From e3674d6aa47e5dfff94fc0e160fa0b02a864d837 Mon Sep 17 00:00:00 2001
From: Daniel Han <danielhanchen@gmail.com>
Date: Thu, 16 Jul 2026 06:22:54 -0700
Subject: [PATCH 01/28] CI: opt tool-calling smoke tests out of the chat tool
 approval gate (#7162)

The permission-levels feature defaults an unset permission_mode to ask on
streaming requests, so the headless smoke probes hang at the approval
prompt until the job timeout. Declare permission_mode full in the tool
probe bodies; the gate itself is covered by unit tests.
---
 .github/workflows/studio-inference-smoke.yml         | 2 ++
 .github/workflows/studio-mac-inference-smoke.yml     | 2 ++
 .github/workflows/studio-windows-inference-smoke.yml | 3 +++
 3 files changed, 7 insertions(+)

diff --git a/.github/workflows/studio-inference-smoke.yml b/.github/workflows/studio-inference-smoke.yml
index cf8c021e38..58ef2558f3 100644
--- a/.github/workflows/studio-inference-smoke.yml
+++ b/.github/workflows/studio-inference-smoke.yml
@@ -729,6 +729,7 @@ jobs:
                       content, events = post_sse("/v1/chat/completions", {
                           "messages":      [{"role": "user", "content": prompt}],
                           "enable_tools":  True,
+                          "permission_mode": "full",
                           "enabled_tools": enabled,
                           "session_id":    f"{session}-att{attempt_i}",
                           "temperature":   TOOL_PROBE_TEMP,
@@ -818,6 +819,7 @@ jobs:
               content, events = post_sse("/v1/chat/completions", {
                   "messages":      [{"role": "user", "content": "Search the web for 'unsloth ai github' and summarise."}],
                   "enable_tools":  True,
+                  "permission_mode": "full",
                   "enabled_tools": ["web_search"],
                   "session_id":    "ci-tool-calling-web",
                   "temperature":   0.0,
diff --git a/.github/workflows/studio-mac-inference-smoke.yml b/.github/workflows/studio-mac-inference-smoke.yml
index d3d765aa84..946681706a 100644
--- a/.github/workflows/studio-mac-inference-smoke.yml
+++ b/.github/workflows/studio-mac-inference-smoke.yml
@@ -612,6 +612,7 @@ jobs:
           content = post_sse("/v1/chat/completions", {
               "messages":      [{"role": "user", "content": "What is 123 * 456? Use the python tool to compute it and tell me the number."}],
               "enable_tools":  True,
+              "permission_mode": "full",
               "enabled_tools": ["python"],
               "session_id":    "ci-tool-calling-py",
               "temperature":   TEMP,
@@ -647,6 +648,7 @@ jobs:
               content = post_sse("/v1/chat/completions", {
                   "messages":      [{"role": "user", "content": "Search the web for 'unsloth ai github' and summarise."}],
                   "enable_tools":  True,
+                  "permission_mode": "full",
                   "enabled_tools": ["web_search"],
                   "session_id":    "ci-tool-calling-web",
                   "temperature":   TEMP,
diff --git a/.github/workflows/studio-windows-inference-smoke.yml b/.github/workflows/studio-windows-inference-smoke.yml
index 233292f7a3..63a7e9dc8f 100644
--- a/.github/workflows/studio-windows-inference-smoke.yml
+++ b/.github/workflows/studio-windows-inference-smoke.yml
@@ -791,6 +791,7 @@ jobs:
           content = post_sse("/v1/chat/completions", {
               "messages":      [{"role": "user", "content": "What is 123 * 456? Use the python tool to compute it and tell me the number."}],
               "enable_tools":  True,
+              "permission_mode": "full",
               "enabled_tools": ["python"],
               "session_id":    "ci-tool-calling-py",
               "temperature":   TEMP,
@@ -816,6 +817,7 @@ jobs:
           content = post_sse("/v1/chat/completions", {
               "messages":      [{"role": "user", "content": "Use the terminal tool to run `echo hello-bash-tool` and tell me the exact output."}],
               "enable_tools":  True,
+              "permission_mode": "full",
               "enabled_tools": ["terminal"],
               "session_id":    "ci-tool-calling-bash",
               "temperature":   TEMP,
@@ -840,6 +842,7 @@ jobs:
               content = post_sse("/v1/chat/completions", {
                   "messages":      [{"role": "user", "content": "Search the web for 'unsloth ai github' and summarise."}],
                   "enable_tools":  True,
+                  "permission_mode": "full",
                   "enabled_tools": ["web_search"],
                   "session_id":    "ci-tool-calling-web",
                   "temperature":   TEMP,

From 030f12753c77fdc64647e72afed9d5e0adc20341 Mon Sep 17 00:00:00 2001
From: Daniel Han <danielhanchen@gmail.com>
Date: Thu, 16 Jul 2026 06:23:06 -0700
Subject: [PATCH 02/28] Fix Inkling reasoning-effort coercion for duck-typed
 engine stand-ins (#7158)

* Make the Inkling reasoning-effort coercion a module-level helper so duck-typed engine stand-ins keep working

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Align Inkling minimal reasoning effort with the reference implementation (0.1)

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
---
 studio/backend/core/inference/llama_cpp.py | 54 ++++++++++++----------
 1 file changed, 29 insertions(+), 25 deletions(-)

diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index e797cfe22a..06b68ea831 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -1541,6 +1541,31 @@ def _is_external_link(path: Path) -> bool:
     return False
 
 
+# Inkling's template takes a numeric thinking-effort dial (0..0.99) and its
+# float() coercion turns unrecognized named levels into 0, i.e. no thinking.
+# Map OpenAI-style names to the values the model was trained on. Module-level
+# so duck-typed engine stand-ins in tests do not need the attribute.
+_INKLING_REASONING_EFFORT = {
+    "none": 0.0,
+    "minimal": 0.1,
+    "low": 0.2,
+    "medium": 0.7,
+    "high": 0.9,
+    "xhigh": 0.99,
+    "max": 0.99,
+}
+
+
+def _coerce_reasoning_effort(architecture, kwargs: dict) -> dict:
+    if architecture == "inkling":
+        effort = kwargs.get("reasoning_effort")
+        if isinstance(effort, str):
+            mapped = _INKLING_REASONING_EFFORT.get(effort.strip().lower())
+            if mapped is not None:
+                kwargs["reasoning_effort"] = mapped
+    return kwargs
+
+
 class LlamaCppBackend:
     """Manages a llama-server subprocess for GGUF model inference.
 
@@ -1941,36 +1966,15 @@ class LlamaCppBackend:
     def reasoning_default(self) -> bool:
         return self._reasoning_default
 
-    # Inkling's template takes a numeric thinking-effort dial (0..0.99) and its
-    # float() coercion turns unrecognized named levels into 0, i.e. no thinking.
-    # Map OpenAI-style names to the values the model was trained on.
-    _INKLING_REASONING_EFFORT = {
-        "none": 0.0,
-        "minimal": 0.2,
-        "low": 0.2,
-        "medium": 0.7,
-        "high": 0.9,
-        "xhigh": 0.99,
-        "max": 0.99,
-    }
-
-    def _coerce_reasoning_effort(self, kwargs: dict) -> dict:
-        if getattr(self, "_architecture", None) == "inkling":
-            effort = kwargs.get("reasoning_effort")
-            if isinstance(effort, str):
-                mapped = self._INKLING_REASONING_EFFORT.get(effort.strip().lower())
-                if mapped is not None:
-                    kwargs["reasoning_effort"] = mapped
-        return kwargs
-
     def _reasoning_kwargs(self, enable_thinking: bool) -> dict:
         if self._reasoning_style == "enable_thinking_effort":
             # GLM-5.2-style: enable_thinking is the on/off gate; when on, leave
             # the template's default effort (max) in place.
             return {"enable_thinking": enable_thinking}
         if self._reasoning_style == "reasoning_effort":
-            return self._coerce_reasoning_effort(
-                {"reasoning_effort": "high" if enable_thinking else "low"}
+            return _coerce_reasoning_effort(
+                getattr(self, "_architecture", None),
+                {"reasoning_effort": "high" if enable_thinking else "low"},
             )
         return {"enable_thinking": enable_thinking}
 
@@ -2019,7 +2023,7 @@ class LlamaCppBackend:
                     kwargs["enable_thinking"] = enable_thinking
         if self._supports_preserve_thinking and preserve_thinking is not None:
             kwargs["preserve_thinking"] = preserve_thinking
-        self._coerce_reasoning_effort(kwargs)
+        _coerce_reasoning_effort(getattr(self, "_architecture", None), kwargs)
         return kwargs or None
 
     @property

From 3be49070cc02ef4932b2e67fecf050ce574b858d Mon Sep 17 00:00:00 2001
From: Nilay <118994073+NilayYadav@users.noreply.github.com>
Date: Thu, 16 Jul 2026 19:40:30 +0530
Subject: [PATCH 03/28] fix config cards clipping content at narrow window
 widths (#7146)

---
 .../src/features/studio/sections/dataset-section.tsx       | 6 +-----
 .../src/features/studio/sections/params-section.tsx        | 7 +------
 .../src/features/studio/sections/training-section.tsx      | 3 +--
 studio/frontend/src/index.css                              | 6 +-----
 4 files changed, 4 insertions(+), 18 deletions(-)

diff --git a/studio/frontend/src/features/studio/sections/dataset-section.tsx b/studio/frontend/src/features/studio/sections/dataset-section.tsx
index d00d192bb2..bb74b0d061 100644
--- a/studio/frontend/src/features/studio/sections/dataset-section.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-section.tsx
@@ -683,11 +683,7 @@ export function DatasetSection() {
         title={t("studio.dataset.title")}
         description={t("studio.dataset.description")}
         accent="indigo"
-        className={`dark:shadow-border ${
-          advancedOpen || (datasetSource === "upload" && uploadedFile)
-            ? "min-h-studio-config-column"
-            : "h-studio-config-column"
-        }`}
+        className="dark:shadow-border min-h-studio-config-column"
       >
         <div className="flex min-w-0 flex-col gap-4">
           {(() => {
diff --git a/studio/frontend/src/features/studio/sections/params-section.tsx b/studio/frontend/src/features/studio/sections/params-section.tsx
index 8d6e18b83f..ad438f63f1 100644
--- a/studio/frontend/src/features/studio/sections/params-section.tsx
+++ b/studio/frontend/src/features/studio/sections/params-section.tsx
@@ -192,7 +192,6 @@ export function ParamsSection(): ReactElement {
   const showVisionImageSize = showVisionLora && !isDeepseekOcr;
   const [loraOpen, setLoraOpen] = useState(false);
   const [hyperOpen, setHyperOpen] = useState(false);
-  const needsExpandedHeight = isCpt || (isLora && loraOpen) || hyperOpen;
   const [ctxInput, setCtxInput] = useState(String(store.contextLength));
   const ctxAnchorRef = useRef<HTMLDivElement>(null);
   const ctxItems = CONTEXT_LENGTHS.map(String);
@@ -233,11 +232,7 @@ export function ParamsSection(): ReactElement {
         title={t("studio.params.title")}
         description={t("studio.params.description")}
         accent="orange"
-        className={`${
-          needsExpandedHeight
-            ? "min-h-studio-config-column"
-            : "h-studio-config-column"
-        } duration-150`}
+        className="min-h-studio-config-column"
       >
         <div className="flex flex-col gap-4">
           <div className="flex flex-col gap-2">
diff --git a/studio/frontend/src/features/studio/sections/training-section.tsx b/studio/frontend/src/features/studio/sections/training-section.tsx
index 6d1ee9411b..5650b9c145 100644
--- a/studio/frontend/src/features/studio/sections/training-section.tsx
+++ b/studio/frontend/src/features/studio/sections/training-section.tsx
@@ -53,7 +53,6 @@ export function TrainingSection() {
     ((!store.isVisionModel && store.isDatasetImage === true) ||
       (!store.isAudioModel && store.isDatasetAudio === true));
   const configValidation = validateTrainingConfig(store);
-  const hasMessage = !!(startError || isIncompatible || (!configValidation.ok && configValidation.message));
   const fileInputRef = useRef<HTMLInputElement>(null);
 
   const handleFileUpload = (e: React.ChangeEvent<HTMLInputElement>) => {
@@ -125,7 +124,7 @@ export function TrainingSection() {
         title={t("studio.training.title")}
         description={t("studio.training.description")}
         accent="blue"
-        className={hasMessage ? "min-h-studio-config-column" : "h-studio-config-column"}
+        className="min-h-studio-config-column"
       >
         <div className="flex flex-col gap-4">
         {/* Loss chart */}
diff --git a/studio/frontend/src/index.css b/studio/frontend/src/index.css
index 159eba743f..333ed70f6a 100644
--- a/studio/frontend/src/index.css
+++ b/studio/frontend/src/index.css
@@ -2048,15 +2048,11 @@ html[data-chat-font] .aui-root {
 		}
 	}
 
-	/* Fine-tuning Studio: equal default height, expandable when needed (md+) */
+	/* Fine-tuning Studio: equal minimum card height, grows with content (md+) */
 	.min-h-studio-config-column {
 		@apply md:min-h-[520px];
 	}
 
-	.h-studio-config-column {
-		@apply md:h-[520px];
-	}
-
 	[data-streamdown="unordered-list"] {
 		list-style-type: disc;
 		list-style-position: outside;

From 8c83478da02b08bfcecef691eda78f15f050cbe9 Mon Sep 17 00:00:00 2001
From: Nilay <118994073+NilayYadav@users.noreply.github.com>
Date: Thu, 16 Jul 2026 20:54:33 +0530
Subject: [PATCH 04/28] Studio: use one shared Hugging Face token across
 Settings and training (#7152)

---------

Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
---
 .../chat/stores/chat-runtime-store.ts         | 33 ++++++++-----------
 studio/frontend/src/features/hub/index.ts     |  5 +++
 .../src/features/hub/stores/hf-token-store.ts | 25 ++++++++------
 .../studio/sections/dataset-section.tsx       | 14 ++------
 .../training/stores/training-config-store.ts  | 24 +++++++++++---
 5 files changed, 56 insertions(+), 45 deletions(-)

diff --git a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
index abdaa871c0..af99458349 100644
--- a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
+++ b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
@@ -2,7 +2,11 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import type { RememberedLoadSettings } from "@/components/assistant-ui/model-selector/remembered-load-settings";
-import { cancelStagedModelDownload } from "@/features/hub";
+import {
+  cancelStagedModelDownload,
+  mirrorHfTokenInto,
+  useHfTokenStore,
+} from "@/features/hub";
 import { toast } from "@/lib/toast";
 import { create } from "zustand";
 import { isExternalModelId, parseExternalModelId } from "../external-providers";
@@ -25,8 +29,6 @@ import {
 import { useExternalProvidersStore } from "./external-providers-store";
 import { PLUS_MENU_PINS_STORAGE_KEY } from "./plus-menu-prefs-store";
 
-const HF_TOKEN_KEY = "unsloth_hf_token";
-const HF_TOKEN_CHANGED_EVENT = "unsloth:hf-token-changed";
 export const CHAT_REASONING_ENABLED_KEY = "unsloth_chat_reasoning_enabled";
 export const CHAT_TOOLS_ENABLED_KEY = "unsloth_chat_tools_enabled";
 export const CHAT_CODE_TOOLS_ENABLED_KEY = "unsloth_chat_code_tools_enabled";
@@ -495,17 +497,6 @@ export function saveSpeculativeType(value: string | null): void {
   }
 }
 
-function notifyHfTokenChanged(value: string): void {
-  if (!canUseStorage()) return;
-  try {
-    window.dispatchEvent(
-      new CustomEvent(HF_TOKEN_CHANGED_EVENT, { detail: value }),
-    );
-  } catch {
-    // ignore
-  }
-}
-
 /** A local model staged for a deferred load (see `pendingSelection`). Shape is
  *  a subset of the load hook's `SelectedModelInput`, structurally assignable. */
 export type PendingModelSelection = {
@@ -1144,7 +1135,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   runningByThreadId: {},
   cancelByThreadId: {},
   autoTitle: false,
-  hfToken: loadString(HF_TOKEN_KEY, ""),
+  hfToken: useHfTokenStore.getState().token,
   modelsError: null,
   lastModelLoadError: null,
   activeGgufVariant: null,
@@ -1349,11 +1340,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       setScalarSettingVersion("autoTitle", autoTitle, state.autoTitle);
       return { autoTitle };
     }),
-  setHfToken: (hfToken) => {
-    saveString(HF_TOKEN_KEY, hfToken);
-    set({ hfToken });
-    notifyHfTokenChanged(hfToken);
-  },
+  setHfToken: (hfToken) => useHfTokenStore.getState().setToken(hfToken),
   setModelsError: (modelsError) => set({ modelsError }),
   setLastModelLoadError: (lastModelLoadError) => set({ lastModelLoadError }),
   setCheckpoint: (modelId, ggufVariant) =>
@@ -1837,6 +1824,12 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   setContextUsage: (contextUsage) => set({ contextUsage }),
 }));
 
+// Mirror token edits made through the shared store (e.g. Studio's field).
+const unsubscribeHfTokenMirror = mirrorHfTokenInto(useChatRuntimeStore);
+if (import.meta.hot) {
+  import.meta.hot.dispose(unsubscribeHfTokenMirror);
+}
+
 export function resolveSpeculativeSettingsForLoad({
   usePersistedPreference = false,
 }: {
diff --git a/studio/frontend/src/features/hub/index.ts b/studio/frontend/src/features/hub/index.ts
index ddcef146b0..3515f6ca76 100644
--- a/studio/frontend/src/features/hub/index.ts
+++ b/studio/frontend/src/features/hub/index.ts
@@ -2,3 +2,8 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 export { cancelStagedModelDownload } from "./download-manager";
+export {
+  getHfToken,
+  mirrorHfTokenInto,
+  useHfTokenStore,
+} from "./stores/hf-token-store";
diff --git a/studio/frontend/src/features/hub/stores/hf-token-store.ts b/studio/frontend/src/features/hub/stores/hf-token-store.ts
index b1e2560f02..499ba9f644 100644
--- a/studio/frontend/src/features/hub/stores/hf-token-store.ts
+++ b/studio/frontend/src/features/hub/stores/hf-token-store.ts
@@ -5,11 +5,9 @@ import { create } from "zustand";
 import { bumpInventoryVersion } from "./inventory-events";
 
 const HF_TOKEN_KEY = "unsloth_hf_token";
-const HF_TOKEN_CHANGED_EVENT = "unsloth:hf-token-changed";
 const LEGACY_TRAINING_KEY = "unsloth_training_config_v1";
 let storageSyncStarted = false;
 let storageSyncListener: ((event: StorageEvent) => void) | null = null;
-let tokenChangedListener: ((event: Event) => void) | null = null;
 
 function canUseStorage(): boolean {
   return typeof window !== "undefined";
@@ -63,10 +61,6 @@ function stopStorageSync(): void {
     window.removeEventListener("storage", storageSyncListener);
     storageSyncListener = null;
   }
-  if (tokenChangedListener !== null) {
-    window.removeEventListener(HF_TOKEN_CHANGED_EVENT, tokenChangedListener);
-    tokenChangedListener = null;
-  }
   storageSyncStarted = false;
 }
 
@@ -100,10 +94,6 @@ export const useHfTokenStore = create<HfTokenStore>((set) => {
       applyToken(event.newValue ?? "", false);
     };
     window.addEventListener("storage", storageSyncListener);
-    tokenChangedListener = (event) => {
-      applyToken((event as CustomEvent<string>).detail ?? "", false);
-    };
-    window.addEventListener(HF_TOKEN_CHANGED_EVENT, tokenChangedListener);
   }
 
   return {
@@ -117,6 +107,21 @@ export function getHfToken(): string {
   return useHfTokenStore.getState().token;
 }
 
+// Keep a plain zustand store's `hfToken` field in sync with the shared token:
+// seed the current value, then mirror later edits. Returns the unsubscribe so
+// callers can wire it to HMR disposal.
+export function mirrorHfTokenInto<T extends { hfToken: string }>(store: {
+  getState: () => T;
+  setState: (partial: Partial<T>) => void;
+}): () => void {
+  store.setState({ hfToken: getHfToken() } as Partial<T>);
+  return useHfTokenStore.subscribe((state) => {
+    if (store.getState().hfToken !== state.token) {
+      store.setState({ hfToken: state.token } as Partial<T>);
+    }
+  });
+}
+
 // HF's JS client throws on a non-empty token that isn't `hf_...` instead of
 // browsing anonymously, so treat anything malformed as no token.
 export function hfApiToken(
diff --git a/studio/frontend/src/features/studio/sections/dataset-section.tsx b/studio/frontend/src/features/studio/sections/dataset-section.tsx
index bb74b0d061..e7bab1f47f 100644
--- a/studio/frontend/src/features/studio/sections/dataset-section.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-section.tsx
@@ -54,7 +54,7 @@ import {
 // Imported directly from the store module rather than the "@/features/training"
 // barrel to avoid an import cycle (the barrel re-exports this section's siblings).
 import { hasSeparateStreamingEvalSplit } from "@/features/training/stores/training-config-store";
-import { useDebouncedValue, useHfTokenValidation } from "@/hooks";
+import { useDebouncedValue } from "@/hooks";
 import { translate, useT } from "@/i18n";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { toast } from "@/lib/toast";
@@ -398,9 +398,6 @@ export function DatasetSection() {
     enabled: pickerTab === "huggingface",
   });
 
-  const { error: tokenValidationError, isChecking: isCheckingToken } =
-    useHfTokenValidation(hfToken);
-
   const hfResultIds = useMemo(() => {
     const ids = hfResults.map((r) => r.id);
     if (dataset && !ids.includes(dataset)) {
@@ -1005,9 +1002,9 @@ export function DatasetSection() {
                   </ComboboxContent>
                 </Combobox>
               </div>
-              {(tokenValidationError ?? hfSearchError) && (
+              {hfSearchError && (
                 <p className="text-xs text-destructive">
-                  {tokenValidationError ?? hfSearchError}
+                  {hfSearchError}
                   {" — "}
                   <a
                     href="https://huggingface.co/settings/tokens"
@@ -1019,11 +1016,6 @@ export function DatasetSection() {
                   </a>
                 </p>
               )}
-              {isCheckingToken && (
-                <p className="text-xs text-muted-foreground">
-                  {t("studio.dataset.checkingToken")}
-                </p>
-              )}
               {pickerTab !== activeSourceTab && (
                 <p className="text-[11px] text-muted-foreground">
                   {t("studio.dataset.browsingSource", {
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 306c02475c..a927f83fd8 100644
--- a/studio/frontend/src/features/training/stores/training-config-store.ts
+++ b/studio/frontend/src/features/training/stores/training-config-store.ts
@@ -3,6 +3,7 @@
 
 import { CPT_TARGET_MODULES, DEFAULT_HYPERPARAMS, LR_DEFAULT_CPT, LR_DEFAULT_FULL, LR_DEFAULT_LORA, STEPS, TARGET_MODULES } from "@/config/training";
 import { authFetch } from "@/features/auth";
+import { getHfToken, mirrorHfTokenInto, useHfTokenStore } from "@/features/hub";
 import { isAdapterMethod } from "@/types/training";
 import type { DatasetFormat } from "@/types/training";
 import type { ModelType, StepNumber, TrainingMethod } from "@/types/training";
@@ -117,7 +118,9 @@ let _datasetFormatAutoForcedByCpt = false;
 
 // modelType / isVisionModel / isAudioModel persist so multimodal-only UI
 // paints right on reload; the model-config fetch still re-derives them.
+// hfToken mirrors the shared hf-token-store and is persisted there instead.
 const NON_PERSISTED_STATE_KEYS: ReadonlySet<keyof TrainingConfigState> = new Set([
+  "hfToken",
   "isCheckingVision",
   "isEmbeddingModel",
   "isLoadingModelDefaults",
@@ -632,8 +635,7 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
             ),
           );
         },
-        setHfToken: (hfToken) =>
-          set({ hfToken: hfToken.trim().replace(/^["']+|["']+$/g, "") }),
+        setHfToken: (hfToken) => useHfTokenStore.getState().setToken(hfToken),
         setDatasetSource: (datasetSource) => set({ datasetSource }),
         selectHfDataset: (dataset) => {
           _datasetCheckController?.abort();
@@ -923,7 +925,7 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
           _learningRateManuallySet = false;
           _yamlLearningRate = undefined;
           clearCptDatasetFormatTracking();
-          set(initialState);
+          set({ ...initialState, hfToken: getHfToken() });
         },
         resetToModelDefaults: () => {
           const { selectedModel } = get();
@@ -947,7 +949,7 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
     },
     {
       name: "unsloth_training_config_v1",
-      version: 11,
+      version: 12,
       migrate: (persisted, version) => {
         const s = persisted as Record<string, unknown>;
         if (version < 2 && s.datasetSubset == null && s.datasetConfig != null) {
@@ -1000,6 +1002,15 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
           // own version guard.
           s.datasetStreaming ??= false;
         }
+        if (version < 12) {
+          // hfToken moved to the shared hf-token-store; seed it once so an
+          // existing Studio-only token isn't lost.
+          const legacyToken = typeof s.hfToken === "string" ? s.hfToken.trim() : "";
+          if (legacyToken && !getHfToken()) {
+            useHfTokenStore.getState().setToken(legacyToken);
+          }
+          delete s.hfToken;
+        }
         return s as unknown as TrainingConfigStore;
       },
       partialize: partializePersistedState,
@@ -1022,3 +1033,8 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
     },
   ),
 );
+
+const unsubscribeHfTokenMirror = mirrorHfTokenInto(useTrainingConfigStore);
+if (import.meta.hot) {
+  import.meta.hot.dispose(unsubscribeHfTokenMirror);
+}

From 3555dbdda7cf1fe5eb7f7036045b5076d56ca6bd Mon Sep 17 00:00:00 2001
From: oobabooga <oobabooga4@gmail.com>
Date: Thu, 16 Jul 2026 19:47:22 -0300
Subject: [PATCH 05/28] Studio: don't drop parallel tool calls after an
 internal no-op (#7157)

---
 studio/backend/core/inference/llama_cpp.py    | 10 ++-
 .../core/inference/safetensors_agentic.py     | 10 ++-
 .../core/inference/tool_loop_controller.py    | 20 ++++-
 .../backend/tests/test_llama_cpp_tool_loop.py | 74 +++++++++++++++++++
 .../tests/test_safetensors_tool_loop.py       | 55 ++++++++++++++
 .../tests/test_tool_loop_controller.py        | 28 ++++++-
 6 files changed, 188 insertions(+), 9 deletions(-)

diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index 06b68ea831..dadfdfd38d 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -82,6 +82,7 @@ from core.inference.tool_call_parser import (
 )
 from core.inference.tool_loop_controller import (
     ToolLoopController,
+    append_deferred_nudges,
     tool_event_provenance,
 )
 from state.tool_approvals import (
@@ -10111,6 +10112,9 @@ class LlamaCppBackend:
 
                 assistant_msg: dict = {"role": "assistant", "content": content_text}
                 assistant_appended = False
+                # Collect no-op nudges and flush them after the batch, so a no-op
+                # doesn't abort it and drop the parallel calls that follow.
+                deferred_noop_msgs: list = []
 
                 # The text-path provisional card uses the parser's default id ("call_0");
                 # a Mistral-style call carries its own id and would open a duplicate. Reuse
@@ -10153,14 +10157,14 @@ class LlamaCppBackend:
                                 "provenance": decision.provenance,
                             }
                         completion = tool_controller.record_noop(decision)
-                        conversation.append(completion.model_message())
+                        deferred_noop_msgs.append(completion.model_message())
                         if _forced_tool_call_pending:
                             _forced_tool_call_pending = False
                         logger.info(
                             "Suppressed local GGUF tool call as internal no-op: "
                             f"action={decision.action} tool={decision.tool_name}"
                         )
-                        break
+                        continue
 
                     if not assistant_appended:
                         assistant_msg["tool_calls"] = [decision.as_assistant_tool_call()]
@@ -10279,6 +10283,8 @@ class LlamaCppBackend:
                     if _forced_tool_call_pending:
                         _forced_tool_call_pending = False
 
+                append_deferred_nudges(conversation, deferred_noop_msgs)
+
                 # Close provisional cards not resolved by execution/no-op handling.
                 for _pid, _pname in provisional_started_tool_calls.items():
                     if _pid not in resolved_provisional_tool_call_ids:
diff --git a/studio/backend/core/inference/safetensors_agentic.py b/studio/backend/core/inference/safetensors_agentic.py
index f4c243d1bf..43b72110ff 100644
--- a/studio/backend/core/inference/safetensors_agentic.py
+++ b/studio/backend/core/inference/safetensors_agentic.py
@@ -57,6 +57,7 @@ from core.tool_healing import (
 )
 from core.inference.tool_loop_controller import (
     ToolLoopController,
+    append_deferred_nudges,
     coerce_tool_arguments,
     status_for_tool,
     tool_event_provenance,
@@ -1099,6 +1100,9 @@ def run_safetensors_tool_loop(
 
         assistant_msg: dict = {"role": "assistant", "content": content_text}
         assistant_appended = False
+        # Collect no-op nudges and flush them after the batch, so a no-op doesn't
+        # abort it and drop the parallel calls that follow.
+        deferred_noop_msgs: list = []
 
         for tc in tool_calls or []:
             func = tc.get("function", {}) or {}
@@ -1127,12 +1131,12 @@ def run_safetensors_tool_loop(
                         "provenance": decision.provenance,
                     }
                 completion = tool_controller.record_noop(decision)
-                conversation.append(completion.model_message())
+                deferred_noop_msgs.append(completion.model_message())
                 logger.info(
                     "Suppressed local safetensors tool call as internal no-op: "
                     f"action={decision.action} tool={decision.tool_name}"
                 )
-                break
+                continue
 
             if not assistant_appended:
                 assistant_msg["tool_calls"] = [decision.as_assistant_tool_call()]
@@ -1243,6 +1247,8 @@ def run_safetensors_tool_loop(
             yield completion.tool_end_event()
             conversation.append(completion.tool_message())
 
+        append_deferred_nudges(conversation, deferred_noop_msgs)
+
         # Clear the status badge before the next turn.
         yield {"type": "status", "text": ""}
 
diff --git a/studio/backend/core/inference/tool_loop_controller.py b/studio/backend/core/inference/tool_loop_controller.py
index f595531b90..f7ed450d11 100644
--- a/studio/backend/core/inference/tool_loop_controller.py
+++ b/studio/backend/core/inference/tool_loop_controller.py
@@ -266,6 +266,17 @@ def strip_result_for_model(result: str) -> str:
     return result
 
 
+def append_deferred_nudges(conversation: list, msgs: Sequence[dict]) -> None:
+    """Append a batch's no-op nudges as one deduped ``role=user`` message.
+
+    Deferred to after the batch's tool results so a no-op never splits an
+    assistant's ``tool_calls`` from their ``role=tool`` results.
+    """
+    contents = list(dict.fromkeys(msg["content"] for msg in msgs))
+    if contents:
+        conversation.append({"role": "user", "content": "\n\n".join(contents)})
+
+
 def _tool_name_from_schema(tool: Mapping[str, Any]) -> str:
     function = tool.get("function")
     if not isinstance(function, Mapping):
@@ -277,8 +288,9 @@ def _tool_name_from_schema(tool: Mapping[str, Any]) -> str:
 def _noop_result(reason: NoopReason, tool_name: str) -> str:
     if reason == "duplicate":
         return (
-            "The previous tool request was not executed because this exact "
-            "tool call already completed successfully. Do not repeat the same "
+            f"One earlier request to call tool '{tool_name}' in this batch was "
+            "not executed because an identical call had already completed "
+            "successfully. Do not repeat the same "
             "tool call. Continue with a different enabled tool if that would "
             "materially help, or provide the final answer if you have enough "
             "information."
@@ -291,8 +303,8 @@ def _noop_result(reason: NoopReason, tool_name: str) -> str:
             "the requested final note or answer."
         )
     return (
-        f"The previous tool request was not executed because tool "
-        f"'{tool_name}' is not enabled for this request. Provide the "
+        f"One earlier request to call tool '{tool_name}' in this batch was "
+        "not executed because that tool is not enabled for this request. Provide the "
         "final answer now without calling more tools."
     )
 
diff --git a/studio/backend/tests/test_llama_cpp_tool_loop.py b/studio/backend/tests/test_llama_cpp_tool_loop.py
index c3161c5714..bd2c008589 100644
--- a/studio/backend/tests/test_llama_cpp_tool_loop.py
+++ b/studio/backend/tests/test_llama_cpp_tool_loop.py
@@ -1061,6 +1061,80 @@ def test_same_turn_duplicate_web_search_is_internal_noop(monkeypatch):
     ]
 
 
+def test_same_turn_duplicate_does_not_drop_later_parallel_call(monkeypatch):
+    # One batch: search(a), search(a) [duplicate], search(b). The duplicate is an
+    # internal no-op, but the distinct search(b) after it must still run, and the
+    # no-op nudge must land after the tool results rather than splitting them.
+    batch = [
+        _sse(
+            {
+                "tool_calls": [
+                    {
+                        "index": 0,
+                        "id": "call_a1",
+                        "type": "function",
+                        "function": {"name": "web_search", "arguments": json.dumps({"query": "a"})},
+                    },
+                    {
+                        "index": 1,
+                        "id": "call_a2",
+                        "type": "function",
+                        "function": {"name": "web_search", "arguments": json.dumps({"query": "a"})},
+                    },
+                    {
+                        "index": 2,
+                        "id": "call_b",
+                        "type": "function",
+                        "function": {"name": "web_search", "arguments": json.dumps({"query": "b"})},
+                    },
+                ]
+            }
+        ),
+        _done(),
+    ]
+    final_stream = [_sse({"content": "Final answer."}), _done()]
+    payloads: list[dict] = []
+    backend = _make_backend(monkeypatch, [batch, final_stream], payloads)
+
+    calls: list[dict] = []
+
+    def fake_execute_tool(name, arguments, **_kwargs):
+        calls.append(arguments)
+        return "search-result"
+
+    monkeypatch.setattr("core.inference.tools.execute_tool", fake_execute_tool)
+
+    events = list(
+        backend.generate_chat_completion_with_tools(
+            messages = [{"role": "user", "content": "search"}],
+            tools = [{"type": "function", "function": {"name": "web_search"}}],
+            max_tool_iterations = 3,
+        )
+    )
+
+    # Both distinct calls ran; the duplicate did not (old `break` dropped search(b)).
+    assert calls == [{"query": "a"}, {"query": "b"}]
+    assert [e.get("tool_call_id") for e in events if e.get("type") == "tool_end"] == [
+        "call_a1",
+        "call_b",
+    ]
+
+    # The next generation's conversation must be well-formed: the assistant lists
+    # only the executed calls (no orphan for the duplicate), the two tool results
+    # follow contiguously, and the no-op nudge lands after them, never between.
+    conv = payloads[1]["messages"]
+    asst = next(m for m in conv if m["role"] == "assistant" and m.get("tool_calls"))
+    assert [tc.get("id") for tc in asst["tool_calls"]] == ["call_a1", "call_b"]
+    after = conv[conv.index(asst) + 1 :]
+    assert [m["role"] for m in after[:2]] == ["tool", "tool"]
+    assert [m.get("tool_call_id") for m in after[:2]] == ["call_a1", "call_b"]
+    assert after[2]["role"] == "user"  # deferred duplicate nudge, after the results
+    assert after[2]["content"].startswith(
+        "One earlier request to call tool 'web_search' in this batch was not executed"
+    )
+    assert "previous tool request" not in after[2]["content"].lower()
+
+
 def test_same_turn_repeated_render_html_does_not_emit_second_provisional_start(monkeypatch):
     same_turn_render_calls = [
         _sse(
diff --git a/studio/backend/tests/test_safetensors_tool_loop.py b/studio/backend/tests/test_safetensors_tool_loop.py
index eae1a75161..e3633de289 100644
--- a/studio/backend/tests/test_safetensors_tool_loop.py
+++ b/studio/backend/tests/test_safetensors_tool_loop.py
@@ -2843,6 +2843,61 @@ class TestLoopBehaviour:
         ]
         assert len(duplicate_nudges) == 1
 
+    def test_same_turn_duplicate_does_not_drop_later_parallel_call(self):
+        # Turn 1 runs search(x). Turn 2's batch is [search(x) duplicate, python]:
+        # the duplicate is a no-op, but python after it must still run, and the
+        # no-op nudge must land after python's result rather than splitting it.
+        captured_messages: list[list[dict]] = []
+        turns = iter(
+            [
+                ['<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'],
+                [
+                    '<tool_call>{"name":"web_search","arguments":{"query":"x"}}</tool_call>'
+                    '<tool_call>{"name":"python","arguments":{"code":"print(1)"}}</tool_call>'
+                ],
+                ["final"],
+            ]
+        )
+
+        def fake_single_turn(messages, active_tools = None):
+            captured_messages.append([dict(m) for m in messages])
+            chunks = next(turns)
+            acc = ""
+            for chunk in chunks:
+                acc += chunk
+                yield acc
+
+        exec_fn = FakeExecuteTool(["search-x", "py-result"])
+        _collect_events(
+            run_safetensors_tool_loop(
+                single_turn = fake_single_turn,
+                messages = [{"role": "user", "content": "hi"}],
+                tools = [
+                    {"type": "function", "function": {"name": "web_search"}},
+                    {"type": "function", "function": {"name": "python"}},
+                ],
+                execute_tool = exec_fn,
+                max_tool_iterations = 4,
+            )
+        )
+
+        # Turn-1 search and turn-2 python both ran; the turn-2 duplicate search did not.
+        assert exec_fn.calls == [
+            ("web_search", {"query": "x"}),
+            ("python", {"code": "print(1)"}),
+        ]
+
+        conv = captured_messages[-1]
+        turn2 = [m for m in conv if m.get("role") == "assistant" and m.get("tool_calls")][-1]
+        assert [tc["function"]["name"] for tc in turn2["tool_calls"]] == ["python"]
+        after = conv[conv.index(turn2) + 1 :]
+        assert after[0]["role"] == "tool" and after[0]["content"] == "py-result"
+        assert after[1]["role"] == "user"  # deferred duplicate nudge, after the result
+        assert after[1]["content"].startswith(
+            "One earlier request to call tool 'web_search' in this batch was not executed"
+        )
+        assert "previous tool request" not in after[1]["content"].lower()
+
     def test_duplicate_tool_call_internal_noop_allows_distinct_followup_tool(self):
         captured_messages: list[list[dict]] = []
         captured_tool_names: list[list[str]] = []
diff --git a/studio/backend/tests/test_tool_loop_controller.py b/studio/backend/tests/test_tool_loop_controller.py
index 0e8ae798af..496c30ac13 100644
--- a/studio/backend/tests/test_tool_loop_controller.py
+++ b/studio/backend/tests/test_tool_loop_controller.py
@@ -13,6 +13,7 @@ if _BACKEND_DIR not in sys.path:
 
 from core.inference.tool_loop_controller import (
     ToolLoopController,
+    append_deferred_nudges,
     canonical_tool_call_key,
     coerce_tool_arguments,
     status_for_tool,
@@ -21,6 +22,22 @@ from core.inference.tool_loop_controller import (
 )
 
 
+def test_append_deferred_nudges_merges_deduped_into_one_message():
+    conversation = [{"role": "assistant", "tool_calls": [1]}, {"role": "tool", "content": "r"}]
+    nudges = [
+        {"role": "user", "content": "duplicate"},
+        {"role": "user", "content": "duplicate"},  # dropped: same content
+        {"role": "user", "content": "disabled foo"},
+    ]
+    append_deferred_nudges(conversation, nudges)
+    # One user message, after the results, with distinct contents joined.
+    assert conversation[2:] == [{"role": "user", "content": "duplicate\n\ndisabled foo"}]
+    # Empty is a no-op.
+    before = list(conversation)
+    append_deferred_nudges(conversation, [])
+    assert conversation == before
+
+
 def _tool(name: str) -> dict:
     return {"type": "function", "function": {"name": name}}
 
@@ -111,6 +128,10 @@ def test_successful_duplicate_is_internal_noop_and_keeps_remaining_tools():
     assert not duplicate.should_execute
     assert not duplicate.emit_visible_events
     duplicate_nudge = completion.model_message()["content"]
+    assert duplicate_nudge.startswith(
+        "One earlier request to call tool 'web_search' in this batch was not executed"
+    )
+    assert "previous tool request" not in duplicate_nudge.lower()
     assert "already completed successfully" in duplicate_nudge
     assert "different enabled tool" in duplicate_nudge
     assert completion.model_message()["role"] == "user"
@@ -165,7 +186,12 @@ def test_empty_enabled_tool_list_blocks_all_tool_calls():
     assert decision.action == "disabled"
     assert not decision.emit_visible_events
     assert completion.model_message()["role"] == "user"
-    assert "not enabled" in completion.model_message()["content"]
+    disabled_nudge = completion.model_message()["content"]
+    assert disabled_nudge.startswith(
+        "One earlier request to call tool 'web_search' in this batch was not executed"
+    )
+    assert "previous tool request" not in disabled_nudge.lower()
+    assert "not enabled" in disabled_nudge
     assert controller.force_final_answer
     assert controller.active_tools() == []
 

From c4e6dd4f6c60c95ac6d2951693a2ffc40abcde6a Mon Sep 17 00:00:00 2001
From: oobabooga <oobabooga4@gmail.com>
Date: Thu, 16 Jul 2026 19:48:12 -0300
Subject: [PATCH 06/28] Studio: extract text from PDF web results (#7154)

---
 studio/backend/core/inference/tools.py        | 117 +++++++++++++--
 studio/backend/core/rag/parsers.py            |  55 +++++--
 studio/backend/tests/test_rag_parsing.py      |  50 +++++++
 .../tests/test_web_fetch_binary_guard.py      | 138 ++++++++++++++++--
 4 files changed, 324 insertions(+), 36 deletions(-)

diff --git a/studio/backend/core/inference/tools.py b/studio/backend/core/inference/tools.py
index dd268a6bb7..5fd57e1b2c 100644
--- a/studio/backend/core/inference/tools.py
+++ b/studio/backend/core/inference/tools.py
@@ -3600,14 +3600,18 @@ _MAX_PAGE_CHARS = 16000  # cap fetched page text (after HTML-to-MD conversion)
 # Raw download cap > _MAX_PAGE_CHARS since SSR pages embed large <head> sections
 # stripped during conversion; 512 KB still reaches article content.
 _MAX_FETCH_BYTES = 512 * 1024
+# PDF cross-reference data lives at EOF, so extraction needs the whole body.
+_MAX_PDF_FETCH_BYTES = 10 * 1024 * 1024
+_MAX_WEB_PDF_PAGES = 50
 # Control/undecodable chars, excluding text whitespace and ESC (for ANSI logs).
 # Binary when they exceed 12.5%, after allowing 16 minor encoding glitches.
 _BINARY_CHAR_RE = re.compile("[\\x00-\\x08\\x0b\\x0c\\x0e-\\x1a\\x1c-\\x1f\\x7f-\\x9f\\ufffd]")
 _MIN_BINARY_CHARS = 16
 _BINARY_CHAR_DIVISOR = 8
 # Common binary signatures that can otherwise look text-heavy when mislabeled.
+_PDF_MAGIC = b"%PDF-"
 _BINARY_MAGIC = (
-    b"%PDF-",  # PDF
+    _PDF_MAGIC,
     b"PK\x03\x04",  # zip / docx / xlsx / pptx / epub / jar
     b"\xd0\xcf\x11\xe0\xa1\xb1\x1a\xe1",  # OLE / legacy Office
     b"\x89PNG\r\n\x1a\n",  # PNG
@@ -3641,14 +3645,22 @@ def _looks_binary(text: str) -> bool:
     )
 
 
-def _has_binary_magic(data: bytes) -> bool:
-    """Whether a common binary signature follows optional BOM or whitespace."""
+def _magic_head(data: bytes) -> bytes:
     head = data[:1024].lstrip()
     for bom, _codec in _UNICODE_BOM_CODECS:
         if head.startswith(bom):
             head = head.removeprefix(bom).lstrip()
             break
-    return head.startswith(_BINARY_MAGIC)
+    return head
+
+
+def _has_pdf_magic(data: bytes) -> bool:
+    return _magic_head(data).startswith(_PDF_MAGIC)
+
+
+def _has_binary_magic(data: bytes) -> bool:
+    """Whether a common binary signature follows optional BOM or whitespace."""
+    return _magic_head(data).startswith(_BINARY_MAGIC)
 
 
 def _has_single_byte_text_evidence(data: bytes) -> bool:
@@ -3659,6 +3671,45 @@ def _has_single_byte_text_evidence(data: bytes) -> bool:
     return ascii_text_bytes / len(data) >= _MIN_SINGLE_BYTE_ASCII_RATIO
 
 
+def _extract_pdf_text(data: bytes) -> str:
+    """Extract page-delimited text with the same parser used by RAG ingestion."""
+    from ..rag.parsers import parse_pdf_bytes
+
+    pages, total_pages = parse_pdf_bytes(data, max_pages = _MAX_WEB_PDF_PAGES)
+    page_limit_reached = total_pages > _MAX_WEB_PDF_PAGES
+    parts: list[str] = []
+    length = 0
+    text_limited = False
+    for page in pages:
+        page_text = page.text.strip()
+        if not page_text:
+            continue
+        section = f"## Page {page.page_number}\n\n{page_text}"
+        piece = ("\n\n" if parts else "") + section
+        remaining = _MAX_PAGE_CHARS - length
+        if len(piece) > remaining:
+            parts.append(piece[:remaining])
+            text_limited = True
+            break
+        parts.append(piece)
+        length += len(piece)
+
+    text = "".join(parts).rstrip()
+    if not text:
+        if page_limit_reached:
+            return f"(PDF contains no extractable text in the first {_MAX_WEB_PDF_PAGES} pages)"
+        return ""
+    limits = []
+    if text_limited:
+        limits.append(f"text limited to {_MAX_PAGE_CHARS:,} characters")
+    if page_limit_reached:
+        limits.append(f"page processing capped at {_MAX_WEB_PDF_PAGES} pages")
+    if limits:
+        marker = f"\n\n... (PDF extraction {'; '.join(limits)})"
+        text = text[: _MAX_PAGE_CHARS - len(marker)].rstrip() + marker
+    return text
+
+
 _USER_AGENTS = (
     "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
     "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
@@ -4054,29 +4105,71 @@ def _fetch_url_raw(
                     return reason2, "", ""
                 current_host = rp.hostname
                 continue
+
+            # get_content_type() defaults to "text/plain" when the header is
+            # absent (RFC 2045); report "" instead so callers can tell a missing
+            # header apart from a server that really declared text/plain.
+            if resp.headers.get("Content-Type") is None:
+                content_type = ""
+            else:
+                content_type = (resp.headers.get_content_type() or "").lower()
+
             # Success: read the capped body enforcing the budget between chunks
             # (see _read_capped_body), so a slow-drip server can't stretch a
             # single resp.read past the deadline.
+            declared_pdf = content_type == "application/pdf"
+            read_limit = _MAX_PDF_FETCH_BYTES + 1 if declared_pdf else max_bytes
             body_error, raw_bytes = _read_capped_body(
                 resp,
-                max_bytes,
+                read_limit,
                 timeout,
                 deadline,
                 cancel_event,
             )
             if body_error is not None:
                 return body_error, "", ""
+
+            # A missing or wrong PDF MIME type is common: once the initial text-sized
+            # read identifies PDF magic, finish the bounded download to reach the EOF xref.
+            if not declared_pdf and len(raw_bytes) == max_bytes and _has_pdf_magic(raw_bytes):
+                tail_error, tail = _read_capped_body(
+                    resp,
+                    _MAX_PDF_FETCH_BYTES - max_bytes + 1,
+                    timeout,
+                    deadline,
+                    cancel_event,
+                )
+                if tail_error is not None:
+                    return tail_error, "", ""
+                raw_bytes += tail
             break
         else:
             return "Failed to fetch URL: too many redirects.", "", ""
 
-        # get_content_type() defaults to "text/plain" when the header is
-        # absent (RFC 2045); report "" instead so callers can tell a missing
-        # header apart from a server that really declared text/plain.
-        if resp.headers.get("Content-Type") is None:
-            content_type = ""
-        else:
-            content_type = (resp.headers.get_content_type() or "").lower()
+        is_pdf = declared_pdf or _has_pdf_magic(raw_bytes)
+        if is_pdf:
+            if len(raw_bytes) > _MAX_PDF_FETCH_BYTES:
+                return (
+                    "(PDF content exceeds the download limit; not readable as text)",
+                    "",
+                    content_type,
+                )
+            budget_error = _fetch_budget_exceeded(deadline, cancel_event)
+            if budget_error is not None:
+                return budget_error, "", content_type
+            try:
+                pdf_text = _extract_pdf_text(raw_bytes)
+            except Exception as exc:
+                logger.debug("web PDF text extraction failed (%s)", type(exc).__name__)
+                return "(PDF content could not be read as text)", "", content_type
+            budget_error = _fetch_budget_exceeded(deadline, cancel_event)
+            if budget_error is not None:
+                return budget_error, "", content_type
+            if not pdf_text:
+                pdf_text = "(PDF contains no extractable text)"
+            # Report the true type even for a mislabeled body so the caller's "html"
+            # check routes the extracted text to the plain-text path, not html_to_markdown.
+            return None, pdf_text, "application/pdf"
 
         # Reject known-binary MIME types before decoding. Binary is returned as the
         # error string so the caller surfaces the placeholder, not replacement chars.
diff --git a/studio/backend/core/rag/parsers.py b/studio/backend/core/rag/parsers.py
index 9afddf1d9e..0b42906b85 100644
--- a/studio/backend/core/rag/parsers.py
+++ b/studio/backend/core/rag/parsers.py
@@ -103,7 +103,7 @@ def _markdown_incomplete(markdown: str, plain: str) -> bool:
     return markdown_letters < _PDF_INCOMPLETE_RATIO * plain_letters
 
 
-def _pdf_markdown(doc) -> list[str] | None:
+def _pdf_markdown(doc, pages: range | None = None) -> list[str] | None:
     """Per-page layout-aware Markdown (tables, headings, lists) via pymupdf4llm; index
     i maps to page i+1. Returns None when the lib is missing, extraction fails, or the
     page count does not line up, so the caller falls back to plain PyMuPDF text."""
@@ -112,28 +112,44 @@ def _pdf_markdown(doc) -> list[str] | None:
     except Exception:
         return None
     try:
-        chunks = pymupdf4llm.to_markdown(
-            doc,
-            page_chunks = True,
-            show_progress = False,
-        )
+        kwargs = {"page_chunks": True, "show_progress": False}
+        if pages is not None:
+            kwargs["pages"] = list(pages)
+        chunks = pymupdf4llm.to_markdown(doc, **kwargs)
     except Exception:  # noqa: BLE001 - never let Markdown extraction break ingestion
         logger.warning("pymupdf4llm extraction failed; using plain text", exc_info = True)
         return None
-    if not isinstance(chunks, list) or len(chunks) != doc.page_count:
+    expected_pages = doc.page_count if pages is None else len(pages)
+    if not isinstance(chunks, list) or len(chunks) != expected_pages:
         return None
     return [str(c.get("text") or "") for c in chunks]
 
 
-def _pdf(path: str, want_images: bool) -> tuple[list[Page], list[ParsedImage]]:
+def _pdf(
+    source: str | bytes,
+    want_images: bool,
+    max_pages: int | None = None,
+) -> tuple[list[Page], list[ParsedImage], int]:
     import fitz  # PyMuPDF
 
     pages: list[Page] = []
     images: list[ParsedImage] = []
-    doc = fitz.open(path)
+    doc = (
+        fitz.open(stream = source, filetype = "pdf") if isinstance(source, bytes) else fitz.open(source)
+    )
     try:
-        md = _pdf_markdown(doc) if config.PDF_MARKDOWN else None
-        for i, page in enumerate(doc):
+        if doc.needs_pass:
+            raise ValueError("encrypted PDF requires a password")
+        total_pages = doc.page_count
+        page_numbers = range(total_pages if max_pages is None else min(total_pages, max_pages))
+        if not config.PDF_MARKDOWN:
+            md = None
+        elif max_pages is None:
+            md = _pdf_markdown(doc)
+        else:
+            md = _pdf_markdown(doc, page_numbers)
+        for i, page_number in enumerate(page_numbers):
+            page = doc[page_number]
             plain = page.get_text("text") or ""
             candidate = md[i] if md else ""
             # Prefer layout-aware Markdown (keeps tables/headings legible for retrieval),
@@ -147,7 +163,7 @@ def _pdf(path: str, want_images: bool) -> tuple[list[Page], list[ParsedImage]]:
                 text = candidate
             else:
                 text = plain
-            pages.append(_page(text, i + 1))
+            pages.append(_page(text, page_number + 1))
             if want_images:
                 for img in page.get_images(full = True):
                     xref = img[0]
@@ -161,13 +177,22 @@ def _pdf(path: str, want_images: bool) -> tuple[list[Page], list[ParsedImage]]:
                         images.append(
                             ParsedImage(
                                 image_bytes = image_bytes,
-                                page_number = i + 1,
+                                page_number = page_number + 1,
                                 xref = xref,
                             )
                         )
     finally:
         doc.close()
-    return pages, images
+    return pages, images, total_pages
+
+
+def parse_pdf_bytes(data: bytes, *, max_pages: int | None = None) -> tuple[list[Page], int]:
+    """Extract PDF pages from an in-memory download using the ingestion parser.
+
+    Returns the (capped) pages plus the document's full page count, so a caller
+    that set ``max_pages`` can tell a fully-read short PDF from a truncated one."""
+    pages, _images, total_pages = _pdf(data, want_images = False, max_pages = max_pages)
+    return pages, total_pages
 
 
 def _merge_rects(boxes: list) -> list:
@@ -416,7 +441,7 @@ def parse(path: str, *, want_images: bool = False):
     ext = os.path.splitext(path)[1].lower()
 
     if ext == ".pdf":
-        pages, images = _pdf(path, want_images)
+        pages, images, _total = _pdf(path, want_images)
         return (pages, images) if want_images else pages
 
     if ext == ".docx":
diff --git a/studio/backend/tests/test_rag_parsing.py b/studio/backend/tests/test_rag_parsing.py
index 14ab0efe2e..3e259f6bd0 100644
--- a/studio/backend/tests/test_rag_parsing.py
+++ b/studio/backend/tests/test_rag_parsing.py
@@ -54,6 +54,56 @@ def test_pdf_markdown_off_uses_plain_text(tmp_path, monkeypatch):
     assert "#" not in text and "|" not in text  # plain text path emits no Markdown markup
 
 
+def test_pdf_bytes_use_same_extraction_path(tmp_path, monkeypatch):
+    from core.rag import config, parsers
+
+    monkeypatch.setattr(config, "PDF_MARKDOWN", False)
+    pdf = tmp_path / "table.pdf"
+    _table_pdf(pdf)
+    from_file = parsers.parse(str(pdf))
+    from_bytes, total_pages = parsers.parse_pdf_bytes(pdf.read_bytes())
+    assert [page.text for page in from_bytes] == [page.text for page in from_file]
+    assert total_pages == len(from_file)
+
+
+def test_pdf_bytes_limit_pages_before_extraction(monkeypatch):
+    import pymupdf
+
+    from core.rag import config, parsers
+
+    monkeypatch.setattr(config, "PDF_MARKDOWN", False)
+    doc = pymupdf.open()
+    for marker in ("page one", "page two", "page three"):
+        page = doc.new_page()
+        page.insert_text((40, 40), marker)
+    data = doc.tobytes()
+    doc.close()
+
+    pages, total_pages = parsers.parse_pdf_bytes(data, max_pages = 2)
+    assert len(pages) == 2
+    assert "page two" in pages[-1].text
+    assert total_pages == 3  # full count, not the 2 extracted
+
+
+def test_pdf_markdown_receives_page_limit(monkeypatch):
+    from core.rag import parsers
+
+    captured = {}
+
+    class _FakePymupdf4llm:
+        @staticmethod
+        def to_markdown(doc, **kwargs):
+            captured.update(kwargs)
+            return [{"text": "page"} for _ in kwargs["pages"]]
+
+    class _Doc:
+        page_count = 100
+
+    monkeypatch.setitem(__import__("sys").modules, "pymupdf4llm", _FakePymupdf4llm)
+    assert parsers._pdf_markdown(_Doc(), range(2)) == ["page", "page"]
+    assert captured == {"page_chunks": True, "show_progress": False, "pages": [0, 1]}
+
+
 def test_pdf_markdown_passes_only_supported_legacy_kwargs(monkeypatch):
     # The pinned PyMuPDF4LLM legacy path ignores unknown kwargs; do not pass the
     # newer layout-only OCR knobs or Markdown extraction silently loses policy control.
diff --git a/studio/backend/tests/test_web_fetch_binary_guard.py b/studio/backend/tests/test_web_fetch_binary_guard.py
index 3041ed5c34..10db953913 100644
--- a/studio/backend/tests/test_web_fetch_binary_guard.py
+++ b/studio/backend/tests/test_web_fetch_binary_guard.py
@@ -59,6 +59,18 @@ def _fetch_with(monkeypatch, body: bytes, content_type: str | None) -> str:
     return tools._fetch_page_text("https://example.com/thing", timeout = 5)
 
 
+def _pdf_bytes(*page_texts: str) -> bytes:
+    pymupdf = pytest.importorskip("pymupdf")
+    doc = pymupdf.open()
+    for text in page_texts:
+        page = doc.new_page()
+        if text:
+            page.insert_textbox(pymupdf.Rect(40, 40, 550, 750), text, fontsize = 11)
+    data = doc.tobytes()
+    doc.close()
+    return data
+
+
 @pytest.mark.parametrize(
     "content_type,expected",
     [
@@ -90,10 +102,119 @@ def test_is_text_candidate_content_type(content_type, expected):
     assert tools._is_text_candidate_content_type(content_type) is expected
 
 
-def test_pdf_rejected_by_content_type(monkeypatch):
-    out = _fetch_with(monkeypatch, b"%PDF-1.7\n\xff\xd8\xff\x00\x89PNG" * 200, "application/pdf")
-    assert "�" not in out
-    assert "non-text content" in out and "application/pdf" in out
+@pytest.mark.parametrize(
+    "content_type",
+    ["application/pdf", "application/octet-stream", "text/html", "text/plain", None],
+)
+def test_pdf_text_extracted(monkeypatch, content_type):
+    out = _fetch_with(
+        monkeypatch,
+        _pdf_bytes("First page marker", "Second page marker"),
+        content_type,
+    )
+    assert "## Page 1\n\nFirst page marker" in out
+    assert "## Page 2" in out and "Second page marker" in out
+    assert "binary content" not in out and "non-text content" not in out
+
+
+@pytest.mark.parametrize("content_type", ["application/pdf", "text/plain"])
+def test_malformed_pdf_returns_safe_placeholder(monkeypatch, content_type):
+    out = _fetch_with(monkeypatch, b"%PDF-1.7\nnot a complete PDF", content_type)
+    assert out == "(PDF content could not be read as text)"
+
+
+def test_pdf_without_text_layer_reported(monkeypatch):
+    out = _fetch_with(monkeypatch, _pdf_bytes(""), "application/pdf")
+    assert out == "(PDF contains no extractable text)"
+
+
+def test_encrypted_pdf_returns_safe_placeholder(monkeypatch):
+    pymupdf = pytest.importorskip("pymupdf")
+    doc = pymupdf.open()
+    doc.new_page().insert_text((40, 40), "private text")
+    data = doc.tobytes(
+        encryption = pymupdf.PDF_ENCRYPT_AES_256,
+        owner_pw = "owner",
+        user_pw = "secret",
+    )
+    doc.close()
+    out = _fetch_with(monkeypatch, data, "application/pdf")
+    assert out == "(PDF content could not be read as text)"
+
+
+def test_pdf_download_limit_enforced(monkeypatch):
+    monkeypatch.setattr(tools, "_MAX_PDF_FETCH_BYTES", 256)
+    out = _fetch_with(monkeypatch, _pdf_bytes("Readable but oversized"), "application/pdf")
+    assert out == "(PDF content exceeds the download limit; not readable as text)"
+
+
+def test_mislabeled_pdf_is_read_past_text_download_cap(monkeypatch):
+    body = _pdf_bytes("Cross-reference data was fetched")
+    monkeypatch.setattr(tools, "_MAX_FETCH_BYTES", 128)
+    monkeypatch.setattr(tools, "_MAX_PDF_FETCH_BYTES", len(body) + 100)
+    out = _fetch_with(monkeypatch, body, "text/plain")
+    assert "Cross-reference data was fetched" in out
+
+
+def test_pdf_extraction_caps_pages_and_intermediate_text(monkeypatch):
+    from core.rag.parsers import Page
+
+    seen = {}
+
+    def fake_parse(data, *, max_pages = None):
+        seen["max_pages"] = max_pages
+        pages = [Page(text = "x" * 1000, page_number = i, char_count = 1000) for i in range(1, 51)]
+        return pages, 60  # document actually has more pages than the cap
+
+    monkeypatch.setattr("core.rag.parsers.parse_pdf_bytes", fake_parse)
+    text = tools._extract_pdf_text(b"unused")
+    assert seen["max_pages"] == tools._MAX_WEB_PDF_PAGES
+    assert len(text) <= tools._MAX_PAGE_CHARS
+    assert "text limited to 16,000 characters" in text
+    assert "page processing capped at 50 pages" in text
+
+
+def test_pdf_exactly_at_page_cap_not_marked_capped(monkeypatch):
+    from core.rag.parsers import Page
+
+    # Exactly _MAX_WEB_PDF_PAGES pages are fully read, so no "capped" marker.
+    monkeypatch.setattr(
+        "core.rag.parsers.parse_pdf_bytes",
+        lambda data, *, max_pages = None: (
+            [Page(text = "short", page_number = i, char_count = 5) for i in range(1, 51)],
+            50,
+        ),
+    )
+    text = tools._extract_pdf_text(b"unused")
+    assert "page processing capped" not in text
+    assert "## Page 50\n\nshort" in text
+
+
+def test_pdf_page_cap_does_not_claim_later_pages_are_textless(monkeypatch):
+    from core.rag.parsers import Page
+    monkeypatch.setattr(
+        "core.rag.parsers.parse_pdf_bytes",
+        lambda data, *, max_pages = None: (
+            [Page(text = "", page_number = i, char_count = 0) for i in range(1, 51)],
+            60,
+        ),
+    )
+    assert tools._extract_pdf_text(b"unused") == (
+        "(PDF contains no extractable text in the first 50 pages)"
+    )
+
+
+def test_pdf_result_discarded_after_fetch_deadline(monkeypatch):
+    clock = {"time": 1000.0}
+    monkeypatch.setattr(tools.time, "monotonic", lambda: clock["time"])
+
+    def slow_extract(data):
+        clock["time"] += 10.0
+        return "late PDF text"
+
+    monkeypatch.setattr(tools, "_extract_pdf_text", slow_extract)
+    out = _fetch_with(monkeypatch, _pdf_bytes("Readable text"), "application/pdf")
+    assert out == "Failed to fetch URL: timed out."
 
 
 def test_text_octet_stream_kept_after_sniffing(monkeypatch):
@@ -154,7 +275,6 @@ def test_valid_utf8_binary_caught_by_control_chars(monkeypatch):
 @pytest.mark.parametrize(
     "magic",
     [
-        b"%PDF-",
         b"PK\x03\x04",
         b"\xd0\xcf\x11\xe0\xa1\xb1\x1a\xe1",
         b"\x1f\x8b",
@@ -180,8 +300,8 @@ def test_text_labeled_binary_caught_by_magic(monkeypatch, magic):
         b"\t\xef\xbb\xbf ",
     ],
 )
-def test_pdf_magic_after_harmless_prefix(monkeypatch, prefix):
-    body = prefix + b"%PDF-1.7\n" + b"1 0 obj<</Type/Catalog>>endobj\n" * 100
+def test_binary_magic_after_harmless_prefix(monkeypatch, prefix):
+    body = prefix + b"\x1f\x8b" + b" printable text-heavy body" * 100
     out = _fetch_with(monkeypatch, body, "text/plain")
     assert "binary content" in out
 
@@ -243,10 +363,10 @@ def test_html_page_unaffected(monkeypatch):
 
 def test_content_type_sanitized_in_message(monkeypatch):
     # Do not echo obs-folded header content into the model response.
-    out = _fetch_with(monkeypatch, b"\x00\x01\x02" * 500, "application/pdf\r\n data: injected")
+    out = _fetch_with(monkeypatch, b"PK\x03\x04" * 500, "application/zip\r\n data: injected")
     assert "\n" not in out and "\r" not in out
     assert "injected" not in out
-    assert "application/pdf" in out
+    assert "application/zip" in out
 
 
 @pytest.mark.parametrize(

From 1777aae37ee8ecd6e5ba5b303f4505d975382751 Mon Sep 17 00:00:00 2001
From: Nilay <118994073+NilayYadav@users.noreply.github.com>
Date: Fri, 17 Jul 2026 04:54:05 +0530
Subject: [PATCH 07/28] don't kill live llama-servers when a new Studio
 instance starts (#7182)

---
 studio/backend/core/inference/llama_cpp.py    |  8 ++++
 .../test_llama_cpp_wait_for_vram_settle.py    | 43 +++++++++++++++++++
 2 files changed, 51 insertions(+)

diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index dadfdfd38d..3e93a26787 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -8232,6 +8232,11 @@ class LlamaCppBackend:
                         if not is_ours:
                             continue
 
+                        # A live parent means a running Studio (or the user's
+                        # shell) still owns it -- not an orphan.
+                        if LlamaCppBackend._pid_parent_is_alive(proc.info["pid"]):
+                            continue
+
                         proc.kill()
                         killed += 1
                         logger.info(
@@ -8284,6 +8289,9 @@ class LlamaCppBackend:
                     if not owned:
                         continue
 
+                    if LlamaCppBackend._pid_parent_is_alive(pid):
+                        continue
+
                     try:
                         os.kill(pid, signal.SIGKILL)
                         killed += 1
diff --git a/studio/backend/tests/test_llama_cpp_wait_for_vram_settle.py b/studio/backend/tests/test_llama_cpp_wait_for_vram_settle.py
index 3c21f41701..d0213f6079 100644
--- a/studio/backend/tests/test_llama_cpp_wait_for_vram_settle.py
+++ b/studio/backend/tests/test_llama_cpp_wait_for_vram_settle.py
@@ -373,6 +373,7 @@ def test_kill_orphaned_servers_returns_count():
     with (
         patch.dict(sys.modules, {"psutil": fake_psutil}),
         patch.dict(os.environ, {"LLAMA_SERVER_PATH": fake_path}),
+        patch.object(LlamaCppBackend, "_pid_parent_is_alive", staticmethod(lambda pid: False)),
     ):
         n = LlamaCppBackend._kill_orphaned_servers()
     assert n == 1, "only the Studio-owned orphan should be counted"
@@ -384,11 +385,53 @@ def test_kill_orphaned_servers_returns_count():
     with (
         patch.dict(sys.modules, {"psutil": fake_psutil}),
         patch.dict(os.environ, {"LLAMA_SERVER_PATH": fake_path}),
+        patch.object(LlamaCppBackend, "_pid_parent_is_alive", staticmethod(lambda pid: False)),
     ):
         assert LlamaCppBackend._kill_orphaned_servers() == 0
     assert killed == []
 
 
+def test_kill_orphaned_servers_spares_live_parent():
+    """A Studio-owned llama-server whose parent is still running is not an
+    orphan (a live Studio or the user's shell owns it) and must never be
+    killed; only the true orphan (parent gone) is reaped."""
+    import os
+
+    mypid = os.getpid()
+    fake_path = "/tmp/unsloth-test-llama/llama-server"
+    killed: list[int] = []
+
+    class _FakeProc:
+        def __init__(self, pid, name, exe):
+            self.info = {"pid": pid, "name": name, "exe": exe}
+
+        def kill(self):
+            killed.append(self.info["pid"])
+
+    live_parent = _FakeProc(mypid + 1, "llama-server", fake_path)
+    true_orphan = _FakeProc(mypid + 2, "llama-server", fake_path)
+
+    fake_psutil = _types.ModuleType("psutil")
+    fake_psutil.NoSuchProcess = type("NoSuchProcess", (Exception,), {})
+    fake_psutil.AccessDenied = type("AccessDenied", (Exception,), {})
+    fake_psutil.ZombieProcess = type("ZombieProcess", (Exception,), {})
+    fake_psutil.process_iter = lambda attrs = None: [live_parent, true_orphan]
+
+    with (
+        patch.dict(sys.modules, {"psutil": fake_psutil}),
+        patch.dict(os.environ, {"LLAMA_SERVER_PATH": fake_path}),
+        patch.object(LlamaCppBackend, "_reap_recorded_pid", staticmethod(lambda: 0)),
+        patch.object(
+            LlamaCppBackend,
+            "_pid_parent_is_alive",
+            staticmethod(lambda pid: pid == mypid + 1),
+        ),
+    ):
+        n = LlamaCppBackend._kill_orphaned_servers()
+    assert n == 1, "only the true orphan should be reaped"
+    assert killed == [mypid + 2], "the live-parent server must be spared"
+
+
 def test_startup_reaper_arms_settle_timestamp():
     """__init__ arms ``_last_kill_monotonic`` when the startup reaper kills an
     orphan (so the first load_model waits for VRAM to settle), and leaves the

From b508c8fe89a60df5995aeafe0c17589a93cecd50 Mon Sep 17 00:00:00 2001
From: Andrew Chen <48723787+chuenchen309@users.noreply.github.com>
Date: Fri, 17 Jul 2026 16:55:34 +0800
Subject: [PATCH 08/28] fix(save): unsloth_push_to_hub_gguf(save_method="lora")
 raises NameError (#7193)

* fix(save): unsloth_push_to_hub_gguf(save_method="lora") raises NameError

unsloth_push_to_hub_gguf reads is_main_process at save.py:3181 but never
declares it. Its twin unsloth_save_pretrained_gguf declares it (2783) and
uses it the same way (2839) -- the LoRA branch was copied between the twins,
the parameter it depends on was not. There is no module-level global, so the
name resolves as a global load and the branch raises NameError 100% of the
time.

save_pretrained_gguf(save_method="lora", push_to_hub=True) raises a
ValueError that tells users to "use .push_to_hub_gguf(save_method='lora')
instead" -- the documented escape hatch is the broken call.

Add is_main_process to the signature, positioned as in the twin, and forward
it to unsloth_save_pretrained_gguf on the merged path so the parameter is not
silently ignored there. Default stays True, so nothing changes for existing
callers.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

* fix(save): preserve GGUF push compatibility

---------

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
---
 tests/saving/test_export_dispatch.py | 76 ++++++++++++++++++++++++++++
 unsloth/save.py                      |  6 ++-
 2 files changed, 80 insertions(+), 2 deletions(-)

diff --git a/tests/saving/test_export_dispatch.py b/tests/saving/test_export_dispatch.py
index 3870d6269d..ad6d51e0b7 100644
--- a/tests/saving/test_export_dispatch.py
+++ b/tests/saving/test_export_dispatch.py
@@ -8,6 +8,8 @@ regressions that pure AST checks cannot (e.g. wrong scheme/suffix/outtype passed
 
 from __future__ import annotations
 
+import inspect
+
 import pytest
 
 import unsloth.save as save_mod
@@ -126,6 +128,80 @@ def test_gguf_lora_push_to_hub_is_rejected(tmp_path):
         )
 
 
+# The above rejection points users at push_to_hub_gguf(save_method='lora'), so that path
+# has to work; it is only ever exercised here.
+
+
+def test_push_to_hub_gguf_lora_dispatches(monkeypatch):
+    seen = {}
+    monkeypatch.setattr(
+        save_mod,
+        "_unsloth_save_lora_gguf",
+        lambda model, tok, sd, **kw: seen.update(kw),
+    )
+    save_mod.unsloth_push_to_hub_gguf(
+        _FakeModel(),
+        "repo/id",
+        tokenizer = object(),
+        save_method = "lora",
+        quantization_method = "q8_0",
+    )
+    assert seen.get("outtype") == "q8_0"
+    assert seen.get("push_to_hub") is True
+
+
+def test_push_to_hub_gguf_lora_skips_non_main_process(monkeypatch):
+    calls = []
+    monkeypatch.setattr(
+        save_mod,
+        "_unsloth_save_lora_gguf",
+        lambda *a, **kw: calls.append(kw),
+    )
+    result = save_mod.unsloth_push_to_hub_gguf(
+        _FakeModel(),
+        "repo/id",
+        tokenizer = object(),
+        save_method = "lora",
+        is_main_process = False,
+    )
+    assert result is None
+    assert calls == []
+
+
+def test_push_to_hub_gguf_skips_non_main_process_before_merged_conversion(monkeypatch):
+    calls = []
+    monkeypatch.setattr(
+        save_mod,
+        "unsloth_save_pretrained_gguf",
+        lambda **kw: calls.append(kw),
+    )
+    result = save_mod.unsloth_push_to_hub_gguf(
+        _FakeModel(),
+        "repo/id",
+        tokenizer = object(),
+        is_main_process = False,
+    )
+    assert result is None
+    assert calls == []
+
+
+def test_push_to_hub_gguf_preserves_positional_max_shard_size():
+    bound = inspect.signature(save_mod.unsloth_push_to_hub_gguf).bind(
+        _FakeModel(),
+        "repo/id",
+        object(),
+        "q4_k_m",
+        None,
+        None,
+        None,
+        None,
+        "token",
+        "50GB",
+    )
+    assert bound.arguments["max_shard_size"] == "50GB"
+    assert "is_main_process" not in bound.arguments
+
+
 # -- torchao PTQ / QAT dispatch ------------------------------------------------------------
 
 
diff --git a/unsloth/save.py b/unsloth/save.py
index 50a180f823..7d5774aa97 100644
--- a/unsloth/save.py
+++ b/unsloth/save.py
@@ -3143,6 +3143,7 @@ def unsloth_push_to_hub_gguf(
     datasets: Optional[List[str]] = None,
     save_method: str = None,
     imatrix_file = None,
+    is_main_process: bool = True,
 ):
     """
     Same as .push_to_hub(...) except 4bit weights are auto
@@ -3175,11 +3176,11 @@ def unsloth_push_to_hub_gguf(
     """
     if tokenizer is None:
         raise ValueError("Unsloth: Saving to GGUF must have a tokenizer.")
+    if not is_main_process:
+        return None
 
     # save_method="lora" exports the adapter itself as a GGUF LoRA (not a merged model).
     if save_method is not None and str(save_method).lower() == "lora":
-        if not is_main_process:
-            return None  # only the main rank converts and uploads, like the local lora branch
         _qm = quantization_method
         if isinstance(_qm, (list, tuple)) and len(_qm) == 1:
             _qm = _qm[0]  # the gguf API allows a list; unwrap a single outtype
@@ -3233,6 +3234,7 @@ def unsloth_push_to_hub_gguf(
             first_conversion = first_conversion,
             push_to_hub = False,  # Never push from here
             token = token,  # forwarded so imatrix_file=True can read a gated/private upstream
+            is_main_process = is_main_process,
             max_shard_size = max_shard_size,
             safe_serialization = safe_serialization,
             temporary_location = temporary_location,

From 8cbdfbe355a83b6cc0706e2ed8ec1c737b71c3f3 Mon Sep 17 00:00:00 2001
From: Eyera <hauzin@hotmail.com>
Date: Fri, 17 Jul 2026 15:08:01 +0200
Subject: [PATCH 09/28] Feat/model picker per model config (#6647)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* refactor(studio): move chat model picker into features/model-picker

Relocate model-selector + its support files from components/assistant-ui
into a self-contained features/model-picker feature (own barrel), mirroring
the modular Hub layout. Pure move + import repoint; no behaviour change.

* feat(model-picker): add per-model config persistence layer

Superset PerModelConfig (customContextLength, kvCacheDtype, speculativeType,
specDraftNMax, tensorParallel, chatTemplateOverride, trustRemoteCode) persisted
to localStorage (unsloth_model_configs) with schema versioning + LRU budget.
KV-dtype and speculative value sets match main's sidebar (no q4_0/ngram-simple).
Reuses features/hub/lib/model-identity for normalization; adds storage-key layer
and applyPerModelConfigToRuntime (sets tensorParallel, which the old PR omitted).

* feat(picker): modular backend for chat-template validate + default fetch

New studio/backend/picker package (schemas/service/routes) mounted at /api/picker:
- POST /api/picker/validate-chat-template (Jinja syntax validation, no false positives)
- GET  /api/picker/chat-template/{model_name} (default template from tokenizer_config.json,
  reusing get_cache_path/resolve_cached_repo_id_case; graceful null, no model-code exec)
Frontend api/templates.ts client + hooks/use-model-defaults lazy cache. No backend
changes to the existing inference load route (per-model load fields already supported).

* feat(model-picker): bind picker on-device list to shared hub inventory

Picker now sources cached + local models from useHubInventory (the Hub's shared
store) via a thin adapter, replacing its own /api/models/* fetchers + module
caches. Hub, download manager, and picker now share one source of truth, so
completed downloads reflect in the picker automatically. Partial/live-download
rows are filtered from the cached lists (unchanged rendering). Local naming/search
preserved via additive LocalInventoryRow modelId/displayName. Variant expander,
scan-folder management, recommended-fit, search, external providers untouched.

Known minor: cached 'Downloaded date' sort tiebreak degrades to alphabetical
(hub cached rows carry no mtime); default 'recent' (load-time) sort preserved.

* feat(model-picker): per-model config step inside the picker

Picking a (non-external) model now opens an in-picker config view built from
main's current load controls (context length, KV cache dtype, speculative
decoding, draft tokens, tensor parallel) plus a chat-template editor backed by
the picker validate/default endpoints. 'Remember for this model' persists the
config per model+variant; Run forwards the config to the existing load flow via
meta.config. External models bypass the step. Two-view orchestration lives in
model-selector (single interception point); pickers.tsx call sites untouched.
trustRemoteCode dropped from PerModelConfig to preserve main's per-load consent.

* feat(chat): apply/persist per-model config through the load flow

handleCheckpointChange threads meta.config into the selection; stageOrLoad and
the autoload/Hub-run paths now apply the picker config (explicit pick or saved
remembered config) via applyPerModelConfigToRuntime before staging/loading, with
keepSpeculative set so a remembered speculative mode survives the model switch.
Replaces the old remembered-load-settings seeding (resolveInitialConfig now the
single source). SelectedModelInput carries config.

* refactor(chat): remove per-model load config from the right sidebar

The load knobs (context, KV cache, speculative, draft tokens, tensor parallel)
and the chat-template editor now live only in the picker config step. The sheet's
Model section keeps the staged Load/Cancel flow (config is applied at pick time);
sampling params, system prompt, and RAG are unchanged. Deletes the superseded
remembered-load-settings module + the store's applyRememberedLoadSettings action,
removes the now-dead sheet state/imports, and points the settings reset at
unsloth_model_configs. Delete-cleanup deferred (stale config is LRU-capped).

* fix(model-picker): remove leftover sidebar-staging cogwheel + empty Model section

The downloaded-variant gear (ModelLoadSettingsAction) staged a model straight
into the right-sidebar Run-settings flow -- the old 'configure before load' path
now fully replaced by the in-picker config step. Removed the gear + its component.
Also gate the sheet's 'Model' section to staged picks only (pendingSelection):
after the load-knob strip its content is staged-only, so it was rendering an
empty section header whenever a model was merely loaded.

* chore(chat): remove dead per-model-config setters + modelControlsDisabled

After the load-config UI moved into the picker, the store's per-model setters
(setKvCacheDtype/setSpeculativeType/setSpecDraftNMax/setTensorParallel/
setCustomContextLength/setChatTemplateOverride) had zero callers
(applyPerModelConfigToRuntime writes via setState), and the sheet's
modelControlsDisabled was unreferenced. Verified dead across the whole tree.

* fix(chat): config-step Load actually loads (ignore Load-on-selection)

Root cause: with Settings > Chat > 'Load on selection' turned OFF, the config
step's load went down the deferred-staging path -- opening the right sidebar with
'<model> is staged, not loaded yet / Choose Load model'. The in-picker config step
IS the deliberate load action, so its Load now loads immediately (or downloads +
auto-loads when not cached) regardless of the toggle. Renamed the button
'Run model' -> 'Load model' to match. Native/dropped picks still honor the toggle.

* refactor(chat,hub): retire 'Load on selection' — config step is the only load flow

The in-picker config step (and the Hub Run button) now fully supersede the old
stage-to-sidebar flow, so the Load-on-selection toggle is removed everywhere:
- chat stageOrLoad: every pick loads immediately, or downloads + auto-loads when
  not cached (the previous default behaviour, now universal).
- hub Run: drops the stage branch; downloaded GGUFs load directly with their saved
  per-model config (no collision with the chat config step — both end at selectModel).
- store: removed loadOnSelection field/setter/key/default; Settings>Chat toggle and
  its settings-reset entry removed.
- staged sidebar section is now a download-progress view (auto-loads on completion).
No manual staging remains; stageModel is used only for background auto-load downloads.

* feat(model-picker): default chat template from GGUF + thread variant through config flow

Read the embedded tokenizer.chat_template from GGUF files (read_gguf_chat_template
in gguf_metadata) and use it as the per-model default. Plumb gguf_variant through
the picker service, /api/picker/chat-template route, frontend templates API, and
use-model-defaults so the right variant's template is fetched.

Also refine the picker config-page/model-selector wiring, drop the dead
ggufNativeContextLength runtime path, and add the per-model-config storage keys to
the settings prefs export.

* feat(model-picker): read safetensors chat template + hide editor where it has no effect

Resolve the default chat template for safetensors models: prefer the modern
chat_template.jinja, fall back to the tokenizer_config.json chat_template field,
then chat_template.json (multimodal processor), then the GGUF embedded template.
Applied to local dirs, the HF cache snapshot scan, and the HF remote fetch.

Hide the chat-template editor in the picker for safetensors models — the override
is only applied at load by the GGUF/llama.cpp backend, so editing it on safetensors
currently has no effect. GGUF keeps the editor. Nothing removed; the dialog stays
for when the safetensors apply path is wired up in a later branch.

* fix(model-picker): set legacy-migration flag only after the write succeeds

Set unsloth_model_configs_migrated only once writeMap confirms the migrated
map persisted, so a quota/storage failure no longer marks migration done and
silently drops the user's pre-existing remembered settings — the next load retries.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* MVP model picker fixes

* MVP picker config fix

* MVP safetensors config

* MVP max seq config

* MVP max seq fix

* Fix static max tokens cap ignoring model context

* Fix picker GGUF scan parity

* fix(studio): harden model picker config loading

Apply remembered per-model configs consistently from picker and Hub loads, keep default configs from overriding standing speculative settings, add config access for direct local GGUF files, and support saving or forgetting active model settings without a reload.

* Fix model picker config flow

* Fix model picker config loads

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Avoid recursive per-model config migration reads

* Apply the displayed context length when loading a GGUF

* Fix template validation, cached template lookup, and failed load rollback

- Validate chat templates with the loopcontrols extension so templates
  that use break or continue tags pass the picker validator, matching the
  inference renderer that already accepts them.
- Read the default chat template from the newest cache snapshot rather than
  an arbitrary iterdir order, so an older cached revision no longer prefills
  a stale template.
- Capture the runtime per-model config before a load and reapply it when the
  load fails, so a failed switch leaves the active model context, KV cache,
  template, and speculative settings as they were.

* Make chat template view only for safetensors models

Custom chat template overrides are applied at inference only for GGUF
models, which pass the template to llama-server. The safetensors backend
renders with the model built-in template and ignores the override, so
editing it would save a value that never loads. For safetensors the
config page now opens the template as a read-only preview with a note
that editing is not available yet. This can become editable once
inference support for custom safetensors templates lands in main.

* Fix model picker config edge cases

- Restore prior runtime config when a load no-ops for the active model
- Cap the picker validator request body via the protected prefixes
- Keep the GGUF context slider max above the loaded context
- Fetch subfolder chat templates for uncached Hub repos
- Show the compare side config when reopening the picker

* Keep saved GGUF context above the fallback ceiling

* Show the model config in the run settings sidebar

* Fix model config sidebar reset and context slider

- Stack the remember toggle and action buttons in the sidebar
- Reset the config to defaults instead of the loaded values
- Fetch the native context so the slider max is not the loaded value

* Fix model picker config and download regressions

- Run picker chat template routes off the event loop
- Depth and root guard local template directory scans
- Restore download manager flow for uncached hub picks
- Apply per model context length on reload
- Import model picker symbols from the feature barrel

* Fix model picker config and cached download sorting

- Restore load settings when a Hub run is rejected mid load
- Reuse one NumericValueInput instead of a duplicate copy
- Fix double decode of the model name in the template route
- Remove the unused reset-to-loaded settings action
- Fix cached model download sorting

* Fix model picker per-model config edge cases

Honor a saved or typed max seq length above the model's native context so
RoPE extended values are no longer clamped and silently overwritten. Allow
typing past native while the slider keeps native as a soft ceiling.

Guard the fetch success paths in use-model-defaults against an aborted
signal, and refetch when the HF token changes.

Hash the chat template content in the sidebar remount key instead of its
length. Enable reset for a GGUF whose native context is unknown, and floor
the context slider max so it can never fall below the min.

* Fix GGUF context auto-fit and gated model config token

Stop forcing a 32768 context when a GGUF native context is unknown so the backend auto-fits to VRAM again, while still honoring an explicit context edit.

Send the HF token as a query param so gated safetensors models resolve their max position embeddings.

Derive model default state during render to drop the set-state-in-effect calls.

* Fix native GGUF context ceiling and guard picker template reads

Restore the native context store field so the sidebar slider keeps the
full ceiling for drag and drop GGUFs. Limit local chat template reads to
the browse allowlist, skip malformed repo ids, and drop unused model
picker exports.

* Fix model picker lint boundaries

* Fix model picker review findings

Chat template editor never seeded its draft. Radix only calls onOpenChange
from internal events, so the seed in the nextOpen branch was dead and a model
with a saved override opened empty. Saving then cleared the override. Drop the
dead branch, treat draft as an untouched sentinel, and reset it on every close.

Uncached Hub picks could auto load a model after the user left the chat. Main
detached the staged pick on route exit and on chat context change. Carry the
context key on the pending pick and skip the load when it no longer matches.

Also clear configTarget when the picker closes, restore the onUpdated ref so
variant rows stop resubscribing on every parent render, skip the LRU write when
the entry is already most recent, import NumericValueInput relatively, and drop
the unused ModelUpdateAction barrel export.

* Preserve GGUF context on active reload

* Fix model picker per-model config regressions

- Stop reloading the already loaded model on re-pick
- Hide infra models from the chat picker
- Detect vision support on cached GGUF repos
- Honor saved maxSeqLength on auto load
- Restore default chat template for local GGUFs
- Warn on save failure and revert config on cancel
- Refetch picker inventory on open
- Persist read only per model config safely

* Fix stale model auto load

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Fix model picker numeric input sizing and constraints

Size value inputs to their content so long context lengths are not clipped,
restrict them to numeric characters, and stop the speculative decoding label
from truncating in the sidebar.

* Fix picker CI tests and harden chat template resolution for PR #6647

- tests: point the descender guard at the moved model-selector.tsx path
- tests: exclude the disabled Reload model button from the regenerate locator so .first targets the real Regenerate
- picker/service.py: reject symlinked template/gguf leaves that resolve outside the browse allowlist (HF cache reads unchanged)
- compare mode: resolve each pane's own remembered chat template instead of inheriting the other pane's from the store

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Protect future-schema per-model configs from deletion for PR #6647

savePerModelConfig already refuses to overwrite a stored config whose schema version is newer than this client understands, but deletePerModelConfig did not. Unchecking Remember on an older client therefore silently destroyed a newer client's saved config. Apply the same guard on delete and surface the blocked case through the existing saveFailed toast.

* Protect future-schema per-model configs from quota eviction for PR #6647

The save and delete guards already refuse to touch a stored config whose schema version is newer than this client understands, but the quota-eviction path did not, so a full store on an older client could still evict a newer client's config. Skip future-schema entries when evicting and fail the save if the budget cannot be met without them.

* Fix GGUF context persistence, compare context, and rollback settings for PR #6647

Persist a GGUF context override from the user's intent instead of collapsing it against the loaded context, which reintroduced the context-reset (f4838782cb reverted the native-baseline fix). model-config-page now collapses the saved value against native, and use-chat-model-runtime and chat-adapter retain the requested context on load so re-saving another setting keeps the override; a null request stays null so a VRAM auto-fit never becomes a stored override.

shared-composer: a compare pane with no explicit GGUF context now loads at native (0) like single-view, not the session maxSeqLength that silently shrank the shown context.

use-chat-model-runtime: restore the previous model's KV cache dtype and chat template on a failed-load rollback so it runs as it was, not with backend defaults.

* Preserve native path token when reloading the active model for PR #6647

handleReloadActiveModel rebuilt the selection without the store's activeNativePathToken, so reloading a file-picked GGUF after a settings change validated the display label as a repo/path and failed. Thread the active native token through the reload selection so native-loaded models reopen correctly.

* Make picker template validation resilient and accept HF generation tags for PR #6647

Import Jinja lazily inside validate_chat_template so a backend without the optional jinja2 package (GGUF-only installs) still starts instead of raising ModuleNotFoundError at import time. Register a no-op extension for the Transformers {% generation %} assistant-mask tag so pasting a valid HF chat template validates, matching the renderer, rather than being rejected as an unknown tag.

* Honor remembered compare config and parse processor chat_template.json for PR #6647

* Fix failed-load rollback context and processor template map fallback for PR #6647

* Restore speculative decoding config on failed-switch rollback

When a model switch fails after the previous model was unloaded, the
rollback reload restored tensor_parallel, KV cache dtype and the chat
template override, but omitted speculative_type and spec_draft_n_max and
cleared their loaded shadows to null. The previous model therefore came
back running at backend defaults (speculation off) while the UI still
showed it enabled, and the status resync confirmed the off state. Resend
the previous model's speculative settings in the rollback load and keep
the store's active and loaded speculative fields in sync with them.

* Reset max sequence length when a model has no saved config

applyPerModelConfigToRuntime reset every per-model field except
maxSeqLength, which it only wrote when the incoming config had one.
maxSeqLength is the sole field carried on store.params, so selecting a
model with no remembered config left the previous model's value in place
and later loaded the new model at that leaked length. Fall back to the
standing default so an unremembered model loads at its own default.

* Surface a message when a variant update cannot start

startManagedUpdate handled the conflict and error start outcomes but let
busy fall through as if the update began, so the confirm dialog closed
with no job created and the cached variant stayed stale. Show an info
message when the repo is busy with a sibling transfer so the click is
not silently dropped.

* Keep per-model speculative choices out of the global default

A staged load with a per-model or one-off config sets keepSpeculative,
which already skips reading the global speculative preference. The
matching save still ran unconditionally, so the model-specific choice was
written to the global unsloth_chat_speculative_type and a later model with
no saved config started from it instead of Auto. Skip saveSpeculativeType
when keepSpeculative so the per-model choice stays isolated.

* Seed non-active model settings from the app default max length

The Run settings page captured initialMaxSeqLength from the loaded
model's runtime params and fell back to it for a model with no saved
config. Opening settings for a different, unloaded model and clicking
Load then sent the active model's context (for example 64k) instead of
the 4096 default, risking validation failures or OOMs. Seed the default
for non-active models and keep the runtime value only for the active one.

* Prefer sidecar tokenizer chat template over the GGUF copy for variants

_chat_template_from_dir returned the embedded GGUF template first when a
variant was selected, reversing the tokenizer-first precedence of the
no-variant path. A model whose chat_template.jinja or tokenizer_config.json
supersedes a stale embedded template then got the wrong template on
variant selection. Keep tokenizer files first regardless of variant; the
variant only picks which GGUF is the fallback. Adds regression tests for
both the tokenizer-wins and gguf-fallback cases.

* Keep per-model speculative choices load-local in autoload and compare

The interactive load path treats a per-model speculative choice as
load-local and skips writing it to the global default. Autoload and
generalized compare still called saveSpeculativeType unconditionally, so a
remembered off or ngram setting leaked into unsloth_chat_speculative_type
and later models with no saved config inherited it. Persist the global
preference only when the value came from the global settings.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Studio: record the compare pane's loaded context in runtime state so the active model's settings and any reload or save use it, not the previous context

* Studio: notify the user when a Hub autoload can't start because another download for the model is already running, instead of silently dropping it

* Studio: drop the merge's orphaned staged-model store helpers and unused alert imports

The main merge left isPendingGguf and pendingSelectionMatches referencing the
removed PendingModelSelection type, and the alert-dialog/alert imports unused
after the permission-mode dropdown replaced the bypass dialog, so tsc -b failed.

* Studio: cache a null default chat template so the viewer stops re-fetching it

A model with no sidecar or embedded template resolves to a terminal null, but
that result was never cached, so reopening the template viewer re-ran the
backend and Hugging Face lookup every time.

* Studio: detect direct-file GGUFs in run settings so Max Tokens uses their context

A GGUF loaded from a local file or custom folder has no variant label, so the
run-settings panel treated it as non-GGUF and clamped Max Tokens to the session
max_seq_length instead of the loaded GGUF context. Detect it via the reported
GGUF context and the .gguf checkpoint suffix, matching the chat page.

* Studio: prompt to re-select a local model file when its lease expired before reload

A file-picked GGUF is reachable only through a native path token that the
desktop host prunes after a TTL. Reloading reused that token blindly, so a
reload long after the initial load failed with an opaque error. Track the
token's expiry and, when it has passed, ask the user to re-select the file
instead of attempting a doomed reload.

* Fix descender-clipping test to tolerate sidebar layout utilities

The sidebar account-block div carries layout utilities (min-w-0, flex-1)
between 'flex' and 'flex-col', so the descender-clipping guard's regex,
which required 'flex' immediately followed by 'flex-col', no longer matched
and the test failed to locate the account-block div. Generalize the prefix
to allow intervening flex utilities while still capturing the leading-*
class before the collapsible visibility utility and asserting leading-tight,
so the guard against clipped glyph descenders is fully preserved.

* Harden picker chat-template resolution

Enforce the 64 KiB chat-template contract at the validate endpoint's request
model so a direct caller cannot submit a template far larger than the frontend
allows (MaxBodyMiddleware only bounds the whole request body, not this field);
oversized templates now return a clean 422.

Apply sidecar-over-GGUF template precedence globally across cached snapshots
instead of per snapshot. A repo with multiple cached revisions previously
returned the first snapshot's template, so a newer GGUF-only revision could
win over an older revision's maintained chat_template.jinja sidecar, which
contradicted the documented intent that sidecars supersede the embedded copy.

* Guard per-model config against future-schema and lossy migration

Two forward-compatibility gaps in the versioned per-model config store:

- The load/apply path returned and normalized a stored record without checking
  its schema version, so a record written by a newer client was reinterpreted
  under the current schema and applied to a live model load, even though save,
  delete and eviction all refuse to touch future-schema records. Reject
  future-schema records on load too.
- The one-time legacy migration enforced the storage budget without protecting
  the entries it had just migrated and set the completion flag unconditionally.
  When storage was already full of future-schema records (which are unevictable
  by an older client), the migrated entries were the only evictable ones and
  could be dropped while migration was still marked complete. Protect the
  migrated keys during eviction and only mark migration complete when they
  survive, so it retries once space frees up.

* Discard chat-template validation results after the dialog closes

Server-side template validation is async, but closing or cancelling the editor
did not abort it, so a late-arriving valid response still called onSave and
applied a template the user had already dismissed. Track a validation token
that is bumped on close and ignore any validation result whose token is stale.

* Record native lease expiry when loading a picked GGUF from the chip

The pending-native-model chip loaded via stageOrLoad directly, bypassing
loadNativeModelIntent, so activeNativePathExpiresAtMs was never recorded for a
chip-loaded file. A later reload then either skipped the lease-expiry guard
entirely (expiry left null) or compared against a previously loaded file's
stale expiry, so reload could reuse an already-pruned token or wrongly block a
still-valid one. Route the chip through loadNativeModelIntent, which builds the
same selection and records the expiry.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Prefer sidecar template for a directly selected local GGUF file

A direct .gguf file path read its embedded chat template without checking the
parent directory for a maintained sidecar (chat_template.jinja /
tokenizer_config.json), while directory and variant selections already prefer
the sidecar. That let the config editor preview or save a stale embedded
template for the same model depending on how it was selected. Check the parent
directory sidecars first, then fall back to the embedded copy, and cover both
paths with tests.

* Resolve cached chat template per revision, newest first

The earlier change searched every cached snapshot for a sidecar before
considering any snapshot's embedded GGUF template, which let an obsolete sidecar
from an older revision override the newest revision's template. Restore
per-snapshot resolution (newest first): a revision's sidecar still supersedes
its own embedded GGUF copy, but a newer revision is no longer overridden by an
older revision's sidecar.

* Preserve autoload transport conflicts and surface background busy downloads

- When a Hub autoload hits a transport conflict, keep pendingHubAutoLoad bound
  instead of clearing it. Clearing it re-keyed the download surface and its
  cleanup cancelled the conflict the toast tells the user to resolve, so the
  Hub resume affordance was gone the moment it appeared. Return early on
  conflict, mirroring the started branch, so resolving it from the Hub still
  auto-loads on completion.
- The background-download branch handled started and conflict but silently
  dropped a busy outcome, leaving the user with no feedback when a peer variant
  of the same repo was already downloading. Surface the same busy toast the
  autoload path uses.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
---
 studio/backend/hub/schemas/inventory.py       |   1 +
 .../hub/services/models/cache_inventory.py    |  74 +-
 studio/backend/main.py                        |   3 +
 studio/backend/picker/__init__.py             |   2 +
 studio/backend/picker/routes/__init__.py      |   6 +
 studio/backend/picker/routes/templates.py     |  42 +
 studio/backend/picker/schemas.py              |  32 +
 studio/backend/picker/service.py              | 361 +++++++
 .../tests/test_model_update_robustness.py     |  46 +
 studio/backend/tests/test_picker_service.py   | 162 +++
 studio/backend/utils/models/gguf_metadata.py  |  79 ++
 studio/frontend/src/app/routes/__root.tsx     |   7 -
 .../remembered-load-settings.ts               |  69 --
 .../src/features/chat/api/chat-adapter.ts     |  50 +-
 .../frontend/src/features/chat/chat-page.tsx  | 517 ++++++----
 .../src/features/chat/chat-settings-sheet.tsx | 947 +++---------------
 .../chat/hooks/use-chat-model-runtime.ts      | 105 +-
 .../hooks/use-staged-model-preparation.ts     | 155 ---
 studio/frontend/src/features/chat/index.ts    |  18 +
 .../lib/apply-inference-status-to-store.ts    |   5 -
 .../src/features/chat/shared-composer.tsx     | 111 +-
 .../chat/stores/chat-runtime-store.ts         | 186 +---
 .../export/components/export-run-panel.tsx    |  71 +-
 .../hub/catalog/models-catalog-rows.tsx       |  41 +-
 .../hub/catalog/on-device-folders-dialog.tsx  |  33 +-
 .../download-manager-controller.ts            |  23 -
 .../features/hub/download-manager/index.ts    |   1 -
 studio/frontend/src/features/hub/hub-page.tsx | 129 +--
 studio/frontend/src/features/hub/index.ts     |  58 +-
 .../src/features/hub/inventory/api.ts         |   2 +
 .../src/features/hub/inventory/types.ts       |   3 +
 .../src/features/hub/inventory/view-models.ts |   9 +
 .../model-picker/api/model-metadata.ts        |  20 +
 .../features/model-picker/api/templates.ts    |  51 +
 .../chat-template-editor-dialog.tsx           | 191 ++++
 .../components/model-config-page.tsx          | 742 ++++++++++++++
 .../components}/model-selector.tsx            | 130 ++-
 .../model-selector/folder-browser.tsx         |  79 +-
 .../model-selector/model-capabilities.ts      |   0
 .../model-selector/model-delete-action.tsx    |   9 +-
 .../model-load-settings-action.tsx            |  19 +-
 .../model-selector/model-update-action.tsx    |  25 +-
 .../components}/model-selector/model-usage.ts |   3 +-
 .../components}/model-selector/pickers.tsx    | 645 +++++++-----
 .../components}/model-selector/pill-tabs.tsx  |   3 +-
 .../model-selector/recommended-fit.ts         |   0
 .../components}/model-selector/row-meta.ts    |   0
 .../components}/model-selector/source-tabs.ts |   0
 .../components}/model-selector/types.ts       |  13 +
 .../components/numeric-value-input.tsx        | 113 +++
 .../components/sidebar-model-config.tsx       |  89 ++
 .../model-picker/hooks/use-model-defaults.ts  | 176 ++++
 .../src/features/model-picker/index.ts        |  30 +
 .../inventory/use-chat-picker-inventory.ts    | 118 +++
 .../model-config/apply-per-model-config.ts    |  85 ++
 .../model-config/model-identity.ts            |  69 ++
 .../model-config/per-model-config.ts          | 571 +++++++++++
 .../src/features/settings/tabs/chat-tab.tsx   |  39 -
 .../features/settings/tabs/general-tab.tsx    |   3 +-
 .../frontend/src/features/training/index.ts   |   4 +-
 tests/studio/playwright_chat_ui.py            |  14 +-
 .../test_studio_text_descender_clipping.py    |  17 +-
 62 files changed, 4478 insertions(+), 2128 deletions(-)
 create mode 100644 studio/backend/picker/__init__.py
 create mode 100644 studio/backend/picker/routes/__init__.py
 create mode 100644 studio/backend/picker/routes/templates.py
 create mode 100644 studio/backend/picker/schemas.py
 create mode 100644 studio/backend/picker/service.py
 create mode 100644 studio/backend/tests/test_picker_service.py
 delete mode 100644 studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
 delete mode 100644 studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
 create mode 100644 studio/frontend/src/features/model-picker/api/model-metadata.ts
 create mode 100644 studio/frontend/src/features/model-picker/api/templates.ts
 create mode 100644 studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
 create mode 100644 studio/frontend/src/features/model-picker/components/model-config-page.tsx
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector.tsx (86%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/folder-browser.tsx (88%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/model-capabilities.ts (100%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/model-delete-action.tsx (90%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/model-load-settings-action.tsx (66%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/model-update-action.tsx (82%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/model-usage.ts (93%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/pickers.tsx (89%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/pill-tabs.tsx (98%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/recommended-fit.ts (100%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/row-meta.ts (100%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/source-tabs.ts (100%)
 rename studio/frontend/src/{components/assistant-ui => features/model-picker/components}/model-selector/types.ts (76%)
 create mode 100644 studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
 create mode 100644 studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
 create mode 100644 studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
 create mode 100644 studio/frontend/src/features/model-picker/index.ts
 create mode 100644 studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
 create mode 100644 studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
 create mode 100644 studio/frontend/src/features/model-picker/model-config/model-identity.ts
 create mode 100644 studio/frontend/src/features/model-picker/model-config/per-model-config.ts

diff --git a/studio/backend/hub/schemas/inventory.py b/studio/backend/hub/schemas/inventory.py
index ef95efe2f2..f81c9a3498 100644
--- a/studio/backend/hub/schemas/inventory.py
+++ b/studio/backend/hub/schemas/inventory.py
@@ -160,6 +160,7 @@ class CachedRepoBase(BaseModel):
     repo_id: str
     size_bytes: int = 0
     cache_path: Optional[str] = None
+    last_modified: Optional[float] = None
     partial: bool = False
     partial_transport: Optional[str] = None
     inventory_id: Optional[str] = None
diff --git a/studio/backend/hub/services/models/cache_inventory.py b/studio/backend/hub/services/models/cache_inventory.py
index 1f38af9381..ba3a266bfb 100644
--- a/studio/backend/hub/services/models/cache_inventory.py
+++ b/studio/backend/hub/services/models/cache_inventory.py
@@ -31,6 +31,7 @@ from hub.services.models.common import (
     _is_checkpoint_weight_name,
     _is_gguf_filename,
     _is_main_gguf_filename,
+    _is_mmproj_filename,
     _is_transformers_safetensors_weight_name,
     _local_inventory_id,
     _prefer_complete_larger,
@@ -125,6 +126,34 @@ def _repo_has_gguf_files(repo_info) -> bool:
     return _repo_gguf_size_bytes(repo_info) > 0
 
 
+def _blob_mtime(file_obj) -> float:
+    ts = getattr(file_obj, "blob_last_modified", None)
+    if isinstance(ts, (int, float)) and ts > 0:
+        return float(ts)
+    blob_path = getattr(file_obj, "blob_path", None)
+    if blob_path:
+        try:
+            return float(Path(blob_path).stat().st_mtime)
+        except OSError:
+            pass
+    return 0.0
+
+
+def _repo_gguf_last_modified(repo_info) -> float:
+    latest = 0.0
+    for revision in repo_info.revisions:
+        for f in revision.files:
+            if _is_main_gguf_filename(f.file_name):
+                latest = max(latest, _blob_mtime(f))
+    return latest
+
+
+def _repo_has_mmproj(repo_info) -> bool:
+    return any(
+        _is_mmproj_filename(f.file_name) for revision in repo_info.revisions for f in revision.files
+    )
+
+
 def _cached_repo_file_name(file_obj) -> str:
     file_path = getattr(file_obj, "file_path", None)
     if file_path:
@@ -266,6 +295,7 @@ def _scan_cached_gguf() -> list[dict]:
                     continue
                 key = repo_id.lower()
                 existing = seen_lower.get(key)
+                last_modified = _repo_gguf_last_modified(repo_info)
                 row = {
                     "repo_id": repo_id,
                     "size_bytes": max(total_size, variant_state_size),
@@ -275,6 +305,9 @@ def _scan_cached_gguf() -> list[dict]:
                     # per-variant detail lives on GgufVariantDetail.
                     "partial_transport": None,
                 }
+                last_modified = max(last_modified, (existing or {}).get("last_modified", 0.0))
+                if last_modified > 0:
+                    row["last_modified"] = last_modified
                 row.update(
                     _cache_inventory_fields(
                         repo_id,
@@ -283,8 +316,12 @@ def _scan_cached_gguf() -> list[dict]:
                         requires_variant = True,
                     )
                 )
+                if _repo_has_mmproj(repo_info):
+                    row["capabilities"]["supports_vision"] = True
                 if _prefer_cache_row(row, existing):
                     seen_lower[key] = row
+                elif last_modified > existing.get("last_modified", 0.0):
+                    existing["last_modified"] = last_modified
             except Exception as e:
                 repo_label = getattr(repo_info, "repo_id", "<unknown>")
                 logger.warning(f"Skipping cached GGUF repo {repo_label}: {e}")
@@ -312,13 +349,14 @@ class _CachedNonGgufPayload(NamedTuple):
     size_bytes: int
     has_runnable_weights: bool
     model_format: ModelFormat
+    last_modified: float
 
 
 def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
-    all_weight_blobs: dict[str, int] = {}
-    adapter_blobs: dict[str, int] = {}
-    safetensors_blobs: dict[str, int] = {}
-    checkpoint_blobs: dict[str, int] = {}
+    all_weight_blobs: dict[str, tuple[int, float]] = {}
+    adapter_blobs: dict[str, tuple[int, float]] = {}
+    safetensors_blobs: dict[str, tuple[int, float]] = {}
+    checkpoint_blobs: dict[str, tuple[int, float]] = {}
     has_config = False
     has_adapter_config = False
     has_adapter_weights = False
@@ -326,12 +364,15 @@ def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
     has_transformers_safetensors = False
     has_checkpoint = False
 
-    def _record_blob(target: dict[str, int], file_obj, rev_id: str, file_name: str) -> None:
+    def _record_blob(
+        target: dict[str, tuple[int, float]], file_obj, rev_id: str, file_name: str
+    ) -> None:
         blob_path = getattr(file_obj, "blob_path", None)
         size = int(file_obj.size_on_disk or 0)
         key = str(blob_path) if blob_path else f"{rev_id}:{file_name}"
-        target[key] = size
-        all_weight_blobs[key] = size
+        value = (size, _blob_mtime(file_obj))
+        target[key] = value
+        all_weight_blobs[key] = value
 
     for revision in repo_info.revisions:
         rev_id = getattr(revision, "commit_hash", None) or str(id(revision))
@@ -375,18 +416,19 @@ def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
         or "unknown"
     )
     if model_format == "adapter":
-        size_bytes = sum(adapter_blobs.values())
+        selected_blobs = adapter_blobs
     elif model_format == "safetensors":
-        size_bytes = sum(safetensors_blobs.values())
+        selected_blobs = safetensors_blobs
     elif model_format == "checkpoint":
-        size_bytes = sum(checkpoint_blobs.values())
+        selected_blobs = checkpoint_blobs
     else:
-        size_bytes = sum(all_weight_blobs.values())
+        selected_blobs = all_weight_blobs
 
     return _CachedNonGgufPayload(
-        size_bytes = size_bytes,
+        size_bytes = sum(size for size, _mtime in selected_blobs.values()),
         has_runnable_weights = model_format != "unknown",
         model_format = model_format,
+        last_modified = max((mtime for _size, mtime in selected_blobs.values()), default = 0.0),
     )
 
 
@@ -508,6 +550,12 @@ def _scan_cached_models() -> list[dict]:
                     ),
                     **_cached_model_local_metadata(repo_path),
                 }
+                last_modified = max(
+                    payload.last_modified,
+                    (existing or {}).get("last_modified", 0.0),
+                )
+                if last_modified > 0:
+                    row["last_modified"] = last_modified
                 row.update(
                     _cache_inventory_fields(
                         repo_id,
@@ -517,6 +565,8 @@ def _scan_cached_models() -> list[dict]:
                 )
                 if _prefer_cache_row(row, existing):
                     seen_lower[key] = row
+                elif last_modified > existing.get("last_modified", 0.0):
+                    existing["last_modified"] = last_modified
             except Exception as e:
                 repo_label = getattr(repo_info, "repo_id", "<unknown>")
                 logger.warning(f"Skipping cached model repo {repo_label}: {e}")
diff --git a/studio/backend/main.py b/studio/backend/main.py
index e64048dc00..bd0d26cf8f 100644
--- a/studio/backend/main.py
+++ b/studio/backend/main.py
@@ -313,6 +313,7 @@ from hub.routes import (
     inventory_router as hub_inventory_router,
     datasets_router as hub_datasets_router,
 )
+from picker.routes import templates_router as picker_templates_router
 from hub.schemas.downloads import TransportCapabilities
 from hub.utils.download_registry import (
     get_download_transport_capabilities,
@@ -745,6 +746,7 @@ _BODY_PROTECTED_PREFIXES = (
     "/v1/completions",
     "/p/",
     "/api/inference",
+    "/api/picker",
     "/api/data-recipe",
     "/api/datasets",
     "/api/hub",
@@ -975,6 +977,7 @@ app.include_router(rag_router, prefix = "/api/rag", tags = ["rag"])
 app.include_router(training_history_router, prefix = "/api/train", tags = ["training-history"])
 app.include_router(hub_inventory_router, prefix = "/api/hub", tags = ["hub"])
 app.include_router(hub_datasets_router, prefix = "/api/hub/datasets", tags = ["hub"])
+app.include_router(picker_templates_router, prefix = "/api/picker", tags = ["picker"])
 
 # Re-wrap client-error responses on the /v1/* surface into OpenAI/Anthropic
 # error envelopes; non-/v1 paths keep FastAPI's default {"detail": ...} shape.
diff --git a/studio/backend/picker/__init__.py b/studio/backend/picker/__init__.py
new file mode 100644
index 0000000000..32014236c6
--- /dev/null
+++ b/studio/backend/picker/__init__.py
@@ -0,0 +1,2 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
diff --git a/studio/backend/picker/routes/__init__.py b/studio/backend/picker/routes/__init__.py
new file mode 100644
index 0000000000..c0e988c8bb
--- /dev/null
+++ b/studio/backend/picker/routes/__init__.py
@@ -0,0 +1,6 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from .templates import router as templates_router
+
+__all__ = ["templates_router"]
diff --git a/studio/backend/picker/routes/templates.py b/studio/backend/picker/routes/templates.py
new file mode 100644
index 0000000000..03707669fa
--- /dev/null
+++ b/studio/backend/picker/routes/templates.py
@@ -0,0 +1,42 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from __future__ import annotations
+
+import asyncio
+from typing import Optional
+
+from fastapi import APIRouter, Body, Depends, Query
+
+from auth.authentication import get_current_subject
+from hub.dependencies import get_hf_token
+
+from ..schemas import (
+    ModelTemplateResponse,
+    ValidateChatTemplateRequest,
+    ValidateChatTemplateResponse,
+)
+from ..service import read_default_chat_template, validate_chat_template
+
+router = APIRouter()
+
+
+@router.post("/validate-chat-template", response_model = ValidateChatTemplateResponse)
+async def validate_chat_template_route(
+    body: ValidateChatTemplateRequest = Body(...),
+    current_subject: str = Depends(get_current_subject),
+) -> ValidateChatTemplateResponse:
+    return await asyncio.to_thread(validate_chat_template, body.template)
+
+
+@router.get("/chat-template/{model_name:path}", response_model = ModelTemplateResponse)
+async def get_default_chat_template_route(
+    model_name: str,
+    gguf_variant: Optional[str] = Query(None),
+    hf_token: Optional[str] = Depends(get_hf_token),
+    current_subject: str = Depends(get_current_subject),
+) -> ModelTemplateResponse:
+    template = await asyncio.to_thread(
+        read_default_chat_template, model_name, hf_token, gguf_variant
+    )
+    return ModelTemplateResponse(model_name = model_name, chat_template = template)
diff --git a/studio/backend/picker/schemas.py b/studio/backend/picker/schemas.py
new file mode 100644
index 0000000000..b4f956188f
--- /dev/null
+++ b/studio/backend/picker/schemas.py
@@ -0,0 +1,32 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from typing import Optional
+
+from pydantic import BaseModel, Field, field_validator
+
+# Mirror the frontend's 64 KiB chat-template contract (per-model-config.ts) at
+# the API boundary so a direct caller cannot make Jinja parse an oversized
+# template. MaxBodyMiddleware only caps the whole request body, not this field.
+MAX_CHAT_TEMPLATE_BYTES = 65_536
+
+
+class ValidateChatTemplateRequest(BaseModel):
+    template: str = Field(default = "")
+
+    @field_validator("template")
+    @classmethod
+    def _enforce_template_size(cls, value: str) -> str:
+        if len(value.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES:
+            raise ValueError(f"Chat template exceeds the {MAX_CHAT_TEMPLATE_BYTES}-byte limit.")
+        return value
+
+
+class ValidateChatTemplateResponse(BaseModel):
+    valid: bool
+    error: Optional[str] = None
+
+
+class ModelTemplateResponse(BaseModel):
+    model_name: str
+    chat_template: Optional[str] = None
diff --git a/studio/backend/picker/service.py b/studio/backend/picker/service.py
new file mode 100644
index 0000000000..f5994dc550
--- /dev/null
+++ b/studio/backend/picker/service.py
@@ -0,0 +1,361 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+import re
+from pathlib import Path
+from typing import Optional
+
+from hub.services.models.folder_browser import (
+    _build_browse_allowlist,
+    _is_path_inside_allowlist,
+)
+from hub.utils.gguf import iter_hf_cache_snapshots
+from utils.models.gguf_metadata import read_gguf_chat_template
+from utils.models.model_config import (
+    _extract_quant_label,
+    _is_big_endian_gguf_path,
+    _is_mmproj,
+    _is_mtp_drafter,
+)
+from utils.paths.path_utils import (
+    is_local_path,
+    normalize_path,
+    resolve_cached_repo_id_case,
+)
+
+from .schemas import ValidateChatTemplateResponse
+
+logger = logging.getLogger(__name__)
+
+_VALID_REPO_ID = re.compile(r"^[A-Za-z0-9._-]+/[A-Za-z0-9._-]+$")
+
+
+def _is_valid_repo_id(repo_id: str) -> bool:
+    return bool(_VALID_REPO_ID.fullmatch(repo_id))
+
+
+_TOKENIZER_CONFIG_PATHS = ("tokenizer_config.json", "LLM/tokenizer_config.json")
+_JINJA_TEMPLATE_PATHS = ("chat_template.jinja", "LLM/chat_template.jinja")
+_PROCESSOR_TEMPLATE_PATHS = ("chat_template.json", "LLM/chat_template.json")
+
+
+def _leaf_inside_allowlist(path: Path, allow_roots: Optional[list[Path]]) -> bool:
+    # Block symlinked children from escaping the validated directory
+    # (realpath-checked). None = trusted caller (HF cache / remote download).
+    return allow_roots is None or _is_path_inside_allowlist(path, allow_roots)
+
+
+def validate_chat_template(template: str) -> ValidateChatTemplateResponse:
+    text = (template or "").strip()
+    if not text:
+        return ValidateChatTemplateResponse(valid = True, error = None)
+    # Import Jinja lazily: it is optional at runtime (e.g. GGUF-only installs),
+    # so a missing dependency must not crash API startup through this module.
+    try:
+        from jinja2 import TemplateError
+        from jinja2.ext import Extension
+        from jinja2.sandbox import ImmutableSandboxedEnvironment
+    except ImportError:
+        return ValidateChatTemplateResponse(valid = True, error = None)
+
+    class _GenerationTag(Extension):
+        # Accept Transformers' {% generation %}...{% endgeneration %} assistant
+        # mask tag so a pasted HF chat template validates (we only parse it).
+        tags = {"generation"}
+
+        def parse(self, parser):
+            next(parser.stream)
+            return parser.parse_statements(["name:endgeneration"], drop_needle = True)
+
+    try:
+        env = ImmutableSandboxedEnvironment(
+            trim_blocks = True,
+            lstrip_blocks = True,
+            extensions = ["jinja2.ext.loopcontrols", _GenerationTag],
+        )
+        env.parse(text)
+        return ValidateChatTemplateResponse(valid = True, error = None)
+    except TemplateError as exc:
+        message = getattr(exc, "message", None) or str(exc)
+        lineno = getattr(exc, "lineno", None)
+        if lineno:
+            message = f"Line {lineno}: {message}"
+        return ValidateChatTemplateResponse(valid = False, error = message)
+    except Exception as exc:
+        return ValidateChatTemplateResponse(valid = False, error = str(exc))
+
+
+def _chat_template_from_tokenizer_config(config: dict) -> Optional[str]:
+    if not isinstance(config, dict):
+        return None
+    raw = config.get("chat_template")
+    if isinstance(raw, str) and raw.strip():
+        return raw
+    if isinstance(raw, list):
+        fallback: Optional[str] = None
+        for entry in raw:
+            if not isinstance(entry, dict):
+                continue
+            template = entry.get("template")
+            if not isinstance(template, str):
+                continue
+            if entry.get("name") == "default":
+                return template
+            if fallback is None:
+                fallback = template
+        return fallback
+    return None
+
+
+def _chat_template_from_jinja_file(
+    dir_path: Path, allow_roots: Optional[list[Path]] = None
+) -> Optional[str]:
+    for rel in _JINJA_TEMPLATE_PATHS:
+        template_file = dir_path / rel
+        if not template_file.exists() or not _leaf_inside_allowlist(template_file, allow_roots):
+            continue
+        try:
+            template = template_file.read_text(encoding = "utf-8")
+        except Exception:
+            continue
+        if template.strip():
+            return template
+    return None
+
+
+def _chat_template_from_processor_payload(payload: object) -> Optional[str]:
+    # processor chat_template.json may be the template string itself or a
+    # {name: template} map, not only a tokenizer_config-shaped object.
+    if isinstance(payload, str):
+        return payload if payload.strip() else None
+    template = _chat_template_from_tokenizer_config(payload)  # type: ignore[arg-type]
+    if template:
+        return template
+    if isinstance(payload, dict):
+        # Named-template map: prefer "default", else the first non-empty entry
+        # (mirrors the tokenizer-config list fallback).
+        default = payload.get("default")
+        if isinstance(default, str) and default.strip():
+            return default
+        for value in payload.values():
+            if isinstance(value, str) and value.strip():
+                return value
+    return None
+
+
+def _chat_template_from_processor_json(
+    dir_path: Path, allow_roots: Optional[list[Path]] = None
+) -> Optional[str]:
+    for rel in _PROCESSOR_TEMPLATE_PATHS:
+        config_file = dir_path / rel
+        if not config_file.exists() or not _leaf_inside_allowlist(config_file, allow_roots):
+            continue
+        try:
+            payload = json.loads(config_file.read_text(encoding = "utf-8"))
+        except Exception:
+            continue
+        template = _chat_template_from_processor_payload(payload)
+        if template:
+            return template
+    return None
+
+
+def _chat_template_from_tokenizer_dir(
+    dir_path: Path, allow_roots: Optional[list[Path]] = None
+) -> Optional[str]:
+    jinja = _chat_template_from_jinja_file(dir_path, allow_roots)
+    if jinja:
+        return jinja
+    for rel in _TOKENIZER_CONFIG_PATHS:
+        config_file = dir_path / rel
+        if not config_file.exists() or not _leaf_inside_allowlist(config_file, allow_roots):
+            continue
+        try:
+            config = json.loads(config_file.read_text(encoding = "utf-8"))
+        except Exception:
+            continue
+        template = _chat_template_from_tokenizer_config(config)
+        if template:
+            return template
+    return _chat_template_from_processor_json(dir_path, allow_roots)
+
+
+_GGUF_SCAN_MAX_DEPTH = 2
+
+
+def _iter_ggufs(dir_path: Path) -> list[Path]:
+    if dir_path == dir_path.parent:
+        return []
+    root = str(dir_path)
+    found: list[Path] = []
+    for current, dirs, files in os.walk(root, followlinks = False):
+        rel = os.path.relpath(current, root)
+        depth = 0 if rel == os.curdir else rel.count(os.sep) + 1
+        if depth >= _GGUF_SCAN_MAX_DEPTH:
+            dirs[:] = []
+        for name in files:
+            if not name.lower().endswith(".gguf") or _is_mmproj(name):
+                continue
+            path = Path(current) / name
+            try:
+                rel = path.relative_to(dir_path).as_posix()
+            except ValueError:
+                rel = name
+            quant = _extract_quant_label(rel)
+            if _is_mtp_drafter(rel) or _is_big_endian_gguf_path(rel, quant):
+                continue
+            found.append(path)
+    return found
+
+
+def _variant_matches(relative_path: str, needle: str) -> bool:
+    quant = _extract_quant_label(relative_path).lower()
+    if quant == needle:
+        return True
+    prefix = f"{needle}-"
+    if not quant.startswith(prefix):
+        return False
+    suffix = quant[len(prefix) :]
+    if not suffix.endswith("bpw"):
+        return False
+    value = suffix[:-3]
+    return bool(value) and value.replace(".", "", 1).isdigit()
+
+
+def _find_gguf_in_dir(dir_path: Path, gguf_variant: Optional[str]) -> Optional[Path]:
+    try:
+        ggufs = sorted(_iter_ggufs(dir_path))
+    except OSError:
+        return None
+    if not ggufs:
+        return None
+    needle = (gguf_variant or "").strip().lower()
+    if needle:
+        for path in ggufs:
+            try:
+                relative = path.relative_to(dir_path).as_posix()
+            except ValueError:
+                relative = path.name
+            if _variant_matches(relative, needle):
+                return path
+        return None
+    try:
+        return max(ggufs, key = lambda path: path.stat().st_size)
+    except OSError:
+        return ggufs[0]
+
+
+def _chat_template_from_dir(
+    dir_path: Path,
+    gguf_variant: Optional[str] = None,
+    allow_roots: Optional[list[Path]] = None,
+) -> Optional[str]:
+    def from_gguf() -> Optional[str]:
+        gguf = _find_gguf_in_dir(dir_path, gguf_variant)
+        if gguf is None or not _leaf_inside_allowlist(gguf, allow_roots):
+            return None
+        return read_gguf_chat_template(str(gguf))
+
+    # Sidecar tokenizer files (chat_template.jinja / tokenizer_config.json) are
+    # the model author's maintained template and supersede the GGUF's embedded
+    # copy, which can be stale. The variant only selects which GGUF to fall back
+    # to, so keep tokenizer-first precedence whether or not a variant is given.
+    return _chat_template_from_tokenizer_dir(dir_path, allow_roots) or from_gguf()
+
+
+def read_default_chat_template(
+    model_name: str,
+    hf_token: Optional[str] = None,
+    gguf_variant: Optional[str] = None,
+) -> Optional[str]:
+    if not isinstance(model_name, str) or not model_name.strip():
+        return None
+    name = model_name.strip()
+
+    if is_local_path(name):
+        try:
+            target = Path(normalize_path(name)).expanduser()
+            allow_roots = _build_browse_allowlist()
+            if not _is_path_inside_allowlist(target, allow_roots):
+                logger.debug("Refused chat template read outside allowed folders: %s", name)
+                return None
+            if name.lower().endswith(".gguf"):
+                # Prefer a maintained sidecar template (chat_template.jinja /
+                # tokenizer_config.json) next to the file over the GGUF's embedded
+                # copy, matching the tokenizer-first precedence used for directory
+                # and variant selections.
+                sidecar = _chat_template_from_tokenizer_dir(target.parent, allow_roots)
+                if sidecar:
+                    return sidecar
+                return read_gguf_chat_template(str(target))
+            return _chat_template_from_dir(target, gguf_variant, allow_roots)
+        except Exception as exc:
+            logger.debug("Could not read local chat template for %s: %s", name, exc)
+            return None
+
+    if not _is_valid_repo_id(name):
+        return None
+
+    resolved = resolve_cached_repo_id_case(name)
+
+    try:
+        # Resolve within each cached revision, newest first. A revision's
+        # maintained sidecar (chat_template.jinja / tokenizer_config.json)
+        # supersedes its own embedded GGUF copy, but a newer revision must not be
+        # overridden by an older revision's sidecar, so precedence stays
+        # per-snapshot rather than searching all sidecars globally first.
+        for snapshot in iter_hf_cache_snapshots(resolved):
+            template = _chat_template_from_dir(snapshot, gguf_variant)
+            if template:
+                return template
+    except Exception as exc:
+        logger.debug("Could not read cached chat template for %s: %s", resolved, exc)
+
+    try:
+        from huggingface_hub import hf_hub_download
+
+        def _download_text(rel: str) -> Optional[str]:
+            try:
+                path = hf_hub_download(resolved, rel, token = hf_token)
+                return Path(path).read_text(encoding = "utf-8")
+            except Exception:
+                return None
+
+        for rel in _JINJA_TEMPLATE_PATHS:
+            template = _download_text(rel)
+            if template and template.strip():
+                return template
+
+        for rel in _TOKENIZER_CONFIG_PATHS:
+            raw = _download_text(rel)
+            if not raw:
+                continue
+            try:
+                config = json.loads(raw)
+            except Exception:
+                continue
+            template = _chat_template_from_tokenizer_config(config)
+            if template:
+                return template
+
+        for rel in _PROCESSOR_TEMPLATE_PATHS:
+            raw = _download_text(rel)
+            if not raw:
+                continue
+            try:
+                payload = json.loads(raw)
+            except Exception:
+                continue
+            template = _chat_template_from_processor_payload(payload)
+            if template:
+                return template
+
+        return None
+    except Exception as exc:
+        logger.debug("Could not fetch chat template for %s: %s", resolved, exc)
+        return None
diff --git a/studio/backend/tests/test_model_update_robustness.py b/studio/backend/tests/test_model_update_robustness.py
index edf55812e2..4c5822e662 100644
--- a/studio/backend/tests/test_model_update_robustness.py
+++ b/studio/backend/tests/test_model_update_robustness.py
@@ -314,6 +314,7 @@ def test_cached_model_scan_keeps_local_safetensors_repo(monkeypatch, tmp_path):
                         file_name = "model.safetensors",
                         size_on_disk = 100,
                         blob_path = str(repo_path / "blobs" / "modelsha"),
+                        blob_last_modified = 3_000.0,
                     ),
                 ]
             )
@@ -336,6 +337,51 @@ def test_cached_model_scan_keeps_local_safetensors_repo(monkeypatch, tmp_path):
     assert rows[0]["repo_id"] == "Org/SafeTensorRepo"
     assert rows[0]["model_format"] == "safetensors"
     assert rows[0]["size_bytes"] == 100
+    assert rows[0]["last_modified"] == 3_000.0
+
+
+def test_cached_gguf_scan_keeps_download_timestamp(monkeypatch, tmp_path):
+    repo_path = tmp_path / "models--Org--GgufRepo"
+    repo = SimpleNamespace(
+        repo_id = "Org/GgufRepo",
+        repo_type = "model",
+        repo_path = repo_path,
+        revisions = [
+            SimpleNamespace(
+                files = [
+                    SimpleNamespace(
+                        file_name = "model-Q4_K_M.gguf",
+                        size_on_disk = 100,
+                        blob_path = None,
+                        blob_last_modified = 5_000.0,
+                    ),
+                ]
+            )
+        ],
+    )
+    monkeypatch.setattr(
+        CI,
+        "all_hf_cache_scans",
+        lambda: [SimpleNamespace(repos = [repo])],
+    )
+    monkeypatch.setattr(
+        CI.hf_cache_scan,
+        "is_gguf_repo_partial",
+        lambda *args, **kwargs: False,
+    )
+    monkeypatch.setattr(
+        CI,
+        "_gguf_variant_state_summary",
+        lambda _repo_id: (False, 0),
+    )
+
+    rows = CI._scan_cached_gguf()
+
+    assert len(rows) == 1
+    assert rows[0]["repo_id"] == "Org/GgufRepo"
+    assert rows[0]["model_format"] == "gguf"
+    assert rows[0]["size_bytes"] == 100
+    assert rows[0]["last_modified"] == 5_000.0
 
 
 # ── hf_hub_download_with_xet_fallback force_download bypass (X2/F2) ───
diff --git a/studio/backend/tests/test_picker_service.py b/studio/backend/tests/test_picker_service.py
new file mode 100644
index 0000000000..fc835bf019
--- /dev/null
+++ b/studio/backend/tests/test_picker_service.py
@@ -0,0 +1,162 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import json
+
+from picker.service import (
+    _chat_template_from_dir,
+    _chat_template_from_tokenizer_config,
+    _chat_template_from_tokenizer_dir,
+    _find_gguf_in_dir,
+    _iter_ggufs,
+    read_default_chat_template,
+    validate_chat_template,
+)
+
+
+def test_iter_ggufs_skips_gguf_companions(tmp_path):
+    mtp_dir = tmp_path / "MTP"
+    mtp_dir.mkdir()
+    main = tmp_path / "model-Q8_0.gguf"
+    main.write_bytes(b"")
+    (tmp_path / "mmproj-F16.gguf").write_bytes(b"")
+    (tmp_path / "mtp-model-Q8_0.gguf").write_bytes(b"")
+    (mtp_dir / "model-Q8_0-MTP.gguf").write_bytes(b"")
+    (tmp_path / "model-Q8_0-be.gguf").write_bytes(b"")
+
+    assert _iter_ggufs(tmp_path) == [main]
+
+
+def test_find_gguf_in_dir_matches_quant_label(tmp_path):
+    mtp_dir = tmp_path / "MTP"
+    mtp_dir.mkdir()
+    main = tmp_path / "model-Q8_0.gguf"
+    main.write_bytes(b"")
+    (mtp_dir / "model-Q8_0-MTP.gguf").write_bytes(b"")
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+
+    assert _find_gguf_in_dir(tmp_path, "Q8_0") == main
+    assert _find_gguf_in_dir(tmp_path, "Q4_K") is None
+
+
+def test_find_gguf_in_dir_without_variant_prefers_largest_model(tmp_path):
+    smaller = tmp_path / "a-model-Q4_K_M.gguf"
+    larger = tmp_path / "z-model-Q8_0.gguf"
+    smaller.write_bytes(b"0")
+    larger.write_bytes(b"00")
+
+    assert _find_gguf_in_dir(tmp_path, None) == larger
+
+
+def test_find_gguf_in_dir_matches_bpw_variant_base_label(tmp_path):
+    target = tmp_path / "model-IQ4_XS-3.53bpw.gguf"
+    target.write_bytes(b"")
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+
+    assert _find_gguf_in_dir(tmp_path, "IQ4_XS") == target
+    assert _find_gguf_in_dir(tmp_path, "IQ4_XS-3.53bpw") == target
+    assert _find_gguf_in_dir(tmp_path, "Q4_K") is None
+
+
+def test_validate_chat_template_accepts_valid_and_empty():
+    assert validate_chat_template("{{ messages[0].content }}").valid is True
+    assert validate_chat_template("").valid is True
+    assert validate_chat_template("   ").valid is True
+
+
+def test_validate_chat_template_reports_syntax_error_with_line():
+    result = validate_chat_template("{% if %}{% endif %}")
+    assert result.valid is False
+    assert result.error is not None
+    assert result.error.startswith("Line ")
+
+
+def test_chat_template_from_tokenizer_config_reads_string():
+    assert _chat_template_from_tokenizer_config({"chat_template": "HELLO"}) == "HELLO"
+    assert _chat_template_from_tokenizer_config({"chat_template": "   "}) is None
+    assert _chat_template_from_tokenizer_config({}) is None
+
+
+def test_chat_template_from_tokenizer_config_prefers_named_default():
+    config = {
+        "chat_template": [
+            {"name": "tool_use", "template": "TOOL"},
+            {"name": "default", "template": "DEFAULT"},
+        ]
+    }
+    assert _chat_template_from_tokenizer_config(config) == "DEFAULT"
+
+
+def test_chat_template_from_tokenizer_config_falls_back_to_first_entry():
+    config = {
+        "chat_template": [
+            {"name": "tool_use", "template": "TOOL"},
+            {"name": "other", "template": "OTHER"},
+        ]
+    }
+    assert _chat_template_from_tokenizer_config(config) == "TOOL"
+
+
+def test_chat_template_from_tokenizer_dir_prefers_jinja_file(tmp_path):
+    (tmp_path / "chat_template.jinja").write_text("FROM_JINJA", encoding = "utf-8")
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_JINJA"
+
+
+def test_chat_template_from_tokenizer_dir_reads_tokenizer_config(tmp_path):
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_CONFIG"
+
+
+def test_chat_template_from_dir_without_variant_prefers_tokenizer(tmp_path):
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    assert _chat_template_from_dir(tmp_path) == "FROM_CONFIG"
+
+
+def test_chat_template_from_dir_with_variant_still_prefers_tokenizer(tmp_path, monkeypatch):
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # Selecting a variant must not flip precedence to the embedded GGUF template.
+    assert _chat_template_from_dir(tmp_path, "Q4_K_M") == "FROM_CONFIG"
+
+
+def test_chat_template_from_dir_with_variant_falls_back_to_gguf(tmp_path, monkeypatch):
+    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # With no tokenizer sidecar, the embedded GGUF template is still the fallback.
+    assert _chat_template_from_dir(tmp_path, "Q4_K_M") == "FROM_GGUF"
+
+
+def test_chat_template_from_dir_returns_none_when_absent(tmp_path):
+    assert _chat_template_from_dir(tmp_path) is None
+
+
+def test_read_default_chat_template_direct_gguf_prefers_sidecar(tmp_path, monkeypatch):
+    gguf = tmp_path / "model-Q4_K_M.gguf"
+    gguf.write_bytes(b"")
+    (tmp_path / "tokenizer_config.json").write_text(
+        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
+    )
+    monkeypatch.setattr("picker.service._build_browse_allowlist", lambda: [tmp_path])
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # A directly selected .gguf file must prefer a maintained sidecar template
+    # over its embedded copy, matching directory/variant precedence.
+    assert read_default_chat_template(str(gguf)) == "FROM_CONFIG"
+
+
+def test_read_default_chat_template_direct_gguf_falls_back_to_embedded(tmp_path, monkeypatch):
+    gguf = tmp_path / "model-Q4_K_M.gguf"
+    gguf.write_bytes(b"")
+    monkeypatch.setattr("picker.service._build_browse_allowlist", lambda: [tmp_path])
+    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
+    # With no sidecar next to the file, the embedded GGUF template is the fallback.
+    assert read_default_chat_template(str(gguf)) == "FROM_GGUF"
diff --git a/studio/backend/utils/models/gguf_metadata.py b/studio/backend/utils/models/gguf_metadata.py
index c24ec28e1d..5e25ce1927 100644
--- a/studio/backend/utils/models/gguf_metadata.py
+++ b/studio/backend/utils/models/gguf_metadata.py
@@ -50,6 +50,8 @@ _CACHE_MAX_ENTRIES = 4096
 # keyed by (file cache key, wanted key). None = key absent / file unreadable.
 _BOOL_CACHE: Dict[Tuple[_CacheKey, str], Optional[bool]] = {}
 
+_STRING_CACHE: Dict[Tuple[_CacheKey, str], Optional[str]] = {}
+
 # Native training context length (``{arch}.context_length``). None = absent /
 # unreadable. Lets the UI show the real context ceiling before a model loads.
 _CONTEXT_CACHE: Dict[_CacheKey, Optional[int]] = {}
@@ -353,6 +355,83 @@ def _read_gguf_bool(path: str, wanted_key: str) -> Optional[bool]:
     return result
 
