diff --git a/README.md b/README.md
index 3d2810fae5..9656f1c634 100644
--- a/README.md
+++ b/README.md
@@ -30,28 +30,119 @@
 
 ## Quick Start
 
-### One-command setup
+### Prerequisites
+
+| Requirement | Linux / WSL | Windows |
+|---|---|---|
+| **GPU** | NVIDIA GPU with working driver | NVIDIA GPU with working driver |
+| **Python** | 3.11 – 3.13 | 3.11 – 3.13 |
+| **Git** | Pre-installed on most distros | Auto-installed by setup script (via `winget`) |
+| **CMake** | Pre-installed or `sudo apt install cmake` | Auto-installed by setup script (via `winget`) |
+| **C++ compiler** | `build-essential` (auto-detected) | Visual Studio Build Tools 2022 (auto-installed by setup script) |
+| **CUDA Toolkit** | Optional — setup auto-detects `nvcc` | Auto-installed by setup script (version matched to driver) |
+
+> [!NOTE]
+> On **WSL**, the setup script will also run `sudo apt-get install build-essential cmake curl git libcurl4-openssl-dev` so that GGUF export works in non-interactive subprocesses. You may be prompted for your password during setup.
+
+---
+
+### Linux / Windows WSL
 
 ```bash
+# 1. Clone the repo
+git clone https://github.com/unslothai/unsloth-studio.git
+cd unsloth-studio
+
+# 2. Run setup (installs Node, builds frontend, creates .venv, builds llama.cpp)
 bash setup.sh
+
+# 3. Open a new terminal (or source your shell rc), then launch:
+unsloth-studio -H 0.0.0.0 -p 8000
 ```
 
-This script will:
-1. Install **Node.js ≥ 20** via nvm (if needed)
-2. Build the frontend to `studio/frontend/dist`
-3. Create a Python virtual environment and install all dependencies (including `unsloth`)
-4. Register a convenient `unsloth-ui` shell alias
+<details>
+<summary><b>What does <code>setup.sh</code> do?</b></summary>
 
-### Launch the studio
+1. Installs **Node.js ≥ 20** via nvm (if needed)
+2. Runs `npm install && npm run build` for the React frontend
+3. Detects the best **Python 3.11 – 3.13** on your system and creates a `.venv`
+4. Installs all Python dependencies (unsloth, PyTorch with CUDA, triton kernels, etc.)
+5. On **WSL**: pre-installs build dependencies via `apt-get`
+6. Clones and builds **llama.cpp** at `~/.unsloth/llama.cpp` (GPU-accelerated if CUDA is found)
+7. Registers `unsloth-studio` and `unsloth-ui` shell aliases in your shell rc (bash, zsh, fish, or ksh)
+
+</details>
+
+---
+
+### Windows (Native)
+
+> [!IMPORTANT]
+> Requires an **NVIDIA GPU** — CPU-only machines are not supported on Windows.
+
+```powershell
+# 1. Clone the repo
+git clone https://github.com/unslothai/unsloth-studio.git
+cd unsloth-studio
+
+# 2. Run setup (Right-click → "Run with PowerShell", or from a terminal):
+.\setup.bat
+# Or directly:
+powershell -ExecutionPolicy Bypass -File setup.ps1
+```
+
+After setup completes, **open a new terminal** and run:
+
+```powershell
+# PowerShell
+unsloth-studio -H 0.0.0.0 -p 8000
+
+# Or cmd.exe
+unsloth-studio -H 0.0.0.0 -p 8000
+```
+
+<details>
+<summary><b>What does <code>setup.ps1</code> do?</b></summary>
+
+1. Enables **Windows Long Paths** (required for deep dependency trees — prompts for UAC)
+2. Auto-installs missing system tools via `winget`: **Git**, **CMake**, **Visual Studio Build Tools 2022**, **CUDA Toolkit** (version-matched to your driver), **Node.js LTS**, **Python 3.12**, **OpenSSL dev**
+3. Builds the React frontend (`npm install && npm run build`)
+4. Creates a `.venv` and installs all Python dependencies (including CUDA-enabled PyTorch from the official index)
+5. Sets `TORCHINDUCTOR_CACHE_DIR=C:\tc` to avoid Windows MAX_PATH issues with Triton
+6. Clones and builds **llama.cpp** at `%USERPROFILE%\.unsloth\llama.cpp` with CUDA + Visual Studio
+7. Registers `unsloth-studio` and `unsloth-ui` commands in both PowerShell profile and `cmd.exe` (via batch files on PATH)
+
+</details>
+
+---
+
+### Google Colab
+
+The setup script auto-detects Colab and installs everything into the existing system Python (no venv):
+
+```python
+!bash setup.sh
+```
+
+---
+
+### Launching the Studio
+
+After setup on any platform, the command is the same:
 
 ```bash
-# After setup, open a new terminal (or source ~/.bashrc), then inside your working directory:
-unsloth-ui -H 0.0.0.0 -p 8000
+unsloth-studio -H 0.0.0.0 -p 8000
 ```
 
-On **first launch**, a one-time setup token is printed to the console. Use it in the browser to create your admin account.
+| Flag | Description |
+|---|---|
+| `-H` / `--host` | Bind address (`0.0.0.0` for all interfaces, `127.0.0.1` for local only) |
+| `-p` / `--port` | Port number (default: `8000`) |
 
-As this repo is in continuous development, please make sure to run the setup.sh file everytime you pull new changes from the repo.
+On **first launch**, a one-time setup token is printed to the console. Open the URL shown in your browser and use this token to create your admin account.
+
+> [!TIP]
+> This repo is in active development. After pulling new changes, **always re-run the setup script** (`bash setup.sh` or `.\setup.bat`) to pick up dependency and build updates.
 
