Marvell Technology Group Ltd. shares reached a record high Tuesday after Nvidia CEO Jensen Huang called the company the next trillion-dollar company [1].
The endorsement from the leader of the world's most prominent AI chip designer signals a shift in investor confidence regarding the broader AI infrastructure supply chain. By highlighting Marvell's importance, Huang has effectively validated the company's strategic position in the hardware ecosystem required to sustain artificial intelligence growth.
Shares of the NASDAQ-listed company saw a significant spike during trading on June 2, 2026. Reports on the exact percentage of the gain varied among financial outlets, with some citing a rise of more than 22% in premarket trading [2], while others reported a surge of more than 25% [1]. One report indicated the jump was even higher, exceeding 27% [3].
"Marvell is the next trillion-dollar company," Huang said [1].
Analysts noted that the market reaction was a direct result of the CEO's public confidence in the firm's trajectory. One analyst said that this endorsement from Nvidia’s CEO sent the stock sharply higher [2].
Huang connected the company's valuation potential to its role in the technical framework supporting generative AI. "We see Marvell playing a pivotal role in the AI infrastructure ecosystem," Huang said [3].
Marvell focuses on data infrastructure, including networking, and storage solutions. The sudden buying pressure reflects a growing belief among traders that the financial success seen by Nvidia will spread to the secondary layer of chipmakers and infrastructure providers — those who enable the connectivity and data flow between massive GPU clusters.
“"Marvell is the next trillion-dollar company," Jensen Huang said.”
This event demonstrates the 'multiplier effect' of Nvidia's influence on the semiconductor industry. Because Nvidia defines the current AI standard, its CEO's public endorsement acts as a powerful market signal, shifting capital toward companies that facilitate the networking and data movement essential for large-scale AI clusters.