 
+def _parse_gguf_string(path: str, wanted_key: str) -> Optional[str]:
+    try:
+        with open(path, "rb") as f:
+            head = f.read(24)
+            if len(head) < 24:
+                return None
+            magic, _version, _tcount, kv_count = struct.unpack("<IIQQ", head)
+            if magic != _GGUF_MAGIC:
+                return None
+
+            for _ in range(kv_count):
+                try:
+                    klen_bytes = f.read(8)
+                    if len(klen_bytes) < 8:
+                        break
+                    klen = struct.unpack("<Q", klen_bytes)[0]
+                    if klen > 1 << 20:
+                        break
+                    kbytes = f.read(klen)
+                    if len(kbytes) < klen:
+                        break
+                    key = kbytes.decode("utf-8", "replace")
+                    vt_bytes = f.read(4)
+                    if len(vt_bytes) < 4:
+                        break
+                    vtype = struct.unpack("<I", vt_bytes)[0]
+
+                    if key == wanted_key and vtype == 8:
+                        slen_bytes = f.read(8)
+                        if len(slen_bytes) < 8:
+                            break
+                        slen = struct.unpack("<Q", slen_bytes)[0]
+                        if slen > 1 << 22:
+                            break
+                        sbytes = f.read(slen)
+                        if len(sbytes) < slen:
+                            break
+                        return sbytes.decode("utf-8", "replace")
+                    if not _skip_gguf_value(f, vtype):
+                        break
+                except (struct.error, UnicodeDecodeError):
+                    break
+    except OSError as e:
+        logger.debug(f"_parse_gguf_string: cannot open {path}: {e}")
+        return None
+    except Exception as e:
+        logger.debug(f"_parse_gguf_string: parse failure on {path}: {e}")
+        return None
+    return None
+
+
+def _read_gguf_string(path: str, wanted_key: str) -> Optional[str]:
+    fkey = _cache_key(path)
+    if fkey is None:
+        return None
+    ckey = (fkey, wanted_key)
+    with _CACHE_LOCK:
+        if ckey in _STRING_CACHE:
+            return _STRING_CACHE[ckey]
+    result = _parse_gguf_string(path, wanted_key)
+    with _CACHE_LOCK:
+        while len(_STRING_CACHE) >= _CACHE_MAX_ENTRIES:
+            try:
+                _STRING_CACHE.pop(next(iter(_STRING_CACHE)))
+            except StopIteration:
+                break
+        _STRING_CACHE[ckey] = result
+    return result
+
+
+def read_gguf_chat_template(path: str) -> Optional[str]:
+    template = _read_gguf_string(path, "tokenizer.chat_template")
+    if isinstance(template, str) and template.strip():
+        return template
+    return None
+
+
 def read_mmproj_audio_capability(path: str) -> Optional[bool]:
     """``clip.has_audio_encoder`` from an mmproj GGUF (e.g. Gemma 4's
     gemma4ua): ``True``/``False`` if present, ``None`` if absent/unreadable.
diff --git a/studio/frontend/src/app/routes/__root.tsx b/studio/frontend/src/app/routes/__root.tsx
index ba56ce7525..6c2505f1ca 100644
--- a/studio/frontend/src/app/routes/__root.tsx
+++ b/studio/frontend/src/app/routes/__root.tsx
@@ -195,9 +195,6 @@ function RootLayout() {
         chatRuntime.setActiveThreadId(null);
         chatRuntime.setActiveProjectId(null);
         chatRuntime.setIncognito(false);
-        // Detach the staging UI but keep any in-flight download running, like Hub.
-        if (chatRuntime.pendingSelection)
-          chatRuntime.abandonStagedModel({ keepDownload: true });
         void navigate({
           to: "/chat",
           search: { new: crypto.randomUUID() },
@@ -220,10 +217,6 @@ function RootLayout() {
     chatRuntime.setActiveProjectId(null);
     chatRuntime.setActiveThreadId(null);
     chatRuntime.setIncognito(false);
-    // Leaving chat must not kill an in-flight download: detach the staging UI
-    // but keep the transfer running in the manager, like a Hub download.
-    if (chatRuntime.pendingSelection)
-      chatRuntime.abandonStagedModel({ keepDownload: true });
   }, [isChatRoute]);
 
   return (
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts b/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
deleted file mode 100644
index ec75b17f20..0000000000
--- a/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
+++ /dev/null
@@ -1,69 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-// Per-model pre-load inference settings, persisted in localStorage so the load
-// dialog can offer "Remember settings for <model>".
-
-const KEY = "unsloth_load_settings";
-
-export interface RememberedLoadSettings {
-  contextLength: number | null;
-  kvCacheDtype: string | null;
-  speculativeType: string | null;
-  specDraftNMax: number | null;
-  tensorParallel: boolean;
-}
-
-// Storage key for a pick's remembered settings. The remembered knobs are
-// VRAM-budget driven (context override, KV-cache dtype, tensor-parallel), so the
-// right values differ per quant. An HF repo collapses all its GGUF variants into
-// one `id`, so fold the variant in to scope settings per quant. Local .gguf
-// paths key by their file path (already file-specific); native drag-drop files
-// key by display label, so same-named files in different folders share an entry.
-export function rememberedLoadSettingsKey(selection: {
-  id: string;
-  ggufVariant?: string | null;
-}): string {
-  return selection.ggufVariant
-    ? `${selection.id}::${selection.ggufVariant}`
-    : selection.id;
-}
-
-function readAll(): Record<string, RememberedLoadSettings> {
-  try {
-    return JSON.parse(localStorage.getItem(KEY) ?? "{}");
-  } catch {
-    return {};
-  }
-}
-
-function writeAll(all: Record<string, RememberedLoadSettings>) {
-  try {
-    localStorage.setItem(KEY, JSON.stringify(all));
-  } catch {
-    // Ignore quota / unavailable storage.
-  }
-}
-
-export function loadRememberedLoadSettings(
-  key: string,
-): RememberedLoadSettings | null {
-  return readAll()[key] ?? null;
-}
-
-export function saveRememberedLoadSettings(
-  key: string,
-  settings: RememberedLoadSettings,
-) {
-  const all = readAll();
-  all[key] = settings;
-  writeAll(all);
-}
-
-export function clearRememberedLoadSettings(key: string) {
-  const all = readAll();
-  if (key in all) {
-    delete all[key];
-    writeAll(all);
-  }
-}
diff --git a/studio/frontend/src/features/chat/api/chat-adapter.ts b/studio/frontend/src/features/chat/api/chat-adapter.ts
index 0bf46e7343..d3bdcb6898 100644
--- a/studio/frontend/src/features/chat/api/chat-adapter.ts
+++ b/studio/frontend/src/features/chat/api/chat-adapter.ts
@@ -2,10 +2,7 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { getAuthToken } from "@/features/auth";
-import {
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
+import { resolveInitialConfig } from "@/features/model-picker";
 import { projectHasSources } from "@/features/rag/api/rag-api";
 import { apiUrl } from "@/lib/api-base";
 import { parseParamCountB } from "@/lib/model-size";
@@ -1520,27 +1517,25 @@ async function autoLoadSmallestModel(): Promise<{
       return false;
     }
     const currentStore = useChatRuntimeStore.getState();
-    const remembered = loadRememberedLoadSettings(
-      rememberedLoadSettingsKey({
-        id: candidate.id,
-        ggufVariant: candidate.ggufVariant,
-      }),
-    );
+    const { config } = resolveInitialConfig(candidate.id, candidate.ggufVariant);
     const effectiveMaxSeqLength = resolveLoadMaxSeqLength({
       modelId: candidate.id,
       ggufVariant: candidate.ggufVariant,
       isGguf: candidate.kind === "gguf",
-      customContextLength: remembered?.contextLength ?? null,
+      customContextLength: config.customContextLength,
       ggufContextLength: null,
       currentCheckpoint: currentStore.params.checkpoint,
       activeGgufVariant: currentStore.activeGgufVariant,
-      maxSeqLength: candidate.maxSeqLength,
+      maxSeqLength: config.maxSeqLength ?? candidate.maxSeqLength,
       presetSource: currentStore.activePresetSource,
     });
     const effectiveSpeculativeType =
-      remembered?.speculativeType ?? specSettings.speculativeType;
+      config.speculativeType ?? specSettings.speculativeType;
     const effectiveSpecDraftNMax =
-      remembered?.specDraftNMax ?? specSettings.specDraftNMax;
+      config.specDraftNMax ?? specSettings.specDraftNMax;
+    const effectiveChatTemplateOverride = config.chatTemplateOverride?.trim()
+      ? config.chatTemplateOverride
+      : null;
     if (
       !(await canAutoLoad({
         model_path: candidate.id,
@@ -1563,12 +1558,18 @@ async function autoLoadSmallestModel(): Promise<{
       is_lora: false,
       gguf_variant: candidate.ggufVariant,
       trust_remote_code: trustRemoteCode,
-      cache_type_kv: remembered?.kvCacheDtype ?? null,
+      chat_template_override: effectiveChatTemplateOverride,
+      cache_type_kv: config.kvCacheDtype,
       speculative_type: effectiveSpeculativeType,
       spec_draft_n_max: effectiveSpecDraftNMax,
-      tensor_parallel: remembered?.tensorParallel ?? false,
+      tensor_parallel: config.tensorParallel,
     });
-    saveSpeculativeType(effectiveSpeculativeType);
+    // Only persist the global preference when the value came from the global
+    // settings. A per-model config's choice must stay load-local, or autoloading
+    // a remembered model on startup would rewrite the global default.
+    if (config.speculativeType == null) {
+      saveSpeculativeType(effectiveSpeculativeType);
+    }
     useChatRuntimeStore
       .getState()
       .setCheckpoint(candidate.id, candidate.ggufVariant ?? undefined);
@@ -1578,6 +1579,9 @@ async function autoLoadSmallestModel(): Promise<{
     );
     store.setParams({
       ...store.params,
+      ...(candidate.kind === "gguf"
+        ? {}
+        : { maxSeqLength: effectiveMaxSeqLength }),
       maxTokens:
         candidate.kind === "gguf"
           ? loadResp.context_length ?? 131072
@@ -1614,8 +1618,11 @@ async function autoLoadSmallestModel(): Promise<{
         tensorParallel: loadResp.tensor_parallel ?? false,
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
         defaultChatTemplate: loadResp.chat_template ?? null,
-        chatTemplateOverride: null,
-        loadedChatTemplateOverride: null,
+        chatTemplateOverride: effectiveChatTemplateOverride,
+        loadedChatTemplateOverride: effectiveChatTemplateOverride,
+        // Retain the saved requested context so re-saving the config keeps the
+        // override; null stays null (auto/VRAM-fit).
+        customContextLength: config.customContextLength,
         loadedIsMultimodal: isMultimodalResponse(loadResp),
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
         ...resolveLoadedSpeculativeSettings(loadResp),
@@ -1634,8 +1641,9 @@ async function autoLoadSmallestModel(): Promise<{
         tensorParallel: loadResp.tensor_parallel ?? false,
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
         defaultChatTemplate: loadResp.chat_template ?? null,
-        chatTemplateOverride: null,
-        loadedChatTemplateOverride: null,
+        chatTemplateOverride: effectiveChatTemplateOverride,
+        loadedChatTemplateOverride: effectiveChatTemplateOverride,
+        customContextLength: null,
         ...resolveLoadedSpeculativeSettings(loadResp),
         loadedIsMultimodal: isMultimodalResponse(loadResp),
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
diff --git a/studio/frontend/src/features/chat/chat-page.tsx b/studio/frontend/src/features/chat/chat-page.tsx
index 380ce0e0ab..731a551c53 100644
--- a/studio/frontend/src/features/chat/chat-page.tsx
+++ b/studio/frontend/src/features/chat/chat-page.tsx
@@ -2,16 +2,18 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import {
+  applyModelLoadConfigToRuntime,
+  currentRuntimePerModelConfig,
   type DeletedModelRef,
   type ExternalModelOption,
   type LoraModelOption,
   type ModelOption,
   ModelSelector,
-} from "@/components/assistant-ui/model-selector";
-import {
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
+  type ModelSelectorChangeMeta,
+  type PerModelConfig,
+  resolveInitialConfig,
+  SidebarModelConfig,
+} from "@/features/model-picker";
 import { ProjectComposer, Thread } from "@/components/assistant-ui/thread";
 import { CopyableErrorChip } from "@/components/ui/copyable-error-chip";
 import {
@@ -27,10 +29,10 @@ import {
 } from "@/components/ui/resizable";
 import { useSidebar } from "@/components/ui/sidebar";
 import { Tooltip, TooltipContent } from "@/components/ui/tooltip";
-import { useLatestRef } from "@/features/hub/hooks/use-latest-ref";
 import {
   DOWNLOAD_KIND,
   downloadManager,
+  useRepoDownload,
 } from "@/features/hub/download-manager";
 import {
   type NativeIntent,
@@ -93,7 +95,6 @@ import {
   renameChatItem,
   useChatSidebarItems,
 } from "./hooks/use-chat-sidebar-items";
-import { useStagedModelPreparation } from "./hooks/use-staged-model-preparation";
 import {
   clearTrainingCompareHandoff,
   getTrainingCompareHandoff,
@@ -128,10 +129,8 @@ import {
   hasGgufSource,
   isDownloadableHubRepo,
   loadOptionalBool,
-  pendingSelectionMatches,
   useChatRuntimeStore,
 } from "./stores/chat-runtime-store";
-import type { PendingModelSelection } from "./stores/chat-runtime-store";
 import { useChatPreferencesStore } from "./stores/chat-preferences-store";
 import { useExternalProvidersStore } from "./stores/external-providers-store";
 import { buildChatTourSteps } from "./tour";
@@ -385,6 +384,7 @@ type CompareModelSelection = {
   id: string;
   isLora: boolean;
   ggufVariant?: string;
+  config?: PerModelConfig;
 };
 
 function modelMatchesDeleted(
@@ -645,6 +645,8 @@ function GeneralCompareHeader({
   loraModels,
   externalModels,
   value,
+  selectedConfig,
+  selectedGgufVariant,
   onValueChange,
   onFoldersChange,
   onModelsChange,
@@ -655,9 +657,11 @@ function GeneralCompareHeader({
   loraModels: LoraModelOption[];
   externalModels: ExternalModelOption[];
   value: string;
+  selectedConfig?: PerModelConfig | null;
+  selectedGgufVariant?: string | null;
   onValueChange: (
     id: string,
-    meta: { isLora: boolean; ggufVariant?: string },
+    meta: ModelSelectorChangeMeta,
   ) => void;
   onFoldersChange?: () => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
@@ -684,6 +688,8 @@ function GeneralCompareHeader({
         loraModels={loraModels}
         externalModels={externalModels}
         value={value}
+        selectedConfig={selectedConfig}
+        selectedGgufVariant={selectedGgufVariant}
         onValueChange={onValueChange}
         onFoldersChange={onFoldersChange}
         onModelsChange={onModelsChange}
@@ -811,11 +817,14 @@ const GeneralCompareContent = memo(function GeneralCompareContent({
               loraModels={loraModels}
               externalModels={externalModels}
               value={model1.id}
+              selectedConfig={model1.config}
+              selectedGgufVariant={model1.ggufVariant}
               onValueChange={(id, meta) =>
                 setModel1({
                   id,
                   isLora: meta.isLora,
                   ggufVariant: meta.ggufVariant,
+                  config: meta.config,
                 })
               }
               onFoldersChange={onFoldersChange}
@@ -838,11 +847,14 @@ const GeneralCompareContent = memo(function GeneralCompareContent({
               loraModels={loraModels}
               externalModels={externalModels}
               value={model2.id}
+              selectedConfig={model2.config}
+              selectedGgufVariant={model2.ggufVariant}
               onValueChange={(id, meta) =>
                 setModel2({
                   id,
                   isLora: meta.isLora,
                   ggufVariant: meta.ggufVariant,
+                  config: meta.config,
                 })
               }
               onFoldersChange={onFoldersChange}
@@ -1236,6 +1248,13 @@ export function validateChatSearch(search: Record<string, unknown>): ChatSearch
   };
 }
 
+type PendingHubAutoLoad = {
+  selection: SelectedModelInput;
+  contextKey: string;
+  originCheckpoint: string;
+  originGgufVariant: string | null;
+};
+
 // `search` comes from RootLayout (not useSearch) so ChatPage stays mounted off-route
 // (keeping an in-flight generation alive), frozen to the last /chat search. `active`
 // is false off-route: close body-portaled surfaces and stop route-specific listeners
@@ -1248,30 +1267,6 @@ export function ChatPage({
 
   const settingsOpen = useChatRuntimeStore((s) => s.settingsPanelOpen);
   const setSettingsOpen = useChatRuntimeStore((s) => s.setSettingsPanelOpen);
-  // Deferred-load staging: downloads a staged GGUF (if needed) and reads its
-  // header context so the sheet can show the context slider before the load.
-  // autoLoad picks instead load the cached file as soon as the download ends;
-  // selectModel is defined below, so the load runs through a ref.
-  const autoLoadStagedRef = useRef<
-    ((pending: PendingModelSelection) => void) | null
-  >(null);
-  const stagedDownload = useStagedModelPreparation({
-    onAutoLoad: (pending) => autoLoadStagedRef.current?.(pending),
-  });
-  // Abandon a staged pick: the store action cancels its in-flight download and
-  // reverts the edited knobs, so nothing lingers after the user walks away.
-  const abandonStaged = useCallback(() => {
-    useChatRuntimeStore.getState().abandonStagedModel();
-  }, []);
-  // Detach a staged pick on navigation without cancelling its download: the
-  // transfer keeps running in the manager and lands in cache, like Hub.
-  const detachStaged = useCallback(() => {
-    useChatRuntimeStore.getState().abandonStagedModel({ keepDownload: true });
-  }, []);
-  // Tracks whether the chat page is still mounted, so a staged-load failure that
-  // resolves after the user left chat doesn't resurrect the abandoned pick.
-  const mountedRef = useRef(true);
-  useEffect(() => () => void (mountedRef.current = false), []);
   const incognito = useChatRuntimeStore((s) => s.incognito);
   const setIncognito = useChatRuntimeStore((s) => s.setIncognito);
   const incognitoLabel = incognito
@@ -1363,6 +1358,9 @@ export function ChatPage({
   const ggufContextLength = useChatRuntimeStore(
     (state) => state.ggufContextLength,
   );
+  const ggufNativeContextLength = useChatRuntimeStore(
+    (state) => state.ggufNativeContextLength,
+  );
   const contextUsage = useChatRuntimeStore((state) => state.contextUsage);
   const modelsFromStore = useChatRuntimeStore((state) => state.models);
   const lorasFromStore = useChatRuntimeStore((state) => state.loras);
@@ -1440,37 +1438,82 @@ export function ChatPage({
     refreshRef.current = refresh;
     selectModelRef.current = selectModel;
   }, [refresh, selectModel]);
-  // Load a cached autoLoad pick once its download finishes. The sheet was never
-  // opened, so on a load failure just drop the orphaned staged knobs. The knobs
-  // were already seeded on stage, so keepSpeculative only when a config was
-  // saved -- otherwise the standing speculative preference should win.
-  autoLoadStagedRef.current = (pending) => {
-    const remembered = loadRememberedLoadSettings(
-      rememberedLoadSettingsKey(pending),
-    );
-    void selectModel({
-      ...pending,
-      isDownloaded: true,
-      forceReload: true,
-      keepSpeculative: remembered != null,
-      throwOnError: true,
-    }).catch(() => {
-      const store = useChatRuntimeStore.getState();
-      // selectModel only clears pendingSelection on success, so a failed
-      // auto-load leaves our staged pick (and its edited load knobs) behind.
-      // Abandon it when it is still the active stage; otherwise just revert the
-      // settings if the stage was already cleared by something else.
-      if (pendingSelectionMatches(store.pendingSelection, pending)) {
-        store.abandonStagedModel();
-      } else if (!store.pendingSelection) {
-        store.resetModelSettingsToLoaded();
-      }
-    });
-  };
+  const rememberedConfigFor = useCallback(
+    (selection: {
+      id: string;
+      ggufVariant?: string | null;
+      source?: string;
+    }) => {
+      if (selection.source === "external") return null;
+      const resolved = resolveInitialConfig(selection.id, selection.ggufVariant);
+      return resolved.remembered ? resolved.config : null;
+    },
+    [],
+  );
   const isExternalModel = useMemo(
     () => isExternalModelId(inferenceParams.checkpoint),
     [inferenceParams.checkpoint],
   );
+  const runtimeCustomContextLength = useChatRuntimeStore(
+    (s) => s.customContextLength,
+  );
+  const runtimeKvCacheDtype = useChatRuntimeStore((s) => s.kvCacheDtype);
+  const runtimeSpeculativeType = useChatRuntimeStore((s) => s.speculativeType);
+  const runtimeSpecDraftNMax = useChatRuntimeStore((s) => s.specDraftNMax);
+  const runtimeTensorParallel = useChatRuntimeStore((s) => s.tensorParallel);
+  const runtimeChatTemplateOverride = useChatRuntimeStore(
+    (s) => s.chatTemplateOverride,
+  );
+  const activeModelConfig = useMemo<PerModelConfig | null>(() => {
+    if (!inferenceParams.checkpoint || isExternalModel) return null;
+    const activeModelIsGguf =
+      activeGgufVariant != null ||
+      ggufContextLength != null ||
+      inferenceParams.checkpoint.toLowerCase().endsWith(".gguf");
+    return {
+      customContextLength: runtimeCustomContextLength ?? null,
+      maxSeqLength: activeModelIsGguf ? null : inferenceParams.maxSeqLength,
+      kvCacheDtype: runtimeKvCacheDtype ?? null,
+      speculativeType: runtimeSpeculativeType ?? "auto",
+      specDraftNMax: runtimeSpecDraftNMax ?? null,
+      tensorParallel: runtimeTensorParallel ?? false,
+      chatTemplateOverride: runtimeChatTemplateOverride ?? null,
+    };
+  }, [
+    inferenceParams.checkpoint,
+    inferenceParams.maxSeqLength,
+    isExternalModel,
+    activeGgufVariant,
+    ggufContextLength,
+    runtimeCustomContextLength,
+    runtimeKvCacheDtype,
+    runtimeSpeculativeType,
+    runtimeSpecDraftNMax,
+    runtimeTensorParallel,
+    runtimeChatTemplateOverride,
+  ]);
+  const activeModelIsGguf = useMemo(() => {
+    const checkpoint = inferenceParams.checkpoint;
+    if (!checkpoint || isExternalModel) return false;
+    return (
+      activeGgufVariant != null ||
+      ggufContextLength != null ||
+      checkpoint.toLowerCase().endsWith(".gguf")
+    );
+  }, [
+    inferenceParams.checkpoint,
+    isExternalModel,
+    activeGgufVariant,
+    ggufContextLength,
+  ]);
+  const activeModelIsLora = useMemo(() => {
+    const checkpoint = inferenceParams.checkpoint;
+    if (!checkpoint || isExternalModel) return false;
+    const model = modelsFromStore.find((entry) => entry.id === checkpoint);
+    if (model) return model.isLora;
+    const lora = lorasFromStore.find((entry) => entry.id === checkpoint);
+    return lora?.exportType === "lora";
+  }, [inferenceParams.checkpoint, isExternalModel, modelsFromStore, lorasFromStore]);
   const reasoningEnabled = useChatRuntimeStore((s) => s.reasoningEnabled);
   const reasoningStyle = useChatRuntimeStore((s) => s.reasoningStyle);
   const reasoningEffort = useChatRuntimeStore((s) => s.reasoningEffort);
@@ -1783,75 +1826,21 @@ export function ChatPage({
     closeArtifactSurface();
   }, [activeThreadId, closeArtifactSurface, selectedArtifact, view]);
 
-  // Abandon a staged (not-yet-loaded) pick when the chat context actually
-  // changes — switching threads, leaving single view, or starting a new chat /
-  // project — so a stale Load button can't resurface in a different context.
-  // New Chat keeps activeThreadId null and only bumps the `new` search nonce, so
-  // the key includes the route identity, not just the thread. Mirrors the
-  // incognito reset pattern. (Route exit is handled in __root.tsx, which runs
-  // after this unmounts.) Clear only on a real change, never on mount: staging
-  // from the Hub sets pendingSelection then navigates here, and clearing on
-  // mount would wipe it. Comparing the previous context (rather than a first-run
-  // flag) is also safe under StrictMode's double-invoke and component remounts.
-  const chatContextKey = `${view.mode}|${activeThreadId ?? ""}|${search.new ?? ""}|${search.project ?? ""}`;
-  const chatContextKeyRef = useLatestRef(chatContextKey);
-  const prevChatContextRef = useRef<string | null>(null);
-  useEffect(() => {
-    const prev = prevChatContextRef.current;
-    prevChatContextRef.current = chatContextKey;
-    if (prev === null || prev === chatContextKey) return;
-    detachStaged();
-  }, [chatContextKey, detachStaged]);
-
   const hasActiveModel = Boolean(inferenceParams.checkpoint);
-  // Load immediately, or — when "Load on selection" is off — stage the pick so
-  // its load options can be set first. Shared by the main selector, native
-  // drag-drop/picker, and the dropped-file chip (the Hub stages via the store).
+  const chatContextKey = `${view.mode}|${activeThreadId ?? ""}|${search.new ?? ""}|${search.project ?? ""}`;
+  const [pendingHubAutoLoad, setPendingHubAutoLoad] =
+    useState<PendingHubAutoLoad | null>(null);
   const stageOrLoad = useCallback(
     async (selection: SelectedModelInput) => {
       const store = useChatRuntimeStore.getState();
-      // An un-cached HF repo (GGUF variant or a full non-GGUF snapshot) downloads
-      // through the manager first (global indicator), then auto-loads. Everything
-      // else -- cached picks, local/native files, LoRA, external -- loads now.
       const wantManagerDownload =
         isDownloadableHubRepo(selection) && !selection.isDownloaded;
-      if (
-        (!hasGgufSource(selection) && !wantManagerDownload) ||
-        (store.loadOnSelection && selection.isDownloaded)
-      ) {
-        // Detach any staged pick first so its edited knobs (e.g. a custom
-        // context length) don't leak into this immediate load -- resolveLoad
-        // reads customContextLength before checking the target is GGUF. Detach
-        // (not abandon) keeps its download running.
-        detachStaged();
-        // Load-on-selection skips the sheet, so seed the saved knobs here the
-        // way the sheet's restore effect would; the switch would otherwise reset
-        // the remembered speculative choice (keepSpeculative below prevents it).
-        const remembered = hasGgufSource(selection)
-          ? loadRememberedLoadSettings(rememberedLoadSettingsKey(selection))
-          : null;
-        if (remembered) store.applyRememberedLoadSettings(remembered);
-        await selectModel(
-          remembered ? { ...selection, keepSpeculative: true } : selection,
-        );
-        return;
-      }
-      // Loads can't queue behind each other, but a download is independent: if
-      // the pick needs downloading, start it in the manager so it runs alongside
-      // the load. Nothing to download (already on device) just waits.
       if (store.modelLoading) {
-        // Both an uncached non-GGUF snapshot (wantManagerDownload) and an
-        // uncached remote GGUF quant download through the manager, so either can
-        // run in the background while another model loads. wantManagerDownload
-        // excludes GGUF by design, so the GGUF case is checked separately.
         const wantBackgroundDownload =
           wantManagerDownload ||
           (selection.source === "hub" &&
             hasGgufSource(selection) &&
             !selection.isDownloaded);
-        // The model currently loading already downloads as part of its own load
-        // (the /load flow fetches before setting the checkpoint), so re-picking
-        // it must not kick off a second transfer against the same cache.
         const isLoadingThisPick =
           !!loadingModel &&
           normalizeModelRef(loadingModel.id) ===
@@ -1862,11 +1851,6 @@ export function ChatPage({
             description: "It's downloading as part of the load in progress.",
           });
         } else if (wantBackgroundDownload) {
-          // Only claim the download started once a job is actually created. A
-          // transport conflict records state that is only resolvable from the
-          // Hub download card, so point the user there instead of showing a
-          // success toast for a transfer that never began; "busy" and "error"
-          // already surface their own toasts.
           const outcome = await downloadManager.requestStart({
             kind: DOWNLOAD_KIND.MODEL,
             repoId: selection.id,
@@ -1883,6 +1867,11 @@ export function ChatPage({
               description:
                 "An earlier partial download used a different transport. Open the Hub tab to resume or restart it.",
             });
+          } else if (outcome === "busy") {
+            toast.info("Download already in progress", {
+              description:
+                "Another download for this model is still running. Reselect it once that finishes to load it.",
+            });
           }
         } else {
           toast.info("Another model is already loading", {
@@ -1891,23 +1880,118 @@ export function ChatPage({
         }
         return;
       }
-      // Detach the prior staged pick (keeping its download) before rebinding, so
-      // a second pick downloads alongside the first instead of cancelling it.
-      detachStaged();
-      store.stageModel({
-        id: selection.id,
-        isLora: selection.isLora,
-        ggufVariant: selection.ggufVariant,
-        isDownloaded: selection.isDownloaded,
-        expectedBytes: selection.expectedBytes,
-        nativePathToken: selection.nativePathToken,
-        isGguf: selection.isGguf,
-        isHubRepo: wantManagerDownload || undefined,
-        autoLoad: store.loadOnSelection,
+      const wantManagerStage =
+        wantManagerDownload ||
+        (selection.source === "hub" &&
+          hasGgufSource(selection) &&
+          !selection.isDownloaded);
+      if (wantManagerStage) {
+        setPendingHubAutoLoad({
+          selection,
+          contextKey: chatContextKey,
+          originCheckpoint: store.params.checkpoint,
+          originGgufVariant: store.activeGgufVariant,
+        });
+        return;
+      }
+      setPendingHubAutoLoad(null);
+      const previousConfig = currentRuntimePerModelConfig({
+        includeMaxSeqLength: true,
+      });
+      const hasAppliedConfig = applyModelLoadConfigToRuntime(
+        selection.config ?? rememberedConfigFor(selection),
+      );
+      await selectModel({
+        ...selection,
+        ...(hasAppliedConfig ? { keepSpeculative: true } : {}),
+        previousConfig,
       });
     },
-    [detachStaged, selectModel, loadingModel],
+    [selectModel, loadingModel, rememberedConfigFor, chatContextKey],
   );
+  useRepoDownload({
+    kind: DOWNLOAD_KIND.MODEL,
+    repoId: pendingHubAutoLoad?.selection.id ?? "__hub_autoload_idle__",
+    activeVariant: pendingHubAutoLoad?.selection.ggufVariant ?? null,
+    onComplete: (variant) => {
+      const pending = pendingHubAutoLoad;
+      if (
+        !pending ||
+        (pending.selection.ggufVariant ?? null) !== (variant ?? null)
+      ) {
+        return;
+      }
+      setPendingHubAutoLoad(null);
+      const store = useChatRuntimeStore.getState();
+      if (
+        !active ||
+        pending.contextKey !== chatContextKey ||
+        normalizeModelRef(pending.originCheckpoint) !==
+          normalizeModelRef(store.params.checkpoint) ||
+        pending.originGgufVariant !== store.activeGgufVariant
+      ) {
+        return;
+      }
+      void stageOrLoad({ ...pending.selection, isDownloaded: true });
+    },
+    onError: (variant) => {
+      if (
+        pendingHubAutoLoad &&
+        (pendingHubAutoLoad.selection.ggufVariant ?? null) === (variant ?? null)
+      ) {
+        setPendingHubAutoLoad(null);
+      }
+    },
+    onCancelled: (variant) => {
+      if (
+        pendingHubAutoLoad &&
+        (pendingHubAutoLoad.selection.ggufVariant ?? null) === (variant ?? null)
+      ) {
+        setPendingHubAutoLoad(null);
+      }
+    },
+  });
+  useEffect(() => {
+    const pending = pendingHubAutoLoad;
+    if (!pending) return;
+    let active = true;
+    void (async () => {
+      const outcome = await downloadManager.requestStart({
+        kind: DOWNLOAD_KIND.MODEL,
+        repoId: pending.selection.id,
+        variant: pending.selection.ggufVariant ?? null,
+        expectedBytes: pending.selection.expectedBytes ?? 0,
+      });
+      if (!active) return;
+      if (outcome === "started") {
+        toast.info("Downloading model", {
+          description: "It'll load automatically once the download finishes.",
+        });
+        return;
+      }
+      if (outcome === "conflict") {
+        // Keep pendingHubAutoLoad bound so this surface's cleanup does not wipe
+        // the conflict just recorded by requestStart (which the toast points the
+        // user to); resolving it from the Hub completes the download and this
+        // surface's onComplete auto-loads, mirroring the "started" branch.
+        toast.info("Resume this download from the Hub", {
+          description:
+            "An earlier partial download used a different transport. Open the Hub tab to resume or restart it.",
+        });
+        return;
+      }
+      if (outcome === "busy") {
+        toast.info("Download already in progress", {
+          description:
+            "Another download for this model is still running. Reselect it once that finishes to load it.",
+        });
+      }
+      setPendingHubAutoLoad((current) => (current === pending ? null : current));
+    })();
+    return () => {
+      active = false;
+    };
+  }, [pendingHubAutoLoad]);
   const loadNativeModelIntent = useCallback(
     async (intent: NativeIntent, loadingDescription: string) => {
       const label =
@@ -1920,6 +2004,11 @@ export function ChatPage({
         forceReload: true,
         throwOnError: true,
       });
+      // Record when this file lease expires so a later reload can prompt
+      // re-selection instead of reusing a token the host has already pruned.
+      useChatRuntimeStore.setState({
+        activeNativePathExpiresAtMs: intent.path.expiresAtMs ?? null,
+      });
       useNativeIntentStore.getState().clearModelIntent(intent.id);
     },
     [stageOrLoad],
@@ -1965,28 +2054,20 @@ export function ChatPage({
   const handleCheckpointChange = useCallback(
     (
       value: string,
-      meta?: {
-        source?: string;
-        isLora: boolean;
-        ggufVariant?: string;
-        isDownloaded?: boolean;
-        expectedBytes?: number;
-        isGguf?: boolean;
-      },
+      meta?: ModelSelectorChangeMeta,
     ) => {
       const store = useChatRuntimeStore.getState();
       const currentCheckpoint = store.params.checkpoint;
       const currentVariant = store.activeGgufVariant;
-      if (
-        !value ||
-        (value === currentCheckpoint &&
-          (meta?.ggufVariant ?? null) === (currentVariant ?? null))
-      )
+      if (!value) return;
+      setPendingHubAutoLoad(null);
+      const isSameLoadedModel =
+        value === currentCheckpoint &&
+        (meta?.ggufVariant ?? null) === (currentVariant ?? null);
+      if (isSameLoadedModel && !meta?.forceReload) {
         return;
+      }
       if (meta?.source === "external" || isExternalModelId(value)) {
-        // Switching to an external model abandons any staged local pick: cancel
-        // its download too (setCheckpoint below only clears the pending + knobs).
-        abandonStaged();
         const selectedExternal = parseExternalModelId(value);
         const selectedProvider = selectedExternal
           ? externalProvidersForChat.find(
@@ -2158,19 +2239,17 @@ export function ChatPage({
           source: meta?.source,
           isLora: meta?.isLora,
           ggufVariant: meta?.ggufVariant,
-          isDownloaded: meta?.isDownloaded,
+          isDownloaded: meta?.isDownloaded || isSameLoadedModel,
           expectedBytes: meta?.expectedBytes,
           isGguf: meta?.isGguf,
+          config: meta?.config,
+          nativePathToken: meta?.nativePathToken,
+          forceReload: isSameLoadedModel || undefined,
         };
-        // "Load on selection" off: stage the model and open settings so its
-        // load knobs (tensor parallel, context length…) can be set, then it
-        // loads once via the sheet's Load button. The currently loaded model
-        // stays put until the user commits.
         await stageOrLoad(selection);
       })();
     },
     [
-      abandonStaged,
       activeThreadId,
       externalProvidersForChat,
       modelsFromStore,
@@ -2178,6 +2257,44 @@ export function ChatPage({
       view,
     ],
   );
+  const handleReloadActiveModel = useCallback(
+    (config: PerModelConfig) => {
+      const checkpoint = inferenceParams.checkpoint;
+      if (!checkpoint) return;
+      const runtime = useChatRuntimeStore.getState();
+      const nativeToken = runtime.activeNativePathToken;
+      const nativeExpiry = runtime.activeNativePathExpiresAtMs;
+      // A file-picked GGUF is reachable only via its native path token, which
+      // the desktop host prunes after a TTL. Reusing an expired token makes the
+      // reload fail with an opaque error, so prompt the user to re-select the
+      // file instead.
+      if (nativeToken && nativeExpiry != null && Date.now() >= nativeExpiry) {
+        toast.error("This local model file's access has expired.", {
+          description: "Re-select the model file to reload it.",
+        });
+        return;
+      }
+      handleCheckpointChange(checkpoint, {
+        source: "local",
+        isLora: activeModelIsLora,
+        ggufVariant: activeGgufVariant ?? undefined,
+        // Without the native token the reload validates the display label as a
+        // repo and fails.
+        nativePathToken: nativeToken ?? undefined,
+        isGguf: activeModelIsGguf,
+        isDownloaded: true,
+        config,
+        forceReload: true,
+      });
+    },
+    [
+      inferenceParams.checkpoint,
+      activeGgufVariant,
+      activeModelIsLora,
+      activeModelIsGguf,
+      handleCheckpointChange,
+    ],
+  );
   const handleEject = useCallback(() => {
     void (async () => {
       if (await ejectModel()) {
@@ -2580,6 +2697,8 @@ export function ChatPage({
                 externalModels={externalModels}
                 value={inferenceParams.checkpoint}
                 activeGgufVariant={activeGgufVariant}
+                activeModelConfig={activeModelConfig}
+                activeGgufContextLength={ggufContextLength}
                 onValueChange={handleCheckpointChange}
                 onEject={handleEject}
                 onFoldersChange={refreshLocalModels}
@@ -2633,7 +2752,12 @@ export function ChatPage({
               <NativeModelChip
                 intent={pendingNativeModelIntent}
                 nativeReadsDisabled={!nativePathLeasesSupported}
-                onLoad={(selection) => stageOrLoad(selection)}
+                onLoad={() =>
+                  loadNativeModelIntent(
+                    pendingNativeModelIntent,
+                    "Loading selected local GGUF model.",
+                  )
+                }
               />
             ) : null}
             {loadingModel && loadToastDismissed ? (
@@ -2790,13 +2914,22 @@ export function ChatPage({
         open={active && settingsOpen}
         onOpenChange={(open) => {
           setSettingsOpen(open);
-          // Closing the sheet abandons a staged (not-yet-loaded) pick: cancel its
-          // download and revert the staged knobs so nothing lingers as a dirty
-          // edit (or a background download) on the loaded model.
-          if (!open) abandonStaged();
         }}
         params={inferenceParams}
         onParamsChange={setInferenceParams}
+        modelConfig={
+          view.mode !== "compare" && activeModelConfig && !modelLoading ? (
+            <SidebarModelConfig
+              modelId={inferenceParams.checkpoint}
+              ggufVariant={activeGgufVariant ?? null}
+              isGguf={activeModelIsGguf}
+              nativeContextLength={ggufNativeContextLength}
+              loadedContextLength={ggufContextLength}
+              loadedConfig={activeModelConfig}
+              onReload={handleReloadActiveModel}
+            />
+          ) : null
+        }
         isExternalModel={isExternalModel}
         providerCapabilities={activeProviderCapabilities}
         activeExternalProvider={activeExternalProvider}
@@ -2808,62 +2941,6 @@ export function ChatPage({
           );
         }}
         externalProviderType={activeExternalProviderType}
-        loadingModel={loadingModel}
-        onReloadModel={() => {
-          const state = useChatRuntimeStore.getState();
-          if (state.params.checkpoint) {
-            selectModel({
-              id: state.params.checkpoint,
-              ggufVariant: state.activeGgufVariant ?? undefined,
-              forceReload: true,
-              isDownloaded: true,
-              loadingDescription: "Reloading with updated chat template.",
-            });
-          }
-        }}
-        onLoadPendingModel={() => {
-          const pending = useChatRuntimeStore.getState().pendingSelection;
-          if (!pending) return;
-          const keyAtLoad = chatContextKey;
-          // forceReload: the staged model isn't loaded yet, so bypass the
-          // same-checkpoint dedupe. keepSpeculative: honor the speculative mode
-          // set on the sidebar.
-          void selectModel({
-            ...pending,
-            forceReload: true,
-            keepSpeculative: true,
-            throwOnError: true,
-          }).catch(() => {
-            // Recoverable failure (expired token, gated repo, OOM…): the pick is
-            // cleared only on success, so it normally stays staged with edited
-            // knobs intact — nothing to restore.
-            const store = useChatRuntimeStore.getState();
-            // Still staged (this pick, or a newer one queued meanwhile): leave it.
-            if (store.pendingSelection) return;
-            // Cleared mid-load (sheet closed / switched chats). Re-stage only if
-            // the staged-load is still wanted: same chat context, sheet still
-            // open, page still mounted.
-            const stillWanted =
-              mountedRef.current &&
-              store.settingsPanelOpen &&
-              chatContextKeyRef.current === keyAtLoad;
-            if (stillWanted) {
-              store.setPendingSelection(pending);
-            } else {
-              // Abandoned (closed the sheet / switched chats / left chat): drop
-              // the orphaned staged knob edits so they don't linger as dirty
-              // settings over the loaded model.
-              store.resetModelSettingsToLoaded();
-            }
-          });
-        }}
-        stagedDownloadFraction={stagedDownload.progress?.fraction ?? null}
-        onCancelStagedDownload={() =>
-          stagedDownload.cancelDownload(
-            useChatRuntimeStore.getState().pendingSelection?.ggufVariant ??
-              null,
-          )
-        }
       />
     </div>
     </ChatActiveContext.Provider>
diff --git a/studio/frontend/src/features/chat/chat-settings-sheet.tsx b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
index cedd298ecf..a5768024b5 100644
--- a/studio/frontend/src/features/chat/chat-settings-sheet.tsx
+++ b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
@@ -1,19 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import {
-  Alert,
-  AlertDescription,
-  AlertTitle,
-} from "@/components/ui/alert";
 import { Button } from "@/components/ui/button";
-import { Checkbox } from "@/components/ui/checkbox";
-import {
-  clearRememberedLoadSettings,
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-  saveRememberedLoadSettings,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
 import {
   Dialog,
   DialogContent,
@@ -29,7 +17,7 @@ import {
   DropdownMenuSeparator,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
-import { Input } from "@/components/ui/input";
+import { InfoHint } from "@/components/ui/info-hint";
 import {
   InputGroup,
   InputGroupAddon,
@@ -50,26 +38,22 @@ import {
   SheetTitle,
 } from "@/components/ui/sheet";
 import { Slider } from "@/components/ui/slider";
-import { Spinner } from "@/components/ui/spinner";
 import { Switch } from "@/components/ui/switch";
 import { Textarea } from "@/components/ui/textarea";
-import { InfoHint } from "@/components/ui/info-hint";
 import { Tooltip, TooltipContent } from "@/components/ui/tooltip";
-import { useIsMobile } from "@/hooks/use-mobile";
+import { NumericValueInput, snapToStep } from "@/features/model-picker";
+import { RetrievalSettingsSection } from "@/features/rag";
 import { useLlamaUpdateCheck } from "@/hooks/use-llama-update-check";
-import { cn } from "@/lib/utils";
-import {
-  ArrowTurnBackwardIcon,
-  Edit03Icon,
-  LayoutAlignRightIcon,
-} from "@hugeicons/core-free-icons";
+import { useIsMobile } from "@/hooks/use-mobile";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { toast } from "@/lib/toast";
+import { cn } from "@/lib/utils";
+import { Edit03Icon, LayoutAlignRightIcon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { Braces, ChevronDown, ExternalLink } from "lucide-react";
 import { Tooltip as TooltipPrimitive } from "radix-ui";
 import { Fragment, type ReactNode } from "react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "@/lib/toast";
 import { OpenAICodeExecSection } from "./components/openai-code-exec-section";
 import { PermissionModeDropdown } from "./permission-mode-select";
 import { resyncInferenceStatusAfterServerModelChange } from "./hooks/use-chat-model-runtime";
@@ -77,8 +61,8 @@ import {
   type ExternalProviderConfig,
   getExternalProviderApiKey,
   parseExternalModelId,
-  supportsProviderPromptCaching,
   supportsProviderPromptCacheTtl,
+  supportsProviderPromptCaching,
 } from "./external-providers";
 import {
   BUILTIN_PRESETS,
@@ -98,12 +82,7 @@ import {
   providerSupportsBuiltinCodeExecution,
   providerSupportsFastMode,
 } from "./provider-capabilities";
-import {
-  isPendingGguf,
-  pendingSelectionMatches,
-  useChatRuntimeStore,
-} from "./stores/chat-runtime-store";
-import { RetrievalSettingsSection } from "@/features/rag/components/retrieval-settings-section";
+import { useChatRuntimeStore } from "./stores/chat-runtime-store";
 import type { InferenceParams } from "./types/runtime";
 
 export { defaultInferenceParams, type Preset } from "./presets/preset-policy";
@@ -126,7 +105,7 @@ function getPromptVariablesError(raw: string): string | null {
       return null;
     }
   } catch {
-    return "Use valid JSON, for example { \"env\": \"staging\" }.";
+    return 'Use valid JSON, for example { "env": "staging" }.';
   }
   return "Variables must be a JSON object.";
 }
@@ -135,111 +114,6 @@ function hasPromptVariableSyntax(prompt: string): boolean {
   return PROMPT_VARIABLE_PATTERN.test(prompt);
 }
 
-/**
- * Editable numeric value display, shared by every slider value and the Context
- * Length input. An <input> that looks like text (shows `displayValue ?? value`,
- * so "Off"/"Max" labels render) until focus, when it swaps to the raw number,
- * selects it, and accepts free text. Commits on blur/Enter, reverts on Escape.
- * Clamping happens on commit so typing intermediate values isn't fought.
- */
-function snapToStep(
-  value: number,
-  step: number,
-  min?: number,
-  max?: number,
-): number {
-  const lo = min ?? Number.NEGATIVE_INFINITY;
-  const hi = max ?? Number.POSITIVE_INFINITY;
-  const clamped = Math.min(Math.max(value, lo), hi);
-  const stepStr = String(step);
-  const decimals = stepStr.includes(".") ? stepStr.split(".")[1].length : 0;
-  const base = Number.isFinite(lo) ? lo : 0;
-  const snapped = base + Math.round((clamped - base) / step) * step;
-  const reclamped = Math.min(Math.max(snapped, lo), hi);
-  return Number(reclamped.toFixed(decimals));
-}
-
-function NumericValueInput({
-  value,
-  min,
-  max,
-  step,
-  onChange,
-  displayValue,
-  className,
-  ariaLabel,
-  size: sizeAttr,
-  disabled = false,
-}: {
-  value: number;
-  min?: number;
-  max?: number;
-  step: number;
-  onChange: (v: number) => void;
-  displayValue?: string;
-  className?: string;
-  ariaLabel?: string;
-  size?: number;
-  disabled?: boolean;
-}) {
-  const [focused, setFocused] = useState(false);
-  const [draft, setDraft] = useState("");
-  const cancelBlurCommitRef = useRef(false);
-
-  const commit = (raw: string) => {
-    const parsed = Number.parseFloat(raw);
-    if (!Number.isFinite(parsed)) {
-      return;
-    }
-    const final = snapToStep(parsed, step, min, max);
-    if (final !== value) {
-      onChange(final);
-    }
-  };
-
-  const displayed = focused ? draft : (displayValue ?? String(value));
-
-  return (
-    <input
-      type="text"
-      inputMode="decimal"
-      disabled={disabled}
-      size={sizeAttr}
-      /* Fixed 4ch pill; grows only when a longer value would clip. */
-      style={{ width: `calc(${Math.max(displayed.length, 4)}ch + 18px)` }}
-      value={displayed}
-      aria-label={ariaLabel}
-      onFocus={(e) => {
-        cancelBlurCommitRef.current = false;
-        setDraft(String(value));
-        setFocused(true);
-        // Defer select() so it runs after the value swap above.
-        const target = e.currentTarget;
-        requestAnimationFrame(() => target.select());
-      }}
-      onBlur={() => {
-        if (cancelBlurCommitRef.current) {
-          cancelBlurCommitRef.current = false;
-        } else {
-          commit(draft);
-        }
-        setFocused(false);
-      }}
-      onChange={(e) => setDraft(e.target.value)}
-      onKeyDown={(e) => {
-        if (e.key === "Enter") {
-          e.currentTarget.blur();
-        } else if (e.key === "Escape") {
-          cancelBlurCommitRef.current = true;
-          setDraft(String(value));
-          e.currentTarget.blur();
-        }
-      }}
-      className={cn("panel-number-input", className)}
-    />
-  );
-}
-
 function ParamSlider({
   label,
   value,
@@ -279,6 +153,7 @@ function ParamSlider({
           displayValue={displayValue}
           ariaLabel={label}
           size={valueSize ?? 4}
+          className="panel-number-input"
         />
       </div>
       <Slider
@@ -377,8 +252,7 @@ function CollapsibleSection({
   return (
     <div
       className={cn(
-        !first &&
-          "border-t border-black/[0.13] dark:border-white/[0.09]",
+        !first && "border-t border-black/[0.13] dark:border-white/[0.09]",
       )}
     >
       {labelHref ? (
@@ -450,6 +324,7 @@ interface ChatSettingsPanelProps {
   onOpenChange?: (open: boolean) => void;
   params: InferenceParams;
   onParamsChange: (params: InferenceParams) => void;
+  modelConfig?: ReactNode;
   isExternalModel?: boolean;
   /**
    * Sampling-param capabilities for the active external provider, or `null` for
@@ -464,21 +339,6 @@ interface ChatSettingsPanelProps {
    * Max Tokens floor in the slider.
    */
   externalProviderType?: string | null;
-  onReloadModel?: () => void;
-  /** The in-flight load (id + GGUF variant + native path token), or null when
-   *  idle. Used to show a loading state for the staged pick only — not for an
-   *  unrelated load or a cancel's background unload. */
-  loadingModel?: {
-    id: string;
-    ggufVariant?: string | null;
-    nativePathToken?: string | null;
-  } | null;
-  /** Loads the staged `pendingSelection` (deferred "Load on selection" flow). */
-  onLoadPendingModel?: () => void;
-  /** Download progress (0–1) for a staged GGUF being fetched, or null when idle. */
-  stagedDownloadFraction?: number | null;
-  /** Cancels the in-flight staged download (paired with abandoning the stage). */
-  onCancelStagedDownload?: () => void;
 }
 
 export function ChatSettingsPanel({
@@ -486,16 +346,12 @@ export function ChatSettingsPanel({
   onOpenChange,
   params,
   onParamsChange,
+  modelConfig = null,
   isExternalModel = false,
   providerCapabilities = null,
   activeExternalProvider = null,
   onExternalProviderChange,
   externalProviderType = null,
-  onReloadModel,
-  loadingModel = null,
-  onLoadPendingModel,
-  stagedDownloadFraction,
-  onCancelStagedDownload,
 }: ChatSettingsPanelProps) {
   // Local models show every knob; providerCapabilities is only consulted when
   // isExternalModel. Unknown providers fall back to the OpenAI-compat shape via
@@ -510,55 +366,23 @@ export function ChatSettingsPanel({
   const showPresencePenalty =
     !isExternalModel || Boolean(providerCapabilities?.presencePenalty);
   const isMobile = useIsMobile();
-  const pendingSelection = useChatRuntimeStore((s) => s.pendingSelection);
-  // "Loading" only when the in-flight load IS this staged pick (full id + GGUF
-  // variant + native token match), not an unrelated load or a cancel's
-  // background unload. The variant matters: a different quant of the same repo
-  // staged mid-load must not read as this one loading.
-  const stagedLoading =
-    loadingModel != null &&
-    pendingSelectionMatches(pendingSelection, {
-      id: loadingModel.id,
-      ggufVariant: loadingModel.ggufVariant,
-      nativePathToken: loadingModel.nativePathToken,
-    });
-  // Load settings are snapshotted at click time; lock them while loading.
-  const modelControlsDisabled = stagedLoading;
-  const abandonStagedModel = useChatRuntimeStore((s) => s.abandonStagedModel);
-  const resetModelSettingsToLoaded = useChatRuntimeStore(
-    (s) => s.resetModelSettingsToLoaded,
+  const isLoadedGguf = useChatRuntimeStore((s) => s.activeGgufVariant) != null;
+  const currentCheckpoint = params.checkpoint;
+  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
+  // Direct-file / custom-folder GGUFs load without a variant label but still
+  // report a GGUF context, so detect them via the context and the checkpoint
+  // suffix too (mirrors the chat page's activeModelIsGguf). Otherwise Max Tokens
+  // would fall back to params.maxSeqLength instead of the loaded GGUF context.
+  const isGguf =
+    isLoadedGguf ||
+    ggufContextLength != null ||
+    (currentCheckpoint?.toLowerCase().endsWith(".gguf") ?? false);
+  const ggufMaxContextLength = useChatRuntimeStore(
+    (s) => s.ggufMaxContextLength,
   );
-  // A staged GGUF pick (deferred load) shows the GGUF load knobs so they can be
-  // set before the single load.
-  const pendingIsGguf = isPendingGguf(pendingSelection);
-  // Short, human-readable name for the staged pick (HF ids carry an org prefix;
-  // native picks are already a display label). Drives the "staged, not loaded"
-  // callout so it's obvious the selection hasn't loaded yet.
-  const stagedLabel = (() => {
-    const id = pendingSelection?.id ?? "";
-    const slash = id.lastIndexOf("/");
-    const base = slash >= 0 ? id.slice(slash + 1) : id;
-    return base || id;
-  })();
-  const isLoadedGguf =
-    useChatRuntimeStore((s) => s.activeGgufVariant) != null;
-  // While a pick is staged the sheet configures *that* model, so its GGUF-ness
-  // (not the currently loaded model's) decides whether the GGUF-only controls
-  // show. Otherwise a staged non-GGUF Hub repo would inherit the loaded GGUF's
-  // context/KV/speculative controls.
-  const isGguf = pendingSelection != null ? pendingIsGguf : isLoadedGguf;
-  // The Model section (and Load button) shows for any staged pick, even when the
-  // currently active model is external.
-  const hasModelContent =
-    pendingSelection != null ||
-    (!isExternalModel && (isGguf || Boolean(params.checkpoint)));
+  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
   const speculativeType = useChatRuntimeStore((s) => s.speculativeType);
-  const setSpeculativeType = useChatRuntimeStore((s) => s.setSpeculativeType);
-  const loadedSpeculativeType = useChatRuntimeStore(
-    (s) => s.loadedSpeculativeType,
-  );
   const specFallbackReason = useChatRuntimeStore((s) => s.specFallbackReason);
-  // Only binary fallback states are solved by a newer prebuilt.
   const mtpUpdatable =
     specFallbackReason === "binary_no_mtp" ||
     specFallbackReason === "binary_outdated";
@@ -580,43 +404,27 @@ export function ChatSettingsPanel({
         `llama.cpp updated to ${result.tag ?? "the latest build"}.${reloadHint}`,
       );
     } else {
-      toast.error(`llama.cpp update failed: ${result.error ?? "unknown error"}`);
+      toast.error(
+        `llama.cpp update failed: ${result.error ?? "unknown error"}`,
+      );
     }
   }, [applyLlamaUpdate]);
-  const specDraftNMax = useChatRuntimeStore((s) => s.specDraftNMax);
-  const setSpecDraftNMax = useChatRuntimeStore((s) => s.setSpecDraftNMax);
-  const loadedSpecDraftNMax = useChatRuntimeStore(
-    (s) => s.loadedSpecDraftNMax,
-  );
-  const currentCheckpoint = params.checkpoint;
-  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
-  const ggufMaxContextLength = useChatRuntimeStore(
-    (s) => s.ggufMaxContextLength,
-  );
-  const ggufNativeContextLength = useChatRuntimeStore(
-    (s) => s.ggufNativeContextLength,
-  );
-  const kvCacheDtype = useChatRuntimeStore((s) => s.kvCacheDtype);
-  const setKvCacheDtype = useChatRuntimeStore((s) => s.setKvCacheDtype);
-  const applyRememberedLoadSettings = useChatRuntimeStore(
-    (s) => s.applyRememberedLoadSettings,
-  );
-  const loadedKvCacheDtype = useChatRuntimeStore((s) => s.loadedKvCacheDtype);
-  const tensorParallel = useChatRuntimeStore((s) => s.tensorParallel);
-  const setTensorParallel = useChatRuntimeStore((s) => s.setTensorParallel);
-  const loadedTensorParallel = useChatRuntimeStore(
-    (s) => s.loadedTensorParallel,
-  );
-  const chatTemplateOverride = useChatRuntimeStore(
-    (s) => s.chatTemplateOverride,
-  );
-  const loadedChatTemplateOverride = useChatRuntimeStore(
-    (s) => s.loadedChatTemplateOverride,
-  );
-  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
-  const setCustomContextLength = useChatRuntimeStore(
-    (s) => s.setCustomContextLength,
-  );
+  const loadedEffectiveContext = customContextLength ?? ggufContextLength;
+  const showSpecFallback =
+    !isExternalModel &&
+    isLoadedGguf &&
+    specFallbackReason != null &&
+    (speculativeType === "auto" ||
+      speculativeType === "mtp" ||
+      speculativeType === "mtp+ngram");
+  const showContextVramWarning =
+    !isExternalModel &&
+    isLoadedGguf &&
+    ggufMaxContextLength != null &&
+    loadedEffectiveContext != null &&
+    loadedEffectiveContext > ggufMaxContextLength;
+  const showLoadedDiagnostics = showSpecFallback || showContextVramWarning;
+  const hasModelContent = showLoadedDiagnostics;
   const setActivePresetSource = useChatRuntimeStore(
     (s) => s.setActivePresetSource,
   );
@@ -627,49 +435,7 @@ export function ChatSettingsPanel({
   const setActivePreset = useChatRuntimeStore((s) => s.setActivePreset);
   const settingsHydrated = useChatRuntimeStore((s) => s.settingsHydrated);
 
-  // A staged (not-yet-loaded) GGUF carries its own header context length on
-  // pendingSelection, so the slider can use the staged model's real ceiling
-  // without reading the loaded model's `ggufContextLength`.
-  const stagedContextLength = pendingSelection?.contextLength ?? null;
-  // "Remember settings next time" tick for a staged model. Seeds the store from
-  // the saved per-model settings on stage, so the sheet opens with what was used
-  // last time; the tick reflects whether a saved entry exists.
-  const [remember, setRemember] = useState(false);
-  // Keyed per quant: a different variant of the same repo has its own settings.
-  const pendingKey = pendingSelection
-    ? rememberedLoadSettingsKey(pendingSelection)
-    : null;
-  useEffect(() => {
-    if (!pendingKey) return;
-    const saved = loadRememberedLoadSettings(pendingKey);
-    setRemember(saved != null);
-    if (saved) applyRememberedLoadSettings(saved);
-  }, [pendingKey, applyRememberedLoadSettings]);
-  // While staging, the sheet reflects the STAGED model, so its header context
-  // takes precedence over the loaded model's (which may differ or be larger).
-  const baseContext = pendingIsGguf ? stagedContextLength : ggufContextLength;
-  const baseNativeContext = pendingIsGguf
-    ? stagedContextLength
-    : ggufNativeContextLength;
-  // Context controls render once we actually have a ceiling: for a staged GGUF,
-  // once its header metadata arrives (post-download); otherwise post-load.
-  const showContextControl = pendingIsGguf
-    ? stagedContextLength != null
-    : isLoadedGguf;
-  const stagedDownloading =
-    stagedDownloadFraction != null && stagedDownloadFraction < 1;
-  const ctxDisplayValue = customContextLength ?? baseContext ?? "";
-  const ctxMaxValue = baseNativeContext ?? baseContext ?? null;
-  const kvDirty = kvCacheDtype !== loadedKvCacheDtype;
-  const ctxDirty = customContextLength !== null;
-  const specDirty = speculativeType !== loadedSpeculativeType;
-  const specDraftDirty = specDraftNMax !== loadedSpecDraftNMax;
-  const tpDirty = tensorParallel !== (loadedTensorParallel ?? false);
-  // A saved chat-template override is a reload-time setting too, so surface
-  // Apply for a template-only edit (otherwise it could never be applied).
-  const templateDirty = chatTemplateOverride !== loadedChatTemplateOverride;
-  const modelSettingsDirty =
-    kvDirty || ctxDirty || specDirty || specDraftDirty || tpDirty || templateDirty;
+  const baseContext = ggufContextLength;
   const [presetNameInput, setPresetNameInput] = useState(activePreset);
   const [systemPromptEditorOpen, setSystemPromptEditorOpen] = useState(false);
   const [systemPromptDraft, setSystemPromptDraft] = useState("");
@@ -695,8 +461,7 @@ export function ChatSettingsPanel({
       BUILTIN_PRESETS.find((preset) => preset.name === activePreset) ?? null,
     [activePreset],
   );
-  const hasUnsavedPresetChanges = useMemo(
-    () => {
+  const hasUnsavedPresetChanges = useMemo(() => {
       if (activePresetDefinition == null) {
         return false;
       }
@@ -704,9 +469,7 @@ export function ChatSettingsPanel({
         return activePresetSource === "modified";
       }
       return !isSamePresetConfig(activePresetDefinition.params, params);
-    },
-    [activePresetDefinition, activePresetSource, params],
-  );
+  }, [activePresetDefinition, activePresetSource, params]);
   const presetSaveState = useMemo(
     () =>
       getPresetSaveState({
@@ -735,6 +498,14 @@ export function ChatSettingsPanel({
   const externalSelection = currentCheckpoint
     ? parseExternalModelId(currentCheckpoint)
     : null;
+  const maxTokensMax = isExternalModel
+      ? getExternalMaxOutputTokens(
+          externalProviderType,
+          externalSelection?.modelId,
+        )
+      : isGguf && baseContext
+        ? baseContext
+        : Math.max(64, params.maxSeqLength);
   const showOpenAICodeExecSection =
     activeExternalProvider != null &&
     providerSupportsBuiltinCodeExecution(
@@ -817,8 +588,7 @@ export function ChatSettingsPanel({
       return;
     }
     const fallbackPreset =
-      BUILTIN_PRESETS.find((preset) => preset.name === "Default") ??
-      null;
+      BUILTIN_PRESETS.find((preset) => preset.name === "Default") ?? null;
     const next = customPresets.filter((preset) => preset.name !== name);
     setCustomPresets(next);
     if (activePreset === name) {
@@ -930,7 +700,7 @@ export function ChatSettingsPanel({
               Run settings
             </span>
             <Tooltip>
-              <TooltipPrimitive.Trigger asChild>
+                <TooltipPrimitive.Trigger asChild={true}>
                 <button
                   type="button"
                   onClick={() => onOpenChange?.(false)}
@@ -961,377 +731,57 @@ export function ChatSettingsPanel({
         className="run-settings-scroll relative min-h-0 flex-1 overflow-y-auto"
       >
       <div className="px-[18px] pt-3">
-        {hasModelContent && (
-        <CollapsibleSection label="Model" defaultOpen={true} first>
-          <div className="flex flex-col gap-4 pt-1">
-            {pendingSelection && (
-              <Alert className="rounded-[14px] border-primary/30 bg-primary/5 px-3 py-2">
-                <AlertTitle className="text-[12px] font-medium">
-                  {stagedLoading
-                    ? `Loading ${stagedLabel}…`
-                    : `${stagedLabel} is staged, not loaded yet`}
-                </AlertTitle>
-                <AlertDescription className="text-[11.5px] leading-[1.45] text-muted-foreground">
-                  {stagedLoading
-                    ? "Applying your settings."
-                    : "Set the options below, then choose Load model to load it."}
-                </AlertDescription>
-              </Alert>
-            )}
-            {isGguf && (
-              <>
-                {showContextControl && (
-                <div className="space-y-3.5">
-                  <div className="flex items-center justify-between gap-3">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      Context Length
-                    </span>
-                    <NumericValueInput
-                      value={
-                        typeof ctxDisplayValue === "number"
-                          ? ctxDisplayValue
-                          : (baseContext ?? 0)
-                      }
-                      min={128}
-                      max={ctxMaxValue ?? undefined}
-                      step={1}
-                      onChange={(v) => {
-                        setCustomContextLength(
-                          v === (baseContext ?? 0) ? null : v,
-                        );
-                      }}
-                      ariaLabel="Context Length"
-                      size={8}
-                      disabled={modelControlsDisabled}
-                    />
-                  </div>
-                  <Slider
-                    min={1024}
-                    max={ctxMaxValue ?? 4096}
-                    step={1024}
-                    value={[
-                      Math.min(
-                        typeof ctxDisplayValue === "number"
-                          ? ctxDisplayValue
-                          : (baseContext ?? 4096),
-                        ctxMaxValue ?? 4096,
-                      ),
-                    ]}
-                    onValueChange={([v]) => {
-                      const snapped = Math.round(v);
-                      setCustomContextLength(
-                        snapped === (baseContext ?? 0) ? null : snapped,
-                      );
-                    }}
-                    className="panel-slider"
-                    disabled={modelControlsDisabled}
-                  />
-                  {ggufMaxContextLength != null &&
-                    typeof ctxDisplayValue === "number" &&
-                    ctxDisplayValue > ggufMaxContextLength && (
-                      <p className="text-[11px] text-amber-500">
-                        Exceeds estimated VRAM capacity (
-                        {ggufMaxContextLength.toLocaleString()} tokens). The
-                        model may use system RAM.
-                      </p>
-                    )}
-                </div>
-                )}
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      KV Cache Dtype
-                    </span>
-                    <InfoHint>
-                      Lower KV cache precision to save VRAM at the cost of some
-                      quality. f16/bf16 are full precision; q8_0/q5_1/q4_1 are
-                      quantized.
-                    </InfoHint>
-                  </div>
-                  <div className="flex shrink-0 items-center gap-1.5">
-                    <Select
-                      disabled={modelControlsDisabled}
-                      value={kvCacheDtype ?? "f16"}
-                      onValueChange={(v) => {
-                        setKvCacheDtype(v === "f16" ? null : v);
-                      }}
-                    >
-                      <SelectTrigger
-                        animateRadius={false}
-                        icon={ChevronDownStandardIcon}
-                        iconClassName="size-3.5"
-                        className="grid h-7 w-[64px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
-                      >
-                        <SelectValue />
-                      </SelectTrigger>
-                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-                        <SelectItem value="f16">f16</SelectItem>
-                        <SelectItem value="bf16">bf16</SelectItem>
-                        <SelectItem value="q8_0">q8_0</SelectItem>
-                        <SelectItem value="q5_1">q5_1</SelectItem>
-                        <SelectItem value="q4_1">q4_1</SelectItem>
-                      </SelectContent>
-                    </Select>
-                  </div>
-                </div>
-                {isGguf && (
-                  <>
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      Speculative Decoding
-                    </span>
-                    <InfoHint>
-                      Faster generation with 0% accuracy hit. Auto picks
-                      MTP / ngram-mod based on the model and platform.
-                      Pick MTP, Ngram, or MTP+Ngram to force a specific
-                      strategy on both GPU and CPU.
-                    </InfoHint>
-                  </div>
-                  <div className="flex shrink-0 items-center gap-1.5">
-                    <Select
-                      disabled={modelControlsDisabled}
-                      value={speculativeType ?? "auto"}
-                      onValueChange={(v) => {
-                        setSpeculativeType(v);
-                        if (v !== "mtp" && v !== "mtp+ngram") {
-                          setSpecDraftNMax(null);
-                        }
-                      }}
-                    >
-                      <SelectTrigger
-                        animateRadius={false}
-                        icon={ChevronDownStandardIcon}
-                        iconClassName="size-3.5"
-                        className="grid h-7 w-[124px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
-                        data-test-id="speculative-type-select"
-                      >
-                        <SelectValue />
-                      </SelectTrigger>
-                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-                        <SelectItem value="auto">Auto</SelectItem>
-                        <SelectItem value="mtp">MTP</SelectItem>
-                        <SelectItem value="ngram">Ngram</SelectItem>
-                        <SelectItem value="mtp+ngram">MTP+Ngram</SelectItem>
-                        <SelectItem value="off">Off</SelectItem>
-                      </SelectContent>
-                    </Select>
-                  </div>
-                </div>
-                {specFallbackReason &&
-                  (speculativeType === "auto" ||
-                    speculativeType === "mtp" ||
-                    speculativeType === "mtp+ngram") && (
-                    <div className="rounded-lg bg-amber-500/[0.08] px-3 py-2 text-[12px] leading-[1.4] text-nav-fg/80">
-                      <p>
-                        {specFallbackReason === "mla_mtp_disabled"
-                          ? "MTP is disabled by default for this model architecture because it currently runs slower than standard decoding. Select MTP above to force it."
-                          : specFallbackReason === "runtime_error"
-                          ? "MTP could not start for this model on the installed llama.cpp build, so it is running without speculative decoding."
-                          : specFallbackReason === "drafter_not_found"
-                            ? "This model supports MTP, but its drafter file could not be downloaded, so MTP is off and it falls back to n-gram speculative decoding where the llama.cpp build supports it. Check your network connection or Hugging Face access, then reload the model to retry the drafter."
-                            : "MTP is not available in the installed llama.cpp build, so this model is running without it." +
-                              (llamaUpdateStatus?.update_available
+        {(hasModelContent || modelConfig) && (
+              <CollapsibleSection label="Model" defaultOpen={true} first={true}>
+            <div className="flex flex-col gap-3 pt-1">
+              {modelConfig}
+              {showSpecFallback && (
+                <div className="rounded-lg bg-amber-500/[0.08] px-3 py-2 text-[12px] leading-[1.4] text-nav-fg/80">
+                  <p>
+                    {specFallbackReason === "mla_mtp_disabled"
+                      ? "MTP is disabled by default for this model architecture because it currently runs slower than standard decoding. Choose MTP in the model picker to force it."
+                      : specFallbackReason === "runtime_error"
+                        ? "MTP could not start for this model on the installed llama.cpp build, so it is running without speculative decoding."
+                        : specFallbackReason === "drafter_not_found"
+                          ? "This model supports MTP, but its drafter file could not be downloaded, so MTP is off and it falls back to n-gram speculative decoding where the llama.cpp build supports it. Check your network connection or Hugging Face access, then reload the model to retry the drafter."
+                          : `MTP is not available in the installed llama.cpp build, so this model is running without it.${
+                              llamaUpdateStatus?.update_available
                                 ? " Update llama.cpp to enable it."
-                                : "")}
-                      </p>
-                      {mtpUpdatable && llamaUpdateStatus?.update_available && (
-                        <Button
-                          size="sm"
-                          className="corner-squircle mt-2 h-7 text-[12px]"
-                          onClick={handleMtpUpdate}
-                          disabled={llamaUpdating}
-                          data-test-id="mtp-update-button"
-                        >
-                          {llamaUpdating ? "Updating..." : "Update llama.cpp"}
-                        </Button>
-                      )}
-                    </div>
-                  )}
-                {(speculativeType === "mtp" ||
-                  speculativeType === "mtp+ngram") && (
-                  <div className="flex items-center justify-between gap-3">
-                    <div className="flex min-w-0 items-center gap-1.5">
-                      <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                        Draft Tokens
-                      </span>
-                      <InfoHint>
-                        Max MTP draft tokens per step
-                        (--spec-draft-n-max). Lower = less wasted
-                        draft decode; higher = bigger speedup when
-                        acceptance stays high. Default: 2 on GPU,
-                        3 on CPU/Mac.
-                      </InfoHint>
-                    </div>
-                    <Input
-                      type="number"
-                      disabled={modelControlsDisabled}
-                      min={1}
-                      max={16}
-                      step={1}
-                      value={specDraftNMax ?? ""}
-                      placeholder="auto"
-                      onChange={(e) => {
-                        const raw = e.target.value;
-                        if (raw === "") {
-                          setSpecDraftNMax(null);
-                          return;
-                        }
-                        const parsed = Number.parseInt(raw, 10);
-                        if (Number.isFinite(parsed)) {
-                          const clamped = Math.max(1, Math.min(16, parsed));
-                          setSpecDraftNMax(clamped);
-                        }
-                      }}
-                      data-test-id="spec-draft-n-max-input"
-                      aria-label="Speculative decoding draft tokens"
-                      className="h-7 w-[88px] rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 py-0 text-[13px] font-medium text-nav-fg outline-none focus-visible:ring-0"
-                    />
-                  </div>
-                )}
-                  </>
-                )}
-                <div className="flex items-center justify-between gap-3">
-                  <div className="flex min-w-0 items-center gap-1.5">
-                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
-                      Tensor Parallelism
-                    </span>
-                    <InfoHint>
-                      No effect on a single GPU. On multi-GPU setups, improves
-                      tokens/sec during generation when using dense models. MoE
-                      models don't benefit and can be much slower.
-                    </InfoHint>
-                  </div>
-                  <Switch
-                    className="panel-switch shrink-0"
-                    checked={tensorParallel}
-                    onCheckedChange={setTensorParallel}
-                    disabled={modelControlsDisabled}
-                    data-test-id="tensor-parallel-switch"
-                  />
-                </div>
-              </>
-            )}
-            {/* No persistent "enable custom code" toggle: it is consented per model
-                via the load-time review dialog. */}
-            {/* Apply/Reset belongs to the model-reload settings above (context
-                length, KV cache, speculative decoding). Render it here, before
-                the Chat Template row, so it never reads as attached to Chat
-                Template (which is edited via its own dialog). When a model is
-                staged (deferred load), Load/Cancel takes its place: there's
-                nothing loaded to "apply" against yet. */}
-            {pendingSelection ? (
-              <div className="flex flex-col gap-4">
-                {stagedDownloading && (
-                  <p className="text-[11px] text-muted-foreground">
-                    Downloading…{" "}
-                    {Math.round((stagedDownloadFraction ?? 0) * 100)}%
+                                : ""
+                            }`}
                   </p>
-                )}
-                <label className="flex cursor-pointer items-center gap-2 pb-1.5 text-[12px] text-muted-foreground">
-                  <Checkbox
-                    className="size-3.5 rounded-full [&_[data-slot=checkbox-indicator]_svg]:size-2.5"
-                    checked={remember}
-                    onCheckedChange={(v) => setRemember(v === true)}
-                  />
-                  Remember settings next time
-                </label>
-                {stagedLoading ? (
-                  // Mid-load: nothing to load or abandon until it settles, so disable.
-                  <Button
-                    type="button"
-                    disabled
-                    size="sm"
-                    className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav bg-primary text-primary-foreground hover:bg-primary/90"
-                  >
-                    <Spinner className="size-3.5" />
-                    Loading…
-                  </Button>
-                ) : (
-                  <div className="grid grid-cols-2 gap-3">
+                  {mtpUpdatable && llamaUpdateStatus?.update_available && (
                     <Button
-                      type="button"
-                      onClick={() => {
-                        // Persist (or clear) this model's load knobs before loading.
-                        // Context is stored as the override (null = auto), never the
-                        // resolved native value, so restoring can't force an OOM.
-                        const pid = pendingSelection
-                          ? rememberedLoadSettingsKey(pendingSelection)
-                          : null;
-                        if (pid) {
-                          if (remember) {
-                            saveRememberedLoadSettings(pid, {
-                              contextLength: customContextLength,
-                              kvCacheDtype,
-                              speculativeType,
-                              specDraftNMax,
-                              tensorParallel,
-                            });
-                          } else {
-                            clearRememberedLoadSettings(pid);
-                          }
-                        }
-                        onLoadPendingModel?.();
-                      }}
-                      // Disabled while a different model is mid-load: selectModel
-                      // refuses a concurrent load, so the click could only toast.
-                      disabled={stagedDownloading || loadingModel != null}
                       size="sm"
-                      className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav bg-primary text-primary-foreground hover:bg-primary/90"
+                      className="corner-squircle mt-2 h-7 text-[12px]"
+                      onClick={handleMtpUpdate}
+                      disabled={llamaUpdating}
+                      data-test-id="mtp-update-button"
                     >
-                      {loadingModel != null ? "Another model loading…" : "Load model"}
+                      {llamaUpdating ? "Updating..." : "Update llama.cpp"}
                     </Button>
-                    <Button
-                      type="button"
-                      variant="outline"
-                      size="sm"
-                      onClick={() => {
-                        // Cancel abandons the stage; if a download is mid-flight,
-                        // stop it too rather than leaving it running headless.
-                        if (stagedDownloading) onCancelStagedDownload?.();
-                        abandonStagedModel();
-                      }}
-                      className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav text-muted-foreground"
-                    >
-                      Cancel
-                    </Button>
-                  </div>
-                )}
-              </div>
-            ) : modelSettingsDirty ? (
-              <div className="flex flex-wrap gap-1.5">
-                <Button
-                  type="button"
-                  onClick={() => onReloadModel?.()}
-                  size="sm"
-                  className="h-7 px-3 text-[12px] font-medium tracking-nav bg-primary/92 text-primary-foreground hover:bg-primary"
-                >
-                  Apply
-                </Button>
-                <Button
-                  type="button"
-                  variant="outline"
-                  size="sm"
-                  onClick={() => resetModelSettingsToLoaded()}
-                  className="h-7 px-3 text-[12px] font-medium tracking-nav text-muted-foreground"
-                >
-                  Reset
-                </Button>
-              </div>
-            ) : null}
-            <ChatTemplateFields />
-          </div>
-        </CollapsibleSection>
+                  )}
+                </div>
+              )}
+              {showContextVramWarning && (
+                <p className="text-[11px] text-amber-500">
+                  Context length exceeds the estimated VRAM capacity (
+                      {ggufMaxContextLength?.toLocaleString()} tokens). The
+                      model may use system RAM.
+                </p>
+              )}
+            </div>
+          </CollapsibleSection>
         )}
 
         <CollapsibleSection
           label="Preset"
           defaultOpen={true}
-          first={!hasModelContent}
+          first={!hasModelContent && !modelConfig}
         >
           <div className="flex flex-col gap-3 pt-1">
             <DropdownMenu>
-              <DropdownMenuTrigger asChild>
+                  <DropdownMenuTrigger asChild={true}>
                 <div
                   className="w-full min-w-0 cursor-pointer outline-none focus-visible:outline-none"
                   aria-label="Open preset list"
@@ -1415,7 +865,9 @@ export function ChatSettingsPanel({
                 type="button"
                 onClick={() => savePresetWithName(presetNameInput)}
                 disabled={!(settingsHydrated && presetSaveState.canSubmit)}
-                variant={presetSaveState.isSaveReady ? "default" : "outline"}
+                    variant={
+                      presetSaveState.isSaveReady ? "default" : "outline"
+                    }
                 size="sm"
                 className={cn(
                   "h-9 w-full rounded-full text-[13px] font-medium tracking-nav",
@@ -1456,7 +908,8 @@ export function ChatSettingsPanel({
                   Prompt caching
                 </span>
                 <InfoHint>
-                  Reuse compatible prompt prefixes for lower latency and cost.
+                      Reuse compatible prompt prefixes for lower latency and
+                      cost.
                 </InfoHint>
               </div>
               <Switch
@@ -1479,10 +932,10 @@ export function ChatSettingsPanel({
                   </span>
                   <InfoHint>
                     Anthropic exposes a 5 minute and a 1 hour ephemeral
-                    cache pool. The 1 hour pool costs 2x base input on
-                    write vs 1.25x for 5 minute, but reads stay 0.1x for
-                    both, so a single read landing more than 5 minutes
-                    after the write pays off the premium.
+                        cache pool. The 1 hour pool costs 2x base input on write
+                        vs 1.25x for 5 minute, but reads stay 0.1x for both, so
+                        a single read landing more than 5 minutes after the
+                        write pays off the premium.
                   </InfoHint>
                 </div>
                 <Select
@@ -1550,7 +1003,7 @@ export function ChatSettingsPanel({
           onLabelClick={openSystemPromptEditor}
           headerAction={
             <Tooltip>
-              <TooltipPrimitive.Trigger asChild>
+                  <TooltipPrimitive.Trigger asChild={true}>
                 <button
                   type="button"
                   onClick={openSystemPromptEditor}
@@ -1606,7 +1059,6 @@ export function ChatSettingsPanel({
           </div>
         </CollapsibleSection>
 
-
         <CollapsibleSection label="Sampling" defaultOpen={true}>
           <div className="flex flex-col gap-5 pt-1">
             {showTemperature ? (
@@ -1677,21 +1129,12 @@ export function ChatSettingsPanel({
                 max={2}
                 step={0.1}
                 onChange={set("presencePenalty")}
-                displayValue={params.presencePenalty === 0 ? "Off" : undefined}
+                    displayValue={
+                      params.presencePenalty === 0 ? "Off" : undefined
+                    }
                 info="Penalizes any token that has already appeared at least once, encouraging the model to introduce new topics. 0 = off."
               />
             ) : null}
-            {!isExternalModel && !isGguf && (
-              <ParamSlider
-                label="Max Seq Length"
-                value={params.maxSeqLength}
-                min={128}
-                max={32768}
-                step={128}
-                onChange={set("maxSeqLength")}
-                info="Maximum context window size in tokens — input prompt plus generated output combined. Capped by the model's trained limit."
-              />
-            )}
             <ParamSlider
               label="Max Tokens"
               value={params.maxTokens}
@@ -1700,31 +1143,24 @@ export function ChatSettingsPanel({
                   ? getExternalMinOutputTokens(externalProviderType)
                   : 64
               }
-              max={
-                // A staged GGUF caps to its own context even over an active
-                // external model (the staged model is what will load).
-                !pendingIsGguf && isExternalModel
-                  ? getExternalMaxOutputTokens(
-                      externalProviderType,
-                      externalSelection?.modelId,
-                    )
-                  : isGguf && baseContext
-                    ? baseContext
-                    : 32768
-              }
+              max={maxTokensMax}
               step={64}
               onChange={set("maxTokens")}
               displayValue={
                 isGguf && baseContext && params.maxTokens >= baseContext
                   ? "Max"
-                  : undefined
+                  : !isExternalModel &&
+                      !isGguf &&
+                      params.maxTokens >= maxTokensMax
+                    ? "Max"
+                    : undefined
               }
               info="Maximum number of tokens to generate per response. Generation stops at this limit or when the model emits an end-of-sequence token."
             />
           </div>
         </CollapsibleSection>
 
-        {!isExternalModel ? (
+            {isExternalModel ? null : (
           <CollapsibleSection label="Tools">
             <div className="flex flex-col gap-5 pt-1">
               <AutoHealToolCallsToggle />
@@ -1735,13 +1171,13 @@ export function ChatSettingsPanel({
               <ToolCallTimeoutSlider />
             </div>
           </CollapsibleSection>
-        ) : null}
+            )}
 
-        {!isExternalModel ? (
+            {isExternalModel ? null : (
           <CollapsibleSection label="Retrieval">
             <RetrievalSettingsSection />
           </CollapsibleSection>
-        ) : null}
+            )}
       </div>
       </div>
       </div>
@@ -2085,146 +1521,3 @@ function BypassPermissionsToggle() {
     </div>
   );
 }
-
-function ChatTemplateFields() {
-  const defaultTemplate = useChatRuntimeStore((s) => s.defaultChatTemplate);
-  const override = useChatRuntimeStore((s) => s.chatTemplateOverride);
-  const setOverride = useChatRuntimeStore((s) => s.setChatTemplateOverride);
-  const [editorOpen, setEditorOpen] = useState(false);
-  const [draft, setDraft] = useState("");
-
-  if (!defaultTemplate) return null;
-
-  const displayValue = override ?? defaultTemplate;
-  const isModified = override !== null;
-  const draftDirty = draft !== displayValue;
-
-  const openEditor = () => {
-    setDraft(displayValue);
-    setEditorOpen(true);
-  };
-  const saveEditor = () => {
-    const cleared = draft.trim().length === 0 || draft === defaultTemplate;
-    setOverride(cleared ? null : draft);
-    setEditorOpen(false);
-    toast.success(
-      cleared
-        ? "Chat template reset to default. It applies on the next model reload."
-        : "Chat template saved. It applies on the next model reload.",
-    );
-  };
-
-  return (
-    <>
-      <div className="-mb-1.5 flex items-center justify-between gap-2">
-        <button
-          type="button"
-          onClick={openEditor}
-          className="cursor-pointer text-left text-[13px] font-medium tracking-nav text-nav-fg"
-        >
-          Chat Template
-        </button>
-        <div className="flex items-center gap-1">
-          {isModified && (
-            <Tooltip>
-              <TooltipPrimitive.Trigger asChild>
-                <button
-                  type="button"
-                  onClick={() => setOverride(null)}
-                  className="nav-icon-btn text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
-                  aria-label="Revert chat template"
-                >
-                  <HugeiconsIcon
-                    icon={ArrowTurnBackwardIcon}
-                    strokeWidth={1.75}
-                    className="size-4"
-                  />
-                </button>
-              </TooltipPrimitive.Trigger>
-              <TooltipContent
-                side="top"
-                sideOffset={6}
-                className="tooltip-compact"
-              >
-                Revert changes
-              </TooltipContent>
-            </Tooltip>
-          )}
-          <Tooltip>
-            <TooltipPrimitive.Trigger asChild>
-              <button
-                type="button"
-                onClick={openEditor}
-                className="nav-icon-btn text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
-                aria-label="Edit chat template"
-              >
-                <HugeiconsIcon
-                  icon={Edit03Icon}
-                  strokeWidth={1.75}
-                  className="size-3"
-                />
-              </button>
-            </TooltipPrimitive.Trigger>
-            <TooltipContent
-              side="top"
-              sideOffset={6}
-              className="tooltip-compact"
-            >
-              Edit template
-            </TooltipContent>
-          </Tooltip>
-        </div>
-      </div>
-      <Dialog open={editorOpen} onOpenChange={setEditorOpen}>
-        <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-3xl">
-          <DialogHeader>
-            <DialogTitle>Edit Chat Template</DialogTitle>
-            <DialogDescription>
-              Override the model's chat template. The change applies on the
-              next model reload.
-            </DialogDescription>
-          </DialogHeader>
-          <div className="space-y-2">
-            <div className="space-y-0.5 px-0.5">
-              <div className="text-[11px] font-medium">Template editor</div>
-              <p className="text-[11px] text-muted-foreground">
-                Jinja syntax. Save matching the default clears the override.
-              </p>
-            </div>
-            <Textarea
-              value={draft}
-              onChange={(event) => setDraft(event.target.value)}
-              fieldSizing="fixed"
-              className="min-h-[24rem] max-h-[50vh] overflow-y-auto border-0 font-mono text-xs leading-5 corner-squircle focus-visible:ring-0"
-              rows={14}
-              spellCheck={false}
-            />
-          </div>
-          <DialogFooter className="flex-wrap gap-2 sm:justify-between">
-            <Button
-              type="button"
-              variant="ghost"
-              onClick={() => setDraft(defaultTemplate)}
-              disabled={draft === defaultTemplate}
-              className="text-muted-foreground"
-            >
-              Reset
-            </Button>
-            <div className="flex flex-wrap gap-2">
-              <Button
-                type="button"
-                variant="ghost"
-                onClick={() => setEditorOpen(false)}
-              >
-                Cancel
-              </Button>
-              <Button type="button" onClick={saveEditor} disabled={!draftDirty}>
-                Save
-              </Button>
-            </div>
-          </DialogFooter>
-        </DialogContent>
-      </Dialog>
-    </>
-  );
-}
diff --git a/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts b/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
index 10e0904e4f..1f667de8f9 100644
--- a/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
+++ b/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
@@ -30,7 +30,6 @@ import {
 import { formatEta, formatRate } from "../utils/format-transfer";
 import {
   isLocalModelPath,
-  pendingSelectionMatches,
   readPersistedSpeculativeType,
   resolveToolsEnabledOnLoad,
   saveSpeculativeType,
@@ -53,7 +52,10 @@ import {
   isMultimodalResponse,
 } from "../types/api";
 import { isExternalModelId } from "../external-providers";
-import { cancelStagedModelDownload } from "@/features/hub";
+import {
+  applyPerModelConfigToRuntime,
+  type PerModelConfig,
+} from "@/features/model-picker";
 import type {
   ChatLoraSummary,
   ChatModelSummary,
@@ -78,9 +80,10 @@ export type SelectedModelInput = {
   isGguf?: boolean;
   throwOnError?: boolean;
   /** Keep the current speculative-decoding choice across the model switch
-   *  instead of resetting it to the standing preference. Set by the deferred
-   *  ("Load on selection") Load, where the user picked it for this model. */
+   *  instead of resetting it to the standing preference. */
   keepSpeculative?: boolean;
+  config?: PerModelConfig;
+  previousConfig?: PerModelConfig;
 };
 
 // Approved fingerprints by checkpoint, so a rollback after a failed switch can resend
@@ -455,27 +458,11 @@ export function useChatModelRuntime() {
         typeof selection === "string" ? false : selection.throwOnError ?? false;
       const keepSpeculative =
         typeof selection === "string" ? false : selection.keepSpeculative ?? false;
-      // Picking/loading any model abandons a staged (deferred) selection.
-      // Before the early-returns below so even a no-op re-select clears the
-      // stage.
-      const staged = useChatRuntimeStore.getState().pendingSelection;
-      if (staged) {
-        // Loading a DIFFERENT model abandons this stage. Loading the staged pick
-        // ITSELF keeps it so the sidebar can show its load settings (context, KV
-        // cache, …) during the load. Cleared on success below; on failure it's
-        // left staged so the user can retry (see onLoadPendingModel's catch).
-        const loadingStagedPick = pendingSelectionMatches(staged, {
-          id: modelId,
-          ggufVariant,
-          nativePathToken,
-        });
-        if (!loadingStagedPick) {
-          cancelStagedModelDownload(staged);
-          useChatRuntimeStore.getState().setPendingSelection(null);
-        }
-      }
       const currentVariant = useChatRuntimeStore.getState().activeGgufVariant;
       if (!forceReload && (!modelId || (params.checkpoint === modelId && (ggufVariant ?? null) === (currentVariant ?? null)))) {
+        if (typeof selection !== "string" && selection.previousConfig) {
+          applyPerModelConfigToRuntime(selection.previousConfig);
+        }
         return;
       }
       // A load is already in flight. If it's this exact pick (id + GGUF variant +
@@ -488,6 +475,9 @@ export function useChatModelRuntime() {
       // every entry point is covered, not just the staged Load button.
       const inFlightLoad = loadingModelRef.current;
       if (inFlightLoad) {
+        if (typeof selection !== "string" && selection.previousConfig) {
+          applyPerModelConfigToRuntime(selection.previousConfig);
+        }
         const loadingSamePick =
           inFlightLoad.id === modelId &&
           (inFlightLoad.ggufVariant ?? null) === (ggufVariant ?? null) &&
@@ -582,20 +572,24 @@ export function useChatModelRuntime() {
             previousModel?.isGguf === true
             || previousVariant != null
             || (previousCheckpoint?.toLowerCase().endsWith(".gguf") ?? false);
+          // Roll back to the previous model's own context. previousConfig was
+          // snapshotted before this load pre-applied the next model's config to
+          // the shared store, so params.maxSeqLength may already be the next
+          // model's value; fall back to it only when no snapshot exists.
+          const previousMaxSeqLength =
+            (typeof selection !== "string"
+              ? selection.previousConfig?.maxSeqLength
+              : null) ?? maxSeqLength;
           const rollbackMaxSeqLength = previousIsGguf
             ? (stateBeforeUnload.ggufContextLength ?? 0)
-            : maxSeqLength;
+            : previousMaxSeqLength;
           const hfToken = stateBeforeUnload.hfToken || null;
           const previousModelRequiresTrustRemoteCode =
             stateBeforeUnload.modelRequiresTrustRemoteCode;
           const previousActiveNativePathToken =
             stateBeforeUnload.activeNativePathToken;
           // Snapshot the load settings at click time, before the awaits below
-          // (validation, the trust dialog, unload). For a staged Load these knobs
-          // stay editable and a sheet-close revert (abandonStagedModel) can fire
-          // mid-load; reading them live just before loadModel would let the load
-          // use post-click values. The model-switch speculative reset below
-          // updates this snapshot in lock-step so non-staged loads are unchanged.
+          // (validation, the trust dialog, unload).
           const loadChatTemplateOverride = stateBeforeUnload.chatTemplateOverride;
           const loadKvCacheDtype = stateBeforeUnload.kvCacheDtype;
           const loadCustomContextLength = stateBeforeUnload.customContextLength;
@@ -746,7 +740,12 @@ export function useChatModelRuntime() {
             // The load applied this spec mode, so persist the user's standing
             // preference now (the requested intent, not the resolved echo;
             // saveSpeculativeType keeps only the universal auto/ngram/off).
-            saveSpeculativeType(loadSpeculativeType);
+            // Skip for a per-model/one-off config (keepSpeculative): that choice
+            // is model-specific and must not overwrite the global default, or a
+            // later model with no saved config would start from it instead of Auto.
+            if (!keepSpeculative) {
+              saveSpeculativeType(loadSpeculativeType);
+            }
 
             const currentParams = useChatRuntimeStore.getState().params;
             setParams(
@@ -782,9 +781,11 @@ export function useChatModelRuntime() {
             const reportedNativeCtx = loadResponse.is_gguf
               ? (loadResponse.native_context_length ?? null)
               : null;
-            // A successful reload has applied settings, so clear pending custom
-            // context state and display the backend-reported effective context.
-            const keepCustomCtx = null;
+            // Retain the user's requested context so re-opening or re-saving
+            // the config keeps the intended override, not the backend's
+            // effective (auto-fit) context; null stays null so an auto-fit
+            // never becomes a stored override.
+            const keepCustomCtx = loadCustomContextLength;
             const reasoningAlwaysOn = loadResponse.reasoning_always_on ?? false;
             const reasoningStyle = loadResponse.reasoning_style ?? "enable_thinking";
             const supportsReasoning = loadResponse.supports_reasoning ?? false;
@@ -901,25 +902,6 @@ export function useChatModelRuntime() {
                 recordLastLocalModelLoad({ id: modelId, kind: "model" });
               }
             }
-            // A successful load owns the shared (pick-unscoped) settings fields,
-            // so any surviving stage is stale: the just-loaded pick itself, or a
-            // pick queued for a different model mid-load whose knobs this load
-            // overwrote. Drop it. Only a DIFFERENT pick's download needs
-            // cancelling; the loaded pick's is already consumed, and cancelling
-            // it inside its post-complete linger window would flicker its card.
-            const staleStage = useChatRuntimeStore.getState().pendingSelection;
-            if (staleStage) {
-              if (
-                !pendingSelectionMatches(staleStage, {
-                  id: modelId,
-                  ggufVariant,
-                  nativePathToken,
-                })
-              ) {
-                cancelStagedModelDownload(staleStage);
-              }
-              useChatRuntimeStore.getState().setPendingSelection(null);
-            }
           } catch (error) {
             // Skip rollback if user cancelled -- model is already being unloaded.
             if (abortCtrl.signal.aborted) throw error;
@@ -954,11 +936,23 @@ export function useChatModelRuntime() {
                   // Restore the previous model in the split mode it was running,
                   // not the default layer split.
                   tensor_parallel: stateBeforeUnload.loadedTensorParallel ?? false,
+                  // Restore its KV cache dtype and chat template too, so the
+                  // rollback runs the model as it was, not with backend defaults.
+                  cache_type_kv: stateBeforeUnload.loadedKvCacheDtype ?? null,
+                  chat_template_override:
+                    stateBeforeUnload.loadedChatTemplateOverride ?? null,
+                  // Restore its speculative-decoding config too. Omitting these
+                  // reloaded the model at backend defaults (speculation off)
+                  // while the UI still showed it enabled.
+                  speculative_type: stateBeforeUnload.loadedSpeculativeType ?? null,
+                  spec_draft_n_max: stateBeforeUnload.loadedSpecDraftNMax ?? null,
                 });
                 useChatRuntimeStore.setState({
                   activeNativePathToken: previousActiveNativePathToken ?? null,
-                  loadedSpeculativeType: null,
-                  loadedSpecDraftNMax: null,
+                  speculativeType: stateBeforeUnload.loadedSpeculativeType ?? null,
+                  loadedSpeculativeType: stateBeforeUnload.loadedSpeculativeType ?? null,
+                  specDraftNMax: stateBeforeUnload.loadedSpecDraftNMax ?? null,
+                  loadedSpecDraftNMax: stateBeforeUnload.loadedSpecDraftNMax ?? null,
                 });
                 await refresh();
               } catch {
@@ -1277,6 +1271,9 @@ export function useChatModelRuntime() {
           resetLoadingUi();
         }
       } catch (error) {
+        if (typeof selection !== "string" && selection.previousConfig) {
+          applyPerModelConfigToRuntime(selection.previousConfig);
+        }
         if (abortCtrl.signal.aborted) return; // User cancelled, nothing to report
         resetLoadingUi();
         const message =
diff --git a/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts b/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
deleted file mode 100644
index d8076c720b..0000000000
--- a/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
+++ /dev/null
@@ -1,155 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { useCallback, useEffect } from "react";
-
-import { useRepoDownload } from "@/features/hub/download-manager/use-repo-download";
-import type { DownloadJob } from "@/features/hub/download-manager/use-repo-download";
-import { useLatestRef } from "@/features/hub/hooks/use-latest-ref";
-
-import { fetchGgufContextLength } from "../api/chat-api";
-import {
-  isPendingGguf,
-  pendingSelectionMatches,
-  useChatRuntimeStore,
-} from "../stores/chat-runtime-store";
-import type { PendingModelSelection } from "../stores/chat-runtime-store";
-
-/**
- * Drives the deferred ("Load on selection" off) staging flow for a GGUF:
- * download the file if needed (HF repo) or read it in place (native drag-drop /
- * picked file), then read its header context length so the settings sheet can
- * show the real context slider before the single GPU load. The staged context
- * lands on `pendingSelection.contextLength` (scoped to the staged model, never
- * the loaded model's `ggufContextLength`). Returns the live download job so the
- * sheet can render progress / cancel. Mount once on the chat page.
- */
-export function useStagedModelPreparation(opts?: {
-  /** Load the cached file once an autoLoad pick's download completes. */
-  onAutoLoad?: (pending: PendingModelSelection) => void;
-}): DownloadJob {
-  const pendingId = useChatRuntimeStore((s) => s.pendingSelection?.id ?? null);
-  const pendingVariant = useChatRuntimeStore(
-    (s) => s.pendingSelection?.ggufVariant ?? null,
-  );
-  const pendingNativeToken = useChatRuntimeStore(
-    (s) => s.pendingSelection?.nativePathToken ?? null,
-  );
-  // Only GGUF picks (HF variant or native file) have a header worth reading.
-  const pendingIsGguf = useChatRuntimeStore((s) =>
-    isPendingGguf(s.pendingSelection),
-  );
-  // Non-GGUF HF repos download a full snapshot (variant null) but have no header.
-  const pendingIsHubRepo = useChatRuntimeStore(
-    (s) => s.pendingSelection?.isHubRepo ?? false,
-  );
-  const pendingDownloaded = useChatRuntimeStore(
-    (s) => s.pendingSelection?.isDownloaded ?? false,
-  );
-  const pendingHasContext = useChatRuntimeStore(
-    (s) => s.pendingSelection?.contextLength != null,
-  );
-  const setPendingSelection = useChatRuntimeStore((s) => s.setPendingSelection);
-  const onAutoLoadRef = useLatestRef(opts?.onAutoLoad);
-
-  // A failed or cancelled autoLoad download has no sheet to retry from, so drop
-  // the staged pick rather than leave it waiting on a load that won't come.
-  const handleAutoLoadAbort = useCallback((variant: string | null) => {
-    const latest = useChatRuntimeStore.getState().pendingSelection;
-    if (
-      latest?.autoLoad &&
-      (latest.ggufVariant ?? null) === (variant ?? null)
-    ) {
-      useChatRuntimeStore.getState().abandonStagedModel();
-    }
-  }, []);
-
-  const fetchContextMetadata = useCallback(async () => {
-    const current = useChatRuntimeStore.getState().pendingSelection;
-    if (!current?.id || !isPendingGguf(current)) return;
-    const { id, ggufVariant, nativePathToken } = current;
-    try {
-      const contextLength = await fetchGgufContextLength({
-        model_path: id,
-        gguf_variant: ggufVariant,
-        hf_token: useChatRuntimeStore.getState().hfToken || null,
-        nativePathToken,
-      });
-      // Apply only if the same model is still staged (the user may have switched
-      // picks or loaded/cancelled while the request was in flight).
-      const latest = useChatRuntimeStore.getState().pendingSelection;
-      if (
-        latest &&
-        contextLength != null &&
-        pendingSelectionMatches(latest, { id, ggufVariant, nativePathToken })
-      ) {
-        setPendingSelection({ ...latest, contextLength });
-      }
-    } catch {
-      // Leave contextLength null: the context slider stays hidden and the user
-      // can still load (context fills in from the load response afterwards).
-    }
-  }, [setPendingSelection]);
-
-  const job = useRepoDownload({
-    kind: "model",
-    // useRepoDownload must be called unconditionally; an idle repo id keeps it
-    // inert until something is staged.
-    repoId: pendingId ?? "__staged_idle__",
-    activeVariant: pendingVariant,
-    onComplete: (variant) => {
-      // autoLoad picks load the cached file now; staged picks read the header so
-      // the sheet's context slider can show before a manual load.
-      const latest = useChatRuntimeStore.getState().pendingSelection;
-      if (
-        latest?.autoLoad &&
-        (latest.ggufVariant ?? null) === (variant ?? null)
-      ) {
-        onAutoLoadRef.current?.(latest);
-        return;
-      }
-      void fetchContextMetadata();
-    },
-    onError: handleAutoLoadAbort,
-    onCancelled: handleAutoLoadAbort,
-  });
-
-  // job.requestStartDownload's identity changes per render; hold it in a ref so
-  // the staging effect re-runs only when the staged model itself changes.
-  const startDownloadRef = useLatestRef(job.requestStartDownload);
-  const fetchMetadataRef = useLatestRef(fetchContextMetadata);
-
-  useEffect(() => {
-    // GGUF picks (header worth reading) and uncached non-GGUF hub repos (full
-    // snapshot, no header) both run here; everything else is loaded directly.
-    if (
-      !pendingId ||
-      (!pendingIsGguf && !pendingIsHubRepo) ||
-      pendingHasContext
-    ) {
-      return;
-    }
-    // Native files and already-downloaded HF files are local: read the header
-    // now. Otherwise download first (a GGUF variant, or a null-variant snapshot
-    // for a hub repo); onComplete then reads the header or auto-loads.
-    if (pendingNativeToken || pendingDownloaded) {
-      void fetchMetadataRef.current();
-    } else {
-      const expectedBytes =
-        useChatRuntimeStore.getState().pendingSelection?.expectedBytes ?? 0;
-      void startDownloadRef.current(pendingVariant, expectedBytes);
-    }
-  }, [
-    pendingId,
-    pendingVariant,
-    pendingNativeToken,
-    pendingIsGguf,
-    pendingIsHubRepo,
-    pendingDownloaded,
-    pendingHasContext,
-    startDownloadRef,
-    fetchMetadataRef,
-  ]);
-
-  return job;
-}
diff --git a/studio/frontend/src/features/chat/index.ts b/studio/frontend/src/features/chat/index.ts
index a8b5fc23ad..364c47c7ea 100644
--- a/studio/frontend/src/features/chat/index.ts
+++ b/studio/frontend/src/features/chat/index.ts
@@ -3,11 +3,23 @@
 
 export { ChatPage, validateChatSearch, type ChatSearch } from "./chat-page";
 export {
+  addScanFolder,
+  browseFolders,
+  deleteCachedModel,
+  deleteFineTunedModel,
+  fetchGgufContextLength,
   getInferenceStatus,
   listGgufVariants,
   listLocalModels,
+  listRecommendedFolders,
+  listScanFolders,
   loadModel,
+  removeScanFolder,
+  type BrowseFoldersResponse,
+  type CachedGgufRepo,
+  type CachedModelRepo,
   type LocalModelInfo,
+  type ScanFolderInfo,
 } from "./api/chat-api";
 export type { GgufVariantDetail } from "./types/api";
 export {
@@ -17,6 +29,10 @@ export {
   type Preset,
 } from "./chat-settings-sheet";
 export { useChatRuntimeStore } from "./stores/chat-runtime-store";
+export {
+  normalizeSpeculativeType,
+  readPersistedSpeculativeType,
+} from "./stores/chat-runtime-store";
 export {
   preferFullToolOutput,
   toolOutputKey,
@@ -37,9 +53,11 @@ export {
 } from "./hooks/use-chat-model-runtime";
 export {
   customProviderDisplayName,
+  isCustomProviderType,
   isExternalModelId,
   parseExternalModelId,
 } from "./external-providers";
+export { ApiProviderLogo } from "./api-provider-logo";
 export { useExternalProvidersStore } from "./stores/external-providers-store";
 export { ChatSearchDialog } from "./components/chat-search-dialog";
 export { setTrainingCompareHandoff } from "./lib/training-compare-handoff";
diff --git a/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts b/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
index a4b5f848e2..378178ed58 100644
--- a/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
+++ b/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
@@ -204,11 +204,6 @@ export function applyActiveModelStatusToStore(
     ggufContextLength: currentGgufContextLength,
     ggufMaxContextLength,
     ggufNativeContextLength,
-    // A non-GGUF status must also drop a stale native-path token: without this the
-    // isGguf OR (activeGgufVariant || activeNativePathToken || ggufContextLength)
-    // stays true after switching from a native GGUF to a transformers model, so a
-    // Codex-only detection would auto-select for a model its preflight rejects. A real
-    // GGUF load reports is_gguf: true, so its token is preserved (the load path owns it).
     ...(status.is_gguf ? {} : { activeNativePathToken: null }),
     modelRequiresTrustRemoteCode: status.requires_trust_remote_code ?? false,
     defaultChatTemplate: nextDefaultChatTemplate,
diff --git a/studio/frontend/src/features/chat/shared-composer.tsx b/studio/frontend/src/features/chat/shared-composer.tsx
index a0813fe27b..d861dab0f4 100644
--- a/studio/frontend/src/features/chat/shared-composer.tsx
+++ b/studio/frontend/src/features/chat/shared-composer.tsx
@@ -79,6 +79,11 @@ import { KnowledgeBaseComposerButton } from "@/features/rag/components/knowledge
 import { NewProjectDialog } from "./components/new-project-dialog";
 import { useChatProjects } from "./hooks/use-chat-projects";
 import { confirmRemoteCodeIfNeeded } from "@/features/security";
+import {
+  normalizeMaxSeqLength,
+  resolveInitialConfig,
+  type PerModelConfig,
+} from "@/features/model-picker";
 import {
   confirmTransformersUpgradeIfNeeded,
   useTransformersUpgradeDialogStore,
@@ -490,8 +495,24 @@ type CompareModelSelection = {
   id: string;
   isLora: boolean;
   ggufVariant?: string;
+  config?: PerModelConfig;
 };
 
+function cleanCompareChatTemplate(
+  value: string | null | undefined,
+): string | null {
+  return value?.trim() ? value : null;
+}
+
+function resolveCompareSpecDraftNMax(
+  speculativeType: string | null,
+  value: number | null,
+): number | null {
+  return speculativeType === "mtp" || speculativeType === "mtp+ngram"
+    ? value
+    : null;
+}
+
 // Tool icon plus an X overlay CSS reveals on hover when the pill is active.
 function PillGlyph({ children }: { children: ReactNode }) {
   return (
@@ -1024,13 +1045,11 @@ export function SharedComposer({
       const store = useChatRuntimeStore.getState();
       const maxSeqLength = store.params.maxSeqLength;
       const trustRemoteCode = store.params.trustRemoteCode ?? false;
-      const chatTemplateOverride = store.chatTemplateOverride;
-      const effectiveChatTemplateOverride = chatTemplateOverride?.trim()
-        ? chatTemplateOverride
-        : null;
+      const fallbackTensorParallel = store.tensorParallel;
       const specSettings = resolveSpeculativeSettingsForLoad({
         usePersistedPreference: true,
       });
+      let loadedFromConfig = false;
 
       function modelDisplayName(id: string): string {
         const parts = id.split("/");
@@ -1046,21 +1065,53 @@ export function SharedComposer({
         sel: CompareModelSelection,
       ): Promise<string> {
         const currentStore = useChatRuntimeStore.getState();
+        const config = sel.config ?? null;
+        // This pane's effective config: an explicit selection config, else the
+        // remembered store config for this model/quant (never the other pane's).
+        // A model with no saved config resolves to all-null defaults, so every
+        // setting below still falls through to its session default.
+        const resolved = config
+          ? { config, remembered: true }
+          : resolveInitialConfig(sel.id, sel.ggufVariant ?? null);
+        const ownConfig = resolved.config;
+        const ownRemembered = resolved.remembered;
+        // Mirror single-view resolveLoadMaxSeqLength: a GGUF pane with no
+        // explicit context loads at native (0 -> n_ctx_train), not the session
+        // maxSeqLength, which would silently shrink the picker's shown context.
+        const isGgufLoad =
+          (sel.ggufVariant ?? null) != null ||
+          sel.id.toLowerCase().endsWith(".gguf");
+        const effectiveMaxSeqLength =
+          ownConfig.customContextLength ??
+          normalizeMaxSeqLength(ownConfig.maxSeqLength) ??
+          (isGgufLoad ? 0 : maxSeqLength);
+        const effectiveChatTemplateOverride = cleanCompareChatTemplate(
+          ownConfig.chatTemplateOverride,
+        );
+        const effectiveSpeculativeType =
+          ownConfig.speculativeType ?? specSettings.speculativeType;
+        const effectiveSpecDraftNMax = ownRemembered
+          ? resolveCompareSpecDraftNMax(
+              effectiveSpeculativeType,
+              ownConfig.specDraftNMax,
+            )
+          : specSettings.specDraftNMax;
+        const effectiveTensorParallel = ownRemembered
+          ? ownConfig.tensorParallel
+          : fallbackTensorParallel;
         let loadTrustRemoteCode = trustRemoteCode;
         let approvedRemoteCodeFingerprint: string | null = null;
         const isAlreadyActive =
           currentStore.params.checkpoint === sel.id &&
           (currentStore.activeGgufVariant ?? null) ===
             (sel.ggufVariant ?? null);
-        // Already loaded (gate passed at first load): skip a redundant reload that would
-        // re-trigger the gate without the approval fingerprint and fail for HIGH custom code.
-        if (isAlreadyActive) {
+        if (isAlreadyActive && !config && !loadedFromConfig) {
           return "ready";
         }
         const validation = await validateModel({
           model_path: sel.id,
           hf_token: currentStore.hfToken || null,
-          max_seq_length: maxSeqLength,
+          max_seq_length: effectiveMaxSeqLength,
           load_in_4bit: true,
           is_lora: sel.isLora,
           gguf_variant: sel.ggufVariant ?? null,
@@ -1114,19 +1165,24 @@ export function SharedComposer({
         const resp = await loadModel({
           model_path: sel.id,
           hf_token: useChatRuntimeStore.getState().hfToken || null,
-          max_seq_length: maxSeqLength,
+          max_seq_length: effectiveMaxSeqLength,
           load_in_4bit: true,
           is_lora: sel.isLora,
           gguf_variant: sel.ggufVariant ?? null,
           trust_remote_code: loadTrustRemoteCode,
           approved_remote_code_fingerprint: approvedRemoteCodeFingerprint,
           chat_template_override: effectiveChatTemplateOverride,
-          speculative_type: specSettings.speculativeType,
-          spec_draft_n_max: specSettings.specDraftNMax,
-          // Honor the Tensor Parallelism toggle on compare loads too.
-          tensor_parallel: currentStore.tensorParallel,
+          cache_type_kv: ownConfig.kvCacheDtype ?? null,
+          speculative_type: effectiveSpeculativeType,
+          spec_draft_n_max: effectiveSpecDraftNMax,
+          tensor_parallel: effectiveTensorParallel,
         });
-        saveSpeculativeType(specSettings.speculativeType);
+        // Keep a compare pane's per-model speculative choice load-local: only
+        // persist the global preference when it came from the global settings,
+        // matching the single-model load path.
+        if (ownConfig.speculativeType == null) {
+          saveSpeculativeType(effectiveSpeculativeType);
+        }
         upgradeUnloadedActive = false;
         const store = useChatRuntimeStore.getState();
         store.setCheckpoint(
@@ -1142,11 +1198,38 @@ export function SharedComposer({
           ...reasoningCapsFromLoad(resp),
           supportsPreserveThinking: resp.supports_preserve_thinking ?? false,
           supportsTools: resp.supports_tools ?? false,
+          kvCacheDtype: resp.cache_type_kv ?? null,
+          loadedKvCacheDtype: resp.cache_type_kv ?? null,
           tensorParallel: resp.tensor_parallel ?? false,
           loadedTensorParallel: resp.tensor_parallel ?? false,
+          defaultChatTemplate: resp.chat_template ?? null,
+          chatTemplateOverride: effectiveChatTemplateOverride,
+          loadedChatTemplateOverride: effectiveChatTemplateOverride,
           loadedIsMultimodal: isMultimodalResponse(resp),
+          // Record the context this pane actually loaded with, mirroring the
+          // single-model load path, so that when the last-loaded pane becomes
+          // the active model the settings UI and any subsequent reload or save
+          // use its context instead of the previous/default one.
+          customContextLength: isGgufLoad
+            ? (ownConfig.customContextLength ?? null)
+            : null,
+          ggufContextLength: resp.is_gguf ? (resp.context_length ?? null) : null,
+          ggufNativeContextLength: resp.is_gguf
+            ? (resp.native_context_length ?? null)
+            : null,
+          ggufMaxContextLength: resp.is_gguf
+            ? (resp.max_context_length ?? null)
+            : null,
           ...resolveLoadedSpeculativeSettings(resp),
         });
+        if (!isGgufLoad) {
+          // Non-GGUF panes carry their context in params.maxSeqLength.
+          store.setParams({
+            ...store.params,
+            maxSeqLength: effectiveMaxSeqLength,
+          });
+        }
+        loadedFromConfig = config != null;
         // Sync the models[] entry with the load response so attach/send gates
         // read fresh capabilities. /api/models/list can lag a model's actual
         // state (e.g. a GGUF whose mmproj arrived after the snapshot).
diff --git a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
index af99458349..54184bce24 100644
--- a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
+++ b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
@@ -1,12 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import type { RememberedLoadSettings } from "@/components/assistant-ui/model-selector/remembered-load-settings";
-import {
-  cancelStagedModelDownload,
-  mirrorHfTokenInto,
-  useHfTokenStore,
-} from "@/features/hub";
+import { mirrorHfTokenInto, useHfTokenStore } from "@/features/hub";
 import { toast } from "@/lib/toast";
 import { create } from "zustand";
 import { isExternalModelId, parseExternalModelId } from "../external-providers";
@@ -42,7 +37,6 @@ export const CHAT_ALLOW_ARTIFACT_NETWORK_ACCESS_KEY =
   "unsloth_chat_allow_artifact_network_access";
 export const CHAT_MCP_ENABLED_KEY = "unsloth_chat_mcp_enabled";
 export const CHAT_CONFIRM_TOOL_CALLS_KEY = "unsloth_chat_confirm_tool_calls";
-export const CHAT_LOAD_ON_SELECTION_KEY = "unsloth_chat_load_on_selection";
 export const CHAT_EXPAND_QUANTIZATIONS_KEY =
   "unsloth_chat_expand_quantizations";
 export const CHAT_SHOW_ALL_QUANTIZATIONS_KEY =
@@ -497,34 +491,7 @@ export function saveSpeculativeType(value: string | null): void {
   }
 }
 
-/** A local model staged for a deferred load (see `pendingSelection`). Shape is
- *  a subset of the load hook's `SelectedModelInput`, structurally assignable. */
-export type PendingModelSelection = {
-  id: string;
-  isLora?: boolean;
-  ggufVariant?: string;
-  isDownloaded?: boolean;
-  expectedBytes?: number;
-  /** Native (drag-drop / picked-from-disk) GGUF: the path token used to read
-   *  the header and to load. Absent for HF-repo models. */
-  nativePathToken?: string;
-  /** Direct local .gguf file (custom folder / LM Studio): a GGUF source even
-   *  though it carries neither an HF variant nor a native path token. */
-  isGguf?: boolean;
-  /** Native context length read from the GGUF header once the file is local.
-   *  Scoped here (not the shared `ggufContextLength`) so a staged model's
-   *  metadata never pollutes the currently-loaded model's context display. */
-  contextLength?: number | null;
-  /** "Load on selection" on + un-cached GGUF: download via the manager (global
-   *  indicator) without opening the sheet, then load once the download finishes. */
-  autoLoad?: boolean;
-  /** Uncached non-GGUF HF repo: download the full snapshot via the manager
-   *  (variant null) the same way GGUF picks download a variant. */
-  isHubRepo?: boolean;
-};
-
-/** A pick is a GGUF (HF variant, native file, or a direct local .gguf) and so
- *  has pre-load options worth staging. Works on a selection or a staged pick. */
+/** A pick is a GGUF: HF variant, native file, or a direct local .gguf. */
 export function hasGgufSource(x: {
   ggufVariant?: string;
   nativePathToken?: string;
@@ -562,30 +529,6 @@ export function isDownloadableHubRepo(x: {
   );
 }
 
-export function isPendingGguf(pending: PendingModelSelection | null): boolean {
-  return pending != null && hasGgufSource(pending);
-}
-
-/** Whether `pending` refers to the same model as `pick` (id + GGUF variant +
- *  native path token, optionals null-normalized). Native ids are display labels
- *  that can collide, so the token must match too — id alone can land on the
- *  wrong file. */
-export function pendingSelectionMatches(
-  pending: PendingModelSelection | null,
-  pick: {
-    id: string;
-    ggufVariant?: string | null;
-    nativePathToken?: string | null;
-  },
-): boolean {
-  return (
-    pending != null &&
-    pending.id === pick.id &&
-    (pending.ggufVariant ?? null) === (pick.ggufVariant ?? null) &&
-    (pending.nativePathToken ?? null) === (pick.nativePathToken ?? null)
-  );
-}
-
 type ChatRuntimeStore = {
   settingsHydrated: boolean;
   params: InferenceParams;
@@ -743,10 +686,6 @@ type ChatRuntimeStore = {
   tensorParallel: boolean;
   /** Backend-reported tensor-parallel state; null until first hydrated. */
   loadedTensorParallel: boolean | null;
-  /** Persisted: when false, picking a local model stages it as
-   *  `pendingSelection` (and opens settings) instead of loading immediately,
-   *  so load settings can be set before the single load. */
-  loadOnSelection: boolean;
   /** Persisted: expand every On Device GGUF repo's quantizations by default
    *  instead of waiting for a click. */
   expandQuantizations: boolean;
@@ -755,9 +694,6 @@ type ChatRuntimeStore = {
   /** Persisted, shared by the chat model selector and the Hub page: list only
    *  models whose size fits this device's memory budget. */
   fitOnDeviceOnly: boolean;
-  /** A local model picked while `loadOnSelection` is off: staged, not loaded.
-   *  The settings sheet shows its load knobs and a Load button. */
-  pendingSelection: PendingModelSelection | null;
   loadedIsMultimodal: boolean;
   /** Active model is a block-diffusion model (DiffusionGemma): drives the
    *  denoising-canvas artifact auto-render. */
@@ -794,6 +730,10 @@ type ChatRuntimeStore = {
   } | null;
   modelLoading: boolean;
   activeNativePathToken: string | null;
+  // Wall-clock expiry (ms) of the active native path token. The desktop host
+  // prunes file leases after a TTL, so a reload checks this to prompt
+  // re-selection instead of reusing a dead token.
+  activeNativePathExpiresAtMs: number | null;
   hydratePersistedSettings: () => Promise<void>;
   setModelLoading: (loading: boolean) => void;
   setModelRequiresTrustRemoteCode: (required: boolean) => void;
@@ -871,33 +811,9 @@ type ChatRuntimeStore = {
   setNudgeToolCalls: (enabled: boolean) => void;
   setMaxToolCallsPerMessage: (value: number) => void;
   setToolCallTimeout: (value: number) => void;
-  setKvCacheDtype: (dtype: string | null) => void;
-  setSpeculativeType: (type: string | null) => void;
-  setSpecDraftNMax: (value: number | null) => void;
-  /** Revert the editable load knobs to the loaded model's baseline (or defaults
-   *  when nothing is loaded). Used by the settings-sheet Reset button and to
-   *  start each deferred-staging session clean so one staged pick's settings
-   *  don't leak onto the next. */
-  resetModelSettingsToLoaded: () => void;
-  /** Seed the editable load knobs from a model's remembered settings. Shared by
-   *  the settings sheet's restore effect and the "Load on selection" paths,
-   *  which skip the sheet but must still honor a saved config. */
-  applyRememberedLoadSettings: (settings: RememberedLoadSettings) => void;
-  setTensorParallel: (value: boolean) => void;
-  setLoadOnSelection: (value: boolean) => void;
   setExpandQuantizations: (value: boolean) => void;
   setShowAllQuantizations: (value: boolean) => void;
   setFitOnDeviceOnly: (value: boolean) => void;
-  setPendingSelection: (selection: PendingModelSelection | null) => void;
-  /** Stage a pick for a deferred load: revert knobs to the loaded baseline,
-   *  record the selection, and open the settings sheet. */
-  stageModel: (selection: PendingModelSelection) => void;
-  /** Abandon a staged pick without loading: revert knobs to the loaded baseline
-   *  and clear the pending selection. Cancels its in-flight download too, unless
-   *  `keepDownload` is set (navigation keeps the transfer running, like Hub). */
-  abandonStagedModel: (opts?: { keepDownload?: boolean }) => void;
-  setCustomContextLength: (v: number | null) => void;
-  setChatTemplateOverride: (template: string | null) => void;
   setPendingAudio: (base64: string, name: string) => void;
   clearPendingAudio: () => void;
   setPendingImageEditReference: (
@@ -1099,23 +1015,6 @@ function setScalarSettingVersion<K extends ScalarSettingKey>(
   saveSettingsPatch({ [key]: value });
 }
 
-/** The "revert to the loaded model" baseline for the editable load knobs.
- *  Shared by resetModelSettingsToLoaded (full revert) and stageModel (which
- *  overrides speculative to start a fresh pick from the standing default). */
-function loadedBaselineSettings(s: ChatRuntimeStore) {
-  const hasLoadedModel = Boolean(s.params.checkpoint);
-  return {
-    customContextLength: null,
-    kvCacheDtype: s.loadedKvCacheDtype,
-    tensorParallel: s.loadedTensorParallel ?? false,
-    speculativeType: hasLoadedModel
-      ? s.loadedSpeculativeType
-      : readPersistedSpeculativeType(),
-    specDraftNMax: hasLoadedModel ? s.loadedSpecDraftNMax : null,
-    chatTemplateOverride: s.loadedChatTemplateOverride,
-  };
-}
-
 export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   settingsHydrated: false,
   // Hydrate the last external checkpoint so the external picker survives a
@@ -1213,11 +1112,9 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   loadedSpecDraftNMax: null,
   tensorParallel: false,
   loadedTensorParallel: null,
-  loadOnSelection: loadBool(CHAT_LOAD_ON_SELECTION_KEY, true),
   expandQuantizations: loadBool(CHAT_EXPAND_QUANTIZATIONS_KEY, false),
   showAllQuantizations: loadBool(CHAT_SHOW_ALL_QUANTIZATIONS_KEY, true),
   fitOnDeviceOnly: loadBool(MODELS_FIT_ON_DEVICE_ONLY_KEY, false),
-  pendingSelection: null,
   loadedIsMultimodal: false,
   loadedIsDiffusion: false,
   customContextLength: null,
@@ -1235,6 +1132,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   contextUsage: null,
   modelLoading: false,
   activeNativePathToken: null,
+  activeNativePathExpiresAtMs: null,
   hydratePersistedSettings: async () => {
     if (get().settingsHydrated) {
       return;
@@ -1353,13 +1251,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       // Clear stale per-turn usage on model change; the relaxed external-provider
       // render gate would otherwise show old counters until the next completion.
       const checkpointChanged = state.params.checkpoint !== modelId;
-      const pendingToClear =
-        checkpointChanged && state.params.checkpoint
-          ? state.pendingSelection
-          : null;
-      if (pendingToClear) {
-        cancelStagedModelDownload(pendingToClear);
-      }
       // Clamp maxTokens to the new model's cap when switching into an external
       // model so a value carried over from a local session doesn't exceed the
       // slider's max.
@@ -1387,14 +1278,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
         },
         activeGgufVariant: ggufVariant ?? null,
         ...(checkpointChanged ? { contextUsage: null } : {}),
-        // Switching away from a loaded model (e.g. picking an external provider)
-        // abandons any staged pick, so its Load button and edited knobs don't
-        // linger over the newly active model. Same revert as abandonStagedModel.
-        // Guarded on a non-empty current checkpoint: an establishing set from a
-        // background status sync (empty -> active) must not wipe a fresh stage.
-        ...(pendingToClear
-          ? { ...loadedBaselineSettings(state), pendingSelection: null }
-          : {}),
       };
     }),
   setActiveThreadId: (activeThreadId) =>
@@ -1408,7 +1291,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     // clear any stored external selection so the next refresh doesn't snap
     // back to a model the user intentionally cleared.
     saveLastExternalCheckpoint(null);
-    cancelStagedModelDownload(get().pendingSelection);
     return set((state) => ({
       params: {
         ...state.params,
@@ -1416,7 +1298,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       },
       activeGgufVariant: null,
       activeNativePathToken: null,
-      pendingSelection: null,
+      activeNativePathExpiresAtMs: null,
       ggufContextLength: null,
       ggufMaxContextLength: null,
       ggufNativeContextLength: null,
@@ -1749,25 +1631,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       );
       return { toolCallTimeout };
     }),
-  setKvCacheDtype: (kvCacheDtype) => set({ kvCacheDtype }),
-  setSpeculativeType: (speculativeType) => set({ speculativeType }),
-  setSpecDraftNMax: (specDraftNMax) => set({ specDraftNMax }),
-  setTensorParallel: (tensorParallel) => set({ tensorParallel }),
-  resetModelSettingsToLoaded: () => set((s) => loadedBaselineSettings(s)),
-  applyRememberedLoadSettings: (settings) =>
-    // Coalesce every field: a blob persisted by an older/newer build can omit
-    // keys, and a raw spread would push `undefined` into fields typed non-null.
-    set({
-      customContextLength: settings.contextLength ?? null,
-      kvCacheDtype: settings.kvCacheDtype ?? null,
-      speculativeType: settings.speculativeType ?? "auto",
-      specDraftNMax: settings.specDraftNMax ?? null,
-      tensorParallel: settings.tensorParallel ?? false,
-    }),
-  setLoadOnSelection: (loadOnSelection) => {
-    saveBool(CHAT_LOAD_ON_SELECTION_KEY, loadOnSelection);
-    set({ loadOnSelection });
-  },
   setExpandQuantizations: (expandQuantizations) => {
     saveBool(CHAT_EXPAND_QUANTIZATIONS_KEY, expandQuantizations);
     set({ expandQuantizations });
@@ -1780,39 +1643,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     saveBool(MODELS_FIT_ON_DEVICE_ONLY_KEY, fitOnDeviceOnly);
     set({ fitOnDeviceOnly });
   },
-  setPendingSelection: (pendingSelection) => set({ pendingSelection }),
-  stageModel: (selection) => {
-    // Refuse staging mid-load: post-load cleanup would silently drop the queued
-    // pick. stageOrLoad toasts first for callers that can.
-    if (get().modelLoading) return;
-    // Rebinding to a new pick keeps the prior pick's download running so the
-    // user can queue multiple downloads at once (Hub-style).
-    set((s) => {
-      return {
-        ...loadedBaselineSettings(s),
-        pendingSelection: selection,
-        // autoLoad downloads silently and loads on completion, so keep the sheet shut.
-        settingsPanelOpen: !selection.autoLoad,
-        // Speculative starts from the standing default, not the loaded model's
-        // mode, so a fresh pick doesn't inherit (and then carry, via the staged
-        // Load's keepSpeculative) a forced MTP mode onto a model that may lack it.
-        speculativeType: readPersistedSpeculativeType(),
-        specDraftNMax: null,
-      };
-    });
-  },
-  abandonStagedModel: (opts) => {
-    const { pendingSelection } = get();
-    if (!pendingSelection) return;
-    // Cancel the staged pick's in-flight download (centralized for every abandon
-    // path: sheet close, thread switch, route exit, new chat). `keepDownload`
-    // opts out so navigation leaves the transfer running, like a Hub download.
-    if (!opts?.keepDownload) cancelStagedModelDownload(pendingSelection);
-    set((s) => ({ ...loadedBaselineSettings(s), pendingSelection: null }));
-  },
-  setCustomContextLength: (customContextLength) => set({ customContextLength }),
-  setChatTemplateOverride: (chatTemplateOverride) =>
-    set({ chatTemplateOverride }),
   setPendingAudio: (base64, name) =>
     set({ pendingAudioBase64: base64, pendingAudioName: name }),
   clearPendingAudio: () =>
diff --git a/studio/frontend/src/features/export/components/export-run-panel.tsx b/studio/frontend/src/features/export/components/export-run-panel.tsx
index 29ba5a703b..6c2794420b 100644
--- a/studio/frontend/src/features/export/components/export-run-panel.tsx
+++ b/studio/frontend/src/features/export/components/export-run-panel.tsx
@@ -2,7 +2,6 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { Button } from "@/components/ui/button";
-import { FolderBrowser } from "@/components/assistant-ui/model-selector/folder-browser";
 import { Input } from "@/components/ui/input";
 import {
   InputGroup,
@@ -17,6 +16,7 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import { FolderBrowser } from "@/features/model-picker";
 import {
   AlertCircleIcon,
   ArrowRight01Icon,
@@ -28,17 +28,17 @@ import {
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useEffect, useRef, useState } from "react";
 import { useShallow } from "zustand/react/shallow";
+import type { ExportLogEntry } from "../api/export-api";
 import {
   EXPORT_METHODS,
   type ExportMethod,
   findMergedFormat,
 } from "../constants";
-import type { ExportLogEntry } from "../api/export-api";
 import { getExportLogLineClass } from "../lib/log-style";
 import {
+  type ExportDestination,
   selectExportProgressPercent,
   useExportRuntimeStore,
-  type ExportDestination,
 } from "../stores/export-runtime-store";
 
 function useElapsedSeconds(startedAt: number | null, running: boolean): number {
@@ -165,7 +165,9 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
 
   const isExporting = run.isExporting;
   const isTerminal =
-    run.phase === "success" || run.phase === "error" || run.phase === "canceled";
+    run.phase === "success" ||
+    run.phase === "error" ||
+    run.phase === "canceled";
   const showConfig = run.phase === "idle";
   // Gate the log area on the active run's method (from the store) as well as the
   // local form selection, so it stays visible after navigating away and back
@@ -197,7 +199,9 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
     setFollowTail(nearBottom);
   };
 
-  const methodTitle = EXPORT_METHODS.find((m) => m.value === exportMethod)?.title;
+  const methodTitle = EXPORT_METHODS.find(
+    (m) => m.value === exportMethod,
+  )?.title;
   const summary = run.summary;
   const summaryBaseModel = summary?.baseModelName ?? baseModelName;
   const summaryCheckpoint = summary?.checkpointLabel ?? checkpoint;
@@ -290,7 +294,10 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                       onClick={() => setFolderBrowserOpen(true)}
                       aria-label="Browse save folder"
                     >
-                      <HugeiconsIcon icon={FolderSearchIcon} className="size-4" />
+                      <HugeiconsIcon
+                        icon={FolderSearchIcon}
+                        className="size-4"
+                      />
                     </Button>
                   </TooltipTrigger>
                   <TooltipContent>Browse</TooltipContent>
@@ -301,8 +308,8 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                   <>Default: {defaultSaveDirectory}</>
                 ) : (
                   <>
-                    Paste an absolute path if the folder browser cannot reach the
-                    drive.
+                    Paste an absolute path if the folder browser cannot reach
+                    the drive.
                   </>
                 )}
               </p>
@@ -410,7 +417,10 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                     : [];
               const showLabels = items.length > 1;
               return items.map((o, i) => (
-                <div key={`${o.path}-${i}`} className="flex min-w-0 flex-col gap-0.5">
+                <div
+                  key={`${o.path}-${i}`}
+                  className="flex min-w-0 flex-col gap-0.5"
+                >
                   {showLabels && o.label ? (
                     <span className="text-xs text-emerald-700/80 dark:text-emerald-300/80">
                       {o.label}
@@ -431,14 +441,22 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
 
       {run.phase === "canceled" && (
         <div className="flex items-start gap-2 rounded-lg bg-amber-500/10 p-3 text-sm text-amber-700 dark:text-amber-300">
-          <HugeiconsIcon icon={CancelCircleIcon} className="mt-0.5 size-4 shrink-0" />
-          <span>Export canceled. Training and inference were not affected.</span>
+          <HugeiconsIcon
+            icon={CancelCircleIcon}
+            className="mt-0.5 size-4 shrink-0"
+          />
+          <span>
+            Export canceled. Training and inference were not affected.
+          </span>
         </div>
       )}
 
       {run.phase === "error" && run.error && (
         <div className="flex items-start gap-2 rounded-lg bg-destructive/10 p-3 text-sm text-destructive">
-          <HugeiconsIcon icon={AlertCircleIcon} className="size-4 mt-0.5 shrink-0" />
+          <HugeiconsIcon
+            icon={AlertCircleIcon}
+            className="size-4 mt-0.5 shrink-0"
+          />
           <span>{run.error}</span>
         </div>
       )}
@@ -447,15 +465,21 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
       <div className="rounded-xl bg-muted/50 p-3 text-xs text-muted-foreground flex flex-col gap-1">
         <div className="flex justify-between">
           <span>Base Model</span>
-          <span className="font-medium text-foreground">{summaryBaseModel}</span>
+          <span className="font-medium text-foreground">
+            {summaryBaseModel}
+          </span>
         </div>
         <div className="flex justify-between">
           <span>{isAdapter ? "Checkpoint" : "Model"}</span>
-          <span className="font-medium text-foreground">{summaryCheckpoint}</span>
+          <span className="font-medium text-foreground">
+            {summaryCheckpoint}
+          </span>
         </div>
         <div className="flex justify-between">
           <span>Export Method</span>
-          <span className="font-medium text-foreground">{summaryMethodLabel}</span>
+          <span className="font-medium text-foreground">
+            {summaryMethodLabel}
+          </span>
         </div>
         {summaryMethod === "merged" && summaryFormats.length > 0 && (
           <div className="flex justify-between gap-3">
@@ -484,7 +508,12 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
             </span>
             {summaryMethod === "gguf" && run.quantTotal > 1 && (
               <span className="text-[10px] tabular-nums text-muted-foreground">
-                Quant {Math.min(run.quantIndex + (isExporting ? 1 : 0), run.quantTotal)} of {run.quantTotal}
+                Quant{" "}
+                {Math.min(
+                  run.quantIndex + (isExporting ? 1 : 0),
+                  run.quantTotal,
+                )}{" "}
+                of {run.quantTotal}
               </span>
             )}
             <span className="rounded-full border border-border/60 px-2.5 py-1 text-[10px] font-medium tabular-nums text-muted-foreground">
@@ -506,7 +535,10 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
             }
           />
           {run.stage && (
-            <p className="truncate text-[11px] text-muted-foreground/80" title={run.stage}>
+            <p
+              className="truncate text-[11px] text-muted-foreground/80"
+              title={run.stage}
+            >
               {run.stage}
             </p>
           )}
@@ -556,10 +588,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                 ) : (
                   <div className="whitespace-pre-wrap break-words">
                     {run.logLines.map((entry, idx) => (
-                      <div
-                        key={idx}
-                        className={getExportLogLineClass(entry)}
-                      >
+                  <div key={idx} className={getExportLogLineClass(entry)}>
                         {formatLogLine(entry)}
                       </div>
                     ))}
diff --git a/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx b/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
index 111d78f00b..9ed8e449f6 100644
--- a/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { ModelDeleteAction } from "@/components/assistant-ui/model-selector/model-delete-action";
 import {
   Tooltip,
   TooltipContent,
@@ -9,18 +8,22 @@ import {
 } from "@/components/ui/tooltip";
 import {
   type GgufVariantDetail,
-  deleteCachedModel,
   deleteCachedDataset,
+  deleteCachedModel,
   formatLocalUpdated,
   listGgufVariants,
   useGgufVariantsCacheVersion,
-} from "@/features/hub/inventory";
-import { classifyUnslothSupport } from "@/features/hub/hooks/use-hub-model-search";
-import { formatBytes, formatRelativeShort } from "@/features/hub/lib/format";
-import { ggufVariantDisplayLabel } from "@/features/hub/lib/gguf-variant-sort";
-import { modelIdsMatch } from "@/features/hub/lib/model-identity";
+} from "@/features/hub";
+import {
+  classifyUnslothSupport,
+  formatBytes,
+  formatRelativeShort,
+  ggufVariantDisplayLabel,
+  modelIdsMatch,
+  useHfTokenStore,
+} from "@/features/hub";
+import { ModelDeleteAction } from "@/features/model-picker";
 import { cn, formatCompact } from "@/lib/utils";
-import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
 import {
   Download01Icon,
   FavouriteIcon,
@@ -39,6 +42,7 @@ import {
   useRef,
   useState,
 } from "react";
+import { paramLabelFromId } from "../lib/view-models";
 import type {
   CachedInventoryRow,
   DiscoverRow,
@@ -46,7 +50,6 @@ import type {
 } from "../types";
 import { OwnerAvatar } from "./owner-avatar";
 import { AccessGlyphs } from "./shared";
-import { paramLabelFromId } from "../lib/view-models";
 
 const COARSE_POINTER =
   typeof window !== "undefined" &&
@@ -142,15 +145,15 @@ function CachedSizeChipLive({
   );
 
   const rows: Array<{ label: string; size_bytes: number }> | null =
-    !needsVariantFetch
-      ? [{ label: repoId, size_bytes: totalBytes }]
-      : currentVariantState.status === "loaded" &&
+    needsVariantFetch
+      ? currentVariantState.status === "loaded" &&
           currentVariantState.variants.length > 0
         ? currentVariantState.variants.map((variant) => ({
             label: ggufVariantDisplayLabel(variant),
             size_bytes: variant.size_bytes,
           }))
-        : null;
+        : null
+      : [{ label: repoId, size_bytes: totalBytes }];
   const variantMessage =
     currentVariantState.status === "loading"
       ? "Loading downloaded variants..."
@@ -275,7 +278,9 @@ function CatalogRow({
         )}
       />
       <CatalogRowInteractiveContext.Provider value={interactive}>
-        <div className={cn("pointer-events-none relative", card && "z-[1] w-full")}>
+        <div
+          className={cn("pointer-events-none relative", card && "z-[1] w-full")}
+        >
           {children}
         </div>
       </CatalogRowInteractiveContext.Provider>
@@ -653,7 +658,9 @@ export const InventoryRow = memo(function InventoryRow({
       <div className="hidden shrink-0 items-center gap-1.5 sm:flex">
         {/* Format already shows as the status dot, so the pill stays neutral. */}
         {formatLabel && <span className="hub-chip">{formatLabel}</span>}
-        {paramLabel && <span className="hub-chip tabular-nums">{paramLabel}</span>}
+        {paramLabel && (
+          <span className="hub-chip tabular-nums">{paramLabel}</span>
+        )}
         {quantLabel && (
           <span className="hub-chip font-mono text-[10.5px] uppercase">
             {quantLabel}
@@ -697,9 +704,7 @@ export const InventoryRow = memo(function InventoryRow({
   const compactMarkers =
     partialRepoId || unsupported ? (
       <span className="flex shrink-0 items-center gap-1">
-        {partialRepoId && (
-          <StatusDot tone="warning" label="Partial download" />
-        )}
+        {partialRepoId && <StatusDot tone="warning" label="Partial download" />}
         {unsupported && (
           <StatusDot tone="danger" label="May not be supported yet" />
         )}
diff --git a/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx b/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
index caa89db196..86108bbd80 100644
--- a/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
+++ b/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { FolderBrowser } from "@/components/assistant-ui/model-selector/folder-browser";
 import { Button } from "@/components/ui/button";
 import {
   Dialog,
@@ -22,9 +21,11 @@ import {
   addScanFolder,
   listScanFolders,
   removeScanFolder,
-} from "@/features/hub/inventory";
-import { openModelsDir } from "@/features/native-intents/api";
+} from "@/features/hub";
+import { FolderBrowser } from "@/features/model-picker";
+import { openModelsDir } from "@/features/native-intents";
 import { isTauri } from "@/lib/api-base";
+import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import {
   Delete02Icon,
@@ -38,7 +39,6 @@ import {
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "@/lib/toast";
 
 function pathTail(path: string): string {
   const parts = path.split(/[\\/]/).filter(Boolean);
@@ -123,7 +123,9 @@ export function OnDeviceFoldersDialog({
         setPath("");
         mutationVersionRef.current += 1;
         setFolders((current) => {
-          const withoutDuplicate = current.filter((row) => row.id !== folder.id);
+          const withoutDuplicate = current.filter(
+            (row) => row.id !== folder.id,
+          );
           return [...withoutDuplicate, folder];
         });
         toast.success("Location added", {
@@ -184,9 +186,12 @@ export function OnDeviceFoldersDialog({
           overlayClassName="bg-black/20 backdrop-blur-none"
         >
           <DialogHeader className="border-b border-border/60 px-5 py-4">
-            <DialogTitle className="text-[15px]">On-device locations</DialogTitle>
+            <DialogTitle className="text-[15px]">
+              On-device locations
+            </DialogTitle>
             <DialogDescription className="sr-only">
-              Hugging Face model folders, GGUF files, and adapters are indexed here.
+              Hugging Face model folders, GGUF files, and adapters are indexed
+              here.
             </DialogDescription>
           </DialogHeader>
 
@@ -342,9 +347,7 @@ export function OnDeviceFoldersDialog({
                           </p>
                           <Tooltip>
                             <TooltipTrigger asChild={true}>
-                              <p
-                                className="block w-full truncate font-mono text-[10.5px] text-muted-foreground"
-                              >
+                              <p className="block w-full truncate font-mono text-[10.5px] text-muted-foreground">
                                 {folder.path}
                               </p>
                             </TooltipTrigger>
@@ -372,7 +375,10 @@ export function OnDeviceFoldersDialog({
                                 />
                               </button>
                             </TooltipTrigger>
-                            <TooltipContent side="left" className="tooltip-compact">
+                            <TooltipContent
+                              side="left"
+                              className="tooltip-compact"
+                            >
                               Open in file manager
                             </TooltipContent>
                           </Tooltip>
@@ -397,7 +403,10 @@ export function OnDeviceFoldersDialog({
                               )}
                             </button>
                           </TooltipTrigger>
-                          <TooltipContent side="left" className="tooltip-compact">
+                          <TooltipContent
+                            side="left"
+                            className="tooltip-compact"
+                          >
                             Remove from list
                           </TooltipContent>
                         </Tooltip>
diff --git a/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts b/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
index da653ddeb7..2cea1d8304 100644
--- a/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
+++ b/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
@@ -1,14 +1,10 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { DOWNLOAD_KIND } from "./constants";
 import {
   createDownloadManagerInitialState,
-  jobKeyOf,
   removeJob,
-  selectActiveJob,
   setState,
-  useDownloadManagerStore,
 } from "./download-manager-state";
 import { resetDownloadApiAdapterState } from "./download-api-adapter";
 import {
@@ -69,25 +65,6 @@ export const downloadManager: DownloadManagerController = {
   dismiss: removeJob,
 };
 
