Google has imposed limits on Meta’s access to its Gemini AI models after the social media company requested more computing capacity than the rival tech group could deliver, the Financial Times reported on Sunday. The shortfall disrupted and delayed some of Meta’s internal AI projects, according to the report, which cited people familiar with the matter.
Compute Constraints at Google
Google, owned by Alphabet, told Meta around March that it could not meet the full Gemini capacity the company had sought, the FT said. Several other Google clients have also been affected, though to a lesser extent. Meta has been particularly impacted due to its exceptionally high demand for Google’s models, the report added.
Due to the restrictions, Meta has encouraged staff to be more efficient with AI tokens, the units that measure AI usage, the FT reported.
Broader Industry Challenges
Even as companies continue to spend billions on chips and data centres, they are still struggling to secure enough computing power to support the growing demand for AI services, the article noted. Google Cloud revenue grew to $20 billion in the first quarter ended March, but CEO Sundar Pichai said computing power constraints prevented even higher growth and contributed to the cloud unit's backlog nearly doubling quarter on quarter.
Implications for Enterprise AI Deployment
The situation highlights the intense competition for AI compute resources among major technology players. For enterprise technology decision-makers, especially those in supply chain, logistics, and trade — sectors increasingly dependent on AI for automation, forecasting, and documentation — the scarcity of AI compute can directly impact project timelines and operational efficiency. The need for efficient token usage and the risk of dependency on a single AI vendor are key takeaways from this incident.
| Operational Impact | Detail |
|---|---|
| Affected projects | Meta’s internal AI projects disrupted and delayed |
| Other clients | Several other Google clients affected, but to a lesser extent |
| Meta’s response | Encouraged staff to be more efficient with AI tokens |
| Google Cloud revenue | $20 billion in Q1 2026, but growth capped by compute limits |
| Backlog | Nearly doubled quarter on quarter due to compute constraints |
Conclusion
The FT report, which Reuters could not independently verify, underscores that even the largest AI developers face compute limitations. For enterprises relying on models like Gemini, this serves as a reminder to plan for capacity bottlenecks and to explore multi-provider strategies.
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