Openai Community Gpt2 Xl speed on RTX 4070 Ti and quantization-level VRAM fit.
RTX 4070 Ti meets the minimum VRAM requirement for Q4 inference of Openai Community Gpt2 Xl. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4070 Ti can run Openai Community Gpt2 Xl with Q4 quantization. At approximately 106 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 11GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 12GB | 106.31 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 12GB | 74.42 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 12GB | 40.40 tok/s | ✅ Fits comfortably |
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RTX 4070 Ti can run Openai Community Gpt2 Xl at Q4 with an estimated 106 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while RTX 4070 Ti has 12GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.