Nvidia invests $2 billion in CoreWeave to speed buildout of “AI factories” through 2030
Nvidia said it is investing $2 billion in CoreWeave as the companies expand a partnership aimed at scaling AI data-center capacity. The plan targets more than 5 gigawatts of “AI factories” by 2030 and deepens platform alignment across compute, storage and CPUs.
Nvidia announced Monday it is investing $2 billion in CoreWeave as the companies deepen a partnership focused on expanding large-scale AI computing infrastructure. The investment is intended to accelerate CoreWeave’s buildout of what the firms describe as “AI factories,” aiming for more than 5 gigawatts of capacity by 2030.
The chipmaker said it purchased CoreWeave Class A common stock at $87.20 per share. Nvidia framed the move as a vote of confidence in CoreWeave’s growth strategy as a cloud platform built around Nvidia infrastructure, at a moment when demand for AI compute continues to rise rapidly across industries.
Beyond the equity investment, the companies described a broader expansion of collaboration across hardware and software. CoreWeave is expected to adopt additional Nvidia platforms, while the relationship will extend into deployment planning that pairs next-generation compute with storage and networking systems needed for modern AI workloads.
The deal underscores the intensity of competition to secure sufficient power and capacity for AI services. Data centers tuned for AI training and inference require dense compute, sophisticated cooling and reliable energy supply, and many operators are racing to lock in equipment and sites years in advance.
For Nvidia, the investment also reinforces the company’s strategy of building an ecosystem that can deliver AI compute at scale beyond the largest hyperscalers. As more enterprises adopt AI, partnerships with specialized cloud providers can help expand capacity in parallel with big-tech spending.
The companies said the expanded partnership is designed to support broad AI adoption globally. Investors will watch for how quickly new capacity comes online, how utilization ramps, and whether the economics of AI cloud services remain durable as competition and power constraints shape the next phase of growth.