Thanks for the feedback. As more and more new ML system architectures emerge over the next few years, these performance comparisons will get even more complicated. Chip-to-chip comparisons and server-to-server comparisons are arbitrary, and it will sometimes be difficult to define these boundaries at all.

Our impression is that top-line performance comparisons independent of system size (like the comparison in the blog post) and performance-per-dollar comparisons are the easiest to understand, but we're certainly open to other ideas.