NVIDIA H100 PCIe 80GB meets the minimum VRAM requirement for Q4 inference of RedHatAI/Meta-Llama-3.1-70B-Instruct-quantized.w4a16. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA H100 PCIe 80GB can run RedHatAI/Meta-Llama-3.1-70B-Instruct-quantized.w4a16 with Q4 quantization. At approximately 106 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 46GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 34GB | 80GB | 105.88 tok/s | ✅ Fits comfortably |
| Q8 | 68GB | 80GB | 69.73 tok/s | ✅ Fits comfortably |
| FP16 | 137GB | 80GB | 38.45 tok/s | ❌ Not recommended |