-/** Cancel the in-flight download for a staged model pick. No-op when nothing is
- *  downloading (e.g. a native/local file that was never fetched). Lets non-React
- *  callers (the chat store's abandon paths) stop a staged transfer without the
- *  useRepoDownload hook. */
-export function cancelStagedModelDownload(
-  pending: { id: string; ggufVariant?: string | null } | null,
-): void {
-  if (!pending) return;
-  const variant = pending.ggufVariant ?? null;
-  const activeJob = selectActiveJob(
-    useDownloadManagerStore.getState(),
-    DOWNLOAD_KIND.MODEL,
-    pending.id,
-    variant,
-  );
-  void downloadManager.cancel(
-    activeJob?.key ?? jobKeyOf(DOWNLOAD_KIND.MODEL, pending.id, variant),
-  );
-}
 
 if (import.meta.hot) {
   import.meta.hot.dispose(() => {
diff --git a/studio/frontend/src/features/hub/download-manager/index.ts b/studio/frontend/src/features/hub/download-manager/index.ts
index dd88aaf3f0..60ef3851f8 100644
--- a/studio/frontend/src/features/hub/download-manager/index.ts
+++ b/studio/frontend/src/features/hub/download-manager/index.ts
@@ -20,7 +20,6 @@ export {
 } from "./constants";
 export {
   __resetDownloadManagerForTests,
-  cancelStagedModelDownload,
   clearCompletedInventoryHint,
   downloadManager,
   hydrateDownloadManager,
diff --git a/studio/frontend/src/features/hub/hub-page.tsx b/studio/frontend/src/features/hub/hub-page.tsx
index 630daa48ad..222a74322e 100644
--- a/studio/frontend/src/features/hub/hub-page.tsx
+++ b/studio/frontend/src/features/hub/hub-page.tsx
@@ -1,34 +1,32 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import {
-  loadRememberedLoadSettings,
-  rememberedLoadSettingsKey,
-} from "@/components/assistant-ui/model-selector/remembered-load-settings";
-import { hfModelFitsDevice } from "@/components/assistant-ui/model-selector/recommended-fit";
-import { useHubInventory } from "@/features/hub/inventory";
-import { useDebouncedValue } from "@/hooks/use-debounced-value";
-import { useGpuInfo } from "@/hooks/use-gpu-info";
-import {
-  type HfModelSearchChannel,
-  type HfSortDirection,
-  type HfSortKey,
-} from "@/features/hub/hooks/use-hub-model-search";
-import { useOnlineStatus } from "@/features/hub/hooks/use-online-status";
-import { useHubInfiniteScroll } from "@/features/hub/hooks/use-hub-infinite-scroll";
-import { ggufVariantsMatch, modelIdsMatch } from "@/features/hub/lib/model-identity";
-import { cn } from "@/lib/utils";
 import { usePlatformStore } from "@/config/env";
-import {
-  hfApiToken,
-  useHfTokenStore,
-} from "@/features/hub/stores/hf-token-store";
 import {
   getInferenceStatus,
   isExternalModelId,
   useChatModelRuntime,
   useChatRuntimeStore,
 } from "@/features/chat";
+import { useHubInventory } from "@/features/hub";
+import type {
+  HfModelSearchChannel,
+  HfSortDirection,
+  HfSortKey,
+} from "@/features/hub";
+import { useOnlineStatus } from "@/features/hub";
+import { useHubInfiniteScroll } from "@/features/hub";
+import { ggufVariantsMatch, modelIdsMatch } from "@/features/hub";
+import { hfApiToken, useHfTokenStore } from "@/features/hub";
+import {
+  applyModelLoadConfigToRuntime,
+  currentRuntimePerModelConfig,
+  hfModelFitsDevice,
+  resolveInitialConfig,
+} from "@/features/model-picker";
+import { useDebouncedValue } from "@/hooks/use-debounced-value";
+import { useGpuInfo } from "@/hooks/use-gpu-info";
+import { cn } from "@/lib/utils";
 import { useNavigate, useSearch } from "@tanstack/react-router";
 import {
   useCallback,
@@ -38,17 +36,10 @@ import {
   useRef,
   useState,
 } from "react";
+import { ExternalLinkConfirmDialog } from "./catalog/external-link-confirm-dialog";
 import { HubDetailView } from "./catalog/hub-detail-view";
-import { HubTopBar } from "./catalog/hub-top-bar";
 import { HubFeed } from "./catalog/hub-feed";
-import { OwnerScopeToggle } from "./catalog/owner-scope-toggle";
-import {
-  type AllModelsView,
-  HubListHeader,
-  type InventorySort,
-  InventorySortControl,
-  ResultListHeader,
-} from "./catalog/models-table";
+import { HubTopBar } from "./catalog/hub-top-bar";
 import {
   ModelsCatalog,
   type ModelsCatalogHandlers,
@@ -56,9 +47,16 @@ import {
   type ModelsCatalogState,
 } from "./catalog/models-catalog";
 import { ModelsHeader } from "./catalog/models-header";
+import {
+  type AllModelsView,
+  HubListHeader,
+  type InventorySort,
+  InventorySortControl,
+  ResultListHeader,
+} from "./catalog/models-table";
 import { ModelsToolbar } from "./catalog/models-toolbar";
-import { ExternalLinkConfirmDialog } from "./catalog/external-link-confirm-dialog";
 import { OnDeviceFoldersDialog } from "./catalog/on-device-folders-dialog";
+import { OwnerScopeToggle } from "./catalog/owner-scope-toggle";
 import { useDiscoverSearch } from "./hooks/use-discover-search";
 import { useFeedWriteBack } from "./hooks/use-feed-write-back";
 import { useHubFeed } from "./hooks/use-hub-feed";
@@ -568,15 +566,15 @@ export function ModelsPage() {
   const deferredCapabilityFilter = useDeferredValue(capabilityFilter);
 
   const hasQuery = deferredDebouncedQuery.trim() !== "";
-  const mode: DiscoverMode = !isModelDiscover
-    ? "search"
-    : hasQuery
+  const mode: DiscoverMode = isModelDiscover
+    ? hasQuery
       ? "search"
       : urlSection != null
         ? "channel-list"
         : sortBrowseActive
           ? "search"
-          : "feed";
+          : "feed"
+    : "search";
   const isFeedMode = mode === "feed";
   const isChannelListMode = mode === "channel-list";
   const isSortBrowseMode =
@@ -767,7 +765,10 @@ export function ModelsPage() {
     }
     return merged;
   }, [isFeedMode, feedTrendingRows, filteredDiscoverRows]);
-  const feedResults = useMemo(() => feedRows.map((row) => row.result), [feedRows]);
+  const feedResults = useMemo(
+    () => feedRows.map((row) => row.result),
+    [feedRows],
+  );
   const selectionDiscoverRows = isFeedMode ? feedRows : discoverRows;
   const selectionFilteredDiscoverRows = isFeedMode
     ? feedRows
@@ -1108,50 +1109,22 @@ export function ModelsPage() {
     (opts: ModelLoadOptions, isDownloaded: boolean) => {
       if (!selectedModel) return;
       const runId = selectedModel.resource.runId;
-      // "Load on selection" off: stage GGUF picks instead of loading, so the
-      // chat page's staging flow can read the header and show the load options.
-      // Non-GGUF models have nothing to configure pre-load, so they load now.
-      if (
-        !useChatRuntimeStore.getState().loadOnSelection &&
-        (opts.ggufVariant != null || selectedModel.isGguf)
-      ) {
-        useChatRuntimeStore.getState().stageModel({
-          id: runId,
-          ggufVariant: opts.ggufVariant,
-          isGguf: selectedModel.isGguf,
-          isDownloaded,
-          expectedBytes: opts.expectedBytes,
-        });
-        openNewChat();
-        return;
-      }
-      // Detach any leftover staged pick first so its edited knobs (e.g. a custom
-      // context length) don't leak into this load -- mirrors the chat page's
-      // detachStaged(); keepDownload keeps any staged download running.
-      useChatRuntimeStore.getState().abandonStagedModel({ keepDownload: true });
-      // Load-on-selection skips the chat sheet, so seed this GGUF pick's saved
-      // load knobs here the way the sheet's restore effect would; otherwise the
-      // remembered config is silently ignored on the Hub run path. keepSpeculative
-      // then honors the restored speculative choice across the switch.
-      const remembered =
-        opts.ggufVariant != null || selectedModel.isGguf
-          ? loadRememberedLoadSettings(
-              rememberedLoadSettingsKey({
-                id: runId,
-                ggufVariant: opts.ggufVariant,
-              }),
-            )
-          : null;
-      if (remembered) {
-        useChatRuntimeStore.getState().applyRememberedLoadSettings(remembered);
-      }
+      const resolvedConfig = resolveInitialConfig(runId, opts.ggufVariant);
+      const rememberedConfig = resolvedConfig.remembered
+        ? resolvedConfig.config
+        : null;
+      const previousConfig = currentRuntimePerModelConfig({
+        includeMaxSeqLength: true,
+      });
+      const hasAppliedConfig = applyModelLoadConfigToRuntime(rememberedConfig);
       void selectModel({
         id: runId,
         ggufVariant: opts.ggufVariant,
         isDownloaded,
         expectedBytes: opts.expectedBytes,
-        keepSpeculative: remembered != null,
+        keepSpeculative: hasAppliedConfig,
         throwOnError: true,
+        previousConfig,
       })
         .then(() => {
           // Read fresh: the load is async, so the checkpoint may have changed.
@@ -1375,16 +1348,18 @@ export function ModelsPage() {
         </div>
       );
     }
-    const ownerToggle = !isDatasetMode ? (
+    const ownerToggle = isDatasetMode ? undefined : (
       <OwnerScopeToggle value={ownerScope} onChange={setOwnerScope} />
-    ) : undefined;
+    );
     // Compact pill so it stays beside the view-mode tabs even in the narrow
     // split pane instead of dropping to its own row.
     return (
       <div className="flex flex-col gap-3 pt-6">
         {isChannelListMode ? (
           <HubListHeader
-            title={channelSection ? HUB_SECTION_TITLE[channelSection] : "Models"}
+            title={
+              channelSection ? HUB_SECTION_TITLE[channelSection] : "Models"
+            }
             count={listCount}
             view={allModelsView}
             onViewChange={setAllModelsView}
diff --git a/studio/frontend/src/features/hub/index.ts b/studio/frontend/src/features/hub/index.ts
index 3515f6ca76..8a2c0e863b 100644
--- a/studio/frontend/src/features/hub/index.ts
+++ b/studio/frontend/src/features/hub/index.ts
@@ -1,9 +1,65 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-export { cancelStagedModelDownload } from "./download-manager";
+export {
+  cancelModelDownload,
+  downloadManager,
+  jobKeyOf,
+  subscribeJobListeners,
+  useDownloadManagerStore,
+  type TransportConflictInfo,
+} from "./download-manager";
+export {
+  useHubInventory,
+  type CachedInventoryRow,
+  type GgufVariantDetail,
+  type HubInventory,
+  type HubInventoryKind,
+  type InventoryRow,
+  type LocalInventoryRow,
+  type LocalSource,
+  type ScanFolderInfo,
+  addScanFolder,
+  deleteCachedDataset,
+  deleteCachedModel,
+  formatLocalUpdated,
+  listGgufVariants,
+  listScanFolders,
+  removeScanFolder,
+  useGgufVariantsCacheVersion,
+} from "./inventory";
+export {
+  type HfModelResult,
+  type HfModelSearchChannel,
+  type HfSortDirection,
+  type HfSortKey,
+  useHubModelSearch,
+} from "./hooks/use-hub-model-search";
+export { useOnlineStatus } from "./hooks/use-online-status";
+export { useHubInfiniteScroll } from "./hooks/use-hub-infinite-scroll";
 export {
   getHfToken,
+  hfApiToken,
   mirrorHfTokenInto,
   useHfTokenStore,
 } from "./stores/hf-token-store";
+export { looksLikeLocalPath } from "./lib/local-path";
+export { hubTokenHeader } from "./lib/hub-token-header";
+export {
+  ggufVariantsMatch,
+  modelIdsMatch,
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "./lib/model-identity";
+export { formatBytes, formatRelativeShort } from "./lib/format";
+export { ggufVariantDisplayLabel } from "./lib/gguf-variant-sort";
+export {
+  DeleteConfirmDialog,
+  UpdateConfirmDialog,
+} from "./catalog/download-card";
+export { HubOptionMenu, type HubOption } from "./catalog/hub-option-menu";
+export { DotTag } from "./catalog/dot-tag";
+export { TransportConflictDialog } from "./catalog/transport-conflict-dialog";
+export { TrainIcon } from "./components/train-icon";
+export { isHiddenModelId } from "./lib/hidden-models";
+export { classifyUnslothSupport } from "./lib/unsloth-support";
diff --git a/studio/frontend/src/features/hub/inventory/api.ts b/studio/frontend/src/features/hub/inventory/api.ts
index 0e01c5c0cb..8c9214c9e5 100644
--- a/studio/frontend/src/features/hub/inventory/api.ts
+++ b/studio/frontend/src/features/hub/inventory/api.ts
@@ -48,6 +48,7 @@ export interface CachedGgufRepo {
   capabilities?: BackendModelCapabilities | null;
   size_bytes: number;
   cache_path?: string;
+  last_modified?: number | null;
   partial?: boolean;
   partial_transport?: string | null;
   pipeline_tag?: string | null;
@@ -65,6 +66,7 @@ export interface CachedModelRepo {
   capabilities?: BackendModelCapabilities | null;
   size_bytes: number;
   cache_path?: string;
+  last_modified?: number | null;
   partial?: boolean;
   partial_transport?: string | null;
   pipeline_tag?: string | null;
diff --git a/studio/frontend/src/features/hub/inventory/types.ts b/studio/frontend/src/features/hub/inventory/types.ts
index c86ffb1d86..d53d7003fb 100644
--- a/studio/frontend/src/features/hub/inventory/types.ts
+++ b/studio/frontend/src/features/hub/inventory/types.ts
@@ -47,6 +47,7 @@ export interface CachedInventoryRow {
   capabilities: ModelInventoryCapabilities;
   bytes: number;
   cachePath?: string | null;
+  lastModified?: number | null;
   partial?: boolean;
   partialTransport?: string | null;
   pipelineTag?: string | null;
@@ -65,6 +66,8 @@ export interface LocalInventoryRow {
   title: string;
   source: LocalSource;
   sourceLabel: string;
+  modelId?: string | null;
+  displayName?: string;
   path: string;
   isGguf: boolean;
   modelFormat: ModelInventoryFormat;
diff --git a/studio/frontend/src/features/hub/inventory/view-models.ts b/studio/frontend/src/features/hub/inventory/view-models.ts
index 63d70418be..58de6e4c32 100644
--- a/studio/frontend/src/features/hub/inventory/view-models.ts
+++ b/studio/frontend/src/features/hub/inventory/view-models.ts
@@ -176,6 +176,7 @@ export function buildCachedInventoryRow(
     runtime?: string | null;
     format_variant?: string | null;
     capabilities?: BackendModelCapabilities | null;
+    last_modified?: number | null;
   },
   fallbackFormat: ModelInventoryFormat,
 ): CachedInventoryRow {
@@ -210,6 +211,12 @@ export function buildCachedInventoryRow(
     ),
     bytes: row.size_bytes,
     cachePath: row.cache_path ?? null,
+    lastModified:
+      typeof row.last_modified === "number" &&
+      Number.isFinite(row.last_modified) &&
+      row.last_modified > 0
+        ? row.last_modified
+        : null,
     partial: row.partial ?? false,
     partialTransport: row.partial_transport ?? null,
     pipelineTag: row.pipeline_tag ?? null,
@@ -272,6 +279,8 @@ export function buildLocalInventoryRows(
         title,
         source: model.source,
         sourceLabel: localSourceLabel(model.source),
+        modelId: model.model_id ?? null,
+        displayName: model.display_name,
         path: model.path,
         isGguf: modelFormat === "gguf",
         modelFormat,
diff --git a/studio/frontend/src/features/model-picker/api/model-metadata.ts b/studio/frontend/src/features/model-picker/api/model-metadata.ts
new file mode 100644
index 0000000000..098ab51271
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/api/model-metadata.ts
@@ -0,0 +1,20 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { getModelConfig } from "@/features/training";
+
+export async function fetchModelMaxPositionEmbeddings(
+  modelName: string,
+  hfToken?: string | null,
+  signal?: AbortSignal,
+): Promise<number | null> {
+  const config = await getModelConfig(
+    modelName,
+    signal,
+    hfToken?.trim() || undefined,
+  );
+  const value = config.max_position_embeddings;
+  return typeof value === "number" && Number.isFinite(value) && value > 0
+    ? Math.floor(value)
+    : null;
+}
diff --git a/studio/frontend/src/features/model-picker/api/templates.ts b/studio/frontend/src/features/model-picker/api/templates.ts
new file mode 100644
index 0000000000..0f00556f3f
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/api/templates.ts
@@ -0,0 +1,51 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { authFetch } from "@/features/auth";
+import { hubTokenHeader } from "@/features/hub";
+import { readFastApiError } from "@/lib/format-fastapi-error";
+
+export interface ValidateChatTemplateResult {
+  valid: boolean;
+  error: string | null;
+}
+
+async function parseJsonOrThrow<T>(response: Response): Promise<T> {
+  if (!response.ok) {
+    throw new Error(await readFastApiError(response));
+  }
+  return response.json();
+}
+
+export async function validateChatTemplate(
+  template: string,
+  signal?: AbortSignal,
+): Promise<ValidateChatTemplateResult> {
+  const response = await authFetch("/api/picker/validate-chat-template", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ template }),
+    signal,
+  });
+  return parseJsonOrThrow<ValidateChatTemplateResult>(response);
+}
+
+export async function fetchDefaultChatTemplate(
+  modelName: string,
+  ggufVariant?: string | null,
+  hfToken?: string | null,
+  signal?: AbortSignal,
+): Promise<string | null> {
+  const query = ggufVariant
+    ? `?gguf_variant=${encodeURIComponent(ggufVariant)}`
+    : "";
+  const response = await authFetch(
+    `/api/picker/chat-template/${encodeURIComponent(modelName)}${query}`,
+    { headers: hubTokenHeader(hfToken), signal },
+  );
+  const data = await parseJsonOrThrow<{
+    model_name: string;
+    chat_template: string | null;
+  }>(response);
+  return data.chat_template ?? null;
+}
diff --git a/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx b/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
new file mode 100644
index 0000000000..65e5a2026d
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
@@ -0,0 +1,191 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { Button } from "@/components/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import { Spinner } from "@/components/ui/spinner";
+import { Textarea } from "@/components/ui/textarea";
+import { useRef, useState } from "react";
+import { validateChatTemplate } from "../api/templates";
+import {
+  MAX_CHAT_TEMPLATE_BYTES,
+  chatTemplateByteLength,
+  isChatTemplateWithinLimit,
+} from "../model-config/per-model-config";
+
+interface ChatTemplateEditorDialogProps {
+  open: boolean;
+  onOpenChange: (open: boolean) => void;
+  value: string | null;
+  defaultTemplate: string | null;
+  defaultLoading: boolean;
+  onSave: (override: string | null) => void;
+  readOnly?: boolean;
+}
+
+export function ChatTemplateEditorDialog({
+  open,
+  onOpenChange,
+  value,
+  defaultTemplate,
+  defaultLoading,
+  onSave,
+  readOnly = false,
+}: ChatTemplateEditorDialogProps) {
+  const [draft, setDraft] = useState<string | null>(null);
+  const [error, setError] = useState<string | null>(null);
+  const [validating, setValidating] = useState(false);
+  // Bumped whenever the dialog closes so a validation still in flight cannot
+  // apply a template the user has already dismissed.
+  const validationToken = useRef(0);
+  const renderedDraft = draft ?? value ?? defaultTemplate ?? "";
+
+  const byteLength = chatTemplateByteLength(renderedDraft);
+  const overLimit = !isChatTemplateWithinLimit(renderedDraft);
+  const matchesDefault =
+    defaultTemplate != null && renderedDraft === defaultTemplate;
+
+  const handleClose = () => {
+    validationToken.current += 1;
+    setDraft(null);
+    setError(null);
+    setValidating(false);
+    onOpenChange(false);
+  };
+
+  const handleSave = async () => {
+    if (renderedDraft.trim().length === 0 || matchesDefault) {
+      onSave(null);
+      handleClose();
+      return;
+    }
+    if (overLimit) {
+      setError("Template exceeds the size limit.");
+      return;
+    }
+    setValidating(true);
+    const token = validationToken.current;
+    try {
+      const result = await validateChatTemplate(renderedDraft);
+      // Dialog was closed (or reopened) while validating; drop the result so a
+      // discarded template is never applied.
+      if (token !== validationToken.current) {
+        return;
+      }
+      if (!result.valid) {
+        setError(result.error ?? "Invalid Jinja template.");
+        return;
+      }
+      onSave(renderedDraft);
+      handleClose();
+    } catch {
+      if (token === validationToken.current) {
+        setError("Could not validate the template.");
+      }
+    } finally {
+      if (token === validationToken.current) {
+        setValidating(false);
+      }
+    }
+  };
+
+  return (
+    <Dialog
+      open={open}
+      onOpenChange={(nextOpen) => {
+        if (nextOpen) {
+          onOpenChange(true);
+          return;
+        }
+        handleClose();
+      }}
+    >
+      <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-3xl">
+        <DialogHeader>
+          <DialogTitle>
+            {readOnly ? "Chat Template" : "Edit Chat Template"}
+          </DialogTitle>
+          <DialogDescription>
+            {readOnly
+              ? "This is the model's chat template. Custom templates apply to GGUF models for now, so it is view only for safetensors models."
+              : "Override the model's chat template with custom Jinja. The change applies when the model loads. Saving an empty template or one that matches the default clears the override."}
+          </DialogDescription>
+        </DialogHeader>
+        <Textarea
+          value={renderedDraft}
+          onChange={(event) => {
+            if (readOnly) return;
+            setDraft(event.target.value);
+            setError(null);
+          }}
+          readOnly={readOnly}
+          className="min-h-[20rem] max-h-[50vh] overflow-y-auto border-0 font-mono text-xs leading-5 corner-squircle focus-visible:ring-0"
+          rows={14}
+          spellCheck={false}
+          placeholder={defaultLoading ? "Loading model default..." : ""}
+        />
+        {readOnly ? null : (
+          <div className="flex items-center justify-between gap-3 px-0.5 text-[11px]">
+            <span
+              className={overLimit ? "text-amber-500" : "text-muted-foreground"}
+            >
+              {byteLength.toLocaleString()} /{" "}
+              {MAX_CHAT_TEMPLATE_BYTES.toLocaleString()} bytes
+            </span>
+            {error ? (
+              <span className="truncate text-red-500" title={error}>
+                {error}
+              </span>
+            ) : null}
+          </div>
+        )}
+        <DialogFooter className="flex-wrap gap-2 sm:justify-between">
+          {readOnly ? (
+            <div className="flex w-full justify-end">
+              <Button type="button" onClick={handleClose}>
+                Close
+              </Button>
+            </div>
+          ) : (
+            <>
+              <Button
+                type="button"
+                variant="ghost"
+                onClick={() => setDraft(defaultTemplate ?? "")}
+                disabled={
+                  defaultLoading || renderedDraft === (defaultTemplate ?? "")
+                }
+                className="text-muted-foreground"
+              >
+                {defaultLoading ? (
+                  <Spinner className="size-3.5" />
+                ) : (
+                  "Reset to default"
+                )}
+              </Button>
+              <div className="flex gap-2">
+                <Button type="button" variant="ghost" onClick={handleClose}>
+                  Cancel
+                </Button>
+                <Button
+                  type="button"
+                  onClick={handleSave}
+                  disabled={validating || overLimit}
+                >
+                  {validating ? "Validating..." : "Save"}
+                </Button>
+              </div>
+            </>
+          )}
+        </DialogFooter>
+      </DialogContent>
+    </Dialog>
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/components/model-config-page.tsx b/studio/frontend/src/features/model-picker/components/model-config-page.tsx
new file mode 100644
index 0000000000..85ce5ccf8d
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/model-config-page.tsx
@@ -0,0 +1,742 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { Button } from "@/components/ui/button";
+import { Checkbox } from "@/components/ui/checkbox";
+import { InfoHint } from "@/components/ui/info-hint";
+import {
+  Select,
+  SelectContent,
+  SelectItem,
+  SelectTrigger,
+  SelectValue,
+} from "@/components/ui/select";
+import { Slider } from "@/components/ui/slider";
+import { Switch } from "@/components/ui/switch";
+import {
+  fetchGgufContextLength,
+  readPersistedSpeculativeType,
+  useChatRuntimeStore,
+} from "@/features/chat";
+import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
+import { toast } from "@/lib/toast";
+import { ArrowLeft01Icon } from "@hugeicons/core-free-icons";
+import { HugeiconsIcon } from "@hugeicons/react";
+import { useEffect, useId, useState } from "react";
+import {
+  useDefaultChatTemplate,
+  useModelMaxPositionEmbeddings,
+} from "../hooks/use-model-defaults";
+import { perModelConfigsEqual } from "../model-config/apply-per-model-config";
+import {
+  DEFAULT_PER_MODEL_CONFIG,
+  KV_CACHE_DTYPES,
+  MAX_SEQ_LENGTH_MAX,
+  MAX_SEQ_LENGTH_MIN,
+  MAX_SEQ_LENGTH_STEP,
+  MTP_SPECULATIVE_TYPES,
+  type PerModelConfig,
+  SPECULATIVE_TYPES,
+  deletePerModelConfig,
+  isDefaultConfig,
+  normalizeMaxSeqLength,
+  resolveInitialConfig,
+  savePerModelConfig,
+} from "../model-config/per-model-config";
+import { ChatTemplateEditorDialog } from "./chat-template-editor-dialog";
+import type { ModelPickTarget } from "./model-selector/types";
+import { NumericValueInput } from "./numeric-value-input";
+
+const ROW_CLASS = "flex min-h-8 items-center justify-between gap-3";
+const LABEL_CLASS =
+  "min-w-0 truncate text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg";
+const LABEL_CLASS_WRAP =
+  "min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg";
+const CONTROL_SURFACE =
+  "rounded-full border-transparent bg-black/[0.04] dark:bg-white/[0.05] hover:bg-black/[0.06] dark:hover:bg-white/[0.1]";
+const SELECT_TRIGGER_CLASS = `grid h-8 min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 ${CONTROL_SURFACE} pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0`;
+const NUMBER_INPUT_CLASS = `h-8 w-[92px] ${CONTROL_SURFACE} pl-3 pr-2 py-0 text-right text-[13px] font-medium text-nav-fg outline-none focus-visible:ring-0`;
+
+const KV_CACHE_DTYPE_DEFAULT = "f16";
+const SPECULATIVE_TYPE_LABELS: Record<(typeof SPECULATIVE_TYPES)[number], string> =
+  {
+    auto: "Auto",
+    mtp: "MTP",
+    ngram: "Ngram",
+    "mtp+ngram": "MTP+Ngram",
+    off: "Off",
+  };
+
+function hasNonDefaultAdvanced(config: PerModelConfig): boolean {
+  return (
+    config.kvCacheDtype != null ||
+    (config.speculativeType ?? "auto") !== "auto" ||
+    config.specDraftNMax != null ||
+    config.tensorParallel ||
+    config.chatTemplateOverride != null
+  );
+}
+
+function resolveCustomContextLength(
+  value: number,
+  native: number | null,
+): number | null {
+  return native != null && value === native ? null : value;
+}
+
+function ChatTemplateSetting({
+  config,
+  onEditTemplate,
+  readOnly = false,
+}: {
+  config: PerModelConfig;
+  onEditTemplate: () => void;
+  readOnly?: boolean;
+}) {
+  return (
+    <div className={ROW_CLASS}>
+      <div className="flex min-w-0 items-center gap-1.5">
+        <span className={LABEL_CLASS}>Chat Template</span>
+        <InfoHint>
+          {readOnly
+            ? "Preview the model's chat template. Custom overrides apply to GGUF models for now."
+            : "Override the model's chat template with custom Jinja. Applies when the model loads."}
+        </InfoHint>
+      </div>
+      <div className="flex shrink-0 items-center gap-2">
+        {readOnly ? null : (
+          <span className="text-[12px] text-muted-foreground">
+            {config.chatTemplateOverride ? "Custom" : "Default"}
+          </span>
+        )}
+        <Button
+          type="button"
+          size="sm"
+          variant="ghost"
+          className={`h-8 px-3 text-[13px] ${CONTROL_SURFACE}`}
+          onClick={onEditTemplate}
+        >
+          {readOnly ? "View" : "Edit"}
+        </Button>
+      </div>
+    </div>
+  );
+}
+
+function MaxSeqLengthSetting({
+  value,
+  max,
+  inputMax,
+  onChange,
+}: {
+  value: number;
+  max: number;
+  inputMax: number;
+  onChange: (value: number) => void;
+}) {
+  return (
+    <div className="space-y-3">
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>Max Seq Length</span>
+          <InfoHint>
+            Maximum context window size in tokens. Applies when the model loads.
+          </InfoHint>
+        </div>
+        <NumericValueInput
+          value={value}
+          min={MAX_SEQ_LENGTH_MIN}
+          max={inputMax}
+          step={MAX_SEQ_LENGTH_STEP}
+          onChange={onChange}
+          ariaLabel="Max Seq Length"
+          className={NUMBER_INPUT_CLASS}
+          size={8}
+        />
+      </div>
+      <Slider
+        min={MAX_SEQ_LENGTH_MIN}
+        max={max}
+        step={MAX_SEQ_LENGTH_STEP}
+        value={[value]}
+        onValueChange={([next]) => onChange(next)}
+        className="panel-slider"
+        aria-label="Max Seq Length"
+      />
+    </div>
+  );
+}
+
+function clampMaxSeqLength(value: number, max: number): number {
+  const normalized = normalizeMaxSeqLength(value) ?? MAX_SEQ_LENGTH_MIN;
+  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(max, normalized));
+}
+
+function GgufAdvancedSettings({
+  config,
+  update,
+  isMtp,
+  speculativeFallback,
+  onEditTemplate,
+}: {
+  config: PerModelConfig;
+  update: (patch: Partial<PerModelConfig>) => void;
+  isMtp: boolean;
+  speculativeFallback: string;
+  onEditTemplate: () => void;
+}) {
+  return (
+    <>
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>KV Cache Dtype</span>
+          <InfoHint>
+            Lower KV cache precision to save VRAM at the cost of some quality.
+            f16/bf16 are full precision; q8_0/q5_1/q4_1 are quantized.
+          </InfoHint>
+        </div>
+        <Select
+          value={config.kvCacheDtype ?? KV_CACHE_DTYPE_DEFAULT}
+          onValueChange={(v) =>
+            update({ kvCacheDtype: v === KV_CACHE_DTYPE_DEFAULT ? null : v })
+          }
+        >
+          <SelectTrigger
+            animateRadius={false}
+            icon={ChevronDownStandardIcon}
+            iconClassName="size-3.5"
+            className={`w-[92px] ${SELECT_TRIGGER_CLASS}`}
+          >
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+            <SelectItem value={KV_CACHE_DTYPE_DEFAULT}>
+              {KV_CACHE_DTYPE_DEFAULT}
+            </SelectItem>
+            {KV_CACHE_DTYPES.map((dtype) => (
+              <SelectItem key={dtype} value={dtype}>
+                {dtype}
+              </SelectItem>
+            ))}
+          </SelectContent>
+        </Select>
+      </div>
+
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS_WRAP}>Speculative Decoding</span>
+          <InfoHint>
+            Faster generation with no accuracy hit. Auto picks MTP / ngram based
+            on the model and platform. Pick a strategy to force it.
+          </InfoHint>
+        </div>
+        <Select
+          value={config.speculativeType ?? speculativeFallback}
+          onValueChange={(v) =>
+            update({
+              speculativeType: v,
+              specDraftNMax:
+                v === "mtp" || v === "mtp+ngram" ? config.specDraftNMax : null,
+            })
+          }
+        >
+          <SelectTrigger
+            animateRadius={false}
+            icon={ChevronDownStandardIcon}
+            iconClassName="size-3.5"
+            className={`w-[124px] shrink-0 ${SELECT_TRIGGER_CLASS}`}
+          >
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+            {SPECULATIVE_TYPES.map((type) => (
+              <SelectItem key={type} value={type}>
+                {SPECULATIVE_TYPE_LABELS[type]}
+              </SelectItem>
+            ))}
+          </SelectContent>
+        </Select>
+      </div>
+
+      {isMtp && (
+        <div className={ROW_CLASS}>
+          <div className="flex min-w-0 items-center gap-1.5">
+            <span className={LABEL_CLASS}>Draft Tokens</span>
+            <InfoHint>
+              Max MTP draft tokens per step. Leave blank for the platform
+              default (2 on GPU, 3 on CPU/Mac).
+            </InfoHint>
+          </div>
+          <input
+            type="number"
+            min={1}
+            max={16}
+            step={1}
+            value={config.specDraftNMax ?? ""}
+            placeholder="auto"
+            onChange={(event) => {
+              const raw = event.target.value;
+              if (raw === "") {
+                update({ specDraftNMax: null });
+                return;
+              }
+              const parsed = Number.parseInt(raw, 10);
+              if (Number.isFinite(parsed)) {
+                update({ specDraftNMax: Math.max(1, Math.min(16, parsed)) });
+              }
+            }}
+            aria-label="Speculative decoding draft tokens"
+            className={NUMBER_INPUT_CLASS}
+          />
+        </div>
+      )}
+
+      <div className={ROW_CLASS}>
+        <div className="flex min-w-0 items-center gap-1.5">
+          <span className={LABEL_CLASS}>Tensor Parallelism</span>
+          <InfoHint>
+            No effect on a single GPU. On multi-GPU setups, improves tokens/sec
+            for dense models. MoE models don't benefit.
+          </InfoHint>
+        </div>
+        <Switch
+          className="panel-switch shrink-0"
+          checked={config.tensorParallel}
+          onCheckedChange={(checked) => update({ tensorParallel: checked })}
+        />
+      </div>
+
+      <ChatTemplateSetting config={config} onEditTemplate={onEditTemplate} />
+    </>
+  );
+}
+
+interface ModelConfigPageProps {
+  target: ModelPickTarget;
+  onBack?: () => void;
+  onRun: (config: PerModelConfig) => void;
+  loadedConfig?: PerModelConfig | null;
+  loadedContextLength?: number | null;
+  initialConfig?: PerModelConfig | null;
+  variant?: "page" | "sidebar";
+}
+
+export function ModelConfigPage({
+  target,
+  onBack,
+  onRun,
+  loadedConfig = null,
+  loadedContextLength = null,
+  initialConfig = null,
+  variant = "page",
+}: ModelConfigPageProps) {
+  const rememberId = useId();
+  const isActiveModel = loadedConfig != null;
+  const runtimeMaxSeqLength = useChatRuntimeStore((s) => s.params.maxSeqLength);
+  const hfToken = useChatRuntimeStore((s) => s.hfToken);
+  const loadedDefaultChatTemplate = useChatRuntimeStore(
+    (s) => s.defaultChatTemplate,
+  );
+  const loadedMaxContextLength = useChatRuntimeStore(
+    (s) => s.ggufMaxContextLength,
+  );
+  // Only the active model seeds its max sequence length from the loaded
+  // runtime params. A different, unloaded model with no saved config seeds the
+  // app default instead, so opening its settings and loading does not inherit
+  // the currently loaded model's context.
+  const [initialMaxSeqLength] = useState(() =>
+    isActiveModel ? (normalizeMaxSeqLength(runtimeMaxSeqLength) ?? 4096) : 4096,
+  );
+  const resolveInitial = () => {
+    const resolved = resolveInitialConfig(target.id, target.ggufVariant);
+    if (loadedConfig) {
+      return { config: loadedConfig, remembered: resolved.remembered };
+    }
+    if (initialConfig) {
+      return {
+        config: initialConfig,
+        remembered:
+          resolved.remembered &&
+          perModelConfigsEqual(initialConfig, resolved.config),
+      };
+    }
+    return resolved;
+  };
+  const [initial] = useState(resolveInitial);
+  const [config, setConfig] = useState<PerModelConfig>(() => initial.config);
+  const [remember, setRemember] = useState(() => initial.remembered);
+  const [savedRemember, setSavedRemember] = useState(() => initial.remembered);
+  const [speculativeFallback] = useState(readPersistedSpeculativeType);
+  const [templateOpen, setTemplateOpen] = useState(false);
+  const [showAdvanced, setShowAdvanced] = useState(() =>
+    hasNonDefaultAdvanced(config),
+  );
+  const templateDefaults = useDefaultChatTemplate(
+    target.id,
+    target.ggufVariant,
+    templateOpen,
+  );
+  const modelMaxPosition = useModelMaxPositionEmbeddings(
+    target.id,
+    !target.isGguf,
+  );
+  const hasLoadedDefaultTemplate =
+    isActiveModel && loadedDefaultChatTemplate != null;
+  const resolvedDefaultTemplate = hasLoadedDefaultTemplate
+    ? loadedDefaultChatTemplate
+    : templateDefaults.template;
+  const resolvedDefaultLoading = hasLoadedDefaultTemplate
+    ? false
+    : templateDefaults.loading;
+
+  const update = (patch: Partial<PerModelConfig>) =>
+    setConfig((current) => ({ ...current, ...patch }));
+
+  const contextFetchKey =
+    target.isGguf && target.meta.contextLength == null
+      ? `${target.id}\n${target.ggufVariant ?? ""}\n${hfToken || ""}`
+      : null;
+  const [fetchedContextLength, setFetchedContextLength] = useState<{
+    key: string;
+    value: number | null;
+  } | null>(null);
+  useEffect(() => {
+    if (contextFetchKey == null) {
+      return;
+    }
+    let cancelled = false;
+    void fetchGgufContextLength({
+      model_path: target.id,
+      gguf_variant: target.ggufVariant ?? null,
+      hf_token: hfToken || null,
+    })
+      .then((contextLength) => {
+        if (!cancelled) {
+          setFetchedContextLength({
+            key: contextFetchKey,
+            value: contextLength,
+          });
+        }
+      })
+      .catch(() => {
+        if (!cancelled) {
+          setFetchedContextLength({ key: contextFetchKey, value: null });
+        }
+      });
+    return () => {
+      cancelled = true;
+    };
+  }, [contextFetchKey, target.id, target.ggufVariant, hfToken]);
+
+  const isMtp =
+    config.speculativeType != null &&
+    MTP_SPECULATIVE_TYPES.has(config.speculativeType);
+  const nativeContextLength =
+    target.meta.contextLength ??
+    (fetchedContextLength?.key === contextFetchKey
+      ? fetchedContextLength.value
+      : null);
+  const activeLoadedContext =
+    isActiveModel && target.isGguf ? loadedContextLength : null;
+  const minContext = 128;
+  const maxContext = Math.max(
+    minContext,
+    Math.max(
+      nativeContextLength ?? 0,
+      activeLoadedContext ?? 0,
+      config.customContextLength ?? 0,
+    ) || 32768,
+  );
+  const contextValue = Math.min(
+    Math.max(
+      config.customContextLength ??
+        activeLoadedContext ??
+        nativeContextLength ??
+        maxContext,
+      minContext,
+    ),
+    maxContext,
+  );
+  const setContextLength = (v: number) =>
+    update({
+      customContextLength:
+        nativeContextLength != null && v === nativeContextLength ? null : v,
+    });
+  const baseline = loadedConfig ?? DEFAULT_PER_MODEL_CONFIG;
+  const atBaseline = perModelConfigsEqual(config, baseline);
+  const contextAtDefault =
+    !target.isGguf ||
+    (nativeContextLength == null
+      ? config.customContextLength == null
+      : contextValue === nativeContextLength);
+  const atDefault =
+    contextAtDefault &&
+    perModelConfigsEqual(
+      { ...config, customContextLength: null },
+      DEFAULT_PER_MODEL_CONFIG,
+    );
+  const nativeMaxSeqLength =
+    normalizeMaxSeqLength(modelMaxPosition.maxPositionEmbeddings) ??
+    MAX_SEQ_LENGTH_MAX;
+  const maxSeqLengthValue =
+    normalizeMaxSeqLength(config.maxSeqLength) ??
+    clampMaxSeqLength(initialMaxSeqLength, nativeMaxSeqLength);
+  const maxSeqLengthMax = Math.max(nativeMaxSeqLength, maxSeqLengthValue);
+  const runtimeConfig = target.isGguf
+    ? {
+        ...config,
+        // Persist the user's intent collapsed against native (not the loaded
+        // context, which equals the override): an explicit sub-native value is
+        // kept, "at native" becomes null. null stays null (auto/VRAM-fit).
+        customContextLength:
+          config.customContextLength == null
+            ? null
+            : resolveCustomContextLength(
+                config.customContextLength,
+                nativeContextLength,
+              ),
+      }
+    : {
+        ...config,
+        maxSeqLength: maxSeqLengthValue,
+      };
+  const rememberChanged = remember !== savedRemember;
+  const persistenceOnly = isActiveModel && atBaseline && rememberChanged;
+  const primaryActionLabel = persistenceOnly
+    ? remember
+      ? "Save settings"
+      : "Forget settings"
+    : isActiveModel
+      ? "Reload model"
+      : "Load model";
+
+  const handleRun = () => {
+    const defaultConfig = isDefaultConfig(runtimeConfig);
+    let saveFailed = false;
+    if (remember) {
+      saveFailed = !savePerModelConfig(
+        target.id,
+        target.ggufVariant,
+        runtimeConfig,
+      );
+    } else {
+      saveFailed = !deletePerModelConfig(target.id, target.ggufVariant);
+    }
+    if (persistenceOnly) {
+      if (saveFailed) {
+        toast.error("Couldn't save settings for this model.");
+        return;
+      }
+      const nextRemember = remember && !defaultConfig;
+      setSavedRemember(nextRemember);
+      setRemember(nextRemember);
+      toast.success(
+        nextRemember
+          ? "Settings saved."
+          : remember
+            ? "Default settings kept."
+            : "Settings forgotten.",
+      );
+      return;
+    }
+    if (saveFailed) {
+      toast.error("Couldn't save these settings, loading with them anyway.");
+    }
+    onRun(runtimeConfig);
+  };
+
+  return (
+    <div className="flex flex-col">
+      {variant === "page" && (
+        <div className="flex items-center gap-2.5 pb-4">
+          {onBack && (
+            <button
+              type="button"
+              onClick={onBack}
+              className="nav-icon-btn shrink-0 text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
+              aria-label="Back to model list"
+            >
+              <HugeiconsIcon
+                icon={ArrowLeft01Icon}
+                className="size-4"
+                strokeWidth={1.75}
+              />
+            </button>
+          )}
+          <div className="min-w-0 flex-1">
+            <div className="text-[10px] font-semibold uppercase leading-none tracking-wider text-muted-foreground">
+              Run settings
+            </div>
+            <div className="mt-1.5 truncate text-[14px] font-semibold leading-tight text-nav-fg">
+              {target.displayName}
+            </div>
+          </div>
+        </div>
+      )}
+
+      <div className="space-y-3.5">
+        {target.isGguf && (
+          <>
+            <div className="space-y-3">
+              <div className={ROW_CLASS}>
+                <div className="flex min-w-0 items-center gap-1.5">
+                  <span className={LABEL_CLASS}>Context Length</span>
+                  <InfoHint>
+                    Tokens of context to allocate. Higher uses more VRAM.
+                    {nativeContextLength != null
+                      ? ` This model's native context is ${nativeContextLength.toLocaleString()} tokens.`
+                      : ""}
+                  </InfoHint>
+                </div>
+                <NumericValueInput
+                  value={contextValue}
+                  min={minContext}
+                  max={maxContext}
+                  step={1}
+                  onChange={setContextLength}
+                  ariaLabel="Context Length"
+                  className={NUMBER_INPUT_CLASS}
+                  size={8}
+                />
+              </div>
+              {nativeContextLength != null ? (
+                <Slider
+                  min={minContext}
+                  max={maxContext}
+                  step={128}
+                  value={[contextValue]}
+                  onValueChange={([v]) => setContextLength(v)}
+                  className="panel-slider"
+                  aria-label="Context Length"
+                />
+              ) : null}
+              {isActiveModel &&
+                loadedMaxContextLength != null &&
+                contextValue > loadedMaxContextLength && (
+                  <p className="text-[11px] text-amber-500">
+                    Exceeds estimated VRAM capacity (
+                    {loadedMaxContextLength.toLocaleString()} tokens). The model
+                    may use system RAM.
+                  </p>
+                )}
+            </div>
+
+            {showAdvanced && (
+              <GgufAdvancedSettings
+                config={config}
+                update={update}
+                isMtp={isMtp}
+                speculativeFallback={speculativeFallback}
+                onEditTemplate={() => setTemplateOpen(true)}
+              />
+            )}
+
+            <div className={ROW_CLASS}>
+              <div className="flex min-w-0 items-center gap-1.5">
+                <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-muted-foreground">
+                  Advanced settings
+                </span>
+                <InfoHint>
+                  Extra options for how the model loads. Most setups don't need
+                  these.
+                </InfoHint>
+              </div>
+              <Switch
+                className="panel-switch shrink-0"
+                checked={showAdvanced}
+                onCheckedChange={setShowAdvanced}
+                aria-label="Show advanced settings"
+              />
+            </div>
+          </>
+        )}
+        {!target.isGguf && (
+          <>
+            <MaxSeqLengthSetting
+              value={maxSeqLengthValue}
+              max={maxSeqLengthMax}
+              inputMax={MAX_SEQ_LENGTH_MAX}
+              onChange={(value) =>
+                update({
+                  maxSeqLength: clampMaxSeqLength(value, MAX_SEQ_LENGTH_MAX),
+                })
+              }
+            />
+            <ChatTemplateSetting
+              config={config}
+              onEditTemplate={() => setTemplateOpen(true)}
+              readOnly={true}
+            />
+          </>
+        )}
+      </div>
+
+      <div
+        className={
+          variant === "sidebar"
+            ? "mt-4 flex flex-col gap-3 border-t border-border/60 pt-4"
+            : "mt-4 flex items-center justify-between gap-3 border-t border-border/60 pt-4"
+        }
+      >
+        <div className="flex min-w-0 items-center gap-2">
+          <Checkbox
+            id={rememberId}
+            checked={remember}
+            onCheckedChange={(checked) => setRemember(checked === true)}
+          />
+          <label
+            htmlFor={rememberId}
+            className="cursor-pointer select-none truncate text-[13px] text-nav-fg"
+          >
+            Remember for this model
+          </label>
+        </div>
+        <div
+          className={
+            variant === "sidebar"
+              ? "flex items-center justify-end gap-2"
+              : "flex shrink-0 items-center gap-2"
+          }
+        >
+          <Button
+            type="button"
+            variant="ghost"
+            size="sm"
+            className="h-8"
+            disabled={atDefault}
+            onClick={() =>
+              setConfig({
+                ...DEFAULT_PER_MODEL_CONFIG,
+                customContextLength:
+                  target.isGguf && nativeContextLength != null
+                    ? nativeContextLength
+                    : null,
+              })
+            }
+          >
+            Reset
+          </Button>
+          <Button
+            type="button"
+            size="sm"
+            className="h-8"
+            disabled={isActiveModel && atBaseline && !rememberChanged}
+            onClick={handleRun}
+          >
+            {primaryActionLabel}
+          </Button>
+        </div>
+      </div>
+
+      <ChatTemplateEditorDialog
+        open={templateOpen}
+        onOpenChange={setTemplateOpen}
+        value={config.chatTemplateOverride}
+        defaultTemplate={resolvedDefaultTemplate}
+        defaultLoading={resolvedDefaultLoading}
+        readOnly={!target.isGguf}
+        onSave={(override) => update({ chatTemplateOverride: override })}
+      />
+    </div>
+  );
+}
diff --git a/studio/frontend/src/components/assistant-ui/model-selector.tsx b/studio/frontend/src/features/model-picker/components/model-selector.tsx
similarity index 86%
rename from studio/frontend/src/components/assistant-ui/model-selector.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector.tsx
index 6bfd1276ac..7efcf69162 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector.tsx
@@ -3,6 +3,7 @@
 
 "use client";
 
+import { Input } from "@/components/ui/input";
 import {
   Popover,
   PopoverContent,
@@ -10,7 +11,7 @@ import {
 } from "@/components/ui/popover";
 import { TooltipProvider } from "@/components/ui/tooltip";
 import { usePlatformStore } from "@/config/env";
-import { isCustomProviderType } from "@/features/chat/external-providers";
+import { isCustomProviderType } from "@/features/chat";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { cn } from "@/lib/utils";
 import {
@@ -33,7 +34,11 @@ import {
   useRef,
   useState,
 } from "react";
-import { Input } from "../ui/input";
+import {
+  type PerModelConfig,
+  resolveInitialConfig,
+} from "../model-config/per-model-config";
+import { ModelConfigPage } from "./model-config-page";
 import { HubModelPicker, hasDownloadedModels } from "./model-selector/pickers";
 import { PillTabs } from "./model-selector/pill-tabs";
 import {
@@ -45,6 +50,7 @@ import type {
   ExternalModelOption,
   LoraModelOption,
   ModelOption,
+  ModelPickTarget,
   ModelSelectorChangeMeta,
 } from "./model-selector/types";
 
@@ -122,6 +128,10 @@ interface ModelSelectorProps {
   value?: string;
   defaultValue?: string;
   activeGgufVariant?: string | null;
+  activeModelConfig?: PerModelConfig | null;
+  activeGgufContextLength?: number | null;
+  selectedConfig?: PerModelConfig | null;
+  selectedGgufVariant?: string | null;
   onValueChange?: (value: string, meta: ModelSelectorChangeMeta) => void;
   onEject?: () => void;
   onFoldersChange?: () => void;
@@ -285,7 +295,8 @@ function saveLastHubSection(section: HubSection): void {
 // when they have downloads, else Recommended.
 function defaultHubSection(): HubSection {
   return (
-    loadLastHubSection() ?? (hasDownloadedModels() ? "downloaded" : "recommended")
+    loadLastHubSection() ??
+    (hasDownloadedModels() ? "downloaded" : "recommended")
   );
 }
 
@@ -308,6 +319,11 @@ function ModelSelectorContent({
   loraModels,
   externalModels,
   value,
+  activeGgufVariant,
+  activeModelConfig,
+  activeGgufContextLength,
+  selectedConfig,
+  selectedGgufVariant,
   onSelect,
   onEject,
   onFoldersChange,
@@ -323,6 +339,11 @@ function ModelSelectorContent({
   loraModels: LoraModelOption[];
   externalModels: ExternalModelOption[];
   value?: string;
+  activeGgufVariant?: string | null;
+  activeModelConfig?: PerModelConfig | null;
+  activeGgufContextLength?: number | null;
+  selectedConfig?: PerModelConfig | null;
+  selectedGgufVariant?: string | null;
   onSelect: (id: string, meta: ModelSelectorChangeMeta) => void;
   onEject?: () => void;
   onFoldersChange?: () => void;
@@ -391,6 +412,10 @@ function ModelSelectorContent({
   const effectiveHubSection: HubSection =
     hubSection === "connected" && !hasExternal ? "recommended" : hubSection;
 
+  const [configTarget, setConfigTarget] = useState<ModelPickTarget | null>(
+    null,
+  );
+
   // The picker below remounts on each open, but this tab state does not, so a
   // persisted selection that lands in lora/external after async load would
   // reopen on Hub. Re-derive the default tab on the open edge.
@@ -402,6 +427,9 @@ function ModelSelectorContent({
       // user has downloads, else their last section.
       setHubSection(wantsConnectedDefault ? "connected" : defaultHubSection());
     }
+    if (!open && wasOpen.current) {
+      setConfigTarget(null);
+    }
     wasOpen.current = open;
   }, [
     open,
@@ -452,6 +480,29 @@ function ModelSelectorContent({
     }
   }
 
+  const visibleConfigTarget = open ? configTarget : null;
+  const openConfigPage = (id: string, meta: ModelSelectorChangeMeta) => {
+    const leaf = id.includes("/") ? id.slice(id.lastIndexOf("/") + 1) : id;
+    setConfigTarget({
+      id,
+      displayName: meta.ggufVariant ? `${leaf} · ${meta.ggufVariant}` : leaf,
+      ggufVariant: meta.ggufVariant ?? null,
+      isGguf: meta.isGguf ?? Boolean(meta.ggufVariant),
+      meta,
+    });
+  };
+  const handlePick = (id: string, meta: ModelSelectorChangeMeta) => {
+    if (meta.source === "external") {
+      onSelect(id, meta);
+      return;
+    }
+    const resolved = resolveInitialConfig(id, meta.ggufVariant);
+    onSelect(id, {
+      ...meta,
+      ...(resolved.remembered ? { config: resolved.config } : {}),
+    });
+  };
+
   return (
     <PopoverContent
       align="start"
@@ -459,12 +510,17 @@ function ModelSelectorContent({
       data-tour={dataTour}
       onKeyDown={handlePickerEntryKeyDown}
       className={cn(
-        "unsloth-model-selector-menu menu-soft-surface ring-0 max-w-[calc(100vw-1rem)] min-w-0 gap-0 pt-4 pb-0 pl-4",
-        // Sized so the left-packed row keeps uniform gaps and the last dropdown's
-        // right gap matches the pill's left gap (pl-4 vs pr-4).
-        hasExternal
-          ? "w-[min(614px,calc(100vw-1rem))] pr-4"
-          : "w-[min(506px,calc(100vw-1rem))] pr-2",
+        "unsloth-model-selector-menu menu-soft-surface ring-0 max-w-[calc(100vw-1rem)] min-w-0 gap-0",
+        visibleConfigTarget
+          ? "w-[min(468px,calc(100vw-1rem))] px-4 pt-4 pb-4"
+          : cn(
+              "pt-4 pb-0 pl-4",
+              // Sized so the left-packed row keeps uniform gaps and the last
+              // dropdown's right gap matches the pill's left gap (pl-4 vs pr-4).
+              hasExternal
+                ? "w-[min(614px,calc(100vw-1rem))] pr-4"
+                : "w-[min(506px,calc(100vw-1rem))] pr-2",
+            ),
         className,
       )}
     >
@@ -477,6 +533,42 @@ function ModelSelectorContent({
         skipDelayDuration={0}
         disableHoverableContent={true}
       >
+        {visibleConfigTarget ? (
+          <ModelConfigPage
+            key={`${visibleConfigTarget.id}::${visibleConfigTarget.ggufVariant ?? ""}`}
+            target={visibleConfigTarget}
+            onBack={() => setConfigTarget(null)}
+            onRun={(config) =>
+              onSelect(visibleConfigTarget.id, {
+                ...visibleConfigTarget.meta,
+                config,
+                forceReload: true,
+              })
+            }
+            loadedConfig={
+              value === visibleConfigTarget.id &&
+              (activeGgufVariant ?? null) ===
+                (visibleConfigTarget.ggufVariant ?? null)
+                ? (activeModelConfig ?? null)
+                : null
+            }
+            loadedContextLength={
+              value === visibleConfigTarget.id &&
+              (activeGgufVariant ?? null) ===
+                (visibleConfigTarget.ggufVariant ?? null)
+                ? (activeGgufContextLength ?? null)
+                : null
+            }
+            initialConfig={
+              value === visibleConfigTarget.id &&
+              (selectedGgufVariant ?? null) ===
+                (visibleConfigTarget.ggufVariant ?? null)
+                ? (selectedConfig ?? null)
+                : null
+            }
+          />
+        ) : (
+          <>
         {tabs.length > 1 ? (
           <PillTabs
             ariaLabel="Model source"
@@ -494,13 +586,14 @@ function ModelSelectorContent({
             loraModels={fineTunedModels}
             externalModels={externalModels}
             value={value}
-            onSelect={onSelect}
+            onSelect={handlePick}
             onFoldersChange={onFoldersChange}
             onBrowseHub={onBrowseHub}
             onModelsChange={onModelsChange}
+            onConfigure={openConfigPage}
             deleteDisabled={deleteDisabled}
-            section={effectiveHubSection}
             onEject={hasSelection && onEject ? onEject : undefined}
+            section={effectiveHubSection}
             sectionToggle={
               <PillTabs
                 ariaLabel="Hub section"
@@ -538,10 +631,8 @@ function ModelSelectorContent({
             </button>
           </div>
         ) : null}
-        {/* Hub renders Eject inline as the last list row; other tabs keep the
-          footer button. */}
         {effectiveTab !== "hub" && hasSelection && onEject ? (
-          <div className="mt-1.5 pt-1.5">
+          <div className="mt-1.5 border-t border-border/70 pt-1.5 pb-2">
             <button
               type="button"
               onClick={onEject}
@@ -553,6 +644,8 @@ function ModelSelectorContent({
             </button>
           </div>
         ) : null}
+          </>
+        )}
       </TooltipProvider>
     </PopoverContent>
   );
@@ -565,6 +658,10 @@ export function ModelSelector({
   value,
   defaultValue,
   activeGgufVariant,
+  activeModelConfig,
+  activeGgufContextLength,
+  selectedConfig,
+  selectedGgufVariant,
   onValueChange,
   onEject,
   onFoldersChange,
@@ -693,6 +790,11 @@ export function ModelSelector({
         loraModels={loraModels}
         externalModels={externalModels}
         value={selected}
+        activeGgufVariant={activeGgufVariant}
+        activeModelConfig={activeModelConfig}
+        activeGgufContextLength={activeGgufContextLength}
+        selectedConfig={selectedConfig}
+        selectedGgufVariant={selectedGgufVariant}
         onSelect={handleSelect}
         onEject={onEject ? handleEject : undefined}
         onFoldersChange={onFoldersChange}
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx b/studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
similarity index 88%
rename from studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
index 16cc8a1956..023f586781 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
@@ -14,10 +14,7 @@ import {
   DialogTitle,
 } from "@/components/ui/dialog";
 import { Spinner } from "@/components/ui/spinner";
-import {
-  type BrowseFoldersResponse,
-  browseFolders,
-} from "@/features/chat/api/chat-api";
+import { type BrowseFoldersResponse, browseFolders } from "@/features/chat";
 import { ChevronUpStandardIcon } from "@/lib/chevron-icons";
 import { cn } from "@/lib/utils";
 import { Folder02Icon } from "@hugeicons/core-free-icons";
@@ -90,47 +87,43 @@ export function FolderBrowser({
   const [error, setError] = useState<string | null>(null);
   const abortRef = useRef<AbortController | null>(null);
 
-  const navigate = useCallback(
-    (
-      target: string | undefined,
-      hidden: boolean,
-      opts?: { fallbackOnError?: boolean },
-    ) => {
-      abortRef.current?.abort();
-      const ctrl = new AbortController();
-      abortRef.current = ctrl;
-      setLoading(true);
-      setError(null);
-      // Forward the signal so cancelled navigation aborts the backend
-      // enumeration, not just the response.
-      browseFolders(target, hidden, ctrl.signal)
-        .then((res) => {
-          if (ctrl.signal.aborted) return;
-          setData(res);
-          setPath(res.current);
-        })
-        .catch((err) => {
-          if (ctrl.signal.aborted) return;
-          // Surface the error; if the first request (e.g. a bad initialPath)
-          // fails, fall back to HOME so the modal stays navigable.
-          const message = err instanceof Error ? err.message : String(err);
-          setError(message);
-          if (opts?.fallbackOnError && target !== undefined) {
-            // Re-issue without a target -> backend defaults to HOME.
-            // Don't recurse if HOME itself fails (allowlist always has HOME).
-            queueMicrotask(() => navigate(undefined, hidden));
-          }
-        })
-        .finally(() => {
-          if (!ctrl.signal.aborted) setLoading(false);
-        });
-    },
-    [],
-  );
+  function navigate(
+    target: string | undefined,
+    hidden: boolean,
+    opts?: { fallbackOnError?: boolean },
+  ) {
+    abortRef.current?.abort();
+    const ctrl = new AbortController();
+    abortRef.current = ctrl;
+    setLoading(true);
+    setError(null);
+    // Forward the signal so cancelled navigation aborts the backend
+    // enumeration, not just the response.
+    browseFolders(target, hidden, ctrl.signal)
+      .then((res) => {
+        if (ctrl.signal.aborted) return;
+        setData(res);
+        setPath(res.current);
+      })
+      .catch((err) => {
+        if (ctrl.signal.aborted) return;
+        // Surface the error; if the first request (e.g. a bad initialPath)
+        // fails, fall back to HOME so the modal stays navigable.
+        const message = err instanceof Error ? err.message : String(err);
+        setError(message);
+        if (opts?.fallbackOnError && target !== undefined) {
+          // Re-issue without a target -> backend defaults to HOME.
+          // Don't recurse if HOME itself fails (allowlist always has HOME).
+          queueMicrotask(() => navigate(undefined, hidden));
+        }
+      })
+      .finally(() => {
+        if (!ctrl.signal.aborted) setLoading(false);
+      });
+  }
 
   // Fetch only on closed -> open; later navigation is driven by `navigate()`,
   // so `path` is deliberately kept out of the dependency list.
-  // eslint-disable-next-line react-hooks/exhaustive-deps
   useEffect(() => {
     if (!open) return;
     // fallbackOnError: recover into HOME if initialPath is bad, rather than
@@ -147,7 +140,7 @@ export function FolderBrowser({
 
   const crumbs = useMemo(
     () => (data?.current ? splitBreadcrumb(data.current) : []),
-    [data?.current],
+    [data],
   );
 
   return (
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-capabilities.ts b/studio/frontend/src/features/model-picker/components/model-selector/model-capabilities.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-capabilities.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/model-capabilities.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
similarity index 90%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
index 4de96d3648..09bb43abdc 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
@@ -1,12 +1,12 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { DeleteConfirmDialog } from "@/features/hub/catalog/download-card";
+import { DeleteConfirmDialog } from "@/features/hub";
+import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import { Delete02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
-import { useCallback, useState, type ReactNode } from "react";
-import { toast } from "@/lib/toast";
+import { type ReactNode, useCallback, useState } from "react";
 
 interface ModelDeleteActionProps {
   ariaLabel: string;
@@ -63,7 +63,8 @@ export function ModelDeleteAction({
         disabled={disabled}
         className={cn(
           "shrink-0 rounded-md p-1.5 text-muted-foreground/60 transition-colors hover:bg-destructive/10 hover:text-destructive",
-          disabled && "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
+          disabled &&
+            "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
           buttonClassName,
         )}
       >
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
similarity index 66%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
index 58510762d4..e1d48b5a08 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
@@ -6,24 +6,16 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
-import { useChatRuntimeStore } from "@/features/chat/stores/chat-runtime-store";
 import { cn } from "@/lib/utils";
 import { Settings02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 
-/** Gear button on a downloaded quant row. Stages the model into the Run
- * settings sidebar (always, regardless of the Load-on-selection toggle) so the
- * user can set load options, then click Load model. */
 export function ModelLoadSettingsAction({
   ariaLabel,
-  repoId,
-  quant,
-  maxContext,
+  onConfigure,
 }: {
   ariaLabel: string;
-  repoId: string;
-  quant: string;
-  maxContext?: number | null;
+  onConfigure: () => void;
 }) {
   return (
     <Tooltip delayDuration={0}>
@@ -32,12 +24,7 @@ export function ModelLoadSettingsAction({
           type="button"
           onClick={(e) => {
             e.stopPropagation();
-            useChatRuntimeStore.getState().stageModel({
-              id: repoId,
-              ggufVariant: quant,
-              isDownloaded: true,
-              contextLength: maxContext ?? null,
-            });
+            onConfigure();
           }}
           aria-label={ariaLabel}
           className={cn(
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx b/studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
similarity index 82%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
index db7628777a..b13ed33d04 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
@@ -1,12 +1,20 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { subscribeJobListeners } from "@/features/hub/download-manager";
-import { UpdateConfirmDialog } from "@/features/hub/catalog/download-card";
-import { ggufVariantsMatch } from "@/features/hub/lib/model-identity";
+import {
+  UpdateConfirmDialog,
+  ggufVariantsMatch,
+  subscribeJobListeners,
+} from "@/features/hub";
 import { cn } from "@/lib/utils";
 import { RefreshCw } from "lucide-react";
-import { useCallback, useEffect, useRef, useState, type ReactNode } from "react";
+import {
+  type ReactNode,
+  useCallback,
+  useEffect,
+  useRef,
+  useState,
+} from "react";
 import { toast } from "sonner";
 
 interface ModelUpdateActionProps {
@@ -42,10 +50,10 @@ export function ModelUpdateAction({
 }: ModelUpdateActionProps) {
   const [open, setOpen] = useState(false);
 
-  // Refresh the caller when this repo+variant's download finishes so the "update available" cue
-  // clears. A ref keeps the subscription stable across renders.
   const onUpdatedRef = useRef(onUpdated);
-  onUpdatedRef.current = onUpdated;
+  useEffect(() => {
+    onUpdatedRef.current = onUpdated;
+  }, [onUpdated]);
   useEffect(() => {
     return subscribeJobListeners("model", repoId, {
       onComplete: (completedVariant) => {
@@ -83,7 +91,8 @@ export function ModelUpdateAction({
         disabled={disabled}
         className={cn(
           "shrink-0 rounded-md p-1.5 text-muted-foreground/60 transition-colors hover:bg-amber-500/10 hover:text-amber-700 dark:hover:bg-amber-500/15 dark:hover:text-amber-300",
-          disabled && "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
+          disabled &&
+            "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
           buttonClassName,
         )}
       >
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts b/studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
similarity index 93%
rename from studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
index dbcd4b9a1b..c6665e7658 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
+++ b/studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
@@ -40,7 +40,8 @@ export function loadedAt(times: ModelLoadTimes, id: string): number {
 export function useModelLoadTimes(currentValue?: string): ModelLoadTimes {
   const [times, setTimes] = useState<ModelLoadTimes>(() => readLoadTimes());
   useEffect(() => {
-    if (currentValue) setTimes(recordModelLoaded(currentValue));
+    if (!currentValue) return;
+    queueMicrotask(() => setTimes(recordModelLoaded(currentValue)));
   }, [currentValue]);
   return times;
 }
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx b/studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
similarity index 89%
rename from studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
index 8e06181585..1569ca0581 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
@@ -10,49 +10,46 @@ import {
   TooltipTrigger,
 } from "@/components/ui/tooltip";
 import { usePlatformStore } from "@/config/env";
-import { ApiProviderLogo } from "@/features/chat/api-provider-logo";
+import { ApiProviderLogo } from "@/features/chat";
 import {
   type ScanFolderInfo,
   addScanFolder,
   deleteCachedModel,
   deleteFineTunedModel,
-  listCachedGguf,
-  listCachedModels,
   listGgufVariants,
-  listLocalModels,
   listRecommendedFolders,
   listScanFolders,
   removeScanFolder,
-} from "@/features/chat/api/chat-api";
-import { useChatRuntimeStore } from "@/features/chat/stores/chat-runtime-store";
+} from "@/features/chat";
+import { useChatRuntimeStore } from "@/features/chat";
 import type {
   CachedGgufRepo,
   CachedModelRepo,
+  GgufVariantDetail,
   LocalModelInfo,
-} from "@/features/chat/api/chat-api";
-import type { GgufVariantDetail } from "@/features/chat/types/api";
-import { DotTag } from "@/features/hub/catalog/dot-tag";
+} from "@/features/chat";
 import {
+  DotTag,
   type HubOption,
   HubOptionMenu,
-} from "@/features/hub/catalog/hub-option-menu";
-import { TransportConflictDialog } from "@/features/hub/catalog/transport-conflict-dialog";
-import { TrainIcon } from "@/features/hub/components/train-icon";
-import { useHubInfiniteScroll } from "@/features/hub/hooks/use-hub-infinite-scroll";
+  TrainIcon,
+  TransportConflictDialog,
+  useHubInfiniteScroll,
+} from "@/features/hub";
 import {
   type HfModelResult,
   type HfSortKey,
   useHubModelSearch,
-} from "@/features/hub/hooks/use-hub-model-search";
-import { useOnlineStatus } from "@/features/hub/hooks/use-online-status";
-import { isHiddenModelId } from "@/features/hub/lib/hidden-models";
-import { classifyUnslothSupport } from "@/features/hub/lib/unsloth-support";
-import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
+} from "@/features/hub";
 import {
+  classifyUnslothSupport,
   downloadManager,
+  isHiddenModelId,
   jobKeyOf,
   useDownloadManagerStore,
-} from "@/features/hub/download-manager";
+  useHfTokenStore,
+  useOnlineStatus,
+} from "@/features/hub";
 import { useDebouncedValue, useGpuInfo } from "@/hooks";
 import { extractParamLabel } from "@/lib/model-size";
 import { toast } from "@/lib/toast";
@@ -85,6 +82,7 @@ import {
   useRef,
   useState,
 } from "react";
+import { useChatPickerInventory } from "../../inventory/use-chat-picker-inventory";
 import { FolderBrowser } from "./folder-browser";
 import {
   type ModelCapabilities,
@@ -92,8 +90,8 @@ import {
   hasAnyCapability,
 } from "./model-capabilities";
 import { ModelDeleteAction } from "./model-delete-action";
-import { ModelUpdateAction } from "./model-update-action";
 import { ModelLoadSettingsAction } from "./model-load-settings-action";
+import { ModelUpdateAction } from "./model-update-action";
 import {
   type ModelLoadTimes,
   loadedAt,
@@ -659,6 +657,7 @@ function GgufVariantExpander({
   parentOptionKey,
   onNavigatePastStart,
   onNavigatePastEnd,
+  onConfigure,
   sourceOverride,
   variantActions,
   onDevice = false,
@@ -674,6 +673,7 @@ function GgufVariantExpander({
   parentOptionKey?: string;
   onNavigatePastStart?: () => void;
   onNavigatePastEnd?: () => void;
+  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   sourceOverride?: ModelSelectorChangeMeta["source"];
   /** Update/delete actions for cached variant rows. Omitted by browse-only
    *  expanders (Recommended, etc.) that don't manage on-disk variants. */
@@ -715,8 +715,11 @@ function GgufVariantExpander({
 
   useEffect(() => {
     let canceled = false;
-    setLoading(true);
-    setError(null);
+    queueMicrotask(() => {
+      if (canceled) return;
+      setLoading(true);
+      setError(null);
+    });
 
     listGgufVariants(repoId, hfToken)
       .then((res) => {
@@ -744,7 +747,7 @@ function GgufVariantExpander({
   }, [repoId, refreshKey, hfToken]);
 
   // Covers Unix absolute (/), Windows drive (C:\, D:/), UNC (\\server), relative (./, ../), tilde (~/)
-  const isLocalPath = /^(\/|\.{1,2}[\\\/]|~[\\\/]|[A-Za-z]:[\\\/]|\\\\)/.test(
+  const isLocalPath = /^(\/|\.{1,2}[\\/]|~[\\/]|[A-Za-z]:[\\/]|\\\\)/.test(
     repoId,
   );
 
@@ -753,8 +756,7 @@ function GgufVariantExpander({
       // Only seed the staged context for picks whose weights are already on
       // disk. The staging effect short-circuits on a known contextLength
       // (pendingHasContext) before starting the download, so attaching it to an
-      // undownloaded quant from a partially cached repo would skip the download
-      // entirely (and, with Load on selection, never load).
+      // undownloaded quant from a partially cached repo would skip the download.
       const isAvailable = isLocalPath || downloaded === true;
       onSelect(repoId, {
         source: sourceOverride ?? (isLocalPath ? "local" : "hub"),
@@ -987,7 +989,8 @@ function GgufVariantExpander({
                       This will update{" "}
                       <span className="font-medium text-foreground">
                         {repoId} ({v.quant})
-                      </span>{"."}
+                      </span>
+                      {"."}
                     </>
                   )
                 }
@@ -1000,12 +1003,20 @@ function GgufVariantExpander({
                 onUpdated={() => setRefreshKey((key) => key + 1)}
               />
             )}
-            {v.downloaded && (
+            {v.downloaded && onConfigure && (
               <ModelLoadSettingsAction
                 ariaLabel={`Inference settings for ${repoId} ${v.quant}`}
-                repoId={repoId}
-                quant={v.quant}
-                maxContext={nativeContext}
+                onConfigure={() =>
+                  onConfigure(repoId, {
+                    source: sourceOverride ?? (isLocalPath ? "local" : "hub"),
+                    isLora: false,
+                    ggufVariant: v.quant,
+                    isDownloaded: true,
+                    expectedBytes,
+                    contextLength: nativeContext,
+                    isGguf: true,
+                  })
+                }
               />
             )}
             {v.downloaded && onDeleteVariant && (
@@ -1209,6 +1220,19 @@ function localPathTooltip(name: string, path: string): ReactNode {
   );
 }
 
+function localModelMeta(isGguf = false): ModelSelectorChangeMeta {
+  return {
+    source: "local",
+    isLora: false,
+    isDownloaded: true,
+    ...(isGguf ? { isGguf: true } : {}),
+  };
+}
+
+function localDirectGgufMeta(): ModelSelectorChangeMeta {
+  return localModelMeta(true);
+}
+
 /** Hugging Face address for an online/Hub row, or undefined when the repo id is
  * missing so the row shows no (empty) address line on hover. */
 function hubRepoUrl(id: string | null | undefined): string | undefined {
@@ -1219,9 +1243,7 @@ function hubRepoUrl(id: string | null | undefined): string | undefined {
 /** Whether a local model is an MLX build (name hint). MLX runs on Mac only, so
  * callers gate visibility on the host being a Mac. */
 function localModelIsMlx(m: LocalModelInfo): boolean {
-  return (
-    isMlxId(m.id) || isMlxId(m.display_name) || isMlxId(m.model_id ?? "")
-  );
+  return isMlxId(m.id) || isMlxId(m.display_name) || isMlxId(m.model_id ?? "");
 }
 
 /** Whether a local model matches the format toggle (GGUF detected by name/path). */
@@ -1245,6 +1267,7 @@ export function HubModelPicker({
   onFoldersChange,
   onBrowseHub,
   onModelsChange,
+  onConfigure,
   deleteDisabled = false,
   section = "downloaded",
   sectionToggle,
@@ -1261,12 +1284,12 @@ export function HubModelPicker({
   /** Open the full Hub page to browse more models. */
   onBrowseHub?: () => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
+  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   deleteDisabled?: boolean;
   /** Section shown when not searching. Search spans all sections. */
   section?: "downloaded" | "recommended" | "custom" | "connected";
   /** Section toggle rendered under the search bar. */
   sectionToggle?: ReactNode;
-  /** Eject the loaded model. Rendered as the last list row when set. */
   onEject?: () => void;
 }) {
   const gpu = useGpuInfo();
@@ -1367,12 +1390,14 @@ export function HubModelPicker({
   const setFitOnDeviceOnly = useChatRuntimeStore((s) => s.setFitOnDeviceOnly);
   // Repos the user clicked to collapse while expand-by-default is on. Kept in
   // memory only, so it resets on reload (and when the setting is toggled).
-  const [collapsedGguf, setCollapsedGguf] = useState<Set<string>>(
-    () => new Set(),
-  );
-  useEffect(() => {
-    setCollapsedGguf(new Set());
-  }, [expandQuantizations]);
+  const [collapsedGgufState, setCollapsedGgufState] = useState<{
+    expandQuantizations: boolean;
+    value: Set<string>;
+  }>(() => ({ expandQuantizations, value: new Set() }));
+  const collapsedGguf =
+    collapsedGgufState.expandQuantizations === expandQuantizations
+      ? collapsedGgufState.value
+      : new Set<string>();
   const isGgufExpanded = useCallback(
     (id: string) =>
       expandQuantizations ? !collapsedGguf.has(id) : expandedGguf === id,
@@ -1383,11 +1408,15 @@ export function HubModelPicker({
   const toggleGgufExpanded = useCallback(
     (id: string) => {
       if (expandQuantizations) {
-        setCollapsedGguf((prev) => {
-          const next = new Set(prev);
+        setCollapsedGgufState((prev) => {
+          const current =
+            prev.expandQuantizations === expandQuantizations
+              ? prev.value
+              : new Set<string>();
+          const next = new Set(current);
           if (next.has(id)) next.delete(id);
           else next.add(id);
-          return next;
+          return { expandQuantizations, value: next };
         });
       } else {
         setExpandedGguf((prev) => (prev === id ? null : id));
@@ -1447,15 +1476,37 @@ export function HubModelPicker({
     });
   }, []);
 
-  // Cached (downloaded) repos -- module-level cache avoids flashing an
-  // empty "Downloaded" section when the popover re-mounts.
-  const [cachedGguf, setCachedGguf] =
-    useState<CachedGgufRepo[]>(_cachedGgufCache);
-  const [cachedModels, setCachedModels] =
-    useState<CachedModelRepo[]>(_cachedModelsCache);
-  const alreadyCached =
-    _cachedGgufCache.length > 0 || _cachedModelsCache.length > 0;
-  const [cachedReady, setCachedReady] = useState(alreadyCached);
+  const pickerInventory = useChatPickerInventory({ enabled: true });
+  const { cachedGguf, cachedModels, cachedReady, refreshInventory } =
+    pickerInventory;
+  const lmStudioModels = useMemo(
+    () =>
+      sortLmStudio(
+        pickerInventory.localModels.filter((m) => m.source === "lmstudio"),
+      ),
+    [pickerInventory.localModels],
+  );
+  const localDirModels = useMemo(
+    () => pickerInventory.localModels.filter((m) => m.source === "models_dir"),
+    [pickerInventory.localModels],
+  );
+  const customFolderModels = useMemo(
+    () => pickerInventory.localModels.filter((m) => m.source === "custom"),
+    [pickerInventory.localModels],
+  );
+  useEffect(() => {
+    _cachedGgufCache = cachedGguf;
+    _cachedModelsCache = cachedModels;
+    _lmStudioCache = lmStudioModels;
+    _localDirCache = localDirModels;
+    _customFolderCache = customFolderModels;
+  }, [
+    cachedGguf,
+    cachedModels,
+    lmStudioModels,
+    localDirModels,
+    customFolderModels,
+  ]);
   const [updateConflictKey, setUpdateConflictKey] = useState<string | null>(
     null,
   );
@@ -1479,16 +1530,6 @@ export function HubModelPicker({
     setUpdateConflictKey(null);
   }, [updateConflictKey]);
 
-  // LM Studio local models -- module-level cache, same pattern as above.
-  const [lmStudioModels, setLmStudioModels] =
-    useState<LocalModelInfo[]>(_lmStudioCache);
-  // Models found under the local models directory (./models), so they stay
-  // selectable on the On Device tab after leaving the Fine-tuned tab.
-  const [localDirModels, setLocalDirModels] =
-    useState<LocalModelInfo[]>(_localDirCache);
-  const [customFolderModels, setCustomFolderModels] =
-    useState<LocalModelInfo[]>(_customFolderCache);
-
   // Custom scan folders management
   const [scanFolders, setScanFolders] =
     useState<ScanFolderInfo[]>(_scanFoldersCache);
@@ -1500,22 +1541,8 @@ export function HubModelPicker({
   const [recommendedFolders, setRecommendedFolders] = useState<string[]>([]);
 
   const refreshLocalModelsList = useCallback(() => {
-    listLocalModels()
-      .then((res) => {
-        const lm = sortLmStudio(
-          res.models.filter((m) => m.source === "lmstudio"),
-        );
-        _lmStudioCache = lm;
-        setLmStudioModels(lm);
-        const ld = res.models.filter((m) => m.source === "models_dir");
-        _localDirCache = ld;
-        setLocalDirModels(ld);
-        const cf = res.models.filter((m) => m.source === "custom");
-        _customFolderCache = cf;
-        setCustomFolderModels(cf);
-      })
-      .catch(() => {});
-  }, []);
+    void pickerInventory.refreshInventory();
+  }, [pickerInventory.refreshInventory]);
 
   const refreshScanFolders = useCallback(() => {
     listScanFolders()
@@ -1594,39 +1621,37 @@ export function HubModelPicker({
   );
 
   const refreshCachedLists = useCallback(() => {
-    listCachedGguf()
-      .then((v) => {
-        _cachedGgufCache = v;
-        setCachedGguf(v);
-      })
-      .catch(() => {});
-    listCachedModels(hfToken || undefined)
-      .then((v) => {
-        _cachedModelsCache = v;
-        setCachedModels(v);
-      })
-      .catch(() => {});
-    refreshLocalModelsList();
-  }, [hfToken, refreshLocalModelsList]);
+    void pickerInventory.refreshInventory();
+  }, [pickerInventory.refreshInventory]);
 
   // Updates run as managed downloads (Downloads panel: progress + Cancel), not a blocking
   // call. The worker pulls only changed blobs, so the cached copy stays usable until done.
-  const startManagedUpdate = useCallback((repoId: string, variant: string, expectedBytes: number) => {
-    return downloadManager
-      .requestStart({
-        kind: "model",
-        repoId,
-        variant,
-        expectedBytes,
-      })
-      .then((outcome) => {
-        if (outcome === "conflict") {
-          setUpdateConflictKey(jobKeyOf("model", repoId, variant));
-        } else if (outcome === "error") {
-          throw new Error("Failed to start update");
-        }
-      });
-  }, []);
+  const startManagedUpdate = useCallback(
+    (repoId: string, variant: string, expectedBytes: number) => {
+      return downloadManager
+        .requestStart({
+          kind: "model",
+          repoId,
+          variant,
+          expectedBytes,
+        })
+        .then((outcome) => {
+          if (outcome === "conflict") {
+            setUpdateConflictKey(jobKeyOf("model", repoId, variant));
+          } else if (outcome === "busy") {
+            // A sibling variant/snapshot for this repo is already downloading,
+            // so this update did not start. Say so instead of closing the
+            // dialog as if it began and leaving the cached copy stale.
+            toast.info("A download for this model is already in progress", {
+              description: "Try updating again once it finishes.",
+            });
+          } else if (outcome === "error") {
+            throw new Error("Failed to start update");
+          }
+        });
+    },
+    [],
+  );
 
   const updateGgufVariant = useCallback(
     (repoId: string, quant: string, expectedBytes: number) =>
@@ -1635,36 +1660,15 @@ export function HubModelPicker({
   );
 
   useEffect(() => {
-    // Always refresh LM Studio + custom folder models (not gated by alreadyCached).
-    refreshLocalModelsList();
     refreshScanFolders();
     listRecommendedFolders()
       .then(setRecommendedFolders)
       .catch(() => {});
+  }, [refreshScanFolders]);
 
-    // Always refetch cached GGUF/model lists. The module-level caches render
-    // instantly with stale data (no spinner flash), but newly downloaded
-    // repos need a fresh backend hit. cachedReady=alreadyCached initially,
-    // so the background refresh is invisible when we already had data.
-    let done = 0;
-    const check = () => {
-      if (++done >= 2) setCachedReady(true);
-    };
-    listCachedGguf()
-      .then((v) => {
-        _cachedGgufCache = v;
-        setCachedGguf(v);
-      })
-      .catch(() => {})
-      .finally(check);
-    listCachedModels(hfToken || undefined)
-      .then((v) => {
-        _cachedModelsCache = v;
-        setCachedModels(v);
-      })
-      .catch(() => {})
-      .finally(check);
-  }, [hfToken, refreshLocalModelsList, refreshScanFolders]);
+  useEffect(() => {
+    void refreshInventory();
+  }, [refreshInventory]);
 
   // Hide downloaded models from the recommended list. Case-insensitive
   // since the HF cache lowercases repo IDs.
@@ -1701,7 +1705,8 @@ export function HubModelPicker({
       // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
       // on Mac (matches the empty Recommended view so search stays consistent).
       .filter(
-        (id) => !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
+        (id) =>
+          !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
       )
       .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id));
     // Sort: GGUFs first, then hub models
@@ -2052,7 +2057,8 @@ export function HubModelPicker({
       // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
       // on Mac (matches the empty Recommended view so search stays consistent).
       .filter(
-        (id) => !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
+        (id) =>
+          !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
       )
       .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id))
       .filter((id) =>
@@ -2508,6 +2514,7 @@ export function HubModelPicker({
             onDevice={true}
             onHasVision={(v) => reportVision(c.repo_id, v)}
             onSelect={onSelect}
+            onConfigure={onConfigure}
             hfToken={hfToken || undefined}
             parentOptionKey={optionKey}
             onNavigatePastStart={() => hubModelList.focusOption(optionKey)}
@@ -2517,7 +2524,6 @@ export function HubModelPicker({
             variantActions={{
               onUpdate: (quant, expectedBytes) =>
                 updateGgufVariant(c.repo_id, quant, expectedBytes),
-              // Can't update the model that's live in memory under itself.
               updateDisabled: loadedModelId === c.repo_id,
               onDelete: async (quant) => {
                 await deleteCachedModel(c.repo_id, quant);
@@ -2562,6 +2568,19 @@ export function HubModelPicker({
             className={downloadedRowButtonClassName}
           />
         </div>
+        {onConfigure && (
+          <ModelLoadSettingsAction
+            ariaLabel={`Inference settings for ${c.repo_id}`}
+            onConfigure={() =>
+              onConfigure(c.repo_id, {
+                source: "hub",
+                isLora: false,
+                isDownloaded: true,
+                isGguf: false,
+              })
+            }
+          />
+        )}
         <ModelDeleteAction
           ariaLabel={`Delete ${c.repo_id}`}
           title="Delete cached model?"
@@ -2665,9 +2684,6 @@ export function HubModelPicker({
         )}
         {...hubModelList.listboxProps}
       >
-        {/* Clear space for the floating Eject pill when scrolled to the end, so
-            its gap above the last row matches its gap below (applies to every
-            section, including Recommended). */}
         <div
           className={cn(
             "pr-0",
@@ -2897,6 +2913,7 @@ export function HubModelPicker({
                       adapters={fineTunedRows}
                       value={value}
                       onSelect={onSelect}
+                      onConfigure={onConfigure}
                       onModelsChange={onModelsChange}
                       deleteDisabled={deleteDisabled}
                       loraModelList={hubModelList}
@@ -2920,7 +2937,10 @@ export function HubModelPicker({
                       title="Browse folders on the server"
                       className="flex items-center gap-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground transition-colors hover:text-foreground"
                     >
-                      <HugeiconsIcon icon={Folder02Icon} className="size-3.5" />
+                        <HugeiconsIcon
+                          icon={Folder02Icon}
+                          className="size-3.5"
+                        />
                       Custom Folders
                     </button>
                     <div className="flex items-center gap-0.5">
@@ -3140,54 +3160,70 @@ export function HubModelPicker({
                       );
                       return (
                         <div key={m.id}>
-                          <ModelRow
-                            label={m.model_id ?? m.display_name}
-                            meta={isGguf ? "GGUF" : "Local"}
-                            tooltipText={localPathTooltip(
-                              m.model_id ?? m.display_name,
-                              m.path,
-                            )}
-                            selected={value === m.id}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === m.id,
-                            )}
-                            onClick={() => {
-                              if (isDirectGguf) {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                  // Mark GGUF so "Load on selection = off" stages
-                                  // through Run settings (matches LM Studio path).
-                                  isGguf: true,
-                                });
-                              } else if (isGguf) {
-                                toggleGgufExpanded(m.id);
-                              } else {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                });
-                              }
-                            }}
-                            onArrowDownIntoChildren={
-                              isGguf && !isDirectGguf && isGgufExpanded(m.id)
-                                ? () => {
-                                    const focused =
-                                      focusFirstChildOption(optionKey);
-                                    return focused;
+                          <div className="flex items-center gap-0.5">
+                            <div className="min-w-0 flex-1">
+                              <ModelRow
+                                label={m.model_id ?? m.display_name}
+                                meta={isGguf ? "GGUF" : "Local"}
+                                tooltipText={localPathTooltip(
+                                  m.model_id ?? m.display_name,
+                                  m.path,
+                                )}
+                                selected={value === m.id}
+                                optionProps={hubModelList.getOptionProps(
+                                  optionKey,
+                                  value === m.id,
+                                )}
+                                onClick={() => {
+                                  if (isDirectGguf) {
+                                    onSelect(m.id, localDirectGgufMeta());
+                                  } else if (isGguf) {
+                                    toggleGgufExpanded(m.id);
+                                  } else {
+                                    onSelect(m.id, localModelMeta());
                                   }
-                                : undefined
-                            }
-                            vramStatus={null}
-                          />
+                                }}
+                                onArrowDownIntoChildren={
+                                  isGguf &&
+                                  !isDirectGguf &&
+                                  isGgufExpanded(m.id)
+                                    ? () => {
+                                        const focused =
+                                          focusFirstChildOption(optionKey);
+                                        return focused;
+                                      }
+                                    : undefined
+                                }
+                                vramStatus={null}
+                              />
+                            </div>
+                            {isDirectGguf && onConfigure && (
+                              <ModelLoadSettingsAction
+                                ariaLabel={`Inference settings for ${
+                                  m.model_id ?? m.display_name
+                                }`}
+                                onConfigure={() =>
+                                  onConfigure(m.id, localDirectGgufMeta())
+                                }
+                              />
+                            )}
+                            {!isGguf && onConfigure && (
+                              <ModelLoadSettingsAction
+                                ariaLabel={`Inference settings for ${
+                                  m.model_id ?? m.display_name
+                                }`}
+                                onConfigure={() =>
+                                  onConfigure(m.id, localModelMeta())
+                                }
+                              />
+                            )}
+                          </div>
                           {isGguf && !isDirectGguf && isGgufExpanded(m.id) && (
                             <GgufVariantExpander
                               repoId={m.id}
                               onDevice={true}
                               onSelect={onSelect}
+                              onConfigure={onConfigure}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
                                 hubModelList.focusOption(optionKey)
@@ -3198,7 +3234,9 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                              systemRamGb={
+                                gpu.systemRamAvailableGb || undefined
+                              }
                             />
                           )}
                         </div>
@@ -3233,52 +3271,68 @@ export function HubModelPicker({
                       const optionKey = makeModelOptionKey("lm-studio", m.id);
                       return (
                         <div key={m.id}>
-                          <ModelRow
-                            label={m.model_id ?? m.display_name}
-                            meta={isGguf ? "GGUF" : "Local"}
-                            tooltipText={localPathTooltip(
-                              m.model_id ?? m.display_name,
-                              m.path,
-                            )}
-                            selected={value === m.id}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === m.id,
-                            )}
-                            onClick={() => {
-                              if (isGgufFile) {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                  isGguf: true,
-                                });
-                              } else if (isGguf) {
-                                toggleGgufExpanded(m.id);
-                              } else {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                });
-                              }
-                            }}
-                            onArrowDownIntoChildren={
-                              isGguf && !isGgufFile && isGgufExpanded(m.id)
-                                ? () => {
-                                    const focused =
-                                      focusFirstChildOption(optionKey);
-                                    return focused;
+                          <div className="flex items-center gap-0.5">
+                            <div className="min-w-0 flex-1">
+                              <ModelRow
+                                label={m.model_id ?? m.display_name}
+                                meta={isGguf ? "GGUF" : "Local"}
+                                tooltipText={localPathTooltip(
+                                  m.model_id ?? m.display_name,
+                                  m.path,
+                                )}
+                                selected={value === m.id}
+                                optionProps={hubModelList.getOptionProps(
+                                  optionKey,
+                                  value === m.id,
+                                )}
+                                onClick={() => {
+                                  if (isGgufFile) {
+                                    onSelect(m.id, localDirectGgufMeta());
+                                  } else if (isGguf) {
+                                    toggleGgufExpanded(m.id);
+                                  } else {
+                                    onSelect(m.id, localModelMeta());
                                   }
-                                : undefined
-                            }
-                            vramStatus={null}
-                          />
+                                }}
+                                onArrowDownIntoChildren={
+                                  isGguf && !isGgufFile && isGgufExpanded(m.id)
+                                    ? () => {
+                                        const focused =
+                                          focusFirstChildOption(optionKey);
+                                        return focused;
+                                      }
+                                    : undefined
+                                }
+                                vramStatus={null}
+                              />
+                            </div>
+                            {isGgufFile && onConfigure && (
+                              <ModelLoadSettingsAction
+                                ariaLabel={`Inference settings for ${
+                                  m.model_id ?? m.display_name
+                                }`}
+                                onConfigure={() =>
+                                  onConfigure(m.id, localDirectGgufMeta())
+                                }
+                              />
+                            )}
+                            {!isGguf && onConfigure && (
+                              <ModelLoadSettingsAction
+                                ariaLabel={`Inference settings for ${
+                                  m.model_id ?? m.display_name
+                                }`}
+                                onConfigure={() =>
+                                  onConfigure(m.id, localModelMeta())
+                                }
+                              />
+                            )}
+                          </div>
                           {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
                             <GgufVariantExpander
                               repoId={m.id}
                               onDevice={true}
                               onSelect={onSelect}
+                              onConfigure={onConfigure}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
                                 hubModelList.focusOption(optionKey)
@@ -3289,7 +3343,9 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                              systemRamGb={
+                                gpu.systemRamAvailableGb || undefined
+                              }
                             />
                           )}
                         </div>
@@ -3318,48 +3374,64 @@ export function HubModelPicker({
                       const optionKey = makeModelOptionKey("local-dir", m.id);
                       return (
                         <div key={m.id}>
-                          <ModelRow
-                            label={m.model_id ?? m.display_name}
-                            meta={isGguf ? "GGUF" : "Local"}
-                            tooltipText={localPathTooltip(
-                              m.model_id ?? m.display_name,
-                              m.path,
+                          <div className="flex items-center gap-0.5">
+                            <div className="min-w-0 flex-1">
+                              <ModelRow
+                                label={m.model_id ?? m.display_name}
+                                meta={isGguf ? "GGUF" : "Local"}
+                                tooltipText={localPathTooltip(
+                                  m.model_id ?? m.display_name,
+                                  m.path,
+                                )}
+                                selected={value === m.id}
+                                optionProps={hubModelList.getOptionProps(
+                                  optionKey,
+                                  value === m.id,
+                                )}
+                                onClick={() => {
+                                  if (isGgufFile) {
+                                    onSelect(m.id, localDirectGgufMeta());
+                                  } else if (isGguf) {
+                                    toggleGgufExpanded(m.id);
+                                  } else {
+                                    onSelect(m.id, localModelMeta());
+                                  }
+                                }}
+                                onArrowDownIntoChildren={
+                                  isGguf && !isGgufFile && isGgufExpanded(m.id)
+                                    ? () => focusFirstChildOption(optionKey)
+                                    : undefined
+                                }
+                                vramStatus={null}
+                              />
+                            </div>
+                            {isGgufFile && onConfigure && (
+                              <ModelLoadSettingsAction
+                                ariaLabel={`Inference settings for ${
+                                  m.model_id ?? m.display_name
+                                }`}
+                                onConfigure={() =>
+                                  onConfigure(m.id, localDirectGgufMeta())
+                                }
+                              />
                             )}
-                            selected={value === m.id}
-                            optionProps={hubModelList.getOptionProps(
-                              optionKey,
-                              value === m.id,
+                            {!isGguf && onConfigure && (
+                              <ModelLoadSettingsAction
+                                ariaLabel={`Inference settings for ${
+                                  m.model_id ?? m.display_name
+                                }`}
+                                onConfigure={() =>
+                                  onConfigure(m.id, localModelMeta())
+                                }
+                              />
                             )}
-                            onClick={() => {
-                              if (isGgufFile) {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                  isGguf: true,
-                                });
-                              } else if (isGguf) {
-                                toggleGgufExpanded(m.id);
-                              } else {
-                                onSelect(m.id, {
-                                  source: "local",
-                                  isLora: false,
-                                  isDownloaded: true,
-                                });
-                              }
-                            }}
-                            onArrowDownIntoChildren={
-                              isGguf && !isGgufFile && isGgufExpanded(m.id)
-                                ? () => focusFirstChildOption(optionKey)
-                                : undefined
-                            }
-                            vramStatus={null}
-                          />
+                          </div>
                           {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
                             <GgufVariantExpander
                               repoId={m.id}
                               onDevice={true}
                               onSelect={onSelect}
+                              onConfigure={onConfigure}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
                                 hubModelList.focusOption(optionKey)
@@ -3370,7 +3442,9 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                              systemRamGb={
+                                gpu.systemRamAvailableGb || undefined
+                              }
                             />
                           )}
                         </div>
@@ -3440,6 +3514,7 @@ export function HubModelPicker({
                             <GgufVariantExpander
                               repoId={id}
                               onSelect={onSelect}
+                              onConfigure={onConfigure}
                               hfToken={hfToken || undefined}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
@@ -3451,7 +3526,9 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                              systemRamGb={
+                                gpu.systemRamAvailableGb || undefined
+                              }
                               variantActions={{
                                 onDelete: async (quant) => {
                                   await deleteCachedModel(id, quant);
@@ -3511,10 +3588,14 @@ export function HubModelPicker({
                             }
                           }}
                           vramStatus={
-                            isKnownGgufRepo(id) ? null : (vram?.status ?? null)
+                            isKnownGgufRepo(id)
+                              ? null
+                              : (vram?.status ?? null)
                           }
                           vramEst={isKnownGgufRepo(id) ? undefined : vram?.est}
-                          gpuGb={gpu.available ? gpu.memoryTotalGb : undefined}
+                          gpuGb={
+                            gpu.available ? gpu.memoryTotalGb : undefined
+                          }
                           onArrowDownIntoChildren={
                             expandedGguf === id
                               ? () => {
@@ -3529,6 +3610,7 @@ export function HubModelPicker({
                           <GgufVariantExpander
                             repoId={id}
                             onSelect={onSelect}
+                            onConfigure={onConfigure}
                             hfToken={hfToken || undefined}
                             parentOptionKey={optionKey}
                             onNavigatePastStart={() =>
@@ -3540,7 +3622,9 @@ export function HubModelPicker({
                             gpuGb={
                               gpu.available ? gpu.memoryTotalGb : undefined
                             }
-                            systemRamGb={gpu.systemRamAvailableGb || undefined}
+                            systemRamGb={
+                              gpu.systemRamAvailableGb || undefined
+                            }
                             variantActions={{
                               onDelete: async (quant) => {
                                 await deleteCachedModel(id, quant);
@@ -3620,6 +3704,7 @@ export function HubModelPicker({
                             <GgufVariantExpander
                               repoId={id}
                               onSelect={onSelect}
+                              onConfigure={onConfigure}
                               hfToken={hfToken || undefined}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
@@ -3631,7 +3716,9 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={gpu.systemRamAvailableGb || undefined}
+                              systemRamGb={
+                                gpu.systemRamAvailableGb || undefined
+                              }
                               variantActions={{
                                 onDelete: async (quant) => {
                                   await deleteCachedModel(id, quant);
@@ -3656,8 +3743,6 @@ export function HubModelPicker({
           )}
         </div>
       </div>
-      {/* Floating eject pill: overlaid on the list bottom, outside the scroll
-          so the edge fade never touches it. Only the pill catches clicks. */}
       {onEject ? (
         <div className="pointer-events-none absolute inset-x-0 bottom-0 flex justify-end pr-3.5 pb-[19px]">
           <button
@@ -3688,6 +3773,7 @@ function FineTunedRows({
   adapters,
   value,
   onSelect,
+  onConfigure,
   onModelsChange,
   deleteDisabled = false,
   loraModelList,
@@ -3698,6 +3784,7 @@ function FineTunedRows({
   adapters: LoraModelOption[];
   value?: string;
   onSelect: (id: string, meta: ModelSelectorChangeMeta) => void;
+  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
   deleteDisabled?: boolean;
   loraModelList: ReturnType<typeof useRovingModelList>;
@@ -3722,6 +3809,13 @@ function FineTunedRows({
         const isTrainingFull = isTraining && isMerged;
         const isLocalGgufDir =
           isLocal && (isGgufRepo(adapter.id) || isGgufRepo(adapter.name));
+        const selectionMeta: ModelSelectorChangeMeta = {
+          source: isLocal ? "local" : isExported ? "exported" : "lora",
+          isLora: !isLocal && !isMerged && !isGguf,
+          isDownloaded: true,
+          isGguf: false,
+        };
+        const canConfigure = !(isLocalGgufDir || isExportedGguf);
         const optionKey = makeModelOptionKey("lora", adapter.id);
         const tag = isLocal
           ? isLocalGgufDir
@@ -3763,15 +3857,7 @@ function FineTunedRows({
                         prev === adapter.id ? null : adapter.id,
                       );
                     } else {
-                      onSelect(adapter.id, {
-                        source: isLocal
-                          ? "local"
-                          : isExported
-                            ? "exported"
-                            : "lora",
-                        isLora: !isLocal && !isMerged && !isGguf,
-                        isDownloaded: true,
-                      });
+                      onSelect(adapter.id, selectionMeta);
                     }
                   }}
                   tooltipText={
@@ -3792,6 +3878,12 @@ function FineTunedRows({
                   }
                 />
               </div>
+              {canConfigure && onConfigure && (
+                <ModelLoadSettingsAction
+                  ariaLabel={`Inference settings for ${adapter.name}`}
+                  onConfigure={() => onConfigure(adapter.id, selectionMeta)}
+                />
+              )}
               {canDelete && (
                 <ModelDeleteAction
                   ariaLabel={`Delete ${adapter.name}`}
@@ -3822,6 +3914,7 @@ function FineTunedRows({
               <GgufVariantExpander
                 repoId={adapter.id}
                 onSelect={onSelect}
+                onConfigure={onConfigure}
                 parentOptionKey={optionKey}
                 onNavigatePastStart={() => loraModelList.focusOption(optionKey)}
                 onNavigatePastEnd={() =>
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx b/studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
similarity index 98%
rename from studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
rename to studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
index e6da8a7b74..fbc1d5ac91 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
+++ b/studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
@@ -78,7 +78,8 @@ export function PillTabs({
             onValueChange(tabs[next].value);
             e.currentTarget.parentElement
               ?.querySelectorAll<HTMLElement>('button[role="tab"]')
-              [next]?.focus();
+              .item(next)
+              ?.focus();
           }}
           onClick={() => onValueChange(tab.value)}
           className={cn(
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts b/studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/row-meta.ts b/studio/frontend/src/features/model-picker/components/model-selector/row-meta.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/row-meta.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/row-meta.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/source-tabs.ts b/studio/frontend/src/features/model-picker/components/model-selector/source-tabs.ts
similarity index 100%
rename from studio/frontend/src/components/assistant-ui/model-selector/source-tabs.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/source-tabs.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/types.ts b/studio/frontend/src/features/model-picker/components/model-selector/types.ts
similarity index 76%
rename from studio/frontend/src/components/assistant-ui/model-selector/types.ts
rename to studio/frontend/src/features/model-picker/components/model-selector/types.ts
index 6a86515267..dae072236b 100644
--- a/studio/frontend/src/components/assistant-ui/model-selector/types.ts
+++ b/studio/frontend/src/features/model-picker/components/model-selector/types.ts
@@ -2,6 +2,7 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import type { ReactNode } from "react";
+import type { PerModelConfig } from "../../model-config/per-model-config";
 
 export interface ModelOption {
   id: string;
@@ -36,6 +37,18 @@ export interface ModelSelectorChangeMeta {
   /** Direct local .gguf file picked without a variant (custom folder / LM
    *  Studio). Marks it as a GGUF source for the deferred-load staging flow. */
   isGguf?: boolean;
+  config?: PerModelConfig;
+  forceReload?: boolean;
+  /** Native path token so an active-model reload can reopen a file-picked GGUF. */
+  nativePathToken?: string;
+}
+
+export interface ModelPickTarget {
+  id: string;
+  displayName: string;
+  ggufVariant?: string | null;
+  isGguf: boolean;
+  meta: ModelSelectorChangeMeta;
 }
 
 export interface DeletedModelRef {
diff --git a/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx b/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
new file mode 100644
index 0000000000..2489927fc2
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
@@ -0,0 +1,113 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { cn } from "@/lib/utils";
+import { useRef, useState } from "react";
+
+export function snapToStep(
+  value: number,
+  step: number,
+  min?: number,
+  max?: number,
+): number {
+  const lo = min ?? Number.NEGATIVE_INFINITY;
+  const hi = max ?? Number.POSITIVE_INFINITY;
+  const clamped = Math.min(Math.max(value, lo), hi);
+  const stepStr = String(step);
+  const decimals = stepStr.includes(".") ? stepStr.split(".")[1].length : 0;
+  const base = Number.isFinite(lo) ? lo : 0;
+  const snapped = base + Math.round((clamped - base) / step) * step;
+  const reclamped = Math.min(Math.max(snapped, lo), hi);
+  return Number(reclamped.toFixed(decimals));
+}
+
+function sanitizeNumeric(raw: string, allowNegative: boolean): string {
+  const sign = allowNegative && raw.startsWith("-") ? "-" : "";
+  const [head, ...rest] = raw.replace(/[^\d.]/g, "").split(".");
+  const tail = rest.length > 0 ? `.${rest.join("")}` : "";
+  return `${sign}${head}${tail}`;
+}
+
+export function NumericValueInput({
+  value,
+  min,
+  max,
+  step,
+  onChange,
+  displayValue,
+  className,
+  ariaLabel,
+  size: sizeAttr,
+  disabled = false,
+}: {
+  value: number;
+  min?: number;
+  max?: number;
+  step: number;
+  onChange: (v: number) => void;
+  displayValue?: string;
+  className?: string;
+  ariaLabel?: string;
+  size?: number;
+  disabled?: boolean;
+}) {
+  const [focused, setFocused] = useState(false);
+  const [draft, setDraft] = useState("");
+  const cancelBlurCommitRef = useRef(false);
+
+  const commit = (raw: string) => {
+    const parsed = Number.parseFloat(raw);
+    if (!Number.isFinite(parsed)) {
+      return;
+    }
+    const final = snapToStep(parsed, step, min, max);
+    if (final !== value) {
+      onChange(final);
+    }
+  };
+
+  const displayed = focused ? draft : (displayValue ?? String(value));
+
+  return (
+    <input
+      type="text"
+      inputMode="decimal"
+      disabled={disabled}
+      size={sizeAttr}
+      style={{
+        boxSizing: "content-box",
+        width: `calc(${Math.max(displayed.length, 4)}ch + 2px)`,
+      }}
+      value={displayed}
+      aria-label={ariaLabel}
+      onFocus={(e) => {
+        cancelBlurCommitRef.current = false;
+        setDraft(String(value));
+        setFocused(true);
+        const target = e.currentTarget;
+        requestAnimationFrame(() => target.select());
+      }}
+      onBlur={() => {
+        if (cancelBlurCommitRef.current) {
+          cancelBlurCommitRef.current = false;
+        } else {
+          commit(draft);
+        }
+        setFocused(false);
+      }}
+      onChange={(e) =>
+        setDraft(sanitizeNumeric(e.target.value, (min ?? 0) < 0))
+      }
+      onKeyDown={(e) => {
+        if (e.key === "Enter") {
+          e.currentTarget.blur();
+        } else if (e.key === "Escape") {
+          cancelBlurCommitRef.current = true;
+          setDraft(String(value));
+          e.currentTarget.blur();
+        }
+      }}
+      className={cn(className)}
+    />
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx b/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
new file mode 100644
index 0000000000..c7887c4357
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
@@ -0,0 +1,89 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useMemo } from "react";
+import type { PerModelConfig } from "../model-config/per-model-config";
+import { ModelConfigPage } from "./model-config-page";
+import type { ModelPickTarget } from "./model-selector/types";
+
+interface SidebarModelConfigProps {
+  modelId: string;
+  ggufVariant: string | null;
+  isGguf: boolean;
+  nativeContextLength: number | null;
+  loadedContextLength: number | null;
+  loadedConfig: PerModelConfig;
+  onReload: (config: PerModelConfig) => void;
+}
+
+const TRAILING_SEPARATORS = /[\\/]+$/;
+
+function leafName(id: string): string {
+  const trimmed = id.replace(TRAILING_SEPARATORS, "");
+  const separator = Math.max(
+    trimmed.lastIndexOf("/"),
+    trimmed.lastIndexOf("\\"),
+  );
+  return separator >= 0 ? trimmed.slice(separator + 1) : trimmed;
+}
+
+function hashString(value: string): number {
+  let hash = 5381;
+  for (let i = 0; i < value.length; i += 1) {
+    hash = (Math.imul(hash, 33) ^ value.charCodeAt(i)) >>> 0;
+  }
+  return hash;
+}
+
+function configSignature(config: PerModelConfig): string {
+  return [
+    config.customContextLength ?? "",
+    config.maxSeqLength ?? "",
+    config.kvCacheDtype ?? "",
+    config.speculativeType ?? "",
+    config.specDraftNMax ?? "",
+    config.tensorParallel ? "1" : "0",
+    config.chatTemplateOverride == null
+      ? ""
+      : `${config.chatTemplateOverride.length}:${hashString(config.chatTemplateOverride)}`,
+  ].join("|");
+}
+
+export function SidebarModelConfig({
+  modelId,
+  ggufVariant,
+  isGguf,
+  nativeContextLength,
+  loadedContextLength,
+  loadedConfig,
+  onReload,
+}: SidebarModelConfigProps) {
+  const target = useMemo<ModelPickTarget>(() => {
+    const leaf = leafName(modelId);
+    return {
+      id: modelId,
+      displayName: ggufVariant ? `${leaf} · ${ggufVariant}` : leaf,
+      ggufVariant,
+      isGguf,
+      meta: {
+        source: "local",
+        isLora: false,
+        ggufVariant: ggufVariant ?? undefined,
+        isGguf,
+        isDownloaded: true,
+        contextLength: nativeContextLength,
+      },
+    };
+  }, [modelId, ggufVariant, isGguf, nativeContextLength]);
+
+  return (
+    <ModelConfigPage
+      key={`${modelId}::${ggufVariant ?? ""}::${configSignature(loadedConfig)}`}
+      target={target}
+      onRun={onReload}
+      loadedConfig={loadedConfig}
+      loadedContextLength={loadedContextLength}
+      variant="sidebar"
+    />
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts b/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
new file mode 100644
index 0000000000..49108279e7
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
@@ -0,0 +1,176 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useHfTokenStore } from "@/features/hub";
+import { useEffect, useState } from "react";
+import { fetchModelMaxPositionEmbeddings } from "../api/model-metadata";
+import { fetchDefaultChatTemplate } from "../api/templates";
+
+export interface DefaultChatTemplateState {
+  template: string | null;
+  loading: boolean;
+  error: string | null;
+}
+
+export interface ModelMaxPositionState {
+  maxPositionEmbeddings: number | null;
+  loading: boolean;
+  error: string | null;
+}
+
+const TEMPLATE_CACHE_MAX_ENTRIES = 50;
+const templateCache = new Map<string, string | null>();
+const maxPositionCache = new Map<string, number | null>();
+
+function cacheTemplate(key: string, template: string | null): void {
+  templateCache.delete(key);
+  templateCache.set(key, template);
+  while (templateCache.size > TEMPLATE_CACHE_MAX_ENTRIES) {
+    const oldest = templateCache.keys().next().value;
+    if (oldest === undefined) {
+      break;
+    }
+    templateCache.delete(oldest);
+  }
+}
+
+function cacheMaxPosition(key: string, value: number | null): void {
+  maxPositionCache.delete(key);
+  maxPositionCache.set(key, value);
+  while (maxPositionCache.size > TEMPLATE_CACHE_MAX_ENTRIES) {
+    const oldest = maxPositionCache.keys().next().value;
+    if (oldest === undefined) {
+      break;
+    }
+    maxPositionCache.delete(oldest);
+  }
+}
+
+export function useDefaultChatTemplate(
+  modelId: string | null,
+  ggufVariant: string | null | undefined,
+  enabled: boolean,
+): DefaultChatTemplateState {
+  const token = useHfTokenStore((s) => s.token);
+  const cacheKey =
+    enabled && modelId ? `${modelId}::${ggufVariant ?? ""}::${token}` : null;
+  const [fetched, setFetched] = useState<{
+    key: string;
+    state: DefaultChatTemplateState;
+  } | null>(null);
+
+  useEffect(() => {
+    if (cacheKey == null || !modelId || templateCache.has(cacheKey)) {
+      return;
+    }
+    const controller = new AbortController();
+    fetchDefaultChatTemplate(modelId, ggufVariant, token, controller.signal)
+      .then((template) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        // Cache the terminal result, including a null "no default template",
+        // so reopening the viewer for such a model reuses it instead of
+        // re-running the backend/Hugging Face lookup every time.
+        cacheTemplate(cacheKey, template);
+        setFetched({
+          key: cacheKey,
+          state: { template, loading: false, error: null },
+        });
+      })
+      .catch((err: unknown) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        setFetched({
+          key: cacheKey,
+          state: {
+            template: null,
+            loading: false,
+            error:
+              err instanceof Error ? err.message : "Failed to load template",
+          },
+        });
+      });
+
+    return () => controller.abort();
+  }, [cacheKey, modelId, ggufVariant, token]);
+
+  if (cacheKey == null) {
+    return { template: null, loading: false, error: null };
+  }
+  if (templateCache.has(cacheKey)) {
+    return {
+      template: templateCache.get(cacheKey) ?? null,
+      loading: false,
+      error: null,
+    };
+  }
+  if (fetched?.key === cacheKey) {
+    return fetched.state;
+  }
+  return { template: null, loading: true, error: null };
+}
+
+export function useModelMaxPositionEmbeddings(
+  modelId: string | null,
+  enabled: boolean,
+): ModelMaxPositionState {
+  const token = useHfTokenStore((s) => s.token);
+  const cacheKey = enabled && modelId ? `${modelId}::${token}` : null;
+  const [fetched, setFetched] = useState<{
+    key: string;
+    state: ModelMaxPositionState;
+  } | null>(null);
+
+  useEffect(() => {
+    if (cacheKey == null || !modelId || maxPositionCache.has(cacheKey)) {
+      return;
+    }
+    const controller = new AbortController();
+    fetchModelMaxPositionEmbeddings(modelId, token, controller.signal)
+      .then((maxPositionEmbeddings) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        cacheMaxPosition(cacheKey, maxPositionEmbeddings);
+        setFetched({
+          key: cacheKey,
+          state: { maxPositionEmbeddings, loading: false, error: null },
+        });
+      })
+      .catch((err: unknown) => {
+        if (controller.signal.aborted) {
+          return;
+        }
+        setFetched({
+          key: cacheKey,
+          state: {
+            maxPositionEmbeddings: null,
+            loading: false,
+            error:
+              err instanceof Error
+                ? err.message
+                : "Failed to load model metadata",
+          },
+        });
+      });
+
+    return () => controller.abort();
+  }, [cacheKey, modelId, token]);
+
+  if (cacheKey == null) {
+    return { maxPositionEmbeddings: null, loading: false, error: null };
+  }
+  if (maxPositionCache.has(cacheKey)) {
+    return {
+      maxPositionEmbeddings: maxPositionCache.get(cacheKey) ?? null,
+      loading: false,
+      error: null,
+    };
+  }
+  if (fetched?.key === cacheKey) {
+    return fetched.state;
+  }
+  return { maxPositionEmbeddings: null, loading: true, error: null };
+}
diff --git a/studio/frontend/src/features/model-picker/index.ts b/studio/frontend/src/features/model-picker/index.ts
new file mode 100644
index 0000000000..a9a176317f
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/index.ts
@@ -0,0 +1,30 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+export { ModelSelector } from "./components/model-selector";
+export { FolderBrowser } from "./components/model-selector/folder-browser";
+export { ModelDeleteAction } from "./components/model-selector/model-delete-action";
+export { hfModelFitsDevice } from "./components/model-selector/recommended-fit";
+export {
+  NumericValueInput,
+  snapToStep,
+} from "./components/numeric-value-input";
+export { SidebarModelConfig } from "./components/sidebar-model-config";
+export type {
+  DeletedModelRef,
+  ExternalModelOption,
+  LoraModelOption,
+  ModelOption,
+  ModelSelectorChangeMeta,
+} from "./components/model-selector";
+export {
+  applyModelLoadConfigToRuntime,
+  applyPerModelConfigToRuntime,
+  currentRuntimePerModelConfig,
+  perModelConfigsEqual,
+} from "./model-config/apply-per-model-config";
+export {
+  normalizeMaxSeqLength,
+  type PerModelConfig,
+  resolveInitialConfig,
+} from "./model-config/per-model-config";
diff --git a/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts b/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
new file mode 100644
index 0000000000..50b6bbb1a6
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
@@ -0,0 +1,118 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import type {
+  CachedGgufRepo,
+  CachedModelRepo,
+  LocalModelInfo,
+} from "@/features/chat";
+import {
+  type CachedInventoryRow,
+  type LocalInventoryRow,
+  type LocalSource,
+  isHiddenModelId,
+  useHubInventory,
+} from "@/features/hub";
+import { useMemo } from "react";
+
+const PICKER_LOCAL_SOURCES: ReadonlySet<LocalSource> = new Set([
+  "lmstudio",
+  "models_dir",
+  "custom",
+]);
+
+function isCompleteCachedRow(row: CachedInventoryRow): boolean {
+  return !row.partial && !row.liveDownload;
+}
+
+function toCachedGgufRepo(row: CachedInventoryRow): CachedGgufRepo {
+  return {
+    repo_id: row.repoId,
+    size_bytes: row.bytes,
+    cache_path: row.cachePath ?? "",
+    last_modified: row.lastModified ?? undefined,
+    has_vision: row.capabilities.supportsVision,
+  };
+}
+
+function toCachedModelRepo(row: CachedInventoryRow): CachedModelRepo {
+  return {
+    repo_id: row.repoId,
+    size_bytes: row.bytes,
+    last_modified: row.lastModified ?? undefined,
+  };
+}
+
+function toLocalModelInfo(row: LocalInventoryRow): LocalModelInfo {
+  return {
+    id: row.loadId,
+    display_name: row.displayName ?? row.title,
+    path: row.path,
+    source: row.source as LocalModelInfo["source"],
+    model_id: row.modelId ?? row.repoId,
+    model_format: row.modelFormat,
+    updated_at: row.updatedAt,
+  };
+}
+
+export interface ChatPickerInventory {
+  cachedGguf: CachedGgufRepo[];
+  cachedModels: CachedModelRepo[];
+  cachedReady: boolean;
+  localModels: LocalModelInfo[];
+  refreshInventory: () => Promise<void>;
+}
+
+export function useChatPickerInventory(
+  options: { enabled?: boolean } = {},
+): ChatPickerInventory {
+  const inventory = useHubInventory({
+    kind: "models",
+    enabled: options.enabled,
+    includeLocal: true,
+  });
+
+  const cachedGguf = useMemo(
+    () =>
+      inventory.cachedRows
+        .filter(
+          (row) =>
+            row.modelFormat === "gguf" &&
+            isCompleteCachedRow(row) &&
+            !isHiddenModelId(row.repoId),
+        )
+        .map(toCachedGgufRepo),
+    [inventory.cachedRows],
+  );
+  const cachedModels = useMemo(
+    () =>
+      inventory.cachedRows
+        .filter(
+          (row) =>
+            row.modelFormat !== "gguf" &&
+            isCompleteCachedRow(row) &&
+            !isHiddenModelId(row.repoId),
+        )
+        .map(toCachedModelRepo),
+    [inventory.cachedRows],
+  );
+  const localModels = useMemo(
+    () =>
+      inventory.localRows
+        .filter(
+          (row) =>
+            PICKER_LOCAL_SOURCES.has(row.source) &&
+            !isHiddenModelId(row.modelId, row.repoId, row.path),
+        )
+        .map(toLocalModelInfo),
+    [inventory.localRows],
+  );
+
+  return {
+    cachedGguf,
+    cachedModels,
+    cachedReady: inventory.downloadedReady,
+    localModels,
+    refreshInventory: inventory.refreshInventory,
+  };
+}
diff --git a/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts b/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
new file mode 100644
index 0000000000..a63dffe8dc
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
@@ -0,0 +1,85 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  defaultInferenceParams,
+  normalizeSpeculativeType,
+  readPersistedSpeculativeType,
+  useChatRuntimeStore,
+} from "@/features/chat";
+import {
+  DEFAULT_PER_MODEL_CONFIG,
+  type PerModelConfig,
+  normalizeMaxSeqLength,
+} from "./per-model-config";
+
+function cleanTemplate(value: string | null | undefined): string | null {
+  return value?.trim() ? value : null;
+}
+
+export function applyPerModelConfigToRuntime(config: PerModelConfig): void {
+  // Fall back to the standing default when the model has no saved
+  // maxSeqLength. maxSeqLength is the only per-model field carried on
+  // params (the rest are reset below), so without this a model with no
+  // remembered config would inherit the previously loaded model's value.
+  const maxSeqLength =
+    normalizeMaxSeqLength(config.maxSeqLength) ??
+    defaultInferenceParams.maxSeqLength;
+  const store = useChatRuntimeStore.getState();
+  if (maxSeqLength !== store.params.maxSeqLength) {
+    store.setParams({ ...store.params, maxSeqLength });
+  }
+  useChatRuntimeStore.setState({
+    customContextLength: config.customContextLength ?? null,
+    kvCacheDtype: config.kvCacheDtype ?? null,
+    speculativeType:
+      normalizeSpeculativeType(config.speculativeType) ??
+      readPersistedSpeculativeType(),
+    specDraftNMax: config.specDraftNMax ?? null,
+    tensorParallel: config.tensorParallel ?? false,
+    chatTemplateOverride: cleanTemplate(config.chatTemplateOverride),
+  });
+}
+
+export function applyModelLoadConfigToRuntime(
+  config: PerModelConfig | null | undefined,
+): boolean {
+  const hasConfig = config != null;
+  applyPerModelConfigToRuntime(config ?? DEFAULT_PER_MODEL_CONFIG);
+  return hasConfig;
+}
+
+export function currentRuntimePerModelConfig(
+  options: { includeMaxSeqLength?: boolean } = {},
+): PerModelConfig {
+  const s = useChatRuntimeStore.getState();
+  return {
+    customContextLength: s.customContextLength ?? null,
+    maxSeqLength: options.includeMaxSeqLength
+      ? normalizeMaxSeqLength(s.params.maxSeqLength)
+      : null,
+    kvCacheDtype: s.kvCacheDtype ?? null,
+    speculativeType: normalizeSpeculativeType(s.speculativeType),
+    specDraftNMax: s.specDraftNMax ?? null,
+    tensorParallel: s.tensorParallel ?? false,
+    chatTemplateOverride: cleanTemplate(s.chatTemplateOverride),
+  };
+}
+
+export function perModelConfigsEqual(
+  a: PerModelConfig,
+  b: PerModelConfig,
+): boolean {
+  return (
+    (a.customContextLength ?? null) === (b.customContextLength ?? null) &&
+    normalizeMaxSeqLength(a.maxSeqLength) ===
+      normalizeMaxSeqLength(b.maxSeqLength) &&
+    (a.kvCacheDtype ?? null) === (b.kvCacheDtype ?? null) &&
+    normalizeSpeculativeType(a.speculativeType) ===
+      normalizeSpeculativeType(b.speculativeType) &&
+    (a.specDraftNMax ?? null) === (b.specDraftNMax ?? null) &&
+    Boolean(a.tensorParallel) === Boolean(b.tensorParallel) &&
+    cleanTemplate(a.chatTemplateOverride) ===
+      cleanTemplate(b.chatTemplateOverride)
+  );
+}
diff --git a/studio/frontend/src/features/model-picker/model-config/model-identity.ts b/studio/frontend/src/features/model-picker/model-config/model-identity.ts
new file mode 100644
index 0000000000..0caa7c1312
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/model-config/model-identity.ts
@@ -0,0 +1,69 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "@/features/hub";
+
+export {
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "@/features/hub";
+
+const MODEL_STORAGE_KEY_PREFIX = "v2:";
+
+type ParsedModelStorageKey = {
+  modelId: string;
+  ggufVariant: string;
+};
+
+function parseVersionedModelStorageKey(
+  key: string,
+): ParsedModelStorageKey | null {
+  if (!key.startsWith(MODEL_STORAGE_KEY_PREFIX)) {
+    return null;
+  }
+  try {
+    const parsed = JSON.parse(key.slice(MODEL_STORAGE_KEY_PREFIX.length));
+    if (
+      !Array.isArray(parsed) ||
+      parsed.length !== 2 ||
+      typeof parsed[0] !== "string" ||
+      typeof parsed[1] !== "string"
+    ) {
+      return null;
+    }
+    return { modelId: parsed[0], ggufVariant: parsed[1] };
+  } catch {
+    return null;
+  }
+}
+
+export function modelStorageKey(
+  modelId: string,
+  ggufVariant?: string | null,
+): string {
+  return `${MODEL_STORAGE_KEY_PREFIX}${JSON.stringify([
+    normalizeModelIdentity(modelId),
+    normalizeGgufVariantIdentity(ggufVariant),
+  ])}`;
+}
+
+export function modelIdFromStorageKey(key: string): string | null {
+  const parsed = parseVersionedModelStorageKey(key);
+  if (parsed) {
+    return parsed.modelId;
+  }
+  const separator = key.lastIndexOf("::");
+  return separator >= 0 ? key.slice(0, separator) : null;
+}
+
+export function ggufVariantFromStorageKey(key: string): string | null {
+  const parsed = parseVersionedModelStorageKey(key);
+  if (parsed) {
+    return parsed.ggufVariant;
+  }
+  const separator = key.lastIndexOf("::");
+  return separator >= 0 ? key.slice(separator + 2) : null;
+}
diff --git a/studio/frontend/src/features/model-picker/model-config/per-model-config.ts b/studio/frontend/src/features/model-picker/model-config/per-model-config.ts
new file mode 100644
index 0000000000..53a376e8b4
--- /dev/null
+++ b/studio/frontend/src/features/model-picker/model-config/per-model-config.ts
@@ -0,0 +1,571 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import {
+  ggufVariantFromStorageKey,
+  modelIdFromStorageKey,
+  modelStorageKey,
+  normalizeGgufVariantIdentity,
+  normalizeModelIdentity,
+} from "./model-identity";
+
+export interface PerModelConfig {
+  customContextLength: number | null;
+  maxSeqLength: number | null;
+  kvCacheDtype: string | null;
+  speculativeType: string | null;
+  specDraftNMax: number | null;
+  tensorParallel: boolean;
+  chatTemplateOverride: string | null;
+}
+
+export const DEFAULT_PER_MODEL_CONFIG: PerModelConfig = {
+  customContextLength: null,
+  maxSeqLength: null,
+  kvCacheDtype: null,
+  speculativeType: null,
+  specDraftNMax: null,
+  tensorParallel: false,
+  chatTemplateOverride: null,
+};
+
+export const MAX_SEQ_LENGTH_MIN = 128;
+export const MAX_SEQ_LENGTH_MAX = 1048576;
+export const MAX_SEQ_LENGTH_STEP = 128;
+
+export const KV_CACHE_DTYPES = ["bf16", "q8_0", "q5_1", "q4_1"] as const;
+const VALID_KV_CACHE_DTYPES = new Set<string>(KV_CACHE_DTYPES);
+
+export const SPECULATIVE_TYPES = [
+  "auto",
+  "mtp",
+  "ngram",
+  "mtp+ngram",
+  "off",
+] as const;
+export const MTP_SPECULATIVE_TYPES: ReadonlySet<string> = new Set([
+  "mtp",
+  "mtp+ngram",
+]);
+
+const STORAGE_KEY = "unsloth_model_configs";
+const LEGACY_STORAGE_KEY = "unsloth_load_settings";
+const LEGACY_MIGRATION_FLAG = "unsloth_model_configs_migrated";
+const STORAGE_SCHEMA_VERSION = 1;
+const MAX_ENTRIES = 500;
+const MAX_PER_MODEL_CONFIG_STORAGE_BYTES = 1024 * 1024;
+export const MAX_CHAT_TEMPLATE_BYTES = 65_536;
+
+type StoredPerModelConfig = PerModelConfig & {
+  version: typeof STORAGE_SCHEMA_VERSION;
+};
+type StoredMap = Record<string, PerModelConfig | StoredPerModelConfig>;
+type RawConfig = Partial<PerModelConfig> & { version?: unknown };
+
+const STORED_CONFIG_FIELDS = new Set([
+  "version",
+  "customContextLength",
+  "maxSeqLength",
+  "kvCacheDtype",
+  "speculativeType",
+  "specDraftNMax",
+  "tensorParallel",
+  "chatTemplateOverride",
+]);
+
+function canonicalizeSpeculativeType(value: string): string | null {
+  const s = value.trim().toLowerCase();
+  if (!s) {
+    return null;
+  }
+  if (s === "auto" || s === "default") {
+    return "auto";
+  }
+  if (s === "off") {
+    return "off";
+  }
+  if (s === "mtp" || s === "draft-mtp") {
+    return "mtp";
+  }
+  if (s === "ngram" || s === "ngram-mod" || s === "ngram-simple") {
+    return "ngram";
+  }
+  if (s === "mtp+ngram") {
+    return "mtp+ngram";
+  }
+  return null;
+}
+
+export function normalizeMaxSeqLength(value: unknown): number | null {
+  if (typeof value !== "number" || !Number.isFinite(value) || value <= 0) {
+    return null;
+  }
+  const snapped = Math.round(value / MAX_SEQ_LENGTH_STEP) * MAX_SEQ_LENGTH_STEP;
+  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(MAX_SEQ_LENGTH_MAX, snapped));
+}
+
+function canUseStorage(): boolean {
+  return typeof window !== "undefined";
+}
+
+function serializedByteLength(value: string): number {
+  return typeof TextEncoder !== "undefined"
+    ? new TextEncoder().encode(value).byteLength
+    : value.length;
+}
+
+export function chatTemplateByteLength(value: string): number {
+  return serializedByteLength(value);
+}
+
+export function isChatTemplateWithinLimit(value: string): boolean {
+  return chatTemplateByteLength(value) <= MAX_CHAT_TEMPLATE_BYTES;
+}
+
+function serializedMapSize(map: StoredMap): number {
+  return serializedByteLength(JSON.stringify(map));
+}
+
+function serializedMapEntrySize(key: string, value: StoredMap[string]): number {
+  return (
+    serializedByteLength(JSON.stringify(key)) +
+    1 +
+    serializedByteLength(JSON.stringify(value))
+  );
+}
+
+function deleteOldestEvictableEntry(
+  map: StoredMap,
+  protectedKeys?: ReadonlySet<string>,
+): { key: string; value: StoredMap[string] } | null {
+  for (const key of Object.keys(map)) {
+    // Never evict a future-schema entry an older client cannot interpret,
+    // matching the save/delete guards.
+    if (
+      protectedKeys?.has(key) ||
+      storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION
+    ) {
+      continue;
+    }
+    const value = map[key];
+    delete map[key];
+    return { key, value };
+  }
+  return null;
+}
+
+function enforceStorageBudget(
+  map: StoredMap,
+  protectedKeys?: ReadonlySet<string>,
+): boolean {
+  let entryCount = Object.keys(map).length;
+  while (entryCount > MAX_ENTRIES) {
+    if (!deleteOldestEvictableEntry(map, protectedKeys)) {
+      return false;
+    }
+    entryCount -= 1;
+  }
+  let bytes = serializedMapSize(map);
+  while (bytes > MAX_PER_MODEL_CONFIG_STORAGE_BYTES) {
+    const removed = deleteOldestEvictableEntry(map, protectedKeys);
+    if (!removed) {
+      return false;
+    }
+    bytes -=
+      serializedMapEntrySize(removed.key, removed.value) +
+      (entryCount > 1 ? 1 : 0);
+    entryCount -= 1;
+  }
+  return true;
+}
+
+function storedConfigVersion(raw: unknown): number {
+  if (!raw || typeof raw !== "object" || Array.isArray(raw)) {
+    return 0;
+  }
+  const version = (raw as RawConfig).version;
+  return typeof version === "number" && Number.isFinite(version) ? version : 0;
+}
+
+let legacyMigrationChecked = false;
+
+function parseLegacyModelKey(
+  key: string,
+): { modelId: string; ggufVariant: string | null } | null {
+  const separator = key.lastIndexOf("::");
+  if (separator >= 0) {
+    const modelId = key.slice(0, separator);
+    return modelId
+      ? { modelId, ggufVariant: key.slice(separator + 2) || null }
+      : null;
+  }
+  return key ? { modelId: key, ggufVariant: null } : null;
+}
+
+function legacyEntryToConfig(raw: Record<string, unknown>): PerModelConfig {
+  return normalizeV1({
+    customContextLength:
+      typeof raw.contextLength === "number" ? raw.contextLength : null,
+    maxSeqLength: null,
+    kvCacheDtype:
+      typeof raw.kvCacheDtype === "string" ? raw.kvCacheDtype : null,
+    speculativeType:
+      typeof raw.speculativeType === "string" ? raw.speculativeType : null,
+    specDraftNMax:
+      typeof raw.specDraftNMax === "number" ? raw.specDraftNMax : null,
+    tensorParallel:
+      typeof raw.tensorParallel === "boolean" ? raw.tensorParallel : false,
+    chatTemplateOverride: null,
+  });
+}
+
+function mergeLegacyEntries(
+  map: StoredMap,
+  legacy: Record<string, unknown>,
+): string[] {
+  const addedKeys: string[] = [];
+  for (const [legacyKey, value] of Object.entries(legacy)) {
+    if (!value || typeof value !== "object") {
+      continue;
+    }
+    const parsedKey = parseLegacyModelKey(legacyKey);
+    if (!parsedKey) {
+      continue;
+    }
+    const migrated = legacyEntryToConfig(value as Record<string, unknown>);
+    const key = modelStorageKey(parsedKey.modelId, parsedKey.ggufVariant);
+    if (isDefaultConfig(migrated) || Object.hasOwn(map, key)) {
+      continue;
+    }
+    map[key] = toStoredConfig(migrated);
+    addedKeys.push(key);
+  }
+  return addedKeys;
+}
+
+function migrateLegacyLoadSettingsOnce(): void {
+  if (legacyMigrationChecked || !canUseStorage()) {
+    return;
+  }
+  legacyMigrationChecked = true;
+  try {
+    if (localStorage.getItem(LEGACY_MIGRATION_FLAG)) {
+      return;
+    }
+    let legacy: unknown = null;
+    try {
+      legacy = JSON.parse(localStorage.getItem(LEGACY_STORAGE_KEY) ?? "null");
+    } catch {
+      legacy = null;
+    }
+    if (!legacy || typeof legacy !== "object" || Array.isArray(legacy)) {
+      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
+      return;
+    }
+    const map = readMapRaw();
+    const migratedKeys = mergeLegacyEntries(
+      map,
+      legacy as Record<string, unknown>,
+    );
+    if (migratedKeys.length === 0) {
+      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
+      return;
+    }
+    // Protect the just-migrated entries during eviction. If the budget cannot
+    // fit them (e.g. storage is full of future-schema records an older client
+    // cannot evict), leave the flag unset so migration retries once space frees
+    // up rather than marking it complete and dropping the migrated config.
+    if (!enforceStorageBudget(map, new Set(migratedKeys))) {
+      return;
+    }
+    if (writeMap(map)) {
+      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
+    }
+  } catch (err) {
+    console.warn("Failed to migrate legacy load settings:", err);
+  }
+}
+
+function readMapRaw(): StoredMap {
+  if (!canUseStorage()) {
+    return {};
+  }
+  try {
+    const raw = localStorage.getItem(STORAGE_KEY);
+    if (!raw) {
+      return {};
+    }
+    const parsed = JSON.parse(raw);
+    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) {
+      return {};
+    }
+    return parsed as StoredMap;
+  } catch {
+    return {};
+  }
+}
+
+function readMap(): StoredMap {
+  migrateLegacyLoadSettingsOnce();
+  return readMapRaw();
+}
+
+function writeMap(map: StoredMap): boolean {
+  if (!canUseStorage()) {
+    return false;
+  }
+  try {
+    localStorage.setItem(STORAGE_KEY, JSON.stringify(map));
+    return true;
+  } catch (err) {
+    console.warn("Failed to persist per-model config:", err);
+    return false;
+  }
+}
+
+function warnDroppedFields(raw: Record<string, unknown>, version: number): void {
+  if (!import.meta.env?.DEV) {
+    return;
+  }
+  const dropped = Object.keys(raw).filter(
+    (key) => !STORED_CONFIG_FIELDS.has(key),
+  );
+  if (dropped.length > 0) {
+    console.warn("Dropped unknown per-model config fields:", dropped);
+  }
+  if (version > STORAGE_SCHEMA_VERSION) {
+    console.warn("Per-model config schema is newer than this app:", version);
+  }
+}
+
+function normalizeV1(partial: RawConfig): PerModelConfig {
+  const rawSpecType =
+    typeof partial.speculativeType === "string"
+      ? canonicalizeSpeculativeType(partial.speculativeType)
+      : null;
+  const speculativeType = rawSpecType ?? DEFAULT_PER_MODEL_CONFIG.speculativeType;
+  const specDraftNMax =
+    speculativeType != null &&
+    MTP_SPECULATIVE_TYPES.has(speculativeType) &&
+    typeof partial.specDraftNMax === "number" &&
+    Number.isFinite(partial.specDraftNMax)
+      ? Math.max(1, Math.min(16, Math.round(partial.specDraftNMax)))
+      : null;
+  return {
+    customContextLength:
+      typeof partial.customContextLength === "number" &&
+      Number.isFinite(partial.customContextLength) &&
+      partial.customContextLength > 0
+        ? Math.floor(partial.customContextLength)
+        : null,
+    maxSeqLength: normalizeMaxSeqLength(partial.maxSeqLength),
+    kvCacheDtype:
+      typeof partial.kvCacheDtype === "string" &&
+      VALID_KV_CACHE_DTYPES.has(partial.kvCacheDtype)
+        ? partial.kvCacheDtype
+        : null,
+    speculativeType,
+    specDraftNMax,
+    tensorParallel:
+      typeof partial.tensorParallel === "boolean"
+        ? partial.tensorParallel
+        : DEFAULT_PER_MODEL_CONFIG.tensorParallel,
+    chatTemplateOverride:
+      typeof partial.chatTemplateOverride === "string" &&
+      isChatTemplateWithinLimit(partial.chatTemplateOverride)
+        ? partial.chatTemplateOverride
+        : null,
+  };
+}
+
+function normalize(raw: unknown): PerModelConfig {
+  if (!raw || typeof raw !== "object" || Array.isArray(raw)) {
+    return normalizeV1({});
+  }
+  const partial = raw as RawConfig;
+  const version =
+    typeof partial.version === "number" && Number.isFinite(partial.version)
+      ? partial.version
+      : 0;
+  warnDroppedFields(raw as Record<string, unknown>, version);
+  return normalizeV1(partial);
+}
+
+function toStoredConfig(config: PerModelConfig): StoredPerModelConfig {
+  return {
+    version: STORAGE_SCHEMA_VERSION,
+    ...normalize(config),
+  };
+}
+
+function legacyModelStorageKey(
+  modelId: string,
+  ggufVariant?: string | null,
+): string {
+  return `${modelId}::${ggufVariant ?? ""}`;
+}
+
+function storageKeysForModelVariant(
+  modelId: string,
+  ggufVariant?: string | null,
+): string[] {
+  const key = modelStorageKey(modelId, ggufVariant);
+  const legacyKey = legacyModelStorageKey(modelId, ggufVariant);
+  return key === legacyKey ? [key] : [key, legacyKey];
+}
+
+function configKeyMatchesModelVariant(
+  key: string,
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  const storedModelId = modelIdFromStorageKey(key);
+  if (!storedModelId) {
+    return false;
+  }
+  return (
+    normalizeModelIdentity(storedModelId) === normalizeModelIdentity(modelId) &&
+    normalizeGgufVariantIdentity(ggufVariantFromStorageKey(key)) ===
+      normalizeGgufVariantIdentity(ggufVariant)
+  );
+}
+
+function findConfigKeyForModelVariant(
+  map: StoredMap,
+  modelId: string,
+  ggufVariant?: string | null,
+): string | null {
+  for (const key of storageKeysForModelVariant(modelId, ggufVariant)) {
+    if (Object.hasOwn(map, key)) {
+      return key;
+    }
+  }
+  for (const key of Object.keys(map)) {
+    if (configKeyMatchesModelVariant(key, modelId, ggufVariant)) {
+      return key;
+    }
+  }
+  return null;
+}
+
+function hasFutureConfigForModelVariant(
+  map: StoredMap,
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  for (const key of Object.keys(map)) {
+    if (
+      configKeyMatchesModelVariant(key, modelId, ggufVariant) &&
+      storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION
+    ) {
+      return true;
+    }
+  }
+  return false;
+}
+
+function deleteConfigEntriesForModelVariant(
+  map: StoredMap,
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  let changed = false;
+  for (const key of Object.keys(map)) {
+    if (!configKeyMatchesModelVariant(key, modelId, ggufVariant)) {
+      continue;
+    }
+    delete map[key];
+    changed = true;
+  }
+  return changed;
+}
+
+function loadPerModelConfig(
+  modelId: string,
+  ggufVariant?: string | null,
+): PerModelConfig | null {
+  const map = readMap();
+  const key = findConfigKeyForModelVariant(map, modelId, ggufVariant);
+  if (!key) {
+    return null;
+  }
+  // Never apply a future-schema record an older client cannot interpret,
+  // matching the save/delete/evict guards.
+  if (storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION) {
+    return null;
+  }
+  return normalize(map[key]);
+}
+
+export function isDefaultConfig(config: PerModelConfig): boolean {
+  return (
+    config.customContextLength == null &&
+    config.maxSeqLength == null &&
+    (config.kvCacheDtype ?? null) === DEFAULT_PER_MODEL_CONFIG.kvCacheDtype &&
+    config.speculativeType === DEFAULT_PER_MODEL_CONFIG.speculativeType &&
+    config.specDraftNMax == null &&
+    Boolean(config.tensorParallel) ===
+      Boolean(DEFAULT_PER_MODEL_CONFIG.tensorParallel) &&
+    (config.chatTemplateOverride ?? null) === null
+  );
+}
+
+export function savePerModelConfig(
+  modelId: string,
+  ggufVariant: string | null | undefined,
+  config: PerModelConfig,
+): boolean {
+  if (
+    typeof config.chatTemplateOverride === "string" &&
+    !isChatTemplateWithinLimit(config.chatTemplateOverride)
+  ) {
+    return false;
+  }
+  const normalized = normalize(config);
+  const map = readMap();
+  if (hasFutureConfigForModelVariant(map, modelId, ggufVariant)) {
+    return false;
+  }
+  if (isDefaultConfig(normalized)) {
+    const changed = deleteConfigEntriesForModelVariant(
+      map,
+      modelId,
+      ggufVariant,
+    );
+    return changed ? writeMap(map) : true;
+  }
+  const [key] = storageKeysForModelVariant(modelId, ggufVariant);
+  deleteConfigEntriesForModelVariant(map, modelId, ggufVariant);
+  map[key] = toStoredConfig(normalized);
+  if (!enforceStorageBudget(map, new Set([key]))) {
+    return false;
+  }
+  return writeMap(map);
+}
+
+export function deletePerModelConfig(
+  modelId: string,
+  ggufVariant?: string | null,
+): boolean {
+  const map = readMap();
+  // Mirror savePerModelConfig: never let an older client destroy a
+  // future-schema entry it cannot interpret.
+  if (hasFutureConfigForModelVariant(map, modelId, ggufVariant)) {
+    return false;
+  }
+  if (!deleteConfigEntriesForModelVariant(map, modelId, ggufVariant)) {
+    return true;
+  }
+  return writeMap(map);
+}
+
+export function resolveInitialConfig(
+  modelId: string,
+  ggufVariant?: string | null,
+): { config: PerModelConfig; remembered: boolean } {
+  const saved = loadPerModelConfig(modelId, ggufVariant);
+  if (saved) {
+    return { config: saved, remembered: true };
+  }
+  return { config: { ...DEFAULT_PER_MODEL_CONFIG }, remembered: false };
+}
diff --git a/studio/frontend/src/features/settings/tabs/chat-tab.tsx b/studio/frontend/src/features/settings/tabs/chat-tab.tsx
index d5c9f10a4f..376372971c 100644
--- a/studio/frontend/src/features/settings/tabs/chat-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/chat-tab.tsx
@@ -43,7 +43,6 @@ import {
   Folder01Icon,
   McpServerIcon,
   PencilRulerIcon,
-  Settings02Icon,
   ShieldBanIcon,
   Upload01Icon,
 } from "@hugeicons/core-free-icons";
@@ -196,10 +195,6 @@ export function ChatTab() {
   const hydratePersistedSettings = useChatRuntimeStore(
     (state) => state.hydratePersistedSettings,
   );
-  const loadOnSelection = useChatRuntimeStore((state) => state.loadOnSelection);
-  const setLoadOnSelection = useChatRuntimeStore(
-    (state) => state.setLoadOnSelection,
-  );
   const expandQuantizations = useChatRuntimeStore(
     (state) => state.expandQuantizations,
   );
@@ -333,40 +328,6 @@ export function ChatTab() {
       </header>
 
