According to Kalshi CEO Tarek Mansour, compute—a term that describes the chips and electricity powering the AI revolution—will eclipse oil as the world’s most valuable commodity, and spur a futures market for hedging it. On a recent TBPN podcast, Tarek predicted that compute will be a $10 trillion industry by 2030. He added that, if compute follows the pattern of derivatives markets for other commodities, its futures market will grow to 10-15 times the size of the underlying spot market—meaning compute futures will one day be worth $100-$150 trillion.

If Mansour’s prediction is even remotely correct, compute futures represent a massive opportunity for whoever can build that market. In July, Kalshi itself announced a new series of events contracts and data tools that it says can be the foundation of a compute derivatives market. Kalshi, though, isn’t the only firm looking to seize that opportunity. The derivatives giant CME Group revealed in May that it plans to roll out a product later this year in partnership with an AI data firm, while stock exchange giant Intercontinental made a similar announcement the same month.

But even as compute futures represent a huge opportunity, the history of commodities markets shows the process for building such products can be slow, complicated and uncertain. Here’s how that process is likely to play out in the compute field.

How exactly do you hedge compute costs?

In the 1970s, a series of economic shocks jolted oil markets, wreaking havoc on industries like airlines, trucking and tourism, where profit margins are closely tied to the price of fuel. This spurred a demand for a futures market in oil like the ones that had long existed for corn and precious metals, and that can provide a hedge against sudden price fluctuations.

Despite this demand, when it came to oil, the financial companies that sold futures for other commodities faced a challenge: Unlike wheat or gold, there was no consensus on what constituted a standard barrel. Over time, the financial markets did come to agree on standards like Brent (named for a type of oil first pumped from a North Sea field of that name) and West Texas Intermediate, but it took years.

This is the situation that now confronts companies looking to hedge their spending on AI compute, where hourly prices can fluctuate as much as 137% over the course of a year, according to research firm Allium. The volatility is especially high when it comes to renting compute powered by the newest models of computer chips, whose availability is frequently subject to manufacturing and supply chain constraints.

According to Kalshi’s Head of Research, Nicole Kagan, this is a big reason why the financial industry, which has long offered hedging tools for other commodities, has been slow to develop a futures market for compute.

“Compute is very different in that it’s very opaque. The way compute is priced is via B2B executed contracts from suppliers like Nvidia directly with corporations like HP, which then go and sell them on. So it’s very difficult to even understand what the expected pricing is on that thing, right?” said Kagan.

Kagan added that the task of developing hedging tools for compute is more difficult still because it is not a commodity like oil or wheat whose basic properties don’t change. In the case of compute, newer chips result in higher efficiency—but the change in efficiency is hard to predict, which complicates any attempt to predict future prices of compute.

Despite these challenges, Kalshi believes its prediction markets provide a way to do just that, and is currently listing wagers for five types of chips. Like every other contract it lists, bettors are invited to take one side in a yes/no outcome. For instance, Kalshi users can currently bet on whether the average hourly cost to rent Nvidia’s H200 chip over the course of August will be above or below $5. As of August 6, the cost of buying the yes side of that bet was 30 cents and, as with every contract, would pay out $1 if a bettor is correct and $0 if not.

To determine the final outcome of the bet, Kalshi relies on a firm called Ornn, which publishes a popular dashboard that shows the cost of renting various hardware.

Kalshi is also using its chip-related prediction markets to produce so-called forward curves, which rely on past data in order to plot price movements as far as a year out. The company published some of these curves, which suggest the cost of compute will be fairly constant, in a recent report. The report also describes other prediction markets that could provide signals about the future cost of compute, including markets related to geopolitics or to the cap-ex spending of giant AI users like Google and Meta.

The coming battle for a multi-trillion dollar market

Kalshi is not the only prediction market service offering compute-related contracts. Its main rival, Polymarket, recently launched similar products but, so far, the two firms’ combined offerings are not even a fraction of the oil futures market, where over $70 billion of futures contracts trade hands daily.

“Kalshi’s GPU rental markets recorded $4.4M in notional volume through July 27 against $285K on Polymarket, roughly 15 times more. Kalshi also covers five chips, compared with Polymarket’s three. The positions traders are still holding are equally small, with about 517K contracts open on Kalshi and about 130K outcome shares on Polymarket, backed by $125K in cash,” the research firm Allium reported in July.

Allium’s report also notes that Kalshi’s contracts have yet to deliver much insight into where prices are heading. For instance, two days before a contract is due to close, the price has typically deviated from the actual closing price by around 10%—an outcome, says Allium, that indicates the contracts are not ready for prime-time as a serious hedging mechanism.

It’s early days, of course, and both the popularity and predictive power of Kalshi’s compute-related contracts are likely to rise. But it is no sure thing as the history of new commodities markets attests.

One prominent failure in this field is an attempt by a West Coast stock exchange to create a futures market for California almonds. Even though almonds are the state’s most valuable crop, the push to launch almond futures never panned out as the industry struggled with standardization questions, and as the market failed to attract a critical number of the speculators who provide essential liquidity.

Given the sheer size of the compute market, it’s likely that financial firms will figure out how to develop a futures market before long. The question is whether that will be Kalshi or a large or more traditional player.

Darrell Duffie, a finance professor at Stanford University’s business school, says it will be the latter. He observes that successful futures markets like the one for oil cater to a massive customer base of both retail traders and institutions, and that exchanges like CME and NYSE-parent Intercontinental—the two big incumbents that announced their intention to get into compute—are best designed to do this.

In addition to the retail futures market, there is another type of popular derivative known as OTC swaps that are used by institutions, and that entail creating one-off contracts between two parties. These type of swaps are likely to become common in the world of compute in coming years, but Duffie says it is deep-pocketed big banks that are likely to dominate this trade.

“There is a narrow lane for Kalshi to offer forward curve contracts for compute in their prediction market but they are not as well positioned as the OTC swap market intermediated by bank dealers and the exchange traded futures market,” said Duffie. “Kalshi does not have the infrastructure and participant capital necessary to safely handle high-volume risk transfer for compute.”

Kalshi, meanwhile, says it is still in stage one of its plans when it comes to compute futures, and that it is not daunted by bigger and more established competitors. On Wednesday, the company announced it has brought back Jeff Bandman, a former senior CFTC official, to run a division focused on futures markets.

Kagan, the company’s head of research, also noted that Kalshi is not seeking to compete across the entire emerging compute market. Rather, she says, the company’s ability to quickly create new compute-related markets will give it a data advantage that will benefit Kalshi’s business directly, but that will also feed into the financial industry more broadly.

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