CoreWeave stock closed 10% higher on Friday after the company said it had signed a multiyear agreement with Anthropic to provide computing power for the AI startup’s models. The deal will use CoreWeave’s cloud services to run Anthropic workloads at production scale, with the first phase rolling out gradually and room to expand later.
The companies did not disclose pricing or how many gigawatts of chips the arrangement covers, leaving investors to guess at the size of the commitment even as the stock moved sharply. CoreWeave said the deal will help Anthropic build and power its AI systems, another sign that the race for cloud capacity is still running hot.
The announcement lands in the middle of an industry-wide scramble for semiconductors and server capacity as AI companies try to lock down enough compute to keep their products running. Earlier this week, Anthropic said it is working with Broadcom and Google to use 3.5 gigawatts of Google’s Broadcom-made Tensor Processing Units, and reported that the company is also considering designing its own chips to contend with the AI chip crunch.
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That push mirrors moves across the sector. In October, OpenAI entered into a partnership with Broadcom to develop upwards of 10 gigawatts of custom semiconductors for its AI services. In January, Microsoft revealed a new custom AI chip aimed at serving as an alternative to Nvidia and AMD’s offerings. Last month, Meta revealed four new custom AI processors, including its MTIA 400, and said CoreWeave would power Meta’s AI services through December 2032.
CoreWeave has its own web of supply arrangements, including deals with Nvidia and AMD, and said Meta’s capacity will be spread across a number of its data center locations. The company also said some of the first deployments of Nvidia’s upcoming Vera Rubin system will be included in that work. Amazon and Google have been using their own chips for years, though unlike Microsoft they are also looking to sell or rent those chips to third-party customers.
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For Anthropic, the new CoreWeave agreement adds another route to the computing muscle it needs, but it does not settle the larger question now shaping the AI buildout: who controls the chips, the cloud, and the cost of staying in the race.
