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Meta Shares Pare Losses on Report of $10 Billion AI Data Center Talks with Anthropic

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Jul 17, 20261 min read
Meta Shares Pare Losses on Report of $10 Billion AI Data Center Talks with Anthropic

Summary

Shares of Meta Platforms recovered from a steep intra-day decline following a New York Times report that the company is in early talks with AI startup Anthropic for a potential $10 billion deal to lease its data center capacity.

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Background

Meta Platforms (NASDAQ:META) shares pared steep earlier losses after a report from The New York Times revealed the company is in early-stage discussions with AI startup Anthropic for a potential $10 billion deal to lease its artificial intelligence data centers.

Following the news, Meta's stock recovered from a 5.7% drop to trade down approximately 3%.

Details of the Proposed Deal

According to the report, Anthropic initiated the proposal in June. The arrangement would involve the AI firm paying Meta in monthly installments over a two-year period for access to its extensive AI computing infrastructure.

The proposed terms would also allow either company to exit the agreement early. The discussions underscore the intense competition among AI developers for the vast, specialized computing power required to train and operate advanced models.

Strategic Implications

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For Meta, a successful deal would establish a significant new business line, allowing it to monetize its massive investments in proprietary AI hardware and data centers. The company has been aggressively expanding its AI infrastructure as a core part of its technology strategy.

For Anthropic, the agreement would secure critical and scarce computing resources. This move mirrors a larger deal the AI company reportedly signed with SpaceX in May, under which it agreed to pay $45 billion over three years for computing power, highlighting the capital-intensive nature of the AI arms race.

Broader Market Context

This potential partnership reflects a growing trend where companies with large-scale computing capacity can lease their excess resources to AI firms facing a hardware shortage. The scarcity of high-end GPUs and other specialized components has become a major bottleneck for the industry, creating new market opportunities for established tech giants with built-out infrastructure.

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