diff --git a/vllm/entrypoints/queue_llm.py b/vllm/entrypoints/queue_llm.py
index 56d6b611f8a37..f2a06f115bdbf 100644
--- a/vllm/entrypoints/queue_llm.py
+++ b/vllm/entrypoints/queue_llm.py
@@ -18,7 +18,6 @@
 from vllm.utils import Counter, deprecate_kwargs
 import multiprocessing as mp
 import queue
-import threading
 
 logger = init_logger(__name__)
 
@@ -167,28 +166,36 @@ def start(self, use_tqdm: bool = True):
         self._pull_tokens_from_input_queue(block=True)
         self._run_engine(use_tqdm=use_tqdm)
 
+    def _pull_all_tokens_from_input_queue(self, block: bool = True):
+        while self._pull_tokens_from_input_queue(block=False):
+            pass
+        if block:
+            self._pull_tokens_from_input_queue(block)
+
     def _pull_tokens_from_input_queue(self, block: bool = True):
         try:
             input = self.input_queue.get() if block else self.input_queue.get_nowait()
             if input is None:
                 self.finish = True
-            for sample_id, token_ids in input:
-                inputs = self._convert_v1_inputs(
-                    prompts=None,
-                    prompt_token_ids=token_ids,
-                    multi_modal_data=None,
-                )
-
-                self._validate_and_add_requests(
-                    inputs=inputs,
-                    params=self.sampling_params,
-                    request_id=sample_id,
-                )
+            else:
+                for sample_id, token_ids in input:
+                    inputs = self._convert_v1_inputs(
+                        prompts=None,
+                        prompt_token_ids=token_ids,
+                        multi_modal_data=None,
+                    )
+
+                    self._validate_and_add_requests(
+                        inputs=inputs,
+                        params=self.sampling_params,
+                        request_id=sample_id,
+                    )
         except queue.Empty:
-            pass
+            return False
         except Exception as e:
             logger.error(f"Unexpected exception during pulling tokens: {e}")
-
+            return False
+        return True
 
     def _convert_v1_inputs(
         self,
@@ -291,24 +298,31 @@ def _run_engine(
             )
         # Run the engine.
         total_toks = 0
-        first_token_sent = set()
-        while not self.finish and self.llm_engine.has_unfinished_requests():
-            self._pull_tokens_from_input_queue(block=False)
+        request_stats = {}
+        while not self.finish or self.llm_engine.has_unfinished_requests():
+            block = not self.llm_engine.has_unfinished_requests() and not self.finish
+            self._pull_all_tokens_from_input_queue(block=block)
             step_outputs = self.llm_engine.step()
             for output in step_outputs:
-                if len(output.outputs) > 0 and (output.request_id not in first_token_sent):
-                    self.first_token_queue.put(output)
-                    first_token_sent.add(output.request_id)
-                if output.finished:
-                    self.result_queue.put_nowait(output)
-                    first_token_sent.remove(output.request_id)
-                    if use_tqdm:
-                        if isinstance(output, RequestOutput):
-                            # Calculate tokens only for RequestOutput
-                            total_toks += sum(
-                                len(stp.token_ids) for stp in output.outputs)
-                            spd = total_toks / pbar.format_dict["elapsed"]
-                            pbar.postfix = f"Generation Speed: {spd:.2f} toks/s"
-                        pbar.update(1)
+                output_len = len(output.outputs[0].token_ids)
+                if output_len > 0 and (output.request_id not in request_stats):
+                    self.first_token_queue.put((output.request_id, output.outputs[0].token_ids))
+                    request_stats[output.request_id] = output_len
+                if request_stats[output.request_id] < output_len:
+                    self.result_queue.put_nowait((output.request_id, output.outputs[0].token_ids[request_stats[output.request_id]: output_len]))
+                    if output.finished:
+                        # signal end of stream with None
+                        self.result_queue.put_nowait((output.request_id, None))
+                        del request_stats[output.request_id]
+                        if use_tqdm:
+                            if isinstance(output, RequestOutput):
+                                # Calculate tokens only for RequestOutput
+                                total_toks += sum(
+                                    len(stp.token_ids) for stp in output.outputs)
+                                spd = total_toks / pbar.format_dict["elapsed"]
+                                pbar.postfix = f"Generation Speed: {spd:.2f} toks/s"
+                            pbar.update(1)
+                    else:
+                        request_stats[output.request_id] = output_len
         if use_tqdm:
             pbar.close()