Deepseek AI Deepseek Coder V2 Instruct 0724 speed on NVIDIA H200 SXM 141GB and quantization-level VRAM fit.
NVIDIA H200 SXM 141GB 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 H200 SXM 141GB can run Deepseek AI Deepseek Coder V2 Instruct 0724 with Q4 quantization. At approximately 172 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 105GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 36GB | 141GB | 172.32 tok/s | ✅ Fits comfortably |
| Q8 | 72GB | 141GB | 120.62 tok/s | ✅ Fits comfortably |
| FP16 | 144GB | 141GB | 65.48 tok/s | ❌ Not recommended |
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NVIDIA H200 SXM 141GB can run Deepseek AI Deepseek Coder V2 Instruct 0724 at Q4 with an estimated 172 tok/s.
Q4 inference is estimated to need about 36GB VRAM on this page, while NVIDIA H200 SXM 141GB has 141GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.