diff --git a/vllm/entrypoints/openai/api_server.py b/vllm/entrypoints/openai/api_server.py
index fbb2d32a229d..fb61865063c4 100644
--- a/vllm/entrypoints/openai/api_server.py
+++ b/vllm/entrypoints/openai/api_server.py
@@ -17,6 +17,7 @@
 from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Callable
 from contextlib import asynccontextmanager
 from http import HTTPStatus
+from multiprocessing import shared_memory
 from typing import Annotated, Any, Literal
 
 import model_hosting_container_standards.sagemaker as sagemaker_standards
@@ -132,6 +133,17 @@
 _running_tasks: set[asyncio.Task] = set()
 
 
+def set_sleep_signal(value: int = 1, shared_memory_name: str = "sleep_signal") -> None:
+    try:
+        shm = shared_memory.SharedMemory(name=shared_memory_name, create=False, size=4)
+    except Exception:
+        shm = shared_memory.SharedMemory(name=shared_memory_name, create=True, size=4)
+
+    if shm is not None:
+        shm.buf[0:4] = value.to_bytes(4, "little")
+        shm.close()
+
+
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     try:
@@ -1082,6 +1094,8 @@ async def reset_mm_cache(raw_request: Request):
 
     @router.post("/sleep")
     async def sleep(raw_request: Request):
+        set_sleep_signal(1)
+
         # get POST params
         level = raw_request.query_params.get("level", "1")
         await engine_client(raw_request).sleep(int(level))
@@ -1091,6 +1105,8 @@ async def sleep(raw_request: Request):
 
     @router.post("/wake_up")
     async def wake_up(raw_request: Request):
+        set_sleep_signal(0)
+
         tags = raw_request.query_params.getlist("tags")
         if tags == []:
             # set to None to wake up all tags if no tags are provided
diff --git a/vllm/v1/core/sched/utils.py b/vllm/v1/core/sched/utils.py
index 82166dc97839..4274be10e76b 100644
--- a/vllm/v1/core/sched/utils.py
+++ b/vllm/v1/core/sched/utils.py
@@ -1,6 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import contextlib
+from multiprocessing import shared_memory
 
 import torch
 
@@ -69,4 +70,18 @@ def check_stop(
     ):
         request.status = RequestStatus.FINISHED_LENGTH_CAPPED
         return True
+
+    # Check if the model is sleeping
+    sleep_signal = 0
+    shared_memory_name = "sleep_signal"
+    try:
+        shm = shared_memory.SharedMemory(name=shared_memory_name)
+        sleep_signal = int.from_bytes(shm.buf[0:4], "little")
+        shm.close()
+    except Exception:
+        pass
+    if sleep_signal == 1:
+        request.status = RequestStatus.FINISHED_STOPPED
+        return True
+
     return False