Openai Gpt Oss 120B speed on NVIDIA RTX 6000 Ada and quantization-level VRAM fit.
NVIDIA RTX 6000 Ada does not meet the minimum VRAM requirement for Q4 inference of Openai Gpt Oss 120B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA RTX 6000 Ada lacks sufficient VRAM for comfortable Openai Gpt Oss 120B operation with Q4 quantization.
Your 48GB GPU is 12GB short of the 60GB minimum.
Options: (1) Try Q2 or Q3 quantization for lower VRAM requirements, (2) Consider cloud GPU rental, (3) Upgrade to a GPU with at least 16GB VRAM.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 60GB | 48GB | 35.70 tok/s | ❌ Not recommended |
| Q8 | 120GB | 48GB | 24.99 tok/s | ❌ Not recommended |
| FP16 | 240GB | 48GB | 13.57 tok/s | ❌ Not recommended |
Check current pricing links for NVIDIA RTX 6000 Ada and similar cards.
Open NVIDIA RTX 6000 Ada buy links →Use workload-focused recommendations before committing to a purchase.
Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →Your GPU doesn't meet the VRAM requirements. Run Openai Gpt Oss 120B on cloud GPU instantly.
NVIDIA RTX 6000 Ada is not a comfortable Q4 fit for Openai Gpt Oss 120B (about 60GB needed).
Q4 inference is estimated to need about 60GB VRAM on this page, while NVIDIA RTX 6000 Ada has 48GB available.
Try lower-bit quantization, choose a smaller model, or move to a higher-VRAM GPU from the alternatives list.