Google told Meta back in March that it couldn’t deliver the full computing capacity Meta wanted for its Gemini AI models. The Financial Times reported the restriction on June 28, noting that the shortfall has caused real disruptions and delays across several of Meta’s internal AI initiatives.
What happened and why it matters
Meta had been purchasing access to Google’s Gemini models through cloud and API services, seeking significantly more capacity than what Google ultimately proved able to supply.
Meta responded by directing employees to optimize their usage of AI tokens, the units that measure compute consumption for AI projects.
Other Google clients also faced limitations, but Meta’s outsized demand put it in a uniquely difficult position. As of late June 2026, the restrictions remain in place.
