
What happened
Philippe Laffont's Coatue Management reduced its Nvidia holding from 49.8 million shares in Q1 2023 to 6.06 million shares in Q2 2026, cutting the stake by roughly 88% over that period. Laffont sold Nvidia stock in 12 of the last 13 quarters, with only Q2 2025 seeing a net addition of 2.9 million shares.
Why it matters
Nvidia's graphics processing units dominate AI-accelerated data centers, yet Laffont's persistent selling suggests concerns beyond simple profit-taking. Major Nvidia customers are developing cheaper in-house AI chips that could reduce demand for Nvidia's hardware and erode the GPU shortage that has supported the company's pricing power. History also shows that game-changing technologies have typically experienced early bubble-bursting events, raising questions about whether investors are overestimating AI adoption speed.
What to watch
Nvidia is scheduled to report operating results on August 26. Laffont's latest quarterly 13F filing (covering Q2 2026 trading activity) was due Friday, August 14, revealing his continued reduction in Nvidia exposure despite the stock having jumped tenfold since his stake peaked in Q1 2023.
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Philippe Laffont's sustained selling of Nvidia over the past three years stands out precisely because Nvidia's product dominance in AI-accelerated data centers is widely acknowledged on Wall Street. Since Q1 2023, when his stake peaked, Nvidia's share price has jumped tenfold—a trajectory that would ordinarily cement confidence in a long-term holding. Yet Laffont has methodically reduced exposure in nearly every subsequent quarter, suggesting his concerns run deeper than harvesting gains from a winning bet.
The body identifies two structural headwinds that likely motivate this selling. First, Nvidia's largest customers—cloud providers and hyperscalers—are now engineering their own proprietary AI chips. These in-house alternatives are not only cheaper and more accessible than Nvidia's offerings but also begin to fill data center capacity that would otherwise demand Nvidia hardware, thereby reducing the GPU shortage that has historically supported Nvidia's pricing power. Second, the article invokes a 30-year historical pattern: every transformative technology has experienced an early bubble-bursting event, driven by investor overestimation of adoption speed and optimization timelines. If this pattern holds, AI may not be exempt, and a correction could follow the current enthusiasm.
Together, these dynamics suggest Laffont is positioning ahead of potential headwinds that the broader market has not yet fully priced in. His continued selling despite Nvidia's valuation of $5.45 trillion implies skepticism about whether the company can maintain its current valuation amid tightening competitive dynamics and a possible AI-adoption plateau.
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