Nvidia CEO Jensen Huang Believes That Marvell Technology Could Become a $1 Trillion Company. Here’s Why He Is Right

Nvidia CEO Jensen Huang Believes That Marvell Technology Could Become a  Trillion Company. Here’s Why He Is Right

Nvidia CEO Jensen Huang Believes That Marvell Technology Could Become a $1 Trillion Company. Here’s Why He Is Right

https://www.fool.com/investing/2026/06/09/nvidia-ceo-jensen-huang-believes-that-marvell-tech/

Publish Date: 2026-06-09 08:49:00

Source Domain: www.fool.com

Shares of chip designer Marvell Technology (MRVL +9.84%) jumped by a whopping 33% on June 2, and Nvidia CEO Jensen Huang was the reason behind this massive surge.

According to Huang, Marvell will join the trillion-dollar market cap club. That seems like an ambitious statement at first, given that Marvell currently has a market cap of almost $230 billion. However, a closer look at the problem that Marvell is solving in the artificial intelligence (AI) infrastructure ecosystem will reveal why the Nvidia CEO is bullish about the company’s prospects.

I won’t be surprised if Marvell eventually becomes a trillion-dollar company. Let’s look at the reasons why.

Image source: The Motley Fool.

The Nvidia CEO believes that Marvell Technology is poised to benefit from the next AI infrastructure bottleneck

Speaking at COMPUTEX Taipei, a technology conference held in Taiwan, Huang noted that the shortage of memory chips has created three trillion-dollar companies lately. He was referring to Samsung, SK Hynix, and Micron Technology, which have seen their market caps hit $1 trillion amid phenomenal revenue and earnings growth.

Marvell Technology Stock Quote

Today’s Change

(9.84%) $25.93

Current Price

$289.40

Key Data Points

Market Cap

$253B

Day’s Range

$281.46 – $304.96

52wk Range

$61.44 – $324.20

Volume

35.3K

Avg Vol

32.3M

Gross Margin

50.64%

Dividend Yield

0.08%

These companies have been benefiting from the incredible demand for memory, which solves an important bottleneck in AI data center chips. Large AI models and inference applications need huge amounts of memory and bandwidth to ensure that AI accelerators don’t sit idle. Faster and larger memory means that AI chips can be consistently fed with huge amounts of data to seamlessly handle AI workloads, which explains why chip designers have been equipping their chips with more memory.

As a result, a massive amount of memory chips is going into data centers. Their demand is so strong that memory chips are expected to be in short supply until 2028. So, the favorable…

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