 ## API Reference
 
@@ -105,7 +196,10 @@ new-ui-prototype/
 │       ├── export.py
 │       ├── ui.py
 │       └── studio.py
-├── setup.sh                   # One-command bootstrap script
+├── setup.sh                   # Bootstrap script (Linux / WSL / Colab)
+├── setup.ps1                  # Bootstrap script (Windows native)
+├── setup.bat                  # Wrapper to launch setup.ps1 via double-click
+├── install_python_stack.py    # Cross-platform Python dependency installer
 └── studio/
     ├── backend/
     │   ├── main.py            # FastAPI app & middleware
diff --git a/install_python_stack.py b/install_python_stack.py
new file mode 100644
index 0000000000..c9b73034b4
--- /dev/null
+++ b/install_python_stack.py
@@ -0,0 +1,245 @@
+#!/usr/bin/env python3
+"""Cross-platform Python dependency installer for Unsloth Studio.
+
+Called by both setup.sh (Linux / WSL) and setup.ps1 (Windows) after the
+virtual environment is already activated.  Expects `pip` and `python` on
+PATH to point at the venv.
+"""
+
+from __future__ import annotations
+
+import os
+import subprocess
+import sys
+import tempfile
+import urllib.request
+from pathlib import Path
+
+IS_WINDOWS = sys.platform == "win32"
+
+# ── Paths ──────────────────────────────────────────────────────────────
+SCRIPT_DIR = Path(__file__).resolve().parent
+REQ_ROOT = SCRIPT_DIR / "studio" / "backend" / "requirements"
+SINGLE_ENV = REQ_ROOT / "single-env"
+CONSTRAINTS = SINGLE_ENV / "constraints.txt"
+
+# ── Color support ──────────────────────────────────────────────────────
+
+def _enable_colors() -> bool:
+    """Try to enable ANSI color support. Returns True if available."""
+    if not hasattr(sys.stdout, "fileno"):
+        return False
+    try:
+        if not os.isatty(sys.stdout.fileno()):
+            return False
+    except Exception:
+        return False
+    if IS_WINDOWS:
+        try:
+            import ctypes
+            kernel32 = ctypes.windll.kernel32
+            # Enable ENABLE_VIRTUAL_TERMINAL_PROCESSING (0x0004) on stdout
+            handle = kernel32.GetStdHandle(-11)  # STD_OUTPUT_HANDLE
+            mode = ctypes.c_ulong()
+            kernel32.GetConsoleMode(handle, ctypes.byref(mode))
+            kernel32.SetConsoleMode(handle, mode.value | 0x0004)
+            return True
+        except Exception:
+            return False
+    return True  # Unix terminals support ANSI by default
+
+_HAS_COLOR = _enable_colors()
+
+def _green(msg: str) -> str:
+    return f"\033[92m{msg}\033[0m" if _HAS_COLOR else msg
+
+def _cyan(msg: str) -> str:
+    return f"\033[96m{msg}\033[0m" if _HAS_COLOR else msg
+
+def _red(msg: str) -> str:
+    return f"\033[91m{msg}\033[0m" if _HAS_COLOR else msg
+
+
+def run(label: str, cmd: list[str], *, quiet: bool = True) -> None:
+    """Run a command; on failure print output and exit."""
+    print(_cyan(f"   {label}..."))
+    result = subprocess.run(
+        cmd,
+        stdout=subprocess.PIPE if quiet else None,
+        stderr=subprocess.STDOUT if quiet else None,
+    )
+    if result.returncode != 0:
+        print(_red(f"❌ {label} failed (exit code {result.returncode}):"))
+        if result.stdout:
+            print(result.stdout.decode(errors="replace"))
+        sys.exit(result.returncode)
+
+
+# Packages to skip on Windows (require special build steps)
+WINDOWS_SKIP_PACKAGES = {"open_spiel"}
+
+
+def _filter_requirements(req: Path, skip: set[str]) -> Path:
+    """Return a temp copy of a requirements file with certain packages removed."""
+    lines = req.read_text(encoding="utf-8").splitlines(keepends=True)
+    filtered = [
+        line for line in lines
+        if not any(line.strip().lower().startswith(pkg) for pkg in skip)
+    ]
+    tmp = tempfile.NamedTemporaryFile(
+        mode="w", suffix=".txt", delete=False, encoding="utf-8",
+    )
+    tmp.writelines(filtered)
+    tmp.close()
+    return Path(tmp.name)
+
+
+def pip_install(
+    label: str,
+    *args: str,
+    req: Path | None = None,
+    constrain: bool = True,
+) -> None:
+    """Build and run a pip install command."""
+    cmd = [sys.executable, "-m", "pip", "install"]
+    cmd.extend(args)
+    if constrain and CONSTRAINTS.is_file():
+        cmd.extend(["-c", str(CONSTRAINTS)])
+    actual_req = req
+    if req is not None and IS_WINDOWS and WINDOWS_SKIP_PACKAGES:
+        actual_req = _filter_requirements(req, WINDOWS_SKIP_PACKAGES)
+    if actual_req is not None:
+        cmd.extend(["-r", str(actual_req)])
+    try:
+        run(label, cmd)
+    finally:
+        # Clean up temp file if we created one
+        if actual_req is not None and actual_req != req:
+            actual_req.unlink(missing_ok=True)
+
+
+
+def download_file(url: str, dest: Path) -> None:
+    """Download a file using urllib (no curl dependency)."""
+    urllib.request.urlretrieve(url, dest)
+
+
+def patch_package_file(package_name: str, relative_path: str, url: str) -> None:
+    """Download a file from url and overwrite a file inside an installed package."""
+    result = subprocess.run(
+        [sys.executable, "-m", "pip", "show", package_name],
+        capture_output=True, text=True,
+    )
+    if result.returncode != 0:
+        print(_red(f"   ⚠️  Could not find package {package_name}, skipping patch"))
+        return
+
+    location = None
+    for line in result.stdout.splitlines():
+        if line.lower().startswith("location:"):
+            location = line.split(":", 1)[1].strip()
+            break
+
+    if not location:
+        print(_red(f"   ⚠️  Could not determine location of {package_name}"))
+        return
+
+    dest = Path(location) / relative_path
+    print(_cyan(f"   Patching {dest.name} in {package_name}..."))
+    download_file(url, dest)
+
+
+# ── Main install sequence ─────────────────────────────────────────────
+
+def install_python_stack() -> int:
+    print(_cyan("── Installing Python stack ──"))
+
+    # 1. Upgrade pip
+    run("Upgrading pip", [sys.executable, "-m", "pip", "install", "--upgrade", "pip"])
+
+    # 2. Core packages: unsloth-zoo + unsloth
+    pip_install(
+        "Installing unsloth-zoo + unsloth",
+        "--no-cache-dir",
+        req=REQ_ROOT / "base.txt",
+    )
+
+    # 3. Extra dependencies
+    pip_install(
+        "Installing additional unsloth dependencies",
+        "--no-cache-dir",
+        req=REQ_ROOT / "extras.txt",
+    )
+
+    # 4. Overrides (torchao, transformers) — force-reinstall
+    pip_install(
+        "Installing torchao + transformers overrides",
+        "--force-reinstall", "--no-cache-dir",
+        req=REQ_ROOT / "overrides.txt",
+    )
+
+    # 5. Triton kernels (no-deps, from source)
+    pip_install(
+        "Installing triton kernels",
+        "--no-deps", "--no-cache-dir",
+        req=REQ_ROOT / "triton-kernels.txt",
+        constrain=False,
+    )
+
+    # 6. Patch: override llama_cpp.py with fix from unsloth-zoo  feature/llama-cpp-windows-support branch
+    patch_package_file(
+        "unsloth-zoo",
+        os.path.join("unsloth_zoo", "llama_cpp.py"),
+        "https://raw.githubusercontent.com/unslothai/unsloth-zoo/refs/heads/main/unsloth_zoo/llama_cpp.py",
+    )
+
+    # 7a. Patch: override vision.py with fix from unsloth PR #4091
+    patch_package_file(
+        "unsloth",
+        os.path.join("unsloth", "models", "vision.py"),
+        "https://raw.githubusercontent.com/unslothai/unsloth/80e0108a684c882965a02a8ed851e3473c1145ab/unsloth/models/vision.py",
+    )
+
+    # 7b. Patch : override save.py with fix from feature/llama-cpp-windows-support
+    patch_package_file(
+        "unsloth",
+        os.path.join("unsloth", "save.py"),
+        "https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/unsloth/save.py",
+    )
+
+    # 8. Studio dependencies
+    pip_install(
+        "Installing studio dependencies",
+        "--no-cache-dir",
+        req=REQ_ROOT / "studio.txt",
+    )
+
+    # 9. Data-designer dependencies
+    pip_install(
+        "Installing data-designer dependencies",
+        "--no-cache-dir",
+        req=SINGLE_ENV / "data-designer-deps.txt",
+    )
+
+    # 10. Data-designer packages (no-deps to avoid conflicts)
+    pip_install(
+        "Installing data-designer",
+        "--no-cache-dir", "--no-deps",
+        req=SINGLE_ENV / "data-designer.txt",
+    )
+
+    # 11. Patch metadata for single-env compatibility
+    run(
+        "Patching single-env metadata",
+        [sys.executable, str(SINGLE_ENV / "patch_metadata.py")],
+    )
+
+    # 12. Final check
+    run("Running pip check", [sys.executable, "-m", "pip", "check"], quiet=False)
+
+    print(_green("✅ Python dependencies installed"))
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(install_python_stack())
diff --git a/setup.bat b/setup.bat
new file mode 100644
index 0000000000..ef16abd263
--- /dev/null
+++ b/setup.bat
@@ -0,0 +1,2 @@
+@echo off
+powershell -ExecutionPolicy Bypass -File "%~dp0setup.ps1" %*
diff --git a/setup.ps1 b/setup.ps1
new file mode 100644
index 0000000000..8a2ec56033
--- /dev/null
+++ b/setup.ps1
@@ -0,0 +1,964 @@
+#Requires -Version 5.1
+<#
+.SYNOPSIS
+    Full environment setup for Unsloth Studio on Windows (bundled version).
+.DESCRIPTION
+    Always installs Node.js if needed. When running from pip install:
+    skips frontend build (already bundled). When running from git repo:
+    full setup including frontend build.
+    Requires an NVIDIA GPU -- CPU-only machines are not supported.
+.NOTES
+    Usage: powershell -ExecutionPolicy Bypass -File setup.ps1
+#>
+
+$ErrorActionPreference = "Stop"
+$ScriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
+$PackageDir = Split-Path -Parent $ScriptDir
+
+# Detect if running from pip install (no studio/frontend/ dir in repo)
+$FrontendDir = Join-Path $ScriptDir "studio\frontend"
+$IsPipInstall = -not (Test-Path $FrontendDir)
+
+# ─────────────────────────────────────────────
+# Helper functions
+# ─────────────────────────────────────────────
+
+# Reload ALL environment variables from registry.
+# Picks up changes made by installers (winget, msi, etc.) including
+# Path, CUDA_PATH, CUDA_PATH_V*, and any other vars they set.
+function Refresh-Environment {
+    foreach ($level in @('Machine', 'User')) {
+        $vars = [System.Environment]::GetEnvironmentVariables($level)
+        foreach ($key in $vars.Keys) {
+            if ($key -eq 'Path') { continue }
+            Set-Item -Path "Env:$key" -Value $vars[$key] -ErrorAction SilentlyContinue
+        }
+    }
+    $machinePath = [System.Environment]::GetEnvironmentVariable('Path', 'Machine')
+    $userPath = [System.Environment]::GetEnvironmentVariable('Path', 'User')
+    $env:Path = "$machinePath;$userPath"
+}
+
+# Find nvcc on PATH, CUDA_PATH, or standard toolkit dirs.
+# Returns the path to nvcc.exe, or $null if not found.
+function Find-Nvcc {
+    param([string]$MaxVersion = "")
+
+    # If MaxVersion is set, we need to find a toolkit <= that version.
+    # CUDA toolkits install side-by-side under C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.Y\
+
+    $toolkitBase = 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA'
+
+    if ($MaxVersion -and (Test-Path $toolkitBase)) {
+        $drMajor = [int]$MaxVersion.Split('.')[0]
+        $drMinor = [int]$MaxVersion.Split('.')[1]
+
+        # Get all installed CUDA dirs, sorted descending (highest first)
+        $cudaDirs = Get-ChildItem -Directory $toolkitBase | Where-Object {
+            $_.Name -match '^v(\d+)\.(\d+)'
+        } | Sort-Object { [version]($_.Name -replace '^v','') } -Descending
+
+        foreach ($dir in $cudaDirs) {
+            if ($dir.Name -match '^v(\d+)\.(\d+)') {
+                $tkMajor = [int]$Matches[1]; $tkMinor = [int]$Matches[2]
+                $compatible = ($tkMajor -lt $drMajor) -or ($tkMajor -eq $drMajor -and $tkMinor -le $drMinor)
+                if ($compatible) {
+                    $nvcc = Join-Path $dir.FullName 'bin\nvcc.exe'
+                    if (Test-Path $nvcc) {
+                        return $nvcc
+                    }
+                }
+            }
+        }
+
+        # No compatible side-by-side version found
+        return $null
+    }
+
+    # Fallback: no version constraint — pick latest or whatever is available
+
+    # 1. Check nvcc on PATH
+    $cmd = Get-Command nvcc -ErrorAction SilentlyContinue
+    if ($cmd) { return $cmd.Source }
+
+    # 2. Check CUDA_PATH env var
+    $cudaRoot = [Environment]::GetEnvironmentVariable('CUDA_PATH', 'Process')
+    if (-not $cudaRoot) { $cudaRoot = [Environment]::GetEnvironmentVariable('CUDA_PATH', 'Machine') }
+    if (-not $cudaRoot) { $cudaRoot = [Environment]::GetEnvironmentVariable('CUDA_PATH', 'User') }
+    if ($cudaRoot -and (Test-Path (Join-Path $cudaRoot 'bin\nvcc.exe'))) {
+        return (Join-Path $cudaRoot 'bin\nvcc.exe')
+    }
+
+    # 3. Scan standard toolkit directory
+    if (Test-Path $toolkitBase) {
+        $latest = Get-ChildItem -Directory $toolkitBase | Sort-Object Name | Select-Object -Last 1
+        if ($latest -and (Test-Path (Join-Path $latest.FullName 'bin\nvcc.exe'))) {
+            return (Join-Path $latest.FullName 'bin\nvcc.exe')
+        }
+    }
+
+    return $null
+}
+
+# Detect CUDA Compute Capability via nvidia-smi.
+# Returns e.g. "80" for A100 (8.0), "89" for RTX 4090 (8.9), etc.
+# Returns $null if detection fails.
+function Get-CudaComputeCapability {
+    $nvSmi = Get-Command nvidia-smi -ErrorAction SilentlyContinue
+    if (-not $nvSmi) { return $null }
+
+    try {
+        $raw = & nvidia-smi --query-gpu=compute_cap --format=csv,noheader 2>$null
+        if ($LASTEXITCODE -ne 0 -or -not $raw) { return $null }
+
+        # nvidia-smi may return multiple GPUs; take the first one
+        $cap = ($raw -split "`n")[0].Trim()
+        if ($cap -match '^(\d+)\.(\d+)$') {
+            $major = $Matches[1]
+            $minor = $Matches[2]
+            return "$major$minor"
+        }
+    } catch { }
+
+    return $null
+}
+
+# Detect driver's max CUDA version from nvidia-smi and return the highest
+# compatible PyTorch CUDA index tag (e.g. "cu128").
+# PyTorch on Windows ships CPU-only by default from PyPI; CUDA wheels live at
+# https://download.pytorch.org/whl/<tag>. The tag must not exceed the driver's
+# capability: e.g. driver "CUDA Version: 12.9" → cu128 (not cu130).
+function Get-PytorchCudaTag {
+    $nvSmi = Get-Command nvidia-smi -ErrorAction SilentlyContinue
+    if (-not $nvSmi) { return "cu124" }
+
+    try {
+        # 2>&1 | Out-String merges stderr into stdout then converts to a single
+        # string.  Plain 2>$null doesn't fully suppress stderr in PS 5.1 —
+        # ErrorRecord objects leak into $output and break the -match.
+        $output = & nvidia-smi 2>&1 | Out-String
+        if ($output -match 'CUDA Version:\s+(\d+)\.(\d+)') {
+            $major = [int]$Matches[1]
+            $minor = [int]$Matches[2]
+            # PyTorch 2.10 offers: cu124, cu126, cu128, cu130
+            if ($major -ge 13) { return "cu130" }
+            if ($major -eq 12 -and $minor -ge 8) { return "cu128" }
+            if ($major -eq 12 -and $minor -ge 6) { return "cu126" }
+            return "cu124"
+        }
+    } catch { }
+
+    return "cu124"
+}
+
+# Find Visual Studio Build Tools for cmake -G flag.
+# Strategy: (1) vswhere, (2) scan filesystem (handles broken vswhere registration).
+# Returns @{ Generator = "Visual Studio 17 2022"; InstallPath = "C:\..."; Source = "..." } or $null.
+function Find-VsBuildTools {
+    $map = @{ '2022' = '17'; '2019' = '16'; '2017' = '15' }
+
+    # --- Try vswhere first (works when VS is properly registered) ---
+    $vsw = "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe"
+    if (Test-Path $vsw) {
+        $info = & $vsw -latest -requires Microsoft.VisualStudio.Component.VC.Tools.x86.x64 -property catalog_productLineVersion 2>$null
+        $path = & $vsw -latest -requires Microsoft.VisualStudio.Component.VC.Tools.x86.x64 -property installationPath 2>$null
+        if ($info -and $path) {
+            $y = $info.Trim()
+            $n = $map[$y]
+            if ($n) {
+                return @{ Generator = "Visual Studio $n $y"; InstallPath = $path.Trim(); Source = 'vswhere' }
+            }
+        }
+    }
+
+    # --- Scan filesystem (handles broken vswhere registration after winget cycles) ---
+    $roots = @($env:ProgramFiles, ${env:ProgramFiles(x86)})
+    $editions = @('BuildTools', 'Community', 'Professional', 'Enterprise')
+    $years = @('2022', '2019', '2017')
+
+    foreach ($y in $years) {
+        foreach ($r in $roots) {
+            foreach ($ed in $editions) {
+                $candidate = Join-Path $r "Microsoft Visual Studio\$y\$ed"
+                if (Test-Path $candidate) {
+                    $vcDir = Join-Path $candidate "VC\Tools\MSVC"
+                    if (Test-Path $vcDir) {
+                        $cl = Get-ChildItem -Path $vcDir -Filter "cl.exe" -Recurse -ErrorAction SilentlyContinue | Select-Object -First 1
+                        if ($cl) {
+                            $n = $map[$y]
+                            if ($n) {
+                                return @{ Generator = "Visual Studio $n $y"; InstallPath = $candidate; Source = "filesystem ($ed)"; ClExe = $cl.FullName }
+                            }
+                        }
+                    }
+                }
+            }
+        }
+    }
+
+    return $null
+}
+
+# ─────────────────────────────────────────────
+# Banner
+# ─────────────────────────────────────────────
+Write-Host "+==============================================+" -ForegroundColor Green
+Write-Host "|       Unsloth Studio Setup (Windows)         |" -ForegroundColor Green
+Write-Host "+==============================================+" -ForegroundColor Green
+
+# ==========================================================================
+#  PHASE 1: System-level prerequisites (winget installs, env vars)
+#  All heavy system tool installs happen here BEFORE touching Python.
+# ==========================================================================
+
+# ============================================
+# 1a. GPU requirement check
+# ============================================
+$HasNvidiaSmi = $null -ne (Get-Command nvidia-smi -ErrorAction SilentlyContinue)
+if (-not $HasNvidiaSmi) {
+    Write-Host ""
+    Write-Host "[ERROR] Unsloth Studio requires an NVIDIA GPU." -ForegroundColor Red
+    Write-Host "        CPU-only machines are not supported." -ForegroundColor Red
+    Write-Host ""
+    Write-Host "        If you have an NVIDIA GPU, ensure the driver is installed:" -ForegroundColor Yellow
+    Write-Host "        https://www.nvidia.com/Download/index.aspx" -ForegroundColor Yellow
+    exit 1
+}
+Write-Host "[OK] NVIDIA GPU detected" -ForegroundColor Green
+
+# ============================================
+# 1a.5. Windows Long Paths (required for deep node_modules / Python paths)
+# ============================================
+$LongPathsEnabled = $false
+try {
+    $regVal = Get-ItemProperty -Path "HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -ErrorAction SilentlyContinue
+    if ($regVal -and $regVal.LongPathsEnabled -eq 1) {
+        $LongPathsEnabled = $true
+    }
+} catch {}
+
+if ($LongPathsEnabled) {
+    Write-Host "[OK] Windows Long Paths enabled" -ForegroundColor Green
+} else {
+    Write-Host "Windows Long Paths not enabled (required for Triton compilation and deep dependency paths)." -ForegroundColor Yellow
+    Write-Host "   Requesting admin access to fix..." -ForegroundColor Yellow
+    try {
+        # Spawn an elevated process to set the registry key (triggers UAC prompt)
+        $proc = Start-Process -FilePath "reg.exe" `
+            -ArgumentList 'add "HKLM\SYSTEM\CurrentControlSet\Control\FileSystem" /v LongPathsEnabled /t REG_DWORD /d 1 /f' `
+            -Verb RunAs -Wait -PassThru -ErrorAction Stop
+        if ($proc.ExitCode -eq 0) {
+            $LongPathsEnabled = $true
+            Write-Host "[OK] Windows Long Paths enabled (via UAC)" -ForegroundColor Green
+        } else {
+            Write-Host "[WARN] Failed to enable Long Paths (exit code: $($proc.ExitCode))" -ForegroundColor Yellow
+        }
+    } catch {
+        Write-Host "[WARN] Could not enable Long Paths (UAC was declined or not available)" -ForegroundColor Yellow
+        Write-Host "       Run this manually in an Admin terminal:" -ForegroundColor Yellow
+        Write-Host '       reg add "HKLM\SYSTEM\CurrentControlSet\Control\FileSystem" /v LongPathsEnabled /t REG_DWORD /d 1 /f' -ForegroundColor Cyan
+    }
+}
+
+# ============================================
+# 1b. Git (required by pip for git+https:// deps and by npm)
+# ============================================
+$HasGit = $null -ne (Get-Command git -ErrorAction SilentlyContinue)
+if (-not $HasGit) {
+    Write-Host "Git not found -- installing via winget..." -ForegroundColor Yellow
+    $HasWinget = $null -ne (Get-Command winget -ErrorAction SilentlyContinue)
+    if ($HasWinget) {
+        try {
+            winget install Git.Git --source winget --accept-package-agreements --accept-source-agreements 2>&1 | Out-Null
+            Refresh-Environment
+            $HasGit = $null -ne (Get-Command git -ErrorAction SilentlyContinue)
+        } catch { }
+    }
+    if (-not $HasGit) {
+        Write-Host "[ERROR] Git is required but could not be installed automatically." -ForegroundColor Red
+        Write-Host "        Install Git from https://git-scm.com/download/win and re-run." -ForegroundColor Red
+        exit 1
+    }
+    Write-Host "[OK] Git installed: $(git --version)" -ForegroundColor Green
+} else {
+    Write-Host "[OK] Git found: $(git --version)" -ForegroundColor Green
+}
+
+# ============================================
+# 1c. CMake (required for llama.cpp build)
+# ============================================
+$HasCmake = $null -ne (Get-Command cmake -ErrorAction SilentlyContinue)
+if (-not $HasCmake) {
+    Write-Host "CMake not found -- installing via winget..." -ForegroundColor Yellow
+    $HasWinget = $null -ne (Get-Command winget -ErrorAction SilentlyContinue)
+    if ($HasWinget) {
+        try {
+            winget install Kitware.CMake --source winget --accept-package-agreements --accept-source-agreements 2>&1 | Out-Null
+            Refresh-Environment
+            $HasCmake = $null -ne (Get-Command cmake -ErrorAction SilentlyContinue)
+        } catch { }
+    }
+    if ($HasCmake) {
+        Write-Host "[OK] CMake installed" -ForegroundColor Green
+    } else {
+        Write-Host "[ERROR] CMake is required but could not be installed." -ForegroundColor Red
+        Write-Host "        Install CMake from https://cmake.org/download/ and re-run." -ForegroundColor Red
+        exit 1
+    }
+} else {
+    Write-Host "[OK] CMake found: $(cmake --version | Select-Object -First 1)" -ForegroundColor Green
+}
+
+# ============================================
+# 1d. Visual Studio Build Tools (C++ compiler for llama.cpp)
+# ============================================
+$CmakeGenerator = $null
+$VsInstallPath = $null
+$vsResult = Find-VsBuildTools
+
+if (-not $vsResult) {
+    Write-Host "Visual Studio Build Tools not found -- installing via winget..." -ForegroundColor Yellow
+    Write-Host "   (This is a one-time install, may take several minutes)" -ForegroundColor Gray
+    $HasWinget = $null -ne (Get-Command winget -ErrorAction SilentlyContinue)
+    if ($HasWinget) {
+        $prevEAPTemp = $ErrorActionPreference
+        $ErrorActionPreference = "Continue"
+        winget install Microsoft.VisualStudio.2022.BuildTools --source winget --accept-package-agreements --accept-source-agreements --override "--add Microsoft.VisualStudio.Workload.VCTools --includeRecommended --passive --wait"
+        $ErrorActionPreference = $prevEAPTemp
+        # Re-scan after install (don't trust vswhere catalog)
+        $vsResult = Find-VsBuildTools
+    }
+}
+
+if ($vsResult) {
+    $CmakeGenerator = $vsResult.Generator
+    $VsInstallPath = $vsResult.InstallPath
+    Write-Host "[OK] $CmakeGenerator detected via $($vsResult.Source)" -ForegroundColor Green
+    if ($vsResult.ClExe) { Write-Host "   cl.exe: $($vsResult.ClExe)" -ForegroundColor Gray }
+} else {
+    Write-Host "[ERROR] Visual Studio Build Tools could not be found or installed." -ForegroundColor Red
+    Write-Host "        Manual install:" -ForegroundColor Red
+    Write-Host '        1. winget install Microsoft.VisualStudio.2022.BuildTools --source winget' -ForegroundColor Yellow
+    Write-Host '        2. Open Visual Studio Installer -> Modify -> check "Desktop development with C++"' -ForegroundColor Yellow
+    exit 1
+}
+
+# ============================================
+# 1e. CUDA Toolkit (nvcc for llama.cpp build + env vars)
+# ============================================
+# IMPORTANT: The CUDA Toolkit version must be <= the max CUDA version the
+# NVIDIA driver supports.  nvidia-smi reports this as "CUDA Version: X.Y".
+# If we install a toolkit newer than the driver supports, llama-server will
+# fail at runtime with "ggml_cuda_init: failed to initialize CUDA: (null)".
+
+# -- Detect max CUDA version the driver supports --
+$DriverMaxCuda = $null
+try {
+    $smiOut = nvidia-smi 2>&1 | Out-String
+    if ($smiOut -match "CUDA Version:\s+([\d]+)\.([\d]+)") {
+        $DriverMaxCuda = "$($Matches[1]).$($Matches[2])"
+        Write-Host "   Driver supports up to CUDA $DriverMaxCuda" -ForegroundColor Gray
+    }
+} catch {}
+
+# -- Find a toolkit that's compatible with the driver --
+$IncompatibleToolkit = $null
+if ($DriverMaxCuda) {
+    $NvccPath = Find-Nvcc -MaxVersion $DriverMaxCuda
+    if ($NvccPath) {
+        Write-Host "   [OK] Found compatible CUDA Toolkit (nvcc: $NvccPath)" -ForegroundColor Green
+    } else {
+        # Check if there's an incompatible (too new) toolkit installed
+        $AnyNvcc = Find-Nvcc
+        if ($AnyNvcc) {
+            $NvccOut = & $AnyNvcc --version 2>&1 | Out-String
+            if ($NvccOut -match "release\s+([\d]+\.[\d]+)") {
+                $IncompatibleToolkit = $Matches[1]
+            }
+        }
+    }
+} else {
+    $NvccPath = Find-Nvcc
+}
+
+# -- If incompatible toolkit is blocking, tell user to uninstall it --
+if (-not $NvccPath -and $IncompatibleToolkit) {
+    Write-Host "" -ForegroundColor Red
+    Write-Host "========================================================================" -ForegroundColor Red
+    Write-Host "[ERROR] CUDA Toolkit $IncompatibleToolkit is installed but INCOMPATIBLE" -ForegroundColor Red
