Google limits Meta’s use of its Gemini AI models, FT reports
Yahoo Finance ·
Google limits Meta’s use of its Gemini AI models, FT reports Reuters Sun, June 28, 2026 at 1:23 AM EDT 1 min read GOOGL META June 28 (Reuters) - Google has put limits on Meta's use of its Gemini AI models after the social media company sought more computing capacity than the rival tech group could provide, the Financial Times reported on Sunday. Google, owned by Alphabet, told Meta around March it could not meet the full Gemini capacity the company had sought to purchase, the newspaper said, adding that the shortfall disrupted and delayed some of Meta's internal AI projects. Several other Google clients have also been affected, though to a lesser extent, according to the report. Meta has been particularly impacted due to its exceptionally high demand for Google's models, the FT said. Reuters could not immediately verify the report, which cited people familiar with the matter. Google and Meta did not immediately respond to requests for comment outside business hours. Due to the restrictions, Meta has encouraged staff to be more efficient with AI tokens, the units that measure AI usage, the FT report said. 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. Revenue at Google Cloud 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. (Reporting by Abu Sultan in Bengaluru; Editing by William Mallard and Sonali Paul)
AI 시장 분석
According to the FT, Google(Alphabet) refused to provide META with the full capacity of the Gemini model requested, which caused delays and disruptions to parts of META's internal AI projects. Other Google customers were also partially affected, but META's demand was unusually large. Companies are still investing billions in chips and data centers, yet persistent compute shortages are constraining cloud growth and delaying service timelines. The fallout is expected to accelerate in-house infrastructure investment, benefit competing cloud providers, and delay product development at AI startups and major platforms.
상승 영향
- Semiconductors/AI accelerators — As firms shift to expand their own GPU and AI accelerator capacity, demand for AI-focused chips such as NVIDIA·AMD is set to surge, driving revenue growth and higher capital expenditures.
- Data centers & cloud infrastructure — Compute shortages are pushing companies to expand their own data centers and increase colocation demand, likely improving profitability for infrastructure construction and operations providers.
- Cloud competitors (AWS, Azure, etc.) — Google's capacity limits could prompt large customers like META to seek alternative suppliers, giving short-term benefits to competing clouds such as AWS and Microsoft Azure.
- AI cost and token optimization solutions — Rising demand for token- and inference-efficiency will expand demand and revenue opportunities for software and service firms that provide cost-reduction and optimization solutions.
하락 영향
- META / Social media & metaverse — Gemini capacity limits are delaying internal AI projects and the product roadmap, slowing new feature rollouts and improvements in ad targeting, which raises concerns about weakening competitiveness.
- Google Cloud customers (SMB AI startups, — Increased compute constraints and backlogs are causing project delays and higher costs, slowing product development and increasing operational uncertainty for these customers.
- AI service startups — Restricted access to third-party models and cloud resources raises development and scaling costs, likely limiting market entry and growth pace for startups providing AI services.
- Cloud services (from some customers' per — Compute constraints can hinder customers' revenue growth and service rollouts, potentially harming cloud customers' business performance and return on investment.
AI가 생성한 분석으로 투자 자문이 아닙니다.
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