CUDA 13.2 Upgrade and Compatibility Guide

CUDA 13.2 Upgrade and Compatibility Guide | Generated by AI

Home 2026.03

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?

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