Install PyTorch 2.8.0 + CUDA 12.8 in WSL Ubuntu 24.04/22.04 = ###### tags: `Note` 1. Uninstall the old version ```bash= $ sudo apt-get --purge remove "*cuda*" "*cublas*" "*cufft*" "*cufile*" "*curand*" "*cusolver*" "*cusparse*" "*gds-tools*" "*npp*" "*nvjpeg*" "nsight*" $ sudo rm -r /usr/local/cuda-X.X ``` 2. Install CUDA tool kit Check [CUDA on WSL User Guide](https://docs.nvidia.com/cuda/wsl-user-guide/index.html) first because version may vary. ```bash= $ wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin $ sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600 $ wget https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda-repo-wsl-ubuntu-12-8-local_12.8.0-1_amd64.deb $ sudo dpkg -i cuda-repo-wsl-ubuntu-12-8-local_12.8.0-1_amd64.deb $ sudo cp /var/cuda-repo-wsl-ubuntu-12-8-local/cuda-*-keyring.gpg /usr/share/keyrings/ $ sudo apt-get update $ sudo apt-get -y install cuda-toolkit-12-8 ``` 3. Add to `$PATH` ```bash= $ export LD_LIBRARY_PATH=/usr/local/cuda-12.8/lib64 $ export CUDA_HOME=/usr/local/cuda-12.8 $ export PATH=$CUDA_HOME/bin:$PATH $ export PATH=/usr/local/cuda/bin:$PATH ``` 4. Install PyTorch ```bash= $ conda create -n myenv python=3.10 $ conda activate myenv (myenv) $ pip3 install torch torchvision ``` ↑ as for now (9/9/2025) or ```bash= (myenv) $ pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu128 ``` 5. Check GPU availability ```bash= (myenv) $ python >>> import torch >>> torch.cuda.is_available() ``` Should return `True` if you're lucky.