CUDA 13.2 Upgrade and Compatibility Guide | Generated by AI
Here’s the breakdown:
📊 CUDA 13.2 Availability
| Check | Result |
|---|---|
cuda-toolkit-13-2 in repo? |
✅ Yes — available |
| Driver 580 supports it? | ✅ Yes — driver 580 ships with CUDA 13.0 runtime, compatible with 13.2 toolkit |
| Currently installed | CUDA 12.8 (toolkit) + Driver 580.126.09 |
Available toolkit versions in the repo:
- 12.5, 12.6, 12.8, 12.9
- 13.0, 13.1, 13.2 ← latest
✅ Yes, you can upgrade to 13.2
The driver 580 supports it. The install would be:
apt install cuda-toolkit-13-2
Then update PATH to /usr/local/cuda-13.2/bin. You could also keep 12.8 alongside it — CUDA toolkits are versioned side by side (/usr/local/cuda-12.8/ and /usr/local/cuda-13.2/), switchable via symlink or PATH.
⚠️ Things to consider
- PyTorch/TensorFlow compatibility — most frameworks currently target CUDA 12.x. CUDA 13.x support is still rolling out. If you’re planning to run ML workloads, 12.8 is the safer bet right now.
- Side-by-side is fine — no need to remove 12.8, just add 13.2 and switch PATH
- Driver is fine as-is — no need to upgrade the driver for CUDA 13.2
Want me to install 13.2 (keep 12.8 alongside), or replace 12.8 entirely?