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And the real maddening part is that search engines have been so enshitfied to make way for AI that's wrong like 9/10, so you're forced to rely on it for answers because if you try google, the snake wraps around and eats it's own tail giving you an AI answer! 
llm end-user energy consumption is pretty low. probably depends on the provider rates and your dev salaries.
Yeah but inference cannot exist without the prohibitively expensive up-front cost of training. And of course the larger the model the more costly the inference. That's why you read stories like "new trend in SV: pay in tokens." Opus 4.6 is gonna mop the floor with a 2B param model designed to run on an edge PC, but the cost of getting to the point that it can be used, and actually using it, is still very high.
Inference is not that cheap. It is cheap when compared with training. Try running LLMs on a laptop and watch how quickly your battery is sucked dry. This is still the case when you have a GPU.
i'm probably using more power to microwave my pasta dinner