diff --git a/fastdeploy/worker/gpu_model_runner.py b/fastdeploy/worker/gpu_model_runner.py
index 2e0055a97..cf1a6d352 100644
--- a/fastdeploy/worker/gpu_model_runner.py
+++ b/fastdeploy/worker/gpu_model_runner.py
@@ -140,17 +140,10 @@ class GPUModelRunner(ModelRunnerBase):
         """
         Check whether prefill stage finished
         """
-        if self.enable_mm:
-            # VL only support 1 batch to prefill
-            prefill_statue = (self.share_inputs["seq_lens_this_time"] != 0) & (
-                self.share_inputs["seq_lens_this_time"] != 1
-            )
-            return not paddle.any(prefill_statue).numpy()
+        if int(paddle.max(self.share_inputs["seq_lens_encoder"])) != 0:
+            return 1
         else:
-            if int(paddle.max(self.share_inputs["seq_lens_encoder"])) != 0:
-                return 1
-            else:
-                return 0
+            return 0
 
     def _init_speculative_proposer(self):
         """
diff --git a/fastdeploy/worker/worker_process.py b/fastdeploy/worker/worker_process.py
index 4b968b179..9e2de2b97 100644
--- a/fastdeploy/worker/worker_process.py
+++ b/fastdeploy/worker/worker_process.py
@@ -278,7 +278,7 @@ class PaddleDisWorkerProc():
             if self.local_rank %  mp_num_per_node == 0:
                 if self.task_queue.num_tasks() > 0:
                     # VL only support 1 batch to prefill
-                    if not self.fd_config.model_config.enable_mm or self.worker.prefill_finished():
+                    if not self.fd_config.model_config.enable_mm or not self.worker.prefill_finished():
                         if self.nnode > 1:
                             self.task_queue.read_finish_flag.set(1)
                         else:
@@ -332,8 +332,7 @@ class PaddleDisWorkerProc():
             # Execute model to generate token. The generated token will be written to the buffer.
             # These generated tokens can be obtained through get_output op.
             self.worker.execute_model(req_dicts)
-            if not self.fd_config.model_config.enable_mm:
-                self.exist_prefill_task_signal.value[0] = self.worker.prefill_finished()
+            self.exist_prefill_task_signal.value[0] = self.worker.prefill_finished()
 
     def determine_num_available_blocks(self) -> None:
         """Profiles the peak memory usage of the model to determine how many