+    Write-Host "        with your NVIDIA driver (which supports up to CUDA $DriverMaxCuda)." -ForegroundColor Red
+    Write-Host "" -ForegroundColor Red
+    Write-Host "  This will cause 'failed to initialize CUDA' errors at runtime." -ForegroundColor Red
+    Write-Host "" -ForegroundColor Red
+    Write-Host "  To fix:" -ForegroundColor Yellow
+    Write-Host "    1. Open Control Panel -> Programs -> Uninstall a program" -ForegroundColor Yellow
+    Write-Host "    2. Uninstall 'NVIDIA CUDA Toolkit $IncompatibleToolkit'" -ForegroundColor Yellow
+    Write-Host "    3. Re-run setup.bat (it will install CUDA $DriverMaxCuda automatically)" -ForegroundColor Yellow
+    Write-Host "" -ForegroundColor Yellow
+    Write-Host "  Alternatively, update your NVIDIA driver to one that supports CUDA $IncompatibleToolkit." -ForegroundColor Gray
+    Write-Host "========================================================================" -ForegroundColor Red
+    exit 1
+}
+
+# -- No toolkit at all: install via winget --
+if (-not $NvccPath) {
+    Write-Host "CUDA toolkit (nvcc) not found -- installing via winget..." -ForegroundColor Yellow
+    $HasWinget = $null -ne (Get-Command winget -ErrorAction SilentlyContinue)
+    if ($HasWinget) {
+        if ($DriverMaxCuda) {
+            # Try descending compatible versions
+            $drMajor = [int]$DriverMaxCuda.Split('.')[0]
+            $drMinor = [int]$DriverMaxCuda.Split('.')[1]
+            for ($m = $drMinor; $m -ge 0; $m--) {
+                $ver = "$drMajor.$m"
+                Write-Host "   Trying CUDA Toolkit $ver via winget..." -ForegroundColor Cyan
+                $prevEAPCuda = $ErrorActionPreference
+                $ErrorActionPreference = "Continue"
+                winget install --id=Nvidia.CUDA --version=$ver -e --source winget --accept-package-agreements --accept-source-agreements 2>&1 | Out-Null
+                $ErrorActionPreference = $prevEAPCuda
+                Refresh-Environment
+                $NvccPath = Find-Nvcc -MaxVersion $DriverMaxCuda
+                if ($NvccPath) {
+                    Write-Host "   [OK] CUDA Toolkit $ver installed (nvcc: $NvccPath)" -ForegroundColor Green
+                    break
+                }
+            }
+        } else {
+            Write-Host "   Installing CUDA Toolkit (latest) via winget..." -ForegroundColor Cyan
+            winget install --id=Nvidia.CUDA -e --source winget --accept-package-agreements --accept-source-agreements
+            Refresh-Environment
+            $NvccPath = Find-Nvcc
+            if ($NvccPath) {
+                Write-Host "   [OK] CUDA Toolkit installed (nvcc: $NvccPath)" -ForegroundColor Green
+            }
+        }
+    }
+}
+
+if (-not $NvccPath) {
+    Write-Host "[ERROR] CUDA Toolkit (nvcc) is required but could not be found or installed." -ForegroundColor Red
+    if ($DriverMaxCuda) {
+        Write-Host "        Install CUDA Toolkit $DriverMaxCuda from https://developer.nvidia.com/cuda-toolkit-archive" -ForegroundColor Yellow
+    } else {
+        Write-Host "        Install CUDA Toolkit from https://developer.nvidia.com/cuda-downloads" -ForegroundColor Yellow
+    }
+    exit 1
+}
+
+# -- Set CUDA env vars so cmake AND MSBuild can find the toolkit --
+$CudaToolkitRoot = Split-Path (Split-Path $NvccPath -Parent) -Parent
+# CUDA_PATH: used by cmake's find_package(CUDAToolkit)
+[Environment]::SetEnvironmentVariable('CUDA_PATH', $CudaToolkitRoot, 'Process')
+# CudaToolkitDir: the MSBuild property that CUDA .targets checks directly
+# Trailing backslash required -- the .targets file appends subpaths to it
+[Environment]::SetEnvironmentVariable('CudaToolkitDir', "$CudaToolkitRoot\", 'Process')
+# Always persist CUDA_PATH to User registry so the compatible toolkit is used
+# in future sessions (overwrites any existing value pointing to a newer, incompatible version)
+[Environment]::SetEnvironmentVariable('CUDA_PATH', $CudaToolkitRoot, 'User')
+Write-Host "   Persisted CUDA_PATH=$CudaToolkitRoot to user environment" -ForegroundColor Gray
+# Ensure nvcc's bin dir is on PATH for this process
+$nvccBinDir = Split-Path $NvccPath -Parent
+if ($env:PATH -notlike "*$nvccBinDir*") {
+    [Environment]::SetEnvironmentVariable('PATH', "$nvccBinDir;$env:PATH", 'Process')
+}
+# Persist nvcc bin dir to User PATH so it works in new terminals
+$userPath = [Environment]::GetEnvironmentVariable('Path', 'User')
+if (-not $userPath -or $userPath -notlike "*$nvccBinDir*") {
+    if ($userPath) {
+        [Environment]::SetEnvironmentVariable('Path', "$nvccBinDir;$userPath", 'User')
+    } else {
+        [Environment]::SetEnvironmentVariable('Path', "$nvccBinDir", 'User')
+    }
+    Write-Host "   Persisted CUDA bin dir to user PATH" -ForegroundColor Gray
+}
+
+Write-Host "[OK] CUDA Toolkit: $NvccPath" -ForegroundColor Green
+Write-Host "   CUDA_PATH      = $CudaToolkitRoot" -ForegroundColor Gray
+Write-Host "   CudaToolkitDir = $CudaToolkitRoot\" -ForegroundColor Gray
+
+# Detect compute capability (used later for llama.cpp cmake)
+$CudaArch = Get-CudaComputeCapability
+if ($CudaArch) {
+    Write-Host "   Compute Capability = $($CudaArch.Insert($CudaArch.Length-1, '.')) (sm_$CudaArch)" -ForegroundColor Gray
+} else {
+    Write-Host "   [WARN] Could not detect compute capability -- cmake will use defaults" -ForegroundColor Yellow
+}
+
+# ============================================
+# 1f. Node.js / npm (always -- needed regardless of install method)
+# ============================================
+# setup.sh installs Node LTS (v22) via nvm. We enforce the same range here:
+# Node >= 20, npm >= 11.
+$NeedNode = $true
+try {
+    $NodeVersion = (node -v 2>$null)
+    $NpmVersion = (npm -v 2>$null)
+    if ($NodeVersion -and $NpmVersion) {
+        $NodeMajor = [int]($NodeVersion -replace 'v','').Split('.')[0]
+        $NpmMajor = [int]$NpmVersion.Split('.')[0]
+
+        if ($NodeMajor -ge 20 -and $NpmMajor -ge 11) {
+            Write-Host "[OK] Node $NodeVersion and npm $NpmVersion already meet requirements." -ForegroundColor Green
+            $NeedNode = $false
+        } else {
+            Write-Host "[WARN] Node $NodeVersion / npm $NpmVersion too old." -ForegroundColor Yellow
+        }
+    }
+} catch {
+    Write-Host "[WARN] Node/npm not found." -ForegroundColor Yellow
+}
+
+if ($NeedNode) {
+    Write-Host "Installing Node.js LTS via winget..." -ForegroundColor Cyan
+    try {
+        winget install OpenJS.NodeJS.LTS --source winget --accept-package-agreements --accept-source-agreements
+        Refresh-Environment
+    } catch {
+        Write-Host "[ERROR] Could not install Node.js automatically." -ForegroundColor Red
+        Write-Host "Please install Node.js >= 20 from https://nodejs.org/" -ForegroundColor Red
+        exit 1
+    }
+}
+
+Write-Host "[OK] Node $(node -v) | npm $(npm -v)" -ForegroundColor Green
+
+# ============================================
+# 1g. Python (>= 3.11 and < 3.14, matching setup.sh)
+# ============================================
+$HasPython = $null -ne (Get-Command python -ErrorAction SilentlyContinue)
+$PythonOk = $false
+
+if ($HasPython) {
+    $PyVer = python --version 2>&1
+    if ($PyVer -match "(\d+)\.(\d+)") {
+        $PyMajor = [int]$Matches[1]; $PyMinor = [int]$Matches[2]
+        if ($PyMajor -eq 3 -and $PyMinor -ge 11 -and $PyMinor -lt 14) {
+            Write-Host "[OK] Python $PyVer" -ForegroundColor Green
+            $PythonOk = $true
+        } else {
+            Write-Host "[ERROR] Python $PyVer is outside supported range (need >= 3.11 and < 3.14)." -ForegroundColor Red
+            Write-Host "        Install Python 3.12 from https://python.org/downloads/" -ForegroundColor Yellow
+            exit 1
+        }
+    }
+} else {
+    # No Python at all -- install 3.12
+    Write-Host "Python not found -- installing Python 3.12 via winget..." -ForegroundColor Yellow
+    $HasWinget = $null -ne (Get-Command winget -ErrorAction SilentlyContinue)
+    if ($HasWinget) {
+        winget install -e --id Python.Python.3.12 --source winget --accept-package-agreements --accept-source-agreements
+        Refresh-Environment
+    }
+    $HasPython = $null -ne (Get-Command python -ErrorAction SilentlyContinue)
+    if (-not $HasPython) {
+        Write-Host "[ERROR] Python could not be installed automatically." -ForegroundColor Red
+        Write-Host "        Install Python 3.12 from https://python.org/downloads/" -ForegroundColor Yellow
+        exit 1
+    }
+    Write-Host "[OK] Python $(python --version)" -ForegroundColor Green
+    $PythonOk = $true
+}
+
+Write-Host ""
+Write-Host "--- System prerequisites ready ---" -ForegroundColor Green
+Write-Host ""
+
+# ==========================================================================
+#  PHASE 2: Frontend build (skip if pip-installed -- already bundled)
+# ==========================================================================
+if ($IsPipInstall) {
+    Write-Host "[OK] Running from pip install - frontend already bundled, skipping build" -ForegroundColor Green
+} else {
+    Write-Host ""
+    Write-Host "Building frontend..." -ForegroundColor Cyan
+    # npm writes warnings to stderr; lower ErrorActionPreference so PS doesn't
+    # treat them as terminating errors (same pattern as the pip section below).
+    $prevEAP_npm = $ErrorActionPreference
+    $ErrorActionPreference = "Continue"
+    Push-Location $FrontendDir
+    # Remove stale node_modules and package-lock.json to avoid version conflicts
+    if (Test-Path "node_modules") { Remove-Item -Recurse -Force "node_modules" }
+    if (Test-Path "package-lock.json") { Remove-Item -Force "package-lock.json" }
+    npm install 2>&1 | Out-Null
+    if ($LASTEXITCODE -ne 0) {
+        Pop-Location
+        $ErrorActionPreference = $prevEAP_npm
+        Write-Host "[ERROR] npm install failed (exit code $LASTEXITCODE)" -ForegroundColor Red
+        Write-Host "   Try running 'npm install' manually in studio/frontend/ to see errors" -ForegroundColor Yellow
+        exit 1
+    }
+    npm run build 2>&1 | Out-Null
+    if ($LASTEXITCODE -ne 0) {
+        Pop-Location
+        $ErrorActionPreference = $prevEAP_npm
+        Write-Host "[ERROR] npm run build failed (exit code $LASTEXITCODE)" -ForegroundColor Red
+        exit 1
+    }
+    Pop-Location
+    $ErrorActionPreference = $prevEAP_npm
+    Write-Host "[OK] Frontend built to studio/frontend/dist" -ForegroundColor Green
+}
+
+# ==========================================================================
+#  PHASE 3: Python environment + dependencies
+# ==========================================================================
+Write-Host ""
+Write-Host "Setting up Python environment..." -ForegroundColor Cyan
+
+# Find Python
+$PythonCmd = $null
+foreach ($candidate in @("python3.12", "python3.11", "python3.10", "python3.9", "python3", "python")) {
+    try {
+        $ver = & $candidate --version 2>&1
+        if ($ver -match 'Python 3\.(\d+)') {
+            $minor = [int]$Matches[1]
+            if ($minor -le 12) {
+                $PythonCmd = $candidate
+                break
+            }
+        }
+    } catch { }
+}
+
+if (-not $PythonCmd) {
+    Write-Host "[ERROR] No Python <= 3.12 found." -ForegroundColor Red
+    exit 1
+}
+
+Write-Host "[OK] Using $PythonCmd ($(& $PythonCmd --version 2>&1))" -ForegroundColor Green
+
+# Always create a .venv for isolation -- even for pip installs.
+# Created in the current working directory (where user ran the command).
+$VenvDir = Join-Path (Get-Location) ".venv"
+if (-not (Test-Path $VenvDir)) {
+    Write-Host "   Creating virtual environment at $VenvDir..." -ForegroundColor Cyan
+    & $PythonCmd -m venv $VenvDir
+} else {
+    Write-Host "   Reusing existing virtual environment at $VenvDir" -ForegroundColor Green
+}
+
+# pip and python write to stderr even on success (progress bars, warnings).
+# With $ErrorActionPreference = "Stop" (set at top of script), PS 5.1
+# converts stderr lines into terminating ErrorRecords, breaking output.
+# Lower to "Continue" for the pip/python section.
+$prevEAP = $ErrorActionPreference
+$ErrorActionPreference = "Continue"
+
+$ActivateScript = Join-Path $VenvDir "Scripts\Activate.ps1"
+. $ActivateScript
+pip install --upgrade pip 2>&1 | Out-Null
+
+# if (-not $IsPipInstall) {
+#     # Running from repo: copy requirements and do editable install
+#     $RepoRoot = (Resolve-Path (Join-Path $ScriptDir "..\..")).Path
+#     $ReqsSrc = Join-Path $RepoRoot "backend\requirements"
+#     $ReqsDst = Join-Path $PackageDir "requirements"
+#     if (-not (Test-Path $ReqsDst)) { New-Item -ItemType Directory -Path $ReqsDst | Out-Null }
+#     Copy-Item (Join-Path $ReqsSrc "*.txt") $ReqsDst -Force
+
+#     Write-Host "   Installing CLI entry point..." -ForegroundColor Cyan
+#     pip install -e $RepoRoot 2>&1 | Out-Null
+# } else {
+#     # Running from pip install: the package is in system Python but not in
+#     # the fresh .venv. Install it so run_install() can find its modules
+#     # and bundled requirements files.
+#     Write-Host "   Installing package into venv..." -ForegroundColor Cyan
+#     pip install unsloth-roland-test 2>&1 | Out-Null
+# }
+
+# Pre-install PyTorch with CUDA support.
+# On Windows, the default PyPI torch wheel is CPU-only.
+# We need PyTorch's CUDA index to get GPU-enabled wheels.
+# PyTorch bundles its own CUDA runtime, so this works regardless
+# of whether the CUDA Toolkit is installed yet.
+# The CUDA tag is chosen based on the driver's max supported CUDA version.
+
+# Windows MAX_PATH (260 chars) causes Triton kernel compilation to fail because
+# the auto-generated filenames are extremely long. Use a short cache directory.
+$TorchCacheDir = "C:\tc"
+if (-not (Test-Path $TorchCacheDir)) { New-Item -ItemType Directory -Path $TorchCacheDir -Force | Out-Null }
+$env:TORCHINDUCTOR_CACHE_DIR = $TorchCacheDir
+[Environment]::SetEnvironmentVariable('TORCHINDUCTOR_CACHE_DIR', $TorchCacheDir, 'User')
+Write-Host "[OK] TORCHINDUCTOR_CACHE_DIR set to $TorchCacheDir (avoids MAX_PATH issues)" -ForegroundColor Green
+
+$CuTag = Get-PytorchCudaTag
+Write-Host "   Installing PyTorch with CUDA support ($CuTag)..." -ForegroundColor Cyan
+pip install torch torchvision torchaudio --index-url "https://download.pytorch.org/whl/$CuTag" 2>&1 | Out-Null
+
+# Ordered heavy dependency installation — shared cross-platform script
+Write-Host "   Running ordered dependency installation..." -ForegroundColor Cyan
+python "$PSScriptRoot\install_python_stack.py"
+# Restore ErrorActionPreference after pip/python work
+$ErrorActionPreference = $prevEAP
+
+# ==========================================================================
+#  PHASE 3.5: Install OpenSSL dev (for HTTPS support in llama-server)
+# ==========================================================================
+# llama-server needs OpenSSL to download models from HuggingFace via -hf.
+# ShiningLight.OpenSSL.Dev includes headers + libs that cmake can find.
+$OpenSslAvailable = $false
+
+# Check if OpenSSL dev is already installed (look for include dir)
+$OpenSslRoots = @(
+    'C:\Program Files\OpenSSL-Win64',
+    'C:\Program Files\OpenSSL',
+    'C:\OpenSSL-Win64'
+)
+$OpenSslRoot = $null
+foreach ($root in $OpenSslRoots) {
+    if (Test-Path (Join-Path $root 'include\openssl\ssl.h')) {
+        $OpenSslRoot = $root
+        break
+    }
+}
+
+if ($OpenSslRoot) {
+    $OpenSslAvailable = $true
+    Write-Host "[OK] OpenSSL dev found at $OpenSslRoot" -ForegroundColor Green
+} else {
+    Write-Host "" 
+    Write-Host "Installing OpenSSL dev (for HTTPS in llama-server)..." -ForegroundColor Cyan
+    $HasWinget = $null -ne (Get-Command winget -ErrorAction SilentlyContinue)
+    if ($HasWinget) {
+        winget install -e --id ShiningLight.OpenSSL.Dev --accept-package-agreements --accept-source-agreements
+        # Re-check after install
+        foreach ($root in $OpenSslRoots) {
+            if (Test-Path (Join-Path $root 'include\openssl\ssl.h')) {
+                $OpenSslRoot = $root
+                $OpenSslAvailable = $true
+                Write-Host "[OK] OpenSSL dev installed at $OpenSslRoot" -ForegroundColor Green
+                break
+            }
+        }
+    }
+    if (-not $OpenSslAvailable) {
+        Write-Host "[WARN] OpenSSL dev not available -- llama-server will be built without HTTPS" -ForegroundColor Yellow
+    }
+}
+
+# ==========================================================================
+#  PHASE 4: Build llama.cpp with CUDA for GGUF inference + export
+# ==========================================================================
+# Builds at ~/.unsloth/llama.cpp — a single shared location under the user's
+# home directory. This is used by both the inference server and the GGUF
+# export pipeline (unsloth-zoo).
+# We build:
+#   - llama-server:   for GGUF model inference (with HTTPS if OpenSSL available)
+#   - llama-quantize: for GGUF export quantization
+# Prerequisites (git, cmake, VS Build Tools, CUDA Toolkit) already installed in Phase 1.
+$UnslothHome = Join-Path $env:USERPROFILE ".unsloth"
+if (-not (Test-Path $UnslothHome)) { New-Item -ItemType Directory -Force $UnslothHome | Out-Null }
+$LlamaCppDir = Join-Path $UnslothHome "llama.cpp"
+$BuildDir = Join-Path $LlamaCppDir "build"
+$LlamaServerBin = Join-Path $BuildDir "bin\Release\llama-server.exe"
+
+if (Test-Path $LlamaServerBin) {
+    Write-Host ""
+    Write-Host "[OK] llama-server already exists at $LlamaServerBin" -ForegroundColor Green
+} else {
+    Write-Host ""
+    Write-Host "Building llama.cpp with CUDA support..." -ForegroundColor Cyan
+    Write-Host "   This typically takes 5-10 minutes on first build." -ForegroundColor Gray
+    Write-Host ""
+
+    # Start total build timer
+    $totalSw = [System.Diagnostics.Stopwatch]::StartNew()
+
+    # Native commands (git, cmake) write to stderr even on success.
+    # With $ErrorActionPreference = "Stop" (set at top of script), PS 5.1
+    # converts stderr lines into terminating ErrorRecords, breaking output.
+    # Lower to "Continue" for the build section.
+    $prevEAP = $ErrorActionPreference
+    $ErrorActionPreference = "Continue"
+
+    $BuildOk = $true
+    $FailedStep = ""
+
+    # -- Step A: Clone or pull llama.cpp --
+
+    if (Test-Path (Join-Path $LlamaCppDir ".git")) {
+        Write-Host "   llama.cpp repo already cloned, pulling latest..." -ForegroundColor Gray
+        git -C $LlamaCppDir pull
+        if ($LASTEXITCODE -ne 0) {
+            Write-Host "   [WARN] git pull failed -- using existing source" -ForegroundColor Yellow
+        }
+    } else {
+        Write-Host "   Cloning llama.cpp..." -ForegroundColor Gray
+        if (Test-Path $LlamaCppDir) { Remove-Item -Recurse -Force $LlamaCppDir }
+        git clone --depth 1 https://github.com/ggml-org/llama.cpp.git $LlamaCppDir
+        if ($LASTEXITCODE -ne 0) {
+            $BuildOk = $false
+            $FailedStep = "git clone"
+        }
+    }
+
+    # -- Step B: cmake configure (CUDA + Unsloth flags) --
+    if ($BuildOk) {
+        Write-Host ""
+        Write-Host "--- cmake configure ---" -ForegroundColor Cyan
+
+        $CmakeArgs = @(
+            '-S', $LlamaCppDir,
+            '-B', $BuildDir,
+            '-G', $CmakeGenerator,
+            '-Wno-dev'
+        )
+        # Tell cmake exactly where VS is (bypasses registry lookup)
+        if ($VsInstallPath) {
+            $CmakeArgs += "-DCMAKE_GENERATOR_INSTANCE=$VsInstallPath"
+        }
+        # Common flags
+        $CmakeArgs += '-DBUILD_SHARED_LIBS=OFF'
+        # HTTPS support via OpenSSL
+        if ($OpenSslAvailable -and $OpenSslRoot) {
+            $CmakeArgs += "-DOPENSSL_ROOT_DIR=$OpenSslRoot"
+            $CmakeArgs += '-DLLAMA_OPENSSL=ON'
+        } else {
+            $CmakeArgs += '-DLLAMA_CURL=OFF'
+        }
+        $CmakeArgs += '-DCMAKE_EXE_LINKER_FLAGS=/NODEFAULTLIB:LIBCMT'
+        # CUDA flags (Unsloth-aligned)
+        $CmakeArgs += '-DGGML_CUDA=ON'
+        $CmakeArgs += "-DCUDAToolkit_ROOT=$CudaToolkitRoot"
+        $CmakeArgs += "-DCMAKE_CUDA_COMPILER=$NvccPath"
+        $CmakeArgs += '-DGGML_CUDA_FA_ALL_QUANTS=ON'
+        $CmakeArgs += '-DGGML_CUDA_F16=OFF'
+        $CmakeArgs += '-DGGML_CUDA_GRAPHS=OFF'
+        $CmakeArgs += '-DGGML_CUDA_FORCE_CUBLAS=OFF'
+        $CmakeArgs += '-DGGML_CUDA_PEER_MAX_BATCH_SIZE=8192'
+        if ($CudaArch) {
+            $CmakeArgs += "-DCMAKE_CUDA_ARCHITECTURES=$CudaArch"
+        }
+
+        Write-Host "   cmake args:" -ForegroundColor Gray
+        foreach ($arg in $CmakeArgs) {
+            Write-Host "     $arg" -ForegroundColor Gray
+        }
+        Write-Host ""
+
+        cmake @CmakeArgs
+        if ($LASTEXITCODE -ne 0) {
+            $BuildOk = $false
+            $FailedStep = "cmake configure"
+        }
+    }
+
+    # -- Step C: Build llama-server --
+    $NumCpu = [Environment]::ProcessorCount
+    if ($NumCpu -lt 1) { $NumCpu = 4 }
+
+    if ($BuildOk) {
+        Write-Host ""
+        Write-Host "--- cmake build (llama-server) ---" -ForegroundColor Cyan
+        Write-Host "   Parallel jobs: $NumCpu" -ForegroundColor Gray
+        Write-Host ""
+
+        cmake --build $BuildDir --config Release --target llama-server -j $NumCpu
+        if ($LASTEXITCODE -ne 0) {
+            $BuildOk = $false
+            $FailedStep = "cmake build (llama-server)"
+        }
+    }
+
+    # -- Step D: Build llama-quantize (optional, best-effort) --
+    if ($BuildOk) {
+        Write-Host ""
+        Write-Host "--- cmake build (llama-quantize) ---" -ForegroundColor Cyan
+        cmake --build $BuildDir --config Release --target llama-quantize -j $NumCpu
+        if ($LASTEXITCODE -ne 0) {
+            Write-Host "   [WARN] llama-quantize build failed (GGUF export may be unavailable)" -ForegroundColor Yellow
+        }
+    }
+
+    # Restore ErrorActionPreference
+    $ErrorActionPreference = $prevEAP
+
+    # Stop timer
+    $totalSw.Stop()
+    $totalMin = [math]::Floor($totalSw.Elapsed.TotalMinutes)
+    $totalSec = [math]::Round($totalSw.Elapsed.TotalSeconds % 60, 1)
+
+    # -- Summary --
+    Write-Host ""
+    if ($BuildOk -and (Test-Path $LlamaServerBin)) {
+        Write-Host "[OK] llama-server built at $LlamaServerBin" -ForegroundColor Green
+        $QuantizeBin = Join-Path $BuildDir "bin\Release\llama-quantize.exe"
+        if (Test-Path $QuantizeBin) {
+            Write-Host "[OK] llama-quantize available for GGUF export" -ForegroundColor Green
+        }
+        Write-Host "   Build time: ${totalMin}m ${totalSec}s" -ForegroundColor Cyan
+    } else {
+        # Check alternate paths (some cmake generators don't use Release subdir)
+        $altBin = Join-Path $BuildDir "bin\llama-server.exe"
+        if ($BuildOk -and (Test-Path $altBin)) {
+            Write-Host "[OK] llama-server built at $altBin" -ForegroundColor Green
+            Write-Host "   Build time: ${totalMin}m ${totalSec}s" -ForegroundColor Cyan
+        } else {
+            Write-Host "[FAILED] llama.cpp build failed at step: $FailedStep (${totalMin}m ${totalSec}s)" -ForegroundColor Red
+            Write-Host "         To retry: delete $LlamaCppDir and re-run setup." -ForegroundColor Yellow
+            exit 1
+        }
+    }
+}
+
+# ============================================
+# Add shell aliases (PowerShell profile + cmd batch files)
+# ============================================
+Write-Host ""
+$RepoDir = $PSScriptRoot
+$VenvPython = Join-Path $RepoDir ".venv\Scripts\python.exe"
+$CliScript = Join-Path $RepoDir "cli.py"
+$FrontendDist = Join-Path $RepoDir "studio\frontend\dist"
+$AliasAdded = $false
+
+# --- PowerShell profile: add functions ---
+$ProfileDir = Split-Path $PROFILE -Parent
+if (-not (Test-Path $ProfileDir)) { New-Item -ItemType Directory -Path $ProfileDir -Force | Out-Null }
+if (-not (Test-Path $PROFILE)) { New-Item -ItemType File -Path $PROFILE -Force | Out-Null }
+
+if (-not (Select-String -Path $PROFILE -Pattern "unsloth-studio" -Quiet -ErrorAction SilentlyContinue)) {
+    $block = @"
+
+# Unsloth Studio launcher
+function unsloth-studio { & "$VenvPython" "$CliScript" studio -f "$FrontendDist" @args }
+function unsloth-ui     { & "$VenvPython" "$CliScript" studio -f "$FrontendDist" @args }
+"@
+    Add-Content -Path $PROFILE -Value $block
+    Write-Host "[OK] Aliases 'unsloth-studio' and 'unsloth-ui' added to $PROFILE" -ForegroundColor Green
+    $AliasAdded = $true
+} else {
+    Write-Host "[OK] Aliases 'unsloth-studio' and 'unsloth-ui' already exist in $PROFILE" -ForegroundColor Green
+}
+
+# --- cmd.exe: create batch files and ensure they're on PATH ---
+$BatDir = Join-Path $RepoDir ".venv\Scripts"
+foreach ($name in @("unsloth-studio", "unsloth-ui")) {
+    $batPath = Join-Path $BatDir "$name.bat"
+    if (-not (Test-Path $batPath)) {
+        Set-Content -Path $batPath -Value "@echo off`r`n`"$VenvPython`" `"$CliScript`" studio -f `"$FrontendDist`" %*"
+    }
+}
+# Persist .venv\Scripts to User PATH so commands work in new cmd.exe terminals without activation
+$userPath = [Environment]::GetEnvironmentVariable('Path', 'User')
+if (-not $userPath -or $userPath -notlike "*$BatDir*") {
+    if ($userPath) {
+        [Environment]::SetEnvironmentVariable('Path', "$BatDir;$userPath", 'User')
+    } else {
+        [Environment]::SetEnvironmentVariable('Path', "$BatDir", 'User')
+    }
+    Write-Host "   Persisted $BatDir to User PATH" -ForegroundColor Gray
+}
+Write-Host "[OK] Batch launchers created (works from any new cmd.exe or PowerShell)" -ForegroundColor Green
+
+# ============================================
+# Done
+# ============================================
+Write-Host ""
+Write-Host "+===============================================+" -ForegroundColor Green
+Write-Host "|           Setup Complete!                     |" -ForegroundColor Green
+Write-Host "|                                               |" -ForegroundColor Green
+Write-Host "|  IMPORTANT: Open a NEW terminal, then run:    |" -ForegroundColor Yellow
+Write-Host "|                                               |" -ForegroundColor Green
+Write-Host "|    unsloth-studio -H 0.0.0.0 -p 8000         |" -ForegroundColor Green
+Write-Host "|                                               |" -ForegroundColor Green
+Write-Host "+===============================================+" -ForegroundColor Green
\ No newline at end of file
diff --git a/setup.sh b/setup.sh
index 8314ef6d75..07ea131125 100755
--- a/setup.sh
+++ b/setup.sh
@@ -170,30 +170,7 @@ SINGLE_ENV_DATA_DESIGNER_DEPS="$REQ_ROOT/single-env/data-designer-deps.txt"
 SINGLE_ENV_PATCH="$REQ_ROOT/single-env/patch_metadata.py"
 
