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Whenever I read discourse on AI energy/water use that focuses on the "median query," I can't help but feel misled. Coding agents like Claude Code send hundreds of longer-than-median queries every session, and I run dozens of sessions a day. On my blog: www.simonpcouch.com/blog/2026-01...

Thanks for the analysis! This does not include model training, right? Do we have a notion of how much the training represents in terms of energy consumption?

If I read correcly, Mistral says that the energy footprint of training is about 18 billion times a standard response (20.4e6/1.14e-3). How many queries does a model serve in its lifetime? w. 1 bn: training footprit/query ~18 times higher than the per-query usage. w. 10 bilion ~1.8 times higher

No idea what is a realistic estimate of usage per training run.

ChatGPT (easy number to get) gets 2.5 Billion queries *daily*