NVIDIA CEO Jen Hsun Huang sold 200K shares of common stock between June 24 and June 26, 2025, at an average price of $152.3271 for a total value of $30.47 million. According to InvestingPro data, these transactions occurred as NVIDIA’s stock traded near its 52-week high of $156.72.
On June 24, Huang sold 4,918 shares at a weighted average price of $146.1433, 42,013 shares at $147.1666 and 3,069 shares at $147.7522.
The following day, June 25, Huang continued selling shares, with 3,043 shares sold at an average price of $149.8507, 6,429 shares at $151.0466, 24,866 shares at $151.8086, 11,499 shares at $152.6631 and 28,277 shares at $153.7151 and 886 shares at $154.352.
The sales concluded on June 26, with 11,324 shares sold at an average price of $154.7779, 54,331 shares at $155.6449 and 9,345 shares at $156.2868.
Following these transactions, Huang directly owns 75,473,225 shares of NVIDIA CORP. He also indirectly owns a significant amount of shares through various trusts, partnerships and limited liability companies.
In other recent news, Barclays has raised its price target for Nvidia to $200, maintaining an Overweight rating, citing a potential $2 billion upside for the company’s July quarter compared to consensus estimates. The firm increased its Compute revenue estimate to about $37 billion, up from $35.6 billion, and forecasts Nvidia’s quarterly revenue to reach $42 billion for the third calendar quarter. Meanwhile, Northrop Grumman (NYSE:NOC) is expanding its use of Nvidia technology to enhance AI applications for space operations, aiming to improve efficiency in spacecraft activities. Cyngn, another company leveraging Nvidia’s platform, was recently featured in a blog post by Nvidia, highlighting its use of the Isaac platform to develop autonomous industrial vehicles. SandboxAQ has released a large dataset using Nvidia chips to accelerate drug discovery, aiming to improve predictions of drug-protein binding. Additionally, Malaysia’s trade ministry is investigating reports of a Chinese firm using Nvidia AI chips in the country to train large language models, ensuring compliance with local regulations.