diff --git a/vllm/v1/worker/gpu_worker.py b/vllm/v1/worker/gpu_worker.py
index 556b1e6c7d..bbab98dbd7 100644
--- a/vllm/v1/worker/gpu_worker.py
+++ b/vllm/v1/worker/gpu_worker.py
@@ -154,7 +154,7 @@ class Worker(WorkerBase):
             self.worker_sentinel = WorkerSentinel(worker=self)
         # Buffers saved before sleep
         self._sleep_saved_buffers: dict[str, torch.Tensor] = {}
-        self._sleep_rebuild_draft_metadata_buffers = False
+        self._sleep_saved_draft_buffers: dict[str, torch.Tensor] = {}
 
         # Weight transfer engine is created in `load_model` once the model
         # is available, since the engine needs a reference to the model.
@@ -200,10 +200,10 @@ class Worker(WorkerBase):
                 name: buffer.cpu().clone() for name, buffer in model.named_buffers()
             }
             draft = self.get_draft_model()
-            inner = getattr(draft, "model", None) if draft is not None else None
-            self._sleep_rebuild_draft_metadata_buffers = inner is not None and hasattr(
-                inner, "_build_fused_kv_buffers"
-            )
+            if draft is not None:
+                self._sleep_saved_draft_buffers = {
+                    name: buffer.cpu().clone() for name, buffer in draft.named_buffers()
+                }
 
         self._get_sleep_mode_backend().suspend(level)
 
@@ -228,20 +228,21 @@ class Worker(WorkerBase):
         self._get_sleep_mode_backend().resume(tags)
 
         # Restore the buffers after level 2 sleep
-        if len(self._sleep_saved_buffers):
+        wake_weights = tags is None or "weights" in tags
+        if wake_weights and len(self._sleep_saved_buffers):
             model = self.model_runner.model
             for name, buffer in model.named_buffers():
                 if name in self._sleep_saved_buffers:
                     buffer.data.copy_(self._sleep_saved_buffers[name].data)
             self._sleep_saved_buffers = {}
 
-        if self._sleep_rebuild_draft_metadata_buffers:
+        if wake_weights and len(self._sleep_saved_draft_buffers):
             draft = self.get_draft_model()
             if draft is not None:
-                inner = getattr(draft, "model", None)
-                if inner is not None and hasattr(inner, "_build_fused_kv_buffers"):
-                    inner._build_fused_kv_buffers()
-            self._sleep_rebuild_draft_metadata_buffers = False
+                for name, buffer in draft.named_buffers():
+                    if name in self._sleep_saved_draft_buffers:
+                        buffer.data.copy_(self._sleep_saved_draft_buffers[name].data)
+            self._sleep_saved_draft_buffers = {}
 
         if tags is None or "kv_cache" in tags:
             self.model_runner.post_kv_cache_wake_up()