AI computing power becomes a tradable asset class as CME starts futures

AI computing power becomes a tradable asset class as CME starts futures


Nvidia showed CNBC its latest Rubin GPU at its Santa Clara, California, headquarters on Feb. 13, 2026.

Marc Ganley | CNBC

Computing power is emerging as a new tradable asset class, with CME Group set to launch the first futures contracts tied to the cost of running the chips that power artificial intelligence.

The exchange is partnering with Silicon Data to introduce two compute futures contracts on Oct. 5, pending regulatory approval, giving companies and investors a way to trade and hedge the price of AI computing capacity much as they do oil, electricity and other commodities.

“For years, two companies buying the exact same GPU capacity could pay wildly different prices with no way to know who got the better deal. They will now have a benchmark to check that against,” Carmen Li, CEO of Silicon Data, said in a statement. “Compute futures give the market something it’s never had: a public, tradable reference price for the resource every AI system runs on.”

The contracts will allow buyers and sellers to trade against the rental cost of Nvidia’s H100 and newer Blackwell B200 graphics processing units and will be based on Silicon Data indexes that track hourly GPU rental prices. Each contract will represent a month’s rent for the Nvidia H100.

The launch comes as Wall Street is finding new ways to finance and gain exposure to the enormous AI infrastructure buildout. Nvidia is working with some of the world’s largest asset managers on an effort that could channel as much as $500 billion into AI infrastructure.

Compute futures would add another layer to that emerging financial ecosystem. Rather than investing directly in data centers, chips or the companies building them, investors could gain exposure to the price of the underlying computing capacity itself, while AI developers and data-center operators could use the contracts to hedge their costs or revenues.

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