AMD Radeon RX 580 8GB
AMD Polaris with 8 GB VRAM. Cheap on used market ($70-100) but Polaris was dropped from ROCm in 2022, so AMD's official AI runtimes won't work. Vulkan via llama.cpp is the only practical path; performance is bandwidth-limited at ~10-20 tok/s on 7B Q4. Mostly relevant for 'I already own one' operators, not buy-this-for-AI.
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Sub-scores sum to 245 / 1000. Headline = 245 × 0.70 (Estimated-confidence discount) = 172. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →
Extrapolated from 256 GB/s bandwidth — 25.6 tok/s estimated. No measured benchmarks yet.
Plain-English: Edge-of-fit for 7B; expect compromises.
Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.
This card is for the operator who already has one in a drawer and wants to experiment with local inference on a tight budget. It is not a card to buy specifically for AI work.
On 7B Q4 models, expect 10-20 tok/s via Vulkan in llama.cpp — usable for chat but not real-time. 13B Q4 models run at 5-10 tok/s, and 8 GB VRAM limits to 13B Q4 or 7B Q8. No room for larger models or context beyond 4K.
The ROCm stack dropped Polaris in 2022, so Vulkan is the only path. No CUDA, no official AMD AI tools. Expect rough edges: no flash attention, no speculative decoding, and potential driver quirks on Linux.
Pass if you are buying a GPU for AI. For $80-100, a used RTX 3060 12GB delivers 2-3x the performance and full CUDA support. This card only makes sense if it is already in the rig and the budget is zero.
At $80 used, the price is tempting, but the performance ceiling and software limitations make it a poor investment for serious local AI work.
›Why this rating
The RX 580 is usable for small models at modest speeds, but the lack of ROCm, CUDA, and modern features cripples its utility. The rating reflects its value only as a free or near-free entry point, not as a purposeful AI purchase.
Overview
AMD Polaris with 8 GB VRAM. Cheap on used market ($70-100) but Polaris was dropped from ROCm in 2022, so AMD's official AI runtimes won't work. Vulkan via llama.cpp is the only practical path; performance is bandwidth-limited at ~10-20 tok/s on 7B Q4. Mostly relevant for 'I already own one' operators, not buy-this-for-AI.
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Specs
| VRAM | 8 GB |
| Power draw (peak) | 185 W |
| Released | 2017 |
| MSRP | $229 |
| Backends | Vulkan |
Models that fit
Open-weight models small enough to run on AMD Radeon RX 580 8GB with usable context.
Frequently asked
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Where next?
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.