Can I Run Qwen3 235B A22B Thinking 2507 on a NVIDIA H200?
Runs at Q4_K_S — good quality with reasonable headroom.
4 quantizations fit your 141GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_SBEST | 135.6 GB | 137.1 GB | 133.7 GB | +5.4 GB |
| Q3_K_M | 99.5 GB | 101.0 GB | 112.5 GB | +41.5 GB |
| Q3_K_S | 91.5 GB | 93.0 GB | 101.4 GB | +49.5 GB |
| Q2_K | 78.3 GB | 79.8 GB | 85.7 GB | +62.7 GB |
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FAQ
Can the NVIDIA H200 run Qwen3 235B A22B Thinking 2507?
Yes. The NVIDIA H200's 141GB of VRAM is enough to run Qwen3 235B A22B Thinking 2507 at Q4_K_S quantization (135.6GB required).
What's the best quantization to use?
Q4_K_S is the highest-precision quantization that fits in your 141GB. It uses about 135.6GB of memory and 137.1GB 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.