Kalshi builds forward curve for computing power as exchanges race to financialize AI infrastructure

Kalshi builds a forward curve for computing power as exchanges race to turn GPUs into a tradable commodity

Kalshi built a forward curve for GPU compute costs using prediction market contracts, joining CME and ICE in financialising AI infrastructure. Kalshi, the prediction markets exchange, has built a forward curve that tracks the future price of computing power, joining a growing list of exchanges and index operators trying to turn GPU rental costs into a standardised financial instrument. The tool uses weekly and monthly event contracts related to compute prices, extending up to a year into the future. An algorithm then stitches those contracts into a single curve that can serve as a reference for futures, options, and other derivatives. "We are using prediction markets to build the forward curve, which will provide the market a view of what compute costs will be in the future for different grades and time-frames of GPUs," Udesh Jha, Kalshi's chief risk officer, told Bloomberg. Forward curves are a staple of commodity markets, used to plot expected future prices of everything from crude oil to natural gas to interest rates. The fact that one now exists for GPU rental costs says something about how far compute has travelled toward becoming a commodity in its own right. Kalshi is not the only exchange moving on compute. CME Group announced compute futures in May, partnering with Silicon Data to build contracts linked to an index tracking the hourly cost of renting high-end GPUs. Days later, Intercontinental Exchange said it would team with Ornn to launch its own cash-settled compute futures, making at least three serious entrants in the race to establish the benchmark contract for AI computing power. Kalshi's approach differs from its larger rivals in one important respect. CME and ICE are building traditional futures contracts that require regulatory approval, while Kalshi is using its existing prediction market framework to construct the curve from event contracts that are already trading. Jha called it a key enabler for hedging, risk management, and speculative activity alike. The underlying dynamic driving all three efforts is the same. AI infrastructure spending is projected to reach trillions of dollars within the next decade, and the companies buying and selling GPU capacity have no standardised way to hedge against price swings. GPU rental rates have been volatile, and the market for compute remains fragmented across cloud providers, data centre operators, and GPU brokers, each pricing capacity through bilateral deals with little transparency. A functioning forward curve gives buyers and sellers a shared view of where prices are headed, which is the foundation on which hedging and risk management are built. Whether Kalshi, CME, or ICE ultimately captures the most liquidity will determine which curve becomes the industry benchmark, much as competing oil contracts settled into the Brent and WTI duopoly that still defines energy markets. For an asset class that did not exist two years ago, the financial infrastructure is assembling remarkably fast.

Kalshi Wants to Predict the Future of Compute Availability

Artificial intelligence labs are after computing power. Kalshi doesn't have any to offer them but they've got something else that might be of some use, according to Bloomberg: a tool that plots the predicted future price of computing power. So, that's something! There really is some value for companies to know where the cost of compute is going -- especially since currently, it's mostly just going up. Having a sense of just how much compute is going to cost allows companies to try to lock in a price with a provider before the price spikes. Demand for compute continues to climb faster than the ongoing data center buildout is able to keep up with. In fact, former Intel CEO Pat Gelsinger recently told CNBC that demand is "almost unlimited." That is notably more than the amount of energy and processing power available, which actually does have an upper limit. Is the cost of compute predictable? A recent report from Apollo Global Management described current compute capacity as "effectively sold out," which has created a bottleneck where the price to rent GPUs keeps climbing faster than new ones are spun up and made available -- an issue that is likely only going to get worse as more and more agentic AI tools become available, as recent research suggests they consume up to 136.5 times more energy per query than most generative AI models. Kalshi's new tool is supposed to serve as a sort of indicator for companies dealing with those realities of limited resources while trying to generate unlimited growth. Per Bloomberg, it'll reportedly offer a forward tracking curve of compute, giving an early outlook as to where the cost of computing power is headed in the near-term. Kalshi will reportedly analyze weekly and monthly contracts for computing power and use an algorithm to predict the future curve, spitting out a price that it expects to see paid in the future. The project reportedly aims to stretch its predictions as far out as a year into the future. Bloomberg didn't have details as to whether or not Kalshi will create a market around the price and let people bet on whether the real price will be higher or lower, but that feels like a pretty safe assumption given that it is kind of the prediction market's whole deal. Plus, it wouldn't be alone in trying to monetize the curve of compute availability. The Bloomberg report notes that a number of exchanges are looking to list compute futures contracts, which would allow people to trade on the resource like an asset. So if you're looking for a way to short the future of AI, well, it seems it's coming.