Google has limited Meta’s access to its Gemini AI models as demand for computing power outpaces available capacity at its data centers. Meta is adapting by leaning on its in-house Muse Spark model and accelerating investments to reduce reliance on external providers.
Google has imposed quotas on Meta’s use of its Gemini AI models due to rising demand for compute resources. The limitations affect tasks such as content moderation and scam detection, with capacity constraints forcing tighter controls at peak usage periods.
In response, Meta has increased reliance on its proprietary Muse Spark model and accelerated capital injections into its own data centers. The company has committed billions of dollars to expand on-premises infrastructure and reduce dependency on external AI compute providers.
The incident underscores the strategic value of AI compute capacity, positioning cloud and chip providers with large data center networks as critical industry gatekeepers. Investors may view Google’s capacity control as a growing competitive advantage in the race for advanced AI model deployment.
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