CoreWeave Expands Agreement with OpenAI by up to $6.5 Billion

CoreWeave Expands Agreement with OpenAI by up to $6.5 Billion

CoreWeave, Inc. (Nasdaq: CRWV), the AI Hyperscaler™, today announced a significantly expanded agreement with OpenAI to power the training of its most advanced next-generation models. The new contract, valued at up to $6.5 billion, reinforces CoreWeave’s position as a leading cloud platform for the most demanding AI workloads.

This latest agreement builds on a series of major partnerships between the two companies. In March 2025, CoreWeave announced an initial deal with OpenAI worth up to $11.9 billion, followed by a May 2025 expansion worth up to $4 billion. With today’s announcement, the total contract value with OpenAI now reaches approximately $22.4 billion.

Executive Commentary

“We are proud to expand our relationship with OpenAI, a company consistently at the forefront of advancing artificial intelligence,” said Michael Intrator, Co-Founder, Chairman, and CEO of CoreWeave. “This milestone affirms the trust that world-leading innovators have in CoreWeave’s ability to power the most demanding inference and training workloads at an unmatched pace.”

“CoreWeave has become an important partner in OpenAI’s broader infrastructure platform,” added Peter Hoeschele, VP of Infrastructure and Industrial Compute at OpenAI. “By delivering compute at unmatched speed and scale, they’re helping us advance the frontier of intelligence and ensure AI’s benefits reach everyone.”

Expanding Role in AI Innovation

The partnership with OpenAI follows a series of recent CoreWeave milestones:

  • A $1.5 billion commitment to support AI innovation and growth in the UK.
  • The launch of CoreWeave Ventures, a fund supporting AI founders and startups.
  • Strategic acquisitions of OpenPipe and Weights & Biases, strengthening CoreWeave’s technology stack and expanding its ecosystem.

CoreWeave continues to position itself as a critical infrastructure provider for the global AI industry, enabling enterprises and labs to scale at speed and meet growing computational demands.

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