diff --git a/docs/contributing/profiling.md b/docs/contributing/profiling.md
index e4bb0b696..1d12d6354 100644
--- a/docs/contributing/profiling.md
+++ b/docs/contributing/profiling.md
@@ -3,6 +3,10 @@
 !!! warning
     Profiling is only intended for vLLM developers and maintainers to understand the proportion of time spent in different parts of the codebase. **vLLM end-users should never turn on profiling** as it will significantly slow down the inference.
 
+!!! tip "Choosing a profiler"
+    - Use **Nsight Systems** for low-overhead, performance-critical profiling.
+    - Use **PyTorch Profiler** for medium-overhead profiling with richer debugging information (e.g., stack traces, memory, shapes). Note that enabling these features adds overhead and is not recommended for benchmarking.
+
 ## Profile with PyTorch Profiler
 
 We support tracing vLLM workers using different profilers. You can enable profiling by setting the `--profiler-config` flag when launching the server.
diff --git a/vllm/config/profiler.py b/vllm/config/profiler.py
index 6a40b9dad..e79e21310 100644
--- a/vllm/config/profiler.py
+++ b/vllm/config/profiler.py
@@ -45,10 +45,10 @@ class ProfilerConfig:
     worker's traces (CPU & GPU) will be saved under this directory. Note that
     it must be an absolute path."""
 
-    torch_profiler_with_stack: bool = False
-    """If `True`, enables stack tracing in the torch profiler. Disabled by default
-    to reduce overhead. Can be enabled via VLLM_TORCH_PROFILER_WITH_STACK=1 env var
-    or --profiler-config.torch_profiler_with_stack=true CLI flag."""
+    torch_profiler_with_stack: bool = True
+    """If `True`, enables stack tracing in the torch profiler. Enabled by default
+    as it is useful for debugging. Can be disabled via 
+    --profiler-config.torch_profiler_with_stack=false CLI flag."""
 
     torch_profiler_with_flops: bool = False
     """If `True`, enables FLOPS counting in the torch profiler. Disabled by default."""