diff --git a/vllm_mlx/cli.py b/vllm_mlx/cli.py
index dcbee8ac..eb744f36 100644
--- a/vllm_mlx/cli.py
+++ b/vllm_mlx/cli.py
@@ -178,6 +178,8 @@ def serve_command(args):
             print(f"Prefix cache: max_entries={args.prefix_cache_size}")
     else:
         print("Mode: Simple (maximum throughput)")
+        if args.enable_mtp:
+            print("MTP: enabled (native speculative decoding)")
 
     # Load model with unified server
     load_model(
@@ -187,6 +189,7 @@ def serve_command(args):
         stream_interval=args.stream_interval if args.continuous_batching else 1,
         max_tokens=args.max_tokens,
         force_mllm=args.mllm,
+        mtp=args.enable_mtp,
     )
 
     # Start server
diff --git a/vllm_mlx/engine/simple.py b/vllm_mlx/engine/simple.py
index 3a7e14e2..6b9bb2eb 100644
--- a/vllm_mlx/engine/simple.py
+++ b/vllm_mlx/engine/simple.py
@@ -32,6 +32,7 @@ def __init__(
         trust_remote_code: bool = True,
         enable_cache: bool = True,
         force_mllm: bool = False,
+        mtp: bool = False,
     ):
         """
         Initialize the simple engine.
@@ -41,11 +42,13 @@ def __init__(
             trust_remote_code: Whether to trust remote code
             enable_cache: Enable VLM cache for multimodal models
             force_mllm: Force loading as MLLM even if not auto-detected
+            mtp: Enable native MTP speculative decoding (model must have MTP head)
         """
         self._model_name = model_name
         self._trust_remote_code = trust_remote_code
         self._enable_cache = enable_cache
         self._is_mllm = force_mllm or is_mllm_model(model_name)
+        self._mtp = mtp
 
         self._model = None
         self._loaded = False
@@ -91,11 +94,15 @@ async def start(self) -> None:
             self._model = MLXLanguageModel(
                 self._model_name,
                 trust_remote_code=self._trust_remote_code,
+                mtp=self._mtp,
             )
 
         self._model.load()
         self._loaded = True
-        logger.info(f"SimpleEngine loaded: {self._model_name} (MLLM={self._is_mllm})")
+        mtp_info = f", MTP={self._mtp}" if self._mtp else ""
+        logger.info(
+            f"SimpleEngine loaded: {self._model_name} (MLLM={self._is_mllm}{mtp_info})"
+        )
 
     async def stop(self) -> None:
         """Stop the engine and cleanup resources."""
diff --git a/vllm_mlx/models/llm.py b/vllm_mlx/models/llm.py
index 092c060e..bb487859 100644
--- a/vllm_mlx/models/llm.py
+++ b/vllm_mlx/models/llm.py
@@ -50,6 +50,7 @@ def __init__(
         model_name: str,
         tokenizer_name: str | None = None,
         trust_remote_code: bool = False,
+        mtp: bool = False,
     ):
         """
         Initialize the MLX language model.
@@ -58,10 +59,12 @@ def __init__(
             model_name: HuggingFace model name or local path
             tokenizer_name: Optional separate tokenizer name
             trust_remote_code: Whether to trust remote code
+            mtp: Enable native MTP speculative decoding (model must have MTP head)
         """
         self.model_name = model_name
         self.tokenizer_name = tokenizer_name or model_name
         self.trust_remote_code = trust_remote_code
+        self._mtp = mtp
 
         self.model = None
         self.tokenizer = None
@@ -203,12 +206,18 @@ def stream_generate(
         token_count = 0
         accumulated_text = ""
 
+        # Pass MTP flag for native speculative decoding if enabled
+        mtp_kwargs = {}
+        if self._mtp:
+            mtp_kwargs["mtp"] = True
+
         for response in stream_generate(
             self.model,
             self.tokenizer,
             prompt=prompt,
             max_tokens=max_tokens,
             sampler=sampler,
+            **mtp_kwargs,
         ):
             token_count += 1
             # response.text is the new token text (not accumulated)
diff --git a/vllm_mlx/server.py b/vllm_mlx/server.py
index f0328d4e..53b5ac6e 100644
--- a/vllm_mlx/server.py
+++ b/vllm_mlx/server.py
@@ -467,6 +467,7 @@ def load_model(
     stream_interval: int = 1,
     max_tokens: int = 32768,
     force_mllm: bool = False,
+    mtp: bool = False,
 ):
     """
     Load a model (auto-detects MLLM vs LLM).
@@ -478,6 +479,7 @@ def load_model(
         stream_interval: Tokens to batch before streaming (batched mode only)
         max_tokens: Default max tokens for generation
         force_mllm: Force loading as MLLM even if not auto-detected
+        mtp: Enable native MTP speculative decoding (SimpleEngine only)
     """
     global _engine, _model_name, _default_max_tokens, _tool_parser_instance
 
@@ -502,7 +504,7 @@ def load_model(
         logger.info(f"Model loaded (batched mode): {model_name}")
     else:
         logger.info(f"Loading model with SimpleEngine: {model_name}")
-        _engine = SimpleEngine(model_name=model_name, force_mllm=force_mllm)
+        _engine = SimpleEngine(model_name=model_name, force_mllm=force_mllm, mtp=mtp)
         # Start SimpleEngine synchronously (no background loop)
         # Use new_event_loop() for Python 3.10+ compatibility (get_event_loop() is deprecated)
         loop = asyncio.new_event_loop()