diff --git a/vllm/envs.py b/vllm/envs.py
index 5b8a65bd6545..595058bcbb02 100644
--- a/vllm/envs.py
+++ b/vllm/envs.py
@@ -174,6 +174,10 @@ def get_default_config_root():
     lambda: (os.environ.get("VLLM_USE_TRITON_FLASH_ATTN", "True").lower() in
              ("true", "1")),
 
+    # Internal flag to enable Dynamo graph capture
+    "VLLM_TEST_DYNAMO_GRAPH_CAPTURE":
+    lambda: int(os.environ.get("VLLM_TEST_DYNAMO_GRAPH_CAPTURE", "0")),
+
     # local rank of the process in the distributed setting, used to determine
     # the GPU device id
     "LOCAL_RANK":
diff --git a/vllm/worker/model_runner.py b/vllm/worker/model_runner.py
index 777344289958..f9c26e0c318b 100644
--- a/vllm/worker/model_runner.py
+++ b/vllm/worker/model_runner.py
@@ -23,6 +23,7 @@
     BatchPrefillWithPagedKVCacheWrapper = None
     FLASHINFER_WORKSPACE_BUFFER_SIZE = 0
 
+import vllm.envs as envs
 from vllm.attention import AttentionMetadata, get_attn_backend
 from vllm.config import (CacheConfig, DeviceConfig, LoadConfig, LoRAConfig,
                          ModelConfig, MultiModalConfig, ParallelConfig,
@@ -786,6 +787,11 @@ def load_model(self) -> None:
                     "provided. Defaulting to scaling factors of 1.0. "
                     "This may lead to less accurate results!")
 
+        if envs.VLLM_TEST_DYNAMO_GRAPH_CAPTURE:
+            self.model = torch.compile(self.model,
+                                       fullgraph=True,
+                                       backend="eager")
+
     def save_sharded_state(
         self,
         path: str,