Why smarter AI models could drive up compute prices 10x

Dwarkesh walks through a gap: Anthropic's revenue has 10x'd three years running, but lab compute only 3x's per year. He argues that closing this gap will push compute prices up, possibly 10x. If one H100 could match a human software engineer, its annual rent should exceed $250k—over 15x today's spot price. Google is already paying SpaceX $900M/month for 110k GB200/GB300 GPUs at 2x the spot price, and spot prices are up over 40% since February. More efficient models that use fewer tokens per task could paradoxically make compute scarcer and pricier, pricing out lower-value AI applications. He flags that this scarcity logic resembles the Simon-Ehrlich bet, where past predictions of resource shortages failed.

Why it matters: Dwarkesh uses the gap between Anthropic's revenue trajectory and compute supply growth to argue compute prices must rise. The numbers are solid and the logic is tight. Not a higher score because it's ultimately a commentary piece, not a product launch or hard news, but it's hi...