Installing PyTorch with the Correct CUDA Version

A common mistake when installing PyTorch is specifying the CUDA version incorrectly. This post clarifies the correct approach and walks through diagnosing a real-world CUDA driver mismatch error.

The Wrong Way

You might instinctively try something like:

pip install torch==128
# or
pip install torch==cu128

Neither of these is correct. The == operator in pip specifies the PyTorch package version (e.g., 2.7.0), not the CUDA toolkit version.

The Right Way

CUDA version selection is done via --index-url, which points pip to a wheel repository built for a specific CUDA version:

# CUDA 12.8
pip install torch --index-url https://download.pytorch.org/whl/cu128

# CUDA 12.4
pip install torch --index-url https://download.pytorch.org/whl/cu124

# CPU only
pip install torch --index-url https://download.pytorch.org/whl/cpu

To pin both the PyTorch version and the CUDA version:

pip install torch==2.7.0 --index-url https://download.pytorch.org/whl/cu128

A Real-World Error: CUDA Driver Too Old

After installing PyTorch without specifying --index-url, you may encounter:

python3.12/site-packages/torch/cuda/__init__.py:187: UserWarning:
CUDA initialization: The NVIDIA driver on your system is too old
(found version 12080). Please update your GPU driver...

What This Means

  • found version 12080 corresponds to CUDA 12.8.
  • The default pip install torch pulled a PyTorch build compiled against a newer CUDA version (e.g., 12.9+).
  • Your NVIDIA driver only supports up to CUDA 12.8, so the newer build fails to initialize.

How to Fix It

Option 1: Install PyTorch matching your driver (recommended)

First, check your driver’s CUDA version:

nvidia-smi

Look at the top-right corner for CUDA Version: 12.8. Then install the matching build:

pip install torch --index-url https://download.pytorch.org/whl/cu128

Option 2: Upgrade your NVIDIA driver

Download the latest driver from NVIDIA Driver Downloads. A newer driver will support higher CUDA versions, allowing the default PyTorch build to work.

Key Takeaway

What you want to specify How to specify it
PyTorch version pip install torch==2.7.0
CUDA version --index-url https://download.pytorch.org/whl/cu128
Both pip install torch==2.7.0 --index-url https://download.pytorch.org/whl/cu128

Always run nvidia-smi first to know which CUDA version your driver supports, then pick the matching --index-url.