{"id":187266,"date":"2026-06-28T23:16:14","date_gmt":"2026-06-29T04:46:14","guid":{"rendered":"https:\/\/newslink360.space\/?p=187266"},"modified":"2026-06-28T23:16:14","modified_gmt":"2026-06-29T04:46:14","slug":"new-twist-in-the-world-of-ai-google-sets-limit-on-metas-gemini-ai-access-know-the-whole-matter","status":"publish","type":"post","link":"https:\/\/newslink360.space\/?p=187266","title":{"rendered":"New twist in the world of AI! Google sets limit on Meta’s Gemini AI access, know the whole matter"},"content":{"rendered":"

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According to the report, Google has limited access to Meta’s Gemini AI models due to lack of computing capacity. Some AI projects of Meta have been affected by this. Know the lack of AI infrastructure and complete details of this report.<\/h2>\n
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Big problem for Meta, Google refused to give full potential of Gemini AI<\/span><\/figure>\n

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In the world of Artificial Intelligence (AI), the competition between big tech companies is continuously intensifying. Meanwhile, a new report has claimed that Google refused to give Meta as much computing capacity as the company had asked for to use its Gemini AI models. It is being told that due to this the pace of some AI projects of Meta has slowed down.<\/p>\n

According to the Financial Times report, around March Google told Meta that it could not provide the full computing capacity requested for Gemini AI models. According to the report, this shortage affected some internal AI projects of Meta and they were delayed.<\/p>\n

It is being said that this limit is still in force. For this reason, Meta has advised its employees to use AI tokens more effectively. AI token is a unit to measure the usage of an AI model and it can better control the expenses related to AI.<\/p>\n

Increasing demand for AI becomes a big challenge
<\/strong>The report shows that not only Meta, some other customers of Google are also facing shortage of computing capacity. However, due to the highest demand for Meta, its impact has been greater.<\/p>\n

This situation shows that the computing resources available around the world are still falling short of the increasing demand for AI models. Big tech companies are investing billions of dollars in chips, data centers and power infrastructure, but still the lack of capacity is being felt.<\/p>\n

Google and Meta did not respond
<\/strong>Meta has been busy expanding its AI business rapidly for some time. According to the report, the company also explored the possibility of using Google’s Gemini models after the delay in its next-generation Avocado AI model.<\/p>\n

However, till now neither Google nor Meta has issued any official statement on this entire matter. At present, this information is based on reports, but it gives a clear hint that the biggest challenge in the race of AI is not only making better models, but also providing adequate infrastructure to run them.<\/p>\n<\/div>\n

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About the Author<\/h2>\n
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Afreen Afaq<\/a><\/p>\n

Afreen Afaq has started her career with Network 18 as a Tech Journalist, and has more than six years experience in ‘Mobile-Technology’ beat. She is a high-performing professional with an established and proven …read more<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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