A lot of the comparison is apples and oranges though - it seems that OpenAI's chip is targeting inference (FP8, FP4), while most of the chips it is being compar

A lot of the comparison is apples and oranges though - it seems that OpenAI's chip is targeting inference (FP8, FP4), while most of the chips it is being compared to are general purpose. Notably the only one of the chips that also has a strong inference focus (but not only) is AMD's M1950X, which trounces OpenAI's chip (20 vs 3.4 FP8 PFLOPS, 40 vs 13.4 FP4 PFLOPS, 23 vs 15 TB/sec memory bandwidth), although it does use a lot more power (2500 vs 700W). Google's TPU (now 8th generation) is glaringly absent from the performance comparison. At the end of the day what really matters is cost not performance since you can always just run more chips. Google are full stack optimized from chip to data center, and might be expected to have an advantage.