AMD GPUs for Local AI: Prices, VRAM & the ROCm Reality
NVIDIA dominates the local-AI conversation, but AMD quietly offers some of the best $/GB VRAM on the market. A RX 7900 XTX gives you 24GB at $620, undercutting a used RTX 3090, and the workstation Radeon Pro W7900 packs 48GB on a single card. The question every buyer asks first: does AMD actually work for AI?
Short version: yes, but with an asterisk. AMD runs LLMs through ROCm instead of CUDA, and that's a real difference. Here's the honest picture, plus live prices for the cards people search for.
The ROCm vs CUDA Reality
This is the thing to understand before you buy AMD for AI. NVIDIA's CUDA is the default everything is built against. AMD's equivalent is ROCm, and the gap has narrowed a lot, but it hasn't closed:
- Inference is fine: llama.cpp (Vulkan/ROCm), Ollama, and LM Studio all run well on modern Radeon cards. For just running LLMs locally, AMD is a non-issue today.
- Training is where it bites: many fine-tuning repos assume CUDA. You'll hit more friction, fewer prebuilt wheels, and the occasional unsupported op.
- Setup is fiddlier: ROCm support varies by card and OS. Linux is the happy path; Windows support is improving but still trails.
- RDNA2 (RX 6000) is older: ROCm support exists but is rougher than on RDNA3 (RX 7000). For a 6700 XT, Vulkan-backed llama.cpp is often the smoother route.
Rule of thumb: buy AMD if you mainly want inference and value VRAM per dollar. Stick with NVIDIA if you plan to fine-tune or want zero setup friction.
AMD Cards for AI: Used Price & $/GB
| GPU | VRAM | Used Price | $/GB | Best For |
|---|---|---|---|---|
| RX 6700 XT | 12GB | $300 | $25.00/GB | Cheapest entry. 7-8B models, gaming double-duty. |
| RX 7900 XT | 20GB | $535 | $26.75/GB | 20GB sweet spot for 14-30B models. |
| RX 7900 XTX | 24GB | $620 | $25.83/GB | Best consumer value. 24GB + display out + fast. |
| Radeon Pro W7800 | 32GB | $1,900 | $59.38/GB | 32GB workstation card. Quiet blower, ECC. |
| Radeon Pro W7900 | 48GB | $3,550 | $73.96/GB | 48GB single card. AMD's answer to the A6000. |
The RX 7900 XTX is the standout: 24GB of fast GDDR6 (960 GB/s) at $620, with display output and a normal cooler, typically cheaper than a used RTX 3090 with the same VRAM. For inference, it's one of the best value 24GB cards you can buy. The cheapest 24GB GPU comparison puts it in context against the NVIDIA options.
Which AMD Card Should You Buy?
- Tightest budget, also game: RX 6700 XT at $300. 12GB runs 7-8B models; use Vulkan llama.cpp for the smoothest path.
- Best all-round value: RX 7900 XTX at $620. 24GB, fast, display output, runs 30B-class models at Q4.
- Step between: RX 7900 XT at $535 if 20GB is enough and you want to save a little.
- Need 32-48GB on one card: W7800 (32GB) or W7900 (48GB). Compare against the RTX A6000 before committing, CUDA may be worth the premium at this tier.
Check ROCm support for your exact card and OS
Before buying, confirm your target card is on AMD's current ROCm support list for your operating system, especially for older RDNA2 (RX 6000) cards and on Windows. For pure inference you can often fall back to Vulkan-backed llama.cpp, which is more forgiving, but verify first so you're not surprised.
Verdict
Great value for inference. Mind the ROCm tax for training.
AMD offers excellent VRAM per dollar, and for running LLMs locally the software story is good enough that the RX 7900 XTX at $620 is a genuinely smart buy. If you mainly want to run models, not train them, don't dismiss AMD on reputation alone.
If you plan to fine-tune, want the absolute smoothest setup, or value the largest software ecosystem, NVIDIA still earns its premium. Match the card to what you'll actually do, and price it by $/GB.
Compare AMD Prices Live
GPUDojo ranks every AMD and NVIDIA GPU by $/GB VRAM with live used prices.
See the Full RankingAlso see the cheapest 24GB GPUs and the RTX A6000 48GB breakdown.