LMArena lets users pick between different model's outputs to show user preferences, and it's clear the users prefer China ๐จ๐ณ
this post was submitted on 13 Oct 2025
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Vast majority of power use comes from inference not training. Training is one massive processing job but inference is done billions of times for some of these models.
Water use is mostly down to the cooling used. Big data centers like to use evaporative cooling which needs tons of water but is cheaper than ac cooling. Electical power also uses water since fossil fuels and nuclear rely on boiling water to spin a turbine but the amount differs heavily by source and is much smaller than using evaporative cooling. Generally you can compare this to running a game (or other program) with similar power draw.
I doubt home use is very significant in terms of environmental impact just like residential water use doesn't matter very much in comparison to industrial use which pales in comparison to animal agriculture.