Evan Conrad: Most AI startups cannot purchase computing power

Evan Conrad published an article on October 22 titled "The end of startups," with the subtitle "The coming credit crunch." Evan Conrad stated that within the next six months, most AI startups will be unable to purchase computing power, as global computing power is sold out. To obtain capacity, new clusters need to be contracted, and it is becoming increasingly difficult for non-investment-grade entities to secure online capacity.

Evan Conrad mentioned that startups are not investment-grade, thus they are required to pay larger upfront payments. He has seen cases where 100% of the contract amount is required to be prepaid, as lenders and cloud providers are unwilling to take on additional credit risk. He believes that investment-grade tenants are scarce, and due to leveraging and selling to non-investment-grade token buyers, their ratings are downgraded, which he refers to as a credit bottleneck. He anticipates that investment-grade GPU buyers will increasingly demand that token buyers themselves be investment-grade or pay large upfront deposits.

In the article, he provides an example where, at the time of writing, B300 could be purchased for $6 per hour and then sold for approximately $30 per hour for inference. He expects GPU prices to rise, and the gross margin for inference layers to decline, making it harder for clients with poor credit to obtain tokens. He proposed that lenders treat GPU clusters as collateral and stated that the physical delivery forward market SF Compute could allow lenders to use GPU hours on a liquidity book as collateral, rather than relying on a single service provider's cluster.