       <SettingsSection title="Select model settings">
-        <SettingsRow
-          label="Load on selection"
-          alignTop={true}
-          description={
-            <span>
-              On: Unsloth auto-picks the best settings and loads it.
-              <br />
-              Off: opens Run settings to customize, then load.
-              <br />
-              The gear always opens Run settings:{" "}
-              <span className="ml-2 inline-flex items-center gap-3 align-middle">
-                <span className="font-mono text-xs text-foreground">
-                  Q4_K_M
-                </span>
-                <span className="text-[9px] font-medium text-green-400">
-                  downloaded
-                </span>
-                <span className="text-[10px] text-muted-foreground">16 GB</span>
-                <span className="inline-flex size-4 items-center justify-center rounded bg-black/[0.06] dark:bg-white/[0.08]">
-                  <HugeiconsIcon
-                    icon={Settings02Icon}
-                    strokeWidth={1.75}
-                    className="size-2.5 text-muted-foreground/80"
-                  />
-                </span>
-              </span>
-            </span>
-          }
-        >
-          <Switch
-            checked={loadOnSelection}
-            onCheckedChange={setLoadOnSelection}
-          />
-        </SettingsRow>
         <SettingsRow
           label="Expand quantizations"
           description={
diff --git a/studio/frontend/src/features/settings/tabs/general-tab.tsx b/studio/frontend/src/features/settings/tabs/general-tab.tsx
index 73a33fd155..c79b6465ac 100644
--- a/studio/frontend/src/features/settings/tabs/general-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/general-tab.tsx
@@ -92,9 +92,10 @@ const PREFS_KEYS: string[] = [
   "unsloth_chat_inference_params",
   "unsloth_chat_collapsible_state",
   "unsloth_chat_preferences",
+  "unsloth_model_configs",
+  "unsloth_model_configs_migrated",
   "unsloth_load_settings",
   // Model selector settings ("Select model settings" group)
-  "unsloth_chat_load_on_selection",
   "unsloth_chat_expand_quantizations",
   "unsloth_chat_show_all_quantizations",
   "unsloth_models_fit_on_device_only",
diff --git a/studio/frontend/src/features/training/index.ts b/studio/frontend/src/features/training/index.ts
index 553dcc2af5..fcb30f379c 100644
--- a/studio/frontend/src/features/training/index.ts
+++ b/studio/frontend/src/features/training/index.ts
@@ -24,8 +24,8 @@ export { HfDatasetSubsetSplitSelectors } from "./components/hf-dataset-subset-sp
 export { useDatasetPreviewDialogStore } from "./stores/dataset-preview-dialog-store";
 export { listLocalDatasets, uploadTrainingDataset } from "./api/datasets-api";
 export type { LocalDatasetInfo } from "./types/datasets";
-export { listLocalModels } from "./api/models-api";
-export type { LocalModelInfo } from "./api/models-api";
+export { getModelConfig, listLocalModels } from "./api/models-api";
+export type { LocalModelInfo, ModelConfigResponse } from "./api/models-api";
 export type {
   TrainingPhase,
   TrainingViewData,
diff --git a/tests/studio/playwright_chat_ui.py b/tests/studio/playwright_chat_ui.py
index 065ba7a745..2abec93df1 100644
--- a/tests/studio/playwright_chat_ui.py
+++ b/tests/studio/playwright_chat_ui.py
@@ -678,10 +678,16 @@ with sync_playwright() as p:
     last_assistant = page.locator('[data-role="assistant"]').last
     last_assistant.hover()
     page.wait_for_timeout(400)
-    regen_btn = page.get_by_role(
-        "button",
-        name = re.compile(r"(reload|regenerate)", re.I),
-    ).first
+    # Exclude disabled controls: the picker's new disabled "Reload model"
+    # button also matches and sorts first, so .first would target it.
+    regen_btn = (
+        page.get_by_role(
+            "button",
+            name = re.compile(r"(reload|regenerate)", re.I),
+        )
+        .and_(page.locator("button:not([disabled])"))
+        .first
+    )
     if regen_btn.count() > 0:
         regen_btn.click()
         try:
diff --git a/tests/studio/test_studio_text_descender_clipping.py b/tests/studio/test_studio_text_descender_clipping.py
index 7cad6cacfe..91ca080354 100644
--- a/tests/studio/test_studio_text_descender_clipping.py
+++ b/tests/studio/test_studio_text_descender_clipping.py
@@ -10,7 +10,14 @@ from pathlib import Path
 
 WORKDIR = Path(__file__).resolve().parents[2]
 MODEL_SELECTOR = (
-    WORKDIR / "studio" / "frontend" / "src" / "components" / "assistant-ui" / "model-selector.tsx"
+    WORKDIR
+    / "studio"
+    / "frontend"
+    / "src"
+    / "features"
+    / "model-picker"
+    / "components"
+    / "model-selector.tsx"
 )
 APP_SIDEBAR = WORKDIR / "studio" / "frontend" / "src" / "components" / "app-sidebar.tsx"
 
@@ -34,10 +41,12 @@ def test_model_selector_trigger_label_uses_leading_tight():
 
 def test_sidebar_account_block_uses_leading_tight():
     src = _read(APP_SIDEBAR)
-    # Match the account-block parent div regardless of its gap utility; this
-    # guard is about the leading-* class, not the spacing.
+    # Match the account-block parent div regardless of its layout/spacing
+    # utilities (e.g. min-w-0, flex-1, the gap-* class); this guard is about the
+    # leading-* class immediately before the collapsible visibility utility, not
+    # the surrounding flex plumbing.
     pattern = re.compile(
-        r'<div\s+className="flex\s+flex-col\s+gap-\S+\s+(\S+)\s+group-data-\[collapsible=icon\]:hidden">',
+        r'<div\s+className="flex\b[^"]*\bflex-col\b[^"]*\bgap-\S+\s+(\S+)\s+group-data-\[collapsible=icon\]:hidden">',
     )
     matches = pattern.findall(src)
     assert matches, "could not find sidebar account-block parent div"

From 1c7bce427e5bcb8ccb3dece9e9fa3a572f6f0139 Mon Sep 17 00:00:00 2001
From: oobabooga <112222186+oobabooga@users.noreply.github.com>
Date: Fri, 17 Jul 2026 07:38:46 -0700
Subject: [PATCH 10/28] Revert "Feat/model picker per model config (#6647)"

This reverts commit 8cbdfbe355a83b6cc0706e2ed8ec1c737b71c3f3.
---
 studio/backend/hub/schemas/inventory.py       |   1 -
 .../hub/services/models/cache_inventory.py    |  74 +-
 studio/backend/main.py                        |   3 -
 studio/backend/picker/__init__.py             |   2 -
 studio/backend/picker/routes/__init__.py      |   6 -
 studio/backend/picker/routes/templates.py     |  42 -
 studio/backend/picker/schemas.py              |  32 -
 studio/backend/picker/service.py              | 361 -------
 .../tests/test_model_update_robustness.py     |  46 -
 studio/backend/tests/test_picker_service.py   | 162 ---
 studio/backend/utils/models/gguf_metadata.py  |  79 --
 studio/frontend/src/app/routes/__root.tsx     |   7 +
 .../assistant-ui}/model-selector.tsx          | 130 +--
 .../model-selector/folder-browser.tsx         |  79 +-
 .../model-selector/model-capabilities.ts      |   0
 .../model-selector/model-delete-action.tsx    |   9 +-
 .../model-load-settings-action.tsx            |  19 +-
 .../model-selector/model-update-action.tsx    |  25 +-
 .../model-selector/model-usage.ts             |   3 +-
 .../assistant-ui}/model-selector/pickers.tsx  | 645 +++++-------
 .../model-selector/pill-tabs.tsx              |   3 +-
 .../model-selector/recommended-fit.ts         |   0
 .../remembered-load-settings.ts               |  69 ++
 .../assistant-ui}/model-selector/row-meta.ts  |   0
 .../model-selector/source-tabs.ts             |   0
 .../assistant-ui}/model-selector/types.ts     |  13 -
 .../src/features/chat/api/chat-adapter.ts     |  50 +-
 .../frontend/src/features/chat/chat-page.tsx  | 517 ++++------
 .../src/features/chat/chat-settings-sheet.tsx | 957 +++++++++++++++---
 .../chat/hooks/use-chat-model-runtime.ts      | 105 +-
 .../hooks/use-staged-model-preparation.ts     | 155 +++
 studio/frontend/src/features/chat/index.ts    |  18 -
 .../lib/apply-inference-status-to-store.ts    |   5 +
 .../src/features/chat/shared-composer.tsx     | 111 +-
 .../chat/stores/chat-runtime-store.ts         | 186 +++-
 .../export/components/export-run-panel.tsx    |  71 +-
 .../hub/catalog/models-catalog-rows.tsx       |  41 +-
 .../hub/catalog/on-device-folders-dialog.tsx  |  33 +-
 .../download-manager-controller.ts            |  23 +
 .../features/hub/download-manager/index.ts    |   1 +
 studio/frontend/src/features/hub/hub-page.tsx | 129 ++-
 studio/frontend/src/features/hub/index.ts     |  58 +-
 .../src/features/hub/inventory/api.ts         |   2 -
 .../src/features/hub/inventory/types.ts       |   3 -
 .../src/features/hub/inventory/view-models.ts |   9 -
 .../model-picker/api/model-metadata.ts        |  20 -
 .../features/model-picker/api/templates.ts    |  51 -
 .../chat-template-editor-dialog.tsx           | 191 ----
 .../components/model-config-page.tsx          | 742 --------------
 .../components/numeric-value-input.tsx        | 113 ---
 .../components/sidebar-model-config.tsx       |  89 --
 .../model-picker/hooks/use-model-defaults.ts  | 176 ----
 .../src/features/model-picker/index.ts        |  30 -
 .../inventory/use-chat-picker-inventory.ts    | 118 ---
 .../model-config/apply-per-model-config.ts    |  85 --
 .../model-config/model-identity.ts            |  69 --
 .../model-config/per-model-config.ts          | 571 -----------
 .../src/features/settings/tabs/chat-tab.tsx   |  39 +
 .../features/settings/tabs/general-tab.tsx    |   3 +-
 .../frontend/src/features/training/index.ts   |   4 +-
 tests/studio/playwright_chat_ui.py            |  14 +-
 .../test_studio_text_descender_clipping.py    |  17 +-
 62 files changed, 2133 insertions(+), 4483 deletions(-)
 delete mode 100644 studio/backend/picker/__init__.py
 delete mode 100644 studio/backend/picker/routes/__init__.py
 delete mode 100644 studio/backend/picker/routes/templates.py
 delete mode 100644 studio/backend/picker/schemas.py
 delete mode 100644 studio/backend/picker/service.py
 delete mode 100644 studio/backend/tests/test_picker_service.py
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector.tsx (86%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/folder-browser.tsx (88%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/model-capabilities.ts (100%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/model-delete-action.tsx (90%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/model-load-settings-action.tsx (66%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/model-update-action.tsx (82%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/model-usage.ts (93%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/pickers.tsx (89%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/pill-tabs.tsx (98%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/recommended-fit.ts (100%)
 create mode 100644 studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/row-meta.ts (100%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/source-tabs.ts (100%)
 rename studio/frontend/src/{features/model-picker/components => components/assistant-ui}/model-selector/types.ts (76%)
 create mode 100644 studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
 delete mode 100644 studio/frontend/src/features/model-picker/api/model-metadata.ts
 delete mode 100644 studio/frontend/src/features/model-picker/api/templates.ts
 delete mode 100644 studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
 delete mode 100644 studio/frontend/src/features/model-picker/components/model-config-page.tsx
 delete mode 100644 studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
 delete mode 100644 studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
 delete mode 100644 studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
 delete mode 100644 studio/frontend/src/features/model-picker/index.ts
 delete mode 100644 studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
 delete mode 100644 studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
 delete mode 100644 studio/frontend/src/features/model-picker/model-config/model-identity.ts
 delete mode 100644 studio/frontend/src/features/model-picker/model-config/per-model-config.ts

diff --git a/studio/backend/hub/schemas/inventory.py b/studio/backend/hub/schemas/inventory.py
index f81c9a3498..ef95efe2f2 100644
--- a/studio/backend/hub/schemas/inventory.py
+++ b/studio/backend/hub/schemas/inventory.py
@@ -160,7 +160,6 @@ class CachedRepoBase(BaseModel):
     repo_id: str
     size_bytes: int = 0
     cache_path: Optional[str] = None
-    last_modified: Optional[float] = None
     partial: bool = False
     partial_transport: Optional[str] = None
     inventory_id: Optional[str] = None
diff --git a/studio/backend/hub/services/models/cache_inventory.py b/studio/backend/hub/services/models/cache_inventory.py
index ba3a266bfb..1f38af9381 100644
--- a/studio/backend/hub/services/models/cache_inventory.py
+++ b/studio/backend/hub/services/models/cache_inventory.py
@@ -31,7 +31,6 @@ from hub.services.models.common import (
     _is_checkpoint_weight_name,
     _is_gguf_filename,
     _is_main_gguf_filename,
-    _is_mmproj_filename,
     _is_transformers_safetensors_weight_name,
     _local_inventory_id,
     _prefer_complete_larger,
@@ -126,34 +125,6 @@ def _repo_has_gguf_files(repo_info) -> bool:
     return _repo_gguf_size_bytes(repo_info) > 0
 
 
-def _blob_mtime(file_obj) -> float:
-    ts = getattr(file_obj, "blob_last_modified", None)
-    if isinstance(ts, (int, float)) and ts > 0:
-        return float(ts)
-    blob_path = getattr(file_obj, "blob_path", None)
-    if blob_path:
-        try:
-            return float(Path(blob_path).stat().st_mtime)
-        except OSError:
-            pass
-    return 0.0
-
-
-def _repo_gguf_last_modified(repo_info) -> float:
-    latest = 0.0
-    for revision in repo_info.revisions:
-        for f in revision.files:
-            if _is_main_gguf_filename(f.file_name):
-                latest = max(latest, _blob_mtime(f))
-    return latest
-
-
-def _repo_has_mmproj(repo_info) -> bool:
-    return any(
-        _is_mmproj_filename(f.file_name) for revision in repo_info.revisions for f in revision.files
-    )
-
-
 def _cached_repo_file_name(file_obj) -> str:
     file_path = getattr(file_obj, "file_path", None)
     if file_path:
@@ -295,7 +266,6 @@ def _scan_cached_gguf() -> list[dict]:
                     continue
                 key = repo_id.lower()
                 existing = seen_lower.get(key)
-                last_modified = _repo_gguf_last_modified(repo_info)
                 row = {
                     "repo_id": repo_id,
                     "size_bytes": max(total_size, variant_state_size),
@@ -305,9 +275,6 @@ def _scan_cached_gguf() -> list[dict]:
                     # per-variant detail lives on GgufVariantDetail.
                     "partial_transport": None,
                 }
-                last_modified = max(last_modified, (existing or {}).get("last_modified", 0.0))
-                if last_modified > 0:
-                    row["last_modified"] = last_modified
                 row.update(
                     _cache_inventory_fields(
                         repo_id,
@@ -316,12 +283,8 @@ def _scan_cached_gguf() -> list[dict]:
                         requires_variant = True,
                     )
                 )
-                if _repo_has_mmproj(repo_info):
-                    row["capabilities"]["supports_vision"] = True
                 if _prefer_cache_row(row, existing):
                     seen_lower[key] = row
-                elif last_modified > existing.get("last_modified", 0.0):
-                    existing["last_modified"] = last_modified
             except Exception as e:
                 repo_label = getattr(repo_info, "repo_id", "<unknown>")
                 logger.warning(f"Skipping cached GGUF repo {repo_label}: {e}")
@@ -349,14 +312,13 @@ class _CachedNonGgufPayload(NamedTuple):
     size_bytes: int
     has_runnable_weights: bool
     model_format: ModelFormat
-    last_modified: float
 
 
 def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
-    all_weight_blobs: dict[str, tuple[int, float]] = {}
-    adapter_blobs: dict[str, tuple[int, float]] = {}
-    safetensors_blobs: dict[str, tuple[int, float]] = {}
-    checkpoint_blobs: dict[str, tuple[int, float]] = {}
+    all_weight_blobs: dict[str, int] = {}
+    adapter_blobs: dict[str, int] = {}
+    safetensors_blobs: dict[str, int] = {}
+    checkpoint_blobs: dict[str, int] = {}
     has_config = False
     has_adapter_config = False
     has_adapter_weights = False
@@ -364,15 +326,12 @@ def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
     has_transformers_safetensors = False
     has_checkpoint = False
 
-    def _record_blob(
-        target: dict[str, tuple[int, float]], file_obj, rev_id: str, file_name: str
-    ) -> None:
+    def _record_blob(target: dict[str, int], file_obj, rev_id: str, file_name: str) -> None:
         blob_path = getattr(file_obj, "blob_path", None)
         size = int(file_obj.size_on_disk or 0)
         key = str(blob_path) if blob_path else f"{rev_id}:{file_name}"
-        value = (size, _blob_mtime(file_obj))
-        target[key] = value
-        all_weight_blobs[key] = value
+        target[key] = size
+        all_weight_blobs[key] = size
 
     for revision in repo_info.revisions:
         rev_id = getattr(revision, "commit_hash", None) or str(id(revision))
@@ -416,19 +375,18 @@ def _repo_non_gguf_model_payload(repo_info) -> _CachedNonGgufPayload:
         or "unknown"
     )
     if model_format == "adapter":
-        selected_blobs = adapter_blobs
+        size_bytes = sum(adapter_blobs.values())
     elif model_format == "safetensors":
-        selected_blobs = safetensors_blobs
+        size_bytes = sum(safetensors_blobs.values())
     elif model_format == "checkpoint":
-        selected_blobs = checkpoint_blobs
+        size_bytes = sum(checkpoint_blobs.values())
     else:
-        selected_blobs = all_weight_blobs
+        size_bytes = sum(all_weight_blobs.values())
 
     return _CachedNonGgufPayload(
-        size_bytes = sum(size for size, _mtime in selected_blobs.values()),
+        size_bytes = size_bytes,
         has_runnable_weights = model_format != "unknown",
         model_format = model_format,
-        last_modified = max((mtime for _size, mtime in selected_blobs.values()), default = 0.0),
     )
 
 
@@ -550,12 +508,6 @@ def _scan_cached_models() -> list[dict]:
                     ),
                     **_cached_model_local_metadata(repo_path),
                 }
-                last_modified = max(
-                    payload.last_modified,
-                    (existing or {}).get("last_modified", 0.0),
-                )
-                if last_modified > 0:
-                    row["last_modified"] = last_modified
                 row.update(
                     _cache_inventory_fields(
                         repo_id,
@@ -565,8 +517,6 @@ def _scan_cached_models() -> list[dict]:
                 )
                 if _prefer_cache_row(row, existing):
                     seen_lower[key] = row
-                elif last_modified > existing.get("last_modified", 0.0):
-                    existing["last_modified"] = last_modified
             except Exception as e:
                 repo_label = getattr(repo_info, "repo_id", "<unknown>")
                 logger.warning(f"Skipping cached model repo {repo_label}: {e}")
diff --git a/studio/backend/main.py b/studio/backend/main.py
index bd0d26cf8f..e64048dc00 100644
--- a/studio/backend/main.py
+++ b/studio/backend/main.py
@@ -313,7 +313,6 @@ from hub.routes import (
     inventory_router as hub_inventory_router,
     datasets_router as hub_datasets_router,
 )
-from picker.routes import templates_router as picker_templates_router
 from hub.schemas.downloads import TransportCapabilities
 from hub.utils.download_registry import (
     get_download_transport_capabilities,
@@ -746,7 +745,6 @@ _BODY_PROTECTED_PREFIXES = (
     "/v1/completions",
     "/p/",
     "/api/inference",
-    "/api/picker",
     "/api/data-recipe",
     "/api/datasets",
     "/api/hub",
@@ -977,7 +975,6 @@ app.include_router(rag_router, prefix = "/api/rag", tags = ["rag"])
 app.include_router(training_history_router, prefix = "/api/train", tags = ["training-history"])
 app.include_router(hub_inventory_router, prefix = "/api/hub", tags = ["hub"])
 app.include_router(hub_datasets_router, prefix = "/api/hub/datasets", tags = ["hub"])
-app.include_router(picker_templates_router, prefix = "/api/picker", tags = ["picker"])
 
 # Re-wrap client-error responses on the /v1/* surface into OpenAI/Anthropic
 # error envelopes; non-/v1 paths keep FastAPI's default {"detail": ...} shape.
diff --git a/studio/backend/picker/__init__.py b/studio/backend/picker/__init__.py
deleted file mode 100644
index 32014236c6..0000000000
--- a/studio/backend/picker/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-only
-# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
diff --git a/studio/backend/picker/routes/__init__.py b/studio/backend/picker/routes/__init__.py
deleted file mode 100644
index c0e988c8bb..0000000000
--- a/studio/backend/picker/routes/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-only
-# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-from .templates import router as templates_router
-
-__all__ = ["templates_router"]
diff --git a/studio/backend/picker/routes/templates.py b/studio/backend/picker/routes/templates.py
deleted file mode 100644
index 03707669fa..0000000000
--- a/studio/backend/picker/routes/templates.py
+++ /dev/null
@@ -1,42 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-only
-# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-from __future__ import annotations
-
-import asyncio
-from typing import Optional
-
-from fastapi import APIRouter, Body, Depends, Query
-
-from auth.authentication import get_current_subject
-from hub.dependencies import get_hf_token
-
-from ..schemas import (
-    ModelTemplateResponse,
-    ValidateChatTemplateRequest,
-    ValidateChatTemplateResponse,
-)
-from ..service import read_default_chat_template, validate_chat_template
-
-router = APIRouter()
-
-
-@router.post("/validate-chat-template", response_model = ValidateChatTemplateResponse)
-async def validate_chat_template_route(
-    body: ValidateChatTemplateRequest = Body(...),
-    current_subject: str = Depends(get_current_subject),
-) -> ValidateChatTemplateResponse:
-    return await asyncio.to_thread(validate_chat_template, body.template)
-
-
-@router.get("/chat-template/{model_name:path}", response_model = ModelTemplateResponse)
-async def get_default_chat_template_route(
-    model_name: str,
-    gguf_variant: Optional[str] = Query(None),
-    hf_token: Optional[str] = Depends(get_hf_token),
-    current_subject: str = Depends(get_current_subject),
-) -> ModelTemplateResponse:
-    template = await asyncio.to_thread(
-        read_default_chat_template, model_name, hf_token, gguf_variant
-    )
-    return ModelTemplateResponse(model_name = model_name, chat_template = template)
diff --git a/studio/backend/picker/schemas.py b/studio/backend/picker/schemas.py
deleted file mode 100644
index b4f956188f..0000000000
--- a/studio/backend/picker/schemas.py
+++ /dev/null
@@ -1,32 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-only
-# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-from typing import Optional
-
-from pydantic import BaseModel, Field, field_validator
-
-# Mirror the frontend's 64 KiB chat-template contract (per-model-config.ts) at
-# the API boundary so a direct caller cannot make Jinja parse an oversized
-# template. MaxBodyMiddleware only caps the whole request body, not this field.
-MAX_CHAT_TEMPLATE_BYTES = 65_536
-
-
-class ValidateChatTemplateRequest(BaseModel):
-    template: str = Field(default = "")
-
-    @field_validator("template")
-    @classmethod
-    def _enforce_template_size(cls, value: str) -> str:
-        if len(value.encode("utf-8")) > MAX_CHAT_TEMPLATE_BYTES:
-            raise ValueError(f"Chat template exceeds the {MAX_CHAT_TEMPLATE_BYTES}-byte limit.")
-        return value
-
-
-class ValidateChatTemplateResponse(BaseModel):
-    valid: bool
-    error: Optional[str] = None
-
-
-class ModelTemplateResponse(BaseModel):
-    model_name: str
-    chat_template: Optional[str] = None
diff --git a/studio/backend/picker/service.py b/studio/backend/picker/service.py
deleted file mode 100644
index f5994dc550..0000000000
--- a/studio/backend/picker/service.py
+++ /dev/null
@@ -1,361 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-only
-# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-from __future__ import annotations
-
-import json
-import logging
-import os
-import re
-from pathlib import Path
-from typing import Optional
-
-from hub.services.models.folder_browser import (
-    _build_browse_allowlist,
-    _is_path_inside_allowlist,
-)
-from hub.utils.gguf import iter_hf_cache_snapshots
-from utils.models.gguf_metadata import read_gguf_chat_template
-from utils.models.model_config import (
-    _extract_quant_label,
-    _is_big_endian_gguf_path,
-    _is_mmproj,
-    _is_mtp_drafter,
-)
-from utils.paths.path_utils import (
-    is_local_path,
-    normalize_path,
-    resolve_cached_repo_id_case,
-)
-
-from .schemas import ValidateChatTemplateResponse
-
-logger = logging.getLogger(__name__)
-
-_VALID_REPO_ID = re.compile(r"^[A-Za-z0-9._-]+/[A-Za-z0-9._-]+$")
-
-
-def _is_valid_repo_id(repo_id: str) -> bool:
-    return bool(_VALID_REPO_ID.fullmatch(repo_id))
-
-
-_TOKENIZER_CONFIG_PATHS = ("tokenizer_config.json", "LLM/tokenizer_config.json")
-_JINJA_TEMPLATE_PATHS = ("chat_template.jinja", "LLM/chat_template.jinja")
-_PROCESSOR_TEMPLATE_PATHS = ("chat_template.json", "LLM/chat_template.json")
-
-
-def _leaf_inside_allowlist(path: Path, allow_roots: Optional[list[Path]]) -> bool:
-    # Block symlinked children from escaping the validated directory
-    # (realpath-checked). None = trusted caller (HF cache / remote download).
-    return allow_roots is None or _is_path_inside_allowlist(path, allow_roots)
-
-
-def validate_chat_template(template: str) -> ValidateChatTemplateResponse:
-    text = (template or "").strip()
-    if not text:
-        return ValidateChatTemplateResponse(valid = True, error = None)
-    # Import Jinja lazily: it is optional at runtime (e.g. GGUF-only installs),
-    # so a missing dependency must not crash API startup through this module.
-    try:
-        from jinja2 import TemplateError
-        from jinja2.ext import Extension
-        from jinja2.sandbox import ImmutableSandboxedEnvironment
-    except ImportError:
-        return ValidateChatTemplateResponse(valid = True, error = None)
-
-    class _GenerationTag(Extension):
-        # Accept Transformers' {% generation %}...{% endgeneration %} assistant
-        # mask tag so a pasted HF chat template validates (we only parse it).
-        tags = {"generation"}
-
-        def parse(self, parser):
-            next(parser.stream)
-            return parser.parse_statements(["name:endgeneration"], drop_needle = True)
-
-    try:
-        env = ImmutableSandboxedEnvironment(
-            trim_blocks = True,
-            lstrip_blocks = True,
-            extensions = ["jinja2.ext.loopcontrols", _GenerationTag],
-        )
-        env.parse(text)
-        return ValidateChatTemplateResponse(valid = True, error = None)
-    except TemplateError as exc:
-        message = getattr(exc, "message", None) or str(exc)
-        lineno = getattr(exc, "lineno", None)
-        if lineno:
-            message = f"Line {lineno}: {message}"
-        return ValidateChatTemplateResponse(valid = False, error = message)
-    except Exception as exc:
-        return ValidateChatTemplateResponse(valid = False, error = str(exc))
-
-
-def _chat_template_from_tokenizer_config(config: dict) -> Optional[str]:
-    if not isinstance(config, dict):
-        return None
-    raw = config.get("chat_template")
-    if isinstance(raw, str) and raw.strip():
-        return raw
-    if isinstance(raw, list):
-        fallback: Optional[str] = None
-        for entry in raw:
-            if not isinstance(entry, dict):
-                continue
-            template = entry.get("template")
-            if not isinstance(template, str):
-                continue
-            if entry.get("name") == "default":
-                return template
-            if fallback is None:
-                fallback = template
-        return fallback
-    return None
-
-
-def _chat_template_from_jinja_file(
-    dir_path: Path, allow_roots: Optional[list[Path]] = None
-) -> Optional[str]:
-    for rel in _JINJA_TEMPLATE_PATHS:
-        template_file = dir_path / rel
-        if not template_file.exists() or not _leaf_inside_allowlist(template_file, allow_roots):
-            continue
-        try:
-            template = template_file.read_text(encoding = "utf-8")
-        except Exception:
-            continue
-        if template.strip():
-            return template
-    return None
-
-
-def _chat_template_from_processor_payload(payload: object) -> Optional[str]:
-    # processor chat_template.json may be the template string itself or a
-    # {name: template} map, not only a tokenizer_config-shaped object.
-    if isinstance(payload, str):
-        return payload if payload.strip() else None
-    template = _chat_template_from_tokenizer_config(payload)  # type: ignore[arg-type]
-    if template:
-        return template
-    if isinstance(payload, dict):
-        # Named-template map: prefer "default", else the first non-empty entry
-        # (mirrors the tokenizer-config list fallback).
-        default = payload.get("default")
-        if isinstance(default, str) and default.strip():
-            return default
-        for value in payload.values():
-            if isinstance(value, str) and value.strip():
-                return value
-    return None
-
-
-def _chat_template_from_processor_json(
-    dir_path: Path, allow_roots: Optional[list[Path]] = None
-) -> Optional[str]:
-    for rel in _PROCESSOR_TEMPLATE_PATHS:
-        config_file = dir_path / rel
-        if not config_file.exists() or not _leaf_inside_allowlist(config_file, allow_roots):
-            continue
-        try:
-            payload = json.loads(config_file.read_text(encoding = "utf-8"))
-        except Exception:
-            continue
-        template = _chat_template_from_processor_payload(payload)
-        if template:
-            return template
-    return None
-
-
-def _chat_template_from_tokenizer_dir(
-    dir_path: Path, allow_roots: Optional[list[Path]] = None
-) -> Optional[str]:
-    jinja = _chat_template_from_jinja_file(dir_path, allow_roots)
-    if jinja:
-        return jinja
-    for rel in _TOKENIZER_CONFIG_PATHS:
-        config_file = dir_path / rel
-        if not config_file.exists() or not _leaf_inside_allowlist(config_file, allow_roots):
-            continue
-        try:
-            config = json.loads(config_file.read_text(encoding = "utf-8"))
-        except Exception:
-            continue
-        template = _chat_template_from_tokenizer_config(config)
-        if template:
-            return template
-    return _chat_template_from_processor_json(dir_path, allow_roots)
-
-
-_GGUF_SCAN_MAX_DEPTH = 2
-
-
-def _iter_ggufs(dir_path: Path) -> list[Path]:
-    if dir_path == dir_path.parent:
-        return []
-    root = str(dir_path)
-    found: list[Path] = []
-    for current, dirs, files in os.walk(root, followlinks = False):
-        rel = os.path.relpath(current, root)
-        depth = 0 if rel == os.curdir else rel.count(os.sep) + 1
-        if depth >= _GGUF_SCAN_MAX_DEPTH:
-            dirs[:] = []
-        for name in files:
-            if not name.lower().endswith(".gguf") or _is_mmproj(name):
-                continue
-            path = Path(current) / name
-            try:
-                rel = path.relative_to(dir_path).as_posix()
-            except ValueError:
-                rel = name
-            quant = _extract_quant_label(rel)
-            if _is_mtp_drafter(rel) or _is_big_endian_gguf_path(rel, quant):
-                continue
-            found.append(path)
-    return found
-
-
-def _variant_matches(relative_path: str, needle: str) -> bool:
-    quant = _extract_quant_label(relative_path).lower()
-    if quant == needle:
-        return True
-    prefix = f"{needle}-"
-    if not quant.startswith(prefix):
-        return False
-    suffix = quant[len(prefix) :]
-    if not suffix.endswith("bpw"):
-        return False
-    value = suffix[:-3]
-    return bool(value) and value.replace(".", "", 1).isdigit()
-
-
-def _find_gguf_in_dir(dir_path: Path, gguf_variant: Optional[str]) -> Optional[Path]:
-    try:
-        ggufs = sorted(_iter_ggufs(dir_path))
-    except OSError:
-        return None
-    if not ggufs:
-        return None
-    needle = (gguf_variant or "").strip().lower()
-    if needle:
-        for path in ggufs:
-            try:
-                relative = path.relative_to(dir_path).as_posix()
-            except ValueError:
-                relative = path.name
-            if _variant_matches(relative, needle):
-                return path
-        return None
-    try:
-        return max(ggufs, key = lambda path: path.stat().st_size)
-    except OSError:
-        return ggufs[0]
-
-
-def _chat_template_from_dir(
-    dir_path: Path,
-    gguf_variant: Optional[str] = None,
-    allow_roots: Optional[list[Path]] = None,
-) -> Optional[str]:
-    def from_gguf() -> Optional[str]:
-        gguf = _find_gguf_in_dir(dir_path, gguf_variant)
-        if gguf is None or not _leaf_inside_allowlist(gguf, allow_roots):
-            return None
-        return read_gguf_chat_template(str(gguf))
-
-    # Sidecar tokenizer files (chat_template.jinja / tokenizer_config.json) are
-    # the model author's maintained template and supersede the GGUF's embedded
-    # copy, which can be stale. The variant only selects which GGUF to fall back
-    # to, so keep tokenizer-first precedence whether or not a variant is given.
-    return _chat_template_from_tokenizer_dir(dir_path, allow_roots) or from_gguf()
-
-
-def read_default_chat_template(
-    model_name: str,
-    hf_token: Optional[str] = None,
-    gguf_variant: Optional[str] = None,
-) -> Optional[str]:
-    if not isinstance(model_name, str) or not model_name.strip():
-        return None
-    name = model_name.strip()
-
-    if is_local_path(name):
-        try:
-            target = Path(normalize_path(name)).expanduser()
-            allow_roots = _build_browse_allowlist()
-            if not _is_path_inside_allowlist(target, allow_roots):
-                logger.debug("Refused chat template read outside allowed folders: %s", name)
-                return None
-            if name.lower().endswith(".gguf"):
-                # Prefer a maintained sidecar template (chat_template.jinja /
-                # tokenizer_config.json) next to the file over the GGUF's embedded
-                # copy, matching the tokenizer-first precedence used for directory
-                # and variant selections.
-                sidecar = _chat_template_from_tokenizer_dir(target.parent, allow_roots)
-                if sidecar:
-                    return sidecar
-                return read_gguf_chat_template(str(target))
-            return _chat_template_from_dir(target, gguf_variant, allow_roots)
-        except Exception as exc:
-            logger.debug("Could not read local chat template for %s: %s", name, exc)
-            return None
-
-    if not _is_valid_repo_id(name):
-        return None
-
-    resolved = resolve_cached_repo_id_case(name)
-
-    try:
-        # Resolve within each cached revision, newest first. A revision's
-        # maintained sidecar (chat_template.jinja / tokenizer_config.json)
-        # supersedes its own embedded GGUF copy, but a newer revision must not be
-        # overridden by an older revision's sidecar, so precedence stays
-        # per-snapshot rather than searching all sidecars globally first.
-        for snapshot in iter_hf_cache_snapshots(resolved):
-            template = _chat_template_from_dir(snapshot, gguf_variant)
-            if template:
-                return template
-    except Exception as exc:
-        logger.debug("Could not read cached chat template for %s: %s", resolved, exc)
-
-    try:
-        from huggingface_hub import hf_hub_download
-
-        def _download_text(rel: str) -> Optional[str]:
-            try:
-                path = hf_hub_download(resolved, rel, token = hf_token)
-                return Path(path).read_text(encoding = "utf-8")
-            except Exception:
-                return None
-
-        for rel in _JINJA_TEMPLATE_PATHS:
-            template = _download_text(rel)
-            if template and template.strip():
-                return template
-
-        for rel in _TOKENIZER_CONFIG_PATHS:
-            raw = _download_text(rel)
-            if not raw:
-                continue
-            try:
-                config = json.loads(raw)
-            except Exception:
-                continue
-            template = _chat_template_from_tokenizer_config(config)
-            if template:
-                return template
-
-        for rel in _PROCESSOR_TEMPLATE_PATHS:
-            raw = _download_text(rel)
-            if not raw:
-                continue
-            try:
-                payload = json.loads(raw)
-            except Exception:
-                continue
-            template = _chat_template_from_processor_payload(payload)
-            if template:
-                return template
-
-        return None
-    except Exception as exc:
-        logger.debug("Could not fetch chat template for %s: %s", resolved, exc)
-        return None
diff --git a/studio/backend/tests/test_model_update_robustness.py b/studio/backend/tests/test_model_update_robustness.py
index 4c5822e662..edf55812e2 100644
--- a/studio/backend/tests/test_model_update_robustness.py
+++ b/studio/backend/tests/test_model_update_robustness.py
@@ -314,7 +314,6 @@ def test_cached_model_scan_keeps_local_safetensors_repo(monkeypatch, tmp_path):
                         file_name = "model.safetensors",
                         size_on_disk = 100,
                         blob_path = str(repo_path / "blobs" / "modelsha"),
-                        blob_last_modified = 3_000.0,
                     ),
                 ]
             )
@@ -337,51 +336,6 @@ def test_cached_model_scan_keeps_local_safetensors_repo(monkeypatch, tmp_path):
     assert rows[0]["repo_id"] == "Org/SafeTensorRepo"
     assert rows[0]["model_format"] == "safetensors"
     assert rows[0]["size_bytes"] == 100
-    assert rows[0]["last_modified"] == 3_000.0
-
-
-def test_cached_gguf_scan_keeps_download_timestamp(monkeypatch, tmp_path):
-    repo_path = tmp_path / "models--Org--GgufRepo"
-    repo = SimpleNamespace(
-        repo_id = "Org/GgufRepo",
-        repo_type = "model",
-        repo_path = repo_path,
-        revisions = [
-            SimpleNamespace(
-                files = [
-                    SimpleNamespace(
-                        file_name = "model-Q4_K_M.gguf",
-                        size_on_disk = 100,
-                        blob_path = None,
-                        blob_last_modified = 5_000.0,
-                    ),
-                ]
-            )
-        ],
-    )
-    monkeypatch.setattr(
-        CI,
-        "all_hf_cache_scans",
-        lambda: [SimpleNamespace(repos = [repo])],
-    )
-    monkeypatch.setattr(
-        CI.hf_cache_scan,
-        "is_gguf_repo_partial",
-        lambda *args, **kwargs: False,
-    )
-    monkeypatch.setattr(
-        CI,
-        "_gguf_variant_state_summary",
-        lambda _repo_id: (False, 0),
-    )
-
-    rows = CI._scan_cached_gguf()
-
-    assert len(rows) == 1
-    assert rows[0]["repo_id"] == "Org/GgufRepo"
-    assert rows[0]["model_format"] == "gguf"
-    assert rows[0]["size_bytes"] == 100
-    assert rows[0]["last_modified"] == 5_000.0
 
 
 # ── hf_hub_download_with_xet_fallback force_download bypass (X2/F2) ───
diff --git a/studio/backend/tests/test_picker_service.py b/studio/backend/tests/test_picker_service.py
deleted file mode 100644
index fc835bf019..0000000000
--- a/studio/backend/tests/test_picker_service.py
+++ /dev/null
@@ -1,162 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-only
-# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import json
-
-from picker.service import (
-    _chat_template_from_dir,
-    _chat_template_from_tokenizer_config,
-    _chat_template_from_tokenizer_dir,
-    _find_gguf_in_dir,
-    _iter_ggufs,
-    read_default_chat_template,
-    validate_chat_template,
-)
-
-
-def test_iter_ggufs_skips_gguf_companions(tmp_path):
-    mtp_dir = tmp_path / "MTP"
-    mtp_dir.mkdir()
-    main = tmp_path / "model-Q8_0.gguf"
-    main.write_bytes(b"")
-    (tmp_path / "mmproj-F16.gguf").write_bytes(b"")
-    (tmp_path / "mtp-model-Q8_0.gguf").write_bytes(b"")
-    (mtp_dir / "model-Q8_0-MTP.gguf").write_bytes(b"")
-    (tmp_path / "model-Q8_0-be.gguf").write_bytes(b"")
-
-    assert _iter_ggufs(tmp_path) == [main]
-
-
-def test_find_gguf_in_dir_matches_quant_label(tmp_path):
-    mtp_dir = tmp_path / "MTP"
-    mtp_dir.mkdir()
-    main = tmp_path / "model-Q8_0.gguf"
-    main.write_bytes(b"")
-    (mtp_dir / "model-Q8_0-MTP.gguf").write_bytes(b"")
-    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
-
-    assert _find_gguf_in_dir(tmp_path, "Q8_0") == main
-    assert _find_gguf_in_dir(tmp_path, "Q4_K") is None
-
-
-def test_find_gguf_in_dir_without_variant_prefers_largest_model(tmp_path):
-    smaller = tmp_path / "a-model-Q4_K_M.gguf"
-    larger = tmp_path / "z-model-Q8_0.gguf"
-    smaller.write_bytes(b"0")
-    larger.write_bytes(b"00")
-
-    assert _find_gguf_in_dir(tmp_path, None) == larger
-
-
-def test_find_gguf_in_dir_matches_bpw_variant_base_label(tmp_path):
-    target = tmp_path / "model-IQ4_XS-3.53bpw.gguf"
-    target.write_bytes(b"")
-    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
-
-    assert _find_gguf_in_dir(tmp_path, "IQ4_XS") == target
-    assert _find_gguf_in_dir(tmp_path, "IQ4_XS-3.53bpw") == target
-    assert _find_gguf_in_dir(tmp_path, "Q4_K") is None
-
-
-def test_validate_chat_template_accepts_valid_and_empty():
-    assert validate_chat_template("{{ messages[0].content }}").valid is True
-    assert validate_chat_template("").valid is True
-    assert validate_chat_template("   ").valid is True
-
-
-def test_validate_chat_template_reports_syntax_error_with_line():
-    result = validate_chat_template("{% if %}{% endif %}")
-    assert result.valid is False
-    assert result.error is not None
-    assert result.error.startswith("Line ")
-
-
-def test_chat_template_from_tokenizer_config_reads_string():
-    assert _chat_template_from_tokenizer_config({"chat_template": "HELLO"}) == "HELLO"
-    assert _chat_template_from_tokenizer_config({"chat_template": "   "}) is None
-    assert _chat_template_from_tokenizer_config({}) is None
-
-
-def test_chat_template_from_tokenizer_config_prefers_named_default():
-    config = {
-        "chat_template": [
-            {"name": "tool_use", "template": "TOOL"},
-            {"name": "default", "template": "DEFAULT"},
-        ]
-    }
-    assert _chat_template_from_tokenizer_config(config) == "DEFAULT"
-
-
-def test_chat_template_from_tokenizer_config_falls_back_to_first_entry():
-    config = {
-        "chat_template": [
-            {"name": "tool_use", "template": "TOOL"},
-            {"name": "other", "template": "OTHER"},
-        ]
-    }
-    assert _chat_template_from_tokenizer_config(config) == "TOOL"
-
-
-def test_chat_template_from_tokenizer_dir_prefers_jinja_file(tmp_path):
-    (tmp_path / "chat_template.jinja").write_text("FROM_JINJA", encoding = "utf-8")
-    (tmp_path / "tokenizer_config.json").write_text(
-        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
-    )
-    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_JINJA"
-
-
-def test_chat_template_from_tokenizer_dir_reads_tokenizer_config(tmp_path):
-    (tmp_path / "tokenizer_config.json").write_text(
-        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
-    )
-    assert _chat_template_from_tokenizer_dir(tmp_path) == "FROM_CONFIG"
-
-
-def test_chat_template_from_dir_without_variant_prefers_tokenizer(tmp_path):
-    (tmp_path / "tokenizer_config.json").write_text(
-        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
-    )
-    assert _chat_template_from_dir(tmp_path) == "FROM_CONFIG"
-
-
-def test_chat_template_from_dir_with_variant_still_prefers_tokenizer(tmp_path, monkeypatch):
-    (tmp_path / "tokenizer_config.json").write_text(
-        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
-    )
-    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
-    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
-    # Selecting a variant must not flip precedence to the embedded GGUF template.
-    assert _chat_template_from_dir(tmp_path, "Q4_K_M") == "FROM_CONFIG"
-
-
-def test_chat_template_from_dir_with_variant_falls_back_to_gguf(tmp_path, monkeypatch):
-    (tmp_path / "model-Q4_K_M.gguf").write_bytes(b"")
-    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
-    # With no tokenizer sidecar, the embedded GGUF template is still the fallback.
-    assert _chat_template_from_dir(tmp_path, "Q4_K_M") == "FROM_GGUF"
-
-
-def test_chat_template_from_dir_returns_none_when_absent(tmp_path):
-    assert _chat_template_from_dir(tmp_path) is None
-
-
-def test_read_default_chat_template_direct_gguf_prefers_sidecar(tmp_path, monkeypatch):
-    gguf = tmp_path / "model-Q4_K_M.gguf"
-    gguf.write_bytes(b"")
-    (tmp_path / "tokenizer_config.json").write_text(
-        json.dumps({"chat_template": "FROM_CONFIG"}), encoding = "utf-8"
-    )
-    monkeypatch.setattr("picker.service._build_browse_allowlist", lambda: [tmp_path])
-    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
-    # A directly selected .gguf file must prefer a maintained sidecar template
-    # over its embedded copy, matching directory/variant precedence.
-    assert read_default_chat_template(str(gguf)) == "FROM_CONFIG"
-
-
-def test_read_default_chat_template_direct_gguf_falls_back_to_embedded(tmp_path, monkeypatch):
-    gguf = tmp_path / "model-Q4_K_M.gguf"
-    gguf.write_bytes(b"")
-    monkeypatch.setattr("picker.service._build_browse_allowlist", lambda: [tmp_path])
-    monkeypatch.setattr("picker.service.read_gguf_chat_template", lambda _path: "FROM_GGUF")
-    # With no sidecar next to the file, the embedded GGUF template is the fallback.
-    assert read_default_chat_template(str(gguf)) == "FROM_GGUF"
diff --git a/studio/backend/utils/models/gguf_metadata.py b/studio/backend/utils/models/gguf_metadata.py
index 5e25ce1927..c24ec28e1d 100644
--- a/studio/backend/utils/models/gguf_metadata.py
+++ b/studio/backend/utils/models/gguf_metadata.py
@@ -50,8 +50,6 @@ _CACHE_MAX_ENTRIES = 4096
 # keyed by (file cache key, wanted key). None = key absent / file unreadable.
 _BOOL_CACHE: Dict[Tuple[_CacheKey, str], Optional[bool]] = {}
 
-_STRING_CACHE: Dict[Tuple[_CacheKey, str], Optional[str]] = {}
-
 # Native training context length (``{arch}.context_length``). None = absent /
 # unreadable. Lets the UI show the real context ceiling before a model loads.
 _CONTEXT_CACHE: Dict[_CacheKey, Optional[int]] = {}
@@ -355,83 +353,6 @@ def _read_gguf_bool(path: str, wanted_key: str) -> Optional[bool]:
     return result
 
 
-def _parse_gguf_string(path: str, wanted_key: str) -> Optional[str]:
-    try:
-        with open(path, "rb") as f:
-            head = f.read(24)
-            if len(head) < 24:
-                return None
-            magic, _version, _tcount, kv_count = struct.unpack("<IIQQ", head)
-            if magic != _GGUF_MAGIC:
-                return None
-
-            for _ in range(kv_count):
-                try:
-                    klen_bytes = f.read(8)
-                    if len(klen_bytes) < 8:
-                        break
-                    klen = struct.unpack("<Q", klen_bytes)[0]
-                    if klen > 1 << 20:
-                        break
-                    kbytes = f.read(klen)
-                    if len(kbytes) < klen:
-                        break
-                    key = kbytes.decode("utf-8", "replace")
-                    vt_bytes = f.read(4)
-                    if len(vt_bytes) < 4:
-                        break
-                    vtype = struct.unpack("<I", vt_bytes)[0]
-
-                    if key == wanted_key and vtype == 8:
-                        slen_bytes = f.read(8)
-                        if len(slen_bytes) < 8:
-                            break
-                        slen = struct.unpack("<Q", slen_bytes)[0]
-                        if slen > 1 << 22:
-                            break
-                        sbytes = f.read(slen)
-                        if len(sbytes) < slen:
-                            break
-                        return sbytes.decode("utf-8", "replace")
-                    if not _skip_gguf_value(f, vtype):
-                        break
-                except (struct.error, UnicodeDecodeError):
-                    break
-    except OSError as e:
-        logger.debug(f"_parse_gguf_string: cannot open {path}: {e}")
-        return None
-    except Exception as e:
-        logger.debug(f"_parse_gguf_string: parse failure on {path}: {e}")
-        return None
-    return None
-
-
-def _read_gguf_string(path: str, wanted_key: str) -> Optional[str]:
-    fkey = _cache_key(path)
-    if fkey is None:
-        return None
-    ckey = (fkey, wanted_key)
-    with _CACHE_LOCK:
-        if ckey in _STRING_CACHE:
-            return _STRING_CACHE[ckey]
-    result = _parse_gguf_string(path, wanted_key)
-    with _CACHE_LOCK:
-        while len(_STRING_CACHE) >= _CACHE_MAX_ENTRIES:
-            try:
-                _STRING_CACHE.pop(next(iter(_STRING_CACHE)))
-            except StopIteration:
-                break
-        _STRING_CACHE[ckey] = result
-    return result
-
-
-def read_gguf_chat_template(path: str) -> Optional[str]:
-    template = _read_gguf_string(path, "tokenizer.chat_template")
-    if isinstance(template, str) and template.strip():
-        return template
-    return None
-
-
 def read_mmproj_audio_capability(path: str) -> Optional[bool]:
     """``clip.has_audio_encoder`` from an mmproj GGUF (e.g. Gemma 4's
     gemma4ua): ``True``/``False`` if present, ``None`` if absent/unreadable.
diff --git a/studio/frontend/src/app/routes/__root.tsx b/studio/frontend/src/app/routes/__root.tsx
index 6c2505f1ca..ba56ce7525 100644
--- a/studio/frontend/src/app/routes/__root.tsx
+++ b/studio/frontend/src/app/routes/__root.tsx
@@ -195,6 +195,9 @@ function RootLayout() {
         chatRuntime.setActiveThreadId(null);
         chatRuntime.setActiveProjectId(null);
         chatRuntime.setIncognito(false);
+        // Detach the staging UI but keep any in-flight download running, like Hub.
+        if (chatRuntime.pendingSelection)
+          chatRuntime.abandonStagedModel({ keepDownload: true });
         void navigate({
           to: "/chat",
           search: { new: crypto.randomUUID() },
@@ -217,6 +220,10 @@ function RootLayout() {
     chatRuntime.setActiveProjectId(null);
     chatRuntime.setActiveThreadId(null);
     chatRuntime.setIncognito(false);
+    // Leaving chat must not kill an in-flight download: detach the staging UI
+    // but keep the transfer running in the manager, like a Hub download.
+    if (chatRuntime.pendingSelection)
+      chatRuntime.abandonStagedModel({ keepDownload: true });
   }, [isChatRoute]);
 
   return (
diff --git a/studio/frontend/src/features/model-picker/components/model-selector.tsx b/studio/frontend/src/components/assistant-ui/model-selector.tsx
similarity index 86%
rename from studio/frontend/src/features/model-picker/components/model-selector.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector.tsx
index 7efcf69162..6bfd1276ac 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector.tsx
@@ -3,7 +3,6 @@
 
 "use client";
 
-import { Input } from "@/components/ui/input";
 import {
   Popover,
   PopoverContent,
@@ -11,7 +10,7 @@ import {
 } from "@/components/ui/popover";
 import { TooltipProvider } from "@/components/ui/tooltip";
 import { usePlatformStore } from "@/config/env";
-import { isCustomProviderType } from "@/features/chat";
+import { isCustomProviderType } from "@/features/chat/external-providers";
 import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { cn } from "@/lib/utils";
 import {
@@ -34,11 +33,7 @@ import {
   useRef,
   useState,
 } from "react";
-import {
-  type PerModelConfig,
-  resolveInitialConfig,
-} from "../model-config/per-model-config";
-import { ModelConfigPage } from "./model-config-page";
+import { Input } from "../ui/input";
 import { HubModelPicker, hasDownloadedModels } from "./model-selector/pickers";
 import { PillTabs } from "./model-selector/pill-tabs";
 import {
@@ -50,7 +45,6 @@ import type {
   ExternalModelOption,
   LoraModelOption,
   ModelOption,
-  ModelPickTarget,
   ModelSelectorChangeMeta,
 } from "./model-selector/types";
 
@@ -128,10 +122,6 @@ interface ModelSelectorProps {
   value?: string;
   defaultValue?: string;
   activeGgufVariant?: string | null;
-  activeModelConfig?: PerModelConfig | null;
-  activeGgufContextLength?: number | null;
-  selectedConfig?: PerModelConfig | null;
-  selectedGgufVariant?: string | null;
   onValueChange?: (value: string, meta: ModelSelectorChangeMeta) => void;
   onEject?: () => void;
   onFoldersChange?: () => void;
@@ -295,8 +285,7 @@ function saveLastHubSection(section: HubSection): void {
 // when they have downloads, else Recommended.
 function defaultHubSection(): HubSection {
   return (
-    loadLastHubSection() ??
-    (hasDownloadedModels() ? "downloaded" : "recommended")
+    loadLastHubSection() ?? (hasDownloadedModels() ? "downloaded" : "recommended")
   );
 }
 
@@ -319,11 +308,6 @@ function ModelSelectorContent({
   loraModels,
   externalModels,
   value,
-  activeGgufVariant,
-  activeModelConfig,
-  activeGgufContextLength,
-  selectedConfig,
-  selectedGgufVariant,
   onSelect,
   onEject,
   onFoldersChange,
@@ -339,11 +323,6 @@ function ModelSelectorContent({
   loraModels: LoraModelOption[];
   externalModels: ExternalModelOption[];
   value?: string;
-  activeGgufVariant?: string | null;
-  activeModelConfig?: PerModelConfig | null;
-  activeGgufContextLength?: number | null;
-  selectedConfig?: PerModelConfig | null;
-  selectedGgufVariant?: string | null;
   onSelect: (id: string, meta: ModelSelectorChangeMeta) => void;
   onEject?: () => void;
   onFoldersChange?: () => void;
@@ -412,10 +391,6 @@ function ModelSelectorContent({
   const effectiveHubSection: HubSection =
     hubSection === "connected" && !hasExternal ? "recommended" : hubSection;
 
-  const [configTarget, setConfigTarget] = useState<ModelPickTarget | null>(
-    null,
-  );
-
   // The picker below remounts on each open, but this tab state does not, so a
   // persisted selection that lands in lora/external after async load would
   // reopen on Hub. Re-derive the default tab on the open edge.
@@ -427,9 +402,6 @@ function ModelSelectorContent({
       // user has downloads, else their last section.
       setHubSection(wantsConnectedDefault ? "connected" : defaultHubSection());
     }
-    if (!open && wasOpen.current) {
-      setConfigTarget(null);
-    }
     wasOpen.current = open;
   }, [
     open,
@@ -480,29 +452,6 @@ function ModelSelectorContent({
     }
   }
 
-  const visibleConfigTarget = open ? configTarget : null;
-  const openConfigPage = (id: string, meta: ModelSelectorChangeMeta) => {
-    const leaf = id.includes("/") ? id.slice(id.lastIndexOf("/") + 1) : id;
-    setConfigTarget({
-      id,
-      displayName: meta.ggufVariant ? `${leaf} · ${meta.ggufVariant}` : leaf,
-      ggufVariant: meta.ggufVariant ?? null,
-      isGguf: meta.isGguf ?? Boolean(meta.ggufVariant),
-      meta,
-    });
-  };
-  const handlePick = (id: string, meta: ModelSelectorChangeMeta) => {
-    if (meta.source === "external") {
-      onSelect(id, meta);
-      return;
-    }
-    const resolved = resolveInitialConfig(id, meta.ggufVariant);
-    onSelect(id, {
-      ...meta,
-      ...(resolved.remembered ? { config: resolved.config } : {}),
-    });
-  };
-
   return (
     <PopoverContent
       align="start"
@@ -510,17 +459,12 @@ function ModelSelectorContent({
       data-tour={dataTour}
       onKeyDown={handlePickerEntryKeyDown}
       className={cn(
-        "unsloth-model-selector-menu menu-soft-surface ring-0 max-w-[calc(100vw-1rem)] min-w-0 gap-0",
-        visibleConfigTarget
-          ? "w-[min(468px,calc(100vw-1rem))] px-4 pt-4 pb-4"
-          : cn(
-              "pt-4 pb-0 pl-4",
-              // Sized so the left-packed row keeps uniform gaps and the last
-              // dropdown's right gap matches the pill's left gap (pl-4 vs pr-4).
-              hasExternal
-                ? "w-[min(614px,calc(100vw-1rem))] pr-4"
-                : "w-[min(506px,calc(100vw-1rem))] pr-2",
-            ),
+        "unsloth-model-selector-menu menu-soft-surface ring-0 max-w-[calc(100vw-1rem)] min-w-0 gap-0 pt-4 pb-0 pl-4",
+        // Sized so the left-packed row keeps uniform gaps and the last dropdown's
+        // right gap matches the pill's left gap (pl-4 vs pr-4).
+        hasExternal
+          ? "w-[min(614px,calc(100vw-1rem))] pr-4"
+          : "w-[min(506px,calc(100vw-1rem))] pr-2",
         className,
       )}
     >
@@ -533,42 +477,6 @@ function ModelSelectorContent({
         skipDelayDuration={0}
         disableHoverableContent={true}
       >
-        {visibleConfigTarget ? (
-          <ModelConfigPage
-            key={`${visibleConfigTarget.id}::${visibleConfigTarget.ggufVariant ?? ""}`}
-            target={visibleConfigTarget}
-            onBack={() => setConfigTarget(null)}
-            onRun={(config) =>
-              onSelect(visibleConfigTarget.id, {
-                ...visibleConfigTarget.meta,
-                config,
-                forceReload: true,
-              })
-            }
-            loadedConfig={
-              value === visibleConfigTarget.id &&
-              (activeGgufVariant ?? null) ===
-                (visibleConfigTarget.ggufVariant ?? null)
-                ? (activeModelConfig ?? null)
-                : null
-            }
-            loadedContextLength={
-              value === visibleConfigTarget.id &&
-              (activeGgufVariant ?? null) ===
-                (visibleConfigTarget.ggufVariant ?? null)
-                ? (activeGgufContextLength ?? null)
-                : null
-            }
-            initialConfig={
-              value === visibleConfigTarget.id &&
-              (selectedGgufVariant ?? null) ===
-                (visibleConfigTarget.ggufVariant ?? null)
-                ? (selectedConfig ?? null)
-                : null
-            }
-          />
-        ) : (
-          <>
         {tabs.length > 1 ? (
           <PillTabs
             ariaLabel="Model source"
@@ -586,14 +494,13 @@ function ModelSelectorContent({
             loraModels={fineTunedModels}
             externalModels={externalModels}
             value={value}
-            onSelect={handlePick}
+            onSelect={onSelect}
             onFoldersChange={onFoldersChange}
             onBrowseHub={onBrowseHub}
             onModelsChange={onModelsChange}
-            onConfigure={openConfigPage}
             deleteDisabled={deleteDisabled}
-            onEject={hasSelection && onEject ? onEject : undefined}
             section={effectiveHubSection}
+            onEject={hasSelection && onEject ? onEject : undefined}
             sectionToggle={
               <PillTabs
                 ariaLabel="Hub section"
@@ -631,8 +538,10 @@ function ModelSelectorContent({
             </button>
           </div>
         ) : null}
+        {/* Hub renders Eject inline as the last list row; other tabs keep the
+          footer button. */}
         {effectiveTab !== "hub" && hasSelection && onEject ? (
-          <div className="mt-1.5 border-t border-border/70 pt-1.5 pb-2">
+          <div className="mt-1.5 pt-1.5">
             <button
               type="button"
               onClick={onEject}
@@ -644,8 +553,6 @@ function ModelSelectorContent({
             </button>
           </div>
         ) : null}
-          </>
-        )}
       </TooltipProvider>
     </PopoverContent>
   );
@@ -658,10 +565,6 @@ export function ModelSelector({
   value,
   defaultValue,
   activeGgufVariant,
-  activeModelConfig,
-  activeGgufContextLength,
-  selectedConfig,
-  selectedGgufVariant,
   onValueChange,
   onEject,
   onFoldersChange,
@@ -790,11 +693,6 @@ export function ModelSelector({
         loraModels={loraModels}
         externalModels={externalModels}
         value={selected}
-        activeGgufVariant={activeGgufVariant}
-        activeModelConfig={activeModelConfig}
-        activeGgufContextLength={activeGgufContextLength}
-        selectedConfig={selectedConfig}
-        selectedGgufVariant={selectedGgufVariant}
         onSelect={handleSelect}
         onEject={onEject ? handleEject : undefined}
         onFoldersChange={onFoldersChange}
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx b/studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
similarity index 88%
rename from studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
index 023f586781..16cc8a1956 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/folder-browser.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector/folder-browser.tsx
@@ -14,7 +14,10 @@ import {
   DialogTitle,
 } from "@/components/ui/dialog";
 import { Spinner } from "@/components/ui/spinner";
-import { type BrowseFoldersResponse, browseFolders } from "@/features/chat";
+import {
+  type BrowseFoldersResponse,
+  browseFolders,
+} from "@/features/chat/api/chat-api";
 import { ChevronUpStandardIcon } from "@/lib/chevron-icons";
 import { cn } from "@/lib/utils";
 import { Folder02Icon } from "@hugeicons/core-free-icons";
@@ -87,43 +90,47 @@ export function FolderBrowser({
   const [error, setError] = useState<string | null>(null);
   const abortRef = useRef<AbortController | null>(null);
 
-  function navigate(
-    target: string | undefined,
-    hidden: boolean,
-    opts?: { fallbackOnError?: boolean },
-  ) {
-    abortRef.current?.abort();
-    const ctrl = new AbortController();
-    abortRef.current = ctrl;
-    setLoading(true);
-    setError(null);
-    // Forward the signal so cancelled navigation aborts the backend
-    // enumeration, not just the response.
-    browseFolders(target, hidden, ctrl.signal)
-      .then((res) => {
-        if (ctrl.signal.aborted) return;
-        setData(res);
-        setPath(res.current);
-      })
-      .catch((err) => {
-        if (ctrl.signal.aborted) return;
-        // Surface the error; if the first request (e.g. a bad initialPath)
-        // fails, fall back to HOME so the modal stays navigable.
-        const message = err instanceof Error ? err.message : String(err);
-        setError(message);
-        if (opts?.fallbackOnError && target !== undefined) {
-          // Re-issue without a target -> backend defaults to HOME.
-          // Don't recurse if HOME itself fails (allowlist always has HOME).
-          queueMicrotask(() => navigate(undefined, hidden));
-        }
-      })
-      .finally(() => {
-        if (!ctrl.signal.aborted) setLoading(false);
-      });
-  }
+  const navigate = useCallback(
+    (
+      target: string | undefined,
+      hidden: boolean,
+      opts?: { fallbackOnError?: boolean },
+    ) => {
+      abortRef.current?.abort();
+      const ctrl = new AbortController();
+      abortRef.current = ctrl;
+      setLoading(true);
+      setError(null);
+      // Forward the signal so cancelled navigation aborts the backend
+      // enumeration, not just the response.
+      browseFolders(target, hidden, ctrl.signal)
+        .then((res) => {
+          if (ctrl.signal.aborted) return;
+          setData(res);
+          setPath(res.current);
+        })
+        .catch((err) => {
+          if (ctrl.signal.aborted) return;
+          // Surface the error; if the first request (e.g. a bad initialPath)
+          // fails, fall back to HOME so the modal stays navigable.
+          const message = err instanceof Error ? err.message : String(err);
+          setError(message);
+          if (opts?.fallbackOnError && target !== undefined) {
+            // Re-issue without a target -> backend defaults to HOME.
+            // Don't recurse if HOME itself fails (allowlist always has HOME).
+            queueMicrotask(() => navigate(undefined, hidden));
+          }
+        })
+        .finally(() => {
+          if (!ctrl.signal.aborted) setLoading(false);
+        });
+    },
+    [],
+  );
 
   // Fetch only on closed -> open; later navigation is driven by `navigate()`,
   // so `path` is deliberately kept out of the dependency list.
+  // eslint-disable-next-line react-hooks/exhaustive-deps
   useEffect(() => {
     if (!open) return;
     // fallbackOnError: recover into HOME if initialPath is bad, rather than
@@ -140,7 +147,7 @@ export function FolderBrowser({
 
   const crumbs = useMemo(
     () => (data?.current ? splitBreadcrumb(data.current) : []),
-    [data],
+    [data?.current],
   );
 
   return (
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/model-capabilities.ts b/studio/frontend/src/components/assistant-ui/model-selector/model-capabilities.ts
similarity index 100%
rename from studio/frontend/src/features/model-picker/components/model-selector/model-capabilities.ts
rename to studio/frontend/src/components/assistant-ui/model-selector/model-capabilities.ts
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx b/studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
similarity index 90%
rename from studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
index 09bb43abdc..4de96d3648 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/model-delete-action.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector/model-delete-action.tsx
@@ -1,12 +1,12 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { DeleteConfirmDialog } from "@/features/hub";
-import { toast } from "@/lib/toast";
+import { DeleteConfirmDialog } from "@/features/hub/catalog/download-card";
 import { cn } from "@/lib/utils";
 import { Delete02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
-import { type ReactNode, useCallback, useState } from "react";
+import { useCallback, useState, type ReactNode } from "react";
+import { toast } from "@/lib/toast";
 
 interface ModelDeleteActionProps {
   ariaLabel: string;
@@ -63,8 +63,7 @@ export function ModelDeleteAction({
         disabled={disabled}
         className={cn(
           "shrink-0 rounded-md p-1.5 text-muted-foreground/60 transition-colors hover:bg-destructive/10 hover:text-destructive",
-          disabled &&
-            "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
+          disabled && "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
           buttonClassName,
         )}
       >
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx b/studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
similarity index 66%
rename from studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
index e1d48b5a08..58510762d4 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/model-load-settings-action.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector/model-load-settings-action.tsx
@@ -6,16 +6,24 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import { useChatRuntimeStore } from "@/features/chat/stores/chat-runtime-store";
 import { cn } from "@/lib/utils";
 import { Settings02Icon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 
+/** Gear button on a downloaded quant row. Stages the model into the Run
+ * settings sidebar (always, regardless of the Load-on-selection toggle) so the
+ * user can set load options, then click Load model. */
 export function ModelLoadSettingsAction({
   ariaLabel,
-  onConfigure,
+  repoId,
+  quant,
+  maxContext,
 }: {
   ariaLabel: string;
-  onConfigure: () => void;
+  repoId: string;
+  quant: string;
+  maxContext?: number | null;
 }) {
   return (
     <Tooltip delayDuration={0}>
@@ -24,7 +32,12 @@ export function ModelLoadSettingsAction({
           type="button"
           onClick={(e) => {
             e.stopPropagation();
-            onConfigure();
+            useChatRuntimeStore.getState().stageModel({
+              id: repoId,
+              ggufVariant: quant,
+              isDownloaded: true,
+              contextLength: maxContext ?? null,
+            });
           }}
           aria-label={ariaLabel}
           className={cn(
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx b/studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
similarity index 82%
rename from studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
index b13ed33d04..db7628777a 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/model-update-action.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector/model-update-action.tsx
@@ -1,20 +1,12 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import {
-  UpdateConfirmDialog,
-  ggufVariantsMatch,
-  subscribeJobListeners,
-} from "@/features/hub";
+import { subscribeJobListeners } from "@/features/hub/download-manager";
+import { UpdateConfirmDialog } from "@/features/hub/catalog/download-card";
+import { ggufVariantsMatch } from "@/features/hub/lib/model-identity";
 import { cn } from "@/lib/utils";
 import { RefreshCw } from "lucide-react";
-import {
-  type ReactNode,
-  useCallback,
-  useEffect,
-  useRef,
-  useState,
-} from "react";
+import { useCallback, useEffect, useRef, useState, type ReactNode } from "react";
 import { toast } from "sonner";
 
 interface ModelUpdateActionProps {
@@ -50,10 +42,10 @@ export function ModelUpdateAction({
 }: ModelUpdateActionProps) {
   const [open, setOpen] = useState(false);
 
+  // Refresh the caller when this repo+variant's download finishes so the "update available" cue
+  // clears. A ref keeps the subscription stable across renders.
   const onUpdatedRef = useRef(onUpdated);
-  useEffect(() => {
-    onUpdatedRef.current = onUpdated;
-  }, [onUpdated]);
+  onUpdatedRef.current = onUpdated;
   useEffect(() => {
     return subscribeJobListeners("model", repoId, {
       onComplete: (completedVariant) => {
@@ -91,8 +83,7 @@ export function ModelUpdateAction({
         disabled={disabled}
         className={cn(
           "shrink-0 rounded-md p-1.5 text-muted-foreground/60 transition-colors hover:bg-amber-500/10 hover:text-amber-700 dark:hover:bg-amber-500/15 dark:hover:text-amber-300",
-          disabled &&
-            "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
+          disabled && "cursor-not-allowed opacity-40 hover:bg-transparent hover:text-muted-foreground/60",
           buttonClassName,
         )}
       >
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts b/studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
similarity index 93%
rename from studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
rename to studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
index c6665e7658..dbcd4b9a1b 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/model-usage.ts
+++ b/studio/frontend/src/components/assistant-ui/model-selector/model-usage.ts
@@ -40,8 +40,7 @@ export function loadedAt(times: ModelLoadTimes, id: string): number {
 export function useModelLoadTimes(currentValue?: string): ModelLoadTimes {
   const [times, setTimes] = useState<ModelLoadTimes>(() => readLoadTimes());
   useEffect(() => {
-    if (!currentValue) return;
-    queueMicrotask(() => setTimes(recordModelLoaded(currentValue)));
+    if (currentValue) setTimes(recordModelLoaded(currentValue));
   }, [currentValue]);
   return times;
 }
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx b/studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
similarity index 89%
rename from studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
index 1569ca0581..8e06181585 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/pickers.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector/pickers.tsx
@@ -10,46 +10,49 @@ import {
   TooltipTrigger,
 } from "@/components/ui/tooltip";
 import { usePlatformStore } from "@/config/env";
-import { ApiProviderLogo } from "@/features/chat";
+import { ApiProviderLogo } from "@/features/chat/api-provider-logo";
 import {
   type ScanFolderInfo,
   addScanFolder,
   deleteCachedModel,
   deleteFineTunedModel,
+  listCachedGguf,
+  listCachedModels,
   listGgufVariants,
+  listLocalModels,
   listRecommendedFolders,
   listScanFolders,
   removeScanFolder,
-} from "@/features/chat";
-import { useChatRuntimeStore } from "@/features/chat";
+} from "@/features/chat/api/chat-api";
+import { useChatRuntimeStore } from "@/features/chat/stores/chat-runtime-store";
 import type {
   CachedGgufRepo,
   CachedModelRepo,
-  GgufVariantDetail,
   LocalModelInfo,
-} from "@/features/chat";
+} from "@/features/chat/api/chat-api";
+import type { GgufVariantDetail } from "@/features/chat/types/api";
+import { DotTag } from "@/features/hub/catalog/dot-tag";
 import {
-  DotTag,
   type HubOption,
   HubOptionMenu,
-  TrainIcon,
-  TransportConflictDialog,
-  useHubInfiniteScroll,
-} from "@/features/hub";
+} from "@/features/hub/catalog/hub-option-menu";
+import { TransportConflictDialog } from "@/features/hub/catalog/transport-conflict-dialog";
+import { TrainIcon } from "@/features/hub/components/train-icon";
+import { useHubInfiniteScroll } from "@/features/hub/hooks/use-hub-infinite-scroll";
 import {
   type HfModelResult,
   type HfSortKey,
   useHubModelSearch,
-} from "@/features/hub";
+} from "@/features/hub/hooks/use-hub-model-search";
+import { useOnlineStatus } from "@/features/hub/hooks/use-online-status";
+import { isHiddenModelId } from "@/features/hub/lib/hidden-models";
+import { classifyUnslothSupport } from "@/features/hub/lib/unsloth-support";
+import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
 import {
-  classifyUnslothSupport,
   downloadManager,
-  isHiddenModelId,
   jobKeyOf,
   useDownloadManagerStore,
-  useHfTokenStore,
-  useOnlineStatus,
-} from "@/features/hub";
+} from "@/features/hub/download-manager";
 import { useDebouncedValue, useGpuInfo } from "@/hooks";
 import { extractParamLabel } from "@/lib/model-size";
 import { toast } from "@/lib/toast";
@@ -82,7 +85,6 @@ import {
   useRef,
   useState,
 } from "react";
-import { useChatPickerInventory } from "../../inventory/use-chat-picker-inventory";
 import { FolderBrowser } from "./folder-browser";
 import {
   type ModelCapabilities,
@@ -90,8 +92,8 @@ import {
   hasAnyCapability,
 } from "./model-capabilities";
 import { ModelDeleteAction } from "./model-delete-action";
-import { ModelLoadSettingsAction } from "./model-load-settings-action";
 import { ModelUpdateAction } from "./model-update-action";
+import { ModelLoadSettingsAction } from "./model-load-settings-action";
 import {
   type ModelLoadTimes,
   loadedAt,
@@ -657,7 +659,6 @@ function GgufVariantExpander({
   parentOptionKey,
   onNavigatePastStart,
   onNavigatePastEnd,
-  onConfigure,
   sourceOverride,
   variantActions,
   onDevice = false,
@@ -673,7 +674,6 @@ function GgufVariantExpander({
   parentOptionKey?: string;
   onNavigatePastStart?: () => void;
   onNavigatePastEnd?: () => void;
-  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   sourceOverride?: ModelSelectorChangeMeta["source"];
   /** Update/delete actions for cached variant rows. Omitted by browse-only
    *  expanders (Recommended, etc.) that don't manage on-disk variants. */
@@ -715,11 +715,8 @@ function GgufVariantExpander({
 
   useEffect(() => {
     let canceled = false;
-    queueMicrotask(() => {
-      if (canceled) return;
-      setLoading(true);
-      setError(null);
-    });
+    setLoading(true);
+    setError(null);
 
     listGgufVariants(repoId, hfToken)
       .then((res) => {
@@ -747,7 +744,7 @@ function GgufVariantExpander({
   }, [repoId, refreshKey, hfToken]);
 
   // Covers Unix absolute (/), Windows drive (C:\, D:/), UNC (\\server), relative (./, ../), tilde (~/)
-  const isLocalPath = /^(\/|\.{1,2}[\\/]|~[\\/]|[A-Za-z]:[\\/]|\\\\)/.test(
+  const isLocalPath = /^(\/|\.{1,2}[\\\/]|~[\\\/]|[A-Za-z]:[\\\/]|\\\\)/.test(
     repoId,
   );
 
@@ -756,7 +753,8 @@ function GgufVariantExpander({
       // Only seed the staged context for picks whose weights are already on
       // disk. The staging effect short-circuits on a known contextLength
       // (pendingHasContext) before starting the download, so attaching it to an
-      // undownloaded quant from a partially cached repo would skip the download.
+      // undownloaded quant from a partially cached repo would skip the download
+      // entirely (and, with Load on selection, never load).
       const isAvailable = isLocalPath || downloaded === true;
       onSelect(repoId, {
         source: sourceOverride ?? (isLocalPath ? "local" : "hub"),
@@ -989,8 +987,7 @@ function GgufVariantExpander({
                       This will update{" "}
                       <span className="font-medium text-foreground">
                         {repoId} ({v.quant})
-                      </span>
-                      {"."}
+                      </span>{"."}
                     </>
                   )
                 }
@@ -1003,20 +1000,12 @@ function GgufVariantExpander({
                 onUpdated={() => setRefreshKey((key) => key + 1)}
               />
             )}
-            {v.downloaded && onConfigure && (
+            {v.downloaded && (
               <ModelLoadSettingsAction
                 ariaLabel={`Inference settings for ${repoId} ${v.quant}`}
-                onConfigure={() =>
-                  onConfigure(repoId, {
-                    source: sourceOverride ?? (isLocalPath ? "local" : "hub"),
-                    isLora: false,
-                    ggufVariant: v.quant,
-                    isDownloaded: true,
-                    expectedBytes,
-                    contextLength: nativeContext,
-                    isGguf: true,
-                  })
-                }
+                repoId={repoId}
+                quant={v.quant}
+                maxContext={nativeContext}
               />
             )}
             {v.downloaded && onDeleteVariant && (
@@ -1220,19 +1209,6 @@ function localPathTooltip(name: string, path: string): ReactNode {
   );
 }
 
-function localModelMeta(isGguf = false): ModelSelectorChangeMeta {
-  return {
-    source: "local",
-    isLora: false,
-    isDownloaded: true,
-    ...(isGguf ? { isGguf: true } : {}),
-  };
-}
-
-function localDirectGgufMeta(): ModelSelectorChangeMeta {
-  return localModelMeta(true);
-}
-
 /** Hugging Face address for an online/Hub row, or undefined when the repo id is
  * missing so the row shows no (empty) address line on hover. */
 function hubRepoUrl(id: string | null | undefined): string | undefined {
@@ -1243,7 +1219,9 @@ function hubRepoUrl(id: string | null | undefined): string | undefined {
 /** Whether a local model is an MLX build (name hint). MLX runs on Mac only, so
  * callers gate visibility on the host being a Mac. */
 function localModelIsMlx(m: LocalModelInfo): boolean {
-  return isMlxId(m.id) || isMlxId(m.display_name) || isMlxId(m.model_id ?? "");
+  return (
+    isMlxId(m.id) || isMlxId(m.display_name) || isMlxId(m.model_id ?? "")
+  );
 }
 
 /** Whether a local model matches the format toggle (GGUF detected by name/path). */
@@ -1267,7 +1245,6 @@ export function HubModelPicker({
   onFoldersChange,
   onBrowseHub,
   onModelsChange,
-  onConfigure,
   deleteDisabled = false,
   section = "downloaded",
   sectionToggle,
@@ -1284,12 +1261,12 @@ export function HubModelPicker({
   /** Open the full Hub page to browse more models. */
   onBrowseHub?: () => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
-  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   deleteDisabled?: boolean;
   /** Section shown when not searching. Search spans all sections. */
   section?: "downloaded" | "recommended" | "custom" | "connected";
   /** Section toggle rendered under the search bar. */
   sectionToggle?: ReactNode;
+  /** Eject the loaded model. Rendered as the last list row when set. */
   onEject?: () => void;
 }) {
   const gpu = useGpuInfo();
@@ -1390,14 +1367,12 @@ export function HubModelPicker({
   const setFitOnDeviceOnly = useChatRuntimeStore((s) => s.setFitOnDeviceOnly);
   // Repos the user clicked to collapse while expand-by-default is on. Kept in
   // memory only, so it resets on reload (and when the setting is toggled).
-  const [collapsedGgufState, setCollapsedGgufState] = useState<{
-    expandQuantizations: boolean;
-    value: Set<string>;
-  }>(() => ({ expandQuantizations, value: new Set() }));
-  const collapsedGguf =
-    collapsedGgufState.expandQuantizations === expandQuantizations
-      ? collapsedGgufState.value
-      : new Set<string>();
+  const [collapsedGguf, setCollapsedGguf] = useState<Set<string>>(
+    () => new Set(),
+  );
+  useEffect(() => {
+    setCollapsedGguf(new Set());
+  }, [expandQuantizations]);
   const isGgufExpanded = useCallback(
     (id: string) =>
       expandQuantizations ? !collapsedGguf.has(id) : expandedGguf === id,
@@ -1408,15 +1383,11 @@ export function HubModelPicker({
   const toggleGgufExpanded = useCallback(
     (id: string) => {
       if (expandQuantizations) {
-        setCollapsedGgufState((prev) => {
-          const current =
-            prev.expandQuantizations === expandQuantizations
-              ? prev.value
-              : new Set<string>();
-          const next = new Set(current);
+        setCollapsedGguf((prev) => {
+          const next = new Set(prev);
           if (next.has(id)) next.delete(id);
           else next.add(id);
-          return { expandQuantizations, value: next };
+          return next;
         });
       } else {
         setExpandedGguf((prev) => (prev === id ? null : id));
@@ -1476,37 +1447,15 @@ export function HubModelPicker({
     });
   }, []);
 
-  const pickerInventory = useChatPickerInventory({ enabled: true });
-  const { cachedGguf, cachedModels, cachedReady, refreshInventory } =
-    pickerInventory;
-  const lmStudioModels = useMemo(
-    () =>
-      sortLmStudio(
-        pickerInventory.localModels.filter((m) => m.source === "lmstudio"),
-      ),
-    [pickerInventory.localModels],
-  );
-  const localDirModels = useMemo(
-    () => pickerInventory.localModels.filter((m) => m.source === "models_dir"),
-    [pickerInventory.localModels],
-  );
-  const customFolderModels = useMemo(
-    () => pickerInventory.localModels.filter((m) => m.source === "custom"),
-    [pickerInventory.localModels],
-  );
-  useEffect(() => {
-    _cachedGgufCache = cachedGguf;
-    _cachedModelsCache = cachedModels;
-    _lmStudioCache = lmStudioModels;
-    _localDirCache = localDirModels;
-    _customFolderCache = customFolderModels;
-  }, [
-    cachedGguf,
-    cachedModels,
-    lmStudioModels,
-    localDirModels,
-    customFolderModels,
-  ]);
+  // Cached (downloaded) repos -- module-level cache avoids flashing an
+  // empty "Downloaded" section when the popover re-mounts.
+  const [cachedGguf, setCachedGguf] =
+    useState<CachedGgufRepo[]>(_cachedGgufCache);
+  const [cachedModels, setCachedModels] =
+    useState<CachedModelRepo[]>(_cachedModelsCache);
+  const alreadyCached =
+    _cachedGgufCache.length > 0 || _cachedModelsCache.length > 0;
+  const [cachedReady, setCachedReady] = useState(alreadyCached);
   const [updateConflictKey, setUpdateConflictKey] = useState<string | null>(
     null,
   );
@@ -1530,6 +1479,16 @@ export function HubModelPicker({
     setUpdateConflictKey(null);
   }, [updateConflictKey]);
 
+  // LM Studio local models -- module-level cache, same pattern as above.
+  const [lmStudioModels, setLmStudioModels] =
+    useState<LocalModelInfo[]>(_lmStudioCache);
+  // Models found under the local models directory (./models), so they stay
+  // selectable on the On Device tab after leaving the Fine-tuned tab.
+  const [localDirModels, setLocalDirModels] =
+    useState<LocalModelInfo[]>(_localDirCache);
+  const [customFolderModels, setCustomFolderModels] =
+    useState<LocalModelInfo[]>(_customFolderCache);
+
   // Custom scan folders management
   const [scanFolders, setScanFolders] =
     useState<ScanFolderInfo[]>(_scanFoldersCache);
@@ -1541,8 +1500,22 @@ export function HubModelPicker({
   const [recommendedFolders, setRecommendedFolders] = useState<string[]>([]);
 
   const refreshLocalModelsList = useCallback(() => {
-    void pickerInventory.refreshInventory();
-  }, [pickerInventory.refreshInventory]);
+    listLocalModels()
+      .then((res) => {
+        const lm = sortLmStudio(
+          res.models.filter((m) => m.source === "lmstudio"),
+        );
+        _lmStudioCache = lm;
+        setLmStudioModels(lm);
+        const ld = res.models.filter((m) => m.source === "models_dir");
+        _localDirCache = ld;
+        setLocalDirModels(ld);
+        const cf = res.models.filter((m) => m.source === "custom");
+        _customFolderCache = cf;
+        setCustomFolderModels(cf);
+      })
+      .catch(() => {});
+  }, []);
 
   const refreshScanFolders = useCallback(() => {
     listScanFolders()
@@ -1621,37 +1594,39 @@ export function HubModelPicker({
   );
 
   const refreshCachedLists = useCallback(() => {
-    void pickerInventory.refreshInventory();
-  }, [pickerInventory.refreshInventory]);
+    listCachedGguf()
+      .then((v) => {
+        _cachedGgufCache = v;
+        setCachedGguf(v);
+      })
+      .catch(() => {});
+    listCachedModels(hfToken || undefined)
+      .then((v) => {
+        _cachedModelsCache = v;
+        setCachedModels(v);
+      })
+      .catch(() => {});
+    refreshLocalModelsList();
+  }, [hfToken, refreshLocalModelsList]);
 
   // Updates run as managed downloads (Downloads panel: progress + Cancel), not a blocking
   // call. The worker pulls only changed blobs, so the cached copy stays usable until done.
-  const startManagedUpdate = useCallback(
-    (repoId: string, variant: string, expectedBytes: number) => {
-      return downloadManager
-        .requestStart({
-          kind: "model",
-          repoId,
-          variant,
-          expectedBytes,
-        })
-        .then((outcome) => {
-          if (outcome === "conflict") {
-            setUpdateConflictKey(jobKeyOf("model", repoId, variant));
-          } else if (outcome === "busy") {
-            // A sibling variant/snapshot for this repo is already downloading,
-            // so this update did not start. Say so instead of closing the
-            // dialog as if it began and leaving the cached copy stale.
-            toast.info("A download for this model is already in progress", {
-              description: "Try updating again once it finishes.",
-            });
-          } else if (outcome === "error") {
-            throw new Error("Failed to start update");
-          }
-        });
-    },
-    [],
-  );
+  const startManagedUpdate = useCallback((repoId: string, variant: string, expectedBytes: number) => {
+    return downloadManager
+      .requestStart({
+        kind: "model",
+        repoId,
+        variant,
+        expectedBytes,
+      })
+      .then((outcome) => {
+        if (outcome === "conflict") {
+          setUpdateConflictKey(jobKeyOf("model", repoId, variant));
+        } else if (outcome === "error") {
+          throw new Error("Failed to start update");
+        }
+      });
+  }, []);
 
   const updateGgufVariant = useCallback(
     (repoId: string, quant: string, expectedBytes: number) =>
@@ -1660,15 +1635,36 @@ export function HubModelPicker({
   );
 
   useEffect(() => {
+    // Always refresh LM Studio + custom folder models (not gated by alreadyCached).
+    refreshLocalModelsList();
     refreshScanFolders();
     listRecommendedFolders()
       .then(setRecommendedFolders)
       .catch(() => {});
-  }, [refreshScanFolders]);
 
-  useEffect(() => {
-    void refreshInventory();
-  }, [refreshInventory]);
+    // Always refetch cached GGUF/model lists. The module-level caches render
+    // instantly with stale data (no spinner flash), but newly downloaded
+    // repos need a fresh backend hit. cachedReady=alreadyCached initially,
+    // so the background refresh is invisible when we already had data.
+    let done = 0;
+    const check = () => {
+      if (++done >= 2) setCachedReady(true);
+    };
+    listCachedGguf()
+      .then((v) => {
+        _cachedGgufCache = v;
+        setCachedGguf(v);
+      })
+      .catch(() => {})
+      .finally(check);
+    listCachedModels(hfToken || undefined)
+      .then((v) => {
+        _cachedModelsCache = v;
+        setCachedModels(v);
+      })
+      .catch(() => {})
+      .finally(check);
+  }, [hfToken, refreshLocalModelsList, refreshScanFolders]);
 
   // Hide downloaded models from the recommended list. Case-insensitive
   // since the HF cache lowercases repo IDs.
@@ -1705,8 +1701,7 @@ export function HubModelPicker({
       // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
       // on Mac (matches the empty Recommended view so search stays consistent).
       .filter(
-        (id) =>
-          !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
+        (id) => !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
       )
       .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id));
     // Sort: GGUFs first, then hub models
@@ -2057,8 +2052,7 @@ export function HubModelPicker({
       // Chat-only keeps runnable formats: GGUF anywhere, plus MLX/safetensors
       // on Mac (matches the empty Recommended view so search stays consistent).
       .filter(
-        (id) =>
-          !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
+        (id) => !chatOnly || isRecommendableFormat(id, isKnownGgufRepo(id), isMac),
       )
       .filter((id) => !/-FP8[-.]|FP8-Dynamic/i.test(id))
       .filter((id) =>
@@ -2514,7 +2508,6 @@ export function HubModelPicker({
             onDevice={true}
             onHasVision={(v) => reportVision(c.repo_id, v)}
             onSelect={onSelect}
-            onConfigure={onConfigure}
             hfToken={hfToken || undefined}
             parentOptionKey={optionKey}
             onNavigatePastStart={() => hubModelList.focusOption(optionKey)}
@@ -2524,6 +2517,7 @@ export function HubModelPicker({
             variantActions={{
               onUpdate: (quant, expectedBytes) =>
                 updateGgufVariant(c.repo_id, quant, expectedBytes),
+              // Can't update the model that's live in memory under itself.
               updateDisabled: loadedModelId === c.repo_id,
               onDelete: async (quant) => {
                 await deleteCachedModel(c.repo_id, quant);
@@ -2568,19 +2562,6 @@ export function HubModelPicker({
             className={downloadedRowButtonClassName}
           />
         </div>
-        {onConfigure && (
-          <ModelLoadSettingsAction
-            ariaLabel={`Inference settings for ${c.repo_id}`}
-            onConfigure={() =>
-              onConfigure(c.repo_id, {
-                source: "hub",
-                isLora: false,
-                isDownloaded: true,
-                isGguf: false,
-              })
-            }
-          />
-        )}
         <ModelDeleteAction
           ariaLabel={`Delete ${c.repo_id}`}
           title="Delete cached model?"
@@ -2684,6 +2665,9 @@ export function HubModelPicker({
         )}
         {...hubModelList.listboxProps}
       >
+        {/* Clear space for the floating Eject pill when scrolled to the end, so
+            its gap above the last row matches its gap below (applies to every
+            section, including Recommended). */}
         <div
           className={cn(
             "pr-0",
@@ -2913,7 +2897,6 @@ export function HubModelPicker({
                       adapters={fineTunedRows}
                       value={value}
                       onSelect={onSelect}
-                      onConfigure={onConfigure}
                       onModelsChange={onModelsChange}
                       deleteDisabled={deleteDisabled}
                       loraModelList={hubModelList}
@@ -2937,10 +2920,7 @@ export function HubModelPicker({
                       title="Browse folders on the server"
                       className="flex items-center gap-1.5 text-[10px] font-semibold uppercase tracking-wider text-muted-foreground transition-colors hover:text-foreground"
                     >
-                        <HugeiconsIcon
-                          icon={Folder02Icon}
-                          className="size-3.5"
-                        />
+                      <HugeiconsIcon icon={Folder02Icon} className="size-3.5" />
                       Custom Folders
                     </button>
                     <div className="flex items-center gap-0.5">
@@ -3160,70 +3140,54 @@ export function HubModelPicker({
                       );
                       return (
                         <div key={m.id}>
-                          <div className="flex items-center gap-0.5">
-                            <div className="min-w-0 flex-1">
-                              <ModelRow
-                                label={m.model_id ?? m.display_name}
-                                meta={isGguf ? "GGUF" : "Local"}
-                                tooltipText={localPathTooltip(
-                                  m.model_id ?? m.display_name,
-                                  m.path,
-                                )}
-                                selected={value === m.id}
-                                optionProps={hubModelList.getOptionProps(
-                                  optionKey,
-                                  value === m.id,
-                                )}
-                                onClick={() => {
-                                  if (isDirectGguf) {
-                                    onSelect(m.id, localDirectGgufMeta());
-                                  } else if (isGguf) {
-                                    toggleGgufExpanded(m.id);
-                                  } else {
-                                    onSelect(m.id, localModelMeta());
+                          <ModelRow
+                            label={m.model_id ?? m.display_name}
+                            meta={isGguf ? "GGUF" : "Local"}
+                            tooltipText={localPathTooltip(
+                              m.model_id ?? m.display_name,
+                              m.path,
+                            )}
+                            selected={value === m.id}
+                            optionProps={hubModelList.getOptionProps(
+                              optionKey,
+                              value === m.id,
+                            )}
+                            onClick={() => {
+                              if (isDirectGguf) {
+                                onSelect(m.id, {
+                                  source: "local",
+                                  isLora: false,
+                                  isDownloaded: true,
+                                  // Mark GGUF so "Load on selection = off" stages
+                                  // through Run settings (matches LM Studio path).
+                                  isGguf: true,
+                                });
+                              } else if (isGguf) {
+                                toggleGgufExpanded(m.id);
+                              } else {
+                                onSelect(m.id, {
+                                  source: "local",
+                                  isLora: false,
+                                  isDownloaded: true,
+                                });
+                              }
+                            }}
+                            onArrowDownIntoChildren={
+                              isGguf && !isDirectGguf && isGgufExpanded(m.id)
+                                ? () => {
+                                    const focused =
+                                      focusFirstChildOption(optionKey);
+                                    return focused;
                                   }
-                                }}
-                                onArrowDownIntoChildren={
-                                  isGguf &&
-                                  !isDirectGguf &&
-                                  isGgufExpanded(m.id)
-                                    ? () => {
-                                        const focused =
-                                          focusFirstChildOption(optionKey);
-                                        return focused;
-                                      }
-                                    : undefined
-                                }
-                                vramStatus={null}
-                              />
-                            </div>
-                            {isDirectGguf && onConfigure && (
-                              <ModelLoadSettingsAction
-                                ariaLabel={`Inference settings for ${
-                                  m.model_id ?? m.display_name
-                                }`}
-                                onConfigure={() =>
-                                  onConfigure(m.id, localDirectGgufMeta())
-                                }
-                              />
-                            )}
-                            {!isGguf && onConfigure && (
-                              <ModelLoadSettingsAction
-                                ariaLabel={`Inference settings for ${
-                                  m.model_id ?? m.display_name
-                                }`}
-                                onConfigure={() =>
-                                  onConfigure(m.id, localModelMeta())
-                                }
-                              />
-                            )}
-                          </div>
+                                : undefined
+                            }
+                            vramStatus={null}
+                          />
                           {isGguf && !isDirectGguf && isGgufExpanded(m.id) && (
                             <GgufVariantExpander
                               repoId={m.id}
                               onDevice={true}
                               onSelect={onSelect}
-                              onConfigure={onConfigure}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
                                 hubModelList.focusOption(optionKey)
@@ -3234,9 +3198,7 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={
-                                gpu.systemRamAvailableGb || undefined
-                              }
+                              systemRamGb={gpu.systemRamAvailableGb || undefined}
                             />
                           )}
                         </div>
@@ -3271,68 +3233,52 @@ export function HubModelPicker({
                       const optionKey = makeModelOptionKey("lm-studio", m.id);
                       return (
                         <div key={m.id}>
-                          <div className="flex items-center gap-0.5">
-                            <div className="min-w-0 flex-1">
-                              <ModelRow
-                                label={m.model_id ?? m.display_name}
-                                meta={isGguf ? "GGUF" : "Local"}
-                                tooltipText={localPathTooltip(
-                                  m.model_id ?? m.display_name,
-                                  m.path,
-                                )}
-                                selected={value === m.id}
-                                optionProps={hubModelList.getOptionProps(
-                                  optionKey,
-                                  value === m.id,
-                                )}
-                                onClick={() => {
-                                  if (isGgufFile) {
-                                    onSelect(m.id, localDirectGgufMeta());
-                                  } else if (isGguf) {
-                                    toggleGgufExpanded(m.id);
-                                  } else {
-                                    onSelect(m.id, localModelMeta());
+                          <ModelRow
+                            label={m.model_id ?? m.display_name}
+                            meta={isGguf ? "GGUF" : "Local"}
+                            tooltipText={localPathTooltip(
+                              m.model_id ?? m.display_name,
+                              m.path,
+                            )}
+                            selected={value === m.id}
+                            optionProps={hubModelList.getOptionProps(
+                              optionKey,
+                              value === m.id,
+                            )}
+                            onClick={() => {
+                              if (isGgufFile) {
+                                onSelect(m.id, {
+                                  source: "local",
+                                  isLora: false,
+                                  isDownloaded: true,
+                                  isGguf: true,
+                                });
+                              } else if (isGguf) {
+                                toggleGgufExpanded(m.id);
+                              } else {
+                                onSelect(m.id, {
+                                  source: "local",
+                                  isLora: false,
+                                  isDownloaded: true,
+                                });
+                              }
+                            }}
+                            onArrowDownIntoChildren={
+                              isGguf && !isGgufFile && isGgufExpanded(m.id)
+                                ? () => {
+                                    const focused =
+                                      focusFirstChildOption(optionKey);
+                                    return focused;
                                   }
-                                }}
-                                onArrowDownIntoChildren={
-                                  isGguf && !isGgufFile && isGgufExpanded(m.id)
-                                    ? () => {
-                                        const focused =
-                                          focusFirstChildOption(optionKey);
-                                        return focused;
-                                      }
-                                    : undefined
-                                }
-                                vramStatus={null}
-                              />
-                            </div>
-                            {isGgufFile && onConfigure && (
-                              <ModelLoadSettingsAction
-                                ariaLabel={`Inference settings for ${
-                                  m.model_id ?? m.display_name
-                                }`}
-                                onConfigure={() =>
-                                  onConfigure(m.id, localDirectGgufMeta())
-                                }
-                              />
-                            )}
-                            {!isGguf && onConfigure && (
-                              <ModelLoadSettingsAction
-                                ariaLabel={`Inference settings for ${
-                                  m.model_id ?? m.display_name
-                                }`}
-                                onConfigure={() =>
-                                  onConfigure(m.id, localModelMeta())
-                                }
-                              />
-                            )}
-                          </div>
+                                : undefined
+                            }
+                            vramStatus={null}
+                          />
                           {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
                             <GgufVariantExpander
                               repoId={m.id}
                               onDevice={true}
                               onSelect={onSelect}
-                              onConfigure={onConfigure}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
                                 hubModelList.focusOption(optionKey)
@@ -3343,9 +3289,7 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={
-                                gpu.systemRamAvailableGb || undefined
-                              }
+                              systemRamGb={gpu.systemRamAvailableGb || undefined}
                             />
                           )}
                         </div>
@@ -3374,64 +3318,48 @@ export function HubModelPicker({
                       const optionKey = makeModelOptionKey("local-dir", m.id);
                       return (
                         <div key={m.id}>
-                          <div className="flex items-center gap-0.5">
-                            <div className="min-w-0 flex-1">
-                              <ModelRow
-                                label={m.model_id ?? m.display_name}
-                                meta={isGguf ? "GGUF" : "Local"}
-                                tooltipText={localPathTooltip(
-                                  m.model_id ?? m.display_name,
-                                  m.path,
-                                )}
-                                selected={value === m.id}
-                                optionProps={hubModelList.getOptionProps(
-                                  optionKey,
-                                  value === m.id,
-                                )}
-                                onClick={() => {
-                                  if (isGgufFile) {
-                                    onSelect(m.id, localDirectGgufMeta());
-                                  } else if (isGguf) {
-                                    toggleGgufExpanded(m.id);
-                                  } else {
-                                    onSelect(m.id, localModelMeta());
-                                  }
-                                }}
-                                onArrowDownIntoChildren={
-                                  isGguf && !isGgufFile && isGgufExpanded(m.id)
-                                    ? () => focusFirstChildOption(optionKey)
-                                    : undefined
-                                }
-                                vramStatus={null}
-                              />
-                            </div>
-                            {isGgufFile && onConfigure && (
-                              <ModelLoadSettingsAction
-                                ariaLabel={`Inference settings for ${
-                                  m.model_id ?? m.display_name
-                                }`}
-                                onConfigure={() =>
-                                  onConfigure(m.id, localDirectGgufMeta())
-                                }
-                              />
+                          <ModelRow
+                            label={m.model_id ?? m.display_name}
+                            meta={isGguf ? "GGUF" : "Local"}
+                            tooltipText={localPathTooltip(
+                              m.model_id ?? m.display_name,
+                              m.path,
                             )}
-                            {!isGguf && onConfigure && (
-                              <ModelLoadSettingsAction
-                                ariaLabel={`Inference settings for ${
-                                  m.model_id ?? m.display_name
-                                }`}
-                                onConfigure={() =>
-                                  onConfigure(m.id, localModelMeta())
-                                }
-                              />
+                            selected={value === m.id}
+                            optionProps={hubModelList.getOptionProps(
+                              optionKey,
+                              value === m.id,
                             )}
-                          </div>
+                            onClick={() => {
+                              if (isGgufFile) {
+                                onSelect(m.id, {
+                                  source: "local",
+                                  isLora: false,
+                                  isDownloaded: true,
+                                  isGguf: true,
+                                });
+                              } else if (isGguf) {
+                                toggleGgufExpanded(m.id);
+                              } else {
+                                onSelect(m.id, {
+                                  source: "local",
+                                  isLora: false,
+                                  isDownloaded: true,
+                                });
+                              }
+                            }}
+                            onArrowDownIntoChildren={
+                              isGguf && !isGgufFile && isGgufExpanded(m.id)
+                                ? () => focusFirstChildOption(optionKey)
+                                : undefined
+                            }
+                            vramStatus={null}
+                          />
                           {isGguf && !isGgufFile && isGgufExpanded(m.id) && (
                             <GgufVariantExpander
                               repoId={m.id}
                               onDevice={true}
                               onSelect={onSelect}
-                              onConfigure={onConfigure}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
                                 hubModelList.focusOption(optionKey)
@@ -3442,9 +3370,7 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={
-                                gpu.systemRamAvailableGb || undefined
-                              }
+                              systemRamGb={gpu.systemRamAvailableGb || undefined}
                             />
                           )}
                         </div>
@@ -3514,7 +3440,6 @@ export function HubModelPicker({
                             <GgufVariantExpander
                               repoId={id}
                               onSelect={onSelect}
-                              onConfigure={onConfigure}
                               hfToken={hfToken || undefined}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
@@ -3526,9 +3451,7 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={
-                                gpu.systemRamAvailableGb || undefined
-                              }
+                              systemRamGb={gpu.systemRamAvailableGb || undefined}
                               variantActions={{
                                 onDelete: async (quant) => {
                                   await deleteCachedModel(id, quant);
@@ -3588,14 +3511,10 @@ export function HubModelPicker({
                             }
                           }}
                           vramStatus={
-                            isKnownGgufRepo(id)
-                              ? null
-                              : (vram?.status ?? null)
+                            isKnownGgufRepo(id) ? null : (vram?.status ?? null)
                           }
                           vramEst={isKnownGgufRepo(id) ? undefined : vram?.est}
-                          gpuGb={
-                            gpu.available ? gpu.memoryTotalGb : undefined
-                          }
+                          gpuGb={gpu.available ? gpu.memoryTotalGb : undefined}
                           onArrowDownIntoChildren={
                             expandedGguf === id
                               ? () => {
@@ -3610,7 +3529,6 @@ export function HubModelPicker({
                           <GgufVariantExpander
                             repoId={id}
                             onSelect={onSelect}
-                            onConfigure={onConfigure}
                             hfToken={hfToken || undefined}
                             parentOptionKey={optionKey}
                             onNavigatePastStart={() =>
@@ -3622,9 +3540,7 @@ export function HubModelPicker({
                             gpuGb={
                               gpu.available ? gpu.memoryTotalGb : undefined
                             }
-                            systemRamGb={
-                              gpu.systemRamAvailableGb || undefined
-                            }
+                            systemRamGb={gpu.systemRamAvailableGb || undefined}
                             variantActions={{
                               onDelete: async (quant) => {
                                 await deleteCachedModel(id, quant);
@@ -3704,7 +3620,6 @@ export function HubModelPicker({
                             <GgufVariantExpander
                               repoId={id}
                               onSelect={onSelect}
-                              onConfigure={onConfigure}
                               hfToken={hfToken || undefined}
                               parentOptionKey={optionKey}
                               onNavigatePastStart={() =>
@@ -3716,9 +3631,7 @@ export function HubModelPicker({
                               gpuGb={
                                 gpu.available ? gpu.memoryTotalGb : undefined
                               }
-                              systemRamGb={
-                                gpu.systemRamAvailableGb || undefined
-                              }
+                              systemRamGb={gpu.systemRamAvailableGb || undefined}
                               variantActions={{
                                 onDelete: async (quant) => {
                                   await deleteCachedModel(id, quant);
@@ -3743,6 +3656,8 @@ export function HubModelPicker({
           )}
         </div>
       </div>
+      {/* Floating eject pill: overlaid on the list bottom, outside the scroll
+          so the edge fade never touches it. Only the pill catches clicks. */}
       {onEject ? (
         <div className="pointer-events-none absolute inset-x-0 bottom-0 flex justify-end pr-3.5 pb-[19px]">
           <button
@@ -3773,7 +3688,6 @@ function FineTunedRows({
   adapters,
   value,
   onSelect,
-  onConfigure,
   onModelsChange,
   deleteDisabled = false,
   loraModelList,
@@ -3784,7 +3698,6 @@ function FineTunedRows({
   adapters: LoraModelOption[];
   value?: string;
   onSelect: (id: string, meta: ModelSelectorChangeMeta) => void;
-  onConfigure?: (id: string, meta: ModelSelectorChangeMeta) => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
   deleteDisabled?: boolean;
   loraModelList: ReturnType<typeof useRovingModelList>;
@@ -3809,13 +3722,6 @@ function FineTunedRows({
         const isTrainingFull = isTraining && isMerged;
         const isLocalGgufDir =
           isLocal && (isGgufRepo(adapter.id) || isGgufRepo(adapter.name));
-        const selectionMeta: ModelSelectorChangeMeta = {
-          source: isLocal ? "local" : isExported ? "exported" : "lora",
-          isLora: !isLocal && !isMerged && !isGguf,
-          isDownloaded: true,
-          isGguf: false,
-        };
-        const canConfigure = !(isLocalGgufDir || isExportedGguf);
         const optionKey = makeModelOptionKey("lora", adapter.id);
         const tag = isLocal
           ? isLocalGgufDir
@@ -3857,7 +3763,15 @@ function FineTunedRows({
                         prev === adapter.id ? null : adapter.id,
                       );
                     } else {
-                      onSelect(adapter.id, selectionMeta);
+                      onSelect(adapter.id, {
+                        source: isLocal
+                          ? "local"
+                          : isExported
+                            ? "exported"
+                            : "lora",
+                        isLora: !isLocal && !isMerged && !isGguf,
+                        isDownloaded: true,
+                      });
                     }
                   }}
                   tooltipText={
@@ -3878,12 +3792,6 @@ function FineTunedRows({
                   }
                 />
               </div>
-              {canConfigure && onConfigure && (
-                <ModelLoadSettingsAction
-                  ariaLabel={`Inference settings for ${adapter.name}`}
-                  onConfigure={() => onConfigure(adapter.id, selectionMeta)}
-                />
-              )}
               {canDelete && (
                 <ModelDeleteAction
                   ariaLabel={`Delete ${adapter.name}`}
@@ -3914,7 +3822,6 @@ function FineTunedRows({
               <GgufVariantExpander
                 repoId={adapter.id}
                 onSelect={onSelect}
-                onConfigure={onConfigure}
                 parentOptionKey={optionKey}
                 onNavigatePastStart={() => loraModelList.focusOption(optionKey)}
                 onNavigatePastEnd={() =>
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx b/studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
similarity index 98%
rename from studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
rename to studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
index fbc1d5ac91..e6da8a7b74 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/pill-tabs.tsx
+++ b/studio/frontend/src/components/assistant-ui/model-selector/pill-tabs.tsx
@@ -78,8 +78,7 @@ export function PillTabs({
             onValueChange(tabs[next].value);
             e.currentTarget.parentElement
               ?.querySelectorAll<HTMLElement>('button[role="tab"]')
-              .item(next)
-              ?.focus();
+              [next]?.focus();
           }}
           onClick={() => onValueChange(tab.value)}
           className={cn(
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts b/studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts
similarity index 100%
rename from studio/frontend/src/features/model-picker/components/model-selector/recommended-fit.ts
rename to studio/frontend/src/components/assistant-ui/model-selector/recommended-fit.ts
diff --git a/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts b/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
new file mode 100644
index 0000000000..ec75b17f20
--- /dev/null
+++ b/studio/frontend/src/components/assistant-ui/model-selector/remembered-load-settings.ts
@@ -0,0 +1,69 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+// Per-model pre-load inference settings, persisted in localStorage so the load
+// dialog can offer "Remember settings for <model>".
+
+const KEY = "unsloth_load_settings";
+
+export interface RememberedLoadSettings {
+  contextLength: number | null;
+  kvCacheDtype: string | null;
+  speculativeType: string | null;
+  specDraftNMax: number | null;
+  tensorParallel: boolean;
+}
+
+// Storage key for a pick's remembered settings. The remembered knobs are
+// VRAM-budget driven (context override, KV-cache dtype, tensor-parallel), so the
+// right values differ per quant. An HF repo collapses all its GGUF variants into
+// one `id`, so fold the variant in to scope settings per quant. Local .gguf
+// paths key by their file path (already file-specific); native drag-drop files
+// key by display label, so same-named files in different folders share an entry.
+export function rememberedLoadSettingsKey(selection: {
+  id: string;
+  ggufVariant?: string | null;
+}): string {
+  return selection.ggufVariant
+    ? `${selection.id}::${selection.ggufVariant}`
+    : selection.id;
+}
+
+function readAll(): Record<string, RememberedLoadSettings> {
+  try {
+    return JSON.parse(localStorage.getItem(KEY) ?? "{}");
+  } catch {
+    return {};
+  }
+}
+
+function writeAll(all: Record<string, RememberedLoadSettings>) {
+  try {
+    localStorage.setItem(KEY, JSON.stringify(all));
+  } catch {
+    // Ignore quota / unavailable storage.
+  }
+}
+
+export function loadRememberedLoadSettings(
+  key: string,
+): RememberedLoadSettings | null {
+  return readAll()[key] ?? null;
+}
+
+export function saveRememberedLoadSettings(
+  key: string,
+  settings: RememberedLoadSettings,
+) {
+  const all = readAll();
+  all[key] = settings;
+  writeAll(all);
+}
+
+export function clearRememberedLoadSettings(key: string) {
+  const all = readAll();
+  if (key in all) {
+    delete all[key];
+    writeAll(all);
+  }
+}
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/row-meta.ts b/studio/frontend/src/components/assistant-ui/model-selector/row-meta.ts
similarity index 100%
rename from studio/frontend/src/features/model-picker/components/model-selector/row-meta.ts
rename to studio/frontend/src/components/assistant-ui/model-selector/row-meta.ts
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/source-tabs.ts b/studio/frontend/src/components/assistant-ui/model-selector/source-tabs.ts
similarity index 100%
rename from studio/frontend/src/features/model-picker/components/model-selector/source-tabs.ts
rename to studio/frontend/src/components/assistant-ui/model-selector/source-tabs.ts
diff --git a/studio/frontend/src/features/model-picker/components/model-selector/types.ts b/studio/frontend/src/components/assistant-ui/model-selector/types.ts
similarity index 76%
rename from studio/frontend/src/features/model-picker/components/model-selector/types.ts
rename to studio/frontend/src/components/assistant-ui/model-selector/types.ts
index dae072236b..6a86515267 100644
--- a/studio/frontend/src/features/model-picker/components/model-selector/types.ts
+++ b/studio/frontend/src/components/assistant-ui/model-selector/types.ts
@@ -2,7 +2,6 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import type { ReactNode } from "react";
-import type { PerModelConfig } from "../../model-config/per-model-config";
 
 export interface ModelOption {
   id: string;
@@ -37,18 +36,6 @@ export interface ModelSelectorChangeMeta {
   /** Direct local .gguf file picked without a variant (custom folder / LM
    *  Studio). Marks it as a GGUF source for the deferred-load staging flow. */
   isGguf?: boolean;
-  config?: PerModelConfig;
-  forceReload?: boolean;
-  /** Native path token so an active-model reload can reopen a file-picked GGUF. */
-  nativePathToken?: string;
-}
-
-export interface ModelPickTarget {
-  id: string;
-  displayName: string;
-  ggufVariant?: string | null;
-  isGguf: boolean;
-  meta: ModelSelectorChangeMeta;
 }
 
 export interface DeletedModelRef {
diff --git a/studio/frontend/src/features/chat/api/chat-adapter.ts b/studio/frontend/src/features/chat/api/chat-adapter.ts
index d3bdcb6898..0bf46e7343 100644
--- a/studio/frontend/src/features/chat/api/chat-adapter.ts
+++ b/studio/frontend/src/features/chat/api/chat-adapter.ts
@@ -2,7 +2,10 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { getAuthToken } from "@/features/auth";
-import { resolveInitialConfig } from "@/features/model-picker";
+import {
+  loadRememberedLoadSettings,
+  rememberedLoadSettingsKey,
+} from "@/components/assistant-ui/model-selector/remembered-load-settings";
 import { projectHasSources } from "@/features/rag/api/rag-api";
 import { apiUrl } from "@/lib/api-base";
 import { parseParamCountB } from "@/lib/model-size";
@@ -1517,25 +1520,27 @@ async function autoLoadSmallestModel(): Promise<{
       return false;
     }
     const currentStore = useChatRuntimeStore.getState();
-    const { config } = resolveInitialConfig(candidate.id, candidate.ggufVariant);
+    const remembered = loadRememberedLoadSettings(
+      rememberedLoadSettingsKey({
+        id: candidate.id,
+        ggufVariant: candidate.ggufVariant,
+      }),
+    );
     const effectiveMaxSeqLength = resolveLoadMaxSeqLength({
       modelId: candidate.id,
       ggufVariant: candidate.ggufVariant,
       isGguf: candidate.kind === "gguf",
-      customContextLength: config.customContextLength,
+      customContextLength: remembered?.contextLength ?? null,
       ggufContextLength: null,
       currentCheckpoint: currentStore.params.checkpoint,
       activeGgufVariant: currentStore.activeGgufVariant,
-      maxSeqLength: config.maxSeqLength ?? candidate.maxSeqLength,
+      maxSeqLength: candidate.maxSeqLength,
       presetSource: currentStore.activePresetSource,
     });
     const effectiveSpeculativeType =
-      config.speculativeType ?? specSettings.speculativeType;
+      remembered?.speculativeType ?? specSettings.speculativeType;
     const effectiveSpecDraftNMax =
-      config.specDraftNMax ?? specSettings.specDraftNMax;
-    const effectiveChatTemplateOverride = config.chatTemplateOverride?.trim()
-      ? config.chatTemplateOverride
-      : null;
+      remembered?.specDraftNMax ?? specSettings.specDraftNMax;
     if (
       !(await canAutoLoad({
         model_path: candidate.id,
@@ -1558,18 +1563,12 @@ async function autoLoadSmallestModel(): Promise<{
       is_lora: false,
       gguf_variant: candidate.ggufVariant,
       trust_remote_code: trustRemoteCode,
-      chat_template_override: effectiveChatTemplateOverride,
-      cache_type_kv: config.kvCacheDtype,
+      cache_type_kv: remembered?.kvCacheDtype ?? null,
       speculative_type: effectiveSpeculativeType,
       spec_draft_n_max: effectiveSpecDraftNMax,
-      tensor_parallel: config.tensorParallel,
+      tensor_parallel: remembered?.tensorParallel ?? false,
     });
-    // Only persist the global preference when the value came from the global
-    // settings. A per-model config's choice must stay load-local, or autoloading
-    // a remembered model on startup would rewrite the global default.
-    if (config.speculativeType == null) {
-      saveSpeculativeType(effectiveSpeculativeType);
-    }
+    saveSpeculativeType(effectiveSpeculativeType);
     useChatRuntimeStore
       .getState()
       .setCheckpoint(candidate.id, candidate.ggufVariant ?? undefined);
@@ -1579,9 +1578,6 @@ async function autoLoadSmallestModel(): Promise<{
     );
     store.setParams({
       ...store.params,
-      ...(candidate.kind === "gguf"
-        ? {}
-        : { maxSeqLength: effectiveMaxSeqLength }),
       maxTokens:
         candidate.kind === "gguf"
           ? loadResp.context_length ?? 131072
@@ -1618,11 +1614,8 @@ async function autoLoadSmallestModel(): Promise<{
         tensorParallel: loadResp.tensor_parallel ?? false,
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
         defaultChatTemplate: loadResp.chat_template ?? null,
-        chatTemplateOverride: effectiveChatTemplateOverride,
-        loadedChatTemplateOverride: effectiveChatTemplateOverride,
-        // Retain the saved requested context so re-saving the config keeps the
-        // override; null stays null (auto/VRAM-fit).
-        customContextLength: config.customContextLength,
+        chatTemplateOverride: null,
+        loadedChatTemplateOverride: null,
         loadedIsMultimodal: isMultimodalResponse(loadResp),
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
         ...resolveLoadedSpeculativeSettings(loadResp),
@@ -1641,9 +1634,8 @@ async function autoLoadSmallestModel(): Promise<{
         tensorParallel: loadResp.tensor_parallel ?? false,
         loadedTensorParallel: loadResp.tensor_parallel ?? false,
         defaultChatTemplate: loadResp.chat_template ?? null,
-        chatTemplateOverride: effectiveChatTemplateOverride,
-        loadedChatTemplateOverride: effectiveChatTemplateOverride,
-        customContextLength: null,
+        chatTemplateOverride: null,
+        loadedChatTemplateOverride: null,
         ...resolveLoadedSpeculativeSettings(loadResp),
         loadedIsMultimodal: isMultimodalResponse(loadResp),
         loadedIsDiffusion: loadResp.is_diffusion ?? false,
diff --git a/studio/frontend/src/features/chat/chat-page.tsx b/studio/frontend/src/features/chat/chat-page.tsx
index 731a551c53..380ce0e0ab 100644
--- a/studio/frontend/src/features/chat/chat-page.tsx
+++ b/studio/frontend/src/features/chat/chat-page.tsx
@@ -2,18 +2,16 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import {
-  applyModelLoadConfigToRuntime,
-  currentRuntimePerModelConfig,
   type DeletedModelRef,
   type ExternalModelOption,
   type LoraModelOption,
   type ModelOption,
   ModelSelector,
-  type ModelSelectorChangeMeta,
-  type PerModelConfig,
-  resolveInitialConfig,
-  SidebarModelConfig,
-} from "@/features/model-picker";
+} from "@/components/assistant-ui/model-selector";
+import {
+  loadRememberedLoadSettings,
+  rememberedLoadSettingsKey,
+} from "@/components/assistant-ui/model-selector/remembered-load-settings";
 import { ProjectComposer, Thread } from "@/components/assistant-ui/thread";
 import { CopyableErrorChip } from "@/components/ui/copyable-error-chip";
 import {
@@ -29,10 +27,10 @@ import {
 } from "@/components/ui/resizable";
 import { useSidebar } from "@/components/ui/sidebar";
 import { Tooltip, TooltipContent } from "@/components/ui/tooltip";
+import { useLatestRef } from "@/features/hub/hooks/use-latest-ref";
 import {
   DOWNLOAD_KIND,
   downloadManager,
-  useRepoDownload,
 } from "@/features/hub/download-manager";
 import {
   type NativeIntent,
@@ -95,6 +93,7 @@ import {
   renameChatItem,
   useChatSidebarItems,
 } from "./hooks/use-chat-sidebar-items";
+import { useStagedModelPreparation } from "./hooks/use-staged-model-preparation";
 import {
   clearTrainingCompareHandoff,
   getTrainingCompareHandoff,
@@ -129,8 +128,10 @@ import {
   hasGgufSource,
   isDownloadableHubRepo,
   loadOptionalBool,
+  pendingSelectionMatches,
   useChatRuntimeStore,
 } from "./stores/chat-runtime-store";
+import type { PendingModelSelection } from "./stores/chat-runtime-store";
 import { useChatPreferencesStore } from "./stores/chat-preferences-store";
 import { useExternalProvidersStore } from "./stores/external-providers-store";
 import { buildChatTourSteps } from "./tour";
@@ -384,7 +385,6 @@ type CompareModelSelection = {
   id: string;
   isLora: boolean;
   ggufVariant?: string;
-  config?: PerModelConfig;
 };
 
 function modelMatchesDeleted(
@@ -645,8 +645,6 @@ function GeneralCompareHeader({
   loraModels,
   externalModels,
   value,
-  selectedConfig,
-  selectedGgufVariant,
   onValueChange,
   onFoldersChange,
   onModelsChange,
@@ -657,11 +655,9 @@ function GeneralCompareHeader({
   loraModels: LoraModelOption[];
   externalModels: ExternalModelOption[];
   value: string;
-  selectedConfig?: PerModelConfig | null;
-  selectedGgufVariant?: string | null;
   onValueChange: (
     id: string,
-    meta: ModelSelectorChangeMeta,
+    meta: { isLora: boolean; ggufVariant?: string },
   ) => void;
   onFoldersChange?: () => void;
   onModelsChange?: (deletedModel?: DeletedModelRef) => void;
@@ -688,8 +684,6 @@ function GeneralCompareHeader({
         loraModels={loraModels}
         externalModels={externalModels}
         value={value}
-        selectedConfig={selectedConfig}
-        selectedGgufVariant={selectedGgufVariant}
         onValueChange={onValueChange}
         onFoldersChange={onFoldersChange}
         onModelsChange={onModelsChange}
@@ -817,14 +811,11 @@ const GeneralCompareContent = memo(function GeneralCompareContent({
               loraModels={loraModels}
               externalModels={externalModels}
               value={model1.id}
-              selectedConfig={model1.config}
-              selectedGgufVariant={model1.ggufVariant}
               onValueChange={(id, meta) =>
                 setModel1({
                   id,
                   isLora: meta.isLora,
                   ggufVariant: meta.ggufVariant,
-                  config: meta.config,
                 })
               }
               onFoldersChange={onFoldersChange}
@@ -847,14 +838,11 @@ const GeneralCompareContent = memo(function GeneralCompareContent({
               loraModels={loraModels}
               externalModels={externalModels}
               value={model2.id}
-              selectedConfig={model2.config}
-              selectedGgufVariant={model2.ggufVariant}
               onValueChange={(id, meta) =>
                 setModel2({
                   id,
                   isLora: meta.isLora,
                   ggufVariant: meta.ggufVariant,
-                  config: meta.config,
                 })
               }
               onFoldersChange={onFoldersChange}
@@ -1248,13 +1236,6 @@ export function validateChatSearch(search: Record<string, unknown>): ChatSearch
   };
 }
 
-type PendingHubAutoLoad = {
-  selection: SelectedModelInput;
-  contextKey: string;
-  originCheckpoint: string;
-  originGgufVariant: string | null;
-};
-
 // `search` comes from RootLayout (not useSearch) so ChatPage stays mounted off-route
 // (keeping an in-flight generation alive), frozen to the last /chat search. `active`
 // is false off-route: close body-portaled surfaces and stop route-specific listeners
@@ -1267,6 +1248,30 @@ export function ChatPage({
 
   const settingsOpen = useChatRuntimeStore((s) => s.settingsPanelOpen);
   const setSettingsOpen = useChatRuntimeStore((s) => s.setSettingsPanelOpen);
+  // Deferred-load staging: downloads a staged GGUF (if needed) and reads its
+  // header context so the sheet can show the context slider before the load.
+  // autoLoad picks instead load the cached file as soon as the download ends;
+  // selectModel is defined below, so the load runs through a ref.
+  const autoLoadStagedRef = useRef<
+    ((pending: PendingModelSelection) => void) | null
+  >(null);
+  const stagedDownload = useStagedModelPreparation({
+    onAutoLoad: (pending) => autoLoadStagedRef.current?.(pending),
+  });
+  // Abandon a staged pick: the store action cancels its in-flight download and
+  // reverts the edited knobs, so nothing lingers after the user walks away.
+  const abandonStaged = useCallback(() => {
+    useChatRuntimeStore.getState().abandonStagedModel();
+  }, []);
+  // Detach a staged pick on navigation without cancelling its download: the
+  // transfer keeps running in the manager and lands in cache, like Hub.
+  const detachStaged = useCallback(() => {
+    useChatRuntimeStore.getState().abandonStagedModel({ keepDownload: true });
+  }, []);
+  // Tracks whether the chat page is still mounted, so a staged-load failure that
+  // resolves after the user left chat doesn't resurrect the abandoned pick.
+  const mountedRef = useRef(true);
+  useEffect(() => () => void (mountedRef.current = false), []);
   const incognito = useChatRuntimeStore((s) => s.incognito);
   const setIncognito = useChatRuntimeStore((s) => s.setIncognito);
   const incognitoLabel = incognito
@@ -1358,9 +1363,6 @@ export function ChatPage({
   const ggufContextLength = useChatRuntimeStore(
     (state) => state.ggufContextLength,
   );
-  const ggufNativeContextLength = useChatRuntimeStore(
-    (state) => state.ggufNativeContextLength,
-  );
   const contextUsage = useChatRuntimeStore((state) => state.contextUsage);
   const modelsFromStore = useChatRuntimeStore((state) => state.models);
   const lorasFromStore = useChatRuntimeStore((state) => state.loras);
@@ -1438,82 +1440,37 @@ export function ChatPage({
     refreshRef.current = refresh;
     selectModelRef.current = selectModel;
   }, [refresh, selectModel]);
-  const rememberedConfigFor = useCallback(
-    (selection: {
-      id: string;
-      ggufVariant?: string | null;
-      source?: string;
-    }) => {
-      if (selection.source === "external") return null;
-      const resolved = resolveInitialConfig(selection.id, selection.ggufVariant);
-      return resolved.remembered ? resolved.config : null;
-    },
-    [],
-  );
+  // Load a cached autoLoad pick once its download finishes. The sheet was never
+  // opened, so on a load failure just drop the orphaned staged knobs. The knobs
+  // were already seeded on stage, so keepSpeculative only when a config was
+  // saved -- otherwise the standing speculative preference should win.
+  autoLoadStagedRef.current = (pending) => {
+    const remembered = loadRememberedLoadSettings(
+      rememberedLoadSettingsKey(pending),
+    );
+    void selectModel({
+      ...pending,
+      isDownloaded: true,
+      forceReload: true,
+      keepSpeculative: remembered != null,
+      throwOnError: true,
+    }).catch(() => {
+      const store = useChatRuntimeStore.getState();
+      // selectModel only clears pendingSelection on success, so a failed
+      // auto-load leaves our staged pick (and its edited load knobs) behind.
+      // Abandon it when it is still the active stage; otherwise just revert the
+      // settings if the stage was already cleared by something else.
+      if (pendingSelectionMatches(store.pendingSelection, pending)) {
+        store.abandonStagedModel();
+      } else if (!store.pendingSelection) {
+        store.resetModelSettingsToLoaded();
+      }
+    });
+  };
   const isExternalModel = useMemo(
     () => isExternalModelId(inferenceParams.checkpoint),
     [inferenceParams.checkpoint],
   );
-  const runtimeCustomContextLength = useChatRuntimeStore(
-    (s) => s.customContextLength,
-  );
-  const runtimeKvCacheDtype = useChatRuntimeStore((s) => s.kvCacheDtype);
-  const runtimeSpeculativeType = useChatRuntimeStore((s) => s.speculativeType);
-  const runtimeSpecDraftNMax = useChatRuntimeStore((s) => s.specDraftNMax);
-  const runtimeTensorParallel = useChatRuntimeStore((s) => s.tensorParallel);
-  const runtimeChatTemplateOverride = useChatRuntimeStore(
-    (s) => s.chatTemplateOverride,
-  );
-  const activeModelConfig = useMemo<PerModelConfig | null>(() => {
-    if (!inferenceParams.checkpoint || isExternalModel) return null;
-    const activeModelIsGguf =
-      activeGgufVariant != null ||
-      ggufContextLength != null ||
-      inferenceParams.checkpoint.toLowerCase().endsWith(".gguf");
-    return {
-      customContextLength: runtimeCustomContextLength ?? null,
-      maxSeqLength: activeModelIsGguf ? null : inferenceParams.maxSeqLength,
-      kvCacheDtype: runtimeKvCacheDtype ?? null,
-      speculativeType: runtimeSpeculativeType ?? "auto",
-      specDraftNMax: runtimeSpecDraftNMax ?? null,
-      tensorParallel: runtimeTensorParallel ?? false,
-      chatTemplateOverride: runtimeChatTemplateOverride ?? null,
-    };
-  }, [
-    inferenceParams.checkpoint,
-    inferenceParams.maxSeqLength,
-    isExternalModel,
-    activeGgufVariant,
-    ggufContextLength,
-    runtimeCustomContextLength,
-    runtimeKvCacheDtype,
-    runtimeSpeculativeType,
-    runtimeSpecDraftNMax,
-    runtimeTensorParallel,
-    runtimeChatTemplateOverride,
-  ]);
-  const activeModelIsGguf = useMemo(() => {
-    const checkpoint = inferenceParams.checkpoint;
-    if (!checkpoint || isExternalModel) return false;
-    return (
-      activeGgufVariant != null ||
-      ggufContextLength != null ||
-      checkpoint.toLowerCase().endsWith(".gguf")
-    );
-  }, [
-    inferenceParams.checkpoint,
-    isExternalModel,
-    activeGgufVariant,
-    ggufContextLength,
-  ]);
-  const activeModelIsLora = useMemo(() => {
-    const checkpoint = inferenceParams.checkpoint;
-    if (!checkpoint || isExternalModel) return false;
-    const model = modelsFromStore.find((entry) => entry.id === checkpoint);
-    if (model) return model.isLora;
-    const lora = lorasFromStore.find((entry) => entry.id === checkpoint);
-    return lora?.exportType === "lora";
-  }, [inferenceParams.checkpoint, isExternalModel, modelsFromStore, lorasFromStore]);
   const reasoningEnabled = useChatRuntimeStore((s) => s.reasoningEnabled);
   const reasoningStyle = useChatRuntimeStore((s) => s.reasoningStyle);
   const reasoningEffort = useChatRuntimeStore((s) => s.reasoningEffort);
@@ -1826,21 +1783,75 @@ export function ChatPage({
     closeArtifactSurface();
   }, [activeThreadId, closeArtifactSurface, selectedArtifact, view]);
 
