Deepseek AI Deepseek R1 Distill Llama 8B speed on RTX 4070 Ti Super and quantization-level VRAM fit.
RTX 4070 Ti Super meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek R1 Distill Llama 8B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4070 Ti Super can run Deepseek AI Deepseek R1 Distill Llama 8B 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 | 5GB | 16GB | 106.13 tok/s | ✅ Fits comfortably |
| Q8 | 9GB | 16GB | 74.29 tok/s | ✅ Fits comfortably |
| FP16 | 17GB | 16GB | 40.33 tok/s | ❌ Not recommended |
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RTX 4070 Ti Super can run Deepseek AI Deepseek R1 Distill Llama 8B at Q4 with an estimated 106 tok/s.
Q4 inference is estimated to need about 5GB VRAM on this page, while RTX 4070 Ti Super has 16GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.