 install_python_stack() {
-    run_quiet "pip upgrade" pip install --upgrade pip
-    echo "   Installing unsloth-zoo + unsloth..."
-    run_quiet "pip install unsloth" pip install --no-cache-dir -c "$SINGLE_ENV_CONSTRAINTS" -r "$REQ_ROOT/base.txt"
-    echo "   Installing additional unsloth dependencies..."
-    run_quiet "pip install extras" pip install --no-cache-dir -c "$SINGLE_ENV_CONSTRAINTS" -r "$REQ_ROOT/extras.txt"
-    run_quiet "pip install torchao+transformers" pip install --force-reinstall --no-cache-dir -c "$SINGLE_ENV_CONSTRAINTS" -r "$REQ_ROOT/overrides.txt"
-    run_quiet "pip install triton_kernels" pip install --no-deps --no-cache-dir -r "$REQ_ROOT/triton-kernels.txt"
-    # Patch: override llama_cpp.py with fix from unsloth-zoo branch
-    LLAMA_CPP_DST="$(pip show unsloth-zoo | grep -i '^Location:' | awk '{print $2}')/unsloth_zoo/llama_cpp.py"
-    curl -sSL "https://raw.githubusercontent.com/unslothai/unsloth-zoo/refs/heads/main/unsloth_zoo/llama_cpp.py" \
-        -o "$LLAMA_CPP_DST"
-    # Patch: override vision.py with fix from unsloth PR: https://github.com/unslothai/unsloth/pull/4091 until next pypi release
-    VISION_DST="$(pip show unsloth | grep -i '^Location:' | awk '{print $2}')/unsloth/models/vision.py"
-    curl -sSL "https://raw.githubusercontent.com/unslothai/unsloth/80e0108a684c882965a02a8ed851e3473c1145ab/unsloth/models/vision.py" \
-        -o "$VISION_DST"
-    echo "   Installing studio dependencies..."
-    run_quiet "pip install studio" pip install --no-cache-dir -c "$SINGLE_ENV_CONSTRAINTS" -r "$REQ_ROOT/studio.txt"
-    echo "   Installing data-designer dependencies..."
-    run_quiet "pip install data-designer deps" pip install --no-cache-dir -c "$SINGLE_ENV_CONSTRAINTS" -r "$SINGLE_ENV_DATA_DESIGNER_DEPS"
-    echo "   Installing data-designer..."
-    run_quiet "pip install data-designer" pip install --no-cache-dir --no-deps -c "$SINGLE_ENV_CONSTRAINTS" -r "$SINGLE_ENV_DATA_DESIGNER"
-    run_quiet "patch single-env metadata" python "$SINGLE_ENV_PATCH"
-    run_quiet "pip check" pip check
-    echo "✅ Python dependencies installed"
+    python "$SCRIPT_DIR/install_python_stack.py"
 }
 
