Can I Run GPT-OSS 120B on a NVIDIA H100 80GB?
Runs at Q4_K_M — good quality with reasonable headroom.
1 quant fit your 80.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_MBEST | 73.8 GB | 75.3 GB | 72.8 GB | +6.3 GB |
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FAQ
Can the NVIDIA H100 80GB run GPT-OSS 120B?
Yes. The NVIDIA H100 80GB's 80.0GB of VRAM is enough to run GPT-OSS 120B at Q4_K_M quantization (73.8GB required).
What's the best quantization to use?
Q4_K_M is the highest-precision quantization that fits in your 80.0GB. It uses about 73.8GB of memory and 75.3GB 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.