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

Major Exchanges Race to Establish GPU Futures Trading

Two of the world's largest derivatives exchanges are launching futures markets for AI computing power, marking a decisive shift in how the financial industry views the infrastructure driving artificial intelligence. CME Group announced on May 12 that it would partner with Silicon Data to create futures contracts for computing power 1

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, while Intercontinental Exchange, owner of the New York Stock Exchange, revealed similar plans with financial-infrastructure firm Ornn 2

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. The near-simultaneous announcements signal that institutional conviction in treating compute as a tradable asset has reached a critical threshold.

CME's chief executive Terry Duffy framed the development bluntly: "Compute is the new oil of the 21st century," adding that it is "becoming a fast-emerging asset class in its own right" 1

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. The new futures contracts for computing power will allow investors and technology firms to bet on or hedge the future cost of GPU rental, which can take months to order and swing sharply in price. Silicon Data currently provides daily rental rates for A100, H100 and B200 chips on financial data platforms such as LSEG and Bloomberg 1

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Addressing the Volatile Compute Market Through Standardized Pricing Mechanism

The timing reflects urgent market need. GPU rental prices have experienced wild swings, with Ornn's index showing Nvidia Blackwell spot rental prices surging 48% between mid-February and mid-April 2026, from $2.75 to $4.08 per GPU-hour 2

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. For AI companies whose training runs for large language models can cost tens of millions of dollars, such volatility creates significant budget uncertainty. Cloud providers, hyperscale data center operators, and lenders financing billions in AI infrastructure buildouts face similar exposure.

Trabue Bland, senior vice president of futures markets at ICE, emphasized that the compute market 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 4

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. The contracts will be US dollar-denominated and cash-settled contracts, rather than requiring physical delivery of GPUs 2

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Financialization of AI Infrastructure Gains Momentum

The emergence of these markets represents the financialization of AI infrastructure, transforming GPU capacity into a commodity similar to oil, metals, or agricultural products. Carmen Li, chief executive of Silicon Data, noted that "there are billions, if not trillions, of dollars of contracts being signed" and that "the desire to manage volatility and risk is real" 1

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. Kush Bavaria, co-founder and CEO of Ornn, stated that 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" 4

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The competition between CME Group and Intercontinental Exchange mirrors the early days of energy futures in the 1980s, when competing exchanges raced to establish benchmark contracts for crude oil. The first futures contract linked to a physical barrel of crude oil was traded in 1983 in New York 1

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. The exchange that captures the most liquidity early will likely set the reference price for the industry, just as ICE Brent and CME WTI did for oil 2

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What This Means for Tech Companies and Investors

For AI companies planning large model training runs or cloud providers locking in capacity, these instruments offer a way to hedge against rising costs amid Big Tech's $650 billion capital expenditure surge in 2026 2

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. The AI boom has fueled massive demand for computing power, which labs use to train AI workloads such as OpenAI's ChatGPT and Anthropic's Claude 1

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. Chipmaker Nvidia is among firms to have highlighted the need for investment in compute to continue scaling AI technology and its capabilities 1

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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. US government-backed Intel is up over 200 percent, while AMD has doubled and Nvidia is up 17 percent 1

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. A functioning futures market would generate transparent price signals that the broader market currently lacks, giving investors, analysts, and policymakers a clearer view of where compute costs are heading. Both CME and ICE aim to launch their contracts later this year, subject to regulatory approval 3

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