return_dict = True, return_tensors = "pt"
+    ).to("cuda")
+    prompt_len = inputs["input_ids"].shape[1]
+
+    with torch.no_grad():
+        output = model.generate(
+            **inputs,
+            min_new_tokens = MIN_NEW_TOKENS,
+            max_new_tokens = MAX_NEW_TOKENS,
+            do_sample = False,
+        )
+
+    # The model produced new tokens on the GPU (the real inference proof)...
+    assert output.shape[1] > prompt_len, "no tokens were generated on the GPU"
+    # ...and they decode to non-empty text (min_new_tokens forces real content).
+    reply = tokenizer.decode(output[0][prompt_len:], skip_special_tokens = True)
+    assert reply.strip(), "expected a non-empty GPU generation"
diff --git a/tests/studio/test_hf_token_validation_tick_contract.py b/tests/studio/test_hf_token_validation_tick_contract.py
new file mode 100644
index 0000000000..a381101801
--- /dev/null
+++ b/tests/studio/test_hf_token_validation_tick_contract.py
@@ -0,0 +1,28 @@
+"""Contracts for the Hugging Face token validation indicator."""
+
+from pathlib import Path
+
+
+REPO = Path(__file__).resolve().parents[2]
+GENERAL_TAB = REPO / "studio/frontend/src/features/settings/tabs/general-tab.tsx"
+VALIDATION_HOOK = REPO / "studio/frontend/src/hooks/use-hf-token-validation.ts"
+
+
+def test_success_tick_requires_the_current_token_to_be_validated():
+    source = GENERAL_TAB.read_text(encoding = "utf-8")
+
+    assert "tokenIsCurrent && tokenValidation.isValid === true" in source
+    assert 'tokenValidated ? "pr-14" : "pr-8"' in source
+    assert "{tokenValidated ? (" in source
+    assert 'aria-label={t("settings.general.tokenValidated")}' in source
+    assert 'aria-label={t("settings.general.tokenSaved")}' not in source
+
+
+def test_validation_result_must_belong_to_the_current_normalized_token():
+    source = VALIDATION_HOOK.read_text(encoding = "utf-8")
+
+    assert "const normalizedToken = token.trim()" in source
+    assert "useDebouncedValue(normalizedToken, 500)" in source
+    assert "if (!COMPLETE_HF_TOKEN.test(normalizedToken)) return INITIAL" in source
+    assert "if (completed.token !== normalizedToken)" in source
+    assert "if (completed.token !== debouncedToken)" not in source
diff --git a/tests/studio/test_install_rollback_lifecycle.ps1 b/tests/studio/test_install_rollback_lifecycle.ps1
new file mode 100644
index 0000000000..d70f384ca7
--- /dev/null
+++ b/tests/studio/test_install_rollback_lifecycle.ps1
@@ -0,0 +1,126 @@
+#!/usr/bin/env pwsh
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+# Unit tests for install.ps1's venv rollback helpers. The functions are AST-extracted
+# so the top-level installer is never executed.
+
+$ErrorActionPreference = "Stop"
+$installPath = [System.IO.Path]::Combine($PSScriptRoot, "..", "..", "install.ps1")
+$installPath = (Resolve-Path $installPath).Path
+
+$tokens = $null; $errors = $null
+$ast = [System.Management.Automation.Language.Parser]::ParseFile($installPath, [ref]$tokens, [ref]$errors)
+if ($errors) { $errors | ForEach-Object { $_.ToString() }; throw "install.ps1 has parse errors" }
+
+$helperNames = @(
+    "Start-StudioVenvRollback",
+    "Remove-StudioVenvTreeWithRetry",
+    "Test-StudioVenvRollbackMustBePreserved",
+    "Remove-StaleStudioVenvRollbacks",
+    "Restore-StudioVenvRollback",
+    "Complete-StudioVenvRollback"
+)
+foreach ($name in $helperNames) {
+    $fn = $ast.FindAll({ param($node)
+        $node -is [System.Management.Automation.Language.FunctionDefinitionAst] -and $node.Name -eq $name
+    }, $true)
+    if ($fn.Count -ne 1) { throw "expected exactly one $name in install.ps1, found $($fn.Count)" }
+    Invoke-Expression $fn[0].Extent.Text
+}
+
+function substep { param([string]$Message, [string]$Color) }
+
+$failures = 0
+function Check($name, $condition) {
+    if ($condition) { Write-Host "  PASS  $name" }
+    else { Write-Host "  FAIL  $name" -ForegroundColor Red; $script:failures++ }
+}
+
+function Reset-RollbackState($target) {
+    $script:StudioVenvRollbackDir = $null
+    $script:StudioVenvRollbackTarget = $target
+    $script:StudioVenvRollbackActive = $false
+}
+
+$StudioHome = Join-Path ([System.IO.Path]::GetTempPath()) "unsloth-rollback-$([guid]::NewGuid().ToString('N'))"
+$VenvDir = Join-Path $StudioHome "unsloth_studio"
+[System.IO.Directory]::CreateDirectory($VenvDir) | Out-Null
+
+try {
+    Write-Host "Successful replacement"
+    [System.IO.File]::WriteAllText((Join-Path $VenvDir "generation"), "old")
+    Reset-RollbackState $VenvDir
+    Start-StudioVenvRollback -ExistingDir $VenvDir
+    [System.IO.Directory]::CreateDirectory($VenvDir) | Out-Null
+    [System.IO.File]::WriteAllText((Join-Path $VenvDir "generation"), "new")
+    Complete-StudioVenvRollback
+    Check "new environment remains" ((Get-Content -LiteralPath (Join-Path $VenvDir "generation") -Raw) -eq "new")
+    Check "current rollback is removed" (-not @(Get-ChildItem -LiteralPath $StudioHome -Directory |
+        Where-Object { $_.Name -like "unsloth_studio.rollback.*" }))
+
+    Write-Host "Stale cleanup"
+    $stale = Join-Path $StudioHome "unsloth_studio.rollback.20000101000000.2147483647"
+    $active = Join-Path $StudioHome "unsloth_studio.rollback.20000101000001.$PID"
+    $unrecognized = Join-Path $StudioHome "unsloth_studio.rollback.user-data"
+    [System.IO.Directory]::CreateDirectory($stale) | Out-Null
+    [System.IO.Directory]::CreateDirectory($active) | Out-Null
+    [System.IO.Directory]::CreateDirectory($unrecognized) | Out-Null
+    Remove-StaleStudioVenvRollbacks
+    Check "dead-owner rollback is removed" (-not (Test-Path -LiteralPath $stale))
+    Check "live-owner rollback is preserved" (Test-Path -LiteralPath $active)
+    Check "unrecognized rollback name is preserved" (Test-Path -LiteralPath $unrecognized)
+    Microsoft.PowerShell.Management\Remove-Item -LiteralPath $active -Recurse -Force
+    Microsoft.PowerShell.Management\Remove-Item -LiteralPath $unrecognized -Recurse -Force
+
+    Write-Host "Failure restoration"
+    [System.IO.File]::WriteAllText((Join-Path $VenvDir "generation"), "old-again")
+    Reset-RollbackState $VenvDir
+    $committed = $false
+    try {
+        try {
+            Start-StudioVenvRollback -ExistingDir $VenvDir
+            [System.IO.Directory]::CreateDirectory($VenvDir) | Out-Null
+            [System.IO.File]::WriteAllText((Join-Path $VenvDir "generation"), "partial")
+            throw "simulated install failure"
+        } finally {
+            if (-not $committed) { Restore-StudioVenvRollback }
+        }
+    } catch {
+        if ($_.Exception.Message -ne "simulated install failure") { throw }
+    }
+    Check "finally restores the previous environment" (
+        (Get-Content -LiteralPath (Join-Path $VenvDir "generation") -Raw) -eq "old-again"
+    )
+    Check "failure restoration consumes the rollback" (-not @(Get-ChildItem -LiteralPath $StudioHome -Directory |
+        Where-Object { $_.Name -like "unsloth_studio.rollback.*" }))
+
+    Write-Host "Locked-file retry"
+    $retryDir = Join-Path $StudioHome "retry"
+    [System.IO.Directory]::CreateDirectory($retryDir) | Out-Null
+    $script:removeAttempts = 0
+    function Remove-Item {
+        param(
+            [string]$LiteralPath,
+            [switch]$Recurse,
+            [switch]$Force,
+            [object]$ErrorAction
+        )
+        $script:removeAttempts++
+        if ($script:removeAttempts -lt 3) { throw "simulated lock" }
+        Microsoft.PowerShell.Management\Remove-Item -LiteralPath $LiteralPath -Recurse:$Recurse -Force:$Force
+    }
+    try {
+        $removed = Remove-StudioVenvTreeWithRetry -Path $retryDir -Label "test rollback"
+    } finally {
+        Microsoft.PowerShell.Management\Remove-Item -LiteralPath Function:\Remove-Item -Force
+    }
+    Check "locked rollback deletion retries" ($removed -and $script:removeAttempts -eq 3)
+} finally {
+    if (Test-Path -LiteralPath $StudioHome) {
+        Microsoft.PowerShell.Management\Remove-Item -LiteralPath $StudioHome -Recurse -Force
+    }
+}
+
+Write-Host ""
+if ($failures -gt 0) { Write-Host "$failures check(s) FAILED" -ForegroundColor Red; exit 1 }
+Write-Host "All checks passed" -ForegroundColor Green
diff --git a/tests/studio/test_model_picker_contracts.py b/tests/studio/test_model_picker_contracts.py
new file mode 100644
index 0000000000..baf0fdf1bf
--- /dev/null
+++ b/tests/studio/test_model_picker_contracts.py
@@ -0,0 +1,444 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Source-contract guards for the model-picker per-model-config feature.
+
+These are cheap, CPU-only, no-browser checks that read the frontend source and
+assert the specific fixes that got the predecessor PR reverted stay in place. If
+a future edit reverts one of them (e.g. rounds the context ceiling up again, or
+puts the HF token back in the URL), the matching assertion reddens. They pair
+with the runtime Playwright checks (which prove the behavior end to end) and the
+backend pytest checks (which prove the backend logic).
+"""
+
+from __future__ import annotations
+
+import re
+from pathlib import Path
+
+WORKDIR = Path(__file__).resolve().parents[2]
+FRONTEND = WORKDIR / "studio" / "frontend" / "src"
+
+
+def _read(rel: str) -> str:
+    path = FRONTEND / rel
+    assert path.exists(), f"missing source file: {path}"
+    return path.read_text()
+
+
+def test_models_api_sends_token_via_header_not_query():
+    """getModelConfig / checkVisionModel / checkEmbeddingModel must pass the HF
+    token through hubTokenHeader, never as a ?hf_token= query param (which leaks
+    the credential into server/proxy access logs)."""
+    src = _read("features/training/api/models-api.ts")
+    assert src.count("hubTokenHeader(") >= 3
+    assert "hf_token=" not in src
+    assert '"hf_token"' not in src and "'hf_token'" not in src
+
+
+def test_model_metadata_probe_never_puts_token_in_query():
+    src = _read("features/model-picker/api/model-metadata.ts")
+    assert "hf_token=" not in src
+    assert '"hf_token"' not in src and "'hf_token'" not in src
+
+
+def test_model_config_page_floors_the_context_ceiling():
+    """The model's native max-context must be FLOORED to the step grid, never
+    rounded up (rounding up can offer/persist a length above the model's real
+    ceiling and break loading)."""
+    src = _read("features/model-picker/components/model-config-page.tsx")
+    assert "floorMaxSeqLength(modelMaxPosition.maxPositionEmbeddings)" in src
+    assert "normalizeMaxSeqLength(modelMaxPosition.maxPositionEmbeddings)" not in src
+
+
+def test_compare_load_clears_stale_native_lease():
+    """A compare-pane load never comes from the desktop file picker, so it must
+    clear any prior picked file's lease token + expiry, otherwise a reload can
+    send a stale lease for the now-active model."""
+    src = _read("features/chat/shared-composer.tsx")
+    assert "activeNativePathToken: null" in src
+    assert "activeNativePathExpiresAtMs: null" in src
+
+
+def test_autoload_records_backend_loaded_model_identity():
+    """An inactive-cache inventory row loads by local path, so startup autoload
+    must key both the active checkpoint and its summary by the backend's loaded
+    model identity instead of the catalog repo id."""
+    src = _read("features/chat/api/chat-adapter.ts")
+    autoload = src.split("async function loadAutoLoadCandidate", 1)[1]
+    autoload = autoload.split("\n  try {", 1)[0]
+    assert "const loadedModelId = loadResp.model || modelPath" in autoload
+    assert "setCheckpoint(loadedModelId," in autoload
+    assert "id: loadedModelId" in autoload
+    assert "m.id === loadedModelId" in autoload
+
+
+def test_rollback_restores_native_lease_expiry_with_token():
+    """A failed model switch that rolls back to a previously loaded picked GGUF
+    must restore the lease expiry paired with the token, never the token alone
+    (which would look non-expiring and skip the expiry guard)."""
+    src = _read("features/chat/hooks/use-chat-model-runtime.ts")
+    assert "previousActiveNativePathExpiresAtMs" in src
+    assert re.search(
+        r"activeNativePathExpiresAtMs:\s*previousActiveNativePathToken", src
+    ), "rollback must restore the expiry alongside the token"
+
+
+def test_default_caches_keyed_on_inventory_version():
+    """The chat-template and max-position caches must key on the inventory
+    version so a model update in the same session invalidates the cached value
+    instead of showing the stale revision."""
+    src = _read("features/model-picker/hooks/use-model-defaults.ts")
+    # Both cache keys (template + max-position) end with the inventory version.
+    assert src.count("${inventoryVersion}") >= 2
+
+
+def test_hidden_infra_model_needles_present():
+    """The frontend static needle list must keep hiding the RAG embedder and the
+    llama.cpp validation probe."""
+    src = _read("features/hub/lib/hidden-models.ts")
+    assert '"bge-small-en-v1.5"' in src
+    assert '"ggml-org/models"' in src
+    assert '"stories260k.gguf"' in src
+
+
+def test_hidden_models_dynamic_exact_ids_wired():
+    """The configured embedder arrives from /api/hub/hidden-models as exact
+    repo ids; a substring needle would let a generic basename like "model"
+    hide unrelated chat models."""
+    src = _read("features/hub/lib/hidden-models.ts")
+    assert "toLowerStrings(data.exact_ids)" in src
+    assert "dynamicExactIds.includes(lower)" in src
+
+
+def test_hidden_model_matchers_refresh_with_inventory_version():
+    src = _read("features/hub/lib/hidden-models.ts")
+    assert "const version = getInventoryVersion()" in src
+    assert "matchersFetchVersion === version" in src
+    assert "getInventoryVersion() !== version" in src
+
+
+def test_diffusion_capability_labeled_image_generation():
+    """The diffusion capability detects image GENERATORS (FLUX, SDXL,
+    text-to-image tags); labeling it "Image to text" showed generators when
+    users asked for captioning models."""
+    for rel in (
+        "features/hub/lib/model-capabilities.ts",
+        "features/hub/lib/model-type-filter.ts",
+        "features/hub/lib/view-models.ts",
+    ):
+        src = _read(rel)
+        assert "Image to text" not in src, rel
+        assert "Image generation" in src, rel
+
+
+def test_active_model_config_round_trips_gpu_fields():
+    """The active model's config must carry the GPU Memory knobs (GGUF only) so
+    a sidebar/hub-gear reload cannot silently reset manual GPU settings, and
+    "Remember settings" cannot persist a GPU-less config over a saved one."""
+    src = _read("features/model-picker/hooks/use-active-model-config.ts")
+    for field in ("gpuMemoryMode", "gpuLayers", "nCpuMoe", "selectedGpuIds"):
+        assert field in src, field
+    assert "if (!isGguf)" in src and "return base" in src
+    for rel in (
+        "features/chat/chat-page.tsx",
+        "features/hub/catalog/sampling-settings-dialog.tsx",
+    ):
+        assert "useActiveModelConfig(" in _read(rel), rel
+    signature = _read("features/model-picker/components/sidebar-model-config.tsx")
+    assert "gpuFieldsSignature(config)" in signature
+    shared = _read("features/model-picker/model-config/apply-per-model-config.ts")
+    assert "export function gpuFieldsSignature" in shared
+
+
+def test_compare_load_uses_each_models_gpu_config():
+    src = _read("features/chat/shared-composer.tsx")
+    assert "ownConfig.gpuMemoryMode ?? compareLoadKnobs.gpuMemoryMode" in src
+    assert "ownConfig.gpuLayers ?? compareLoadKnobs.gpuLayers" in src
+    assert "ownConfig.nCpuMoe ?? compareLoadKnobs.nCpuMoe" in src
+    assert "if (ownConfig.selectedGpuIds != null)" in src
+    assert "reconcilePersistedGpuIds(ownConfig.selectedGpuIds)" in src
+    for field in (
+        "gpu_memory_mode: effectiveGpuMemoryMode",
+        "gpu_layers: effectiveGpuLayers",
+        "n_cpu_moe: effectiveNCpuMoe",
+        "gpu_ids: effectiveSelectedGpuIds ?? undefined",
+    ):
+        assert field in src
+
+
+def test_active_native_gguf_metadata_uses_path_token():
+    src = _read("features/model-picker/components/model-config-page.tsx")
+    assert "(isActiveModel ? activeNativePathToken : null)" in src
+    assert "target.meta.nativePathToken ??" in src
+    assert "nativePathToken," in src
+    assert '${nativePathToken ?? ""}' in src
+
+
+def test_model_default_hooks_do_not_reset_state_in_effect():
+    src = _read("features/model-picker/hooks/use-model-defaults.ts")
+    assert "setFetched(null)" not in src
+
+
+def test_variant_expander_refreshes_after_delete():
+    """Deleting a downloaded quant from an expanded repo that still has other
+    cached quants must bump the expander refresh key, or the deleted quant stays
+    shown as downloaded and clickable and tries to reload the removed file."""
+    src = _read("features/model-picker/components/model-selector/pickers.tsx")
+    del_confirm = re.search(
+        r"await onDeleteVariant\(v\.quant\);.*?setRefreshKey\(\(key\) => key \+ 1\)",
+        src,
+        re.S,
+    )
+    assert del_confirm, "delete onConfirm must bump refreshKey after a successful delete"
+
+
+def test_local_picker_rows_require_chat_capability():
+    """Local inventory rows can be classified non-chat (canChat false, e.g. a
+    folder with only config.json). The picker must filter those out, or selecting
+    one loads a weightless path; toLocalModelInfo drops capabilities so the memo
+    is the only place the guard can live."""
+    src = _read("features/model-picker/inventory/use-chat-picker-inventory.ts")
+    memo = re.search(r"const localModels = useMemo\(.*?\[inventory\.localRows\]", src, re.S)
+    assert memo, "localModels memo not found"
+    assert "row.capabilities.canChat" in memo.group(0)
+
+
+def test_native_picked_gguf_template_read_through_lease():
+    """A native (picked / drag-drop) GGUF's path lives only in its signed lease,
+    and the picker chat-template GET has no lease plumbing, so the default
+    template must be read through the lease-aware validate probe: mint a
+    validate-model lease and post include_chat_template. The native token also
+    has to reach the fetch (threaded through the hook) and be part of the cache
+    key so two picks of the same basename don't share a template."""
+    api = _read("features/model-picker/api/templates.ts")
+    assert 'consumeNativePathToken(nativePathToken, "validate-model")' in api
+    assert "include_chat_template: true" in api
+    assert "/api/inference/validate" in api
+    hook = _read("features/model-picker/hooks/use-model-defaults.ts")
+    assert "nativePathToken," in hook
+    assert '${nativePathToken ?? ""}' in hook
+
+
+def test_model_load_guard_is_cross_instance():
+    """The in-flight load guard must consult the shared store pick (not only the
+    per-hook ref) and ejectModel must refuse while any instance is loading:
+    three live useChatModelRuntime instances exist (chat page, hub page, hub
+    gear dialog)."""
+    src = _read("features/chat/hooks/use-chat-model-runtime.ts")
+    assert "useChatRuntimeStore.getState().loadingModelPick" in src
+    assert "clearLoadingModelPick" in src
+    eject_body = src.split("const ejectModel", 1)[1]
+    assert "loadingModelPick" in eject_body.split("ejectModel,", 1)[0]
+
+
+def test_partial_safetensors_download_keeps_delete_menu():
+    """A stopped partial safetensors download must keep its options menu (the
+    Delete affordance) like the GGUF card does, or partial downloads can only
+    be cleaned up by finishing or leaving them. During an ACTIVE download the
+    menu stays hidden (every item would be disabled: no Copy path while not
+    downloaded, no Delete while downloading, pin suppressed in the run bar)."""
+    src = _read("features/hub/catalog/safetensors-download-card.tsx")
+    assert "(isDownloaded || (isPartial && !downloading))" in src
+
+
+def test_pinned_validation_uses_cached_local_variant_listing():
+    """Pinned-quant validation must use the TTL-cached hub client with
+    preferLocalCache (downloaded-ness is local state) instead of one uncached
+    round-trip per pinned repo on every picker open. Picker deletes must go
+    through the hub inventory client, whose delete invalidates both the
+    variants TTL cache and the server-side HF cache scan (the legacy
+    /api/models/delete-cached route invalidates neither, so a post-delete
+    inventory refresh would resurrect the deleted row until the scan TTL)."""
+    src = _read("features/model-picker/components/model-selector/pickers.tsx")
+    assert "listGgufVariantsCached(" in src
+    assert "preferLocalCache: true" in src
+    assert re.search(r'import \{[^}]*\bdeleteCachedModel\b[^}]*\} from "@/features/hub"', src)
+    hub_api = _read("features/hub/inventory/api.ts")
+    delete_fn = hub_api.split("export async function deleteCachedModel", 1)[1]
+    delete_fn = delete_fn.split("export ", 1)[0]
+    assert "invalidateGgufVariantsCache(" in delete_fn
+    assert "bumpInventoryVersion(" in delete_fn
+
+
+def test_chat_autoload_scopes_variant_lookup_to_cached_repo_path():
+    """Autoload must probe the exact cache row it will load, including rows
+    retained from a previously selected Hugging Face cache."""
+    src = _read("features/chat/api/chat-adapter.ts")
+    auto_load = src.split("async function autoLoadSmallestModel", 1)[1]
+    assert auto_load.count("preferLocalCache: true") >= 2
+    assert auto_load.count("localPath: repo.cache_path") >= 2
+
+    chat_api = _read("features/chat/api/chat-api.ts")
+    variants_fn = chat_api.split("export async function listGgufVariants", 1)[1]
+    variants_fn = variants_fn.split("export interface KvCacheEstimate", 1)[0]
+    assert 'params.set("prefer_local_cache", "true")' in variants_fn
+    assert 'params.set("local_path", localPath)' in variants_fn
+
+
+def test_cache_location_update_invalidates_frontend_inventory():
+    """A successful cache switch must refresh both inventory rows and cached
+    GGUF variant results before any stale active-cache identity can be reused."""
+    src = _read("features/settings/api/hugging-face-cache.ts")
+    update_fn = src.split("export async function updateHuggingFaceCacheSettings", 1)[1]
+    assert "bumpInventoryVersion();" in update_fn
+    assert "invalidateGgufVariantsCache();" in update_fn
+
+
+def test_downloaded_list_offsets_virtual_rows():
+    """The On Device virtualized list sits below the Pinned block in the same
+    scroll element, so it must pass its measured offset as scrollMargin or rows
+    past the overscan render blank."""
+    src = _read("features/hub/catalog/models-catalog-lists.tsx")
+    assert "scrollMargin={scrollMargin}" in src
+
+
+def test_local_gguf_diagnostics_gate_on_broad_is_gguf():
+    """The MTP fallback note and the context/VRAM warning must gate on the broad
+    isGguf (variant, loaded gguf context, or .gguf suffix), not the variant-only
+    isLoadedGguf, so direct-file and custom-folder GGUF loads keep those
+    diagnostics."""
+    src = _read("features/chat/chat-settings-sheet.tsx")
+    spec = re.search(r"const showSpecFallback =.*?;", src, re.S)
+    vram = re.search(r"const showContextVramWarning =.*?;", src, re.S)
+    assert spec and "isGguf &&" in spec.group(0) and "isLoadedGguf" not in spec.group(0)
+    assert vram and "isGguf &&" in vram.group(0) and "isLoadedGguf" not in vram.group(0)
+
+
+def test_fixed_layer_gguf_pins_displayed_context():
+    """An already-loaded auto-fit GGUF saved with Manual fixed GPU layers must
+    pin the shown context, so a later fresh load keeps the fitted placement
+    instead of sending native/0 and recreating the OOM."""
+    src = _read("features/model-picker/components/model-config-page.tsx")
+    assert "const pinFixedLayerContext =" in src
+    assert 'config.gpuMemoryMode === "manual"' in src
+    assert "customContextLength: activeLoadedContext" in src
+
+
+def test_auto_defaults_not_persisted_as_overrides():
+    """Auto GPU memory mode and Auto/default speculative type are follow-global
+    defaults; normalization must not persist them as per-model overrides, else a
+    model stops following later changes to the global preference."""
+    src = _read("features/model-picker/model-config/per-model-config.ts")
+    assert 'if (partial.gpuMemoryMode === "manual") {' in src
+    assert 'partial.gpuMemoryMode === "auto" || partial.gpuMemoryMode === "manual"' not in src
+    spec = re.search(r'if \(s === "auto" \|\| s === "default"\) \{\s*return ([^;]+);', src)
+    assert spec and spec.group(1).strip() == "null"
+
+
+def test_compare_pane_context_from_own_config_only():
+    """A compare pane's context comes from its own config only (a saved pin, else
+    null for Auto/native); it must not inherit the active model's shared snapshot,
+    which resolveFitMaxSeqLength would treat as an explicit pin (VRAM/OOM)."""
+    src = _read("features/chat/shared-composer.tsx")
+    assert "const effectiveCustomContextLength = ownConfig.customContextLength;" in src
+    assert "compareLoadKnobs.customContextLength" not in src
+
+
+def test_reset_max_seq_length_falls_back_to_app_default():
+    """After Reset clears maxSeqLength (null), a non-GGUF active model's shown
+    max sequence length must fall back to the app default, never the loaded
+    runtime snapshot, or a remembered/active override can never be cleared."""
+    src = _read("features/model-picker/components/model-config-page.tsx")
+    # The null fallback resolves to the app-default constant, not a runtime value.
+    assert "clampMaxSeqLength(DEFAULT_MAX_SEQ_LENGTH, nativeMaxSeqLength)" in src
+    # The buggy runtime-seeded fallback must not come back.
+    assert "clampMaxSeqLength(initialMaxSeqLength" not in src
+
+
+def test_reset_persists_null_max_length_and_substitutes_only_for_load():
+    """The persisted per-model record must keep config.maxSeqLength (null after
+    Reset) so isDefaultConfig can clear a remembered override; the concrete
+    fallback is substituted only into the load request, not the saved record."""
+    src = _read("features/model-picker/components/model-config-page.tsx")
+    # Load-only substitution of the resolved value.
+    assert "maxSeqLength: maxSeqLengthValue" in src
+    assert "const loadConfig" in src
+    # The persisted record is loaded via onRun(loadConfig), and save uses the
+    # untouched runtimeConfig (so a reset/default config stays default).
+    assert "onRun(loadConfig)" in src
+    assert "savePerModelConfig(" in src
+
+
+def test_reset_enabled_for_explicit_context_pin_at_native():
+    """An explicit customContextLength that equals the native ceiling is still a
+    user override, so contextAtDefault must require customContextLength == null.
+    The buggy form treated `contextValue === native` alone as default, wedging
+    the Reset button disabled for a deliberate pin-to-native."""
+    src = " ".join(_read("features/model-picker/components/model-config-page.tsx").split())
+    assert (
+        "const contextAtDefault = !target.isGguf || "
+        "(config.customContextLength == null && "
+        "(nativeContextLength == null || contextValue === nativeContextLength));" in src
+    )
+    # The old form that ignored an explicit pin equal to native must not return.
+    assert (
+        "(nativeContextLength == null ? config.customContextLength == null : "
+        "contextValue === nativeContextLength)" not in src
+    )
+    # The app-default constant is the single source of truth (imported, not local).
+    assert "DEFAULT_MAX_SEQ_LENGTH," in src
+    assert "const DEFAULT_MAX_SEQ_LENGTH = 4096" not in src
+
+
+def test_compare_pane_non_gguf_falls_back_to_app_default():
+    """A non-GGUF compare pane with no saved maxSeqLength must fall back to the
+    shared app default, not the active model's runtime snapshot; otherwise an
+    unconfigured pane inherits a saved 128K neighbor's context and can OOM."""
+    per_model = _read("features/model-picker/model-config/per-model-config.ts")
+    assert "export const DEFAULT_MAX_SEQ_LENGTH = 4096;" in per_model
+    barrel = _read("features/model-picker/index.ts")
+    assert "DEFAULT_MAX_SEQ_LENGTH," in barrel
+    src = " ".join(_read("features/chat/shared-composer.tsx").split())
+    assert "DEFAULT_MAX_SEQ_LENGTH," in src
+    assert (
+        "const effectiveMaxSeqLength = ownConfig.customContextLength ?? "
+        "normalizeMaxSeqLength(ownConfig.maxSeqLength) ?? "
+        "(isGgufLoad ? 0 : DEFAULT_MAX_SEQ_LENGTH);" in src
+    )
+    # The buggy fallback to the active model's shared runtime value must not return.
+    assert "(isGgufLoad ? 0 : maxSeqLength)" not in src
+    assert "const maxSeqLength = store.params.maxSeqLength;" not in src
+
+
+def test_default_gpu_mode_clears_manual_knobs():
+    """Switching GPU Memory back to Default must clear the Manual-only knobs
+    (gpuLayers/nCpuMoe/selectedGpuIds); otherwise a remembered config keeps stale
+    pins that a later load re-applies when the global preference is Manual."""
+    src = _read("features/model-picker/components/model-config-page.tsx")
+    assert 'gpuMemoryMode: "auto",' in src
+    assert "gpuLayers: undefined," in src
+    assert "nCpuMoe: undefined," in src
+    assert "selectedGpuIds: undefined," in src
+
+
+def test_legacy_migration_is_idempotent_and_non_destructive():
+    """The v1->v2 localStorage migration (unsloth_load_settings ->
+    unsloth_model_configs) is invoked on every store read, so it must be
+    idempotent: repeated reads, browser reloads, and Studio restarts must never
+    re-migrate, duplicate records, or overwrite a newer per-model config. This
+    was the class of regression that reverted the predecessor PR, so pin all
+    three idempotency layers at source level; dropping any of them reddens here.
+    """
+    raw = _read("features/model-picker/model-config/per-model-config.ts")
+    src = " ".join(raw.split())
+    # Migration runs from readMap (every store read), so it must be safe to repeat.
+    assert (
+        "function readMap(): StoredMap { migrateLegacyLoadSettingsOnce(); "
+        "return readMapRaw(); }" in src
+    )
+    # Layer 1: in-memory once-per-session guard so repeated readMap() calls
+    # migrate at most once.
+    assert "let legacyMigrationChecked = false;" in src
+    assert "if (legacyMigrationChecked || !canUseStorage()) {" in src
+    assert "legacyMigrationChecked = true;" in src
+    # Layer 2: persistent cross-session flag so a completed migration is never
+    # redone. Set in every terminal branch (malformed data, nothing to migrate,
+    # successful write); a failed quota write leaves it unset so the next session
+    # retries. Three set-sites encode exactly that.
+    assert 'const LEGACY_MIGRATION_FLAG = "unsloth_model_configs_migrated";' in src
+    assert "if (localStorage.getItem(LEGACY_MIGRATION_FLAG)) {" in src
+    assert src.count('localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");') >= 3
+    # Layer 3: non-overwriting merge skips an existing (or default) key, so even a
+    # forced re-run cannot duplicate or clobber a user's config.
+    assert "if (isDefaultConfig(migrated) || Object.hasOwn(map, key)) {" in src
diff --git a/tests/studio/test_reveal_file_manager.py b/tests/studio/test_reveal_file_manager.py
new file mode 100644
index 0000000000..8a1df586e5
--- /dev/null
+++ b/tests/studio/test_reveal_file_manager.py
@@ -0,0 +1,128 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Platform guards for the reveal-in-file-manager endpoint.
+
+A stock WSL distro has no Linux desktop, so the generic Linux branch
+(``xdg-open``) fails there. Under WSL the reveal must route through Windows
+interop (``wslpath -w`` + ``explorer.exe``), fall back to ``xdg-open`` when
+interop is unavailable, and leave native Linux behavior unchanged.
+"""
+
+from __future__ import annotations
+
+import os
+import subprocess
+import sys
+import types
+from pathlib import Path
+
+import pytest
+
+
+def _find_repo_root() -> Path | None:
+    env = os.environ.get("UNSLOTH_REPO_ROOT")
+    if env:
+        p = Path(env).resolve()
+        if (p / "studio" / "backend").is_dir():
+            return p
+    here = Path(__file__).resolve()
+    for parent in (here, *here.parents):
+        if (parent / "studio" / "backend").is_dir():
+            return parent
+    return None
+
+
+_REPO_ROOT = _find_repo_root()
+if _REPO_ROOT is None:
+    pytest.skip(
+        "Could not locate studio/backend. Set UNSLOTH_REPO_ROOT or run from "
+        "the repository checkout.",
+        allow_module_level = True,
+    )
+
+_STUDIO_BACKEND = _REPO_ROOT / "studio" / "backend"
+if str(_STUDIO_BACKEND) not in sys.path:
+    sys.path.insert(0, str(_STUDIO_BACKEND))
+
+pytest.importorskip("fastapi")
+pytest.importorskip("huggingface_hub")
+
+try:
+    from routes import models as routes_models
+    from utils.paths import path_utils
+except Exception as exc:
+    pytest.skip(f"studio backend import unavailable: {exc}", allow_module_level = True)
+
+_WINDOWS_PATH = r"\\wsl.localhost\Distro\cache\model.gguf"
+
+
+@pytest.fixture()
+def linux_host(monkeypatch):
+    monkeypatch.setattr(sys, "platform", "linux")
+    monkeypatch.setattr(os, "name", "posix")
+
+
+@pytest.fixture()
+def spawned(monkeypatch):
+    calls = types.SimpleNamespace(run = [], popen = [], run_error = None)
+
+    def fake_run(cmd, **kwargs):
+        calls.run.append(list(cmd))
+        if calls.run_error is not None:
+            raise calls.run_error
+        return types.SimpleNamespace(stdout = _WINDOWS_PATH + "\n")
+
+    def fake_popen(cmd, **kwargs):
+        calls.popen.append(list(cmd))
+        return types.SimpleNamespace()
+
+    monkeypatch.setattr(subprocess, "run", fake_run)
+    monkeypatch.setattr(subprocess, "Popen", fake_popen)
+    return calls
+
+
+def test_wsl_file_is_selected_in_explorer(linux_host, spawned, monkeypatch, tmp_path):
+    monkeypatch.setattr(path_utils, "_IS_WSL", True)
+    target = tmp_path / "model.gguf"
+    target.write_bytes(b"gguf")
+    routes_models._reveal_in_file_manager(target)
+    assert spawned.run == [["wslpath", "-w", str(target)]]
+    assert spawned.popen == [["explorer.exe", f"/select,{_WINDOWS_PATH}"]]
+
+
+def test_wsl_directory_opens_in_explorer(linux_host, spawned, monkeypatch, tmp_path):
+    monkeypatch.setattr(path_utils, "_IS_WSL", True)
+    routes_models._reveal_in_file_manager(tmp_path)
+    assert spawned.popen == [["explorer.exe", _WINDOWS_PATH]]
+
+
+def test_wsl_without_interop_falls_back_to_xdg_open(linux_host, spawned, monkeypatch, tmp_path):
+    monkeypatch.setattr(path_utils, "_IS_WSL", True)
+    spawned.run_error = FileNotFoundError("wslpath")
+    target = tmp_path / "model.gguf"
+    target.write_bytes(b"gguf")
+    routes_models._reveal_in_file_manager(target)
+    assert spawned.popen == [["xdg-open", str(tmp_path)]]
+
+
+def test_wsl_empty_conversion_falls_back_to_xdg_open(linux_host, spawned, monkeypatch, tmp_path):
+    monkeypatch.setattr(path_utils, "_IS_WSL", True)
+
+    def empty_run(cmd, **kwargs):
+        return types.SimpleNamespace(stdout = "\n")
+
+    monkeypatch.setattr(subprocess, "run", empty_run)
+    routes_models._reveal_in_file_manager(tmp_path)
+    assert spawned.popen == [["xdg-open", str(tmp_path)]]
+
+
+def test_native_linux_keeps_xdg_open_on_parent_directory(
+    linux_host, spawned, monkeypatch, tmp_path
+):
+    monkeypatch.setattr(path_utils, "_IS_WSL", False)
+    target = tmp_path / "model.gguf"
+    target.write_bytes(b"gguf")
+    routes_models._reveal_in_file_manager(target)
+    assert spawned.run == []
+    assert spawned.popen == [["xdg-open", str(tmp_path)]]
diff --git a/tests/studio/test_studio_text_descender_clipping.py b/tests/studio/test_studio_text_descender_clipping.py
index 359ca4873a..98fb3b4b13 100644
--- a/tests/studio/test_studio_text_descender_clipping.py
+++ b/tests/studio/test_studio_text_descender_clipping.py
@@ -10,7 +10,14 @@ from pathlib import Path
 