 if [ "$IS_COLAB" = true ]; then
@@ -220,11 +197,14 @@ else
 fi
 
 # ── 8. Build llama.cpp binaries for GGUF inference + export ──
-# Builds in-tree at $REPO/llama.cpp/. This directory is shared with
-# unsloth-zoo's GGUF export pipeline. We build:
+# Builds at ~/.unsloth/llama.cpp — a single shared location under the user's
+# home directory. This is used by both the inference server and the GGUF
+# export pipeline (unsloth-zoo).
 #   - llama-server: for GGUF model inference
 #   - llama-quantize: for GGUF export quantization (symlinked to root for check_llama_cpp())
-LLAMA_CPP_DIR="$SCRIPT_DIR/llama.cpp"
+UNSLOTH_HOME="$HOME/.unsloth"
+mkdir -p "$UNSLOTH_HOME"
+LLAMA_CPP_DIR="$UNSLOTH_HOME/llama.cpp"
 LLAMA_SERVER_BIN="$LLAMA_CPP_DIR/build/bin/llama-server"
 rm -rf "$LLAMA_CPP_DIR"
 {
diff --git a/studio/backend/core/export/export.py b/studio/backend/core/export/export.py
index bc4e267f75..3d3db2d560 100644
--- a/studio/backend/core/export/export.py
+++ b/studio/backend/core/export/export.py
@@ -418,9 +418,8 @@ class ExportBackend:
                 pre_existing_ggufs = set(glob.glob(os.path.join(cwd, "*.gguf")))
 
                 # Pass absolute path — no os.chdir needed.
-                # unsloth saves intermediate HF model files into model_save_path,
-                # while check_llama_cpp("llama.cpp") resolves against cwd (repo root)
-                # where setup.sh already built llama.cpp with quantizer.
+                # unsloth saves intermediate HF model files into model_save_path.
+                # unsloth-zoo's check_llama_cpp() uses ~/.unsloth/llama.cpp by default.
                 model_save_path = os.path.join(abs_save_dir, "model")
                 self.current_model.save_pretrained_gguf(
                     model_save_path,
diff --git a/studio/backend/core/inference/inference.py b/studio/backend/core/inference/inference.py
index a2449c534c..d194f08045 100644
--- a/studio/backend/core/inference/inference.py
+++ b/studio/backend/core/inference/inference.py
@@ -1593,6 +1593,7 @@ class InferenceBackend:
             return False
 
 
+
 # Global inference backend instance
 inference_backend = InferenceBackend()
 
diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index b7b87e9cfb..f47b9132db 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -76,33 +76,83 @@ class LlamaCppBackend:
         Locate the llama-server binary.
 
         Search order:
-        1. LLAMA_SERVER_PATH environment variable
-        2. ./llama.cpp/build/bin/llama-server  (built by setup.sh in-tree)
-        3. llama-server on PATH  (system install)
-        4. ./bin/llama-server  (legacy: extracted binary)
+        1.  LLAMA_SERVER_PATH environment variable (direct path to binary)
+        1b. UNSLOTH_LLAMA_CPP_PATH env var (custom llama.cpp install dir)
+        2.  ~/.unsloth/llama.cpp/llama-server        (make build, root dir)
+        3.  ~/.unsloth/llama.cpp/build/bin/llama-server  (cmake build, Linux)
+        4.  ~/.unsloth/llama.cpp/build/bin/Release/llama-server.exe  (cmake build, Windows)
+        5.  ./llama.cpp/llama-server                 (legacy: make build, root dir)
+        6.  ./llama.cpp/build/bin/llama-server        (legacy: cmake in-tree build)
+        7.  llama-server on PATH                     (system install)
+        8.  ./bin/llama-server                       (legacy: extracted binary)
         """
         import os
+        import sys
 
-        # 1. Env var
+        binary_name = "llama-server.exe" if sys.platform == "win32" else "llama-server"
+
+        # 1. Env var — direct path to binary
         env_path = os.environ.get("LLAMA_SERVER_PATH")
         if env_path and Path(env_path).is_file():
             return env_path
 
-        # Project root: llama_cpp.py → inference/ → core/ → backend/ → studio/ → root
-        project_root = Path(__file__).resolve().parents[4]
+        # 1b. UNSLOTH_LLAMA_CPP_PATH — custom llama.cpp install directory
+        custom_llama_cpp = os.environ.get("UNSLOTH_LLAMA_CPP_PATH")
+        if custom_llama_cpp:
+            custom_dir = Path(custom_llama_cpp)
+            # Root dir (make builds)
+            root_bin = custom_dir / binary_name
+            if root_bin.is_file():
+                return str(root_bin)
+            # build/bin/ (cmake builds on Linux)
+            cmake_bin = custom_dir / "build" / "bin" / binary_name
+            if cmake_bin.is_file():
+                return str(cmake_bin)
+            # build/bin/Release/ (cmake builds on Windows)
+            if sys.platform == "win32":
+                win_bin = custom_dir / "build" / "bin" / "Release" / binary_name
+                if win_bin.is_file():
+                    return str(win_bin)
 
-        # 2. In-tree llama.cpp build (setup.sh builds here)
-        build_path = project_root / "llama.cpp" / "build" / "bin" / "llama-server"
+        # 2–4. ~/.unsloth/llama.cpp (primary — setup.sh / setup.ps1 build here)
+        unsloth_home = Path.home() / ".unsloth" / "llama.cpp"
+        # Root dir (make builds copy binaries here)
+        home_root = unsloth_home / binary_name
+        if home_root.is_file():
+            return str(home_root)
+        # build/bin/ (cmake builds on Linux)
+        home_linux = unsloth_home / "build" / "bin" / binary_name
+        if home_linux.is_file():
+            return str(home_linux)
+
+        # 3. Windows MSVC build has Release subdir
+        if sys.platform == "win32":
+            home_win = unsloth_home / "build" / "bin" / "Release" / binary_name
+            if home_win.is_file():
+                return str(home_win)
+
+        # 5–6. Legacy: in-tree build (older setup.sh / setup.ps1 versions)
+        project_root = Path(__file__).resolve().parents[4]
+        # Root dir (make builds)
+        root_path = project_root / "llama.cpp" / binary_name
+        if root_path.is_file():
+            return str(root_path)
+        # build/bin/ (cmake builds)
+        build_path = project_root / "llama.cpp" / "build" / "bin" / binary_name
         if build_path.is_file():
             return str(build_path)
+        if sys.platform == "win32":
+            win_path = project_root / "llama.cpp" / "build" / "bin" / "Release" / binary_name
+            if win_path.is_file():
+                return str(win_path)
 
-        # 3. System PATH
+        # 7. System PATH
         system_path = shutil.which("llama-server")
         if system_path:
             return system_path
 
-        # 4. Legacy: extracted to bin/
-        bin_path = project_root / "bin" / "llama-server"
+        # 8. Legacy: extracted to bin/
+        bin_path = project_root / "bin" / binary_name
         if bin_path.is_file():
             return str(bin_path)
 
@@ -184,16 +234,58 @@ class LlamaCppBackend:
 
             # Build command based on mode
             if hf_repo:
-                hf_spec = f"{hf_repo}:{hf_variant}" if hf_variant else hf_repo
+                # Download the GGUF file ourselves using huggingface_hub
+                # (llama-server's -hf flag requires HTTPS/curl which may not
+                #  be available, e.g. Windows builds with -DLLAMA_CURL=OFF)
+                try:
+                    from huggingface_hub import hf_hub_download
+                except ImportError:
+                    raise RuntimeError(
+                        "huggingface_hub is required for HF model loading. "
+                        "Install it with: pip install huggingface_hub"
+                    )
+
+                # Determine the filename from the variant (e.g., "Q4_K_M" -> find matching file)
+                gguf_filename = None
+                if hf_variant:
+                    # Try common naming patterns
+                    try:
+                        from huggingface_hub import list_repo_files
+                        files = list_repo_files(hf_repo, token=hf_token)
+                        variant_lower = hf_variant.lower()
+                        for f in files:
+                            if f.endswith(".gguf") and variant_lower in f.lower():
+                                gguf_filename = f
+                                break
+                    except Exception as e:
+                        logger.warning(f"Could not list repo files: {e}")
+
+                    if not gguf_filename:
+                        # Fallback: construct common filename pattern
+                        # e.g., "unsloth/gemma-3-4b-it-GGUF" + "Q4_K_M" -> try model name
+                        repo_name = hf_repo.split("/")[-1].replace("-GGUF", "")
+                        gguf_filename = f"{repo_name}-{hf_variant}.gguf"
+
+                logger.info(f"Downloading GGUF: {hf_repo}/{gguf_filename}")
+                try:
+                    local_path = hf_hub_download(
+                        repo_id=hf_repo,
+                        filename=gguf_filename,
+                        token=hf_token,
+                    )
+                except Exception as e:
+                    raise RuntimeError(
+                        f"Failed to download GGUF file '{gguf_filename}' from {hf_repo}: {e}"
+                    )
+
+                logger.info(f"GGUF downloaded to: {local_path}")
                 cmd = [
                     binary,
-                    "-hf", hf_spec,
+                    "-m", local_path,
                     "--port", str(self._port),
                     "-c", str(n_ctx),
                     "-ngl", str(n_gpu_layers),
                 ]
-                if hf_token:
-                    cmd.extend(["--hf-token", hf_token])
             elif gguf_path:
                 if not Path(gguf_path).is_file():
                     raise FileNotFoundError(f"GGUF file not found: {gguf_path}")
@@ -220,13 +312,31 @@ class LlamaCppBackend:
 
             logger.info(f"Starting llama-server: {' '.join(cmd)}")
 
-            # Set LD_LIBRARY_PATH so llama-server can find its shared libs
-            # (libmtmd.so, libllama.so, etc.) which live next to the binary
+            # Set library paths so llama-server can find its shared libs and CUDA DLLs
             import os
+            import sys
             env = os.environ.copy()
             binary_dir = str(Path(binary).parent)
-            existing_ld = env.get("LD_LIBRARY_PATH", "")
-            env["LD_LIBRARY_PATH"] = f"{binary_dir}:{existing_ld}" if existing_ld else binary_dir
+
+            if sys.platform == "win32":
+                # On Windows, CUDA DLLs (cublas64_12.dll, cudart64_12.dll, etc.)
+                # must be on PATH. Add CUDA_PATH\bin if available.
+                path_dirs = [binary_dir]
+                cuda_path = os.environ.get("CUDA_PATH", "")
+                if cuda_path:
+                    cuda_bin = os.path.join(cuda_path, "bin")
+                    if os.path.isdir(cuda_bin):
+                        path_dirs.append(cuda_bin)
+                    # Some CUDA installs put DLLs in bin\x64
+                    cuda_bin_x64 = os.path.join(cuda_path, "bin", "x64")
+                    if os.path.isdir(cuda_bin_x64):
+                        path_dirs.append(cuda_bin_x64)
+                existing_path = env.get("PATH", "")
+                env["PATH"] = ";".join(path_dirs) + ";" + existing_path
+            else:
+                # Linux: set LD_LIBRARY_PATH for shared libs next to the binary
+                existing_ld = env.get("LD_LIBRARY_PATH", "")
+                env["LD_LIBRARY_PATH"] = f"{binary_dir}:{existing_ld}" if existing_ld else binary_dir
 
             self._stdout_lines = []
             self._process = subprocess.Popen(
@@ -249,9 +359,8 @@ class LlamaCppBackend:
             self._is_vision = is_vision
             self._model_identifier = model_identifier
 
-            # HF mode: llama-server downloads before becoming healthy — need longer timeout
-            timeout = 600.0 if hf_repo else 120.0
-            if not self._wait_for_health(timeout=timeout):
+            # Wait for llama-server to become healthy
+            if not self._wait_for_health(timeout=120.0):
                 self._kill_process()
                 raise RuntimeError(
                     "llama-server failed to start. "
diff --git a/studio/backend/core/training/trainer.py b/studio/backend/core/training/trainer.py
index a36c45ca36..ab16b72a15 100644
--- a/studio/backend/core/training/trainer.py
+++ b/studio/backend/core/training/trainer.py
@@ -1716,7 +1716,9 @@ class UnslothTrainer:
                      subset: str = None,
                      train_split: str = "train",
                      eval_split: str = None,
-                     eval_steps: float = 0.00) -> Optional[tuple]:
+                     eval_steps: float = 0.00,
+                     dataset_slice_start: int = None,
+                     dataset_slice_end: int = None) -> Optional[tuple]:
         """
         Load and prepare dataset for training.
 
@@ -1808,6 +1810,18 @@ class UnslothTrainer:
             if dataset is None:
                 raise ValueError("No dataset provided")
 
+            # Apply index range slicing if requested (inclusive on both ends)
+            if dataset_slice_start is not None or dataset_slice_end is not None:
+                total_rows = len(dataset)
+                start = dataset_slice_start if dataset_slice_start is not None else 0
+                end = dataset_slice_end if dataset_slice_end is not None else total_rows - 1
+                # Clamp to valid range
+                start = max(0, min(start, total_rows - 1))
+                end = max(start, min(end, total_rows - 1))
+                dataset = dataset.select(range(start, end + 1))
+                print(f"Sliced dataset to rows [{start}, {end}]: {len(dataset)} of {total_rows} rows\n")
+                self._update_progress(status_message=f"Sliced dataset to {len(dataset)} rows (indices {start}-{end})")
+
             # Check if stopped before applying template
             if self.should_stop:
                 print("Stopped before applying chat template\n")
@@ -1851,6 +1865,7 @@ class UnslothTrainer:
                 format_type=format_type,
                 dataset_name=dataset_source,
                 custom_format_mapping=custom_format_mapping,
+                progress_callback=self._update_progress,
             )
 
             # Check if stopped during formatting
@@ -1858,6 +1873,14 @@ class UnslothTrainer:
                 print("Stopped during dataset formatting\n")
                 return None
 
+            # Abort if dataset formatting/conversion failed
+            if not dataset_info.get("success", True):
+                errors = dataset_info.get("errors", [])
+                error_msg = "; ".join(errors) if errors else "Dataset formatting failed"
+                logger.error(f"Dataset conversion failed: {error_msg}")
+                self._update_progress(error=error_msg)
+                return None
+
             self._update_progress(status_message=f"Dataset formatted and ready for training")
             print(f"Dataset formatted successfully\n")
 
diff --git a/studio/backend/core/training/training.py b/studio/backend/core/training/training.py
index 4bff972447..147dd2238c 100644
--- a/studio/backend/core/training/training.py
+++ b/studio/backend/core/training/training.py
@@ -117,7 +117,9 @@ class TrainingBackend:
                        eval_split: str = None,
                        eval_steps: float = 0.00,
                        is_dataset_image: bool = False,
-                       is_dataset_audio: bool = False) -> bool:
+                       is_dataset_audio: bool = False,
+                       dataset_slice_start: int = None,
+                       dataset_slice_end: int = None) -> bool:
         """
         Start training.
 
