Deepseek AI Deepseek V2 5 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 V2 5. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA H200 SXM 141GB can run Deepseek AI Deepseek V2 5 with Q4 quantization. At approximately 1034 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 140GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 141GB | 1033.90 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 141GB | 723.73 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 141GB | 392.88 tok/s | ✅ Fits comfortably |
Check current pricing links for NVIDIA H200 SXM 141GB and similar cards.
Open NVIDIA H200 SXM 141GB 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 →NVIDIA H200 SXM 141GB can run Deepseek AI Deepseek V2 5 at Q4 with an estimated 1034 tok/s.
Q4 inference is estimated to need about 1GB 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.