The Beginning of Scarcity in AI | Tomasz Tunguz
The Beginning of Scarcity in AI
April 13, 2026
AI infrastructure
For the first time since the 2000s, technology companies are confronting the limits of their supply chain.
GPU rental prices for Nvidia’s Blackwell chips hit $4.08 per hour this week, up 48% from $2.75 just two months ago.1 CoreWeave raised prices 20% & extended minimum contracts from one year to three.1
“We’re making some very tough trades at the moment on things we’re not pursuing because we don’t have enough compute.” - Sarah Friar, OpenAI CFO1
This scarcity is already reshaping access. Anthropic has limited its newest model to roughly forty organizations.2 Access to the bleeding edge is becoming a gated privilege, for both capacity & security.
If the largest AI companies are having problems, startups face a tougher proposition. Five hallmarks define this era :
- Relationship Based Selling : State-of-the-art models may no longer be open to everyone as providers limit access to their most profitable or strategic customers.
- AI to the Highest Bidder : Even when they do become available, SOTA models may become prohibitively expensive. Companies that can raise large amounts of capital or generate strong profits will have an advantage.
- Available but Slow : Even if you can pay, there may not be guarantees the models will be fast.
- Inflationary Commodity : This imbalance will inevitably drive prices higher as demand compounds against a fixed supply. Procurement & margin management will become key disciplines in software companies.
- Forced Diversification : Developers will be forced to look elsewhere, from smaller models to on-premise deployments, until energy infrastructure & data center buildouts catch up, which could take years.
The age of abundant AI is over, & it will remain so for years.3 1. Wall Street Journal, “AI Is Using So Much Energy That Computing Firepower Is Running Out,” April 2026. ↩︎ ↩︎ ↩︎