diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index 42cce3c4d8..8ea7e1e816 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -10,6 +10,7 @@ through its OpenAI-compatible /v1/chat/completions endpoint.
 
 import atexit
 import json
+import struct
 import structlog
 from loggers import get_logger
 import shutil
@@ -45,6 +46,8 @@ class LlamaCppBackend:
         self._hf_variant: Optional[str] = None
         self._is_vision: bool = False
         self._healthy = False
+        self._context_length: Optional[int] = None
+        self._chat_template: Optional[str] = None
         self._lock = threading.Lock()
         self._stdout_lines: list[str] = []
         self._stdout_thread: Optional[threading.Thread] = None
@@ -80,6 +83,14 @@ class LlamaCppBackend:
     def hf_variant(self) -> Optional[str]:
         return self._hf_variant
 
+    @property
+    def context_length(self) -> Optional[int]:
+        return self._context_length
+
+    @property
+    def chat_template(self) -> Optional[str]:
+        return self._chat_template
+
     # ── Binary discovery ──────────────────────────────────────────
 
     @staticmethod
@@ -371,6 +382,85 @@ class LlamaCppBackend:
             # Pipe closed — process is terminating
             pass
 
+    # GGUF KV type sizes for fast skipping
+    _GGUF_TYPE_SIZE = {0: 1, 1: 1, 2: 2, 3: 2, 4: 4, 5: 4, 6: 4, 7: 1, 10: 8, 11: 8, 12: 8}
+
+    @staticmethod
+    def _gguf_skip_value(f, vtype: int) -> None:
+        """Skip a GGUF KV value without reading it."""
+        sz = LlamaCppBackend._GGUF_TYPE_SIZE.get(vtype)
+        if sz is not None:
+            f.seek(sz, 1)
+        elif vtype == 8:  # STRING
+            slen = struct.unpack("<Q", f.read(8))[0]
+            f.seek(slen, 1)
+        elif vtype == 9:  # ARRAY
+            atype = struct.unpack("<I", f.read(4))[0]
+            alen = struct.unpack("<Q", f.read(8))[0]
+            elem_sz = LlamaCppBackend._GGUF_TYPE_SIZE.get(atype)
+            if elem_sz is not None:
+                f.seek(elem_sz * alen, 1)
+            elif atype == 8:
+                for _ in range(alen):
+                    slen = struct.unpack("<Q", f.read(8))[0]
+                    f.seek(slen, 1)
+            else:
+                for _ in range(alen):
+                    LlamaCppBackend._gguf_skip_value(f, atype)
+
+    def _read_gguf_metadata(self, gguf_path: str) -> None:
+        """Read context_length and chat_template from a GGUF file's KV header.
+
+        Parses only the KV pairs we need (~30ms even for multi-GB files).
+        For split GGUFs, metadata is always in shard 1.
+        """
+        try:
+            WANTED = {"general.architecture", "tokenizer.chat_template"}
+            arch = None
+            ctx_key = None
+
+            with open(gguf_path, "rb") as f:
+                magic = struct.unpack("<I", f.read(4))[0]
+                if magic != 0x46554747:  # b"GGUF" as little-endian u32
+                    return
+                _version = struct.unpack("<I", f.read(4))[0]
+                _tensor_count, kv_count = struct.unpack("<QQ", f.read(16))
+
+                for _ in range(kv_count):
+                    key_len = struct.unpack("<Q", f.read(8))[0]
+                    key = f.read(key_len).decode("utf-8")
+                    vtype = struct.unpack("<I", f.read(4))[0]
+
+                    if key in WANTED or (ctx_key and key == ctx_key):
+                        # Read this value
+                        if vtype == 8:  # STRING
+                            slen = struct.unpack("<Q", f.read(8))[0]
+                            val_s = f.read(slen).decode("utf-8")
+                            if key == "general.architecture":
+                                arch = val_s
+                                ctx_key = f"{arch}.context_length"
+                            elif key == "tokenizer.chat_template":
+                                self._chat_template = val_s
+                        elif vtype == 4:  # UINT32
+                            val_i = struct.unpack("<I", f.read(4))[0]
+                            if ctx_key and key == ctx_key:
+                                self._context_length = val_i
+                        elif vtype == 10:  # UINT64
+                            val_i = struct.unpack("<Q", f.read(8))[0]
+                            if ctx_key and key == ctx_key:
+                                self._context_length = val_i
+                        else:
+                            self._gguf_skip_value(f, vtype)
+                    else:
+                        self._gguf_skip_value(f, vtype)
+
+            if self._context_length:
+                logger.info(f"GGUF metadata: context_length={self._context_length}")
+            if self._chat_template:
+                logger.info(f"GGUF metadata: chat_template={len(self._chat_template)} chars")
+        except Exception as e:
+            logger.warning(f"Failed to read GGUF metadata: {e}")
+
     # ── HF download (no lock held) ───────────────────────────────
 
     def _download_gguf(
@@ -642,6 +732,9 @@ class LlamaCppBackend:
         else:
             raise ValueError("Either gguf_path or hf_repo must be provided")
 
