Major exchanges launch futures markets for AI computing power as GPU costs become tradable asset

CME plans to launch futures market for AI computing power

CME Group is launching the first futures market for computing power, in a sign that the AI boom is turning the output of sophisticated chips into a major asset class. The new contracts for the future rental of graphics processing units, or GPUs, which can take months to order and can swing sharply in price, will allow investors and technology firms to bet on or hedge the future cost of computing power. CME, one of the world's biggest derivatives exchanges, is partnering with Silicon Data, a firm backed by Chicago-based trading giant DRW that provides pricing indices and other market data about AI computing power. The new contracts will be based on Silicon Data's indices. "Compute is the new oil of the 21st century," said CME's chief executive Terry Duffy, adding that it is "becoming a fast-emerging asset class in its own right". The AI boom has fuelled massive demand for computing power, which labs use to train large language models such as OpenAI's ChatGPT and Anthropic's Claude. Chipmaker Nvidia is among firms to have highlighted the need for investment in compute to continue scaling AI technology and its capabilities. Silicon Data currently provides daily rental rates for A100, H100 and B200 chips on financial data platforms such as LSEG and Bloomberg. Futures markets allow market participants to lock in the price of a commodity to be bought or sold at a mutually agreed date in the future. The first futures contract linked to a physical barrel of crude oil, the world's largest commodity market, was traded in 1983 in New York. The firms aims to launch the contracts later this year to meet the significant demand from tech companies, banks, investors and others, according to Carmen Li, chief executive of Silicon Data. "There are billions, if not trillions, of dollars of contracts being signed," she said in an interview. "The desire to manage volatility and risk is real." In an interview with the Financial Times at the end of 2024, DRW founder Don Wilson said that compute could become the biggest commodity in the world and that he was exploring ways to trade it. Shares in major chip providers have rallied hard this year, as tech hyperscalers have committed hundreds of billions of dollars to grow their AI-related infrastructure, including chips. US government-backed Intel is up over 200 per cent, while AMD has doubled. Nvidia is up 17 per cent.

ICE plans GPU compute futures with Ornn index partner

Intercontinental Exchange, the parent company of the New York Stock Exchange, is preparing to launch futures contracts tied to the cost of computing power, marking the latest sign that Wall Street sees AI infrastructure as the next great commodity market. ICE announced on Monday that it will team with Ornn, a financial-infrastructure firm whose index products track GPU computing costs in real time, to develop the new contracts. The futures will be US dollar-denominated, cash-settled, and referenced against Ornn's indexes covering a variety of major GPU types. The plans remain subject to regulatory approval. The partnership pairs one of the world's largest exchange operators with a startup that has quietly built the plumbing for compute price discovery. Ornn, formally Ornn AI Inc, publishes the Ornn Compute Price Index, which tracks live traded spot prices for GPU compute across hardware types including Nvidia's H100, H200, and B200 chips. The index, now available on the Bloomberg Terminal, draws on real transaction data from live GPU markets and has attracted more than 400 data centre operators, investors, and AI companies to its platform. Trabue Bland, senior vice president of futures markets at ICE, framed the move as a response to a market that has outgrown its informal pricing mechanisms. The compute market, he said, is "in desperate need of a globally accepted pricing mechanism and risk management tool" as AI shifts from research labs to becoming a central driver of the global economy. The contracts will settle in cash rather than through physical delivery, a structure familiar from energy and financial futures. For AI companies planning large model training runs or cloud providers locking in capacity, the instruments would offer a way to hedge against the kind of volatile compute costs that have accompanied Big Tech's $650 billion capex surge in 2026. ICE is not alone in spotting this opportunity. CME Group, the world's largest derivatives exchange, announced its own compute futures contracts on 12 May, partnering with Silicon Data to build products based on daily GPU benchmark rental rates. CME's contracts will reference the Silicon Data H100 Rental Index, which tracks the cost of renting high-end GPUs used for AI training workloads. The fact that two of the world's most established futures exchanges have moved on compute within days of each other signals that institutional conviction in compute-as-commodity has reached a tipping point. It mirrors the early days of energy futures in the 1980s, when competing exchanges raced to establish benchmark contracts for crude oil and natural gas. The exchange that captures the most liquidity early on will likely set the reference price for the industry, just as ICE Brent and CME WTI did for oil. The competitive dynamic also extends beyond the big two. Architect Financial Technologies partnered with Ornn in January to launch exchange-traded perpetual futures on GPU and RAM prices through its AX platform, and prediction market Kalshi has offered contracts allowing users to wager on Nvidia GPU compute prices. But ICE and CME bring something the newer entrants lack: deep institutional liquidity, regulatory credibility, and the clearing infrastructure that large-scale GPU-as-a-service providers and their customers will demand. Kush Bavaria, co-founder and CEO of Ornn, put the scale of the problem bluntly. Compute, he said, "has grown into a trillion-dollar market, yet it still lacks the pricing and risk-transfer infrastructure that every other major commodity relies on." That gap has real consequences. GPU rental prices have been wildly volatile, with Ornn's own index showing the Nvidia Blackwell spot rental price surging 48% between mid-February and mid-April 2026, from $2.75 to $4.08 per GPU-hour. For AI companies whose training runs can cost tens of millions of dollars, that kind of price swing can blow through budgets with little warning. Cloud providers, data centre operators, and the lenders financing billions of dollars in AI infrastructure buildouts face similar exposure. A functioning futures market would allow these participants to lock in forward prices, transfer risk to willing counterparties, and plan capital expenditure with greater certainty. It would also generate transparent price signals that the broader market currently lacks, giving investors, analysts, and policymakers a clearer view of where compute costs are heading. The emergence of compute futures reflects a deeper structural shift. As AI moves from an experimental technology to core economic infrastructure, the inputs that power it are being financialised in much the same way that energy, metals, and agricultural products were in previous decades. The surging demand for advanced semiconductors has already reshaped chip supply chains and driven record capital investment across the technology sector. Futures contracts add a new layer to this ecosystem. They create standardised benchmarks that can underpin lending decisions, insurance products, and investment strategies tied to AI infrastructure. A bank financing a new data centre, for instance, could use compute futures to assess the facility's projected revenue against forward GPU prices, much as energy lenders use oil futures to evaluate drilling projects. There are complications, of course. Unlike oil sitting in a tank, compute is what traders call a flow commodity, one that is consumed in real time and cannot be stored. Ornn has addressed this by designing its futures with Asian-style settlement, meaning contracts settle on the arithmetic average of daily index values across the contract's tenor rather than on a single expiry-day price. This structure aligns the financial instrument with the way compute is actually purchased and consumed. Whether ICE or CME ultimately captures the lion's share of this market will depend on liquidity, the breadth of GPU types covered, and which index providers gain the most institutional trust. But the direction of travel is clear. Computing power, the resource that underpins everything from energy-hungry AI data centres to autonomous vehicle development, is being transformed from a bespoke procurement headache into a standardised, tradable financial asset. For an industry accustomed to negotiating GPU access through opaque, bilateral deals, that is a significant change.

