Deepseek AI Deepseek R1 speed on RTX 4070 Super and quantization-level VRAM fit.
RTX 4070 Super meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek R1. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4070 Super can run Deepseek AI Deepseek R1 with Q4 quantization. At approximately 109 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 8GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 4GB | 12GB | 108.98 tok/s | ✅ Fits comfortably |
| Q8 | 7GB | 12GB | 76.29 tok/s | ✅ Fits comfortably |
| FP16 | 14GB | 12GB | 41.41 tok/s | ❌ Not recommended |
Check current pricing links for RTX 4070 Super and similar cards.
Open RTX 4070 Super 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 →Rent cloud GPUs by the hour — no upfront hardware cost.
RTX 4070 Super can run Deepseek AI Deepseek R1 at Q4 with an estimated 109 tok/s.
Q4 inference is estimated to need about 4GB 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.