+        # Read GGUF metadata (context_length, chat_template) -- fast, header only
+        self._read_gguf_metadata(model_path)
+
         # Check cancel after download
         if self._cancel_event.is_set():
             logger.info("Load cancelled after download phase")
@@ -781,6 +874,8 @@ class LlamaCppBackend:
             self._is_vision = False
             self._port = None
             self._healthy = False
+            self._context_length = None
+            self._chat_template = None
             return True
 
     def _kill_process(self):
diff --git a/studio/backend/models/inference.py b/studio/backend/models/inference.py
index 620304f37a..f45ec5890d 100644
--- a/studio/backend/models/inference.py
+++ b/studio/backend/models/inference.py
@@ -119,6 +119,9 @@ class LoadResponse(BaseModel):
     inference: dict = Field(
         ..., description = "Inference parameters (temperature, top_p, top_k, min_p)"
     )
+    context_length: Optional[int] = Field(
+        None, description = "Model's native context length (from GGUF metadata)"
+    )
 
 
 class UnloadResponse(BaseModel):
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index 55bd9710a5..65368b69ca 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -165,6 +165,7 @@ async def load_model(
                 is_lora = False,
                 is_gguf = True,
                 inference = inference_config,
+                context_length = llama_backend.context_length,
             )
 
         # ── Standard path: load via Unsloth/transformers ──────────
diff --git a/studio/frontend/src/features/chat/api/chat-adapter.ts b/studio/frontend/src/features/chat/api/chat-adapter.ts
index 30a8d97461..7bdfc55e8b 100644
--- a/studio/frontend/src/features/chat/api/chat-adapter.ts
+++ b/studio/frontend/src/features/chat/api/chat-adapter.ts
@@ -194,7 +194,8 @@ function waitForModelReady(abortSignal?: AbortSignal): Promise<void> {
 async function autoLoadSmallestModel(): Promise<boolean> {
   const toastId = toast("Loading a model…", {
     description: "Auto-selecting the smallest downloaded model.",
-    duration: Infinity,
+    duration: 5000,
+    closeButton: true,
   });
   try {
     const [ggufRepos, modelRepos] = await Promise.all([
@@ -214,7 +215,7 @@ async function autoLoadSmallestModel(): Promise<boolean> {
             .sort((a, b) => a.size_bytes - b.size_bytes);
           if (downloaded.length > 0) {
             const variant = downloaded[0];
-            await loadModel({
+            const loadResp = await loadModel({
               model_path: repo.repo_id,
               hf_token: null,
               max_seq_length: 4096,
@@ -223,7 +224,9 @@ async function autoLoadSmallestModel(): Promise<boolean> {
               gguf_variant: variant.quant,
               trust_remote_code: false,
             });
-            useChatRuntimeStore.getState().setCheckpoint(repo.repo_id, variant.quant);
+            const store = useChatRuntimeStore.getState();
+            store.setCheckpoint(repo.repo_id, variant.quant);
+            store.setParams({ ...store.params, maxTokens: loadResp.context_length ?? 131072 });
             toast.success(`Loaded ${repo.repo_id} (${variant.quant})`, { id: toastId });
             return true;
           }
@@ -247,7 +250,9 @@ async function autoLoadSmallestModel(): Promise<boolean> {
             gguf_variant: null,
             trust_remote_code: false,
           });
-          useChatRuntimeStore.getState().setCheckpoint(repo.repo_id);
+          const store = useChatRuntimeStore.getState();
+          store.setCheckpoint(repo.repo_id);
+          store.setParams({ ...store.params, maxTokens: 4096 });
           toast.success(`Loaded ${repo.repo_id}`, { id: toastId });
           return true;
         } catch {
diff --git a/studio/frontend/src/features/chat/chat-settings-sheet.tsx b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
index bb2b05f9da..302bc17335 100644
--- a/studio/frontend/src/features/chat/chat-settings-sheet.tsx
+++ b/studio/frontend/src/features/chat/chat-settings-sheet.tsx
@@ -340,10 +340,10 @@ export function ChatSettingsPanel({
                 label="Max Tokens"
                 value={params.maxTokens}
                 min={64}
-                max={isGguf ? 131072 : 32768}
-                step={64}
+                max={isGguf ? params.maxTokens : 32768}
+                step={isGguf ? params.maxTokens : 64}
                 onChange={set("maxTokens")}
-                displayValue={isGguf && params.maxTokens >= 131072 ? "Max" : undefined}
+                displayValue={isGguf ? "Max" : undefined}
               />
             </div>
           </CollapsibleSection>
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 47bd0698a8..b2ec407d4c 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
@@ -132,9 +132,11 @@ function mergeRecommendedInference(
   modelId: string,
 ): InferenceParams {
   const inference = response.inference;
-  // GGUF: max tokens = 131072 (effectively unlimited, model decides)
-  // Non-GGUF: max tokens = 4096
-  const defaultMaxTokens = response.is_gguf ? 131072 : 4096;
+  // GGUF: use actual context length from GGUF metadata, fallback to 131072
+  // Non-GGUF: 4096
+  const defaultMaxTokens = response.is_gguf
+    ? (response.context_length ?? 131072)
+    : 4096;
   return {
     ...current,
     checkpoint: modelId,
diff --git a/studio/frontend/src/features/chat/types/api.ts b/studio/frontend/src/features/chat/types/api.ts
index 4046deb4c2..54ce25c1e2 100644
--- a/studio/frontend/src/features/chat/types/api.ts
+++ b/studio/frontend/src/features/chat/types/api.ts
@@ -82,6 +82,7 @@ export interface LoadModelResponse {
     min_p?: number;
     trust_remote_code?: boolean;
   };
+  context_length?: number | null;
 }
 
 export interface UnloadModelRequest {