CME Group and Silicon Data to launch AI compute futures market - SiliconANGLE

CME Group and Silicon Data to launch AI compute futures market Silicon Data, the startup that provides market intelligence for artificial intelligence compute infrastructure, will provide the price indexes for a new futures market that will allow investors to hedge their bets on the semiconductor industry. CME Group's new "compute futures market" will give investors the opportunity to bet on the price of renting cloud-based computing power for AI workloads, the companies explained. Investors will be able to take out contracts and lock in a price for compute capacity based on Silicon Data's benchmark for graphics processing units. It provides a way for them to hedge against the rising costs of renting graphics processing units, at a time when demand for the chips is going through the roof. "GPU markets have historically lacked standardized reference pricing," said Silicon Data Chief Executive Carmen Li. "The launch of compute futures is an important step towards giving AI builders, cloud providers and investors more reliable tools for valuation, hedging and long-term planning." Futures markets are usually associated with commodities such as oil and other petroleum products, precious metals and basic foodstuffs, but they've also become common for assembled components in fast-growing industries, where prices and demand change rapidly. Silicon Data is a natural partner for CME Group in this endeavor. Last month it launched a new service called the GPU Forward Curve, which offers the first standardized look at the anticipated costs of GPU capacity both now and in the future. Its products also include a standardized GPU price index and a dynamic random-access price index. When it launched the GPU Forward Curve last month, Silicon Data said its intention was to transform AI compute into a financialized commodity, and it has wasted little time in making that vision a reality. The launch of the new index is especially timely because few industry observers, or investors for that matter, see demand for GPU rentals slowing down any time soon. Morgan Stanley analyst Shawn Kim said in a note to clients this week that demand for GPUs and also central processing units is going to explode in future as more autonomous AI agents come online. "The AI system in the future will look like a distributed system consisting of GPU racks for dense model compute ... [and] agentic CPU racks for orchestration, processing data and tool execution," he wrote. The price of memory chips has soared this year as AI infrastructure providers continue to gobble up the world's supply of GPUs and now, increasingly, CPUs as well. Hyperscale data center operators like Amazon Web Services Inc., Google LLC, Microsoft Corp. and Meta Platforms Inc. have all announced plans to increase their capital expenditures this year, leading to shortages of memory chips that are driving prices higher. Memory chip makers are benefiting enormously from this demand, with their stocks being among the biggest gainers in the year to date.

Nyse's owner plans its own futures market for computing power

Intercontinental Exchange plans to launch futures contracts linked to computing power, enabling investors to hedge rising AI infrastructure costs. Partnering with Ornn, the contracts will track GPU pricing. The move reflects growing institutional interest in treating compute as a tradable asset, with CME also entering the emerging market. Intercontinental Exchange Inc., owner of the New York Stock Exchange, is adding futures contracts for computing power as the market for tracking the price of what's driving AI technology continues to develop. The exchange operator is teaming with financial-infrastructure firm Ornn and will use its index products that track graphics processing unit, or GPU, computing costs to underpin its new futures contracts, the companies said on Tuesday. The plans are subject to regulatory approval. "As AI has rapidly moved from research labs and academic campuses to becoming one of the most important drivers for the global economy, the market for compute has evolved just as quickly and is in desperate need of a globally accepted pricing mechanism and risk management tool," Trabue Bland, senior vice president of futures markets at ICE, said in a statement. Computing power, also known as compute, has been in high demand as AI companies use it to power their systems. But as the cost of running AI technology rises, users have had little to no way to hedge against price swings. Futures contracts give investors the ability to bet on the value of a commodity, such as oil or metals, on a certain date. Soon, they could do the same with compute costs. ICE's move signals that more of the institutional marketplace is embracing compute as a tradable asset. Chicago-based CME Group Inc., which announced its own plans for compute futures contracts last week, will be another venue where futures contracts can change hands and help make costs more transparent. Read More: CME to Create Futures Market for Computing Power Backing AI ICE said its futures contracts will be US dollar-denominated and settle in cash, rather than physical delivery. The futures contracts will reference Ornn's indexes, which cover a variety of major GPU types, the firms said. "Compute has grown into a trillion-dollar market, yet it still lacks the pricing and risk-transfer infrastructure that every other major commodity relies on," Kush Bavaria, co-founder and chief executive officer of Ornn, said in the statement.