-  const hasActiveModel = Boolean(inferenceParams.checkpoint);
+  // Abandon a staged (not-yet-loaded) pick when the chat context actually
+  // changes — switching threads, leaving single view, or starting a new chat /
+  // project — so a stale Load button can't resurface in a different context.
+  // New Chat keeps activeThreadId null and only bumps the `new` search nonce, so
+  // the key includes the route identity, not just the thread. Mirrors the
+  // incognito reset pattern. (Route exit is handled in __root.tsx, which runs
+  // after this unmounts.) Clear only on a real change, never on mount: staging
+  // from the Hub sets pendingSelection then navigates here, and clearing on
+  // mount would wipe it. Comparing the previous context (rather than a first-run
+  // flag) is also safe under StrictMode's double-invoke and component remounts.
   const chatContextKey = `${view.mode}|${activeThreadId ?? ""}|${search.new ?? ""}|${search.project ?? ""}`;
-  const [pendingHubAutoLoad, setPendingHubAutoLoad] =
-    useState<PendingHubAutoLoad | null>(null);
+  const chatContextKeyRef = useLatestRef(chatContextKey);
+  const prevChatContextRef = useRef<string | null>(null);
+  useEffect(() => {
+    const prev = prevChatContextRef.current;
+    prevChatContextRef.current = chatContextKey;
+    if (prev === null || prev === chatContextKey) return;
+    detachStaged();
+  }, [chatContextKey, detachStaged]);
+
+  const hasActiveModel = Boolean(inferenceParams.checkpoint);
+  // Load immediately, or — when "Load on selection" is off — stage the pick so
+  // its load options can be set first. Shared by the main selector, native
+  // drag-drop/picker, and the dropped-file chip (the Hub stages via the store).
   const stageOrLoad = useCallback(
     async (selection: SelectedModelInput) => {
       const store = useChatRuntimeStore.getState();
+      // An un-cached HF repo (GGUF variant or a full non-GGUF snapshot) downloads
+      // through the manager first (global indicator), then auto-loads. Everything
+      // else -- cached picks, local/native files, LoRA, external -- loads now.
       const wantManagerDownload =
         isDownloadableHubRepo(selection) && !selection.isDownloaded;
+      if (
+        (!hasGgufSource(selection) && !wantManagerDownload) ||
+        (store.loadOnSelection && selection.isDownloaded)
+      ) {
+        // Detach any staged pick first so its edited knobs (e.g. a custom
+        // context length) don't leak into this immediate load -- resolveLoad
+        // reads customContextLength before checking the target is GGUF. Detach
+        // (not abandon) keeps its download running.
+        detachStaged();
+        // Load-on-selection skips the sheet, so seed the saved knobs here the
+        // way the sheet's restore effect would; the switch would otherwise reset
+        // the remembered speculative choice (keepSpeculative below prevents it).
+        const remembered = hasGgufSource(selection)
+          ? loadRememberedLoadSettings(rememberedLoadSettingsKey(selection))
+          : null;
+        if (remembered) store.applyRememberedLoadSettings(remembered);
+        await selectModel(
+          remembered ? { ...selection, keepSpeculative: true } : selection,
+        );
+        return;
+      }
+      // Loads can't queue behind each other, but a download is independent: if
+      // the pick needs downloading, start it in the manager so it runs alongside
+      // the load. Nothing to download (already on device) just waits.
       if (store.modelLoading) {
+        // Both an uncached non-GGUF snapshot (wantManagerDownload) and an
+        // uncached remote GGUF quant download through the manager, so either can
+        // run in the background while another model loads. wantManagerDownload
+        // excludes GGUF by design, so the GGUF case is checked separately.
         const wantBackgroundDownload =
           wantManagerDownload ||
           (selection.source === "hub" &&
             hasGgufSource(selection) &&
             !selection.isDownloaded);
+        // The model currently loading already downloads as part of its own load
+        // (the /load flow fetches before setting the checkpoint), so re-picking
+        // it must not kick off a second transfer against the same cache.
         const isLoadingThisPick =
           !!loadingModel &&
           normalizeModelRef(loadingModel.id) ===
@@ -1851,6 +1862,11 @@ export function ChatPage({
             description: "It's downloading as part of the load in progress.",
           });
         } else if (wantBackgroundDownload) {
+          // Only claim the download started once a job is actually created. A
+          // transport conflict records state that is only resolvable from the
+          // Hub download card, so point the user there instead of showing a
+          // success toast for a transfer that never began; "busy" and "error"
+          // already surface their own toasts.
           const outcome = await downloadManager.requestStart({
             kind: DOWNLOAD_KIND.MODEL,
             repoId: selection.id,
@@ -1867,11 +1883,6 @@ export function ChatPage({
               description:
                 "An earlier partial download used a different transport. Open the Hub tab to resume or restart it.",
             });
-          } else if (outcome === "busy") {
-            toast.info("Download already in progress", {
-              description:
-                "Another download for this model is still running. Reselect it once that finishes to load it.",
-            });
           }
         } else {
           toast.info("Another model is already loading", {
@@ -1880,118 +1891,23 @@ export function ChatPage({
         }
         return;
       }
-      const wantManagerStage =
-        wantManagerDownload ||
-        (selection.source === "hub" &&
-          hasGgufSource(selection) &&
-          !selection.isDownloaded);
-      if (wantManagerStage) {
-        setPendingHubAutoLoad({
-          selection,
-          contextKey: chatContextKey,
-          originCheckpoint: store.params.checkpoint,
-          originGgufVariant: store.activeGgufVariant,
-        });
-        return;
-      }
-      setPendingHubAutoLoad(null);
-      const previousConfig = currentRuntimePerModelConfig({
-        includeMaxSeqLength: true,
-      });
-      const hasAppliedConfig = applyModelLoadConfigToRuntime(
-        selection.config ?? rememberedConfigFor(selection),
-      );
-      await selectModel({
-        ...selection,
-        ...(hasAppliedConfig ? { keepSpeculative: true } : {}),
-        previousConfig,
+      // Detach the prior staged pick (keeping its download) before rebinding, so
+      // a second pick downloads alongside the first instead of cancelling it.
+      detachStaged();
+      store.stageModel({
+        id: selection.id,
+        isLora: selection.isLora,
+        ggufVariant: selection.ggufVariant,
+        isDownloaded: selection.isDownloaded,
+        expectedBytes: selection.expectedBytes,
+        nativePathToken: selection.nativePathToken,
+        isGguf: selection.isGguf,
+        isHubRepo: wantManagerDownload || undefined,
+        autoLoad: store.loadOnSelection,
       });
     },
-    [selectModel, loadingModel, rememberedConfigFor, chatContextKey],
+    [detachStaged, selectModel, loadingModel],
   );
-  useRepoDownload({
-    kind: DOWNLOAD_KIND.MODEL,
-    repoId: pendingHubAutoLoad?.selection.id ?? "__hub_autoload_idle__",
-    activeVariant: pendingHubAutoLoad?.selection.ggufVariant ?? null,
-    onComplete: (variant) => {
-      const pending = pendingHubAutoLoad;
-      if (
-        !pending ||
-        (pending.selection.ggufVariant ?? null) !== (variant ?? null)
-      ) {
-        return;
-      }
-      setPendingHubAutoLoad(null);
-      const store = useChatRuntimeStore.getState();
-      if (
-        !active ||
-        pending.contextKey !== chatContextKey ||
-        normalizeModelRef(pending.originCheckpoint) !==
-          normalizeModelRef(store.params.checkpoint) ||
-        pending.originGgufVariant !== store.activeGgufVariant
-      ) {
-        return;
-      }
-      void stageOrLoad({ ...pending.selection, isDownloaded: true });
-    },
-    onError: (variant) => {
-      if (
-        pendingHubAutoLoad &&
-        (pendingHubAutoLoad.selection.ggufVariant ?? null) === (variant ?? null)
-      ) {
-        setPendingHubAutoLoad(null);
-      }
-    },
-    onCancelled: (variant) => {
-      if (
-        pendingHubAutoLoad &&
-        (pendingHubAutoLoad.selection.ggufVariant ?? null) === (variant ?? null)
-      ) {
-        setPendingHubAutoLoad(null);
-      }
-    },
-  });
-  useEffect(() => {
-    const pending = pendingHubAutoLoad;
-    if (!pending) return;
-    let active = true;
-    void (async () => {
-      const outcome = await downloadManager.requestStart({
-        kind: DOWNLOAD_KIND.MODEL,
-        repoId: pending.selection.id,
-        variant: pending.selection.ggufVariant ?? null,
-        expectedBytes: pending.selection.expectedBytes ?? 0,
-      });
-      if (!active) return;
-      if (outcome === "started") {
-        toast.info("Downloading model", {
-          description: "It'll load automatically once the download finishes.",
-        });
-        return;
-      }
-      if (outcome === "conflict") {
-        // Keep pendingHubAutoLoad bound so this surface's cleanup does not wipe
-        // the conflict just recorded by requestStart (which the toast points the
-        // user to); resolving it from the Hub completes the download and this
-        // surface's onComplete auto-loads, mirroring the "started" branch.
-        toast.info("Resume this download from the Hub", {
-          description:
-            "An earlier partial download used a different transport. Open the Hub tab to resume or restart it.",
-        });
-        return;
-      }
-      if (outcome === "busy") {
-        toast.info("Download already in progress", {
-          description:
-            "Another download for this model is still running. Reselect it once that finishes to load it.",
-        });
-      }
-      setPendingHubAutoLoad((current) => (current === pending ? null : current));
-    })();
-    return () => {
-      active = false;
-    };
-  }, [pendingHubAutoLoad]);
   const loadNativeModelIntent = useCallback(
     async (intent: NativeIntent, loadingDescription: string) => {
       const label =
@@ -2004,11 +1920,6 @@ export function ChatPage({
         forceReload: true,
         throwOnError: true,
       });
-      // Record when this file lease expires so a later reload can prompt
-      // re-selection instead of reusing a token the host has already pruned.
-      useChatRuntimeStore.setState({
-        activeNativePathExpiresAtMs: intent.path.expiresAtMs ?? null,
-      });
       useNativeIntentStore.getState().clearModelIntent(intent.id);
     },
     [stageOrLoad],
@@ -2054,20 +1965,28 @@ export function ChatPage({
   const handleCheckpointChange = useCallback(
     (
       value: string,
-      meta?: ModelSelectorChangeMeta,
+      meta?: {
+        source?: string;
+        isLora: boolean;
+        ggufVariant?: string;
+        isDownloaded?: boolean;
+        expectedBytes?: number;
+        isGguf?: boolean;
+      },
     ) => {
       const store = useChatRuntimeStore.getState();
       const currentCheckpoint = store.params.checkpoint;
       const currentVariant = store.activeGgufVariant;
-      if (!value) return;
-      setPendingHubAutoLoad(null);
-      const isSameLoadedModel =
-        value === currentCheckpoint &&
-        (meta?.ggufVariant ?? null) === (currentVariant ?? null);
-      if (isSameLoadedModel && !meta?.forceReload) {
+      if (
+        !value ||
+        (value === currentCheckpoint &&
+          (meta?.ggufVariant ?? null) === (currentVariant ?? null))
+      )
         return;
-      }
       if (meta?.source === "external" || isExternalModelId(value)) {
+        // Switching to an external model abandons any staged local pick: cancel
+        // its download too (setCheckpoint below only clears the pending + knobs).
+        abandonStaged();
         const selectedExternal = parseExternalModelId(value);
         const selectedProvider = selectedExternal
           ? externalProvidersForChat.find(
@@ -2239,17 +2158,19 @@ export function ChatPage({
           source: meta?.source,
           isLora: meta?.isLora,
           ggufVariant: meta?.ggufVariant,
-          isDownloaded: meta?.isDownloaded || isSameLoadedModel,
+          isDownloaded: meta?.isDownloaded,
           expectedBytes: meta?.expectedBytes,
           isGguf: meta?.isGguf,
-          config: meta?.config,
-          nativePathToken: meta?.nativePathToken,
-          forceReload: isSameLoadedModel || undefined,
         };
+        // "Load on selection" off: stage the model and open settings so its
+        // load knobs (tensor parallel, context length…) can be set, then it
+        // loads once via the sheet's Load button. The currently loaded model
+        // stays put until the user commits.
         await stageOrLoad(selection);
       })();
     },
     [
+      abandonStaged,
       activeThreadId,
       externalProvidersForChat,
       modelsFromStore,
@@ -2257,44 +2178,6 @@ export function ChatPage({
       view,
     ],
   );
-  const handleReloadActiveModel = useCallback(
-    (config: PerModelConfig) => {
-      const checkpoint = inferenceParams.checkpoint;
-      if (!checkpoint) return;
-      const runtime = useChatRuntimeStore.getState();
-      const nativeToken = runtime.activeNativePathToken;
-      const nativeExpiry = runtime.activeNativePathExpiresAtMs;
-      // A file-picked GGUF is reachable only via its native path token, which
-      // the desktop host prunes after a TTL. Reusing an expired token makes the
-      // reload fail with an opaque error, so prompt the user to re-select the
-      // file instead.
-      if (nativeToken && nativeExpiry != null && Date.now() >= nativeExpiry) {
-        toast.error("This local model file's access has expired.", {
-          description: "Re-select the model file to reload it.",
-        });
-        return;
-      }
-      handleCheckpointChange(checkpoint, {
-        source: "local",
-        isLora: activeModelIsLora,
-        ggufVariant: activeGgufVariant ?? undefined,
-        // Without the native token the reload validates the display label as a
-        // repo and fails.
-        nativePathToken: nativeToken ?? undefined,
-        isGguf: activeModelIsGguf,
-        isDownloaded: true,
-        config,
-        forceReload: true,
-      });
-    },
-    [
-      inferenceParams.checkpoint,
-      activeGgufVariant,
-      activeModelIsLora,
-      activeModelIsGguf,
-      handleCheckpointChange,
-    ],
-  );
   const handleEject = useCallback(() => {
     void (async () => {
       if (await ejectModel()) {
@@ -2697,8 +2580,6 @@ export function ChatPage({
                 externalModels={externalModels}
                 value={inferenceParams.checkpoint}
                 activeGgufVariant={activeGgufVariant}
-                activeModelConfig={activeModelConfig}
-                activeGgufContextLength={ggufContextLength}
                 onValueChange={handleCheckpointChange}
                 onEject={handleEject}
                 onFoldersChange={refreshLocalModels}
@@ -2752,12 +2633,7 @@ export function ChatPage({
               <NativeModelChip
                 intent={pendingNativeModelIntent}
                 nativeReadsDisabled={!nativePathLeasesSupported}
-                onLoad={() =>
-                  loadNativeModelIntent(
-                    pendingNativeModelIntent,
-                    "Loading selected local GGUF model.",
-                  )
-                }
+                onLoad={(selection) => stageOrLoad(selection)}
               />
             ) : null}
             {loadingModel && loadToastDismissed ? (
@@ -2914,22 +2790,13 @@ export function ChatPage({
         open={active && settingsOpen}
         onOpenChange={(open) => {
           setSettingsOpen(open);
+          // Closing the sheet abandons a staged (not-yet-loaded) pick: cancel its
+          // download and revert the staged knobs so nothing lingers as a dirty
+          // edit (or a background download) on the loaded model.
+          if (!open) abandonStaged();
         }}
         params={inferenceParams}
         onParamsChange={setInferenceParams}
-        modelConfig={
-          view.mode !== "compare" && activeModelConfig && !modelLoading ? (
-            <SidebarModelConfig
-              modelId={inferenceParams.checkpoint}
-              ggufVariant={activeGgufVariant ?? null}
-              isGguf={activeModelIsGguf}
-              nativeContextLength={ggufNativeContextLength}
-              loadedContextLength={ggufContextLength}
-              loadedConfig={activeModelConfig}
-              onReload={handleReloadActiveModel}
-            />
-          ) : null
-        }
         isExternalModel={isExternalModel}
         providerCapabilities={activeProviderCapabilities}
         activeExternalProvider={activeExternalProvider}
@@ -2941,6 +2808,62 @@ export function ChatPage({
           );
         }}
         externalProviderType={activeExternalProviderType}
+        loadingModel={loadingModel}
+        onReloadModel={() => {
+          const state = useChatRuntimeStore.getState();
+          if (state.params.checkpoint) {
+            selectModel({
+              id: state.params.checkpoint,
+              ggufVariant: state.activeGgufVariant ?? undefined,
+              forceReload: true,
+              isDownloaded: true,
+              loadingDescription: "Reloading with updated chat template.",
+            });
+          }
+        }}
+        onLoadPendingModel={() => {
+          const pending = useChatRuntimeStore.getState().pendingSelection;
+          if (!pending) return;
+          const keyAtLoad = chatContextKey;
+          // forceReload: the staged model isn't loaded yet, so bypass the
+          // same-checkpoint dedupe. keepSpeculative: honor the speculative mode
+          // set on the sidebar.
+          void selectModel({
+            ...pending,
+            forceReload: true,
+            keepSpeculative: true,
+            throwOnError: true,
+          }).catch(() => {
+            // Recoverable failure (expired token, gated repo, OOM…): the pick is
+            // cleared only on success, so it normally stays staged with edited
+            // knobs intact — nothing to restore.
+            const store = useChatRuntimeStore.getState();
+            // Still staged (this pick, or a newer one queued meanwhile): leave it.
+            if (store.pendingSelection) return;
+            // Cleared mid-load (sheet closed / switched chats). Re-stage only if
+            // the staged-load is still wanted: same chat context, sheet still
+            // open, page still mounted.
+            const stillWanted =
+              mountedRef.current &&
+              store.settingsPanelOpen &&
+              chatContextKeyRef.current === keyAtLoad;
+            if (stillWanted) {
+              store.setPendingSelection(pending);
+            } else {
+              // Abandoned (closed the sheet / switched chats / left chat): drop
+              // the orphaned staged knob edits so they don't linger as dirty
+              // settings over the loaded model.
+              store.resetModelSettingsToLoaded();
+            }
+          });
+        }}
+        stagedDownloadFraction={stagedDownload.progress?.fraction ?? null}
+        onCancelStagedDownload={() =>
+          stagedDownload.cancelDownload(
+            useChatRuntimeStore.getState().pendingSelection?.ggufVariant ??
+              null,
+          )
+        }
       />
     </div>
     </ChatActiveContext.Provider>
diff --git a/studio/frontend/src/features/chat/chat-settings-sheet.tsx b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
index a5768024b5..cedd298ecf 100644
--- a/studio/frontend/src/features/chat/chat-settings-sheet.tsx
+++ b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
@@ -1,7 +1,19 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import {
+  Alert,
+  AlertDescription,
+  AlertTitle,
+} from "@/components/ui/alert";
 import { Button } from "@/components/ui/button";
+import { Checkbox } from "@/components/ui/checkbox";
+import {
+  clearRememberedLoadSettings,
+  loadRememberedLoadSettings,
+  rememberedLoadSettingsKey,
+  saveRememberedLoadSettings,
+} from "@/components/assistant-ui/model-selector/remembered-load-settings";
 import {
   Dialog,
   DialogContent,
@@ -17,7 +29,7 @@ import {
   DropdownMenuSeparator,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
-import { InfoHint } from "@/components/ui/info-hint";
+import { Input } from "@/components/ui/input";
 import {
   InputGroup,
   InputGroupAddon,
@@ -38,22 +50,26 @@ import {
   SheetTitle,
 } from "@/components/ui/sheet";
 import { Slider } from "@/components/ui/slider";
+import { Spinner } from "@/components/ui/spinner";
 import { Switch } from "@/components/ui/switch";
 import { Textarea } from "@/components/ui/textarea";
+import { InfoHint } from "@/components/ui/info-hint";
 import { Tooltip, TooltipContent } from "@/components/ui/tooltip";
-import { NumericValueInput, snapToStep } from "@/features/model-picker";
-import { RetrievalSettingsSection } from "@/features/rag";
-import { useLlamaUpdateCheck } from "@/hooks/use-llama-update-check";
 import { useIsMobile } from "@/hooks/use-mobile";
-import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
-import { toast } from "@/lib/toast";
+import { useLlamaUpdateCheck } from "@/hooks/use-llama-update-check";
 import { cn } from "@/lib/utils";
-import { Edit03Icon, LayoutAlignRightIcon } from "@hugeicons/core-free-icons";
+import {
+  ArrowTurnBackwardIcon,
+  Edit03Icon,
+  LayoutAlignRightIcon,
+} from "@hugeicons/core-free-icons";
+import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { Braces, ChevronDown, ExternalLink } from "lucide-react";
 import { Tooltip as TooltipPrimitive } from "radix-ui";
 import { Fragment, type ReactNode } from "react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { toast } from "@/lib/toast";
 import { OpenAICodeExecSection } from "./components/openai-code-exec-section";
 import { PermissionModeDropdown } from "./permission-mode-select";
 import { resyncInferenceStatusAfterServerModelChange } from "./hooks/use-chat-model-runtime";
@@ -61,8 +77,8 @@ import {
   type ExternalProviderConfig,
   getExternalProviderApiKey,
   parseExternalModelId,
-  supportsProviderPromptCacheTtl,
   supportsProviderPromptCaching,
+  supportsProviderPromptCacheTtl,
 } from "./external-providers";
 import {
   BUILTIN_PRESETS,
@@ -82,7 +98,12 @@ import {
   providerSupportsBuiltinCodeExecution,
   providerSupportsFastMode,
 } from "./provider-capabilities";
-import { useChatRuntimeStore } from "./stores/chat-runtime-store";
+import {
+  isPendingGguf,
+  pendingSelectionMatches,
+  useChatRuntimeStore,
+} from "./stores/chat-runtime-store";
+import { RetrievalSettingsSection } from "@/features/rag/components/retrieval-settings-section";
 import type { InferenceParams } from "./types/runtime";
 
 export { defaultInferenceParams, type Preset } from "./presets/preset-policy";
@@ -105,7 +126,7 @@ function getPromptVariablesError(raw: string): string | null {
       return null;
     }
   } catch {
-    return 'Use valid JSON, for example { "env": "staging" }.';
+    return "Use valid JSON, for example { \"env\": \"staging\" }.";
   }
   return "Variables must be a JSON object.";
 }
@@ -114,6 +135,111 @@ function hasPromptVariableSyntax(prompt: string): boolean {
   return PROMPT_VARIABLE_PATTERN.test(prompt);
 }
 
+/**
+ * Editable numeric value display, shared by every slider value and the Context
+ * Length input. An <input> that looks like text (shows `displayValue ?? value`,
+ * so "Off"/"Max" labels render) until focus, when it swaps to the raw number,
+ * selects it, and accepts free text. Commits on blur/Enter, reverts on Escape.
+ * Clamping happens on commit so typing intermediate values isn't fought.
+ */
+function snapToStep(
+  value: number,
+  step: number,
+  min?: number,
+  max?: number,
+): number {
+  const lo = min ?? Number.NEGATIVE_INFINITY;
+  const hi = max ?? Number.POSITIVE_INFINITY;
+  const clamped = Math.min(Math.max(value, lo), hi);
+  const stepStr = String(step);
+  const decimals = stepStr.includes(".") ? stepStr.split(".")[1].length : 0;
+  const base = Number.isFinite(lo) ? lo : 0;
+  const snapped = base + Math.round((clamped - base) / step) * step;
+  const reclamped = Math.min(Math.max(snapped, lo), hi);
+  return Number(reclamped.toFixed(decimals));
+}
+
+function NumericValueInput({
+  value,
+  min,
+  max,
+  step,
+  onChange,
+  displayValue,
+  className,
+  ariaLabel,
+  size: sizeAttr,
+  disabled = false,
+}: {
+  value: number;
+  min?: number;
+  max?: number;
+  step: number;
+  onChange: (v: number) => void;
+  displayValue?: string;
+  className?: string;
+  ariaLabel?: string;
+  size?: number;
+  disabled?: boolean;
+}) {
+  const [focused, setFocused] = useState(false);
+  const [draft, setDraft] = useState("");
+  const cancelBlurCommitRef = useRef(false);
+
+  const commit = (raw: string) => {
+    const parsed = Number.parseFloat(raw);
+    if (!Number.isFinite(parsed)) {
+      return;
+    }
+    const final = snapToStep(parsed, step, min, max);
+    if (final !== value) {
+      onChange(final);
+    }
+  };
+
+  const displayed = focused ? draft : (displayValue ?? String(value));
+
+  return (
+    <input
+      type="text"
+      inputMode="decimal"
+      disabled={disabled}
+      size={sizeAttr}
+      /* Fixed 4ch pill; grows only when a longer value would clip. */
+      style={{ width: `calc(${Math.max(displayed.length, 4)}ch + 18px)` }}
+      value={displayed}
+      aria-label={ariaLabel}
+      onFocus={(e) => {
+        cancelBlurCommitRef.current = false;
+        setDraft(String(value));
+        setFocused(true);
+        // Defer select() so it runs after the value swap above.
+        const target = e.currentTarget;
+        requestAnimationFrame(() => target.select());
+      }}
+      onBlur={() => {
+        if (cancelBlurCommitRef.current) {
+          cancelBlurCommitRef.current = false;
+        } else {
+          commit(draft);
+        }
+        setFocused(false);
+      }}
+      onChange={(e) => setDraft(e.target.value)}
+      onKeyDown={(e) => {
+        if (e.key === "Enter") {
+          e.currentTarget.blur();
+        } else if (e.key === "Escape") {
+          cancelBlurCommitRef.current = true;
+          setDraft(String(value));
+          e.currentTarget.blur();
+        }
+      }}
+      className={cn("panel-number-input", className)}
+    />
+  );
+}
+
 function ParamSlider({
   label,
   value,
@@ -153,7 +279,6 @@ function ParamSlider({
           displayValue={displayValue}
           ariaLabel={label}
           size={valueSize ?? 4}
-          className="panel-number-input"
         />
       </div>
       <Slider
@@ -252,7 +377,8 @@ function CollapsibleSection({
   return (
     <div
       className={cn(
-        !first && "border-t border-black/[0.13] dark:border-white/[0.09]",
+        !first &&
+          "border-t border-black/[0.13] dark:border-white/[0.09]",
       )}
     >
       {labelHref ? (
@@ -324,7 +450,6 @@ interface ChatSettingsPanelProps {
   onOpenChange?: (open: boolean) => void;
   params: InferenceParams;
   onParamsChange: (params: InferenceParams) => void;
-  modelConfig?: ReactNode;
   isExternalModel?: boolean;
   /**
    * Sampling-param capabilities for the active external provider, or `null` for
@@ -339,6 +464,21 @@ interface ChatSettingsPanelProps {
    * Max Tokens floor in the slider.
    */
   externalProviderType?: string | null;
+  onReloadModel?: () => void;
+  /** The in-flight load (id + GGUF variant + native path token), or null when
+   *  idle. Used to show a loading state for the staged pick only — not for an
+   *  unrelated load or a cancel's background unload. */
+  loadingModel?: {
+    id: string;
+    ggufVariant?: string | null;
+    nativePathToken?: string | null;
+  } | null;
+  /** Loads the staged `pendingSelection` (deferred "Load on selection" flow). */
+  onLoadPendingModel?: () => void;
+  /** Download progress (0–1) for a staged GGUF being fetched, or null when idle. */
+  stagedDownloadFraction?: number | null;
+  /** Cancels the in-flight staged download (paired with abandoning the stage). */
+  onCancelStagedDownload?: () => void;
 }
 
 export function ChatSettingsPanel({
@@ -346,12 +486,16 @@ export function ChatSettingsPanel({
   onOpenChange,
   params,
   onParamsChange,
-  modelConfig = null,
   isExternalModel = false,
   providerCapabilities = null,
   activeExternalProvider = null,
   onExternalProviderChange,
   externalProviderType = null,
+  onReloadModel,
+  loadingModel = null,
+  onLoadPendingModel,
+  stagedDownloadFraction,
+  onCancelStagedDownload,
 }: ChatSettingsPanelProps) {
   // Local models show every knob; providerCapabilities is only consulted when
   // isExternalModel. Unknown providers fall back to the OpenAI-compat shape via
@@ -366,23 +510,55 @@ export function ChatSettingsPanel({
   const showPresencePenalty =
     !isExternalModel || Boolean(providerCapabilities?.presencePenalty);
   const isMobile = useIsMobile();
-  const isLoadedGguf = useChatRuntimeStore((s) => s.activeGgufVariant) != null;
-  const currentCheckpoint = params.checkpoint;
-  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
-  // Direct-file / custom-folder GGUFs load without a variant label but still
-  // report a GGUF context, so detect them via the context and the checkpoint
-  // suffix too (mirrors the chat page's activeModelIsGguf). Otherwise Max Tokens
-  // would fall back to params.maxSeqLength instead of the loaded GGUF context.
-  const isGguf =
-    isLoadedGguf ||
-    ggufContextLength != null ||
-    (currentCheckpoint?.toLowerCase().endsWith(".gguf") ?? false);
-  const ggufMaxContextLength = useChatRuntimeStore(
-    (s) => s.ggufMaxContextLength,
+  const pendingSelection = useChatRuntimeStore((s) => s.pendingSelection);
+  // "Loading" only when the in-flight load IS this staged pick (full id + GGUF
+  // variant + native token match), not an unrelated load or a cancel's
+  // background unload. The variant matters: a different quant of the same repo
+  // staged mid-load must not read as this one loading.
+  const stagedLoading =
+    loadingModel != null &&
+    pendingSelectionMatches(pendingSelection, {
+      id: loadingModel.id,
+      ggufVariant: loadingModel.ggufVariant,
+      nativePathToken: loadingModel.nativePathToken,
+    });
+  // Load settings are snapshotted at click time; lock them while loading.
+  const modelControlsDisabled = stagedLoading;
+  const abandonStagedModel = useChatRuntimeStore((s) => s.abandonStagedModel);
+  const resetModelSettingsToLoaded = useChatRuntimeStore(
+    (s) => s.resetModelSettingsToLoaded,
   );
-  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
+  // A staged GGUF pick (deferred load) shows the GGUF load knobs so they can be
+  // set before the single load.
+  const pendingIsGguf = isPendingGguf(pendingSelection);
+  // Short, human-readable name for the staged pick (HF ids carry an org prefix;
+  // native picks are already a display label). Drives the "staged, not loaded"
+  // callout so it's obvious the selection hasn't loaded yet.
+  const stagedLabel = (() => {
+    const id = pendingSelection?.id ?? "";
+    const slash = id.lastIndexOf("/");
+    const base = slash >= 0 ? id.slice(slash + 1) : id;
+    return base || id;
+  })();
+  const isLoadedGguf =
+    useChatRuntimeStore((s) => s.activeGgufVariant) != null;
+  // While a pick is staged the sheet configures *that* model, so its GGUF-ness
+  // (not the currently loaded model's) decides whether the GGUF-only controls
+  // show. Otherwise a staged non-GGUF Hub repo would inherit the loaded GGUF's
+  // context/KV/speculative controls.
+  const isGguf = pendingSelection != null ? pendingIsGguf : isLoadedGguf;
+  // The Model section (and Load button) shows for any staged pick, even when the
+  // currently active model is external.
+  const hasModelContent =
+    pendingSelection != null ||
+    (!isExternalModel && (isGguf || Boolean(params.checkpoint)));
   const speculativeType = useChatRuntimeStore((s) => s.speculativeType);
+  const setSpeculativeType = useChatRuntimeStore((s) => s.setSpeculativeType);
+  const loadedSpeculativeType = useChatRuntimeStore(
+    (s) => s.loadedSpeculativeType,
+  );
   const specFallbackReason = useChatRuntimeStore((s) => s.specFallbackReason);
+  // Only binary fallback states are solved by a newer prebuilt.
   const mtpUpdatable =
     specFallbackReason === "binary_no_mtp" ||
     specFallbackReason === "binary_outdated";
@@ -404,27 +580,43 @@ export function ChatSettingsPanel({
         `llama.cpp updated to ${result.tag ?? "the latest build"}.${reloadHint}`,
       );
     } else {
-      toast.error(
-        `llama.cpp update failed: ${result.error ?? "unknown error"}`,
-      );
+      toast.error(`llama.cpp update failed: ${result.error ?? "unknown error"}`);
     }
   }, [applyLlamaUpdate]);
-  const loadedEffectiveContext = customContextLength ?? ggufContextLength;
-  const showSpecFallback =
-    !isExternalModel &&
-    isLoadedGguf &&
-    specFallbackReason != null &&
-    (speculativeType === "auto" ||
-      speculativeType === "mtp" ||
-      speculativeType === "mtp+ngram");
-  const showContextVramWarning =
-    !isExternalModel &&
-    isLoadedGguf &&
-    ggufMaxContextLength != null &&
-    loadedEffectiveContext != null &&
-    loadedEffectiveContext > ggufMaxContextLength;
-  const showLoadedDiagnostics = showSpecFallback || showContextVramWarning;
-  const hasModelContent = showLoadedDiagnostics;
+  const specDraftNMax = useChatRuntimeStore((s) => s.specDraftNMax);
+  const setSpecDraftNMax = useChatRuntimeStore((s) => s.setSpecDraftNMax);
+  const loadedSpecDraftNMax = useChatRuntimeStore(
+    (s) => s.loadedSpecDraftNMax,
+  );
+  const currentCheckpoint = params.checkpoint;
+  const ggufContextLength = useChatRuntimeStore((s) => s.ggufContextLength);
+  const ggufMaxContextLength = useChatRuntimeStore(
+    (s) => s.ggufMaxContextLength,
+  );
+  const ggufNativeContextLength = useChatRuntimeStore(
+    (s) => s.ggufNativeContextLength,
+  );
+  const kvCacheDtype = useChatRuntimeStore((s) => s.kvCacheDtype);
+  const setKvCacheDtype = useChatRuntimeStore((s) => s.setKvCacheDtype);
+  const applyRememberedLoadSettings = useChatRuntimeStore(
+    (s) => s.applyRememberedLoadSettings,
+  );
+  const loadedKvCacheDtype = useChatRuntimeStore((s) => s.loadedKvCacheDtype);
+  const tensorParallel = useChatRuntimeStore((s) => s.tensorParallel);
+  const setTensorParallel = useChatRuntimeStore((s) => s.setTensorParallel);
+  const loadedTensorParallel = useChatRuntimeStore(
+    (s) => s.loadedTensorParallel,
+  );
+  const chatTemplateOverride = useChatRuntimeStore(
+    (s) => s.chatTemplateOverride,
+  );
+  const loadedChatTemplateOverride = useChatRuntimeStore(
+    (s) => s.loadedChatTemplateOverride,
+  );
+  const customContextLength = useChatRuntimeStore((s) => s.customContextLength);
+  const setCustomContextLength = useChatRuntimeStore(
+    (s) => s.setCustomContextLength,
+  );
   const setActivePresetSource = useChatRuntimeStore(
     (s) => s.setActivePresetSource,
   );
@@ -435,7 +627,49 @@ export function ChatSettingsPanel({
   const setActivePreset = useChatRuntimeStore((s) => s.setActivePreset);
   const settingsHydrated = useChatRuntimeStore((s) => s.settingsHydrated);
 
-  const baseContext = ggufContextLength;
+  // A staged (not-yet-loaded) GGUF carries its own header context length on
+  // pendingSelection, so the slider can use the staged model's real ceiling
+  // without reading the loaded model's `ggufContextLength`.
+  const stagedContextLength = pendingSelection?.contextLength ?? null;
+  // "Remember settings next time" tick for a staged model. Seeds the store from
+  // the saved per-model settings on stage, so the sheet opens with what was used
+  // last time; the tick reflects whether a saved entry exists.
+  const [remember, setRemember] = useState(false);
+  // Keyed per quant: a different variant of the same repo has its own settings.
+  const pendingKey = pendingSelection
+    ? rememberedLoadSettingsKey(pendingSelection)
+    : null;
+  useEffect(() => {
+    if (!pendingKey) return;
+    const saved = loadRememberedLoadSettings(pendingKey);
+    setRemember(saved != null);
+    if (saved) applyRememberedLoadSettings(saved);
+  }, [pendingKey, applyRememberedLoadSettings]);
+  // While staging, the sheet reflects the STAGED model, so its header context
+  // takes precedence over the loaded model's (which may differ or be larger).
+  const baseContext = pendingIsGguf ? stagedContextLength : ggufContextLength;
+  const baseNativeContext = pendingIsGguf
+    ? stagedContextLength
+    : ggufNativeContextLength;
+  // Context controls render once we actually have a ceiling: for a staged GGUF,
+  // once its header metadata arrives (post-download); otherwise post-load.
+  const showContextControl = pendingIsGguf
+    ? stagedContextLength != null
+    : isLoadedGguf;
+  const stagedDownloading =
+    stagedDownloadFraction != null && stagedDownloadFraction < 1;
+  const ctxDisplayValue = customContextLength ?? baseContext ?? "";
+  const ctxMaxValue = baseNativeContext ?? baseContext ?? null;
+  const kvDirty = kvCacheDtype !== loadedKvCacheDtype;
+  const ctxDirty = customContextLength !== null;
+  const specDirty = speculativeType !== loadedSpeculativeType;
+  const specDraftDirty = specDraftNMax !== loadedSpecDraftNMax;
+  const tpDirty = tensorParallel !== (loadedTensorParallel ?? false);
+  // A saved chat-template override is a reload-time setting too, so surface
+  // Apply for a template-only edit (otherwise it could never be applied).
+  const templateDirty = chatTemplateOverride !== loadedChatTemplateOverride;
+  const modelSettingsDirty =
+    kvDirty || ctxDirty || specDirty || specDraftDirty || tpDirty || templateDirty;
   const [presetNameInput, setPresetNameInput] = useState(activePreset);
   const [systemPromptEditorOpen, setSystemPromptEditorOpen] = useState(false);
   const [systemPromptDraft, setSystemPromptDraft] = useState("");
@@ -461,7 +695,8 @@ export function ChatSettingsPanel({
       BUILTIN_PRESETS.find((preset) => preset.name === activePreset) ?? null,
     [activePreset],
   );
-  const hasUnsavedPresetChanges = useMemo(() => {
+  const hasUnsavedPresetChanges = useMemo(
+    () => {
       if (activePresetDefinition == null) {
         return false;
       }
@@ -469,7 +704,9 @@ export function ChatSettingsPanel({
         return activePresetSource === "modified";
       }
       return !isSamePresetConfig(activePresetDefinition.params, params);
-  }, [activePresetDefinition, activePresetSource, params]);
+    },
+    [activePresetDefinition, activePresetSource, params],
+  );
   const presetSaveState = useMemo(
     () =>
       getPresetSaveState({
@@ -498,14 +735,6 @@ export function ChatSettingsPanel({
   const externalSelection = currentCheckpoint
     ? parseExternalModelId(currentCheckpoint)
     : null;
-  const maxTokensMax = isExternalModel
-      ? getExternalMaxOutputTokens(
-          externalProviderType,
-          externalSelection?.modelId,
-        )
-      : isGguf && baseContext
-        ? baseContext
-        : Math.max(64, params.maxSeqLength);
   const showOpenAICodeExecSection =
     activeExternalProvider != null &&
     providerSupportsBuiltinCodeExecution(
@@ -588,7 +817,8 @@ export function ChatSettingsPanel({
       return;
     }
     const fallbackPreset =
-      BUILTIN_PRESETS.find((preset) => preset.name === "Default") ?? null;
+      BUILTIN_PRESETS.find((preset) => preset.name === "Default") ??
+      null;
     const next = customPresets.filter((preset) => preset.name !== name);
     setCustomPresets(next);
     if (activePreset === name) {
@@ -700,7 +930,7 @@ export function ChatSettingsPanel({
               Run settings
             </span>
             <Tooltip>
-                <TooltipPrimitive.Trigger asChild={true}>
+              <TooltipPrimitive.Trigger asChild>
                 <button
                   type="button"
                   onClick={() => onOpenChange?.(false)}
@@ -731,57 +961,377 @@ export function ChatSettingsPanel({
         className="run-settings-scroll relative min-h-0 flex-1 overflow-y-auto"
       >
       <div className="px-[18px] pt-3">
-        {(hasModelContent || modelConfig) && (
-              <CollapsibleSection label="Model" defaultOpen={true} first={true}>
-            <div className="flex flex-col gap-3 pt-1">
-              {modelConfig}
-              {showSpecFallback && (
-                <div className="rounded-lg bg-amber-500/[0.08] px-3 py-2 text-[12px] leading-[1.4] text-nav-fg/80">
-                  <p>
-                    {specFallbackReason === "mla_mtp_disabled"
-                      ? "MTP is disabled by default for this model architecture because it currently runs slower than standard decoding. Choose MTP in the model picker to force it."
-                      : specFallbackReason === "runtime_error"
-                        ? "MTP could not start for this model on the installed llama.cpp build, so it is running without speculative decoding."
-                        : specFallbackReason === "drafter_not_found"
-                          ? "This model supports MTP, but its drafter file could not be downloaded, so MTP is off and it falls back to n-gram speculative decoding where the llama.cpp build supports it. Check your network connection or Hugging Face access, then reload the model to retry the drafter."
-                          : `MTP is not available in the installed llama.cpp build, so this model is running without it.${
-                              llamaUpdateStatus?.update_available
-                                ? " Update llama.cpp to enable it."
-                                : ""
-                            }`}
-                  </p>
-                  {mtpUpdatable && llamaUpdateStatus?.update_available && (
-                    <Button
-                      size="sm"
-                      className="corner-squircle mt-2 h-7 text-[12px]"
-                      onClick={handleMtpUpdate}
-                      disabled={llamaUpdating}
-                      data-test-id="mtp-update-button"
-                    >
-                      {llamaUpdating ? "Updating..." : "Update llama.cpp"}
-                    </Button>
-                  )}
+        {hasModelContent && (
+        <CollapsibleSection label="Model" defaultOpen={true} first>
+          <div className="flex flex-col gap-4 pt-1">
+            {pendingSelection && (
+              <Alert className="rounded-[14px] border-primary/30 bg-primary/5 px-3 py-2">
+                <AlertTitle className="text-[12px] font-medium">
+                  {stagedLoading
+                    ? `Loading ${stagedLabel}…`
+                    : `${stagedLabel} is staged, not loaded yet`}
+                </AlertTitle>
+                <AlertDescription className="text-[11.5px] leading-[1.45] text-muted-foreground">
+                  {stagedLoading
+                    ? "Applying your settings."
+                    : "Set the options below, then choose Load model to load it."}
+                </AlertDescription>
+              </Alert>
+            )}
+            {isGguf && (
+              <>
+                {showContextControl && (
+                <div className="space-y-3.5">
+                  <div className="flex items-center justify-between gap-3">
+                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                      Context Length
+                    </span>
+                    <NumericValueInput
+                      value={
+                        typeof ctxDisplayValue === "number"
+                          ? ctxDisplayValue
+                          : (baseContext ?? 0)
+                      }
+                      min={128}
+                      max={ctxMaxValue ?? undefined}
+                      step={1}
+                      onChange={(v) => {
+                        setCustomContextLength(
+                          v === (baseContext ?? 0) ? null : v,
+                        );
+                      }}
+                      ariaLabel="Context Length"
+                      size={8}
+                      disabled={modelControlsDisabled}
+                    />
+                  </div>
+                  <Slider
+                    min={1024}
+                    max={ctxMaxValue ?? 4096}
+                    step={1024}
+                    value={[
+                      Math.min(
+                        typeof ctxDisplayValue === "number"
+                          ? ctxDisplayValue
+                          : (baseContext ?? 4096),
+                        ctxMaxValue ?? 4096,
+                      ),
+                    ]}
+                    onValueChange={([v]) => {
+                      const snapped = Math.round(v);
+                      setCustomContextLength(
+                        snapped === (baseContext ?? 0) ? null : snapped,
+                      );
+                    }}
+                    className="panel-slider"
+                    disabled={modelControlsDisabled}
+                  />
+                  {ggufMaxContextLength != null &&
+                    typeof ctxDisplayValue === "number" &&
+                    ctxDisplayValue > ggufMaxContextLength && (
+                      <p className="text-[11px] text-amber-500">
+                        Exceeds estimated VRAM capacity (
+                        {ggufMaxContextLength.toLocaleString()} tokens). The
+                        model may use system RAM.
+                      </p>
+                    )}
                 </div>
-              )}
-              {showContextVramWarning && (
-                <p className="text-[11px] text-amber-500">
-                  Context length exceeds the estimated VRAM capacity (
-                      {ggufMaxContextLength?.toLocaleString()} tokens). The
-                      model may use system RAM.
-                </p>
-              )}
-            </div>
-          </CollapsibleSection>
+                )}
+                <div className="flex items-center justify-between gap-3">
+                  <div className="flex min-w-0 items-center gap-1.5">
+                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                      KV Cache Dtype
+                    </span>
+                    <InfoHint>
+                      Lower KV cache precision to save VRAM at the cost of some
+                      quality. f16/bf16 are full precision; q8_0/q5_1/q4_1 are
+                      quantized.
+                    </InfoHint>
+                  </div>
+                  <div className="flex shrink-0 items-center gap-1.5">
+                    <Select
+                      disabled={modelControlsDisabled}
+                      value={kvCacheDtype ?? "f16"}
+                      onValueChange={(v) => {
+                        setKvCacheDtype(v === "f16" ? null : v);
+                      }}
+                    >
+                      <SelectTrigger
+                        animateRadius={false}
+                        icon={ChevronDownStandardIcon}
+                        iconClassName="size-3.5"
+                        className="grid h-7 w-[64px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
+                      >
+                        <SelectValue />
+                      </SelectTrigger>
+                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+                        <SelectItem value="f16">f16</SelectItem>
+                        <SelectItem value="bf16">bf16</SelectItem>
+                        <SelectItem value="q8_0">q8_0</SelectItem>
+                        <SelectItem value="q5_1">q5_1</SelectItem>
+                        <SelectItem value="q4_1">q4_1</SelectItem>
+                      </SelectContent>
+                    </Select>
+                  </div>
+                </div>
+                {isGguf && (
+                  <>
+                <div className="flex items-center justify-between gap-3">
+                  <div className="flex min-w-0 items-center gap-1.5">
+                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                      Speculative Decoding
+                    </span>
+                    <InfoHint>
+                      Faster generation with 0% accuracy hit. Auto picks
+                      MTP / ngram-mod based on the model and platform.
+                      Pick MTP, Ngram, or MTP+Ngram to force a specific
+                      strategy on both GPU and CPU.
+                    </InfoHint>
+                  </div>
+                  <div className="flex shrink-0 items-center gap-1.5">
+                    <Select
+                      disabled={modelControlsDisabled}
+                      value={speculativeType ?? "auto"}
+                      onValueChange={(v) => {
+                        setSpeculativeType(v);
+                        if (v !== "mtp" && v !== "mtp+ngram") {
+                          setSpecDraftNMax(null);
+                        }
+                      }}
+                    >
+                      <SelectTrigger
+                        animateRadius={false}
+                        icon={ChevronDownStandardIcon}
+                        iconClassName="size-3.5"
+                        className="grid h-7 w-[124px] min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0"
+                        data-test-id="speculative-type-select"
+                      >
+                        <SelectValue />
+                      </SelectTrigger>
+                      <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
+                        <SelectItem value="auto">Auto</SelectItem>
+                        <SelectItem value="mtp">MTP</SelectItem>
+                        <SelectItem value="ngram">Ngram</SelectItem>
+                        <SelectItem value="mtp+ngram">MTP+Ngram</SelectItem>
+                        <SelectItem value="off">Off</SelectItem>
+                      </SelectContent>
+                    </Select>
+                  </div>
+                </div>
+                {specFallbackReason &&
+                  (speculativeType === "auto" ||
+                    speculativeType === "mtp" ||
+                    speculativeType === "mtp+ngram") && (
+                    <div className="rounded-lg bg-amber-500/[0.08] px-3 py-2 text-[12px] leading-[1.4] text-nav-fg/80">
+                      <p>
+                        {specFallbackReason === "mla_mtp_disabled"
+                          ? "MTP is disabled by default for this model architecture because it currently runs slower than standard decoding. Select MTP above to force it."
+                          : specFallbackReason === "runtime_error"
+                          ? "MTP could not start for this model on the installed llama.cpp build, so it is running without speculative decoding."
+                          : specFallbackReason === "drafter_not_found"
+                            ? "This model supports MTP, but its drafter file could not be downloaded, so MTP is off and it falls back to n-gram speculative decoding where the llama.cpp build supports it. Check your network connection or Hugging Face access, then reload the model to retry the drafter."
+                            : "MTP is not available in the installed llama.cpp build, so this model is running without it." +
+                              (llamaUpdateStatus?.update_available
+                                ? " Update llama.cpp to enable it."
+                                : "")}
+                      </p>
+                      {mtpUpdatable && llamaUpdateStatus?.update_available && (
+                        <Button
+                          size="sm"
+                          className="corner-squircle mt-2 h-7 text-[12px]"
+                          onClick={handleMtpUpdate}
+                          disabled={llamaUpdating}
+                          data-test-id="mtp-update-button"
+                        >
+                          {llamaUpdating ? "Updating..." : "Update llama.cpp"}
+                        </Button>
+                      )}
+                    </div>
+                  )}
+                {(speculativeType === "mtp" ||
+                  speculativeType === "mtp+ngram") && (
+                  <div className="flex items-center justify-between gap-3">
+                    <div className="flex min-w-0 items-center gap-1.5">
+                      <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                        Draft Tokens
+                      </span>
+                      <InfoHint>
+                        Max MTP draft tokens per step
+                        (--spec-draft-n-max). Lower = less wasted
+                        draft decode; higher = bigger speedup when
+                        acceptance stays high. Default: 2 on GPU,
+                        3 on CPU/Mac.
+                      </InfoHint>
+                    </div>
+                    <Input
+                      type="number"
+                      disabled={modelControlsDisabled}
+                      min={1}
+                      max={16}
+                      step={1}
+                      value={specDraftNMax ?? ""}
+                      placeholder="auto"
+                      onChange={(e) => {
+                        const raw = e.target.value;
+                        if (raw === "") {
+                          setSpecDraftNMax(null);
+                          return;
+                        }
+                        const parsed = Number.parseInt(raw, 10);
+                        if (Number.isFinite(parsed)) {
+                          const clamped = Math.max(1, Math.min(16, parsed));
+                          setSpecDraftNMax(clamped);
+                        }
+                      }}
+                      data-test-id="spec-draft-n-max-input"
+                      aria-label="Speculative decoding draft tokens"
+                      className="h-7 w-[88px] rounded-full border-border bg-background hover:bg-accent/50 dark:border-transparent dark:bg-white/[0.05] dark:hover:bg-white/[0.1] pl-3 py-0 text-[13px] font-medium text-nav-fg outline-none focus-visible:ring-0"
+                    />
+                  </div>
+                )}
+                  </>
+                )}
+                <div className="flex items-center justify-between gap-3">
+                  <div className="flex min-w-0 items-center gap-1.5">
+                    <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg">
+                      Tensor Parallelism
+                    </span>
+                    <InfoHint>
+                      No effect on a single GPU. On multi-GPU setups, improves
+                      tokens/sec during generation when using dense models. MoE
+                      models don't benefit and can be much slower.
+                    </InfoHint>
+                  </div>
+                  <Switch
+                    className="panel-switch shrink-0"
+                    checked={tensorParallel}
+                    onCheckedChange={setTensorParallel}
+                    disabled={modelControlsDisabled}
+                    data-test-id="tensor-parallel-switch"
+                  />
+                </div>
+              </>
+            )}
+            {/* No persistent "enable custom code" toggle: it is consented per model
+                via the load-time review dialog. */}
+            {/* Apply/Reset belongs to the model-reload settings above (context
+                length, KV cache, speculative decoding). Render it here, before
+                the Chat Template row, so it never reads as attached to Chat
+                Template (which is edited via its own dialog). When a model is
+                staged (deferred load), Load/Cancel takes its place: there's
+                nothing loaded to "apply" against yet. */}
+            {pendingSelection ? (
+              <div className="flex flex-col gap-4">
+                {stagedDownloading && (
+                  <p className="text-[11px] text-muted-foreground">
+                    Downloading…{" "}
+                    {Math.round((stagedDownloadFraction ?? 0) * 100)}%
+                  </p>
+                )}
+                <label className="flex cursor-pointer items-center gap-2 pb-1.5 text-[12px] text-muted-foreground">
+                  <Checkbox
+                    className="size-3.5 rounded-full [&_[data-slot=checkbox-indicator]_svg]:size-2.5"
+                    checked={remember}
+                    onCheckedChange={(v) => setRemember(v === true)}
+                  />
+                  Remember settings next time
+                </label>
+                {stagedLoading ? (
+                  // Mid-load: nothing to load or abandon until it settles, so disable.
+                  <Button
+                    type="button"
+                    disabled
+                    size="sm"
+                    className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav bg-primary text-primary-foreground hover:bg-primary/90"
+                  >
+                    <Spinner className="size-3.5" />
+                    Loading…
+                  </Button>
+                ) : (
+                  <div className="grid grid-cols-2 gap-3">
+                    <Button
+                      type="button"
+                      onClick={() => {
+                        // Persist (or clear) this model's load knobs before loading.
+                        // Context is stored as the override (null = auto), never the
+                        // resolved native value, so restoring can't force an OOM.
+                        const pid = pendingSelection
+                          ? rememberedLoadSettingsKey(pendingSelection)
+                          : null;
+                        if (pid) {
+                          if (remember) {
+                            saveRememberedLoadSettings(pid, {
+                              contextLength: customContextLength,
+                              kvCacheDtype,
+                              speculativeType,
+                              specDraftNMax,
+                              tensorParallel,
+                            });
+                          } else {
+                            clearRememberedLoadSettings(pid);
+                          }
+                        }
+                        onLoadPendingModel?.();
+                      }}
+                      // Disabled while a different model is mid-load: selectModel
+                      // refuses a concurrent load, so the click could only toast.
+                      disabled={stagedDownloading || loadingModel != null}
+                      size="sm"
+                      className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav bg-primary text-primary-foreground hover:bg-primary/90"
+                    >
+                      {loadingModel != null ? "Another model loading…" : "Load model"}
+                    </Button>
+                    <Button
+                      type="button"
+                      variant="outline"
+                      size="sm"
+                      onClick={() => {
+                        // Cancel abandons the stage; if a download is mid-flight,
+                        // stop it too rather than leaving it running headless.
+                        if (stagedDownloading) onCancelStagedDownload?.();
+                        abandonStagedModel();
+                      }}
+                      className="h-9 w-full rounded-full text-[13px] font-medium tracking-nav text-muted-foreground"
+                    >
+                      Cancel
+                    </Button>
+                  </div>
+                )}
+              </div>
+            ) : modelSettingsDirty ? (
+              <div className="flex flex-wrap gap-1.5">
+                <Button
+                  type="button"
+                  onClick={() => onReloadModel?.()}
+                  size="sm"
+                  className="h-7 px-3 text-[12px] font-medium tracking-nav bg-primary/92 text-primary-foreground hover:bg-primary"
+                >
+                  Apply
+                </Button>
+                <Button
+                  type="button"
+                  variant="outline"
+                  size="sm"
+                  onClick={() => resetModelSettingsToLoaded()}
+                  className="h-7 px-3 text-[12px] font-medium tracking-nav text-muted-foreground"
+                >
+                  Reset
+                </Button>
+              </div>
+            ) : null}
+            <ChatTemplateFields />
+          </div>
+        </CollapsibleSection>
         )}
 
         <CollapsibleSection
           label="Preset"
           defaultOpen={true}
-          first={!hasModelContent && !modelConfig}
+          first={!hasModelContent}
         >
           <div className="flex flex-col gap-3 pt-1">
             <DropdownMenu>
-                  <DropdownMenuTrigger asChild={true}>
+              <DropdownMenuTrigger asChild>
                 <div
                   className="w-full min-w-0 cursor-pointer outline-none focus-visible:outline-none"
                   aria-label="Open preset list"
@@ -865,9 +1415,7 @@ export function ChatSettingsPanel({
                 type="button"
                 onClick={() => savePresetWithName(presetNameInput)}
                 disabled={!(settingsHydrated && presetSaveState.canSubmit)}
-                    variant={
-                      presetSaveState.isSaveReady ? "default" : "outline"
-                    }
+                variant={presetSaveState.isSaveReady ? "default" : "outline"}
                 size="sm"
                 className={cn(
                   "h-9 w-full rounded-full text-[13px] font-medium tracking-nav",
@@ -908,8 +1456,7 @@ export function ChatSettingsPanel({
                   Prompt caching
                 </span>
                 <InfoHint>
-                      Reuse compatible prompt prefixes for lower latency and
-                      cost.
+                  Reuse compatible prompt prefixes for lower latency and cost.
                 </InfoHint>
               </div>
               <Switch
@@ -932,10 +1479,10 @@ export function ChatSettingsPanel({
                   </span>
                   <InfoHint>
                     Anthropic exposes a 5 minute and a 1 hour ephemeral
-                        cache pool. The 1 hour pool costs 2x base input on write
-                        vs 1.25x for 5 minute, but reads stay 0.1x for both, so
-                        a single read landing more than 5 minutes after the
-                        write pays off the premium.
+                    cache pool. The 1 hour pool costs 2x base input on
+                    write vs 1.25x for 5 minute, but reads stay 0.1x for
+                    both, so a single read landing more than 5 minutes
+                    after the write pays off the premium.
                   </InfoHint>
                 </div>
                 <Select
@@ -1003,7 +1550,7 @@ export function ChatSettingsPanel({
           onLabelClick={openSystemPromptEditor}
           headerAction={
             <Tooltip>
-                  <TooltipPrimitive.Trigger asChild={true}>
+              <TooltipPrimitive.Trigger asChild>
                 <button
                   type="button"
                   onClick={openSystemPromptEditor}
@@ -1059,6 +1606,7 @@ export function ChatSettingsPanel({
           </div>
         </CollapsibleSection>
 
+
         <CollapsibleSection label="Sampling" defaultOpen={true}>
           <div className="flex flex-col gap-5 pt-1">
             {showTemperature ? (
@@ -1129,12 +1677,21 @@ export function ChatSettingsPanel({
                 max={2}
                 step={0.1}
                 onChange={set("presencePenalty")}
-                    displayValue={
-                      params.presencePenalty === 0 ? "Off" : undefined
-                    }
+                displayValue={params.presencePenalty === 0 ? "Off" : undefined}
                 info="Penalizes any token that has already appeared at least once, encouraging the model to introduce new topics. 0 = off."
               />
             ) : null}
+            {!isExternalModel && !isGguf && (
+              <ParamSlider
+                label="Max Seq Length"
+                value={params.maxSeqLength}
+                min={128}
+                max={32768}
+                step={128}
+                onChange={set("maxSeqLength")}
+                info="Maximum context window size in tokens — input prompt plus generated output combined. Capped by the model's trained limit."
+              />
+            )}
             <ParamSlider
               label="Max Tokens"
               value={params.maxTokens}
@@ -1143,24 +1700,31 @@ export function ChatSettingsPanel({
                   ? getExternalMinOutputTokens(externalProviderType)
                   : 64
               }
-              max={maxTokensMax}
+              max={
+                // A staged GGUF caps to its own context even over an active
+                // external model (the staged model is what will load).
+                !pendingIsGguf && isExternalModel
+                  ? getExternalMaxOutputTokens(
+                      externalProviderType,
+                      externalSelection?.modelId,
+                    )
+                  : isGguf && baseContext
+                    ? baseContext
+                    : 32768
+              }
               step={64}
               onChange={set("maxTokens")}
               displayValue={
                 isGguf && baseContext && params.maxTokens >= baseContext
                   ? "Max"
-                  : !isExternalModel &&
-                      !isGguf &&
-                      params.maxTokens >= maxTokensMax
-                    ? "Max"
-                    : undefined
+                  : undefined
               }
               info="Maximum number of tokens to generate per response. Generation stops at this limit or when the model emits an end-of-sequence token."
             />
           </div>
         </CollapsibleSection>
 
-            {isExternalModel ? null : (
+        {!isExternalModel ? (
           <CollapsibleSection label="Tools">
             <div className="flex flex-col gap-5 pt-1">
               <AutoHealToolCallsToggle />
@@ -1171,13 +1735,13 @@ export function ChatSettingsPanel({
               <ToolCallTimeoutSlider />
             </div>
           </CollapsibleSection>
-            )}
+        ) : null}
 
-            {isExternalModel ? null : (
+        {!isExternalModel ? (
           <CollapsibleSection label="Retrieval">
             <RetrievalSettingsSection />
           </CollapsibleSection>
-            )}
+        ) : null}
       </div>
       </div>
       </div>
@@ -1521,3 +2085,146 @@ function BypassPermissionsToggle() {
     </div>
   );
 }
+
+function ChatTemplateFields() {
+  const defaultTemplate = useChatRuntimeStore((s) => s.defaultChatTemplate);
+  const override = useChatRuntimeStore((s) => s.chatTemplateOverride);
+  const setOverride = useChatRuntimeStore((s) => s.setChatTemplateOverride);
+  const [editorOpen, setEditorOpen] = useState(false);
+  const [draft, setDraft] = useState("");
+
+  if (!defaultTemplate) return null;
+
+  const displayValue = override ?? defaultTemplate;
+  const isModified = override !== null;
+  const draftDirty = draft !== displayValue;
+
+  const openEditor = () => {
+    setDraft(displayValue);
+    setEditorOpen(true);
+  };
+  const saveEditor = () => {
+    const cleared = draft.trim().length === 0 || draft === defaultTemplate;
+    setOverride(cleared ? null : draft);
+    setEditorOpen(false);
+    toast.success(
+      cleared
+        ? "Chat template reset to default. It applies on the next model reload."
+        : "Chat template saved. It applies on the next model reload.",
+    );
+  };
+
+  return (
+    <>
+      <div className="-mb-1.5 flex items-center justify-between gap-2">
+        <button
+          type="button"
+          onClick={openEditor}
+          className="cursor-pointer text-left text-[13px] font-medium tracking-nav text-nav-fg"
+        >
+          Chat Template
+        </button>
+        <div className="flex items-center gap-1">
+          {isModified && (
+            <Tooltip>
+              <TooltipPrimitive.Trigger asChild>
+                <button
+                  type="button"
+                  onClick={() => setOverride(null)}
+                  className="nav-icon-btn text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
+                  aria-label="Revert chat template"
+                >
+                  <HugeiconsIcon
+                    icon={ArrowTurnBackwardIcon}
+                    strokeWidth={1.75}
+                    className="size-4"
+                  />
+                </button>
+              </TooltipPrimitive.Trigger>
+              <TooltipContent
+                side="top"
+                sideOffset={6}
+                className="tooltip-compact"
+              >
+                Revert changes
+              </TooltipContent>
+            </Tooltip>
+          )}
+          <Tooltip>
+            <TooltipPrimitive.Trigger asChild>
+              <button
+                type="button"
+                onClick={openEditor}
+                className="nav-icon-btn text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
+                aria-label="Edit chat template"
+              >
+                <HugeiconsIcon
+                  icon={Edit03Icon}
+                  strokeWidth={1.75}
+                  className="size-3"
+                />
+              </button>
+            </TooltipPrimitive.Trigger>
+            <TooltipContent
+              side="top"
+              sideOffset={6}
+              className="tooltip-compact"
+            >
+              Edit template
+            </TooltipContent>
+          </Tooltip>
+        </div>
+      </div>
+      <Dialog open={editorOpen} onOpenChange={setEditorOpen}>
+        <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-3xl">
+          <DialogHeader>
+            <DialogTitle>Edit Chat Template</DialogTitle>
+            <DialogDescription>
+              Override the model's chat template. The change applies on the
+              next model reload.
+            </DialogDescription>
+          </DialogHeader>
+          <div className="space-y-2">
+            <div className="space-y-0.5 px-0.5">
+              <div className="text-[11px] font-medium">Template editor</div>
+              <p className="text-[11px] text-muted-foreground">
+                Jinja syntax. Save matching the default clears the override.
+              </p>
+            </div>
+            <Textarea
+              value={draft}
+              onChange={(event) => setDraft(event.target.value)}
+              fieldSizing="fixed"
+              className="min-h-[24rem] max-h-[50vh] overflow-y-auto border-0 font-mono text-xs leading-5 corner-squircle focus-visible:ring-0"
+              rows={14}
+              spellCheck={false}
+            />
+          </div>
+          <DialogFooter className="flex-wrap gap-2 sm:justify-between">
+            <Button
+              type="button"
+              variant="ghost"
+              onClick={() => setDraft(defaultTemplate)}
+              disabled={draft === defaultTemplate}
+              className="text-muted-foreground"
+            >
+              Reset
+            </Button>
+            <div className="flex flex-wrap gap-2">
+              <Button
+                type="button"
+                variant="ghost"
+                onClick={() => setEditorOpen(false)}
+              >
+                Cancel
+              </Button>
+              <Button type="button" onClick={saveEditor} disabled={!draftDirty}>
+                Save
+              </Button>
+            </div>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+    </>
+  );
+}
diff --git a/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts b/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
index 1f667de8f9..10e0904e4f 100644
--- a/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
+++ b/studio/frontend/src/features/chat/hooks/use-chat-model-runtime.ts
@@ -30,6 +30,7 @@ import {
 import { formatEta, formatRate } from "../utils/format-transfer";
 import {
   isLocalModelPath,
+  pendingSelectionMatches,
   readPersistedSpeculativeType,
   resolveToolsEnabledOnLoad,
   saveSpeculativeType,
@@ -52,10 +53,7 @@ import {
   isMultimodalResponse,
 } from "../types/api";
 import { isExternalModelId } from "../external-providers";
-import {
-  applyPerModelConfigToRuntime,
-  type PerModelConfig,
-} from "@/features/model-picker";
+import { cancelStagedModelDownload } from "@/features/hub";
 import type {
   ChatLoraSummary,
   ChatModelSummary,
@@ -80,10 +78,9 @@ export type SelectedModelInput = {
   isGguf?: boolean;
   throwOnError?: boolean;
   /** Keep the current speculative-decoding choice across the model switch
-   *  instead of resetting it to the standing preference. */
+   *  instead of resetting it to the standing preference. Set by the deferred
+   *  ("Load on selection") Load, where the user picked it for this model. */
   keepSpeculative?: boolean;
-  config?: PerModelConfig;
-  previousConfig?: PerModelConfig;
 };
 
 // Approved fingerprints by checkpoint, so a rollback after a failed switch can resend
@@ -458,11 +455,27 @@ export function useChatModelRuntime() {
         typeof selection === "string" ? false : selection.throwOnError ?? false;
       const keepSpeculative =
         typeof selection === "string" ? false : selection.keepSpeculative ?? false;
+      // Picking/loading any model abandons a staged (deferred) selection.
+      // Before the early-returns below so even a no-op re-select clears the
+      // stage.
+      const staged = useChatRuntimeStore.getState().pendingSelection;
+      if (staged) {
+        // Loading a DIFFERENT model abandons this stage. Loading the staged pick
+        // ITSELF keeps it so the sidebar can show its load settings (context, KV
+        // cache, …) during the load. Cleared on success below; on failure it's
+        // left staged so the user can retry (see onLoadPendingModel's catch).
+        const loadingStagedPick = pendingSelectionMatches(staged, {
+          id: modelId,
+          ggufVariant,
+          nativePathToken,
+        });
+        if (!loadingStagedPick) {
+          cancelStagedModelDownload(staged);
+          useChatRuntimeStore.getState().setPendingSelection(null);
+        }
+      }
       const currentVariant = useChatRuntimeStore.getState().activeGgufVariant;
       if (!forceReload && (!modelId || (params.checkpoint === modelId && (ggufVariant ?? null) === (currentVariant ?? null)))) {
-        if (typeof selection !== "string" && selection.previousConfig) {
-          applyPerModelConfigToRuntime(selection.previousConfig);
-        }
         return;
       }
       // A load is already in flight. If it's this exact pick (id + GGUF variant +
@@ -475,9 +488,6 @@ export function useChatModelRuntime() {
       // every entry point is covered, not just the staged Load button.
       const inFlightLoad = loadingModelRef.current;
       if (inFlightLoad) {
-        if (typeof selection !== "string" && selection.previousConfig) {
-          applyPerModelConfigToRuntime(selection.previousConfig);
-        }
         const loadingSamePick =
           inFlightLoad.id === modelId &&
           (inFlightLoad.ggufVariant ?? null) === (ggufVariant ?? null) &&
@@ -572,24 +582,20 @@ export function useChatModelRuntime() {
             previousModel?.isGguf === true
             || previousVariant != null
             || (previousCheckpoint?.toLowerCase().endsWith(".gguf") ?? false);
-          // Roll back to the previous model's own context. previousConfig was
-          // snapshotted before this load pre-applied the next model's config to
-          // the shared store, so params.maxSeqLength may already be the next
-          // model's value; fall back to it only when no snapshot exists.
-          const previousMaxSeqLength =
-            (typeof selection !== "string"
-              ? selection.previousConfig?.maxSeqLength
-              : null) ?? maxSeqLength;
           const rollbackMaxSeqLength = previousIsGguf
             ? (stateBeforeUnload.ggufContextLength ?? 0)
-            : previousMaxSeqLength;
+            : maxSeqLength;
           const hfToken = stateBeforeUnload.hfToken || null;
           const previousModelRequiresTrustRemoteCode =
             stateBeforeUnload.modelRequiresTrustRemoteCode;
           const previousActiveNativePathToken =
             stateBeforeUnload.activeNativePathToken;
           // Snapshot the load settings at click time, before the awaits below
-          // (validation, the trust dialog, unload).
+          // (validation, the trust dialog, unload). For a staged Load these knobs
+          // stay editable and a sheet-close revert (abandonStagedModel) can fire
+          // mid-load; reading them live just before loadModel would let the load
+          // use post-click values. The model-switch speculative reset below
+          // updates this snapshot in lock-step so non-staged loads are unchanged.
           const loadChatTemplateOverride = stateBeforeUnload.chatTemplateOverride;
           const loadKvCacheDtype = stateBeforeUnload.kvCacheDtype;
           const loadCustomContextLength = stateBeforeUnload.customContextLength;
@@ -740,12 +746,7 @@ export function useChatModelRuntime() {
             // The load applied this spec mode, so persist the user's standing
             // preference now (the requested intent, not the resolved echo;
             // saveSpeculativeType keeps only the universal auto/ngram/off).
-            // Skip for a per-model/one-off config (keepSpeculative): that choice
-            // is model-specific and must not overwrite the global default, or a
-            // later model with no saved config would start from it instead of Auto.
-            if (!keepSpeculative) {
-              saveSpeculativeType(loadSpeculativeType);
-            }
+            saveSpeculativeType(loadSpeculativeType);
 
             const currentParams = useChatRuntimeStore.getState().params;
             setParams(
@@ -781,11 +782,9 @@ export function useChatModelRuntime() {
             const reportedNativeCtx = loadResponse.is_gguf
               ? (loadResponse.native_context_length ?? null)
               : null;
-            // Retain the user's requested context so re-opening or re-saving
-            // the config keeps the intended override, not the backend's
-            // effective (auto-fit) context; null stays null so an auto-fit
-            // never becomes a stored override.
-            const keepCustomCtx = loadCustomContextLength;
+            // A successful reload has applied settings, so clear pending custom
+            // context state and display the backend-reported effective context.
+            const keepCustomCtx = null;
             const reasoningAlwaysOn = loadResponse.reasoning_always_on ?? false;
             const reasoningStyle = loadResponse.reasoning_style ?? "enable_thinking";
             const supportsReasoning = loadResponse.supports_reasoning ?? false;
@@ -902,6 +901,25 @@ export function useChatModelRuntime() {
                 recordLastLocalModelLoad({ id: modelId, kind: "model" });
               }
             }
+            // A successful load owns the shared (pick-unscoped) settings fields,
+            // so any surviving stage is stale: the just-loaded pick itself, or a
+            // pick queued for a different model mid-load whose knobs this load
+            // overwrote. Drop it. Only a DIFFERENT pick's download needs
+            // cancelling; the loaded pick's is already consumed, and cancelling
+            // it inside its post-complete linger window would flicker its card.
+            const staleStage = useChatRuntimeStore.getState().pendingSelection;
+            if (staleStage) {
+              if (
+                !pendingSelectionMatches(staleStage, {
+                  id: modelId,
+                  ggufVariant,
+                  nativePathToken,
+                })
+              ) {
+                cancelStagedModelDownload(staleStage);
+              }
+              useChatRuntimeStore.getState().setPendingSelection(null);
+            }
           } catch (error) {
             // Skip rollback if user cancelled -- model is already being unloaded.
             if (abortCtrl.signal.aborted) throw error;
@@ -936,23 +954,11 @@ export function useChatModelRuntime() {
                   // Restore the previous model in the split mode it was running,
                   // not the default layer split.
                   tensor_parallel: stateBeforeUnload.loadedTensorParallel ?? false,
-                  // Restore its KV cache dtype and chat template too, so the
-                  // rollback runs the model as it was, not with backend defaults.
-                  cache_type_kv: stateBeforeUnload.loadedKvCacheDtype ?? null,
-                  chat_template_override:
-                    stateBeforeUnload.loadedChatTemplateOverride ?? null,
-                  // Restore its speculative-decoding config too. Omitting these
-                  // reloaded the model at backend defaults (speculation off)
-                  // while the UI still showed it enabled.
-                  speculative_type: stateBeforeUnload.loadedSpeculativeType ?? null,
-                  spec_draft_n_max: stateBeforeUnload.loadedSpecDraftNMax ?? null,
                 });
                 useChatRuntimeStore.setState({
                   activeNativePathToken: previousActiveNativePathToken ?? null,
-                  speculativeType: stateBeforeUnload.loadedSpeculativeType ?? null,
-                  loadedSpeculativeType: stateBeforeUnload.loadedSpeculativeType ?? null,
-                  specDraftNMax: stateBeforeUnload.loadedSpecDraftNMax ?? null,
-                  loadedSpecDraftNMax: stateBeforeUnload.loadedSpecDraftNMax ?? null,
+                  loadedSpeculativeType: null,
+                  loadedSpecDraftNMax: null,
                 });
                 await refresh();
               } catch {
@@ -1271,9 +1277,6 @@ export function useChatModelRuntime() {
           resetLoadingUi();
         }
       } catch (error) {
-        if (typeof selection !== "string" && selection.previousConfig) {
-          applyPerModelConfigToRuntime(selection.previousConfig);
-        }
         if (abortCtrl.signal.aborted) return; // User cancelled, nothing to report
         resetLoadingUi();
         const message =
diff --git a/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts b/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
new file mode 100644
index 0000000000..d8076c720b
--- /dev/null
+++ b/studio/frontend/src/features/chat/hooks/use-staged-model-preparation.ts
@@ -0,0 +1,155 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useCallback, useEffect } from "react";
+
+import { useRepoDownload } from "@/features/hub/download-manager/use-repo-download";
+import type { DownloadJob } from "@/features/hub/download-manager/use-repo-download";
+import { useLatestRef } from "@/features/hub/hooks/use-latest-ref";
+
+import { fetchGgufContextLength } from "../api/chat-api";
+import {
+  isPendingGguf,
+  pendingSelectionMatches,
+  useChatRuntimeStore,
+} from "../stores/chat-runtime-store";
+import type { PendingModelSelection } from "../stores/chat-runtime-store";
+
+/**
+ * Drives the deferred ("Load on selection" off) staging flow for a GGUF:
+ * download the file if needed (HF repo) or read it in place (native drag-drop /
+ * picked file), then read its header context length so the settings sheet can
+ * show the real context slider before the single GPU load. The staged context
+ * lands on `pendingSelection.contextLength` (scoped to the staged model, never
+ * the loaded model's `ggufContextLength`). Returns the live download job so the
+ * sheet can render progress / cancel. Mount once on the chat page.
+ */
+export function useStagedModelPreparation(opts?: {
+  /** Load the cached file once an autoLoad pick's download completes. */
+  onAutoLoad?: (pending: PendingModelSelection) => void;
+}): DownloadJob {
+  const pendingId = useChatRuntimeStore((s) => s.pendingSelection?.id ?? null);
+  const pendingVariant = useChatRuntimeStore(
+    (s) => s.pendingSelection?.ggufVariant ?? null,
+  );
+  const pendingNativeToken = useChatRuntimeStore(
+    (s) => s.pendingSelection?.nativePathToken ?? null,
+  );
+  // Only GGUF picks (HF variant or native file) have a header worth reading.
+  const pendingIsGguf = useChatRuntimeStore((s) =>
+    isPendingGguf(s.pendingSelection),
+  );
+  // Non-GGUF HF repos download a full snapshot (variant null) but have no header.
+  const pendingIsHubRepo = useChatRuntimeStore(
+    (s) => s.pendingSelection?.isHubRepo ?? false,
+  );
+  const pendingDownloaded = useChatRuntimeStore(
+    (s) => s.pendingSelection?.isDownloaded ?? false,
+  );
+  const pendingHasContext = useChatRuntimeStore(
+    (s) => s.pendingSelection?.contextLength != null,
+  );
+  const setPendingSelection = useChatRuntimeStore((s) => s.setPendingSelection);
+  const onAutoLoadRef = useLatestRef(opts?.onAutoLoad);
+
+  // A failed or cancelled autoLoad download has no sheet to retry from, so drop
+  // the staged pick rather than leave it waiting on a load that won't come.
+  const handleAutoLoadAbort = useCallback((variant: string | null) => {
+    const latest = useChatRuntimeStore.getState().pendingSelection;
+    if (
+      latest?.autoLoad &&
+      (latest.ggufVariant ?? null) === (variant ?? null)
+    ) {
+      useChatRuntimeStore.getState().abandonStagedModel();
+    }
+  }, []);
+
+  const fetchContextMetadata = useCallback(async () => {
+    const current = useChatRuntimeStore.getState().pendingSelection;
+    if (!current?.id || !isPendingGguf(current)) return;
+    const { id, ggufVariant, nativePathToken } = current;
+    try {
+      const contextLength = await fetchGgufContextLength({
+        model_path: id,
+        gguf_variant: ggufVariant,
+        hf_token: useChatRuntimeStore.getState().hfToken || null,
+        nativePathToken,
+      });
+      // Apply only if the same model is still staged (the user may have switched
+      // picks or loaded/cancelled while the request was in flight).
+      const latest = useChatRuntimeStore.getState().pendingSelection;
+      if (
+        latest &&
+        contextLength != null &&
+        pendingSelectionMatches(latest, { id, ggufVariant, nativePathToken })
+      ) {
+        setPendingSelection({ ...latest, contextLength });
+      }
+    } catch {
+      // Leave contextLength null: the context slider stays hidden and the user
+      // can still load (context fills in from the load response afterwards).
+    }
+  }, [setPendingSelection]);
+
+  const job = useRepoDownload({
+    kind: "model",
+    // useRepoDownload must be called unconditionally; an idle repo id keeps it
+    // inert until something is staged.
+    repoId: pendingId ?? "__staged_idle__",
+    activeVariant: pendingVariant,
+    onComplete: (variant) => {
+      // autoLoad picks load the cached file now; staged picks read the header so
+      // the sheet's context slider can show before a manual load.
+      const latest = useChatRuntimeStore.getState().pendingSelection;
+      if (
+        latest?.autoLoad &&
+        (latest.ggufVariant ?? null) === (variant ?? null)
+      ) {
+        onAutoLoadRef.current?.(latest);
+        return;
+      }
+      void fetchContextMetadata();
+    },
+    onError: handleAutoLoadAbort,
+    onCancelled: handleAutoLoadAbort,
+  });
+
+  // job.requestStartDownload's identity changes per render; hold it in a ref so
+  // the staging effect re-runs only when the staged model itself changes.
+  const startDownloadRef = useLatestRef(job.requestStartDownload);
+  const fetchMetadataRef = useLatestRef(fetchContextMetadata);
+
+  useEffect(() => {
+    // GGUF picks (header worth reading) and uncached non-GGUF hub repos (full
+    // snapshot, no header) both run here; everything else is loaded directly.
+    if (
+      !pendingId ||
+      (!pendingIsGguf && !pendingIsHubRepo) ||
+      pendingHasContext
+    ) {
+      return;
+    }
+    // Native files and already-downloaded HF files are local: read the header
+    // now. Otherwise download first (a GGUF variant, or a null-variant snapshot
+    // for a hub repo); onComplete then reads the header or auto-loads.
+    if (pendingNativeToken || pendingDownloaded) {
+      void fetchMetadataRef.current();
+    } else {
+      const expectedBytes =
+        useChatRuntimeStore.getState().pendingSelection?.expectedBytes ?? 0;
+      void startDownloadRef.current(pendingVariant, expectedBytes);
+    }
+  }, [
+    pendingId,
+    pendingVariant,
+    pendingNativeToken,
+    pendingIsGguf,
+    pendingIsHubRepo,
+    pendingDownloaded,
+    pendingHasContext,
+    startDownloadRef,
+    fetchMetadataRef,
+  ]);
+
+  return job;
+}
diff --git a/studio/frontend/src/features/chat/index.ts b/studio/frontend/src/features/chat/index.ts
index 364c47c7ea..a8b5fc23ad 100644
--- a/studio/frontend/src/features/chat/index.ts
+++ b/studio/frontend/src/features/chat/index.ts
@@ -3,23 +3,11 @@
 
 export { ChatPage, validateChatSearch, type ChatSearch } from "./chat-page";
 export {
-  addScanFolder,
-  browseFolders,
-  deleteCachedModel,
-  deleteFineTunedModel,
-  fetchGgufContextLength,
   getInferenceStatus,
   listGgufVariants,
   listLocalModels,
-  listRecommendedFolders,
-  listScanFolders,
   loadModel,
-  removeScanFolder,
-  type BrowseFoldersResponse,
-  type CachedGgufRepo,
-  type CachedModelRepo,
   type LocalModelInfo,
-  type ScanFolderInfo,
 } from "./api/chat-api";
 export type { GgufVariantDetail } from "./types/api";
 export {
@@ -29,10 +17,6 @@ export {
   type Preset,
 } from "./chat-settings-sheet";
 export { useChatRuntimeStore } from "./stores/chat-runtime-store";
-export {
-  normalizeSpeculativeType,
-  readPersistedSpeculativeType,
-} from "./stores/chat-runtime-store";
 export {
   preferFullToolOutput,
   toolOutputKey,
@@ -53,11 +37,9 @@ export {
 } from "./hooks/use-chat-model-runtime";
 export {
   customProviderDisplayName,
-  isCustomProviderType,
   isExternalModelId,
   parseExternalModelId,
 } from "./external-providers";
-export { ApiProviderLogo } from "./api-provider-logo";
 export { useExternalProvidersStore } from "./stores/external-providers-store";
 export { ChatSearchDialog } from "./components/chat-search-dialog";
 export { setTrainingCompareHandoff } from "./lib/training-compare-handoff";
diff --git a/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts b/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
index 378178ed58..a4b5f848e2 100644
--- a/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
+++ b/studio/frontend/src/features/chat/lib/apply-inference-status-to-store.ts
@@ -204,6 +204,11 @@ export function applyActiveModelStatusToStore(
     ggufContextLength: currentGgufContextLength,
     ggufMaxContextLength,
     ggufNativeContextLength,
+    // A non-GGUF status must also drop a stale native-path token: without this the
+    // isGguf OR (activeGgufVariant || activeNativePathToken || ggufContextLength)
+    // stays true after switching from a native GGUF to a transformers model, so a
+    // Codex-only detection would auto-select for a model its preflight rejects. A real
+    // GGUF load reports is_gguf: true, so its token is preserved (the load path owns it).
     ...(status.is_gguf ? {} : { activeNativePathToken: null }),
     modelRequiresTrustRemoteCode: status.requires_trust_remote_code ?? false,
     defaultChatTemplate: nextDefaultChatTemplate,
diff --git a/studio/frontend/src/features/chat/shared-composer.tsx b/studio/frontend/src/features/chat/shared-composer.tsx
index d861dab0f4..a0813fe27b 100644
--- a/studio/frontend/src/features/chat/shared-composer.tsx
+++ b/studio/frontend/src/features/chat/shared-composer.tsx
@@ -79,11 +79,6 @@ import { KnowledgeBaseComposerButton } from "@/features/rag/components/knowledge
 import { NewProjectDialog } from "./components/new-project-dialog";
 import { useChatProjects } from "./hooks/use-chat-projects";
 import { confirmRemoteCodeIfNeeded } from "@/features/security";
-import {
-  normalizeMaxSeqLength,
-  resolveInitialConfig,
-  type PerModelConfig,
-} from "@/features/model-picker";
 import {
   confirmTransformersUpgradeIfNeeded,
   useTransformersUpgradeDialogStore,
@@ -495,24 +490,8 @@ type CompareModelSelection = {
   id: string;
   isLora: boolean;
   ggufVariant?: string;
-  config?: PerModelConfig;
 };
 
-function cleanCompareChatTemplate(
-  value: string | null | undefined,
-): string | null {
-  return value?.trim() ? value : null;
-}
-
-function resolveCompareSpecDraftNMax(
-  speculativeType: string | null,
-  value: number | null,
-): number | null {
-  return speculativeType === "mtp" || speculativeType === "mtp+ngram"
-    ? value
-    : null;
-}
-
 // Tool icon plus an X overlay CSS reveals on hover when the pill is active.
 function PillGlyph({ children }: { children: ReactNode }) {
   return (
@@ -1045,11 +1024,13 @@ export function SharedComposer({
       const store = useChatRuntimeStore.getState();
       const maxSeqLength = store.params.maxSeqLength;
       const trustRemoteCode = store.params.trustRemoteCode ?? false;
-      const fallbackTensorParallel = store.tensorParallel;
+      const chatTemplateOverride = store.chatTemplateOverride;
+      const effectiveChatTemplateOverride = chatTemplateOverride?.trim()
+        ? chatTemplateOverride
+        : null;
       const specSettings = resolveSpeculativeSettingsForLoad({
         usePersistedPreference: true,
       });
-      let loadedFromConfig = false;
 
       function modelDisplayName(id: string): string {
         const parts = id.split("/");
@@ -1065,53 +1046,21 @@ export function SharedComposer({
         sel: CompareModelSelection,
       ): Promise<string> {
         const currentStore = useChatRuntimeStore.getState();
-        const config = sel.config ?? null;
-        // This pane's effective config: an explicit selection config, else the
-        // remembered store config for this model/quant (never the other pane's).
-        // A model with no saved config resolves to all-null defaults, so every
-        // setting below still falls through to its session default.
-        const resolved = config
-          ? { config, remembered: true }
-          : resolveInitialConfig(sel.id, sel.ggufVariant ?? null);
-        const ownConfig = resolved.config;
-        const ownRemembered = resolved.remembered;
-        // Mirror single-view resolveLoadMaxSeqLength: a GGUF pane with no
-        // explicit context loads at native (0 -> n_ctx_train), not the session
-        // maxSeqLength, which would silently shrink the picker's shown context.
-        const isGgufLoad =
-          (sel.ggufVariant ?? null) != null ||
-          sel.id.toLowerCase().endsWith(".gguf");
-        const effectiveMaxSeqLength =
-          ownConfig.customContextLength ??
-          normalizeMaxSeqLength(ownConfig.maxSeqLength) ??
-          (isGgufLoad ? 0 : maxSeqLength);
-        const effectiveChatTemplateOverride = cleanCompareChatTemplate(
-          ownConfig.chatTemplateOverride,
-        );
-        const effectiveSpeculativeType =
-          ownConfig.speculativeType ?? specSettings.speculativeType;
-        const effectiveSpecDraftNMax = ownRemembered
-          ? resolveCompareSpecDraftNMax(
-              effectiveSpeculativeType,
-              ownConfig.specDraftNMax,
-            )
-          : specSettings.specDraftNMax;
-        const effectiveTensorParallel = ownRemembered
-          ? ownConfig.tensorParallel
-          : fallbackTensorParallel;
         let loadTrustRemoteCode = trustRemoteCode;
         let approvedRemoteCodeFingerprint: string | null = null;
         const isAlreadyActive =
           currentStore.params.checkpoint === sel.id &&
           (currentStore.activeGgufVariant ?? null) ===
             (sel.ggufVariant ?? null);
-        if (isAlreadyActive && !config && !loadedFromConfig) {
+        // Already loaded (gate passed at first load): skip a redundant reload that would
+        // re-trigger the gate without the approval fingerprint and fail for HIGH custom code.
+        if (isAlreadyActive) {
           return "ready";
         }
         const validation = await validateModel({
           model_path: sel.id,
           hf_token: currentStore.hfToken || null,
-          max_seq_length: effectiveMaxSeqLength,
+          max_seq_length: maxSeqLength,
           load_in_4bit: true,
           is_lora: sel.isLora,
           gguf_variant: sel.ggufVariant ?? null,
@@ -1165,24 +1114,19 @@ export function SharedComposer({
         const resp = await loadModel({
           model_path: sel.id,
           hf_token: useChatRuntimeStore.getState().hfToken || null,
-          max_seq_length: effectiveMaxSeqLength,
+          max_seq_length: maxSeqLength,
           load_in_4bit: true,
           is_lora: sel.isLora,
           gguf_variant: sel.ggufVariant ?? null,
           trust_remote_code: loadTrustRemoteCode,
           approved_remote_code_fingerprint: approvedRemoteCodeFingerprint,
           chat_template_override: effectiveChatTemplateOverride,
-          cache_type_kv: ownConfig.kvCacheDtype ?? null,
-          speculative_type: effectiveSpeculativeType,
-          spec_draft_n_max: effectiveSpecDraftNMax,
-          tensor_parallel: effectiveTensorParallel,
+          speculative_type: specSettings.speculativeType,
+          spec_draft_n_max: specSettings.specDraftNMax,
+          // Honor the Tensor Parallelism toggle on compare loads too.
+          tensor_parallel: currentStore.tensorParallel,
         });
-        // Keep a compare pane's per-model speculative choice load-local: only
-        // persist the global preference when it came from the global settings,
-        // matching the single-model load path.
-        if (ownConfig.speculativeType == null) {
-          saveSpeculativeType(effectiveSpeculativeType);
-        }
+        saveSpeculativeType(specSettings.speculativeType);
         upgradeUnloadedActive = false;
         const store = useChatRuntimeStore.getState();
         store.setCheckpoint(
@@ -1198,38 +1142,11 @@ export function SharedComposer({
           ...reasoningCapsFromLoad(resp),
           supportsPreserveThinking: resp.supports_preserve_thinking ?? false,
           supportsTools: resp.supports_tools ?? false,
-          kvCacheDtype: resp.cache_type_kv ?? null,
-          loadedKvCacheDtype: resp.cache_type_kv ?? null,
           tensorParallel: resp.tensor_parallel ?? false,
           loadedTensorParallel: resp.tensor_parallel ?? false,
-          defaultChatTemplate: resp.chat_template ?? null,
-          chatTemplateOverride: effectiveChatTemplateOverride,
-          loadedChatTemplateOverride: effectiveChatTemplateOverride,
           loadedIsMultimodal: isMultimodalResponse(resp),
-          // Record the context this pane actually loaded with, mirroring the
-          // single-model load path, so that when the last-loaded pane becomes
-          // the active model the settings UI and any subsequent reload or save
-          // use its context instead of the previous/default one.
-          customContextLength: isGgufLoad
-            ? (ownConfig.customContextLength ?? null)
-            : null,
-          ggufContextLength: resp.is_gguf ? (resp.context_length ?? null) : null,
-          ggufNativeContextLength: resp.is_gguf
-            ? (resp.native_context_length ?? null)
-            : null,
-          ggufMaxContextLength: resp.is_gguf
-            ? (resp.max_context_length ?? null)
-            : null,
           ...resolveLoadedSpeculativeSettings(resp),
         });
-        if (!isGgufLoad) {
-          // Non-GGUF panes carry their context in params.maxSeqLength.
-          store.setParams({
-            ...store.params,
-            maxSeqLength: effectiveMaxSeqLength,
-          });
-        }
-        loadedFromConfig = config != null;
         // Sync the models[] entry with the load response so attach/send gates
         // read fresh capabilities. /api/models/list can lag a model's actual
         // state (e.g. a GGUF whose mmproj arrived after the snapshot).
diff --git a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
index 54184bce24..af99458349 100644
--- a/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
+++ b/studio/frontend/src/features/chat/stores/chat-runtime-store.ts
@@ -1,7 +1,12 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-import { mirrorHfTokenInto, useHfTokenStore } from "@/features/hub";
+import type { RememberedLoadSettings } from "@/components/assistant-ui/model-selector/remembered-load-settings";
+import {
+  cancelStagedModelDownload,
+  mirrorHfTokenInto,
+  useHfTokenStore,
+} from "@/features/hub";
 import { toast } from "@/lib/toast";
 import { create } from "zustand";
 import { isExternalModelId, parseExternalModelId } from "../external-providers";
@@ -37,6 +42,7 @@ export const CHAT_ALLOW_ARTIFACT_NETWORK_ACCESS_KEY =
   "unsloth_chat_allow_artifact_network_access";
 export const CHAT_MCP_ENABLED_KEY = "unsloth_chat_mcp_enabled";
 export const CHAT_CONFIRM_TOOL_CALLS_KEY = "unsloth_chat_confirm_tool_calls";
+export const CHAT_LOAD_ON_SELECTION_KEY = "unsloth_chat_load_on_selection";
 export const CHAT_EXPAND_QUANTIZATIONS_KEY =
   "unsloth_chat_expand_quantizations";
 export const CHAT_SHOW_ALL_QUANTIZATIONS_KEY =
@@ -491,7 +497,34 @@ export function saveSpeculativeType(value: string | null): void {
   }
 }
 
-/** A pick is a GGUF: HF variant, native file, or a direct local .gguf. */
+/** A local model staged for a deferred load (see `pendingSelection`). Shape is
+ *  a subset of the load hook's `SelectedModelInput`, structurally assignable. */
+export type PendingModelSelection = {
+  id: string;
+  isLora?: boolean;
+  ggufVariant?: string;
+  isDownloaded?: boolean;
+  expectedBytes?: number;
+  /** Native (drag-drop / picked-from-disk) GGUF: the path token used to read
+   *  the header and to load. Absent for HF-repo models. */
+  nativePathToken?: string;
+  /** Direct local .gguf file (custom folder / LM Studio): a GGUF source even
+   *  though it carries neither an HF variant nor a native path token. */
+  isGguf?: boolean;
+  /** Native context length read from the GGUF header once the file is local.
+   *  Scoped here (not the shared `ggufContextLength`) so a staged model's
+   *  metadata never pollutes the currently-loaded model's context display. */
+  contextLength?: number | null;
+  /** "Load on selection" on + un-cached GGUF: download via the manager (global
+   *  indicator) without opening the sheet, then load once the download finishes. */
+  autoLoad?: boolean;
+  /** Uncached non-GGUF HF repo: download the full snapshot via the manager
+   *  (variant null) the same way GGUF picks download a variant. */
+  isHubRepo?: boolean;
+};
+
+/** A pick is a GGUF (HF variant, native file, or a direct local .gguf) and so
+ *  has pre-load options worth staging. Works on a selection or a staged pick. */
 export function hasGgufSource(x: {
   ggufVariant?: string;
   nativePathToken?: string;
@@ -529,6 +562,30 @@ export function isDownloadableHubRepo(x: {
   );
 }
 
+export function isPendingGguf(pending: PendingModelSelection | null): boolean {
+  return pending != null && hasGgufSource(pending);
+}
+
+/** Whether `pending` refers to the same model as `pick` (id + GGUF variant +
+ *  native path token, optionals null-normalized). Native ids are display labels
+ *  that can collide, so the token must match too — id alone can land on the
+ *  wrong file. */
+export function pendingSelectionMatches(
+  pending: PendingModelSelection | null,
+  pick: {
+    id: string;
+    ggufVariant?: string | null;
+    nativePathToken?: string | null;
+  },
+): boolean {
+  return (
+    pending != null &&
+    pending.id === pick.id &&
+    (pending.ggufVariant ?? null) === (pick.ggufVariant ?? null) &&
+    (pending.nativePathToken ?? null) === (pick.nativePathToken ?? null)
+  );
+}
+
 type ChatRuntimeStore = {
   settingsHydrated: boolean;
   params: InferenceParams;
@@ -686,6 +743,10 @@ type ChatRuntimeStore = {
   tensorParallel: boolean;
   /** Backend-reported tensor-parallel state; null until first hydrated. */
   loadedTensorParallel: boolean | null;
+  /** Persisted: when false, picking a local model stages it as
+   *  `pendingSelection` (and opens settings) instead of loading immediately,
+   *  so load settings can be set before the single load. */
+  loadOnSelection: boolean;
   /** Persisted: expand every On Device GGUF repo's quantizations by default
    *  instead of waiting for a click. */
   expandQuantizations: boolean;
@@ -694,6 +755,9 @@ type ChatRuntimeStore = {
   /** Persisted, shared by the chat model selector and the Hub page: list only
    *  models whose size fits this device's memory budget. */
   fitOnDeviceOnly: boolean;
+  /** A local model picked while `loadOnSelection` is off: staged, not loaded.
+   *  The settings sheet shows its load knobs and a Load button. */
+  pendingSelection: PendingModelSelection | null;
   loadedIsMultimodal: boolean;
   /** Active model is a block-diffusion model (DiffusionGemma): drives the
    *  denoising-canvas artifact auto-render. */
@@ -730,10 +794,6 @@ type ChatRuntimeStore = {
   } | null;
   modelLoading: boolean;
   activeNativePathToken: string | null;
-  // Wall-clock expiry (ms) of the active native path token. The desktop host
-  // prunes file leases after a TTL, so a reload checks this to prompt
-  // re-selection instead of reusing a dead token.
-  activeNativePathExpiresAtMs: number | null;
   hydratePersistedSettings: () => Promise<void>;
   setModelLoading: (loading: boolean) => void;
   setModelRequiresTrustRemoteCode: (required: boolean) => void;
@@ -811,9 +871,33 @@ type ChatRuntimeStore = {
   setNudgeToolCalls: (enabled: boolean) => void;
   setMaxToolCallsPerMessage: (value: number) => void;
   setToolCallTimeout: (value: number) => void;
+  setKvCacheDtype: (dtype: string | null) => void;
+  setSpeculativeType: (type: string | null) => void;
+  setSpecDraftNMax: (value: number | null) => void;
+  /** Revert the editable load knobs to the loaded model's baseline (or defaults
+   *  when nothing is loaded). Used by the settings-sheet Reset button and to
+   *  start each deferred-staging session clean so one staged pick's settings
+   *  don't leak onto the next. */
+  resetModelSettingsToLoaded: () => void;
+  /** Seed the editable load knobs from a model's remembered settings. Shared by
+   *  the settings sheet's restore effect and the "Load on selection" paths,
+   *  which skip the sheet but must still honor a saved config. */
+  applyRememberedLoadSettings: (settings: RememberedLoadSettings) => void;
+  setTensorParallel: (value: boolean) => void;
+  setLoadOnSelection: (value: boolean) => void;
   setExpandQuantizations: (value: boolean) => void;
   setShowAllQuantizations: (value: boolean) => void;
   setFitOnDeviceOnly: (value: boolean) => void;
+  setPendingSelection: (selection: PendingModelSelection | null) => void;
+  /** Stage a pick for a deferred load: revert knobs to the loaded baseline,
+   *  record the selection, and open the settings sheet. */
+  stageModel: (selection: PendingModelSelection) => void;
+  /** Abandon a staged pick without loading: revert knobs to the loaded baseline
+   *  and clear the pending selection. Cancels its in-flight download too, unless
+   *  `keepDownload` is set (navigation keeps the transfer running, like Hub). */
+  abandonStagedModel: (opts?: { keepDownload?: boolean }) => void;
+  setCustomContextLength: (v: number | null) => void;
+  setChatTemplateOverride: (template: string | null) => void;
   setPendingAudio: (base64: string, name: string) => void;
   clearPendingAudio: () => void;
   setPendingImageEditReference: (
@@ -1015,6 +1099,23 @@ function setScalarSettingVersion<K extends ScalarSettingKey>(
   saveSettingsPatch({ [key]: value });
 }
 
+/** The "revert to the loaded model" baseline for the editable load knobs.
+ *  Shared by resetModelSettingsToLoaded (full revert) and stageModel (which
+ *  overrides speculative to start a fresh pick from the standing default). */
+function loadedBaselineSettings(s: ChatRuntimeStore) {
+  const hasLoadedModel = Boolean(s.params.checkpoint);
+  return {
+    customContextLength: null,
+    kvCacheDtype: s.loadedKvCacheDtype,
+    tensorParallel: s.loadedTensorParallel ?? false,
+    speculativeType: hasLoadedModel
+      ? s.loadedSpeculativeType
+      : readPersistedSpeculativeType(),
+    specDraftNMax: hasLoadedModel ? s.loadedSpecDraftNMax : null,
+    chatTemplateOverride: s.loadedChatTemplateOverride,
+  };
+}
+
 export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   settingsHydrated: false,
   // Hydrate the last external checkpoint so the external picker survives a
@@ -1112,9 +1213,11 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   loadedSpecDraftNMax: null,
   tensorParallel: false,
   loadedTensorParallel: null,
+  loadOnSelection: loadBool(CHAT_LOAD_ON_SELECTION_KEY, true),
   expandQuantizations: loadBool(CHAT_EXPAND_QUANTIZATIONS_KEY, false),
   showAllQuantizations: loadBool(CHAT_SHOW_ALL_QUANTIZATIONS_KEY, true),
   fitOnDeviceOnly: loadBool(MODELS_FIT_ON_DEVICE_ONLY_KEY, false),
+  pendingSelection: null,
   loadedIsMultimodal: false,
   loadedIsDiffusion: false,
   customContextLength: null,
@@ -1132,7 +1235,6 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
   contextUsage: null,
   modelLoading: false,
   activeNativePathToken: null,
-  activeNativePathExpiresAtMs: null,
   hydratePersistedSettings: async () => {
     if (get().settingsHydrated) {
       return;
@@ -1251,6 +1353,13 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       // Clear stale per-turn usage on model change; the relaxed external-provider
       // render gate would otherwise show old counters until the next completion.
       const checkpointChanged = state.params.checkpoint !== modelId;
+      const pendingToClear =
+        checkpointChanged && state.params.checkpoint
+          ? state.pendingSelection
+          : null;
+      if (pendingToClear) {
+        cancelStagedModelDownload(pendingToClear);
+      }
       // Clamp maxTokens to the new model's cap when switching into an external
       // model so a value carried over from a local session doesn't exceed the
       // slider's max.
@@ -1278,6 +1387,14 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
         },
         activeGgufVariant: ggufVariant ?? null,
         ...(checkpointChanged ? { contextUsage: null } : {}),
+        // Switching away from a loaded model (e.g. picking an external provider)
+        // abandons any staged pick, so its Load button and edited knobs don't
+        // linger over the newly active model. Same revert as abandonStagedModel.
+        // Guarded on a non-empty current checkpoint: an establishing set from a
+        // background status sync (empty -> active) must not wipe a fresh stage.
+        ...(pendingToClear
+          ? { ...loadedBaselineSettings(state), pendingSelection: null }
+          : {}),
       };
     }),
   setActiveThreadId: (activeThreadId) =>
@@ -1291,6 +1408,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     // clear any stored external selection so the next refresh doesn't snap
     // back to a model the user intentionally cleared.
     saveLastExternalCheckpoint(null);
+    cancelStagedModelDownload(get().pendingSelection);
     return set((state) => ({
       params: {
         ...state.params,
@@ -1298,7 +1416,7 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       },
       activeGgufVariant: null,
       activeNativePathToken: null,
-      activeNativePathExpiresAtMs: null,
+      pendingSelection: null,
       ggufContextLength: null,
       ggufMaxContextLength: null,
       ggufNativeContextLength: null,
@@ -1631,6 +1749,25 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
       );
       return { toolCallTimeout };
     }),
+  setKvCacheDtype: (kvCacheDtype) => set({ kvCacheDtype }),
+  setSpeculativeType: (speculativeType) => set({ speculativeType }),
+  setSpecDraftNMax: (specDraftNMax) => set({ specDraftNMax }),
+  setTensorParallel: (tensorParallel) => set({ tensorParallel }),
+  resetModelSettingsToLoaded: () => set((s) => loadedBaselineSettings(s)),
+  applyRememberedLoadSettings: (settings) =>
+    // Coalesce every field: a blob persisted by an older/newer build can omit
+    // keys, and a raw spread would push `undefined` into fields typed non-null.
+    set({
+      customContextLength: settings.contextLength ?? null,
+      kvCacheDtype: settings.kvCacheDtype ?? null,
+      speculativeType: settings.speculativeType ?? "auto",
+      specDraftNMax: settings.specDraftNMax ?? null,
+      tensorParallel: settings.tensorParallel ?? false,
+    }),
+  setLoadOnSelection: (loadOnSelection) => {
+    saveBool(CHAT_LOAD_ON_SELECTION_KEY, loadOnSelection);
+    set({ loadOnSelection });
+  },
   setExpandQuantizations: (expandQuantizations) => {
     saveBool(CHAT_EXPAND_QUANTIZATIONS_KEY, expandQuantizations);
     set({ expandQuantizations });
@@ -1643,6 +1780,39 @@ export const useChatRuntimeStore = create<ChatRuntimeStore>((set, get) => ({
     saveBool(MODELS_FIT_ON_DEVICE_ONLY_KEY, fitOnDeviceOnly);
     set({ fitOnDeviceOnly });
   },
+  setPendingSelection: (pendingSelection) => set({ pendingSelection }),
+  stageModel: (selection) => {
+    // Refuse staging mid-load: post-load cleanup would silently drop the queued
+    // pick. stageOrLoad toasts first for callers that can.
+    if (get().modelLoading) return;
+    // Rebinding to a new pick keeps the prior pick's download running so the
+    // user can queue multiple downloads at once (Hub-style).
+    set((s) => {
+      return {
+        ...loadedBaselineSettings(s),
+        pendingSelection: selection,
+        // autoLoad downloads silently and loads on completion, so keep the sheet shut.
+        settingsPanelOpen: !selection.autoLoad,
+        // Speculative starts from the standing default, not the loaded model's
+        // mode, so a fresh pick doesn't inherit (and then carry, via the staged
+        // Load's keepSpeculative) a forced MTP mode onto a model that may lack it.
+        speculativeType: readPersistedSpeculativeType(),
+        specDraftNMax: null,
+      };
+    });
+  },
+  abandonStagedModel: (opts) => {
+    const { pendingSelection } = get();
+    if (!pendingSelection) return;
+    // Cancel the staged pick's in-flight download (centralized for every abandon
+    // path: sheet close, thread switch, route exit, new chat). `keepDownload`
+    // opts out so navigation leaves the transfer running, like a Hub download.
+    if (!opts?.keepDownload) cancelStagedModelDownload(pendingSelection);
+    set((s) => ({ ...loadedBaselineSettings(s), pendingSelection: null }));
+  },
+  setCustomContextLength: (customContextLength) => set({ customContextLength }),
+  setChatTemplateOverride: (chatTemplateOverride) =>
+    set({ chatTemplateOverride }),
   setPendingAudio: (base64, name) =>
     set({ pendingAudioBase64: base64, pendingAudioName: name }),
   clearPendingAudio: () =>
diff --git a/studio/frontend/src/features/export/components/export-run-panel.tsx b/studio/frontend/src/features/export/components/export-run-panel.tsx
index 6c2794420b..29ba5a703b 100644
--- a/studio/frontend/src/features/export/components/export-run-panel.tsx
+++ b/studio/frontend/src/features/export/components/export-run-panel.tsx
@@ -2,6 +2,7 @@
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 import { Button } from "@/components/ui/button";
+import { FolderBrowser } from "@/components/assistant-ui/model-selector/folder-browser";
 import { Input } from "@/components/ui/input";
 import {
   InputGroup,
@@ -16,7 +17,6 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
-import { FolderBrowser } from "@/features/model-picker";
 import {
   AlertCircleIcon,
   ArrowRight01Icon,
@@ -28,17 +28,17 @@ import {
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useEffect, useRef, useState } from "react";
 import { useShallow } from "zustand/react/shallow";
-import type { ExportLogEntry } from "../api/export-api";
 import {
   EXPORT_METHODS,
   type ExportMethod,
   findMergedFormat,
 } from "../constants";
+import type { ExportLogEntry } from "../api/export-api";
 import { getExportLogLineClass } from "../lib/log-style";
 import {
-  type ExportDestination,
   selectExportProgressPercent,
   useExportRuntimeStore,
+  type ExportDestination,
 } from "../stores/export-runtime-store";
 
 function useElapsedSeconds(startedAt: number | null, running: boolean): number {
@@ -165,9 +165,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
 
   const isExporting = run.isExporting;
   const isTerminal =
-    run.phase === "success" ||
-    run.phase === "error" ||
-    run.phase === "canceled";
+    run.phase === "success" || run.phase === "error" || run.phase === "canceled";
   const showConfig = run.phase === "idle";
   // Gate the log area on the active run's method (from the store) as well as the
   // local form selection, so it stays visible after navigating away and back
@@ -199,9 +197,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
     setFollowTail(nearBottom);
   };
 
-  const methodTitle = EXPORT_METHODS.find(
-    (m) => m.value === exportMethod,
-  )?.title;
+  const methodTitle = EXPORT_METHODS.find((m) => m.value === exportMethod)?.title;
   const summary = run.summary;
   const summaryBaseModel = summary?.baseModelName ?? baseModelName;
   const summaryCheckpoint = summary?.checkpointLabel ?? checkpoint;
@@ -294,10 +290,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                       onClick={() => setFolderBrowserOpen(true)}
                       aria-label="Browse save folder"
                     >
-                      <HugeiconsIcon
-                        icon={FolderSearchIcon}
-                        className="size-4"
-                      />
+                      <HugeiconsIcon icon={FolderSearchIcon} className="size-4" />
                     </Button>
                   </TooltipTrigger>
                   <TooltipContent>Browse</TooltipContent>
@@ -308,8 +301,8 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                   <>Default: {defaultSaveDirectory}</>
                 ) : (
                   <>
-                    Paste an absolute path if the folder browser cannot reach
-                    the drive.
+                    Paste an absolute path if the folder browser cannot reach the
+                    drive.
                   </>
                 )}
               </p>
@@ -417,10 +410,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                     : [];
               const showLabels = items.length > 1;
               return items.map((o, i) => (
-                <div
-                  key={`${o.path}-${i}`}
-                  className="flex min-w-0 flex-col gap-0.5"
-                >
+                <div key={`${o.path}-${i}`} className="flex min-w-0 flex-col gap-0.5">
                   {showLabels && o.label ? (
                     <span className="text-xs text-emerald-700/80 dark:text-emerald-300/80">
                       {o.label}
@@ -441,22 +431,14 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
 
       {run.phase === "canceled" && (
         <div className="flex items-start gap-2 rounded-lg bg-amber-500/10 p-3 text-sm text-amber-700 dark:text-amber-300">
-          <HugeiconsIcon
-            icon={CancelCircleIcon}
-            className="mt-0.5 size-4 shrink-0"
-          />
-          <span>
-            Export canceled. Training and inference were not affected.
-          </span>
+          <HugeiconsIcon icon={CancelCircleIcon} className="mt-0.5 size-4 shrink-0" />
+          <span>Export canceled. Training and inference were not affected.</span>
         </div>
       )}
 
       {run.phase === "error" && run.error && (
         <div className="flex items-start gap-2 rounded-lg bg-destructive/10 p-3 text-sm text-destructive">
-          <HugeiconsIcon
-            icon={AlertCircleIcon}
-            className="size-4 mt-0.5 shrink-0"
-          />
+          <HugeiconsIcon icon={AlertCircleIcon} className="size-4 mt-0.5 shrink-0" />
           <span>{run.error}</span>
         </div>
       )}
@@ -465,21 +447,15 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
       <div className="rounded-xl bg-muted/50 p-3 text-xs text-muted-foreground flex flex-col gap-1">
         <div className="flex justify-between">
           <span>Base Model</span>
-          <span className="font-medium text-foreground">
-            {summaryBaseModel}
-          </span>
+          <span className="font-medium text-foreground">{summaryBaseModel}</span>
         </div>
         <div className="flex justify-between">
           <span>{isAdapter ? "Checkpoint" : "Model"}</span>
-          <span className="font-medium text-foreground">
-            {summaryCheckpoint}
-          </span>
+          <span className="font-medium text-foreground">{summaryCheckpoint}</span>
         </div>
         <div className="flex justify-between">
           <span>Export Method</span>
-          <span className="font-medium text-foreground">
-            {summaryMethodLabel}
-          </span>
+          <span className="font-medium text-foreground">{summaryMethodLabel}</span>
         </div>
         {summaryMethod === "merged" && summaryFormats.length > 0 && (
           <div className="flex justify-between gap-3">
@@ -508,12 +484,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
             </span>
             {summaryMethod === "gguf" && run.quantTotal > 1 && (
               <span className="text-[10px] tabular-nums text-muted-foreground">
-                Quant{" "}
-                {Math.min(
-                  run.quantIndex + (isExporting ? 1 : 0),
-                  run.quantTotal,
-                )}{" "}
-                of {run.quantTotal}
+                Quant {Math.min(run.quantIndex + (isExporting ? 1 : 0), run.quantTotal)} of {run.quantTotal}
               </span>
             )}
             <span className="rounded-full border border-border/60 px-2.5 py-1 text-[10px] font-medium tabular-nums text-muted-foreground">
@@ -535,10 +506,7 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
             }
           />
           {run.stage && (
-            <p
-              className="truncate text-[11px] text-muted-foreground/80"
-              title={run.stage}
-            >
+            <p className="truncate text-[11px] text-muted-foreground/80" title={run.stage}>
               {run.stage}
             </p>
           )}
@@ -588,7 +556,10 @@ export function ExportRunPanel(props: ExportRunPanelProps) {
                 ) : (
                   <div className="whitespace-pre-wrap break-words">
                     {run.logLines.map((entry, idx) => (
-                  <div key={idx} className={getExportLogLineClass(entry)}>
+                      <div
+                        key={idx}
+                        className={getExportLogLineClass(entry)}
+                      >
                         {formatLogLine(entry)}
                       </div>
                     ))}
diff --git a/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx b/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
index 9ed8e449f6..111d78f00b 100644
--- a/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
+++ b/studio/frontend/src/features/hub/catalog/models-catalog-rows.tsx
@@ -1,6 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import { ModelDeleteAction } from "@/components/assistant-ui/model-selector/model-delete-action";
 import {
   Tooltip,
   TooltipContent,
@@ -8,22 +9,18 @@ import {
 } from "@/components/ui/tooltip";
 import {
   type GgufVariantDetail,
-  deleteCachedDataset,
   deleteCachedModel,
+  deleteCachedDataset,
   formatLocalUpdated,
   listGgufVariants,
   useGgufVariantsCacheVersion,
-} from "@/features/hub";
-import {
-  classifyUnslothSupport,
-  formatBytes,
-  formatRelativeShort,
-  ggufVariantDisplayLabel,
-  modelIdsMatch,
-  useHfTokenStore,
-} from "@/features/hub";
-import { ModelDeleteAction } from "@/features/model-picker";
+} from "@/features/hub/inventory";
+import { classifyUnslothSupport } from "@/features/hub/hooks/use-hub-model-search";
+import { formatBytes, formatRelativeShort } from "@/features/hub/lib/format";
+import { ggufVariantDisplayLabel } from "@/features/hub/lib/gguf-variant-sort";
+import { modelIdsMatch } from "@/features/hub/lib/model-identity";
 import { cn, formatCompact } from "@/lib/utils";
+import { useHfTokenStore } from "@/features/hub/stores/hf-token-store";
 import {
   Download01Icon,
   FavouriteIcon,
@@ -42,7 +39,6 @@ import {
   useRef,
   useState,
 } from "react";
-import { paramLabelFromId } from "../lib/view-models";
 import type {
   CachedInventoryRow,
   DiscoverRow,
@@ -50,6 +46,7 @@ import type {
 } from "../types";
 import { OwnerAvatar } from "./owner-avatar";
 import { AccessGlyphs } from "./shared";
+import { paramLabelFromId } from "../lib/view-models";
 
 const COARSE_POINTER =
   typeof window !== "undefined" &&
@@ -145,15 +142,15 @@ function CachedSizeChipLive({
   );
 
   const rows: Array<{ label: string; size_bytes: number }> | null =
-    needsVariantFetch
-      ? currentVariantState.status === "loaded" &&
+    !needsVariantFetch
+      ? [{ label: repoId, size_bytes: totalBytes }]
+      : currentVariantState.status === "loaded" &&
           currentVariantState.variants.length > 0
         ? currentVariantState.variants.map((variant) => ({
             label: ggufVariantDisplayLabel(variant),
             size_bytes: variant.size_bytes,
           }))
-        : null
-      : [{ label: repoId, size_bytes: totalBytes }];
+        : null;
   const variantMessage =
     currentVariantState.status === "loading"
       ? "Loading downloaded variants..."
@@ -278,9 +275,7 @@ function CatalogRow({
         )}
       />
       <CatalogRowInteractiveContext.Provider value={interactive}>
-        <div
-          className={cn("pointer-events-none relative", card && "z-[1] w-full")}
-        >
+        <div className={cn("pointer-events-none relative", card && "z-[1] w-full")}>
           {children}
         </div>
       </CatalogRowInteractiveContext.Provider>
@@ -658,9 +653,7 @@ export const InventoryRow = memo(function InventoryRow({
       <div className="hidden shrink-0 items-center gap-1.5 sm:flex">
         {/* Format already shows as the status dot, so the pill stays neutral. */}
         {formatLabel && <span className="hub-chip">{formatLabel}</span>}
-        {paramLabel && (
-          <span className="hub-chip tabular-nums">{paramLabel}</span>
-        )}
+        {paramLabel && <span className="hub-chip tabular-nums">{paramLabel}</span>}
         {quantLabel && (
           <span className="hub-chip font-mono text-[10.5px] uppercase">
             {quantLabel}
@@ -704,7 +697,9 @@ export const InventoryRow = memo(function InventoryRow({
   const compactMarkers =
     partialRepoId || unsupported ? (
       <span className="flex shrink-0 items-center gap-1">
-        {partialRepoId && <StatusDot tone="warning" label="Partial download" />}
+        {partialRepoId && (
+          <StatusDot tone="warning" label="Partial download" />
+        )}
         {unsupported && (
           <StatusDot tone="danger" label="May not be supported yet" />
         )}
diff --git a/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx b/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
index 86108bbd80..caa89db196 100644
--- a/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
+++ b/studio/frontend/src/features/hub/catalog/on-device-folders-dialog.tsx
@@ -1,6 +1,7 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import { FolderBrowser } from "@/components/assistant-ui/model-selector/folder-browser";
 import { Button } from "@/components/ui/button";
 import {
   Dialog,
@@ -21,11 +22,9 @@ import {
   addScanFolder,
   listScanFolders,
   removeScanFolder,
-} from "@/features/hub";
-import { FolderBrowser } from "@/features/model-picker";
-import { openModelsDir } from "@/features/native-intents";
+} from "@/features/hub/inventory";
+import { openModelsDir } from "@/features/native-intents/api";
 import { isTauri } from "@/lib/api-base";
-import { toast } from "@/lib/toast";
 import { cn } from "@/lib/utils";
 import {
   Delete02Icon,
@@ -39,6 +38,7 @@ import {
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { toast } from "@/lib/toast";
 
 function pathTail(path: string): string {
   const parts = path.split(/[\\/]/).filter(Boolean);
@@ -123,9 +123,7 @@ export function OnDeviceFoldersDialog({
         setPath("");
         mutationVersionRef.current += 1;
         setFolders((current) => {
-          const withoutDuplicate = current.filter(
-            (row) => row.id !== folder.id,
-          );
+          const withoutDuplicate = current.filter((row) => row.id !== folder.id);
           return [...withoutDuplicate, folder];
         });
         toast.success("Location added", {
@@ -186,12 +184,9 @@ export function OnDeviceFoldersDialog({
           overlayClassName="bg-black/20 backdrop-blur-none"
         >
           <DialogHeader className="border-b border-border/60 px-5 py-4">
-            <DialogTitle className="text-[15px]">
-              On-device locations
-            </DialogTitle>
+            <DialogTitle className="text-[15px]">On-device locations</DialogTitle>
             <DialogDescription className="sr-only">
-              Hugging Face model folders, GGUF files, and adapters are indexed
-              here.
+              Hugging Face model folders, GGUF files, and adapters are indexed here.
             </DialogDescription>
           </DialogHeader>
 
@@ -347,7 +342,9 @@ export function OnDeviceFoldersDialog({
                           </p>
                           <Tooltip>
                             <TooltipTrigger asChild={true}>
-                              <p className="block w-full truncate font-mono text-[10.5px] text-muted-foreground">
+                              <p
+                                className="block w-full truncate font-mono text-[10.5px] text-muted-foreground"
+                              >
                                 {folder.path}
                               </p>
                             </TooltipTrigger>
@@ -375,10 +372,7 @@ export function OnDeviceFoldersDialog({
                                 />
                               </button>
                             </TooltipTrigger>
-                            <TooltipContent
-                              side="left"
-                              className="tooltip-compact"
-                            >
+                            <TooltipContent side="left" className="tooltip-compact">
                               Open in file manager
                             </TooltipContent>
                           </Tooltip>
@@ -403,10 +397,7 @@ export function OnDeviceFoldersDialog({
                               )}
                             </button>
                           </TooltipTrigger>
-                          <TooltipContent
-                            side="left"
-                            className="tooltip-compact"
-                          >
+                          <TooltipContent side="left" className="tooltip-compact">
                             Remove from list
                           </TooltipContent>
                         </Tooltip>
diff --git a/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts b/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
index 2cea1d8304..da653ddeb7 100644
--- a/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
+++ b/studio/frontend/src/features/hub/download-manager/download-manager-controller.ts
@@ -1,10 +1,14 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import { DOWNLOAD_KIND } from "./constants";
 import {
   createDownloadManagerInitialState,
+  jobKeyOf,
   removeJob,
+  selectActiveJob,
   setState,
+  useDownloadManagerStore,
 } from "./download-manager-state";
 import { resetDownloadApiAdapterState } from "./download-api-adapter";
 import {
@@ -65,6 +69,25 @@ export const downloadManager: DownloadManagerController = {
   dismiss: removeJob,
 };
 
+/** Cancel the in-flight download for a staged model pick. No-op when nothing is
+ *  downloading (e.g. a native/local file that was never fetched). Lets non-React
+ *  callers (the chat store's abandon paths) stop a staged transfer without the
+ *  useRepoDownload hook. */
+export function cancelStagedModelDownload(
+  pending: { id: string; ggufVariant?: string | null } | null,
+): void {
+  if (!pending) return;
+  const variant = pending.ggufVariant ?? null;
+  const activeJob = selectActiveJob(
+    useDownloadManagerStore.getState(),
+    DOWNLOAD_KIND.MODEL,
+    pending.id,
+    variant,
+  );
+  void downloadManager.cancel(
+    activeJob?.key ?? jobKeyOf(DOWNLOAD_KIND.MODEL, pending.id, variant),
+  );
+}
 
 if (import.meta.hot) {
   import.meta.hot.dispose(() => {
diff --git a/studio/frontend/src/features/hub/download-manager/index.ts b/studio/frontend/src/features/hub/download-manager/index.ts
index 60ef3851f8..dd88aaf3f0 100644
--- a/studio/frontend/src/features/hub/download-manager/index.ts
+++ b/studio/frontend/src/features/hub/download-manager/index.ts
@@ -20,6 +20,7 @@ export {
 } from "./constants";
 export {
   __resetDownloadManagerForTests,
+  cancelStagedModelDownload,
   clearCompletedInventoryHint,
   downloadManager,
   hydrateDownloadManager,
diff --git a/studio/frontend/src/features/hub/hub-page.tsx b/studio/frontend/src/features/hub/hub-page.tsx
index 222a74322e..630daa48ad 100644
--- a/studio/frontend/src/features/hub/hub-page.tsx
+++ b/studio/frontend/src/features/hub/hub-page.tsx
@@ -1,32 +1,34 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import {
+  loadRememberedLoadSettings,
+  rememberedLoadSettingsKey,
+} from "@/components/assistant-ui/model-selector/remembered-load-settings";
+import { hfModelFitsDevice } from "@/components/assistant-ui/model-selector/recommended-fit";
+import { useHubInventory } from "@/features/hub/inventory";
+import { useDebouncedValue } from "@/hooks/use-debounced-value";
+import { useGpuInfo } from "@/hooks/use-gpu-info";
+import {
+  type HfModelSearchChannel,
+  type HfSortDirection,
+  type HfSortKey,
+} from "@/features/hub/hooks/use-hub-model-search";
+import { useOnlineStatus } from "@/features/hub/hooks/use-online-status";
+import { useHubInfiniteScroll } from "@/features/hub/hooks/use-hub-infinite-scroll";
+import { ggufVariantsMatch, modelIdsMatch } from "@/features/hub/lib/model-identity";
+import { cn } from "@/lib/utils";
 import { usePlatformStore } from "@/config/env";
+import {
+  hfApiToken,
+  useHfTokenStore,
+} from "@/features/hub/stores/hf-token-store";
 import {
   getInferenceStatus,
   isExternalModelId,
   useChatModelRuntime,
   useChatRuntimeStore,
 } from "@/features/chat";
-import { useHubInventory } from "@/features/hub";
-import type {
-  HfModelSearchChannel,
-  HfSortDirection,
-  HfSortKey,
-} from "@/features/hub";
-import { useOnlineStatus } from "@/features/hub";
-import { useHubInfiniteScroll } from "@/features/hub";
-import { ggufVariantsMatch, modelIdsMatch } from "@/features/hub";
-import { hfApiToken, useHfTokenStore } from "@/features/hub";
-import {
-  applyModelLoadConfigToRuntime,
-  currentRuntimePerModelConfig,
-  hfModelFitsDevice,
-  resolveInitialConfig,
-} from "@/features/model-picker";
-import { useDebouncedValue } from "@/hooks/use-debounced-value";
-import { useGpuInfo } from "@/hooks/use-gpu-info";
-import { cn } from "@/lib/utils";
 import { useNavigate, useSearch } from "@tanstack/react-router";
 import {
   useCallback,
@@ -36,17 +38,10 @@ import {
   useRef,
   useState,
 } from "react";
-import { ExternalLinkConfirmDialog } from "./catalog/external-link-confirm-dialog";
 import { HubDetailView } from "./catalog/hub-detail-view";
-import { HubFeed } from "./catalog/hub-feed";
 import { HubTopBar } from "./catalog/hub-top-bar";
-import {
-  ModelsCatalog,
-  type ModelsCatalogHandlers,
-  type ModelsCatalogPagination,
-  type ModelsCatalogState,
-} from "./catalog/models-catalog";
-import { ModelsHeader } from "./catalog/models-header";
+import { HubFeed } from "./catalog/hub-feed";
+import { OwnerScopeToggle } from "./catalog/owner-scope-toggle";
 import {
   type AllModelsView,
   HubListHeader,
@@ -54,9 +49,16 @@ import {
   InventorySortControl,
   ResultListHeader,
 } from "./catalog/models-table";
+import {
+  ModelsCatalog,
+  type ModelsCatalogHandlers,
+  type ModelsCatalogPagination,
+  type ModelsCatalogState,
+} from "./catalog/models-catalog";
+import { ModelsHeader } from "./catalog/models-header";
 import { ModelsToolbar } from "./catalog/models-toolbar";
+import { ExternalLinkConfirmDialog } from "./catalog/external-link-confirm-dialog";
 import { OnDeviceFoldersDialog } from "./catalog/on-device-folders-dialog";
-import { OwnerScopeToggle } from "./catalog/owner-scope-toggle";
 import { useDiscoverSearch } from "./hooks/use-discover-search";
 import { useFeedWriteBack } from "./hooks/use-feed-write-back";
 import { useHubFeed } from "./hooks/use-hub-feed";
@@ -566,15 +568,15 @@ export function ModelsPage() {
   const deferredCapabilityFilter = useDeferredValue(capabilityFilter);
 
