Wall Street is turning Nvidia's AI chips into a new futures market: Chart of the Day

AI spending keeps getting bigger. Figuring out how to price it is still surprisingly hard.

Nvidia ( NVDA ) put an exclamation mark on the scale of the boom this week, forecasting roughly 70% revenue growth in fiscal 2028 even as supply struggles to keep up.

The company is also moving beyond simply selling chips, helping to finance customers, and participating in rental revenue as Wall Street increasingly likens Nvidia to the central bank of AI .

CEO Jensen Huang put the shift more simply: "Now, compute is revenue."

Wall Street is preparing to put a tradable price on some of that computing power.

CME Group plans to launch futures on Oct. 5 tied to the hourly rental cost of Nvidia's H100 and B200 graphics processors, pending regulatory approval. The contracts would settle against benchmarks from Silicon Data , which tracks what companies pay to rent those chips.

Silicon Data's H100 benchmark is currently around $2.68 per GPU-hour , while its newer B200 benchmark is about $5.66. Both have moved substantially over the past year, and not always together.

Think about hotel rooms. A night at the Ritz and one at a Motel 6 both buy a bed, but not at the same price.

Computing power works much the same way. The chip matters, but so do the provider, location, rental term, networking, and availability.

And a futures contract does not reserve the chips themselves. It pays out based on where the benchmark price goes.

If the hotel is sold out, even if room prices go up, it still doesn't give you somewhere to sleep.

Wall Street has a mixed record of creating new markets

The DRAM attempt ran into a problem that sounds familiar today. "The biggest hurdle was getting agreement within the industry about what the standard chip would be," former exchange executive Charles Rose later recalled .

Weather futures faced a different obstacle — a company's actual exposure can be too specific to fit neatly into one standardized contract.

Bandwidth may be the closest parallel. During the late-1990s fiber boom, Enron tried to turn network capacity into a commodity that could trade like energy, but the market never caught on. The same fiber glut has become a warning for today's AI infrastructure build-out , after excess capacity helped drive prices lower.