Can I Run GPT-OSS 120B 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 | 241.8 GB | 243.3 GB | 65.4 GB | +542.2 GB |
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FAQ
Can the NVIDIA DGX Station (Blackwell Ultra) run GPT-OSS 120B?
Yes. The NVIDIA DGX Station (Blackwell Ultra)'s 784GB of unified memory is enough to run GPT-OSS 120B at fp16 quantization (241.8GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 784GB. It uses about 241.8GB of memory and 243.3GB 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.