Meta Expands CoreWeave Deal to $21 Billion as AI Cloud Demand Grows

Meta expanded its agreement with CoreWeave to $21 billion for AI compute capacity, according to a Thursday (April 9) report from Bloomberg. The deal runs through 2032 and builds on a prior multibillion-dollar contract between the companies.

The agreement gives Meta access to large-scale GPU clusters used to train and run artificial intelligence models. CoreWeave builds its infrastructure around chips from Nvidia. These systems support both training and inference workloads.

Meta has increased spending on AI infrastructure as it scales its models and products. The company has outlined plans to spend more than $100 billion on AI infrastructure this year. The CoreWeave contract secures supply at a time when demand for GPUs exceeds available capacity.

Demand for AI compute has driven the growth of specialized cloud providers often called neoclouds. These companies focus on AI workloads rather than general-purpose computing. They offer direct access to high-performance chips and optimized infrastructure. CoreWeave is one of the largest providers in this group, according to PYMNTS.

CoreWeave has expanded its position through partnerships and acquisitions. The company acquired Monolith to extend its cloud into industrial design workloads. It has also attracted investment tied to infrastructure buildout. Nvidia committed $2 billion to CoreWeave to support data center expansion.

The company’s model depends on long-term contracts with large customers. Meta is now one of its largest clients, alongside Microsoft. These agreements provide predictable revenue and support continued investment in data centers and hardware.

CoreWeave plans to spend tens of billions of dollars to expand its infrastructure. The company has relied on debt markets to fund that growth. Its costs are tied to building data centers and securing chip supply at scale.

AI workloads are shifting toward inference, where models run inside products after training. That shift requires sustained access to compute rather than one-time training capacity. Companies are securing infrastructure to support ongoing usage as AI systems move into production.

Meta is also expanding its AI model lineup. The company introduced Muse Spark, a new large language model aimed at consumer and multimodal use cases, as reported by PYMNTS.

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