 WORKDIR = Path(__file__).resolve().parents[2]
 MODEL_SELECTOR = (
-    WORKDIR / "studio" / "frontend" / "src" / "components" / "assistant-ui" / "model-selector.tsx"
+    WORKDIR
+    / "studio"
+    / "frontend"
+    / "src"
+    / "features"
+    / "model-picker"
+    / "components"
+    / "model-selector.tsx"
 )
 APP_SIDEBAR = WORKDIR / "studio" / "frontend" / "src" / "components" / "app-sidebar.tsx"
 
@@ -23,7 +30,7 @@ def _read(path: Path) -> str:
 def test_model_selector_trigger_label_uses_leading_tight():
     src = _read(MODEL_SELECTOR)
     pattern = re.compile(
-        r'<span\s+className="[^"]*\bmin-w-0\b[^"]*\bflex-1\b[^"]*\btruncate\b[^"]*\bfont-heading\b[^"]*\btext-\[16px\][^"]*"',
+        r'<span\s+className="[^"]*\bmin-w-0\b[^"]*\bflex-1\b[^"]*\btruncate\b[^"]*\bfont-heading\b[^"]*\btext-ui-16[^"]*"',
     )
     matches = pattern.findall(src)
     assert matches, "could not find ModelSelectorTrigger model-name span"
diff --git a/tests/studio/test_ui_font_scale_contract.py b/tests/studio/test_ui_font_scale_contract.py
new file mode 100644
index 0000000000..393c60dd6b
--- /dev/null
+++ b/tests/studio/test_ui_font_scale_contract.py
@@ -0,0 +1,145 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""UI font size scaling contracts (Settings > Appearance).
+
+The preference must scale typography through the --ui-font-scale tokens,
+never by mutating the root font size, so rem-based layout stays put. These
+contracts also act as the guard against reintroducing raw pixel typography
+that would silently ignore the preference.
+"""
+
+import re
+from pathlib import Path
+
+REPO = Path(__file__).resolve().parents[2]
+SRC = REPO / "studio/frontend/src"
+INDEX_CSS = (SRC / "index.css").read_text(encoding = "utf-8")
+STORE = (SRC / "features/settings/stores/appearance-custom-store.ts").read_text(encoding = "utf-8")
+SELECT = (SRC / "components/ui/select.tsx").read_text(encoding = "utf-8")
+
+# Raw numeric fontSize props are only allowed where a scaled stylesheet rule
+# (.recharts-text) overrides the presentation attribute at render time.
+FONTSIZE_PROP_ALLOWED_DIRS = (
+    "features/studio/sections/charts",
+    "features/studio/sections/training-section.tsx",
+)
+
+# Non-visible typography that intentionally stays fixed.
+FONTSIZE_STYLE_ALLOWLIST = {
+    # Offscreen textarea; 12pt+ suppresses the iOS focus zoom. Never rendered.
+    "lib/copy-to-clipboard.ts",
+}
+
+
+def _frontend_sources():
+    for path in sorted(SRC.rglob("*")):
+        if path.suffix in {".ts", ".tsx", ".css"}:
+            yield path
+
+
+def test_preference_writes_a_scale_not_the_root_font_size():
+    assert 'setVar("--ui-font-scale"' in STORE
+    assert 'el.setAttribute("data-ui-font-size"' in STORE
+    # Older builds set an inline root font-size; the applier must clear it.
+    assert 'style.removeProperty("font-size")' in STORE
+    assert "style.fontSize" not in STORE
+
+
+def test_named_text_tokens_scale():
+    for token, rem in (
+        ("--text-xs", "0.75rem"),
+        ("--text-sm", "0.875rem"),
+        ("--text-base", "1rem"),
+        ("--text-lg", "1.125rem"),
+    ):
+        assert f"{token}: calc({rem} * var(--ui-font-scale, 1));" in INDEX_CSS
+
+
+def test_numeric_leading_scales_with_the_preference():
+    for n, rem in ((3, "0.75rem"), (5, "1.25rem"), (6, "1.5rem")):
+        assert f"--leading-{n}: calc({rem} * var(--ui-font-scale, 1));" in INDEX_CSS
+
+
+def test_ui_token_families_exist():
+    assert "--text-ui-11: calc(0.6875rem * var(--ui-font-scale, 1));" in INDEX_CSS
+    assert "--text-ui-10p5: calc(0.65625rem * var(--ui-font-scale, 1));" in INDEX_CSS
+    assert "--leading-ui-17: calc(1.0625rem * var(--ui-font-scale, 1));" in INDEX_CSS
+
+
+def test_explicit_code_font_size_is_never_multiplied():
+    match = re.search(r"html\[data-code-font-size\][^{]*\{([^}]*)\}", INDEX_CSS)
+    assert match is not None
+    body = match.group(1)
+    assert "var(--custom-code-font-size)" in body
+    assert "--ui-font-scale" not in body
+
+
+def test_radix_select_viewport_owns_the_scroll_state():
+    viewport = SELECT[SELECT.index("SelectPrimitive.Viewport") :]
+    assert "overflow-y-auto" in viewport.split("</SelectPrimitive.Viewport>")[0]
+    # The rounded surface itself must not scroll (WebKit squares its corners).
+    content_cls = re.search(
+        r"SelectPrimitive\.Content[\s\S]*?className=\{cn\(\s*\"([^\"]+)\"", SELECT
+    )
+    assert content_cls is not None
+    assert "overflow-hidden" in content_cls.group(1)
+    assert "overflow-y-auto" not in content_cls.group(1)
+
+
+def test_no_raw_pixel_text_utilities():
+    offenders = []
+    for path in _frontend_sources():
+        text = path.read_text(encoding = "utf-8")
+        for m in re.finditer(r"(?<![\w-])(?:text|leading)-\[[0-9.]+px\]", text):
+            offenders.append(f"{path.relative_to(SRC)}: {m.group(0)}")
+    assert offenders == [], (
+        "Raw px text utilities ignore the UI font size preference; use the "
+        f"text-ui-* / leading-ui-* tokens in index.css instead: {offenders[:10]}"
+    )
+
+
+def test_css_font_sizes_reference_the_scale():
+    offenders = []
+    for path in _frontend_sources():
+        if path.suffix != ".css":
+            continue
+        text = path.read_text(encoding = "utf-8")
+        for m in re.finditer(r"(font-size|line-height):[^;{}]*;", text):
+            decl = m.group(0)
+            if re.search(r"[0-9.]+(px|rem)", decl) is None:
+                continue  # unitless ratios and vars scale naturally
+            if "--ui-font-scale" in decl:
+                continue
+            if "1px" in decl:
+                continue  # library layout tricks (KaTeX-style), not text
+            offenders.append(f"{path.relative_to(SRC)}: {decl.strip()[:80]}")
+    assert offenders == [], (
+        "CSS typography must multiply by var(--ui-font-scale, 1) or be "
+        f"allowlisted here with a reason: {offenders[:10]}"
+    )
+
+
+def test_inline_font_size_styles_reference_the_scale():
+    offenders = []
+    for path in _frontend_sources():
+        rel = str(path.relative_to(SRC))
+        if rel in FONTSIZE_STYLE_ALLOWLIST:
+            continue
+        text = path.read_text(encoding = "utf-8")
+        for m in re.finditer(r"fontSize:\s*([\"'][^\"']+[\"']|[0-9.]+)", text):
+            value = m.group(1)
+            if "--ui-font-scale" in value:
+                continue
+            if value.replace(".", "").isdigit() and any(
+                rel.startswith(d) for d in FONTSIZE_PROP_ALLOWED_DIRS
+            ):
+                continue  # covered by the .recharts-text override
+            offenders.append(f"{rel}: fontSize {value}")
+        for m in re.finditer(r"fontSize=\{?([0-9.]+)\}?", text):
+            if not any(rel.startswith(d) for d in FONTSIZE_PROP_ALLOWED_DIRS):
+                offenders.append(f"{rel}: fontSize={m.group(1)}")
+    assert offenders == [], (
+        "Inline font sizes must scale with var(--ui-font-scale, 1) or be "
+        f"documented in the allowlist: {offenders[:10]}"
+    )
diff --git a/tests/studio/test_voice_settings_select_width.py b/tests/studio/test_voice_settings_select_width.py
new file mode 100644
index 0000000000..2f657b851e
--- /dev/null
+++ b/tests/studio/test_voice_settings_select_width.py
@@ -0,0 +1,16 @@
+"""Width contract for voice settings selects."""
+
+from pathlib import Path
+
+
+REPO = Path(__file__).resolve().parents[2]
+VOICE_TAB = REPO / "studio/frontend/src/features/settings/tabs/voice-tab.tsx"
+SELECT = REPO / "studio/frontend/src/components/ui/select.tsx"
+
+
+def test_voice_selects_grow_without_overflowing_the_dialog():
+    source = VOICE_TAB.read_text(encoding = "utf-8")
+    assert source.count('className="min-w-56 max-w-72"') == 4
+
+    select_source = SELECT.read_text(encoding = "utf-8")
+    assert "*:data-[slot=select-value]:line-clamp-1" in select_source
diff --git a/tests/test_installer_unsloth_version.py b/tests/test_installer_unsloth_version.py
new file mode 100644
index 0000000000..5ee1cfac71
--- /dev/null
+++ b/tests/test_installer_unsloth_version.py
@@ -0,0 +1,75 @@
+"""Regression coverage for installer version reporting."""
+
+from __future__ import annotations
+
+import re
+import shutil
+import subprocess
+import sys
+from importlib.metadata import version
+from pathlib import Path
+
+import pytest
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+INSTALL_SH = REPO_ROOT / "install.sh"
+INSTALL_PS1 = REPO_ROOT / "install.ps1"
+
+
+def _extract(pattern: str, source: str) -> str:
+    match = re.search(pattern, source, flags = re.DOTALL | re.MULTILINE)
+    assert match is not None, f"installer block not found: {pattern}"
+    return match.group(0)
+
+
+@pytest.mark.skipif(shutil.which("sh") is None, reason = "POSIX shell is unavailable")
+def test_posix_installer_reports_installed_distribution_version():
+    source = INSTALL_SH.read_text(encoding = "utf-8")
+    reporter = _extract(
+        r"_installed_package_version=\$\(.*?^fi",
+        source,
+    )
+    result = subprocess.run(
+        [
+            "sh",
+            "-c",
+            (
+                'step() { printf "%s %s\\n" "$1" "$2"; }\n'
+                'substep() { printf "WARN %s\\n" "$1"; }\n'
+                f"_VENV_PY={sys.executable!r}\n"
+                "PACKAGE_NAME=pytest\n"
+                f"{reporter}"
+            ),
+        ],
+        check = True,
+        capture_output = True,
+        text = True,
+    )
+    assert result.stdout.strip() == f"pytest {version('pytest')} installed"
+
+
+@pytest.mark.skipif(shutil.which("pwsh") is None, reason = "PowerShell is unavailable")
+def test_windows_version_reporter_uses_distribution_metadata():
+    source = INSTALL_PS1.read_text(encoding = "utf-8")
+    reporter = _extract(
+        r"    \$installedPackageVersion = .*?^    if .*?^    \} else \{.*?^    \}",
+        source,
+    )
+    result = subprocess.run(
+        [
+            "pwsh",
+            "-NoProfile",
+            "-NonInteractive",
+            "-Command",
+            (
+                'function step { param($Label, $Value) Write-Output "$Label $Value" }; '
+                'function substep { param($Message, $Color) Write-Output "WARN $Message" }; '
+                f"$VenvPython = '{sys.executable}'; $PackageName = 'pytest'; "
+                f"{reporter}"
+            ),
+        ],
+        check = True,
+        capture_output = True,
+        text = True,
+    )
+    assert result.stdout.strip() == f"pytest {version('pytest')} installed"
diff --git a/tests/test_raw_text.py b/tests/test_raw_text.py
index 18549adfe8..bc75c2e44d 100644
--- a/tests/test_raw_text.py
+++ b/tests/test_raw_text.py
@@ -312,8 +312,100 @@ def test_load_from_file_skips_non_object_json_lines():
     return True
 
 
+def test_smart_chunk_text_empty_input_returns_no_chunks():
+    """Empty/whitespace text must yield no chunks. This tokenizer keeps one token
+    per char (like BPE/SentencePiece keeping spaces), so a len(tokens)==0 check
+    would miss whitespace; the fix guards on text.strip() before tokenizing."""
+
+    class WhitespacePreservingTokenizer:
+        def __init__(self, eos_token_id):
+            self.eos_token = "</s>" if eos_token_id is not None else None
+            self.eos_token_id = eos_token_id
+
+        def __call__(
+            self,
+            text,
+            return_tensors = None,
+            add_special_tokens = False,
+        ):
+            token_ids = [ord(c) % 100 for c in text]  # whitespace -> real tokens
+            if return_tensors == "pt":
+                return {"input_ids": [token_ids]}
+            return {"input_ids": token_ids}
+
+        def decode(
+            self,
+            token_ids,
+            skip_special_tokens = False,
+        ):
+            return "".join(chr(32 + (t % 90)) for t in token_ids)
+
+    for eos_token_id in (2, None):
+        loader = RawTextDataLoader(
+            WhitespacePreservingTokenizer(eos_token_id), chunk_size = 2048, stride = 512
+        )
+        # Whitespace tokenizes to >0 tokens, so [] proves the pre-tokenize guard.
+        assert len(loader.tokenizer("   \n\t  ")["input_ids"]) > 0
+        for text in ("", "   \n\t  "):
+            for return_tokenized in (True, False):
+                assert (
+                    loader.smart_chunk_text(
+                        text, chunk_size = 2048, stride = 512, return_tokenized = return_tokenized
+                    )
+                    == []
+                ), f"no chunks for empty input (eos={eos_token_id}, text={text!r}, tokenized={return_tokenized})"
+                assert loader.chunk_text(text, return_tokenized = return_tokenized) == [], (
+                    f"chunk_text: no chunks for empty input "
+                    f"(eos={eos_token_id}, text={text!r}, tokenized={return_tokenized})"
+                )
+    print("test_smart_chunk_text_empty_input_returns_no_chunks passed")
+    return True
+
+
+def test_load_from_files_all_empty_raises():
+    """All-empty file list must raise (like load_from_file) instead of returning
+    a 0-row text-column dataset in return_tokenized mode."""
+
+    class WhitespacePreservingTokenizer:
+        eos_token = "</s>"
+        eos_token_id = 2
+
+        def __call__(
+            self,
+            text,
+            return_tensors = None,
+            add_special_tokens = False,
+        ):
+            token_ids = [ord(c) % 100 for c in text]
+            if return_tensors == "pt":
+                return {"input_ids": [token_ids]}
+            return {"input_ids": token_ids}
+
+    loader = RawTextDataLoader(WhitespacePreservingTokenizer(), chunk_size = 2048, stride = 512)
+    paths = []
+    try:
+        for content in ("", "   \n\t  "):
+            with tempfile.NamedTemporaryFile("w", suffix = ".txt", delete = False) as f:
+                f.write(content)
+                paths.append(f.name)
+        raised = False
+        try:
+            loader.load_from_files(paths, return_tokenized = True)
+        except ValueError as e:
+            raised = True
+            assert "empty" in str(e).lower() or "whitespace" in str(e).lower(), str(e)
+        assert raised, "load_from_files must raise when all files are empty/whitespace"
+    finally:
+        for p in paths:
+            os.unlink(p)
+    print("test_load_from_files_all_empty_raises passed")
+    return True
+
+
 if __name__ == "__main__":
     success = test_raw_text_loader()
     success = test_smart_chunk_text_single_chunk_no_eos_returns_plain_list() and success
     success = test_load_from_file_skips_non_object_json_lines() and success
+    success = test_smart_chunk_text_empty_input_returns_no_chunks() and success
+    success = test_load_from_files_all_empty_raises() and success
     sys.exit(0 if success else 1)
diff --git a/tests/test_studio_install_workspace_guard.py b/tests/test_studio_install_workspace_guard.py
index ea5b34672c..18678a9b4a 100644
--- a/tests/test_studio_install_workspace_guard.py
+++ b/tests/test_studio_install_workspace_guard.py
@@ -254,6 +254,14 @@ def test_setup_ps1_prebuilt_llama_cpp_has_ownership_guard():
     ), "Assert-StudioOwnedOrAbsent must precede the install_llama_prebuilt.py call"
 
 
+def test_setup_ps1_adopts_existing_whisper_prebuilt_marker():
+    text = SETUP_PS1.read_text(encoding = "utf-8")
+    helper_start = text.index("function Test-StudioOwnedAdoptable")
+    helper_end = text.index("function Assert-StudioOwnedOrAbsent", helper_start)
+    helper = text[helper_start:helper_end]
+    assert "UNSLOTH_WHISPER_PREBUILT_INFO.json" in helper
+
+
 def test_env_mode_passes_when_venv_marker_present(tmp_path):
     """install.sh env-mode guard must accept the in-VENV .unsloth-studio-owned marker as a sentinel."""
     studio_home = tmp_path / "ws"
diff --git a/tests/test_uma_safetensors_load.py b/tests/test_uma_safetensors_load.py
new file mode 100644
index 0000000000..c6d304ab4f
--- /dev/null
+++ b/tests/test_uma_safetensors_load.py
@@ -0,0 +1,229 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2023-present Daniel Han-Chen & the Unsloth team. All rights reserved.
+
+"""Unit tests for the UMA safetensors clone-then-move fast load.
+
+The module loads in isolation with a fake ``transformers.modeling_utils``. The
+CUDA correctness check needs a GPU; gating, passthrough, idempotency and opt-out
+are GPU-free. The gate is lazy (wrapper-time), so the wrapper installs
+everywhere and passes through when it's off.
+"""
+
+from __future__ import annotations
+
+import importlib.util
+import sys
+import types
+from pathlib import Path
+
+import pytest
+
+torch = pytest.importorskip("torch")
+safetensors_torch = pytest.importorskip("safetensors.torch")
+import safetensors  # noqa: E402
+
+_MODULE_PATH = Path(__file__).resolve().parent.parent / "unsloth" / "models" / "_uma_safetensors.py"
+
+
+def _load_module():
+    spec = importlib.util.spec_from_file_location("uma_safetensors_under_test", _MODULE_PATH)
+    assert spec is not None and spec.loader is not None
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+@pytest.fixture()
+def uma():
+    return _load_module()
+
+
+@pytest.fixture()
+def force_uma(uma, monkeypatch):
+    """Force the UMA gate on (or off) and keep the lru_cache from sticking."""
+
+    def _set(on):
+        monkeypatch.setenv("UNSLOTH_FORCE_UMA", "1" if on else "0")
+        uma.is_integrated_unified_memory_gpu.cache_clear()
+
+    yield _set
+    uma.is_integrated_unified_memory_gpu.cache_clear()
+
+
+@pytest.fixture()
+def tiny_safetensors(tmp_path):
+    tensors = {
+        "w": torch.arange(32, dtype = torch.float32).reshape(4, 8),
+        "b": torch.tensor([1.0, 2.0, 3.0, 4.0], dtype = torch.float32),
+    }
+    path = tmp_path / "model.safetensors"
+    safetensors_torch.save_file(tensors, str(path))
+    return path, tensors
+
+
+def _install_fake_modeling_utils(monkeypatch, safe_open_fn):
+    fake_transformers = types.ModuleType("transformers")
+    fake_mu = types.ModuleType("transformers.modeling_utils")
+    fake_mu.safe_open = safe_open_fn
+    fake_transformers.modeling_utils = fake_mu
+    monkeypatch.setitem(sys.modules, "transformers", fake_transformers)
+    monkeypatch.setitem(sys.modules, "transformers.modeling_utils", fake_mu)
+    return fake_mu
+
+
+# --- detection / gate ---
+
+
+def test_force_uma_on(uma, monkeypatch):
+    monkeypatch.setenv("UNSLOTH_FORCE_UMA", "1")
+    uma.is_integrated_unified_memory_gpu.cache_clear()
+    assert uma.is_integrated_unified_memory_gpu() is True
+
+
+def test_force_uma_off(uma, monkeypatch):
+    monkeypatch.setenv("UNSLOTH_FORCE_UMA", "0")
+    uma.is_integrated_unified_memory_gpu.cache_clear()
+    assert uma.is_integrated_unified_memory_gpu() is False
+
+
+@pytest.mark.parametrize(
+    "device,expected",
+    [
+        (0, True),
+        ("cuda", True),
+        ("cuda:0", True),
+        ("cpu", False),
+        ("disk", False),
+        (None, False),
+        (True, False),  # a bool is not a device index
+    ],
+)
+def test_is_cuda_target(uma, device, expected):
+    assert uma._is_cuda_target(device) is expected
+
+
+def test_is_cuda_target_torch_device(uma):
+    assert uma._is_cuda_target(torch.device("cuda", 0)) is True
+    assert uma._is_cuda_target(torch.device("cpu")) is False
+
+
+# --- patch gating ---
+
+
+def test_wrapper_passes_through_off_uma(uma, force_uma, monkeypatch):
+    """Gate OFF: every call -- including CUDA targets -- passes straight through
+    to the real safe_open (the gate is evaluated lazily inside the wrapper)."""
+    force_uma(False)
+    sentinel = object()
+    calls = []
+
+    def fake_safe_open(*args, **kwargs):
+        calls.append((args, kwargs))
+        return sentinel
+
+    fake_mu = _install_fake_modeling_utils(monkeypatch, fake_safe_open)
+    assert uma.patch_unified_memory_safetensors_load() is True
+    assert getattr(fake_mu.safe_open, "_unsloth_uma_clone", False) is True
+    out = fake_mu.safe_open("shard.safetensors", "pt", "cuda:0")
+    assert out is sentinel
+    assert calls == [(("shard.safetensors", "pt", "cuda:0"), {})]
+
+
+def test_patch_install_does_not_evaluate_gate(uma, monkeypatch):
+    """Installing the wrapper must NOT query the integrated-GPU property -- that
+    would init CUDA at ``import unsloth`` (fork-unsafe, and before the Spark
+    allocator config is set)."""
+
+    def _boom():
+        raise AssertionError("gate must not be evaluated at install time")
+
+    _install_fake_modeling_utils(monkeypatch, safetensors.safe_open)
+    monkeypatch.setattr(uma, "is_integrated_unified_memory_gpu", _boom)
+    assert uma.patch_unified_memory_safetensors_load() is True
+
+
+def test_patch_noop_when_opted_out(uma, force_uma, monkeypatch):
+    force_uma(True)
+    monkeypatch.setenv("UNSLOTH_DISABLE_UMA_CLONE_LOAD", "1")
+    real = object()
+    fake_mu = _install_fake_modeling_utils(monkeypatch, real)
+    assert uma.patch_unified_memory_safetensors_load() is False
+    assert fake_mu.safe_open is real
+
+
+def test_patch_installs_and_is_idempotent(uma, force_uma, monkeypatch):
+    force_uma(True)
+    fake_mu = _install_fake_modeling_utils(monkeypatch, safetensors.safe_open)
+    assert uma.patch_unified_memory_safetensors_load() is True
+    wrapped = fake_mu.safe_open
+    assert getattr(wrapped, "_unsloth_uma_clone", False) is True
+    # second call must not double-wrap
+    assert uma.patch_unified_memory_safetensors_load() is True
+    assert fake_mu.safe_open is wrapped
+
+
+# --- correctness ---
+
+
+def test_cpu_target_is_passthrough(uma, force_uma, monkeypatch, tiny_safetensors):
+    path, tensors = tiny_safetensors
+    force_uma(True)
+    fake_mu = _install_fake_modeling_utils(monkeypatch, safetensors.safe_open)
+    uma.patch_unified_memory_safetensors_load()
+    # device="cpu" must NOT be intercepted -> identical data, still on CPU.
+    with fake_mu.safe_open(str(path), framework = "pt", device = "cpu") as f:
+        for key, expected in tensors.items():
+            got = f.get_slice(key)[:]
+            assert got.device.type == "cpu"
+            assert torch.equal(got, expected)
+
+
+@pytest.mark.skipif(
+    not (hasattr(torch, "cuda") and torch.cuda.is_available()),
+    reason = "needs a GPU for the host->device clone-and-move path",
+)
+def test_cuda_target_clones_and_moves(uma, force_uma, monkeypatch, tiny_safetensors):
+    path, tensors = tiny_safetensors
+    force_uma(True)
+    fake_mu = _install_fake_modeling_utils(monkeypatch, safetensors.safe_open)
+    uma.patch_unified_memory_safetensors_load()
+    # device="cuda" IS intercepted -> tensors land on cuda, byte-identical.
+    with fake_mu.safe_open(str(path), framework = "pt", device = "cuda") as f:
+        for key, expected in tensors.items():
+            got = f.get_slice(key)[:]
+            assert got.device.type == "cuda"
+            assert torch.equal(got.cpu(), expected)
+            got_full = f.get_tensor(key)
+            assert got_full.device.type == "cuda"
+            assert torch.equal(got_full.cpu(), expected)
+
+
+@pytest.mark.skipif(
+    not (hasattr(torch, "cuda") and torch.cuda.is_available()),
+    reason = "needs a GPU for the low-memory fallback path",
+)
+def test_low_memory_falls_back_to_direct_move(uma, force_uma, monkeypatch, tiny_safetensors):
+    path, tensors = tiny_safetensors
+    force_uma(True)
+    fake_mu = _install_fake_modeling_utils(monkeypatch, safetensors.safe_open)
+    uma.patch_unified_memory_safetensors_load()
+    # Clone OOMs (transient CPU doubling on a constrained UMA box): the wrapper
+    # must fall back to the direct move and still succeed.
+    real_clone = torch.Tensor.clone
+
+    def _oom_clone(self, *a, **k):
+        raise RuntimeError("[enforce fail] not enough memory")
+
+    monkeypatch.setattr(torch.Tensor, "clone", _oom_clone)
+    try:
+        with fake_mu.safe_open(str(path), framework = "pt", device = "cuda") as f:
+            for key, expected in tensors.items():
+                got = f.get_slice(key)[:]
+                assert got.device.type == "cuda"
+                got_full = f.get_tensor(key)
+                assert got_full.device.type == "cuda"
+    finally:
+        monkeypatch.setattr(torch.Tensor, "clone", real_clone)
+    for key, expected in tensors.items():
+        with fake_mu.safe_open(str(path), framework = "pt", device = "cuda") as f:
+            assert torch.equal(f.get_tensor(key).cpu(), expected)
diff --git a/unsloth/dataprep/raw_text.py b/unsloth/dataprep/raw_text.py
index 8623285a25..fdaba181f1 100644
--- a/unsloth/dataprep/raw_text.py
+++ b/unsloth/dataprep/raw_text.py
@@ -87,6 +87,10 @@ class RawTextDataLoader:
                 text_content, self.chunk_size, self.stride, return_tokenized
             )
             all_chunks.extend(chunks)
+        if not all_chunks:
+            # All files empty/whitespace: raise like load_from_file instead of
+            # create_causal_dataset([]) returning a 0-row text-column dataset.
+            raise ValueError("All files are empty or contain only whitespace")
         return self.create_causal_dataset(all_chunks)
 
     def chunk_text(
@@ -139,6 +143,12 @@ class RawTextDataLoader:
                 f"stride ({stride}) must be smaller than chunk_size ({chunk_size}) to progress the chunking loop"
             )
 
