Openai Gpt Oss 20B speed on RTX 4070 Super and quantization-level VRAM fit.
RTX 4070 Super 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 4070 Super can run Openai Gpt Oss 20B with Q4 quantization. At approximately 48 tokens/second, you can expect Moderate speed - useful for batch processing.
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 | 12GB | 47.95 tok/s | ✅ Fits comfortably |
| Q8 | 20GB | 12GB | 33.57 tok/s | ❌ Not recommended |
| FP16 | 40GB | 12GB | 18.22 tok/s | ❌ Not recommended |
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RTX 4070 Super can run Openai Gpt Oss 20B at Q4 with an estimated 48 tok/s.
Q4 inference is estimated to need about 10GB VRAM on this page, while RTX 4070 Super has 12GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.