Deepseek AI Deepseek Coder 33B Instruct speed on NVIDIA A100 80GB SXM4 and quantization-level VRAM fit.
NVIDIA A100 80GB SXM4 meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek Coder 33B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA A100 80GB SXM4 can run Deepseek AI Deepseek Coder 33B Instruct with Q4 quantization. At approximately 128 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 63GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 17GB | 80GB | 127.78 tok/s | ✅ Fits comfortably |
| Q8 | 33GB | 80GB | 89.44 tok/s | ✅ Fits comfortably |
| FP16 | 66GB | 80GB | 48.56 tok/s | ✅ Fits comfortably |
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NVIDIA A100 80GB SXM4 can run Deepseek AI Deepseek Coder 33B Instruct at Q4 with an estimated 128 tok/s.
Q4 inference is estimated to need about 17GB VRAM on this page, while NVIDIA A100 80GB SXM4 has 80GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.