Can I Run Qwen 3 Next 80B A3B on a NVIDIA RTX 6000 Ada?
Runs at Q4_K_S — good quality with reasonable headroom.
6 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_SBEST | 46.8 GB | 48.3 GB | 46.9 GB | +1.2 GB |
| Q4_0 | 46.0 GB | 47.5 GB | 46.1 GB | +2.0 GB |
| Q3_K_L | 36.6 GB | 38.1 GB | 38.2 GB | +11.4 GB |
| Q3_K_M | 34.5 GB | 36.0 GB | 36.7 GB | +13.5 GB |
| Q3_K_S | 31.8 GB | 33.3 GB | 34.9 GB | +16.2 GB |
| Q2_K | 27.3 GB | 28.8 GB | 28.2 GB | +20.7 GB |
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Top-ranked open-source models that fit in 48.0GB.
FAQ
Can the NVIDIA RTX 6000 Ada run Qwen 3 Next 80B A3B?
Yes. The NVIDIA RTX 6000 Ada's 48.0GB of VRAM is enough to run Qwen 3 Next 80B A3B at Q4_K_S quantization (46.8GB required).
What's the best quantization to use?
Q4_K_S is the highest-precision quantization that fits in your 48.0GB. It uses about 46.8GB of memory and 48.3GB 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.