Can I Run Qwen3 VL 235B A22B Instruct on a NVIDIA H200?
Runs at Q4_K_S — good quality with reasonable headroom.
5 quantizations fit your 141GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_SBEST | 135.9 GB | 137.4 GB | 133.7 GB | +5.1 GB |
| Q3_K_L | 105.9 GB | 107.4 GB | 121.8 GB | +35.1 GB |
| Q3_K_M | 99.7 GB | 101.2 GB | 112.5 GB | +41.3 GB |
| Q3_K_S | 91.7 GB | 93.2 GB | 101.4 GB | +49.3 GB |
| Q2_K | 78.5 GB | 80.0 GB | 85.7 GB | +62.5 GB |
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FAQ
Can the NVIDIA H200 run Qwen3 VL 235B A22B Instruct?
Yes. The NVIDIA H200's 141GB of VRAM is enough to run Qwen3 VL 235B A22B Instruct at Q4_K_S quantization (135.9GB required).
What's the best quantization to use?
Q4_K_S is the highest-precision quantization that fits in your 141GB. It uses about 135.9GB of memory and 137.4GB 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.