Google Limits Meta’s Gemini Usage Over Compute Shortages
Meta was told to ration token use after Google could not meet the full Gemini compute request, delaying internal AI projects, sources said.
- Google capped Meta's access to its Gemini AI model after Mark Zuckerberg's company exceeded its computing capacity. The tech giant informed Meta in March that it could no longer supply the requested volume, forcing the company to ration token usage.
- Current artificial intelligence infrastructure faces severe physical constraints rather than a supply glut, with major companies struggling to secure enough capacity for their needs. This scarcity forces buyers to ration resources despite massive, industrial-scale investments into data centers.
- Google Cloud is spending over $180 billion on capacity this year and recently agreed to pay SpaceX $920 million monthly for roughly 110,000 Nvidia GPUs. This "bridge" capacity supports Gemini Enterprise, which faces demand higher than Google can serve.
- Meta, which initially chose Gemini because it outperformed its own Llama models for content moderation, is now accelerating its shift back to in-house technology. The company committed over $100 billion to build its own data centers to reduce reliance.
- While critics warn of an AI bubble, persistent rationing and massive backlogs suggest demand is outstripping physical supply. This bottleneck positions companies controlling chips, networking, and power as primary beneficiaries of the infrastructure buildout.
17 Articles
17 Articles
Google couldn't give Meta enough AI power — here's why running AI locally suddenly makes even more sense
Cloud AI has felt limitless for years. But according to a Financial Times report, Google told Meta back in March that it couldn't supply all the Gemini computing capacity Meta wanted to buy. Meta had been paying for access to Google's models through cloud and API services, leaning on Gemini for internal jobs like content moderation and scam detection, where it outperformed Meta's own Llama models. When Google couldn't meet the full request, the …
Google restricts Meta’s Gemini AI access amid computing crunch
Google restricts Meta's access to Gemini AI models, disrupting Meta's internal AI projects amid a computing power shortage. The AI sector faces a severe capacity crunch, with Google's cloud unit backlogged by $460 billion in undelivered contracts. Google leases $920 million/month in computing power from SpaceX to address infrastructure shortages, mirroring deals by Anthropic. Meta shifts to its own Muse Spark model to reduce reliance on rival…
Meta has been secretly relying on Google's AI for customer service, ad tools, and content moderation – then got cut off
According to the Financial Times, Google warned Meta around March that it could not provide all the capacity the company wanted, disrupting and delaying internal AI projects.Read Entire Article
The artificial intelligence hyperdemand has caused an unusual bottleneck: not even Google, owner of the world’s third public cloud, can serve all the capacity demanded by its customers. Meta, one of the biggest consumers of foreign computing, has encountered the closed tap. Keys of the operation Google ratioizes access to Gemini by saturation. The company cannot meet Meta’s additional demand for fraud detection, advertising chatbots and programm…
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