diff --git a/tests/ut/spec_decode/test_mtp_proposer.py b/tests/ut/spec_decode/test_mtp_proposer.py
index c52ef569..3047b3d9 100644
--- a/tests/ut/spec_decode/test_mtp_proposer.py
+++ b/tests/ut/spec_decode/test_mtp_proposer.py
@@ -97,7 +97,6 @@ class TestMtpProposer:
         proposer = MtpProposer(vllm_config, torch.device("cpu"), runner)
 
         assert proposer.use_aclgraph is True
-        assert proposer.cudagraph_batch_sizes == [1, 2, 4, 8]
 
     @patch("vllm.config.get_layers_from_vllm_config")
     @patch("vllm_ascend.spec_decode.mtp_proposer.get_model_loader")
diff --git a/vllm_ascend/spec_decode/mtp_proposer.py b/vllm_ascend/spec_decode/mtp_proposer.py
index 4deef9a2..14a61a79 100644
--- a/vllm_ascend/spec_decode/mtp_proposer.py
+++ b/vllm_ascend/spec_decode/mtp_proposer.py
@@ -107,11 +107,6 @@ class MtpProposer(Proposer):
 
         self.use_aclgraph = self.runner._use_aclgraph()
 
-        self.cudagraph_batch_sizes = (list(
-            sorted(
-                self.vllm_config.compilation_config.cudagraph_capture_sizes))
-                                      if self.use_aclgraph else [])
-
         # persistent buffers for aclgraph graph
         self.input_ids = torch.zeros(self.max_num_tokens,
                                      dtype=torch.int32,
@@ -697,11 +692,13 @@ class MtpProposer(Proposer):
 
         assert self.runner is not None
 
-        if self.runner.use_aclgraph and num_scheduled_tokens <= self.cudagraph_batch_sizes[
+        # Note(qcs): We may need to refactor these check logics.
+        if self.runner.use_aclgraph and num_scheduled_tokens <= self.runner.cudagraph_batch_sizes[
                 -1]:
             num_input_tokens = self.vllm_config.pad_for_cudagraph(
                 num_scheduled_tokens)
-        elif self.use_aclgraph and num_tokens <= self.cudagraph_batch_sizes[-1]:
+        elif self.use_aclgraph and num_tokens <= self.runner.cudagraph_batch_sizes[
+                -1]:
             # Acl graph mode, add padding to the batch size
             num_input_tokens = self.vllm_config.pad_for_cudagraph(num_tokens)
         else: