Can I Run Qwen 3 Next 80B A3B on a NVIDIA A100 80GB?
Runs comfortably at Q6_K — minimal quality loss.
12 quantizations fit your 80.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 66.9 GB | 68.4 GB | 65.5 GB | +13.1 GB |
| Q5_K_M | 57.8 GB | 59.3 GB | 56.7 GB | +22.2 GB |
| Q5_K_S | 56.2 GB | 57.7 GB | 55.0 GB | +23.8 GB |
| Q5_0 | 56.0 GB | 57.5 GB | 55.0 GB | +24.0 GB |
| Q4_1 | 51.0 GB | 52.5 GB | 50.0 GB | +29.0 GB |
| Q4_K_M | 49.5 GB | 51.0 GB | 48.7 GB | +30.5 GB |
| Q4_K_S | 46.8 GB | 48.3 GB | 46.9 GB | +33.2 GB |
| Q4_0 | 46.0 GB | 47.5 GB | 46.1 GB | +34.0 GB |
| Q3_K_L | 36.6 GB | 38.1 GB | 38.2 GB | +43.4 GB |
| Q3_K_M | 34.5 GB | 36.0 GB | 36.7 GB | +45.5 GB |
| Q3_K_S | 31.8 GB | 33.3 GB | 34.9 GB | +48.2 GB |
| Q2_K | 27.3 GB | 28.8 GB | 28.2 GB | +52.7 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 80.0GB.
FAQ
Can the NVIDIA A100 80GB run Qwen 3 Next 80B A3B?
Yes. The NVIDIA A100 80GB's 80.0GB of VRAM is enough to run Qwen 3 Next 80B A3B at Q6_K quantization (66.9GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 80.0GB. It uses about 66.9GB of memory and 68.4GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.