diff --git a/verl/workers/rollout/schemas.py b/verl/workers/rollout/schemas.py
index f43cfe02405..145fa7cf143 100644
--- a/verl/workers/rollout/schemas.py
+++ b/verl/workers/rollout/schemas.py
@@ -103,12 +103,12 @@ class AsyncRolloutRequest(BaseModel):
         }
     }
 
-    def get_generation_prompt(self, tokenizer: PreTrainedTokenizer) -> str:
+    def get_generation_prompt(self, tokenizer: PreTrainedTokenizer) -> list[int]:
         return tokenizer.apply_chat_template(  # type: ignore
             conversation=[msg.model_dump() for msg in self.messages],
             tools=[tool.model_dump() for tool in self.tools] if self.tools else None,
             add_generation_prompt=True,
-            tokenize=False,
+            tokenize=True,
         )
 
     def add_assistant_message(
diff --git a/verl/workers/rollout/sglang_rollout/async_sglang_rollout.py b/verl/workers/rollout/sglang_rollout/async_sglang_rollout.py
index ada5eb3d2a5..3e8102483b8 100644
--- a/verl/workers/rollout/sglang_rollout/async_sglang_rollout.py
+++ b/verl/workers/rollout/sglang_rollout/async_sglang_rollout.py
@@ -482,7 +482,11 @@ async def _async_rollout_a_request(self, req: AsyncRolloutRequest, do_sample: bo
                 else:
                     raise ValueError(f"Unexpected tool calling last message state: {_req.messages[-1]}")
             elif _req.state == AsyncRolloutRequestStateEnum.RUNNING:
-                generation_prompt = _req.get_generation_prompt(self.tokenizer)
+                generation_prompt_ids = _req.get_generation_prompt(self.tokenizer)
+                max_new_tokens = min(self.config.response_length, self.config.max_model_len - len(generation_prompt_ids) - 1)
+                if max_new_tokens <= 0:
+                    finish_reason_type = FinishReasonTypeEnum.STOP
+                    break
                 if not do_sample:
                     kwargs = dict(
                         n=1,
@@ -494,7 +498,6 @@ async def _async_rollout_a_request(self, req: AsyncRolloutRequest, do_sample: bo
                         top_k=-1,
                         ignore_eos=False,
                         min_new_tokens=0,
-                        max_new_tokens=self.config.response_length,
                         skip_special_tokens=True,
                         spaces_between_special_tokens=True,
                     )
@@ -506,12 +509,13 @@ async def _async_rollout_a_request(self, req: AsyncRolloutRequest, do_sample: bo
                         "temperature": self.config.val_kwargs.temperature,
                         "n": 1,  # if validate, already repeat in ray_trainer
                     }
+                kwargs["max_new_tokens"] = max_new_tokens
                 if "n" not in kwargs or kwargs["n"] > 1:  # group size is supported in preprocess
                     kwargs["n"] = 1
                 # users can customize different sampling_params at different run
                 with self.update_sampling_params(**kwargs):
                     output = await self._engine.async_generate(
-                        prompt=generation_prompt,
+                        input_ids=generation_prompt_ids,
                         sampling_params=self.sampling_params,
                         return_logprob=False,
                     )