---
# System prepended metadata

title: Install PyTorch 2.8.0 + CUDA 12.8 in WSL Ubuntu 24.04/22.04
tags: [Note]

---

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.