CoreWeave Surges 15% as It Signs $14 Billion AI Infrastructure Deal with Meta

Reuters
昨天

CoreWeave said it has signed a $14 billion agreement with Meta to supply computing power, the latest multi-billion-dollar deal as businesses ramp up infrastructure to meet the demand for artificial intelligence applications.

Shares of CoreWeave surged about 15% following the news on Tuesday.

Under the agreement, Meta has committed to pay around $14.2 billion through December 14, 2031, with the option to expand through 2032 for additional cloud computing capacity, CoreWeave said in a filing.

AI technology developers are rushing to sign multi-billion-dollar deals to lock in infrastructure quickly, boosting valuations of these backend service providers such as CoreWeave, which is now valued at $60 billion.

The boom has also raised questions about the "circular" financing, as many AI tech firms invest in and sign supply deals with each other. This has also sparked worries about whether the surge in valuation is a bubble.

The deal with Meta would also allow CoreWeave to fill data center capacity beyond its largest customer, Microsoft.

Meta has been one of the biggest proponents of AI, investing tens of billions into data centers across the U.S. and paying athlete salaries to hire top AI software engineers while competition intensifies. The social media firm did not immediately respond to a Reuters request for comment.

As a part of the agreement, CoreWeave will provide the Facebook-parent access to Nvidia's latest GB300 systems, according to a Bloomberg report, citing an interview with the data center operator's CEO Michael Intrator.

The new deal comes a week after CoreWeave signed a third multi-billion dollar cloud expansion deal with OpenAI to aid the ChatGPT maker with its computational needs. CoreWeave executives had then noted sky-high demand from clients.

CoreWeave operates AI data centers in the U.S. and Europe, offering access to Nvidia's graphic processing units, which are highly sought after for training and running large AI models.

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