microsoft / microsoft/TRELLIS.2

Ubuntu 24.04 with CUDA 13.1 + RTX 5090 impossible to use it

Open
#19 12 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
11.3k
Forks
1.4k
PR merge metrics
No merged PRs in 30d

Description

I am trying to get it work with help from copilot but its extremely impossible level to install this on with

nvidia-smi
Wed Dec 17 22:44:48 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 590.44.01              Driver Version: 590.44.01      CUDA Version: 13.1     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 5090        On  |   00000000:01:00.0  On |                  N/A |
|  0%   43C    P0             54W /  600W |    1091MiB /  32607MiB |      3%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

Can Microsoft fix for newest cuda to install it?
At this momment I can't compile anything. I just countless see errors


raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
      RuntimeError:
      The detected CUDA version (13.1) mismatches the version that was used to compile
      PyTorch (12.4). Please make sure to use the same CUDA versions.

I got dual boot with win 11 + ubuntu 24.04 but both ways I am on same. I really need help.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No project file or test is named. Start by reading the repository's installation instructions and reproducing the reported environment on Ubuntu 24.04 with the RTX 5090, then inspect the dependency and PyTorch CUDA requirements. Done means the supported installation can compile without the reported CUDA 13.1 versus PyTorch 12.4 mismatch.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch, ubuntu
Domain
machine-learning, operating-systems
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
32/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.