Google limits Meta access to Gemini as AI demand strains capacity

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Last Updated:June 28, 2026, 16:10 IST

Google reportedly limited Meta access to Gemini AI after failing to meet its capacity request, disrupting Meta projects and highlighting infrastructure strains in the AI race.

 AFP/File)

Google reportedly limited Meta access to Gemini AI after failing to meet its capacity request, disrupting Meta projects and highlighting infrastructure strains in the AI race. (Image: AFP/File)

Google has reportedly restricted Meta’s use of its Gemini artificial intelligence models after the Facebook parent requested more computing capacity than the tech giant could provide, highlighting growing infrastructure constraints in the AI race.

According to a Financial Times report, Google informed Meta around March that it could not fulfil the full Gemini capacity the company wanted to purchase. The shortfall is said to have disrupted and delayed some of Meta’s internal AI projects.

AI Boom Strains Infrastructure

The report said the restrictions remain in place, prompting Meta to encourage employees to use AI tokens—units that measure AI usage—more efficiently as part of a broader effort to control AI-related costs.

While other Google customers have also reportedly faced capacity limits, Meta has been affected the most because of its exceptionally high demand for Gemini models.

Pressure Mounts In AI Race

The development underscores the mounting pressure on major AI companies as demand for advanced models outpaces the availability of computing resources, despite billions of dollars being invested in chips, data centres and power infrastructure.

Meta has been investing heavily in artificial intelligence after delays in rolling out its next-generation “Avocado" AI model and has previously explored licensing Google’s Gemini models to support some of its AI products.

Neither Company Comments

Google and Meta have not publicly commented on the reported capacity restrictions.

The episode offers a rare glimpse into the infrastructure bottlenecks facing even the world’s biggest technology companies as they compete to develop increasingly powerful AI systems.

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