@@ -228,6 +230,8 @@ class TrainingBackend:
                 train_split=train_split,
                 eval_split=eval_split,
                 eval_steps=eval_steps,
+                dataset_slice_start=dataset_slice_start,
+                dataset_slice_end=dataset_slice_end,
             )
 
             # Unpack: load_and_format_dataset returns (dataset, eval_dataset)
diff --git a/studio/backend/models/datasets.py b/studio/backend/models/datasets.py
index b545c4be76..0fd3db7955 100644
--- a/studio/backend/models/datasets.py
+++ b/studio/backend/models/datasets.py
@@ -37,3 +37,4 @@ class CheckFormatResponse(BaseModel):
     detected_speaker_column: Optional[str] = None
     preview_samples: Optional[List[Dict]] = None
     total_rows: Optional[int] = None
+    warning: Optional[str] = None
diff --git a/studio/backend/models/training.py b/studio/backend/models/training.py
index afa04f491c..5cc8141bac 100644
--- a/studio/backend/models/training.py
+++ b/studio/backend/models/training.py
@@ -22,6 +22,8 @@ class TrainingStartRequest(BaseModel):
     train_split: Optional[str] = Field("train", description="Training split name")
     eval_split: Optional[str] = Field(None, description="Eval split name. None = auto-detect")
     eval_steps: float = Field(0.00, description="Fraction of total steps between evals (0-1)")
+    dataset_slice_start: Optional[int] = Field(None, description="Inclusive start row index for dataset slicing")
+    dataset_slice_end: Optional[int] = Field(None, description="Inclusive end row index for dataset slicing")
 
     @model_validator(mode="before")
     @classmethod
diff --git a/studio/backend/routes/datasets.py b/studio/backend/routes/datasets.py
index 822f6c972b..4669f05a93 100644
--- a/studio/backend/routes/datasets.py
+++ b/studio/backend/routes/datasets.py
@@ -5,7 +5,7 @@ import base64
 import io
 import sys
 from pathlib import Path
-from fastapi import APIRouter, HTTPException
+from fastapi import APIRouter, Depends, HTTPException
 import logging
 
 # Add backend directory to path
@@ -15,6 +15,7 @@ if str(backend_path) not in sys.path:
 
 # Import dataset utilities
 from utils.datasets import check_dataset_format
+from auth.authentication import get_current_subject
 
 router = APIRouter()
 logger = logging.getLogger(__name__)
@@ -84,7 +85,10 @@ DATA_EXTS = (
 
 
 @router.post("/check-format", response_model=CheckFormatResponse)
-def check_format(request: CheckFormatRequest):
+def check_format(
+    request: CheckFormatRequest,
+    current_subject: str = Depends(get_current_subject),
+):
     """
     Check if a dataset requires manual column mapping.
 
@@ -207,6 +211,21 @@ def check_format(request: CheckFormatRequest):
         else:
             preview_samples = _serialize_preview_rows(preview_slice)
 
+        # Lightweight URL-based image detection for VLM datasets
+        warning = None
+        image_col = result.get("detected_image_column")
+        if image_col and image_col in (result.get("columns") or []):
+            try:
+                sample_val = preview_slice[0][image_col]
+                if isinstance(sample_val, str) and sample_val.startswith(("http://", "https://")):
+                    warning = (
+                        "This dataset contains image URLs instead of embedded images. "
+                        "Images will be downloaded during training, which may be slow for large datasets."
+                    )
+                    logger.info(f"URL-based image column detected: {image_col}")
+            except Exception:
+                pass
+
         return CheckFormatResponse(
             requires_manual_mapping=result["requires_manual_mapping"],
             detected_format=result["detected_format"],
@@ -221,6 +240,7 @@ def check_format(request: CheckFormatRequest):
             detected_speaker_column=result.get("detected_speaker_column"),
             preview_samples=preview_samples,
             total_rows=total_rows,
+            warning=warning,
         )
 
     except HTTPException:
diff --git a/studio/backend/routes/training.py b/studio/backend/routes/training.py
index 27c7fad91a..0cb97d9801 100644
--- a/studio/backend/routes/training.py
+++ b/studio/backend/routes/training.py
@@ -149,6 +149,8 @@ async def start_training(
             "train_split": request.train_split,
             "eval_split": request.eval_split,
             "eval_steps": request.eval_steps,
+            "dataset_slice_start": request.dataset_slice_start,
+            "dataset_slice_end": request.dataset_slice_end,
             "custom_format_mapping": request.custom_format_mapping,
             "num_epochs": request.num_epochs,
             "learning_rate": request.learning_rate,
diff --git a/studio/backend/utils/datasets/dataset_utils.py b/studio/backend/utils/datasets/dataset_utils.py
index 6b3cc70105..9c78d1a49a 100644
--- a/studio/backend/utils/datasets/dataset_utils.py
+++ b/studio/backend/utils/datasets/dataset_utils.py
@@ -621,6 +621,7 @@ def format_and_template_dataset(
     aliases_for_assistant=["gpt", "assistant", "output",],
     batch_size=1000,
     num_proc=None,
+    progress_callback=None,
 ):
     """
     Convenience function that combines format_dataset and apply_chat_template_to_dataset.
@@ -666,6 +667,7 @@ def format_and_template_dataset(
                         text_column=user_vlm_text_column,
                         image_column=user_vlm_image_column,
                         dataset_name=dataset_name,
+                        progress_callback=progress_callback,
                     )
                     warnings.append(f"Applied user VLM mapping: image='{user_vlm_image_column}', text='{user_vlm_text_column}'")
                     
@@ -762,6 +764,7 @@ def format_and_template_dataset(
                     text_column=vlm_text_column,
                     image_column=vlm_image_column,
                     dataset_name=dataset_name,
+                    progress_callback=progress_callback,
                 )
 
                 if vlm_instruction:
diff --git a/studio/backend/utils/datasets/format_conversion.py b/studio/backend/utils/datasets/format_conversion.py
index 6436e7a82a..41a9617857 100644
--- a/studio/backend/utils/datasets/format_conversion.py
+++ b/studio/backend/utils/datasets/format_conversion.py
@@ -238,24 +238,51 @@ def convert_alpaca_to_chatml(dataset, batch_size=1000, num_proc=None):
     return dataset.map(_convert, **dataset_map_kwargs)
 
 
+def _format_eta(seconds):
+    """Format seconds into a human-readable ETA string."""
+    if seconds < 60:
+        return f"{seconds:.0f}s"
+    elif seconds < 3600:
+        m, s = divmod(int(seconds), 60)
+        return f"{m}m {s}s"
+    else:
+        h, remainder = divmod(int(seconds), 3600)
+        m, _ = divmod(remainder, 60)
+        return f"{h}h {m}m"
+
+
 def convert_to_vlm_format(
     dataset,
     instruction=None,
     text_column="text",
     image_column="image",
     dataset_name=None,
+    progress_callback=None,
 ):
     """
     Converts simple {image, text} format to VLM messages format.
 
     Returns a LIST, not a HuggingFace Dataset (to preserve PIL Images).
 
+    For URL-based image datasets, runs a 200-sample parallel probe first to
+    estimate download speed and failure rate, then reports time estimate or
+    warning through progress_callback before proceeding with the full conversion.
+
+    Args:
+        progress_callback: Optional callable(status_message=str) to report
+                          progress to the training overlay.
+
     Returns:
         list: List of dicts with 'messages' field
     """
     from PIL import Image
     from .vlm_processing import generate_smart_vlm_instruction
 
+    def _notify(msg):
+        """Send status update to the training overlay if callback is available."""
+        if progress_callback:
+            progress_callback(status_message=msg)
+
     # Generate smart instruction if not provided
     if instruction is None:
         instruction_info = generate_smart_vlm_instruction(
@@ -281,12 +308,17 @@ def convert_to_vlm_format(
 
     def _convert_single_sample(sample):
         """Convert a single sample to VLM format."""
-        # Get image (might be PIL Image or path)
+        # Get image (might be PIL Image, local path, or URL)
         image_data = sample[image_column]
 
-        # Handle image paths
         if isinstance(image_data, str):
-            image_data = Image.open(image_data).convert("RGB")
+            if image_data.startswith(("http://", "https://")):
+                import fsspec
+                from io import BytesIO
+                with fsspec.open(image_data, "rb", expand=True) as f:
+                    image_data = Image.open(BytesIO(f.read())).convert("RGB")
+            else:
+                image_data = Image.open(image_data).convert("RGB")
 
         # Get text
         text_data = sample[text_column]
@@ -317,11 +349,143 @@ def convert_to_vlm_format(
         # Return dict with messages
         return {"messages": messages}
 
-    # Use list comprehension and return the LIST directly
-    print(f"🔄 Converting {len(dataset)} samples to VLM format...")
-    converted_list = [_convert_single_sample(sample) for sample in dataset]
+    total = len(dataset)
+    first_image = next(iter(dataset))[image_column]
+    has_urls = isinstance(first_image, str) and first_image.startswith(("http://", "https://"))
 
-    print(f"✅ Converted {len(converted_list)} samples")
+    # ── URL probe: 200 samples with parallel workers to estimate speed + failure rate ──
+    PROBE_SIZE = 200
+    MAX_FAIL_RATE = 0.3
+
+    if has_urls and total > PROBE_SIZE:
+        import time
+        from concurrent.futures import ThreadPoolExecutor, as_completed
+        from utils.hardware import safe_num_proc
+
+        num_workers = safe_num_proc()
+        _notify(f"Probing {PROBE_SIZE} image URLs with {num_workers} workers...")
+        print(f"🔍 Probing {PROBE_SIZE}/{total} image URLs with {num_workers} workers...")
+
+        probe_samples = [dataset[i] for i in range(PROBE_SIZE)]
+        probe_ok = 0
+        probe_fail = 0
+        probe_start = time.time()
+
+        with ThreadPoolExecutor(max_workers=num_workers) as executor:
+            futures = {executor.submit(_convert_single_sample, s): s for s in probe_samples}
+            for future in as_completed(futures):
+                try:
+                    future.result()
+                    probe_ok += 1
+                except Exception:
+                    probe_fail += 1
+
+        probe_elapsed = time.time() - probe_start
+        probe_total = probe_ok + probe_fail
+        fail_rate = probe_fail / probe_total if probe_total > 0 else 0
+        throughput = probe_total / probe_elapsed if probe_elapsed > 0 else 0
+
+        if fail_rate >= MAX_FAIL_RATE:
+            msg = (
+                f"⚠️ {fail_rate:.0%} of the first {PROBE_SIZE} images failed to download "
+                f"({probe_fail}/{probe_total}). "
+                "This dataset has too many broken or unreachable image URLs. "
+                "Consider using a dataset with embedded images instead."
+            )
+            print(msg)
+            _notify(msg)
+            raise ValueError(msg)
+
+        # Estimate total time for remaining samples
+        remaining = total - PROBE_SIZE
+        estimated_seconds = remaining / throughput if throughput > 0 else 0
+        eta_str = _format_eta(estimated_seconds)
+
+        info_msg = (
+            f"Downloading {total:,} images ({num_workers} workers, ~{throughput:.1f} img/s). "
+            f"Estimated time: ~{eta_str}"
+        )
+        if probe_fail > 0:
+            info_msg += f" | {fail_rate:.0%} broken URLs will be skipped"
+
+        print(f"✅ Probe passed: {probe_ok}/{probe_total} ok, {probe_fail} failed ({fail_rate:.0%}), {throughput:.1f} img/s")
+        print(f"⏱️ Estimated time for {total:,} samples: ~{eta_str}")
+        _notify(info_msg)
+
+    # ── Full conversion with progress ──
+    from tqdm import tqdm
+
+    print(f"🔄 Converting {total} samples to VLM format...")
+    converted_list = []
+    failed_count = 0
+
+    if has_urls:
+        # Parallel conversion for URL-based datasets
+        import time
+        from concurrent.futures import ThreadPoolExecutor, as_completed
+        from utils.hardware import safe_num_proc
+
+        num_workers = safe_num_proc()
+        batch_size = 500
+        start_time = time.time()
+
+        for batch_start in range(0, total, batch_size):
+            batch_end = min(batch_start + batch_size, total)
+            batch_samples = [dataset[i] for i in range(batch_start, batch_end)]
+
+            with ThreadPoolExecutor(max_workers=num_workers) as executor:
+                futures = {executor.submit(_convert_single_sample, s): i for i, s in enumerate(batch_samples)}
+                batch_results = [None] * len(batch_samples)
+                for future in as_completed(futures):
+                    idx = futures[future]
+                    try:
+                        batch_results[idx] = future.result()
+                    except Exception:
+                        failed_count += 1
+
+            converted_list.extend(r for r in batch_results if r is not None)
+
+            # Progress update every batch
+            elapsed = time.time() - start_time
+            done = batch_end
+            rate = done / elapsed if elapsed > 0 else 0
+            remaining_time = (total - done) / rate if rate > 0 else 0
+            eta_str = _format_eta(remaining_time)
+            progress_msg = f"Downloading images: {done:,}/{total:,} ({done*100//total}%) | ~{eta_str} remaining | {failed_count} skipped"
+            print(f"  [{done}/{total}] {rate:.1f} img/s, {failed_count} failed, ETA {eta_str}")
+            _notify(progress_msg)
+    else:
+        # Sequential conversion for local/embedded images (fast, no I/O bottleneck)
+        pbar = tqdm(dataset, total=total, desc="Converting VLM samples", unit="sample")
+        for sample in pbar:
+            try:
+                converted_list.append(_convert_single_sample(sample))
+            except Exception:
+                failed_count += 1
+            pbar.set_postfix(ok=len(converted_list), failed=failed_count, refresh=False)
+        pbar.close()
+
+    if failed_count > 0:
+        fail_rate = failed_count / total
+        print(f"⚠️ Skipped {failed_count}/{total} ({fail_rate:.0%}) samples with broken/unreachable images")
+        # For datasets that skipped the probe (small URL datasets), check fail rate now
+        if has_urls and fail_rate >= MAX_FAIL_RATE:
+            msg = (
+                f"⚠️ {fail_rate:.0%} of images failed to download ({failed_count}/{total}). "
+                "This dataset has too many broken or unreachable image URLs. "
+                "Consider using a dataset with embedded images instead."
+            )
+            _notify(msg)
+            raise ValueError(msg)
+
+    if len(converted_list) == 0:
+        raise ValueError(
+            f"All {total} samples failed during VLM conversion — no usable images found. "
+            "This dataset may contain only image URLs that are no longer accessible."
+        )
+
+    print(f"✅ Converted {len(converted_list)}/{total} samples")
+    _notify(f"Converted {len(converted_list):,}/{total:,} images successfully")
 
     # Return list, NOT Dataset
     return converted_list
diff --git a/studio/backend/utils/hardware/hardware.py b/studio/backend/utils/hardware/hardware.py
index b885e130d5..fd43e620bb 100644
--- a/studio/backend/utils/hardware/hardware.py
+++ b/studio/backend/utils/hardware/hardware.py
@@ -423,6 +423,11 @@ def safe_num_proc(desired: Optional[int] = None) -> int:
     """
     Return a safe ``num_proc`` for ``dataset.map()`` calls.
 
