AMD Radeon RX 6900 XT
RDNA 2 flagship. 16 GB VRAM at 512 GB/s, more compute than the 6800 XT. ROCm officially supported. ~95-130 tok/s on 7B Q4. The peak of RDNA 2 consumer AMD; used $450-550 in 2026. Comfortable for any 7B/13B + 32B Q4 with offload.
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Sub-scores sum to 432 / 1000. Headline = 432 × 0.70 (Estimated-confidence discount) = 302. 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 512 GB/s bandwidth — 51.2 tok/s estimated. No measured benchmarks yet.
Plain-English: Comfortable at 14B and below — snappy enough for a coding agent.
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 wants to run 13B and 32B models at home without compromise, and who is comfortable with AMD's ROCm stack. The RX 6900 XT delivers 95-130 tok/s on 7B Q4, 50-70 tok/s on 13B Q4, and can handle 32B Q4 with partial offload at 20-30 tok/s. The 16 GB VRAM is a sweet spot for local inference, enabling full 13B Q4 models and most 32B Q4 models with some offloading. What breaks: ROCm support, while official, still lags behind CUDA in ecosystem maturity—some newer model architectures or custom kernels may require workarounds. The 300W TDP means the rig needs adequate cooling and power supply. When to pass: if the workload demands 70B+ models or requires plug-and-play compatibility with the latest PyTorch features, a used RTX 3090 with 24 GB VRAM and CUDA is a better fit. At ~$500 used, this card offers strong value for local AI inference, especially for operators willing to navigate ROCm's quirks.
›Why this rating
The RX 6900 XT offers excellent VRAM and bandwidth for its used price, making it a strong choice for 13B and 32B models. However, ROCm's ecosystem limitations and higher power draw prevent it from being a top-tier recommendation for all local AI workloads.
Overview
RDNA 2 flagship. 16 GB VRAM at 512 GB/s, more compute than the 6800 XT. ROCm officially supported. ~95-130 tok/s on 7B Q4. The peak of RDNA 2 consumer AMD; used $450-550 in 2026. Comfortable for any 7B/13B + 32B Q4 with offload.
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Specs
| VRAM | 16 GB |
| Power draw (peak) | 300 W |
| Released | 2020 |
| MSRP | $999 |
| Backends | ROCm Vulkan |
Models that fit
Open-weight models small enough to run on AMD Radeon RX 6900 XT 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.