diff --git a/tests/config/test_mp_reducer.py b/tests/config/test_mp_reducer.py
new file mode 100644
index 000000000000..ee351cbfa7c1
--- /dev/null
+++ b/tests/config/test_mp_reducer.py
@@ -0,0 +1,57 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+import sys
+from unittest.mock import patch
+
+from vllm.config import VllmConfig
+from vllm.engine.arg_utils import AsyncEngineArgs
+from vllm.v1.engine.async_llm import AsyncLLM
+
+
+def test_mp_reducer(monkeypatch):
+    """
+    Test that _reduce_config reducer is registered when AsyncLLM is instantiated
+    without transformers_modules. This is a regression test for
+    https://github.com/vllm-project/vllm/pull/18640.
+    """
+
+    # Use V1 AsyncLLM which calls maybe_register_config_serialize_by_value
+    monkeypatch.setenv('VLLM_USE_V1', '1')
+
+    # Ensure transformers_modules is not in sys.modules
+    if 'transformers_modules' in sys.modules:
+        del sys.modules['transformers_modules']
+
+    with patch('multiprocessing.reducer.register') as mock_register:
+        engine_args = AsyncEngineArgs(
+            model="facebook/opt-125m",
+            max_model_len=32,
+            gpu_memory_utilization=0.1,
+            disable_log_stats=True,
+            disable_log_requests=True,
+        )
+
+        async_llm = AsyncLLM.from_engine_args(
+            engine_args,
+            start_engine_loop=False,
+        )
+
+        assert mock_register.called, (
+            "multiprocessing.reducer.register should have been called")
+
+        vllm_config_registered = False
+        for call_args in mock_register.call_args_list:
+            # Verify that a reducer for VllmConfig was registered
+            if len(call_args[0]) >= 2 and call_args[0][0] == VllmConfig:
+                vllm_config_registered = True
+
+                reducer_func = call_args[0][1]
+                assert callable(
+                    reducer_func), "Reducer function should be callable"
+                break
+
+        assert vllm_config_registered, (
+            "VllmConfig should have been registered to multiprocessing.reducer"
+        )
+
+        async_llm.shutdown()
diff --git a/vllm/transformers_utils/config.py b/vllm/transformers_utils/config.py
index 3cc112790013..5c422a9e3fce 100644
--- a/vllm/transformers_utils/config.py
+++ b/vllm/transformers_utils/config.py
@@ -655,34 +655,35 @@ def maybe_register_config_serialize_by_value() -> None:
     """ # noqa
     try:
         import transformers_modules
+        transformers_modules_available = True
     except ImportError:
-        # the config does not need trust_remote_code
-        return
+        transformers_modules_available = False
 
     try:
-        import cloudpickle
-        cloudpickle.register_pickle_by_value(transformers_modules)
-
-        # ray vendors its own version of cloudpickle
-        from vllm.executor.ray_utils import ray
-        if ray:
-            ray.cloudpickle.register_pickle_by_value(transformers_modules)
-
-        # multiprocessing uses pickle to serialize arguments when using spawn
-        # Here we get pickle to use cloudpickle to serialize config objects
-        # that contain instances of the custom config class to avoid
-        # serialization problems if the generated module (and model) has a `.`
-        # in its name
         import multiprocessing
         import pickle
 
+        import cloudpickle
+
         from vllm.config import VllmConfig
 
+        # Register multiprocessing reducers to handle cross-process
+        # serialization of VllmConfig objects that may contain custom configs
+        # from transformers_modules
         def _reduce_config(config: VllmConfig):
             return (pickle.loads, (cloudpickle.dumps(config), ))
 
         multiprocessing.reducer.register(VllmConfig, _reduce_config)
 
+        # Register transformers_modules with cloudpickle if available
+        if transformers_modules_available:
+            cloudpickle.register_pickle_by_value(transformers_modules)
+
+            # ray vendors its own version of cloudpickle
+            from vllm.executor.ray_utils import ray
+            if ray:
+                ray.cloudpickle.register_pickle_by_value(transformers_modules)
+
     except Exception as e:
         logger.warning(
             "Unable to register remote classes used by"