GPU

Yesterday brought two data points about the health of inference businesses : SpaceX’s third-quarter report¹ & DeepSeek’s inference post.²

Overall, they demonstrate that inference businesses can be quite healthy even at current prices & efficiencies. Plus there is a tremendous amount of upside assuming demand persists at higher prices per card hour.

DeepSeek calculates a $38 maximum per GPU card-hour.³ It describes a GPU running under optimal conditions : maximum utilization for external customers rather than internal work, & 100% of its output usable & billable, sold at full list price.

GPU prices have doubled in the last six months, from $4.40 to $8.08 per GPU-hour. But AI prices are falling. How can that be?

It is not a simple answer. Higher GPU costs are likely to remain while the industry races to build out new data centers. Every component of the buildout is increasing in cost, from concrete to copper to credit.¹ Above all, electricity remains the limiting factor, which Oracle is experiencing : last week it invoked force majeure on its New Mexico campus after the natural-gas pipeline feeding it slipped by six months.²

One search ad every 40 minutes pays for a trillion-parameter model. One content ad every 3 minutes does the same. The math on ad-supported AI is better than you think.

When Anthropic pulled Claude Code from the $20 plan last month, it signaled an industry assumption : frontier intelligence requires frontier pricing. For open models, the economics flip.

A B200 GPU costs $4.50/hour on spot markets.¹ Google Search ads generate $38.40 CPM (cost per thousand impressions),² while Google Display runs $3.12.³