PALO ALTO, June 28 — Google has reportedly put limits on Meta’s use of its Gemini AI models, a move that has disrupted and delayed some of the social media company’s internal AI projects, according to a Financial Times report. It’s a story that, for families and businesses watching this space, underscores just how fierce the scramble for computing power has become. Even as companies pour billions into chips and data centres, they are still struggling to secure enough computing power to support the growing demand for AI services.
The report says Google told Meta around March that it could not meet the full Gemini capacity the company had sought to purchase. Meta, it appears, wanted more than Google could provide.
And while several other Google clients have also been affected—though to a lesser extent—Meta has been particularly impacted due to its exceptionally high demand, the FT said.
Token efficiency becomes the focus
What this means for the people working on those internal projects is a new kind of pressure. The Financial Times reports that Meta has encouraged staff to be more efficient with AI tokens, the units that measure AI usage. The company is essentially asking its teams to do more with less.
Behind the breakthrough, there is a very human scramble for resources. Revenue at Google Cloud grew to $20 billion in the first quarter ended March, but CEO Sundar Pichai has said that computing power constraints prevented even higher growth.
He noted the constraints contributed to the cloud unit’s backlog nearly doubling quarter on quarter. This isn’t just a technical hiccup. It’s a sign of how the AI arms race is playing out in real time, with even the biggest players feeling the pinch.
A complicated relationship
The relationship between these two tech giants has been a complex one. In September 2025, it was reported that Meta was in talks with Google Cloud to leverage its Gemini AI models for more effective advertising. According to The Information, Meta was exploring options to fine-tune Google’s Gemini and open-source Gemma models with its own advertising data.
All of this despite the fact that Meta and Google directly compete in the online advertising market. Meta had also been considering partnerships with Google or ChatGPT maker OpenAI to improve AI features, including conversational responses for queries on its chatbot.
For now, the limits Google has placed on Meta’s use of Gemini serve as a reminder that even the most ambitious AI plans can be slowed by the simple, stubborn reality of not having enough computing power to go around. The question for the months ahead is how these companies will navigate the bottleneck—and what it means for the rest of us waiting to see what AI can truly deliver.
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