The First Frontier AI Token Price Index

The Singularity has had a price for the compute that powers it, but never one for the tokens that compute produces, until now.

Earlier this year I wrote about the moment GPU compute became a tradable asset class, when Ornn put the Ornn Compute Price Index (OCPI) on the Bloomberg Terminal, and brought the first compute futures to the Intercontinental Exchange. But compute is only the input. What the AI economy meters, sells, and budgets is the inference token, and the token has never had an honest price.

A commodity cannot be priced until its unit is fixed. In August 1866, oil producers met in Titusville, Pennsylvania, and agreed that a barrel would hold 42 gallons; until then crude moved in 40- and 45-gallon casks, and no two contracts matched. The token is already the AI economy’s barrel, the unit every lab prices in. What the market still lacks is the price.

Posted model rate cards are public, yet no buyer pays the rate card. The phrase “posted price” is itself an inheritance from oil. For decades the majors declared the price of crude, and when they unilaterally cut it, in 1959 and again in August 1960, the producing states convened in Baghdad that September and founded OPEC. A posted price is a declaration; a transacted price is a discovery. In oil the gap between them was political, a number the sellers chose; in AI it is structural. Caching, the input/output split, provider routing, and the mix of models a buyer chooses mean the rate card and the realized cost have never been the same number.

That changes today.

Ornn, a company I helped form and advise with backing from 021T Capital, is launching the Ornn Token Price Indices (OTPI), the first benchmark to price frontier-lab tokens from real transactions, not posted rate cards. OTPI launches with separate daily indices for the two leading frontier labs by benchmarked capability, Anthropic and OpenAI. Enterprises budgeting AI spend, investors marking the demand thesis, and labs benchmarking their monetization now have one number.

For each lab, OTPI weights every model by transacted token volume into a single daily figure in dollars per million tokens, built from executed, paid inference rather than rate cards. It is a unit-value index, total dollars paid over total tokens bought. Bishop William Fleetwood built the first true price index in 1707 to value a £5 cap in a fifteenth-century Oxford statute, data Adam Smith later borrowed for the Wealth of Nations; he could average prices but not weight them. Laspeyres and Paasche added the weighting in the 1870s, each fixing a basket to isolate pure price. A unit-value index does the reverse, letting the live mix into the number, so it moves with what the market pays. Because every input is paid inference, hundreds of billions to trillions of tokens a day, the number is the market itself, not a survey of it.

OCPI prices the input to the AI economy, the cost of GPU time. OTPI prices the output, the cost of the tokens that compute produces. Together they read both sides of the AI cost curve. The output side holds the deepest question in AI, not whether AI is used, but whether buyers keep paying for it. OpenAI estimates the cost per unit of a given level of intelligence is falling about 40x a year. That is what a token buys, not what it costs. OTPI prices the token, which holds up as buyers climb to the frontier and slips only as the frontier commoditizes. The gap between the two is the real deflation, the half no rate card or capability headline can show. Because it is volume-weighted from transacted traffic, the index carries something nobody outside a lab can see, how a provider’s traffic actually splits across its models, and how fast a new release wins that traffic once it ships. That migration, normally a lab’s most guarded number, is the demand signal itself. Nearly $7 trillion in data-center investment is projected through 2030 on the bet that demand is real, and a token price is the first hard read on it.

As Peter Diamandis and I argued in Solve Everything, the Intelligence Revolution turns every scarce domain it touches into an abundant one, but abundance has to be priced before it can be financed. Compute went from a benchmark to a futures market. OTPI is the same first step for the cost of intelligence. Every commodity that powered an age had its unit standardized, then its realized price discovered. The token cleared the first gate when the labs began billing by it; today it clears the second. OTPI is the discovery.

OTPI is live now for subscribers of Ornn Data, the company’s market data platform. See it at data.ornn.com.

Compute is what the AI economy buys. Tokens are what it sells. As of today, both have a price.

(This post is for informational purposes only and does not constitute investment, financial, or trading advice. Nothing herein is a recommendation to buy, sell, or enter into any transaction involving compute, tokens, derivatives, or any other instrument. Statements about future capabilities and demand are forward-looking and subject to uncertainty, descriptions of methodology are not endorsements of accuracy, and past results are not indicative of future results. I have a financial interest in Ornn.)