Compute providers lock customers into long-term contracts not just for predictable revenue, but because these agreements are prerequisites for securing financing. A bank won't underwrite the construction of a new data center without a multi-year offtake agreement from a credible counterparty, making these contracts foundational to supply growth.

While some neoclouds have 30% to 60% customer revenue concentration with a few frontier labs, AWS caps individual customer allocations at single-digit percentages. Matt Garman explains that AWS actively rations compute across frontier labs, enterprises, and startups. This diversification shields AWS from potential AI industry downturns while ensuring their capacity is backed by real, production-level workloads that demonstrate immediate positive return on investment.

Goldman Sachs and JPMorgan are exploring the creation of futures contracts based on the hourly rental cost of a GPU. This move would transform scarce computing power into a tradable commodity, similar to oil or corn, allowing companies to hedge against price volatility. It marks a significant step in the financialization of the AI industry's core resource.

To finance AI infrastructure without massive equity dilution, firms use debt collateralized by guaranteed, long-term purchase contracts from investment-grade customers. The rapidly depreciating GPUs are only secondary collateral, making the financing far less risky than it appears and debunking common criticisms about its speculative nature.

Early AI compute debt structures required contracts solely from investment-grade giants. Now, financiers create blended portfolios, mixing contracts from hyperscalers with those from non-investment-grade AI startups. This innovation allows startups to access large-scale compute financing previously unavailable to them, accelerating their growth.

By offering depreciation insurance and standardized data center designs, Nvidia is making GPU-backed debt predictable and tradable. This allows banks to repackage it into securities, attracting conservative capital and lowering financing costs for AI companies from venture equity levels to real estate levels.

By guaranteeing GPU value and standardizing data center designs, NVIDIA makes them fungible assets. This allows debt to be repackaged into asset-backed securities, attracting institutional capital like pension funds and moving the data center game beyond venture capital.

Commercial labs demonstrate willingness to pay massive premiums for on-demand compute access during critical training cycles. This premium spread can be leveraged to subsidize and guarantee accessible hardware for government and educational research.

The emerging market for AI compute financial instruments was kickstarted by CoreWeave. They innovated by using GPUs as collateral for debt, enabling them to fund huge infrastructure deployments ahead of competitors. This novel financing model is now becoming mainstream, paving the way for derivatives.