diff --git a/tensorrt_llm/_torch/visual_gen/pipeline.py b/tensorrt_llm/_torch/visual_gen/pipeline.py
index ec35e53bd95..9f1d0452e26 100644
--- a/tensorrt_llm/_torch/visual_gen/pipeline.py
+++ b/tensorrt_llm/_torch/visual_gen/pipeline.py
@@ -170,16 +170,19 @@ def _cuda_profiler_stop(self):
                 logger.info("CUDA profiler stopped")
 
     def _setup_cuda_graphs(self):
-        """Wrap all transformer components with CUDA graph capture/replay."""
+        """Wrap all transformer components with CUDA graph capture/replay.
+
+        Composes with torch.compile: the runner wraps the (outer) transformer
+        ``forward`` while torch.compile compiles the inner transformer blocks
+        (see ``torch_compile``). Graph capture happens during warmup, by which
+        point the runner's own ``WARMUP_STEPS`` eager iterations have already
+        triggered torch.compile's lazy compilation, so the captured graph
+        contains the optimized compiled kernels. (The ``LTX2Pipeline`` override
+        relies on the same ordering.)
+        """
         if not self.pipeline_config.cuda_graph.enable:
             return
 
-        if self.pipeline_config.torch_compile.enable:
-            logger.warning(
-                "CUDA graphs with torch.compile not yet supported. Using torch.compile only."
-            )
-            return
-
         if len(self.transformer_components) > 1:
             logger.info(
                 "CUDA graph runner: multiple transformer components, using shared graph pool"
@@ -188,6 +191,7 @@ def _setup_cuda_graphs(self):
         else:
             shared_pool = None
 
+        compile_note = " (with torch.compile)" if self.pipeline_config.torch_compile.enable else ""
         for name in self.transformer_components:
             model = getattr(self, name, None)
             if model is None:
@@ -198,7 +202,7 @@ def _setup_cuda_graphs(self):
                 shared_pool,
             )
             model.register_cuda_graph_extra_key_fns(runner)
-            logger.info(f"CUDA graph runner: wrapping {name}.forward")
+            logger.info(f"CUDA graph runner: wrapping {name}.forward{compile_note}")
             model.forward = runner.wrap(model.forward)
             self._cuda_graph_runners[name] = runner
 
diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt
index 799077d8fe9..d5436def024 100644
--- a/tests/integration/test_lists/waives.txt
+++ b/tests/integration/test_lists/waives.txt
@@ -458,6 +458,7 @@ unittest/_torch/multi_gpu/test_user_buffers.py::test_user_buffers_pass[2-fp16-_t
 unittest/_torch/ray_orchestrator/multi_gpu/test_llm_update_weights_multi_gpu.py::test_llm_partial_update_weights_nvfp4[auto-Qwen3/Qwen3-8B] SKIP (https://nvbugs/6372690)
 unittest/_torch/ray_orchestrator/multi_gpu/test_llm_update_weights_multi_gpu.py::test_llm_partial_update_weights_nvfp4[fp8-Qwen3/Qwen3-30B-A3B] SKIP (https://nvbugs/6372690)
 unittest/_torch/ray_orchestrator/multi_gpu/test_llm_update_weights_multi_gpu.py::test_llm_partial_update_weights_nvfp4[fp8-Qwen3/Qwen3-8B] SKIP (https://nvbugs/6372690)
+unittest/_torch/sampler/test_beam_search_speculative_d2h.py::test_speculative_d2h_predictor_hit_is_sync_free SKIP (https://nvbugs/6378901)
 unittest/_torch/thop/parallel/test_fp8_rowwise_linear.py::test_fp8_rowwise_linear[dtype1] SKIP (https://nvbugs/6301807)
 unittest/_torch/thop/serial/test_moe.py::TestMoeFp4::test_no_autotune[use_score_as_input-RoutingDSv3-swiglu-1024-1024-1] SKIP (https://nvbugs/5908070)
 unittest/_torch/thop/serial/test_moe.py::TestMoeFp4::test_no_autotune[use_score_as_input-RoutingRenormalize_qwen_next-swiglu-1024-1024-150] SKIP (https://nvbugs/5908070)