diff --git a/docs/source/contributing/profiling/profiling_index.md b/docs/source/contributing/profiling/profiling_index.md
index d6e597ea..ce25daa3 100644
--- a/docs/source/contributing/profiling/profiling_index.md
+++ b/docs/source/contributing/profiling/profiling_index.md
@@ -124,3 +124,52 @@ nsys stats report1.nsys-rep
 GUI example:
 
 <img width="1799" alt="Screenshot 2025-03-05 at 11 48 42 AM" src="https://github.com/user-attachments/assets/c7cff1ae-6d6f-477d-a342-bd13c4fc424c" />
+
+## Profiling vLLM Python Code
+
+The Python standard library includes
+[cProfile](https://docs.python.org/3/library/profile.html) for profiling Python
+code. vLLM includes a couple of helpers that make it easy to apply it to a section of vLLM.
+Both the `vllm.utils.cprofile` and `vllm.utils.cprofile_context` functions can be
+used to profile a section of code.
+
+### Example usage - decorator
+
+The first helper is a Python decorator that can be used to profile a function.
+If a filename is specified, the profile will be saved to that file. If no filename is
+specified, profile data will be printed to stdout.
+
+```python
+import vllm.utils
+
+@vllm.utils.cprofile("expensive_function.prof")
+def expensive_function():
+    # some expensive code
+    pass
+```
+
+### Example Usage - context manager
+
+The second helper is a context manager that can be used to profile a block of
+code. Similar to the decorator, the filename is optional.
+
+```python
+import vllm.utils
+
+def another_function():
+    # more expensive code
+    pass
+
+with vllm.utils.cprofile_context("another_function.prof"):
+    another_function()
+```
+
+### Analyzing Profile Results
+
+There are multiple tools available that can help analyze the profile results.
+One example is [snakeviz](https://jiffyclub.github.io/snakeviz/).
+
+```bash
+pip install snakeviz
+snakeviz expensive_function.prof
+```
diff --git a/vllm/utils.py b/vllm/utils.py
index 55ee044b..64d9faeb 100644
--- a/vllm/utils.py
+++ b/vllm/utils.py
@@ -2405,3 +2405,51 @@ def swap_dict_values(obj: dict[_K, _V], key1: _K, key2: _K) -> None:
         obj[key1] = v2
     else:
         obj.pop(key1, None)
+
+
+@contextlib.contextmanager
+def cprofile_context(save_file: Optional[str] = None):
+    """Run a cprofile
+
+    Args:
+        save_file: path to save the profile result. "1" or
+          None will result in printing to stdout.
+    """
+    import cProfile
+
+    prof = cProfile.Profile()
+    prof.enable()
+
+    try:
+        yield
+    finally:
+        prof.disable()
+        if save_file and save_file != "1":
+            prof.dump_stats(save_file)
+        else:
+            prof.print_stats(sort="cumtime")
+
+
+def cprofile(save_file: Optional[str] = None, enabled: bool = True):
+    """Decorator to profile a Python method using cProfile.
+
+    Args:
+        save_file: Path to save the profile result.
+            If "1", None, or "", results will be printed to stdout.
+        enabled: Set to false to turn this into a no-op
+    """
+
+    def decorator(func: Callable):
+
+        @wraps(func)
+        def wrapper(*args, **kwargs):
+            if not enabled:
+                # If profiling is disabled, just call the function directly.
+                return func(*args, **kwargs)
+
+            with cprofile_context(save_file):
+                return func(*args, **kwargs)
+
+        return wrapper
+
+    return decorator