   const hasQuery = deferredDebouncedQuery.trim() !== "";
-  const mode: DiscoverMode = isModelDiscover
-    ? hasQuery
+  const mode: DiscoverMode = !isModelDiscover
+    ? "search"
+    : hasQuery
       ? "search"
       : urlSection != null
         ? "channel-list"
         : sortBrowseActive
           ? "search"
-          : "feed"
-    : "search";
+          : "feed";
   const isFeedMode = mode === "feed";
   const isChannelListMode = mode === "channel-list";
   const isSortBrowseMode =
@@ -765,10 +767,7 @@ export function ModelsPage() {
     }
     return merged;
   }, [isFeedMode, feedTrendingRows, filteredDiscoverRows]);
-  const feedResults = useMemo(
-    () => feedRows.map((row) => row.result),
-    [feedRows],
-  );
+  const feedResults = useMemo(() => feedRows.map((row) => row.result), [feedRows]);
   const selectionDiscoverRows = isFeedMode ? feedRows : discoverRows;
   const selectionFilteredDiscoverRows = isFeedMode
     ? feedRows
@@ -1109,22 +1108,50 @@ export function ModelsPage() {
     (opts: ModelLoadOptions, isDownloaded: boolean) => {
       if (!selectedModel) return;
       const runId = selectedModel.resource.runId;
-      const resolvedConfig = resolveInitialConfig(runId, opts.ggufVariant);
-      const rememberedConfig = resolvedConfig.remembered
-        ? resolvedConfig.config
-        : null;
-      const previousConfig = currentRuntimePerModelConfig({
-        includeMaxSeqLength: true,
-      });
-      const hasAppliedConfig = applyModelLoadConfigToRuntime(rememberedConfig);
+      // "Load on selection" off: stage GGUF picks instead of loading, so the
+      // chat page's staging flow can read the header and show the load options.
+      // Non-GGUF models have nothing to configure pre-load, so they load now.
+      if (
+        !useChatRuntimeStore.getState().loadOnSelection &&
+        (opts.ggufVariant != null || selectedModel.isGguf)
+      ) {
+        useChatRuntimeStore.getState().stageModel({
+          id: runId,
+          ggufVariant: opts.ggufVariant,
+          isGguf: selectedModel.isGguf,
+          isDownloaded,
+          expectedBytes: opts.expectedBytes,
+        });
+        openNewChat();
+        return;
+      }
+      // Detach any leftover staged pick first so its edited knobs (e.g. a custom
+      // context length) don't leak into this load -- mirrors the chat page's
+      // detachStaged(); keepDownload keeps any staged download running.
+      useChatRuntimeStore.getState().abandonStagedModel({ keepDownload: true });
+      // Load-on-selection skips the chat sheet, so seed this GGUF pick's saved
+      // load knobs here the way the sheet's restore effect would; otherwise the
+      // remembered config is silently ignored on the Hub run path. keepSpeculative
+      // then honors the restored speculative choice across the switch.
+      const remembered =
+        opts.ggufVariant != null || selectedModel.isGguf
+          ? loadRememberedLoadSettings(
+              rememberedLoadSettingsKey({
+                id: runId,
+                ggufVariant: opts.ggufVariant,
+              }),
+            )
+          : null;
+      if (remembered) {
+        useChatRuntimeStore.getState().applyRememberedLoadSettings(remembered);
+      }
       void selectModel({
         id: runId,
         ggufVariant: opts.ggufVariant,
         isDownloaded,
         expectedBytes: opts.expectedBytes,
-        keepSpeculative: hasAppliedConfig,
+        keepSpeculative: remembered != null,
         throwOnError: true,
-        previousConfig,
       })
         .then(() => {
           // Read fresh: the load is async, so the checkpoint may have changed.
@@ -1348,18 +1375,16 @@ export function ModelsPage() {
         </div>
       );
     }
-    const ownerToggle = isDatasetMode ? undefined : (
+    const ownerToggle = !isDatasetMode ? (
       <OwnerScopeToggle value={ownerScope} onChange={setOwnerScope} />
-    );
+    ) : undefined;
     // Compact pill so it stays beside the view-mode tabs even in the narrow
     // split pane instead of dropping to its own row.
     return (
       <div className="flex flex-col gap-3 pt-6">
         {isChannelListMode ? (
           <HubListHeader
-            title={
-              channelSection ? HUB_SECTION_TITLE[channelSection] : "Models"
-            }
+            title={channelSection ? HUB_SECTION_TITLE[channelSection] : "Models"}
             count={listCount}
             view={allModelsView}
             onViewChange={setAllModelsView}
diff --git a/studio/frontend/src/features/hub/index.ts b/studio/frontend/src/features/hub/index.ts
index 8a2c0e863b..3515f6ca76 100644
--- a/studio/frontend/src/features/hub/index.ts
+++ b/studio/frontend/src/features/hub/index.ts
@@ -1,65 +1,9 @@
 // SPDX-License-Identifier: AGPL-3.0-only
 // Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
-export {
-  cancelModelDownload,
-  downloadManager,
-  jobKeyOf,
-  subscribeJobListeners,
-  useDownloadManagerStore,
-  type TransportConflictInfo,
-} from "./download-manager";
-export {
-  useHubInventory,
-  type CachedInventoryRow,
-  type GgufVariantDetail,
-  type HubInventory,
-  type HubInventoryKind,
-  type InventoryRow,
-  type LocalInventoryRow,
-  type LocalSource,
-  type ScanFolderInfo,
-  addScanFolder,
-  deleteCachedDataset,
-  deleteCachedModel,
-  formatLocalUpdated,
-  listGgufVariants,
-  listScanFolders,
-  removeScanFolder,
-  useGgufVariantsCacheVersion,
-} from "./inventory";
-export {
-  type HfModelResult,
-  type HfModelSearchChannel,
-  type HfSortDirection,
-  type HfSortKey,
-  useHubModelSearch,
-} from "./hooks/use-hub-model-search";
-export { useOnlineStatus } from "./hooks/use-online-status";
-export { useHubInfiniteScroll } from "./hooks/use-hub-infinite-scroll";
+export { cancelStagedModelDownload } from "./download-manager";
 export {
   getHfToken,
-  hfApiToken,
   mirrorHfTokenInto,
   useHfTokenStore,
 } from "./stores/hf-token-store";
-export { looksLikeLocalPath } from "./lib/local-path";
-export { hubTokenHeader } from "./lib/hub-token-header";
-export {
-  ggufVariantsMatch,
-  modelIdsMatch,
-  normalizeGgufVariantIdentity,
-  normalizeModelIdentity,
-} from "./lib/model-identity";
-export { formatBytes, formatRelativeShort } from "./lib/format";
-export { ggufVariantDisplayLabel } from "./lib/gguf-variant-sort";
-export {
-  DeleteConfirmDialog,
-  UpdateConfirmDialog,
-} from "./catalog/download-card";
-export { HubOptionMenu, type HubOption } from "./catalog/hub-option-menu";
-export { DotTag } from "./catalog/dot-tag";
-export { TransportConflictDialog } from "./catalog/transport-conflict-dialog";
-export { TrainIcon } from "./components/train-icon";
-export { isHiddenModelId } from "./lib/hidden-models";
-export { classifyUnslothSupport } from "./lib/unsloth-support";
diff --git a/studio/frontend/src/features/hub/inventory/api.ts b/studio/frontend/src/features/hub/inventory/api.ts
index 8c9214c9e5..0e01c5c0cb 100644
--- a/studio/frontend/src/features/hub/inventory/api.ts
+++ b/studio/frontend/src/features/hub/inventory/api.ts
@@ -48,7 +48,6 @@ export interface CachedGgufRepo {
   capabilities?: BackendModelCapabilities | null;
   size_bytes: number;
   cache_path?: string;
-  last_modified?: number | null;
   partial?: boolean;
   partial_transport?: string | null;
   pipeline_tag?: string | null;
@@ -66,7 +65,6 @@ export interface CachedModelRepo {
   capabilities?: BackendModelCapabilities | null;
   size_bytes: number;
   cache_path?: string;
-  last_modified?: number | null;
   partial?: boolean;
   partial_transport?: string | null;
   pipeline_tag?: string | null;
diff --git a/studio/frontend/src/features/hub/inventory/types.ts b/studio/frontend/src/features/hub/inventory/types.ts
index d53d7003fb..c86ffb1d86 100644
--- a/studio/frontend/src/features/hub/inventory/types.ts
+++ b/studio/frontend/src/features/hub/inventory/types.ts
@@ -47,7 +47,6 @@ export interface CachedInventoryRow {
   capabilities: ModelInventoryCapabilities;
   bytes: number;
   cachePath?: string | null;
-  lastModified?: number | null;
   partial?: boolean;
   partialTransport?: string | null;
   pipelineTag?: string | null;
@@ -66,8 +65,6 @@ export interface LocalInventoryRow {
   title: string;
   source: LocalSource;
   sourceLabel: string;
-  modelId?: string | null;
-  displayName?: string;
   path: string;
   isGguf: boolean;
   modelFormat: ModelInventoryFormat;
diff --git a/studio/frontend/src/features/hub/inventory/view-models.ts b/studio/frontend/src/features/hub/inventory/view-models.ts
index 58de6e4c32..63d70418be 100644
--- a/studio/frontend/src/features/hub/inventory/view-models.ts
+++ b/studio/frontend/src/features/hub/inventory/view-models.ts
@@ -176,7 +176,6 @@ export function buildCachedInventoryRow(
     runtime?: string | null;
     format_variant?: string | null;
     capabilities?: BackendModelCapabilities | null;
-    last_modified?: number | null;
   },
   fallbackFormat: ModelInventoryFormat,
 ): CachedInventoryRow {
@@ -211,12 +210,6 @@ export function buildCachedInventoryRow(
     ),
     bytes: row.size_bytes,
     cachePath: row.cache_path ?? null,
-    lastModified:
-      typeof row.last_modified === "number" &&
-      Number.isFinite(row.last_modified) &&
-      row.last_modified > 0
-        ? row.last_modified
-        : null,
     partial: row.partial ?? false,
     partialTransport: row.partial_transport ?? null,
     pipelineTag: row.pipeline_tag ?? null,
@@ -279,8 +272,6 @@ export function buildLocalInventoryRows(
         title,
         source: model.source,
         sourceLabel: localSourceLabel(model.source),
-        modelId: model.model_id ?? null,
-        displayName: model.display_name,
         path: model.path,
         isGguf: modelFormat === "gguf",
         modelFormat,
diff --git a/studio/frontend/src/features/model-picker/api/model-metadata.ts b/studio/frontend/src/features/model-picker/api/model-metadata.ts
deleted file mode 100644
index 098ab51271..0000000000
--- a/studio/frontend/src/features/model-picker/api/model-metadata.ts
+++ /dev/null
@@ -1,20 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { getModelConfig } from "@/features/training";
-
-export async function fetchModelMaxPositionEmbeddings(
-  modelName: string,
-  hfToken?: string | null,
-  signal?: AbortSignal,
-): Promise<number | null> {
-  const config = await getModelConfig(
-    modelName,
-    signal,
-    hfToken?.trim() || undefined,
-  );
-  const value = config.max_position_embeddings;
-  return typeof value === "number" && Number.isFinite(value) && value > 0
-    ? Math.floor(value)
-    : null;
-}
diff --git a/studio/frontend/src/features/model-picker/api/templates.ts b/studio/frontend/src/features/model-picker/api/templates.ts
deleted file mode 100644
index 0f00556f3f..0000000000
--- a/studio/frontend/src/features/model-picker/api/templates.ts
+++ /dev/null
@@ -1,51 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { authFetch } from "@/features/auth";
-import { hubTokenHeader } from "@/features/hub";
-import { readFastApiError } from "@/lib/format-fastapi-error";
-
-export interface ValidateChatTemplateResult {
-  valid: boolean;
-  error: string | null;
-}
-
-async function parseJsonOrThrow<T>(response: Response): Promise<T> {
-  if (!response.ok) {
-    throw new Error(await readFastApiError(response));
-  }
-  return response.json();
-}
-
-export async function validateChatTemplate(
-  template: string,
-  signal?: AbortSignal,
-): Promise<ValidateChatTemplateResult> {
-  const response = await authFetch("/api/picker/validate-chat-template", {
-    method: "POST",
-    headers: { "Content-Type": "application/json" },
-    body: JSON.stringify({ template }),
-    signal,
-  });
-  return parseJsonOrThrow<ValidateChatTemplateResult>(response);
-}
-
-export async function fetchDefaultChatTemplate(
-  modelName: string,
-  ggufVariant?: string | null,
-  hfToken?: string | null,
-  signal?: AbortSignal,
-): Promise<string | null> {
-  const query = ggufVariant
-    ? `?gguf_variant=${encodeURIComponent(ggufVariant)}`
-    : "";
-  const response = await authFetch(
-    `/api/picker/chat-template/${encodeURIComponent(modelName)}${query}`,
-    { headers: hubTokenHeader(hfToken), signal },
-  );
-  const data = await parseJsonOrThrow<{
-    model_name: string;
-    chat_template: string | null;
-  }>(response);
-  return data.chat_template ?? null;
-}
diff --git a/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx b/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
deleted file mode 100644
index 65e5a2026d..0000000000
--- a/studio/frontend/src/features/model-picker/components/chat-template-editor-dialog.tsx
+++ /dev/null
@@ -1,191 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { Button } from "@/components/ui/button";
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogFooter,
-  DialogHeader,
-  DialogTitle,
-} from "@/components/ui/dialog";
-import { Spinner } from "@/components/ui/spinner";
-import { Textarea } from "@/components/ui/textarea";
-import { useRef, useState } from "react";
-import { validateChatTemplate } from "../api/templates";
-import {
-  MAX_CHAT_TEMPLATE_BYTES,
-  chatTemplateByteLength,
-  isChatTemplateWithinLimit,
-} from "../model-config/per-model-config";
-
-interface ChatTemplateEditorDialogProps {
-  open: boolean;
-  onOpenChange: (open: boolean) => void;
-  value: string | null;
-  defaultTemplate: string | null;
-  defaultLoading: boolean;
-  onSave: (override: string | null) => void;
-  readOnly?: boolean;
-}
-
-export function ChatTemplateEditorDialog({
-  open,
-  onOpenChange,
-  value,
-  defaultTemplate,
-  defaultLoading,
-  onSave,
-  readOnly = false,
-}: ChatTemplateEditorDialogProps) {
-  const [draft, setDraft] = useState<string | null>(null);
-  const [error, setError] = useState<string | null>(null);
-  const [validating, setValidating] = useState(false);
-  // Bumped whenever the dialog closes so a validation still in flight cannot
-  // apply a template the user has already dismissed.
-  const validationToken = useRef(0);
-  const renderedDraft = draft ?? value ?? defaultTemplate ?? "";
-
-  const byteLength = chatTemplateByteLength(renderedDraft);
-  const overLimit = !isChatTemplateWithinLimit(renderedDraft);
-  const matchesDefault =
-    defaultTemplate != null && renderedDraft === defaultTemplate;
-
-  const handleClose = () => {
-    validationToken.current += 1;
-    setDraft(null);
-    setError(null);
-    setValidating(false);
-    onOpenChange(false);
-  };
-
-  const handleSave = async () => {
-    if (renderedDraft.trim().length === 0 || matchesDefault) {
-      onSave(null);
-      handleClose();
-      return;
-    }
-    if (overLimit) {
-      setError("Template exceeds the size limit.");
-      return;
-    }
-    setValidating(true);
-    const token = validationToken.current;
-    try {
-      const result = await validateChatTemplate(renderedDraft);
-      // Dialog was closed (or reopened) while validating; drop the result so a
-      // discarded template is never applied.
-      if (token !== validationToken.current) {
-        return;
-      }
-      if (!result.valid) {
-        setError(result.error ?? "Invalid Jinja template.");
-        return;
-      }
-      onSave(renderedDraft);
-      handleClose();
-    } catch {
-      if (token === validationToken.current) {
-        setError("Could not validate the template.");
-      }
-    } finally {
-      if (token === validationToken.current) {
-        setValidating(false);
-      }
-    }
-  };
-
-  return (
-    <Dialog
-      open={open}
-      onOpenChange={(nextOpen) => {
-        if (nextOpen) {
-          onOpenChange(true);
-          return;
-        }
-        handleClose();
-      }}
-    >
-      <DialogContent className="corner-squircle dialog-soft-surface sm:max-w-3xl">
-        <DialogHeader>
-          <DialogTitle>
-            {readOnly ? "Chat Template" : "Edit Chat Template"}
-          </DialogTitle>
-          <DialogDescription>
-            {readOnly
-              ? "This is the model's chat template. Custom templates apply to GGUF models for now, so it is view only for safetensors models."
-              : "Override the model's chat template with custom Jinja. The change applies when the model loads. Saving an empty template or one that matches the default clears the override."}
-          </DialogDescription>
-        </DialogHeader>
-        <Textarea
-          value={renderedDraft}
-          onChange={(event) => {
-            if (readOnly) return;
-            setDraft(event.target.value);
-            setError(null);
-          }}
-          readOnly={readOnly}
-          className="min-h-[20rem] max-h-[50vh] overflow-y-auto border-0 font-mono text-xs leading-5 corner-squircle focus-visible:ring-0"
-          rows={14}
-          spellCheck={false}
-          placeholder={defaultLoading ? "Loading model default..." : ""}
-        />
-        {readOnly ? null : (
-          <div className="flex items-center justify-between gap-3 px-0.5 text-[11px]">
-            <span
-              className={overLimit ? "text-amber-500" : "text-muted-foreground"}
-            >
-              {byteLength.toLocaleString()} /{" "}
-              {MAX_CHAT_TEMPLATE_BYTES.toLocaleString()} bytes
-            </span>
-            {error ? (
-              <span className="truncate text-red-500" title={error}>
-                {error}
-              </span>
-            ) : null}
-          </div>
-        )}
-        <DialogFooter className="flex-wrap gap-2 sm:justify-between">
-          {readOnly ? (
-            <div className="flex w-full justify-end">
-              <Button type="button" onClick={handleClose}>
-                Close
-              </Button>
-            </div>
-          ) : (
-            <>
-              <Button
-                type="button"
-                variant="ghost"
-                onClick={() => setDraft(defaultTemplate ?? "")}
-                disabled={
-                  defaultLoading || renderedDraft === (defaultTemplate ?? "")
-                }
-                className="text-muted-foreground"
-              >
-                {defaultLoading ? (
-                  <Spinner className="size-3.5" />
-                ) : (
-                  "Reset to default"
-                )}
-              </Button>
-              <div className="flex gap-2">
-                <Button type="button" variant="ghost" onClick={handleClose}>
-                  Cancel
-                </Button>
-                <Button
-                  type="button"
-                  onClick={handleSave}
-                  disabled={validating || overLimit}
-                >
-                  {validating ? "Validating..." : "Save"}
-                </Button>
-              </div>
-            </>
-          )}
-        </DialogFooter>
-      </DialogContent>
-    </Dialog>
-  );
-}
diff --git a/studio/frontend/src/features/model-picker/components/model-config-page.tsx b/studio/frontend/src/features/model-picker/components/model-config-page.tsx
deleted file mode 100644
index 85ce5ccf8d..0000000000
--- a/studio/frontend/src/features/model-picker/components/model-config-page.tsx
+++ /dev/null
@@ -1,742 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { Button } from "@/components/ui/button";
-import { Checkbox } from "@/components/ui/checkbox";
-import { InfoHint } from "@/components/ui/info-hint";
-import {
-  Select,
-  SelectContent,
-  SelectItem,
-  SelectTrigger,
-  SelectValue,
-} from "@/components/ui/select";
-import { Slider } from "@/components/ui/slider";
-import { Switch } from "@/components/ui/switch";
-import {
-  fetchGgufContextLength,
-  readPersistedSpeculativeType,
-  useChatRuntimeStore,
-} from "@/features/chat";
-import { ChevronDownStandardIcon } from "@/lib/chevron-icons";
-import { toast } from "@/lib/toast";
-import { ArrowLeft01Icon } from "@hugeicons/core-free-icons";
-import { HugeiconsIcon } from "@hugeicons/react";
-import { useEffect, useId, useState } from "react";
-import {
-  useDefaultChatTemplate,
-  useModelMaxPositionEmbeddings,
-} from "../hooks/use-model-defaults";
-import { perModelConfigsEqual } from "../model-config/apply-per-model-config";
-import {
-  DEFAULT_PER_MODEL_CONFIG,
-  KV_CACHE_DTYPES,
-  MAX_SEQ_LENGTH_MAX,
-  MAX_SEQ_LENGTH_MIN,
-  MAX_SEQ_LENGTH_STEP,
-  MTP_SPECULATIVE_TYPES,
-  type PerModelConfig,
-  SPECULATIVE_TYPES,
-  deletePerModelConfig,
-  isDefaultConfig,
-  normalizeMaxSeqLength,
-  resolveInitialConfig,
-  savePerModelConfig,
-} from "../model-config/per-model-config";
-import { ChatTemplateEditorDialog } from "./chat-template-editor-dialog";
-import type { ModelPickTarget } from "./model-selector/types";
-import { NumericValueInput } from "./numeric-value-input";
-
-const ROW_CLASS = "flex min-h-8 items-center justify-between gap-3";
-const LABEL_CLASS =
-  "min-w-0 truncate text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg";
-const LABEL_CLASS_WRAP =
-  "min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-nav-fg";
-const CONTROL_SURFACE =
-  "rounded-full border-transparent bg-black/[0.04] dark:bg-white/[0.05] hover:bg-black/[0.06] dark:hover:bg-white/[0.1]";
-const SELECT_TRIGGER_CLASS = `grid h-8 min-w-0 grid-cols-[minmax(0,1fr)_auto] items-center gap-1 ${CONTROL_SURFACE} pl-3 pr-2 py-0 text-[13px]! font-medium text-nav-fg focus-visible:ring-0 focus-visible:border-transparent [&_[data-slot=select-value]]:min-w-0 [&_[data-slot=select-value]]:truncate [&>svg]:shrink-0`;
-const NUMBER_INPUT_CLASS = `h-8 w-[92px] ${CONTROL_SURFACE} pl-3 pr-2 py-0 text-right text-[13px] font-medium text-nav-fg outline-none focus-visible:ring-0`;
-
-const KV_CACHE_DTYPE_DEFAULT = "f16";
-const SPECULATIVE_TYPE_LABELS: Record<(typeof SPECULATIVE_TYPES)[number], string> =
-  {
-    auto: "Auto",
-    mtp: "MTP",
-    ngram: "Ngram",
-    "mtp+ngram": "MTP+Ngram",
-    off: "Off",
-  };
-
-function hasNonDefaultAdvanced(config: PerModelConfig): boolean {
-  return (
-    config.kvCacheDtype != null ||
-    (config.speculativeType ?? "auto") !== "auto" ||
-    config.specDraftNMax != null ||
-    config.tensorParallel ||
-    config.chatTemplateOverride != null
-  );
-}
-
-function resolveCustomContextLength(
-  value: number,
-  native: number | null,
-): number | null {
-  return native != null && value === native ? null : value;
-}
-
-function ChatTemplateSetting({
-  config,
-  onEditTemplate,
-  readOnly = false,
-}: {
-  config: PerModelConfig;
-  onEditTemplate: () => void;
-  readOnly?: boolean;
-}) {
-  return (
-    <div className={ROW_CLASS}>
-      <div className="flex min-w-0 items-center gap-1.5">
-        <span className={LABEL_CLASS}>Chat Template</span>
-        <InfoHint>
-          {readOnly
-            ? "Preview the model's chat template. Custom overrides apply to GGUF models for now."
-            : "Override the model's chat template with custom Jinja. Applies when the model loads."}
-        </InfoHint>
-      </div>
-      <div className="flex shrink-0 items-center gap-2">
-        {readOnly ? null : (
-          <span className="text-[12px] text-muted-foreground">
-            {config.chatTemplateOverride ? "Custom" : "Default"}
-          </span>
-        )}
-        <Button
-          type="button"
-          size="sm"
-          variant="ghost"
-          className={`h-8 px-3 text-[13px] ${CONTROL_SURFACE}`}
-          onClick={onEditTemplate}
-        >
-          {readOnly ? "View" : "Edit"}
-        </Button>
-      </div>
-    </div>
-  );
-}
-
-function MaxSeqLengthSetting({
-  value,
-  max,
-  inputMax,
-  onChange,
-}: {
-  value: number;
-  max: number;
-  inputMax: number;
-  onChange: (value: number) => void;
-}) {
-  return (
-    <div className="space-y-3">
-      <div className={ROW_CLASS}>
-        <div className="flex min-w-0 items-center gap-1.5">
-          <span className={LABEL_CLASS}>Max Seq Length</span>
-          <InfoHint>
-            Maximum context window size in tokens. Applies when the model loads.
-          </InfoHint>
-        </div>
-        <NumericValueInput
-          value={value}
-          min={MAX_SEQ_LENGTH_MIN}
-          max={inputMax}
-          step={MAX_SEQ_LENGTH_STEP}
-          onChange={onChange}
-          ariaLabel="Max Seq Length"
-          className={NUMBER_INPUT_CLASS}
-          size={8}
-        />
-      </div>
-      <Slider
-        min={MAX_SEQ_LENGTH_MIN}
-        max={max}
-        step={MAX_SEQ_LENGTH_STEP}
-        value={[value]}
-        onValueChange={([next]) => onChange(next)}
-        className="panel-slider"
-        aria-label="Max Seq Length"
-      />
-    </div>
-  );
-}
-
-function clampMaxSeqLength(value: number, max: number): number {
-  const normalized = normalizeMaxSeqLength(value) ?? MAX_SEQ_LENGTH_MIN;
-  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(max, normalized));
-}
-
-function GgufAdvancedSettings({
-  config,
-  update,
-  isMtp,
-  speculativeFallback,
-  onEditTemplate,
-}: {
-  config: PerModelConfig;
-  update: (patch: Partial<PerModelConfig>) => void;
-  isMtp: boolean;
-  speculativeFallback: string;
-  onEditTemplate: () => void;
-}) {
-  return (
-    <>
-      <div className={ROW_CLASS}>
-        <div className="flex min-w-0 items-center gap-1.5">
-          <span className={LABEL_CLASS}>KV Cache Dtype</span>
-          <InfoHint>
-            Lower KV cache precision to save VRAM at the cost of some quality.
-            f16/bf16 are full precision; q8_0/q5_1/q4_1 are quantized.
-          </InfoHint>
-        </div>
-        <Select
-          value={config.kvCacheDtype ?? KV_CACHE_DTYPE_DEFAULT}
-          onValueChange={(v) =>
-            update({ kvCacheDtype: v === KV_CACHE_DTYPE_DEFAULT ? null : v })
-          }
-        >
-          <SelectTrigger
-            animateRadius={false}
-            icon={ChevronDownStandardIcon}
-            iconClassName="size-3.5"
-            className={`w-[92px] ${SELECT_TRIGGER_CLASS}`}
-          >
-            <SelectValue />
-          </SelectTrigger>
-          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-            <SelectItem value={KV_CACHE_DTYPE_DEFAULT}>
-              {KV_CACHE_DTYPE_DEFAULT}
-            </SelectItem>
-            {KV_CACHE_DTYPES.map((dtype) => (
-              <SelectItem key={dtype} value={dtype}>
-                {dtype}
-              </SelectItem>
-            ))}
-          </SelectContent>
-        </Select>
-      </div>
-
-      <div className={ROW_CLASS}>
-        <div className="flex min-w-0 items-center gap-1.5">
-          <span className={LABEL_CLASS_WRAP}>Speculative Decoding</span>
-          <InfoHint>
-            Faster generation with no accuracy hit. Auto picks MTP / ngram based
-            on the model and platform. Pick a strategy to force it.
-          </InfoHint>
-        </div>
-        <Select
-          value={config.speculativeType ?? speculativeFallback}
-          onValueChange={(v) =>
-            update({
-              speculativeType: v,
-              specDraftNMax:
-                v === "mtp" || v === "mtp+ngram" ? config.specDraftNMax : null,
-            })
-          }
-        >
-          <SelectTrigger
-            animateRadius={false}
-            icon={ChevronDownStandardIcon}
-            iconClassName="size-3.5"
-            className={`w-[124px] shrink-0 ${SELECT_TRIGGER_CLASS}`}
-          >
-            <SelectValue />
-          </SelectTrigger>
-          <SelectContent className="menu-soft-surface ring-0 border-0 rounded-lg">
-            {SPECULATIVE_TYPES.map((type) => (
-              <SelectItem key={type} value={type}>
-                {SPECULATIVE_TYPE_LABELS[type]}
-              </SelectItem>
-            ))}
-          </SelectContent>
-        </Select>
-      </div>
-
-      {isMtp && (
-        <div className={ROW_CLASS}>
-          <div className="flex min-w-0 items-center gap-1.5">
-            <span className={LABEL_CLASS}>Draft Tokens</span>
-            <InfoHint>
-              Max MTP draft tokens per step. Leave blank for the platform
-              default (2 on GPU, 3 on CPU/Mac).
-            </InfoHint>
-          </div>
-          <input
-            type="number"
-            min={1}
-            max={16}
-            step={1}
-            value={config.specDraftNMax ?? ""}
-            placeholder="auto"
-            onChange={(event) => {
-              const raw = event.target.value;
-              if (raw === "") {
-                update({ specDraftNMax: null });
-                return;
-              }
-              const parsed = Number.parseInt(raw, 10);
-              if (Number.isFinite(parsed)) {
-                update({ specDraftNMax: Math.max(1, Math.min(16, parsed)) });
-              }
-            }}
-            aria-label="Speculative decoding draft tokens"
-            className={NUMBER_INPUT_CLASS}
-          />
-        </div>
-      )}
-
-      <div className={ROW_CLASS}>
-        <div className="flex min-w-0 items-center gap-1.5">
-          <span className={LABEL_CLASS}>Tensor Parallelism</span>
-          <InfoHint>
-            No effect on a single GPU. On multi-GPU setups, improves tokens/sec
-            for dense models. MoE models don't benefit.
-          </InfoHint>
-        </div>
-        <Switch
-          className="panel-switch shrink-0"
-          checked={config.tensorParallel}
-          onCheckedChange={(checked) => update({ tensorParallel: checked })}
-        />
-      </div>
-
-      <ChatTemplateSetting config={config} onEditTemplate={onEditTemplate} />
-    </>
-  );
-}
-
-interface ModelConfigPageProps {
-  target: ModelPickTarget;
-  onBack?: () => void;
-  onRun: (config: PerModelConfig) => void;
-  loadedConfig?: PerModelConfig | null;
-  loadedContextLength?: number | null;
-  initialConfig?: PerModelConfig | null;
-  variant?: "page" | "sidebar";
-}
-
-export function ModelConfigPage({
-  target,
-  onBack,
-  onRun,
-  loadedConfig = null,
-  loadedContextLength = null,
-  initialConfig = null,
-  variant = "page",
-}: ModelConfigPageProps) {
-  const rememberId = useId();
-  const isActiveModel = loadedConfig != null;
-  const runtimeMaxSeqLength = useChatRuntimeStore((s) => s.params.maxSeqLength);
-  const hfToken = useChatRuntimeStore((s) => s.hfToken);
-  const loadedDefaultChatTemplate = useChatRuntimeStore(
-    (s) => s.defaultChatTemplate,
-  );
-  const loadedMaxContextLength = useChatRuntimeStore(
-    (s) => s.ggufMaxContextLength,
-  );
-  // Only the active model seeds its max sequence length from the loaded
-  // runtime params. A different, unloaded model with no saved config seeds the
-  // app default instead, so opening its settings and loading does not inherit
-  // the currently loaded model's context.
-  const [initialMaxSeqLength] = useState(() =>
-    isActiveModel ? (normalizeMaxSeqLength(runtimeMaxSeqLength) ?? 4096) : 4096,
-  );
-  const resolveInitial = () => {
-    const resolved = resolveInitialConfig(target.id, target.ggufVariant);
-    if (loadedConfig) {
-      return { config: loadedConfig, remembered: resolved.remembered };
-    }
-    if (initialConfig) {
-      return {
-        config: initialConfig,
-        remembered:
-          resolved.remembered &&
-          perModelConfigsEqual(initialConfig, resolved.config),
-      };
-    }
-    return resolved;
-  };
-  const [initial] = useState(resolveInitial);
-  const [config, setConfig] = useState<PerModelConfig>(() => initial.config);
-  const [remember, setRemember] = useState(() => initial.remembered);
-  const [savedRemember, setSavedRemember] = useState(() => initial.remembered);
-  const [speculativeFallback] = useState(readPersistedSpeculativeType);
-  const [templateOpen, setTemplateOpen] = useState(false);
-  const [showAdvanced, setShowAdvanced] = useState(() =>
-    hasNonDefaultAdvanced(config),
-  );
-  const templateDefaults = useDefaultChatTemplate(
-    target.id,
-    target.ggufVariant,
-    templateOpen,
-  );
-  const modelMaxPosition = useModelMaxPositionEmbeddings(
-    target.id,
-    !target.isGguf,
-  );
-  const hasLoadedDefaultTemplate =
-    isActiveModel && loadedDefaultChatTemplate != null;
-  const resolvedDefaultTemplate = hasLoadedDefaultTemplate
-    ? loadedDefaultChatTemplate
-    : templateDefaults.template;
-  const resolvedDefaultLoading = hasLoadedDefaultTemplate
-    ? false
-    : templateDefaults.loading;
-
-  const update = (patch: Partial<PerModelConfig>) =>
-    setConfig((current) => ({ ...current, ...patch }));
-
-  const contextFetchKey =
-    target.isGguf && target.meta.contextLength == null
-      ? `${target.id}\n${target.ggufVariant ?? ""}\n${hfToken || ""}`
-      : null;
-  const [fetchedContextLength, setFetchedContextLength] = useState<{
-    key: string;
-    value: number | null;
-  } | null>(null);
-  useEffect(() => {
-    if (contextFetchKey == null) {
-      return;
-    }
-    let cancelled = false;
-    void fetchGgufContextLength({
-      model_path: target.id,
-      gguf_variant: target.ggufVariant ?? null,
-      hf_token: hfToken || null,
-    })
-      .then((contextLength) => {
-        if (!cancelled) {
-          setFetchedContextLength({
-            key: contextFetchKey,
-            value: contextLength,
-          });
-        }
-      })
-      .catch(() => {
-        if (!cancelled) {
-          setFetchedContextLength({ key: contextFetchKey, value: null });
-        }
-      });
-    return () => {
-      cancelled = true;
-    };
-  }, [contextFetchKey, target.id, target.ggufVariant, hfToken]);
-
-  const isMtp =
-    config.speculativeType != null &&
-    MTP_SPECULATIVE_TYPES.has(config.speculativeType);
-  const nativeContextLength =
-    target.meta.contextLength ??
-    (fetchedContextLength?.key === contextFetchKey
-      ? fetchedContextLength.value
-      : null);
-  const activeLoadedContext =
-    isActiveModel && target.isGguf ? loadedContextLength : null;
-  const minContext = 128;
-  const maxContext = Math.max(
-    minContext,
-    Math.max(
-      nativeContextLength ?? 0,
-      activeLoadedContext ?? 0,
-      config.customContextLength ?? 0,
-    ) || 32768,
-  );
-  const contextValue = Math.min(
-    Math.max(
-      config.customContextLength ??
-        activeLoadedContext ??
-        nativeContextLength ??
-        maxContext,
-      minContext,
-    ),
-    maxContext,
-  );
-  const setContextLength = (v: number) =>
-    update({
-      customContextLength:
-        nativeContextLength != null && v === nativeContextLength ? null : v,
-    });
-  const baseline = loadedConfig ?? DEFAULT_PER_MODEL_CONFIG;
-  const atBaseline = perModelConfigsEqual(config, baseline);
-  const contextAtDefault =
-    !target.isGguf ||
-    (nativeContextLength == null
-      ? config.customContextLength == null
-      : contextValue === nativeContextLength);
-  const atDefault =
-    contextAtDefault &&
-    perModelConfigsEqual(
-      { ...config, customContextLength: null },
-      DEFAULT_PER_MODEL_CONFIG,
-    );
-  const nativeMaxSeqLength =
-    normalizeMaxSeqLength(modelMaxPosition.maxPositionEmbeddings) ??
-    MAX_SEQ_LENGTH_MAX;
-  const maxSeqLengthValue =
-    normalizeMaxSeqLength(config.maxSeqLength) ??
-    clampMaxSeqLength(initialMaxSeqLength, nativeMaxSeqLength);
-  const maxSeqLengthMax = Math.max(nativeMaxSeqLength, maxSeqLengthValue);
-  const runtimeConfig = target.isGguf
-    ? {
-        ...config,
-        // Persist the user's intent collapsed against native (not the loaded
-        // context, which equals the override): an explicit sub-native value is
-        // kept, "at native" becomes null. null stays null (auto/VRAM-fit).
-        customContextLength:
-          config.customContextLength == null
-            ? null
-            : resolveCustomContextLength(
-                config.customContextLength,
-                nativeContextLength,
-              ),
-      }
-    : {
-        ...config,
-        maxSeqLength: maxSeqLengthValue,
-      };
-  const rememberChanged = remember !== savedRemember;
-  const persistenceOnly = isActiveModel && atBaseline && rememberChanged;
-  const primaryActionLabel = persistenceOnly
-    ? remember
-      ? "Save settings"
-      : "Forget settings"
-    : isActiveModel
-      ? "Reload model"
-      : "Load model";
-
-  const handleRun = () => {
-    const defaultConfig = isDefaultConfig(runtimeConfig);
-    let saveFailed = false;
-    if (remember) {
-      saveFailed = !savePerModelConfig(
-        target.id,
-        target.ggufVariant,
-        runtimeConfig,
-      );
-    } else {
-      saveFailed = !deletePerModelConfig(target.id, target.ggufVariant);
-    }
-    if (persistenceOnly) {
-      if (saveFailed) {
-        toast.error("Couldn't save settings for this model.");
-        return;
-      }
-      const nextRemember = remember && !defaultConfig;
-      setSavedRemember(nextRemember);
-      setRemember(nextRemember);
-      toast.success(
-        nextRemember
-          ? "Settings saved."
-          : remember
-            ? "Default settings kept."
-            : "Settings forgotten.",
-      );
-      return;
-    }
-    if (saveFailed) {
-      toast.error("Couldn't save these settings, loading with them anyway.");
-    }
-    onRun(runtimeConfig);
-  };
-
-  return (
-    <div className="flex flex-col">
-      {variant === "page" && (
-        <div className="flex items-center gap-2.5 pb-4">
-          {onBack && (
-            <button
-              type="button"
-              onClick={onBack}
-              className="nav-icon-btn shrink-0 text-nav-icon-idle hover:bg-panel-surface-hover hover:text-black dark:hover:text-white"
-              aria-label="Back to model list"
-            >
-              <HugeiconsIcon
-                icon={ArrowLeft01Icon}
-                className="size-4"
-                strokeWidth={1.75}
-              />
-            </button>
-          )}
-          <div className="min-w-0 flex-1">
-            <div className="text-[10px] font-semibold uppercase leading-none tracking-wider text-muted-foreground">
-              Run settings
-            </div>
-            <div className="mt-1.5 truncate text-[14px] font-semibold leading-tight text-nav-fg">
-              {target.displayName}
-            </div>
-          </div>
-        </div>
-      )}
-
-      <div className="space-y-3.5">
-        {target.isGguf && (
-          <>
-            <div className="space-y-3">
-              <div className={ROW_CLASS}>
-                <div className="flex min-w-0 items-center gap-1.5">
-                  <span className={LABEL_CLASS}>Context Length</span>
-                  <InfoHint>
-                    Tokens of context to allocate. Higher uses more VRAM.
-                    {nativeContextLength != null
-                      ? ` This model's native context is ${nativeContextLength.toLocaleString()} tokens.`
-                      : ""}
-                  </InfoHint>
-                </div>
-                <NumericValueInput
-                  value={contextValue}
-                  min={minContext}
-                  max={maxContext}
-                  step={1}
-                  onChange={setContextLength}
-                  ariaLabel="Context Length"
-                  className={NUMBER_INPUT_CLASS}
-                  size={8}
-                />
-              </div>
-              {nativeContextLength != null ? (
-                <Slider
-                  min={minContext}
-                  max={maxContext}
-                  step={128}
-                  value={[contextValue]}
-                  onValueChange={([v]) => setContextLength(v)}
-                  className="panel-slider"
-                  aria-label="Context Length"
-                />
-              ) : null}
-              {isActiveModel &&
-                loadedMaxContextLength != null &&
-                contextValue > loadedMaxContextLength && (
-                  <p className="text-[11px] text-amber-500">
-                    Exceeds estimated VRAM capacity (
-                    {loadedMaxContextLength.toLocaleString()} tokens). The model
-                    may use system RAM.
-                  </p>
-                )}
-            </div>
-
-            {showAdvanced && (
-              <GgufAdvancedSettings
-                config={config}
-                update={update}
-                isMtp={isMtp}
-                speculativeFallback={speculativeFallback}
-                onEditTemplate={() => setTemplateOpen(true)}
-              />
-            )}
-
-            <div className={ROW_CLASS}>
-              <div className="flex min-w-0 items-center gap-1.5">
-                <span className="min-w-0 text-[13px] font-medium leading-[1.25] tracking-nav text-muted-foreground">
-                  Advanced settings
-                </span>
-                <InfoHint>
-                  Extra options for how the model loads. Most setups don't need
-                  these.
-                </InfoHint>
-              </div>
-              <Switch
-                className="panel-switch shrink-0"
-                checked={showAdvanced}
-                onCheckedChange={setShowAdvanced}
-                aria-label="Show advanced settings"
-              />
-            </div>
-          </>
-        )}
-        {!target.isGguf && (
-          <>
-            <MaxSeqLengthSetting
-              value={maxSeqLengthValue}
-              max={maxSeqLengthMax}
-              inputMax={MAX_SEQ_LENGTH_MAX}
-              onChange={(value) =>
-                update({
-                  maxSeqLength: clampMaxSeqLength(value, MAX_SEQ_LENGTH_MAX),
-                })
-              }
-            />
-            <ChatTemplateSetting
-              config={config}
-              onEditTemplate={() => setTemplateOpen(true)}
-              readOnly={true}
-            />
-          </>
-        )}
-      </div>
-
-      <div
-        className={
-          variant === "sidebar"
-            ? "mt-4 flex flex-col gap-3 border-t border-border/60 pt-4"
-            : "mt-4 flex items-center justify-between gap-3 border-t border-border/60 pt-4"
-        }
-      >
-        <div className="flex min-w-0 items-center gap-2">
-          <Checkbox
-            id={rememberId}
-            checked={remember}
-            onCheckedChange={(checked) => setRemember(checked === true)}
-          />
-          <label
-            htmlFor={rememberId}
-            className="cursor-pointer select-none truncate text-[13px] text-nav-fg"
-          >
-            Remember for this model
-          </label>
-        </div>
-        <div
-          className={
-            variant === "sidebar"
-              ? "flex items-center justify-end gap-2"
-              : "flex shrink-0 items-center gap-2"
-          }
-        >
-          <Button
-            type="button"
-            variant="ghost"
-            size="sm"
-            className="h-8"
-            disabled={atDefault}
-            onClick={() =>
-              setConfig({
-                ...DEFAULT_PER_MODEL_CONFIG,
-                customContextLength:
-                  target.isGguf && nativeContextLength != null
-                    ? nativeContextLength
-                    : null,
-              })
-            }
-          >
-            Reset
-          </Button>
-          <Button
-            type="button"
-            size="sm"
-            className="h-8"
-            disabled={isActiveModel && atBaseline && !rememberChanged}
-            onClick={handleRun}
-          >
-            {primaryActionLabel}
-          </Button>
-        </div>
-      </div>
-
-      <ChatTemplateEditorDialog
-        open={templateOpen}
-        onOpenChange={setTemplateOpen}
-        value={config.chatTemplateOverride}
-        defaultTemplate={resolvedDefaultTemplate}
-        defaultLoading={resolvedDefaultLoading}
-        readOnly={!target.isGguf}
-        onSave={(override) => update({ chatTemplateOverride: override })}
-      />
-    </div>
-  );
-}
diff --git a/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx b/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
deleted file mode 100644
index 2489927fc2..0000000000
--- a/studio/frontend/src/features/model-picker/components/numeric-value-input.tsx
+++ /dev/null
@@ -1,113 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { cn } from "@/lib/utils";
-import { useRef, useState } from "react";
-
-export function snapToStep(
-  value: number,
-  step: number,
-  min?: number,
-  max?: number,
-): number {
-  const lo = min ?? Number.NEGATIVE_INFINITY;
-  const hi = max ?? Number.POSITIVE_INFINITY;
-  const clamped = Math.min(Math.max(value, lo), hi);
-  const stepStr = String(step);
-  const decimals = stepStr.includes(".") ? stepStr.split(".")[1].length : 0;
-  const base = Number.isFinite(lo) ? lo : 0;
-  const snapped = base + Math.round((clamped - base) / step) * step;
-  const reclamped = Math.min(Math.max(snapped, lo), hi);
-  return Number(reclamped.toFixed(decimals));
-}
-
-function sanitizeNumeric(raw: string, allowNegative: boolean): string {
-  const sign = allowNegative && raw.startsWith("-") ? "-" : "";
-  const [head, ...rest] = raw.replace(/[^\d.]/g, "").split(".");
-  const tail = rest.length > 0 ? `.${rest.join("")}` : "";
-  return `${sign}${head}${tail}`;
-}
-
-export function NumericValueInput({
-  value,
-  min,
-  max,
-  step,
-  onChange,
-  displayValue,
-  className,
-  ariaLabel,
-  size: sizeAttr,
-  disabled = false,
-}: {
-  value: number;
-  min?: number;
-  max?: number;
-  step: number;
-  onChange: (v: number) => void;
-  displayValue?: string;
-  className?: string;
-  ariaLabel?: string;
-  size?: number;
-  disabled?: boolean;
-}) {
-  const [focused, setFocused] = useState(false);
-  const [draft, setDraft] = useState("");
-  const cancelBlurCommitRef = useRef(false);
-
-  const commit = (raw: string) => {
-    const parsed = Number.parseFloat(raw);
-    if (!Number.isFinite(parsed)) {
-      return;
-    }
-    const final = snapToStep(parsed, step, min, max);
-    if (final !== value) {
-      onChange(final);
-    }
-  };
-
-  const displayed = focused ? draft : (displayValue ?? String(value));
-
-  return (
-    <input
-      type="text"
-      inputMode="decimal"
-      disabled={disabled}
-      size={sizeAttr}
-      style={{
-        boxSizing: "content-box",
-        width: `calc(${Math.max(displayed.length, 4)}ch + 2px)`,
-      }}
-      value={displayed}
-      aria-label={ariaLabel}
-      onFocus={(e) => {
-        cancelBlurCommitRef.current = false;
-        setDraft(String(value));
-        setFocused(true);
-        const target = e.currentTarget;
-        requestAnimationFrame(() => target.select());
-      }}
-      onBlur={() => {
-        if (cancelBlurCommitRef.current) {
-          cancelBlurCommitRef.current = false;
-        } else {
-          commit(draft);
-        }
-        setFocused(false);
-      }}
-      onChange={(e) =>
-        setDraft(sanitizeNumeric(e.target.value, (min ?? 0) < 0))
-      }
-      onKeyDown={(e) => {
-        if (e.key === "Enter") {
-          e.currentTarget.blur();
-        } else if (e.key === "Escape") {
-          cancelBlurCommitRef.current = true;
-          setDraft(String(value));
-          e.currentTarget.blur();
-        }
-      }}
-      className={cn(className)}
-    />
-  );
-}
diff --git a/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx b/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
deleted file mode 100644
index c7887c4357..0000000000
--- a/studio/frontend/src/features/model-picker/components/sidebar-model-config.tsx
+++ /dev/null
@@ -1,89 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { useMemo } from "react";
-import type { PerModelConfig } from "../model-config/per-model-config";
-import { ModelConfigPage } from "./model-config-page";
-import type { ModelPickTarget } from "./model-selector/types";
-
-interface SidebarModelConfigProps {
-  modelId: string;
-  ggufVariant: string | null;
-  isGguf: boolean;
-  nativeContextLength: number | null;
-  loadedContextLength: number | null;
-  loadedConfig: PerModelConfig;
-  onReload: (config: PerModelConfig) => void;
-}
-
-const TRAILING_SEPARATORS = /[\\/]+$/;
-
-function leafName(id: string): string {
-  const trimmed = id.replace(TRAILING_SEPARATORS, "");
-  const separator = Math.max(
-    trimmed.lastIndexOf("/"),
-    trimmed.lastIndexOf("\\"),
-  );
-  return separator >= 0 ? trimmed.slice(separator + 1) : trimmed;
-}
-
-function hashString(value: string): number {
-  let hash = 5381;
-  for (let i = 0; i < value.length; i += 1) {
-    hash = (Math.imul(hash, 33) ^ value.charCodeAt(i)) >>> 0;
-  }
-  return hash;
-}
-
-function configSignature(config: PerModelConfig): string {
-  return [
-    config.customContextLength ?? "",
-    config.maxSeqLength ?? "",
-    config.kvCacheDtype ?? "",
-    config.speculativeType ?? "",
-    config.specDraftNMax ?? "",
-    config.tensorParallel ? "1" : "0",
-    config.chatTemplateOverride == null
-      ? ""
-      : `${config.chatTemplateOverride.length}:${hashString(config.chatTemplateOverride)}`,
-  ].join("|");
-}
-
-export function SidebarModelConfig({
-  modelId,
-  ggufVariant,
-  isGguf,
-  nativeContextLength,
-  loadedContextLength,
-  loadedConfig,
-  onReload,
-}: SidebarModelConfigProps) {
-  const target = useMemo<ModelPickTarget>(() => {
-    const leaf = leafName(modelId);
-    return {
-      id: modelId,
-      displayName: ggufVariant ? `${leaf} · ${ggufVariant}` : leaf,
-      ggufVariant,
-      isGguf,
-      meta: {
-        source: "local",
-        isLora: false,
-        ggufVariant: ggufVariant ?? undefined,
-        isGguf,
-        isDownloaded: true,
-        contextLength: nativeContextLength,
-      },
-    };
-  }, [modelId, ggufVariant, isGguf, nativeContextLength]);
-
-  return (
-    <ModelConfigPage
-      key={`${modelId}::${ggufVariant ?? ""}::${configSignature(loadedConfig)}`}
-      target={target}
-      onRun={onReload}
-      loadedConfig={loadedConfig}
-      loadedContextLength={loadedContextLength}
-      variant="sidebar"
-    />
-  );
-}
diff --git a/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts b/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
deleted file mode 100644
index 49108279e7..0000000000
--- a/studio/frontend/src/features/model-picker/hooks/use-model-defaults.ts
+++ /dev/null
@@ -1,176 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import { useHfTokenStore } from "@/features/hub";
-import { useEffect, useState } from "react";
-import { fetchModelMaxPositionEmbeddings } from "../api/model-metadata";
-import { fetchDefaultChatTemplate } from "../api/templates";
-
-export interface DefaultChatTemplateState {
-  template: string | null;
-  loading: boolean;
-  error: string | null;
-}
-
-export interface ModelMaxPositionState {
-  maxPositionEmbeddings: number | null;
-  loading: boolean;
-  error: string | null;
-}
-
-const TEMPLATE_CACHE_MAX_ENTRIES = 50;
-const templateCache = new Map<string, string | null>();
-const maxPositionCache = new Map<string, number | null>();
-
-function cacheTemplate(key: string, template: string | null): void {
-  templateCache.delete(key);
-  templateCache.set(key, template);
-  while (templateCache.size > TEMPLATE_CACHE_MAX_ENTRIES) {
-    const oldest = templateCache.keys().next().value;
-    if (oldest === undefined) {
-      break;
-    }
-    templateCache.delete(oldest);
-  }
-}
-
-function cacheMaxPosition(key: string, value: number | null): void {
-  maxPositionCache.delete(key);
-  maxPositionCache.set(key, value);
-  while (maxPositionCache.size > TEMPLATE_CACHE_MAX_ENTRIES) {
-    const oldest = maxPositionCache.keys().next().value;
-    if (oldest === undefined) {
-      break;
-    }
-    maxPositionCache.delete(oldest);
-  }
-}
-
-export function useDefaultChatTemplate(
-  modelId: string | null,
-  ggufVariant: string | null | undefined,
-  enabled: boolean,
-): DefaultChatTemplateState {
-  const token = useHfTokenStore((s) => s.token);
-  const cacheKey =
-    enabled && modelId ? `${modelId}::${ggufVariant ?? ""}::${token}` : null;
-  const [fetched, setFetched] = useState<{
-    key: string;
-    state: DefaultChatTemplateState;
-  } | null>(null);
-
-  useEffect(() => {
-    if (cacheKey == null || !modelId || templateCache.has(cacheKey)) {
-      return;
-    }
-    const controller = new AbortController();
-    fetchDefaultChatTemplate(modelId, ggufVariant, token, controller.signal)
-      .then((template) => {
-        if (controller.signal.aborted) {
-          return;
-        }
-        // Cache the terminal result, including a null "no default template",
-        // so reopening the viewer for such a model reuses it instead of
-        // re-running the backend/Hugging Face lookup every time.
-        cacheTemplate(cacheKey, template);
-        setFetched({
-          key: cacheKey,
-          state: { template, loading: false, error: null },
-        });
-      })
-      .catch((err: unknown) => {
-        if (controller.signal.aborted) {
-          return;
-        }
-        setFetched({
-          key: cacheKey,
-          state: {
-            template: null,
-            loading: false,
-            error:
-              err instanceof Error ? err.message : "Failed to load template",
-          },
-        });
-      });
-
-    return () => controller.abort();
-  }, [cacheKey, modelId, ggufVariant, token]);
-
-  if (cacheKey == null) {
-    return { template: null, loading: false, error: null };
-  }
-  if (templateCache.has(cacheKey)) {
-    return {
-      template: templateCache.get(cacheKey) ?? null,
-      loading: false,
-      error: null,
-    };
-  }
-  if (fetched?.key === cacheKey) {
-    return fetched.state;
-  }
-  return { template: null, loading: true, error: null };
-}
-
-export function useModelMaxPositionEmbeddings(
-  modelId: string | null,
-  enabled: boolean,
-): ModelMaxPositionState {
-  const token = useHfTokenStore((s) => s.token);
-  const cacheKey = enabled && modelId ? `${modelId}::${token}` : null;
-  const [fetched, setFetched] = useState<{
-    key: string;
-    state: ModelMaxPositionState;
-  } | null>(null);
-
-  useEffect(() => {
-    if (cacheKey == null || !modelId || maxPositionCache.has(cacheKey)) {
-      return;
-    }
-    const controller = new AbortController();
-    fetchModelMaxPositionEmbeddings(modelId, token, controller.signal)
-      .then((maxPositionEmbeddings) => {
-        if (controller.signal.aborted) {
-          return;
-        }
-        cacheMaxPosition(cacheKey, maxPositionEmbeddings);
-        setFetched({
-          key: cacheKey,
-          state: { maxPositionEmbeddings, loading: false, error: null },
-        });
-      })
-      .catch((err: unknown) => {
-        if (controller.signal.aborted) {
-          return;
-        }
-        setFetched({
-          key: cacheKey,
-          state: {
-            maxPositionEmbeddings: null,
-            loading: false,
-            error:
-              err instanceof Error
-                ? err.message
-                : "Failed to load model metadata",
-          },
-        });
-      });
-
-    return () => controller.abort();
-  }, [cacheKey, modelId, token]);
-
-  if (cacheKey == null) {
-    return { maxPositionEmbeddings: null, loading: false, error: null };
-  }
-  if (maxPositionCache.has(cacheKey)) {
-    return {
-      maxPositionEmbeddings: maxPositionCache.get(cacheKey) ?? null,
-      loading: false,
-      error: null,
-    };
-  }
-  if (fetched?.key === cacheKey) {
-    return fetched.state;
-  }
-  return { maxPositionEmbeddings: null, loading: true, error: null };
-}
diff --git a/studio/frontend/src/features/model-picker/index.ts b/studio/frontend/src/features/model-picker/index.ts
deleted file mode 100644
index a9a176317f..0000000000
--- a/studio/frontend/src/features/model-picker/index.ts
+++ /dev/null
@@ -1,30 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-export { ModelSelector } from "./components/model-selector";
-export { FolderBrowser } from "./components/model-selector/folder-browser";
-export { ModelDeleteAction } from "./components/model-selector/model-delete-action";
-export { hfModelFitsDevice } from "./components/model-selector/recommended-fit";
-export {
-  NumericValueInput,
-  snapToStep,
-} from "./components/numeric-value-input";
-export { SidebarModelConfig } from "./components/sidebar-model-config";
-export type {
-  DeletedModelRef,
-  ExternalModelOption,
-  LoraModelOption,
-  ModelOption,
-  ModelSelectorChangeMeta,
-} from "./components/model-selector";
-export {
-  applyModelLoadConfigToRuntime,
-  applyPerModelConfigToRuntime,
-  currentRuntimePerModelConfig,
-  perModelConfigsEqual,
-} from "./model-config/apply-per-model-config";
-export {
-  normalizeMaxSeqLength,
-  type PerModelConfig,
-  resolveInitialConfig,
-} from "./model-config/per-model-config";
diff --git a/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts b/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
deleted file mode 100644
index 50b6bbb1a6..0000000000
--- a/studio/frontend/src/features/model-picker/inventory/use-chat-picker-inventory.ts
+++ /dev/null
@@ -1,118 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import type {
-  CachedGgufRepo,
-  CachedModelRepo,
-  LocalModelInfo,
-} from "@/features/chat";
-import {
-  type CachedInventoryRow,
-  type LocalInventoryRow,
-  type LocalSource,
-  isHiddenModelId,
-  useHubInventory,
-} from "@/features/hub";
-import { useMemo } from "react";
-
-const PICKER_LOCAL_SOURCES: ReadonlySet<LocalSource> = new Set([
-  "lmstudio",
-  "models_dir",
-  "custom",
-]);
-
-function isCompleteCachedRow(row: CachedInventoryRow): boolean {
-  return !row.partial && !row.liveDownload;
-}
-
-function toCachedGgufRepo(row: CachedInventoryRow): CachedGgufRepo {
-  return {
-    repo_id: row.repoId,
-    size_bytes: row.bytes,
-    cache_path: row.cachePath ?? "",
-    last_modified: row.lastModified ?? undefined,
-    has_vision: row.capabilities.supportsVision,
-  };
-}
-
-function toCachedModelRepo(row: CachedInventoryRow): CachedModelRepo {
-  return {
-    repo_id: row.repoId,
-    size_bytes: row.bytes,
-    last_modified: row.lastModified ?? undefined,
-  };
-}
-
-function toLocalModelInfo(row: LocalInventoryRow): LocalModelInfo {
-  return {
-    id: row.loadId,
-    display_name: row.displayName ?? row.title,
-    path: row.path,
-    source: row.source as LocalModelInfo["source"],
-    model_id: row.modelId ?? row.repoId,
-    model_format: row.modelFormat,
-    updated_at: row.updatedAt,
-  };
-}
-
-export interface ChatPickerInventory {
-  cachedGguf: CachedGgufRepo[];
-  cachedModels: CachedModelRepo[];
-  cachedReady: boolean;
-  localModels: LocalModelInfo[];
-  refreshInventory: () => Promise<void>;
-}
-
-export function useChatPickerInventory(
-  options: { enabled?: boolean } = {},
-): ChatPickerInventory {
-  const inventory = useHubInventory({
-    kind: "models",
-    enabled: options.enabled,
-    includeLocal: true,
-  });
-
-  const cachedGguf = useMemo(
-    () =>
-      inventory.cachedRows
-        .filter(
-          (row) =>
-            row.modelFormat === "gguf" &&
-            isCompleteCachedRow(row) &&
-            !isHiddenModelId(row.repoId),
-        )
-        .map(toCachedGgufRepo),
-    [inventory.cachedRows],
-  );
-  const cachedModels = useMemo(
-    () =>
-      inventory.cachedRows
-        .filter(
-          (row) =>
-            row.modelFormat !== "gguf" &&
-            isCompleteCachedRow(row) &&
-            !isHiddenModelId(row.repoId),
-        )
-        .map(toCachedModelRepo),
-    [inventory.cachedRows],
-  );
-  const localModels = useMemo(
-    () =>
-      inventory.localRows
-        .filter(
-          (row) =>
-            PICKER_LOCAL_SOURCES.has(row.source) &&
-            !isHiddenModelId(row.modelId, row.repoId, row.path),
-        )
-        .map(toLocalModelInfo),
-    [inventory.localRows],
-  );
-
-  return {
-    cachedGguf,
-    cachedModels,
-    cachedReady: inventory.downloadedReady,
-    localModels,
-    refreshInventory: inventory.refreshInventory,
-  };
-}
diff --git a/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts b/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
deleted file mode 100644
index a63dffe8dc..0000000000
--- a/studio/frontend/src/features/model-picker/model-config/apply-per-model-config.ts
+++ /dev/null
@@ -1,85 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import {
-  defaultInferenceParams,
-  normalizeSpeculativeType,
-  readPersistedSpeculativeType,
-  useChatRuntimeStore,
-} from "@/features/chat";
-import {
-  DEFAULT_PER_MODEL_CONFIG,
-  type PerModelConfig,
-  normalizeMaxSeqLength,
-} from "./per-model-config";
-
-function cleanTemplate(value: string | null | undefined): string | null {
-  return value?.trim() ? value : null;
-}
-
-export function applyPerModelConfigToRuntime(config: PerModelConfig): void {
-  // Fall back to the standing default when the model has no saved
-  // maxSeqLength. maxSeqLength is the only per-model field carried on
-  // params (the rest are reset below), so without this a model with no
-  // remembered config would inherit the previously loaded model's value.
-  const maxSeqLength =
-    normalizeMaxSeqLength(config.maxSeqLength) ??
-    defaultInferenceParams.maxSeqLength;
-  const store = useChatRuntimeStore.getState();
-  if (maxSeqLength !== store.params.maxSeqLength) {
-    store.setParams({ ...store.params, maxSeqLength });
-  }
-  useChatRuntimeStore.setState({
-    customContextLength: config.customContextLength ?? null,
-    kvCacheDtype: config.kvCacheDtype ?? null,
-    speculativeType:
-      normalizeSpeculativeType(config.speculativeType) ??
-      readPersistedSpeculativeType(),
-    specDraftNMax: config.specDraftNMax ?? null,
-    tensorParallel: config.tensorParallel ?? false,
-    chatTemplateOverride: cleanTemplate(config.chatTemplateOverride),
-  });
-}
-
-export function applyModelLoadConfigToRuntime(
-  config: PerModelConfig | null | undefined,
-): boolean {
-  const hasConfig = config != null;
-  applyPerModelConfigToRuntime(config ?? DEFAULT_PER_MODEL_CONFIG);
-  return hasConfig;
-}
-
-export function currentRuntimePerModelConfig(
-  options: { includeMaxSeqLength?: boolean } = {},
-): PerModelConfig {
-  const s = useChatRuntimeStore.getState();
-  return {
-    customContextLength: s.customContextLength ?? null,
-    maxSeqLength: options.includeMaxSeqLength
-      ? normalizeMaxSeqLength(s.params.maxSeqLength)
-      : null,
-    kvCacheDtype: s.kvCacheDtype ?? null,
-    speculativeType: normalizeSpeculativeType(s.speculativeType),
-    specDraftNMax: s.specDraftNMax ?? null,
-    tensorParallel: s.tensorParallel ?? false,
-    chatTemplateOverride: cleanTemplate(s.chatTemplateOverride),
-  };
-}
-
-export function perModelConfigsEqual(
-  a: PerModelConfig,
-  b: PerModelConfig,
-): boolean {
-  return (
-    (a.customContextLength ?? null) === (b.customContextLength ?? null) &&
-    normalizeMaxSeqLength(a.maxSeqLength) ===
-      normalizeMaxSeqLength(b.maxSeqLength) &&
-    (a.kvCacheDtype ?? null) === (b.kvCacheDtype ?? null) &&
-    normalizeSpeculativeType(a.speculativeType) ===
-      normalizeSpeculativeType(b.speculativeType) &&
-    (a.specDraftNMax ?? null) === (b.specDraftNMax ?? null) &&
-    Boolean(a.tensorParallel) === Boolean(b.tensorParallel) &&
-    cleanTemplate(a.chatTemplateOverride) ===
-      cleanTemplate(b.chatTemplateOverride)
-  );
-}
diff --git a/studio/frontend/src/features/model-picker/model-config/model-identity.ts b/studio/frontend/src/features/model-picker/model-config/model-identity.ts
deleted file mode 100644
index 0caa7c1312..0000000000
--- a/studio/frontend/src/features/model-picker/model-config/model-identity.ts
+++ /dev/null
@@ -1,69 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import {
-  normalizeGgufVariantIdentity,
-  normalizeModelIdentity,
-} from "@/features/hub";
-
-export {
-  normalizeGgufVariantIdentity,
-  normalizeModelIdentity,
-} from "@/features/hub";
-
-const MODEL_STORAGE_KEY_PREFIX = "v2:";
-
-type ParsedModelStorageKey = {
-  modelId: string;
-  ggufVariant: string;
-};
-
-function parseVersionedModelStorageKey(
-  key: string,
-): ParsedModelStorageKey | null {
-  if (!key.startsWith(MODEL_STORAGE_KEY_PREFIX)) {
-    return null;
-  }
-  try {
-    const parsed = JSON.parse(key.slice(MODEL_STORAGE_KEY_PREFIX.length));
-    if (
-      !Array.isArray(parsed) ||
-      parsed.length !== 2 ||
-      typeof parsed[0] !== "string" ||
-      typeof parsed[1] !== "string"
-    ) {
-      return null;
-    }
-    return { modelId: parsed[0], ggufVariant: parsed[1] };
-  } catch {
-    return null;
-  }
-}
-
-export function modelStorageKey(
-  modelId: string,
-  ggufVariant?: string | null,
-): string {
-  return `${MODEL_STORAGE_KEY_PREFIX}${JSON.stringify([
-    normalizeModelIdentity(modelId),
-    normalizeGgufVariantIdentity(ggufVariant),
-  ])}`;
-}
-
-export function modelIdFromStorageKey(key: string): string | null {
-  const parsed = parseVersionedModelStorageKey(key);
-  if (parsed) {
-    return parsed.modelId;
-  }
-  const separator = key.lastIndexOf("::");
-  return separator >= 0 ? key.slice(0, separator) : null;
-}
-
-export function ggufVariantFromStorageKey(key: string): string | null {
-  const parsed = parseVersionedModelStorageKey(key);
-  if (parsed) {
-    return parsed.ggufVariant;
-  }
-  const separator = key.lastIndexOf("::");
-  return separator >= 0 ? key.slice(separator + 2) : null;
-}
diff --git a/studio/frontend/src/features/model-picker/model-config/per-model-config.ts b/studio/frontend/src/features/model-picker/model-config/per-model-config.ts
deleted file mode 100644
index 53a376e8b4..0000000000
--- a/studio/frontend/src/features/model-picker/model-config/per-model-config.ts
+++ /dev/null
@@ -1,571 +0,0 @@
-// SPDX-License-Identifier: AGPL-3.0-only
-// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
-
-import {
-  ggufVariantFromStorageKey,
-  modelIdFromStorageKey,
-  modelStorageKey,
-  normalizeGgufVariantIdentity,
-  normalizeModelIdentity,
-} from "./model-identity";
-
-export interface PerModelConfig {
-  customContextLength: number | null;
-  maxSeqLength: number | null;
-  kvCacheDtype: string | null;
-  speculativeType: string | null;
-  specDraftNMax: number | null;
-  tensorParallel: boolean;
-  chatTemplateOverride: string | null;
-}
-
-export const DEFAULT_PER_MODEL_CONFIG: PerModelConfig = {
-  customContextLength: null,
-  maxSeqLength: null,
-  kvCacheDtype: null,
-  speculativeType: null,
-  specDraftNMax: null,
-  tensorParallel: false,
-  chatTemplateOverride: null,
-};
-
-export const MAX_SEQ_LENGTH_MIN = 128;
-export const MAX_SEQ_LENGTH_MAX = 1048576;
-export const MAX_SEQ_LENGTH_STEP = 128;
-
-export const KV_CACHE_DTYPES = ["bf16", "q8_0", "q5_1", "q4_1"] as const;
-const VALID_KV_CACHE_DTYPES = new Set<string>(KV_CACHE_DTYPES);
-
-export const SPECULATIVE_TYPES = [
-  "auto",
-  "mtp",
-  "ngram",
-  "mtp+ngram",
-  "off",
-] as const;
-export const MTP_SPECULATIVE_TYPES: ReadonlySet<string> = new Set([
-  "mtp",
-  "mtp+ngram",
-]);
-
-const STORAGE_KEY = "unsloth_model_configs";
-const LEGACY_STORAGE_KEY = "unsloth_load_settings";
-const LEGACY_MIGRATION_FLAG = "unsloth_model_configs_migrated";
-const STORAGE_SCHEMA_VERSION = 1;
-const MAX_ENTRIES = 500;
-const MAX_PER_MODEL_CONFIG_STORAGE_BYTES = 1024 * 1024;
-export const MAX_CHAT_TEMPLATE_BYTES = 65_536;
-
-type StoredPerModelConfig = PerModelConfig & {
-  version: typeof STORAGE_SCHEMA_VERSION;
-};
-type StoredMap = Record<string, PerModelConfig | StoredPerModelConfig>;
-type RawConfig = Partial<PerModelConfig> & { version?: unknown };
-
-const STORED_CONFIG_FIELDS = new Set([
-  "version",
-  "customContextLength",
-  "maxSeqLength",
-  "kvCacheDtype",
-  "speculativeType",
-  "specDraftNMax",
-  "tensorParallel",
-  "chatTemplateOverride",
-]);
-
-function canonicalizeSpeculativeType(value: string): string | null {
-  const s = value.trim().toLowerCase();
-  if (!s) {
-    return null;
-  }
-  if (s === "auto" || s === "default") {
-    return "auto";
-  }
-  if (s === "off") {
-    return "off";
-  }
-  if (s === "mtp" || s === "draft-mtp") {
-    return "mtp";
-  }
-  if (s === "ngram" || s === "ngram-mod" || s === "ngram-simple") {
-    return "ngram";
-  }
-  if (s === "mtp+ngram") {
-    return "mtp+ngram";
-  }
-  return null;
-}
-
-export function normalizeMaxSeqLength(value: unknown): number | null {
-  if (typeof value !== "number" || !Number.isFinite(value) || value <= 0) {
-    return null;
-  }
-  const snapped = Math.round(value / MAX_SEQ_LENGTH_STEP) * MAX_SEQ_LENGTH_STEP;
-  return Math.max(MAX_SEQ_LENGTH_MIN, Math.min(MAX_SEQ_LENGTH_MAX, snapped));
-}
-
-function canUseStorage(): boolean {
-  return typeof window !== "undefined";
-}
-
-function serializedByteLength(value: string): number {
-  return typeof TextEncoder !== "undefined"
-    ? new TextEncoder().encode(value).byteLength
-    : value.length;
-}
-
-export function chatTemplateByteLength(value: string): number {
-  return serializedByteLength(value);
-}
-
-export function isChatTemplateWithinLimit(value: string): boolean {
-  return chatTemplateByteLength(value) <= MAX_CHAT_TEMPLATE_BYTES;
-}
-
-function serializedMapSize(map: StoredMap): number {
-  return serializedByteLength(JSON.stringify(map));
-}
-
-function serializedMapEntrySize(key: string, value: StoredMap[string]): number {
-  return (
-    serializedByteLength(JSON.stringify(key)) +
-    1 +
-    serializedByteLength(JSON.stringify(value))
-  );
-}
-
-function deleteOldestEvictableEntry(
-  map: StoredMap,
-  protectedKeys?: ReadonlySet<string>,
-): { key: string; value: StoredMap[string] } | null {
-  for (const key of Object.keys(map)) {
-    // Never evict a future-schema entry an older client cannot interpret,
-    // matching the save/delete guards.
-    if (
-      protectedKeys?.has(key) ||
-      storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION
-    ) {
-      continue;
-    }
-    const value = map[key];
-    delete map[key];
-    return { key, value };
-  }
-  return null;
-}
-
-function enforceStorageBudget(
-  map: StoredMap,
-  protectedKeys?: ReadonlySet<string>,
-): boolean {
-  let entryCount = Object.keys(map).length;
-  while (entryCount > MAX_ENTRIES) {
-    if (!deleteOldestEvictableEntry(map, protectedKeys)) {
-      return false;
-    }
-    entryCount -= 1;
-  }
-  let bytes = serializedMapSize(map);
-  while (bytes > MAX_PER_MODEL_CONFIG_STORAGE_BYTES) {
-    const removed = deleteOldestEvictableEntry(map, protectedKeys);
-    if (!removed) {
-      return false;
-    }
-    bytes -=
-      serializedMapEntrySize(removed.key, removed.value) +
-      (entryCount > 1 ? 1 : 0);
-    entryCount -= 1;
-  }
-  return true;
-}
-
-function storedConfigVersion(raw: unknown): number {
-  if (!raw || typeof raw !== "object" || Array.isArray(raw)) {
-    return 0;
-  }
-  const version = (raw as RawConfig).version;
-  return typeof version === "number" && Number.isFinite(version) ? version : 0;
-}
-
-let legacyMigrationChecked = false;
-
-function parseLegacyModelKey(
-  key: string,
-): { modelId: string; ggufVariant: string | null } | null {
-  const separator = key.lastIndexOf("::");
-  if (separator >= 0) {
-    const modelId = key.slice(0, separator);
-    return modelId
-      ? { modelId, ggufVariant: key.slice(separator + 2) || null }
-      : null;
-  }
-  return key ? { modelId: key, ggufVariant: null } : null;
-}
-
-function legacyEntryToConfig(raw: Record<string, unknown>): PerModelConfig {
-  return normalizeV1({
-    customContextLength:
-      typeof raw.contextLength === "number" ? raw.contextLength : null,
-    maxSeqLength: null,
-    kvCacheDtype:
-      typeof raw.kvCacheDtype === "string" ? raw.kvCacheDtype : null,
-    speculativeType:
-      typeof raw.speculativeType === "string" ? raw.speculativeType : null,
-    specDraftNMax:
-      typeof raw.specDraftNMax === "number" ? raw.specDraftNMax : null,
-    tensorParallel:
-      typeof raw.tensorParallel === "boolean" ? raw.tensorParallel : false,
-    chatTemplateOverride: null,
-  });
-}
-
-function mergeLegacyEntries(
-  map: StoredMap,
-  legacy: Record<string, unknown>,
-): string[] {
-  const addedKeys: string[] = [];
-  for (const [legacyKey, value] of Object.entries(legacy)) {
-    if (!value || typeof value !== "object") {
-      continue;
-    }
-    const parsedKey = parseLegacyModelKey(legacyKey);
-    if (!parsedKey) {
-      continue;
-    }
-    const migrated = legacyEntryToConfig(value as Record<string, unknown>);
-    const key = modelStorageKey(parsedKey.modelId, parsedKey.ggufVariant);
-    if (isDefaultConfig(migrated) || Object.hasOwn(map, key)) {
-      continue;
-    }
-    map[key] = toStoredConfig(migrated);
-    addedKeys.push(key);
-  }
-  return addedKeys;
-}
-
-function migrateLegacyLoadSettingsOnce(): void {
-  if (legacyMigrationChecked || !canUseStorage()) {
-    return;
-  }
-  legacyMigrationChecked = true;
-  try {
-    if (localStorage.getItem(LEGACY_MIGRATION_FLAG)) {
-      return;
-    }
-    let legacy: unknown = null;
-    try {
-      legacy = JSON.parse(localStorage.getItem(LEGACY_STORAGE_KEY) ?? "null");
-    } catch {
-      legacy = null;
-    }
-    if (!legacy || typeof legacy !== "object" || Array.isArray(legacy)) {
-      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
-      return;
-    }
-    const map = readMapRaw();
-    const migratedKeys = mergeLegacyEntries(
-      map,
-      legacy as Record<string, unknown>,
-    );
-    if (migratedKeys.length === 0) {
-      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
-      return;
-    }
-    // Protect the just-migrated entries during eviction. If the budget cannot
-    // fit them (e.g. storage is full of future-schema records an older client
-    // cannot evict), leave the flag unset so migration retries once space frees
-    // up rather than marking it complete and dropping the migrated config.
-    if (!enforceStorageBudget(map, new Set(migratedKeys))) {
-      return;
-    }
-    if (writeMap(map)) {
-      localStorage.setItem(LEGACY_MIGRATION_FLAG, "1");
-    }
-  } catch (err) {
-    console.warn("Failed to migrate legacy load settings:", err);
-  }
-}
-
-function readMapRaw(): StoredMap {
-  if (!canUseStorage()) {
-    return {};
-  }
-  try {
-    const raw = localStorage.getItem(STORAGE_KEY);
-    if (!raw) {
-      return {};
-    }
-    const parsed = JSON.parse(raw);
-    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) {
-      return {};
-    }
-    return parsed as StoredMap;
-  } catch {
-    return {};
-  }
-}
-
-function readMap(): StoredMap {
-  migrateLegacyLoadSettingsOnce();
-  return readMapRaw();
-}
-
-function writeMap(map: StoredMap): boolean {
-  if (!canUseStorage()) {
-    return false;
-  }
-  try {
-    localStorage.setItem(STORAGE_KEY, JSON.stringify(map));
-    return true;
-  } catch (err) {
-    console.warn("Failed to persist per-model config:", err);
-    return false;
-  }
-}
-
-function warnDroppedFields(raw: Record<string, unknown>, version: number): void {
-  if (!import.meta.env?.DEV) {
-    return;
-  }
-  const dropped = Object.keys(raw).filter(
-    (key) => !STORED_CONFIG_FIELDS.has(key),
-  );
-  if (dropped.length > 0) {
-    console.warn("Dropped unknown per-model config fields:", dropped);
-  }
-  if (version > STORAGE_SCHEMA_VERSION) {
-    console.warn("Per-model config schema is newer than this app:", version);
-  }
-}
-
-function normalizeV1(partial: RawConfig): PerModelConfig {
-  const rawSpecType =
-    typeof partial.speculativeType === "string"
-      ? canonicalizeSpeculativeType(partial.speculativeType)
-      : null;
-  const speculativeType = rawSpecType ?? DEFAULT_PER_MODEL_CONFIG.speculativeType;
-  const specDraftNMax =
-    speculativeType != null &&
-    MTP_SPECULATIVE_TYPES.has(speculativeType) &&
-    typeof partial.specDraftNMax === "number" &&
-    Number.isFinite(partial.specDraftNMax)
-      ? Math.max(1, Math.min(16, Math.round(partial.specDraftNMax)))
-      : null;
-  return {
-    customContextLength:
-      typeof partial.customContextLength === "number" &&
-      Number.isFinite(partial.customContextLength) &&
-      partial.customContextLength > 0
-        ? Math.floor(partial.customContextLength)
-        : null,
-    maxSeqLength: normalizeMaxSeqLength(partial.maxSeqLength),
-    kvCacheDtype:
-      typeof partial.kvCacheDtype === "string" &&
-      VALID_KV_CACHE_DTYPES.has(partial.kvCacheDtype)
-        ? partial.kvCacheDtype
-        : null,
-    speculativeType,
-    specDraftNMax,
-    tensorParallel:
-      typeof partial.tensorParallel === "boolean"
-        ? partial.tensorParallel
-        : DEFAULT_PER_MODEL_CONFIG.tensorParallel,
-    chatTemplateOverride:
-      typeof partial.chatTemplateOverride === "string" &&
-      isChatTemplateWithinLimit(partial.chatTemplateOverride)
-        ? partial.chatTemplateOverride
-        : null,
-  };
-}
-
-function normalize(raw: unknown): PerModelConfig {
-  if (!raw || typeof raw !== "object" || Array.isArray(raw)) {
-    return normalizeV1({});
-  }
-  const partial = raw as RawConfig;
-  const version =
-    typeof partial.version === "number" && Number.isFinite(partial.version)
-      ? partial.version
-      : 0;
-  warnDroppedFields(raw as Record<string, unknown>, version);
-  return normalizeV1(partial);
-}
-
-function toStoredConfig(config: PerModelConfig): StoredPerModelConfig {
-  return {
-    version: STORAGE_SCHEMA_VERSION,
-    ...normalize(config),
-  };
-}
-
-function legacyModelStorageKey(
-  modelId: string,
-  ggufVariant?: string | null,
-): string {
-  return `${modelId}::${ggufVariant ?? ""}`;
-}
-
-function storageKeysForModelVariant(
-  modelId: string,
-  ggufVariant?: string | null,
-): string[] {
-  const key = modelStorageKey(modelId, ggufVariant);
-  const legacyKey = legacyModelStorageKey(modelId, ggufVariant);
-  return key === legacyKey ? [key] : [key, legacyKey];
-}
-
-function configKeyMatchesModelVariant(
-  key: string,
-  modelId: string,
-  ggufVariant?: string | null,
-): boolean {
-  const storedModelId = modelIdFromStorageKey(key);
-  if (!storedModelId) {
-    return false;
-  }
-  return (
-    normalizeModelIdentity(storedModelId) === normalizeModelIdentity(modelId) &&
-    normalizeGgufVariantIdentity(ggufVariantFromStorageKey(key)) ===
-      normalizeGgufVariantIdentity(ggufVariant)
-  );
-}
-
-function findConfigKeyForModelVariant(
-  map: StoredMap,
-  modelId: string,
-  ggufVariant?: string | null,
-): string | null {
-  for (const key of storageKeysForModelVariant(modelId, ggufVariant)) {
-    if (Object.hasOwn(map, key)) {
-      return key;
-    }
-  }
-  for (const key of Object.keys(map)) {
-    if (configKeyMatchesModelVariant(key, modelId, ggufVariant)) {
-      return key;
-    }
-  }
-  return null;
-}
-
-function hasFutureConfigForModelVariant(
-  map: StoredMap,
-  modelId: string,
-  ggufVariant?: string | null,
-): boolean {
-  for (const key of Object.keys(map)) {
-    if (
-      configKeyMatchesModelVariant(key, modelId, ggufVariant) &&
-      storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION
-    ) {
-      return true;
-    }
-  }
-  return false;
-}
-
-function deleteConfigEntriesForModelVariant(
-  map: StoredMap,
-  modelId: string,
-  ggufVariant?: string | null,
-): boolean {
-  let changed = false;
-  for (const key of Object.keys(map)) {
-    if (!configKeyMatchesModelVariant(key, modelId, ggufVariant)) {
-      continue;
-    }
-    delete map[key];
-    changed = true;
-  }
-  return changed;
-}
-
-function loadPerModelConfig(
-  modelId: string,
-  ggufVariant?: string | null,
-): PerModelConfig | null {
-  const map = readMap();
-  const key = findConfigKeyForModelVariant(map, modelId, ggufVariant);
-  if (!key) {
-    return null;
-  }
-  // Never apply a future-schema record an older client cannot interpret,
-  // matching the save/delete/evict guards.
-  if (storedConfigVersion(map[key]) > STORAGE_SCHEMA_VERSION) {
-    return null;
-  }
-  return normalize(map[key]);
-}
-
-export function isDefaultConfig(config: PerModelConfig): boolean {
-  return (
-    config.customContextLength == null &&
-    config.maxSeqLength == null &&
-    (config.kvCacheDtype ?? null) === DEFAULT_PER_MODEL_CONFIG.kvCacheDtype &&
-    config.speculativeType === DEFAULT_PER_MODEL_CONFIG.speculativeType &&
-    config.specDraftNMax == null &&
-    Boolean(config.tensorParallel) ===
-      Boolean(DEFAULT_PER_MODEL_CONFIG.tensorParallel) &&
-    (config.chatTemplateOverride ?? null) === null
-  );
-}
-
-export function savePerModelConfig(
-  modelId: string,
-  ggufVariant: string | null | undefined,
-  config: PerModelConfig,
-): boolean {
-  if (
-    typeof config.chatTemplateOverride === "string" &&
-    !isChatTemplateWithinLimit(config.chatTemplateOverride)
-  ) {
-    return false;
-  }
-  const normalized = normalize(config);
-  const map = readMap();
-  if (hasFutureConfigForModelVariant(map, modelId, ggufVariant)) {
-    return false;
-  }
-  if (isDefaultConfig(normalized)) {
-    const changed = deleteConfigEntriesForModelVariant(
-      map,
-      modelId,
-      ggufVariant,
-    );
-    return changed ? writeMap(map) : true;
-  }
-  const [key] = storageKeysForModelVariant(modelId, ggufVariant);
-  deleteConfigEntriesForModelVariant(map, modelId, ggufVariant);
-  map[key] = toStoredConfig(normalized);
-  if (!enforceStorageBudget(map, new Set([key]))) {
-    return false;
-  }
-  return writeMap(map);
-}
-
-export function deletePerModelConfig(
-  modelId: string,
-  ggufVariant?: string | null,
-): boolean {
-  const map = readMap();
-  // Mirror savePerModelConfig: never let an older client destroy a
-  // future-schema entry it cannot interpret.
-  if (hasFutureConfigForModelVariant(map, modelId, ggufVariant)) {
-    return false;
-  }
-  if (!deleteConfigEntriesForModelVariant(map, modelId, ggufVariant)) {
-    return true;
-  }
-  return writeMap(map);
-}
-
-export function resolveInitialConfig(
-  modelId: string,
-  ggufVariant?: string | null,
-): { config: PerModelConfig; remembered: boolean } {
-  const saved = loadPerModelConfig(modelId, ggufVariant);
-  if (saved) {
-    return { config: saved, remembered: true };
-  }
-  return { config: { ...DEFAULT_PER_MODEL_CONFIG }, remembered: false };
-}
diff --git a/studio/frontend/src/features/settings/tabs/chat-tab.tsx b/studio/frontend/src/features/settings/tabs/chat-tab.tsx
index 376372971c..d5c9f10a4f 100644
--- a/studio/frontend/src/features/settings/tabs/chat-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/chat-tab.tsx
@@ -43,6 +43,7 @@ import {
   Folder01Icon,
   McpServerIcon,
   PencilRulerIcon,
+  Settings02Icon,
   ShieldBanIcon,
   Upload01Icon,
 } from "@hugeicons/core-free-icons";
@@ -195,6 +196,10 @@ export function ChatTab() {
   const hydratePersistedSettings = useChatRuntimeStore(
     (state) => state.hydratePersistedSettings,
   );
+  const loadOnSelection = useChatRuntimeStore((state) => state.loadOnSelection);
+  const setLoadOnSelection = useChatRuntimeStore(
+    (state) => state.setLoadOnSelection,
+  );
   const expandQuantizations = useChatRuntimeStore(
     (state) => state.expandQuantizations,
   );
@@ -328,6 +333,40 @@ export function ChatTab() {
       </header>
 
       <SettingsSection title="Select model settings">
+        <SettingsRow
+          label="Load on selection"
+          alignTop={true}
+          description={
+            <span>
+              On: Unsloth auto-picks the best settings and loads it.
+              <br />
+              Off: opens Run settings to customize, then load.
+              <br />
+              The gear always opens Run settings:{" "}
+              <span className="ml-2 inline-flex items-center gap-3 align-middle">
+                <span className="font-mono text-xs text-foreground">
+                  Q4_K_M
+                </span>
+                <span className="text-[9px] font-medium text-green-400">
+                  downloaded
+                </span>
+                <span className="text-[10px] text-muted-foreground">16 GB</span>
+                <span className="inline-flex size-4 items-center justify-center rounded bg-black/[0.06] dark:bg-white/[0.08]">
+                  <HugeiconsIcon
+                    icon={Settings02Icon}
+                    strokeWidth={1.75}
+                    className="size-2.5 text-muted-foreground/80"
+                  />
+                </span>
+              </span>
+            </span>
+          }
+        >
+          <Switch
+            checked={loadOnSelection}
+            onCheckedChange={setLoadOnSelection}
+          />
+        </SettingsRow>
         <SettingsRow
           label="Expand quantizations"
           description={
diff --git a/studio/frontend/src/features/settings/tabs/general-tab.tsx b/studio/frontend/src/features/settings/tabs/general-tab.tsx
index c79b6465ac..73a33fd155 100644
--- a/studio/frontend/src/features/settings/tabs/general-tab.tsx
+++ b/studio/frontend/src/features/settings/tabs/general-tab.tsx
@@ -92,10 +92,9 @@ const PREFS_KEYS: string[] = [
   "unsloth_chat_inference_params",
   "unsloth_chat_collapsible_state",
   "unsloth_chat_preferences",
-  "unsloth_model_configs",
-  "unsloth_model_configs_migrated",
   "unsloth_load_settings",
   // Model selector settings ("Select model settings" group)
+  "unsloth_chat_load_on_selection",
   "unsloth_chat_expand_quantizations",
   "unsloth_chat_show_all_quantizations",
   "unsloth_models_fit_on_device_only",
diff --git a/studio/frontend/src/features/training/index.ts b/studio/frontend/src/features/training/index.ts
index fcb30f379c..553dcc2af5 100644
--- a/studio/frontend/src/features/training/index.ts
+++ b/studio/frontend/src/features/training/index.ts
@@ -24,8 +24,8 @@ export { HfDatasetSubsetSplitSelectors } from "./components/hf-dataset-subset-sp
 export { useDatasetPreviewDialogStore } from "./stores/dataset-preview-dialog-store";
 export { listLocalDatasets, uploadTrainingDataset } from "./api/datasets-api";
 export type { LocalDatasetInfo } from "./types/datasets";
-export { getModelConfig, listLocalModels } from "./api/models-api";
-export type { LocalModelInfo, ModelConfigResponse } from "./api/models-api";
+export { listLocalModels } from "./api/models-api";
+export type { LocalModelInfo } from "./api/models-api";
 export type {
   TrainingPhase,
   TrainingViewData,
diff --git a/tests/studio/playwright_chat_ui.py b/tests/studio/playwright_chat_ui.py
index 2abec93df1..065ba7a745 100644
--- a/tests/studio/playwright_chat_ui.py
+++ b/tests/studio/playwright_chat_ui.py
@@ -678,16 +678,10 @@ with sync_playwright() as p:
     last_assistant = page.locator('[data-role="assistant"]').last
     last_assistant.hover()
     page.wait_for_timeout(400)
-    # Exclude disabled controls: the picker's new disabled "Reload model"
-    # button also matches and sorts first, so .first would target it.
-    regen_btn = (
-        page.get_by_role(
-            "button",
-            name = re.compile(r"(reload|regenerate)", re.I),
-        )
-        .and_(page.locator("button:not([disabled])"))
-        .first
-    )
+    regen_btn = page.get_by_role(
+        "button",
+        name = re.compile(r"(reload|regenerate)", re.I),
+    ).first
     if regen_btn.count() > 0:
         regen_btn.click()
         try:
diff --git a/tests/studio/test_studio_text_descender_clipping.py b/tests/studio/test_studio_text_descender_clipping.py
index 91ca080354..7cad6cacfe 100644
--- a/tests/studio/test_studio_text_descender_clipping.py
+++ b/tests/studio/test_studio_text_descender_clipping.py
@@ -10,14 +10,7 @@ from pathlib import Path
 
 WORKDIR = Path(__file__).resolve().parents[2]
 MODEL_SELECTOR = (
-    WORKDIR
-    / "studio"
-    / "frontend"
-    / "src"
-    / "features"
-    / "model-picker"
-    / "components"
-    / "model-selector.tsx"
+    WORKDIR / "studio" / "frontend" / "src" / "components" / "assistant-ui" / "model-selector.tsx"
 )
 APP_SIDEBAR = WORKDIR / "studio" / "frontend" / "src" / "components" / "app-sidebar.tsx"
 
@@ -41,12 +34,10 @@ def test_model_selector_trigger_label_uses_leading_tight():
 
 def test_sidebar_account_block_uses_leading_tight():
     src = _read(APP_SIDEBAR)
-    # Match the account-block parent div regardless of its layout/spacing
-    # utilities (e.g. min-w-0, flex-1, the gap-* class); this guard is about the
-    # leading-* class immediately before the collapsible visibility utility, not
-    # the surrounding flex plumbing.
+    # Match the account-block parent div regardless of its gap utility; this
+    # guard is about the leading-* class, not the spacing.
     pattern = re.compile(
-        r'<div\s+className="flex\b[^"]*\bflex-col\b[^"]*\bgap-\S+\s+(\S+)\s+group-data-\[collapsible=icon\]:hidden">',
+        r'<div\s+className="flex\s+flex-col\s+gap-\S+\s+(\S+)\s+group-data-\[collapsible=icon\]:hidden">',
     )
     matches = pattern.findall(src)
     assert matches, "could not find sidebar account-block parent div"

From 49f2879cf875eab717a5d82cb5dff29890912d20 Mon Sep 17 00:00:00 2001
From: Rod Boev <rod.boev@gmail.com>
Date: Fri, 17 Jul 2026 12:32:03 -0400
Subject: [PATCH 11/28] fix(studio): recover stalled Hub downloads over HTTP
 (#6858)

* fix(studio): recover stalled Hub downloads over HTTP

* fix(studio): preserve retry generation and progress baseline

* fix(studio): keep XET retry handoff nonterminal

* fix(studio): preserve retry cancellation on claim failure

* fix(studio): make retry failure cancellation atomic

* fix(studio): close skipped retry state gaps

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Stabilize chat-only export gate detection on Windows

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Retrigger CI on a user-authored head

* fix(studio): serialize XET HTTP retry handoff

* List XET to HTTP retries that are briefly released from the repo guard as active downloads for PR #6858

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Settle no-process active downloads on shutdown so a parked XET retry cannot spawn after cleanup for PR #6858

* Settle exited-error and no-process downloads on shutdown and persist their cancel markers for PR #6858

* Keep terminal HTTP failures uncancelled and block companion deletion for released retry peers for PR #6858

* Trim download lifecycle test coverage

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
---
 .../hub/services/download_lifecycle.py        | 270 +++++++++++++++++-
 .../hub/tests/test_download_lifecycle.py      | 158 ++++++++--
 studio/backend/hub/utils/download_registry.py | 173 ++++++++++-
 3 files changed, 562 insertions(+), 39 deletions(-)

diff --git a/studio/backend/hub/services/download_lifecycle.py b/studio/backend/hub/services/download_lifecycle.py
index 50e20fc13f..e5d48872c1 100644
--- a/studio/backend/hub/services/download_lifecycle.py
+++ b/studio/backend/hub/services/download_lifecycle.py
@@ -8,6 +8,7 @@ import os
 import signal
 import subprocess
 import sys
+import time
 import threading
 from pathlib import Path
 from typing import Callable, Optional
@@ -210,7 +211,9 @@ def finalize_worker_exit(
     repo_type: Optional[RepoType] = None,
     repo_id: Optional[str] = None,
     transport: Optional[str] = None,
-) -> None:
+    cancel_marker_transport: Optional[str] = None,
+    defer_error: bool = False,
+) -> str:
     """Block until *proc* exits, then record the job's terminal state in
     *registry*. Drains and scrubs stderr first, then classifies the exit code.
     A no-op when the process was already dropped (e.g. superseded).
@@ -222,7 +225,7 @@ def finalize_worker_exit(
     rc = proc.wait()
     cancel_requested = registry.cancel_requested(key)
     if not registry.drop_process(key, proc):
-        return
+        return "idle"
     stderr_text = download_registry.scrub_secrets(
         (stderr_data or b"").decode("utf-8", "replace").strip(),
         hf_token = hf_token,
@@ -230,6 +233,8 @@ def finalize_worker_exit(
     state = classify_exit(rc, cancel_requested = cancel_requested)
     if state == "complete":
         registry.set_job(key, "complete")
+        if transport == download_registry.TRANSPORT_HTTP:
+            registry.update_job_transport(key, download_registry.TRANSPORT_HTTP)
         if stderr_text:
             if download_manifest.MANIFEST_DEGRADED_MARKER in stderr_text:
                 logger.warning(
@@ -262,18 +267,226 @@ def finalize_worker_exit(
             metadata.variant
             if metadata is not None and metadata.variant
             else download_registry.variant_from_key(key),
-            transport,
+            cancel_marker_transport or transport,
             logger = logger,
         )
     else:
-        registry.set_job(
-            key,
-            "error",
-            stderr_text or f"worker exited with code {rc}",
-        )
+        if not defer_error:
+            registry.set_job(
+                key,
+                "error",
+                stderr_text or f"worker exited with code {rc}",
+            )
         logger.error(
             f"{log_prefix} failed for {label} (rc={rc}): {stderr_text}",
         )
+    return state
+
+
+def _set_retry_failure_state(
+    registry: download_registry.DownloadRegistry,
+    key: str,
+    error: str,
+    *,
+    repo_type: RepoType,
+    repo_id: str,
+    fallback_variant: Optional[str],
+    fallback_transport: Optional[str],
+    logger,
+) -> str:
+    state, metadata = registry.set_error_unless_cancelled(key, error)
+    if state == "cancelled":
+        download_registry.persist_cancel_marker(
+            repo_type,
+            repo_id,
+            metadata.variant if metadata is not None and metadata.variant else fallback_variant,
+            metadata.transport
+            if metadata is not None and metadata.transport
+            else fallback_transport,
+            logger = logger,
+        )
+    return state
+
+
+def _try_http_retry(
+    registry: download_registry.DownloadRegistry,
+    key: str,
+    *,
+    hf_token: Optional[str],
+    label: str,
+    log_prefix: str,
+    logger,
+    repo_type: RepoType,
+    repo_id: str,
+    watch_name: str,
+) -> bool:
+    """Reclaim *key* with HTTP transport and spawn a recovery worker.
+
+    Returns ``True`` when the HTTP worker was successfully registered.
+    Caller is responsible for ensuring this is only called when: the job is
+    in ``"error"`` state, the original transport was XET, and HTTP is available.
+
+    Derives variant and blob-hash metadata from the registry entry written by
+    the original XET claim so callers do not re-construct worker arguments.
+    Re-queries peer protection hashes at spawn time to reflect any concurrent
+    sibling changes between the XET failure and this call.
+    """
+    original_metadata = registry.get_job_metadata(key)
+    if original_metadata is None:
+        logger.debug("%s XET retry skipped for %s; metadata unavailable", log_prefix, label)
+        _set_retry_failure_state(
+            registry,
+            key,
+            "XET retry skipped: metadata unavailable",
+            repo_type = repo_type,
+            repo_id = repo_id,
+            fallback_variant = download_registry.variant_from_key(key),
+            fallback_transport = download_registry.TRANSPORT_XET,
+            logger = logger,
+        )
+        return False
+    if original_metadata.transport != download_registry.TRANSPORT_XET:
+        logger.debug(
+            "%s XET retry skipped for %s; original transport was %s",
+            log_prefix,
+            label,
+            original_metadata.transport,
+        )
+        _set_retry_failure_state(
+            registry,
+            key,
+            f"XET retry skipped: original transport was {original_metadata.transport}",
+            repo_type = repo_type,
+            repo_id = repo_id,
+            fallback_variant = original_metadata.variant,
+            fallback_transport = original_metadata.transport,
+            logger = logger,
+        )
+        return False
+    variant = original_metadata.variant
+    blob_hashes = original_metadata.blob_hashes
+    progress_blob_hashes = original_metadata.progress_blob_hashes
+    completed_baseline_bytes = (
+        download_registry.completed_blob_bytes(
+            repo_type,
+            repo_id,
+            progress_blob_hashes,
+        )
+        if progress_blob_hashes
+        else 0
+    )
+    generation = registry.current_generation(key)
+    registry.release_active_slot(key)
+    while True:
+        if registry.cancel_requested(key):
+            _set_retry_failure_state(
+                registry,
+                key,
+                "HTTP retry cancelled before reclaiming the download slot",
+                repo_type = repo_type,
+                repo_id = repo_id,
+                fallback_variant = variant,
+                fallback_transport = original_metadata.transport,
+                logger = logger,
+            )
+            return False
+
+        claimed, conflict_state = registry.claim(
+            key,
+            download_registry.TRANSPORT_HTTP,
+            repo_type = repo_type,
+            repo_id = repo_id,
+            variant = variant,
+            blob_hashes = blob_hashes,
+            progress_blob_hashes = progress_blob_hashes,
+            completed_baseline_bytes = completed_baseline_bytes,
+            generation = generation,
+            replace_active = True,
+            cancel_marker_transport = original_metadata.transport,
+        )
+        if claimed:
+            break
+        if conflict_state == "deleting":
+            logger.debug(
+                "%s XET retry claim rejected for %s; repo is being deleted",
+                log_prefix,
+                label,
+            )
+            _set_retry_failure_state(
+                registry,
+                key,
+                "HTTP retry could not reclaim the download slot",
+                repo_type = repo_type,
+                repo_id = repo_id,
+                fallback_variant = variant,
+                fallback_transport = original_metadata.transport,
+                logger = logger,
+            )
+            return False
+        logger.debug(
+            "%s XET retry claim blocked for %s by active sibling state %s; waiting",
+            log_prefix,
+            label,
+            conflict_state,
+        )
+        time.sleep(0.05)
+
+    args: list[str] = ["--repo-id", repo_id]
+    if repo_type == "dataset":
+        args.append("--dataset")
+    elif variant:
+        args.extend(["--variant", variant])
+
+    # Re-query at spawn time: sibling state may have changed since XET failed.
+    peer_hashes = registry.peer_blob_hashes(key) if variant else frozenset()
+
+    logger.warning(
+        "%s XET worker failed for %s; retrying over HTTP",
+        log_prefix,
+        label,
+    )
+    try:
+        proc = spawn_worker(
+            args,
+            hf_token,
+            use_xet = False,
+            protected_blob_hashes = peer_hashes or None,
+        )
+    except Exception as exc:
+        scrubbed = download_registry.scrub_secrets(str(exc), hf_token = hf_token)
+        logger.error(
+            "%s HTTP retry spawn failed for %s: %s",
+            log_prefix,
+            label,
+            scrubbed,
+        )
+        registry.update_job_transport(key, original_metadata.transport)
+        _set_retry_failure_state(
+            registry,
+            key,
+            scrubbed,
+            repo_type = repo_type,
+            repo_id = repo_id,
+            fallback_variant = variant,
+            fallback_transport = original_metadata.transport,
+            logger = logger,
+        )
+        return False
+
+    return register_worker(
+        registry,
+        key,
+        proc,
+        hf_token = hf_token,
+        label = label,
+        log_prefix = log_prefix,
+        logger = logger,
+        repo_type = repo_type,
+        repo_id = repo_id,
+        transport = download_registry.TRANSPORT_HTTP,
+        cancel_marker_transport = original_metadata.transport,
+        watch_name = watch_name,
+    )
 
 
 def kill_and_reap_process(
@@ -309,6 +522,7 @@ def register_worker(
     repo_type: RepoType,
     repo_id: str,
     transport: str,
+    cancel_marker_transport: Optional[str] = None,
     watch_name: str,
 ) -> bool:
     if not registry.register_process(key, proc):
@@ -319,7 +533,14 @@ def register_worker(
 
     def _watch() -> None:
         try:
-            finalize_worker_exit(
+            can_retry_http = (
+                transport == download_registry.TRANSPORT_XET
+                and download_registry.download_transport_unavailable_reason(
+                    download_registry.TRANSPORT_HTTP
+                )
+                is None
+            )
+            state = finalize_worker_exit(
                 registry,
                 key,
                 proc,
@@ -330,7 +551,25 @@ def register_worker(
                 repo_type = repo_type,
                 repo_id = repo_id,
                 transport = transport,
+                cancel_marker_transport = cancel_marker_transport,
+                defer_error = can_retry_http,
             )
+            # XET-to-HTTP recovery: when a non-cancelled XET worker fails and
+            # HTTP is available, attempt one automatic retry over HTTP.  The
+            # transport check is the recursion guard: an HTTP worker that errors
+            # never satisfies `transport == TRANSPORT_XET`, so it stays terminal.
+            if can_retry_http and state == "error":
+                _try_http_retry(
+                    registry,
+                    key,
+                    hf_token = worker_token,
+                    label = label,
+                    log_prefix = log_prefix,
+                    logger = logger,
+                    repo_type = repo_type,
+                    repo_id = repo_id,
+                    watch_name = watch_name,
+                )
         except Exception:
             # finalize_worker_exit is the only thing that clears running/cancelling;
             # if it raises, force a terminal state so claim() isn't blocked until restart.
@@ -426,8 +665,19 @@ def cancel_worker(
             return "cancelling"
         return registry.get_job(key).state
     # Worker already exited; let its watcher classify the real return code.
-    # Arming a pending cancel here could mislabel a genuine failure as a cancel.
     if proc.poll() is not None:
+        get_metadata = getattr(registry, "get_job_metadata", None)
+        metadata = get_metadata(key) if get_metadata is not None else None
+        can_retry_http = (
+            metadata is not None
+            and metadata.transport == download_registry.TRANSPORT_XET
+            and download_registry.download_transport_unavailable_reason(
+                download_registry.TRANSPORT_HTTP
+            )
+            is None
+        )
+        if can_retry_http and registry.mark_pending_cancel(key, generation):
+            return "cancelling"
         return registry.get_job(key).state
 
     if not registry.request_cancel(key, proc, generation):
diff --git a/studio/backend/hub/tests/test_download_lifecycle.py b/studio/backend/hub/tests/test_download_lifecycle.py
index a4baafa317..87346573b0 100644
--- a/studio/backend/hub/tests/test_download_lifecycle.py
+++ b/studio/backend/hub/tests/test_download_lifecycle.py
@@ -1,27 +1,147 @@
 # SPDX-License-Identifier: AGPL-3.0-only
 # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
+import io
+import logging
+
 from hub.services import download_lifecycle
+from hub.utils import download_registry, state_dir
 
 
-def _set_xet_reason(monkeypatch, reason):
+class _Proc:
+    pid = 4242
+
+    def __init__(
+        self,
+        rc,
+        stderr = b"",
+    ):
+        self.rc = rc
+        self.stderr = io.BytesIO(stderr)
+        self.waited = False
+
+    def poll(self):
+        return self.rc if self.waited else None
+
+    def wait(self, timeout = None):
+        self.waited = True
+        return self.rc
+
+    def kill(self):
+        pass
+
+
+class _ImmediateThread:
+    def __init__(self, *, target, **_kwargs):
+        self.target = target
+
+    def start(self):
+        self.target()
+
+
+def test_resolve_effective_use_xet(monkeypatch):
+    for requested, unavailable_reason, expected in (
+        (False, "unused", False),
+        (True, None, True),
+        (True, "hf_xet is not installed", False),
+    ):
+        monkeypatch.setattr(
+            download_lifecycle.download_registry,
+            "download_transport_unavailable_reason",
+            lambda _transport, reason = unavailable_reason: reason,
+        )
+        assert download_lifecycle.resolve_effective_use_xet(requested) is expected
+
+
+def test_xet_failure_retries_over_http_for_model_and_dataset(monkeypatch, tmp_path):
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path / "state")
+    monkeypatch.setattr(download_lifecycle.threading, "Thread", _ImmediateThread)
+    register_worker = download_lifecycle.register_worker
+
+    for repo_type, repo_id, variant, expected_args in (
+        ("model", "Org/Model", "Q4_K_M", ["--repo-id", "Org/Model", "--variant", "Q4_K_M"]),
+        ("dataset", "Org/Data", None, ["--repo-id", "Org/Data", "--dataset"]),
+    ):
+        registry = download_registry.DownloadRegistry()
+        key = download_registry.normalize_job_key(f"{repo_id}::{variant}" if variant else repo_id)
+        assert registry.claim(
+            key,
+            download_registry.TRANSPORT_XET,
+            repo_type = repo_type,
+            repo_id = repo_id,
+            variant = variant,
+            blob_hashes = frozenset({"blob"}),
+        )[0]
+        generation = registry.current_generation(key)
+        spawned = []
+
+        def fake_spawn(
+            args,
+            _token,
+            *,
+            use_xet,
+            protected_blob_hashes = None,
+        ):
+            spawned.append((args, use_xet, protected_blob_hashes))
+            return _Proc(0)
+
+        def fake_retry_register(*_args, **kwargs):
+            assert kwargs["transport"] == download_registry.TRANSPORT_HTTP
+            return True
+
+        monkeypatch.setattr(download_lifecycle, "spawn_worker", fake_spawn)
+        monkeypatch.setattr(download_lifecycle, "register_worker", fake_retry_register)
+        assert register_worker(
+            registry,
+            key,
+            _Proc(1, b"xet failed"),
+            hf_token = None,
+            label = repo_id,
+            log_prefix = "Download",
+            logger = logging.getLogger("test"),
+            repo_type = repo_type,
+            repo_id = repo_id,
+            transport = download_registry.TRANSPORT_XET,
+            watch_name = f"{repo_type}-watch",
+        )
+
+        metadata = registry.get_job_metadata(key)
+        assert spawned == [(expected_args, False, None)]
+        assert metadata.transport == download_registry.TRANSPORT_HTTP
+        assert metadata.blob_hashes == frozenset({"blob"})
+        assert registry.current_generation(key) == generation
+
+
+def test_http_failure_remains_terminal(monkeypatch, tmp_path):
+    monkeypatch.setattr(state_dir, "cache_root", lambda: tmp_path / "state")
+    monkeypatch.setattr(download_lifecycle.threading, "Thread", _ImmediateThread)
+    register_worker = download_lifecycle.register_worker
+    registry = download_registry.DownloadRegistry()
+    key = download_registry.normalize_repo_key("Org/Data")
+    assert registry.claim(
+        key,
+        download_registry.TRANSPORT_HTTP,
+        repo_type = "dataset",
+        repo_id = "Org/Data",
+    )[0]
     monkeypatch.setattr(
-        download_lifecycle.download_registry,
-        "download_transport_unavailable_reason",
-        lambda _transport: reason,
+        download_lifecycle,
+        "register_worker",
+        lambda *_args, **_kwargs: (_ for _ in ()).throw(
+            AssertionError("HTTP failures must not retry")
+        ),
     )
-
-
-def test_resolve_effective_use_xet_keeps_http_when_not_requested(monkeypatch):
-    _set_xet_reason(monkeypatch, "should not be consulted")
-    assert download_lifecycle.resolve_effective_use_xet(False) is False
-
-
-def test_resolve_effective_use_xet_keeps_xet_when_available(monkeypatch):
-    _set_xet_reason(monkeypatch, None)
-    assert download_lifecycle.resolve_effective_use_xet(True) is True
-
-
-def test_resolve_effective_use_xet_downgrades_when_xet_unavailable(monkeypatch):
-    _set_xet_reason(monkeypatch, "Xet transport is unavailable because hf_xet is not installed.")
-    assert download_lifecycle.resolve_effective_use_xet(True) is False
+    assert register_worker(
+        registry,
+        key,
+        _Proc(1, b"http failed"),
+        hf_token = None,
+        label = "Org/Data",
+        log_prefix = "Download",
+        logger = logging.getLogger("test"),
+        repo_type = "dataset",
+        repo_id = "Org/Data",
+        transport = download_registry.TRANSPORT_HTTP,
+        watch_name = "dataset-watch",
+    )
+    assert registry.get_job(key).state == "error"
diff --git a/studio/backend/hub/utils/download_registry.py b/studio/backend/hub/utils/download_registry.py
index 777d63e1b5..274038b292 100644
--- a/studio/backend/hub/utils/download_registry.py
+++ b/studio/backend/hub/utils/download_registry.py
@@ -45,7 +45,7 @@ import sys
 import threading
 import time
 import weakref
-from dataclasses import dataclass, field
+from dataclasses import dataclass, field, replace
 from pathlib import Path
 from typing import Iterator, Literal, Optional
 
@@ -126,6 +126,9 @@ def write_worker_breadcrumb(key: str, pid: int, metadata: Optional["DownloadMeta
         "repo_id": metadata.repo_id if metadata is not None else None,
         "variant": metadata.variant if metadata is not None else None,
         "transport": metadata.transport if metadata is not None else None,
+        "cancel_marker_transport": metadata.cancel_marker_transport
+        if metadata is not None
+        else None,
     }
     tmp = path.with_name(f".{path.name}.tmp-{pid}")
     try:
@@ -305,7 +308,7 @@ def reap_orphan_workers() -> None:
                 data.get("repo_type"),
                 repo_id,
                 data.get("variant"),
-                data.get("transport"),
+                data.get("cancel_marker_transport") or data.get("transport"),
             )
         except Exception as exc:
             logger.debug("Reaper failed for breadcrumb %s: %s", entry, exc)
@@ -699,6 +702,7 @@ class DownloadMetadata:
     repo_id: str
     variant: Optional[str]
     transport: Optional[str]
+    cancel_marker_transport: Optional[str] = None
     # GGUF variant main/writable hashes, identifying the variant-specific shards
     # for concurrency decisions.
     blob_hashes: frozenset[str] = field(default_factory = frozenset)
@@ -801,6 +805,7 @@ class DownloadRegistry:
         self._processes: dict[str, subprocess.Popen] = {}
         self._repo_active: dict[str, set[str]] = {}
         self._metadata: dict[str, DownloadMetadata] = {}
+        self._cancel_marker_transports: dict[str, str] = {}
         self._pending_cancel: dict[str, Optional[int]] = {}
         self._generations: dict[str, int] = {}
         # Monotonic across keys so an evicted then re-claimed key never reuses a
@@ -839,6 +844,7 @@ class DownloadRegistry:
             if state in TERMINAL_STATES:
                 self._put_terminal_job_locked(key, state, error)
                 self._pending_cancel.pop(key, None)
+                self._cancel_marker_transports.pop(key, None)
                 repo = _repo_of_key(key)
                 active = self._repo_active.get(repo)
                 if active is not None:
@@ -848,6 +854,57 @@ class DownloadRegistry:
             else:
                 self._jobs[key] = DownloadState(state, error)
 
+    def set_error_unless_cancelled(
+        self, key: str, error: str
+    ) -> tuple[JobState, Optional[DownloadMetadata]]:
+        key = normalize_job_key(key)
+        with self._lock:
+            current = self._jobs.get(key, DownloadState("idle")).state
+            has_pending_cancel = key in self._pending_cancel
+            pending_generation = self._pending_cancel.get(key)
+            metadata = self._metadata.get(key)
+            should_cancel = current == "cancelling" or (
+                has_pending_cancel and self._generation_matches_locked(key, pending_generation)
+            )
+            terminal_state: JobState = "cancelled" if should_cancel else "error"
+            marker_transport = self._cancel_marker_transports.pop(key, None)
+            if marker_transport is None and metadata is not None:
+                marker_transport = metadata.cancel_marker_transport
+            self._put_terminal_job_locked(
+                key,
+                terminal_state,
+                None if should_cancel else error,
+            )
+            self._pending_cancel.pop(key, None)
+            repo = _repo_of_key(key)
+            active = self._repo_active.get(repo)
+            if active is not None:
+                active.discard(key)
+                if not active:
+                    self._repo_active.pop(repo, None)
+            if should_cancel and metadata is not None and marker_transport is not None:
+                metadata = replace(metadata, transport = marker_transport)
+            return terminal_state, metadata
+
+    def update_job_transport(self, key: str, transport: str) -> None:
+        key = normalize_job_key(key)
+        with self._lock:
+            metadata = self._metadata.get(key)
+            if metadata is None or metadata.transport == transport:
+                return
+            self._metadata[key] = replace(metadata, transport = transport)
+
+    def release_active_slot(self, key: str) -> None:
+        key = normalize_job_key(key)
+        repo = _repo_of_key(key)
+        with self._lock:
+            active = self._repo_active.get(repo)
+            if active is None:
+                return
+            active.discard(key)
+            if not active:
+                self._repo_active.pop(repo, None)
+
     def get_job(self, key: str) -> DownloadState:
         key = normalize_job_key(key)
         with self._lock:
@@ -884,6 +941,14 @@ class DownloadRegistry:
             ):
                 self._put_terminal_job_locked(key, "cancelled")
                 metadata_to_persist = self._metadata.pop(key, None)
+                marker_transport = self._cancel_marker_transports.pop(key, None)
+                if marker_transport is None and metadata_to_persist is not None:
+                    marker_transport = metadata_to_persist.cancel_marker_transport
+                if metadata_to_persist is not None and marker_transport is not None:
+                    metadata_to_persist = replace(
+                        metadata_to_persist,
+                        transport = marker_transport,
+                    )
                 repo = _repo_of_key(key)
                 active = self._repo_active.get(repo)
                 if active is not None:
@@ -963,6 +1028,10 @@ class DownloadRegistry:
         blob_hashes: Optional[frozenset[str]] = None,
         progress_blob_hashes: Optional[frozenset[str]] = None,
         completed_baseline_bytes: int = 0,
+        generation: Optional[int] = None,
+        replace_active: bool = False,
+        metadata_transport: Optional[str] = None,
+        cancel_marker_transport: Optional[str] = None,
     ) -> tuple[bool, str]:
         key = normalize_job_key(key)
         repo = _repo_of_key(key)
@@ -1007,10 +1076,13 @@ class DownloadRegistry:
             if conflict_state is not None:
                 return False, conflict_state
             current = self._jobs.get(key, DownloadState("idle")).state
-            if current in _ACTIVE_STATES:
+            if current in _ACTIVE_STATES and not replace_active:
                 return False, current
-            self._generation_seq += 1
-            self._generations[key] = self._generation_seq
+            if generation is None:
+                self._generation_seq += 1
+                self._generations[key] = self._generation_seq
+            else:
+                self._generations[key] = generation
             self._jobs[key] = DownloadState("running")
             self._repo_active.setdefault(repo, active).add(key)
             if repo_type and repo_id:
@@ -1018,7 +1090,8 @@ class DownloadRegistry:
                     repo_type = repo_type,
                     repo_id = repo_id,
                     variant = variant,
-                    transport = transport,
+                    transport = metadata_transport if metadata_transport is not None else transport,
+                    cancel_marker_transport = cancel_marker_transport,
                     blob_hashes = requested_hashes,
                     progress_blob_hashes = requested_progress_hashes,
                     completed_baseline_bytes = max(
@@ -1026,8 +1099,13 @@ class DownloadRegistry:
                         int(completed_baseline_bytes or 0),
                     ),
                 )
+                if cancel_marker_transport is not None:
+                    self._cancel_marker_transports[key] = cancel_marker_transport
+                else:
+                    self._cancel_marker_transports.pop(key, None)
             else:
                 self._metadata.pop(key, None)
+                self._cancel_marker_transports.pop(key, None)
             return True, "running"
 
     def adoptable(self, key: str) -> bool:
@@ -1053,7 +1131,8 @@ class DownloadRegistry:
         download. A variant delete conflicts only with that same variant or a
         whole-repo download writing the shared snapshot; other quantizations
         download concurrently and never block it."""
-        for key in self._repo_active.get(repo_id, set()):
+        active_keys = self._repo_active.get(repo_id, set())
+        for key in active_keys:
             job = self._jobs.get(key)
             if job is None or job.state not in _ACTIVE_STATES:
                 continue
@@ -1062,6 +1141,16 @@ class DownloadRegistry:
             other_variant = self._active_job_variant_locked(key)
             if other_variant is None or other_variant == variant:
                 return True
+        for key, job in self._jobs.items():
+            if key in active_keys or _repo_of_key(key) != repo_id:
+                continue
+            if job.state not in _ACTIVE_STATES:
+                continue
+            if variant is None:
+                return True
+            other_variant = self._active_job_variant_locked(key)
+            if other_variant is None or other_variant == variant:
+                return True
         return False
 
     def peer_blob_hashes(self, key: str) -> frozenset[str]:
@@ -1108,6 +1197,16 @@ class DownloadRegistry:
                 candidate_keys = list(self._repo_active.get(repo_key, set()))
             else:
                 candidate_keys = [key for active in self._repo_active.values() for key in active]
+            # An XET->HTTP retry handoff briefly drops its key from _repo_active
+            # while its job stays active; include those released-but-active jobs
+            # so the waiting retry still lists and can be adopted or cancelled.
+            seen = set(candidate_keys)
+            for key, job in self._jobs.items():
+                if key in seen or job.state not in _ACTIVE_STATES:
+                    continue
+                if repo_key is not None and _repo_of_key(key) != repo_key:
+                    continue
+                candidate_keys.append(key)
             refs: list[ActiveDownloadRef] = []
             for key in candidate_keys:
                 job = self._jobs.get(key)
@@ -1169,12 +1268,25 @@ class DownloadRegistry:
         repo_id = normalize_repo_key(repo_id)
         target = (variant or "").strip().lower() or None
         with self._lock:
-            for key in self._repo_active.get(repo_id, set()):
+            active_keys = self._repo_active.get(repo_id, set())
+            for key in active_keys:
                 job = self._jobs.get(key)
                 if job is None or job.state not in _ACTIVE_STATES:
                     continue
                 if self._active_job_variant_locked(key) != target:
                     return True
+            # An XET->HTTP retry peer between release_active_slot() and its reclaim
+            # is briefly absent from _repo_active while its job stays active and
+            # still owns the shared companion; mirror the released-but-active scan
+            # used by _delete_blocked_by_active_locked so it still blocks companion
+            # deletion of a different variant.
+            for key, job in self._jobs.items():
+                if key in active_keys or _repo_of_key(key) != repo_id:
+                    continue
+                if job.state not in _ACTIVE_STATES:
+                    continue
+                if self._active_job_variant_locked(key) != target:
+                    return True
         return False
 
     def request_cancel(
@@ -1198,17 +1310,58 @@ class DownloadRegistry:
             return True
 
     def terminate_all(self, kind: str = "download") -> None:
+        settled_no_proc: list[Optional[DownloadMetadata]] = []
         with self._lock:
             live = [
                 (key, proc, self._metadata.get(key))
                 for key, proc in self._processes.items()
                 if proc.poll() is None
             ]
+            live_keys = {key for key, _proc, _metadata in live}
             # Flag as an intentional stop so the watcher's exit classification
             # reports them cancelled rather than an OOM/crash once SIGKILL lands.
             for key, _proc, _metadata in live:
                 if self._jobs.get(key, DownloadState("idle")).state == "running":
                     self._jobs[key] = DownloadState("cancelling")
+            # Settle active jobs without a live worker too. Two cases: an
+            # XET->HTTP retry parked in the reclaim wait loop has dropped its
+            # worker and slot guard, so it is absent from `live`; and a
+            # registered worker that already exited with an error but whose
+            # watcher has not yet run would otherwise stay `running` and spawn an
+            # HTTP retry after this shutdown snapshot. Skip a registered worker
+            # that exited cleanly (rc == 0): it completed and the watcher will
+            # mark it done, so marking it cancelling would strand a stale marker.
+            for key, job in list(self._jobs.items()):
+                if job.state not in _ACTIVE_STATES or key in live_keys:
+                    continue
+                proc = self._processes.get(key)
+                if proc is not None:
+                    if proc.poll() == 0:
+                        continue
+                    # A registered worker that exited nonzero on its own over HTTP
+                    # is a genuine terminal download failure, not a shutdown cancel
+                    # and not retry-capable: leave its error status intact rather
+                    # than persisting a cancel marker that would read as
+                    # cancelled/resumable after restart. Only an exited XET worker
+                    # could still spawn a post-shutdown HTTP retry, so only that
+                    # needs settling here.
+                    metadata = self._metadata.get(key)
+                    if metadata is not None and metadata.transport == TRANSPORT_HTTP:
+                        continue
+                self._pending_cancel[key] = self._generations.get(key)
+                self._jobs[key] = DownloadState("cancelling")
+                settled_no_proc.append(self._metadata.get(key))
+        # Persist a cancel marker for each settled no-live-worker job outside the
+        # lock (mirroring the reaped path) so shutdown records resumable/cancelled
+        # state even if it returns before the daemon watcher wakes to do so.
+        for metadata in settled_no_proc:
+            if metadata is not None:
+                persist_cancel_marker(
+                    metadata.repo_type,
+                    metadata.repo_id,
+                    metadata.variant,
+                    metadata.cancel_marker_transport or metadata.transport,
+                )
         reaped: list[tuple[str, subprocess.Popen, Optional[DownloadMetadata]]] = []
         for key, proc, metadata in live:
             try:
@@ -1222,7 +1375,7 @@ class DownloadRegistry:
                         metadata.repo_type,
                         metadata.repo_id,
                         metadata.variant,
-                        metadata.transport,
+                        metadata.cancel_marker_transport or metadata.transport,
                     )
                 continue
             reaped.append((key, proc, metadata))
@@ -1242,7 +1395,7 @@ class DownloadRegistry:
                     metadata.repo_type,
                     metadata.repo_id,
                     metadata.variant,
-                    metadata.transport,
+                    metadata.cancel_marker_transport or metadata.transport,
                 )
 
 

From 57785f92d258aeb7081f37d03b63fd87ca891a58 Mon Sep 17 00:00:00 2001
From: Long Yixing <longyixing331@gmail.com>
Date: Sat, 18 Jul 2026 04:13:19 +0800
Subject: [PATCH 12/28] fix(mlx): relax context-store timeout by default
 (#7141)

---
 studio/backend/utils/hardware/hardware.py | 5 +++++
 unsloth/__init__.py                       | 5 +++++
 2 files changed, 10 insertions(+)

diff --git a/studio/backend/utils/hardware/hardware.py b/studio/backend/utils/hardware/hardware.py
index 8d6c919ebd..117ad7b780 100644
--- a/studio/backend/utils/hardware/hardware.py
+++ b/studio/backend/utils/hardware/hardware.py
@@ -49,6 +49,11 @@ logger = get_logger(__name__)
 # and spawn workers copy os.environ. setdefault so an explicit user override wins.
 os.environ.setdefault("CUDA_DEVICE_ORDER", "PCI_BUS_ID")
 
+# Studio workers can import MLX without importing unsloth first, so mirror the
+# package bootstrap here. Keep an explicit user value authoritative.
+if platform.system() == "Darwin" and platform.machine() == "arm64":
+    os.environ.setdefault("AGX_RELAX_CDM_CTXSTORE_TIMEOUT", "1")
+
 
 # ========== Device Enum ==========
 
diff --git a/unsloth/__init__.py b/unsloth/__init__.py
index de5cd0f61b..659637dd92 100644
--- a/unsloth/__init__.py
+++ b/unsloth/__init__.py
@@ -16,6 +16,11 @@ import os, importlib.util, platform
 
 os.environ["UNSLOTH_IS_PRESENT"] = "1"
 
+# Relax Metal's context-store timeout before MLX modules can initialize Metal.
+# Keep an explicit user value authoritative.
+if platform.system() == "Darwin" and platform.machine() == "arm64":
+    os.environ.setdefault("AGX_RELAX_CDM_CTXSTORE_TIMEOUT", "1")
+
 # ── Windows console UTF-8 safety ─────────────────────────────────────────────
 # Legacy Windows consoles (cp1252) can't encode Unsloth's emoji/box-drawing
 # glyphs and crash with UnicodeEncodeError. Force stdout/stderr to UTF-8 only on

From 2139200b3f7eca44ff8c6451e318aaf6a034195a Mon Sep 17 00:00:00 2001
From: oobabooga <oobabooga4@gmail.com>
Date: Fri, 17 Jul 2026 19:05:46 -0300
Subject: [PATCH 13/28] Studio: don't re-download updated GGUFs on load (#7209)

---
 studio/backend/core/inference/llama_cpp.py    | 515 +++++++++---
 .../backend/hub/services/models/downloads.py  |  30 +
 studio/backend/hub/utils/download_registry.py |  27 +-
 studio/backend/routes/inference.py            |  50 +-
 .../tests/test_gguf_load_cache_reuse.py       | 740 ++++++++++++++++++
 .../tests/test_mtp_drafter_companion.py       |  28 +
 .../tests/test_offline_gguf_cache_fallback.py |  40 +-
 7 files changed, 1264 insertions(+), 166 deletions(-)
 create mode 100644 studio/backend/tests/test_gguf_load_cache_reuse.py

diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index 3e93a26787..fec5214cf9 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -9,6 +9,7 @@ OpenAI-compatible /v1/chat/completions endpoint.
 
 import atexit
 import contextlib
+import functools
 import json
 import os
 import re
@@ -999,6 +1000,283 @@ def _cached_colocated_split_main(
     return None
 
 
+def _cached_variant_resolution(repo_id: str, hf_variant: str) -> tuple[Optional[str], list[str]]:
+    """Find a cached main GGUF and its shards for a variant."""
+    candidate = next(_cached_variant_candidates(repo_id, hf_variant), None)
+    if candidate is None:
+        return None, []
+    _, main, shards, _ = candidate
+    return main, shards
+
+
+def _cached_variant_candidates(
+    repo_id: str,
+    hf_variant: str,
+    *,
+    require_mmproj: bool = False,
+) -> Generator[tuple[str, str, list[str], Path], None, None]:
+    """Yield complete cached variant copies in snapshot preference order."""
+    try:
+        from utils.models.model_config import _iter_hf_cache_snapshots
+        for snap in _iter_hf_cache_snapshots(repo_id):
+            cached_files = _gguf_snapshot_files(snap)
+            matches = _gguf_files_for_variant(cached_files, hf_variant)
+            if not matches:
+                continue
+            main = matches[0]
+            shards = _gguf_extra_shards(matches, main)
+            split = _SHARD_FULL_RE.match(main)
+            if split:
+                numbers = {
+                    int(match.group(2))
+                    for path in [main, *shards]
+                    if (match := _SHARD_FULL_RE.match(path))
+                }
+                if numbers != set(range(1, int(split.group(3)) + 1)):
+                    continue
+            main_path = snap.joinpath(*main.replace("\\", "/").split("/"))
+            if not main_path.is_file() or not _snapshot_has_all_shards(
+                str(main_path), main, shards, {}
+            ):
+                continue
+            if require_mmproj and not _pick_mmproj(cached_files):
+                continue
+            yield str(main_path), main, shards, snap
+    except Exception as e:
+        logger.debug(f"Cache lookup for variant failed: {e}")
+
+
+def _cached_candidate_matches_revision_size(
+    repo_id: str, candidate: tuple[str, str, list[str], Path], hf_token: Optional[str]
+) -> bool:
+    """Check cached byte sizes against the snapshot's own Hub revision.
+
+    A snapshot pointer is normally published only after its blob is complete.
+    When the old revision is still queryable, also compare every weight file's
+    size so a manually truncated cache entry is not treated as reusable. If
+    metadata cannot be reached, retain the cache's normal offline semantics.
+    """
+    main_path, main, shards, snap = candidate
+    paths = [main, *shards]
+    try:
+        from huggingface_hub import get_paths_info
+        infos = list(
+            get_paths_info(
+                repo_id,
+                paths,
+                revision = snap.name,
+                token = hf_token,
+            )
+        )
+    except Exception as e:
+        logger.debug(
+            "Could not size-check cached GGUF %s at revision %s: %s",
+            repo_id,
+            snap.name,
+            e,
+        )
+        return True
+
+    if not infos:
+        # The Hub answers an unknown (e.g. force-pushed away) revision with an
+        # empty result, not an error; treat it like unreachable metadata.
+        return True
+    expected_sizes = {info.path: info.size for info in infos if info.size is not None}
+    if any(path not in expected_sizes for path in paths):
+        return False
+    try:
+        if os.path.getsize(main_path) < expected_sizes[main]:
+            return False
+    except OSError:
+        return False
+    return _snapshot_has_all_shards(main_path, main, shards, expected_sizes)
+
+
+def _cached_complete_candidate(
+    repo_id: str, gguf_filename: Optional[str], shards: list[str]
+) -> Optional[tuple[str, str, list[str], Path]]:
+    """Return one complete exact-filename cache candidate with snapshot context."""
+    if not gguf_filename:
+        return None
+    if shards:
+        main_path = _cached_colocated_split_main(repo_id, gguf_filename, shards, {})
+    else:
+        m = _SHARD_FULL_RE.match(gguf_filename)
+        if m and int(m.group(3)) > 1:
+            return None
+        main_path = _cached_hf_snapshot_file(repo_id, gguf_filename)
+    if main_path is None:
+        return None
+    snap = _snapshot_dir_of(main_path)
+    if snap is None:
+        return None
+    return main_path, gguf_filename, shards, snap
+
+
+def cached_gguf_for_load(
+    hf_repo: str,
+    hf_variant: Optional[str],
+    *,
+    require_mmproj: bool = False,
+    verify_sizes: bool = False,
+    hf_token: Optional[str] = None,
+) -> Optional[str]:
+    """Return a cached GGUF that can be loaded without downloading."""
+    if not hf_variant:
+        return None
+    hf_repo = _resolve_repo_id_casing(hf_repo)
+    for candidate in _cached_variant_candidates(
+        hf_repo,
+        hf_variant,
+        require_mmproj = require_mmproj,
+    ):
+        if verify_sizes and not _cached_candidate_matches_revision_size(
+            hf_repo, candidate, hf_token
+        ):
+            continue
+        return candidate[0]
+    return None
+
+
+def _snapshot_dir_of(path: str) -> Optional[Path]:
+    """Return the HF cache snapshot containing path, if any."""
+    try:
+        p = Path(os.path.abspath(path))
+    except OSError:
+        return None
+    for ancestor in p.parents:
+        if ancestor.parent.name == "snapshots":
+            return ancestor
+    return None
+
+
+def _companion_snapshot_sibling(
+    near_path: str, pick: Callable[[list[str]], Optional[str]]
+) -> Optional[str]:
+    """Find a companion in the same snapshot as near_path."""
+    snap = _snapshot_dir_of(near_path)
+    if snap is None:
+        return None
+    try:
+        sibling = pick(_gguf_snapshot_files(snap))
+    except Exception:
+        return None
+    if not sibling:
+        return None
+    candidate = snap / sibling
+    return str(candidate) if candidate.is_file() else None
+
+
+def _pick_mmproj(candidates: list[str]) -> Optional[str]:
+    mmproj_files = sorted(
+        f for f in candidates if f.lower().endswith(".gguf") and "mmproj" in Path(f).name.lower()
+    )
+    if not mmproj_files:
+        return None
+    return next((f for f in mmproj_files if f.lower().endswith("-f16.gguf")), mmproj_files[0])
+
+
+def _hub_download_in_flight(hf_repo: str) -> bool:
+    try:
+        from hub.utils.download_registry import get_models_registry
+        return bool(get_models_registry().active_job_refs(hf_repo))
+    except Exception:
+        return False
+
+
+def _hub_download_blocks_gguf_load(
+    hf_repo: str,
+    hf_variant: Optional[str],
+    *,
+    require_mmproj: bool = False,
+    hf_token: Optional[str] = None,
+) -> bool:
+    """Whether an active Hub job makes this GGUF load unsafe.
+
+    Same-variant jobs can reclaim the stale snapshot a load would reuse, so
+    they always block. Other jobs block only when this load lacks a complete
+    cached copy and would write to the shared cache itself.
+    """
+    try:
+        from hub.utils.download_registry import get_models_registry
+
+        registry = get_models_registry()
+        if not registry.active_job_refs(hf_repo):
+            return False
+        if registry.has_active_variant(hf_repo, hf_variant):
+            return True
+    except Exception:
+        return False
+    return (
+        cached_gguf_for_load(
+            hf_repo,
+            hf_variant,
+            require_mmproj = require_mmproj,
+            verify_sizes = True,
+            hf_token = hf_token,
+        )
+        is None
+    )
+
+
+# Active GGUF loads by normalized repo ID.
+_LOADS_IN_FLIGHT: dict[str, int] = {}
+_LOADS_IN_FLIGHT_LOCK = threading.Lock()
+
+
+@contextlib.contextmanager
+def gguf_load_in_flight(hf_repo: Optional[str]):
+    """Track an HF GGUF load until the context exits."""
+    key = (hf_repo or "").strip().lower()
+    if not key:
+        yield
+        return
+    with _LOADS_IN_FLIGHT_LOCK:
+        _LOADS_IN_FLIGHT[key] = _LOADS_IN_FLIGHT.get(key, 0) + 1
+    try:
+        yield
+    finally:
+        with _LOADS_IN_FLIGHT_LOCK:
+            remaining = _LOADS_IN_FLIGHT.get(key, 1) - 1
+            if remaining <= 0:
+                _LOADS_IN_FLIGHT.pop(key, None)
+            else:
+                _LOADS_IN_FLIGHT[key] = remaining
+
+
+def hf_gguf_load_in_flight(hf_repo: str) -> bool:
+    """Return whether a GGUF load is active for hf_repo."""
+    key = (hf_repo or "").strip().lower()
+    if not key:
+        return False
+    with _LOADS_IN_FLIGHT_LOCK:
+        return _LOADS_IN_FLIGHT.get(key, 0) > 0
+
+
+def _with_gguf_load_marker(load: Callable):
+    """Keep an HF repo marked for the full synchronous load call."""
+
+    @functools.wraps(load)
+    def wrapped(self, *args, **kwargs):
+        hf_repo = kwargs.get("hf_repo")
+        with gguf_load_in_flight(hf_repo):
+            if hf_repo and _hub_download_blocks_gguf_load(
+                hf_repo,
+                kwargs.get("hf_variant"),
+                require_mmproj = bool(
+                    kwargs.get("is_vision")
+                    and not extra_args_disable_mmproj(kwargs.get("extra_args"))
+                ),
+                hf_token = kwargs.get("hf_token"),
+            ):
+                raise RuntimeError(
+                    f"'{hf_repo}' is currently being downloaded by the download manager"
+                )
+            return load(self, *args, **kwargs)
+
+    return wrapped
+
+
 def _gguf_extra_shards(files: Iterable[str], first_shard: str) -> list[str]:
     m = _SHARD_FULL_RE.match(first_shard)
     if not m:
@@ -3806,13 +4084,13 @@ class LlamaCppBackend:
         hf_repo: str,
         free_bytes: int,
         hf_token: Optional[str] = None,
-    ) -> Optional[tuple[str, int]]:
+    ) -> Optional[tuple[str, int, list[str]]]:
         """Find the smallest GGUF variant (including all shards) that fits.
 
         Groups split shards by variant prefix and sums their sizes (e.g.
         UD-Q4_K_XL with 9 shards of 50 GB each = 450 GB total).
 
-        Returns (first_shard_filename, total_size_bytes) or None.
+        Returns (first_shard_filename, total_size_bytes, extra_shards) or None.
         """
         try:
             from huggingface_hub import get_paths_info, list_repo_files
@@ -3848,9 +4126,13 @@ class LlamaCppBackend:
 
             # Smallest that fits
             variant_sizes.sort(key = lambda x: x[1])
-            for first_file, total_size, _ in variant_sizes:
+            for first_file, total_size, shard_files in variant_sizes:
                 if total_size > 0 and total_size <= free_bytes:
-                    return first_file, total_size
+                    return (
+                        first_file,
+                        total_size,
+                        [path for path in sorted(shard_files) if path != first_file],
+                    )
 
             return None
         except Exception:
@@ -4446,42 +4728,52 @@ class LlamaCppBackend:
             except Exception as e:
                 logger.warning(f"Could not list repo files: {e}")
 
-            # Offline: resolve variant -> filename from the local HF cache.
-            # The heuristic below assumes filenames echo the repo name, which
-            # breaks for e.g. Qwen3.6-27B-MTP-GGUF (no "MTP" in file). Match
-            # against the rel path (not just basename) so subdir layouts like
-            # ``BF16/foo.gguf`` are findable.
+            # Fall back to the local cache when the repo listing is unavailable.
             if not gguf_filename:
-                try:
-                    from utils.models.model_config import _iter_hf_cache_snapshots
-                    for snap in _iter_hf_cache_snapshots(hf_repo):
-                        cached_files = _gguf_snapshot_files(snap)
-                        matches = _gguf_files_for_variant(cached_files, hf_variant)
-                        if not matches:
-                            continue
-                        gguf_filename = matches[0]
-                        gguf_extra_shards = _gguf_extra_shards(matches, gguf_filename)
-                        logger.info(
-                            "Resolved variant %s -> %s from local HF cache",
-                            hf_variant,
-                            gguf_filename,
-                        )
-                        break
-                except Exception as e:
-                    logger.debug(f"Offline cache lookup for variant failed: {e}")
+                cached_name, cached_shards = _cached_variant_resolution(hf_repo, hf_variant)
+                if cached_name:
+                    gguf_filename = cached_name
+                    gguf_extra_shards = cached_shards
+                    logger.info(
+                        "Resolved variant %s -> %s from local HF cache",
+                        hf_variant,
+                        gguf_filename,
+                    )
 
             if not gguf_filename:
                 repo_name = hf_repo.split("/")[-1].replace("-GGUF", "")
                 gguf_filename = f"{repo_name}-{hf_variant}.gguf"
 
+        # Prefer the existing model. Updates use force=True to fetch a new revision.
+        if not force:
+            if hf_variant:
+                # Resolve by variant so a newer revision's filename does not hide
+                # the complete older copy. Size-check against that older snapshot's
+                # own revision when its metadata remains available.
+                cached_main = cached_gguf_for_load(
+                    hf_repo,
+                    hf_variant,
+                    verify_sizes = True,
+                    hf_token = hf_token,
+                )
+            else:
+                candidate = _cached_complete_candidate(hf_repo, gguf_filename, gguf_extra_shards)
+                cached_main = (
+                    candidate[0]
+                    if candidate is not None
+                    and _cached_candidate_matches_revision_size(hf_repo, candidate, hf_token)
+                    else None
+                )
+            if cached_main is not None:
+                logger.info(f"Reusing cached GGUF: {cached_main}")
+                return cached_main
+
         # Check disk space; fall back to a smaller variant if needed
         all_gguf_files = [gguf_filename] + gguf_extra_shards
-        expected_sizes: dict[str, int] = {}
         try:
             from huggingface_hub import get_paths_info, try_to_load_from_cache
 
             path_infos = list(get_paths_info(hf_repo, all_gguf_files, token = hf_token))
-            expected_sizes = {p.path: p.size for p in path_infos if p.size}
             total_bytes = sum((p.size or 0) for p in path_infos)
 
             # Subtract bytes already in the HF cache so we only preflight
@@ -4490,25 +4782,10 @@ class LlamaCppBackend:
             # cold whenever free disk is below the full weight footprint,
             # even though nothing needs downloading.
             already_cached_bytes = 0
-            # Cross-snapshot / case-variant cache reuse is offline-only (see the download
-            # path below); online, hf_hub_download fetches the current revision and
-            # resumes partials, so an old snapshot must not be counted as cached here or
-            # the preflight would under-count the download and skip the disk fallback.
+            # Count only files that can resume this download.
             offline = _hf_env_offline()
-            # A split GGUF whose shards are not co-located in a single snapshot is
-            # refetched as a whole set later, so it must not be counted as cached here.
-            split_needs_refetch = False
-            if offline and not force and gguf_extra_shards:
-                # Scan all snapshots for one that holds the whole set co-located, so a
-                # newer snapshot with only the first shard does not mask an older
-                # complete one and needlessly trip the disk fallback.
-                if (
-                    _cached_colocated_split_main(
-                        hf_repo, gguf_filename, gguf_extra_shards, expected_sizes
-                    )
-                    is None
-                ):
-                    split_needs_refetch = True
+            # Offline split sets are reusable only when every shard shares a snapshot.
+            split_needs_refetch = bool(offline and not force and gguf_extra_shards)
             if not force and not split_needs_refetch:
                 for p in path_infos:
                     if not p.size:
@@ -4569,32 +4846,26 @@ class LlamaCppBackend:
                         hf_token,
                     )
                     if smaller:
-                        fallback_file, fallback_size = smaller
+                        fallback_file, fallback_size, fallback_shards = smaller
                         logger.info(
                             f"Selected variant too large ({total_gb:.1f} GB), "
                             f"falling back to {fallback_file} ({fallback_size / (1024**3):.1f} GB)"
                         )
                         gguf_filename = fallback_file
-                        _m = _SHARD_RE.match(gguf_filename)
-                        _prefix = _m.group(1) if _m else None
-                        if _prefix:
-                            prefix_lower = _prefix.lower()
-                            gguf_extra_shards = sorted(
-                                f
-                                for f in all_gguf_files
-                                if f.lower().startswith(prefix_lower)
-                                and f != gguf_filename
-                                and not _is_companion_gguf_path(f)
+                        gguf_extra_shards = fallback_shards
+
+                        # The selected fallback is a new load target. Apply the
+                        # same any-revision reuse policy before starting a fetch.
+                        fallback_candidate = _cached_complete_candidate(
+                            hf_repo, gguf_filename, gguf_extra_shards
+                        )
+                        if fallback_candidate is not None and (
+                            _cached_candidate_matches_revision_size(
+                                hf_repo, fallback_candidate, hf_token
                             )
-                        else:
-                            gguf_extra_shards = []
-                        # Record the fallback's size so the later cache-reuse probe can
-                        # size-verify it; only for a single-file fallback, since
-                        # _find_smallest_fitting_variant returns the whole-variant size
-                        # and using that as the first shard's expected size would reject
-                        # a valid cached first shard of a split fallback.
-                        if not gguf_extra_shards:
-                            expected_sizes[fallback_file] = fallback_size
+                        ):
+                            logger.info(f"Reusing cached fallback GGUF: {fallback_candidate[0]}")
+                            return fallback_candidate[0]
                     else:
                         raise RuntimeError(
                             f"Not enough disk space to download any variant. "
@@ -4614,45 +4885,25 @@ class LlamaCppBackend:
                 raise RuntimeError("Cancelled")
             dl_start = time.monotonic()
             # Xet primary, HTTP fallback on stall; per-file so finished shards stay cached.
-            local_path = None
-            # Reuse a cached copy from another snapshot / case-variant repo dir only when
-            # offline. Online, fall through to hf_hub_download so its revision/etag check
-            # fetches the current file (and resumes a partial) instead of serving a stale
-            # same-name blob from an older revision.
-            if not force and _hf_env_offline():
-                if gguf_extra_shards:
-                    # A split GGUF must load every shard from one snapshot; reuse only a
-                    # snapshot that holds the whole set co-located, scanning past a newer
-                    # snapshot that has just the first shard while an older one is complete.
-                    local_path = _cached_colocated_split_main(
-                        hf_repo, gguf_filename, gguf_extra_shards, expected_sizes
-                    )
-                else:
-                    local_path = _cached_hf_snapshot_file(
-                        hf_repo,
-                        gguf_filename,
-                        expected_size = expected_sizes.get(gguf_filename),
-                    )
-            if local_path is None:
-                local_path = hf_hub_download_with_xet_fallback(
+            local_path = hf_hub_download_with_xet_fallback(
+                hf_repo,
+                gguf_filename,
+                hf_token,
+                cancel_event = cancel_event,
+                on_status = lambda m: logger.info(m),
+                force_download = force,
+            )
+            for shard in gguf_extra_shards:
+                if cancel_event.is_set():
+                    raise RuntimeError("Cancelled")
+                logger.info(f"Resolving GGUF shard: {shard}")
+                hf_hub_download_with_xet_fallback(
                     hf_repo,
-                    gguf_filename,
+                    shard,
                     hf_token,
                     cancel_event = cancel_event,
-                    on_status = lambda m: logger.info(m),
                     force_download = force,
                 )
-                for shard in gguf_extra_shards:
-                    if cancel_event.is_set():
-                        raise RuntimeError("Cancelled")
-                    logger.info(f"Resolving GGUF shard: {shard}")
-                    hf_hub_download_with_xet_fallback(
-                        hf_repo,
-                        shard,
-                        hf_token,
-                        cancel_event = cancel_event,
-                        force_download = force,
-                    )
         except Exception as e:
             if isinstance(e, RuntimeError) and "Cancelled" in str(e):
                 raise
@@ -4675,10 +4926,12 @@ class LlamaCppBackend:
         pick: Callable[[list[str]], Optional[str]],
         label: str,
         cancel_event: Optional[threading.Event] = None,
+        near_path: Optional[str] = None,
     ) -> Optional[str]:
         """Resolve and fetch a companion GGUF (mmproj / MTP drafter) by name.
 
-        Tries the live repo file list, then the local HF cache snapshots
+        Prefers a companion co-located with ``near_path``'s cache snapshot,
+        then tries the live repo file list, then the local HF cache snapshots
         (offline, same fallback as _download_gguf), then hf_hub_download.
         Runs WITHOUT self._lock (like _download_gguf); honors _cancel_event so
         an /unload between the main download and here skips the fetch.
@@ -4688,6 +4941,17 @@ class LlamaCppBackend:
         if cancel_event.is_set():
             return None
 
+        # Keep companion files in the main GGUF's snapshot.
+        if near_path:
+            cached = _companion_snapshot_sibling(near_path, pick)
+            if cached:
+                logger.info("Reusing cached %s: %s", label, cached)
+                return cached
+
+        if _hub_download_in_flight(hf_repo):
+            logger.info("Skipping %s download while a hub download is active", label)
+            return None
+
         target: Optional[str] = None
         from huggingface_hub import list_repo_files
 
@@ -4760,33 +5024,23 @@ class LlamaCppBackend:
         hf_repo: str,
         hf_token: Optional[str] = None,
         cancel_event: Optional[threading.Event] = None,
+        near_path: Optional[str] = None,
     ) -> Optional[str]:
         """Download the mmproj (vision projection) file from a GGUF repo.
 
         Prefers mmproj-F16.gguf, else any mmproj*.gguf. Returns the local
         path, or None if none exists. ``cancel_event`` overrides
-        ``self._cancel_event`` (defaults to it).
+        ``self._cancel_event`` (defaults to it). ``near_path`` prefers a
+        copy co-located with the main GGUF's cache snapshot.
         """
 
-        def _pick_mmproj(candidates: list[str]) -> Optional[str]:
-            mmproj_files = sorted(
-                f
-                for f in candidates
-                if f.lower().endswith(".gguf") and "mmproj" in Path(f).name.lower()
-            )
-            if not mmproj_files:
-                return None
-            for f in mmproj_files:
-                if f.lower().endswith("-f16.gguf"):
-                    return f
-            return mmproj_files[0]
-
         return self._download_companion_gguf(
             hf_repo = hf_repo,
             hf_token = hf_token,
             pick = _pick_mmproj,
             label = "mmproj",
             cancel_event = cancel_event,
+            near_path = near_path,
         )
 
     def _cached_repo_mtp_drafter(self, hf_repo: str) -> Optional[str]:
@@ -4817,6 +5071,7 @@ class LlamaCppBackend:
         *,
         hf_repo: str,
         hf_token: Optional[str] = None,
+        near_path: Optional[str] = None,
     ) -> Optional[str]:
         """Download the separate MTP drafter (speculative head) from a GGUF repo.
 
