Nvidia (NASDAQ: NVDA) CEO Jensen Huang isn’t afraid to praise other companies and call out their potential, and he did just that recently on stage at the Computex event in Taipei. He applauded Marvell Technology (NASDAQ: MRVL), saying it could be set to become the “next trillion-dollar company.”
Huang’s comments sent shares of the semiconductor stock soaring 32.5% last Tuesday (June 2). Following the big move, the stock now has a market cap of over $250 billion. So, if Huang is right, the stock could still quadruple from here. For its part, Nvidia took a $2 billion stake in Marvell earlier this year.
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An optics winner
Marvell has two main businesses. Along with Broadcom, the company is a leader in ASIC (application-specific integrated circuit) technology, providing IP to companies designing their own chips. It tends to take a more à la carte approach to ASIC designs compared to Broadcom, which is more about offering an entire ecosystem. Marvell also has some important IP around SRAM (static random-access memory), which is the memory used in Nvidia‘s language processing units and Cerebras‘ chips for inference.
While Marvell has more than 20 custom chip customers, its biggest customer is Amazon, which uses some of Marvell’s IP for its Trainium chip. However, there has been some concern that Marvell is going to play a less prominent role with Trainium chips in future iterations, with Taiwanese company AIchip taking over the lead role. Marvell also provides IP for Microsoft‘s newer Maia chips. That could help fill any losses from business with Amazon, although Microsoft’s custom chips have yet to gain traction. It’s also possible that the Amazon whole pie just continues to grow fast enough that Marvell sees no material impact and that Microsoft has enough internal demand to fuel growth in Maia use.
However, Marvell’s ASIC business isn’t the main reason Nvidia made an investment in Marvell or why Huang thinks it could become a trillion-dollar company. That would be its connectivity business, where Marvell is a leader in optical interconnects. AI clusters continue to grow in size, and hyperscalers are starting to disaggregate server architectures into specialized clusters to separately handle the prefill and decode phases of inference. This all needs lightning-quick connectivity, and optical interconnects are starting to replace copper wires as a result.
