Hahaha — wait, do you think that the models take more energy to train than the cumulative amount used to serve them for inference across the lifetime of the model?

And if not, then what you are saying is effectively gibberish as any reasonable assessment would need to divide the training cost across all post-trained inference. So if it was only 50% the lifetime inference usage, it'd be a 1.5x multiplier to that I said above, which doesn't change either the Netflix 4k or gas mileage points.