diff --git a/cosyvoice/cli/cosyvoice.py b/cosyvoice/cli/cosyvoice.py
index b8fe756..f67c6d7 100644
--- a/cosyvoice/cli/cosyvoice.py
+++ b/cosyvoice/cli/cosyvoice.py
@@ -49,6 +49,7 @@ class CosyVoice:
         self.model.load('{}/llm.pt'.format(model_dir),
                         '{}/flow.pt'.format(model_dir),
                         '{}/hift.pt'.format(model_dir))
+        self.vllm_codec_engine = None
         if load_jit:
             self.model.load_jit('{}/llm.text_encoder.{}.zip'.format(model_dir, 'fp16' if self.fp16 is True else 'fp32'),
                                 '{}/llm.llm.{}.zip'.format(model_dir, 'fp16' if self.fp16 is True else 'fp32'),
@@ -149,8 +150,16 @@ class CosyVoice2(CosyVoice):
         self.model.load('{}/llm.pt'.format(model_dir),
                         '{}/flow.pt'.format(model_dir),
                         '{}/hift.pt'.format(model_dir))
+        self.vllm_codec_engine = None
         if use_vllm:
+            from vllm import EngineArgs, LLMEngine
             self.model.export_codec_vllm(''.join([model_dir, '/codec_vllm_model']))
+            engine_args = EngineArgs(model=''.join([model_dir, '/codec_vllm_model']),
+                         skip_tokenizer_init=True,
+                         gpu_memory_utilization=0.1)
+            self.vllm_codec_engine = LLMEngine.from_engine_args(engine_args)
+            self.model.llm.vllm_codec_engine = self.vllm_codec_engine
+
         if load_jit:
             self.model.load_jit('{}/flow.encoder.{}.zip'.format(model_dir, 'fp16' if self.fp16 is True else 'fp32'))
         if load_trt:
diff --git a/cosyvoice/llm/llm.py b/cosyvoice/llm/llm.py
index bbd3305..a7f12a5 100644
--- a/cosyvoice/llm/llm.py
+++ b/cosyvoice/llm/llm.py
@@ -282,6 +282,7 @@ class Qwen2LM(TransformerLM):
         # 4. sampling method
         self.sampling = sampling
         self.mix_ratio = mix_ratio
+        self.vllm_codec_engine = None
 
     @torch.inference_mode()
     def inference(