Topic
The Frontier Wire compared every per-prompt energy and water figure in its dataset. The extremes differ 2,300-fold for energy and over 1,600-fold for water, but four independent estimates for an ordinary text prompt sit within a factor of 1.75. Scope, request length and modality explain the rest.
In the spring of 2026, engineers at large technology companies competed on leaderboards ranked by how many AI tokens they consumed. By summer the leaderboards were gone and the budgets were blown. The episode is a lesson in what a token is: a unit of cost, not a unit of work.
Models that think before they answer are billed for every token of that thinking, whether or not you see it. The controls have moved from token budgets to effort levels, and the price of a request now depends on how hard the question is.
The idea that a model can get better by thinking longer, rather than by being bigger, reshaped how labs spend their money. The evidence behind it, method by method, and the limits the papers themselves report.