Can I Run Qwen 3.5 9B on a NVIDIA DGX Station (Blackwell Ultra)?
Runs at full precision (fp16). Zero quality loss.
5 quantizations fit your 784GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 19.0 GB | 20.5 GB | 18.0 GB | +765.0 GB |
| Q8_0 | 10.6 GB | 12.1 GB | 9.6 GB | +773.4 GB |
| Q6_K | 8.4 GB | 9.9 GB | 7.4 GB | +775.6 GB |
| Q5_K_M | 7.4 GB | 8.9 GB | 6.4 GB | +776.6 GB |
| Q4_K_M | 6.5 GB | 8.0 GB | 5.5 GB | +777.5 GB |
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FAQ
Can the NVIDIA DGX Station (Blackwell Ultra) run Qwen 3.5 9B?
Yes. The NVIDIA DGX Station (Blackwell Ultra)'s 784GB of unified memory is enough to run Qwen 3.5 9B at fp16 quantization (19.0GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 784GB. It uses about 19.0GB of memory and 20.5GB 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.