diff --git a/rllm/engine/agent_execution_engine.py b/rllm/engine/agent_execution_engine.py
index 7033a8c02..7ed14a044 100644
--- a/rllm/engine/agent_execution_engine.py
+++ b/rllm/engine/agent_execution_engine.py
@@ -13,6 +13,7 @@
     convert_messages_to_tokens_and_masks,
     get_recent_assistant_user_messages,
 )
+from rllm.engine.rollout.rollout_engine import ModelOutput
 from rllm.environments.base.base_env import BaseEnv
 from rllm.environments.env_utils import (
     compute_mc_return,
@@ -126,7 +127,7 @@ def __init__(
         # Create a thread pool executor for environment interactions (i.e. step, reset, close)
         self.executor = concurrent.futures.ThreadPoolExecutor(max_workers=max_workers)
 
-    async def get_model_response(self, prompt, application_id, **kwargs) -> str:
+    async def get_model_response(self, prompt, application_id, **kwargs) -> ModelOutput:
         """
         Compute model response asynchronously based on the engine type.
 
@@ -507,12 +508,9 @@ async def trajectory_generator(self, reset_seed=0, timing_raw=None, mode="Text",
         assert all(env is not None and isinstance(env, BaseEnv) for env in self.envs), "All environments must be inheriting from BaseEnv"
         assert all(env.is_multithread_safe() for env in self.envs), "All environments must be multithread safe for async engine"  # type: ignore
         max_concurrency = self.n_parallel_agents
-        if self.engine_name == "verl":
-            free_cache_engine = self.config.actor_rollout_ref.rollout.free_cache_engine if self.config else False
-
         self.executor = ThreadPoolExecutor(max_workers=max_concurrency)
 
-        if self.engine_name == "verl" and free_cache_engine:
+        if self.engine_name == "verl":
             await self.rollout_engine.wake_up()  # type: ignore
 
         async def launch_one_trajectory_task(env_idx: int):
@@ -546,7 +544,7 @@ async def launch_one_trajectory_task(env_idx: int):
             except Exception as e:
                 raise e
 
-        if self.engine_name == "verl" and free_cache_engine:
+        if self.engine_name == "verl":
             await self.rollout_engine.sleep()  # type: ignore
 
         self.executor.shutdown(wait=False, cancel_futures=True)
diff --git a/rllm/engine/agent_workflow_engine.py b/rllm/engine/agent_workflow_engine.py
index ff2aa1fbc..0099c3aa4 100644
--- a/rllm/engine/agent_workflow_engine.py
+++ b/rllm/engine/agent_workflow_engine.py
@@ -165,13 +165,11 @@ async def execute_tasks_verl(self, batch: "DataProto", **kwargs) -> "DataProto":
         Returns:
             DataProto: Transformed results compatible with Verl training.
         """
-        free_cache_engine = self.config.actor_rollout_ref.rollout.free_cache_engine if self.config else False
-        if free_cache_engine:
-            # TODO: later probably should make the `wake_up` and `sleep` methods in base class to be async
-            if isinstance(self.rollout_engine, VerlEngine):
-                await self.rollout_engine.wake_up()
-            else:
-                self.rollout_engine.wake_up()
+        if isinstance(self.rollout_engine, VerlEngine):
+            await self.rollout_engine.wake_up()
+        else:
+            # for most other engines, this simply does nothing
+            self.rollout_engine.wake_up()
 
         if batch.meta_info.get("validate", False):
             self.rollout_engine.validate = True
@@ -180,11 +178,10 @@ async def execute_tasks_verl(self, batch: "DataProto", **kwargs) -> "DataProto":
         results = await self.execute_tasks(tasks, task_ids, **kwargs)  # list of Episodes
         self.rollout_engine.validate = False
 
-        if free_cache_engine:
-            if isinstance(self.rollout_engine, VerlEngine):
-                await self.rollout_engine.sleep()
-            else:
-                self.rollout_engine.sleep()
+        if isinstance(self.rollout_engine, VerlEngine):
+            await self.rollout_engine.sleep()
+        else:
+            self.rollout_engine.sleep()
         return self.transform_results_for_verl(results, task_ids)
 
     def transform_results_for_verl(self, episodes: list[Episode], task_ids: np.ndarray) -> "DataProto":
diff --git a/rllm/trainer/verl/agent_ppo_trainer.py b/rllm/trainer/verl/agent_ppo_trainer.py
index ae6650590..6ce2f4df6 100644
--- a/rllm/trainer/verl/agent_ppo_trainer.py
+++ b/rllm/trainer/verl/agent_ppo_trainer.py
@@ -82,6 +82,10 @@ def init_workers(self):
             **self.config.rllm.agent.get("engine_args", {}),
         )
 
+        # If `free_cache_engine` is False, we need to manually `sleep` at the start
+        if self.config.actor_rollout_ref.rollout.get("free_cache_engine", False):
+            self.async_rollout_manager.sleep()
+
     def init_envs_and_agents(self, batch):
         """
         Initialize environment depending on env_class with the necessary extra_info, also set uid of the batch.