+    On Windows, always returns 1 because Python uses ``spawn`` instead of
+    ``fork`` for multiprocessing — the overhead of re-importing torch,
+    transformers, unsloth etc. per worker is typically slower than
+    single-process for normal dataset sizes.
+
     On multi-GPU machines the NVIDIA driver spawns extra background threads,
     making ``os.fork()`` prone to deadlocks when many workers are created.
     This helper caps ``num_proc`` to 4 on such machines.
@@ -438,6 +443,12 @@ def safe_num_proc(desired: Optional[int] = None) -> int:
         A safe integer ≥ 1.
     """
     import os
+    import sys
+
+    # Windows uses 'spawn' for multiprocessing — the overhead of re-importing
+    # torch/transformers/unsloth per worker is typically slower than single-process.
+    if sys.platform == "win32":
+        return 1
 
     if desired is None or not isinstance(desired, int):
         desired = max(1, os.cpu_count() // 3)
diff --git a/studio/frontend/src/components/ui/select.tsx b/studio/frontend/src/components/ui/select.tsx
index 52fe4e5a75..4c500af08e 100644
--- a/studio/frontend/src/components/ui/select.tsx
+++ b/studio/frontend/src/components/ui/select.tsx
@@ -4,8 +4,8 @@ import { Select as SelectPrimitive } from "radix-ui";
 import type * as React from "react";
 import { createContext, useContext, useState } from "react";
 
-import { cn } from "@/lib/utils";
-import { useDialogPortalContainer } from "@/components/ui/dialog";
+import { cn } from "@/lib/utils";
+import { useDialogPortalContainer } from "@/components/ui/dialog";
 import {
   ArrowDown01Icon,
   ArrowUp01Icon,
@@ -92,22 +92,22 @@ function SelectTrigger({
   );
 }
 
-function SelectContent({
-  className,
-  children,
-  position = "item-aligned",
-  align = "center",
-  container,
-  ...props
-}: React.ComponentProps<typeof SelectPrimitive.Content> & {
-  container?: HTMLElement | null;
-}) {
-  const dialogContainer = useDialogPortalContainer();
-  return (
-    <SelectPrimitive.Portal container={container ?? dialogContainer ?? undefined}>
-      <SelectPrimitive.Content
-        data-slot="select-content"
-        data-align-trigger={position === "item-aligned"}
+function SelectContent({
+  className,
+  children,
+  position = "item-aligned",
+  align = "center",
+  container,
+  ...props
+}: React.ComponentProps<typeof SelectPrimitive.Content> & {
+  container?: HTMLElement | null;
+}) {
+  const dialogContainer = useDialogPortalContainer();
+  return (
+    <SelectPrimitive.Portal container={container ?? dialogContainer ?? undefined}>
+      <SelectPrimitive.Content
+        data-slot="select-content"
+        data-align-trigger={position === "item-aligned"}
         className={cn(
           "bg-popover text-popover-foreground 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 shadow-border ring-1 ring-border 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 ",
           position === "popper" &&
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 abdce2bd47..aa1dc5bd4f 100644
--- a/studio/frontend/src/features/studio/sections/dataset-preview-dialog.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-preview-dialog.tsx
@@ -341,6 +341,13 @@ export function DatasetPreviewDialog({
                 />
               </div>
 
+              {data.warning && (
+                <div className="rounded-lg border border-amber-200 bg-amber-50 px-4 py-3 text-xs text-amber-700 dark:border-amber-800 dark:bg-amber-950 dark:text-amber-400 mb-4 flex items-start gap-2.5">
+                  <HugeiconsIcon icon={AlertCircleIcon} className="size-4 shrink-0 mt-0.5" />
+                  <span>{data.warning}</span>
+                </div>
+              )}
+
               {mappingEnabled && (
                 <DatasetMappingCard
                   mapping={manualMapping}
diff --git a/studio/frontend/src/features/studio/sections/dataset-section.tsx b/studio/frontend/src/features/studio/sections/dataset-section.tsx
index 57e50bced5..28254adcc7 100644
--- a/studio/frontend/src/features/studio/sections/dataset-section.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-section.tsx
@@ -13,6 +13,7 @@ import {
   ComboboxItem,
   ComboboxList,
 } from "@/components/ui/combobox";
+import { Input } from "@/components/ui/input";
 import { InputGroupAddon } from "@/components/ui/input-group";
 import {
   Select,
@@ -75,6 +76,10 @@ export function DatasetSection() {
     setDatasetEvalSplit,
     hfToken,
     modelType,
+    datasetSliceStart,
+    setDatasetSliceStart,
+    datasetSliceEnd,
+    setDatasetSliceEnd,
   } = useTrainingConfigStore(
     useShallow((s) => ({
       dataset: s.dataset,
@@ -89,6 +94,10 @@ export function DatasetSection() {
       setDatasetEvalSplit: s.setDatasetEvalSplit,
       hfToken: s.hfToken,
       modelType: s.modelType,
+      datasetSliceStart: s.datasetSliceStart,
+      setDatasetSliceStart: s.setDatasetSliceStart,
+      datasetSliceEnd: s.datasetSliceEnd,
+      setDatasetSliceEnd: s.setDatasetSliceEnd,
     })),
   );
 
@@ -293,51 +302,118 @@ export function DatasetSection() {
             Advanced
           </CollapsibleTrigger>
           <CollapsibleContent className="mt-3">
-            <div className="flex flex-col gap-2">
-              <span className="flex items-center gap-1.5 text-xs font-medium text-muted-foreground">
-                Target Format
-                <Tooltip>
-                  <TooltipTrigger asChild={true}>
-                    <button
-                      type="button"
-                      className="text-foreground/70 hover:text-foreground"
-                    >
-                      <HugeiconsIcon
-                        icon={InformationCircleIcon}
-                        className="size-3"
-                      />
-                    </button>
-                  </TooltipTrigger>
-                  <TooltipContent>
-                    Format of your training data. Auto-detect works for most
-                    datasets.{" "}
-                    <a
-                      href="https://unsloth.ai/docs/get-started/fine-tuning-llms-guide/datasets-guide"
-                      target="_blank"
-                      rel="noopener noreferrer"
-                      className="text-primary underline"
-                    >
-                      Read more
-                    </a>
-                  </TooltipContent>
-                </Tooltip>
-              </span>
-              <Select
-                value={datasetFormat}
-                onValueChange={(v) =>
-                  setDatasetFormat(v as typeof datasetFormat)
-                }
-              >
-                <SelectTrigger className="w-full">
-                  <SelectValue />
-                </SelectTrigger>
-                <SelectContent>
-                  <SelectItem value="auto">Auto</SelectItem>
-                  <SelectItem value="alpaca">Alpaca</SelectItem>
-                  <SelectItem value="chatml">ChatML</SelectItem>
-                  <SelectItem value="sharegpt">ShareGPT</SelectItem>
-                </SelectContent>
-              </Select>
+            <div className="flex flex-col gap-4">
+              <div className="flex flex-col gap-2">
+                <span className="flex items-center gap-1.5 text-xs font-medium text-muted-foreground">
+                  Target Format
+                  <Tooltip>
+                    <TooltipTrigger asChild={true}>
+                      <button
+                        type="button"
+                        className="text-foreground/70 hover:text-foreground"
+                      >
+                        <HugeiconsIcon
+                          icon={InformationCircleIcon}
+                          className="size-3"
+                        />
+                      </button>
+                    </TooltipTrigger>
+                    <TooltipContent>
+                      Format of your training data. Auto-detect works for most
+                      datasets.{" "}
+                      <a
+                        href="https://unsloth.ai/docs/get-started/fine-tuning-llms-guide/datasets-guide"
+                        target="_blank"
+                        rel="noopener noreferrer"
+                        className="text-primary underline"
+                      >
+                        Read more
+                      </a>
+                    </TooltipContent>
+                  </Tooltip>
+                </span>
+                <Select
+                  value={datasetFormat}
+                  onValueChange={(v) =>
+                    setDatasetFormat(v as typeof datasetFormat)
+                  }
+                >
+                  <SelectTrigger className="w-full">
+                    <SelectValue />
+                  </SelectTrigger>
+                  <SelectContent>
+                    <SelectItem value="auto">Auto</SelectItem>
+                    <SelectItem value="alpaca">Alpaca</SelectItem>
+                    <SelectItem value="chatml">ChatML</SelectItem>
+                    <SelectItem value="sharegpt">ShareGPT</SelectItem>
+                  </SelectContent>
+                </Select>
+              </div>
+              <div className="grid grid-cols-2 gap-3">
+                <div className="flex flex-col gap-1.5">
+                  <span className="flex items-center gap-1.5 text-xs font-medium text-muted-foreground">
+                    Train Split Start
+                    <Tooltip>
+                      <TooltipTrigger asChild={true}>
+                        <button
+                          type="button"
+                          className="text-foreground/70 hover:text-foreground"
+                        >
+                          <HugeiconsIcon
+                            icon={InformationCircleIcon}
+                            className="size-3"
+                          />
+                        </button>
+                      </TooltipTrigger>
+                      <TooltipContent>
+                        Only train on a subset of your training split by
+                        specifying a start row index (inclusive, 0-based).
+                        Leave empty to start from the first row.
+                      </TooltipContent>
+                    </Tooltip>
+                  </span>
+                  <Input
+                    inputMode="numeric"
+                    placeholder="0"
+                    value={datasetSliceStart ?? ""}
+                    onChange={(e) =>
+                      setDatasetSliceStart(e.target.value || null)
+                    }
+                  />
+                </div>
+                <div className="flex flex-col gap-1.5">
+                  <span className="flex items-center gap-1.5 text-xs font-medium text-muted-foreground">
+                    Train Split End
+                    <Tooltip>
+                      <TooltipTrigger asChild={true}>
+                        <button
+                          type="button"
+                          className="text-foreground/70 hover:text-foreground"
+                        >
+                          <HugeiconsIcon
+                            icon={InformationCircleIcon}
+                            className="size-3"
+                          />
+                        </button>
+                      </TooltipTrigger>
+                      <TooltipContent>
+                        Last row index to include from the training split
+                        (inclusive, 0-based). For example, set Start to 0 and
+                        End to 99 to train on the first 100 rows. Leave empty
+                        to use all remaining rows.
+                      </TooltipContent>
+                    </Tooltip>
+                  </span>
+                  <Input
+                    inputMode="numeric"
+                    placeholder="End"
+                    value={datasetSliceEnd ?? ""}
+                    onChange={(e) =>
+                      setDatasetSliceEnd(e.target.value || null)
+                    }
+                  />
+                </div>
+              </div>
             </div>
           </CollapsibleContent>
         </Collapsible>
diff --git a/studio/frontend/src/features/training/api/datasets-api.ts b/studio/frontend/src/features/training/api/datasets-api.ts
index 7bba75ca38..b2348abed8 100644
--- a/studio/frontend/src/features/training/api/datasets-api.ts
+++ b/studio/frontend/src/features/training/api/datasets-api.ts
@@ -1,3 +1,4 @@
+import { authFetch } from "@/features/auth";
 import type { CheckFormatResponse } from "../types/datasets";
 
 type CheckDatasetFormatArgs = {
@@ -15,7 +16,7 @@ export async function checkDatasetFormat({
   split,
   isVlm,
 }: CheckDatasetFormatArgs): Promise<CheckFormatResponse> {
-  const res = await fetch("/api/datasets/check-format", {
+  const res = await authFetch("/api/datasets/check-format", {
     method: "POST",
     headers: { "Content-Type": "application/json" },
     body: JSON.stringify({
diff --git a/studio/frontend/src/features/training/api/mappers.ts b/studio/frontend/src/features/training/api/mappers.ts
index ed8142f6ad..ca4339838c 100644
--- a/studio/frontend/src/features/training/api/mappers.ts
+++ b/studio/frontend/src/features/training/api/mappers.ts
@@ -4,6 +4,15 @@ import type { TrainingStartRequest } from "../types/api";
 const BACKEND_LORA_TYPE = "LoRA/QLoRA";
 const BACKEND_FULL_TYPE = "Full Finetuning";
 
+function parseSliceValue(value: string | null): number | null {
+  if (value == null) return null;
+  const trimmed = value.trim();
+  if (!trimmed) return null;
+  const num = Number(trimmed);
+  if (!Number.isFinite(num) || !Number.isInteger(num)) return null;
+  return num;
+}
+
 export function toBackendTrainingType(trainingMethod: string): string {
   return trainingMethod === "full" ? BACKEND_FULL_TYPE : BACKEND_LORA_TYPE;
 }
@@ -27,6 +36,8 @@ export function buildTrainingStartPayload(
     subset: hfDataset ? config.datasetSubset : null,
     train_split: hfDataset ? config.datasetSplit : null,
     eval_split: hfDataset ? config.datasetEvalSplit : null,
+    dataset_slice_start: parseSliceValue(config.datasetSliceStart),
+    dataset_slice_end: parseSliceValue(config.datasetSliceEnd),
     local_datasets: [],
     format_type: config.datasetFormat,
     custom_format_mapping: customFormatMapping,
diff --git a/studio/frontend/src/features/training/components/hf-dataset-subset-split-selectors.tsx b/studio/frontend/src/features/training/components/hf-dataset-subset-split-selectors.tsx
index d21fd55ff4..148341e4de 100644
--- a/studio/frontend/src/features/training/components/hf-dataset-subset-split-selectors.tsx
+++ b/studio/frontend/src/features/training/components/hf-dataset-subset-split-selectors.tsx
@@ -106,7 +106,7 @@ export function HfDatasetSubsetSplitSelectors({
               : "rounded-lg border border-amber-200 bg-amber-50 px-3.5 py-2.5 text-xs text-amber-700 dark:border-amber-800 dark:bg-amber-950 dark:text-amber-400"
           }
         >
-          Could not fetch dataset splits: {error}
+          {error}
         </div>
       )}
 
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 2225857c07..1aaa58ea12 100644
--- a/studio/frontend/src/features/training/hooks/use-training-actions.ts
+++ b/studio/frontend/src/features/training/hooks/use-training-actions.ts
@@ -16,6 +16,19 @@ const ROLE_REMAP: Record<string, Record<string, string>> = {
   sharegpt: { user: "human", assistant: "gpt", system: "system" },
 };
 
+function normalizeTrainingStartError(message: string): string {
+  const normalized = message.toLowerCase();
+  const isLegacyDatasetScriptError =
+    normalized.includes("failed to check dataset format") &&
+    normalized.includes("dataset scripts are no longer supported");
+
+  if (isLegacyDatasetScriptError) {
+    return "This Hub dataset relies on a legacy custom script and isn’t supported in this training flow.";
+  }
+
+  return message;
+}
+
 export function useTrainingActions() {
   const isStarting = useTrainingRuntimeStore((state) => state.isStarting);
   const startError = useTrainingRuntimeStore((state) => state.startError);
@@ -94,7 +107,9 @@ export function useTrainingActions() {
       const response = await startTraining(payload);
 
       if (response.status === "error") {
-        runtimeStore.setStartError(response.error || response.message);
+        const rawMessage = response.error || response.message;
+        const safeMessage = normalizeTrainingStartError(rawMessage);
+        runtimeStore.setStartError(safeMessage);
         runtimeStore.setStarting(false);
         return false;
       }
@@ -103,9 +118,10 @@ export function useTrainingActions() {
       await syncTrainingRuntimeFromBackend();
       return true;
     } catch (error) {
-      const message =
+      const rawMessage =
         error instanceof Error ? error.message : "Failed to start training";
-      runtimeStore.setStartError(message);
+      const safeMessage = normalizeTrainingStartError(rawMessage);
+      runtimeStore.setStartError(safeMessage);
       runtimeStore.setStarting(false);
       return false;
     }
diff --git a/studio/frontend/src/features/training/stores/training-config-store.ts b/studio/frontend/src/features/training/stores/training-config-store.ts
index b9aa2953ef..a88a110ea5 100644
--- a/studio/frontend/src/features/training/stores/training-config-store.ts
+++ b/studio/frontend/src/features/training/stores/training-config-store.ts
@@ -28,6 +28,8 @@ const initialState: TrainingConfigState = {
   datasetSplit: null,
   datasetEvalSplit: null,
   datasetManualMapping: emptyManualMapping(),
+  datasetSliceStart: null,
+  datasetSliceEnd: null,
   uploadedFile: null,
   isCheckingVision: false,
   isVisionModel: false,
@@ -261,6 +263,8 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
             datasetSplit: null,
             datasetEvalSplit: null,
             datasetManualMapping: emptyManualMapping(),
+            datasetSliceStart: null,
+            datasetSliceEnd: null,
             isDatasetImage: null,
             isCheckingDataset: false,
           });
@@ -317,7 +321,10 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
         },
         setDatasetManualMapping: (datasetManualMapping) =>
           set({ datasetManualMapping }),
-        setUploadedFile: (uploadedFile) => set({ uploadedFile }),
+        setDatasetSliceStart: (datasetSliceStart) => set({ datasetSliceStart }),
+        setDatasetSliceEnd: (datasetSliceEnd) => set({ datasetSliceEnd }),
+        setUploadedFile: (uploadedFile) =>
+          set({ uploadedFile, datasetSliceStart: null, datasetSliceEnd: null }),
         setEpochs: (epochs) => set({ epochs }),
         setContextLength: (contextLength) => set({ contextLength }),
         setLearningRate: (learningRate) => set({ learningRate }),
@@ -374,7 +381,7 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
     },
     {
       name: "unsloth_training_config_v1",
-      version: 6,
+      version: 7,
       migrate: (persisted, version) => {
         const s = persisted as Record<string, unknown>;
         if (version < 2 && s.datasetSubset == null && s.datasetConfig != null) {
@@ -393,6 +400,10 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
         if (version < 6 && s.datasetEvalSplit == null) {
           s.datasetEvalSplit = null;
         }
+        if (version < 7) {
+          s.datasetSliceStart ??= null;
+          s.datasetSliceEnd ??= null;
+        }
         return s as unknown as TrainingConfigStore;
       },
       partialize: partializePersistedState,
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 7d5c86549b..41b0fcca07 100644
--- a/studio/frontend/src/features/training/stores/training-runtime-store.ts
+++ b/studio/frontend/src/features/training/stores/training-runtime-store.ts
@@ -187,7 +187,6 @@ export const useTrainingRuntimeStore = create<TrainingRuntimeStore>()((set) => (
         evalEnabled: payload.eval_enabled ?? state.evalEnabled,
         message: payload.message,
         error: payload.error,
-        startError: null,
         currentStep:
           typeof detailStep === "number" ? Math.max(detailStep, 0) : state.currentStep,
         totalSteps:
diff --git a/studio/frontend/src/features/training/types/api.ts b/studio/frontend/src/features/training/types/api.ts
index e22bd2b9ac..0dcb18b1bf 100644
--- a/studio/frontend/src/features/training/types/api.ts
+++ b/studio/frontend/src/features/training/types/api.ts
@@ -8,6 +8,8 @@ export interface TrainingStartRequest {
   subset: string | null;
   train_split: string | null;
   eval_split: string | null;
+  dataset_slice_start: number | null;
+  dataset_slice_end: number | null;
   local_datasets: string[];
   format_type: string;
   custom_format_mapping?: Record<string, string> | null;
diff --git a/studio/frontend/src/features/training/types/config.ts b/studio/frontend/src/features/training/types/config.ts
index c66d0ad160..f773eee129 100644
--- a/studio/frontend/src/features/training/types/config.ts
+++ b/studio/frontend/src/features/training/types/config.ts
@@ -26,6 +26,8 @@ export interface TrainingConfigState {
   datasetSplit: string | null;
   datasetEvalSplit: string | null;
   datasetManualMapping: DatasetManualMapping;
+  datasetSliceStart: string | null;
+  datasetSliceEnd: string | null;
   uploadedFile: string | null;
   epochs: number;
   contextLength: number;
@@ -85,6 +87,8 @@ export interface TrainingConfigActions {
   setDatasetSplit: (split: string | null) => void;
   setDatasetEvalSplit: (split: string | null) => void;
   setDatasetManualMapping: (mapping: DatasetManualMapping) => void;
+  setDatasetSliceStart: (value: string | null) => void;
+  setDatasetSliceEnd: (value: string | null) => void;
   setUploadedFile: (file: string | null) => void;
   setEpochs: (epochs: number) => void;
   setContextLength: (length: number) => void;
diff --git a/studio/frontend/src/features/training/types/datasets.ts b/studio/frontend/src/features/training/types/datasets.ts
index 1e556a9d43..3f0d640e5f 100644
--- a/studio/frontend/src/features/training/types/datasets.ts
+++ b/studio/frontend/src/features/training/types/datasets.ts
@@ -12,5 +12,6 @@ export type CheckFormatResponse = {
   is_image?: boolean;
   is_audio?: boolean;
   multimodal_columns?: string[] | null;
+  warning?: string | null;
 };
 