+        # Skip empty/whitespace text before tokenizing: BPE/SentencePiece emit
+        # real tokens for spaces/newlines, so a len(tokens)==0 check misses it
+        # and would yield a degenerate lone-EOS sample. Mirrors load_from_file.
+        if not text or not text.strip():
+            return []
+
         # Tokenize the whole text once for accurate token counts
         tokenized = self.tokenizer(text, return_tensors = "pt", add_special_tokens = False)
         tokens = tokenized["input_ids"]
diff --git a/unsloth/models/_uma_safetensors.py b/unsloth/models/_uma_safetensors.py
new file mode 100644
index 0000000000..38d8b7d33a
--- /dev/null
+++ b/unsloth/models/_uma_safetensors.py
@@ -0,0 +1,169 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2023-present Daniel Han-Chen & the Unsloth team. All rights reserved.
+
+"""Faster safetensors weight loading on unified-memory (integrated) GPUs.
+
+A direct ``safe_open(..., device=<cuda>)`` on CUDA/HIP UMA GPUs (AMD APUs,
+NVIDIA GB10 Spark) misses torch's fast pinned-DMA path: the mmap-backed
+safetensors buffers aren't recognized, so it falls to a slow per-tensor copy
+with page faults. Cloning each tensor into a normal torch CPU allocation before
+moving it restores the fast path; outputs are bit-identical.
+
+CUDA/HIP only, and only for loads that pass a CUDA device to ``safe_open``
+directly: Intel XPU iGPUs and the CPU-open + later ``.to()`` flows (e.g. bnb /
+HQQ quantized loads) keep the stock path until they can be validated on real
+hardware.
+"""
+
+import os
+import functools
+
+import torch
+
+__all__ = [
+    "is_integrated_unified_memory_gpu",
+    "patch_unified_memory_safetensors_load",
+]
+
+
+@functools.lru_cache(maxsize = None)
+def is_integrated_unified_memory_gpu():
+    """True only when EVERY visible CUDA/HIP device is integrated (UMA).
+
+    Discrete and mixed discrete+iGPU boxes return False (pinned-DMA already
+    works there). Test override: ``UNSLOTH_FORCE_UMA=1`` / ``=0``.
+    """
+    _force = os.environ.get("UNSLOTH_FORCE_UMA")
+    if _force == "1":
+        return True
+    if _force == "0":
+        return False
+    try:
+        if not (hasattr(torch, "cuda") and torch.cuda.is_available()):
+            return False
+        count = torch.cuda.device_count()
+        if count == 0:
+            return False
+        for index in range(count):
+            props = torch.cuda.get_device_properties(index)
+            if not getattr(props, "is_integrated", 0):
+                return False
+        return True
+    except Exception:
+        return False
+
+
+def _is_cuda_target(device):
+    """Does a ``safe_open`` ``device=`` arg name a CUDA/HIP device?"""
+    if isinstance(device, bool):
+        return False
+    if isinstance(device, int):
+        return True
+    if isinstance(device, str):
+        return device == "cuda" or device.startswith("cuda:")
+    try:
+        return isinstance(device, torch.device) and device.type == "cuda"
+    except Exception:
+        return False
+
+
+def patch_unified_memory_safetensors_load():
+    """Wrap ``transformers.modeling_utils.safe_open`` so CUDA-target shard loads
+    open on CPU then clone+``.to(device)``, restoring the UMA fast path.
+
+    Gated to integrated GPUs (no-op on discrete/CPU/XPU/MLX), ``framework="pt"``
+    CUDA targets only, idempotent. Opt out: ``UNSLOTH_DISABLE_UMA_CLONE_LOAD=1``.
+
+    The gate runs lazily inside the wrapper, never here: probing device
+    properties at install would init CUDA during ``import unsloth`` -- breaking
+    fork multiprocessing and preempting ``patch_dgx_spark_memory_config``'s
+    allocator config. Returns ``True`` if the wrapper was installed.
+    """
+    if os.environ.get("UNSLOTH_DISABLE_UMA_CLONE_LOAD") == "1":
+        return False
+    try:
+        from transformers import modeling_utils as _mu
+    except Exception:
+        return False
+    real_safe_open = getattr(_mu, "safe_open", None)
+    if real_safe_open is None:
+        return False
+    if getattr(real_safe_open, "_unsloth_uma_clone", False):
+        return True
+
+    def _clone_move(tensor, device):
+        # Clone into a regular CPU allocation to restore fast pinned-DMA, then
+        # move. The clone transiently doubles the tensor's CPU footprint and can
+        # OOM a low-memory UMA box; fall back to the direct, allocation-free move
+        # (a genuine non-memory error re-raises identically from it).
+        try:
+            return tensor.clone().to(device, non_blocking = False)
+        except (MemoryError, RuntimeError):
+            return tensor.to(device, non_blocking = False)
+
+    class _ClonedSlice:
+        """Proxy over a safetensors ``PySafeSlice`` that clones+moves on read."""
+
+        __slots__ = ("_real", "_device")
+
+        def __init__(self, real, device):
+            self._real = real
+            self._device = device
+
+        def __getattr__(self, name):
+            if name in ("_real", "_device"):
+                raise AttributeError(name)
+            return getattr(self._real, name)
+
+        def __getitem__(self, key):
+            return _clone_move(self._real[key], self._device)
+
+    class _ClonedSafeOpen:
+        """Safetensors-handle proxy: load on CPU, clone+move tensors to CUDA."""
+
+        __slots__ = ("_real", "_device")
+
+        def __init__(self, args, kwargs):
+            self._device = kwargs.get("device", args[2] if len(args) > 2 else "cpu")
+            # Open on CPU; move ourselves.
+            if len(args) > 2:
+                args = args[:2] + ("cpu",) + tuple(args[3:])
+            else:
+                kwargs = dict(kwargs)
+                kwargs["device"] = "cpu"
+            self._real = real_safe_open(*args, **kwargs)
+
+        def __enter__(self):
+            self._real.__enter__()
+            return self
+
+        def __exit__(self, *exc):
+            return self._real.__exit__(*exc)
+
+        def __getattr__(self, name):
+            if name in ("_real", "_device"):
+                raise AttributeError(name)
+            return getattr(self._real, name)
+
+        def get_slice(self, name):
+            return _ClonedSlice(self._real.get_slice(name), self._device)
+
+        def get_tensor(self, name):
+            return _clone_move(self._real.get_tensor(name), self._device)
+
+    @functools.wraps(real_safe_open)
+    def _uma_safe_open(*args, **kwargs):
+        framework = kwargs.get("framework", args[1] if len(args) > 1 else None)
+        device = kwargs.get("device", args[2] if len(args) > 2 else "cpu")
+        # Device check first: non-CUDA loads must not trigger the CUDA-init gate.
+        if (
+            framework in ("pt", "pytorch")
+            and _is_cuda_target(device)
+            and is_integrated_unified_memory_gpu()
+        ):
+            return _ClonedSafeOpen(args, kwargs)
+        return real_safe_open(*args, **kwargs)
+
+    _uma_safe_open._unsloth_uma_clone = True
+    _mu.safe_open = _uma_safe_open
+    return True
diff --git a/unsloth/models/_utils.py b/unsloth/models/_utils.py
index 57169fa3de..0b3a3698c2 100644
--- a/unsloth/models/_utils.py
+++ b/unsloth/models/_utils.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "2026.7.4"
+__version__ = "2026.7.5"
 
 __all__ = [
     "SUPPORTS_BFLOAT16",
@@ -1670,6 +1670,13 @@ except:
 from transformers.modeling_utils import logger as transformers_logger
 
 
+# Faster safetensors loads on UMA (integrated) GPUs; lazy gate keeps this import
+# fork-safe (no CUDA init). No-op off-UMA. Opt out: UNSLOTH_DISABLE_UMA_CLONE_LOAD=1.
+from ._uma_safetensors import patch_unified_memory_safetensors_load
+
+patch_unified_memory_safetensors_load()
+
+
 def _all_missing_keys_are_position_ids(record_str):
     """True only when EVERY key in the 'newly initialized: [...]' list is a position_ids
     buffer.
diff --git a/unsloth_cli/_inference.py b/unsloth_cli/_inference.py
index 551bef4787..a2b0f9c04f 100644
--- a/unsloth_cli/_inference.py
+++ b/unsloth_cli/_inference.py
@@ -235,7 +235,7 @@ def collect_stream(stream, show_thinking: bool) -> str:
 def raise_on_streamed_error(stream):
     # Match real backend errors by type (GenStreamError), not the "Error:" text
     # prefix, so a completion whose text opens with "Error:" is not misread as a
-    # failure that aborts a distributed run.
+    # backend failure.
     try:
         ensure_studio_backend_path()
         from core.inference.orchestrator import GenStreamError
diff --git a/unsloth_cli/claude_subagent_mcp.py b/unsloth_cli/claude_subagent_mcp.py
new file mode 100644
index 0000000000..b86368515b
--- /dev/null
+++ b/unsloth_cli/claude_subagent_mcp.py
@@ -0,0 +1,366 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Small stdio MCP bridge from cloud Claude Code to a local Claude Code child."""
+
+from __future__ import annotations
+
+import json
+import os
+import signal
+import shutil
+import subprocess
+import sys
+import threading
+import time
+from typing import Any, Callable
+
+from unsloth_cli.commands.start import (
+    _CLAUDE_ENV_UNSET,
+    _SUBAGENT_DESCRIPTION,
+    _SUBAGENT_INSTRUCTIONS,
+    _claude_flags,
+    _claude_local_env,
+    _wsl_shim_env,
+)
+
+_MAX_RESULT_CHARACTERS = 100_000
+_CANCEL_POLL_SECONDS = 0.1
+_CANCEL_GRACE_SECONDS = 2.0
+
+
+def _required_env(name: str) -> str:
+    value = os.environ.get(name, "").strip()
+    if not value:
+        raise RuntimeError(f"Missing {name}.")
+    return value
+
+
+def _bounded(text: str) -> str:
+    if len(text) <= _MAX_RESULT_CHARACTERS:
+        return text
+    return text[:_MAX_RESULT_CHARACTERS] + "\n\n[Local agent output truncated]"
+
+
+def _result_text(stdout: str) -> str:
+    lines = [line for line in stdout.splitlines() if line.strip()]
+    candidates = [stdout.strip(), *reversed(lines)]
+    for candidate in candidates:
+        try:
+            payload = json.loads(candidate)
+        except ValueError:
+            continue
+        if not isinstance(payload, dict):
+            continue
+        result = payload.get("result")
+        if payload.get("is_error"):
+            raise RuntimeError(str(result or "The local Claude agent failed."))
+        if isinstance(result, str) and result.strip():
+            return _bounded(result.strip())
+    raise RuntimeError("The local Claude agent returned no readable result.")
+
+
+def _stop_child(process: subprocess.Popen) -> None:
+    """Stop the Claude child and any tool processes it started."""
+    if process.poll() is not None:
+        if os.name != "nt":
+            # Leader exited, but its tool processes may still be running.
+            try:
+                os.killpg(process.pid, signal.SIGTERM)
+            except OSError:
+                return
+            time.sleep(_CANCEL_GRACE_SECONDS)
+            try:
+                os.killpg(process.pid, signal.SIGKILL)
+            except OSError:
+                pass
+        return
+    if os.name == "nt":
+        try:
+            completed = subprocess.run(
+                ["taskkill", "/PID", str(process.pid), "/T", "/F"],
+                capture_output = True,
+                timeout = 15,
+                check = False,
+            )
+        except Exception:
+            completed = None
+        # A failed taskkill must not leave the child running through the grace wait.
+        if (completed is None or completed.returncode != 0) and process.poll() is None:
+            process.terminate()
+    else:
+        try:
+            os.killpg(process.pid, signal.SIGTERM)
+        except OSError:
+            process.terminate()
+    try:
+        process.wait(timeout = _CANCEL_GRACE_SECONDS)
+    except subprocess.TimeoutExpired:
+        if os.name == "nt":
+            process.kill()
+        else:
+            try:
+                os.killpg(process.pid, signal.SIGKILL)
+            except OSError:
+                process.kill()
+        process.wait()
+    else:
+        if os.name != "nt":
+            # Leader is gone; kill any surviving group members.
+            try:
+                os.killpg(process.pid, signal.SIGKILL)
+            except OSError:
+                pass
+
+
+def run_local_agent(task: str, cancel_event: threading.Event | None = None) -> str:
+    base = _required_env("UNSLOTH_CLAUDE_SUBAGENT_BASE_URL")
+    key = _required_env("UNSLOTH_CLAUDE_SUBAGENT_API_KEY")
+    model = _required_env("UNSLOTH_CLAUDE_SUBAGENT_MODEL")
+    window = int(os.environ.get("UNSLOTH_CLAUDE_SUBAGENT_CONTEXT_WINDOW", "0") or 0)
+    entry = {"id": model, "context_length": window}
+    local_env = _claude_local_env(base, key, entry)
+    child_env = dict(os.environ)
+
+    executable = shutil.which("claude")
+    if executable is None:
+        raise RuntimeError("`claude` is not installed or is not on PATH.")
+    cancel_event = cancel_event or threading.Event()
+    if cancel_event.is_set():
+        raise RuntimeError("The local Claude agent was cancelled.")
+    command = [
+        "claude",
+        "--model",
+        model,
+        *_claude_flags(model),
+        "--permission-mode",
+        (
+            "bypassPermissions"
+            if os.environ.get("UNSLOTH_CLAUDE_SUBAGENT_BYPASS_PERMISSIONS") == "1"
+            else "acceptEdits"
+        ),
+        "--print",
+        "--output-format",
+        "json",
+        "--no-session-persistence",
+        "--append-system-prompt",
+        _SUBAGENT_INSTRUCTIONS,
+        f"Task: {task}",
+    ]
+    bridged, wsl_names = _wsl_shim_env(command, local_env, _CLAUDE_ENV_UNSET)
+    if wsl_names:
+        from unsloth_cli.commands.start import _merge_wslenv
+
+        bridged = {**bridged, "PWD": os.getcwd()}
+        child_env["WSLENV"] = _merge_wslenv(child_env.get("WSLENV", ""), wsl_names)
+        for name in _CLAUDE_ENV_UNSET:
+            child_env[name] = ""
+    else:
+        for name in _CLAUDE_ENV_UNSET:
+            child_env.pop(name, None)
+    child_env.update(bridged)
+    popen_kwargs: dict[str, Any] = {
+        "cwd": os.environ.get("CLAUDE_PROJECT_DIR") or os.getcwd(),
+        "env": child_env,
+        "stdin": subprocess.DEVNULL,
+        "stdout": subprocess.PIPE,
+        "stderr": subprocess.PIPE,
+        "text": True,
+    }
+    if os.name == "nt":
+        popen_kwargs["creationflags"] = subprocess.CREATE_NEW_PROCESS_GROUP
+    else:
+        popen_kwargs["start_new_session"] = True
+    process = subprocess.Popen(
+        [executable, *command[1:]],
+        **popen_kwargs,
+    )
+    try:
+        while True:
+            try:
+                stdout, stderr = process.communicate(timeout = _CANCEL_POLL_SECONDS)
+                break
+            except subprocess.TimeoutExpired:
+                if cancel_event.is_set():
+                    _stop_child(process)
+                    raise RuntimeError("The local Claude agent was cancelled.")
+    except BaseException:
+        if process.poll() is None:
+            _stop_child(process)
+        raise
+    if process.returncode != 0:
+        detail = stderr.strip() or stdout.strip()
+        raise RuntimeError(
+            _bounded(detail) or f"Local Claude exited with code {process.returncode}."
+        )
+    return _result_text(stdout)
+
+
+def _response(request: dict, run_agent: Callable[[str], str] = run_local_agent) -> dict | None:
+    request_id = request.get("id")
+    method = request.get("method")
+    if request_id is None:
+        return None
+    if method == "initialize":
+        protocol = (request.get("params") or {}).get("protocolVersion") or "2025-06-18"
+        result = {
+            "protocolVersion": protocol,
+            "capabilities": {"tools": {"listChanged": False}},
+            "serverInfo": {"name": "unsloth-local-agent", "version": "1.0.0"},
+        }
+    elif method == "ping":
+        result = {}
+    elif method == "tools/list":
+        result = {
+            "tools": [
+                {
+                    "name": "unsloth_agent",
+                    "title": "Unsloth local agent",
+                    "description": _SUBAGENT_DESCRIPTION,
+                    "inputSchema": {
+                        "type": "object",
+                        "properties": {
+                            "task": {
+                                "type": "string",
+                                "description": "The complete task for the local Unsloth agent.",
+                            }
+                        },
+                        "required": ["task"],
+                        "additionalProperties": False,
+                    },
+                    "annotations": {
+                        "readOnlyHint": False,
+                        "destructiveHint": True,
+                        "idempotentHint": False,
+                        "openWorldHint": True,
+                    },
+                    "_meta": {"anthropic/maxResultSizeChars": _MAX_RESULT_CHARACTERS},
+                }
+            ]
+        }
+    elif method == "tools/call":
+        params = request.get("params") or {}
+        arguments = params.get("arguments") or {}
+        task = arguments.get("task") if params.get("name") == "unsloth_agent" else None
+        if not isinstance(task, str) or not task.strip():
+            result = {
+                "content": [{"type": "text", "text": "A non-empty task is required."}],
+                "isError": True,
+            }
+        else:
+            try:
+                text = run_agent(task.strip())
+                result = {"content": [{"type": "text", "text": text}], "isError": False}
+            except Exception as exc:
+                result = {
+                    "content": [{"type": "text", "text": str(exc)}],
+                    "isError": True,
+                }
+    else:
+        return {
+            "jsonrpc": "2.0",
+            "id": request_id,
+            "error": {"code": -32601, "message": f"Method not found: {method}"},
+        }
+    return {"jsonrpc": "2.0", "id": request_id, "result": result}
+
+
+def serve(
+    stdin: Any = sys.stdin,
+    stdout: Any = sys.stdout,
+    run_agent: Callable[[str, threading.Event], str] = run_local_agent,
+) -> None:
+    active: dict[object, threading.Event] = {}
+    workers: list[threading.Thread] = []
+    state_lock = threading.RLock()
+    output_lock = threading.Lock()
+    shutdown_started = threading.Event()
+
+    def cancel_active() -> None:
+        with state_lock:
+            pending = list(active.values())
+        for cancel_event in pending:
+            cancel_event.set()
+
+    def handle_shutdown(_signum: int, _frame: Any) -> None:
+        # Claude Code sends SIGINT (possibly repeatedly) to cancel a tool call. Only
+        # the first unwinds stdin; later ones must not interrupt process-tree cleanup.
+        first_signal = not shutdown_started.is_set()
+        shutdown_started.set()
+        cancel_active()
+        if first_signal:
+            raise KeyboardInterrupt
+
+    previous_handlers: dict[int, Any] = {}
+    if threading.current_thread() is threading.main_thread():
+        for signum in (signal.SIGINT, signal.SIGTERM):
+            previous_handlers[signum] = signal.signal(signum, handle_shutdown)
+
+    def send(response: dict | None) -> None:
+        if response is None:
+            return
+        with output_lock:
+            stdout.write(json.dumps(response, separators = (",", ":")) + "\n")
+            stdout.flush()
+
+    def call_tool(request: dict, request_id: object, cancel_event: threading.Event) -> None:
+        try:
+            response = _response(
+                request,
+                run_agent = lambda task: run_agent(task, cancel_event),
+            )
+            if not cancel_event.is_set():
+                send(response)
+        finally:
+            with state_lock:
+                if active.get(request_id) is cancel_event:
+                    active.pop(request_id, None)
+
+    try:
+        for line in stdin:
+            try:
+                request = json.loads(line)
+                if not isinstance(request, dict):
+                    response = None
+                elif request.get("method") == "notifications/cancelled":
+                    request_id = (request.get("params") or {}).get("requestId")
+                    with state_lock:
+                        cancel_event = active.get(request_id)
+                    if cancel_event is not None:
+                        cancel_event.set()
+                    response = None
+                elif request.get("method") == "tools/call" and request.get("id") is not None:
+                    request_id = request["id"]
+                    cancel_event = threading.Event()
+                    with state_lock:
+                        active[request_id] = cancel_event
+                    worker = threading.Thread(
+                        target = call_tool,
+                        args = (request, request_id, cancel_event),
+                        name = f"unsloth-agent-{request_id}",
+                    )
+                    workers.append(worker)
+                    worker.start()
+                    response = None
+                else:
+                    response = _response(request)
+            except Exception as exc:
+                response = {
+                    "jsonrpc": "2.0",
+                    "id": None,
+                    "error": {"code": -32603, "message": str(exc)},
+                }
+            send(response)
+    except KeyboardInterrupt:
+        pass
+    finally:
+        cancel_active()
+        for worker in workers:
+            if worker.ident is not None:
+                worker.join()
+        for signum, handler in previous_handlers.items():
+            signal.signal(signum, handler)
+
+
+if __name__ == "__main__":
+    serve()
diff --git a/unsloth_cli/commands/_password_prompt.py b/unsloth_cli/commands/_password_prompt.py
index b6fd8ca34d..55f50acbf1 100644
--- a/unsloth_cli/commands/_password_prompt.py
+++ b/unsloth_cli/commands/_password_prompt.py
@@ -191,6 +191,10 @@ def prompt_new_password(verify_current: Callable[[str], bool], out: TextIO | Non
             out.write(f"Password must be at least {MIN_PASSWORD_LENGTH} characters. Try again.\n")
             out.flush()
             continue
+        if any(ch.isspace() for ch in password):
+            out.write("Password cannot contain spaces. Try again.\n")
+            out.flush()
+            continue
         if verify_current(password):
             out.write("New password must differ from the current password. Try again.\n")
             out.flush()
@@ -233,6 +237,8 @@ def validate_new_password(candidate: str, verify_current: Callable[[str], bool])
     current password), else None. Same policy as the interactive loop."""
     if len(candidate) < MIN_PASSWORD_LENGTH:
         return f"Password must be at least {MIN_PASSWORD_LENGTH} characters."
+    if any(ch.isspace() for ch in candidate):
+        return "Password cannot contain spaces."
     if verify_current(candidate):
         return "New password must differ from the current password."
     return None
diff --git a/unsloth_cli/commands/chat.py b/unsloth_cli/commands/chat.py
index bba5fab08e..fdc5577700 100644
--- a/unsloth_cli/commands/chat.py
+++ b/unsloth_cli/commands/chat.py
@@ -331,7 +331,7 @@ def chat(
             enable_thinking = show_thinking,
             use_adapter = use_adapter,
         )
-        return raise_on_streamed_error(stream) if is_mlx_distributed else stream
+        return raise_on_streamed_error(stream)
 
     if should_print:
         console.print()
diff --git a/unsloth_cli/commands/inference.py b/unsloth_cli/commands/inference.py
index 524d8fd015..7df05cef94 100644
--- a/unsloth_cli/commands/inference.py
+++ b/unsloth_cli/commands/inference.py
@@ -111,15 +111,12 @@ def inference(
             repetition_penalty = repetition_penalty,
             enable_thinking = think,
         )
-        if is_mlx_distributed:
-            stream = raise_on_streamed_error(stream)
+        stream = raise_on_streamed_error(stream)
         if rank == 0:
             typer.echo("Assistant:")
             try:
                 stream_to_stdout(stream, show_thinking = think)
             except RuntimeError as exc:
-                if not is_mlx_distributed:
-                    raise
                 typer.echo(f"Error: {exc}", err = True)
                 raise typer.Exit(code = 1)
         else:
diff --git a/unsloth_cli/commands/start.py b/unsloth_cli/commands/start.py
index 3d73df65be..01dffa0634 100644
--- a/unsloth_cli/commands/start.py
+++ b/unsloth_cli/commands/start.py
@@ -14,15 +14,17 @@ import signal
 import subprocess
 import sys
 import tempfile
+import threading
 import time
 import urllib.error
 import urllib.request
 from pathlib import Path
 from typing import NamedTuple, NoReturn, Optional
-from urllib.parse import urlparse
+from urllib.parse import urlencode, urlparse
 
 import click
 import typer
+from typer.core import TyperCommand
 
 from unsloth_cli._inference import (
     _USER_AGENT,
@@ -72,63 +74,135 @@ _HERMES_POSIX_INSTALL_HINT = (
 # windows and scales the compaction threshold back down to the real window.
 _HERMES_MIN_CONTEXT = 65536
 _PI_PROVIDER = "unsloth"
-# OpenCode selects a model by "<providerID>/<modelID>" and honors a user
-# disabled_providers list. Register the session provider under a dedicated id a
-# user's disable list would never target, so the model is always selectable
-# without the wrapper having to reconstruct (and override) OpenCode's full,
-# multi-layer disabled_providers resolution.
+_SUBAGENT_NAME = "unsloth"
+_SUBAGENT_DESCRIPTION = (
+    "Local coding subagent powered by Unsloth for debugging, implementation, and codebase "
+    "research. Use when the user asks to spawn an Unsloth or local agent."
+)
+_SUBAGENT_INSTRUCTIONS = (
+    "You are a local coding subagent powered by Unsloth. Complete the assigned task directly, "
+    "use the available tools when useful, verify your work, and return a concise result to the "
+    "parent agent."
+)
+_CLAUDE_SUBAGENT_MCP_MODULE = "unsloth_cli.claude_subagent_mcp"
+_CLAUDE_SUBAGENT_TOOL = "mcp__plugin_unsloth-local-agent_unsloth__unsloth_agent"
+_PI_SUBAGENT_EXTENSION = Path(__file__).parent.parent / "pi_subagent.ts"
+# OpenCode selects a model by "<providerID>/<modelID>". Use a dedicated id to avoid
+# colliding with a user's providers; provider filters are set in the launch-time overlay.
 _OPENCODE_PROVIDER = "unsloth-studio"
 _PROVIDER_HEADER = f"[model_providers.{_CODEX_PROFILE}]"
 _PASSTHROUGH = {"allow_extra_args": True, "ignore_unknown_options": True}
+
+
+class _PassthroughCommand(TyperCommand):
+    """Preserve the option separator when forwarding arguments to an agent."""
+
+    def parse_args(self, ctx: click.Context, args: list[str]) -> list[str]:
+        raw_args = list(args)
+        try:
+            separator = raw_args.index("--")
+        except ValueError:
+            return super().parse_args(ctx, args)
+        trailing_count = len(raw_args) - separator - 1
+        remaining = super().parse_args(ctx, args)
+        insert_at = max(0, len(remaining) - trailing_count)
+        if insert_at >= len(remaining) or remaining[insert_at] != "--":
+            remaining.insert(insert_at, "--")
+            ctx.args = remaining
+        return remaining
+
+
 _CLAUDE_ENV_UNSET = ("ANTHROPIC_API_KEY", "CLAUDE_CODE_OAUTH_TOKEN")
 
 # Shared by every agent command; only the config/env/command differ.
+# Help is grouped into rich panels so `--help` reads as Model / Server / Session
+# instead of one long unaligned list.
+_PANEL_MODEL = "Model"
+_PANEL_SERVER = "Server"
+_PANEL_SESSION = "Agent session"
+
 _MODEL_OPTION = typer.Option(
-    None, "--model", "-m", help = "Model for the agent; defaults to the one loaded in Unsloth."
-)
-_KEY_OPTION = typer.Option(
     None,
-    "--api-key",
-    envvar = "UNSLOTH_API_KEY",
-    help = (
-        "Unsloth API key. For a local Unsloth it is minted automatically and "
-        "remembered per server. For a remote server, pass one with --api-key "
-        "(or UNSLOTH_API_KEY); it is remembered for next time."
-    ),
+    "--model",
+    "-m",
+    rich_help_panel = _PANEL_MODEL,
+    help = "Model for the agent, or a bare `org/name(:variant)` positional. "
+    "Defaults to the one loaded in Unsloth.",
 )
-_LAUNCH_OPTION = typer.Option(
-    True,
-    "--launch/--no-launch",
-    help = "--no-launch prints the env and command instead (remote shells, WSL).",
-)
-_SERVE_OPTION = typer.Option(
-    True,
-    "--serve/--no-serve",
-    help = (
-        "If no Unsloth server is running, auto-start one for --model and stop it when the "
-        "agent exits. --no-serve keeps the old behavior of erroring out."
-    ),
-)
-# Model-load knobs mirrored from `unsloth run`; only used when --model triggers a
-# load on the server. Server-startup flags (--host/--port/--cloudflare/...) do not
-# apply here because `unsloth start` attaches to an already-running server.
 _GGUF_VARIANT_OPTION = typer.Option(
-    None, "--gguf-variant", help = "GGUF quant variant to load (e.g. UD-Q4_K_XL)."
+    None,
+    "--gguf-variant",
+    rich_help_panel = _PANEL_MODEL,
+    help = "GGUF quant variant to load (e.g. UD-Q4_K_XL). Defaults to UD-Q4_K_XL for "
+    "unsloth/* GGUF repos, else Q4_K_M.",
 )
 _CONTEXT_OPTION = typer.Option(
     0,
     "--max-seq-length",
     "--context-length",
+    rich_help_panel = _PANEL_MODEL,
     help = "Context length in tokens for the load (0 = model default).",
 )
 _LOAD_4BIT_OPTION = typer.Option(
-    True, "--load-in-4bit/--no-load-in-4bit", help = "Load hub models in 4-bit (ignored for GGUF)."
+    True,
+    "--load-in-4bit/--no-load-in-4bit",
+    rich_help_panel = _PANEL_MODEL,
+    help = "Load hub models in 4-bit (ignored for GGUF).",
 )
 _TENSOR_PARALLEL_OPTION = typer.Option(
     False,
     "--tensor-parallel/--no-tensor-parallel",
+    rich_help_panel = _PANEL_MODEL,
     help = "Split a GGUF across GPUs by tensor instead of by layer (multi-GPU only).",
 )
+
+# Server knobs. Only used when `unsloth start` auto-starts the server (--serve);
+# they have no effect when attaching to a server someone else already started.
+_SERVE_OPTION = typer.Option(
+    True,
+    "--serve/--no-serve",
+    rich_help_panel = _PANEL_SERVER,
+    help = "If no Unsloth server is running, auto-start one for --model and keep it "
+    "available after the agent exits. --no-serve errors out instead.",
+)
+_ENABLE_TOOLS_OPTION = typer.Option(
+    False,
+    "--enable-tools/--disable-tools",
+    rich_help_panel = _PANEL_SERVER,
+    help = "Server-side tools (web search, code execution) for the auto-started server. "
+    "Default off so the agent's own tools are relayed unchanged.",
+)
+_TOOL_CALL_HEALING_OPTION = typer.Option(
+    None,
+    "--enable-tool-call-healing/--disable-tool-call-healing",
+    rich_help_panel = _PANEL_SERVER,
+    help = "Promote text-form tool calls from small GGUFs back into structured calls. On by "
+    "default; when the flag is omitted an inherited UNSLOTH_DISABLE_TOOL_CALL_HEALING is kept.",
+)
+_TOOL_CALL_NUDGING_OPTION = typer.Option(
+    None,
+    "--enable-tool-call-nudging/--disable-tool-call-nudging",
+    rich_help_panel = _PANEL_SERVER,
+    help = "Retry once with a nudge when a non-streaming passthrough tool call can't be healed. "
+    "On by default; when the flag is omitted an inherited UNSLOTH_TOOL_CALL_NUDGE is kept.",
+)
+
+# Agent-session knobs.
+_KEY_OPTION = typer.Option(
+    None,
+    "--api-key",
+    envvar = "UNSLOTH_API_KEY",
+    rich_help_panel = _PANEL_SESSION,
+    help = "Unsloth API key. For a local Unsloth it is minted automatically and "
+    "remembered per server. For a remote server, pass one with --api-key "
+    "(or UNSLOTH_API_KEY); it is remembered for next time.",
+)
+_LAUNCH_OPTION = typer.Option(
+    True,
+    "--launch/--no-launch",
+    rich_help_panel = _PANEL_SESSION,
+    help = "--no-launch prints the env and command instead (remote shells, WSL).",
+)
 # One normalized "run tools without prompting" switch. Each agent spells this
 # differently and it's easy to forget which is which, so accept every spelling and
 # route to the agent's own mechanism in _yolo_command_flags / the config writers.
@@ -137,14 +211,14 @@ _YOLO_OPTION = typer.Option(
     "--yolo",
     "--dangerously-skip-permissions",
     "--dangerously-bypass-approvals-and-sandbox",
-    help = (
-        "Auto-approve all tool actions for this session; routed to the agent's own "
-        "flag/config. Any of the three spellings works for any agent."
-    ),
+    rich_help_panel = _PANEL_SESSION,
+    help = "Auto-approve all tool actions for this session; routed to the agent's own "
+    "flag/config. Any of the three spellings works for any agent.",
 )
 _PERSIST_OPTION = typer.Option(
     False,
     "--persist/--no-persist",
+    rich_help_panel = _PANEL_SESSION,
     help = (
         "Keep this agent's Unsloth-managed session dir so you can resume it later. "
         "codex/openclaw/hermes/pi have their whole home relocated into an Unsloth dir "
@@ -157,6 +231,12 @@ _PERSIST_OPTION = typer.Option(
         "the agent unchanged."
     ),
 )
+_AS_SUBAGENT_OPTION = typer.Option(
+    False,
+    "--as-subagent",
+    rich_help_panel = _PANEL_SESSION,
+    help = "Keep the coding agent's current model and add Unsloth as a local subagent.",
+)
 
 # Per-agent CLI flag for "run tools without prompting". OpenCode (native --auto is
 # command-scoped, handled below) and OpenClaw (config-only) are absent from this prefix map.
@@ -303,6 +383,14 @@ class LoadOptions(NamedTuple):
     tensor_parallel: bool = False
 
 
+class ServerOptions(NamedTuple):
+    """Tool-call knobs forwarded to an auto-started `unsloth run` server."""
+
+    enable_tools: bool = False
+    tool_call_healing: Optional[bool] = None
+    tool_call_nudging: Optional[bool] = None
+
+
 def _split_repo_variant(model: str) -> tuple:
     """Split ``org/name:QUANT`` into ``(repo, variant)`` -> ``("org/name", "QUANT")``.
 
