Why compute might get 10x+ more expensive in coming years

算力价格未来可能上涨 10 倍以上

Dwarkesh Patel argues that if a model matches a human software engineer, an H100 should rent for over $250k/year—15x today's spot price. Anthropic may hit $100–150B revenue this year, but training compute only grows 3x annually; sustaining 10x revenue growth would require inference compute to get far more expensive. Google and Anthropic already pay ~2x spot for SpaceX GB200/GB300 clusters, and spot prices are up 40%+ since February. The post doesn't give a timeline, but the logic is clear: smarter models make the same compute more valuable, making it harder for latecomers to compete.

Why it matters: Dwarkesh reverse-engineers compute pricing from engineer salaries, providing a concrete valuation anchor rather than vague trend talk. But it's a personal thought piece, not an industry event, so the score sits at the featured threshold.