Mlx Community Gpt Oss 20B Mxfp4 Q8 speed on NVIDIA A100 80GB SXM4 and quantization-level VRAM fit.
NVIDIA A100 80GB SXM4 meets the minimum VRAM requirement for Q4 inference of Mlx Community Gpt Oss 20B Mxfp4 Q8. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA A100 80GB SXM4 can run Mlx Community Gpt Oss 20B Mxfp4 Q8 with Q4 quantization. At approximately 161 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 70GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 10GB | 80GB | 160.64 tok/s | ✅ Fits comfortably |
| Q8 | 20GB | 80GB | 112.44 tok/s | ✅ Fits comfortably |
| FP16 | 40GB | 80GB | 61.04 tok/s | ✅ Fits comfortably |
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NVIDIA A100 80GB SXM4 can run Mlx Community Gpt Oss 20B Mxfp4 Q8 at Q4 with an estimated 161 tok/s.
Q4 inference is estimated to need about 10GB VRAM on this page, while NVIDIA A100 80GB SXM4 has 80GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.