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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How bad for the environment is it if you run a small local model? Like I can run deepseek 8b easily on my laptop, and my laptop doesnt have any water to burn like OpenAI server farms do, so it can't be nearly as bad, right? Is there any stats about this, like how much of the bad-for-the-environment stuff comes from actively running the LLM, and how much comes from training it?
Running it on your laptop doesn't matter any more than running a high powered game or any other computing task on you laptop, especially if you're using an open source model (since your contribution to any training costs/externalities is negligible)
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.
Global training energy cost seems to be about 0.1% - 0.3% of global electricity use.
Could you link me the source? I don't doubt your number, I just want to look deeper into that