This page answers Mlx Community Gpt Oss 20B Mxfp4 Q8 q6_k quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.
Short answer: Mlx Community Gpt Oss 20B Mxfp4 Q8 typically needs around 18GB VRAM at Q6_K, and 22GB is safer for smoother usage.
Estimated between Q4 and Q8 using a weighted interpolation toward Q8 memory footprint.
Throughput data below uses available compatibility measurements/estimates and is sorted by tokens per second for this model.
Need general guidance? Review full methodology.
| GPU | VRAM | Quantization | Speed | Compatibility | Buy |
|---|---|---|---|---|---|
| AMD Instinct MI300X | 192GB | Q8 | 294 tok/s | View full compatibility | Buy options |
| NVIDIA H200 SXM 141GB | 141GB | Q8 | 265 tok/s | View full compatibility | Buy options |
| NVIDIA H100 SXM5 80GB | 80GB | Q8 | 191 tok/s | View full compatibility | Buy options |
| AMD Instinct MI250X | 128GB | Q8 | 184 tok/s | View full compatibility | Buy options |
| NVIDIA H100 PCIe 80GB | 80GB | Q8 | 121 tok/s | View full compatibility | Buy options |
| RTX 5090 | 32GB | Q8 | 115 tok/s | View full compatibility | Buy options |
| NVIDIA A100 80GB SXM4 | 80GB | Q8 | 112 tok/s | View full compatibility | Buy options |
| AMD Instinct MI210 | 64GB | Q8 | 92 tok/s | View full compatibility | Buy options |
| NVIDIA A100 40GB PCIe | 40GB | Q8 | 87 tok/s | View full compatibility | Buy options |
| RTX 4090 | 24GB | Q8 | 69 tok/s | View full compatibility | Buy options |
| NVIDIA RTX 6000 Ada | 48GB | Q8 | 69 tok/s | View full compatibility | Buy options |
| NVIDIA L40 | 48GB | Q8 | 64 tok/s | View full compatibility | Buy options |
Mlx Community Gpt Oss 20B Mxfp4 Q8 at Q6_K is estimated to require about 18GB VRAM minimum, with 22GB recommended for smoother operation.
Start with AMD Instinct MI300X, NVIDIA H200 SXM 141GB, NVIDIA H100 SXM5 80GB and review each compatibility page for full speed and fit details.
Q6_K is a balance point between memory usage and quality. If your GPU is below 18GB, consider lower-bit quantization; if you have extra VRAM, compare Q8/FP16 options for quality-sensitive workloads.