NVIDIA H100 SXM5 80GB meets the minimum VRAM requirement for Q4 inference of context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA H100 SXM5 80GB can run context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 with Q4 quantization. At approximately 573 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 78GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 2GB | 80GB | 573.48 tok/s | ✅ Fits comfortably |
| Q8 | 3GB | 80GB | 413.68 tok/s | ✅ Fits comfortably |
| FP16 | 6GB | 80GB | 243.57 tok/s | ✅ Fits comfortably |