AMD or NVIDIA for Local AI?

ROCm 10 just changed the answer · October 2026

For years, if you asked me what to buy for running AI on your own machine, the answer was easy: NVIDIA. Not because their cards were always faster, but because their software, CUDA, was the only thing everything just worked on. AMD's version, ROCm, was Linux-only, picky about which cards it supported, and a headache to set up.

That has changed a lot this year.

What AMD Just Did

AMD released ROCm 10 at the end of August, skipping straight from version 7, and ROCm 10.1 dropped on October 5. The big points:

• Windows 11 is supported now, not just Linux.
• It works across the Radeon AI PRO R9700, the whole RX 9000 lineup, and the RX 7000 cards like the 7900 XTX.
• The major AI tools are on board, including PyTorch and vLLM.
• AMD claims around 3.3x faster inference and 2.4x faster training compared to ROCm 7. Those are AMD's numbers, and I'm waiting on independent testing before I take them as gospel.

Where NVIDIA Still Wins

• Everything supports it first. New AI tools and models almost always show up on CUDA before anything else. If you want zero friction, NVIDIA is still the safe bet.
• The biggest single card. The RTX PRO 6000 Blackwell has 96GB of memory on one card. Nothing from AMD matches that in a single card right now.
• Raw speed at the top end. If you want the fastest card money can buy and budget isn't the issue, NVIDIA still holds that crown.

Where AMD Wins Now

• Memory for the money. For local AI, memory decides what you can run. The Radeon AI PRO R9700 gives you 32GB for a fraction of what NVIDIA charges for that much.
• Two cards punch above their weight. In Phoronix's testing, two R9700s matched the response speed of NVIDIA's RTX 6000 Ada workstation card while costing far less.
• Open source. ROCm is open, which matters for businesses that don't want to be locked into one vendor.

Don't Forget Intel

Intel's Arc Pro B60 (24GB) and B70 (32GB) are the budget way into local AI. They're not the fastest, but they get a lot of memory into a machine without the big price tag.

So Which Is Better?

• Go NVIDIA if you need the biggest models on one card, want every tool to work on day one, or the budget is wide open.
• Go AMD if you want the most memory for your money, are running mid-size models, or want to scale with two or more cards.
• Go Intel if you're just getting into local AI and want to keep the cost down.

The honest answer is that it depends on what you want to run. That's the conversation I have with every customer before I spec a build. Check out the AI GPU lineup and the AI workstation builds, or text me and I'll match the card to the job.

Sources: AMD ROCm 10.1.0 release notes · AMD Newsroom: ROCm 10 · Phoronix: Radeon AI PRO R9700 benchmarks (tested on ROCm 7)