diff --git a/src/llm_models/model_client/openai_client.py b/src/llm_models/model_client/openai_client.py
index 35630c20f..f18ba652b 100644
--- a/src/llm_models/model_client/openai_client.py
+++ b/src/llm_models/model_client/openai_client.py
@@ -384,8 +384,8 @@ def _default_normal_response_parser(
 @client_registry.register_client_class("openai")
 class OpenaiClient(BaseClient):
     # 类级别的全局缓存：所有 OpenaiClient 实例共享
-    _global_client_cache: ClassVar[dict[int, AsyncOpenAI] ] = {}
-    """全局 AsyncOpenAI 客户端缓存：config_hash -> AsyncOpenAI 实例"""
+    _global_client_cache: ClassVar[dict[tuple[int, int | None], AsyncOpenAI]] = {}
+    """全局 AsyncOpenAI 客户端缓存：(config_hash, loop_id) -> AsyncOpenAI 实例"""
 
     def __init__(self, api_provider: APIProvider):
         super().__init__(api_provider)
@@ -401,20 +401,44 @@ class OpenaiClient(BaseClient):
         )
         return hash(config_tuple)
 
+    @staticmethod
+    def _get_current_loop_id() -> int | None:
+        """获取当前事件循环的ID"""
+        try:
+            loop = asyncio.get_running_loop()
+            return id(loop)
+        except RuntimeError:
+            # 没有运行中的事件循环
+            return None
+
     def _create_client(self) -> AsyncOpenAI:
         """
-        获取或创建 OpenAI 客户端实例（全局缓存）
+        获取或创建 OpenAI 客户端实例（全局缓存，支持事件循环检测）
 
-        多个 OpenaiClient 实例如果配置相同（base_url + api_key + timeout），
+        多个 OpenaiClient 实例如果配置相同（base_url + api_key + timeout）且在同一事件循环中，
         将共享同一个 AsyncOpenAI 客户端实例，最大化连接池复用。
+        当事件循环变化时，会自动创建新的客户端实例。
         """
-        # 检查全局缓存
-        if self._config_hash in self._global_client_cache:
-            return self._global_client_cache[self._config_hash]
+        # 获取当前事件循环ID
+        current_loop_id = self._get_current_loop_id()
+        cache_key = (self._config_hash, current_loop_id)
+
+        # 清理其他事件循环的过期缓存
+        keys_to_remove = [
+            key for key in self._global_client_cache.keys() 
+            if key[0] == self._config_hash and key[1] != current_loop_id
+        ]
+        for key in keys_to_remove:
+            logger.debug(f"清理过期的 AsyncOpenAI 客户端缓存 (loop_id={key[1]})")
+            del self._global_client_cache[key]
+
+        # 检查当前事件循环的缓存
+        if cache_key in self._global_client_cache:
+            return self._global_client_cache[cache_key]
 
         # 创建新的 AsyncOpenAI 实例
         logger.debug(
-            f"创建新的 AsyncOpenAI 客户端实例 (base_url={self.api_provider.base_url}, config_hash={self._config_hash})"
+            f"创建新的 AsyncOpenAI 客户端实例 (base_url={self.api_provider.base_url}, config_hash={self._config_hash}, loop_id={current_loop_id})"
         )
 
         client = AsyncOpenAI(
@@ -424,8 +448,8 @@ class OpenaiClient(BaseClient):
             timeout=self.api_provider.timeout,
         )
 
-        # 存入全局缓存
-        self._global_client_cache[self._config_hash] = client
+        # 存入全局缓存（带事件循环ID）
+        self._global_client_cache[cache_key] = client
 
         return client
 
@@ -434,7 +458,10 @@ class OpenaiClient(BaseClient):
         """获取全局缓存统计信息"""
         return {
             "cached_openai_clients": len(cls._global_client_cache),
-            "config_hashes": list(cls._global_client_cache.keys()),
+            "cache_keys": [
+                {"config_hash": k[0], "loop_id": k[1]} 
+                for k in cls._global_client_cache.keys()
+            ],
         }
 
     async def get_response(