Deepseek AI Deepseek Coder V2 Instruct 0724 speed on NVIDIA RTX 6000 Ada and quantization-level VRAM fit.
NVIDIA RTX 6000 Ada meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek Coder V2 Instruct 0724. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA RTX 6000 Ada can run Deepseek AI Deepseek Coder V2 Instruct 0724 with Q4 quantization. At approximately 45 tokens/second, you can expect Moderate speed - useful for batch processing.
You have 12GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 36GB | 48GB | 44.62 tok/s | ✅ Fits comfortably |
| Q8 | 72GB | 48GB | 31.24 tok/s | ❌ Not recommended |
| FP16 | 144GB | 48GB | 16.96 tok/s | ❌ Not recommended |
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NVIDIA RTX 6000 Ada can run Deepseek AI Deepseek Coder V2 Instruct 0724 at Q4 with an estimated 45 tok/s.
Q4 inference is estimated to need about 36GB VRAM on this page, while NVIDIA RTX 6000 Ada has 48GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.