diff --git a/tests/ut/test_utils.py b/tests/ut/test_utils.py
index 7bc8f5b..32f2d7b 100644
--- a/tests/ut/test_utils.py
+++ b/tests/ut/test_utils.py
@@ -272,6 +272,7 @@ class TestUtils(TestBase):
             len(test_vllm_config.compilation_config.cudagraph_capture_sizes))
 
         test_vllm_config.speculative_config = mock.MagicMock()
+        test_vllm_config.speculative_config.num_speculative_tokens = 2
         test_vllm_config.speculative_config.draft_model_config = mock.MagicMock(
         )
         test_vllm_config.speculative_config.draft_model_config.hf_config = mock.MagicMock(
diff --git a/vllm_ascend/utils.py b/vllm_ascend/utils.py
index 0929e40..d4ddbd9 100644
--- a/vllm_ascend/utils.py
+++ b/vllm_ascend/utils.py
@@ -410,6 +410,26 @@ def update_aclgraph_sizes(vllm_config: VllmConfig) -> None:
             vllm_config.model_config.architectures[0], num_hidden_layers,
             len(original_sizes))
 
+    # default or defined cudagraph_capture_sizes may not consider num_speculative_tokens>1 scenario
+    # the maximum size cudagraph_capture_sizes[0] should be greater or equal than
+    # (num_speculative_tokens+1)*max_num_seqs, otherwise draft model will run in eager mode
+    if vllm_config.speculative_config is not None and \
+        vllm_config.speculative_config.num_speculative_tokens > 1:
+        num_speculative_tokens = vllm_config.speculative_config.num_speculative_tokens
+        max_num_seqs = vllm_config.scheduler_config.max_num_seqs
+        original_sizes, compilation_config.cudagraph_capture_sizes = \
+            compilation_config.cudagraph_capture_sizes, None
+        assert len(original_sizes) > 0
+        if original_sizes[0] < (num_speculative_tokens + 1) * max_num_seqs:
+            enlarged_sizes = [(num_speculative_tokens + 1) * size
+                              for size in original_sizes]
+            compilation_config.init_with_cudagraph_sizes(enlarged_sizes)
+            logger.info(
+                "Adjusted ACL graphs: %s → %s for speculative decoding",
+                original_sizes, enlarged_sizes)
+        else:
+            compilation_config.cudagraph_capture_sizes = original_sizes
+
 
 # TODO(wxy): Move to ops module
 def dispose_tensor(x: torch.Tensor):