Deepseek AI Deepseek Coder V2 Instruct 0724 speed on NVIDIA A100 40GB PCIe and quantization-level VRAM fit.
NVIDIA A100 40GB PCIe 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 A100 40GB PCIe can run Deepseek AI Deepseek Coder V2 Instruct 0724 with Q4 quantization. At approximately 57 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 4GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 36GB | 40GB | 56.81 tok/s | ✅ Fits comfortably |
| Q8 | 72GB | 40GB | 39.77 tok/s | ❌ Not recommended |
| FP16 | 144GB | 40GB | 21.59 tok/s | ❌ Not recommended |
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NVIDIA A100 40GB PCIe can run Deepseek AI Deepseek Coder V2 Instruct 0724 at Q4 with an estimated 57 tok/s.
Q4 inference is estimated to need about 36GB VRAM on this page, while NVIDIA A100 40GB PCIe has 40GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.