Hello (sighs),
I’m unable to find proper versions for cuda enabled pytorch and its matching torchvision. I have tried multiple links, forum guides etc but all of them leads to some version mismatch errors in the end.
Can someone pls help me biuld correct and latest working versions? (If u had tried few weeks/months before this post then forget replying as they no longer work).
To start this thread with formal trial and error example, I’ll show my recent work below:
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Downloaded pytorch 2.8.0 from jp6/cu126 index [https://pypi.jetson-ai-lab.io/jp6/cu126/+f/564/4d4458f1ba159/torch-2.8.0-cp310-cp310-linux_aarch64.whl#sha256=5644d4458f1ba15950995f17f6ea91f3b3e4adf0d1dfef816b04a5d7325598c8\\]
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Installed the cusparselt and then Installed using pip install <.whl>
3. Ran python3 in terminal to import torch but ended up getting:
import torch
Traceback (most recent call last):
File “”, line 1, in
File “/home/nvidia/.local/lib/python3.10/site-packages/torch/init.py”, line 416, in
from torch._C import * # noqa: F403
ImportError: libnccl.so.2: cannot open shared object file: No such file or directory
quit()
before this one more error had come:
nvidia@nvidia-desktop:~$ python3
Python 3.10.12 (main, Aug 15 2025, 14:32:43) [GCC 11.4.0] on linux
Type “help”, “copyright”, “credits” or “license” for more information.
import torch
Traceback (most recent call last):
File “”, line 1, in
File “/home/nvidia/.local/lib/python3.10/site-packages/torch/init.py”, line 416, in
from torch._C import * # noqa: F403
ImportError: libcudss.so.0: cannot open shared object file: No such file or directory
but solved that using chatgpt (below is the response from chatgpt so solve ImportError: libcudss.so.0: cannot open shared object file: No such file or directory only :
CHATGPT reply below:
1. Download the Correct Archive
Run this command:
mkdir -p tmp_cudss && cd tmp_cudss
CUSPARSE_SOLVER_NAME="libcudss-linux-sbsa-0.6.0.5_cuda12-archive"
curl -L -O https://developer.download.nvidia.com/compute/cudss/redist/libcudss/linux-sbsa/${CUSPARSE_SOLVER_NAME}.tar.xz
Note: The -L flag ensures redirects are followed.
2. Extract and Install
tar xf ${CUSPARSE_SOLVER_NAME}.tar.xz
sudo cp -a ${CUSPARSE_SOLVER_NAME}/include/* /usr/local/cuda/include/
sudo cp -a ${CUSPARSE_SOLVER_NAME}/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudss
sudo ldconfig
3. Verify It Worked
ls /usr/local/cuda/lib64 | grep cudss
You should see:
libcudss.so
libcudss.so.0
4. Test PyTorch
python3 -c "import torch; print(torch.__version__)"
If everything went well, the import should now work without the missing library error.
#############################################################################
Coming back to the PyTorch wheels provided by NVIDIA — I’ve noticed some inconsistencies. Initially, the links pointed to a .dev domain, then later changed to .io, and the available wheels seem to change over time. Some versions install, but then lead to runtime errors.
This makes the developer experience quite frustrating. I’ve spent several days just trying to get PyTorch and torchvision set up properly on the Jetson kit, and it’s been more difficult than expected.
I really like the potential of the Jetson platform, but I think many users would benefit from clearer, stable, and well-documented support for essential libraries like PyTorch and torchvision.
Does anyone have a known working set of versions (torch + torchvision) for JetPack 6.2.1 that they could share? That would save a lot of time for developers who are just trying to get their projects running.
