Google limits Meta access to Gemini

The AI bottleneck is real, and hardware capacity, not model quality, remains the ultimate choke point for scaling intelligence.

• –Meta's heavy reliance on external API models like Google Gemini for internal tasks reveals limits in its own model serving and hardware infrastructure, despite championing the open-source Llama series.
• –Google's inability to supply Meta's requested computing power highlights the severe physical scaling limitations faced by major cloud providers.
• –This capacity crunch will likely accelerate industry efforts around token efficiency, model quantization, and the deployment of smaller, specialized local models.