The banks are exploring trading futures contracts tied to rental prices for graphics processing units, as well as other ways to trade on the cost of computing power, according to the report.
They are in the early stages of exploration of the idea and may not move forward, the report said.
While compute trading is new, it could be a natural next step because banks already trade power and other commodities related to artificial intelligence (AI) infrastructure, per the report.
Making a formal financial market out of GPU rental pricing would enable prices to be tracked and hedged amid the current price swings of this major cost of AI, the report said.
At the same time, this emerging market faces challenges that include the need for a reliable price benchmark and the need to overcome potential regulatory hurdles, per the report.
Prediction market Polymarket said Tuesday (June 2) that it closed its first on-chain institutional block trade tied to AI compute infrastructure. The company said the transaction settled against Ornn AI’s Ornn Compute Price Index, which is a transaction-based benchmark that tracks Nvidia H100 GPU compute rental pricing.
“Prediction markets are emerging as one of the most powerful venues for institutional block trades, and this transaction is proof,” Brooke Rizzetto, head of institutional liquidity at Polymarket, said at the time in a press release. “Seeing an institutional counterparty use Polymarket to hedge real GPU compute exposure at scale is exactly the future we have been building toward.”
Google disclosed Friday (June 5) that it will pay SpaceX $920 million per month for compute capacity. Under the companies’ agreement, Google will pay that amount monthly from October through June 2029. From now through September, the company will pay a reduced fee as SpaceX ramps up capacity.
Pinterest said Thursday (June 4) that it signed a $4 billion cloud services agreement with Amazon Web Services (AWS) to power visual search. Pinterest said deal will give it the significantly greater amount of computing power it needs to train and run at scale its new AI models that understand visual context and user intent.
