diff --git a/vllm_omni/model_executor/stage_configs/qwen3_omni_moe.yaml b/vllm_omni/model_executor/stage_configs/qwen3_omni_moe.yaml
index 802f8dd249..eb5bf71012 100644
--- a/vllm_omni/model_executor/stage_configs/qwen3_omni_moe.yaml
+++ b/vllm_omni/model_executor/stage_configs/qwen3_omni_moe.yaml
@@ -72,7 +72,7 @@ stage_args:
     stage_type: llm  # Use llm stage type to launch OmniLLM
     runtime:
       devices: "1"
-      max_batch_size: 64
+      max_batch_size: 32
     engine_args:
       model_stage: code2wav
       model_arch: Qwen3OmniMoeForConditionalGeneration
diff --git a/vllm_omni/worker/gpu_ar_model_runner.py b/vllm_omni/worker/gpu_ar_model_runner.py
index e332db8b0a..cf261429fd 100644
--- a/vllm_omni/worker/gpu_ar_model_runner.py
+++ b/vllm_omni/worker/gpu_ar_model_runner.py
@@ -416,6 +416,14 @@ def sample_tokens(
         if grammar_output is not None:
             apply_grammar_bitmask(scheduler_output, grammar_output, self.input_batch, logits)
 
+        # Correct padding values of prompt_token_ids to match the logits vocabulary size
+        if logits is not None and not self.input_batch.sampling_metadata.no_penalties:
+            smd = self.input_batch.sampling_metadata
+            if smd.prompt_token_ids is not None:
+                logits_vocab = logits.shape[-1]
+                if self.input_batch.vocab_size > logits_vocab:
+                    smd.prompt_token_ids = smd.prompt_token_ids.clamp(max=logits_vocab)
+
         with record_function_or_nullcontext("gpu_model_runner: sample"):
             sampler_output = self._sample(logits, spec_decode_metadata)