@@ -326,11 +414,87 @@ def _split_repo_variant(model: str) -> tuple:
     return repo, variant
 
 
+def _looks_like_model(token: str) -> bool:
+    """True for a bare `org/name(:variant)` hub id that is not a flag or a local path.
+
+    Reuses `_is_hub_model_id`, so a relative dir like `owner/repo` that actually exists
+    is left for the agent (e.g. OpenCode opens it as a project) instead of being taken
+    as a model; a non-existent `org/name` is treated as a hub id.
+    """
+    if not token or token.startswith("-") or " " in token:
+        return False
+    repo, _ = _split_repo_variant(token)
+    return _is_hub_model_id(repo)
+
+
+def _consume_positional_model(model: Optional[str], args: list) -> tuple:
+    """Route a leading `org/name` positional to --model when --model was not given.
+
+    Only the FIRST token is considered so an option value like `--profile owner/repo`
+    is never stolen, and only when --model is absent so an explicit --model always wins.
+    Returns (model, remaining_args) with the consumed token removed from the passthrough.
+    """
+    args = list(args)
+    if model or not args or not _looks_like_model(args[0]):
+        return model, args
+    return args[0], args[1:]
+
+
+def _display_model_spec(model: str, variant: Optional[str]) -> str:
+    """Return a user-facing model name that includes the selected GGUF variant."""
+    repo, inline_variant = _split_repo_variant(model)
+    selected_variant = variant or inline_variant
+    return f"{repo}:{selected_variant}" if selected_variant else model
+
+
+def _subagent_model_id(
+    base: str,
+    key: str,
+    entry: dict,
+    requested_model: Optional[str],
+    requested_variant: Optional[str],
+) -> str:
+    """Return an API model id that preserves the selected GGUF variant.
+
+    Coding-agent model definitions outlive the initial load. If Unsloth later
+    unloads the model, a bare repository id may resolve to a different cached
+    quant. Include the explicit or currently loaded variant so an automatic
+    reload selects the same weights.
+    """
+    model_id = str(entry["id"])
+    _, inline_variant = _split_repo_variant(requested_model or "")
+    variant = requested_variant or inline_variant
+    if not variant:
+        try:
+            status = _http_json("GET", f"{base}/api/inference/status", key)
+        except Exception:
+            status = {}
+            typer.echo(
+                "Warning: could not verify the loaded GGUF variant; a later reload "
+                "may pick a different cached quant. Pass :variant to pin it.",
+                err = True,
+            )
+        if status.get("is_gguf"):
+            variant = status.get("gguf_variant")
+    return (
+        _display_model_spec(model_id, str(variant))
+        if variant and _is_hub_model_id(model_id)
+        else model_id
+    )
+
+
 def _fail(message: str) -> NoReturn:
     typer.echo(message, err = True)
     raise typer.Exit(code = 1)
 
 
+def _reject_as_subagent(agent: str, args: list) -> None:
+    # Reject early; otherwise the flag reaches the agent binary and fails after
+    # Studio has already loaded the model.
+    if "--as-subagent" in args:
+        _fail(f"--as-subagent is not supported for {agent}.")
+
+
 def _http_error_detail(exc: urllib.error.HTTPError) -> str:
     try:
         body = json.loads(exc.read().decode())
@@ -373,11 +537,265 @@ def _http_json(
 
 
 # A server that WE auto-started (never one we merely found). Kept at module scope so
-# _run's finally and the atexit backstop can tear it down without threading a handle
+# failure paths and the atexit backstop can tear it down without threading a handle
 # through all six agent commands. Only one agent runs per process, so one slot is enough.
 _auto_served_server: Optional[subprocess.Popen] = None
 # Model download + load can be slow; give the auto-started server room before giving up.
 _SERVER_START_TIMEOUT_S = 900
+_DOWNLOAD_POLL_INTERVAL_S = 1.0
+_START_API_KEY_PREFIX = "UNSLOTH_START_API_KEY: "
+_START_API_KEY_MARKER_ENV = "_UNSLOTH_START_API_KEY_MARKER"
+
+
+def _format_download_bytes(value: int) -> str:
+    value = max(0, int(value))
+    for unit in ("B", "KiB", "MiB", "GiB", "TiB"):
+        if value < 1024 or unit == "TiB":
+            precision = 0 if unit in ("B", "KiB") else 1
+            return f"{value:.{precision}f} {unit}"
+        value /= 1024
+    return "0 B"
+
+
+def _format_download_eta(seconds: float) -> str:
+    seconds = max(0, int(seconds))
+    if seconds < 60:
+        return f"{seconds}s"
+    minutes, seconds = divmod(seconds, 60)
+    if minutes < 60:
+        return f"{minutes}m {seconds:02d}s"
+    hours, minutes = divmod(minutes, 60)
+    return f"{hours}h {minutes:02d}m"
+
+
+class _DownloadProgressDisplay:
+    """Render download progress without making redirected output noisy."""
+
+    def __init__(self) -> None:
+        self._samples: list[tuple[float, int]] = []
+        self._shown = False
+        self._last_bucket = -1
+        self._last_line_length = 0
+        self._last_expected = 0
+        self._interactive = bool(getattr(sys.stdout, "isatty", lambda: False)())
+
+    def update(self, progress: dict) -> None:
+        downloaded = max(0, int(progress.get("downloaded_bytes") or 0))
+        completed = max(0, int(progress.get("completed_bytes") or 0))
+        expected = max(0, int(progress.get("expected_bytes") or 0))
+        self._last_expected = max(self._last_expected, expected)
+        fraction = float(progress.get("progress") or 0)
+        if downloaded <= 0:
+            return
+        # A fully cached snapshot can report 99% with no incomplete bytes; that is
+        # not a transfer, so don't show it as a download.
+        if completed >= downloaded > 0:
+            return
+
+        now = time.monotonic()
+        if self._samples and downloaded < self._samples[-1][1]:
+            self._samples.clear()
+        self._samples.append((now, downloaded))
+        cutoff = now - 15.0
+        while len(self._samples) > 2 and self._samples[0][0] < cutoff:
+            self._samples.pop(0)
+
+        rate = 0.0
+        if len(self._samples) >= 2:
+            elapsed = self._samples[-1][0] - self._samples[0][0]
+            delta = self._samples[-1][1] - self._samples[0][1]
+            if elapsed >= 1.0 and delta > 0:
+                rate = delta / elapsed
+
+        if expected > 0:
+            # The endpoint caps at 99% while bytes remain in an incomplete file; trust it.
+            fraction = min(1.0, max(0.0, fraction))
+            percent = min(100, max(0, int(fraction * 100)))
+            filled = min(24, int(fraction * 24))
+            bar = "=" * filled + ">" + "." * max(0, 23 - filled) if filled < 24 else "=" * 24
+            line = (
+                f"Downloading model [{bar}] {percent:3d}% "
+                f"{_format_download_bytes(downloaded)} / {_format_download_bytes(expected)}"
+            )
+            bucket = percent // 10
+            if rate > 0:
+                line += f" | {_format_download_bytes(rate)}/s"
+                if downloaded < expected:
+                    line += f" | ETA {_format_download_eta((expected - downloaded) / rate)}"
+        else:
+            line = f"Downloading model: {_format_download_bytes(downloaded)}"
+            bucket = downloaded // (1024**3)
+            if rate > 0:
+                line += f" | {_format_download_bytes(rate)}/s"
+
+        if self._interactive:
+            padding = " " * max(0, self._last_line_length - len(line))
+            typer.echo(f"\r{line}{padding}", nl = False)
+            sys.stdout.flush()
+            self._last_line_length = len(line)
+        elif not self._shown or bucket > self._last_bucket:
+            typer.echo(line)
+            self._last_bucket = bucket
+        self._shown = True
+
+    def close(self) -> None:
+        if self._interactive and self._shown:
+            typer.echo()
+        self._last_line_length = 0
+
+    def complete(self) -> None:
+        """Finish a displayed transfer after the model load confirms success."""
+        if not self._shown:
+            return
+        downloaded = self._samples[-1][1] if self._samples else 0
+        expected = max(downloaded, getattr(self, "_last_expected", 0))
+        self.update(
+            {
+                "downloaded_bytes": expected,
+                "expected_bytes": expected,
+                "progress": 1.0,
+            }
+        )
+
+
+def _normalized_variant(value: object) -> str:
+    return re.sub(r"[^a-z0-9]", "", str(value or "").lower())
+
+
+class _ModelDownloadProgress:
+    """Best-effort polling of the model download endpoints."""
+
+    def __init__(self, base: str, key: str, model: str, variant: Optional[str]) -> None:
+        self._base = base
+        self._key = key
+        self._model = model
+        self._variant = variant or ""
+        self._expected_bytes = 0
+        self._display = _DownloadProgressDisplay()
+        self._configured = False
+        self._disabled = not _is_hub_model_id(model)
+        self._progress_prefix = "/api/hub"
+
+    def _configure(self) -> None:
+        self._configured = True
+        if self._disabled:
+            return
+        # GGUF repos need the selected quant's size; the repo endpoint totals every
+        # quant. Resolve the variant first, otherwise show bytes only.
+        if self._variant or "gguf" in self._model.lower():
+            try:
+                params = urlencode({"repo_id": self._model})
+                try:
+                    info = _http_json(
+                        "GET",
+                        f"{self._base}/api/hub/gguf-variants?{params}",
+                        self._key,
+                        timeout = 10,
+                    )
+                except urllib.error.HTTPError as exc:
+                    if exc.code != 404:
+                        raise
+                    self._progress_prefix = "/api/models"
+                    info = _http_json(
+                        "GET",
+                        f"{self._base}/api/models/gguf-variants?{params}",
+                        self._key,
+                        timeout = 10,
+                    )
+                self._variant = self._variant or str(info.get("default_variant") or "")
+                wanted = _normalized_variant(self._variant)
+                for item in info.get("variants") or []:
+                    quant = _normalized_variant(item.get("quant"))
+                    filename = _normalized_variant(item.get("filename"))
+                    if wanted and (wanted == quant or wanted in filename):
+                        self._expected_bytes = int(
+                            item.get("download_size_bytes") or item.get("size_bytes") or 0
+                        )
+                        break
+            except Exception:
+                # Older servers lack this endpoint; byte progress is still useful.
+                pass
+
+    def poll(self) -> None:
+        if not self._configured:
+            self._configure()
+        if self._disabled:
+            return
+        try:
+            if self._variant or "gguf" in self._model.lower():
+                params = urlencode(
+                    {
+                        "repo_id": self._model,
+                        "variant": self._variant,
+                        "expected_bytes": self._expected_bytes,
+                    }
+                )
+                url = f"{self._base}{self._progress_prefix}/gguf-download-progress?{params}"
+            else:
+                url = (
+                    f"{self._base}{self._progress_prefix}/download-progress?"
+                    f"{urlencode({'repo_id': self._model})}"
+                )
+            try:
+                reading = _http_json("GET", url, self._key, timeout = 10)
+            except urllib.error.HTTPError as exc:
+                if exc.code != 404 or self._progress_prefix == "/api/models":
+                    raise
+                self._progress_prefix = "/api/models"
+                self.poll()
+                return
+            self._display.update(reading)
+        except Exception:
+            # Progress is best-effort; never fail the load over a polling error.
+            self._disabled = True
+
+    def close(self) -> None:
+        self._display.close()
+
+    def complete(self) -> None:
+        self._display.complete()
+
+
+def _load_model_with_progress(
+    base: str, key: str, model: str, load: LoadOptions, payload: dict
+) -> dict:
+    """Run the blocking load request while polling its download progress."""
+    result: list[tuple[bool, object]] = []
+    done = threading.Event()
+
+    def _load() -> None:
+        try:
+            value = _http_json(
+                "POST",
+                f"{base}/api/inference/load",
+                key,
+                payload,
+                timeout = 3600,
+                error = "Model load failed",
+            )
+            result.append((True, value))
+        except BaseException as exc:
+            result.append((False, exc))
+        finally:
+            done.set()
+
+    threading.Thread(target = _load, name = "unsloth-model-load", daemon = True).start()
+    progress = _ModelDownloadProgress(base, key, model, load.gguf_variant)
+    loading_announced = False
+    try:
+        while not done.wait(_DOWNLOAD_POLL_INTERVAL_S):
+            if not loading_announced:
+                typer.echo(f"Loading model: {_display_model_spec(model, load.gguf_variant)}")
+                loading_announced = True
+            progress.poll()
+        ok, value = result[0]
+        if not ok:
+            assert isinstance(value, BaseException)
+            raise value
+        progress.complete()
+        return value if isinstance(value, dict) else {}
+    finally:
+        progress.close()
 
 
 def _studio_healthy(base: str, timeout: float = 3.0) -> bool:
@@ -396,6 +814,11 @@ def _log_tail(path: Path, lines: int = 20) -> str:
         return "(no server log)"
 
 
+def _redacted_log_tail(path: Path, lines: int = 20) -> str:
+    """Tail with minted keys removed; only for tails shown on the terminal."""
+    return re.sub(r"sk-unsloth-\S+", "sk-unsloth-[redacted]", _log_tail(path, lines))
+
+
 def _shutdown_server(server: Optional[subprocess.Popen]) -> None:
     # Idempotent teardown of a server WE started, plus its own children (llama-server,
     # cloudflared). A no-op once the process is already gone.
@@ -438,13 +861,28 @@ def _shutdown_auto_served() -> None:
         _shutdown_server(server)
 
 
-def _start_studio_server(base: str, model: str, load: LoadOptions) -> subprocess.Popen:
+def _keep_auto_served() -> bool:
+    """Release ownership so a successfully started server survives this CLI."""
+    global _auto_served_server
+    server, _auto_served_server = _auto_served_server, None
+    atexit.unregister(_shutdown_auto_served)
+    return server is not None and server.poll() is None
+
+
+def _start_studio_server(
+    base: str,
+    model: str,
+    load: LoadOptions,
+    server: ServerOptions = ServerOptions(),
+) -> subprocess.Popen:
     """Spawn `unsloth run` for `model`, wait until it is fully ready, and return it."""
     global _auto_served_server
     unsloth = shutil.which("unsloth") or "unsloth"
     parsed = urlparse(base)
-    # --disable-tools = passthrough mode (relay the agent's own tools); --no-cloudflare =
-    # loopback only, no tunnel. Mirrors .github/scripts/serve-unsloth-run.sh.
+    # Tools default off = passthrough mode (relay the agent's own tools); --no-cloudflare =
+    # loopback only, no tunnel. Mirrors .github/scripts/serve-unsloth-run.sh. Healing/nudging
+    # travel via the child env below (version-agnostic) rather than new run flags that an
+    # older re-exec'd run could mistake for llama-server args.
     command = [
         unsloth,
         "run",
@@ -452,7 +890,7 @@ def _start_studio_server(base: str, model: str, load: LoadOptions) -> subprocess
         parsed.hostname or "127.0.0.1",
         "-p",
         str(parsed.port or 8888),
-        "--disable-tools",
+        "--enable-tools" if server.enable_tools else "--disable-tools",
         "--no-cloudflare",
         "--model",
         model,
@@ -467,9 +905,8 @@ def _start_studio_server(base: str, model: str, load: LoadOptions) -> subprocess
         command += ["--tensor-parallel"]
 
     log_path = Path(tempfile.gettempdir()) / f"unsloth-start-server-{os.getpid()}.log"
-    typer.echo(
-        f"No Unsloth server at {base}. Starting one for {model} (loading the model can take a while)…"
-    )
+    typer.echo("Starting Unsloth server")
+    typer.echo(f"Model: {_display_model_spec(model, load.gguf_variant)}")
     typer.echo(f"Server log: {log_path}")
     # 0600: the `unsloth run` banner in this log carries the minted sk-unsloth- key, and
     # the tempdir is world-traversable. Unlink first so a stale looser-mode file (pid
@@ -477,8 +914,30 @@ def _start_studio_server(base: str, model: str, load: LoadOptions) -> subprocess
     log_path.unlink(missing_ok = True)
     log = os.fdopen(os.open(log_path, os.O_WRONLY | os.O_CREAT | os.O_EXCL, 0o600), "wb")
     # Own session/process group so a mid-session Ctrl+C (cancel a turn) doesn't reach the
-    # server; we tear it down explicitly when the agent exits.
-    kwargs: dict = {"stdout": log, "stderr": subprocess.STDOUT, "stdin": subprocess.DEVNULL}
+    # server. It survives a successful agent session; torn down on startup/launch failure.
+    child_env = os.environ.copy()
+    # Pass the marker via env so an older launcher ignores it instead of treating an
+    # unknown CLI flag as a llama-server arg; new launchers preserve it across re-exec.
+    child_env[_START_API_KEY_MARKER_ENV] = "1"
+    # Convey healing/nudging through the env; `unsloth run` reads these when its own
+    # flags are omitted, so this works even if run re-execs into an older Studio venv.
+    # Only write when the operator set the flag explicitly; otherwise keep whatever they
+    # already exported (child_env is a copy of os.environ), falling back to the start
+    # defaults (healing on, nudging on) when nothing was inherited.
+    if server.tool_call_healing is not None:
+        child_env["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] = "0" if server.tool_call_healing else "1"
+    elif "UNSLOTH_DISABLE_TOOL_CALL_HEALING" not in child_env:
+        child_env["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] = "0"
+    if server.tool_call_nudging is not None:
+        child_env["UNSLOTH_TOOL_CALL_NUDGE"] = "1" if server.tool_call_nudging else "0"
+    elif "UNSLOTH_TOOL_CALL_NUDGE" not in child_env:
+        child_env["UNSLOTH_TOOL_CALL_NUDGE"] = "1"
+    kwargs: dict = {
+        "stdout": log,
+        "stderr": subprocess.STDOUT,
+        "stdin": subprocess.DEVNULL,
+        "env": child_env,
+    }
     if os.name == "nt":
         kwargs["creationflags"] = subprocess.CREATE_NEW_PROCESS_GROUP
     else:
@@ -491,17 +950,45 @@ def _start_studio_server(base: str, model: str, load: LoadOptions) -> subprocess
     atexit.register(_shutdown_auto_served)
 
     deadline = time.monotonic() + _SERVER_START_TIMEOUT_S
-    while time.monotonic() < deadline:
-        if server.poll() is not None:
-            tail = _log_tail(log_path)
-            _shutdown_auto_served()
-            _fail(f"The Unsloth server stopped before it was ready. Last log lines:\n{tail}")
-        # `unsloth run` prints the minted key only after the server is up AND the model is
-        # loaded, so it is the fully-ready signal (same contract serve-unsloth-run.sh uses).
-        if _studio_healthy(base) and "sk-unsloth-" in _log_tail(log_path, lines = 400):
-            typer.echo(f"Unsloth server ready at {base}.")
-            return server
-        time.sleep(2.0)
+    progress: Optional[_ModelDownloadProgress] = None
+    early_key_seen = False
+    try:
+        while time.monotonic() < deadline:
+            if server.poll() is not None:
+                # The early key marker lands here before load finishes; redact it.
+                tail = _redacted_log_tail(log_path)
+                _shutdown_auto_served()
+                _fail(f"The Unsloth server stopped before it was ready. Last log lines:\n{tail}")
+            tail = _log_tail(log_path, lines = 400)
+            if progress is None:
+                marker = re.search(
+                    rf"^{re.escape(_START_API_KEY_PREFIX)}(sk-unsloth-[^\s]+)$",
+                    tail,
+                    flags = re.MULTILINE,
+                )
+                if marker:
+                    early_key_seen = True
+                    progress = _ModelDownloadProgress(
+                        base,
+                        marker.group(1),
+                        model,
+                        load.gguf_variant,
+                    )
+            if progress is not None:
+                progress.poll()
+            # New children emit an early key marker, so wait for the final model banner;
+            # older children only print the key after load, so fall back to that.
+            ready_signal = "Model loaded:" in tail if early_key_seen else "sk-unsloth-" in tail
+            if _studio_healthy(base) and ready_signal:
+                if progress is not None:
+                    progress.complete()
+                    progress.close()
+                    progress = None
+                return server
+            time.sleep(2.0)
+    finally:
+        if progress is not None:
+            progress.close()
     _shutdown_auto_served()
     _fail(
         f"The Unsloth server didn't become ready within {_SERVER_START_TIMEOUT_S}s. See {log_path}."
@@ -527,6 +1014,7 @@ def _require_studio(
     *,
     serve: bool = False,
     launch: bool = True,
+    server_options: ServerOptions = ServerOptions(),
 ) -> tuple:
     """Return (base, server). server is a Popen only when WE auto-started it."""
     base = find_studio_server()
@@ -547,7 +1035,11 @@ def _require_studio(
         # Normalize to the port unsloth run actually binds, so the health poll and the
         # returned base hit the same server we launch (not a portless :80).
         expected = _effective_base(expected)
-        return expected, _start_studio_server(expected, model, load or LoadOptions())
+        load = load or LoadOptions()
+        # Leave a bare GGUF repo's variant unset: the server's own quant preference already
+        # picks the best available (UD-Q4_K_XL for Unsloth uploads, else Q4_K_M) and falls back
+        # when that exact quant is missing, which forcing a fixed variant here would break.
+        return expected, _start_studio_server(expected, model, load, server_options)
     model_hint = "" if model else " Pass --model to have it start one for you, or"
     _fail(
         f"No running Unsloth server found at {expected}.{model_hint} start one with "
@@ -796,6 +1288,7 @@ def _resolve_model(
     load: LoadOptions = LoadOptions(),
 ) -> dict:
     models = _loaded_models(base, key)
+    load_requested = False
     # Only casefold-match ids against a loopback Unsloth, where _is_hub_model_id's
     # local existence probe can actually reject a server-side path; see the note there.
     allow_casefold = is_loopback_url(base)
@@ -825,11 +1318,30 @@ def _resolve_model(
         )
     )
     if requested and match is None:
-        typer.echo(
-            f"Loading {requested} - please wait…"
-            if load_has_overrides
-            else f"Loading {requested} on the Unsloth server (this can take a while)…"
-        )
+        load_requested = True
+        active = next((m for m in models if m.get("loaded") is not False), None)
+        active_id = active.get("id") if active else None
+        if active_id and not _model_id_matches(
+            active_id,
+            requested,
+            allow_casefold = allow_casefold,
+        ):
+            typer.echo(f"Switching the Unsloth server from {active_id} to {requested}.")
+            typer.echo("This unloads the current model for every attached session.")
+        elif active_id and load.gguf_variant:
+            # Same repo id but an explicit quant still replaces the resident
+            # weights; /v1/models has no variant, so ask the status endpoint.
+            try:
+                status = _http_json("GET", f"{base}/api/inference/status", key)
+            except Exception:
+                status = {}
+            resident = status.get("gguf_variant") if status.get("is_gguf") else None
+            if resident and _normalized_variant(resident) != _normalized_variant(load.gguf_variant):
+                typer.echo(
+                    f"Switching the Unsloth server from {active_id}:{resident} "
+                    f"to {requested}:{load.gguf_variant}."
+                )
+                typer.echo("This unloads the current model for every attached session.")
         # Mirror `unsloth run`'s load knobs; keep the default payload as just
         # model_path so a bare `--model` load is unchanged.
         payload = {"model_path": requested}
@@ -841,14 +1353,9 @@ def _resolve_model(
             payload["load_in_4bit"] = False
         if load.tensor_parallel:
             payload["tensor_parallel"] = True
-        loaded = _http_json(
-            "POST",
-            f"{base}/api/inference/load",
-            key,
-            payload,
-            timeout = 3600,
-            error = "Model load failed",
-        )
+        loaded = _load_model_with_progress(base, key, requested, load, payload)
+        if loaded.get("status") == "already_loaded":
+            typer.echo(f"Reusing loaded model: {_display_model_spec(requested, load.gguf_variant)}")
         # Unsloth registers the model under a canonical id (resolved identifier,
         # casing) that /v1/models echoes but which may differ from the path we
         # passed; match on the id the load reports so we don't silently fall
@@ -861,13 +1368,16 @@ def _resolve_model(
             (
                 m
                 for m in models
-                if any(
+                if m.get("loaded") is not False
+                and any(
                     _model_id_matches(m.get("id"), w, allow_casefold = allow_casefold) for w in wanted
                 )
             ),
             None,
         )
     if match is not None:
+        if requested and not load_requested:
+            typer.echo(f"Reusing loaded model: {_display_model_spec(requested, load.gguf_variant)}")
         return match
     if requested:
         # We asked Unsloth to load it and it didn't surface in /v1/models; don't
@@ -881,7 +1391,13 @@ def _resolve_model(
             "No model is loaded in Unsloth. Load one from the model dropdown in "
             "the UI, or pass --model <hf-id-or-path> to load it from here."
         )
-    return models[0]
+    resident = next((m for m in models if m.get("loaded") is not False), None)
+    if resident is None:
+        _fail(
+            "No model is currently resident in Unsloth. Pass --model <hf-id-or-path> "
+            "to reload one, or load it from the model dropdown in the UI."
+        )
+    return resident
 
 
 def _require_gguf_for_codex(base: str, key: str, model_id: str) -> None:
@@ -943,6 +1459,25 @@ def _claude_flags(model_id: str) -> list:
     return [_DYNAMIC_SECTIONS_FLAG, "--settings", _claude_settings_overlay(model_id)]
 
 
+def _claude_local_env(base: str, key: str, entry: dict) -> dict:
+    """Build the local endpoint, cache, display, and compaction environment."""
+    model_id = entry["id"]
+    env = {
+        "ANTHROPIC_BASE_URL": base,
+        "ANTHROPIC_AUTH_TOKEN": key,
+        "ANTHROPIC_MODEL": model_id,
+        "CLAUDE_CODE_ATTRIBUTION_HEADER": "0",
+        "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1",
+        "CLAUDE_CODE_DISABLE_EXPERIMENTAL_BETAS": "1",
+        "CLAUDE_CODE_NO_FLICKER": "1",
+    }
+    window = entry.get("context_length") or entry.get("max_context_length")
+    if window:
+        env["CLAUDE_CODE_AUTO_COMPACT_WINDOW"] = str(int(window))
+        env["CLAUDE_AUTOCOMPACT_PCT_OVERRIDE"] = "90"
+    return env
+
+
 def _merge_codex_config(existing: str, base: str) -> str:
     chunks = re.split(r"(?m)^(?=\[)", existing)  # preamble, then one chunk per table
     if not re.search(r"(?m)^\s*oss_provider\s*=", chunks[0]):
@@ -1056,6 +1591,206 @@ def write_codex_config(base: str, model: dict, home: Path) -> None:
         typer.echo(f"Updated {profile}")
 
 
+def write_codex_subagent_config(base: str, key: str, model: dict, home: Path) -> Path:
+    """Write a session-scoped Codex custom agent without replacing the main model."""
+    home.mkdir(parents = True, exist_ok = True)
+    model_id = model["id"]
+    window = model.get("context_length") or model.get("max_context_length")
+    catalog_name = "unsloth-model-catalog.json"
+    text = (
+        f"name = {json.dumps(_SUBAGENT_NAME)}\n"
+        f"description = {json.dumps(_SUBAGENT_DESCRIPTION)}\n"
+        f"developer_instructions = {json.dumps(_SUBAGENT_INSTRUCTIONS)}\n"
+        f"model_provider = {json.dumps(_CODEX_PROFILE)}\n"
+        f"model = {json.dumps(model_id)}\n"
+    )
+    if _codex_supports_model_catalog() and _CODEX_FALLBACK_PROMPT.is_file():
+        catalog = home / catalog_name
+        catalog_text = json.dumps(_codex_model_catalog(model), indent = 2) + "\n"
+        if not catalog.exists() or catalog.read_text(encoding = "utf-8") != catalog_text:
+            catalog.write_text(catalog_text, encoding = "utf-8")
+            typer.echo(f"Updated {catalog}")
+        text += f"model_catalog_json = {json.dumps(catalog_name)}\n"
+    if window:
+        text += f"model_context_window = {int(window)}\n"
+    credential = home / "unsloth-auth.json"
+    _write_private_json(credential, {"token": key})
+    auth_command = sys.executable
+    auth_args = [
+        "-c",
+        "import json,sys; print(json.load(open(sys.argv[1], encoding='utf-8'))['token'])",
+        str(credential),
+    ]
+    if _wsl_windows_executable(["codex"]):
+        auth_command = "wsl.exe"
+        auth_args = [
+            "-d",
+            os.environ["WSL_DISTRO_NAME"],
+            "--",
+            sys.executable,
+            *auth_args,
+        ]
+    text += (
+        f"\n{_PROVIDER_HEADER}\n"
+        'name = "Unsloth Studio"\n'
+        f"base_url = {json.dumps(base + '/v1')}\n"
+        'wire_api = "responses"\n'
+        f"\n{_PROVIDER_HEADER[:-1]}.auth]\n"
+        f"command = {json.dumps(auth_command)}\n"
+        f"args = {json.dumps(auth_args)}\n"
+        "timeout_ms = 5000\n"
+    )
+    path = home / f"{_SUBAGENT_NAME}.toml"
+    if not path.exists() or path.read_text(encoding = "utf-8") != text:
+        path.write_text(text, encoding = "utf-8")
+        typer.echo(f"Updated {path}")
+    return path
+
+
+def _agent_config_path(path: Path, command: list) -> str:
+    """Translate a generated config path when a Windows agent runs through WSL."""
+    return _wsl_windows_path(path) if _wsl_windows_executable(command) else str(path)
+
+
+def _opencode_subagent_inline_config(path: Path, permission: dict) -> dict:
+    """Keep the local provider visible without hiding the parent's allowed providers."""
+    inline: dict = {}
+    inherited = os.environ.get("OPENCODE_CONFIG_CONTENT")
+    if inherited:
+        try:
+            parsed = json.loads(inherited)
+        except ValueError:
+            _fail("OPENCODE_CONFIG_CONTENT is not valid JSON.")
+        if not isinstance(parsed, dict):
+            _fail("OPENCODE_CONFIG_CONTENT must contain a JSON object.")
+        inline.update(parsed)
+
+    def merge_provider_filters(effective_config: dict) -> None:
+        enabled = effective_config.get("enabled_providers")
+        if isinstance(enabled, list):
+            inline["enabled_providers"] = list(dict.fromkeys([*enabled, _OPENCODE_PROVIDER]))
+        disabled = effective_config.get("disabled_providers")
+        if isinstance(disabled, list) and _OPENCODE_PROVIDER in disabled:
+            inline["disabled_providers"] = [
+                provider for provider in disabled if provider != _OPENCODE_PROVIDER
+            ]
+
+    # The inherited inline layer is already highest priority. Merge it even when
+    # OpenCode is not installed yet, as in fresh-install and --no-launch flows.
+    merge_provider_filters(inline)
+    effective = inline
+
+    executable = _which_with_install_dirs("opencode")
+    if executable is None:
+        typer.echo(
+            f"Warning: OpenCode is not installed, so provider filters could not be checked. "
+            f"The target configuration must allow '{_OPENCODE_PROVIDER}'.",
+            err = True,
+        )
+    else:
+        env = os.environ.copy()
+        env["OPENCODE_CONFIG"] = _agent_config_path(path, ["opencode"])
+        try:
+            resolved = subprocess.run(
+                [executable, "debug", "config"],
+                capture_output = True,
+                text = True,
+                timeout = 15,
+                env = env,
+            )
+        except Exception as exc:
+            _fail(f"Could not inspect OpenCode provider filters: {exc}")
+        if resolved.returncode != 0:
+            detail = resolved.stderr.strip() or resolved.stdout.strip()
+            _fail(f"Could not inspect OpenCode provider filters: {detail or 'unknown error'}")
+        try:
+            effective = json.loads(resolved.stdout)
+        except ValueError:
+            _fail("Could not inspect OpenCode provider filters: invalid JSON response.")
+        if not isinstance(effective, dict):
+            _fail("Could not inspect OpenCode provider filters: expected a JSON object.")
+
+        merge_provider_filters(effective)
+
+    depth = effective.get("subagent_depth")
+    inline["subagent_depth"] = (
+        depth if isinstance(depth, int) and not isinstance(depth, bool) and depth > 0 else 1
+    )
+    if permission:
+        inline["permission"] = permission
+    return inline
+
+
+def write_claude_subagent_plugin(path: Path, server_env: dict) -> Path:
+    """Write a session plugin that exposes the local Claude child through MCP."""
+    plugin = path / "unsloth-local-agent"
+    command = sys.executable
+    args = ["-m", _CLAUDE_SUBAGENT_MCP_MODULE]
+    mcp_env = dict(server_env)
+    if _wsl_windows_executable(["claude"]):
+        command = "wsl.exe"
+        args = [
+            "-d",
+            os.environ["WSL_DISTRO_NAME"],
+            "--",
+            sys.executable,
+            "-m",
+            _CLAUDE_SUBAGENT_MCP_MODULE,
+        ]
+        mcp_env["WSLENV"] = _merge_wslenv(
+            os.environ.get("WSLENV", ""),
+            _wsl_bridge_names(server_env, ()),
+        )
+    _write_private_json(
+        plugin / ".claude-plugin" / "plugin.json",
+        {
+            "name": "unsloth-local-agent",
+            "version": "1.0.0",
+            "description": _SUBAGENT_DESCRIPTION,
+            "author": {"name": "Unsloth AI"},
+        },
+    )
+    _write_private_json(
+        plugin / ".mcp.json",
+        {
+            "mcpServers": {
+                "unsloth": {
+                    "type": "stdio",
+                    "command": command,
+                    "args": args,
+                    "env": mcp_env,
+                }
+            }
+        },
+    )
+    skill = plugin / "skills" / "local-agent" / "SKILL.md"
+    skill.parent.mkdir(parents = True, exist_ok = True, mode = 0o700)
+    skill.write_text(
+        "---\n"
+        "description: Delegate a task to the local agent powered by Unsloth. Use when the "
+        "user asks to spawn an Unsloth agent or local agent.\n"
+        "---\n\n"
+        "Call the Unsloth local agent tool once with the complete task. Return its result "
+        "to the user without claiming that the cloud parent completed the local work.\n",
+        encoding = "utf-8",
+    )
+    return plugin
+
+
+def _codex_subagent_flags(path: Path) -> list[str]:
+    config_path = _agent_config_path(path, ["codex"])
+    return [
+        "--enable",
+        "multi_agent",
+        "-c",
+        "agents.max_depth=1",
+        "-c",
+        f"agents.{_SUBAGENT_NAME}.description={json.dumps(_SUBAGENT_DESCRIPTION)}",
+        "-c",
+        f"agents.{_SUBAGENT_NAME}.config_file={json.dumps(config_path)}",
+    ]
+
+
 def _wsl_windows_executable(command: list) -> Optional[str]:
     if os.name == "nt" or not os.environ.get("WSL_DISTRO_NAME"):
         return None
@@ -1356,7 +2091,7 @@ def _launch(
     env: dict,
     install_hint: str,
     unset_env: tuple = (),
-) -> NoReturn:
+) -> int:
     # Resolve well-known install dirs (e.g. ~/.local/bin) first, so an already-installed
     # agent not yet on PATH is found instead of prompting a needless reinstall.
     _augment_path_with_install_dirs()
@@ -1382,7 +2117,7 @@ def _launch(
     finally:
         signal.signal(signal.SIGINT, previous)
     # Negative returncode means killed by signal N; shells expect 128+N.
-    raise typer.Exit(code = code if code >= 0 else 128 - code)
+    return code if code >= 0 else 128 - code
 