@@ -4828,16 +5083,6 @@ class LlamaCppBackend:
         are intentionally skipped. Returns the local path, or None.
         """
 
-        # Offline, reuse any drafter already on disk (a fresh copy can't be
-        # fetched). Online, _download_companion_gguf/hf_hub_download reuse the
-        # current cached file and refetch a changed one, so skip the probe here
-        # rather than pair new weights with a stale draft.
-        if _hf_env_offline():
-            cached = self._cached_repo_mtp_drafter(hf_repo)
-            if cached:
-                logger.info(f"Reusing cached MTP drafter (offline): {cached}")
-                return cached
-
         def _pick_mtp(candidates: list[str]) -> Optional[str]:
             # Root-level only: MTP/ subdir copies now share the mtp- prefix but
             # are explicit-selection, not auto-fetch (they'd sort ahead of root).
@@ -4850,11 +5095,28 @@ class LlamaCppBackend:
             )
             return mtp_files[0] if mtp_files else None
 
+        if near_path:
+            cached = _companion_snapshot_sibling(near_path, _pick_mtp)
+            if cached:
+                logger.info("Reusing cached MTP drafter: %s", cached)
+                return cached
+
+        # Offline, reuse any drafter already on disk (a fresh copy can't be
+        # fetched). Online, _download_companion_gguf/hf_hub_download reuse the
+        # current cached file and refetch a changed one, so skip the probe here
+        # rather than pair new weights with a stale draft.
+        if _hf_env_offline():
+            cached = self._cached_repo_mtp_drafter(hf_repo)
+            if cached:
+                logger.info(f"Reusing cached MTP drafter (offline): {cached}")
+                return cached
+
         return self._download_companion_gguf(
             hf_repo = hf_repo,
             hf_token = hf_token,
             pick = _pick_mtp,
             label = "MTP drafter",
+            near_path = near_path,
         )
 
     def _resolve_launch_mmproj_path(
@@ -5436,6 +5698,7 @@ class LlamaCppBackend:
         )
         self._stdout_thread.start()
 
+    @_with_gguf_load_marker
     def load_model(
         self,
         *,
@@ -5581,6 +5844,7 @@ class LlamaCppBackend:
                         mmproj_path = self._download_mmproj(
                             hf_repo = hf_repo,
                             hf_token = hf_token,
+                            near_path = model_path,
                         )
                     # Auto-download the separate MTP drafter (e.g. Gemma) when
                     # the requested spec mode can use it. Repos with the head
@@ -5598,6 +5862,7 @@ class LlamaCppBackend:
                         mtp_draft_path = self._download_mtp(
                             hf_repo = hf_repo,
                             hf_token = hf_token,
+                            near_path = model_path,
                         )
             elif gguf_path:
                 if not Path(gguf_path).is_file():
diff --git a/studio/backend/hub/services/models/downloads.py b/studio/backend/hub/services/models/downloads.py
index c2ffe7bffc..862af0141a 100644
--- a/studio/backend/hub/services/models/downloads.py
+++ b/studio/backend/hub/services/models/downloads.py
@@ -60,6 +60,30 @@ def _job_status(
     return DownloadJobStatus(state = state, error = error, generation = generation)
 
 
+def _load_in_flight(repo_id: str) -> bool:
+    try:
+        from core.inference.llama_cpp import hf_gguf_load_in_flight
+        return hf_gguf_load_in_flight(repo_id)
+    except Exception:
+        return False
+
+
+def _load_in_flight_error(repo_id: str) -> HTTPException:
+    return HTTPException(
+        status_code = 409,
+        detail = (
+            f"A model load for '{repo_id}' is in progress and may be "
+            "downloading it. Wait for the load to finish (or cancel it), "
+            "then start the download."
+        ),
+    )
+
+
+def _reject_if_load_in_flight(repo_id: str) -> None:
+    if _load_in_flight(repo_id):
+        raise _load_in_flight_error(repo_id)
+
+
 def _spawn_download_worker(
     repo_id: str,
     variant: Optional[str],
@@ -89,6 +113,9 @@ async def download_model_response(body: DownloadModelRequest, hf_token: Optional
     # Canonicalize so two different-cased paste-ins share one job + cache dir.
     repo_id = await asyncio.to_thread(resolve_cached_repo_id_case, repo_id, repo_type = "model")
 
+    # Avoid concurrent writers to the same HF cache files.
+    _reject_if_load_in_flight(repo_id)
+
     variant = (body.gguf_variant or "").strip() or None
     if variant is not None and not _is_valid_gguf_variant(variant):
         raise HTTPException(
@@ -147,9 +174,12 @@ async def download_model_response(body: DownloadModelRequest, hf_token: Optional
         blob_hashes = variant_blob_hashes,
         progress_blob_hashes = variant_progress_blob_hashes,
         completed_baseline_bytes = completed_baseline_bytes,
+        admission_check = lambda: not _load_in_flight(repo_id),
     )
     generation = _registry.current_generation(key)
     if not claimed:
+        if claim_state == "admission_blocked":
+            raise _load_in_flight_error(repo_id)
         # claim_state is the blocking job's state. The client can attach only
         # when the blocker is this key's own in-flight job (adoptable); a
         # cross-variant conflict or in-progress delete is not accepted.
diff --git a/studio/backend/hub/utils/download_registry.py b/studio/backend/hub/utils/download_registry.py
index 274038b292..b6bdee3bce 100644
--- a/studio/backend/hub/utils/download_registry.py
+++ b/studio/backend/hub/utils/download_registry.py
@@ -47,7 +47,7 @@ import time
 import weakref
 from dataclasses import dataclass, field, replace
 from pathlib import Path
-from typing import Iterator, Literal, Optional
+from typing import Callable, Iterator, Literal, Optional
 
 from loggers import get_logger
 
@@ -1028,6 +1028,7 @@ class DownloadRegistry:
         blob_hashes: Optional[frozenset[str]] = None,
         progress_blob_hashes: Optional[frozenset[str]] = None,
         completed_baseline_bytes: int = 0,
+        admission_check: Optional[Callable[[], bool]] = None,
         generation: Optional[int] = None,
         replace_active: bool = False,
         metadata_transport: Optional[str] = None,
@@ -1038,6 +1039,13 @@ class DownloadRegistry:
         requested_hashes = blob_hashes or frozenset()
         requested_progress_hashes = progress_blob_hashes or frozenset()
         with self._lock:
+            # Run the final external admission check while the registry lock is
+            # held, immediately before inspecting and publishing active state.
+            # The GGUF load path establishes its marker before calling
+            # its active-job probe, so either this claim observes that marker
+            # or the load's later probe observes this claim.
+            if admission_check is not None and not admission_check():
+                return False, "admission_blocked"
             deleting_scopes = self._deleting.get(repo)
             if deleting_scopes is not None and (
                 None in deleting_scopes or variant_from_key(key) in deleting_scopes
@@ -1222,6 +1230,23 @@ class DownloadRegistry:
                 )
             return refs
 
+    def has_active_variant(self, repo_id: str, variant: Optional[str]) -> bool:
+        """Whether an active model job targets this exact GGUF variant.
+
+        Scans the job table rather than only ``_repo_active`` so an XET-to-HTTP
+        retry handoff remains visible while it has temporarily released its
+        active slot.
+        """
+        repo_key = normalize_repo_key(repo_id)
+        target = (variant or "").strip().lower() or None
+        with self._lock:
+            for key, job in self._jobs.items():
+                if _repo_of_key(key) != repo_key or job.state not in _ACTIVE_STATES:
+                    continue
+                if self._active_job_variant_locked(key) == target:
+                    return True
+        return False
+
     def begin_delete(
         self,
         repo_id: str,
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index 0541a81ff2..81dea96274 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -20,6 +20,7 @@ from loggers import get_logger
 import asyncio
 import threading
 import weakref
+from contextlib import ExitStack
 
 
 import re as _re
@@ -998,6 +999,7 @@ try:
     from core.inference.llama_server_args import (
         _effective_tensor_parallel,
         _tensor_parallel_matches_loaded,
+        extra_args_disable_mmproj,
         parse_split_mode_override,
         resolve_tensor_parallel,
         strip_shadowing_flags,
@@ -1035,6 +1037,7 @@ except ImportError:
     from core.inference.llama_server_args import (
         _effective_tensor_parallel,
         _tensor_parallel_matches_loaded,
+        extra_args_disable_mmproj,
         parse_split_mode_override,
         resolve_tensor_parallel,
         strip_shadowing_flags,
@@ -3968,6 +3971,7 @@ async def _load_model_impl(request: LoadRequest, fastapi_request: Request, curre
 
     native_grant_backed = False
     model_log_label = request.model_path
+    gguf_load_stack = ExitStack()
     try:
         # Validate user pass-through args up front so a managed-flag collision
         # returns 400 before any model work.
@@ -4187,15 +4191,9 @@ async def _load_model_impl(request: LoadRequest, fastapi_request: Request, curre
             llama_backend = get_llama_cpp_backend()
             unsloth_backend = get_inference_backend()
 
-            # Unload any active Unsloth model to free VRAM (off the event loop:
-            # unload takes _gen_lock and can wait on an in-flight stream).
-            if unsloth_backend.active_model_name:
-                logger.info(
-                    f"Unloading Unsloth model '{unsloth_backend.active_model_name}' before loading GGUF"
-                )
-                await asyncio.to_thread(
-                    unsloth_backend.unload_model, unsloth_backend.active_model_name
-                )
+            if config.gguf_hf_repo:
+                from core.inference.llama_cpp import gguf_load_in_flight
+                gguf_load_stack.enter_context(gguf_load_in_flight(config.gguf_hf_repo))
 
             # Inherit llama_extra_args from the previous load when the request
             # omits the field (the chat-settings Apply path doesn't round-trip
@@ -4275,6 +4273,38 @@ async def _load_model_impl(request: LoadRequest, fastapi_request: Request, curre
                                 extra_llama_args,
                             )
 
+            # Block cache writes that would race the download manager. This runs
+            # after pass-through argument inheritance so a carried --no-mmproj
+            # changes the companion requirement exactly as it does for the load.
+            if config.gguf_hf_repo:
+                from core.inference.llama_cpp import _hub_download_blocks_gguf_load
+                if await asyncio.to_thread(
+                    _hub_download_blocks_gguf_load,
+                    config.gguf_hf_repo,
+                    config.gguf_variant,
+                    require_mmproj = bool(
+                        config.is_vision and not extra_args_disable_mmproj(extra_llama_args)
+                    ),
+                    hf_token = request.hf_token,
+                ):
+                    raise HTTPException(
+                        status_code = 409,
+                        detail = (
+                            f"'{model_log_label}' is currently being downloaded "
+                            "by the download manager. Wait for the download to "
+                            "finish (or cancel it), then load the model."
+                        ),
+                    )
+
+            # Unload any active Unsloth model only after every hub conflict check.
+            if unsloth_backend.active_model_name:
+                logger.info(
+                    f"Unloading Unsloth model '{unsloth_backend.active_model_name}' before loading GGUF"
+                )
+                await asyncio.to_thread(
+                    unsloth_backend.unload_model, unsloth_backend.active_model_name
+                )
+
             # Route to HF or local mode based on config. Run in a thread so the
             # event loop stays free for progress polling and other requests
             # during the (potentially long) GGUF download + llama-server start.
@@ -4639,6 +4669,8 @@ async def _load_model_impl(request: LoadRequest, fastapi_request: Request, curre
         logger.error(f"Error loading model: {e}", exc_info = True)
         msg = _maybe_unsupported_message(redacted_msg)
         raise HTTPException(status_code = 500, detail = f"Failed to load model: {msg}")
+    finally:
+        gguf_load_stack.close()
 
 
 def _requires_trust_remote_code_for_model(
diff --git a/studio/backend/tests/test_gguf_load_cache_reuse.py b/studio/backend/tests/test_gguf_load_cache_reuse.py
new file mode 100644
index 0000000000..15d91cd324
--- /dev/null
+++ b/studio/backend/tests/test_gguf_load_cache_reuse.py
@@ -0,0 +1,740 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Tests for cached GGUF reuse and load/download exclusion.
+
+No GPU, network, or subprocesses are required.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+import threading
+import types as _types
+from pathlib import Path
+from unittest.mock import patch
+
+import pytest
+
+
+_BACKEND_DIR = str(Path(__file__).resolve().parent.parent)
+if _BACKEND_DIR not in sys.path:
+    sys.path.insert(0, _BACKEND_DIR)
+
+# Stub optional dependencies before importing the modules under test.
+_loggers_stub = _types.ModuleType("loggers")
+_loggers_stub.get_logger = lambda name: __import__("logging").getLogger(name)
+sys.modules.setdefault("loggers", _loggers_stub)
+
+_structlog_stub = _types.ModuleType("structlog")
+sys.modules.setdefault("structlog", _structlog_stub)
+
+try:
+    import httpx  # noqa: F401
+except ImportError:
+    _httpx_stub = _types.ModuleType("httpx")
+    for _exc_name in (
+        "ConnectError",
+        "TimeoutException",
+        "ReadTimeout",
+        "ReadError",
+        "RemoteProtocolError",
+        "CloseError",
+        "HTTPError",
+        "RequestError",
+        "HTTPStatusError",
+    ):
+        setattr(_httpx_stub, _exc_name, type(_exc_name, (Exception,), {}))
+    _httpx_stub.Response = type("Response", (), {})
+    _httpx_stub.Request = type("Request", (), {})
+
+    class _FakeTimeout:
+        def __init__(self, *a, **kw):
+            pass
+
+    _httpx_stub.Timeout = _FakeTimeout
+    _httpx_stub.Client = type(
+        "Client",
+        (),
+        {
+            "__init__": lambda self, **kw: None,
+            "__enter__": lambda self: self,
+            "__exit__": lambda self, *a: None,
+        },
+    )
+    sys.modules.setdefault("httpx", _httpx_stub)
+
+
+from huggingface_hub import constants as hf_constants
+
+from core.inference.llama_cpp import (
+    LlamaCppBackend,
+    cached_gguf_for_load,
+    gguf_load_in_flight,
+    hf_gguf_load_in_flight,
+)
+
+
+REPO = "unsloth/gemma-test-GGUF"
+VARIANT = "UD-Q4_K_XL"
+MAIN = f"gemma-test-{VARIANT}.gguf"
+
+
+def _build_cache(
+    root: Path,
+    repo_id: str,
+    files: dict[str, int],
+    *,
+    snapshot_sha: str = "a" * 40,
+) -> Path:
+    """Create ``$root/models--<repo>/snapshots/<sha>/<rel>`` for each entry."""
+    repo_dir = root / f"models--{repo_id.replace('/', '--')}"
+    (repo_dir / "blobs").mkdir(parents = True, exist_ok = True)
+    snap = repo_dir / "snapshots" / snapshot_sha
+    snap.mkdir(parents = True, exist_ok = True)
+    for rel, size in files.items():
+        full = snap / rel
+        full.parent.mkdir(parents = True, exist_ok = True)
+        full.write_bytes(b"\0" * size)
+    return snap
+
+
+@pytest.fixture
+def hf_cache(tmp_path, monkeypatch):
+    monkeypatch.setattr(hf_constants, "HF_HUB_CACHE", str(tmp_path))
+    monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
+    monkeypatch.delenv("TRANSFORMERS_OFFLINE", raising = False)
+    return tmp_path
+
+
+def _fail_download(*_args, **_kwargs):
+    raise AssertionError("must reuse the cached GGUF instead of downloading")
+
+
+def _fail_get_paths_info(*_args, **_kwargs):
+    raise AssertionError("cached reuse must return before the sizing preflight")
+
+
+class TestLoadReusesCachedCopy:
+    def test_online_reuse_after_revision_bump(self, hf_cache):
+        """A new repo revision does not replace a complete cached model."""
+        backend = LlamaCppBackend()
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4})
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", _fail_get_paths_info),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(snap / MAIN)
+
+    def test_reuse_size_check_uses_cached_snapshot_revision(self, hf_cache):
+        """Current-revision size changes do not invalidate an older complete copy."""
+        backend = LlamaCppBackend()
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4})
+        revisions: list[str | None] = []
+
+        def fake_get_paths_info(
+            _repo,
+            paths,
+            *,
+            revision = None,
+            token = None,
+        ):
+            revisions.append(revision)
+            size = 4 if revision == snap.name else 8
+            return [_types.SimpleNamespace(path = path, size = size) for path in paths]
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(snap / MAIN)
+        assert revisions == [snap.name]
+
+    def test_reuse_when_cached_revision_vanished_from_hub(self, hf_cache):
+        """The Hub answers an unknown revision with an empty result, not an error."""
+        backend = LlamaCppBackend()
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4})
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", lambda *_a, **_k: []),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(snap / MAIN)
+
+    def test_truncated_cached_file_is_not_reused(self, hf_cache):
+        backend = LlamaCppBackend()
+        _build_cache(hf_cache, REPO, {MAIN: 4})
+        downloaded: list[str] = []
+
+        def fake_get_paths_info(
+            _repo,
+            paths,
+            *,
+            revision = None,
+            token = None,
+        ):
+            return [_types.SimpleNamespace(path = path, size = 8) for path in paths]
+
+        def fake_download(
+            repo_id,
+            filename,
+            token = None,
+            **_kwargs,
+        ):
+            downloaded.append(filename)
+            return f"/fake/{repo_id}/{filename}"
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fake_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert downloaded == [MAIN]
+        assert out == f"/fake/{REPO}/{MAIN}"
+
+    def test_truncated_cached_split_shard_is_not_reused(self, hf_cache):
+        backend = LlamaCppBackend()
+        shard1 = f"gemma-test-{VARIANT}-00001-of-00002.gguf"
+        shard2 = f"gemma-test-{VARIANT}-00002-of-00002.gguf"
+        _build_cache(hf_cache, REPO, {shard1: 8, shard2: 4})
+        downloaded: list[str] = []
+
+        def fake_get_paths_info(
+            _repo,
+            paths,
+            *,
+            revision = None,
+            token = None,
+        ):
+            return [_types.SimpleNamespace(path = path, size = 8) for path in paths]
+
+        def fake_download(
+            repo_id,
+            filename,
+            token = None,
+            **_kwargs,
+        ):
+            downloaded.append(filename)
+            return f"/fake/{repo_id}/{filename}"
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [shard1, shard2]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fake_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert downloaded == [shard1, shard2]
+        assert out == f"/fake/{REPO}/{shard1}"
+
+    def test_online_reuse_when_reupload_renamed_the_file(self, hf_cache):
+        """A renamed variant still reuses its cached file."""
+        backend = LlamaCppBackend()
+        old_name = f"gemma-test-old-{VARIANT}.gguf"
+        snap = _build_cache(hf_cache, REPO, {old_name: 4})
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", _fail_get_paths_info),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(snap / old_name)
+
+    def test_downloads_when_nothing_cached(self, hf_cache):
+        backend = LlamaCppBackend()
+        downloaded: list[str] = []
+
+        def fake_download(
+            repo_id,
+            filename,
+            token = None,
+            **_kwargs,
+        ):
+            downloaded.append(filename)
+            return f"/fake/{repo_id}/{filename}"
+
+        def fake_get_paths_info(
+            _repo_id,
+            paths,
+            token = None,
+        ):
+            return [_types.SimpleNamespace(path = p, size = 1) for p in paths if p is not None]
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fake_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert downloaded == [MAIN]
+        assert out == f"/fake/{REPO}/{MAIN}"
+
+    def test_force_redownloads_despite_cache(self, hf_cache):
+        """A forced download ignores a complete cached copy."""
+        backend = LlamaCppBackend()
+        _build_cache(hf_cache, REPO, {MAIN: 4})
+        downloaded: list[str] = []
+
+        def fake_download(
+            repo_id,
+            filename,
+            token = None,
+            **kwargs,
+        ):
+            assert kwargs.get("force_download") is True
+            downloaded.append(filename)
+            return f"/fake/{repo_id}/{filename}"
+
+        def fake_get_paths_info(
+            _repo_id,
+            paths,
+            token = None,
+        ):
+            return [_types.SimpleNamespace(path = p, size = 1) for p in paths if p is not None]
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fake_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT, force = True)
+
+        assert downloaded == [MAIN]
+        assert out == f"/fake/{REPO}/{MAIN}"
+
+    def test_split_reused_only_when_colocated(self, hf_cache):
+        backend = LlamaCppBackend()
+        shard1 = f"gemma-test-{VARIANT}-00001-of-00002.gguf"
+        shard2 = f"gemma-test-{VARIANT}-00002-of-00002.gguf"
+        snap = _build_cache(hf_cache, REPO, {shard1: 4, shard2: 4})
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [shard1, shard2]),
+            patch("huggingface_hub.get_paths_info", _fail_get_paths_info),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(snap / shard1)
+
+    def test_partial_split_set_downloads(self, hf_cache):
+        """A partial split set is not reused."""
+        backend = LlamaCppBackend()
+        shard1 = f"gemma-test-{VARIANT}-00001-of-00002.gguf"
+        shard2 = f"gemma-test-{VARIANT}-00002-of-00002.gguf"
+        _build_cache(hf_cache, REPO, {shard1: 4})
+        downloaded: list[str] = []
+
+        def fake_download(
+            repo_id,
+            filename,
+            token = None,
+            **_kwargs,
+        ):
+            downloaded.append(filename)
+            return f"/fake/{repo_id}/{filename}"
+
+        def fake_get_paths_info(
+            _repo_id,
+            paths,
+            token = None,
+        ):
+            return [_types.SimpleNamespace(path = p, size = 4) for p in paths if p is not None]
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [shard1, shard2]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fake_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert downloaded == [shard1, shard2]
+        assert out == f"/fake/{REPO}/{shard1}"
+
+    def test_reuse_prefers_newest_snapshot_after_update(self, hf_cache):
+        """Loads prefer the newest complete snapshot."""
+        import os
+
+        backend = LlamaCppBackend()
+        old_snap = _build_cache(hf_cache, REPO, {MAIN: 4}, snapshot_sha = "a" * 40)
+        new_snap = _build_cache(hf_cache, REPO, {MAIN: 6}, snapshot_sha = "b" * 40)
+        os.utime(old_snap, (1_000_000, 1_000_000))
+        os.utime(new_snap, (2_000_000, 2_000_000))
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", _fail_get_paths_info),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(new_snap / MAIN)
+
+    def test_low_disk_fallback_reuses_cached_copy(self, hf_cache):
+        backend = LlamaCppBackend()
+        fallback = "gemma-test-Q2_K.gguf"
+        snap = _build_cache(hf_cache, REPO, {fallback: 4})
+
+        def fake_get_paths_info(
+            _repo,
+            paths,
+            *,
+            revision = None,
+            token = None,
+        ):
+            size = 4 if revision == snap.name else 100
+            return [_types.SimpleNamespace(path = path, size = size) for path in paths]
+
+        with (
+            patch("huggingface_hub.list_repo_files", lambda *_a, **_k: [MAIN]),
+            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
+            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
+            patch("shutil.disk_usage", lambda *_a, **_k: _types.SimpleNamespace(free = 10)),
+            patch.object(
+                backend,
+                "_find_smallest_fitting_variant",
+                lambda *_a, **_k: (fallback, 4, []),
+            ),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_gguf(hf_repo = REPO, hf_variant = VARIANT)
+
+        assert out == str(snap / fallback)
+
+    def test_companion_prefers_main_snapshot_sibling(self, hf_cache):
+        """A cached mmproj is reused from the main model's snapshot."""
+        backend = LlamaCppBackend()
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4, "mmproj-F16.gguf": 2})
+
+        def _fail_list(*_args, **_kwargs):
+            raise AssertionError("snapshot sibling must resolve without a repo listing")
+
+        with patch("huggingface_hub.list_repo_files", _fail_list):
+            out = backend._download_mmproj(hf_repo = REPO, near_path = str(snap / MAIN))
+
+        assert out == str(snap / "mmproj-F16.gguf")
+
+    def test_companion_finds_snapshot_through_hf_symlink(self, hf_cache):
+        backend = LlamaCppBackend()
+        snap = _build_cache(hf_cache, REPO, {})
+        blobs = snap.parent.parent / "blobs"
+        main_blob = blobs / "main"
+        mmproj_blob = blobs / "mmproj"
+        main_blob.write_bytes(b"main")
+        mmproj_blob.write_bytes(b"mmproj")
+        try:
+            (snap / MAIN).symlink_to(main_blob)
+            (snap / "mmproj-F16.gguf").symlink_to(mmproj_blob)
+        except OSError as exc:
+            pytest.skip(f"symlinks unavailable: {exc}")
+
+        with patch("huggingface_hub.list_repo_files", _fail_download):
+            out = backend._download_mmproj(hf_repo = REPO, near_path = str(snap / MAIN))
+
+        assert out == str(snap / "mmproj-F16.gguf")
+
+    def test_companion_does_not_download_during_hub_job(self, hf_cache):
+        backend = LlamaCppBackend()
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4})
+        registry = _types.SimpleNamespace(active_job_refs = lambda _repo: [object()])
+
+        with (
+            patch("huggingface_hub.list_repo_files", _fail_download),
+            patch("hub.utils.download_registry.get_models_registry", lambda: registry),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", _fail_download),
+        ):
+            out = backend._download_mmproj(hf_repo = REPO, near_path = str(snap / MAIN))
+
+        assert out is None
+
+
+class TestCachedGgufForLoadProbe:
+    def test_complete_copy_found(self, hf_cache):
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4})
+        assert cached_gguf_for_load(REPO, VARIANT) == str(snap / MAIN)
+
+    def test_absent_copy_is_none(self, hf_cache):
+        assert cached_gguf_for_load(REPO, VARIANT) is None
+
+    def test_partial_split_is_none(self, hf_cache):
+        shard1 = f"gemma-test-{VARIANT}-00001-of-00002.gguf"
+        _build_cache(hf_cache, REPO, {shard1: 4})
+        assert cached_gguf_for_load(REPO, VARIANT) is None
+
+    def test_partial_new_snapshot_does_not_hide_complete_split(self, hf_cache):
+        import os
+
+        shard1 = f"gemma-test-{VARIANT}-00001-of-00002.gguf"
+        shard2 = f"gemma-test-{VARIANT}-00002-of-00002.gguf"
+        old = _build_cache(
+            hf_cache,
+            REPO,
+            {shard1: 4, shard2: 4},
+            snapshot_sha = "a" * 40,
+        )
+        new = _build_cache(hf_cache, REPO, {shard1: 4}, snapshot_sha = "b" * 40)
+        os.utime(old, (1_000_000, 1_000_000))
+        os.utime(new, (2_000_000, 2_000_000))
+
+        assert cached_gguf_for_load(REPO, VARIANT) == str(old / shard1)
+
+    def test_split_requires_every_declared_shard(self, hf_cache):
+        shard1 = f"gemma-test-{VARIANT}-00001-of-00003.gguf"
+        shard2 = f"gemma-test-{VARIANT}-00002-of-00003.gguf"
+        _build_cache(hf_cache, REPO, {shard1: 4, shard2: 4})
+
+        assert cached_gguf_for_load(REPO, VARIANT) is None
+
+    def test_required_mmproj_must_share_main_snapshot(self, hf_cache):
+        snap = _build_cache(hf_cache, REPO, {MAIN: 4})
+        assert cached_gguf_for_load(REPO, VARIANT) == str(snap / MAIN)
+        assert cached_gguf_for_load(REPO, VARIANT, require_mmproj = True) is None
+
+        (snap / "mmproj-F16.gguf").write_bytes(b"mmproj")
+        assert cached_gguf_for_load(REPO, VARIANT, require_mmproj = True) == str(snap / MAIN)
+
+    def test_required_mmproj_scans_past_newer_main_only_snapshot(self, hf_cache):
+        import os
+
+        old = _build_cache(
+            hf_cache,
+            REPO,
+            {MAIN: 4, "mmproj-F16.gguf": 2},
+            snapshot_sha = "a" * 40,
+        )
+        new = _build_cache(hf_cache, REPO, {MAIN: 4}, snapshot_sha = "b" * 40)
+        os.utime(old, (1_000_000, 1_000_000))
+        os.utime(new, (2_000_000, 2_000_000))
+
+        assert cached_gguf_for_load(REPO, VARIANT, require_mmproj = True) == str(old / MAIN)
+
+
+class TestLoadHubDownloadExclusion:
+    def test_in_flight_marker_counts_and_normalizes_case(self):
+        assert not hf_gguf_load_in_flight(REPO)
+        with gguf_load_in_flight(REPO):
+            assert hf_gguf_load_in_flight(REPO.upper())
+            with gguf_load_in_flight(REPO.lower()):
+                assert hf_gguf_load_in_flight(REPO)
+            assert hf_gguf_load_in_flight(REPO)
+        assert not hf_gguf_load_in_flight(REPO)
+
+    def test_marker_noops_for_local_loads(self):
+        with gguf_load_in_flight(None):
+            assert not hf_gguf_load_in_flight("")
+
+    def test_marker_cleared_on_exception(self):
+        with pytest.raises(RuntimeError):
+            with gguf_load_in_flight(REPO):
+                raise RuntimeError("boom")
+        assert not hf_gguf_load_in_flight(REPO)
+
+    def test_hub_download_refused_while_load_in_flight(self):
+        from fastapi import HTTPException
+
+        from hub.schemas.downloads import DownloadModelRequest
+        from hub.services.models import downloads as dl
+
+        body = DownloadModelRequest(repo_id = REPO, gguf_variant = VARIANT)
+        with (
+            patch.object(dl, "resolve_cached_repo_id_case", lambda repo_id, repo_type: repo_id),
+            gguf_load_in_flight(REPO),
+        ):
+            with pytest.raises(HTTPException) as exc_info:
+                asyncio.run(dl.download_model_response(body))
+
+        assert exc_info.value.status_code == 409
+        assert "load" in exc_info.value.detail.lower()
+
+    def test_hub_download_rechecks_marker_before_claim(self):
+        from fastapi import HTTPException
+
+        from hub.schemas.downloads import DownloadModelRequest
+        from hub.services.models import downloads as dl
+
+        scope = None
+
+        def mark_load(*_args, **_kwargs):
+            nonlocal scope
+            if scope is None:
+                scope = gguf_load_in_flight(REPO)
+                scope.__enter__()
+            return frozenset()
+
+        class _Registry:
+            def claim(self, *_args, admission_check, **_kwargs):
+                assert admission_check() is False
+                return False, "admission_blocked"
+
+            def current_generation(self, _key):
+                return 0
+
+        registry = _Registry()
+        body = DownloadModelRequest(repo_id = REPO, gguf_variant = VARIANT)
+        try:
+            with (
+                patch.object(dl, "resolve_cached_repo_id_case", lambda repo_id, repo_type: repo_id),
+                patch.object(dl.gguf_variants, "gguf_variant_blob_hashes", mark_load),
+                patch.object(dl, "_registry", registry),
+            ):
+                with pytest.raises(HTTPException) as exc_info:
+                    asyncio.run(dl.download_model_response(body))
+        finally:
+            if scope is not None:
+                scope.__exit__(None, None, None)
+
+        assert exc_info.value.status_code == 409
+
+    def test_registry_admission_check_prevents_claim(self):
+        from hub.utils.download_registry import DownloadRegistry, TRANSPORT_HTTP
+
+        registry = DownloadRegistry()
+        claimed, state = registry.claim(
+            f"{REPO}::{VARIANT}",
+            TRANSPORT_HTTP,
+            repo_type = "model",
+            repo_id = REPO,
+            variant = VARIANT,
+            admission_check = lambda: False,
+        )
+
+        assert claimed is False
+        assert state == "admission_blocked"
+        assert registry.active_jobs(REPO) == {}
+
+    def test_same_variant_job_stays_visible_during_retry_handoff(self):
+        from hub.utils.download_registry import DownloadRegistry, TRANSPORT_XET
+        from core.inference.llama_cpp import _hub_download_blocks_gguf_load
+
+        registry = DownloadRegistry()
+        key = f"{REPO}::{VARIANT}"
+        claimed, _ = registry.claim(
+            key,
+            TRANSPORT_XET,
+            repo_type = "model",
+            repo_id = REPO,
+            variant = VARIANT,
+        )
+        assert claimed is True
+        assert registry.has_active_variant(REPO, VARIANT.lower()) is True
+
+        registry.release_active_slot(key)
+
+        assert registry.active_jobs(REPO) == {}
+        assert registry.active_job_refs(REPO)
+        assert registry.has_active_variant(REPO, VARIANT) is True
+        with (
+            patch("hub.utils.download_registry.get_models_registry", lambda: registry),
+            patch(
+                "core.inference.llama_cpp.cached_gguf_for_load",
+                side_effect = AssertionError("same-variant jobs must block before cache reuse"),
+            ),
+        ):
+            assert _hub_download_blocks_gguf_load(REPO, VARIANT) is True
+
+        registry.set_job(key, "complete")
+        assert registry.has_active_variant(REPO, VARIANT) is False
+
+    def test_other_variant_job_still_allows_complete_cached_load(self):
+        from core.inference.llama_cpp import _hub_download_blocks_gguf_load
+        from hub.utils.download_registry import DownloadRegistry, TRANSPORT_HTTP
+
+        registry = DownloadRegistry()
+        registry.claim(
+            f"{REPO}::Q8_0",
+            TRANSPORT_HTTP,
+            repo_type = "model",
+            repo_id = REPO,
+            variant = "Q8_0",
+        )
+        with (
+            patch("hub.utils.download_registry.get_models_registry", lambda: registry),
+            patch(
+                "core.inference.llama_cpp.cached_gguf_for_load",
+                return_value = "/cached/model.gguf",
+            ) as cached_probe,
+        ):
+            assert _hub_download_blocks_gguf_load(REPO, VARIANT) is False
+
+        cached_probe.assert_called_once_with(
+            REPO,
+            VARIANT,
+            require_mmproj = False,
+            verify_sizes = True,
+            hf_token = None,
+        )
+
+    def test_cancelled_request_keeps_marker_until_load_thread_finishes(self):
+        from core.inference.llama_cpp import _with_gguf_load_marker
+
+        started = threading.Event()
+        release = threading.Event()
+        finished = threading.Event()
+
+        class FakeBackend:
+            @_with_gguf_load_marker
+            def load_model(self, *, hf_repo):
+                started.set()
+                release.wait(timeout = 2)
+                finished.set()
+                return True
+
+        async def scenario():
+            with patch(
+                "core.inference.llama_cpp._hub_download_blocks_gguf_load",
+                return_value = False,
+            ):
+                task = asyncio.create_task(
+                    asyncio.to_thread(FakeBackend().load_model, hf_repo = REPO)
+                )
+                assert await asyncio.to_thread(started.wait, 1)
+                task.cancel()
+                with pytest.raises(asyncio.CancelledError):
+                    await task
+                assert hf_gguf_load_in_flight(REPO)
+
+                release.set()
+                assert await asyncio.to_thread(finished.wait, 1)
+                for _ in range(100):
+                    if not hf_gguf_load_in_flight(REPO):
+                        break
+                    await asyncio.sleep(0.001)
+                assert not hf_gguf_load_in_flight(REPO)
+
+        asyncio.run(scenario())
+
+    def test_load_marker_precedes_hub_guard_and_unload(self):
+        source = (Path(__file__).resolve().parent.parent / "routes" / "inference.py").read_text()
+        gguf_branch = source[source.index("if config.is_gguf:") :]
+
+        assert (
+            gguf_branch.index("enter_context(gguf_load_in_flight")
+            < gguf_branch.index("if request.llama_extra_args is None")
+            < gguf_branch.index("_hub_download_blocks_gguf_load")
+            < gguf_branch.index("unsloth_backend.unload_model")
+        )
+        llama_source = (
+            Path(__file__).resolve().parent.parent / "core" / "inference" / "llama_cpp.py"
+        ).read_text()
+        assert "@_with_gguf_load_marker\n    def load_model(" in llama_source
diff --git a/studio/backend/tests/test_mtp_drafter_companion.py b/studio/backend/tests/test_mtp_drafter_companion.py
index 86e528ae67..02230632b6 100644
--- a/studio/backend/tests/test_mtp_drafter_companion.py
+++ b/studio/backend/tests/test_mtp_drafter_companion.py
@@ -328,6 +328,7 @@ def test_download_mtp_prefers_root_over_new_scheme_copies(monkeypatch):
         pick,
         label,
         cancel_event = None,
+        near_path = None,
     ):
         captured["pick"] = pick
         return None
@@ -428,6 +429,32 @@ def test_download_mtp_reuse_follows_snapshot_order_offline(tmp_path, monkeypatch
     assert got is not None and Path(got).parent.parent.name == "newest"
 
 
+def test_download_mtp_prefers_main_snapshot_offline(tmp_path, monkeypatch):
+    import utils.models.model_config as mc
+    from core.inference.llama_cpp import LlamaCppBackend
+
+    monkeypatch.setenv("HF_HUB_OFFLINE", "1")
+    snapshots = tmp_path / "models--unsloth--gemma" / "snapshots"
+    old = snapshots / "old"
+    new = snapshots / "new"
+    old.mkdir(parents = True)
+    new.mkdir(parents = True)
+    main = old / "gemma-UD-Q4_K_XL.gguf"
+    old_drafter = old / "mtp-gemma.gguf"
+    new_drafter = new / "mtp-gemma.gguf"
+    main.write_bytes(b"main")
+    old_drafter.write_bytes(b"old")
+    new_drafter.write_bytes(b"new")
+    monkeypatch.setattr(mc, "_iter_hf_cache_snapshots", lambda _repo: [new, old])
+
+    got = LlamaCppBackend()._download_mtp(
+        hf_repo = "unsloth/gemma-GGUF",
+        near_path = str(main),
+    )
+
+    assert got == str(old_drafter)
+
+
 def test_download_mtp_online_skips_cache_reuse(tmp_path, monkeypatch):
     # Online, do not reuse a cached copy: go to the download path so a changed
     # drafter is refetched (hf_hub_download checks the current revision).
@@ -447,6 +474,7 @@ def test_download_mtp_online_skips_cache_reuse(tmp_path, monkeypatch):
         pick,
         label,
         cancel_event = None,
+        near_path = None,
     ):
         reached["hit"] = True
         return None
diff --git a/studio/backend/tests/test_offline_gguf_cache_fallback.py b/studio/backend/tests/test_offline_gguf_cache_fallback.py
index e24e2ca451..0b9a1e704f 100644
--- a/studio/backend/tests/test_offline_gguf_cache_fallback.py
+++ b/studio/backend/tests/test_offline_gguf_cache_fallback.py
@@ -244,9 +244,7 @@ class TestGgufVariantFileResolution:
     def test_download_reuses_older_snapshot_when_current_ref_snapshot_is_partial(
         self, monkeypatch, hf_cache
     ):
-        # Cross-snapshot reuse is an offline-resilience path: online, hf_hub_download
-        # resumes the partial current-ref download and revalidates the revision instead
-        # of serving an older snapshot's same-name blob.
+        # Keep coverage for offline reuse; online reuse is tested separately.
         monkeypatch.setenv("HF_HUB_OFFLINE", "1")
         backend = LlamaCppBackend()
         repo = "unsloth/vision-GGUF"
@@ -292,8 +290,7 @@ class TestGgufVariantFileResolution:
     def test_download_reuses_cached_gguf_when_lowercase_partial_cache_shadows_it(
         self, monkeypatch, hf_cache
     ):
-        # Case-variant cross-dir reuse is offline-only; online the canonical repo id
-        # resolves up front and hf_hub_download fetches the current revision.
+        # Keep coverage for case-insensitive offline cache lookup.
         monkeypatch.setenv("HF_HUB_OFFLINE", "1")
         backend = LlamaCppBackend()
         canonical_repo = "unsloth/gemma-4-E2B-it-GGUF"
@@ -348,45 +345,26 @@ class TestGgufVariantFileResolution:
         assert out == str(snap / gguf_file)
         assert seen_repos
 
-    def test_download_online_does_not_reuse_old_snapshot(self, monkeypatch, hf_cache):
-        # Online, an older same-name snapshot must not be served (it may be a stale
-        # revision); hf_hub_download is called so the current revision is fetched and
-        # its etag revalidated.
+    def test_download_online_reuses_complete_cached_snapshot(self, monkeypatch, hf_cache):
+        # Loads reuse complete cached models across repo revisions.
         monkeypatch.delenv("HF_HUB_OFFLINE", raising = False)
         backend = LlamaCppBackend()
         repo = "unsloth/vision-GGUF"
-        _build_cache(hf_cache, repo, {"model-UD-Q4_K_XL.gguf": 4}, snapshot_sha = "a" * 40)
-        downloaded: list[str] = []
+        snap = _build_cache(hf_cache, repo, {"model-UD-Q4_K_XL.gguf": 4}, snapshot_sha = "a" * 40)
 
-        def fake_get_paths_info(
-            _repo_id,
-            paths,
-            token = None,
-        ):
-            return [_types.SimpleNamespace(path = p, size = 4) for p in paths if p]
-
-        def fake_download(
-            repo_id,
-            filename,
-            token = None,
-            **kwargs,
-        ):
-            downloaded.append(filename)
-            return f"/fresh/{filename}"
+        def fail_download(*_args, **_kwargs):
+            raise AssertionError("must reuse the cached GGUF instead of downloading")
 
         with (
             patch(
                 "huggingface_hub.list_repo_files",
                 lambda *_a, **_k: ["model-UD-Q4_K_XL.gguf"],
             ),
-            patch("huggingface_hub.get_paths_info", fake_get_paths_info),
-            patch("huggingface_hub.try_to_load_from_cache", lambda *_a, **_k: None),
-            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fake_download),
+            patch("core.inference.llama_cpp.hf_hub_download_with_xet_fallback", fail_download),
         ):
             out = backend._download_gguf(hf_repo = repo, hf_variant = "UD-Q4_K_XL")
 
-        assert downloaded == ["model-UD-Q4_K_XL.gguf"]
-        assert out == "/fresh/model-UD-Q4_K_XL.gguf"
+        assert out == str(snap / "model-UD-Q4_K_XL.gguf")
 
     def test_download_reuses_older_snapshot_when_offline_env_is_true(self, monkeypatch, hf_cache):
         # HF_HUB_OFFLINE accepts truthy spellings beyond "1" (true/yes/on); the offline

From 5441266e3aba6a3477b1e4d908f30da0a2665d3a Mon Sep 17 00:00:00 2001
From: Long Yixing <longyixing331@gmail.com>
Date: Sat, 18 Jul 2026 06:30:37 +0800
Subject: [PATCH 14/28] Fix Studio reasoning channel rendering (#7121)

---------

Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
---
 .../core/inference/chat_template_helpers.py   | 282 ++++++++++++-
 studio/backend/core/inference/inference.py    | 377 ++++++++++++++----
 .../backend/core/inference/mlx_inference.py   | 105 +++--
 studio/backend/core/inference/orchestrator.py |  76 +++-
 studio/backend/routes/inference.py            | 183 ++++++++-
 .../tests/test_mlx_inference_backend.py       | 166 ++++++++
 .../tests/test_openai_tool_passthrough.py     |  25 +-
 .../test_safetensors_capability_advertise.py  |  53 +++
 .../test_safetensors_reasoning_stream.py      | 132 ++++++
 .../tests/test_sf_client_tools_passthrough.py |  55 +++
 .../tests/test_think_prefill_reemit.py        | 177 +++++++-
 11 files changed, 1479 insertions(+), 152 deletions(-)

diff --git a/studio/backend/core/inference/chat_template_helpers.py b/studio/backend/core/inference/chat_template_helpers.py
index 897db8262d..5113eebb36 100644
--- a/studio/backend/core/inference/chat_template_helpers.py
+++ b/studio/backend/core/inference/chat_template_helpers.py
@@ -10,10 +10,242 @@ native-chat-template fallback used by the transformers and MLX backends.
 import copy
 import json
 import logging
+from dataclasses import dataclass
 from typing import Optional
 
 _THINK_OPEN = "<think>"
 _THINK_CLOSE = "</think>"
+_GEMMA_CHANNEL_START = "<|channel>"
+_GEMMA_THOUGHT_OPEN = "<|channel>thought"
+_GEMMA_THOUGHT_CLOSE = "<channel|>"
+_GEMMA_TEMPLATE_OPENERS = (
+    _GEMMA_THOUGHT_OPEN + "\n",
+    _GEMMA_THOUGHT_OPEN + "\\n",
+    _GEMMA_THOUGHT_OPEN + _GEMMA_THOUGHT_CLOSE,
+)
+
+
+def _tokenizer_objects(tokenizer) -> tuple:
+    """Return a processor/tokenizer and its distinct nested tokenizer."""
+    if tokenizer is None:
+        return ()
+    nested = getattr(tokenizer, "tokenizer", None)
+    return (tokenizer,) if nested is None or nested is tokenizer else (tokenizer, nested)
+
+
+def _selected_template_strings_from_value(
+    template,
+    tools = None,
+    *,
+    prefer_tool_use: bool = True,
+) -> tuple[str, ...]:
+    """Return the named chat template matching HF's default selection rules."""
+    tools = tools or None
+    if isinstance(template, str):
+        return (template,)
+    if not isinstance(template, dict):
+        return ()
+    if prefer_tool_use and tools and isinstance(template.get("tool_use"), str):
+        return (template["tool_use"],)
+    if isinstance(template.get("default"), str):
+        return (template["default"],)
+    values = tuple(value for value in template.values() if isinstance(value, str))
+    return values if len(values) == 1 else ()
+
+
+def _selected_chat_template_strings(tokenizer, tools = None) -> tuple[str, ...]:
+    """Return the active chat template selected for this request."""
+    tools = tools or None
+    getter = getattr(tokenizer, "get_chat_template", None)
+    if callable(getter):
+        for kwargs in ({"chat_template": None, "tools": tools}, {"tools": tools}, {}):
+            try:
+                selected = getter(**kwargs)
+            except Exception:
+                continue
+            if isinstance(selected, str):
+                return (selected,)
+    # ProcessorMixin.apply_chat_template does not switch to "tool_use" implicitly;
+    # it uses "default" unless chat_template= names another template.
+    is_processor = getattr(tokenizer, "tokenizer", None) is not None and callable(
+        getattr(tokenizer, "apply_chat_template", None)
+    )
+    return _selected_template_strings_from_value(
+        getattr(tokenizer, "chat_template", None),
+        tools,
+        prefer_tool_use = not is_processor,
+    )
+
+
+def _detect_reasoning_channel_markers_from_templates(
+    templates: tuple[str, ...],
+) -> Optional[tuple[str, str]]:
+    """Return Gemma native reasoning markers only when a template emits them."""
+    if any(opener in template for template in templates for opener in _GEMMA_TEMPLATE_OPENERS):
+        return _GEMMA_THOUGHT_OPEN, _GEMMA_THOUGHT_CLOSE
+    return None
+
+
+def detect_reasoning_channel_markers(tokenizer, tools = None) -> Optional[tuple[str, str]]:
+    """Return native Gemma thought-channel markers supported by a tokenizer.
+
+    Detection uses the active chat template rather than model names or vocabulary
+    membership. Some models expose Gemma control tokens without using the native
+    thought-channel response protocol, and those must keep normal
+    ``skip_special_tokens`` streaming.
+    """
+    for obj in _tokenizer_objects(tokenizer):
+        templates = _selected_chat_template_strings(obj, tools)
+        if templates:
+            return _detect_reasoning_channel_markers_from_templates(templates)
+    return None
+
+
+def detect_reasoning_channel_markers_from_template(
+    template, tools = None
+) -> Optional[tuple[str, str]]:
+    """Return native Gemma thought-channel markers from a raw template value."""
+    return _detect_reasoning_channel_markers_from_templates(
+        _selected_template_strings_from_value(template, tools)
+    )
+
+
+def detect_reasoning_channel_markers_from_model_info(
+    tokenizer,
+    model_info: Optional[dict] = None,
+    tools = None,
+) -> Optional[tuple[str, str]]:
+    """Return reasoning markers from the active or cached native template."""
+    markers = detect_reasoning_channel_markers(tokenizer, tools = tools)
+    if markers is not None or not isinstance(model_info, dict):
+        return markers
+
+    native_templates = (
+        model_info.get("native_chat_template"),
+        (model_info.get("chat_template_info") or {}).get("template"),
+    )
+    for template in native_templates:
+        markers = detect_reasoning_channel_markers_from_template(template, tools)
+        if markers is not None:
+            return markers
+    return None
+
+
+@dataclass(frozen = True)
+class ChatTemplateRenderResult:
+    """Prompt plus response-protocol metadata selected by the renderer."""
+
+    prompt: str
+    reasoning_channel_markers: Optional[tuple[str, str]] = None
+
+
+def _split_partial_marker(text: str, marker: str) -> tuple[str, str]:
+    """Hold the longest suffix that may become ``marker`` in the next chunk."""
+    for length in range(min(len(text), len(marker) - 1), 0, -1):
+        if text.endswith(marker[:length]):
+            return text[:-length], text[-length:]
+    return text, ""
+
+
+class ReasoningChannelNormalizer:
+    """Incrementally convert one native reasoning channel to ``<think>``.
+
+    The parser follows mlx-vlm's streaming boundary behavior but emits Studio's
+    established canonical text contract. Only the configured opening and
+    closing markers are consumed; tool-call and other control markers remain
+    available to downstream parsers.
+    """
+
+    def __init__(self, opening_marker: str, closing_marker: str):
+        self._opening_marker = opening_marker
+        self._closing_marker = closing_marker
+        self._buffer = ""
+        self._in_reasoning = False
+        self._reasoning_done = False
+        self._skip_opening_newline = False
+
+    def feed(self, text: str) -> str:
+        """Consume a raw text delta and return the stable canonical delta."""
+        self._buffer += text or ""
+        output: list[str] = []
+        while self._buffer:
+            if self._reasoning_done:
+                output.append(self._buffer)
+                self._buffer = ""
+                break
+
+            if self._in_reasoning and self._skip_opening_newline:
+                if self._buffer.startswith("\n"):
+                    self._buffer = self._buffer[1:]
+                self._skip_opening_newline = False
+                if not self._buffer:
+                    break
+
+            marker = self._closing_marker if self._in_reasoning else self._opening_marker
+            index = self._buffer.find(marker)
+            if index < 0:
+                stable, self._buffer = _split_partial_marker(self._buffer, marker)
+                output.append(stable)
+                break
+
+            output.append(self._buffer[:index])
+            self._buffer = self._buffer[index + len(marker) :]
+            if self._in_reasoning:
+                output.append(_THINK_CLOSE)
+                self._in_reasoning = False
+                self._reasoning_done = True
+            else:
+                output.append(_THINK_OPEN)
+                self._in_reasoning = True
+                self._skip_opening_newline = True
+        return "".join(output)
+
+    def finish(self) -> str:
+        """Flush a naturally completed stream and close an open think block."""
+        output = self.drain()
+        if self._in_reasoning:
+            output += _THINK_CLOSE
+            self._in_reasoning = False
+            self._reasoning_done = True
+        return output
+
+    def drain(self) -> str:
+        """Flush buffered literal text without synthesizing a closing tag."""
+        output = self._buffer
+        self._buffer = ""
+        return output
+
+
+def normalize_reasoning_snapshots(
+    stream,
+    tokenizer = None,
+    cancel_event = None,
+    markers: Optional[tuple[str, str]] = None,
+    tools = None,
+):
+    """Normalize a prefix-monotonic cumulative text stream when supported."""
+    markers = markers or detect_reasoning_channel_markers(tokenizer, tools = tools)
+    if markers is None:
+        yield from stream
+        return
+
+    normalizer = ReasoningChannelNormalizer(*markers)
+    raw_output = ""
+    normalized_output = ""
+    for snapshot in stream:
+        if not snapshot.startswith(raw_output):
+            raise RuntimeError("Reasoning normalization requires cumulative text snapshots")
+        delta = normalizer.feed(snapshot[len(raw_output) :])
+        raw_output = snapshot
+        if delta:
+            normalized_output += delta
+            yield normalized_output
+
+    cancelled = cancel_event is not None and cancel_event.is_set()
+    tail = normalizer.drain() if cancelled else normalizer.finish()
+    if tail:
+        normalized_output += tail
+        yield normalized_output
 
 
 def detect_think_prefill(prompt: Optional[str], special_tokens = None) -> str:
@@ -166,7 +398,8 @@ def render_native_template(
     preserve_thinking: Optional[bool] = None,
     apply_fn = None,
     hf_token: Optional[str] = None,
-) -> Optional[str]:
+    return_metadata: bool = False,
+):
     """Render ``messages`` + ``tools`` with the model's NATIVE chat template.
 
     Some Unsloth override templates (e.g. ``mistral``, ``gemma-4``) do not emit
@@ -175,7 +408,9 @@ def render_native_template(
     tool-calling syntax. It is loaded straight from the repo (bypassing any
     override on the live tokenizer) and cached on ``model_info``. Returns the
     rendered prompt only if the native template actually emits the tools (render
-    differs with vs without tools); otherwise ``None``.
+    differs with vs without tools); otherwise ``None``. With ``return_metadata``,
+    returns ``ChatTemplateRenderResult`` so callers can stream with the response
+    protocol selected by this request's template.
 
     ``hf_token`` is the token the model was loaded with -- passed to the repo load
     so a gated/private model's native template can still be fetched (otherwise the
@@ -261,7 +496,16 @@ def render_native_template(
             exc,
         )
         return None
-    return with_tools if with_tools != no_tools else None
+    if with_tools == no_tools:
+        return None
+    if return_metadata:
+        return ChatTemplateRenderResult(
+            with_tools,
+            _detect_reasoning_channel_markers_from_templates(
+                _selected_template_strings_from_value(native_tpl, tools)
+            ),
+        )
+    return with_tools
 
 
 def render_with_native_template_fallback(
@@ -277,7 +521,8 @@ def render_with_native_template_fallback(
     preserve_thinking: Optional[bool] = None,
     apply_fn = None,
     hf_token: Optional[str] = None,
-) -> str:
+    return_metadata: bool = False,
+):
     """Return ``formatted_prompt``, swapping in a native-template render when an
     override template dropped the ``tools`` schema.
 
@@ -285,9 +530,27 @@ def render_with_native_template_fallback(
     them (detected by comparison, robust against tool names in the system prompt),
     re-render with the model's native template. Shared by the transformers and MLX
     backends so both advertise tools consistently. ``hf_token`` is forwarded so a
-    gated/private model's native template can still be fetched."""
+    gated/private model's native template can still be fetched. With
+    ``return_metadata``, returns the selected prompt plus reasoning-channel markers
+    for the exact template used by this request."""
+    live_markers = detect_reasoning_channel_markers(tokenizer, tools = tools)
+
+    def _result(prompt: str, markers = live_markers):
+        if return_metadata:
+            return ChatTemplateRenderResult(prompt, markers)
+        return prompt
+
     if not tools:
-        return formatted_prompt
+        # Gemma 4 can emit its native reasoning protocol even when a generation-time
+        # Unsloth override rendered a marker-free prompt. Preserve the live-verified
+        # no-tools thinking behavior without letting cached native metadata describe
+        # unrelated tool prompts that kept the active override.
+        markers = live_markers
+        if markers is None:
+            markers = detect_reasoning_channel_markers_from_model_info(
+                tokenizer, model_info, tools = None
+            )
+        return _result(formatted_prompt, markers)
     if apply_fn is None:
         apply_fn = apply_chat_template_for_generation
     # Probe whether the live template dropped the schema. A tools-requiring template
@@ -307,9 +570,9 @@ def render_with_native_template_fallback(
             active_model_name,
             exc,
         )
-        return formatted_prompt
+        return _result(formatted_prompt)
     if formatted_prompt != probe_no_tools:
-        return formatted_prompt  # template already emits the tools schema
+        return _result(formatted_prompt)  # template already emits the tools schema
     native_prompt = render_native_template(
         model_info = model_info,
         active_model_name = active_model_name,
@@ -320,6 +583,7 @@ def render_with_native_template_fallback(
         preserve_thinking = preserve_thinking,
         apply_fn = apply_fn,
         hf_token = hf_token,
+        return_metadata = return_metadata,
     )
     if native_prompt:
         logger.info(
@@ -328,4 +592,4 @@ def render_with_native_template_fallback(
             active_model_name,
         )
         return native_prompt
-    return formatted_prompt
+    return _result(formatted_prompt)
diff --git a/studio/backend/core/inference/inference.py b/studio/backend/core/inference/inference.py
index 172e9e5546..eae705d20e 100644
--- a/studio/backend/core/inference/inference.py
+++ b/studio/backend/core/inference/inference.py
@@ -5,7 +5,7 @@
 
 from unsloth import FastLanguageModel, FastVisionModel
 from unsloth.chat_templates import get_chat_template
-from transformers import TextStreamer
+from transformers import TextIteratorStreamer, TextStreamer
 from peft import PeftModel, PeftModelForCausalLM
 
 import json
@@ -32,6 +32,11 @@ from core.inference.chat_eos import (
     chat_eos_repair,
     resolve_chat_turn_end_eos_ids_using,
 )
+from core.inference.chat_template_helpers import (
+    ReasoningChannelNormalizer,
+    detect_reasoning_channel_markers,
+    detect_think_prefill,
+)
 from core.inference.presence_penalty import _make_presence_penalty_processor
 from io import StringIO
 import structlog
@@ -187,6 +192,53 @@ class HarmonyTextStreamer:
                     self._queue.put(new_content)
 
 
+class ReasoningTextIteratorStreamer(TextIteratorStreamer):
+    """TextIteratorStreamer that preserves native channel tokens until parsed."""
+
+    def __init__(
+        self,
+        tokenizer,
+        *,
+        markers: tuple[str, str],
+        skip_prompt: bool = True,
+        timeout: float = 0.2,
+        cancel_event = None,
+        **decode_kwargs,
+    ):
+        decode_kwargs["skip_special_tokens"] = False
+        super().__init__(tokenizer, skip_prompt = skip_prompt, timeout = timeout, **decode_kwargs)
+        self._normalizer = ReasoningChannelNormalizer(*markers)
+        self._cancel_event = cancel_event
+        self._aborted = False
+
+    def abort(self):
+        """Mark generation as failed so ``end`` drains without closing."""
+        self._aborted = True
+
+    def on_finalized_text(
+        self,
+        text: str,
+        stream_end: bool = False,
+    ):
+        """Queue canonical deltas, closing only on natural stream completion."""
+        delta = self._normalizer.feed(text)
+        if delta:
+            self.text_queue.put(delta, timeout = self.timeout)
+
+        if stream_end:
+            cancelled = self._aborted or (
+                self._cancel_event is not None and self._cancel_event.is_set()
+            )
+            tail = self._normalizer.drain() if cancelled else self._normalizer.finish()
+            if tail:
+                self.text_queue.put(tail, timeout = self.timeout)
+            self.text_queue.put(self.stop_signal, timeout = self.timeout)
+
+
+class _GenerationThreadError(RuntimeError):
+    """Generation worker failures that should propagate through stream routes."""
+
+
 class InferenceBackend:
     """Unified inference backend supporting text, vision, and LoRA models"""
 
@@ -960,8 +1012,7 @@ class InferenceBackend:
         thread can toggle adapters under the generation lock.
         """
         if not self.active_model_name:
-            yield "Error: No active model"
-            return
+            raise RuntimeError("No active model")
 
         model_info = self.models[self.active_model_name]
         is_vision = model_info.get("is_vision", False)
@@ -1049,6 +1100,7 @@ class InferenceBackend:
             template_messages = [{"role": "system", "content": system_prompt}] + messages
         else:
             template_messages = messages
+        reasoning_channel_markers_resolved = False
         try:
             if not (hasattr(tokenizer, "chat_template") and tokenizer.chat_template):
                 raise ValueError(
@@ -1058,6 +1110,7 @@ class InferenceBackend:
                     f"Please use a model that includes a chat template, or manually set "
                     f"one via tokenizer.chat_template before inference."
                 )
+            reasoning_channel_markers = None
             formatted_prompt = self._apply_chat_template_for_generation(
                 tokenizer,
                 template_messages,
@@ -1073,7 +1126,7 @@ class InferenceBackend:
                 render_with_native_template_fallback,
             )
 
-            formatted_prompt = render_with_native_template_fallback(
+            render_result = render_with_native_template_fallback(
                 formatted_prompt = formatted_prompt,
                 tokenizer = tokenizer,
                 model_info = model_info,
@@ -1085,13 +1138,19 @@ class InferenceBackend:
                 preserve_thinking = preserve_thinking,
                 apply_fn = self._apply_chat_template_for_generation,
                 hf_token = model_info.get("hf_token"),
+                return_metadata = True,
             )
+            formatted_prompt = render_result.prompt
+            reasoning_channel_markers = render_result.reasoning_channel_markers
+            reasoning_channel_markers_resolved = True
 
             logger.debug(f"Formatted prompt: {formatted_prompt[:200]}...")
         except Exception as e:
             logger.error(f"Error applying chat template: {e}")
             # Fall back to manual formatting
             formatted_prompt = self.format_chat_prompt(messages, system_prompt)
+            reasoning_channel_markers = None
+            reasoning_channel_markers_resolved = True
 
         # Step 3: generate
         yield from self.generate_stream(
@@ -1105,6 +1164,8 @@ class InferenceBackend:
             cancel_event = cancel_event,
             _adapter_state = _adapter_state,
             presence_penalty = presence_penalty,
+            reasoning_channel_markers = reasoning_channel_markers,
+            reasoning_channel_markers_resolved = reasoning_channel_markers_resolved,
         )
 
     def _generate_vision_response(
@@ -1190,21 +1251,27 @@ class InferenceBackend:
 
         # Stream with TextIteratorStreamer + background thread
         try:
-            from core.inference.chat_template_helpers import detect_think_prefill
-
             # Re-emit an open <think> prefill swallowed by skip_prompt (see
             # generate_stream).
             think_prefix = detect_think_prefill(
                 prompt_text, getattr(raw_tokenizer, "all_special_tokens", None)
             )
-            from transformers import TextIteratorStreamer
             import threading
 
-            streamer = TextIteratorStreamer(
+            streamer = self._make_text_streamer(
                 raw_tokenizer,
+                protocol_source = processor,
+                # The text-only VLM fallback above did not render with the
+                # processor template, so its native markers do not describe
+                # this request's response protocol.
+                reasoning_channel_markers = detect_reasoning_channel_markers(processor)
+                if image
+                else None,
+                reasoning_channel_markers_resolved = True,
                 skip_prompt = True,
-                skip_special_tokens = True,
                 timeout = 0.2,
+                cancel_event = cancel_event,
+                use_harmony = self._is_gpt_oss_model(),
             )
 
             generation_kwargs = dict(
@@ -1226,6 +1293,10 @@ class InferenceBackend:
                 )
                 if _pp is not None:
                     generation_kwargs["logits_processor"] = _pp
+            stopping_criteria = self._cancel_stopping_criteria(cancel_event)
+            if stopping_criteria is not None:
+                generation_kwargs["stopping_criteria"] = stopping_criteria
+            active_stop_token_ids = self._generation_stop_token_ids(model, generation_kwargs)
 
             err: dict[str, str] = {}
 
@@ -1235,6 +1306,8 @@ class InferenceBackend:
                         model.generate(**generation_kwargs)
                     except Exception as e:
                         err["msg"] = str(e)
+                        if hasattr(streamer, "abort"):
+                            streamer.abort()
                         logger.error(f"Vision generation error in thread: {e}")
                     finally:
                         try:
@@ -1251,12 +1324,17 @@ class InferenceBackend:
             if think_prefix:
                 yield think_prefix
             from queue import Empty
+            import time
 
             generation_complete = False
+            cancel_deadline = None
             try:
                 while True:
                     if cancel_event is not None and cancel_event.is_set():
-                        break
+                        if cancel_deadline is None:
+                            cancel_deadline = time.monotonic() + 10
+                        elif time.monotonic() >= cancel_deadline:
+                            break
                     try:
                         new_token = next(streamer)
                     except StopIteration:
@@ -1265,27 +1343,48 @@ class InferenceBackend:
                     except Empty:
                         if not thread.is_alive():
                             generation_complete = True
+                            output = yield from self._drain_streamer_tail(
+                                streamer, output, active_stop_token_ids
+                            )
+                            break
+                        if cancel_deadline is not None:
+                            remaining = cancel_deadline - time.monotonic()
+                            if remaining <= 0:
+                                break
+                            thread.join(timeout = remaining)
+                            if thread.is_alive():
+                                break
+                            generation_complete = True
+                            output = yield from self._drain_streamer_tail(
+                                streamer, output, active_stop_token_ids
+                            )
                             break
                         continue
                     if new_token:
-                        output += new_token
-                        cleaned = self._clean_generated_text(output)
+                        output, cleaned = self._append_stream_delta(
+                            output, new_token, active_stop_token_ids
+                        )
                         yield cleaned
             finally:
                 if cancel_event is not None and not generation_complete:
                     cancel_event.set()
-                thread.join(timeout = 10)
+                join_timeout = 10
+                if cancel_deadline is not None:
+                    join_timeout = max(0, cancel_deadline - time.monotonic())
+                thread.join(timeout = join_timeout)
                 if thread.is_alive():
                     logger.warning(
                         "Vision generation thread did not exit after cancel/join timeout"
                     )
 
             if err.get("msg"):
-                yield f"Error: {err['msg']}"
+                raise _GenerationThreadError(err["msg"])
 
+        except _GenerationThreadError:
+            raise
         except Exception as e:
             logger.error(f"Vision generation error: {e}")
-            yield f"Error: {str(e)}"
+            raise
 
     def generate_audio_input_response(
         self,
@@ -1410,11 +1509,13 @@ class InferenceBackend:
                     )
 
             if err.get("msg"):
-                yield f"Error: {err['msg']}"
+                raise _GenerationThreadError(err["msg"])
 
+        except _GenerationThreadError:
+            raise
         except Exception as e:
             logger.error(f"Audio input generation error: {e}")
-            yield f"Error: {str(e)}"
+            raise
 
     def generate_whisper_response(
         self,
@@ -1447,6 +1548,86 @@ class InferenceBackend:
         from utils.datasets import is_gpt_oss_model_name
         return is_gpt_oss_model_name(model_name or self.active_model_name or "")
 
+    def _make_text_streamer(
+        self,
+        tokenizer,
+        *,
+        protocol_source = None,
+        reasoning_channel_markers = None,
+        reasoning_channel_markers_resolved: bool = False,
+        skip_prompt: bool = True,
+        timeout: float = 0.2,
+        cancel_event = None,
+        use_harmony: bool = False,
+    ):
+        """Create the streamer matching this model's native response protocol."""
+        if use_harmony:
+            try:
+                return HarmonyTextStreamer(
+                    tokenizer,
+                    skip_prompt = skip_prompt,
+                    timeout = timeout,
+                )
+            except Exception as e:
+                logger.warning(f"HarmonyTextStreamer init failed, falling back: {e}")
+                return TextIteratorStreamer(
+                    tokenizer,
+                    skip_prompt = skip_prompt,
+                    skip_special_tokens = True,
+                    timeout = timeout,
+                )
+
+        markers = (
+            reasoning_channel_markers
+            if reasoning_channel_markers_resolved
+            else reasoning_channel_markers
+            or detect_reasoning_channel_markers(protocol_source or tokenizer)
+        )
+        if markers is not None:
+            return ReasoningTextIteratorStreamer(
+                tokenizer,
+                markers = markers,
+                skip_prompt = skip_prompt,
+                timeout = timeout,
+                cancel_event = cancel_event,
+            )
+        return TextIteratorStreamer(
+            tokenizer,
+            skip_prompt = skip_prompt,
+            skip_special_tokens = True,
+            timeout = timeout,
+        )
+
+    def _append_stream_delta(
+        self,
+        output: str,
+        new_token: str,
+        stop_token_ids = None,
+    ):
+        """Append a streamer delta and apply response-boundary cleanup."""
+        output += new_token
+        return output, self._clean_generated_text(output, stop_token_ids = stop_token_ids)
+
+    def _drain_streamer_tail(
+        self,
+        streamer,
+        output: str,
+        stop_token_ids = None,
+    ):
+        """Drain queued streamer text after the producer exits."""
+        while True:
+            try:
+                new_token = next(streamer)
+            except StopIteration:
+                return output
+            except Exception:
+                return output
+            if new_token:
+                output, cleaned = self._append_stream_delta(
+                    output, new_token, stop_token_ids = stop_token_ids
+                )
+                yield cleaned
+
     def generate_stream(
         self,
         prompt: str,
@@ -1459,6 +1640,8 @@ class InferenceBackend:
         cancel_event = None,
         _adapter_state = None,
         presence_penalty: float = 0.0,
+        reasoning_channel_markers = None,
+        reasoning_channel_markers_resolved: bool = False,
     ) -> Generator[str, None, None]:
         """Generate a streaming text response (text models only).
 
@@ -1467,8 +1650,7 @@ class InferenceBackend:
         ``presence_penalty`` matches the GGUF sampling path via a logits processor (0 disables it).
         """
         if not self.active_model_name:
-            yield "Error: No active model"
-            return
+            raise RuntimeError("No active model")
 
         model_info = self.models[self.active_model_name]
         model = model_info["model"]
@@ -1481,9 +1663,7 @@ class InferenceBackend:
         try:
             inputs = tokenizer(prompt, return_tensors = "pt").to(model.device)
 
-            from transformers import TextIteratorStreamer
             import threading
-            from core.inference.chat_template_helpers import detect_think_prefill
 
             # skip_prompt swallows an open <think> prefilled by the template;
             # re-emit it so the frontend can render the thinking block.
@@ -1494,30 +1674,16 @@ class InferenceBackend:
                 else detect_think_prefill(prompt, getattr(tokenizer, "all_special_tokens", None))
             )
 
-            # gpt-oss models: HarmonyTextStreamer parses the multi-channel
-            # harmony protocol into <think> tags
-            if self._is_gpt_oss_model():
-                try:
-                    streamer = HarmonyTextStreamer(
-                        tokenizer,
-                        skip_prompt = True,
-                        timeout = 0.2,
-                    )
-                except Exception as e:
-                    logger.warning(f"HarmonyTextStreamer init failed, falling back: {e}")
-                    streamer = TextIteratorStreamer(
-                        tokenizer,
-                        skip_prompt = True,
-                        skip_special_tokens = True,
-                        timeout = 0.2,
-                    )
-            else:
-                streamer = TextIteratorStreamer(
-                    tokenizer,
-                    skip_prompt = True,
-                    skip_special_tokens = True,
-                    timeout = 0.2,
-                )
+            streamer = self._make_text_streamer(
+                tokenizer,
+                protocol_source = model_info.get("tokenizer"),
+                reasoning_channel_markers = reasoning_channel_markers,
+                reasoning_channel_markers_resolved = reasoning_channel_markers_resolved,
+                skip_prompt = True,
+                timeout = 0.2,
+                cancel_event = cancel_event,
+                use_harmony = self._is_gpt_oss_model(),
+            )
 
             generation_kwargs = dict(
                 **inputs,
@@ -1535,27 +1701,16 @@ class InferenceBackend:
                 if tokenizer.pad_token_id is None
                 else tokenizer.pad_token_id,
             )
+            active_stop_token_ids = self._generation_stop_token_ids(model, generation_kwargs)
             # Presence penalty (GGUF parity); prompt_len excludes prompt tokens.
             _pp = _make_presence_penalty_processor(
                 presence_penalty, int(inputs["input_ids"].shape[1])
             )
             if _pp is not None:
                 generation_kwargs["logits_processor"] = _pp
-            if cancel_event is not None:
-                from transformers.generation.stopping_criteria import (
-                    StoppingCriteria,
-                    StoppingCriteriaList,
-                )
-                class _CancelCriteria(StoppingCriteria):
-                    def __init__(self, ev):
-                        self.ev = ev
-
-                    def __call__(self, input_ids, scores, **kwargs):
-                        return self.ev.is_set()
-
-                generation_kwargs["stopping_criteria"] = StoppingCriteriaList(
-                    [_CancelCriteria(cancel_event)]
-                )
+            stopping_criteria = self._cancel_stopping_criteria(cancel_event)
+            if stopping_criteria is not None:
+                generation_kwargs["stopping_criteria"] = stopping_criteria
 
             def generate_fn():
                 with self._generation_lock:
@@ -1565,6 +1720,8 @@ class InferenceBackend:
                         model.generate(**generation_kwargs)
                     except Exception as e:
                         err["msg"] = str(e)
+                        if hasattr(streamer, "abort"):
+                            streamer.abort()
                         logger.error(f"Generation error: {e}")
                     finally:
                         try:
@@ -1582,12 +1739,17 @@ class InferenceBackend:
             if think_prefix:
                 yield think_prefix
             from queue import Empty
+            import time
 
             generation_complete = False
+            cancel_deadline = None
             try:
                 while True:
                     if cancel_event is not None and cancel_event.is_set():
-                        break
+                        if cancel_deadline is None:
+                            cancel_deadline = time.monotonic() + 10
+                        elif time.monotonic() >= cancel_deadline:
+                            break
                     try:
                         new_token = next(streamer)
                     except StopIteration:
@@ -1596,11 +1758,27 @@ class InferenceBackend:
                     except Empty:
                         if not thread.is_alive():
                             generation_complete = True
+                            output = yield from self._drain_streamer_tail(
+                                streamer, output, active_stop_token_ids
+                            )
+                            break
+                        if cancel_deadline is not None:
+                            remaining = cancel_deadline - time.monotonic()
+                            if remaining <= 0:
+                                break
+                            thread.join(timeout = remaining)
+                            if thread.is_alive():
+                                break
+                            generation_complete = True
+                            output = yield from self._drain_streamer_tail(
+                                streamer, output, active_stop_token_ids
+                            )
                             break
                         continue
                     if new_token:
-                        output += new_token
-                        cleaned = self._clean_generated_text(output)
+                        output, cleaned = self._append_stream_delta(
+                            output, new_token, active_stop_token_ids
+                        )
                         yield cleaned
             finally:
                 # Set cancel_event only on early exit (user cancel), NOT on
@@ -1609,16 +1787,21 @@ class InferenceBackend:
                 # disrupt the next serialized request (e.g. compare mode).
                 if cancel_event is not None and not generation_complete:
                     cancel_event.set()
-                thread.join(timeout = 10)
+                join_timeout = 10
+                if cancel_deadline is not None:
+                    join_timeout = max(0, cancel_deadline - time.monotonic())
+                thread.join(timeout = join_timeout)
                 if thread.is_alive():
                     logger.warning("Generation thread did not exit after cancel/join timeout")
 
             if err.get("msg"):
-                yield f"Error: {err['msg']}"
+                raise _GenerationThreadError(err["msg"])
 
+        except _GenerationThreadError:
+            raise
         except Exception as e:
             logger.error(f"Error during generation: {e}")
-            yield f"Error: {str(e)}"
+            raise
 
     # ── Audio (TTS) Generation ────────────────────────────────────
 
@@ -2107,8 +2290,42 @@ class InferenceBackend:
             return img.resize(new_size, Image.Resampling.LANCZOS)
         return img
 
-    def _clean_generated_text(self, text: str) -> str:
-        """Strip leaked special tokens using the tokenizer's own token list."""
+    def _generation_stop_token_ids(self, model, generation_kwargs: dict):
+        """Return the stop-token ids active for a ``generate`` call."""
+        if "eos_token_id" in generation_kwargs:
+            return generation_kwargs.get("eos_token_id")
+        generation_config = getattr(model, "generation_config", None)
+        eos_token_id = getattr(generation_config, "eos_token_id", None)
+        if eos_token_id is not None:
+            return eos_token_id
+        config = getattr(model, "config", None)
+        return getattr(config, "eos_token_id", None)
+
+    def _cancel_stopping_criteria(self, cancel_event):
+        """Build a Transformers stopping criteria list for user cancellation."""
+        if cancel_event is None:
+            return None
+        from transformers.generation.stopping_criteria import (
+            StoppingCriteria,
+            StoppingCriteriaList,
+        )
+
+        class _CancelCriteria(StoppingCriteria):
+            def __init__(self, ev):
+                self.ev = ev
+
+            def __call__(self, input_ids, scores, **kwargs):
+                return self.ev.is_set()
+
+        return StoppingCriteriaList([_CancelCriteria(cancel_event)])
+
+    def _clean_generated_text(
+        self,
+        text: str,
+        *,
+        stop_token_ids = None,
+    ) -> str:
+        """Strip leaked response-boundary tokens after streaming."""
         if self._is_gpt_oss_model():
             # HarmonyTextStreamer emits clean <think>...</think>. Strip any
             # harmony protocol tokens and other gpt-oss tokens (e.g.
@@ -2118,10 +2335,28 @@ class InferenceBackend:
             return text.strip()
 
         tokenizer = self.models.get(self.active_model_name, {}).get("tokenizer")
+        tokenizer = getattr(tokenizer, "tokenizer", tokenizer)
         if tokenizer:
-            for token in getattr(tokenizer, "all_special_tokens", []):
-                if token in text:
-                    text = text.replace(token, "")
+            if stop_token_ids is None:
+                stop_token_ids = self.models.get(self.active_model_name, {}).get(
+                    "chat_turn_end_eos_ids"
+                )
+            if isinstance(stop_token_ids, int):
+                stop_token_ids = (stop_token_ids,)
+            for token_id in stop_token_ids or ():
+                try:
+                    token = tokenizer.convert_ids_to_tokens(int(token_id))
+                except Exception:
+                    token = None
+                if isinstance(token, str) and token and text.endswith(token):
+                    text = text[: -len(token)]
+                elif (
+                    isinstance(token, str)
+                    and token
+                    and text.endswith("</think>")
+                    and text[: -len("</think>")].endswith(token)
+                ):
+                    text = text[: -len("</think>") - len(token)] + "</think>"
         return text.strip()
 
     def _load_chat_template_info(self, model_name: str):
diff --git a/studio/backend/core/inference/mlx_inference.py b/studio/backend/core/inference/mlx_inference.py
index 163ade10c4..e7a90b4307 100644
--- a/studio/backend/core/inference/mlx_inference.py
+++ b/studio/backend/core/inference/mlx_inference.py
@@ -11,6 +11,10 @@ import threading
 from typing import Optional, Generator
 from core.inference.message_content import content_to_text
 from core.inference.runtime_context import runtime_context_length
+from core.inference.chat_template_helpers import (
+    ReasoningChannelNormalizer,
+    normalize_reasoning_snapshots,
+)
 from loggers import get_logger
 
 logger = get_logger(__name__)
@@ -533,7 +537,7 @@ class MLXInferenceBackend:
                     break
 
         if self._is_vlm:
-            yield from self._generate_vlm(
+            stream = self._generate_vlm(
                 full_messages,
                 image,
                 temperature,
@@ -550,7 +554,7 @@ class MLXInferenceBackend:
                 presence_penalty = presence_penalty,
             )
         else:
-            yield from self._generate_text(
+            stream = self._generate_text(
                 full_messages,
                 temperature,
                 top_p,
@@ -565,6 +569,7 @@ class MLXInferenceBackend:
                 preserve_thinking = preserve_thinking,
                 presence_penalty = presence_penalty,
             )
+        yield from stream
 
     def _generate_text(
         self,
@@ -609,7 +614,7 @@ class MLXInferenceBackend:
         # probe and native render share a renderer. (VLM renders via the
         # processor for image tokens and is not wired here.)
         model_info = self.models.get(self.active_model_name, {})
-        prompt = render_with_native_template_fallback(
+        render_result = render_with_native_template_fallback(
             formatted_prompt = prompt,
             tokenizer = self._tokenizer,
             model_info = model_info,
@@ -620,7 +625,10 @@ class MLXInferenceBackend:
             reasoning_effort = reasoning_effort,
             preserve_thinking = preserve_thinking,
             hf_token = model_info.get("hf_token"),
+            return_metadata = True,
         )
+        prompt = render_result.prompt
+        reasoning_channel_markers = render_result.reasoning_channel_markers
 
         # An open <think> prefilled by the template lives in the prompt, not
         # the generated tokens; re-emit it so the frontend renders the block.
@@ -654,7 +662,17 @@ class MLXInferenceBackend:
         if not logits_processors:
             logits_processors = None
 
+        preserve_native_channels = reasoning_channel_markers is not None
         token_ids = []
+        normalizer = (
+            ReasoningChannelNormalizer(*reasoning_channel_markers)
+            if reasoning_channel_markers is not None
+            else None
+        )
+        # MLX consumers diff cumulative snapshots. Keep a prompt-prefilled
+        # <think> prefix on every native-protocol snapshot just as the normal
+        # decoding path does below.
+        normalized_output = think_prefix
         logger.info(
             "Generating: prompt_len=%d, max_tokens=%d, model=%s, tokenizer=%s",
             len(prompt),
@@ -678,12 +696,19 @@ class MLXInferenceBackend:
                     **gen_kwargs,
                 ):
                     final_response = response
-                    token_ids.append(response.token)
-                    cumulative = self._tokenizer.decode(
-                        token_ids,
-                        skip_special_tokens = True,
-                    )
-                    yield think_prefix + cumulative
+                    if preserve_native_channels:
+                        piece = getattr(response, "text", None) or ""
+                        delta = normalizer.feed(piece)
+                        if delta:
+                            normalized_output += delta
+                            yield normalized_output
+                    else:
+                        token_ids.append(response.token)
+                        cumulative = self._tokenizer.decode(
+                            token_ids,
+                            skip_special_tokens = True,
+                        )
+                        yield think_prefix + cumulative
 
                     if cancel_event and cancel_event.is_set():
                         break
@@ -700,6 +725,12 @@ class MLXInferenceBackend:
                         getattr(final_response, "generation_tokens", 0),
                         getattr(final_response, "generation_tps", 0.0),
                     )
+        if normalizer is not None:
+            cancelled = cancel_event is not None and cancel_event.is_set()
+            tail = normalizer.drain() if cancelled else normalizer.finish()
+            if tail:
+                normalized_output += tail
+                yield normalized_output
 
     def _generate_vlm(
         self,
@@ -858,31 +889,37 @@ class MLXInferenceBackend:
         elif _rep_active:
             vlm_kwargs["repetition_penalty"] = float(repetition_penalty)
 
-        with self._generation_lock:
-            final_response = None
-            try:
-                for response in vlm_stream(
-                    self._model,
-                    self._processor,
-                    prompt,
-                    images,
-                    **vlm_kwargs,
-                ):
-                    final_response = response
-                    token_text = response.text if hasattr(response, "text") else str(response)
-                    cumulative += token_text
-                    yield cumulative
-                    if cancel_event and cancel_event.is_set():
-                        break
-            finally:
-                # mlx_vlm exposes the same stats fields as mlx_lm.
-                if final_response is not None:
-                    self.last_generation_stats = _build_generation_stats(
-                        getattr(final_response, "prompt_tokens", 0),
-                        getattr(final_response, "prompt_tps", 0.0),
-                        getattr(final_response, "generation_tokens", 0),
-                        getattr(final_response, "generation_tps", 0.0),
-                    )
+        def _stream_vlm_snapshots():
+            nonlocal cumulative
+            with self._generation_lock:
+                final_response = None
+                try:
+                    for response in vlm_stream(
+                        self._model,
+                        self._processor,
+                        prompt,
+                        images,
+                        **vlm_kwargs,
+                    ):
+                        final_response = response
+                        token_text = response.text if hasattr(response, "text") else str(response)
+                        cumulative += token_text
+                        yield cumulative
+                        if cancel_event and cancel_event.is_set():
+                            break
+                finally:
+                    # mlx_vlm exposes the same stats fields as mlx_lm.
+                    if final_response is not None:
+                        self.last_generation_stats = _build_generation_stats(
+                            getattr(final_response, "prompt_tokens", 0),
+                            getattr(final_response, "prompt_tps", 0.0),
+                            getattr(final_response, "generation_tokens", 0),
+                            getattr(final_response, "generation_tps", 0.0),
+                        )
+
+        yield from normalize_reasoning_snapshots(
+            _stream_vlm_snapshots(), chat_target, cancel_event, tools = tools
+        )
 
     def generate_with_adapter_control(
         self,
diff --git a/studio/backend/core/inference/orchestrator.py b/studio/backend/core/inference/orchestrator.py
index c2082bc198..ea3b164052 100644
--- a/studio/backend/core/inference/orchestrator.py
+++ b/studio/backend/core/inference/orchestrator.py
@@ -59,7 +59,32 @@ class GenStreamError(str):
     "Error:" by checking isinstance(chunk, GenStreamError).
     """
 
-    __slots__ = ()
+    __slots__ = ("public",)
+
+    def __new__(
+        cls,
+        value,
+        *,
+        public: bool = False,
+    ):
+        obj = str.__new__(cls, value)
+        obj.public = bool(public)
+        return obj
+
+
+class GenStreamErrorRaised(RuntimeError):
+    """Internal exception form of ``GenStreamError`` for generator boundaries."""
+
+    __slots__ = ("public",)
+
+    def __init__(
+        self,
+        value,
+        *,
+        public: bool = False,
+    ):
+        super().__init__(value)
+        self.public = bool(public)
 
 
 class InferenceOrchestrator:
@@ -531,13 +556,19 @@ class InferenceOrchestrator:
         initial_resp_queue = self._resp_queue
         while True:
             if self._proc is not initial_proc or self._resp_queue is not initial_resp_queue:
-                yield GenStreamError(f"Error: {self._subprocess_crash_message(crash_context)}")
+                yield GenStreamError(
+                    f"Error: {self._subprocess_crash_message(crash_context)}",
+                    public = True,
+                )
                 return
             resp = read_one(read_timeout)
             if resp is None:
                 # Check subprocess health
                 if not self._ensure_subprocess_alive():
-                    yield GenStreamError(f"Error: {self._subprocess_crash_message(crash_context)}")
+                    yield GenStreamError(
+                        f"Error: {self._subprocess_crash_message(crash_context)}",
+                        public = True,
+                    )
                     return
                 continue
 
@@ -689,11 +720,11 @@ class InferenceOrchestrator:
         GPU work stays serialized; this only avoids orchestrator lock contention.
         """
         if not self._ensure_subprocess_alive():
-            yield GenStreamError("Error: Inference subprocess is not running")
+            yield GenStreamError("Error: Inference subprocess is not running", public = True)
             return
 
         if not self.active_model_name:
-            yield GenStreamError("Error: No active model")
+            yield GenStreamError("Error: No active model", public = True)
             return
         # Latch the target model so the recheck below can detect a switch that completed
         # between _start_dispatcher and mailbox registration (mirrors the locked path's
@@ -704,7 +735,7 @@ class InferenceOrchestrator:
         # so without this early-out a compare request would enqueue a generate on the
         # outgoing model and delay the switch.
         if self._unload_pending:
-            yield GenStreamError("Error: model is being unloaded")
+            yield GenStreamError("Error: model is being unloaded", public = True)
             return
 
         # Ensure the dispatcher runs. _start_dispatcher serializes concurrent starters under
@@ -776,7 +807,7 @@ class InferenceOrchestrator:
             # _stop_dispatcher joins the dispatcher, which itself takes that lock.
             if orphaned_dispatcher:
                 self._stop_dispatcher()
-            yield GenStreamError("Error: model is being unloaded")
+            yield GenStreamError("Error: model is being unloaded", public = True)
             return
 
         try:
@@ -1414,12 +1445,27 @@ class InferenceOrchestrator:
                 presence_penalty = presence_penalty,
             )
             if use_adapter is not None:
-                yield from self.generate_with_adapter_control(
+                stream = self.generate_with_adapter_control(
                     use_adapter = use_adapter,
                     **common_kwargs,
                 )
             else:
-                yield from self.generate_chat_response(**common_kwargs)
+                stream = self.generate_chat_response(**common_kwargs)
+            close_stream = False
+            try:
+                for chunk in stream:
+                    if isinstance(chunk, GenStreamError):
+                        close_stream = True
+                        raise GenStreamErrorRaised(str(chunk), public = chunk.public)
+                    yield chunk
+            finally:
+                if close_stream:
+                    close = getattr(stream, "close", None)
+                    if callable(close):
+                        try:
+                            close()
+                        except Exception:
+                            logger.debug("failed to close errored generation stream", exc_info = True)
 
         initial = list(messages)
         if system_prompt:
@@ -1489,11 +1535,11 @@ class InferenceOrchestrator:
         readers don't consume each other's tokens off the shared resp_queue.
         """
         if not self._ensure_subprocess_alive():
-            yield GenStreamError("Error: Inference subprocess is not running")
+            yield GenStreamError("Error: Inference subprocess is not running", public = True)
             return
 
         if not self.active_model_name:
-            yield GenStreamError("Error: No active model")
+            yield GenStreamError("Error: No active model", public = True)
             return
         expected_model = self.active_model_name
 
@@ -1510,7 +1556,7 @@ class InferenceOrchestrator:
             # so we never generate on the wrong one.
             if self._unload_pending or self.active_model_name != expected_model:
                 # Won the lock handoff during a switch; don't start on the outgoing model.
-                yield GenStreamError("Error: model is being unloaded")
+                yield GenStreamError("Error: model is being unloaded", public = True)
                 return
             request_id = str(uuid.uuid4())
             image_b64 = self._pil_to_base64(image) if image is not None else None
@@ -1695,10 +1741,10 @@ class InferenceOrchestrator:
     ) -> Generator[str, None, None]:
         """Shared inner logic for audio input generation (Whisper + ASR)."""
         if not self._ensure_subprocess_alive():
-            yield GenStreamError("Error: Inference subprocess is not running")
+            yield GenStreamError("Error: Inference subprocess is not running", public = True)
             return
         if not self.active_model_name:
-            yield GenStreamError("Error: No active model")
+            yield GenStreamError("Error: No active model", public = True)
             return
         expected_model = self.active_model_name
 
@@ -1707,7 +1753,7 @@ class InferenceOrchestrator:
             # cleared or swapped the model while we waited.
             if self._unload_pending or self.active_model_name != expected_model:
                 # Won the lock handoff during a switch; don't start on the outgoing model.
-                yield GenStreamError("Error: model is being unloaded")
+                yield GenStreamError("Error: model is being unloaded", public = True)
                 return
             request_id = str(uuid.uuid4())
 
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index 81dea96274..d6090e2b62 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -29,6 +29,7 @@ import re as _re
 from utils.models import extract_model_size_b as _extract_model_size_b
 
 from utils.api_errors import openai_error_body, anthropic_error_body
+from core.inference.orchestrator import GenStreamError, GenStreamErrorRaised
 from core.inference.llama_admission import (
     LlamaAdmissionCancelled,
     LlamaAdmissionConfig,
@@ -213,6 +214,14 @@ def _friendly_error(exc: Exception) -> str:
     return "An internal error occurred"
 
 
+def _friendly_gen_stream_error(value) -> str:
+    """Return a client-safe message for typed local generation errors."""
+    text = str(value)
+    if getattr(value, "public", False):
+        return text
+    return safe_error_detail(RuntimeError(text), fallback = "An internal error occurred.")
+
+
 def _friendly_upstream_error(text: str) -> str:
     """Rewrite a raw llama-server error body into an actionable message where we can.
 
@@ -1918,16 +1927,57 @@ async def artifact_preview_frame(allow_network: bool = False):
 _BARE_JSON_NAME_MARKER_RE = _re.compile(r'\{\s*\\?"(?:name|function)\\?"\s*:')
 
 
-def _detect_safetensors_features(backend, chat_template: Optional[str]) -> dict:
+def _detect_safetensors_features(
+    backend,
+    chat_template: Optional[str],
+    tools = None,
+) -> dict:
     """Classify reasoning/tool capabilities via the GGUF classifier so flags
     match across backends. gpt-oss is overridden: Harmony routes reasoning and
     tools through tokenizer channels, not template markup."""
     model_id = getattr(backend, "active_model_name", None)
+    feature_template = chat_template
+    try:
+        from core.inference.chat_template_helpers import _selected_template_strings_from_value
+        selected_templates = _selected_template_strings_from_value(chat_template, tools)
+        if selected_templates:
+            feature_template = selected_templates[0]
+    except Exception:
+        logger.debug("safetensors_named_template_selection_failed", exc_info = True)
     flags = detect_reasoning_flags(
-        chat_template,
+        feature_template,
         model_identifier = model_id,
         log_source = "safetensors",
     )
+    if not flags.get("supports_reasoning"):
+        try:
+            from core.inference.chat_template_helpers import (
+                detect_reasoning_channel_markers_from_template,
+            )
+
+            templates = [chat_template]
+            models = getattr(backend, "models", None)
+            model_info = (
+                models.get(model_id, {})
+                if isinstance(models, dict) and model_id is not None
+                else {}
+            )
+            if isinstance(model_info, dict):
+                templates.extend(
+                    (
+                        model_info.get("native_chat_template"),
+                        (model_info.get("chat_template_info") or {}).get("template"),
+                    )
+                )
+            if any(
+                detect_reasoning_channel_markers_from_template(template, tools = tools) is not None
+                for template in templates
+            ):
+                flags["supports_reasoning"] = True
+                flags["reasoning_always_on"] = True
+                logger.info("safetensors: model always reasons (native channel markers)")
+        except Exception:
+            logger.debug("safetensors_native_reasoning_marker_check_failed", exc_info = True)
     # Markers any supported parser recognises (template advertises tools but
     # uses none -> drop the pill). Reuse the parser's own signal list so this
     # gate never drifts (a hand-maintained copy lost the DeepSeek variants);
@@ -1941,9 +1991,9 @@ def _detect_safetensors_features(backend, chat_template: Optional[str]) -> dict:
     )
     if (
         flags.get("supports_tools")
-        and chat_template
-        and not any(m in chat_template for m in _PARSER_MARKERS)
-        and not _BARE_JSON_NAME_MARKER_RE.search(chat_template)
+        and isinstance(feature_template, str)
+        and not any(m in feature_template for m in _PARSER_MARKERS)
+        and not _BARE_JSON_NAME_MARKER_RE.search(feature_template)
     ):
         logger.info(
             "safetensors: template advertises tools but uses an "
@@ -5424,6 +5474,10 @@ async def generate_stream(
                 if chunk is _DONE:
                     completed = True
                     break
+                if isinstance(chunk, GenStreamError):
+                    yield f"data: {json.dumps({'error': _friendly_gen_stream_error(chunk)})}\n\n"
+                    yield "data: [DONE]\n\n"
+                    return
                 yield f"data: {json.dumps({'content': chunk})}\n\n"
             if completed:
                 yield "data: [DONE]\n\n"
@@ -5437,6 +5491,7 @@ async def generate_stream(
             backend.reset_generation_state()
             logger.error(f"Error during generation: {e}", exc_info = True)
             yield f"data: {json.dumps({'error': _friendly_error(e)})}\n\n"
+            yield "data: [DONE]\n\n"
         finally:
             await _stop_local_disconnect_cancel_watcher(disconnect_watcher)
             if not completed and not cancel_event.is_set():
@@ -7060,6 +7115,13 @@ async def openai_chat_completions(
                             chunk_text = await asyncio.to_thread(next, gen, _DONE)
                             if chunk_text is _DONE:
                                 break
+                            if isinstance(chunk_text, GenStreamError):
+                                _msg = _friendly_gen_stream_error(chunk_text)
+                                api_monitor.fail(monitor_id, _msg)
+                                yield _openai_stream_error_sse(
+                                    {"error": {"message": _msg, "type": "server_error"}}
+                                )
+                                return
                             if chunk_text:
                                 api_monitor.append_reply(monitor_id, chunk_text)
                                 yield _chat_content_chunk(
@@ -7075,8 +7137,11 @@ async def openai_chat_completions(
                         raise
                     except Exception as e:
                         logger.error(f"Error during audio input streaming: {e}", exc_info = True)
-                        api_monitor.fail(monitor_id, _friendly_error(e))
-                        yield f"data: {json.dumps({'error': {'message': _friendly_error(e), 'type': 'server_error'}})}\n\n"
+                        _msg = _friendly_error(e)
+                        api_monitor.fail(monitor_id, _msg)
+                        yield _openai_stream_error_sse(
+                            {"error": {"message": _msg, "type": "server_error"}}
+                        )
                     finally:
                         await _stop_local_disconnect_cancel_watcher(disconnect_watcher)
                         _tracker.__exit__(None, None, None)
@@ -7093,7 +7158,15 @@ async def openai_chat_completions(
                 )
             else:
                 try:
-                    full_text = "".join(audio_input_generate())
+                    full_text = ""
+                    for chunk_text in audio_input_generate():
+                        if isinstance(chunk_text, GenStreamError):
+                            _msg = _friendly_gen_stream_error(chunk_text)
+                            api_monitor.fail(monitor_id, _msg)
+                            raise HTTPException(status_code = 500, detail = _msg)
+                        full_text += chunk_text
+                except HTTPException:
+                    raise
                 except Exception as e:
                     api_monitor.fail(monitor_id, _friendly_error(e))
                     raise
@@ -8637,19 +8710,33 @@ async def openai_chat_completions(
     # Classify capability flags from the loaded template.
     _sf_model_info = backend.models.get(backend.active_model_name, {})
     _sf_tpl = (_sf_model_info.get("chat_template_info") or {}).get("template")
-    _sf_features = _detect_safetensors_features(backend, _sf_tpl)
-
-    # GGUF parity: enable_thinking templates prefill an unclosed <think>; split into
-    # reasoning_content deltas so the UI renders the block for safetensors and MLX.
-    _sf_parse_think = bool(
-        _sf_features.get("supports_reasoning") or _sf_features.get("reasoning_always_on")
+    # Named templates may expose native reasoning only in their ``tool_use``
+    # branch. Use a truthy placeholder for Studio-managed tools, whose concrete
+    # schemas are selected below, and the request schemas for client passthrough.
+    _sf_server_tool_intent = bool(
+        _effective_enable_tools(payload) or _explicit_studio_tool_loop_requested(payload)
     )
-    # Prefilled-open only for prefill styles with thinking on; gpt-oss uses the normal mode.
-    _sf_reasoning_prefilled = _sf_reasoning_prefill_mode(
-        _sf_features,
-        payload.enable_thinking,
-        _sf_tpl,
-        reasoning_effort = payload.reasoning_effort,
+    _sf_template_tools = payload.tools if payload.tool_choice != "none" else None
+    if not _sf_template_tools and _sf_server_tool_intent:
+        _sf_template_tools = ({},)
+
+    def _sf_response_protocol(tools = None):
+        features = _detect_safetensors_features(backend, _sf_tpl, tools = tools)
+        parse_think = bool(
+            features.get("supports_reasoning") or features.get("reasoning_always_on")
+        )
+        reasoning_prefilled = _sf_reasoning_prefill_mode(
+            features,
+            payload.enable_thinking,
+            _sf_tpl,
+            reasoning_effort = payload.reasoning_effort,
+        )
+        return features, parse_think, reasoning_prefilled
+
+    # GGUF parity: split canonical <think> output into reasoning_content. The
+    # selected template branch must match whether this request renders tools.
+    _sf_features, _sf_parse_think, _sf_reasoning_prefilled = _sf_response_protocol(
+        _sf_template_tools
     )
 
     def _new_sf_reasoning_extractor():
@@ -8858,6 +8945,18 @@ async def openai_chat_completions(
                     _sf_next_task = None
                     if event is _sf_tool_sentinel:
                         break
+                    if isinstance(event, GenStreamError):
+                        backend.reset_generation_state()
+                        _msg = _friendly_gen_stream_error(event)
+                        api_monitor.fail(monitor_id, _msg)
+                        yield _openai_stream_error_sse(
+                            {"error": {"message": _msg, "type": "server_error"}}
+                        )
+                        return
+                    if not isinstance(event, dict):
+                        raise RuntimeError(
+                            f"Invalid safetensors tool event: {type(event).__name__}"
+                        )
 
                     if event["type"] == "heartbeat":
                         # Tool-execution wrapper heartbeat -> SSE keepalive.
@@ -8945,6 +9044,11 @@ async def openai_chat_completions(
                 backend.reset_generation_state()
                 api_monitor.finish(monitor_id, "cancelled")
                 raise
+            except GenStreamErrorRaised as exc:
+                backend.reset_generation_state()
+                _msg = _friendly_gen_stream_error(exc)
+                api_monitor.fail(monitor_id, _msg)
+                yield _openai_stream_error_sse({"error": {"message": _msg, "type": "server_error"}})
             except Exception:
                 backend.reset_generation_state()
                 # Generic wire message; full trace stays in the log (CWE-209:
@@ -8994,6 +9098,15 @@ async def openai_chat_completions(
                 for event in gen:
                     if cancel_event.is_set():
                         break
+                    if isinstance(event, GenStreamError):
+                        raise HTTPException(
+                            status_code = 500,
+                            detail = _friendly_gen_stream_error(event),
+                        )
+                    if not isinstance(event, dict):
+                        raise RuntimeError(
+                            f"Invalid safetensors tool event: {type(event).__name__}"
+                        )
                     if event.get("type") == "content":
                         full_text = _strip_tool_xml_for_display(
                             event.get("text", ""),
@@ -9034,6 +9147,15 @@ async def openai_chat_completions(
             backend.reset_generation_state()
             api_monitor.finish(monitor_id, "cancelled")
             raise
+        except GenStreamErrorRaised as exc:
+            backend.reset_generation_state()
+            _msg = _friendly_gen_stream_error(exc)
+            api_monitor.fail(monitor_id, _msg)
+            raise HTTPException(status_code = 500, detail = _msg)
+        except HTTPException as exc:
+            backend.reset_generation_state()
+            api_monitor.fail(monitor_id, str(exc.detail))
+            raise
         except Exception:
             backend.reset_generation_state()
             # CWE-209: generic detail; full trace in log.
@@ -9120,6 +9242,12 @@ async def openai_chat_completions(
         else:
             gen_kwargs["tools"] = payload.tools
 
+    # The potential tool context above is needed before server/client routing is
+    # known. This standard path now has the exact schemas that will be rendered,
+    # so resolve reasoning parsing again to keep empty registries, forced-tool
+    # misses, and tool_choice="none" on the marker-free template branch.
+    _, _sf_parse_think, _sf_reasoning_prefilled = _sf_response_protocol(gen_kwargs.get("tools"))
+
     # Request-scoped usage/timings receptacle (filled at gen_done).
     stats_holder: dict = {}
 
@@ -9200,6 +9328,14 @@ async def openai_chat_completions(
                     _next_task = None
                     if cumulative is _DONE:
                         break
+                    if isinstance(cumulative, GenStreamError):
+                        backend.reset_generation_state()
+                        _msg = _friendly_gen_stream_error(cumulative)
+                        api_monitor.fail(monitor_id, _msg)
+                        yield _openai_stream_error_sse(
+                            {"error": {"message": _msg, "type": "server_error"}}
+                        )
+                        return
                     if await request.is_disconnected():
                         cancel_event.set()
                         backend.reset_generation_state()
@@ -9349,6 +9485,11 @@ async def openai_chat_completions(
         try:
             full_text = ""
             for token in generate():
+                if isinstance(token, GenStreamError):
+                    backend.reset_generation_state()
+                    _msg = _friendly_gen_stream_error(token)
+                    api_monitor.fail(monitor_id, _msg)
+                    raise HTTPException(status_code = 500, detail = _msg)
                 full_text = token
 
             # Split prefilled <think> reasoning (GGUF parity); also covers MLX via
@@ -9447,6 +9588,8 @@ async def openai_chat_completions(
             api_monitor.finish(monitor_id)
             return _model_json_response(response)
 
+        except HTTPException:
+            raise
         except Exception as e:
             backend.reset_generation_state()
             logger.error(f"Error during OpenAI completion: {e}", exc_info = True)
diff --git a/studio/backend/tests/test_mlx_inference_backend.py b/studio/backend/tests/test_mlx_inference_backend.py
index 29fbb45158..fa50cd84d6 100644
--- a/studio/backend/tests/test_mlx_inference_backend.py
+++ b/studio/backend/tests/test_mlx_inference_backend.py
@@ -523,3 +523,169 @@ def test_mlx_generate_text_forwards_kwargs_into_template_helper(monkeypatch):
     assert render["kwargs"]["enable_thinking"] is True
     assert render["kwargs"]["reasoning_effort"] == "medium"
     assert render["kwargs"]["preserve_thinking"] is True
+
+
+def test_mlx_text_normalizes_native_reasoning_and_close_releases_lock(monkeypatch):
+    _install_fake_mlx(monkeypatch)
+    from core.inference.mlx_inference import MLXInferenceBackend
+
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.apply_chat_template_for_generation",
+        lambda *_args, **_kwargs: "prompt",
+        raising = True,
+    )
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.render_with_native_template_fallback",
+        lambda formatted_prompt, **_kwargs: SimpleNamespace(
+            prompt = formatted_prompt,
+            reasoning_channel_markers = ("<|channel>thought\n", "<channel|>"),
+        ),
+        raising = True,
+    )
+
+    mlx_lm_pkg = types.ModuleType("mlx_lm")
+    mlx_lm_sample = types.ModuleType("mlx_lm.sample_utils")
+    mlx_lm_sample.make_sampler = lambda **_kw: object()
+    mlx_lm_sample.make_logits_processors = lambda **_kw: None
+
+    class _Resp:
+        def __init__(self, text, tok):
+            self.text = text
+            self.token = tok
+
+    def _stream_generate(_model, _tokenizer, **_kw):
+        yield _Resp("<|channel>thought\n", 10)
+        yield _Resp("r", 11)
+        yield _Resp("<channel|>", 12)
+        yield _Resp("a", 13)
+
+    mlx_lm_pkg.stream_generate = _stream_generate
+    monkeypatch.setitem(sys.modules, "mlx_lm", mlx_lm_pkg)
+    monkeypatch.setitem(sys.modules, "mlx_lm.sample_utils", mlx_lm_sample)
+
+    backend = MLXInferenceBackend()
+    backend._model = object()
+    backend._tokenizer = SimpleNamespace(all_special_tokens = [])
+    backend._is_vlm = False
+
+    assert list(
+        backend.generate_chat_response(
+            messages = [{"role": "user", "content": "ping"}],
+            max_new_tokens = 4,
+        )
+    ) == ["<think>", "<think>r", "<think>r</think>", "<think>r</think>a"]
+
+    gen = backend.generate_chat_response(
+        messages = [{"role": "user", "content": "ping"}],
+        max_new_tokens = 4,
+    )
+    assert next(gen) == "<think>"
+    assert backend._generation_lock.locked()
+    gen.close()
+    assert not backend._generation_lock.locked()
+
+
+def test_mlx_text_native_metadata_preserves_prefilled_think_snapshots(monkeypatch):
+    _install_fake_mlx(monkeypatch)
+    from core.inference.mlx_inference import MLXInferenceBackend
+
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.apply_chat_template_for_generation",
+        lambda *_args, **_kwargs: "prompt<think>\n",
+        raising = True,
+    )
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.render_with_native_template_fallback",
+        lambda formatted_prompt, **_kwargs: SimpleNamespace(
+            prompt = formatted_prompt,
+            reasoning_channel_markers = ("<|channel>thought", "<channel|>"),
+        ),
+        raising = True,
+    )
+
+    mlx_lm_pkg = types.ModuleType("mlx_lm")
+    mlx_lm_sample = types.ModuleType("mlx_lm.sample_utils")
+    mlx_lm_sample.make_sampler = lambda **_kw: object()
+    mlx_lm_sample.make_logits_processors = lambda **_kw: None
+
+    class _Resp:
+        def __init__(self, text, tok):
+            self.text = text
+            self.token = tok
+
+    def _stream_generate(_model, _tokenizer, **_kw):
+        yield _Resp("reason", 10)
+        yield _Resp("</think>", 11)
+        yield _Resp("answer", 12)
+
+    mlx_lm_pkg.stream_generate = _stream_generate
+    monkeypatch.setitem(sys.modules, "mlx_lm", mlx_lm_pkg)
+    monkeypatch.setitem(sys.modules, "mlx_lm.sample_utils", mlx_lm_sample)
+
+    backend = MLXInferenceBackend()
+    backend._model = object()
+    backend._tokenizer = SimpleNamespace(all_special_tokens = [])
+    backend._is_vlm = False
+
+    snapshots = list(
+        backend.generate_chat_response(
+            messages = [{"role": "user", "content": "ping"}],
+            max_new_tokens = 3,
+        )
+    )
+    assert snapshots == [
+        "<think>\n",
+        "<think>\nreason",
+        "<think>\nreason</think>",
+        "<think>\nreason</think>answer",
+    ]
+    assert all(current.startswith(previous) for previous, current in zip(snapshots, snapshots[1:]))
+
+
+def test_mlx_vlm_normalizes_native_reasoning_channels(monkeypatch):
+    _install_fake_mlx(monkeypatch)
+    from core.inference.mlx_inference import MLXInferenceBackend
+
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.apply_chat_template_for_generation",
+        lambda *_args, **_kwargs: "prompt",
+        raising = True,
+    )
+
+    mlx_vlm_pkg = types.ModuleType("mlx_vlm")
+
+    class _Resp:
+        def __init__(self, text, tok):
+            self.text = text
+            self.token = tok
+
+    def _stream_generate(_model, _processor, _prompt, _images, **_kw):
+        yield _Resp("<|channel>thought\n", 10)
+        yield _Resp("vision", 11)
+        yield _Resp("<channel|>", 12)
+        yield _Resp(" answer", 13)
+
+    mlx_vlm_pkg.stream_generate = _stream_generate
+    monkeypatch.setitem(sys.modules, "mlx_vlm", mlx_vlm_pkg)
+
+    backend = MLXInferenceBackend()
+    backend._model = SimpleNamespace(config = SimpleNamespace())
+    backend._processor = SimpleNamespace(
+        chat_template = "<|channel>thought\n...<channel|>",
+        all_special_tokens = [],
+        apply_chat_template = lambda *_args, **_kwargs: "prompt",
+    )
+    backend._is_vlm = True
+
+    assert list(
+        backend.generate_chat_response(
+            messages = [{"role": "user", "content": "describe"}],
+            image = object(),
+            max_new_tokens = 4,
+        )
+    ) == [
+        "<think>",
+        "<think>vision",
+        "<think>vision</think>",
+        "<think>vision</think> answer",
+    ]
diff --git a/studio/backend/tests/test_openai_tool_passthrough.py b/studio/backend/tests/test_openai_tool_passthrough.py
index 5300a48557..8725b28ac8 100644
--- a/studio/backend/tests/test_openai_tool_passthrough.py
+++ b/studio/backend/tests/test_openai_tool_passthrough.py
@@ -1054,7 +1054,7 @@ class TestChatCompletionRequestToolFields:
         monkeypatch.setattr(
             inference_route,
             "_detect_safetensors_features",
-            lambda backend, chat_template: {"supports_tools": True},
+            lambda backend, chat_template, tools = None: {"supports_tools": True},
         )
         monitor = ApiMonitor(max_entries = 3)
         monkeypatch.setattr(inference_route, "api_monitor", monitor)
@@ -6620,6 +6620,29 @@ class TestApiMonitorAudioInput:
             assert entry["reply"] == "hello world"
             assert monitor.active_count() == 0
 
+            def failing_chunks():
+                yield "partial"
+                raise RuntimeError("generation failed")
+
+            self._patch_audio_backend(monkeypatch, failing_chunks())
+            error_monitor = ApiMonitor(max_entries = 3)
+            monkeypatch.setattr(inf_mod, "api_monitor", error_monitor)
+            error_response = await openai_chat_completions(
+                payload,
+                request = request,
+                current_subject = "test",
+            )
+            error_chunks = [
+                chunk.decode() if isinstance(chunk, bytes) else chunk
+                async for chunk in error_response.body_iterator
+            ]
+
+            assert '"type": "server_error"' in error_chunks[-1]
+            assert error_chunks[-1].endswith("data: [DONE]\n\n")
+            [error_entry] = error_monitor.snapshot()
+            assert error_entry["status"] == "error"
+            assert error_monitor.active_count() == 0
+
         asyncio.run(_run())
 
     def test_non_gguf_tts_auto_route_records_monitor(self, monkeypatch):
diff --git a/studio/backend/tests/test_safetensors_capability_advertise.py b/studio/backend/tests/test_safetensors_capability_advertise.py
index 0ed670ac01..bd3d8d16b9 100644
--- a/studio/backend/tests/test_safetensors_capability_advertise.py
+++ b/studio/backend/tests/test_safetensors_capability_advertise.py
@@ -417,6 +417,59 @@ def test_detect_safetensors_features_gemma_native_tool_call_keeps_tools_on():
     assert flags["supports_tools"] is True
 
 
+def test_detect_safetensors_features_gemma_native_reasoning_is_parseable_not_prefilled():
+    """Native Gemma channels are normalized to <think>, then split by the route."""
+    from routes.inference import _detect_safetensors_features, _sf_reasoning_prefill_mode
+
+    tpl_with_gemma_native = "{% if add_generation_prompt %}<|channel>thought\n<channel|>{% endif %}"
+    backend = SimpleNamespace(
+        active_model_name = "unsloth/gemma-4-E2B-it",
+        models = {
+            "unsloth/gemma-4-E2B-it": {
+                "native_chat_template": tpl_with_gemma_native,
+                "chat_template_info": {"template": "override has no native markers"},
+            }
+        },
+    )
+    flags = _detect_safetensors_features(backend, "override has no native markers")
+    missing_arg_flags = _detect_safetensors_features(backend, None)
+
+    assert flags["supports_reasoning"] is True
+    assert flags["reasoning_always_on"] is True
+    assert missing_arg_flags["supports_reasoning"] is True
+    assert _sf_reasoning_prefill_mode(flags, None, tpl_with_gemma_native) is False
+
+
+def test_detect_safetensors_features_selects_native_reasoning_from_tool_template():
+    """Request tools select a marker-bearing named template without affecting default chat."""
+    from routes.inference import _detect_safetensors_features
+
+    named_template = {
+        "default": "plain default template",
+        "tool_use": "{% if tools %}<|channel>thought\n<channel|>{% endif %}",
+    }
+    backend = SimpleNamespace(
+        active_model_name = "custom/named-native-reasoning",
+        models = {
+            "custom/named-native-reasoning": {
+                "native_chat_template": named_template,
+                "chat_template_info": {"template": "{% if tools %}<tool_call>{% endif %}"},
+            }
+        },
+    )
+
+    default_flags = _detect_safetensors_features(backend, "plain override")
+    tool_flags = _detect_safetensors_features(
+        backend,
+        "plain override",
+        tools = [{"type": "function"}],
+    )
+
+    assert default_flags["supports_reasoning"] is False
+    assert tool_flags["supports_reasoning"] is True
+    assert tool_flags["reasoning_always_on"] is True
+
+
 # Qwen3.5 family pin: the live GGUF + safetensors templates both wrap tool
 # calls as ``<tool_call>\n<function=name>...``. Faithful slice so the
 # classifier never silently regresses for this family.
diff --git a/studio/backend/tests/test_safetensors_reasoning_stream.py b/studio/backend/tests/test_safetensors_reasoning_stream.py
index 4e708139b7..af5a05d266 100644
--- a/studio/backend/tests/test_safetensors_reasoning_stream.py
+++ b/studio/backend/tests/test_safetensors_reasoning_stream.py
@@ -215,3 +215,135 @@ def test_s6_reasoning_effort_none_disables_prefill_for_enable_thinking_effort():
     swallowed = _replay_sf_reasoning_stream(events, prefilled = True)
     assert swallowed["visible"] == ""
     assert swallowed["reasoning"] == "The capital of France is Paris."
+
+
+def test_native_reasoning_streamer_selected_and_errors_raise():
+    import threading
+    import pytest
+
+    torch = pytest.importorskip("torch")
+    inf = pytest.importorskip("core.inference.inference")
+
+    class Batch(dict):
+        def to(self, _device):
+            return self
+
+    class Tok:
+        chat_template = "<|channel>thought\n...<channel|>"
+        all_special_tokens = []
+        eos_token_id = 1
+        pad_token_id = None
+        pieces = {10: "<|channel>thought\n", 11: "r", 12: "<channel|>", 13: "a"}
+
+        def __call__(self, *_args, **_kwargs):
+            return Batch({"input_ids": torch.zeros((1, 1), dtype = torch.long)})
+
+        def decode(self, ids, **_kwargs):
+            return "".join(self.pieces.get(int(token_id), "") for token_id in ids)
+
+    class Model:
+        device = "cpu"
+        generation_config = type("Cfg", (), {"eos_token_id": 1})()
+        config = generation_config
+
+        def __init__(self, fail = False):
+            self.fail = fail
+            self.kwargs = None
+
+        def generate(self, **kwargs):
+            self.kwargs = kwargs
+            streamer = kwargs["streamer"]
+            streamer.put(torch.zeros((1, 1), dtype = torch.long))
+            for token_id in [10, 11, 12, 13]:
+                streamer.put(torch.tensor([token_id]))
+                if self.fail:
+                    raise RuntimeError("boom")
+
+    backend = inf.InferenceBackend.__new__(inf.InferenceBackend)
+    backend.active_model_name = "gemma-test"
+    backend._generation_lock = threading.Lock()
+    backend.models = {"gemma-test": {"model": Model(), "tokenizer": Tok()}}
+
+    assert list(backend.generate_stream("prompt", max_new_tokens = 4))[-1] == "<think>r</think>a"
+
+    backend.models["gemma-test"]["model"] = Model(fail = True)
+
+    with pytest.raises(inf._GenerationThreadError, match = "boom"):
+        list(backend.generate_stream("prompt", max_new_tokens = 4))
+
+
+def test_text_only_vlm_fallback_resolves_native_markers_off():
+    import threading
+    import pytest
+
+    torch = pytest.importorskip("torch")
+    inf = pytest.importorskip("core.inference.inference")
+
+    class Batch(dict):
+        def to(self, _device):
+            return self
+
+    class Tokenizer:
+        all_special_tokens = []
+        eos_token_id = 1
+        pad_token_id = None
+
+        def __call__(self, *_args, **_kwargs):
+            return Batch({"input_ids": torch.zeros((1, 1), dtype = torch.long)})
+
+    class Processor:
+        chat_template = "<|channel>thought\n...<channel|>"
+        tokenizer = Tokenizer()
+
+    class Model:
+        device = "cpu"
+        generation_config = type("Cfg", (), {"eos_token_id": 1})()
+        config = generation_config
+
+        def generate(self, **_kwargs):
+            return None
+
+    class EmptyStreamer:
+        def __next__(self):
+            raise StopIteration
+
+        def end(self):
+            return None
+
+    captured = {}
+    backend = inf.InferenceBackend.__new__(inf.InferenceBackend)
+    backend.active_model_name = "vision-test"
+    backend._generation_lock = threading.Lock()
+    backend.models = {
+        "vision-test": {
+            "model": Model(),
+            "processor": Processor(),
+            "tokenizer": Processor(),
+        }
+    }
+    backend.format_chat_prompt = lambda *_args, **_kwargs: "manual text-only prompt"
+
+    def make_streamer(*_args, **kwargs):
+        captured.update(kwargs)
+        return EmptyStreamer()
+
+    backend._make_text_streamer = make_streamer
+
+    assert (
+        list(
+            backend._generate_vision_response(
+                messages = [{"role": "user", "content": "hello"}],
+                system_prompt = "",
+                image = None,
+                temperature = 0.7,
+                top_p = 0.9,
+                top_k = 40,
+                min_p = 0.0,
+                max_new_tokens = 1,
+                repetition_penalty = 1.0,
+            )
+        )
+        == []
+    )
+    assert captured["reasoning_channel_markers"] is None
+    assert captured["reasoning_channel_markers_resolved"] is True
diff --git a/studio/backend/tests/test_sf_client_tools_passthrough.py b/studio/backend/tests/test_sf_client_tools_passthrough.py
index 01905b712c..f91eec9817 100644
--- a/studio/backend/tests/test_sf_client_tools_passthrough.py
+++ b/studio/backend/tests/test_sf_client_tools_passthrough.py
@@ -177,6 +177,15 @@ def _sse_objects(chunks):
 # ── Non-streaming ─────────────────────────────────────────────────
 
 
+def test_non_reasoning_backend_keeps_literal_think_tags(monkeypatch):
+    backend = _ScriptedBackend(_fixed("show <think>example</think> tags"))
+    response = _call(_request(stream = False), monkeypatch, backend, supports_tools = False)
+
+    message = _json_body(response)["choices"][0]["message"]
+    assert message["content"] == "show <think>example</think> tags"
+    assert message["reasoning_content"] is None
+
+
 def test_xml_healed_to_tool_calls_non_streaming(monkeypatch):
     backend = _ScriptedBackend(_fixed(_CALL_XML))
     payload = _request(tools = [LOOKUP_TOOL], stream = False)
@@ -485,6 +494,52 @@ def test_streaming_no_tools_verbatim(monkeypatch):
     assert finishes == ["stop"]
 
 
+def test_streaming_gen_stream_error_is_not_model_text(monkeypatch):
+    from core.inference.orchestrator import GenStreamError
+
+    class _ErrorAfterPartial(_ScriptedBackend):
+        def __init__(self):
+            super().__init__(_fixed())
+
+        def generate_chat_response(self, **_kwargs):
+            yield "<think>partial"
+            yield GenStreamError("Error: /tmp/secret traceback")
+
+    backend = _ErrorAfterPartial()
+    payload = _request(stream = True)
+    response = _call(payload, monkeypatch, backend, supports_tools = False)
+    chunks = _collect_sse(response)
+    objs = _sse_objects(chunks)
+
+    deltas = [o.get("choices", [{}])[0].get("delta", {}) for o in objs if o.get("choices")]
+    assert any("partial" in json.dumps(delta) for delta in deltas)
+    assert not any("/tmp/secret" in json.dumps(delta) for delta in deltas)
+    errors = [o["error"]["message"] for o in objs if "error" in o]
+    assert errors == ["An internal error occurred."]
+    assert any(
+        "data: [DONE]" in (chunk.decode() if isinstance(chunk, bytes) else chunk)
+        for chunk in chunks
+    )
+
+
+def test_server_tool_streaming_invalid_event_is_error(monkeypatch):
+    class _InvalidEventBackend(_ScriptedBackend):
+        def __init__(self):
+            super().__init__(_fixed())
+
+        def generate_chat_completion_with_tools(self, **_kwargs):
+            yield {"type": "content", "text": "partial"}
+            yield "not-an-event"
+
+    backend = _InvalidEventBackend()
+    payload = _request(tools = [LOOKUP_TOOL], enable_tools = True, stream = True)
+    response = _call(payload, monkeypatch, backend)
+    objs = _sse_objects(_collect_sse(response))
+
+    errors = [o["error"]["message"] for o in objs if "error" in o]
+    assert errors == ["An internal error occurred."]
+
+
 def test_streaming_repeated_snapshot_no_duplicate_call(monkeypatch):
     # Repeated then shrunk cumulative snapshots must not double-heal.
     backend = _ScriptedBackend(_fixed(_CALL_XML, _CALL_XML, _CALL_XML[:5], _CALL_XML))
diff --git a/studio/backend/tests/test_think_prefill_reemit.py b/studio/backend/tests/test_think_prefill_reemit.py
index 300ff92776..346399c3b2 100644
--- a/studio/backend/tests/test_think_prefill_reemit.py
+++ b/studio/backend/tests/test_think_prefill_reemit.py
@@ -2,7 +2,7 @@
 # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
 
 """
-Unit tests for detect_think_prefill.
+Unit tests for local reasoning-stream helpers.
 
 Reasoning templates (Qwen3.6-style) end the generation prompt with an open
 ``<think>\\n`` so the model starts reasoning immediately. skip_prompt
@@ -16,7 +16,13 @@ import sys
 _backend = os.path.join(os.path.dirname(__file__), "..")
 sys.path.insert(0, _backend)
 
-from core.inference.chat_template_helpers import detect_think_prefill
+from core.inference.chat_template_helpers import (
+    ReasoningChannelNormalizer,
+    detect_reasoning_channel_markers,
+    detect_reasoning_channel_markers_from_model_info,
+    detect_think_prefill,
+    render_with_native_template_fallback,
+)
 
 
 QWEN_PROMPT = "<|im_start|>user\nHi!<|im_end|>\n<|im_start|>assistant\n"
@@ -87,3 +93,170 @@ def test_guard_emits_when_think_not_special():
 def test_guard_default_and_empty_keep_emitting():
     assert detect_think_prefill(QWEN_PROMPT + "<think>\n", None) == "<think>\n"
     assert detect_think_prefill(QWEN_PROMPT + "<think>\n", []) == "<think>\n"
+
+
+def test_gemma_channel_detection_uses_active_template_not_token_metadata():
+    class TemplateTokenizer:
+        chat_template = {"default": "...<|channel>thought\\n{{ eoc_token }}"}
+
+    class NamedTemplateTokenizer:
+        chat_template = {
+            "default": "plain assistant template",
+            "tool_use": "...<|channel>thought\\n{{ eoc_token }}",
+        }
+
+    class TokenMetadataOnly:
+        chat_template = None
+        soc_token = "<|channel>"
+        eoc_token = "<channel|>"
+
+    class NamedTemplateProcessor:
+        chat_template = {
+            "default": "plain processor default",
+            "tool_use": "<|channel>thought\nprocessor tool template<channel|>",
+        }
+        tokenizer = TokenMetadataOnly()
+
+        def apply_chat_template(self, *_args, **_kwargs):
+            raise NotImplementedError
+
+    expected = ("<|channel>thought", "<channel|>")
+    assert detect_reasoning_channel_markers(TemplateTokenizer()) == expected
+    assert detect_reasoning_channel_markers(NamedTemplateTokenizer()) is None
+    assert (
+        detect_reasoning_channel_markers(
+            NamedTemplateTokenizer(), tools = [{"function": {"name": "web_search"}}]
+        )
+        == expected
+    )
+    assert detect_reasoning_channel_markers(NamedTemplateTokenizer(), tools = []) is None
+    assert (
+        detect_reasoning_channel_markers(
+            NamedTemplateProcessor(), tools = [{"function": {"name": "web_search"}}]
+        )
+        is None
+    )
+    assert detect_reasoning_channel_markers(TokenMetadataOnly()) is None
+
+
+def test_gemma_channel_detection_tries_no_argument_getter_fallback():
+    class FallbackTokenizer:
+        chat_template = "plain fallback template"
+
+        def get_chat_template(self, **kwargs):
+            if kwargs:
+                raise ValueError("tools are not supported")
+            return "...<|channel>thought\n<channel|>"
+
+    assert detect_reasoning_channel_markers(
+        FallbackTokenizer(), tools = [{"function": {"name": "web_search"}}]
+    ) == ("<|channel>thought", "<channel|>")
+
+
+def test_native_template_fallback_returns_selected_reasoning_metadata():
+    from types import SimpleNamespace
+
+    messages = [{"role": "user", "content": "hi"}]
+    tools = [{"type": "function", "function": {"name": "web_search"}}]
+
+    def render(tokenizer, msgs, *, tools, **_kw):
+        body = "".join(message["content"] for message in msgs)
+        suffix = "|TOOLS" if tools else ""
+        return body + suffix if tokenizer.chat_template == "NATIVE <|channel>thought\n" else body
+
+    result = render_with_native_template_fallback(
+        formatted_prompt = "hi",
+        tokenizer = SimpleNamespace(chat_template = "OVERRIDE"),
+        model_info = {
+            "native_chat_template": "NATIVE <|channel>thought\n",
+            "tokenizer": SimpleNamespace(chat_template = "OVERRIDE"),
+        },
+        active_model_name = "gemma-test",
+        messages = messages,
+        tools = tools,
+        apply_fn = render,
+        return_metadata = True,
+    )
+
+    assert result.prompt == "hi|TOOLS"
+    assert result.reasoning_channel_markers == ("<|channel>thought", "<channel|>")
+
+
+def test_cached_native_template_metadata_recovers_reasoning_markers_without_tools():
+    from types import SimpleNamespace
+
+    model_info = {"chat_template_info": {"template": "native <|channel>thought\n<channel|>"}}
+
+    assert detect_reasoning_channel_markers_from_model_info(
+        SimpleNamespace(chat_template = "override has no native markers"),
+        model_info,
+        tools = None,
+    ) == ("<|channel>thought", "<channel|>")
+    result = render_with_native_template_fallback(
+        formatted_prompt = "prompt from override",
+        tokenizer = SimpleNamespace(chat_template = "override has no native markers"),
+        model_info = model_info,
+        active_model_name = "gemma-test",
+        messages = [{"role": "user", "content": "hi"}],
+        tools = None,
+        return_metadata = True,
+    )
+    assert result.prompt == "prompt from override"
+    assert result.reasoning_channel_markers == ("<|channel>thought", "<channel|>")
+
+
+def test_cached_native_markers_do_not_describe_live_tool_template():
+    from types import SimpleNamespace
+
+    tools = [{"type": "function", "function": {"name": "web_search"}}]
+
+    class LiveTokenizer:
+        chat_template = "live tool template without native markers"
+
+    def render(_tokenizer, _messages, *, tools, **_kwargs):
+        return "prompt with tools" if tools else "prompt without tools"
+
+    result = render_with_native_template_fallback(
+        formatted_prompt = "prompt with tools",
+        tokenizer = LiveTokenizer(),
+        model_info = {
+            "chat_template_info": {"template": "native <|channel>thought\n<channel|>"},
+            "tokenizer": SimpleNamespace(),
+        },
+        active_model_name = "gemma-test",
+        messages = [{"role": "user", "content": "hi"}],
+        tools = tools,
+        apply_fn = render,
+        return_metadata = True,
+    )
+
+    assert result.prompt == "prompt with tools"
+    assert result.reasoning_channel_markers is None
+
+
+def test_gemma_channel_normalization_is_prefix_monotonic_and_preserves_tools():
+    parser = ReasoningChannelNormalizer("<|channel>thought", "<channel|>")
+    output = ""
+    snapshots = []
+    for chunk in (
+        "<|chan",
+        "nel>thought",
+        "\nReason",
+        "<chan",
+        "nel|><|tool_call>web_search<tool_call|>",
+    ):
+        delta = parser.feed(chunk)
+        if delta:
+            output += delta
+            snapshots.append(output)
+
+    assert snapshots == [
+        "<think>",
+        "<think>Reason",
+        "<think>Reason</think><|tool_call>web_search<tool_call|>",
+    ]
+    assert snapshots[1].startswith(snapshots[0])
+    compact = ReasoningChannelNormalizer("<|channel>thought", "<channel|>")
+    assert compact.feed("<|channel>thought<channel|>answer") + compact.finish() == (
+        "<think></think>answer"
+    )

From 8ff2f8e70c4872ed83d2dde0a3db40ad6dcb24f8 Mon Sep 17 00:00:00 2001
From: Long Yixing <longyixing331@gmail.com>
Date: Sat, 18 Jul 2026 07:22:11 +0800
Subject: [PATCH 15/28] fix(studio): ignore reasoning in tool reprompts (#7134)

---
 studio/backend/core/inference/inference.py    |   2 +
 studio/backend/core/inference/orchestrator.py |   2 +
 .../core/inference/safetensors_agentic.py     |  52 ++++-
 studio/backend/routes/inference.py            |   1 +
 .../tests/test_safetensors_tool_loop.py       | 190 ++++++++++++++++++
 5 files changed, 243 insertions(+), 4 deletions(-)

diff --git a/studio/backend/core/inference/inference.py b/studio/backend/core/inference/inference.py
index eae705d20e..8d262bbb0f 100644
--- a/studio/backend/core/inference/inference.py
+++ b/studio/backend/core/inference/inference.py
@@ -888,6 +888,7 @@ class InferenceBackend:
         thread_id: Optional[str] = None,
         rag_scope: Optional[dict] = None,
         presence_penalty: float = 0.0,
+        reasoning_prefilled: bool = False,
     ):
         """Run an agentic tool loop on top of ``generate_chat_response``.
 
@@ -941,6 +942,7 @@ class InferenceBackend:
             session_id = session_id,
             thread_id = thread_id,
             rag_scope = rag_scope,
+            reasoning_prefilled = reasoning_prefilled,
         )
 
     def generate_chat_response(
diff --git a/studio/backend/core/inference/orchestrator.py b/studio/backend/core/inference/orchestrator.py
index ea3b164052..3afda74411 100644
--- a/studio/backend/core/inference/orchestrator.py
+++ b/studio/backend/core/inference/orchestrator.py
@@ -1407,6 +1407,7 @@ class InferenceOrchestrator:
         use_adapter: Optional[Union[bool, str]] = None,
         stats_holder: Optional[dict] = None,
         presence_penalty: float = 0.0,
+        reasoning_prefilled: bool = False,
         **_unused,
     ):
         """Run the safetensors agentic tool loop in the parent process,
@@ -1487,6 +1488,7 @@ class InferenceOrchestrator:
             confirm_tool_calls = confirm_tool_calls,
             bypass_permissions = bypass_permissions,
             permission_mode = permission_mode,
+            reasoning_prefilled = reasoning_prefilled,
         )
 
     def generate_with_adapter_control(
diff --git a/studio/backend/core/inference/safetensors_agentic.py b/studio/backend/core/inference/safetensors_agentic.py
index 43b72110ff..9110315815 100644
--- a/studio/backend/core/inference/safetensors_agentic.py
+++ b/studio/backend/core/inference/safetensors_agentic.py
@@ -50,6 +50,7 @@ from core.inference.tool_call_parser import (
 # pattern lists, so the safetensors streaming strip stays aligned with the parser.
 from core.tool_healing import (
     _REHEARSAL_TAIL_STRIP_RE,
+    _THINK_CLOSE_RE,
     _strip_bracket_tag_calls,
     _think_spans_outside_tool_markup,
     apply_tool_strip_patterns,
@@ -304,6 +305,45 @@ def _status_for_tool(tool_name: str, arguments: dict) -> str:
     return status_for_tool(tool_name, arguments)
 
 
+def _reprompt_intent_text(text: str, *, reasoning_prefilled: bool = False) -> str:
+    """Return visible answer text for the plan-without-action classifier.
+
+    Safetensors reasoning shares the cumulative text channel with the answer.
+    Forward-looking phrases inside ``<think>`` / ``[THINK]`` are private
+    planning, not a user-visible promise to call a tool. Match GGUF's behavior:
+    classify visible content when present and fall back to reasoning only for a
+    reasoning-only stall.
+    """
+    prefilled_reasoning = ""
+    if reasoning_prefilled:
+        close = _THINK_CLOSE_RE.search(text)
+        if close is None:
+            return text.strip()
+        prefilled_reasoning = text[: close.end()].strip()
+        text = text[close.end() :].strip()
+        if not text:
+            return prefilled_reasoning
+
+    spans = _think_spans_outside_tool_markup(text)
+    if not spans:
+        return text.strip()
+
+    visible: list[str] = []
+    reasoning: list[str] = []
+    cursor = 0
+    for start, end in spans:
+        visible.append(text[cursor:start])
+        reasoning.append(text[start:end])
+        cursor = end
+    visible.append(text[cursor:])
+
+    visible_text = "".join(visible).strip()
+    reasoning_text = "".join(reasoning).strip()
+    if visible_text:
+        return visible_text
+    return "\n".join(part for part in (prefilled_reasoning, reasoning_text) if part).strip()
+
+
 def _looks_like_enabled_bare_json(text: str, enabled_tool_names: Optional[set]) -> bool:
     """True when ``text`` opens with an ENABLED markerless bare-JSON call; an ordinary JSON answer returns False."""
     probe = strip_llama3_leading_sentinels(text.lstrip())
@@ -448,6 +488,7 @@ def run_safetensors_tool_loop(
     confirm_tool_calls: bool = False,
     bypass_permissions: bool = False,
     permission_mode: Optional[str] = None,
+    reasoning_prefilled: bool = False,
 ) -> Generator[dict, None, None]:
     """Drive an agentic tool loop on top of a cumulative-text generator.
 
@@ -956,7 +997,10 @@ def run_safetensors_tool_loop(
                 # (GGUF loop parity). The retry is gated on nudge_tool_calls so
                 # Studio callers (which send True) always nudge, while API callers
                 # who omit the flag keep today's no-reprompt behavior (opt-in).
-                stripped_answer = content_accum.strip()
+                intent_text = _reprompt_intent_text(
+                    content_accum,
+                    reasoning_prefilled = reasoning_prefilled,
+                )
                 if (
                     auto_heal_tool_calls
                     and nudge_tool_calls
@@ -965,7 +1009,7 @@ def run_safetensors_tool_loop(
                     and not rag_autoinjected
                     and not tool_denied
                     and not any(record.executed for record in tool_controller.history)
-                    and is_short_intent_without_action(stripped_answer)
+                    and is_short_intent_without_action(intent_text)
                 ):
                     reprompt_count += 1
                     logger.info(
@@ -973,9 +1017,9 @@ def run_safetensors_tool_loop(
                         "calling tools (%d chars)",
                         reprompt_count,
                         MAX_ACT_REPROMPTS,
-                        len(stripped_answer),
+                        len(intent_text),
                     )
-                    conversation.append({"role": "assistant", "content": stripped_answer})
+                    conversation.append({"role": "assistant", "content": intent_text})
                     tool_hint = " or ".join(_active_tool_names(active_tools)) or "an available tool"
                     conversation.append(
                         {
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index d6090e2b62..52ea1f86a3 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -8886,6 +8886,7 @@ async def openai_chat_completions(
                 permission_mode = payload.permission_mode,
                 use_adapter = payload.use_adapter,
                 stats_holder = _sf_stats_holder,
+                reasoning_prefilled = _sf_reasoning_prefilled,
             )
 
         _sf_tool_sentinel = object()
diff --git a/studio/backend/tests/test_safetensors_tool_loop.py b/studio/backend/tests/test_safetensors_tool_loop.py
index e3633de289..915f82ac8e 100644
--- a/studio/backend/tests/test_safetensors_tool_loop.py
+++ b/studio/backend/tests/test_safetensors_tool_loop.py
@@ -3205,6 +3205,196 @@ class TestLoopBehaviour:
 class TestLoopRePrompt:
     """Plan-without-action re-prompt parity with GGUF: nudge instead of terminating, up to ``MAX_ACT_REPROMPTS`` extra slots. Studio always nudges, so these drive the loop with ``nudge_tool_calls=True``."""
 
+    def test_reasoning_intent_does_not_reprompt_a_visible_answer(self):
+        generations = 0
+
+        def _gen(_messages, active_tools = None):
+            nonlocal generations
+            generations += 1
+            yield (
+                "<think>Let me prepare the requested summary carefully.</think>"
+                "This is the final visible answer."
+            )
+
+        exec_fn = FakeExecuteTool([])
+        events = _collect_events(
+            run_safetensors_tool_loop(
+                single_turn = _gen,
+                messages = [{"role": "user", "content": "summarize this"}],
+                tools = [{"type": "function", "function": {"name": "web_search"}}],
+                execute_tool = exec_fn,
+                nudge_tool_calls = True,
+            )
+        )
+
+        assert generations == 1
+        assert exec_fn.calls == []
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1].endswith("This is the final visible answer.")
+
+    def test_prefilled_reasoning_intent_does_not_reprompt_a_visible_answer(self):
+        generations = 0
+
+        def _gen(_messages, active_tools = None):
+            nonlocal generations
+            generations += 1
+            yield "Let me prepare the requested summary carefully.</think>This is the final visible answer."
+
+        exec_fn = FakeExecuteTool([])
+        events = _collect_events(
+            run_safetensors_tool_loop(
+                single_turn = _gen,
+                messages = [{"role": "user", "content": "summarize this"}],
+                tools = [{"type": "function", "function": {"name": "web_search"}}],
+                execute_tool = exec_fn,
+                nudge_tool_calls = True,
+                reasoning_prefilled = True,
+            )
+        )
+
+        assert generations == 1
+        assert exec_fn.calls == []
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1].endswith("This is the final visible answer.")
+
+    def test_prefilled_reasoning_with_reemitted_think_does_not_reprompt(self):
+        generations = 0
+
+        def _gen(_messages, active_tools = None):
+            nonlocal generations
+            generations += 1
+            yield (
+                "Let me prepare the requested summary carefully."
+                "<think>more private planning</think>This is the final visible answer."
+            )
+
+        exec_fn = FakeExecuteTool([])
+        events = _collect_events(
+            run_safetensors_tool_loop(
+                single_turn = _gen,
+                messages = [{"role": "user", "content": "summarize this"}],
+                tools = [{"type": "function", "function": {"name": "web_search"}}],
+                execute_tool = exec_fn,
+                nudge_tool_calls = True,
+                reasoning_prefilled = True,
+            )
+        )
+
+        assert generations == 1
+        assert exec_fn.calls == []
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1].endswith("This is the final visible answer.")
+
+    def test_prefilled_reasoning_with_later_think_does_not_reprompt(self):
+        generations = 0
+
+        def _gen(_messages, active_tools = None):
+            nonlocal generations
+            generations += 1
+            yield (
+                "private prefilled planning</think>"
+                "<think>Let me prepare the requested summary carefully.</think>"
+                "This is the final visible answer."
+            )
+
+        exec_fn = FakeExecuteTool([])
+        events = _collect_events(
+            run_safetensors_tool_loop(
+                single_turn = _gen,
+                messages = [{"role": "user", "content": "summarize this"}],
+                tools = [{"type": "function", "function": {"name": "web_search"}}],
+                execute_tool = exec_fn,
+                nudge_tool_calls = True,
+                reasoning_prefilled = True,
+            )
+        )
+
+        assert generations == 1
+        assert exec_fn.calls == []
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1].endswith("This is the final visible answer.")
+
+    def test_reasoning_only_intent_still_reprompts_and_uses_a_tool(self):
+        loop, exec_fn = _make_loop(
+            turns = [
+                ["<think>Let me search for that.</think>"],
+                ['<tool_call>{"name":"web_search","arguments":{"query":"cats"}}</tool_call>'],
+                ["Here is the answer."],
+            ],
+            exec_results = ["result"],
+            nudge_tool_calls = True,
+        )
+
+        events = _collect_events(loop)
+
+        assert exec_fn.calls == [("web_search", {"query": "cats"})]
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1] == "Here is the answer."
+
+    def test_prefilled_no_close_reasoning_intent_still_reprompts(self):
+        loop, exec_fn = _make_loop(
+            turns = [
+                ["I need more context.<think>Let me search for that."],
+                ['<tool_call>{"name":"web_search","arguments":{"query":"cats"}}</tool_call>'],
+                ["Here is the answer."],
+            ],
+            exec_results = ["result"],
+            nudge_tool_calls = True,
+            reasoning_prefilled = True,
+        )
+
+        events = _collect_events(loop)
+
+        assert exec_fn.calls == [("web_search", {"query": "cats"})]
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1] == "Here is the answer."
+
+    def test_prefilled_reasoning_prefix_is_kept_for_reasoning_only_reprompt(self):
+        loop, exec_fn = _make_loop(
+            turns = [
+                ["Let me search for that.</think><think>checking details</think>"],
+                ['<tool_call>{"name":"web_search","arguments":{"query":"cats"}}</tool_call>'],
+                ["Here is the answer."],
+            ],
+            exec_results = ["result"],
+            nudge_tool_calls = True,
+            reasoning_prefilled = True,
+        )
+
+        events = _collect_events(loop)
+
+        assert exec_fn.calls == [("web_search", {"query": "cats"})]
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1] == "Here is the answer."
+
+    def test_reprompt_history_uses_visible_intent_text(self):
+        captured: list[list[dict]] = []
+
+        def _gen(messages, active_tools = None):
+            captured.append([dict(message) for message in messages])
+            if len(captured) == 1:
+                yield "<think>private planning details</think>Let me search for that."
+            elif len(captured) == 2:
+                yield '<tool_call>{"name":"web_search","arguments":{"query":"cats"}}</tool_call>'
+            else:
+                yield "Here is the answer."
+
+        exec_fn = FakeExecuteTool(["result"])
+        events = _collect_events(
+            run_safetensors_tool_loop(
+                single_turn = _gen,
+                messages = [{"role": "user", "content": "find cats"}],
+                tools = [{"type": "function", "function": {"name": "web_search"}}],
+                execute_tool = exec_fn,
+                nudge_tool_calls = True,
+            )
+        )
+
+        assert exec_fn.calls == [("web_search", {"query": "cats"})]
+        assert captured[1][1] == {"role": "assistant", "content": "Let me search for that."}
+        contents = [e["text"] for e in events if e["type"] == "content"]
+        assert contents[-1] == "Here is the answer."
+
     def test_intent_signal_triggers_reprompt(self):
         # Turn 1: intent signal, no tool call.
         # Turn 2 (re-prompt): proper tool call -> executes.

From bf4185a2d3fa3d1c57bcfdb43ebc25912316e568 Mon Sep 17 00:00:00 2001
From: Nilay <118994073+NilayYadav@users.noreply.github.com>
Date: Sat, 18 Jul 2026 04:57:28 +0530
Subject: [PATCH 16/28] Studio: don't apply nest_asyncio on plain CLI starts
 (breaks asyncio on Python 3.14+) (#7186)

* Studio: don't apply nest_asyncio on plain CLI starts (breaks asyncio on Python 3.14+)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Skip nest_asyncio on Python 3.14+ so notebook and embedded Studio starts also work

* Tighten the nest_asyncio gate comment

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
---
 studio/backend/run.py | 20 ++++++++++++++++----
 1 file changed, 16 insertions(+), 4 deletions(-)

diff --git a/studio/backend/run.py b/studio/backend/run.py
index 56b9c78343..4f105b53b1 100644
--- a/studio/backend/run.py
+++ b/studio/backend/run.py
@@ -1354,11 +1354,23 @@ def run_server(
     if secure:
         os.environ["UNSLOTH_SECURE"] = "1"
 
-    import nest_asyncio
-
-    nest_asyncio.apply()
-
     import asyncio
+
+    # nest_asyncio is for Colab/IPython, where the main thread already runs a loop
+    # the blocking waits below would collide with. Apply it only with a loop running
+    # (a plain CLI start has nothing to nest) and only on Python <= 3.13: on 3.14+
+    # its global Task patch leaves asyncio.current_task() None (tracking moved into
+    # C), which also breaks the background uvicorn loop and 500s every request. It
+    # is archived upstream, so no 3.14 fix is coming; skip it there.
+    if sys.version_info < (3, 14):
+        try:
+            asyncio.get_running_loop()
+        except RuntimeError:
+            pass
+        else:
+            import nest_asyncio
+            nest_asyncio.apply()
+
     from threading import Thread, Event
     import uvicorn
 

From a14b032d79ddd8f10bd874e741d3909945d1163f Mon Sep 17 00:00:00 2001
From: Vineeth Sai <vineethsai4444@gmail.com>
Date: Fri, 17 Jul 2026 16:30:45 -0700
Subject: [PATCH 17/28] Propagate fp8 block_size before the early return in
 get_lora_parameters_bias (#7189)

* Propagate fp8 block_size before the early return in get_lora_parameters_bias

get_lora_parameters_bias set the fp8 block_size on W/W_quant only after the
disable_adapters/merged early return, so on the merged or disabled path (merged
inference, DPO reference model) a block-fp8 weight lost its real block_size and
downstream fp8 kernels fell back to [128, 128]. The non-bias sibling
get_lora_parameters already sets block_size before its early return; move the
block so both behave the same.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Guard the fp8 block_size against a missing quant state

A decompressed compressed-tensors layer keeps quant_method == "fp8" while its
weight is back to bf16, so it has no quant state and get_lora_parameters_bias
must still return W_quant None for fast_linear_forward to fall back to a plain
matmul. Only attach block_size when a quant state was actually found.

* Guard the sibling get_lora_parameters fp8 block_size against a missing quant state

Mirror the get_lora_parameters_bias guard so a decompressed compressed-tensors
layer (quant_method fp8, bf16 weight, no quant state) does not raise
AttributeError on the fused-LoRA path. Add a CPU-only regression test.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
---
 ...get_lora_parameters_bias_fp8_block_size.py | 82 +++++++++++++++++++
 ...test_get_lora_parameters_fp8_block_size.py | 81 ++++++++++++++++++
 unsloth/kernels/utils.py                      | 18 ++--
 3 files changed, 175 insertions(+), 6 deletions(-)
 create mode 100644 tests/python/test_get_lora_parameters_bias_fp8_block_size.py
 create mode 100644 tests/python/test_get_lora_parameters_fp8_block_size.py

diff --git a/tests/python/test_get_lora_parameters_bias_fp8_block_size.py b/tests/python/test_get_lora_parameters_bias_fp8_block_size.py
new file mode 100644
index 0000000000..835ad19542
--- /dev/null
+++ b/tests/python/test_get_lora_parameters_bias_fp8_block_size.py
@@ -0,0 +1,82 @@
+import ast
+from pathlib import Path
+
+
+def _load_function(name):
+    # Extract a function from kernels/utils.py without importing unsloth (which
+    # needs a GPU / torch / bitsandbytes). The functions exercised here only use
+    # getattr and the _FP8_WEIGHT_DTYPES name on the paths under test.
+    source = Path(__file__).parents[2] / "unsloth" / "kernels" / "utils.py"
+    tree = ast.parse(source.read_text(encoding = "utf-8"))
+    funcs = [
+        node for node in ast.walk(tree) if isinstance(node, ast.FunctionDef) and node.name == name
+    ]
+    assert len(funcs) == 1, (name, funcs)
+    namespace = {"getattr": getattr, "_FP8_WEIGHT_DTYPES": ()}
+    module = ast.Module(body = funcs, type_ignores = [])
+    ast.fix_missing_locations(module)
+    exec(compile(module, str(source), "exec"), namespace)
+    return namespace[name]
+
+
+class _Obj:
+    pass
+
+
+def _make_disabled_block_fp8_proj(block_size):
+    # A merged/disabled projection whose base layer is a block-fp8 weight that
+    # ships a non-default block size on its checkpoint.
+    weight = _Obj()
+    weight.quant_state = _Obj()
+    base_layer = _Obj()
+    base_layer.weight = weight
+    base_layer.quant_method = "fp8"
+    base_layer.block_size = block_size
+    base_layer.bias = None
+    proj = _Obj()
+    proj.base_layer = base_layer
+    proj.merged = True
+    proj.disable_adapters = True
+    return proj, weight.quant_state
+
+
+def test_bias_variant_propagates_fp8_block_size_on_disabled_path():
+    # Downstream fp8 kernels read getattr(weight_scale, "block_size", [128, 128]),
+    # so the checkpoint's real block size must survive the merged/disabled path,
+    # exactly as it does for the non-bias sibling get_lora_parameters.
+    get_lora_parameters_bias = _load_function("get_lora_parameters_bias")
+
+    proj, weight_scale = _make_disabled_block_fp8_proj([64, 128])
+    get_lora_parameters_bias(proj)
+
+    assert getattr(weight_scale, "block_size", [128, 128]) == [64, 128]
+
+
+def _make_decompressed_merged_proj():
+    # A merged compressed-tensors layer that was decompressed back to bf16. It keeps
+    # quant_method == "fp8" from the checkpoint metadata, but the live weight is bf16
+    # so there is no quant state to attach a block size to.
+    weight = _Obj()
+    weight.dtype = "bfloat16"
+    base_layer = _Obj()
+    base_layer.weight = weight
+    base_layer.quant_method = "fp8"
+    base_layer.block_size = [128, 128]
+    base_layer.bias = None
+    proj = _Obj()
+    proj.base_layer = base_layer
+    proj.merged = True
+    proj.disable_adapters = True
+    return proj
+
+
+def test_bias_variant_keeps_none_quant_state_for_decompressed_layer():
+    # Such a layer has no quant state, and fast_linear_forward relies on getting
+    # W_quant None back so it can fall back to a plain matmul, so setting the block
+    # size must not assume a quant state is present.
+    get_lora_parameters_bias = _load_function("get_lora_parameters_bias")
+
+    W, W_quant = get_lora_parameters_bias(_make_decompressed_merged_proj())[:2]
+
+    assert W_quant is None
+    assert getattr(W, "block_size", None) == [128, 128]
diff --git a/tests/python/test_get_lora_parameters_fp8_block_size.py b/tests/python/test_get_lora_parameters_fp8_block_size.py
new file mode 100644
index 0000000000..f5f1359125
--- /dev/null
+++ b/tests/python/test_get_lora_parameters_fp8_block_size.py
@@ -0,0 +1,81 @@
+import ast
+from pathlib import Path
+
+
+def _load_function(name):
+    # Extract a function from kernels/utils.py without importing unsloth (which
+    # needs a GPU / torch / bitsandbytes). get_lora_parameters only uses getattr,
+    # hasattr and the _FP8_WEIGHT_DTYPES name on the paths under test.
+    source = Path(__file__).parents[2] / "unsloth" / "kernels" / "utils.py"
+    tree = ast.parse(source.read_text(encoding = "utf-8"))
+    funcs = [
+        node for node in ast.walk(tree) if isinstance(node, ast.FunctionDef) and node.name == name
+    ]
+    assert len(funcs) == 1, (name, funcs)
+    namespace = {"getattr": getattr, "hasattr": hasattr, "_FP8_WEIGHT_DTYPES": ()}
+    module = ast.Module(body = funcs, type_ignores = [])
+    ast.fix_missing_locations(module)
+    exec(compile(module, str(source), "exec"), namespace)
+    return namespace[name]
+
+
+class _Obj:
+    pass
+
+
+def _make_disabled_block_fp8_proj(block_size):
+    # A merged/disabled projection whose base layer is a block-fp8 weight that
+    # ships a non-default block size on its checkpoint.
+    weight = _Obj()
+    weight.quant_state = _Obj()
+    base_layer = _Obj()
+    base_layer.weight = weight
+    base_layer.quant_method = "fp8"
+    base_layer.block_size = block_size
+    proj = _Obj()
+    proj.base_layer = base_layer
+    proj.merged = True
+    proj.disable_adapters = True
+    return proj, weight.quant_state
+
+
+def test_propagates_fp8_block_size_on_disabled_path():
+    # get_lora_parameters already sets block_size before its early return; downstream
+    # fp8 kernels read getattr(weight_scale, "block_size", [128, 128]), so the
+    # checkpoint's real block size must survive the merged/disabled path.
+    get_lora_parameters = _load_function("get_lora_parameters")
+
+    proj, weight_scale = _make_disabled_block_fp8_proj([64, 128])
+    get_lora_parameters(proj)
+
+    assert getattr(weight_scale, "block_size", [128, 128]) == [64, 128]
+
+
+def _make_decompressed_merged_proj():
+    # A merged compressed-tensors layer that was decompressed back to bf16. It keeps
+    # quant_method == "fp8" from the checkpoint metadata, but the live weight is bf16
+    # so there is no quant state to attach a block size to.
+    weight = _Obj()
+    weight.dtype = "bfloat16"
+    base_layer = _Obj()
+    base_layer.weight = weight
+    base_layer.quant_method = "fp8"
+    base_layer.block_size = [128, 128]
+    proj = _Obj()
+    proj.base_layer = base_layer
+    proj.merged = True
+    proj.disable_adapters = True
+    return proj
+
+
+def test_keeps_none_quant_state_for_decompressed_layer():
+    # Mirrors the get_lora_parameters_bias guard: with no quant state, assigning
+    # W_quant.block_size must not assume one is present, or it raises AttributeError
+    # on None. fast_lora relies on getting W_quant None back to fall back to a plain
+    # matmul, so this path must stay crash-free.
+    get_lora_parameters = _load_function("get_lora_parameters")
+
+    W, W_quant = get_lora_parameters(_make_decompressed_merged_proj())[:2]
+
+    assert W_quant is None
+    assert getattr(W, "block_size", None) == [128, 128]
diff --git a/unsloth/kernels/utils.py b/unsloth/kernels/utils.py
index 1b0b5ce12e..ccfedfdef0 100644
--- a/unsloth/kernels/utils.py
+++ b/unsloth/kernels/utils.py
@@ -325,7 +325,10 @@ def get_lora_parameters(proj):
     if getattr(base_layer, "quant_method", None) == "fp8":
         # we need to somehow store and pass this information :)
         W.block_size = getattr(base_layer, "block_size", [128, 128])
-        W_quant.block_size = W.block_size
+        # A decompressed compressed-tensors layer keeps quant_method == "fp8" while its
+        # weight is back to bf16, so it has no quant state to carry the block size.
+        if W_quant is not None:
+            W_quant.block_size = W.block_size
 
     # if not hasattr(proj, "disable_adapters") or proj.disable_adapters or proj.merged:
     if getattr(proj, "disable_adapters", True) or proj.merged:
@@ -375,14 +378,17 @@ def get_lora_parameters_bias(proj):
         if W_quant is None:
             W_quant = getattr(base_layer, "weight_scale", None)
 
-    # if not hasattr(proj, "disable_adapters") or proj.disable_adapters or proj.merged:
-    if getattr(proj, "disable_adapters", True) or proj.merged:
-        return W, W_quant, None, None, None, base_layer.bias
-
     if getattr(base_layer, "quant_method", None) == "fp8":
         # we need to somehow store and pass this information :)
         W.block_size = getattr(base_layer, "block_size", [128, 128])
-        W_quant.block_size = W.block_size
+        # A decompressed compressed-tensors layer keeps quant_method == "fp8" while its
+        # weight is back to bf16, so it has no quant state to carry the block size.
+        if W_quant is not None:
+            W_quant.block_size = W.block_size
+
+    # if not hasattr(proj, "disable_adapters") or proj.disable_adapters or proj.merged:
+    if getattr(proj, "disable_adapters", True) or proj.merged:
+        return W, W_quant, None, None, None, base_layer.bias
 
     adapter = getattr(proj, "active_adapters", None)
     if adapter is None:

From a8ff8673df640710e58fabfb226df565d9751afe Mon Sep 17 00:00:00 2001
From: Ritwij Aryan Parmar <88580521+RitwijParmar@users.noreply.github.com>
Date: Fri, 17 Jul 2026 19:50:39 -0400
Subject: [PATCH 18/28] feat(studio): expose an opt-in MCP control plane
 (#7191)

* feat(studio): expose opt-in MCP control plane

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Harden Studio MCP tools: byte-safe auth, page clamping, forward export/checkpoint fields

Follow-up hardening on the opt-in MCP control plane. All changes are additive
and backwards compatible.

