Evan Conrad: Most AI Startups Will Be Unable to Purchase Computing Power in the Next 6 Months

Evan Conrad published an article stating that in the next 6 months, most AI startups will be unable to purchase computing power as global computing resources are sold out, requiring contracts for new clusters to obtain capacity. Startups are required to pay higher upfront fees due to their non-investment-grade status, with some contracts demanding 100% prepayment, and lenders and cloud providers are unwilling to take on additional credit risk. Investment-grade tenants are scarce, as ratings are downgraded due to leveraging and selling to non-investment-grade token buyers, creating a credit bottleneck. Investment-grade GPU buyers will increasingly require token buyers to have investment-grade qualifications or to make large upfront deposits. The article mentions that during the writing, B300 could be purchased for $6 per hour and sold for approximately $30 per hour for inference. GPU prices are expected to rise, with gross margins for inference layers declining, making it harder for credit-challenged customers to obtain tokens. Evan Conrad suggests that lenders could treat GPU clusters as collateral and recommends that the physical delivery forward market SF Compute allows lenders to use GPU hours on liquidity books as collateral, rather than relying on a single service provider's cluster.

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