diff --git a/vllm_ascend/worker/model_runner_v1.py b/vllm_ascend/worker/model_runner_v1.py
index 86fa7a4b..0850c382 100644
--- a/vllm_ascend/worker/model_runner_v1.py
+++ b/vllm_ascend/worker/model_runner_v1.py
@@ -934,23 +934,27 @@ class NPUModelRunner(GPUModelRunner):
 
             # TODO: We should make this official ASAP. Also note that if we pad here,
             # the builders won’t need to add any extra padding.
-            max_decode_tokens = self.scheduler_config.max_num_seqs * self.uniform_decode_query_len
             if self.compilation_config.cudagraph_mode.decode_mode() == CUDAGraphMode.FULL and \
-                uniform_decode and self.uniform_decode_query_len <= num_input_tokens <= max_decode_tokens:
-                num_reqs_padded = num_input_tokens // self.uniform_decode_query_len
-                pad_size = num_reqs_padded - num_reqs
-                if pad_size > 0:
-                    last_query_loc = self.query_start_loc.np[num_reqs]
+                uniform_decode:
+                max_decode_tokens = min(
+                    self.scheduler_config.max_num_seqs *
+                    self.uniform_decode_query_len,
+                    self.cudagraph_batch_sizes[-1])
+                if self.uniform_decode_query_len <= num_input_tokens <= max_decode_tokens:
+                    num_reqs_padded = num_input_tokens // self.uniform_decode_query_len
+                    pad_size = num_reqs_padded - num_reqs
+                    if pad_size > 0:
+                        last_query_loc = self.query_start_loc.np[num_reqs]
 
-                    self.query_start_loc.np[
-                        num_reqs + 1:num_reqs_padded + 1] = self.arange_np[
-                            1:pad_size +
-                            1] * self.uniform_decode_query_len + last_query_loc
-                    self.query_start_loc.copy_to_gpu(num_reqs_padded + 1)
+                        self.query_start_loc.np[
+                            num_reqs + 1:num_reqs_padded + 1] = self.arange_np[
+                                1:pad_size +
+                                1] * self.uniform_decode_query_len + last_query_loc
+                        self.query_start_loc.copy_to_gpu(num_reqs_padded + 1)
 
-                # So we are trying to simulate the behavior of GPUModelRunner's
-                # prepare_inputs for uniform decode mode by padding query_start_loc
-                num_reqs = num_reqs_padded
+                    # So we are trying to simulate the behavior of GPUModelRunner's
+                    # prepare_inputs for uniform decode mode by padding query_start_loc
+                    num_reqs = num_reqs_padded
 
             # Make AscendCommonAttentionMetadata
             common_attn_metadata = AscendCommonAttentionMetadata(