What are the benefits of using an H100 over an A100 (both at 80 GB and both using FP16) for LLM inference?
Seeing the datasheet for both GPUS, the H100 has twice the max flops, but they have almost the same memory bandwidth (2000 GB/sec). As memory latency dominates inference, I wonder what benefits the H100 has. One benefit could, of course, be the ability to use FP8 (which is extremely useful), but I’m interested in the difference in the hardware specs in this question.
You must log in or register to comment.
H100 was additionally specialized to have higher performance for transformer models. I think it is about 8x faster than a A100 for transformers, but don’t nail me down on it
There was quite a detailed technical blog published when H100 was announced with plenty of of comparison to A100.
A100 is like a 3070ti with 80gb Vram. H100 is like a 4090 with 80gb of ram and optimized hardware for transformers.