diff --git a/tensorrt_llm/_torch/pyexecutor/model_engine.py b/tensorrt_llm/_torch/pyexecutor/model_engine.py
index 110b05b4f6..9a2bdcf738 100644
--- a/tensorrt_llm/_torch/pyexecutor/model_engine.py
+++ b/tensorrt_llm/_torch/pyexecutor/model_engine.py
@@ -3380,9 +3380,13 @@ class PyTorchModelEngine(ModelEngine):
                                                        no_cache=kv_cache_manager
                                                        is None)
             # attn_metadata now depends on spec_metadata since it determines the shape/content of spec_dec parameter Tensors
+            enable_mla = is_mla(self.model.model_config.pretrained_config)
             is_spec_dec_mode = spec_metadata.spec_dec_mode.attention_need_spec_dec_mode(
-                spec_resource_manager, self.is_draft_model, self.attn_backend,
-                self.model_is_wrapped)
+                spec_resource_manager,
+                self.is_draft_model,
+                self.attn_backend,
+                self.model_is_wrapped,
+                is_mla=enable_mla)
             attn_metadata.update_spec_dec_param(
                 batch_size=scheduled_requests.batch_size,
                 is_spec_decoding_enabled=is_spec_dec_mode,
diff --git a/tensorrt_llm/_torch/speculative/interface.py b/tensorrt_llm/_torch/speculative/interface.py
index 6bc0846650..a155bac5a0 100644
--- a/tensorrt_llm/_torch/speculative/interface.py
+++ b/tensorrt_llm/_torch/speculative/interface.py
@@ -151,11 +151,12 @@ class SpeculativeDecodingMode(IntEnum):
                               TrtllmAttention) or not xqa_supported
 
     def attention_need_spec_dec_mode(
-            self,
-            spec_resource_manager: Optional[BaseResourceManager],
-            is_draft_model: bool,
-            attention_backend: Type[AttentionBackend],
-            use_chain_drafter: bool,  # CDL
+        self,
+        spec_resource_manager: Optional[BaseResourceManager],
+        is_draft_model: bool,
+        attention_backend: Type[AttentionBackend],
+        use_chain_drafter: bool,  # CDL
+        is_mla: bool,
     ):
         """
         If true, the attention backend kernel needs to run in spec-dec mode (multi-token query mode).
@@ -168,7 +169,7 @@ class SpeculativeDecodingMode(IntEnum):
         is_trtllm_attention = issubclass(attention_backend, TrtllmAttention)
 
         # Always use the multi-token query mode for 1-model if the kernels are available.
-        xqa_supported = get_sm_version() < 120
+        xqa_supported = not is_mla or get_sm_version() < 120
         use_case_1 = self.use_one_engine() and xqa_supported
         # For 2-model, we need to enable it when we process multiple tokens at once. This occurs with
         # the target model (verification) or on the first draft for CDL based speculation.