Sketchy inforrmation and loadsa misleading stuff, but anyway, here goes...
1. Find your CUDA version
2. Find the code you need from here:
https://developer.nvidia.com/cudnn-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=24.04&target_type=deb_local
Click the matrix to get the code:
$ wget https://developer.download.nvidia.com/compute/cudnn/9.14.0/local_installers/cudnn-local-repo-ubuntu2404-9.14.0_1.0-1_amd64.deb
$ sudo dpkg -i cudnn-local-repo-ubuntu2404-9.14.0_1.0-1_amd64.deb
$ sudo cp /var/cudnn-local-repo-ubuntu2404-9.14.0/cudnn-*-keyring.gpg /usr/share/keyrings/
$ sudo apt-get update
$ sudo apt-get -y install cudnn9-cuda-13Check the installationI used the venv I already had for setiastrosuitepro:
(venv) steve@pop-os:~/setiastrosuitepro$ python
Python 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.backends.cudnn.version())
91002
>>>
**EDIT
(venv) steve@pop-os:~/setiastrosuitepro$ python
Python 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.backends.cudnn.version())
91002
>>>
**EDIT
Also works for Kubuntu 25.10
for the GraXpert stuff to work in both seti and siril, we needed:
sudo apt-get -y install cudnn9-cuda-12
And don't forget that for the venv this is also neededfor the GraXpert stuff to work in both seti and siril, we needed:
sudo apt-get -y install cudnn9-cuda-12
sudo apt install python3-venv
We just installed via that command from a system prompt. No reference to version numbers seemed necessary. It's working at least😁



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