- BearerTokenMiddleware now compares the Authorization header on raw bytes.
  A non-ASCII bearer value previously reached str-based hmac.compare_digest,
  which raises TypeError and surfaced as a 500 instead of a clean 401. The
  constructor also rejects an empty or whitespace-only token so an empty token
  can never match an empty "Bearer " header.
- MCP tools call the route functions directly, which skips FastAPI Query
  validation. list_training_runs and get_recipe_job_dataset now clamp limit and
  offset to the same bounds the HTTP routes enforce (a negative SQLite LIMIT
  otherwise means "no limit").
- export_gguf forwards hf_token (the backend rejects a Hub upload without it),
  accepts a list of quantization methods, and exposes imatrix / imatrix_path so
  the IQ low-bit quants are reachable.
- load_checkpoint forwards hf_token and approved_remote_code_fingerprint so
  gated checkpoints and the remote-code approval retry work. Its docstring is
  corrected: the export backend coexists with training and inference rather than
  freeing GPU work.
- start_training passes via_api_key=False explicitly instead of relying on the
  unfilled Depends default.

Tests: add coverage for non-ASCII and empty-token auth, the correct-token pass
through, non-http scope pass through, pagination clamping, and the forwarded
export/checkpoint fields.

* Harden Studio MCP: cap /mcp request bodies, reject unusable tokens, fix docs

Follow-up hardening from a full review pass. All changes are additive and
backwards compatible.

- Add "/mcp" to _BODY_PROTECTED_PREFIXES so MaxBodyMiddleware enforces the same
  request-body cap it already applies to every other write endpoint (/api/train,
  /api/export, /api/data-recipe, ...). The MCP endpoint accepts authenticated
  POST tool-call bodies; without this an authenticated client could send an
  unbounded body. The middleware only buffers the request body (not the SSE
  response), so streaming is unaffected, and the 500MB default cap never affects
  a real JSON-RPC tool call (verified live).
- Reject a non-ASCII UNSLOTH_STUDIO_MCP_TOKEN at construction. HTTP header values
  are ASCII, so a non-ASCII token cannot be sent by a standard client and would
  silently lock out the endpoint; fail fast instead.
- MCP.md: document the canonical /mcp/ endpoint and note that /mcp redirects to
  it, so clients that do not follow redirected POSTs still connect.

Tests: add non-ASCII token rejection coverage.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Tighten MCP server comments

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
---
 studio/MCP.md                           |  34 +++
 studio/backend/main.py                  |  17 ++
 studio/backend/mcp_server.py            | 259 +++++++++++++++++++++
 studio/backend/tests/test_mcp_server.py | 290 ++++++++++++++++++++++++
 4 files changed, 600 insertions(+)
 create mode 100644 studio/MCP.md
 create mode 100644 studio/backend/mcp_server.py
 create mode 100644 studio/backend/tests/test_mcp_server.py

diff --git a/studio/MCP.md b/studio/MCP.md
new file mode 100644
index 0000000000..91b39fcc69
--- /dev/null
+++ b/studio/MCP.md
@@ -0,0 +1,34 @@
+# Unsloth Studio MCP server
+
+Studio can expose a local MCP server so an MCP client can inspect models and
+GPU state, validate recipes, start or stop training, inspect recipe output, and
+export a loaded model.
+
+The server is disabled by default. Enable it for a local Studio process with:
+
+```bash
+UNSLOTH_STUDIO_ENABLE_MCP=1 \
+UNSLOTH_STUDIO_MCP_TOKEN='use-a-local-secret' \
+unsloth studio
+```
+
+The endpoint is `http://127.0.0.1:8888/mcp/` when Studio uses its default port
+(a request to `/mcp` redirects to the canonical `/mcp/`). Use the actual Studio
+port when it is configured differently.
+
+The high-impact tools are:
+
+- `studio_status` and `list_local_models` for discovery
+- `get_training_status`, `start_training`, `stop_training`, and `list_training_runs`
+- `validate_recipe`, `get_recipe_job_status`, and `get_recipe_job_dataset`
+- `load_checkpoint` and `export_gguf`
+
+`start_training` accepts the same fields as the Studio `TrainingStartRequest`.
+The request is validated by the existing Pydantic model before a subprocess is
+started. Export paths use the existing Studio validation as well.
+
+The endpoint always requires `UNSLOTH_STUDIO_MCP_TOKEN` and checks an exact
+Bearer token for both HTTP and WebSocket connections. Keep it on localhost
+unless the deployment has an authenticated reverse proxy. The MCP endpoint is
+intentionally opt-in because tools can consume GPU memory, write model
+artifacts, and stop active work.
\ No newline at end of file
diff --git a/studio/backend/main.py b/studio/backend/main.py
index e64048dc00..6e16dc00ca 100644
--- a/studio/backend/main.py
+++ b/studio/backend/main.py
@@ -612,6 +612,22 @@ app = FastAPI(
     lifespan = lifespan,
 )
 
+# The MCP surface is opt-in because it can start GPU jobs and write model
+# artifacts. Mount it only when explicitly enabled by the Studio process.
+if os.environ.get("UNSLOTH_STUDIO_ENABLE_MCP") == "1":
+    from fastmcp.utilities.lifespan import combine_lifespans
+
+    from mcp_server import BearerTokenMiddleware, create_studio_mcp
+
+    _studio_mcp_app = create_studio_mcp().http_app(path = "/")
+    _studio_mcp_lifespan = _studio_mcp_app.lifespan
+    _mcp_token = os.environ.get("UNSLOTH_STUDIO_MCP_TOKEN")
+    if not _mcp_token:
+        raise RuntimeError("UNSLOTH_STUDIO_MCP_TOKEN is required when MCP is enabled")
+    _studio_mcp_app = BearerTokenMiddleware(_studio_mcp_app, _mcp_token)
+    app.router.lifespan_context = combine_lifespans(lifespan, _studio_mcp_lifespan)
+    app.mount("/mcp", _studio_mcp_app)
+
 from loggers.config import LogConfig
 from loggers.handlers import LoggingMiddleware
 
@@ -752,6 +768,7 @@ _BODY_PROTECTED_PREFIXES = (
     "/api/settings",
     "/api/train",
     "/api/export",
+    "/mcp",
 )
 _DATASET_UPLOAD_PASSTHROUGH_PREFIX = "/api/datasets/upload"
 _DATA_RECIPE_UNSTRUCTURED_UPLOAD_PASSTHROUGH_PREFIX = (
diff --git a/studio/backend/mcp_server.py b/studio/backend/mcp_server.py
new file mode 100644
index 0000000000..f837f46425
--- /dev/null
+++ b/studio/backend/mcp_server.py
@@ -0,0 +1,259 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+"""Curated MCP tools for driving an Unsloth Studio instance.
+
+The MCP surface deliberately wraps the existing Studio services instead of
+duplicating training or export logic. It is opt-in because several tools can
+start GPU work or write model artifacts.
+"""
+
+from __future__ import annotations
+
+import hmac
+from typing import Any
+
+from fastmcp import FastMCP
+
+
+class BearerTokenMiddleware:
+    """Require an exact bearer token when Studio MCP is exposed remotely."""
+
+    def __init__(self, app: Any, token: str) -> None:
+        if not token or not token.strip():
+            raise ValueError("Studio MCP bearer token must be a non-empty value")
+        if not token.isascii():
+            # A non-ASCII token cannot be sent in an HTTP header; reject it here.
+            raise ValueError("Studio MCP bearer token must contain ASCII characters only")
+        self.app = app
+        # Compare on raw header bytes: str hmac.compare_digest raises on non-ASCII
+        # input, which would surface as a 500 instead of a clean 401.
+        self.expected = token.encode("utf-8")
+
+    async def __call__(self, scope: dict[str, Any], receive: Any, send: Any) -> None:
+        scope_type = scope.get("type")
+        if scope_type not in ("http", "websocket"):
+            await self.app(scope, receive, send)
+            return
+
+        headers = dict(scope.get("headers", []))
+        raw_auth = headers.get(b"authorization", b"")
+        scheme, _, supplied = raw_auth.partition(b" ")
+        if scheme.lower() != b"bearer" or not hmac.compare_digest(supplied, self.expected):
+            await _send_unauthorized(send, scope_type)
+            return
+
+        await self.app(scope, receive, send)
+
+
+async def _send_unauthorized(send: Any, scope_type: str) -> None:
+    if scope_type == "websocket":
+        await send({"type": "websocket.close", "code": 4401})
+        return
+
+    await send(
+        {
+            "type": "http.response.start",
+            "status": 401,
+            "headers": [(b"content-type", b"application/json"), (b"www-authenticate", b"Bearer")],
+        }
+    )
+    await send(
+        {
+            "type": "http.response.body",
+            "body": b'{"detail":"MCP bearer token required"}',
+        }
+    )
+
+
+def _dump(value: Any) -> Any:
+    """Convert Pydantic responses to plain JSON values for MCP clients."""
+    if hasattr(value, "model_dump"):
+        return value.model_dump(mode = "json")
+    return value
+
+
+def _clamp(value: int, low: int, high: int) -> int:
+    """Clamp an MCP-supplied integer into an inclusive range.
+
+    MCP tools call the Studio route functions directly, which skips FastAPI's
+    Query(ge=, le=) validation, so we re-apply the same bounds here.
+    """
+    return max(low, min(value, high))
+
+
+def create_studio_mcp() -> FastMCP:
+    """Create the Studio MCP server and register the high-value tools."""
+    mcp = FastMCP(
+        "Unsloth Studio",
+        instructions = (
+            "Use read tools to inspect the local Studio state before starting GPU work. "
+            "Training and export tools can consume substantial VRAM and write files. "
+            "Never expose tokens or local paths from tool results unless the user asks."
+        ),
+    )
+
+    @mcp.tool
+    async def studio_status() -> dict[str, Any]:
+        """Return the current training, export, inference, and GPU state."""
+        from routes.export import get_export_status
+        from routes.inference import get_status as get_inference_status
+        from routes.training import get_training_status
+
+        from utils.hardware import get_gpu_utilization
+
+        training, export, inference = await _gather_status(
+            get_training_status(current_subject = "mcp"),
+            get_export_status(current_subject = "mcp"),
+            get_inference_status(current_subject = "mcp"),
+        )
+        return {
+            "training": _dump(training),
+            "export": _dump(export),
+            "inference": _dump(inference),
+            "hardware": get_gpu_utilization(),
+        }
+
+    @mcp.tool
+    async def list_local_models(models_dir: str = "./models") -> dict[str, Any]:
+        """List local and cached models available to Studio."""
+        from routes.models import list_local_models as list_models
+        return _dump(await list_models(models_dir = models_dir, current_subject = "mcp"))
+
+    @mcp.tool
+    async def get_training_status() -> dict[str, Any]:
+        """Read the active training job, phase, progress, and recent metrics."""
+        from routes.training import get_training_status as get_status
+        return _dump(await get_status(current_subject = "mcp"))
+
+    @mcp.tool
+    async def start_training(config: dict[str, Any]) -> dict[str, Any]:
+        """Start a validated Studio training job from a TrainingStartRequest-shaped object.
+
+        The config is validated by the same Pydantic model used by the Studio UI.
+        Call get_training_status first and do not start work while another job runs.
+        """
+        from models import TrainingStartRequest
+        from routes.training import start_training as start
+
+        request = TrainingStartRequest.model_validate(config)
+        # Pass via_api_key explicitly (a direct call leaves it a Depends object).
+        # MCP drives Studio like the UI session, so it coexists and frees VRAM.
+        return _dump(await start(request, current_subject = "mcp", via_api_key = False))
+
+    @mcp.tool
+    async def stop_training(save: bool = True) -> dict[str, Any]:
+        """Ask the active training process to stop at its next safe checkpoint."""
+        from routes.training import TrainingStopRequest, stop_training as stop
+        return _dump(await stop(TrainingStopRequest(save = save), current_subject = "mcp"))
+
+    @mcp.tool
+    async def list_training_runs(limit: int = 50, offset: int = 0) -> dict[str, Any]:
+        """List completed and stopped training runs, newest first."""
+        from routes.training_history import list_training_runs as list_runs
+
+        # Clamp here (direct call skips Query bounds); a negative LIMIT = no limit.
+        limit = _clamp(limit, 1, 200)
+        offset = max(0, offset)
+        return _dump(await list_runs(limit = limit, offset = offset, current_subject = "mcp"))
+
+    @mcp.tool
+    def validate_recipe(recipe: dict[str, Any]) -> dict[str, Any]:
+        """Validate a Data Recipe with the same validator used by Studio."""
+        from models.data_recipe import RecipePayload
+        from routes.data_recipe.validate import validate
+
+        return _dump(validate(RecipePayload(recipe = recipe)))
+
+    @mcp.tool
+    def get_recipe_job_status(job_id: str) -> dict[str, Any]:
+        """Read the status of a Data Recipe job."""
+        from routes.data_recipe.jobs import job_status
+        return _dump(job_status(job_id))
+
+    @mcp.tool
+    def get_recipe_job_dataset(
+        job_id: str,
+        limit: int = 20,
+        offset: int = 0,
+    ) -> dict[str, Any]:
+        """Read a bounded page of generated Data Recipe rows."""
+        from routes.data_recipe.jobs import job_dataset
+
+        # Clamp here (direct call skips FastAPI's Query bounds).
+        limit = _clamp(limit, 1, 500)
+        offset = max(0, offset)
+        return _dump(job_dataset(job_id, limit = limit, offset = offset))
+
+    @mcp.tool
+    async def load_checkpoint(
+        checkpoint_path: str,
+        max_seq_length: int = 2048,
+        load_in_4bit: bool = True,
+        trust_remote_code: bool = False,
+        approved_remote_code_fingerprint: str | None = None,
+        hf_token: str | None = None,
+    ) -> dict[str, Any]:
+        """Load a checkpoint into the export backend.
+
+        Export runs in its own subprocess and coexists with training and
+        inference; it does not unload them, so a load can fail with a clear
+        out-of-memory error if the GPU is already full. Pass hf_token to load a
+        gated checkpoint, and approved_remote_code_fingerprint to retry a
+        trust_remote_code load that was blocked pending review.
+        """
+        from models import LoadCheckpointRequest
+        from routes.export import load_checkpoint as load
+
+        request = LoadCheckpointRequest(
+            checkpoint_path = checkpoint_path,
+            max_seq_length = max_seq_length,
+            load_in_4bit = load_in_4bit,
+            trust_remote_code = trust_remote_code,
+            approved_remote_code_fingerprint = approved_remote_code_fingerprint,
+            hf_token = hf_token,
+        )
+        return _dump(await load(request, current_subject = "mcp"))
+
+    @mcp.tool
+    async def export_gguf(
+        save_directory: str,
+        quantization_method: str | list[str] = "Q4_K_M",
+        push_to_hub: bool = False,
+        repo_id: str | None = None,
+        hf_token: str | None = None,
+        imatrix: bool = False,
+        imatrix_path: str | None = None,
+    ) -> dict[str, Any]:
+        """Export the loaded model to GGUF using Studio's existing path validation.
+
+        quantization_method may be a single method or a list to produce several
+        GGUFs from one load. Pass hf_token when push_to_hub is set (the backend
+        rejects a Hub upload without it). Set imatrix (or imatrix_path) for the
+        IQ low-bit quants that require an importance matrix.
+        """
+        from models import ExportGGUFRequest
+        from routes.export import export_gguf as export
+
+        request = ExportGGUFRequest(
+            save_directory = save_directory,
+            quantization_method = quantization_method,
+            push_to_hub = push_to_hub,
+            repo_id = repo_id,
+            hf_token = hf_token,
+            imatrix = imatrix,
+            imatrix_path = imatrix_path,
+        )
+        return _dump(await export(request, current_subject = "mcp"))
+
+    return mcp
+
+
+async def _gather_status(*coroutines: Any) -> tuple[Any, ...]:
+    """Gather independent status calls without letting one optional backend fail all state."""
+    import asyncio
+
+    results = await asyncio.gather(*coroutines, return_exceptions = True)
+    return tuple(
+        {"error": str(result)} if isinstance(result, Exception) else result for result in results
+    )
diff --git a/studio/backend/tests/test_mcp_server.py b/studio/backend/tests/test_mcp_server.py
new file mode 100644
index 0000000000..71792605ae
--- /dev/null
+++ b/studio/backend/tests/test_mcp_server.py
@@ -0,0 +1,290 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import asyncio
+import sys
+import types
+
+import pytest
+
+from mcp_server import BearerTokenMiddleware, _clamp, _dump, create_studio_mcp
+
+
+def _get_tool(name):
+    tools = asyncio.run(create_studio_mcp().list_tools())
+    return {tool.name: tool for tool in tools}[name]
+
+
+def test_studio_mcp_registers_control_plane_tools():
+    tools = asyncio.run(create_studio_mcp().list_tools())
+
+    assert {tool.name for tool in tools} == {
+        "studio_status",
+        "list_local_models",
+        "get_training_status",
+        "start_training",
+        "stop_training",
+        "list_training_runs",
+        "validate_recipe",
+        "get_recipe_job_status",
+        "get_recipe_job_dataset",
+        "load_checkpoint",
+        "export_gguf",
+    }
+
+
+def test_dump_serializes_pydantic_values():
+    class Response:
+        def model_dump(self, *, mode):
+            assert mode == "json"
+            return {"ok": True}
+
+    assert _dump(Response()) == {"ok": True}
+    assert _dump({"already": "json"}) == {"already": "json"}
+
+
+def test_bearer_token_middleware_rejects_wrong_token():
+    events = []
+
+    async def app(scope, receive, send):
+        events.append("app")
+
+    async def send(message):
+        events.append(message)
+
+    middleware = BearerTokenMiddleware(app, "secret")
+    asyncio.run(
+        middleware(
+            {"type": "http", "headers": [(b"authorization", b"Bearer wrong")]},
+            None,
+            send,
+        )
+    )
+
+    assert events[0]["status"] == 401
+    assert "app" not in events
+
+
+def test_bearer_token_middleware_closes_unauthorized_websocket():
+    events = []
+
+    async def app(scope, receive, send):
+        events.append("app")
+
+    async def send(message):
+        events.append(message)
+
+    middleware = BearerTokenMiddleware(app, "secret")
+    asyncio.run(
+        middleware(
+            {"type": "websocket", "headers": []},
+            None,
+            send,
+        )
+    )
+
+    assert events == [{"type": "websocket.close", "code": 4401}]
+
+
+def test_bearer_token_middleware_rejects_non_ascii_authorization():
+    # A non-ASCII bearer value must produce a clean 401, not a 500. Comparing on
+    # bytes avoids the str hmac.compare_digest TypeError on non-ASCII input.
+    events = []
+
+    async def app(scope, receive, send):
+        events.append("app")
+
+    async def send(message):
+        events.append(message)
+
+    middleware = BearerTokenMiddleware(app, "secret")
+    asyncio.run(
+        middleware(
+            {"type": "http", "headers": [(b"authorization", b"Bearer \xff\xff")]},
+            None,
+            send,
+        )
+    )
+
+    assert events[0]["status"] == 401
+    assert "app" not in events
+
+
+def test_bearer_token_middleware_accepts_correct_token():
+    events = []
+
+    async def app(scope, receive, send):
+        events.append("app")
+
+    async def send(message):
+        events.append(message)
+
+    middleware = BearerTokenMiddleware(app, "secret")
+    asyncio.run(
+        middleware(
+            {"type": "http", "headers": [(b"authorization", b"Bearer secret")]},
+            None,
+            send,
+        )
+    )
+
+    assert events == ["app"]
+
+
+def test_bearer_token_middleware_requires_non_empty_token():
+    async def app(scope, receive, send):
+        pass
+
+    for bad in ("", "   "):
+        with pytest.raises(ValueError):
+            BearerTokenMiddleware(app, bad)
+
+
+def test_bearer_token_middleware_rejects_non_ascii_token():
+    async def app(scope, receive, send):
+        pass
+
+    # non-ASCII tokens cannot be transmitted in an HTTP header by a standard
+    # client, so they are rejected at construction instead of locking out.
+    for bad in ("töken", "\U0001f600"):
+        with pytest.raises(ValueError):
+            BearerTokenMiddleware(app, bad)
+
+
+def test_bearer_token_middleware_passes_through_non_http_scopes():
+    events = []
+
+    async def app(scope, receive, send):
+        events.append("app")
+
+    async def send(message):
+        events.append(message)
+
+    middleware = BearerTokenMiddleware(app, "secret")
+    asyncio.run(middleware({"type": "lifespan"}, None, send))
+
+    assert events == ["app"]
+
+
+def test_clamp_restricts_to_inclusive_bounds():
+    assert _clamp(5, 1, 200) == 5
+    assert _clamp(-10, 1, 200) == 1
+    assert _clamp(10_000, 1, 200) == 200
+    assert _clamp(0, 1, 500) == 1
+    assert _clamp(1_000, 1, 500) == 500
+
+
+def test_export_and_checkpoint_tools_expose_forwarded_fields():
+    export_props = set(_get_tool("export_gguf").parameters["properties"])
+    assert {"hf_token", "imatrix", "imatrix_path"} <= export_props
+
+    checkpoint_props = set(_get_tool("load_checkpoint").parameters["properties"])
+    assert {"hf_token", "approved_remote_code_fingerprint"} <= checkpoint_props
+
+
+def _stub_module(monkeypatch, name, **attrs):
+    module = types.ModuleType(name)
+    for key, value in attrs.items():
+        setattr(module, key, value)
+    if "." in name:
+        module.__path__ = []  # mark package-like so submodule imports resolve
+    monkeypatch.setitem(sys.modules, name, module)
+    return module
+
+
+def test_export_gguf_forwards_hf_token_and_imatrix(monkeypatch):
+    captured = {}
+
+    class FakeExportGGUFRequest:
+        def __init__(self, **kwargs):
+            captured.update(kwargs)
+
+    async def fake_export(request, current_subject):
+        return {"current_subject": current_subject}
+
+    _stub_module(monkeypatch, "models", ExportGGUFRequest = FakeExportGGUFRequest)
+    _stub_module(monkeypatch, "routes")
+    _stub_module(monkeypatch, "routes.export", export_gguf = fake_export)
+
+    tool = _get_tool("export_gguf")
+    result = asyncio.run(
+        tool.fn(
+            save_directory = "/tmp/out",
+            quantization_method = ["Q4_K_M", "Q8_0"],
+            push_to_hub = True,
+            repo_id = "me/model",
+            hf_token = "hf_secret",
+            imatrix = True,
+            imatrix_path = "/tmp/imatrix.dat",
+        )
+    )
+
+    assert captured["hf_token"] == "hf_secret"
+    assert captured["imatrix"] is True
+    assert captured["imatrix_path"] == "/tmp/imatrix.dat"
+    assert captured["quantization_method"] == ["Q4_K_M", "Q8_0"]
+    assert result["current_subject"] == "mcp"
+
+
+def test_load_checkpoint_forwards_token_and_fingerprint(monkeypatch):
+    captured = {}
+
+    class FakeLoadCheckpointRequest:
+        def __init__(self, **kwargs):
+            captured.update(kwargs)
+
+    async def fake_load(request, current_subject):
+        return {"current_subject": current_subject}
+
+    _stub_module(monkeypatch, "models", LoadCheckpointRequest = FakeLoadCheckpointRequest)
+    _stub_module(monkeypatch, "routes")
+    _stub_module(monkeypatch, "routes.export", load_checkpoint = fake_load)
+
+    tool = _get_tool("load_checkpoint")
+    asyncio.run(
+        tool.fn(
+            checkpoint_path = "/tmp/ckpt",
+            approved_remote_code_fingerprint = "sha256:abc",
+            hf_token = "hf_secret",
+        )
+    )
+
+    assert captured["hf_token"] == "hf_secret"
+    assert captured["approved_remote_code_fingerprint"] == "sha256:abc"
+
+
+def test_list_training_runs_clamps_pagination(monkeypatch):
+    captured = {}
+
+    async def fake_list_runs(limit, offset, current_subject):
+        captured["limit"] = limit
+        captured["offset"] = offset
+        return {"ok": True}
+
+    _stub_module(monkeypatch, "routes")
+    _stub_module(monkeypatch, "routes.training_history", list_training_runs = fake_list_runs)
+
+    tool = _get_tool("list_training_runs")
+    asyncio.run(tool.fn(limit = 10_000, offset = -5))
+
+    assert captured["limit"] == 200
+    assert captured["offset"] == 0
+
+
+def test_get_recipe_job_dataset_clamps_pagination(monkeypatch):
+    captured = {}
+
+    def fake_job_dataset(job_id, limit, offset):
+        captured["limit"] = limit
+        captured["offset"] = offset
+        return {"ok": True}
+
+    _stub_module(monkeypatch, "routes")
+    _stub_module(monkeypatch, "routes.data_recipe")
+    _stub_module(monkeypatch, "routes.data_recipe.jobs", job_dataset = fake_job_dataset)
+
+    tool = _get_tool("get_recipe_job_dataset")  # this tool is synchronous
+    tool.fn(job_id = "job-1", limit = -1, offset = -9)
+
+    assert captured["limit"] == 1
+    assert captured["offset"] == 0

From 4e09328c3bb42dcdcfe1f3de916803ad0ecc016d Mon Sep 17 00:00:00 2001
From: Andrew Chen <48723787+chuenchen309@users.noreply.github.com>
Date: Sat, 18 Jul 2026 20:53:33 +0800
Subject: [PATCH 19/28] fix(tokenizer): check for tokenizer.model after saving
 it, not before (#7194)

* fix(tokenizer): check for tokenizer.model after saving it, not before

`fix_sentencepiece_tokenizer` creates its temporary directory, then returns
early unless that directory already contains a tokenizer.model:

    if not os.path.exists(temporary_location):
        os.makedirs(temporary_location)          # fresh, empty

    if not os.path.isfile(f"{temporary_location}/tokenizer.model"):
        return new_tokenizer                     # always true

    old_tokenizer.save_pretrained(temporary_location)   # writes that file

The file only appears on the line after the check, so the guard is always
true and the body never runs. Nothing else writes that path either --
`convert_to_fast_tokenizer` saves into a per-name subdirectory, not
`{temporary_location}/tokenizer.model`.

Both call sites are in `get_chat_template` and are commented "Must fix the
sentence piece tokenizer since there's no tokenizer.model file!" -- the
guard defeats the exact intent the caller states. The effect is silent: the
caller still gets a working `new_tokenizer`, but the sentencepiece piece
rename is skipped, so the mapped token (e.g. the eos token remapped to
`<|im_end|>`) is missing from tokenizer.model and GGUF/llama.cpp exports
carry the old piece.

`check_if_sentencepiece_model` in save.py does the same probe in the right
order -- makedirs, save_pretrained, then isfile. Match it.

Tests are added under tests/saving/ next to the existing sentencepiece
coverage, and to the two Bucket-A lists in consolidated-tests-ci.yml, since
Repo tests (CPU) --ignores tests/saving and these need protobuf.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Clear stale tokenizer.model before the sentencepiece guard

The guard now runs after old_tokenizer.save_pretrained, but the default
temporary_location is a fixed reusable directory. A fast-only tokenizer writes
no tokenizer.model, so a stale file from an earlier sentencepiece call could
pass the guard and patch the wrong model (e.g. mixing models in one process,
like a long-running server). Remove any existing tokenizer.model first, and add
a regression test.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Empty the reusable sentencepiece scratch directory each call

The final AutoTokenizer.from_pretrained reloads the whole temporary_location, so
removing only a stale tokenizer.model still let other artifacts from a previous
tokenizer (added_tokens.json, chat template, etc.) leak into the reload when the
default reusable directory is used across models in one process. Recreate the
directory instead, and add a regression test for the leaked-artifact case.

* Clear only top-level scratch files, keep subdirectories

Recreating the whole reusable directory deleted the {name} subtree that
convert_to_fast_tokenizer stores a converted tokenizer's source vocab in, so
old_tokenizer.save_pretrained could not copy tokenizer.model and the guard
returned the tokenizer unpatched for those legacy converted tokenizers. Remove
only stale top-level files (all the final reload reads) and leave subdirectories
intact. Add a regression test for the converted-source subdirectory.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Keep the current tokenizer's own source vocab when clearing

On a repeated get_chat_template(map_eos_token=True) call, the returned tokenizer's
vocab_file points back at the top-level tokenizer.model, and the cleanup deleted
that source before old_tokenizer.save_pretrained could re-emit it, so the guard
returned the tokenizer unpatched. Skip removing the old tokenizer's own source
vocab while still clearing stale files from a different tokenizer, and add a
regression test.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Use a per-call temporary directory for the sentencepiece fix

The scratch directory defaulted to a single shared path, so concurrent or repeated
get_chat_template(map_eos_token=True) calls could delete or overwrite each other's
tokenizer.model between save and reload (tripping the piece assertion or reloading
the wrong model), and stale files from an earlier tokenizer could leak into the
reload. Work in a unique per-call subdirectory instead: this isolates every call
without deleting anything the caller owns, and replaces the earlier per-file cleanup.
Tests updated to read the patched model from the reloaded directory and to cover
isolation and source-vocab preservation.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Pass only the applied token mappings into the sentencepiece fix

get_chat_template mirrors token remaps into tokenizer.model via
fix_sentencepiece_tokenizer, but two caller paths passed a mapping that did not
match what they wrote to the fast tokenizer JSON, so once the sentencepiece patch
runs the model and JSON disagree:
- the mapped-token path skipped entries whose target already existed but still
  passed the full mapping, renaming a piece the JSON never changed;
- the EOS-swap path swapped both tokens in the JSON but passed only one direction,
  leaving two stop_word pieces and no old EOS piece.
Pass the applied mapping (and both swap directions) instead. Add regression tests.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Tighten sentencepiece guard comments

* Add SPDX license identifier to sentencepiece guard test

* Reclaim the per-call sentencepiece scratch directory

The per-call tempfile.mkdtemp fixed the shared-directory race but never cleaned
up, so a long-running process leaked one scratch dir per call. The dir cannot be
deleted eagerly for sentencepiece tokenizers because the returned tokenizer's
vocab_file points into it (a later save_pretrained copies the patched
tokenizer.model from there). Reclaim it correctly instead: remove the dir right
away on the fast-only path (the returned tokenizer never references it), and
attach a weakref.finalize so the sentencepiece dir is removed once its tokenizer
is garbage collected. Add regression tests for both.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Tighten the scratch-dir reclaim comment

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
---
 .github/workflows/consolidated-tests-ci.yml   |   2 +
 .../test_fix_sentencepiece_tokenizer_guard.py | 307 ++++++++++++++++++
 unsloth/chat_templates.py                     |  12 +-
 unsloth/tokenizer_utils.py                    |  18 +-
 4 files changed, 333 insertions(+), 6 deletions(-)
 create mode 100644 tests/saving/test_fix_sentencepiece_tokenizer_guard.py

diff --git a/.github/workflows/consolidated-tests-ci.yml b/.github/workflows/consolidated-tests-ci.yml
index fa84471d36..d1bea819eb 100644
--- a/.github/workflows/consolidated-tests-ci.yml
+++ b/.github/workflows/consolidated-tests-ci.yml
@@ -268,6 +268,7 @@ jobs:
             tests/saving/test_save_shell_injection.py \
             tests/saving/test_patch_saving_none_tokenizer.py \
             tests/saving/test_fix_sentencepiece_gguf_robustness.py \
+            tests/saving/test_fix_sentencepiece_tokenizer_guard.py \
             tests/saving/test_compressed_export_schemes.py \
             tests/saving/test_export_api_surface.py \
             tests/saving/test_export_dispatch.py \
@@ -358,6 +359,7 @@ jobs:
             tests/saving/test_save_shell_injection.py \
             tests/saving/test_patch_saving_none_tokenizer.py \
             tests/saving/test_fix_sentencepiece_gguf_robustness.py \
+            tests/saving/test_fix_sentencepiece_tokenizer_guard.py \
             tests/saving/test_compressed_export_schemes.py \
             tests/saving/test_export_api_surface.py \
             tests/saving/test_export_dispatch.py \
diff --git a/tests/saving/test_fix_sentencepiece_tokenizer_guard.py b/tests/saving/test_fix_sentencepiece_tokenizer_guard.py
new file mode 100644
index 0000000000..1ee523d57b
--- /dev/null
+++ b/tests/saving/test_fix_sentencepiece_tokenizer_guard.py
@@ -0,0 +1,307 @@
+# SPDX-License-Identifier: AGPL-3.0-only
+import gc
+import os
+
+os.environ.setdefault("PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION", "python")
+
+import transformers
+from transformers.utils import sentencepiece_model_pb2
+
+from unsloth.tokenizer_utils import fix_sentencepiece_tokenizer
+
+
+NORMAL, CONTROL = 1, 3
+
+
+def _spm_bytes(pieces):
+    m = sentencepiece_model_pb2.ModelProto()
+    for piece, score, typ in pieces:
+        p = m.pieces.add()
+        p.piece = piece
+        p.score = score
+        p.type = typ
+    return m.SerializeToString()
+
+
+def _read_pieces(path):
+    m = sentencepiece_model_pb2.ModelProto()
+    with open(path, "rb") as f:
+        m.ParseFromString(f.read())
+    return [p.piece for p in m.pieces]
+
+
+class _FakeTokenizer:
+    """Minimal stand-in for a sentencepiece-backed slow tokenizer.
+
+    ``save_pretrained`` writes a tokenizer.model, which is what the real slow
+    tokenizers do and what fix_sentencepiece_tokenizer reads back.
+    """
+
+    def __init__(
+        self,
+        name,
+        spm_bytes = None,
+        vocab = None,
+    ):
+        self.name = name
+        self.eos_token = "</s>"
+        self.pad_token = "<pad>"
+        self._spm_bytes = spm_bytes
+        self._vocab = vocab or {}
+        self.saved_to = []
+
+    def save_pretrained(self, location):
+        self.saved_to.append(location)
+        os.makedirs(location, exist_ok = True)
+        if self._spm_bytes is not None:
+            with open(os.path.join(location, "tokenizer.model"), "wb") as f:
+                f.write(self._spm_bytes)
+
+    def __call__(
+        self,
+        texts,
+        add_special_tokens = False,
+    ):
+        class _Encoded:
+            pass
+
+        encoded = _Encoded()
+        encoded.input_ids = [[self._vocab[text]] for text in texts]
+        return encoded
+
+
+def _tokenizers():
+    pieces = [("<s>", 0.0, CONTROL), ("a", -1.0, NORMAL), ("</s>", 0.0, CONTROL)]
+    old = _FakeTokenizer("old", spm_bytes = _spm_bytes(pieces), vocab = {"</s>": 2})
+    new = _FakeTokenizer("new")
+    return old, new
+
+
+class _ReloadedTokenizer:
+    """Weakref-able stand-in for the tokenizer AutoTokenizer.from_pretrained returns."""
+
+    def __init__(self, location):
+        self.location = location
+
+
+def _stub_auto_tokenizer(monkeypatch):
+    """fix_sentencepiece_tokenizer reloads the patched directory through
+    AutoTokenizer at the end; that needs a full tokenizer on disk, which is
+    out of scope here. Record the reload location and hand back a sentinel.
+    """
+    loaded = []
+
+    class _StubAutoTokenizer:
+        @staticmethod
+        def from_pretrained(location, **kwargs):
+            loaded.append(location)
+            return _ReloadedTokenizer(location)
+
+    monkeypatch.setattr(transformers, "AutoTokenizer", _StubAutoTokenizer)
+    return loaded
+
+
+def test_old_tokenizer_is_saved_so_its_model_can_be_read(tmp_path, monkeypatch):
+    """The guard must not skip the body on a fresh temporary directory.
+
+    fix_sentencepiece_tokenizer creates its scratch directory itself and then
+    checks for a tokenizer.model inside it, but that file only appears once
+    old_tokenizer.save_pretrained() has run.
+    """
+    _stub_auto_tokenizer(monkeypatch)
+    old, new = _tokenizers()
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+
+    fix_sentencepiece_tokenizer(old, new, {"</s>": "<|im_end|>"}, temporary_location = location)
+
+    assert old.saved_to, "old tokenizer was never saved: the body did not run"
+
+
+def test_token_mapping_is_applied_to_the_sentencepiece_model(tmp_path, monkeypatch):
+    loaded = _stub_auto_tokenizer(monkeypatch)
+    old, new = _tokenizers()
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+
+    # Hold the returned tokenizer so its scratch dir survives until we read it.
+    tok = fix_sentencepiece_tokenizer(old, new, {"</s>": "<|im_end|>"}, temporary_location = location)
+
+    assert "<|im_end|>" in _read_pieces(f"{loaded[-1]}/tokenizer.model")
+    assert tok is not None
+
+
+def test_tokenizer_without_a_sentencepiece_model_is_returned_untouched(tmp_path, monkeypatch):
+    """A fast-only tokenizer writes no tokenizer.model, so the guard still
+    short-circuits and the caller gets new_tokenizer back unchanged. Its scratch
+    dir is unreferenced and reclaimed immediately.
+    """
+    _stub_auto_tokenizer(monkeypatch)
+    old = _FakeTokenizer("old", spm_bytes = None)
+    new = _FakeTokenizer("new")
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+
+    result = fix_sentencepiece_tokenizer(
+        old, new, {"</s>": "<|im_end|>"}, temporary_location = location
+    )
+
+    assert result is new
+    assert not any(
+        name.startswith("tokenizer_") for name in os.listdir(location)
+    ), "the fast-only scratch dir was not reclaimed"
+
+
+def test_each_call_uses_a_fresh_isolated_subdirectory(tmp_path, monkeypatch):
+    """Each call must work in its own unique subdirectory, so concurrent or
+    repeated calls never share scratch files, stale artifacts never leak into
+    the reload, and nothing the caller left in the scratch location is deleted.
+    """
+    loaded = _stub_auto_tokenizer(monkeypatch)
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+    os.makedirs(location, exist_ok = True)
+
+    # A pre-existing artifact in the shared scratch location.
+    marker = os.path.join(location, "leftover.json")
+    with open(marker, "w") as f:
+        f.write("{}")
+
+    old1, new1 = _tokenizers()
+    old2, new2 = _tokenizers()
+    # Hold both returned tokenizers so their scratch dirs stay alive.
+    tok1 = fix_sentencepiece_tokenizer(
+        old1, new1, {"</s>": "<|im_end|>"}, temporary_location = location
+    )
+    tok2 = fix_sentencepiece_tokenizer(
+        old2, new2, {"</s>": "<|im_end|>"}, temporary_location = location
+    )
+
+    work1, work2 = loaded[0], loaded[1]
+    assert work1 != work2, "two calls reused the same directory"
+    assert os.path.dirname(work1) == location and os.path.dirname(work2) == location
+    assert os.path.isdir(work1) and os.path.isdir(work2)
+    # Nothing the caller left behind is deleted, and it never leaks into a work dir.
+    assert os.path.isfile(marker), "a pre-existing scratch file was deleted"
+    assert not os.path.isfile(os.path.join(work1, "leftover.json"))
+    assert not os.path.isfile(os.path.join(work2, "leftover.json"))
+    assert tok1 is not None and tok2 is not None
+
+
+def test_sentencepiece_scratch_dir_is_reclaimed_once_the_tokenizer_is_gone(tmp_path, monkeypatch):
+    """The scratch dir must live as long as the returned tokenizer (its vocab_file
+    points there), then be reclaimed when the tokenizer is garbage collected.
+    """
+    loaded = _stub_auto_tokenizer(monkeypatch)
+    old, new = _tokenizers()
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+
+    tok = fix_sentencepiece_tokenizer(old, new, {"</s>": "<|im_end|>"}, temporary_location = location)
+    work = loaded[-1]
+    assert os.path.isdir(work), "scratch dir vanished while the tokenizer was alive"
+
+    del tok
+    gc.collect()
+    assert not os.path.isdir(work), "scratch dir was not reclaimed after the tokenizer was freed"
+
+
+class _CopyFromSubdirTokenizer:
+    """A slow tokenizer whose sentencepiece source lives elsewhere (like the
+    tokenizers convert_to_fast_tokenizer produces under {location}/{name}).
+    save_pretrained copies that source into the destination, as HF slow
+    tokenizers copy their vocab_file.
+    """
+
+    def __init__(self, source_model_path):
+        self.eos_token = "</s>"
+        self.pad_token = "<pad>"
+        self._source_model_path = source_model_path
+
+    def save_pretrained(self, location):
+        os.makedirs(location, exist_ok = True)
+        if os.path.isfile(self._source_model_path):
+            with open(self._source_model_path, "rb") as src:
+                data = src.read()
+            with open(os.path.join(location, "tokenizer.model"), "wb") as dst:
+                dst.write(data)
+
+    def __call__(
+        self,
+        texts,
+        add_special_tokens = False,
+    ):
+        class _Encoded:
+            pass
+
+        encoded = _Encoded()
+        encoded.input_ids = [[2] for _ in texts]
+        return encoded
+
+
+def test_source_vocab_outside_the_work_directory_is_not_disturbed(tmp_path, monkeypatch):
+    """A tokenizer whose sentencepiece source lives elsewhere (e.g. the subtree
+    convert_to_fast_tokenizer created) is copied into the fresh work directory
+    and patched there; the original source is left untouched.
+    """
+    loaded = _stub_auto_tokenizer(monkeypatch)
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+    subdir = os.path.join(location, "some_model")
+    os.makedirs(subdir, exist_ok = True)
+
+    pieces = [("<s>", 0.0, CONTROL), ("a", -1.0, NORMAL), ("</s>", 0.0, CONTROL)]
+    source_model = os.path.join(subdir, "tokenizer.model")
+    with open(source_model, "wb") as f:
+        f.write(_spm_bytes(pieces))
+
+    old = _CopyFromSubdirTokenizer(source_model)
+    new = _FakeTokenizer("new")
+    tok = fix_sentencepiece_tokenizer(old, new, {"</s>": "<|im_end|>"}, temporary_location = location)
+
+    assert _read_pieces(source_model) == [
+        "<s>",
+        "a",
+        "</s>",
+    ], "the original source vocab was modified"
+    assert "<|im_end|>" in _read_pieces(f"{loaded[-1]}/tokenizer.model")
+    assert tok is not None
+
+
+def test_swap_mapping_swaps_both_pieces_without_duplicating(tmp_path, monkeypatch):
+    """When the caller swaps eos and stop_word in the fast JSON it must pass both
+    directions here; a one-way mapping would leave two stop_word pieces and no eos.
+    """
+    loaded = _stub_auto_tokenizer(monkeypatch)
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+
+    pieces = [("<s>", 0.0, CONTROL), ("<|im_end|>", -1.0, NORMAL), ("</s>", 0.0, CONTROL)]
+    old = _FakeTokenizer("old", spm_bytes = _spm_bytes(pieces), vocab = {"</s>": 2, "<|im_end|>": 1})
+    new = _FakeTokenizer("new")
+
+    tok = fix_sentencepiece_tokenizer(
+        old, new, {"</s>": "<|im_end|>", "<|im_end|>": "</s>"}, temporary_location = location
+    )
+
+    result = _read_pieces(f"{loaded[-1]}/tokenizer.model")
+    assert result.count("<|im_end|>") == 1 and result.count("</s>") == 1, result
+    assert tok is not None
+
+
+def test_only_applied_mappings_are_patched(tmp_path, monkeypatch):
+    """When the caller skips a mapping whose target already exists, it must not
+    pass that mapping here, or the skipped source token gets renamed anyway and
+    duplicates the existing target in the model.
+    """
+    loaded = _stub_auto_tokenizer(monkeypatch)
+    location = str(tmp_path / "_unsloth_sentencepiece_temp")
+
+    pieces = [
+        ("<s>", 0.0, CONTROL),
+        ("aa", -1.0, NORMAL),
+        ("bb", -1.0, NORMAL),
+        ("X", -1.0, NORMAL),
+    ]
+    old = _FakeTokenizer("old", spm_bytes = _spm_bytes(pieces), vocab = {"aa": 1, "bb": 2})
+    new = _FakeTokenizer("new")
+
+    # Caller skipped aa->X (X already exists) and applied bb->Y, so only bb->Y is passed.
+    tok = fix_sentencepiece_tokenizer(old, new, {"bb": "Y"}, temporary_location = location)
+
+    result = _read_pieces(f"{loaded[-1]}/tokenizer.model")
+    assert result.count("X") == 1 and "Y" in result and "aa" in result, result
+    assert tok is not None
diff --git a/unsloth/chat_templates.py b/unsloth/chat_templates.py
index 2d3674fb04..bd612db1d5 100644
--- a/unsloth/chat_templates.py
+++ b/unsloth/chat_templates.py
@@ -1929,6 +1929,9 @@ def get_chat_template(
             string_vocab = tokenizer._tokenizer.to_str()
 
             skipped = 0
+            # Only mirror applied mappings into the spm model; a skipped one would
+            # rename a piece the JSON never changed and desync the two.
+            applied_mapping = {}
             for old_token, new_token in token_mapping.items():
                 old_count = string_vocab.count(f'"{old_token}"')
                 new_count = string_vocab.count(f'"{new_token}"')
@@ -1939,6 +1942,7 @@ def get_chat_template(
                     raise RuntimeError(f"{old_token} was not part of the tokenizer!")
                 else:
                     string_vocab = string_vocab.replace(f'"{old_token}"', f'"{new_token}"')
+                    applied_mapping[old_token] = new_token
                 pass
             pass
 
@@ -1973,7 +1977,7 @@ def get_chat_template(
 
                 # Must fix the sentence piece tokenizer since there's no tokenizer.model file!
                 from .tokenizer_utils import fix_sentencepiece_tokenizer
-                tokenizer = fix_sentencepiece_tokenizer(tokenizer, new_tokenizer, token_mapping,)
+                tokenizer = fix_sentencepiece_tokenizer(tokenizer, new_tokenizer, applied_mapping,)
             else:
                 pass
 
@@ -1997,8 +2001,11 @@ def get_chat_template(
                 string_vocab = string_vocab.replace(old_eos_token, temporary_stop_token)
                 string_vocab = string_vocab.replace(stop_word, old_eos_token)
                 string_vocab = string_vocab.replace(temporary_stop_token, stop_word)
+                # JSON swapped both, so swap both here too; a one-way map leaves two stop_word pieces.
+                sentencepiece_mapping = { old_eos_token : stop_word, stop_word : old_eos_token, }
             else:
                 string_vocab = string_vocab.replace(old_eos_token, stop_word)
+                sentencepiece_mapping = { old_eos_token : stop_word, }
             pass
             new_tokenizer = tokenizer._tokenizer.from_str(string_vocab)
 
@@ -2017,9 +2024,8 @@ def get_chat_template(
             )
 
             # Must fix the sentence piece tokenizer since there's no tokenizer.model file!
-            token_mapping = { old_eos_token : stop_word, }
             from .tokenizer_utils import fix_sentencepiece_tokenizer
-            tokenizer = fix_sentencepiece_tokenizer(tokenizer, new_tokenizer, token_mapping,)
+            tokenizer = fix_sentencepiece_tokenizer(tokenizer, new_tokenizer, sentencepiece_mapping,)
         pass
 
     else:
diff --git a/unsloth/tokenizer_utils.py b/unsloth/tokenizer_utils.py
index 3a91ef188d..d6e8247ec4 100644
--- a/unsloth/tokenizer_utils.py
+++ b/unsloth/tokenizer_utils.py
@@ -17,6 +17,9 @@ from transformers.convert_slow_tokenizer import convert_slow_tokenizer
 from transformers import PreTrainedTokenizerFast
 import re
 import os
+import shutil
+import tempfile
+import weakref
 from transformers.models.llama.modeling_llama import logger
 from peft import PeftModelForCausalLM
 import torch
@@ -370,13 +373,19 @@ def fix_sentencepiece_tokenizer(
     if not os.path.exists(temporary_location):
         os.makedirs(temporary_location)
 
-    # Check if tokenizer.model exists
-    if not os.path.isfile(f"{temporary_location}/tokenizer.model"):
-        return new_tokenizer
+    # Fresh per-call subdir so concurrent/repeated calls can't clobber each other's
+    # tokenizer.model or leak stale files, without deleting anything the caller owns.
+    temporary_location = tempfile.mkdtemp(prefix = "tokenizer_", dir = temporary_location)
 
     # First save the old tokenizer
     old_tokenizer.save_pretrained(temporary_location)
 
+    # Only sentencepiece tokenizers write tokenizer.model, so check after the save.
+    if not os.path.isfile(f"{temporary_location}/tokenizer.model"):
+        # new_tokenizer was built in memory and never references this dir, so drop it.
+        shutil.rmtree(temporary_location, ignore_errors = True)
+        return new_tokenizer
+
     tokenizer_file = sentencepiece_model_pb2.ModelProto()
     tokenizer_file.ParseFromString(open(f"{temporary_location}/tokenizer.model", "rb").read())
 
@@ -414,6 +423,9 @@ def fix_sentencepiece_tokenizer(
         eos_token = new_tokenizer.eos_token,
         pad_token = new_tokenizer.pad_token,
     )
+    # vocab_file points here, so the dir must outlive the tokenizer (a later
+    # save_pretrained copies the patched tokenizer.model from it); reclaim it on GC.
+    weakref.finalize(tokenizer, shutil.rmtree, temporary_location, ignore_errors = True)
     return tokenizer
 
 

From 9db639f708f52906ecc7ada0939063d6e5b9b166 Mon Sep 17 00:00:00 2001
From: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
Date: Sat, 18 Jul 2026 05:54:00 -0700
Subject: [PATCH 20/28] Stabilize Studio regression tests (#7192)

* Stabilize Studio regression tests

Rebuild on current main. Restore the set-membership sidebar account-block matcher
(#6647, which fixed the same order-sensitive regex, was reverted on main, so the
guard is failing on main again) and keep the watchdog replacement-race fix, whose
blocked-watchdog stub now waits without a timeout so a superseded watchdog stays
alive until cleanup regardless of scheduler load.

* Tighten the blocked-watchdog stub comment

---------

Co-authored-by: Daniel Han <unslothshared@gmail.com>
---
 .../tests/test_training_stop_watchdog.py      | 22 ++++++++++++----
 .../test_studio_text_descender_clipping.py    | 25 +++++++++++--------
 2 files changed, 32 insertions(+), 15 deletions(-)

diff --git a/studio/backend/tests/test_training_stop_watchdog.py b/studio/backend/tests/test_training_stop_watchdog.py
index 457dfc8ea2..0cd702bce2 100644
--- a/studio/backend/tests/test_training_stop_watchdog.py
+++ b/studio/backend/tests/test_training_stop_watchdog.py
@@ -258,15 +258,27 @@ def test_watchdog_no_op_when_worker_superseded(monkeypatch):
 def test_new_run_gets_its_own_watchdog(monkeypatch):
     # A stale watchdog sleeping on an old proc must not stop a new run's stop from
     # creating its own watcher.
-    monkeypatch.setitem(_G, "_STOP_GRACE_S", 100.0)
-    monkeypatch.setitem(_G, "_STOP_TIMEOUT_S", 100.0)
     b = TrainingBackend()
-    _record_force_terminate(monkeypatch, b)
+    started = []
+    release = threading.Event()
+
+    def _blocked_watchdog(
+        target_proc,
+        cancel,
+        watched_job_id = None,
+    ):
+        started.append(target_proc)
+        # No timeout: the finally always releases this, so a superseded watchdog stays
+        # alive through the assertions regardless of load; as a daemon it can't hang exit.
+        release.wait()
+
+    monkeypatch.setattr(b, "_stop_watchdog_loop", _blocked_watchdog)
 
     old_proc = _FakeProc(alive = True)
     b._proc = old_proc
     b._start_stop_watchdog(cancel = False)
     first_wd = b._stop_watchdog
+    assert _wait_until(lambda: started == [old_proc])
 
     # New run: fresh worker replaces the handle; its stop must get a new watcher
     # even though the old (superseded) watchdog is still alive.
@@ -276,12 +288,12 @@ def test_new_run_gets_its_own_watchdog(monkeypatch):
     second_wd = b._stop_watchdog
 
     try:
+        assert _wait_until(lambda: started == [old_proc, new_proc])
         assert first_wd.is_alive()
         assert second_wd is not first_wd, "a new run must get its own watchdog"
         assert b._stop_watchdog_proc is new_proc
     finally:
-        old_proc._alive = False
-        new_proc._alive = False
+        release.set()
         first_wd.join(timeout = 5)
         second_wd.join(timeout = 5)
 
diff --git a/tests/studio/test_studio_text_descender_clipping.py b/tests/studio/test_studio_text_descender_clipping.py
index 7cad6cacfe..73d1244ee3 100644
--- a/tests/studio/test_studio_text_descender_clipping.py
+++ b/tests/studio/test_studio_text_descender_clipping.py
@@ -34,17 +34,22 @@ def test_model_selector_trigger_label_uses_leading_tight():
 
 def test_sidebar_account_block_uses_leading_tight():
     src = _read(APP_SIDEBAR)
-    # Match the account-block parent div regardless of its gap utility; this
-    # guard is about the leading-* class, not the spacing.
-    pattern = re.compile(
-        r'<div\s+className="flex\s+flex-col\s+gap-\S+\s+(\S+)\s+group-data-\[collapsible=icon\]:hidden">',
-    )
-    matches = pattern.findall(src)
+    class_names = re.findall(r'<div\s+className="([^"]+)"', src)
+    required = {
+        "flex",
+        "flex-1",
+        "flex-col",
+        "group-data-[collapsible=icon]:hidden",
+    }
+    matches = [classes for classes in class_names if required <= set(classes.split())]
     assert matches, "could not find sidebar account-block parent div"
-    leading_classes = [m for m in matches if m.startswith("leading-")]
-    assert leading_classes, f"no leading-* class on sidebar account-block parent: {matches}"
-    for cls in leading_classes:
-        assert cls == "leading-tight", f"sidebar account-block must use leading-tight, got: {cls}"
+    for classes in matches:
+        leading_classes = [cls for cls in classes.split() if cls.startswith("leading-")]
+        assert leading_classes, f"no leading-* class on sidebar account-block parent: {classes}"
+        for cls in leading_classes:
+            assert (
+                cls == "leading-tight"
+            ), f"sidebar account-block must use leading-tight, got: {cls}"
 
 
 def test_no_truncate_plus_leading_none_in_changed_files():

From e55d0e6c75437af79f3338aca1ec12c7ea16e3bd Mon Sep 17 00:00:00 2001
From: Andrew Chen <48723787+chuenchen309@users.noreply.github.com>
Date: Sat, 18 Jul 2026 20:54:50 +0800
Subject: [PATCH 21/28] fix(dataprep): skip .jsonl lines that are valid JSON
 but not objects (#7195)

* fix(dataprep): skip .jsonl lines that are valid JSON but not objects

`_read_file_by_format` json.loads each line and hands the result to
`_extract_text_from_json`, which assumes a dict:

    for field in self._TEXT_FIELDS:
        if field in data and isinstance(data[field], str):

A JSON line does not have to be an object -- `"context"`, `["text"]` and
`42` are all valid JSON. For those, `field in data` stops being a key
lookup and becomes a substring/membership test, so `data[field]` raises:

    "context"        -> "text" in "context" is True (substring!)
                     -> TypeError: string indices must be integers
    ["text", "foo"]  -> TypeError: list indices must be integers
    42               -> TypeError: argument of type 'int' is not iterable

The TypeError escapes past `except json.JSONDecodeError: continue`, so the
whole load dies on one odd line.

That except clause is also the tell: a *malformed* line is already skipped
gracefully. A *well-formed* line that happens not to be an object should be
too -- it carries no text either way. This makes the two agree.

Reachable from `unsloth-cli.py:253` (`--dataset foo.jsonl` auto-detect) and
`RawTextDataLoader` is exported from `unsloth/__init__.py`.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Slim the non-object jsonl regression test and shorten the guard comment

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
---
 tests/test_raw_text.py       | 18 ++++++++++++++++++
 unsloth/dataprep/raw_text.py |  4 ++++
 2 files changed, 22 insertions(+)

diff --git a/tests/test_raw_text.py b/tests/test_raw_text.py
index ba16e0cfc4..18549adfe8 100644
--- a/tests/test_raw_text.py
+++ b/tests/test_raw_text.py
@@ -295,7 +295,25 @@ def test_smart_chunk_text_single_chunk_no_eos_returns_plain_list():
     return True
 
 
+def test_load_from_file_skips_non_object_json_lines():
+    """Non-object .jsonl lines (valid JSON, not dicts) are skipped, not fatal."""
+    # "context" contains "text", ["text"] holds it, 42 isn't iterable -- each
+    # would reach data[field] and raise TypeError without the isinstance guard.
+    with tempfile.NamedTemporaryFile("w", suffix = ".jsonl", delete = False) as f:
+        f.write('"context"\n["text", "x"]\n42\n{"text": "keep this"}\n')
+        path = f.name
+    try:
+        text = RawTextDataLoader(None)._read_file_by_format(path, "json_lines")
+        assert text == "keep this", text
+    finally:
+        os.unlink(path)
+
+    print("test_load_from_file_skips_non_object_json_lines passed")
+    return True
+
+
 if __name__ == "__main__":
     success = test_raw_text_loader()
     success = test_smart_chunk_text_single_chunk_no_eos_returns_plain_list() and success
+    success = test_load_from_file_skips_non_object_json_lines() and success
     sys.exit(0 if success else 1)
diff --git a/unsloth/dataprep/raw_text.py b/unsloth/dataprep/raw_text.py
index 128d966ecd..8623285a25 100644
--- a/unsloth/dataprep/raw_text.py
+++ b/unsloth/dataprep/raw_text.py
@@ -236,6 +236,10 @@ class RawTextDataLoader:
 
     def _extract_text_from_json(self, data):
         """Extract text from JSON object using common field names."""
+        # Skip non-object lines (str/list/number): `field in data` would be a
+        # substring/membership test, not a key lookup, and `data[field]` raises.
+        if not isinstance(data, dict):
+            return ""
         for field in self._TEXT_FIELDS:
             if field in data and isinstance(data[field], str):
                 return data[field]

From 9073f07705488601ab4ff59e3828fe698083894e Mon Sep 17 00:00:00 2001
From: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
Date: Sat, 18 Jul 2026 21:08:55 -0700
Subject: [PATCH 22/28] fix(studio): equal padding in the dataset source
 segmented control (#7230)

* fix(studio): equal padding in dataset source segmented control

* fix(studio): scope dataset source pill layoutId per component instance
---
 .../studio/sections/dataset-section.tsx       | 43 ++++++++++++-------
 1 file changed, 28 insertions(+), 15 deletions(-)

diff --git a/studio/frontend/src/features/studio/sections/dataset-section.tsx b/studio/frontend/src/features/studio/sections/dataset-section.tsx
index e7bab1f47f..6aa9329609 100644
--- a/studio/frontend/src/features/studio/sections/dataset-section.tsx
+++ b/studio/frontend/src/features/studio/sections/dataset-section.tsx
@@ -70,11 +70,13 @@ import {
 } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
 import { useNavigate } from "@tanstack/react-router";
+import { motion, useReducedMotion } from "motion/react";
 import {
   type ChangeEvent,
   type DragEvent,
   useCallback,
   useEffect,
+  useId,
   useMemo,
   useRef,
   useState,
@@ -153,6 +155,9 @@ function normalizeSliceInput(value: string): string | null {
 export function DatasetSection() {
   const t = useT();
   const navigate = useNavigate();
+  const reducedMotion = useReducedMotion();
+  // Scopes the pill layoutId so multiple instances never share one.
+  const sourcePillLayoutId = useId();
   const {
     dataset,
     datasetSource,
@@ -686,6 +691,9 @@ export function DatasetSection() {
           {(() => {
             // Hub-style sliding-pill segmented control, matching the Hub tabs
             // via the shared .hub-tab-toggle / .hub-tab-toggle-pill classes.
+            // flex-auto buttons share leftover space equally so padding stays
+            // equal for all labels; the pill sits inside the active button so
+            // it always matches its bounds.
             const sourceTabs: {
               value: "huggingface" | "upload" | "s3";
               label: string;
@@ -696,24 +704,12 @@ export function DatasetSection() {
                 ? []
                 : [{ value: "s3" as const, label: "Amazon S3" }]),
             ];
-            const activeIndex = Math.max(
-              0,
-              sourceTabs.findIndex((item) => item.value === datasetSource),
-            );
             return (
               <div
                 role="radiogroup"
                 aria-label="Dataset source"
-                className="hub-tab-toggle relative inline-flex h-9 w-full items-center rounded-full"
+                className="hub-tab-toggle relative flex h-9 w-full items-center rounded-full"
               >
-                <span
-                  aria-hidden="true"
-                  className="hub-tab-toggle-pill pointer-events-none absolute inset-y-0 left-0 rounded-full transition-transform duration-200 ease-out"
-                  style={{
-                    width: `${100 / sourceTabs.length}%`,
-                    transform: `translateX(${activeIndex * 100}%)`,
-                  }}
-                />
                 {sourceTabs.map((item) => (
                   <button
                     key={item.value}
@@ -732,13 +728,30 @@ export function DatasetSection() {
                       }
                     }}
                     className={cn(
-                      "relative z-10 inline-flex h-9 flex-1 cursor-pointer items-center justify-center rounded-full px-3 text-[12.5px] font-medium transition-colors",
+                      "relative inline-flex h-9 flex-auto cursor-pointer items-center justify-center rounded-full px-3 text-[12.5px] font-medium transition-colors",
                       datasetSource === item.value
                         ? "text-foreground"
                         : "text-muted-foreground hover:text-foreground",
                     )}
                   >
-                    {item.label}
+                    {datasetSource === item.value && (
+                      <motion.span
+                        aria-hidden="true"
+                        layoutId={sourcePillLayoutId}
+                        className="hub-tab-toggle-pill absolute inset-0 rounded-full"
+                        transition={
+                          reducedMotion
+                            ? { duration: 0 }
+                            : {
+                                type: "spring",
+                                stiffness: 500,
+                                damping: 35,
+                                mass: 0.5,
+                              }
+                        }
+                      />
+                    )}
+                    <span className="relative z-10">{item.label}</span>
                   </button>
                 ))}
               </div>

From d8aa0df66e728cacd677773adb9c4a9ce66cd13a Mon Sep 17 00:00:00 2001
From: Nilay <118994073+NilayYadav@users.noreply.github.com>
Date: Sun, 19 Jul 2026 11:09:49 +0530
Subject: [PATCH 23/28] Studio: keep stale canvas from surviving into a new
 chat (#7229)

---
 .../src/features/chat/artifacts/artifact-card.tsx      |  7 +++++--
 studio/frontend/src/features/chat/chat-page.tsx        | 10 ++++------
 2 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/studio/frontend/src/features/chat/artifacts/artifact-card.tsx b/studio/frontend/src/features/chat/artifacts/artifact-card.tsx
index ee8c26abf1..0345dc6e2a 100644
--- a/studio/frontend/src/features/chat/artifacts/artifact-card.tsx
+++ b/studio/frontend/src/features/chat/artifacts/artifact-card.tsx
@@ -8,7 +8,7 @@ import { cn } from "@/lib/utils";
 import { useAuiState } from "@assistant-ui/react";
 import { LayoutTwoColumnIcon as Layout2ColumnIcon } from "@hugeicons/core-free-icons";
 import { HugeiconsIcon } from "@hugeicons/react";
-import { useLayoutEffect, useMemo } from "react";
+import { useLayoutEffect, useMemo, useRef } from "react";
 import { useChatRuntimeStore } from "../stores/chat-runtime-store";
 import type { ArtifactViewMode } from "./html-frame";
 import {
@@ -83,15 +83,18 @@ export function ArtifactCard({
     ],
   );
   const surface = artifactThreadId ? "panel" : "overlay";
+  // Once per mount, so a view-change cleanup can't re-trigger a stale open.
+  const autoOpenAttemptedRef = useRef(false);
 
   useLayoutEffect(() => {
     if (selectedArtifactId === artifact.id) {
       updateArtifact(artifact);
     }
 
-    if (!autoOpen) {
+    if (!autoOpen || autoOpenAttemptedRef.current) {
       return;
     }
+    autoOpenAttemptedRef.current = true;
     if (hasAutoOpenedArtifact(artifact.id)) {
       return;
     }
diff --git a/studio/frontend/src/features/chat/chat-page.tsx b/studio/frontend/src/features/chat/chat-page.tsx
index 380ce0e0ab..ec0ad977bf 100644
--- a/studio/frontend/src/features/chat/chat-page.tsx
+++ b/studio/frontend/src/features/chat/chat-page.tsx
@@ -247,13 +247,13 @@ const SingleContent = memo(function SingleContent({
     useState(false);
   const [isArtifactSurfaceVisible, setIsArtifactSurfaceVisible] =
     useState(false);
+  // Without a URL threadId the artifact must belong to the active thread.
   const showArtifactPanel = Boolean(
     artifact &&
       artifactSurface === "panel" &&
       (threadId
         ? !artifact.threadId || artifact.threadId === threadId
-        : Boolean(newThreadNonce) ||
-          Boolean(artifact.threadId && artifact.threadId === activeThreadId)),
+        : Boolean(artifact.threadId && artifact.threadId === activeThreadId)),
   );
 
   const artifactLayoutActive = showArtifactPanel || isArtifactPanelLayoutActive;
@@ -1771,10 +1771,8 @@ export function ChatPage({
 
   useEffect(() => {
     if (view.mode !== "single") return;
-    if (view.threadId || view.newThreadNonce || !selectedArtifact) return;
-    // view excludes __LOCALID_ threads (they fall through to mode:"single"
-    // with no threadId/nonce). Don't close a canvas whose thread is the
-    // active local thread.
+    if (view.threadId || !selectedArtifact) return;
+    // Close any canvas that doesn't belong to the active thread.
     if (
       selectedArtifact.threadId &&
       selectedArtifact.threadId === activeThreadId

From 95fa3fbe30198917bdcce4000881530b9adab079 Mon Sep 17 00:00:00 2001
From: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
Date: Sat, 18 Jul 2026 22:47:00 -0700
Subject: [PATCH 24/28] Allow API key for Ollama connections (#7173)

The Connections form hid the API key field for the Ollama preset, which
blocked Ollama cloud (it requires a key). Show the optional field for
Ollama; the backend already sends Authorization: Bearer when a key is
set and omits the header when empty, so local keyless servers are
unaffected.

Fixes #7163
---
 studio/backend/core/inference/providers.py                  | 5 +++--
 studio/frontend/src/features/chat/chat-providers-dialog.tsx | 4 ++--
 studio/frontend/src/features/chat/external-providers.ts     | 5 +++--
 3 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/studio/backend/core/inference/providers.py b/studio/backend/core/inference/providers.py
index 5b72373c03..d3bffc2f3d 100644
--- a/studio/backend/core/inference/providers.py
+++ b/studio/backend/core/inference/providers.py
@@ -276,8 +276,9 @@ PROVIDER_REGISTRY: dict[str, dict[str, Any]] = {
         "auth_header": "Authorization",
         "auth_prefix": "Bearer ",
         "notes": (
-            "Local Ollama server. OpenAI-compatible /v1/chat/completions; "
-            "no API key. Surfaced via CUSTOM_PROVIDER_PRESETS in the frontend."
+            "Ollama server (local or cloud). OpenAI-compatible "
+            "/v1/chat/completions; API key optional (required by Ollama "
+            "cloud). Surfaced via CUSTOM_PROVIDER_PRESETS in the frontend."
         ),
         "hidden": True,
     },
diff --git a/studio/frontend/src/features/chat/chat-providers-dialog.tsx b/studio/frontend/src/features/chat/chat-providers-dialog.tsx
index 95e5cfbd79..e39955e576 100644
--- a/studio/frontend/src/features/chat/chat-providers-dialog.tsx
+++ b/studio/frontend/src/features/chat/chat-providers-dialog.tsx
@@ -244,8 +244,8 @@ export function ChatProvidersSettings({
     (s) => s.setConnectionsEnabled,
   );
   const isCustomProvider = isCustomProviderType(providerType);
-  // Local presets (Ollama, llama.cpp) never use API keys — hide the field.
-  // vLLM may optionally use a bearer token on secured deployments.
+  // llama.cpp hides the key field. Ollama and vLLM show an optional key:
+  // Ollama cloud and secured vLLM need one; local servers leave it empty.
   const showApiKeyField = !customPresetSkipsApiKeyField(providerType);
   const showReasoningToggle = supportsProviderReasoningToggle(providerType);
 
diff --git a/studio/frontend/src/features/chat/external-providers.ts b/studio/frontend/src/features/chat/external-providers.ts
index bc718abbba..eb9e4656b0 100644
--- a/studio/frontend/src/features/chat/external-providers.ts
+++ b/studio/frontend/src/features/chat/external-providers.ts
@@ -184,11 +184,12 @@ export function supportsRemoteModelCatalog(
   );
 }
 
-/** Presets that skip the API-key field (local servers with no auth by default). */
+/** Presets that hide the API-key field. Ollama is not skipped: Ollama cloud
+ * requires a key; local servers leave the optional field empty. */
 export function customPresetSkipsApiKeyField(
   providerType: string | null | undefined,
 ): boolean {
-  return providerType === "ollama" || providerType === "llama_cpp";
+  return providerType === "llama_cpp";
 }
 
 /** Catalog load plus optional manual model IDs. */

From c2cf2b4a1e023f3e9de80b8889971f4d04ded9c7 Mon Sep 17 00:00:00 2001
From: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
Date: Sat, 18 Jul 2026 23:15:13 -0700
Subject: [PATCH 25/28] Studio: keep the permission pill label when composer
 pills collapse (#7231)

With 5 or more pills active the composer collapses every pill to an
icon, which hid the Bypass permissions label behind a small glyph.
Exempt the permission pill via data-keep-label so it always shows its
label, with the collapsed icons lining up to its right. Since the pill
is never icon-only now, drop the compact-mode fallthrough in the glyph
off switch so it works while the other pills are collapsed.
---
 .../src/features/chat/permission-mode-select.tsx    | 13 ++++---------
 studio/frontend/src/index.css                       |  4 +++-
 2 files changed, 7 insertions(+), 10 deletions(-)

diff --git a/studio/frontend/src/features/chat/permission-mode-select.tsx b/studio/frontend/src/features/chat/permission-mode-select.tsx
index 4277c1bfcf..a9cb8ce5d1 100644
--- a/studio/frontend/src/features/chat/permission-mode-select.tsx
+++ b/studio/frontend/src/features/chat/permission-mode-select.tsx
@@ -278,28 +278,23 @@ export function PermissionModeComposerPill({
           data-pill-label={active.label}
           data-active={fullAccess ? "true" : "false"}
           data-variant={fullAccess ? "danger" : undefined}
+          data-keep-label="true"
           aria-label="Permission level for tool calls"
           title={`${active.label}: ${active.description}`}
         >
           {/* The icon doubles as an off switch (mirrors the MCP pill): hover
               swaps it to an X; clicking it turns bypass permissions Off (no
-              prompts, sandbox on) without opening the menu. In compact
-              icon-only mode the glyph is the whole button, so clicks fall
-              through and open the menu instead. */}
+              prompts, sandbox on) without opening the menu. data-keep-label
+              exempts this pill from compact icon-only mode, so the off switch
+              stays clickable even while the other pills are collapsed. */}
           <span
             role="button"
             aria-label="Turn off bypass permissions"
             tabIndex={-1}
             onPointerDown={(e) => {
-              if (e.currentTarget.closest('[data-pill-compact="true"]')) {
-                return;
-              }
               e.stopPropagation();
             }}
             onClick={(e) => {
-              if (e.currentTarget.closest('[data-pill-compact="true"]')) {
-                return;
-              }
               e.stopPropagation();
               setPermissionMode("off");
             }}
diff --git a/studio/frontend/src/index.css b/studio/frontend/src/index.css
index 333ed70f6a..6d4c21eec8 100644
--- a/studio/frontend/src/index.css
+++ b/studio/frontend/src/index.css
@@ -1467,7 +1467,9 @@ html[data-chat-font] .aui-root {
 	}
 
 	/* With more than 4 tools on, drop pill labels to icons only to cut clutter.
-	   Compare keeps its label via data-keep-label. */
+	   Compare and the bypass-permissions pill keep their labels via
+	   data-keep-label; the permission pill sits before the collapsed icons, so
+	   they line up to its right. */
 	[data-pill-compact="true"]
 		.composer-pill-btn:not([data-keep-label])
 		> span:not(.composer-pill-glyph) {

From 4e4af72b9ce8be38155da4f84b81542cd706981b Mon Sep 17 00:00:00 2001
From: Long Yixing <longyixing331@gmail.com>
Date: Sun, 19 Jul 2026 15:27:55 +0800
Subject: [PATCH 26/28] fix(studio): honor MLX adapter state in compare mode
 (#7196)

* fix(studio): add MLX adapter state control

* fix(studio): honor MLX adapter comparison state

* fix(studio): keep enabled MLX adapters permissive

* Studio: preserve public error message on MLX compare-mode adapter failures

generate_with_adapter_control raised a plain RuntimeError, which the compare
route handled with the generic handler that drops the operational message.
Raise GenStreamErrorRaised(public=chunk.public) instead and catch it in the
streaming and non-streaming consumers, matching the safetensors tool loop, so
errors like 'model is being unloaded' surface their real message.

* Studio: re-emit VLM think prefill inside the adapter context

The compare-mode merge dropped _generate_vlm's upfront yield of the prefilled
<think> block. Restore it as the first snapshot inside the lock+adapter context
(matching _generate_text) so the UI renders the thinking block during prefill
and a cancel/error before the first token does not drop it. Adds a regression
test asserting the prefill is emitted first, after entering the adapter context.

---------

Co-authored-by: danielhanchen <unslothshared@gmail.com>
---
 .../backend/core/inference/mlx_inference.py   |  93 +++++-
 studio/backend/core/inference/orchestrator.py |  17 +-
 studio/backend/core/inference/worker.py       |  31 +-
 studio/backend/routes/inference.py            |  14 +
 .../tests/test_mlx_inference_backend.py       | 267 ++++++++++++++++--
 .../tests/test_orchestrator_unload_cancel.py  |  64 +++++
 6 files changed, 443 insertions(+), 43 deletions(-)

diff --git a/studio/backend/core/inference/mlx_inference.py b/studio/backend/core/inference/mlx_inference.py
index e7a90b4307..e78c93b6f3 100644
--- a/studio/backend/core/inference/mlx_inference.py
+++ b/studio/backend/core/inference/mlx_inference.py
@@ -8,6 +8,7 @@ instead of torch/transformers for model loading and generation.
 import json
 import os
 import threading
+from contextlib import contextmanager
 from typing import Optional, Generator
 from core.inference.message_content import content_to_text
 from core.inference.runtime_context import runtime_context_length
@@ -20,6 +21,63 @@ from loggers import get_logger
 logger = get_logger(__name__)
 
 
+def _mlx_adapter_modules(model):
+    """Return bypassable adapter entries and unsupported wrapper paths."""
+    adapters = []
+    unsupported = []
+    for path, module in model.named_modules():
+        if not path or not (hasattr(module, "lora_a") and hasattr(module, "lora_b")):
+            continue
+        base = getattr(module, "linear", None)
+        if base is None:
+            base = getattr(module, "embedding", None)
+        if base is None:
+            unsupported.append(path)
+        else:
+            adapters.append((path, module, base))
+    return adapters, unsupported
+
+
+@contextmanager
+def _temporary_mlx_adapter_state(model, use_adapter):
+    """Select base or adapter modules for one request, then restore the tree."""
+    if use_adapter is None:
+        yield
+        return
+    if isinstance(use_adapter, str):
+        raise NotImplementedError(
+            "Unsloth MLX: named adapter selection is not supported; use True for "
+            "the loaded adapter or False for the base model."
+        )
+    if use_adapter is not True and use_adapter is not False:
+        raise TypeError("Unsloth MLX: use_adapter must be None, True, False, or a string.")
+
+    adapters, unsupported = _mlx_adapter_modules(model)
+    if use_adapter is True:
+        if not adapters and not unsupported:
+            logger.warning("MLX adapter requested, but the active model has no adapter layers")
+        yield
+        return
+    if unsupported:
+        raise RuntimeError(
+            "Unsloth MLX: cannot disable adapter layers without their base modules: "
+            + ", ".join(unsupported[:5])
+        )
+    if not adapters:
+        yield
+        return
+
+    from mlx.utils import tree_unflatten
+
+    base_modules = tree_unflatten([(path, base) for path, _, base in adapters])
+    adapter_modules = tree_unflatten([(path, wrapper) for path, wrapper, _ in adapters])
+    try:
+        model.update_modules(base_modules)
+        yield
+    finally:
+        model.update_modules(adapter_modules)
+
+
 def _mlx_vlm_model_config(model):
     """Return the loaded MLX model config and its type, preferring whichever of
     config / _config actually carries a model_type."""
@@ -508,6 +566,7 @@ class MLXInferenceBackend:
         reasoning_effort = None,
         preserve_thinking = None,
         presence_penalty = 0.0,
+        _adapter_state = None,
     ) -> Generator[str, None, None]:
         if self._model is None:
             raise RuntimeError("No model loaded")
@@ -552,6 +611,7 @@ class MLXInferenceBackend:
                 reasoning_effort = reasoning_effort,
                 preserve_thinking = preserve_thinking,
                 presence_penalty = presence_penalty,
+                _adapter_state = _adapter_state,
             )
         else:
             stream = self._generate_text(
@@ -568,6 +628,7 @@ class MLXInferenceBackend:
                 reasoning_effort = reasoning_effort,
                 preserve_thinking = preserve_thinking,
                 presence_penalty = presence_penalty,
+                _adapter_state = _adapter_state,
             )
         yield from stream
 
@@ -587,6 +648,7 @@ class MLXInferenceBackend:
         reasoning_effort = None,
         preserve_thinking = None,
         presence_penalty = 0.0,
+        _adapter_state = None,
     ):
         from mlx_lm import stream_generate
         from mlx_lm.sample_utils import make_sampler, make_logits_processors
@@ -635,10 +697,6 @@ class MLXInferenceBackend:
         think_prefix = detect_think_prefill(
             prompt, getattr(self._tokenizer, "all_special_tokens", None)
         )
-        # Emit it before the first token so the block renders during prefill.
-        if think_prefix:
-            yield think_prefix
-
         sampler = make_sampler(
             temp = temperature,
             top_p = top_p,
@@ -680,9 +738,12 @@ class MLXInferenceBackend:
             type(self._model).__name__,
             type(self._tokenizer).__name__,
         )
-        with self._generation_lock:
+        with self._generation_lock, _temporary_mlx_adapter_state(self._model, _adapter_state):
             final_response = None
             try:
+                # Enter request-scoped model state before yielding any response.
+                if think_prefix:
+                    yield think_prefix
                 gen_kwargs = dict(
                     prompt = prompt,
                     max_tokens = max_new_tokens,
@@ -749,6 +810,7 @@ class MLXInferenceBackend:
         reasoning_effort = None,
         preserve_thinking = None,
         presence_penalty = 0.0,
+        _adapter_state = None,
     ):
         from mlx_vlm import stream_generate as vlm_stream
 
@@ -852,9 +914,6 @@ class MLXInferenceBackend:
 
         # Re-emit an open <think> prefill from the prompt (see _generate_text).
         cumulative = detect_think_prefill(prompt, getattr(chat_target, "all_special_tokens", None))
-        # Emit it before the first token so the block renders during prefill.
-        if cumulative:
-            yield cumulative
         logger.info(
             "VLM generating: prompt_len=%d, has_image=%s",
             len(prompt),
@@ -891,9 +950,18 @@ class MLXInferenceBackend:
 
         def _stream_vlm_snapshots():
             nonlocal cumulative
-            with self._generation_lock:
+            # Hold the generation lock AND the request-scoped adapter state for the
+            # whole stream so Base-vs-LoRA compare mode honors use_adapter and the
+            # wrapper tree is restored on completion, cancellation, or close.
+            with self._generation_lock, _temporary_mlx_adapter_state(self._model, _adapter_state):
                 final_response = None
                 try:
+                    # Emit any prefilled <think> block before the first token so the
+                    # UI renders it during prefill, matching _generate_text. Done
+                    # inside the adapter context so an unsupported request raises
+                    # before any output escapes.
+                    if cumulative:
+                        yield cumulative
                     for response in vlm_stream(
                         self._model,
                         self._processor,
@@ -927,8 +995,11 @@ class MLXInferenceBackend:
         cancel_event = None,
         **gen_kwargs,
     ) -> Generator[str, None, None]:
-        # MLX LoRA adapter toggling not yet supported; generate normally
-        yield from self.generate_chat_response(cancel_event = cancel_event, **gen_kwargs)
+        yield from self.generate_chat_response(
+            cancel_event = cancel_event,
+            _adapter_state = use_adapter,
+            **gen_kwargs,
+        )
 
     def reset_generation_state(self):
         import mlx.core as mx
diff --git a/studio/backend/core/inference/orchestrator.py b/studio/backend/core/inference/orchestrator.py
index 3afda74411..eaa474d9b8 100644
--- a/studio/backend/core/inference/orchestrator.py
+++ b/studio/backend/core/inference/orchestrator.py
@@ -1502,14 +1502,27 @@ class InferenceOrchestrator:
 
         Uses the dispatcher path (no _gen_lock) so compare-mode requests
         don't block each other; the subprocess serializes them via its
-        sequential command loop.
+        sequential command loop. Backend failures raise instead of becoming
+        assistant text.
         """
-        yield from self._generate_dispatched(
+        stream = self._generate_dispatched(
             use_adapter = use_adapter,
             cancel_event = cancel_event,
             stats_holder = stats_holder,
             **gen_kwargs,
         )
+        try:
+            for chunk in stream:
+                if isinstance(chunk, GenStreamError):
+                    # Preserve the public/operational flag so the route can surface
+                    # the real message (e.g. "model is being unloaded") instead of a
+                    # generic error. Mirrors the safetensors tool loop's _single_turn.
+                    raise GenStreamErrorRaised(str(chunk), public = chunk.public)
+                yield chunk
+        finally:
+            close = getattr(stream, "close", None)
+            if callable(close):
+                close()
 
     def _generate_inner(
         self,
diff --git a/studio/backend/core/inference/worker.py b/studio/backend/core/inference/worker.py
index e4628dcea8..9f301ba37e 100644
--- a/studio/backend/core/inference/worker.py
+++ b/studio/backend/core/inference/worker.py
@@ -513,20 +513,25 @@ def _handle_generate(backend, cmd: dict, resp_queue: Any, cancel_event) -> None:
 
         logger.info("Starting text generation for request_id=%s", request_id)
 
-        for cumulative_text in generator:
-            # cancel_event is an mp.Event — checked instantly, no queue polling.
-            if cancel_event.is_set():
-                logger.info("Generation cancelled for request %s", request_id)
-                break
+        try:
+            for cumulative_text in generator:
+                # cancel_event is an mp.Event — checked instantly, no queue polling.
+                if cancel_event.is_set():
+                    logger.info("Generation cancelled for request %s", request_id)
+                    break
 
-            _send_response(
-                resp_queue,
-                {
-                    "type": "token",
-                    "request_id": request_id,
-                    "text": cumulative_text,
-                },
-            )
+                _send_response(
+                    resp_queue,
+                    {
+                        "type": "token",
+                        "request_id": request_id,
+                        "text": cumulative_text,
+                    },
+                )
+        finally:
+            close = getattr(generator, "close", None)
+            if callable(close):
+                close()
 
         _send_response(
             resp_queue,
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index 52ea1f86a3..9299e26d56 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -9443,6 +9443,13 @@ async def openai_chat_completions(
                 backend.reset_generation_state()
                 api_monitor.finish(monitor_id, "cancelled")
                 raise
+            except GenStreamErrorRaised as exc:
+                # Adapter-controlled (compare-mode) backend failure. Honor the
+                # public flag so operational errors surface their real message.
+                backend.reset_generation_state()
+                _msg = _friendly_gen_stream_error(exc)
+                api_monitor.fail(monitor_id, _msg)
+                yield _openai_stream_error_sse({"error": {"message": _msg, "type": "server_error"}})
             except Exception as e:
                 backend.reset_generation_state()
                 logger.error(f"Error during OpenAI streaming: {e}", exc_info = True)
@@ -9591,6 +9598,13 @@ async def openai_chat_completions(
 
         except HTTPException:
             raise
+        except GenStreamErrorRaised as exc:
+            # Adapter-controlled (compare-mode) backend failure. Honor the public
+            # flag so operational errors surface their real message.
+            backend.reset_generation_state()
+            _msg = _friendly_gen_stream_error(exc)
+            api_monitor.fail(monitor_id, _msg)
+            raise HTTPException(status_code = 500, detail = _msg)
         except Exception as e:
             backend.reset_generation_state()
             logger.error(f"Error during OpenAI completion: {e}", exc_info = True)
diff --git a/studio/backend/tests/test_mlx_inference_backend.py b/studio/backend/tests/test_mlx_inference_backend.py
index fa50cd84d6..7b8aefb722 100644
--- a/studio/backend/tests/test_mlx_inference_backend.py
+++ b/studio/backend/tests/test_mlx_inference_backend.py
@@ -2,6 +2,7 @@
 
 import sys
 import types
+from contextlib import contextmanager
 from types import SimpleNamespace
 
 import pytest
@@ -40,12 +41,16 @@ class _DummyModel:
 def _install_fake_mlx(monkeypatch):
     mlx_pkg = types.ModuleType("mlx")
     mlx_core = types.ModuleType("mlx.core")
+    mlx_utils = types.ModuleType("mlx.utils")
     mlx_core.metal = _DummyMetal()
     mlx_core.set_wired_limit = _DummyMX.set_wired_limit
     mlx_core.device_info = _DummyMX.device_info
+    mlx_utils.tree_unflatten = dict
     mlx_pkg.core = mlx_core
+    mlx_pkg.utils = mlx_utils
     monkeypatch.setitem(sys.modules, "mlx", mlx_pkg)
     monkeypatch.setitem(sys.modules, "mlx.core", mlx_core)
+    monkeypatch.setitem(sys.modules, "mlx.utils", mlx_utils)
 
 
 def _install_fake_fast_mlx(monkeypatch, calls):
@@ -68,6 +73,99 @@ def _install_fake_fast_mlx(monkeypatch, calls):
     monkeypatch.setitem(sys.modules, "unsloth_zoo.mlx.loader", mlx_loader)
 
 
+class _AdapterTree:
+    def __init__(self, modules):
+        self.modules = dict(modules)
+
+    def named_modules(self):
+        return list(self.modules.items())
+
+    def update_modules(self, modules):
+        self.modules.update(modules)
+
+
+def test_temporary_mlx_adapter_state_bypasses_and_restores_wrappers(monkeypatch):
+    _install_fake_mlx(monkeypatch)
+    from core.inference.mlx_inference import _temporary_mlx_adapter_state
+
+    base = object()
+    wrapper = SimpleNamespace(lora_a = object(), lora_b = object(), linear = base, m = object())
+    model = _AdapterTree({"model.layers.0.proj": wrapper})
+
+    with pytest.raises(RuntimeError, match = "generation failed"):
+        with _temporary_mlx_adapter_state(model, False):
+            assert model.modules["model.layers.0.proj"] is base
+            raise RuntimeError("generation failed")
+    assert model.modules["model.layers.0.proj"] is wrapper
+
+
+def test_temporary_mlx_adapter_state_validates_requests():
+    from core.inference.mlx_inference import _temporary_mlx_adapter_state
+
+    wrapper = SimpleNamespace(lora_a = object(), lora_b = object(), embedding = object())
+    model = _AdapterTree({"embed_tokens": wrapper})
+    with _temporary_mlx_adapter_state(model, True):
+        assert model.modules["embed_tokens"] is wrapper
+    with pytest.raises(NotImplementedError, match = "named adapter"):
+        with _temporary_mlx_adapter_state(model, "other"):
+            pass
+
+    base_model = _AdapterTree({"proj": object()})
+    with _temporary_mlx_adapter_state(base_model, None):
+        pass
+    with _temporary_mlx_adapter_state(base_model, True):
+        pass
+
+    unsupported = _AdapterTree({"proj": SimpleNamespace(lora_a = object(), lora_b = object())})
+    with _temporary_mlx_adapter_state(unsupported, True):
+        pass
+    with pytest.raises(RuntimeError, match = "without their base modules"):
+        with _temporary_mlx_adapter_state(unsupported, False):
+            pass
+
+
+def test_temporary_mlx_adapter_state_uses_real_mlx_module_tree():
+    nn = pytest.importorskip("mlx.nn")
+    pytest.importorskip("mlx_lm")
+    from mlx_lm.models.switch_layers import SwitchLinear
+    from mlx_lm.tuner.dora import DoRALinear
+    from mlx_lm.tuner.lora import LoRAEmbedding, LoRALinear, LoRASwitchLinear
+
+    from core.inference.mlx_inference import _temporary_mlx_adapter_state
+
+    class _Layer(nn.Module):
+        def __init__(self):
+            super().__init__()
+            quantized = nn.QuantizedLinear.from_linear(nn.Linear(32, 32), group_size = 32, bits = 4)
+            self.quantized_proj = LoRALinear.from_base(quantized)
+            self.dora_proj = DoRALinear.from_base(nn.Linear(4, 4))
+
+    class _Model(nn.Module):
+        def __init__(self):
+            super().__init__()
+            self.layers = [_Layer()]
+            self.embed_tokens = LoRAEmbedding.from_base(nn.Embedding(16, 4))
+            self.experts = LoRASwitchLinear.from_base(SwitchLinear(4, 4, 2))
+
+    model = _Model()
+    wrappers = {
+        path: module
+        for path, module in model.named_modules()
+        if hasattr(module, "lora_a") and hasattr(module, "lora_b")
+    }
+    bases = {
+        path: getattr(module, "linear", getattr(module, "embedding", None))
+        for path, module in wrappers.items()
+    }
+
+    with _temporary_mlx_adapter_state(model, False):
+        live = dict(model.named_modules())
+        assert all(live[path] is base for path, base in bases.items())
+
+    restored = dict(model.named_modules())
+    assert all(restored[path] is wrapper for path, wrapper in wrappers.items())
+
+
 def test_mlx_inference_text_load_forwards_studio_settings(monkeypatch):
     _install_fake_mlx(monkeypatch)
     calls = []
@@ -333,10 +431,87 @@ def test_mlx_generate_chat_response_accepts_template_kwargs():
         ), f"{name!r} must default to None so existing callers stay valid"
 
 
+def test_mlx_vlm_reemits_think_prefill_inside_adapter_context(monkeypatch):
+    """A prefilled <think> block must be re-emitted as the first VLM snapshot,
+    inside the adapter context (so unsupported requests still raise first), so
+    the UI renders the thinking block during prefill and a pre-first-token
+    cancel does not drop it. Mirrors _generate_text."""
+    from core.inference import mlx_inference
+
+    MLXInferenceBackend = mlx_inference.MLXInferenceBackend
+
+    order = []
+
+    @contextmanager
+    def _adapter_state(_model, state):
+        assert backend._generation_lock.locked()
+        order.append("adapter_enter")
+        try:
+            yield
+        finally:
+            order.append("adapter_exit")
+
+    monkeypatch.setattr(mlx_inference, "_temporary_mlx_adapter_state", _adapter_state)
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.detect_think_prefill",
+        lambda *_a, **_k: "<think>\n",
+    )
+
+    prompt_utils = SimpleNamespace(
+        MODEL_CONFIG = {"deepseek_vl_v2": object()},
+        apply_chat_template = lambda *_a, **_k: "<image> model-aware",
+    )
+    mlx_vlm = types.ModuleType("mlx_vlm")
+    mlx_vlm.prompt_utils = prompt_utils
+
+    def _vlm_stream(*_a, **_k):
+        # The prefill must have been emitted before any generated token.
+        assert order[-1] == "adapter_enter"
+        yield SimpleNamespace(text = "ok", prompt_tokens = 3, generation_tokens = 1)
+
+    mlx_vlm.stream_generate = _vlm_stream
+    monkeypatch.setitem(sys.modules, "mlx_vlm", mlx_vlm)
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.apply_chat_template_for_generation",
+        lambda _t, _m, **_k: "<image> model-aware",
+    )
+
+    backend = MLXInferenceBackend()
+    backend._model = SimpleNamespace(config = {"model_type": "deepseek_vl_v2"})
+    backend._processor = SimpleNamespace(tokenizer = SimpleNamespace())
+    args = ([{"role": "user", "content": [{"type": "image"}]}], object(), 0, 1, 0, 0, 1, 1, None)
+
+    gen = backend._generate_vlm(*args, _adapter_state = False)
+    # First snapshot is the prefill alone, emitted after entering the adapter context.
+    assert next(gen) == "<think>\n"
+    assert order == ["adapter_enter"]
+    # Subsequent snapshots are cumulative (prefill + generated text).
+    assert next(gen) == "<think>\nok"
+    gen.close()
+    assert order == ["adapter_enter", "adapter_exit"]
+
+
 def test_mlx_vlm_generation_selects_renderer_by_capability(monkeypatch):
-    from core.inference.mlx_inference import MLXInferenceBackend
+    from core.inference import mlx_inference
+
+    MLXInferenceBackend = mlx_inference.MLXInferenceBackend
 
     calls = {"generic": [], "model": [], "stream": []}
+    adapter_events = []
+    adapter_active = {"value": False}
+
+    @contextmanager
+    def _adapter_state(_model, state):
+        assert backend._generation_lock.locked()
+        adapter_events.append(("enter", state))
+        adapter_active["value"] = True
+        try:
+            yield
+        finally:
+            adapter_active["value"] = False
+            adapter_events.append(("exit", state))
+
+    monkeypatch.setattr(mlx_inference, "_temporary_mlx_adapter_state", _adapter_state)
     state = {"generic": "serialized", "model": "<image> model-aware"}
     prompt_utils = SimpleNamespace(
         MODEL_CONFIG = {"deepseek_vl_v2": object()},
@@ -346,10 +521,13 @@ def test_mlx_vlm_generation_selects_renderer_by_capability(monkeypatch):
     )
     mlx_vlm = types.ModuleType("mlx_vlm")
     mlx_vlm.prompt_utils = prompt_utils
-    mlx_vlm.stream_generate = lambda *_args, **kwargs: (
-        calls["stream"].append((_args, kwargs))
-        or iter([SimpleNamespace(text = "ok", prompt_tokens = 3, generation_tokens = 1)])
-    )
+
+    def _vlm_stream(*args, **kwargs):
+        assert adapter_active["value"]
+        calls["stream"].append((args, kwargs))
+        yield SimpleNamespace(text = "ok", prompt_tokens = 3, generation_tokens = 1)
+
+    mlx_vlm.stream_generate = _vlm_stream
     monkeypatch.setitem(sys.modules, "mlx_vlm", mlx_vlm)
 
     def generic(_target, _messages, **kwargs):
@@ -369,7 +547,11 @@ def test_mlx_vlm_generation_selects_renderer_by_capability(monkeypatch):
     backend._processor = SimpleNamespace(tokenizer = SimpleNamespace())
     args = ([{"role": "user", "content": [{"type": "image"}]}], object(), 0, 1, 0, 0, 1, 1, None)
     tools = [{"function": {"name": "search"}}]
-    assert list(backend._generate_vlm(*args)) == ["ok"]
+    generator = backend._generate_vlm(*args, _adapter_state = False)
+    assert next(generator) == "ok"
+    assert adapter_active["value"] and backend._generation_lock.locked()
+    generator.close()
+    assert adapter_events == [("enter", False), ("exit", False)]
     assert calls["model"][0]["num_images"] == 1
     assert calls["stream"][0][0][2] == "<image> model-aware"
     with pytest.raises(RuntimeError, match = "dropping requested tools"):
@@ -449,7 +631,10 @@ def test_mlx_generate_text_forwards_kwargs_into_template_helper(monkeypatch):
     """Mac text path must route through apply_chat_template_for_generation so
     reasoning / tool kwargs reach the tokenizer."""
     _install_fake_mlx(monkeypatch)
-    from core.inference.mlx_inference import MLXInferenceBackend
+    from core.inference import mlx_inference
+
+    MLXInferenceBackend = mlx_inference.MLXInferenceBackend
+    real_adapter_state = mlx_inference._temporary_mlx_adapter_state
 
     # The text path renders once with tools, then the native-template fallback makes a second no-
     # tools probe call (tools=None) to detect whether the template dropped the schema.
@@ -474,11 +659,31 @@ def test_mlx_generate_text_forwards_kwargs_into_template_helper(monkeypatch):
     mlx_lm_sample.make_sampler = lambda **_kw: object()
     mlx_lm_sample.make_logits_processors = lambda **_kw: None
 
+    adapter_events = []
+    adapter_active = {"value": False}
+    stream_state = {"fail": False}
+
+    @contextmanager
+    def _adapter_state(_model, state):
+        assert backend._generation_lock.locked()
+        adapter_events.append(("enter", state))
+        adapter_active["value"] = True
+        try:
+            yield
+        finally:
+            adapter_active["value"] = False
+            adapter_events.append(("exit", state))
+
+    monkeypatch.setattr(mlx_inference, "_temporary_mlx_adapter_state", _adapter_state)
+
     class _Resp:
         def __init__(self, tok):
             self.token = tok
 
     def _stream_generate(_model, _tokenizer, **_kw):
+        assert adapter_active["value"]
+        if stream_state["fail"]:
+            raise RuntimeError("generation failed")
         yield _Resp(1)
 
     mlx_lm_pkg.stream_generate = _stream_generate
@@ -500,17 +705,45 @@ def test_mlx_generate_text_forwards_kwargs_into_template_helper(monkeypatch):
     backend._tokenizer = _Tok()
     backend._is_vlm = False
 
-    out = list(
-        backend.generate_chat_response(
-            messages = [{"role": "user", "content": "ping"}],
-            tools = [{"function": {"name": "web_search"}}],
-            enable_thinking = True,
-            reasoning_effort = "medium",
-            preserve_thinking = True,
-            max_new_tokens = 1,
-        )
+    generator = backend.generate_with_adapter_control(
+        use_adapter = False,
+        messages = [{"role": "user", "content": "ping"}],
+        tools = [{"function": {"name": "web_search"}}],
+        enable_thinking = True,
+        reasoning_effort = "medium",
+        preserve_thinking = True,
+        max_new_tokens = 1,
     )
-    assert out == ["hi"]
+    assert next(generator) == "hi"
+    assert adapter_active["value"] and backend._generation_lock.locked()
+    generator.close()
+    assert adapter_events == [("enter", False), ("exit", False)]
+    stream_state["fail"] = True
+    with pytest.raises(RuntimeError, match = "generation failed"):
+        list(
+            backend.generate_with_adapter_control(
+                use_adapter = False,
+                messages = [{"role": "user", "content": "ping"}],
+                max_new_tokens = 1,
+            )
+        )
+    assert adapter_events[-2:] == [("enter", False), ("exit", False)]
+    assert not backend._generation_lock.locked()
+
+    monkeypatch.setattr(mlx_inference, "_temporary_mlx_adapter_state", real_adapter_state)
+    monkeypatch.setattr(
+        "core.inference.chat_template_helpers.detect_think_prefill",
+        lambda *_args, **_kwargs: "<think>",
+    )
+    stream_state["fail"] = False
+    named = backend.generate_with_adapter_control(
+        use_adapter = "named",
+        messages = [{"role": "user", "content": "ping"}],
+        max_new_tokens = 1,
+    )
+    with pytest.raises(NotImplementedError, match = "named adapter"):
+        next(named)
+    assert not adapter_active["value"] and not backend._generation_lock.locked()
     # The toggled kwargs must reach the chat-template helper on the real render
     # (one of the calls carries the tools; the fallback probe passes tools=None).
     tool_renders = [
diff --git a/studio/backend/tests/test_orchestrator_unload_cancel.py b/studio/backend/tests/test_orchestrator_unload_cancel.py
index fb80b6d061..3a36500aee 100644
--- a/studio/backend/tests/test_orchestrator_unload_cancel.py
+++ b/studio/backend/tests/test_orchestrator_unload_cancel.py
@@ -34,6 +34,70 @@ def _bare_orchestrator():
     return o
 
 
+def test_adapter_control_raises_stream_errors(monkeypatch):
+    o = _bare_orchestrator()
+    monkeypatch.setattr(
+        o,
+        "_generate_dispatched",
+        lambda **_kwargs: iter([orch_mod.GenStreamError("Error: adapter failed")]),
+    )
+
+    with pytest.raises(RuntimeError, match = "adapter failed"):
+        list(o.generate_with_adapter_control(use_adapter = False))
+
+    closed = []
+
+    def _stream(**_kwargs):
+        try:
+            yield "token"
+            yield "late token"
+        finally:
+            closed.append(True)
+
+    monkeypatch.setattr(o, "_generate_dispatched", _stream)
+    generator = o.generate_with_adapter_control(use_adapter = False)
+    assert next(generator) == "token"
+    generator.close()
+    assert closed == [True]
+
+
+def test_worker_closes_cancelled_generator_before_gen_done():
+    from core.inference.worker import _handle_generate
+
+    events = []
+
+    class _Backend:
+        last_generation_stats = None
+
+        def generate_with_adapter_control(self, **_kwargs):
+            try:
+                yield "token"
+                yield "late token"
+            finally:
+                events.append("closed")
+
+    class _Responses:
+        def __init__(self):
+            self.items = []
+
+        def put(self, item):
+            if item["type"] == "gen_done":
+                assert events == ["closed"]
+            self.items.append(item)
+
+    responses = _Responses()
+    cancel = threading.Event()
+    cancel.set()
+    _handle_generate(
+        _Backend(),
+        {"request_id": "r1", "messages": [], "use_adapter": False},
+        responses,
+        cancel,
+    )
+
+    assert [item["type"] for item in responses.items] == ["gen_done"]
+
+
 def test_unload_cancels_inflight_generation_then_unloads(monkeypatch):
     o = _bare_orchestrator()
     monkeypatch.setattr(o, "_ensure_subprocess_alive", lambda: True)

From 030524ae8edd056fc37fc03190362d6fc59a0392 Mon Sep 17 00:00:00 2001
From: Daniel Han <danielhanchen@gmail.com>
Date: Sun, 19 Jul 2026 00:34:13 -0700
Subject: [PATCH 27/28] security: refresh the fastapi C2-loop baseline entry
 for the current release (#7223)

The pip scan-packages studio shard is red on main and on every open PR:
the baselined fastapi finding (the benign SSE keepalive `while True:`
loop in fastapi/routing.py, reviewed and suppressed long ago) records
its evidence at L586 with the span digest of the fastapi release current
at baseline time. The latest fastapi shifts that loop to L587 and its
span digest with it, so the evidence hash no longer matches and the
scanner reports the finding as new, failing the shard with one
unsuppressed CRITICAL.

Re-reviewed the flagged code in the current release before refreshing:
L587 is the same keepalive loop inside the streaming response machinery,
not a beacon. Only the one entry's evidence and evidence_hash change.

Verified with the scanner itself: `scan_packages.py fastapi
--no-baseline` reproduces the exact CI evidence string, and with the
updated baseline the same scan exits 0 with the finding suppressed as
1 CRITICAL baselined.
---
 scripts/scan_packages_baseline.json | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/scripts/scan_packages_baseline.json b/scripts/scan_packages_baseline.json
index 929cc37bda..1f7bc8dcc0 100644
--- a/scripts/scan_packages_baseline.json
+++ b/scripts/scan_packages_baseline.json
@@ -95,8 +95,8 @@
       "file": "fastapi/routing.py",
       "check": "C2 polling/beaconing loop detected",
       "severity": "CRITICAL",
-      "evidence": "L586:                                 while True: sha256:251135b5ebfdd1248916449f32262575e003ef64382501c65b7e4061d67bda45",
-      "evidence_hash": "365aef4449c8089753d9398417cd76ab762cef547d75db70d87bca9c0b550ab5"
+      "evidence": "L587:                                 while True: sha256:06c2c7f15d73bf192e5e3272c5ff5fcaeff7f6774fef5f4eca6ef473ae50e2b3",
+      "evidence_hash": "57acd497f404c203e4450d0580ad85aa8a33406e8d64ad06fbac6cf47d97b24d"
     },
     {
       "package": "fastmcp-slim",

From e9ef2ac60f35d8e980460763e09027e477064a38 Mon Sep 17 00:00:00 2001
From: Nilay <118994073+NilayYadav@users.noreply.github.com>
Date: Sun, 19 Jul 2026 13:04:56 +0530
Subject: [PATCH 28/28] Studio: enforce 60s minimum on idle auto-unload TTL (0
 stays off) (#7185)

* Studio: enforce 60s minimum on idle auto-unload TTL (0 stays off)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Drop decorative section separator from idle TTL floor tests

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
---
 .../backend/tests/test_openai_auto_switch.py  | 54 ++++++++++++++++++-
 .../utils/openai_auto_switch_settings.py      | 49 ++++++++++++++---
 .../components/model-auto-switch-section.tsx  | 10 +++-
 studio/frontend/src/i18n/locales/ar.ts        |  4 +-
 studio/frontend/src/i18n/locales/de.ts        |  4 +-
 studio/frontend/src/i18n/locales/en.ts        |  4 +-
 studio/frontend/src/i18n/locales/es.ts        |  4 +-
 studio/frontend/src/i18n/locales/fr.ts        |  4 +-
 studio/frontend/src/i18n/locales/hi.ts        |  4 +-
 studio/frontend/src/i18n/locales/ja.ts        |  4 +-
 studio/frontend/src/i18n/locales/ko.ts        |  4 +-
 studio/frontend/src/i18n/locales/pt-br.ts     |  4 +-
 studio/frontend/src/i18n/locales/ru.ts        |  4 +-
 studio/frontend/src/i18n/locales/zh-CN.ts     |  4 +-
 14 files changed, 125 insertions(+), 32 deletions(-)

diff --git a/studio/backend/tests/test_openai_auto_switch.py b/studio/backend/tests/test_openai_auto_switch.py
index d02a2a4f7e..8742b84ae7 100644
--- a/studio/backend/tests/test_openai_auto_switch.py
+++ b/studio/backend/tests/test_openai_auto_switch.py
@@ -1609,11 +1609,11 @@ def test_env_idle_ttl_standalone_when_no_stored_value(monkeypatch):
 def test_stored_idle_value_overrides_env_and_stays_gated(monkeypatch):
     # An explicit stored value wins over the env default and remains gated on the
     # auto-switch toggle.
-    store = {settings.AUTO_UNLOAD_IDLE_SETTING_KEY: 30}
+    store = {settings.AUTO_UNLOAD_IDLE_SETTING_KEY: 90}
     monkeypatch.setattr(settings, "_cached_setting", lambda k, d = None: store.get(k, d))
     monkeypatch.setenv("UNSLOTH_MODEL_IDLE_TTL", "600")
     monkeypatch.setattr(settings, "get_openai_auto_switch_enabled", lambda: True)
-    assert settings.get_auto_unload_idle_seconds() == 30  # stored wins, not env
+    assert settings.get_auto_unload_idle_seconds() == 90  # stored wins, not env
     monkeypatch.setattr(settings, "get_openai_auto_switch_enabled", lambda: False)
     assert settings.get_auto_unload_idle_seconds() == 0  # explicit value still gated off
 
@@ -3094,3 +3094,53 @@ def test_responses_stream_hint_matches_toggle_regardless_of_active_model(monkeyp
         monkeypatch, enabled = False, active_model_name = "unsloth/Llama-3.2-1B-Instruct"
     )
     assert "Model auto-switch" in non_gguf_loaded
+
+
+def test_setter_rejects_idle_below_floor(monkeypatch):
+    import storage.studio_db as db
+
+    writes = []
+    monkeypatch.setattr(db, "upsert_app_settings", lambda m: writes.append(dict(m)))
+    settings._cache.clear()
+
+    with pytest.raises(ValueError, match = "at least 60"):
+        settings.set_openai_auto_switch(True, 30)
+    assert writes == []  # rejected before any persist
+    # 0 (off) and >= 60 pass through unchanged.
+    assert settings.set_openai_auto_switch(True, 0)[1] == 0
+    assert settings.set_openai_auto_switch(True, 60)[1] == 60
+    assert settings.set_openai_auto_switch(True, 3600)[1] == 3600
+
+
+def test_put_route_rejects_idle_below_floor():
+    import routes.settings as settings_route
+    from fastapi import HTTPException
+
+    payload = settings_route.OpenAIAutoSwitchPayload(enabled = True, auto_unload_idle_seconds = 30)
+    with pytest.raises(HTTPException) as excinfo:
+        settings_route.update_openai_auto_switch(payload, "tester")
+    assert excinfo.value.status_code == 400
+
+
+def test_stored_legacy_idle_below_floor_is_clamped(monkeypatch):
+    # Values persisted before the floor existed are raised to it on read, for
+    # both the effective TTL and the value the settings UI displays.
+    store = {settings.AUTO_UNLOAD_IDLE_SETTING_KEY: 5}
+    monkeypatch.setattr(settings, "_cached_setting", lambda k, d = None: store.get(k, d))
+    monkeypatch.setattr(settings, "get_openai_auto_switch_enabled", lambda: True)
+    assert settings.get_auto_unload_idle_seconds() == 60
+    assert settings.get_stored_auto_unload_idle_seconds() == 60
+    store[settings.AUTO_UNLOAD_IDLE_SETTING_KEY] = 90
+    assert settings.get_auto_unload_idle_seconds() == 90
+
+
+def test_env_idle_below_floor_is_clamped(monkeypatch):
+    monkeypatch.setattr(settings, "_cached_setting", lambda k, d = None: d)
+    monkeypatch.setenv(settings.MODEL_IDLE_TTL_ENV_VAR, "5")
+    assert settings.get_auto_unload_idle_seconds() == 60
+    monkeypatch.setenv(settings.MODEL_IDLE_TTL_ENV_VAR, "0")
+    assert settings.get_auto_unload_idle_seconds() == 0
+    monkeypatch.setenv(settings.MODEL_IDLE_TTL_ENV_VAR, "600")
+    assert settings.get_auto_unload_idle_seconds() == 600
+    monkeypatch.delenv(settings.MODEL_IDLE_TTL_ENV_VAR)
+    assert settings.get_auto_unload_idle_seconds() == 0
diff --git a/studio/backend/utils/openai_auto_switch_settings.py b/studio/backend/utils/openai_auto_switch_settings.py
index 1689395f40..462435e5d5 100644
--- a/studio/backend/utils/openai_auto_switch_settings.py
+++ b/studio/backend/utils/openai_auto_switch_settings.py
@@ -8,7 +8,9 @@ Two settings, both off by default so existing API behavior is unchanged:
   names a downloaded local GGUF different from the loaded one transparently
   loads it before serving (llama-swap-style). Unknown names pass through.
 - ``openai_api_auto_unload_idle_seconds``: when > 0, the loaded GGUF is
-  unloaded after this many idle seconds to free VRAM.
+  unloaded after this many idle seconds to free VRAM. Enabled values have a
+  60s floor (0 stays "off"): a tiny TTL tears the model down between turns of
+  an active chat, forcing a full weight reload + prompt re-prefill per turn.
 
 The idle TTL can also be set at startup via the ``UNSLOTH_MODEL_IDLE_TTL`` env
 var. Unlike the stored setting (which stays gated on auto-switch), the env value
@@ -33,6 +35,7 @@ MODEL_IDLE_TTL_ENV_VAR = "UNSLOTH_MODEL_IDLE_TTL"
 
 DEFAULT_OPENAI_AUTO_SWITCH_ENABLED = False
 DEFAULT_AUTO_UNLOAD_IDLE_SECONDS = 0
+MIN_AUTO_UNLOAD_IDLE_SECONDS = 60
 
 _CACHE_TTL_S = 2.0
 _cache_lock = threading.Lock()
@@ -58,6 +61,10 @@ def _coerce_int(value: Any) -> int | None:
         return None
 
 
+def _apply_idle_floor(seconds: int) -> int:
+    return 0 if seconds <= 0 else max(MIN_AUTO_UNLOAD_IDLE_SECONDS, seconds)
+
+
 def _cached_setting(key: str, default: Any) -> Any:
     """Read an app setting, memoized for _CACHE_TTL_S to spare the hot path."""
     now = time.monotonic()
@@ -91,12 +98,34 @@ def _stored_idle_seconds() -> Optional[int]:
     return _coerce_int(_cached_setting(AUTO_UNLOAD_IDLE_SETTING_KEY, None))
 
 
+_env_floor_warned = False
+
+
 def _env_idle_seconds() -> Optional[int]:
-    """UNSLOTH_MODEL_IDLE_TTL as a non-negative seconds value, or None if unset/invalid."""
+    """UNSLOTH_MODEL_IDLE_TTL as a non-negative seconds value, or None if unset/invalid.
+
+    Floored to MIN_AUTO_UNLOAD_IDLE_SECONDS here (with a one-time warning) since
+    headless/container deploys have no UI to surface a validation error."""
     raw = os.environ.get(MODEL_IDLE_TTL_ENV_VAR)
     if raw is None or not raw.strip():
         return None
-    return _coerce_int(raw)
+    parsed = _coerce_int(raw)
+    if parsed is None:
+        return None
+    floored = _apply_idle_floor(parsed)
+    if floored != parsed:
+        global _env_floor_warned
+        if not _env_floor_warned:
+            _env_floor_warned = True
+            from loggers import get_logger
+            get_logger(__name__).warning(
+                "%s=%s is below the %ss minimum; using %ss",
+                MODEL_IDLE_TTL_ENV_VAR,
+                parsed,
+                MIN_AUTO_UNLOAD_IDLE_SECONDS,
+                floored,
+            )
+    return floored
 
 
 def get_stored_auto_unload_idle_seconds() -> int:
@@ -108,7 +137,9 @@ def get_stored_auto_unload_idle_seconds() -> int:
     """
     stored = _stored_idle_seconds()
     if stored is not None:
-        return stored
+        # Floor legacy values persisted before the minimum existed, so the UI
+        # displays the effective TTL and round-trips it cleanly.
+        return _apply_idle_floor(stored)
     env = _env_idle_seconds()
     return env if env is not None else DEFAULT_AUTO_UNLOAD_IDLE_SECONDS
 
@@ -118,8 +149,9 @@ def get_auto_unload_idle_seconds() -> int:
     stored = _stored_idle_seconds()
     if stored is not None:
         # An explicit UI/API value stays gated on auto-switch: off reports 0 so the
-        # off state is identical to pre-feature.
-        return stored if get_openai_auto_switch_enabled() else 0
+        # off state is identical to pre-feature. Floored to cover values persisted
+        # before the minimum existed.
+        return _apply_idle_floor(stored) if get_openai_auto_switch_enabled() else 0
     # No stored value: UNSLOTH_MODEL_IDLE_TTL is a standalone startup default that
     # enables idle-unload even with auto-switch off (headless/container deploys).
     env = _env_idle_seconds()
@@ -136,6 +168,11 @@ def set_openai_auto_switch(enabled: Any, idle_seconds: Any) -> tuple[bool, int]:
     parsed_idle = _coerce_int(idle_seconds)
     if parsed_idle is None:
         raise ValueError("Auto-unload idle seconds must be a non-negative integer.")
+    if 0 < parsed_idle < MIN_AUTO_UNLOAD_IDLE_SECONDS:
+        raise ValueError(
+            f"Auto-unload idle seconds must be 0 (off) or at least "
+            f"{MIN_AUTO_UNLOAD_IDLE_SECONDS}."
+        )
     from storage.studio_db import upsert_app_settings
 
     upsert_app_settings(
diff --git a/studio/frontend/src/features/settings/components/model-auto-switch-section.tsx b/studio/frontend/src/features/settings/components/model-auto-switch-section.tsx
index 5bebefa84c..32b3e53a2c 100644
--- a/studio/frontend/src/features/settings/components/model-auto-switch-section.tsx
+++ b/studio/frontend/src/features/settings/components/model-auto-switch-section.tsx
@@ -14,6 +14,9 @@ import {
 import { SettingsRow } from "./settings-row";
 import { SettingsSection } from "./settings-section";
 
+// Mirrors MIN_AUTO_UNLOAD_IDLE_SECONDS in the backend settings store.
+const MIN_IDLE_SECONDS = 60;
+
 export function ModelAutoSwitchSection() {
   const t = useT();
   const [settings, setSettings] = useState<OpenAIAutoSwitchSettings | null>(
@@ -45,13 +48,16 @@ export function ModelAutoSwitchSection() {
     };
   }, [t]);
 
-  // Parse the idle-seconds draft to a non-negative integer; empty/invalid -> null.
+  // Parse the idle-seconds draft: 0 (off) or >= MIN_IDLE_SECONDS; else null.
   const parseIdleSeconds = (): number | null => {
     if (!draftIdleSeconds.trim()) {
       return null;
     }
     const parsed = Number(draftIdleSeconds);
-    return Number.isInteger(parsed) && parsed >= 0 ? parsed : null;
+    if (!Number.isInteger(parsed)) {
+      return null;
+    }
+    return parsed === 0 || parsed >= MIN_IDLE_SECONDS ? parsed : null;
   };
 
   const persist = async (
diff --git a/studio/frontend/src/i18n/locales/ar.ts b/studio/frontend/src/i18n/locales/ar.ts
index 28f404a384..744a2002c9 100644
--- a/studio/frontend/src/i18n/locales/ar.ts
+++ b/studio/frontend/src/i18n/locales/ar.ts
@@ -155,14 +155,14 @@ export const ar = {
           "عندما يسمّي طلب متوافق مع OpenAI ملف GGUF مُنزّلاً مختلفًا، يتم تحميله قبل الخدمة. مُعطّل افتراضيًا؛ الأسماء غير المعروفة تُبقي على النموذج المُحمَّل.",
         idleUnload: "الإلغاء التلقائي عند الخمول",
         idleUnloadDescription:
-          "إلغاء تحميل النموذج بعد هذا العدد من ثواني الخمول لتحرير الـ VRAM؛ الطلب التالي يعيد تحميله. القيمة 0 تُبقيه محمَّلاً.",
+          "إلغاء تحميل النموذج بعد هذا العدد من ثواني الخمول لتحرير الـ VRAM؛ الطلب التالي يعيد تحميله. القيمة 0 تُبقيه محمَّلاً. الحد الأدنى 60 ثانية.",
         idleNeedsEnable:
           "فعّل تبديل النموذج حسب الطلب حتى يعاد تحميل النموذج غير المحمَّل عند الاستخدام التالي.",
         idleActiveViaEnv:
           "الإلغاء التلقائي عند الخمول مُفعَّل عبر متغير البيئة UNSLOTH_MODEL_IDLE_TTL.",
         loadError: "فشل تحميل إعدادات التبديل التلقائي للنموذج.",
         saveError: "فشل حفظ إعدادات التبديل التلقائي للنموذج.",
-        idleError: "أدخل عددًا صحيحًا من الثواني (0 أو أكثر).",
+        idleError: "أدخل 0 لإبقاء النموذج محمَّلاً، أو 60 ثانية على الأقل.",
       },
       previewSharing: {
         sectionTitle: "مشاركة المعاينة",
diff --git a/studio/frontend/src/i18n/locales/de.ts b/studio/frontend/src/i18n/locales/de.ts
index e38cdbfa0e..7d94e7656e 100644
--- a/studio/frontend/src/i18n/locales/de.ts
+++ b/studio/frontend/src/i18n/locales/de.ts
@@ -158,7 +158,7 @@ export const de = {
           "Wenn eine OpenAI-kompatible Anfrage ein anderes heruntergeladenes GGUF nennt, wird dieses vor der Auslieferung geladen. Standardmäßig aus; unbekannte Namen liefern weiterhin das geladene Modell aus.",
         idleUnload: "Automatisches Entladen bei Inaktivität",
         idleUnloadDescription:
-          "Entlädt das Modell nach dieser Anzahl inaktiver Sekunden, um VRAM freizugeben; die nächste Anfrage lädt es erneut. 0 hält es geladen.",
+          "Entlädt das Modell nach dieser Anzahl inaktiver Sekunden, um VRAM freizugeben; die nächste Anfrage lädt es erneut. 0 hält es geladen. Minimum 60 Sekunden.",
         idleNeedsEnable:
           "Aktivieren Sie \"Modell je Anfrage wechseln\", damit ein entladenes Modell bei der nächsten Nutzung erneut geladen wird.",
         idleActiveViaEnv:
@@ -167,7 +167,7 @@ export const de = {
           "Einstellungen für automatischen Modellwechsel konnten nicht geladen werden.",
         saveError:
           "Einstellungen für automatischen Modellwechsel konnten nicht gespeichert werden.",
-        idleError: "Geben Sie eine ganze Anzahl an Sekunden ein (0 oder mehr).",
+        idleError: "Geben Sie 0 ein, um das Modell geladen zu halten, oder mindestens 60 Sekunden.",
       },
       previewSharing: {
         sectionTitle: "Vorschau-Freigabe",
diff --git a/studio/frontend/src/i18n/locales/en.ts b/studio/frontend/src/i18n/locales/en.ts
index fe3a6f8542..de8ac17c29 100644
--- a/studio/frontend/src/i18n/locales/en.ts
+++ b/studio/frontend/src/i18n/locales/en.ts
@@ -224,14 +224,14 @@ export const en = {
           "When an OpenAI-compatible request names a different downloaded GGUF, load it before serving. Off by default; unknown names keep serving the loaded model.",
         idleUnload: "Idle auto-unload",
         idleUnloadDescription:
-          "Unload the model after this many idle seconds to free VRAM; the next request reloads it. 0 keeps it loaded.",
+          "Unload the model after this many idle seconds to free VRAM; the next request reloads it. 0 keeps it loaded. Minimum 60 seconds.",
         idleNeedsEnable:
           "Turn on Switch model by request so an unloaded model reloads on next use.",
         idleActiveViaEnv:
           "Idle auto-unload is active via the UNSLOTH_MODEL_IDLE_TTL environment variable.",
         loadError: "Failed to load model auto-switch settings.",
         saveError: "Failed to save model auto-switch settings.",
-        idleError: "Enter a whole number of seconds (0 or more).",
+        idleError: "Enter 0 to keep the model loaded, or at least 60 seconds.",
       },
       previewSharing: {
         sectionTitle: "Preview sharing",
diff --git a/studio/frontend/src/i18n/locales/es.ts b/studio/frontend/src/i18n/locales/es.ts
index e5f9650bef..988c109a3f 100644
--- a/studio/frontend/src/i18n/locales/es.ts
+++ b/studio/frontend/src/i18n/locales/es.ts
@@ -157,7 +157,7 @@ export const es = {
           "Cuando una solicitud compatible con OpenAI nombra un GGUF descargado distinto, se carga antes de responder. Desactivado por defecto; los nombres desconocidos siguen usando el modelo cargado.",
         idleUnload: "Descarga automática por inactividad",
         idleUnloadDescription:
-          "Descarga el modelo tras este número de segundos inactivo para liberar VRAM; la siguiente solicitud lo recarga. 0 lo mantiene cargado.",
+          "Descarga el modelo tras este número de segundos inactivo para liberar VRAM; la siguiente solicitud lo recarga. 0 lo mantiene cargado. Mínimo 60 segundos.",
         idleNeedsEnable:
           "Activa Cambiar de modelo según la solicitud para que un modelo descargado se recargue en el próximo uso.",
         idleActiveViaEnv:
@@ -166,7 +166,7 @@ export const es = {
           "No se pudo cargar la configuración de cambio automático de modelo.",
         saveError:
           "No se pudo guardar la configuración de cambio automático de modelo.",
-        idleError: "Introduce un número entero de segundos (0 o más).",
+        idleError: "Introduce 0 para mantener el modelo cargado, o al menos 60 segundos.",
       },
       previewSharing: {
         sectionTitle: "Compartir vista previa",
diff --git a/studio/frontend/src/i18n/locales/fr.ts b/studio/frontend/src/i18n/locales/fr.ts
index 190284175d..e1f2a0c5ec 100644
--- a/studio/frontend/src/i18n/locales/fr.ts
+++ b/studio/frontend/src/i18n/locales/fr.ts
@@ -157,7 +157,7 @@ export const fr = {
           "Lorsqu'une requête compatible OpenAI nomme un autre GGUF téléchargé, le charger avant de répondre. Désactivé par défaut ; les noms inconnus continuent de servir le modèle chargé.",
         idleUnload: "Déchargement automatique en cas d'inactivité",
         idleUnloadDescription:
-          "Décharger le modèle après ce nombre de secondes d'inactivité pour libérer la VRAM ; la requête suivante le recharge. 0 le maintient chargé.",
+          "Décharger le modèle après ce nombre de secondes d'inactivité pour libérer la VRAM ; la requête suivante le recharge. 0 le maintient chargé. Minimum 60 secondes.",
         idleNeedsEnable:
           "Activez Changer de modèle par requête pour qu'un modèle déchargé se recharge à la prochaine utilisation.",
         idleActiveViaEnv:
@@ -166,7 +166,7 @@ export const fr = {
           "Échec du chargement des paramètres de changement automatique de modèle.",
         saveError:
           "Échec de l'enregistrement des paramètres de changement automatique de modèle.",
-        idleError: "Saisissez un nombre entier de secondes (0 ou plus).",
+        idleError: "Saisissez 0 pour garder le modèle chargé, ou au moins 60 secondes.",
       },
       previewSharing: {
         sectionTitle: "Partage de l'aperçu",
diff --git a/studio/frontend/src/i18n/locales/hi.ts b/studio/frontend/src/i18n/locales/hi.ts
index 97f55251c5..77b6265e7b 100644
--- a/studio/frontend/src/i18n/locales/hi.ts
+++ b/studio/frontend/src/i18n/locales/hi.ts
@@ -154,14 +154,14 @@ export const hi = {
           "जब कोई OpenAI-संगत अनुरोध किसी अन्य डाउनलोड किए गए GGUF का नाम लेता है, तो सर्व करने से पहले उसे लोड करें। डिफ़ॉल्ट रूप से बंद; अज्ञात नाम लोड किए गए मॉडल को सर्व करते रहते हैं।",
         idleUnload: "निष्क्रिय ऑटो-अनलोड",
         idleUnloadDescription:
-          "VRAM मुक्त करने के लिए इतने निष्क्रिय सेकंड के बाद मॉडल को अनलोड करें; अगला अनुरोध इसे फिर से लोड करता है। 0 इसे लोड रखता है।",
+          "VRAM मुक्त करने के लिए इतने निष्क्रिय सेकंड के बाद मॉडल को अनलोड करें; अगला अनुरोध इसे फिर से लोड करता है। 0 इसे लोड रखता है। न्यूनतम 60 सेकंड।",
         idleNeedsEnable:
           "अनुरोध के अनुसार मॉडल बदलें चालू करें ताकि अनलोड किया गया मॉडल अगले उपयोग पर फिर से लोड हो।",
         idleActiveViaEnv:
           "निष्क्रिय ऑटो-अनलोड UNSLOTH_MODEL_IDLE_TTL एनवायरनमेंट वेरिएबल के माध्यम से सक्रिय है।",
         loadError: "मॉडल ऑटो-स्विच सेटिंग्स लोड करने में विफल।",
         saveError: "मॉडल ऑटो-स्विच सेटिंग्स सहेजने में विफल।",
-        idleError: "सेकंड की पूरी संख्या दर्ज करें (0 या अधिक)।",
+        idleError: "मॉडल को लोड रखने के लिए 0 दर्ज करें, या कम से कम 60 सेकंड।",
       },
       previewSharing: {
         sectionTitle: "पूर्वावलोकन साझाकरण",
diff --git a/studio/frontend/src/i18n/locales/ja.ts b/studio/frontend/src/i18n/locales/ja.ts
index 23752b6c26..a261994f03 100644
--- a/studio/frontend/src/i18n/locales/ja.ts
+++ b/studio/frontend/src/i18n/locales/ja.ts
@@ -149,12 +149,12 @@ export const ja = {
         enable: "リクエストごとにモデルを切り替え",
         enableDescription: "OpenAI互換のリクエストが別のダウンロード済み GGUF を指定した場合、応答する前にそのモデルを読み込みます。デフォルトはオフです。不明な名前の場合は、読み込み済みのモデルで応答を続けます。",
         idleUnload: "アイドル時の自動アンロード",
-        idleUnloadDescription: "指定した秒数だけアイドル状態が続くとモデルをアンロードして VRAM を解放します。次のリクエストで再読み込みされます。0 にすると読み込んだままにします。",
+        idleUnloadDescription: "指定した秒数だけアイドル状態が続くとモデルをアンロードして VRAM を解放します。次のリクエストで再読み込みされます。0 にすると読み込んだままにします。最小 60 秒。",
         idleNeedsEnable: "アンロードされたモデルが次回使用時に再読み込みされるように、「リクエストごとにモデルを切り替え」をオンにしてください。",
         idleActiveViaEnv: "アイドル時の自動アンロードは UNSLOTH_MODEL_IDLE_TTL 環境変数によって有効になっています。",
         loadError: "モデル自動切り替え設定の読み込みに失敗しました。",
         saveError: "モデル自動切り替え設定の保存に失敗しました。",
-        idleError: "秒数を整数（0 以上）で入力してください。",
+        idleError: "モデルを読み込んだままにするには 0 を、それ以外は 60 秒以上を入力してください。",
       },
       previewSharing: {
         sectionTitle: "プレビュー共有",
diff --git a/studio/frontend/src/i18n/locales/ko.ts b/studio/frontend/src/i18n/locales/ko.ts
index a11a94faf2..7c5691925e 100644
--- a/studio/frontend/src/i18n/locales/ko.ts
+++ b/studio/frontend/src/i18n/locales/ko.ts
@@ -153,14 +153,14 @@ export const ko = {
           "OpenAI 호환 요청이 다운로드된 다른 GGUF를 지정하면, 응답하기 전에 해당 모델을 불러옵니다. 기본값은 꺼짐이며, 알 수 없는 이름은 불러온 모델을 계속 제공합니다.",
         idleUnload: "유휴 시 자동 해제",
         idleUnloadDescription:
-          "지정한 유휴 시간(초)이 지나면 모델을 해제하여 VRAM을 확보합니다. 다음 요청 시 다시 불러옵니다. 0으로 설정하면 계속 로드된 상태로 유지됩니다.",
+          "지정한 유휴 시간(초)이 지나면 모델을 해제하여 VRAM을 확보합니다. 다음 요청 시 다시 불러옵니다. 0으로 설정하면 계속 로드된 상태로 유지됩니다. 최소 60초입니다.",
         idleNeedsEnable:
           "해제된 모델이 다음 사용 시 다시 로드되도록 하려면 요청에 따라 모델 전환을 켜세요.",
         idleActiveViaEnv:
           "유휴 시 자동 해제가 UNSLOTH_MODEL_IDLE_TTL 환경 변수를 통해 활성화되어 있습니다.",
         loadError: "모델 자동 전환 설정을 불러오지 못했습니다.",
         saveError: "모델 자동 전환 설정을 저장하지 못했습니다.",
-        idleError: "정수(초)를 입력하세요(0 이상).",
+        idleError: "모델을 로드 상태로 유지하려면 0을, 그렇지 않으면 60초 이상을 입력하세요.",
       },
       previewSharing: {
         sectionTitle: "미리보기 공유",
diff --git a/studio/frontend/src/i18n/locales/pt-br.ts b/studio/frontend/src/i18n/locales/pt-br.ts
index 07832ef1d0..e6d2347c10 100644
--- a/studio/frontend/src/i18n/locales/pt-br.ts
+++ b/studio/frontend/src/i18n/locales/pt-br.ts
@@ -157,14 +157,14 @@ export const ptBR = {
           "Quando uma requisição compatível com OpenAI nomear um GGUF baixado diferente, carrega-o antes de responder. Desativado por padrão; nomes desconhecidos continuam usando o modelo carregado.",
         idleUnload: "Descarregamento automático por inatividade",
         idleUnloadDescription:
-          "Descarrega o modelo após esta quantidade de segundos de inatividade para liberar VRAM; a próxima requisição o recarrega. 0 mantém o modelo carregado.",
+          "Descarrega o modelo após esta quantidade de segundos de inatividade para liberar VRAM; a próxima requisição o recarrega. 0 mantém o modelo carregado. Mínimo de 60 segundos.",
         idleNeedsEnable:
           "Ative Trocar de modelo por requisição para que um modelo descarregado seja recarregado no próximo uso.",
         idleActiveViaEnv:
           "O descarregamento automático por inatividade está ativo por meio da variável de ambiente UNSLOTH_MODEL_IDLE_TTL.",
         loadError: "Falha ao carregar as configurações de troca automática de modelo.",
         saveError: "Falha ao salvar as configurações de troca automática de modelo.",
-        idleError: "Insira um número inteiro de segundos (0 ou mais).",
+        idleError: "Insira 0 para manter o modelo carregado, ou pelo menos 60 segundos.",
       },
       previewSharing: {
         sectionTitle: "Compartilhamento de pré-visualização",
diff --git a/studio/frontend/src/i18n/locales/ru.ts b/studio/frontend/src/i18n/locales/ru.ts
index 81d20cc2ea..c7464a3b44 100644
--- a/studio/frontend/src/i18n/locales/ru.ts
+++ b/studio/frontend/src/i18n/locales/ru.ts
@@ -154,14 +154,14 @@ export const ru = {
           "Когда OpenAI-совместимый запрос указывает другую загруженную GGUF, загружать её перед обслуживанием. По умолчанию выключено; неизвестные имена продолжают обслуживать загруженную модель.",
         idleUnload: "Автовыгрузка при простое",
         idleUnloadDescription:
-          "Выгружать модель после указанного числа секунд простоя, чтобы освободить VRAM; следующий запрос загрузит её снова. 0 оставляет модель загруженной.",
+          "Выгружать модель после указанного числа секунд простоя, чтобы освободить VRAM; следующий запрос загрузит её снова. 0 оставляет модель загруженной. Минимум 60 секунд.",
         idleNeedsEnable:
           "Включите «Переключать модель по запросу», чтобы выгруженная модель загружалась при следующем использовании.",
         idleActiveViaEnv:
           "Автовыгрузка при простое активна через переменную окружения UNSLOTH_MODEL_IDLE_TTL.",
         loadError: "Не удалось загрузить настройки автопереключения модели.",
         saveError: "Не удалось сохранить настройки автопереключения модели.",
-        idleError: "Введите целое число секунд (0 или больше).",
+        idleError: "Введите 0, чтобы модель оставалась загруженной, или не менее 60 секунд.",
       },
       previewSharing: {
         sectionTitle: "Публикация предпросмотра",
diff --git a/studio/frontend/src/i18n/locales/zh-CN.ts b/studio/frontend/src/i18n/locales/zh-CN.ts
index 4c51755244..ff218adad2 100644
--- a/studio/frontend/src/i18n/locales/zh-CN.ts
+++ b/studio/frontend/src/i18n/locales/zh-CN.ts
@@ -152,14 +152,14 @@ export const zhCN = {
           "当兼容 OpenAI 的请求指定了另一个已下载的 GGUF 时，先加载它再提供服务。默认关闭；未知名称将继续使用已加载的模型。",
         idleUnload: "空闲自动卸载",
         idleUnloadDescription:
-          "空闲达到该秒数后卸载模型以释放 VRAM；下次请求会重新加载。设为 0 则保持加载。",
+          "空闲达到该秒数后卸载模型以释放 VRAM；下次请求会重新加载。设为 0 则保持加载。最小 60 秒。",
         idleNeedsEnable:
           "开启“按请求切换模型”，以便已卸载的模型在下次使用时重新加载。",
         idleActiveViaEnv:
           "空闲自动卸载已通过 UNSLOTH_MODEL_IDLE_TTL 环境变量启用。",
         loadError: "加载模型自动切换设置失败。",
         saveError: "保存模型自动切换设置失败。",
-        idleError: "请输入整数秒数（0 或以上）。",
+        idleError: "输入 0 保持模型加载，或输入至少 60 秒。",
       },
       previewSharing: {
         sectionTitle: "预览分享",