They claim 1.1x to 7x, depending on what you're doing. The 10% to 50% is for the ~10k GPU LLM training, where the main bottleneck tends to be networking:
> DGX GH200 enables more efficient parallel mapping and alleviates the networking communication bottleneck. As a result, up to 1.5x faster training time can be achieved over a DGX H100-based solution for LLM training at scale.
It's been on the roadmap for a few years although there were no performance numbers. I assume GH200 is more expensive so the price/performance advantage may not be overwhelming. Worst case you order GH200s and then scalp your H100s on the used market.
> DGX GH200 enables more efficient parallel mapping and alleviates the networking communication bottleneck. As a result, up to 1.5x faster training time can be achieved over a DGX H100-based solution for LLM training at scale.