 
 def _connect(
@@ -1392,6 +2127,7 @@ def _connect(
     *,
     serve: bool = False,
     launch: bool = True,
+    server_options: ServerOptions = ServerOptions(),
 ) -> tuple:
     # `--model org/name:QUANT` is shorthand for `--model org/name --gguf-variant QUANT`.
     # Split it before we match/serve so the attach path resolves against the already-loaded
@@ -1403,7 +2139,9 @@ def _connect(
             model = repo
             if not load.gguf_variant:
                 load = load._replace(gguf_variant = variant)
-    base, server = _require_studio(model, load, serve = serve, launch = launch)
+    base, server = _require_studio(
+        model, load, serve = serve, launch = launch, server_options = server_options
+    )
     try:
         key = _agent_api_key(base, api_key, auto_started = server is not None)
         # A server we just started has exactly the requested model loaded, so resolve to
@@ -1434,16 +2172,35 @@ def _run(
     # --no-launch recipes stay intact.
     if launch and clear_screen:
         click.clear()
-    typer.echo(f"Unsloth {base} · model {entry['id']}")
+    typer.echo(f"Unsloth ready at {base} · model {entry['id']}")
     if not launch:
         env, wsl_env_bridge = _wsl_shim_env(command, env, unset_env)
         _print_env(env, command, unset_env = unset_env, wsl_env_bridge = wsl_env_bridge)
+        if _keep_auto_served():
+            typer.echo(f"Unsloth Studio is still running at {base}.")
+            typer.echo("Stop it with: unsloth studio stop")
         return
     try:
-        _launch(command, env, install_hint = install_hint, unset_env = unset_env)
-    finally:
-        # Tear down a server we auto-started once the agent session ends (no-op otherwise).
+        code = _launch(command, env, install_hint = install_hint, unset_env = unset_env)
+    except BaseException:
+        # Startup succeeded but the agent failed to launch; tear the server down
+        # rather than orphan it.
         _shutdown_auto_served()
+        raise
+    auto_started = _auto_served_server is not None
+    kept = _keep_auto_served()
+    if auto_started and not kept:
+        typer.echo(f"The auto-started Unsloth server at {base} stopped during the session.")
+        raise typer.Exit(code = code)
+    if code:
+        # The server status below must not read as a successful agent session.
+        typer.echo(f"The agent exited with code {code}.")
+    if is_loopback_url(base):
+        typer.echo(f"Unsloth Studio is still running at {base}.")
+        typer.echo("Stop it with: unsloth studio stop")
+    else:
+        typer.echo(f"The remote Unsloth server is still running at {base}.")
+    raise typer.Exit(code = code)
 
 
 def _agents_config_root() -> Path:
@@ -1620,6 +2377,7 @@ def write_opencode_config(
     model: dict,
     path: Path,
     yolo: bool = False,
+    as_subagent: bool = False,
 ) -> dict:
     config = _read_json_object(path)
     if config is None:
@@ -1631,10 +2389,8 @@ def write_opencode_config(
         return {}
     before = json.dumps(config, sort_keys = True)
     config.setdefault("$schema", "https://opencode.ai/config.json")
-    # The session provider is registered under a dedicated id (_OPENCODE_PROVIDER)
-    # that a user's disabled_providers list would never target, so it is always
-    # selectable without this overlay having to reconstruct or override OpenCode's
-    # disabled_providers resolution.
+    # Keep the provider definition in this private session file. The launch path
+    # adjusts effective provider filters in the higher-priority inline overlay.
     model_entry = {"name": model["id"]}
     window = model.get("context_length") or model.get("max_context_length")
     if window:
@@ -1649,15 +2405,36 @@ def write_opencode_config(
         "options": {"baseURL": f"{base}/v1", "apiKey": key},
         "models": {model["id"]: model_entry},
     }
-    # OpenCode selects a model by "<providerID>/<modelID>".
-    config["model"] = f"{_OPENCODE_PROVIDER}/{model['id']}"
-    if window:
+    # Normal mode pins this as the session model. Subagent mode leaves the user's
+    # main/small models alone and exposes the local model to @unsloth and /models.
+    opencode_model = f"{_OPENCODE_PROVIDER}/{model['id']}"
+    if as_subagent:
+        for field in ("model", "small_model"):
+            if str(config.get(field) or "").startswith(f"{_OPENCODE_PROVIDER}/"):
+                config.pop(field, None)
+        managed_compaction = {"auto": True, "reserved": max(1, window // 10)} if window else None
+        if managed_compaction and config.get("compaction") == managed_compaction:
+            config.pop("compaction", None)
+        _subdict(config, "agent")[_SUBAGENT_NAME] = {
+            "description": _SUBAGENT_DESCRIPTION,
+            "mode": "subagent",
+            "model": opencode_model,
+            "prompt": _SUBAGENT_INSTRUCTIONS,
+        }
+    else:
+        config["model"] = opencode_model
+        agents = config.get("agent")
+        if isinstance(agents, dict):
+            agents.pop(_SUBAGENT_NAME, None)
+            if not agents:
+                config.pop("agent", None)
+    if window and not as_subagent:
         # Compact with ~10% headroom (near 90% full). The fixed 20k-token default
         # buffer over-compacts, or never settles, on a small local context.
         compaction = _subdict(config, "compaction")
         compaction["auto"] = True
         compaction["reserved"] = max(1, window // 10)
-    tools = ("edit", "bash", "webfetch")
+    tools = ("edit", "bash", "webfetch", *(("task",) if as_subagent else ()))
     if yolo:
         # Fallback for commands without native --auto and for the append-safe bare
         # --no-launch command (subcommand unknown yet). Rides inline (OPENCODE_CONFIG_CONTENT)
@@ -1786,7 +2563,23 @@ def write_pi_config(base: str, key: str, model: dict, path: Path) -> None:
         typer.echo(f"Updated {path}")
 
 
-@start_app.command("claude", context_settings = _PASSTHROUGH)
+def write_pi_subagent_config(base: str, key: str, model: dict, path: Path) -> None:
+    """Write private bootstrap data for the bundled Pi extension."""
+    window = model.get("context_length") or model.get("max_context_length")
+    window = int(window) if window else 32768
+    _write_private_json(
+        path,
+        {
+            "baseUrl": f"{base}/v1",
+            "apiKey": key,
+            "model": model["id"],
+            "contextWindow": window,
+            "maxTokens": min(window // 4, 8192),
+        },
+    )
+
+
+@start_app.command("claude", cls = _PassthroughCommand, context_settings = _PASSTHROUGH)
 def claude(
     ctx: typer.Context,
     model: Optional[str] = _MODEL_OPTION,
@@ -1796,50 +2589,72 @@ def claude(
     max_seq_length: int = _CONTEXT_OPTION,
     load_in_4bit: bool = _LOAD_4BIT_OPTION,
     tensor_parallel: bool = _TENSOR_PARALLEL_OPTION,
+    enable_tools: bool = _ENABLE_TOOLS_OPTION,
+    tool_call_healing: Optional[bool] = _TOOL_CALL_HEALING_OPTION,
+    tool_call_nudging: Optional[bool] = _TOOL_CALL_NUDGING_OPTION,
     serve: bool = _SERVE_OPTION,
     yolo: bool = _YOLO_OPTION,
     persist: bool = _PERSIST_OPTION,
+    as_subagent: bool = _AS_SUBAGENT_OPTION,
 ):
     """Point Claude Code at the running Unsloth server and start it."""
+    # Route a leading `org/name` positional to --model; forward the rest to the agent.
+    model, ctx.args[:] = _consume_positional_model(model, ctx.args)
     base, key, entry = _connect(
         api_key,
         model,
         LoadOptions(gguf_variant, max_seq_length, load_in_4bit, tensor_parallel),
         serve = serve,
         launch = launch,
+        server_options = ServerOptions(enable_tools, tool_call_healing, tool_call_nudging),
     )
     model_id = entry["id"]
+    install_hint = (
+        "irm https://claude.ai/install.ps1 | iex"
+        if os.name == "nt"
+        else "curl -fsSL https://claude.ai/install.sh | bash"
+    )
+    if as_subagent:
+        subagent_id = _subagent_model_id(base, key, entry, model, gguf_variant)
+        subagent_model = {**entry, "id": subagent_id}
+        window = subagent_model.get("context_length") or subagent_model.get("max_context_length")
+        server_env = {
+            "UNSLOTH_CLAUDE_SUBAGENT_BASE_URL": base,
+            "UNSLOTH_CLAUDE_SUBAGENT_API_KEY": key,
+            "UNSLOTH_CLAUDE_SUBAGENT_MODEL": subagent_id,
+            "UNSLOTH_CLAUDE_SUBAGENT_BYPASS_PERMISSIONS": "1" if yolo else "0",
+        }
+        if window:
+            server_env["UNSLOTH_CLAUDE_SUBAGENT_CONTEXT_WINDOW"] = str(int(window))
+        with _session_config("claude-subagent", launch, persist = persist) as config:
+            plugin = write_claude_subagent_plugin(config, server_env)
+            command = [
+                "claude",
+                "--plugin-dir",
+                _agent_config_path(plugin, ["claude"]),
+                # Before ctx.args: a forwarded `--` would turn later flags positional.
+                "--allowedTools",
+                _CLAUDE_SUBAGENT_TOOL,
+                *_yolo_command_flags("claude", yolo),
+                *ctx.args,
+            ]
+            typer.echo(
+                "Unsloth is available as a local agent. "
+                "Ask Claude to spawn an Unsloth or local agent."
+            )
+            _run(
+                base,
+                subagent_model,
+                {},
+                command,
+                launch = launch,
+                install_hint = install_hint,
+            )
+        return
 
-    env = {
-        "ANTHROPIC_BASE_URL": base,
-        "ANTHROPIC_AUTH_TOKEN": key,
-        "ANTHROPIC_MODEL": model_id,
-        # Session-only (no ~/.claude write): suppress the attribution header so
-        # llama.cpp KV-cache reuse is preserved; --settings below reinforces it.
-        "CLAUDE_CODE_ATTRIBUTION_HEADER": "0",
-        # Update checks, beta features, and other background requests either
-        # stall against a local server or evict the conversation from
-        # llama-server's KV-cache slots, so turn off everything nonessential.
-        "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1",
-        "CLAUDE_CODE_DISABLE_EXPERIMENTAL_BETAS": "1",
-        # A local server streams in bursts; disable the full-screen TUI redraw so the
-        # terminal doesn't flicker between tokens.
-        "CLAUDE_CODE_NO_FLICKER": "1",
-    }
-    # Claude Code auto-compacts against its native (~600k token) window; a local
-    # model's context is usually far smaller, so size the window to the loaded
-    # model's real context length. Otherwise the conversation overflows the
-    # server's window (silent truncation) long before Claude decides to compact.
-    # codex/openclaw get the same value through their config (model_context_window
-    # / contextWindow); Claude has no config file, so it rides on the env var.
-    window = entry.get("context_length") or entry.get("max_context_length")
-    if window:
-        env["CLAUDE_CODE_AUTO_COMPACT_WINDOW"] = str(int(window))
-        # Compact at 90% of that window; the override only takes effect once the
-        # window is set, and it can only lower the threshold, so it just guarantees
-        # headroom before the server's context limit instead of relying on Claude's
-        # default (which is tuned for its native 200K/1M window).
-        env["CLAUDE_AUTOCOMPACT_PCT_OVERRIDE"] = "90"
+    env = _claude_local_env(base, key, entry)
+    # Claude Code auto-compacts against its native context window. The local env
+    # above supplies the loaded model's real window and a 90% threshold instead.
     # --yolo (or its aliases) maps to Claude's own --dangerously-skip-permissions.
     # IS_SANDBOX is left unset on purpose: Claude refuses bypass mode as root unless a
     # sandbox is detected, and we don't want to falsely claim one on the user's host.
@@ -1854,11 +2669,6 @@ def claude(
         *_yolo_command_flags("claude", yolo),
         *ctx.args,
     ]
-    install_hint = (
-        "irm https://claude.ai/install.ps1 | iex"
-        if os.name == "nt"
-        else "curl -fsSL https://claude.ai/install.sh | bash"
-    )
     _run(
         base,
         entry,
@@ -1870,7 +2680,7 @@ def claude(
     )
 
 
-@start_app.command("codex", context_settings = _PASSTHROUGH)
+@start_app.command("codex", cls = _PassthroughCommand, context_settings = _PASSTHROUGH)
 def codex(
     ctx: typer.Context,
     model: Optional[str] = _MODEL_OPTION,
@@ -1880,26 +2690,57 @@ def codex(
     max_seq_length: int = _CONTEXT_OPTION,
     load_in_4bit: bool = _LOAD_4BIT_OPTION,
     tensor_parallel: bool = _TENSOR_PARALLEL_OPTION,
+    enable_tools: bool = _ENABLE_TOOLS_OPTION,
+    tool_call_healing: Optional[bool] = _TOOL_CALL_HEALING_OPTION,
+    tool_call_nudging: Optional[bool] = _TOOL_CALL_NUDGING_OPTION,
     serve: bool = _SERVE_OPTION,
     yolo: bool = _YOLO_OPTION,
     persist: bool = _PERSIST_OPTION,
+    as_subagent: bool = _AS_SUBAGENT_OPTION,
 ):
     """Point OpenAI Codex at the running Unsloth server and start it."""
+    # Route a leading `org/name` positional to --model; forward the rest to the agent.
+    model, ctx.args[:] = _consume_positional_model(model, ctx.args)
     base, key, entry = _connect(
         api_key,
         model,
         LoadOptions(gguf_variant, max_seq_length, load_in_4bit, tensor_parallel),
         serve = serve,
         launch = launch,
+        server_options = ServerOptions(enable_tools, tool_call_healing, tool_call_nudging),
     )
     # This preflight runs after _connect may have auto-started a server but before _run
-    # installs its teardown finally, so tear the server down here if it rejects the model
+    # takes over its lifecycle, so tear the server down here if it rejects the model
     # (e.g. a transformers-backend model) rather than leaving it on the atexit backstop.
     try:
         _require_gguf_for_codex(base, key, entry["id"])
     except BaseException:
         _shutdown_auto_served()
         raise
+    if as_subagent:
+        subagent_id = _subagent_model_id(base, key, entry, model, gguf_variant)
+        subagent_model = {**entry, "id": subagent_id}
+        with _session_config("codex-subagent", launch, persist = persist) as home:
+            agent_config = write_codex_subagent_config(base, key, subagent_model, home)
+            command = [
+                "codex",
+                *_codex_subagent_flags(agent_config),
+                *_yolo_command_flags("codex", yolo),
+                *ctx.args,
+            ]
+            typer.echo(
+                "Unsloth is available as the `unsloth` local agent. "
+                "Ask Codex to spawn an Unsloth or local agent."
+            )
+            _run(
+                base,
+                subagent_model,
+                {},
+                command,
+                launch = launch,
+                install_hint = "npm install -g @openai/codex",
+            )
+        return
     command = [
         "codex",
         "--oss",
@@ -1914,7 +2755,7 @@ def codex(
         _run(base, entry, env, command, launch = launch, install_hint = "npm install -g @openai/codex")
 
 
-@start_app.command("openclaw", context_settings = _PASSTHROUGH)
+@start_app.command("openclaw", cls = _PassthroughCommand, context_settings = _PASSTHROUGH)
 def openclaw(
     ctx: typer.Context,
     model: Optional[str] = _MODEL_OPTION,
@@ -1924,17 +2765,24 @@ def openclaw(
     max_seq_length: int = _CONTEXT_OPTION,
     load_in_4bit: bool = _LOAD_4BIT_OPTION,
     tensor_parallel: bool = _TENSOR_PARALLEL_OPTION,
+    enable_tools: bool = _ENABLE_TOOLS_OPTION,
+    tool_call_healing: Optional[bool] = _TOOL_CALL_HEALING_OPTION,
+    tool_call_nudging: Optional[bool] = _TOOL_CALL_NUDGING_OPTION,
     serve: bool = _SERVE_OPTION,
     yolo: bool = _YOLO_OPTION,
     persist: bool = _PERSIST_OPTION,
 ):
     """Point OpenClaw at the running Unsloth server and start it."""
+    # Route a leading `org/name` positional to --model; forward the rest to the agent.
+    model, ctx.args[:] = _consume_positional_model(model, ctx.args)
+    _reject_as_subagent("openclaw", ctx.args)
     base, key, entry = _connect(
         api_key,
         model,
         LoadOptions(gguf_variant, max_seq_length, load_in_4bit, tensor_parallel),
         serve = serve,
         launch = launch,
+        server_options = ServerOptions(enable_tools, tool_call_healing, tool_call_nudging),
     )
     openclaw_args = list(ctx.args)
     # Default a bare `unsloth start openclaw` to the local TUI. Anything the caller
@@ -1971,7 +2819,7 @@ def openclaw(
         _run(base, entry, env, command, launch = launch, install_hint = install_hint)
 
 
-@start_app.command("opencode", context_settings = _PASSTHROUGH)
+@start_app.command("opencode", cls = _PassthroughCommand, context_settings = _PASSTHROUGH)
 def opencode(
     ctx: typer.Context,
     model: Optional[str] = _MODEL_OPTION,
@@ -1981,18 +2829,69 @@ def opencode(
     max_seq_length: int = _CONTEXT_OPTION,
     load_in_4bit: bool = _LOAD_4BIT_OPTION,
     tensor_parallel: bool = _TENSOR_PARALLEL_OPTION,
+    enable_tools: bool = _ENABLE_TOOLS_OPTION,
+    tool_call_healing: Optional[bool] = _TOOL_CALL_HEALING_OPTION,
+    tool_call_nudging: Optional[bool] = _TOOL_CALL_NUDGING_OPTION,
     serve: bool = _SERVE_OPTION,
     yolo: bool = _YOLO_OPTION,
     persist: bool = _PERSIST_OPTION,
+    as_subagent: bool = _AS_SUBAGENT_OPTION,
 ):
     """Point OpenCode at the running Unsloth server and start it."""
+    # Route a leading `org/name` positional to --model; forward the rest to the agent.
+    model, ctx.args[:] = _consume_positional_model(model, ctx.args)
     base, key, entry = _connect(
         api_key,
         model,
         LoadOptions(gguf_variant, max_seq_length, load_in_4bit, tensor_parallel),
         serve = serve,
         launch = launch,
+        server_options = ServerOptions(enable_tools, tool_call_healing, tool_call_nudging),
     )
+    if as_subagent:
+        subagent_id = _subagent_model_id(base, key, entry, model, gguf_variant)
+        subagent_model = {**entry, "id": subagent_id}
+        # Stay append-safe for a bare no-launch recipe: a later `run <prompt>` would make
+        # `opencode --auto run ...` parse as the TUI, so keep yolo in the inline fallback.
+        route_native_auto = yolo and _opencode_supports_native_auto() and (launch or bool(ctx.args))
+        opencode_args, native_auto = _opencode_native_auto_args(list(ctx.args), route_native_auto)
+        command = ["opencode", *opencode_args]
+        with _session_config("opencode-subagent", launch, persist = persist) as cfg:
+            config_path = cfg / "opencode.json"
+            session_permission = write_opencode_config(
+                base,
+                key,
+                subagent_model,
+                config_path,
+                yolo = yolo and not native_auto,
+                as_subagent = True,
+            )
+            env = {"OPENCODE_CONFIG": str(config_path)}
+            if launch and _which_with_install_dirs("opencode") is None:
+                # Provider-filter inspection needs the binary; offer the install now so
+                # a global/project allowlist is honored on this first launch instead of
+                # being read only after _launch installs OpenCode.
+                _install_agent("opencode", "npm install -g opencode-ai")
+            inline_config = _opencode_subagent_inline_config(config_path, session_permission)
+            # A project opencode.json outranks the session file and could field-merge its
+            # own agent.unsloth over ours. Pin ours in the inline overlay so it wins.
+            inline_config.setdefault("agent", {})[_SUBAGENT_NAME] = {
+                "description": _SUBAGENT_DESCRIPTION,
+                "mode": "subagent",
+                "model": f"{_OPENCODE_PROVIDER}/{subagent_model['id']}",
+                "prompt": _SUBAGENT_INSTRUCTIONS,
+            }
+            env["OPENCODE_CONFIG_CONTENT"] = json.dumps(inline_config)
+            typer.echo("Unsloth is available as @unsloth and in /models.")
+            _run(
+                base,
+                subagent_model,
+                env,
+                command,
+                launch = launch,
+                install_hint = "npm install -g opencode-ai",
+            )
+        return
     opencode_model = f"{_OPENCODE_PROVIDER}/{entry['id']}"
     # The inline OPENCODE_CONFIG_CONTENT below pins the model in the highest-priority
     # layer, so the session model is forced without a --model flag. Only add --model for
@@ -2064,7 +2963,7 @@ def opencode(
         _run(base, entry, env, command, launch = launch, install_hint = "npm install -g opencode-ai")
 
 
-@start_app.command("hermes", context_settings = _PASSTHROUGH)
+@start_app.command("hermes", cls = _PassthroughCommand, context_settings = _PASSTHROUGH)
 def hermes(
     ctx: typer.Context,
     model: Optional[str] = _MODEL_OPTION,
@@ -2074,11 +2973,17 @@ def hermes(
     max_seq_length: int = _CONTEXT_OPTION,
     load_in_4bit: bool = _LOAD_4BIT_OPTION,
     tensor_parallel: bool = _TENSOR_PARALLEL_OPTION,
+    enable_tools: bool = _ENABLE_TOOLS_OPTION,
+    tool_call_healing: Optional[bool] = _TOOL_CALL_HEALING_OPTION,
+    tool_call_nudging: Optional[bool] = _TOOL_CALL_NUDGING_OPTION,
     serve: bool = _SERVE_OPTION,
     yolo: bool = _YOLO_OPTION,
     persist: bool = _PERSIST_OPTION,
 ):
     """Point Hermes (Nous Research) at the running Unsloth server and start it."""
+    # Route a leading `org/name` positional to --model; forward the rest to the agent.
+    model, ctx.args[:] = _consume_positional_model(model, ctx.args)
+    _reject_as_subagent("hermes", ctx.args)
     native_args = [*_yolo_command_flags("hermes", yolo), *ctx.args]
     command = ["hermes", *_hermes_resume_oneshot_args(native_args)]
     base, key, entry = _connect(
@@ -2087,6 +2992,7 @@ def hermes(
         LoadOptions(gguf_variant, max_seq_length, load_in_4bit, tensor_parallel),
         serve = serve,
         launch = launch,
+        server_options = ServerOptions(enable_tools, tool_call_healing, tool_call_nudging),
     )
     install_hint = _hermes_install_hint()
     with _session_config("hermes", launch, persist = persist) as home:
@@ -2097,7 +3003,7 @@ def hermes(
         _run(base, entry, env, command, launch = launch, install_hint = install_hint)
 
 
-@start_app.command("pi", context_settings = _PASSTHROUGH)
+@start_app.command("pi", cls = _PassthroughCommand, context_settings = _PASSTHROUGH)
 def pi(
     ctx: typer.Context,
     model: Optional[str] = _MODEL_OPTION,
@@ -2107,18 +3013,56 @@ def pi(
     max_seq_length: int = _CONTEXT_OPTION,
     load_in_4bit: bool = _LOAD_4BIT_OPTION,
     tensor_parallel: bool = _TENSOR_PARALLEL_OPTION,
+    enable_tools: bool = _ENABLE_TOOLS_OPTION,
+    tool_call_healing: Optional[bool] = _TOOL_CALL_HEALING_OPTION,
+    tool_call_nudging: Optional[bool] = _TOOL_CALL_NUDGING_OPTION,
     serve: bool = _SERVE_OPTION,
     yolo: bool = _YOLO_OPTION,
     persist: bool = _PERSIST_OPTION,
+    as_subagent: bool = _AS_SUBAGENT_OPTION,
 ):
     """Point Pi (coding agent) at the running Unsloth server and start it."""
+    # Route a leading `org/name` positional to --model; forward the rest to the agent.
+    model, ctx.args[:] = _consume_positional_model(model, ctx.args)
     base, key, entry = _connect(
         api_key,
         model,
         LoadOptions(gguf_variant, max_seq_length, load_in_4bit, tensor_parallel),
         serve = serve,
         launch = launch,
+        server_options = ServerOptions(enable_tools, tool_call_healing, tool_call_nudging),
     )
+    install_hint = "npm install -g --ignore-scripts @earendil-works/pi-coding-agent"
+    if as_subagent:
+        if not _PI_SUBAGENT_EXTENSION.is_file():
+            _fail(f"Missing Pi subagent extension: {_PI_SUBAGENT_EXTENSION}")
+        subagent_id = _subagent_model_id(base, key, entry, model, gguf_variant)
+        subagent_model = {**entry, "id": subagent_id}
+        extension = _agent_config_path(_PI_SUBAGENT_EXTENSION, ["pi"])
+        with _session_config("pi-subagent", launch, persist = persist) as config:
+            config_path = config / "subagent.json"
+            write_pi_subagent_config(base, key, subagent_model, config_path)
+            command = [
+                "pi",
+                "--extension",
+                extension,
+                *_yolo_command_flags("pi", yolo),
+                *ctx.args,
+            ]
+            typer.echo(
+                "Unsloth is available as a local agent and in /model. "
+                "Ask Pi to spawn an Unsloth or local agent."
+            )
+            _run(
+                base,
+                subagent_model,
+                {"UNSLOTH_PI_SUBAGENT_CONFIG": str(config_path)},
+                command,
+                launch = launch,
+                install_hint = install_hint,
+                clear_screen = True,
+            )
+        return
     # Pi defaults to the google provider, so pin our provider/model on the command
     # line; the custom OpenAI-compatible endpoint itself is only configurable via
     # ~/.pi/agent/models.json.
@@ -2133,7 +3077,6 @@ def pi(
     ]
     # --ignore-scripts matches Pi's documented install recipe (its README notes Pi needs
     # no install scripts), so accepting the prompt skips dependency lifecycle scripts.
-    install_hint = "npm install -g --ignore-scripts @earendil-works/pi-coding-agent"
     with _session_config("pi", launch, persist = persist) as home:
         # Pi resolves its config dir from PI_CODING_AGENT_DIR first (getAgentDir() prefers
         # it over $HOME/.pi/agent), so pin it at the session dir: an inherited
diff --git a/unsloth_cli/commands/studio.py b/unsloth_cli/commands/studio.py
index f2f41fc583..9a472d2996 100644
--- a/unsloth_cli/commands/studio.py
+++ b/unsloth_cli/commands/studio.py
@@ -106,6 +106,13 @@ API_KEY_PBKDF2_SALT_KEY = "api_key_pbkdf2_salt"
 DESKTOP_SECRET_HASH_KEY = "desktop_secret_hash"
 DESKTOP_SECRET_CREATED_AT_KEY = "desktop_secret_created_at"
 PBKDF2_ITERATIONS = 100_000
+_START_API_KEY_MARKER_ENV = "_UNSLOTH_START_API_KEY_MARKER"
+
+
+def _consume_start_api_key_marker_env() -> bool:
+    """Consume the one-shot readiness marker passed across a Studio re-exec."""
+    return os.environ.pop(_START_API_KEY_MARKER_ENV, None) == "1"
+
 
 # __file__ is unsloth_cli/commands/studio.py -- two parents up is the package root
 # (either site-packages or the repo root for editable installs).
@@ -1650,6 +1657,13 @@ def _consume_legacy_short_aliases(
     return value, out
 
