Meta Llama Meta Llama 3 70B Instruct speed on NVIDIA H200 SXM 141GB and quantization-level VRAM fit.
NVIDIA H200 SXM 141GB meets the minimum VRAM requirement for Q4 inference of Meta Llama Meta Llama 3 70B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA H200 SXM 141GB can run Meta Llama Meta Llama 3 70B Instruct with Q4 quantization. At approximately 241 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 106GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 35GB | 141GB | 241.24 tok/s | ✅ Fits comfortably |
| Q8 | 70GB | 141GB | 168.87 tok/s | ✅ Fits comfortably |
| FP16 | 140GB | 141GB | 91.67 tok/s | ⚠️ Tight fit |
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NVIDIA H200 SXM 141GB can run Meta Llama Meta Llama 3 70B Instruct at Q4 with an estimated 241 tok/s.
Q4 inference is estimated to need about 35GB 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.