Computing Capital Markets

Computing is being integrated into a comprehensive capital market, much like electricity was in the 1990s.

Written by: Vaidik Mandloi
Compiled by: Block unicorn

Google is one of the top three cloud service providers globally, and it currently purchases $920 million worth of computing resources from SpaceX (a rocket company) each month.

This is the chaotic state of the GPU capacity market. There are no pricing benchmarks, and lenders cannot hedge the risks of financing their hardware; everything is based on blind capital allocation. But this is about to change, as the Chicago Mercantile Exchange (CME) and Intercontinental Exchange (ICE) have announced plans to launch GPU computing time futures contracts.

Computing is being integrated into a comprehensive capital market, much like electricity was in the 1990s. Today, I will delve into this new liquidity forward curve driven by stablecoin settlements and explore the transformations it can bring to the largest infrastructure buildout since the railroads.

Making Computing Tradable

When I say that computing is entering the capital markets along the path of electricity, I mean it very specifically, and understanding this will tell us how this market is being constructed.

In commodity markets, traders make a significant distinction between stock and flow commodities. For example, oil is a stock commodity because you can store it in tankers until you find a buyer. You can hoard crude oil when prices are low and sell it when prices soar. Computing power, on the other hand, is a flow commodity because you rent GPUs for a period and pay for that. Any computing power that is not used during the rental period will disappear permanently.

GPUs sitting idle on racks are not equivalent to "stored computing," just as disconnected power plants are not equivalent to "stored electricity," because in both cases, the valuable product is the flow—GPU hours or kilowatt-hours—not the physical machines that generate that flow.

This is crucial for pricing because stock commodities have the built-in stabilizer of inventory, while flow commodities lack this stabilizer. Inventory can be released during periods of extreme price volatility to offset price increases. Flow commodities do not have this buffer; this is why the spot prices of computing often fluctuate wildly.

In mid-2025, a massive influx of new supply due to the release of Nvidia's next-generation Blackwell chips led to a drop in demand for H100 graphics cards, causing computing spot prices to plummet by 70% within 18 months. However, this year, due to the mass production of HBM chips, demand surged, and with no inventory on the market to absorb it, the price of H100 graphics cards skyrocketed by 48% in just four days. This volatility, which lacks hedging tools, is a matter of life and death for AI companies (whose training runs can cost tens of millions of dollars) and the lenders providing over $120 billion in data center credit for this hardware.

Additionally, there is a second issue. A barrel of crude oil is identical to any other barrel of crude oil, no matter where in the world it is, which is why it can be traded on exchanges without physical inspection. However, an H100 located in Virginia is a completely different product from an H100 located in Iceland, as the chips, cluster configurations, and adjacent workloads all affect their actual performance.

Benchmark testing from global GPU suppliers shows that even nominally identical hardware can have performance differences of up to 38%. The electricity industry faced the same issue in the 1990s: electricity from the Texas grid was entirely different from that in the Mid-Atlantic region because transmission and local demand created different conditions at each node in the grid. The only solution at the time was to set different prices for each node and quote based on the price differential to a reference benchmark. And this reference benchmark is what the computing market currently lacks.

SF Compute has built a real-time order book for GPU time, where buyers and sellers can trade time just like any commodity in the spot market. The logic is that once a liquid spot market exists, trading activity can be used to derive index prices. These index prices can then be used to construct cash-settled futures contracts.

Once data centers can sell futures contracts and lock in revenue months in advance, they can approach lenders to show that their revenue is hedged, allowing them to secure lower interest rates and expand. This, in turn, can lower the overall computing costs for everyone.

Another company, Silicon Data, has built a daily index called SDH100RT, which has been live on Bloomberg terminals since May last year and has aggregated 3.5 million data points from global suppliers to form a single benchmark, costing only the equivalent of one hour of H100 GPU runtime. The newly announced futures contracts from the Chicago Mercantile Exchange (CME) will settle based on this index. Several companies are currently competing to build similar indices, as becoming a reference price means they can capture a small portion of every transaction in the market as long as it exists.

The electricity market also went through a similar phase: in 1993, Nord Pool opened the first electricity futures exchange, leading to the emergence of over 200 new electricity marketing companies. Industry insiders spent a decade debating whether electricity legally constituted a commodity, but today it has become a market worth $6 trillion annually. The computing market is currently undergoing a similar journey.

Intermediaries

Thus, we now have what can be called the first computing spot market adopting some form of price index, and exchanges have announced relevant intentions. However, there is a crucial link supporting the operation between the index prices on Bloomberg terminals and a well-functioning capital market, and this link operates quite differently from traditional trading methods.

The operation of the computing futures market is fundamentally different from stock exchanges, which conduct standardized stock trades between anonymous buyers. The computing futures market will be dominated by dealers, who act as a bridge between GPU owners (looking to lock in revenue) and AI companies (looking to lock in costs).

For example, suppose a data center in the U.S. has a large number of H200 servers available starting in October. A startup needs 500 GPUs but only cares whether the interconnect is InfiniBand (a type of GPU communication medium) and does not care about the specific location of the servers. This is a very specialized demand that requires someone to handle this custom order while hedging the risks associated with the standardized index.

This is not a new concept; every commodity in the past has required such a link to allow relevant parties to untangle the complex relationships of physical products and convert them into interchangeable units that can be traded on exchanges. An H100 contract on the shelf is just a custom contract that others cannot price. It can only generate revenue for one party based on a private agreement, and other parts of the financial system cannot even touch it. But if it can be combined with index prices and a public settlement layer, it can become a living commodity that lenders can hedge against.

In 2023, CoreWeave borrowed $2.3 billion using Nvidia GPUs as collateral, marking the first time H100 hardware secured a loan. Its most recent financing received an investment-grade rating from Moody's, based on Meta's creditworthiness rather than CoreWeave's, because Meta signed a

Disclaimer: This content is provided for general branding and informational purposes only and doesn't constitute financial, investment, legal, or tax advice. Any events, rewards, online events, or related information mentioned herein should not be considered a recommendation, solicitation, or invitation to purchase, sell, trade, or otherwise deal in any crypto assets or to use any services. Crypto assets are highly volatile and may result in loss. WEEX services and online events may not be available in all regions and are subject to applicable laws, regulations, and eligibility requirements. You are responsible for ensuring that your use of WEEX services complies with local laws and for carefully assessing the risks before participating in any crypto-related activities.