Bigscience Bloomz 560M speed on NVIDIA H100 SXM5 80GB and quantization-level VRAM fit.
NVIDIA H100 SXM5 80GB meets the minimum VRAM requirement for Q4 inference of Bigscience Bloomz 560M. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA H100 SXM5 80GB can run Bigscience Bloomz 560M with Q4 quantization. At approximately 594 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 79GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 80GB | 594.08 tok/s | ✅ Fits comfortably |
| Q8 | 1GB | 80GB | 415.86 tok/s | ✅ Fits comfortably |
| FP16 | 2GB | 80GB | 225.75 tok/s | ✅ Fits comfortably |
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NVIDIA H100 SXM5 80GB can run Bigscience Bloomz 560M at Q4 with an estimated 594 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while NVIDIA H100 SXM5 80GB has 80GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.