[Deanallen]

It’s not clear from the article, but do these statistics taken into account the amount of electricity and water required to train the model in addition to inference?

For example, the article says their daily average use of Claude code is similar to the dishwasher running. Is that just including inference or also training Opus 4.5?

[deaux]

This is a great question. To my understanding the industry consensus is that for the big three providers, energy spend on inference had already surpassed training by summer last year, and the former's share only keeps increasing. The problem is that there's no hard data in public.

What we need to do here is write an article that makes a wild claim in either direction ("99% is inference!"), post it on HN, and wait for the comments to roll in that prove it right or wrong.