diff --git a/tests/compile/test_wrapper.py b/tests/compile/test_wrapper.py
index cef516ad..3668c1fa 100644
--- a/tests/compile/test_wrapper.py
+++ b/tests/compile/test_wrapper.py
@@ -2,7 +2,7 @@ from typing import Optional
 
 import torch
 
-from vllm.compilation.wrapper import TorchCompileWrapperWithCustomDispacther
+from vllm.compilation.wrapper import TorchCompileWrapperWithCustomDispatcher
 
 
 class MyMod(torch.nn.Module):
@@ -13,7 +13,7 @@ class MyMod(torch.nn.Module):
         return x * 2
 
 
-class MyWrapper(TorchCompileWrapperWithCustomDispacther):
+class MyWrapper(TorchCompileWrapperWithCustomDispatcher):
 
     def __init__(self, model):
         self.model = model
diff --git a/vllm/compilation/wrapper.py b/vllm/compilation/wrapper.py
index c3d86329..e923bd36 100644
--- a/vllm/compilation/wrapper.py
+++ b/vllm/compilation/wrapper.py
@@ -10,7 +10,7 @@ import torch
 import vllm.envs as envs
 
 
-class TorchCompileWrapperWithCustomDispacther:
+class TorchCompileWrapperWithCustomDispatcher:
     """
     A wrapper class for torch.compile, with a custom dispatch logic.
     Subclasses should:
diff --git a/vllm/worker/tpu_model_runner.py b/vllm/worker/tpu_model_runner.py
index 684c54b7..db306bc7 100644
--- a/vllm/worker/tpu_model_runner.py
+++ b/vllm/worker/tpu_model_runner.py
@@ -11,7 +11,7 @@ import torch_xla.core.xla_model as xm
 import torch_xla.runtime as xr
 
 from vllm.attention import AttentionMetadata, get_attn_backend
-from vllm.compilation.wrapper import TorchCompileWrapperWithCustomDispacther
+from vllm.compilation.wrapper import TorchCompileWrapperWithCustomDispatcher
 from vllm.config import (CacheConfig, DeviceConfig, LoadConfig, ModelConfig,
                          ParallelConfig, SchedulerConfig)
 from vllm.logger import init_logger
@@ -611,7 +611,7 @@ class TPUModelRunner(ModelRunnerBase[ModelInputForTPU]):
         return [SamplerOutput(sampler_outputs)]
 
 
-class ModelWrapper(TorchCompileWrapperWithCustomDispacther):
+class ModelWrapper(TorchCompileWrapperWithCustomDispatcher):
 
     def __init__(self, model: nn.Module):
         self.model = model