 
+# Help panels so `unsloth run --help` groups options instead of one long list.
+_RUN_PANEL_MODEL = "Model"
+_RUN_PANEL_SERVER = "Server & network"
+_RUN_PANEL_TOOLS = "Tool calls"
+_RUN_PANEL_ADVANCED = "Advanced"
+
+
 @studio_app.command(
     context_settings = {
         "allow_extra_args": True,
@@ -1666,6 +1680,7 @@ def run(
         # `-m` / `-hfr` removed (Click would cluster `-mg`/`-md`/...).
         # Exact-match `-m`/`-hfr` still work via the legacy shim below.
         # `-hf` stays (multi-char shorts don't cluster).
+        rich_help_panel = _RUN_PANEL_MODEL,
         help = (
             "Model path or HF repo. Accepts llama.cpp-style "
             "`org/repo:variant` syntax. `-hf` / `--hf-repo` match "
@@ -1673,12 +1688,16 @@ def run(
         ),
     ),
     gguf_variant: Optional[str] = typer.Option(
-        None, "--gguf-variant", help = "GGUF quant variant (e.g. UD-Q4_K_XL)"
+        None,
+        "--gguf-variant",
+        rich_help_panel = _RUN_PANEL_MODEL,
+        help = "GGUF quant variant (e.g. UD-Q4_K_XL)",
     ),
     verbose: bool = typer.Option(
         False,
         "--verbose",
         "-v",
+        rich_help_panel = _RUN_PANEL_ADVANCED,
         help = "Log every API request, including the high-frequency polling that is "
         "deduplicated by default.",
     ),
@@ -1686,35 +1705,64 @@ def run(
         0,
         "--max-seq-length",
         "--context-length",
+        rich_help_panel = _RUN_PANEL_MODEL,
         help = "Runtime context length in tokens (0 = model default for GGUF; 2048 for hub models)",
     ),
-    load_in_4bit: bool = typer.Option(True, "--load-in-4bit/--no-load-in-4bit"),
-    api_key_name: str = typer.Option(
-        "cli", "--api-key-name", help = "Label for the auto-generated API key"
+    load_in_4bit: bool = typer.Option(
+        True, "--load-in-4bit/--no-load-in-4bit", rich_help_panel = _RUN_PANEL_MODEL
     ),
-    port: int = typer.Option(8888, "--port", "-p"),
-    host: str = typer.Option("127.0.0.1", "--host", "-H"),
+    api_key_name: str = typer.Option(
+        "cli",
+        "--api-key-name",
+        rich_help_panel = _RUN_PANEL_ADVANCED,
+        help = "Label for the auto-generated API key",
+    ),
+    port: int = typer.Option(8888, "--port", "-p", rich_help_panel = _RUN_PANEL_SERVER),
+    host: str = typer.Option("127.0.0.1", "--host", "-H", rich_help_panel = _RUN_PANEL_SERVER),
     # `-f` removed (clustered `-fa`/`-fit*`); studio_default keeps it.
-    frontend: Optional[Path] = typer.Option(None, "--frontend"),
+    frontend: Optional[Path] = typer.Option(None, "--frontend", rich_help_panel = _RUN_PANEL_SERVER),
     api_only: bool = typer.Option(
         False,
         "--api-only",
+        rich_help_panel = _RUN_PANEL_SERVER,
         help = "Serve only the API (no web UI), for a headless model server. "
         "Pairs with --secure to expose the API over the Cloudflare link alone.",
     ),
-    silent: bool = typer.Option(False, "--silent", "-q"),
+    silent: bool = typer.Option(False, "--silent", "-q", rich_help_panel = _RUN_PANEL_ADVANCED),
     enable_tools: Optional[bool] = typer.Option(
         None,
         "--enable-tools/--disable-tools",
+        rich_help_panel = _RUN_PANEL_TOOLS,
         help = (
             "Force server-side tools (web search, code execution) on or off for "
             "every request. Default: on for every bind."
         ),
     ),
+    tool_call_healing: Optional[bool] = typer.Option(
+        None,
+        "--enable-tool-call-healing/--disable-tool-call-healing",
+        rich_help_panel = _RUN_PANEL_TOOLS,
+        help = (
+            "Promote text-form tool calls (small GGUFs often emit <tool_call>...) "
+            "back into structured calls on the client-tool passthrough. Default: on. "
+            "An explicit --disable-tool-call-healing is an absolute server kill-switch."
+        ),
+    ),
+    tool_call_nudging: Optional[bool] = typer.Option(
+        None,
+        "--enable-tool-call-nudging/--disable-tool-call-nudging",
+        rich_help_panel = _RUN_PANEL_TOOLS,
+        help = (
+            "On the non-streaming client-tool passthrough, retry once with a short "
+            "nudge when the model emitted a tool signal that healing could not repair. "
+            "Default: on. No effect on streaming requests or the server-side agentic loop."
+        ),
+    ),
     yes: bool = typer.Option(
         False,
         "--yes",
         "-y",
+        rich_help_panel = _RUN_PANEL_ADVANCED,
         help = "Accepted for backward compatibility; the tool policy no longer prompts.",
     ),
     parallel: int = typer.Option(
@@ -1724,6 +1772,7 @@ def run(
         "-np",
         min = _PARALLEL_MIN,
         max = _PARALLEL_MAX,
+        rich_help_panel = _RUN_PANEL_SERVER,
         help = (
             "llama-server parallel decode slots. N requests share one "
             "loaded model; each slot gets ctx/N KV cache. Default "
@@ -1733,6 +1782,7 @@ def run(
     cloudflare: Optional[bool] = typer.Option(
         None,
         "--cloudflare/--no-cloudflare",
+        rich_help_panel = _RUN_PANEL_SERVER,
         help = "Expose Unsloth on a PUBLIC internet URL via a free Cloudflare HTTPS "
         "tunnel, for non-api-only wildcard binds (0.0.0.0 or ::). Off by default; "
         "pass --cloudflare to enable it (--secure implies it). --no-cloudflare forces "
@@ -1741,6 +1791,7 @@ def run(
     secure: bool = typer.Option(
         False,
         "--secure/--no-secure",
+        rich_help_panel = _RUN_PANEL_SERVER,
         help = "Expose ONLY a Cloudflare HTTPS link: bind localhost and fail closed "
         "if the tunnel can't start. Without it, --no-secure also serves the raw "
         "0.0.0.0 port, which is reachable from anywhere on the network.",
@@ -1754,15 +1805,23 @@ def run(
     tensor_parallel: bool = typer.Option(
         False,
         "--tensor-parallel/--no-tensor-parallel",
+        rich_help_panel = _RUN_PANEL_MODEL,
         help = (
             "Split a GGUF across GPUs by tensor (--split-mode tensor) instead of "
             "by layer. Multi-GPU only (no effect on one GPU); dense models gain "
             "decode speed, MoE usually don't."
         ),
     ),
+    start_api_key_marker: bool = typer.Option(
+        False,
+        "--start-api-key-marker",
+        hidden = True,
+        help = "Emit an early API key marker for the unsloth start parent process.",
+    ),
     password: str = typer.Option(
         "",
         "--password",
+        rich_help_panel = _RUN_PANEL_ADVANCED,
         help = "Set the INITIAL admin password non-interactively (headless setups), "
         "only when none is set yet. Also reads the UNSLOTH_STUDIO_PASSWORD env var, or "
         "`--password -` to read one line from stdin. A literal value is visible in the "
@@ -1786,10 +1845,31 @@ def run(
         unsloth studio run --model some-model --chat-template-file /path/to/tpl.jinja
         unsloth studio run --model unsloth/Qwen3-27B-GGUF --gguf-variant Q8_0 --tensor-parallel
     """
+    # A newer outer CLI can re-exec into an older Studio venv; pass this signal via
+    # env so an older child ignores it instead of treating it as a llama-server arg.
+    inherited_start_api_key_marker = _consume_start_api_key_marker_env()
+    start_api_key_marker = start_api_key_marker or inherited_start_api_key_marker
+
     # Back-compat: --not-secure is a deprecated alias for --no-secure.
     secure = _resolve_secure(secure, not_secure)
     extra_llama_args: List[str] = list(ctx.args) if ctx.args else []
 
+    # Tool-call healing/nudging are read from the env at backend import. Resolve here
+    # (before any re-exec/import) so the in-venv child inherits the decision. When the
+    # flag is omitted, respect a value the parent already set (e.g. `unsloth start`
+    # forwards its choice via the env) and otherwise apply the default: healing on,
+    # nudging on for a CLI-launched server.
+    _healing_disabled = (
+        os.environ.get("UNSLOTH_DISABLE_TOOL_CALL_HEALING") == "1"
+        if tool_call_healing is None
+        else not tool_call_healing
+    )
+    os.environ["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] = "1" if _healing_disabled else "0"
+    if tool_call_nudging is not None:
+        os.environ["UNSLOTH_TOOL_CALL_NUDGE"] = "1" if tool_call_nudging else "0"
+    elif "UNSLOTH_TOOL_CALL_NUDGE" not in os.environ:
+        os.environ["UNSLOTH_TOOL_CALL_NUDGE"] = "1"
+
     # Set before any re-exec so the in-venv server inherits it via the env.
     # `run --verbose` used to pass through to llama-server (its own -v); keep
     # that by forwarding --log-verbose so we add Unsloth logs without dropping it.
@@ -1991,15 +2071,21 @@ def run(
         if extra_llama_args:
             args.extend(extra_llama_args)
 
-        if sys.platform == "win32":
-            proc = subprocess.Popen(args)
-            try:
-                rc = proc.wait()
-            except KeyboardInterrupt:
-                rc = proc.wait()
-            raise typer.Exit(rc)
-        else:
-            os.execvp(str(studio_bin), args)
+        if start_api_key_marker:
+            os.environ[_START_API_KEY_MARKER_ENV] = "1"
+        try:
+            if sys.platform == "win32":
+                proc = subprocess.Popen(args)
+                try:
+                    rc = proc.wait()
+                except KeyboardInterrupt:
+                    rc = proc.wait()
+                raise typer.Exit(rc)
+            else:
+                os.execvp(str(studio_bin), args)
+        finally:
+            # execvp doesn't return on success; restore env after a Windows wait or a failed launch.
+            os.environ.pop(_START_API_KEY_MARKER_ENV, None)
 
     # ── 2. Start server (always suppress built-in banner) ─────────────
     run_mod = _load_run_module()
@@ -2045,6 +2131,10 @@ def run(
 
         # 4. Create API key in-process.
         api_key = _create_api_key_inprocess(api_key_name)
+        if start_api_key_marker:
+            # `unsloth start` reads this key from a private 0600 log to authenticate
+            # download-progress polling; the normal `unsloth run` output is unchanged.
+            typer.echo(f"UNSLOTH_START_API_KEY: {api_key}")
 
         # 5. Load model via HTTP.
         if not silent:
@@ -2236,7 +2326,8 @@ def stop():
     # Send SIGTERM (graceful shutdown) or TerminateProcess on Windows
     try:
         if sys.platform == "win32":
-            subprocess.run(["taskkill", "/PID", str(pid), "/F"], check = True)
+            # /T also stops llama-server children, which otherwise keep GPU and port.
+            subprocess.run(["taskkill", "/PID", str(pid), "/T", "/F"], check = True)
         else:
             os.kill(pid, _signal.SIGTERM)
         typer.echo(f"Sent shutdown signal to Unsloth server (PID {pid}).")
diff --git a/unsloth_cli/pi_subagent.ts b/unsloth_cli/pi_subagent.ts
new file mode 100644
index 0000000000..d712fc89ae
--- /dev/null
+++ b/unsloth_cli/pi_subagent.ts
@@ -0,0 +1,241 @@
+import { spawn, type ChildProcess } from "node:child_process";
+import * as fs from "node:fs";
+import * as path from "node:path";
+import { fileURLToPath } from "node:url";
+import type { ExtensionAPI } from "@earendil-works/pi-coding-agent";
+import { Type } from "typebox";
+
+const provider = "unsloth";
+const maxResultCharacters = 100_000;
+const cancelGraceMilliseconds = 2_000;
+const configPath = process.env.UNSLOTH_PI_SUBAGENT_CONFIG || "";
+delete process.env.UNSLOTH_PI_SUBAGENT_CONFIG;
+let config: Record<string, unknown> = {};
+if (configPath) {
+	try {
+		const parsed = JSON.parse(fs.readFileSync(configPath, "utf8"));
+		if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) {
+			throw new Error("expected a JSON object");
+		}
+		config = parsed;
+	} catch (error) {
+		throw new Error(`Could not read Unsloth subagent configuration: ${error}`);
+	}
+}
+const model = typeof config.model === "string" ? config.model : "";
+const baseUrl = typeof config.baseUrl === "string" ? config.baseUrl : "";
+const apiKey = typeof config.apiKey === "string" ? config.apiKey : "";
+const contextWindow = positiveInt(config.contextWindow, 32768);
+const maxTokens = positiveInt(config.maxTokens, Math.min(Math.floor(contextWindow / 4), 8192));
+
+function positiveInt(value: unknown, fallback: number): number {
+	const parsed = Number.parseInt(typeof value === "string" ? value : String(value || ""), 10);
+	return Number.isFinite(parsed) && parsed > 0 ? parsed : fallback;
+}
+
+function finalText(message: any): string {
+	if (message?.role !== "assistant" || !Array.isArray(message.content)) return "";
+	return message.content
+		.filter((part: any) => part?.type === "text" && typeof part.text === "string")
+		.map((part: any) => part.text)
+		.join("\n")
+		.trim();
+}
+
+function boundedResult(text: string): string {
+	if (text.length <= maxResultCharacters) return text;
+	return `${text.slice(0, maxResultCharacters)}\n\n[Local agent output truncated]`;
+}
+
+function piInvocation(args: string[]): { command: string; args: string[] } {
+	const currentScript = process.argv[1];
+	const bunVirtualScript = currentScript?.startsWith("/$bunfs/root/");
+	if (currentScript && !bunVirtualScript && fs.existsSync(currentScript)) {
+		return { command: process.execPath, args: [currentScript, ...args] };
+	}
+	const executable = path.basename(process.execPath).toLowerCase();
+	if (!/^(node|bun)(\.exe)?$/.test(executable)) return { command: process.execPath, args };
+	return { command: "pi", args };
+}
+
+function signalProcessGroup(child: ChildProcess, signal: NodeJS.Signals): void {
+	if (!child.pid) return;
+	try {
+		process.kill(-child.pid, signal);
+	} catch {
+		try {
+			child.kill(signal);
+		} catch {
+			// The process tree already exited.
+		}
+	}
+}
+
+async function stopChildTree(child: ChildProcess): Promise<void> {
+	if (!child.pid) return;
+	if (process.platform === "win32") {
+		await new Promise<void>((resolve) => {
+			const killer = spawn("taskkill", ["/PID", String(child.pid), "/T", "/F"], {
+				shell: false,
+				stdio: "ignore",
+				windowsHide: true,
+			});
+			killer.once("error", () => {
+				try {
+					child.kill("SIGKILL");
+				} catch {
+					// The child already exited.
+				}
+				resolve();
+			});
+			killer.once("close", (code) => {
+				if (code !== 0) {
+					try {
+						child.kill("SIGKILL");
+					} catch {
+						// The child already exited.
+					}
+				}
+				resolve();
+			});
+		});
+		return;
+	}
+
+	signalProcessGroup(child, "SIGTERM");
+	await new Promise((resolve) => setTimeout(resolve, cancelGraceMilliseconds));
+	signalProcessGroup(child, "SIGKILL");
+}
+
+export default function unslothSubagent(pi: ExtensionAPI): void {
+	if (!model || !baseUrl || !apiKey || !configPath) {
+		throw new Error("Unsloth subagent configuration is incomplete.");
+	}
+
+	pi.registerProvider(provider, {
+		name: "Unsloth Studio",
+		baseUrl,
+		apiKey,
+		api: "openai-completions",
+		authHeader: true,
+		models: [
+			{
+				id: model,
+				name: `${model} via Unsloth`,
+				reasoning: false,
+				input: ["text"],
+				cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+				contextWindow,
+				maxTokens,
+			},
+		],
+	});
+
+	if (process.env.UNSLOTH_PI_SUBAGENT_CHILD === "1") return;
+
+	pi.registerTool({
+		name: "unsloth_agent",
+		label: "Unsloth agent",
+		description:
+			"Local coding subagent powered by Unsloth for debugging, implementation, and codebase research. Use when the user asks to spawn an Unsloth or local agent.",
+		parameters: Type.Object({
+			task: Type.String({ description: "The complete task for the local Unsloth agent." }),
+		}),
+		async execute(_toolCallId, params, signal, _onUpdate, ctx) {
+			const extension = fileURLToPath(import.meta.url);
+			const args = [
+				"--mode",
+				"json",
+				"--print",
+				"--no-session",
+				"--provider",
+				provider,
+				"--model",
+				model,
+				"--no-extensions",
+				"--extension",
+				extension,
+				`Task: ${params.task}`,
+			];
+			const invocation = piInvocation(args);
+			let output = "";
+			let stderr = "";
+			let lastResponse = "";
+			let childError = "";
+			let aborted = false;
+			const processLine = (line: string) => {
+				try {
+					const event = JSON.parse(line);
+					if (event.type !== "message_end") return;
+					const message = event.message;
+					// Pi reports model/API failures as message_end events while still
+					// exiting 0, so the exit status alone cannot surface them.
+					if (message?.stopReason === "error" || message?.stopReason === "aborted") {
+						childError =
+							(typeof message.errorMessage === "string" && message.errorMessage) ||
+							`The local Unsloth agent stopped: ${message.stopReason}.`;
+						return;
+					}
+					const response = finalText(message);
+					if (response) {
+						lastResponse = boundedResult(response);
+						childError = "";
+					}
+				} catch {
+					// Ignore non-JSON diagnostic lines. The exit status still reports failures.
+				}
+			};
+
+			const exitCode = await new Promise<number>((resolve, reject) => {
+				const child = spawn(invocation.command, invocation.args, {
+					cwd: ctx.cwd,
+					detached: process.platform !== "win32",
+					shell: false,
+					stdio: ["ignore", "pipe", "pipe"],
+					env: {
+						...process.env,
+						UNSLOTH_PI_SUBAGENT_CHILD: "1",
+						UNSLOTH_PI_SUBAGENT_CONFIG: configPath,
+					},
+				});
+				let cleanup: Promise<void> | undefined;
+				const cancel = () => {
+					if (aborted) return;
+					aborted = true;
+					cleanup = stopChildTree(child);
+				};
+				child.on("error", (error) => {
+					signal?.removeEventListener("abort", cancel);
+					reject(error);
+				});
+				child.stdout.on("data", (chunk) => {
+					output += chunk.toString();
+					const lines = output.split("\n");
+					output = lines.pop() || "";
+					for (const line of lines) processLine(line);
+				});
+				child.stderr.on("data", (chunk) => {
+					stderr = (stderr + chunk.toString()).slice(-100_000);
+				});
+				child.on("close", async (code) => {
+					signal?.removeEventListener("abort", cancel);
+					await cleanup;
+					if (output.trim()) processLine(output);
+					resolve(code ?? 1);
+				});
+				signal?.addEventListener("abort", cancel, { once: true });
+				if (signal?.aborted) cancel();
+			});
+
+			if (aborted) throw new Error("The local Unsloth agent was cancelled.");
+			if (exitCode !== 0) {
+				throw new Error(stderr.trim() || `The local Unsloth agent exited with code ${exitCode}.`);
+			}
+			if (childError) throw new Error(boundedResult(childError));
+			return {
+				content: [{ type: "text", text: lastResponse || "The local agent returned no text." }],
+				details: { provider, model },
+			};
+		},
+	});
+}
diff --git a/unsloth_cli/tests/test_claude_subagent_mcp.py b/unsloth_cli/tests/test_claude_subagent_mcp.py
new file mode 100644
index 0000000000..13a9bd6255
--- /dev/null
+++ b/unsloth_cli/tests/test_claude_subagent_mcp.py
@@ -0,0 +1,338 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from __future__ import annotations
+
+import io
+import json
+import os
+import subprocess
+import sys
+import time
+
+import pytest
+
+import unsloth_cli.claude_subagent_mcp as bridge
+
+
+def test_protocol_lists_and_calls_local_agent():
+    initialized = bridge._response(
+        {"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {}},
+    )
+    assert initialized["result"]["serverInfo"]["name"] == "unsloth-local-agent"
+
+    listed = bridge._response({"jsonrpc": "2.0", "id": 2, "method": "tools/list"})
+    tool = listed["result"]["tools"][0]
+    assert tool["name"] == "unsloth_agent"
+    assert "spawn an Unsloth or local agent" in tool["description"]
+    assert tool["inputSchema"]["required"] == ["task"]
+    assert tool["_meta"]["anthropic/maxResultSizeChars"] == 100_000
+
+    called = bridge._response(
+        {
+            "jsonrpc": "2.0",
+            "id": 3,
+            "method": "tools/call",
+            "params": {"name": "unsloth_agent", "arguments": {"task": " inspect this "}},
+        },
+        run_agent = lambda task: f"completed: {task}",
+    )
+    assert called["result"] == {
+        "content": [{"type": "text", "text": "completed: inspect this"}],
+        "isError": False,
+    }
+
+
+def test_protocol_returns_tool_errors_to_parent():
+    response = bridge._response(
+        {
+            "jsonrpc": "2.0",
+            "id": 1,
+            "method": "tools/call",
+            "params": {"name": "unsloth_agent", "arguments": {"task": "test"}},
+        },
+        run_agent = lambda task: (_ for _ in ()).throw(RuntimeError("local failure")),
+    )
+    assert response["result"]["isError"] is True
+    assert response["result"]["content"][0]["text"] == "local failure"
+
+
+def test_stdio_server_ignores_notifications_and_answers_requests():
+    requests = "\n".join(
+        [
+            json.dumps({"jsonrpc": "2.0", "method": "notifications/initialized"}),
+            json.dumps({"jsonrpc": "2.0", "id": 4, "method": "ping"}),
+        ]
+    )
+    output = io.StringIO()
+    bridge.serve(io.StringIO(requests), output)
+    assert json.loads(output.getvalue()) == {"jsonrpc": "2.0", "id": 4, "result": {}}
+
+
+def test_stdio_cancellation_reaches_the_running_local_agent():
+    requests = "\n".join(
+        [
+            json.dumps(
+                {
+                    "jsonrpc": "2.0",
+                    "id": "call-1",
+                    "method": "tools/call",
+                    "params": {"name": "unsloth_agent", "arguments": {"task": "wait"}},
+                }
+            ),
+            json.dumps(
+                {
+                    "jsonrpc": "2.0",
+                    "method": "notifications/cancelled",
+                    "params": {"requestId": "call-1", "reason": "user cancelled"},
+                }
+            ),
+        ]
+    )
+    output = io.StringIO()
+    cancelled = []
+
+    def run_agent(task, cancel_event):
+        assert task == "wait"
+        assert cancel_event.wait(timeout = 1)
+        cancelled.append(task)
+        raise RuntimeError("The local Claude agent was cancelled.")
+
+    bridge.serve(io.StringIO(requests), output, run_agent = run_agent)
+    assert cancelled == ["wait"]
+    assert output.getvalue() == ""
+
+
+def test_stdio_sigint_stops_the_running_local_agent(monkeypatch):
+    request = json.dumps(
+        {
+            "jsonrpc": "2.0",
+            "id": "call-1",
+            "method": "tools/call",
+            "params": {"name": "unsloth_agent", "arguments": {"task": "wait"}},
+        }
+    )
+    handlers = {}
+    started = bridge.threading.Event()
+    cancelled = []
+
+    def set_handler(signum, handler):
+        previous = handlers.get(signum, bridge.signal.SIG_DFL)
+        handlers[signum] = handler
+        return previous
+
+    monkeypatch.setattr(bridge.signal, "signal", set_handler)
+
+    class InterruptingInput:
+        def __init__(self):
+            self.sent = False
+
+        def __iter__(self):
+            return self
+
+        def __next__(self):
+            if not self.sent:
+                self.sent = True
+                return request + "\n"
+            assert started.wait(timeout = 1)
+            handlers[bridge.signal.SIGINT](bridge.signal.SIGINT, None)
+            raise AssertionError("SIGINT handler must unwind the stdin loop")
+
+    def run_agent(task, cancel_event):
+        assert task == "wait"
+        started.set()
+        assert cancel_event.wait(timeout = 1)
+        # Real Claude Code sends SIGINT twice. The second one must not abort cleanup.
+        handlers[bridge.signal.SIGINT](bridge.signal.SIGINT, None)
+        cancelled.append(task)
+        raise RuntimeError("The local Claude agent was cancelled.")
+
+    output = io.StringIO()
+    bridge.serve(InterruptingInput(), output, run_agent = run_agent)
+    assert cancelled == ["wait"]
+    assert output.getvalue() == ""
+
+
+@pytest.mark.parametrize(
+    ("bypass", "permission"),
+    [("0", "acceptEdits"), ("1", "bypassPermissions")],
+)
+def test_local_child_uses_unsloth_without_overwriting_parent_auth(
+    monkeypatch, tmp_path, bypass, permission
+):
+    captured = {}
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_BASE_URL", "http://127.0.0.1:8888")
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_API_KEY", "sk-unsloth-test")
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_MODEL", "unsloth/model-GGUF:Q4_K_M")
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_CONTEXT_WINDOW", "32768")
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_BYPASS_PERMISSIONS", bypass)
+    monkeypatch.setenv("ANTHROPIC_API_KEY", "cloud-key")
+    monkeypatch.setenv("CLAUDE_CODE_OAUTH_TOKEN", "cloud-oauth")
+    monkeypatch.setenv("CLAUDE_PROJECT_DIR", str(tmp_path))
+    monkeypatch.setattr(bridge.shutil, "which", lambda _: "/usr/local/bin/claude")
+    monkeypatch.setattr(bridge, "_claude_flags", lambda model: ["--settings", "{}"])
+
+    class Process:
+        pid = 1234
+        returncode = 0
+
+        def communicate(self, timeout):
+            captured["timeout"] = timeout
+            return json.dumps({"is_error": False, "result": "LOCAL_OK"}), ""
+
+        def poll(self):
+            return self.returncode
+
+    def popen(command, **kwargs):
+        captured["command"] = command
+        captured.update(kwargs)
+        return Process()
+
+    monkeypatch.setattr(bridge.subprocess, "Popen", popen)
+    assert bridge.run_local_agent("reply exactly LOCAL_OK") == "LOCAL_OK"
+    command = captured["command"]
+    assert command[:3] == ["/usr/local/bin/claude", "--model", "unsloth/model-GGUF:Q4_K_M"]
+    assert command[command.index("--permission-mode") + 1] == permission
+    assert "--no-session-persistence" in command
+    assert captured["cwd"] == str(tmp_path)
+    assert captured["stdin"] is bridge.subprocess.DEVNULL
+    assert captured["stdout"] is bridge.subprocess.PIPE
+    assert captured["stderr"] is bridge.subprocess.PIPE
+    if os.name == "nt":
+        assert captured["creationflags"] == bridge.subprocess.CREATE_NEW_PROCESS_GROUP
+    else:
+        assert captured["start_new_session"] is True
+    child_env = captured["env"]
+    assert child_env["ANTHROPIC_BASE_URL"] == "http://127.0.0.1:8888"
+    assert child_env["ANTHROPIC_AUTH_TOKEN"] == "sk-unsloth-test"
+    assert child_env["ANTHROPIC_MODEL"] == "unsloth/model-GGUF:Q4_K_M"
+    assert child_env["CLAUDE_CODE_AUTO_COMPACT_WINDOW"] == "32768"
+    assert child_env["CLAUDE_AUTOCOMPACT_PCT_OVERRIDE"] == "90"
+    assert "ANTHROPIC_API_KEY" not in child_env
+    assert "CLAUDE_CODE_OAUTH_TOKEN" not in child_env
+
+
+def test_local_child_process_is_stopped_on_cancellation(monkeypatch, tmp_path):
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_BASE_URL", "http://127.0.0.1:8888")
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_API_KEY", "sk-unsloth-test")
+    monkeypatch.setenv("UNSLOTH_CLAUDE_SUBAGENT_MODEL", "unsloth/model-GGUF:Q4_K_M")
+    monkeypatch.setenv("CLAUDE_PROJECT_DIR", str(tmp_path))
+    monkeypatch.setattr(bridge.shutil, "which", lambda _: "/usr/local/bin/claude")
+    monkeypatch.setattr(bridge, "_claude_flags", lambda model: [])
+    cancel_event = bridge.threading.Event()
+    stopped = []
+
+    class Process:
+        pid = 1234
+        returncode = None
+
+        def communicate(self, timeout):
+            cancel_event.set()
+            raise bridge.subprocess.TimeoutExpired("claude", timeout)
+
+        def poll(self):
+            return self.returncode
+
+    process = Process()
+    monkeypatch.setattr(bridge.subprocess, "Popen", lambda *args, **kwargs: process)
+
+    def stop(child):
+        stopped.append(child)
+        child.returncode = -15
+
+    monkeypatch.setattr(bridge, "_stop_child", stop)
+    with pytest.raises(RuntimeError, match = "cancelled"):
+        bridge.run_local_agent("wait", cancel_event)
+    assert stopped == [process]
+
+
+def test_windows_cancellation_stops_the_child_process_tree(monkeypatch):
+    monkeypatch.setattr(bridge.os, "name", "nt")
+    captured = {}
+
+    class Process:
+        pid = 4321
+        returncode = None
+
+        def poll(self):
+            return self.returncode
+
+        def wait(self, timeout = None):
+            captured["wait_timeout"] = timeout
+            self.returncode = 1
+
+        def terminate(self):
+            raise AssertionError("taskkill should handle the process tree")
+
+    def run(command, **kwargs):
+        captured["command"] = command
+        captured.update(kwargs)
+        return bridge.subprocess.CompletedProcess(command, 0)
+
+    monkeypatch.setattr(bridge.subprocess, "run", run)
+    bridge._stop_child(Process())
+
+    assert captured["command"] == ["taskkill", "/PID", "4321", "/T", "/F"]
+    assert captured["capture_output"] is True
+    assert captured["check"] is False
+    assert captured["wait_timeout"] == bridge._CANCEL_GRACE_SECONDS
+
+
+def test_windows_failed_taskkill_still_terminates_the_child(monkeypatch):
+    monkeypatch.setattr(bridge.os, "name", "nt")
+    captured = {}
+
+    class Process:
+        pid = 4321
+        returncode = None
+
+        def poll(self):
+            return self.returncode
+
+        def wait(self, timeout = None):
+            self.returncode = 1
+
+        def terminate(self):
+            captured["terminated"] = True
+            self.returncode = 1
+
+    monkeypatch.setattr(
+        bridge.subprocess,
+        "run",
+        lambda command, **kwargs: bridge.subprocess.CompletedProcess(command, 1),
+    )
+    bridge._stop_child(Process())
+
+    assert captured.get("terminated") is True
+
+
+@pytest.mark.skipif(os.name == "nt", reason = "POSIX process groups")
+def test_stop_child_kills_survivors_after_leader_exit(monkeypatch, tmp_path):
+    monkeypatch.setattr(bridge, "_CANCEL_GRACE_SECONDS", 0.2)
+    marker = tmp_path / "grandchild-survived"
+    grandchild = (
+        "import pathlib, sys, time; time.sleep(1.0); "
+        "pathlib.Path(sys.argv[1]).write_text('alive')"
+    )
+    process = subprocess.Popen(
+        [
+            sys.executable,
+            "-c",
+            "import subprocess, sys; "
+            "subprocess.Popen([sys.executable, '-c', sys.argv[1], sys.argv[2]])",
+            grandchild,
+            str(marker),
+        ],
+        start_new_session = True,
+    )
+    process.wait()
+
+    bridge._stop_child(process)
+
+    time.sleep(1.2)
+    assert not marker.exists()
+
+
+def test_result_parser_accepts_diagnostics_before_json():
+    output = "connector warning\n" + json.dumps({"is_error": False, "result": "OK"})
+    assert bridge._result_text(output) == "OK"
diff --git a/unsloth_cli/tests/test_inference_chat.py b/unsloth_cli/tests/test_inference_chat.py
index ae6f8dcfd4..07eed01e97 100644
--- a/unsloth_cli/tests/test_inference_chat.py
+++ b/unsloth_cli/tests/test_inference_chat.py
@@ -873,6 +873,104 @@ def test_chat_compare_on_mlx_loads_base_model_side_by_side(monkeypatch):
     assert set(closed) == {"tuned", "base"}
 
