It doesn't have Claude Fable yet, so I went with GPT 5.5 Pro. And so I'd estimate it at 22 gallons of water used (different from consumed, of course). That's quite a lot! It amazes me how much the different use cases and models use dramatically different amounts of water. My takeaway from playing with that calculator has been the folks who talk about water usage are overstating the impact of chatbots, but not overstating when it comes to vibecoding.
The good thing is that competition should drive down how efficient these models are in the long run. This blog post makes me not want to run Fable because of the cost, and that incidentally also means selecting models that aren't as wasteful in terms of water and electricity.
I tried using this calculator: https://www.andymasley.com/visuals/ai-prompt-footprint/
It doesn't have Claude Fable yet, so I went with GPT 5.5 Pro. And so I'd estimate it at 22 gallons of water used (different from consumed, of course). That's quite a lot! It amazes me how much the different use cases and models use dramatically different amounts of water. My takeaway from playing with that calculator has been the folks who talk about water usage are overstating the impact of chatbots, but not overstating when it comes to vibecoding.
The good thing is that competition should drive down how efficient these models are in the long run. This blog post makes me not want to run Fable because of the cost, and that incidentally also means selecting models that aren't as wasteful in terms of water and electricity.
Yeah, testing changes rigorously is for schmucks
You can test rigorously without token incinerators.
But testing rigorously requires time and effort, while incinerating tokens lets me do many things at once.