AI carbon and energy calculator – > pick greener cloud regions

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We built a little LLM use -> energy and carbon footprint calculator at work to spark some discussion with our user base about the impact of using AI to solve problems in the climate space, a side effect of playing around with it is we 4x decreased our own carbon intensity on our productby switching to a lower intensity region. We often have people (rightly) asking how we justify that, so we wanted to do the work to be able to speak to it. The reason i wanted to show HN though, is that after we updated it to include some sub-national regional granularity for datacenters, i realised this was a super easy carbon intensity reduction win for picking cloud regions, when i normally dont put much thought into region selection. us-east-1 -> us-west-2 was a 4x decrease in carbon intensity! IDK about others, keen to hear, but i have no metric for picking regions to use hosted LLM models, because all the normal things i would think about like latency dont matter cause the models themselve dominate those metrics. So i just pick first usually. But the tool got me thinking i could quickly and for no tradeoff (provided the model exists) switch to a lower carbon intensity data center. F If you play with the calculator you can easily see an individuals use has to be suuuuuper sustained and large to make a difference compared to other personal activities, but when you have a product with many users a small change like region can have a real impact! Super cool side effect of a tool to spark client discussion. Is this something anyone even cares about? How much effort does it need to be to switch/pick a lower intensity region?

Visit product View on Hacker NewsOct 24, 2025

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