CoreWeave’s next test: From GPU scarcity to a durable AI cloud

Ahead of CoreWeave’s Fully Connected conference, we have made a notable investment in proprietary customer research with Qualitate. Rather than simply repeat the earnings call, we went to the people evaluating, buying and running the infrastructure. This analysis draws on thirteen in-depth interviews and more than seven hours of interview time. We then compared that evidence with CoreWeave’s financial disclosures and the public statements of CEO Michael Intrator and CFO Nitin Agrawal. Our research indicates that GPU scarcity opens the door, but performance, cost and the operating experience give customers reasons to stay. Inference is growing alongside training. Notably, training is not declining at the expense of inference. Inference is growing on a very steep curve and training workloads continue to grow as well. At the same time, the hyperscalers remain deeply embedded in the application estate, and not every successful CoreWeave eval turns into a signed customer. The question is whether CoreWeave is converting an availability advantage into a durable AI cloud. We believe the customer evidence strengthens that case. It also shows exactly where the case still needs work.