diff --git a/cpp/tensorrt_llm/common/attentionOp.cpp b/cpp/tensorrt_llm/common/attentionOp.cpp
index 32a9332a0191..845ad8084c40 100644
--- a/cpp/tensorrt_llm/common/attentionOp.cpp
+++ b/cpp/tensorrt_llm/common/attentionOp.cpp
@@ -1271,14 +1271,6 @@ int AttentionOp::mlaGeneration(
                 mXqaDispatcher->run(xqaParams, kv_cache_buffer, kv_scale_cache_buffer);
                 return 0;
             }
-            else if (mIsSpecDecodingEnabled && mUseSpecDecoding)
-            {
-                TLLM_CHECK_WITH_INFO(false, "No available XQA kernels are found for speculative decoding mode.");
-            }
-            else if (mFuseFp4Quant)
-            {
-                TLLM_CHECK_WITH_INFO(false, "No available kernels are found for FP4 output.");
-            }
         }
 
         // Use FMHA otherwise.
diff --git a/tensorrt_llm/_torch/pyexecutor/model_engine.py b/tensorrt_llm/_torch/pyexecutor/model_engine.py
index 6604dfb260f5..8663ffb53b5c 100644
--- a/tensorrt_llm/_torch/pyexecutor/model_engine.py
+++ b/tensorrt_llm/_torch/pyexecutor/model_engine.py
@@ -3246,13 +3246,9 @@ def forward(self,
                                                        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,
-                is_mla=enable_mla)
+                spec_resource_manager, self.is_draft_model, self.attn_backend,
+                self.model_is_wrapped)
             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 5037057699ed..fe59ca865f72 100644
--- a/tensorrt_llm/_torch/speculative/interface.py
+++ b/tensorrt_llm/_torch/speculative/interface.py
@@ -146,12 +146,11 @@ def extend_ctx(self, attention_backend: Type[AttentionBackend]):
                               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
-        is_mla: bool,
+            self,
+            spec_resource_manager: Optional[BaseResourceManager],
+            is_draft_model: bool,
+            attention_backend: Type[AttentionBackend],
+            use_chain_drafter: bool,  # CDL
     ):
         """
         If true, the attention backend kernel needs to run in spec-dec mode (multi-token query mode).
@@ -164,8 +163,7 @@ def attention_need_spec_dec_mode(
         is_trtllm_attention = issubclass(attention_backend, TrtllmAttention)
 
         # Always use the multi-token query mode for 1-model if the kernels are available.
-        xqa_supported = not is_mla or get_sm_version() < 120
-        use_case_1 = self.use_one_engine() and xqa_supported
+        use_case_1 = self.use_one_engine()
         # 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.
         use_case_2 = not self.use_one_engine() and (
diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt
index e2bcbb9bedcb..8d0c02bc5843 100644
--- a/tests/integration/test_lists/waives.txt
+++ b/tests/integration/test_lists/waives.txt
@@ -324,7 +324,6 @@ accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_vswa_reuse_4gpus[one_m
 accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_vswa_reuse_4gpus[two_model] SKIP (https://nvbugs/5756028)
 accuracy/test_llm_api_pytorch.py::TestLlama3_2_1B::test_fp8_prequantized SKIP (https://nvbugs/5785465)
 accuracy/test_llm_api_pytorch.py::TestMinistral8BInstruct::test_fp8 SKIP (https://nvbugs/5785485)
-accuracy/test_llm_api_pytorch.py::TestLlama3_3_70BInstruct::test_fp8_eagle3_tp8[eagle3_one_model=True-torch_compile=False] SKIP (https://nvbugs/5787892)
 accuracy/test_llm_api_pytorch.py::TestLlama3_3_70BInstruct::test_fp8_eagle3_tp8[eagle3_one_model=False-torch_compile=False] SKIP (https://nvbugs/5787892)
 accuracy/test_llm_api_pytorch.py::TestLlama4MaverickInstruct::test_fp8_chunked_prefill[tp8ep8-cuda_graph=True] SKIP (https://nvbugs/5791839)
 accuracy/test_llm_api_pytorch.py::TestLlama4MaverickInstruct::test_fp8_chunked_prefill[tp8ep8-cuda_graph=False] SKIP (https://nvbugs/5795918)