Google limits Meta’s Gemini AI access as compute demand outpaces supply

Investing.com -- Google has restricted Meta Platforms’ access to its Gemini artificial intelligence models after the Facebook parent sought more computing capacity than Google could provide, the Financial Times reported on Sunday, citing people familiar with the matter.

According to the report, Google informed Meta around March that it could not meet all of the company’s requested Gemini capacity. The restrictions remain in place and have delayed some of Meta’s internal AI projects.

Meta has also encouraged employees to use AI resources more efficiently as part of a broader effort to reduce computing costs. Other Google customers have reportedly been affected by similar capacity limits, though the impact has been greatest on Meta because of its unusually high demand.

The move highlights growing infrastructure constraints across the AI industry, where surging demand for computing power continues to outpace available capacity despite heavy investment in chips, data centers, and power infrastructure.

Google has been expanding its own computing resources to address rising demand. Earlier this month, the company agreed to lease computing capacity from SpaceX in a deal reportedly worth about $920 million per month.

Speaking during the company’s first-quarter earnings call in April, Chief Executive Sundar Pichai said Google Cloud revenue exceeded $20 billion for the first time, while the backlog of signed but undelivered cloud contracts nearly doubled from the previous quarter to more than $460 billion.

Pichai also acknowledged that computing capacity remains constrained in the near term, adding that cloud revenue would have been higher if Google had been able to meet customer demand.

Meta has been investing heavily in artificial intelligence infrastructure as Chief Executive Mark Zuckerberg seeks to strengthen the company’s AI capabilities. The company has committed to investing up to $600 billion in the United States through 2028 to expand data center capacity.

Internally, Meta has used Google’s Gemini models for coding, customer service, advertising tools, and content moderation. The report said the company has recently begun shifting some workloads to its own Muse Spark model, reducing its reliance on third-party AI models for certain applications.