- OpenAI agrees to buy up to 750 megawatts of computing capacity from start-up Cerebras over three years.
- The deal highlights how AI firms are diversifying beyond traditional chip suppliers to scale next-generation models.
What happened: Massive AI compute commitment
OpenAI has struck an agreement to acquire up to 750 megawatts of dedicated computing power from chip start-up Cerebras Systems over a three-year period in a contract valued at more than $10 billion, according to people familiar with the matter.
The capacity will be delivered in phases through to 2028 and will underpin the infrastructure for the company’s large-scale AI systems, including its flagship ChatGPT service. The arrangement follows a blog announcement by OpenAI and represents one of the largest single compute commitments in the industry to date.
Cerebras, known for its wafer-scale engine architecture that integrates massive compute, memory and bandwidth on a single giant chip, has historically competed against GPU-based systems from companies such as Nvidia. The start-up has been diversifying its customer base beyond its early backer, UAE-based G42.
Both partners are navigating growth phases: Cerebras is reportedly preparing for an initial public offering, while OpenAI has laid groundwork for its own potential IPO with valuations discussed as high as $1 trillion in some reports.
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Why it’s important
Compute capacity has become a strategic asset in the AI arms race. Companies like OpenAI must secure access to specialised hardware not just for training but for inference — the real-time processing that enables applications such as ChatGPT to respond quickly.
By partnering with Cerebras, OpenAI is diversifying its hardware supply chain beyond mainstream GPU vendors, addressing latency and scalability as AI workloads grow. Experts see such bespoke deals as critical for the next wave of AI services that demand high throughput with low energy cost.
For Cerebras, the contract provides a marquee customer and a revenue stream that could bolster its position ahead of a planned IPO. Its wafer-scale technology has drawn interest from other AI developers seeking alternatives to conventional GPU architectures.
However, the scale of spending by AI firms has prompted some in the industry to caution about potential overheating in the sector, with comparisons drawn to earlier technology bubbles.
