diff --git a/docs/source/getting_started/installation/gpu-cuda.md b/docs/source/getting_started/installation/gpu-cuda.md
index 1cd513177bf0d..c985c6dd47cc9 100644
--- a/docs/source/getting_started/installation/gpu-cuda.md
+++ b/docs/source/getting_started/installation/gpu-cuda.md
@@ -2,7 +2,7 @@
 
 # Installation for CUDA
 
-vLLM is a Python library that also contains pre-compiled C++ and CUDA (12.1) binaries.
+vLLM is a Python library that also contains pre-compiled C++ and CUDA (12.4) binaries.
 
 ## Requirements
 
@@ -43,12 +43,12 @@ Therefore, it is recommended to install vLLM with a **fresh new** environment. I
 You can install vLLM using either `pip` or `uv pip`:
 
 ```console
-$ # Install vLLM with CUDA 12.1.
+$ # Install vLLM with CUDA 12.4.
 $ pip install vllm # If you are using pip.
 $ uv pip install vllm # If you are using uv.
 ```
 
-As of now, vLLM's binaries are compiled with CUDA 12.1 and public PyTorch release versions by default. We also provide vLLM binaries compiled with CUDA 11.8 and public PyTorch release versions:
+As of now, vLLM's binaries are compiled with CUDA 12.4 and public PyTorch release versions by default. We also provide vLLM binaries compiled with CUDA 11.8 and public PyTorch release versions:
 
 ```console
 $ # Install vLLM with CUDA 11.8.