Openai Gpt Oss 20B speed on RTX 3080 and quantization-level VRAM fit.
RTX 3080 meets the minimum VRAM requirement for Q4 inference of Openai Gpt Oss 20B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 3080 can run Openai Gpt Oss 20B with Q4 quantization. At approximately 69 tokens/second, you can expect Good speed - acceptable for interactive use.
VRAM usage will be very close to your GPU's limit. Consider closing other applications or using Q3 quantization for more margin.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 10GB | 10GB | 69.13 tok/s | ⚠️ Tight fit |
| Q8 | 20GB | 10GB | 48.39 tok/s | ❌ Not recommended |
| FP16 | 40GB | 10GB | 26.27 tok/s | ❌ Not recommended |
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RTX 3080 can run Openai Gpt Oss 20B at Q4 with an estimated 69 tok/s.
Q4 inference is estimated to need about 10GB VRAM on this page, while RTX 3080 has 10GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.