Can I Run Qwen3 VL 235B A22B Instruct on a NVIDIA DGX Station (Blackwell Ultra)?
Runs at full precision (fp16). Zero quality loss.
1 quant fit your 784GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 472.4 GB | 473.9 GB | 1.2 GB | +311.6 GB |
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FAQ
Can the NVIDIA DGX Station (Blackwell Ultra) run Qwen3 VL 235B A22B Instruct?
Yes. The NVIDIA DGX Station (Blackwell Ultra)'s 784GB of unified memory is enough to run Qwen3 VL 235B A22B Instruct at fp16 quantization (472.4GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 784GB. It uses about 472.4GB of memory and 473.9GB 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.