diff --git a/studio/frontend/src/hooks/use-hf-dataset-splits.ts b/studio/frontend/src/hooks/use-hf-dataset-splits.ts
index 7b8e4906ec..cda2fcbc34 100644
--- a/studio/frontend/src/hooks/use-hf-dataset-splits.ts
+++ b/studio/frontend/src/hooks/use-hf-dataset-splits.ts
@@ -35,6 +35,36 @@ export interface HfDatasetSplitsResult {
 
 const HF_SPLITS_API = "https://datasets-server.huggingface.co/splits";
 
+function normalizeDatasetSplitsError(message: string): string {
+  const normalized = message.toLowerCase();
+
+  // datasets-server returns technical script/runtime details for legacy datasets.
+  if (
+    normalized.includes("dataset scripts are no longer supported") ||
+    normalized.includes("runs arbitrary python code")
+  ) {
+    return "We can’t load subset/split options for this Hub dataset because it relies on a legacy custom script.";
+  }
+
+  if (
+    normalized.includes("unauthorized") ||
+    normalized.includes("forbidden") ||
+    normalized.includes("access token") ||
+    normalized.includes("private") ||
+    normalized.includes("gated") ||
+    normalized.includes("401") ||
+    normalized.includes("403")
+  ) {
+    return "Unable to load dataset splits. This dataset may be private or gated. Add a Hugging Face token with access and try again.";
+  }
+
+  if (normalized.includes("not found") || normalized.includes("404")) {
+    return "Dataset not found. Check the dataset name and try again.";
+  }
+
+  return "Unable to load dataset split options for this dataset.";
+}
+
 // ---------------------------------------------------------------------------
 // Hook
 // ---------------------------------------------------------------------------
@@ -101,7 +131,18 @@ export function useHfDatasetSplits(
       })
       .catch((err) => {
         if (!controller.signal.aborted) {
-          setError(err.message || "Failed to fetch dataset splits");
+          const rawErrorMessage =
+            err instanceof Error
+              ? err.message
+              : typeof err === "string"
+                ? err
+                : "Failed to fetch dataset splits";
+          console.warn("[useHfDatasetSplits] Failed to fetch dataset splits", {
+            datasetName,
+            message: rawErrorMessage,
+            error: err,
+          });
+          setError(normalizeDatasetSplitsError(rawErrorMessage));
           setEntries([]);
         }
       })
diff --git a/studio/frontend/src/index.css b/studio/frontend/src/index.css
index 2ef1ed7d96..57d6e451c8 100644
--- a/studio/frontend/src/index.css
+++ b/studio/frontend/src/index.css
@@ -270,6 +270,9 @@
     @apply font-sans;
     scrollbar-gutter: stable;
   }
+  body[data-scroll-locked] {
+    margin-right: 0 !important;
+  }
   h1,
   h2,
   h3,
diff --git a/test_llama_cpp.ps1 b/test_llama_cpp.ps1
new file mode 100644
index 0000000000..b98177eac6
--- /dev/null
+++ b/test_llama_cpp.ps1
@@ -0,0 +1,234 @@
+<#
+.SYNOPSIS
+    Test script for llama.cpp compilation and binary validation on Windows.
+    Verifies that llama-server was built with CUDA support and can start.
+
+.USAGE
+    .\test_llama_cpp.ps1
+    .\test_llama_cpp.ps1 -BinaryPath "C:\path\to\llama-server.exe"
+#>
+param(
+    [string]$BinaryPath = ""
+)
+
+$ErrorActionPreference = "Continue"
+
+Write-Host ""
+Write-Host "============================================" -ForegroundColor Cyan
+Write-Host "  llama.cpp Windows Build Test" -ForegroundColor Cyan
+Write-Host "============================================" -ForegroundColor Cyan
+Write-Host ""
+
+# -- Step 1: Locate the binary ------------------------------------------
+Write-Host "1. Locating llama-server binary..." -ForegroundColor Yellow
+
+$SearchPaths = @()
+
+if ($BinaryPath) {
+    $SearchPaths += $BinaryPath
+}
+
+# Add all known locations
+$RepoRoot = $PSScriptRoot
+$SearchPaths += Join-Path $RepoRoot "llama.cpp\build\bin\Release\llama-server.exe"
+$SearchPaths += Join-Path $RepoRoot "llama.cpp\build\bin\llama-server.exe"
+# Legacy: older setup.ps1 built under ~/.unsloth
+$SearchPaths += Join-Path $env:USERPROFILE ".unsloth\llama.cpp\build\bin\Release\llama-server.exe"
+
+# Check LLAMA_SERVER_PATH env var
+$envPath = $env:LLAMA_SERVER_PATH
+if ($envPath) {
+    $SearchPaths = @($envPath) + $SearchPaths
+}
+
+# Also check system PATH
+$systemPath = (Get-Command llama-server -ErrorAction SilentlyContinue)
+if ($systemPath) {
+    $SearchPaths += $systemPath.Source
+}
+
+$FoundBinary = $null
+foreach ($p in $SearchPaths) {
+    if (Test-Path $p) {
+        $FoundBinary = $p
+        break
+    }
+}
+
+if (-not $FoundBinary) {
+    Write-Host "   [FAIL] llama-server.exe not found!" -ForegroundColor Red
+    Write-Host ""
+    Write-Host "   Searched locations:" -ForegroundColor Gray
+    foreach ($p in $SearchPaths) {
+        Write-Host "     - $p" -ForegroundColor Gray
+    }
+    Write-Host ""
+    Write-Host "   To fix: Run setup.bat to build llama.cpp, or set:" -ForegroundColor Yellow
+    Write-Host '   $env:LLAMA_SERVER_PATH = "C:\path\to\llama-server.exe"' -ForegroundColor Yellow
+    exit 1
+}
+
+Write-Host "   [OK] Found: $FoundBinary" -ForegroundColor Green
+
+# -- Step 2: Check file info --------------------------------------------
+Write-Host ""
+Write-Host "2. Binary info..." -ForegroundColor Yellow
+
+$fileInfo = Get-Item $FoundBinary
+$sizeMB = [math]::Round($fileInfo.Length / 1MB, 1)
+Write-Host "   Size:     $sizeMB MB" -ForegroundColor Gray
+Write-Host "   Modified: $($fileInfo.LastWriteTime)" -ForegroundColor Gray
+
+# -- Step 3: Check for CUDA symbols ------------------------------------
+Write-Host ""
+Write-Host "3. Checking for CUDA support..." -ForegroundColor Yellow
+
+# Run with --help or -v and capture output to check for CUDA indicators
+$helpOutput = & $FoundBinary --version 2>&1 | Out-String
+if (-not $helpOutput) {
+    $helpOutput = ""
+}
+
+# Check binary dependencies for CUDA DLLs using dumpbin if available
+$dumpbin = (Get-Command dumpbin -ErrorAction SilentlyContinue)
+$hasCudaDlls = $false
+
+if ($dumpbin) {
+    $deps = & dumpbin /dependents $FoundBinary 2>&1 | Out-String
+    if ($deps -match "cudart|cublas|cublasLt|nvcuda") {
+        $hasCudaDlls = $true
+        Write-Host "   [OK] CUDA DLLs found in dependencies (dumpbin)" -ForegroundColor Green
+        # Extract CUDA DLL names
+        $cudaDlls = ($deps -split "`n") | Where-Object { $_ -match "cuda|cublas|nvcuda" } | ForEach-Object { $_.Trim() }
+        foreach ($dll in $cudaDlls) {
+            if ($dll) { Write-Host "     - $dll" -ForegroundColor Gray }
+        }
+    } else {
+        Write-Host "   [WARN] No CUDA DLLs found in dependencies!" -ForegroundColor Red
+        Write-Host "   This binary was likely compiled WITHOUT -DGGML_CUDA=ON" -ForegroundColor Red
+    }
+} else {
+    # Fallback: check file size (CUDA builds are typically > 50MB)
+    if ($sizeMB -gt 40) {
+        Write-Host "   [LIKELY OK] Binary is $sizeMB MB (CUDA builds are typically > 50MB)" -ForegroundColor Green
+    } else {
+        Write-Host "   [WARN] Binary is only $sizeMB MB (CPU-only builds are typically < 30MB)" -ForegroundColor Yellow
+        Write-Host "   dumpbin not available for detailed check. Install VS Build Tools." -ForegroundColor Gray
+    }
+}
+
+# -- Step 4: Quick startup test -----------------------------------------
+Write-Host ""
+Write-Host "4. Running startup test (will start and immediately stop)..." -ForegroundColor Yellow
+
+# Start llama-server on a random port with no model -- just check it initializes
+$testPort = Get-Random -Minimum 49152 -Maximum 65535
+$proc = $null
+
+try {
+    $proc = Start-Process -FilePath $FoundBinary `
+        -ArgumentList "--port", $testPort, "--host", "127.0.0.1" `
+        -PassThru -NoNewWindow -RedirectStandardError "$env:TEMP\llama_test_stderr.txt" `
+        -RedirectStandardOutput "$env:TEMP\llama_test_stdout.txt"
+
+    # Give it 3 seconds to start
+    Start-Sleep -Seconds 3
+
+    # Check if it crashed
+    if ($proc.HasExited) {
+        $exitCode = $proc.ExitCode
+        $stderr = ""
+        if (Test-Path "$env:TEMP\llama_test_stderr.txt") {
+            $stderr = Get-Content "$env:TEMP\llama_test_stderr.txt" -Raw
+        }
+        $stdout = ""
+        if (Test-Path "$env:TEMP\llama_test_stdout.txt") {
+            $stdout = Get-Content "$env:TEMP\llama_test_stdout.txt" -Raw
+        }
+
+        $allOutput = "$stdout`n$stderr"
+
+        if ($allOutput -match "failed to initialize CUDA") {
+            Write-Host "   [FAIL] CUDA initialization failed!" -ForegroundColor Red
+            Write-Host "   The binary was compiled without CUDA support or CUDA drivers are missing." -ForegroundColor Red
+            Write-Host ""
+            Write-Host "   Rebuild with: cmake -DGGML_CUDA=ON ..." -ForegroundColor Yellow
+        } elseif ($allOutput -match "HTTPS is not supported") {
+            # This is expected when LLAMA_CURL=OFF -- not a real failure
+            Write-Host "   [OK] Binary started (HTTPS warning is expected -- we use local files)" -ForegroundColor Green
+        } else {
+            Write-Host "   [WARN] Process exited with code $exitCode" -ForegroundColor Yellow
+        }
+
+        if ($allOutput.Trim()) {
+            Write-Host ""
+            Write-Host "   --- Output ---" -ForegroundColor Gray
+            $allOutput.Trim().Split("`n") | ForEach-Object { Write-Host "   $_" -ForegroundColor Gray }
+        }
+    } else {
+        Write-Host "   [OK] llama-server started successfully on port $testPort" -ForegroundColor Green
+
+        # Check CUDA detection from startup output
+        Start-Sleep -Seconds 1
+        $stderr = ""
+        if (Test-Path "$env:TEMP\llama_test_stderr.txt") {
+            $stderr = Get-Content "$env:TEMP\llama_test_stderr.txt" -Raw
+        }
+
+        if ($stderr -match "CUDA") {
+            if ($stderr -match "failed to initialize CUDA") {
+                Write-Host "   [FAIL] CUDA init failed at runtime!" -ForegroundColor Red
+            } else {
+                Write-Host "   [OK] CUDA detected at runtime" -ForegroundColor Green
+            }
+        }
+
+        # Kill it
+        Stop-Process -Id $proc.Id -Force -ErrorAction SilentlyContinue
+        Write-Host "   Stopped test server." -ForegroundColor Gray
+    }
+} catch {
+    Write-Host "   [ERROR] Could not start llama-server: $_" -ForegroundColor Red
+} finally {
+    if ($proc -and -not $proc.HasExited) {
+        Stop-Process -Id $proc.Id -Force -ErrorAction SilentlyContinue
+    }
+    Remove-Item "$env:TEMP\llama_test_stderr.txt" -ErrorAction SilentlyContinue
+    Remove-Item "$env:TEMP\llama_test_stdout.txt" -ErrorAction SilentlyContinue
+}
+
+# -- Step 5: Check llama-quantize ---------------------------------------
+Write-Host ""
+Write-Host "5. Checking llama-quantize..." -ForegroundColor Yellow
+
+$quantizePath = Join-Path (Split-Path $FoundBinary) "llama-quantize.exe"
+if (Test-Path $quantizePath) {
+    $qSize = [math]::Round((Get-Item $quantizePath).Length / 1MB, 1)
+    Write-Host "   [OK] Found: $quantizePath ($qSize MB)" -ForegroundColor Green
+} else {
+    Write-Host "   [WARN] llama-quantize.exe not found alongside llama-server" -ForegroundColor Yellow
+    Write-Host "   GGUF export/quantization won't work without it" -ForegroundColor Yellow
+}
+
+# -- Summary ------------------------------------------------------------
+Write-Host ""
+Write-Host "============================================" -ForegroundColor Cyan
+Write-Host "  Summary" -ForegroundColor Cyan
+Write-Host "============================================" -ForegroundColor Cyan
+Write-Host "   Binary:    $FoundBinary" -ForegroundColor Gray
+Write-Host "   Size:      $sizeMB MB" -ForegroundColor Gray
+if ($hasCudaDlls) {
+    Write-Host "   CUDA:      YES (confirmed via DLL deps)" -ForegroundColor Green
+} elseif ($sizeMB -gt 40) {
+    Write-Host "   CUDA:      LIKELY (large binary size)" -ForegroundColor Yellow
+} else {
+    Write-Host "   CUDA:      NO (rebuild with -DGGML_CUDA=ON)" -ForegroundColor Red
+}
+Write-Host ""
+
+if (-not $hasCudaDlls -and $sizeMB -le 40) {
+    Write-Host "To rebuild with CUDA:" -ForegroundColor Yellow
+    Write-Host '  1. Delete the build dir: Remove-Item -Recurse -Force "$env:USERPROFILE\.unsloth\llama.cpp\build"' -ForegroundColor Gray
+    Write-Host '  2. Re-run: .\setup.bat' -ForegroundColor Gray
+    Write-Host ""
+}