 
+@pytest.mark.parametrize(
+    ("chunk_kind", "expected_exit"),
+    [
+        ("answer", 0),
+        ("model_text_error", 0),
+        ("real_error", 1),
+    ],
+)
+def test_inference_local_handles_stream(monkeypatch, chunk_kind, expected_exit):
+    from unsloth_cli.commands import inference as infermod
+    from unsloth_cli._inference import ensure_studio_backend_path
+
+    ensure_studio_backend_path()
+    from core.inference.orchestrator import GenStreamError
+
+    chunks = {
+        "answer": ["answer"],
+        "model_text_error": ["Error: printed by the model, not a backend failure"],
+        "real_error": [GenStreamError("Error: generation failed")],
+    }[chunk_kind]
+    closed = []
+
+    class _FakeBackend:
+        def stream(self, messages, **kwargs):
+            return iter(chunks)
+
+        def close(self):
+            closed.append(True)
+
+    monkeypatch.setattr(
+        infermod,
+        "connect_studio_server",
+        lambda *_a, **_k: (_ for _ in ()).throw(AssertionError("server disabled")),
+    )
+    monkeypatch.setattr(infermod, "load_chat_backend", lambda *a, **k: _FakeBackend())
+
+    result = CliRunner().invoke(
+        _inference_app(),
+        ["fake-model", "hello", "--no-server"],
+    )
+
+    assert result.exit_code == expected_exit, result.output
+    assert closed == [True]
+    if chunk_kind == "real_error":
+        assert result.stdout == "Assistant:\n"
+        assert result.stderr == "Error: generation failed\n"
+    else:
+        assert chunks[0] in result.output
+
+
+@pytest.mark.parametrize("chunk_kind", ["answer", "model_text_error", "real_error"])
+def test_chat_local_handles_stream(monkeypatch, chunk_kind):
+    from unsloth_cli._inference import ensure_studio_backend_path
+
+    ensure_studio_backend_path()
+    from core.inference.orchestrator import GenStreamError
+
+    first_chunk = {
+        "answer": "answer",
+        "model_text_error": "Error: printed by the model, not a backend failure",
+        "real_error": GenStreamError("Error: generation failed"),
+    }[chunk_kind]
+    calls, closed = [], []
+
+    class _FakeChatBackend:
+        def stream(self, messages, **kwargs):
+            calls.append([dict(message) for message in messages])
+            return iter([first_chunk if len(calls) == 1 else "second answer"])
+
+        def close(self):
+            closed.append(True)
+
+    monkeypatch.setattr(chatmod, "resolve_model_config", lambda *a, **k: _FakeConfig())
+    monkeypatch.setattr(chatmod, "connect_studio_server", lambda *a, **k: None)
+    monkeypatch.setattr(chatmod, "load_chat_backend", lambda *a, **k: _FakeChatBackend())
+    monkeypatch.setattr(chatmod, "_compare_needs_second_model", lambda: False)
+
+    result = CliRunner().invoke(
+        _chat_app(),
+        ["fake-model"],
+        input = "first\nsecond\n/exit\n",
+    )
+
+    assert result.exit_code == 0, result.output
+    assert closed == [True]
+    if chunk_kind == "real_error":
+        assert calls[1] == [{"role": "user", "content": "second"}]
+        assert "(error: generation failed)" in result.output
+        assert "Error: generation failed" not in result.output
+    else:
+        assert calls[1] == [
+            {"role": "user", "content": "first"},
+            {"role": "assistant", "content": first_chunk},
+            {"role": "user", "content": "second"},
+        ]
+        assert first_chunk in result.output
+
+
 @pytest.mark.parametrize(
     ("chunk_kind", "expected_exit"),
     [
diff --git a/unsloth_cli/tests/test_pi_subagent.py b/unsloth_cli/tests/test_pi_subagent.py
new file mode 100644
index 0000000000..beac6770df
--- /dev/null
+++ b/unsloth_cli/tests/test_pi_subagent.py
@@ -0,0 +1,191 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import os
+from pathlib import Path
+import json
+import shutil
+import subprocess
+
+import pytest
+
+
+@pytest.mark.skipif(os.name == "nt", reason = "POSIX process group regression test")
+def test_pi_cancel_kills_child_process_group(tmp_path):
+    bun = shutil.which("bun")
+    if bun is None:
+        pytest.skip("Bun is required to execute the bundled Pi extension")
+
+    ready = tmp_path / "grandchild-ready"
+    marker = tmp_path / "grandchild-survived"
+    config = tmp_path / "subagent.json"
+    config.write_text(
+        json.dumps(
+            {
+                "baseUrl": "http://127.0.0.1:8000/v1",
+                "apiKey": "private-token",
+                "model": "local-model",
+                "contextWindow": 32768,
+                "maxTokens": 8192,
+            }
+        ),
+        encoding = "utf-8",
+    )
+    driver = tmp_path / "pi-driver.js"
+    driver.write_text(
+        """
+import { spawn } from "node:child_process";
+
+spawn(
+    process.execPath,
+    [
+        "-e",
+        `
+            const fs = require("node:fs");
+            process.on("SIGTERM", () => {});
+            fs.writeFileSync(process.env.PI_CHILD_READY, "ready");
+            setTimeout(() => fs.writeFileSync(process.env.PI_CANCEL_MARKER, "alive"), 3000);
+            setInterval(() => {}, 1000);
+        `,
+    ],
+    { stdio: "inherit" },
+);
+process.on("SIGTERM", () => {});
+setInterval(() => {}, 1000);
+""",
+        encoding = "utf-8",
+    )
+    extension = Path(__file__).parents[1] / "pi_subagent.ts"
+    test_file = tmp_path / "pi-cancel.test.ts"
+    test_file.write_text(
+        f"""
+import {{ expect, mock, test }} from "bun:test";
+import {{ existsSync }} from "node:fs";
+import {{ pathToFileURL }} from "node:url";
+
+mock.module("typebox", () => ({{
+    Type: {{ Object: (value) => value, String: (value) => value }},
+}}));
+
+test("cancellation stops the Pi child process group", async () => {{
+    process.env.UNSLOTH_PI_SUBAGENT_CONFIG = {str(config)!r};
+    process.env.PI_CHILD_READY = {str(ready)!r};
+    process.env.PI_CANCEL_MARKER = {str(marker)!r};
+    process.argv[1] = {str(driver)!r};
+
+    const loaded = await import(pathToFileURL({str(extension)!r}).href);
+    let tool;
+    let provider;
+    loaded.default({{
+        registerProvider(_name, value) {{ provider = value; }},
+        registerTool(value) {{ tool = value; }},
+    }});
+    expect(process.env.UNSLOTH_PI_SUBAGENT_CONFIG).toBeUndefined();
+    expect(process.env.UNSLOTH_PI_SUBAGENT_API_KEY).toBeUndefined();
+    expect(provider.apiKey).toBe("private-token");
+
+    const controller = new AbortController();
+    const execution = tool.execute(
+        "call",
+        {{ task: "wait" }},
+        controller.signal,
+        undefined,
+        {{ cwd: {str(tmp_path)!r} }},
+    );
+    for (let attempt = 0; attempt < 100 && !existsSync({str(ready)!r}); attempt++) {{
+        await Bun.sleep(20);
+    }}
+    expect(existsSync({str(ready)!r})).toBe(true);
+    controller.abort();
+    await expect(execution).rejects.toThrow("cancelled");
+    await Bun.sleep(3200);
+    expect(existsSync({str(marker)!r})).toBe(false);
+}}, 10_000);
+""",
+        encoding = "utf-8",
+    )
+
+    completed = subprocess.run(
+        [bun, "test", str(test_file)],
+        capture_output = True,
+        text = True,
+        timeout = 15,
+    )
+
+    assert completed.returncode == 0, completed.stdout + completed.stderr
+
+
+@pytest.mark.skipif(os.name == "nt", reason = "POSIX driver script")
+def test_pi_child_error_events_fail_the_tool_call(tmp_path):
+    bun = shutil.which("bun")
+    if bun is None:
+        pytest.skip("Bun is required to execute the bundled Pi extension")
+
+    config = tmp_path / "subagent.json"
+    config.write_text(
+        json.dumps(
+            {
+                "baseUrl": "http://127.0.0.1:8000/v1",
+                "apiKey": "private-token",
+                "model": "local-model",
+                "contextWindow": 32768,
+                "maxTokens": 8192,
+            }
+        ),
+        encoding = "utf-8",
+    )
+    # Pi reports model/API failures as message_end events while exiting 0.
+    driver = tmp_path / "pi-driver.js"
+    driver.write_text(
+        """
+const event = {
+    type: "message_end",
+    message: { role: "assistant", stopReason: "error", errorMessage: "backend unreachable", content: [] },
+};
+console.log(JSON.stringify(event));
+""",
+        encoding = "utf-8",
+    )
+    extension = Path(__file__).parents[1] / "pi_subagent.ts"
+    test_file = tmp_path / "pi-error.test.ts"
+    test_file.write_text(
+        f"""
+import {{ expect, mock, test }} from "bun:test";
+import {{ pathToFileURL }} from "node:url";
+
+mock.module("typebox", () => ({{
+    Type: {{ Object: (value) => value, String: (value) => value }},
+}}));
+
+test("child error events fail the tool call", async () => {{
+    process.env.UNSLOTH_PI_SUBAGENT_CONFIG = {str(config)!r};
+    process.argv[1] = {str(driver)!r};
+
+    const loaded = await import(pathToFileURL({str(extension)!r}).href);
+    let tool;
+    loaded.default({{
+        registerProvider() {{}},
+        registerTool(value) {{ tool = value; }},
+    }});
+
+    const execution = tool.execute(
+        "call",
+        {{ task: "fail" }},
+        undefined,
+        undefined,
+        {{ cwd: {str(tmp_path)!r} }},
+    );
+    await expect(execution).rejects.toThrow("backend unreachable");
+}}, 10_000);
+""",
+        encoding = "utf-8",
+    )
+
+    completed = subprocess.run(
+        [bun, "test", str(test_file)],
+        capture_output = True,
+        text = True,
+        timeout = 15,
+    )
+
+    assert completed.returncode == 0, completed.stdout + completed.stderr
diff --git a/unsloth_cli/tests/test_start.py b/unsloth_cli/tests/test_start.py
index 1e03d390d1..e76ae24f8b 100644
--- a/unsloth_cli/tests/test_start.py
+++ b/unsloth_cli/tests/test_start.py
@@ -20,6 +20,7 @@ if str(_REPO_ROOT) not in sys.path:
 
 
 import pytest
+import typer
 from typer.testing import CliRunner
 
 import unsloth_cli.commands.start as start
@@ -618,6 +619,104 @@ def test_write_codex_config_omits_catalog_for_old_codex(tmp_path, monkeypatch):
     assert not (tmp_path / "model-catalog.json").exists()
 
 
+def test_write_codex_subagent_config_keeps_parent_model_out(tmp_path, monkeypatch):
+    monkeypatch.setattr(start, "_codex_supports_model_catalog", lambda: True)
+    local = {**MODEL, "id": MODEL["id"] + ":UD-Q4_K_XL"}
+    path = start.write_codex_subagent_config(BASE, "private-token", local, tmp_path)
+    agent = _parse_toml(path.read_text())
+    assert agent["name"] == "unsloth"
+    assert "local agent" in agent["description"].lower()
+    assert agent["model_provider"] == start._CODEX_PROFILE
+    assert agent["model"] == local["id"]
+    assert agent["model_context_window"] == MODEL["context_length"]
+    assert agent["model_providers"][start._CODEX_PROFILE] == {
+        "name": "Unsloth Studio",
+        "base_url": f"{BASE}/v1",
+        "wire_api": "responses",
+        "auth": {
+            "command": sys.executable,
+            "args": [
+                "-c",
+                "import json,sys; print(json.load(open(sys.argv[1], encoding='utf-8'))['token'])",
+                str(tmp_path / "unsloth-auth.json"),
+            ],
+            "timeout_ms": 5000,
+        },
+    }
+    assert json.loads((tmp_path / "unsloth-auth.json").read_text()) == {"token": "private-token"}
+    catalog = json.loads((tmp_path / agent["model_catalog_json"]).read_text())
+    assert catalog["models"][0]["slug"] == local["id"]
+
+
+@pytest.mark.skipif(os.name == "nt", reason = "WSL scenario")
+def test_codex_subagent_auth_uses_wsl_for_windows_codex(monkeypatch, tmp_path):
+    monkeypatch.setenv("WSL_DISTRO_NAME", "Ubuntu")
+    monkeypatch.setattr(start, "_codex_supports_model_catalog", lambda: False)
+    monkeypatch.setattr(
+        start.shutil,
+        "which",
+        lambda _: "/mnt/c/Users/x/AppData/Roaming/npm/codex.exe",
+    )
+
+    path = start.write_codex_subagent_config(BASE, "private-token", MODEL, tmp_path)
+    auth = _parse_toml(path.read_text())["model_providers"][start._CODEX_PROFILE]["auth"]
+
+    assert auth["command"] == "wsl.exe"
+    assert auth["args"][:5] == ["-d", "Ubuntu", "--", sys.executable, "-c"]
+    assert auth["args"][-1] == str(tmp_path / "unsloth-auth.json")
+
+
+@pytest.mark.skipif(os.name == "nt", reason = "WSL scenario")
+def test_agent_config_path_translates_for_windows_agent(monkeypatch, tmp_path):
+    windows_path = r"\\wsl.localhost\Ubuntu\tmp\unsloth.toml"
+    monkeypatch.setenv("WSL_DISTRO_NAME", "Ubuntu")
+    monkeypatch.setattr(
+        start.shutil,
+        "which",
+        lambda _: "/mnt/c/Users/x/AppData/Roaming/npm/codex",
+    )
+    monkeypatch.setattr(start.subprocess, "check_output", lambda *args, **kwargs: windows_path)
+
+    assert start._agent_config_path(tmp_path / "unsloth.toml", ["codex"]) == windows_path
+
+
+def test_subagent_model_id_preserves_explicit_variant(monkeypatch):
+    monkeypatch.setattr(
+        start,
+        "_http_json",
+        lambda *args, **kwargs: pytest.fail("explicit variant should not need status"),
+    )
+    assert (
+        start._subagent_model_id(BASE, "key", MODEL, MODEL["id"], "UD-Q4_K_XL")
+        == MODEL["id"] + ":UD-Q4_K_XL"
+    )
+
+
+def test_subagent_model_id_uses_loaded_variant(monkeypatch):
+    monkeypatch.setattr(
+        start,
+        "_http_json",
+        lambda *args, **kwargs: {"is_gguf": True, "gguf_variant": "Q5_K_M"},
+    )
+    assert start._subagent_model_id(BASE, "key", MODEL, None, None) == MODEL["id"] + ":Q5_K_M"
+
+
+def test_subagent_model_id_warns_when_status_unavailable(monkeypatch, capsys):
+    def raise_error(*args, **kwargs):
+        raise OSError("connection refused")
+
+    monkeypatch.setattr(start, "_http_json", raise_error)
+    assert start._subagent_model_id(BASE, "key", MODEL, None, None) == MODEL["id"]
+    assert "could not verify the loaded GGUF variant" in capsys.readouterr().err
+
+
+@pytest.mark.parametrize("agent", ["openclaw", "hermes"])
+def test_unsupported_agents_reject_as_subagent(agent):
+    result = CliRunner().invoke(start.start_app, [agent, "--as-subagent"])
+    assert result.exit_code == 1
+    assert f"--as-subagent is not supported for {agent}." in result.output
+
+
 @pytest.fixture()
 def fake_studio(tmp_path, monkeypatch):
     calls = []
@@ -639,8 +738,13 @@ def fake_studio(tmp_path, monkeypatch):
         if url.endswith("/api/auth/api-keys"):
             return {"key": "sk-unsloth-feedfacefeedface"}
         if url.endswith("/api/inference/load"):
+            already_loaded = state["models"][0]["id"] == payload["model_path"]
             state["models"] = [{"id": payload["model_path"], "context_length": 4096}]
-            return {}
+            return {
+                "status": "already_loaded" if already_loaded else "loaded",
+                "model": payload["model_path"],
+                "display_name": payload["model_path"],
+            }
         raise AssertionError(f"unexpected request: {method} {url}")
 
     monkeypatch.setattr(start, "find_studio_server", lambda: BASE)
@@ -684,6 +788,82 @@ def test_connect_claude_no_launch(fake_studio):
     assert ".claude/settings.json" not in result.output
 
 
+def test_connect_claude_as_subagent_preserves_cloud_parent(fake_studio, tmp_path):
+    result = CliRunner().invoke(
+        start.start_app,
+        [
+            "claude",
+            "--as-subagent",
+            "--no-launch",
+            "--model",
+            MODEL["id"] + ":UD-Q4_K_XL",
+            "hello",
+        ],
+    )
+    assert result.exit_code == 0, result.output
+    command = _launch_command(result.output)
+    plugin = tmp_path / "agents" / "claude-subagent" / "unsloth-local-agent"
+    assert command == [
+        "claude",
+        "--plugin-dir",
+        str(plugin),
+        "--allowedTools",
+        start._CLAUDE_SUBAGENT_TOOL,
+        "hello",
+    ]
+    assert "--model" not in command
+    parent_base = "$env:ANTHROPIC_BASE_URL" if os.name == "nt" else "export ANTHROPIC_BASE_URL="
+    parent_token = (
+        "$env:ANTHROPIC_AUTH_TOKEN" if os.name == "nt" else "export ANTHROPIC_AUTH_TOKEN="
+    )
+    assert parent_base not in result.output
+    assert parent_token not in result.output
+    assert "unset ANTHROPIC_API_KEY" not in result.output
+    assert "UNSLOTH_CLAUDE_SUBAGENT_API_KEY" not in result.output
+    assert "sk-unsloth-feedfacefeedface" not in result.output
+    assert json.loads((plugin / ".claude-plugin" / "plugin.json").read_text())["name"] == (
+        "unsloth-local-agent"
+    )
+    mcp = json.loads((plugin / ".mcp.json").read_text())["mcpServers"]["unsloth"]
+    assert mcp["command"] == sys.executable
+    assert mcp["args"] == ["-m", start._CLAUDE_SUBAGENT_MCP_MODULE]
+    assert mcp["env"] == {
+        "UNSLOTH_CLAUDE_SUBAGENT_BASE_URL": BASE,
+        "UNSLOTH_CLAUDE_SUBAGENT_API_KEY": "sk-unsloth-feedfacefeedface",
+        "UNSLOTH_CLAUDE_SUBAGENT_MODEL": MODEL["id"] + ":UD-Q4_K_XL",
+        "UNSLOTH_CLAUDE_SUBAGENT_BYPASS_PERMISSIONS": "0",
+        "UNSLOTH_CLAUDE_SUBAGENT_CONTEXT_WINDOW": "4096",
+    }
+    skill = (plugin / "skills" / "local-agent" / "SKILL.md").read_text()
+    assert "spawn an Unsloth agent or local agent" in skill
+    assert "Ask Claude to spawn an Unsloth or local agent." in result.output
+
+
+@pytest.mark.skipif(os.name == "nt", reason = "WSL scenario")
+def test_claude_subagent_plugin_uses_wsl_for_windows_claude(monkeypatch, tmp_path):
+    monkeypatch.setenv("WSL_DISTRO_NAME", "Ubuntu")
+    monkeypatch.setenv("WSLENV", "EXISTING")
+    monkeypatch.setattr(
+        start.shutil,
+        "which",
+        lambda _: "/mnt/c/Users/x/AppData/Local/Programs/claude.exe",
+    )
+    server_env = {"UNSLOTH_CLAUDE_SUBAGENT_API_KEY": "secret"}
+    plugin = start.write_claude_subagent_plugin(tmp_path, server_env)
+    mcp = json.loads((plugin / ".mcp.json").read_text())["mcpServers"]["unsloth"]
+    assert mcp["command"] == "wsl.exe"
+    assert mcp["args"] == [
+        "-d",
+        "Ubuntu",
+        "--",
+        sys.executable,
+        "-m",
+        start._CLAUDE_SUBAGENT_MCP_MODULE,
+    ]
+    assert mcp["env"]["UNSLOTH_CLAUDE_SUBAGENT_API_KEY"] == "secret"
+    assert mcp["env"]["WSLENV"].split(":") == ["EXISTING", "UNSLOTH_CLAUDE_SUBAGENT_API_KEY"]
+
+
 def test_connect_claude_compact_window_omitted_without_context(fake_studio, monkeypatch):
     # A model that doesn't report a context length -> leave Claude's default window
     # rather than guessing one.
@@ -808,6 +988,38 @@ def test_connect_codex_no_launch(fake_studio, tmp_path):
     assert (home / "unsloth_api.config.toml").exists()
 
 
+def test_connect_codex_as_subagent_preserves_cloud_parent(fake_studio, tmp_path, monkeypatch):
+    monkeypatch.setattr(start, "_codex_supports_model_catalog", lambda: True)
+    result = CliRunner().invoke(
+        start.start_app,
+        [
+            "codex",
+            "--as-subagent",
+            "--no-launch",
+            "--model",
+            MODEL["id"] + ":UD-Q4_K_XL",
+        ],
+    )
+    assert result.exit_code == 0, result.output
+    command = _launch_command(result.output)
+    assert command[0] == "codex"
+    assert command[1:3] == ["--enable", "multi_agent"]
+    assert "agents.max_depth=1" in command
+    assert "--oss" not in command
+    assert "--profile" not in command
+    assert "--model" not in command
+    assert "CODEX_HOME" not in result.output
+    assert start._CODEX_ENV_KEY not in result.output
+    assert "sk-unsloth-feedfacefeedface" not in result.output
+    home = tmp_path / "agents" / "codex-subagent"
+    agent_path = home / "unsloth.toml"
+    agent = _parse_toml(agent_path.read_text())
+    assert agent["model"] == MODEL["id"] + ":UD-Q4_K_XL"
+    assert "env_key" not in agent["model_providers"][start._CODEX_PROFILE]
+    assert f"agents.unsloth.config_file={json.dumps(str(agent_path))}" in command
+    assert "Ask Codex to spawn an Unsloth or local agent." in result.output
+
+
 def test_connect_codex_matches_requested_model_case_insensitively(fake_studio, tmp_path):
     result = CliRunner().invoke(
         start.start_app,
@@ -824,7 +1036,7 @@ def test_connect_codex_matches_requested_model_case_insensitively(fake_studio, t
     assert profile["model"] == MODEL["id"]
 
 
-def test_resolve_model_matches_loaded_canonical_case_after_load(monkeypatch):
+def test_resolve_model_matches_loaded_canonical_case_after_load(monkeypatch, capsys):
     calls = []
     state = {"loaded": False}
 
@@ -862,6 +1074,8 @@ def test_resolve_model_matches_loaded_canonical_case_after_load(monkeypatch):
 
     assert entry["id"] == "unsloth/gemma-4-E2B-it-GGUF"
     assert any(c[1].endswith("/api/inference/load") for c in calls)
+    output = capsys.readouterr().out
+    assert "please wait" not in output
 
 
 def test_resolve_model_loads_when_catalog_hit_is_not_loaded(monkeypatch):
@@ -903,6 +1117,35 @@ def test_resolve_model_loads_when_catalog_hit_is_not_loaded(monkeypatch):
     assert any(u.endswith("/api/inference/load") for _, u in calls)
 
 
+def test_resolve_model_does_not_attach_if_catalog_stays_unloaded(monkeypatch):
+    def http_json(
+        method,
+        url,
+        token,
+        payload = None,
+        timeout = 30,
+        error = None,
+    ):
+        if url.endswith("/v1/models"):
+            return {
+                "data": [
+                    {
+                        "id": "unsloth/Gemma-4-GGUF",
+                        "loaded": False,
+                        "context_length": 131072,
+                    }
+                ]
+            }
+        if url.endswith("/api/inference/load"):
+            return {"status": "loaded", "model": "unsloth/Gemma-4-GGUF"}
+        raise AssertionError(f"unexpected request: {method} {url}")
+
+    monkeypatch.setattr(start, "_http_json", http_json)
+
+    with pytest.raises(typer.Exit):
+        start._resolve_model(BASE, "sk-test", "unsloth/gemma-4-gguf")
+
+
 def test_resolve_model_attaches_to_loaded_catalog_hit_without_reload(monkeypatch):
     # The mirror case: a loaded entry (loaded == True) that case-matches attaches with
     # no /api/inference/load call.
@@ -931,6 +1174,25 @@ def test_resolve_model_attaches_to_loaded_catalog_hit_without_reload(monkeypatch
     assert not any(u.endswith("/api/inference/load") for _, u in calls)
 
 
+def test_resolve_model_without_request_rejects_unloaded_catalog(monkeypatch):
+    monkeypatch.setattr(
+        start,
+        "_http_json",
+        lambda *a, **k: {
+            "data": [
+                {
+                    "id": "unsloth/Gemma-4-GGUF",
+                    "loaded": False,
+                    "context_length": 131072,
+                }
+            ]
+        },
+    )
+
+    with pytest.raises(typer.Exit):
+        start._resolve_model(BASE, "sk-test", None)
+
+
 def test_resolve_model_remote_studio_does_not_casefold_attach(monkeypatch):
     # Against a remote Unsloth the local existence probe cannot see server-side paths,
     # so a case-variant loaded id must NOT attach without a load: it could be a distinct
@@ -1213,6 +1475,9 @@ def test_connect_model_flag_loads_on_server(fake_studio):
     assert loads == [
         ("POST", f"{BASE}/api/inference/load", {"model_path": "unsloth/Qwen3.5-35B-A3B"})
     ]
+    assert result.output.index(
+        f"Switching the Unsloth server from {MODEL['id']} to unsloth/Qwen3.5-35B-A3B.\n"
+    ) < result.output.index("This unloads the current model for every attached session.\n")
     _assert_env_set(result.output, "ANTHROPIC_MODEL", "unsloth/Qwen3.5-35B-A3B")
 
 
@@ -1296,6 +1561,211 @@ def test_split_repo_variant(model, expected):
     assert start._split_repo_variant(model) == expected
 
 
+@pytest.mark.parametrize(
+    "token, expected",
+    [
+        ("unsloth/gemma-4-E2B-it-GGUF", True),
+        ("unsloth/gemma-4-E2B-it-GGUF:UD-Q4_K_XL", True),
+        ("some-org/model.name_1", True),
+        ("--continue", False),  # flag
+        ("resume", False),  # single word, no slash
+        ("/models/local.gguf", False),  # absolute path
+        ("./rel.gguf", False),  # relative path
+        ("C:\\models\\x.gguf", False),  # Windows drive
+        ("my models/foo", False),  # has a space
+        ("owner/repo/extra", False),  # too many segments
+    ],
+)
+def test_looks_like_model(token, expected):
+    assert start._looks_like_model(token) is expected
+
+
+def test_consume_positional_model_leading_token():
+    # A leading org/name positional routes to --model and is dropped from the passthrough.
+    model, rest = start._consume_positional_model(None, ["unsloth/Model-GGUF", "--continue"])
+    assert model == "unsloth/Model-GGUF"
+    assert rest == ["--continue"]
+
+
+def test_looks_like_model_leaves_existing_local_dir_for_agent(tmp_path, monkeypatch):
+    # A relative `owner/repo` that actually exists (e.g. an OpenCode project dir) must
+    # stay an agent argument, not be consumed as a model.
+    monkeypatch.chdir(tmp_path)
+    (tmp_path / "owner" / "repo").mkdir(parents = True)
+    assert start._looks_like_model("owner/repo") is False
+    model, rest = start._consume_positional_model(None, ["owner/repo"])
+    assert model is None and rest == ["owner/repo"]
+    # The same shape, when it does not exist locally, is still treated as a model.
+    assert start._looks_like_model("owner/absent-repo") is True
+
+
+def test_consume_positional_model_ignores_non_leading_and_explicit_model():
+    # An org/name that is an option value (not leading) is never stolen.
+    model, rest = start._consume_positional_model(None, ["--profile", "owner/repo"])
+    assert model is None and rest == ["--profile", "owner/repo"]
+    # An explicit --model always wins; the positional is left untouched.
+    model, rest = start._consume_positional_model("explicit/model", ["owner/repo"])
+    assert model == "explicit/model" and rest == ["owner/repo"]
+
+
+def test_start_separator_preserves_model_shaped_agent_argument(fake_studio):
+    result = CliRunner().invoke(
+        start.start_app,
+        ["codex", "--no-launch", "--", "owner/repo"],
+    )
+
+    assert result.exit_code == 0, result.output
+    command = _launch_command(result.output)
+    assert command[-2:] == ["--", "owner/repo"]
+
+    result = CliRunner().invoke(
+        start.start_app,
+        ["codex", "--no-launch", MODEL["id"], "--", "--continue"],
+    )
+    assert result.exit_code == 0, result.output
+    command = _launch_command(result.output)
+    assert command[-2:] == ["--", "--continue"]
+
+
+def test_start_positional_model_routes_to_model_on_auto_serve(fake_studio, monkeypatch):
+    # `unsloth start claude unsloth/Model-GGUF` (no --model): the positional becomes the
+    # model; the GGUF variant is left unset so the server's own quant preference selects it.
+    monkeypatch.setenv("UNSLOTH_STUDIO_URL", "http://127.0.0.1:8888")
+    monkeypatch.setattr(start, "find_studio_server", lambda: None)
+    captured = {}
+    fake = SimpleNamespace(pid = 1, poll = lambda: None)
+
+    def fake_start(
+        base,
+        model,
+        load,
+        server_options = None,
+    ):
+        captured["model"] = model
+        captured["load"] = load
+        captured["server_options"] = server_options
+        start._auto_served_server = fake
+        return fake
+
+    monkeypatch.setattr(start, "_start_studio_server", fake_start)
+    monkeypatch.setattr(start, "_shutdown_server", lambda server: None)
+    monkeypatch.setattr(start.shutil, "which", lambda _: "/usr/local/bin/claude")
+    monkeypatch.setattr(start.subprocess, "run", lambda command, env: SimpleNamespace(returncode = 0))
+
+    result = CliRunner().invoke(start.start_app, ["claude", "unsloth/gemma-4-E2B-it-GGUF"])
+    assert result.exit_code == 0, result.output
+    assert captured["model"] == "unsloth/gemma-4-E2B-it-GGUF"
+    assert captured["load"].gguf_variant is None
+
+
+def test_start_local_gguf_path_keeps_no_default_variant(fake_studio, monkeypatch, tmp_path):
+    # A local GGUF dir/path ending in -GGUF must NOT get a forced default quant: the dir
+    # may only hold a different quant, and pre-PR the server picked whatever was available.
+    monkeypatch.setenv("UNSLOTH_STUDIO_URL", "http://127.0.0.1:8888")
+    monkeypatch.setattr(start, "find_studio_server", lambda: None)
+    local = tmp_path / "Qwen3-1.7B-GGUF"
+    local.mkdir()
+    captured = {}
+    fake = SimpleNamespace(pid = 1, poll = lambda: None)
+
+    def fake_start(
+        base,
+        model,
+        load,
+        server_options = None,
+    ):
+        captured["load"] = load
+        start._auto_served_server = fake
+        return fake
+
+    monkeypatch.setattr(start, "_start_studio_server", fake_start)
+    monkeypatch.setattr(start, "_shutdown_server", lambda server: None)
+    monkeypatch.setattr(start.shutil, "which", lambda _: "/usr/local/bin/claude")
+    monkeypatch.setattr(start.subprocess, "run", lambda command, env: SimpleNamespace(returncode = 0))
+
+    result = CliRunner().invoke(start.start_app, ["claude", "--model", str(local)])
+    assert result.exit_code == 0, result.output
+    assert captured["load"].gguf_variant is None
+
+
+def test_start_studio_server_forwards_tool_flags_via_command_and_env(monkeypatch):
+    captured = {}
+
+    class FakePopen:
+        def __init__(self, command, **kwargs):
+            captured["command"] = command
+            captured["kwargs"] = kwargs
+            self.pid = 1
+
+        def poll(self):
+            return None
+
+    monkeypatch.setattr(start.subprocess, "Popen", FakePopen)
+    monkeypatch.setattr(start, "_studio_healthy", lambda base, timeout = 3.0: True)
+    monkeypatch.setattr(start, "_log_tail", lambda path, lines = 20: "API Key: sk-unsloth-x")
+    monkeypatch.setattr(start.time, "sleep", lambda _s: None)
+    # No inherited kill switches, so the omitted-flag default applies.
+    monkeypatch.delenv("UNSLOTH_DISABLE_TOOL_CALL_HEALING", raising = False)
+    monkeypatch.delenv("UNSLOTH_TOOL_CALL_NUDGE", raising = False)
+
+    # Default start: tools off (passthrough), healing + nudging on.
+    start._start_studio_server("http://127.0.0.1:8888", "unsloth/M-GGUF", start.LoadOptions())
+    cmd, env = captured["command"], captured["kwargs"]["env"]
+    assert "--disable-tools" in cmd and "--enable-tools" not in cmd
+    assert env["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] == "0"
+    assert env["UNSLOTH_TOOL_CALL_NUDGE"] == "1"
+
+    # Flipped: tools on, healing off, nudging off.
+    start._start_studio_server(
+        "http://127.0.0.1:8888",
+        "unsloth/M-GGUF",
+        start.LoadOptions(),
+        start.ServerOptions(enable_tools = True, tool_call_healing = False, tool_call_nudging = False),
+    )
+    cmd, env = captured["command"], captured["kwargs"]["env"]
+    assert "--enable-tools" in cmd and "--disable-tools" not in cmd
+    assert env["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] == "1"
+    assert env["UNSLOTH_TOOL_CALL_NUDGE"] == "0"
+
+
+def test_start_studio_server_respects_inherited_tool_call_env(monkeypatch):
+    # With the flags omitted, an operator's pre-exported kill switch must survive into the
+    # child server instead of being overwritten with the start defaults.
+    captured = {}
+
+    class FakePopen:
+        def __init__(self, command, **kwargs):
+            captured["kwargs"] = kwargs
+            self.pid = 1
+
+        def poll(self):
+            return None
+
+    monkeypatch.setattr(start.subprocess, "Popen", FakePopen)
+    monkeypatch.setattr(start, "_studio_healthy", lambda base, timeout = 3.0: True)
+    monkeypatch.setattr(start, "_log_tail", lambda path, lines = 20: "API Key: sk-unsloth-x")
+    monkeypatch.setattr(start.time, "sleep", lambda _s: None)
+    monkeypatch.setenv("UNSLOTH_DISABLE_TOOL_CALL_HEALING", "1")
+    monkeypatch.setenv("UNSLOTH_TOOL_CALL_NUDGE", "0")
+
+    # Flags omitted -> inherited values are preserved.
+    start._start_studio_server("http://127.0.0.1:8888", "unsloth/M-GGUF", start.LoadOptions())
+    env = captured["kwargs"]["env"]
+    assert env["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] == "1"
+    assert env["UNSLOTH_TOOL_CALL_NUDGE"] == "0"
+
+    # An explicit flag still overrides the inherited env.
+    start._start_studio_server(
+        "http://127.0.0.1:8888",
+        "unsloth/M-GGUF",
+        start.LoadOptions(),
+        start.ServerOptions(tool_call_healing = True, tool_call_nudging = True),
+    )
+    env = captured["kwargs"]["env"]
+    assert env["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] == "0"
+    assert env["UNSLOTH_TOOL_CALL_NUDGE"] == "1"
+
+
 def test_connect_model_bare_id_matches_loaded_without_reload(fake_studio):
     # A bare `--model <loaded repo>` (no load knobs) attaches to the already-loaded model
     # without touching /api/inference/load, so it can never evict another session.
@@ -1303,6 +1773,7 @@ def test_connect_model_bare_id_matches_loaded_without_reload(fake_studio):
     assert result.exit_code == 0, result.output
     loads = [c for c in fake_studio if c[1].endswith("/api/inference/load")]
     assert loads == []
+    assert f"Reusing loaded model: {MODEL['id']}\n" in result.output
     _assert_env_set(result.output, "ANTHROPIC_MODEL", MODEL["id"])
 
 
@@ -1324,6 +1795,7 @@ def test_connect_model_variant_suffix_defers_to_server_dedup(fake_studio):
             {"model_path": MODEL["id"], "gguf_variant": "UD-Q4_K_XL"},
         )
     ]
+    assert f"Reusing loaded model: {MODEL['id']}:UD-Q4_K_XL\n" in result.output
     _assert_env_set(result.output, "ANTHROPIC_MODEL", MODEL["id"])
 
 
@@ -1730,8 +2202,9 @@ def _reset_auto_served():
     start._auto_served_server = None
 
 
-def test_start_studio_server_builds_command_and_waits(monkeypatch):
+def test_start_studio_server_builds_command_and_waits(monkeypatch, capsys):
     captured = {}
+    monkeypatch.setenv(start._START_API_KEY_MARKER_ENV, "parent")
 
     class FakePopen:
         def __init__(self, command, **kwargs):
@@ -1761,18 +2234,210 @@ def test_start_studio_server_builds_command_and_waits(monkeypatch):
     assert cmd[cmd.index("--gguf-variant") + 1] == "UD-Q4_K_XL"
     assert cmd[cmd.index("--context-length") + 1] == "8192"
     assert "--tensor-parallel" in cmd
+    assert "--start-api-key-marker" not in cmd
+    assert captured["kwargs"]["env"][start._START_API_KEY_MARKER_ENV] == "1"
+    assert start.os.environ[start._START_API_KEY_MARKER_ENV] == "parent"
     assert cmd[cmd.index("-p") + 1] == "8888"
     assert start.LoadOptions().load_in_4bit is True and "--no-load-in-4bit" not in cmd
     assert captured["kwargs"].get("start_new_session") is True  # own process group
     assert server.pid == 4321
+    output = capsys.readouterr().out
+    assert "Starting Unsloth server\n" in output
+    assert "Model: unsloth/Qwen3-1.7B-GGUF:UD-Q4_K_XL\n" in output
+    assert "No Unsloth server at" not in output
+    assert "server ready" not in output
 
 
-def test_auto_serves_when_no_server_then_tears_down(fake_studio, monkeypatch):
+def test_start_studio_server_polls_progress_from_early_key(monkeypatch):
+    class FakePopen:
+        pid = 4321
+
+        def poll(self):
+            return None
+
+    tails = iter(
+        [
+            "UNSLOTH_START_API_KEY: sk-unsloth-early\nLoading model...",
+            "UNSLOTH_START_API_KEY: sk-unsloth-early\nModel loaded: owner/model",
+        ]
+    )
+    created = []
+
+    class FakeProgress:
+        def __init__(self, base, key, model, variant):
+            created.append((base, key, model, variant, "created"))
+
+        def poll(self):
+            created.append("poll")
+
+        def close(self):
+            created.append("close")
+
+        def complete(self):
+            created.append("complete")
+
+    monkeypatch.setattr(start.subprocess, "Popen", lambda *a, **k: FakePopen())
+    monkeypatch.setattr(start, "_studio_healthy", lambda *a, **k: True)
+    monkeypatch.setattr(start, "_log_tail", lambda *a, **k: next(tails))
+    monkeypatch.setattr(start, "_ModelDownloadProgress", FakeProgress)
+    monkeypatch.setattr(start.time, "sleep", lambda _s: None)
+    monkeypatch.setattr(
+        start.typer,
+        "echo",
+        lambda message = "", **_kwargs: created.append(("echo", message)),
+    )
+
+    server = start._start_studio_server(
+        BASE,
+        "owner/model-GGUF",
+        start.LoadOptions(gguf_variant = "Q4_K_M"),
+    )
+
+    assert server.pid == 4321
+    assert (BASE, "sk-unsloth-early", "owner/model-GGUF", "Q4_K_M", "created") in created
+    assert created.count("poll") == 2
+    assert created[-2:] == ["complete", "close"]
+    assert not any(isinstance(event, tuple) and "server ready" in event[-1] for event in created)
+
+
+def test_load_model_with_progress_uses_selected_gguf_size(monkeypatch, capsys):
+    release = start.threading.Event()
+    calls = []
+
+    def http_json(
+        method,
+        url,
+        token,
+        payload = None,
+        timeout = 30,
+        error = None,
+    ):
+        calls.append((method, url, payload))
+        if url.endswith("/api/inference/load"):
+            assert release.wait(timeout = 2)
+            return {"model": "owner/model-GGUF"}
+        if "/api/hub/gguf-variants?" in url:
+            return {
+                "default_variant": "Q8_0",
+                "variants": [
+                    {
+                        "quant": "UD-Q4_K_XL",
+                        "filename": "model-UD-Q4_K_XL.gguf",
+                        "size_bytes": 4 * 1024**3,
+                        "download_size_bytes": 4 * 1024**3,
+                    }
+                ],
+            }
+        if "/api/hub/gguf-download-progress?" in url:
+            release.set()
+            return {
+                "downloaded_bytes": 2 * 1024**3,
+                "expected_bytes": 4 * 1024**3,
+                "progress": 0.5,
+            }
+        raise AssertionError(f"unexpected request: {method} {url}")
+
+    monkeypatch.setattr(start, "_http_json", http_json)
+    monkeypatch.setattr(start, "_DOWNLOAD_POLL_INTERVAL_S", 0.001)
+    result = start._load_model_with_progress(
+        BASE,
+        "sk-test",
+        "owner/model-GGUF",
+        start.LoadOptions(gguf_variant = "UD-Q4_K_XL"),
+        {"model_path": "owner/model-GGUF", "gguf_variant": "UD-Q4_K_XL"},
+    )
+
+    assert result == {"model": "owner/model-GGUF"}
+    output = capsys.readouterr().out
+    assert "Downloading model" in output
+    assert "100%" in output
+    progress_url = next(url for method, url, _ in calls if "gguf-download-progress" in url)
+    assert "variant=UD-Q4_K_XL" in progress_url
+    assert f"expected_bytes={4 * 1024**3}" in progress_url
+
+
+def test_download_progress_ignores_fully_cached_bytes(capsys):
+    display = start._DownloadProgressDisplay()
+    display.update(
+        {
+            "downloaded_bytes": 4 * 1024**3,
+            "completed_bytes": 4 * 1024**3,
+            "expected_bytes": 4 * 1024**3,
+            "progress": 0.99,
+        }
+    )
+    display.close()
+
+    assert capsys.readouterr().out == ""
+
+
+def test_resolve_model_warns_on_same_repo_quant_switch(monkeypatch, capsys):
+    models = [{"id": "owner/model-GGUF", "loaded": True}]
+
+    def http_json(
+        method,
+        url,
+        key,
+        payload = None,
+        timeout = 30,
+        error = None,
+    ):
+        assert url.endswith("/api/inference/status"), url
+        return {"is_gguf": True, "gguf_variant": "Q4_K_M"}
+
+    monkeypatch.setattr(start, "_loaded_models", lambda base, key: models)
+    monkeypatch.setattr(start, "_http_json", http_json)
+    monkeypatch.setattr(
+        start,
+        "_load_model_with_progress",
+        lambda base, key, model, load, payload: {"status": "loaded", "model": "owner/model-GGUF"},
+    )
+
+    start._resolve_model(BASE, "key", "owner/model-GGUF", start.LoadOptions(gguf_variant = "Q8_0"))
+
+    out = capsys.readouterr().out
+    assert (
+        "Switching the Unsloth server from owner/model-GGUF:Q4_K_M to owner/model-GGUF:Q8_0." in out
+    )
+    assert "every attached session" in out
+
+
+def test_resolve_model_same_quant_prints_no_switch_warning(monkeypatch, capsys):
+    models = [{"id": "owner/model-GGUF", "loaded": True}]
+
+    monkeypatch.setattr(start, "_loaded_models", lambda base, key: models)
+    monkeypatch.setattr(
+        start,
+        "_http_json",
+        lambda *a, **k: {"is_gguf": True, "gguf_variant": "Q8_0"},
+    )
+    monkeypatch.setattr(
+        start,
+        "_load_model_with_progress",
+        lambda base, key, model, load, payload: {
+            "status": "already_loaded",
+            "model": "owner/model-GGUF",
+        },
+    )
+
+    start._resolve_model(BASE, "key", "owner/model-GGUF", start.LoadOptions(gguf_variant = "Q8_0"))
+
+    out = capsys.readouterr().out
+    assert "Switching" not in out
+    assert "Reusing loaded model: owner/model-GGUF:Q8_0" in out
+
+
+def test_auto_serves_when_no_server_then_keeps_server(fake_studio, monkeypatch):
     monkeypatch.setattr(start, "find_studio_server", lambda: None)
     started = {}
     fake = SimpleNamespace(pid = 999, poll = lambda: None)
 
-    def fake_start(base, model, load):
+    def fake_start(
+        base,
+        model,
+        load,
+        server_options = None,
+    ):
         started.update(base = base, model = model, load = load)
         start._auto_served_server = fake
         return fake
@@ -1793,8 +2458,134 @@ def test_auto_serves_when_no_server_then_tears_down(fake_studio, monkeypatch):
     assert started["model"] == "unsloth/Qwen3-1.7B-GGUF"
     assert started["load"].gguf_variant == "UD-Q4_K_XL"
     assert started["base"] == BASE
-    # Torn down after the agent session ended.
-    assert started.get("down") is fake
+    # A successful agent exit releases ownership and leaves the server available
+    # for another terminal. Explicit startup failures still use the cleanup path.
+    assert "down" not in started
+    assert start._auto_served_server is None
+    assert "is still running" in result.output
+    assert "unsloth studio stop" in result.output
+
+
+def test_auto_served_agent_launch_failure_stops_server(fake_studio, monkeypatch):
+    monkeypatch.setattr(start, "find_studio_server", lambda: None)
+    stopped = []
+    fake = SimpleNamespace(pid = 999, poll = lambda: None)
+
+    def fake_start(*_args):
+        start._auto_served_server = fake
+        return fake
+
+    monkeypatch.setattr(start, "_start_studio_server", fake_start)
+    monkeypatch.setattr(start, "_shutdown_server", stopped.append)
+    monkeypatch.setattr(
+        start,
+        "_launch",
+        lambda *a, **k: (_ for _ in ()).throw(RuntimeError("agent launch failed")),
+    )
+
+    result = CliRunner().invoke(
+        start.start_app,
+        ["claude", "--model", "unsloth/Qwen3-1.7B-GGUF"],
+    )
+
+    assert result.exit_code == 1
+    assert stopped == [fake]
+    assert "is still running" not in result.output
+
+
+def test_auto_served_server_exit_is_not_reported_as_running(fake_studio, monkeypatch):
+    monkeypatch.setattr(start, "find_studio_server", lambda: None)
+    fake = SimpleNamespace(pid = 999, poll = lambda: 1)
+
+    def fake_start(*_args):
+        start._auto_served_server = fake
+        return fake
+
+    monkeypatch.setattr(start, "_start_studio_server", fake_start)
+    monkeypatch.setattr(start, "_launch", lambda *a, **k: 0)
+
+    result = CliRunner().invoke(
+        start.start_app,
+        ["claude", "--model", "unsloth/Qwen3-1.7B-GGUF"],
+    )
+
+    assert result.exit_code == 0, result.output
+    assert "stopped during the session" in result.output
+    assert "is still running" not in result.output
+
+
+def test_attached_server_prints_stop_hint_after_agent_exits(fake_studio, monkeypatch):
+    monkeypatch.setattr(start.shutil, "which", lambda _: "/usr/local/bin/claude")
+    monkeypatch.setattr(start, "_claude_flags", lambda *a, **k: [])
+    monkeypatch.setattr(
+        start.subprocess,
+        "run",
+        lambda command, env: SimpleNamespace(returncode = 0),
+    )
+
+    result = CliRunner().invoke(start.start_app, ["claude"])
+
+    assert result.exit_code == 0, result.output
+    assert f"Unsloth ready at {BASE} · model {MODEL['id']}\n" in result.output
+    assert f"Unsloth Studio is still running at {BASE}." in result.output
+    assert "Stop it with: unsloth studio stop\n" in result.output
+
+
+def test_no_launch_recipe_does_not_print_stop_hint(fake_studio):
+    result = CliRunner().invoke(start.start_app, ["claude", "--no-launch"])
+    assert result.exit_code == 0, result.output
+    assert "is still running" not in result.output
+
+
+def test_nonzero_agent_exit_notes_code_before_stop_hint(fake_studio, monkeypatch):
+    monkeypatch.setattr(start.shutil, "which", lambda _: "/usr/local/bin/claude")
+    monkeypatch.setattr(start, "_claude_flags", lambda *a, **k: [])
+    monkeypatch.setattr(
+        start.subprocess,
+        "run",
+        lambda command, env: SimpleNamespace(returncode = 3),
+    )
+
+    result = CliRunner().invoke(start.start_app, ["claude"])
+
+    assert result.exit_code == 3
+    assert "The agent exited with code 3." in result.output
+    assert f"Unsloth Studio is still running at {BASE}." in result.output
+
+
+def test_redacted_log_tail_strips_minted_keys(tmp_path):
+    log = tmp_path / "server.log"
+    log.write_text(
+        "booting\nUNSLOTH_START_API_KEY: sk-unsloth-feedfacefeedface\nerror: load failed\n",
+        encoding = "utf-8",
+    )
+
+    tail = start._redacted_log_tail(log)
+
+    assert "sk-unsloth-feedfacefeedface" not in tail
+    assert "sk-unsloth-[redacted]" in tail
+    assert "error: load failed" in tail
+
+
+def test_startup_failure_output_redacts_minted_key(monkeypatch, tmp_path, capsys):
+    monkeypatch.setattr(start.tempfile, "gettempdir", lambda: str(tmp_path))
+    fake = SimpleNamespace(pid = 4242, poll = lambda: 1)
+
+    def fake_popen(command, **kwargs):
+        # The child prints the early key marker, then dies before it is ready.
+        kwargs["stdout"].write(b"UNSLOTH_START_API_KEY: sk-unsloth-secretsecret\nload failed\n")
+        kwargs["stdout"].flush()
+        return fake
+
+    monkeypatch.setattr(start.subprocess, "Popen", fake_popen)
+
+    with pytest.raises(start.typer.Exit):
+        start._start_studio_server(BASE, "owner/model-GGUF", start.LoadOptions())
+
+    err = capsys.readouterr().err
+    assert "stopped before it was ready" in err
+    assert "sk-unsloth-secretsecret" not in err
+    assert "sk-unsloth-[redacted]" in err
 
 
 def test_codex_preflight_failure_tears_down_auto_served(fake_studio, monkeypatch):
@@ -1805,7 +2596,12 @@ def test_codex_preflight_failure_tears_down_auto_served(fake_studio, monkeypatch
     started = {}
     fake = SimpleNamespace(pid = 999, poll = lambda: None)
 
-    def fake_start(base, model, load):
+    def fake_start(
+        base,
+        model,
+        load,
+        server_options = None,
+    ):
         started.update(base = base, model = model)
         start._auto_served_server = fake
         return fake
@@ -1900,7 +2696,12 @@ def test_auto_serve_normalizes_portless_url(fake_studio, monkeypatch):
     started = {}
     fake = SimpleNamespace(pid = 999, poll = lambda: None)
 
-    def fake_start(base, model, load):
+    def fake_start(
+        base,
+        model,
+        load,
+        server_options = None,
+    ):
         started["base"] = base
         start._auto_served_server = fake
         return fake
@@ -2092,8 +2893,7 @@ def test_write_opencode_config_fresh(tmp_path):
         MODEL["id"]: {"name": MODEL["id"], "limit": {"context": 131072, "output": 8192}}
     }
     assert config["model"] == f"{start._OPENCODE_PROVIDER}/{MODEL['id']}"
-    # The overlay never writes disabled_providers; the dedicated provider id is one a
-    # user's disable list would not target, so nothing needs re-enabling.
+    # Provider filters belong to the launch-time inline overlay, not this config writer.
     assert "disabled_providers" not in config
     # Compaction buffer scaled to ~10% of the window (compact near 90%).
     assert config["compaction"] == {"auto": True, "reserved": 131072 // 10}
@@ -2134,6 +2934,109 @@ def test_write_opencode_config_keeps_foreign_disabled_providers(tmp_path):
     assert config["disabled_providers"] == ["openai", "gemini"]
 
 
+def test_write_opencode_config_as_subagent_preserves_parent_model(tmp_path):
+    path = tmp_path / "opencode.json"
+    path.write_text(
+        json.dumps(
+            {
+                "model": "anthropic/claude-sonnet-4-5",
+                "small_model": "anthropic/claude-haiku-4-5",
+                "compaction": {"auto": False},
+            }
+        )
+    )
+    local = {**MODEL, "id": MODEL["id"] + ":UD-Q4_K_XL"}
+    start.write_opencode_config(
+        BASE,
+        "sk-unsloth-abc",
+        local,
+        path,
+        as_subagent = True,
+    )
+    config = json.loads(path.read_text())
+    assert config["model"] == "anthropic/claude-sonnet-4-5"
+    assert config["small_model"] == "anthropic/claude-haiku-4-5"
+    assert config["compaction"] == {"auto": False}
+    agent = config["agent"]["unsloth"]
+    assert agent["mode"] == "subagent"
+    assert agent["model"] == f"{start._OPENCODE_PROVIDER}/{local['id']}"
+    assert "local agent" in agent["description"].lower()
+    assert local["id"] in config["provider"][start._OPENCODE_PROVIDER]["models"]
+
+
+def test_opencode_subagent_inline_keeps_parent_provider_filters(monkeypatch, tmp_path):
+    config_path = tmp_path / "opencode.json"
+    inherited = {"theme": "tokyonight"}
+    monkeypatch.setenv("OPENCODE_CONFIG_CONTENT", json.dumps(inherited))
+    monkeypatch.setattr(start, "_which_with_install_dirs", lambda _: "/usr/bin/opencode")
+    captured = {}
+
+    def run(command, **kwargs):
+        captured["command"] = command
+        captured.update(kwargs)
+        return SimpleNamespace(
+            returncode = 0,
+            stdout = json.dumps(
+                {
+                    "enabled_providers": ["opencode-go"],
+                    "disabled_providers": ["ollama", start._OPENCODE_PROVIDER],
+                    "subagent_depth": 0,
+                }
+            ),
+            stderr = "",
+        )
+
+    monkeypatch.setattr(start.subprocess, "run", run)
+    permission = {"edit": "allow"}
+    inline = start._opencode_subagent_inline_config(config_path, permission)
+
+    assert captured["command"] == ["/usr/bin/opencode", "debug", "config"]
+    assert captured["env"]["OPENCODE_CONFIG"] == str(config_path)
+    assert inline == {
+        "theme": "tokyonight",
+        "enabled_providers": ["opencode-go", start._OPENCODE_PROVIDER],
+        "disabled_providers": ["ollama"],
+        "subagent_depth": 1,
+        "permission": permission,
+    }
+
+
+def test_opencode_subagent_inline_preserves_positive_depth(monkeypatch, tmp_path):
+    monkeypatch.setattr(start, "_which_with_install_dirs", lambda _: "/usr/bin/opencode")
+    monkeypatch.setattr(
+        start.subprocess,
+        "run",
+        lambda *args, **kwargs: SimpleNamespace(
+            returncode = 0,
+            stdout = json.dumps({"subagent_depth": 3}),
+            stderr = "",
+        ),
+    )
+
+    inline = start._opencode_subagent_inline_config(tmp_path / "opencode.json", {})
+
+    assert inline["subagent_depth"] == 3
+
+
+def test_opencode_subagent_inline_merges_inherited_filters_without_binary(monkeypatch, tmp_path):
+    monkeypatch.setenv(
+        "OPENCODE_CONFIG_CONTENT",
+        json.dumps(
+            {
+                "enabled_providers": ["opencode-go"],
+                "disabled_providers": ["ollama", start._OPENCODE_PROVIDER],
+            }
+        ),
+    )
+    monkeypatch.setattr(start, "_which_with_install_dirs", lambda _: None)
+
+    inline = start._opencode_subagent_inline_config(tmp_path / "opencode.json", {})
+
+    assert inline["enabled_providers"] == ["opencode-go", start._OPENCODE_PROVIDER]
+    assert inline["disabled_providers"] == ["ollama"]
+    assert inline["subagent_depth"] == 1
+
+
 def _opencode_inline_config(output: str) -> dict:
     # --no-launch prints OPENCODE_CONFIG_CONTENT as a POSIX `export NAME=<shell-quoted>`
     # line on Unix/WSL and a PowerShell `$env:NAME = "<escaped>"` line on native Windows;
@@ -2222,6 +3125,130 @@ def test_connect_opencode_no_launch(fake_studio, tmp_path):
     assert not any(c[1].endswith("/api/inference/status") for c in fake_studio)
 
 
+def test_connect_opencode_as_subagent_preserves_cloud_parent(fake_studio, tmp_path, monkeypatch):
+    monkeypatch.setattr(start, "_opencode_subagent_inline_config", lambda path, permission: {})
+    result = CliRunner().invoke(
+        start.start_app,
+        [
+            "opencode",
+            "--as-subagent",
+            "--no-launch",
+            "--model",
+            MODEL["id"] + ":UD-Q4_K_XL",
+        ],
+    )
+    assert result.exit_code == 0, result.output
+    assert _launch_command(result.output) == ["opencode"]
+    expected_model = f"{start._OPENCODE_PROVIDER}/{MODEL['id']}:UD-Q4_K_XL"
+    # The agent rides in the inline overlay; nothing else comes from the empty base.
+    assert _opencode_inline_config(result.output) == {
+        "agent": {
+            "unsloth": {
+                "description": start._SUBAGENT_DESCRIPTION,
+                "mode": "subagent",
+                "model": expected_model,
+                "prompt": start._SUBAGENT_INSTRUCTIONS,
+            }
+        }
+    }
+    path = tmp_path / "agents" / "opencode-subagent" / "opencode.json"
+    config = json.loads(path.read_text())
+    assert "model" not in config
+    assert "small_model" not in config
+    assert "compaction" not in config
+    agent = config["agent"]["unsloth"]
+    assert agent["model"] == expected_model
+    assert "Unsloth is available as @unsloth and in /models." in result.output
+
+
+def test_claude_subagent_allowed_tools_precede_forwarded_delimiter(fake_studio):
+    # A forwarded `--` makes everything after it positional; the tool pre-approval
+    # must be parsed as an option, so it rides before ctx.args.
+    result = CliRunner().invoke(
+        start.start_app,
+        ["claude", "--as-subagent", "--no-launch", "--", "--resume", "abc123"],
+    )
+    assert result.exit_code == 0, result.output
+    command = _launch_command(result.output)
+    assert command.index("--allowedTools") < command.index("--resume")
+
+
+def test_opencode_subagent_installs_binary_before_filter_inspection(fake_studio, monkeypatch):
+    # The effective-config inspection needs the opencode binary; a first launch must
+    # offer the install before building the overlay, or a global allowlist read only
+    # after _launch installs OpenCode would filter out the new provider.
+    installed = {}
+    monkeypatch.setattr(
+        start,
+        "_which_with_install_dirs",
+        lambda name: "/usr/local/bin/opencode" if installed.get("done") else None,
+    )
+
+    def install(name, hint):
+        installed["done"] = True
+        installed["name"] = name
+        return "/usr/local/bin/opencode"
+
+    monkeypatch.setattr(start, "_install_agent", install)
+    inspected = {}
+
+    def inline(path, permission):
+        inspected["binary"] = start._which_with_install_dirs("opencode")
+        return {}
+
+    monkeypatch.setattr(start, "_opencode_subagent_inline_config", inline)
+    monkeypatch.setattr(start, "_run", lambda *a, **k: None)
+
+    result = CliRunner().invoke(start.start_app, ["opencode", "--as-subagent"])
+
+    assert result.exit_code == 0, result.output
+    assert installed["name"] == "opencode"
+    assert inspected["binary"] == "/usr/local/bin/opencode"
+
+
+def test_opencode_subagent_pins_agent_in_inline_overlay(fake_studio, monkeypatch):
+    # A project opencode.json outranks the session file, so the agent must ride in
+    # OPENCODE_CONFIG_CONTENT where a repo's own agent.unsloth cannot field-merge over it.
+    monkeypatch.setattr(start, "_opencode_subagent_inline_config", lambda path, permission: {})
+    result = CliRunner().invoke(
+        start.start_app,
+        ["opencode", "--as-subagent", "--no-launch", "--model", MODEL["id"] + ":UD-Q4_K_XL"],
+    )
+    assert result.exit_code == 0, result.output
+    agent = _opencode_inline_config(result.output)["agent"]["unsloth"]
+    assert agent["mode"] == "subagent"
+    assert agent["model"] == f"{start._OPENCODE_PROVIDER}/{MODEL['id']}:UD-Q4_K_XL"
+    assert agent["prompt"] == start._SUBAGENT_INSTRUCTIONS
+    assert agent["description"] == start._SUBAGENT_DESCRIPTION
+
+
+def test_connect_opencode_subagent_yolo_no_launch_stays_append_safe(fake_studio, monkeypatch):
+    monkeypatch.setattr(start, "_opencode_supports_native_auto", lambda: True)
+    captured = {}
+
+    def inline(path, permission):
+        captured["permission"] = permission
+        return {"permission": permission}
+
+    monkeypatch.setattr(start, "_opencode_subagent_inline_config", inline)
+    result = CliRunner().invoke(
+        start.start_app,
+        ["opencode", "--as-subagent", "--no-launch", "--yolo"],
+    )
+
+    assert result.exit_code == 0, result.output
+    assert _launch_command(result.output) == ["opencode"]
+    assert "--auto" not in result.output
+    assert captured["permission"] == {
+        "edit": "allow",
+        "bash": "allow",
+        "webfetch": "allow",
+        "task": "allow",
+        "external_directory": {"*": "allow"},
+    }
+    assert _opencode_inline_config(result.output)["permission"] == captured["permission"]
+
+
 # ── Hermes (OpenAI /v1/chat/completions, key via env) ────────────────
 
 
@@ -2364,6 +3391,39 @@ def test_connect_pi_no_launch(fake_studio, tmp_path):
     assert not any(c[1].endswith("/api/inference/status") for c in fake_studio)
 
 
+def test_connect_pi_as_subagent_preserves_cloud_parent(fake_studio, tmp_path):
+    result = CliRunner().invoke(
+        start.start_app,
+        [
+            "pi",
+            "--as-subagent",
+            "--no-launch",
+            "--model",
+            MODEL["id"] + ":UD-Q4_K_XL",
+        ],
+    )
+    assert result.exit_code == 0, result.output
+    command = _launch_command(result.output)
+    assert command[:2] == ["pi", "--extension"]
+    assert command[2].endswith("unsloth_cli/pi_subagent.ts")
+    assert "--provider" not in command
+    assert "--model" not in command
+    assert "PI_CODING_AGENT_DIR" not in result.output
+    assert "export HOME=" not in result.output
+    assert "UNSLOTH_PI_SUBAGENT_API_KEY" not in result.output
+    assert "sk-unsloth-feedfacefeedface" not in result.output
+    config_path = tmp_path / "agents" / "pi-subagent" / "subagent.json"
+    _assert_env_set(result.output, "UNSLOTH_PI_SUBAGENT_CONFIG", str(config_path))
+    assert json.loads(config_path.read_text()) == {
+        "baseUrl": f"{BASE}/v1",
+        "apiKey": "sk-unsloth-feedfacefeedface",
+        "model": MODEL["id"] + ":UD-Q4_K_XL",
+        "contextWindow": 4096,
+        "maxTokens": 1024,
+    }
+    assert "Ask Pi to spawn an Unsloth or local agent." in result.output
+
+
 def test_connect_pi_no_launch_windows_relocates_userprofile(fake_studio, tmp_path, monkeypatch):
     # On native Windows Node resolves ~/.pi via USERPROFILE, not HOME, so the session
     # must point USERPROFILE at the relocated home or Pi reads the user's real ~/.pi.
@@ -2907,6 +3967,27 @@ def test_opencode_non_yolo_flips_only_explicit_allow(tmp_path):
     assert session == {}  # a non-yolo session carries no permission inline
 
 
+def test_opencode_subagent_non_yolo_clears_yolo_task_permission(tmp_path):
+    path = tmp_path / "opencode.json"
+    start.write_opencode_config(
+        BASE,
+        "sk-unsloth-abc",
+        MODEL,
+        path,
+        yolo = True,
+        as_subagent = True,
+    )
+    start.write_opencode_config(
+        BASE,
+        "sk-unsloth-abc",
+        MODEL,
+        path,
+        as_subagent = True,
+    )
+
+    assert json.loads(path.read_text())["permission"]["task"] == "ask"
+
+
 def test_opencode_non_yolo_leaves_string_permission(tmp_path):
     # A global string rule ("deny") is a user-managed catch-all; leave it untouched and
     # carry no inline override.
diff --git a/unsloth_cli/tests/test_studio_run_parallel_flag.py b/unsloth_cli/tests/test_studio_run_parallel_flag.py
index 558b268a4d..b2fc421359 100644
--- a/unsloth_cli/tests/test_studio_run_parallel_flag.py
+++ b/unsloth_cli/tests/test_studio_run_parallel_flag.py
@@ -170,13 +170,24 @@ def _install_reexec_capture(monkeypatch, *, platform):
 
     monkeypatch.setattr(sys, "platform", platform)
 
+    def capture(kind, argv):
+        captured.append(
+            {
+                "kind": kind,
+                "argv": list(argv),
+                "start_api_key_marker": studio_mod.os.environ.get(
+                    studio_mod._START_API_KEY_MARKER_ENV
+                ),
+            }
+        )
+
     def fake_execvp(file, argv):
-        captured.append({"kind": "execvp", "argv": list(argv)})
+        capture("execvp", argv)
         raise _ExecCaptured(argv)
 
     class _FakePopen:
         def __init__(self, argv, *a, **kw):
-            captured.append({"kind": "popen", "argv": list(argv)})
+            capture("popen", argv)
             self._argv = argv
 
         def wait(self):
@@ -235,6 +246,65 @@ def test_reexec_forwards_parallel_all_aliases(monkeypatch, flag, value):
     ), f"{flag} {value} was dropped on re-exec; argv = {argv}"
 
 
+@pytest.mark.parametrize("platform", ["linux", "darwin", "win32"])
+def test_reexec_hands_off_start_api_key_marker_out_of_band(monkeypatch, platform):
+    """A new child receives the marker while an old child sees no unknown flag."""
+    result, captured = _invoke_run(
+        monkeypatch,
+        _BASE + ["--start-api-key-marker"],
+        platform = platform,
+    )
+    assert len(captured) == 1, result.output
+    assert "--start-api-key-marker" not in captured[0]["argv"]
+    assert captured[0]["start_api_key_marker"] == "1"
+
+
+def test_reexeced_child_consumes_start_api_key_marker_env(monkeypatch):
+    """A supported child consumes the handoff before starting descendants."""
+    studio_mod = _load_run_command()
+    monkeypatch.setenv(studio_mod._START_API_KEY_MARKER_ENV, "1")
+
+    inherited = studio_mod._consume_start_api_key_marker_env()
+
+    assert inherited is True
+    assert studio_mod._START_API_KEY_MARKER_ENV not in studio_mod.os.environ
+
+
+def test_run_default_sets_tool_call_env(monkeypatch):
+    """Plain `unsloth run` enables healing and nudging via the inherited env
+    (written before the re-exec so the child server picks them up at import)."""
+    studio_mod = _load_run_command()
+    monkeypatch.delenv("UNSLOTH_DISABLE_TOOL_CALL_HEALING", raising = False)
+    monkeypatch.delenv("UNSLOTH_TOOL_CALL_NUDGE", raising = False)
+    _invoke_run(monkeypatch, _BASE)
+    assert studio_mod.os.environ["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] == "0"
+    assert studio_mod.os.environ["UNSLOTH_TOOL_CALL_NUDGE"] == "1"
+
+
+def test_run_disable_flags_set_tool_call_env(monkeypatch):
+    """`--disable-tool-call-healing --disable-tool-call-nudging` flips both env vars."""
+    studio_mod = _load_run_command()
+    monkeypatch.delenv("UNSLOTH_DISABLE_TOOL_CALL_HEALING", raising = False)
+    monkeypatch.delenv("UNSLOTH_TOOL_CALL_NUDGE", raising = False)
+    _invoke_run(
+        monkeypatch,
+        _BASE + ["--disable-tool-call-healing", "--disable-tool-call-nudging"],
+    )
+    assert studio_mod.os.environ["UNSLOTH_DISABLE_TOOL_CALL_HEALING"] == "1"
+    assert studio_mod.os.environ["UNSLOTH_TOOL_CALL_NUDGE"] == "0"
+
+
+@pytest.mark.parametrize("inherited", ["0", "false", "False", "no", ""])
+def test_run_omitted_flag_respects_inherited_env(monkeypatch, inherited):
+    """When the flag is omitted, a value the parent set (e.g. `unsloth start`) wins
+    instead of being reset to the default."""
+    studio_mod = _load_run_command()
+    monkeypatch.setenv("UNSLOTH_TOOL_CALL_NUDGE", inherited)
+    monkeypatch.delenv("UNSLOTH_DISABLE_TOOL_CALL_HEALING", raising = False)
+    _invoke_run(monkeypatch, _BASE)
+    assert studio_mod.os.environ["UNSLOTH_TOOL_CALL_NUDGE"] == inherited
+
+
 @pytest.mark.parametrize("platform", ["linux", "darwin", "win32"])
 def test_reexec_argv_is_consistent_across_platforms(monkeypatch, platform):
     """Linux/Darwin (execvp) and Windows (Popen) must build the same argv."""