As the leader in Graphics Processing Unit (GPU) manufacturing, Nvidia has solidified its position as a ‘pick and shovel’ play in the AI chip gold rush. The company’s stock has seen a remarkable surge of 900% since the release of ChatGPT, with its GPU revenue experiencing an annual growth rate of 67% over the last three years.
The Nvidia Bear Thesis
However, many investors fear that the demand for AI infrastructure, primarily driven by Big Tech companies, may stall once these tech giants adjust their spending plans. This potential shift forms the foundation of the Nvidia bear thesis.
Understanding GPU Revenue Growth
To comprehend the future prospects of Nvidia’s revenue growth, we need to examine the underlying technology driving this expansion. For over five decades, the semiconductor industry was governed by Moore’s Law, which stated that the number of transistors on a microchip would double every two years, fueled by the increasing demand for computing power.
The Demise of Moore’s Law
While technological advancements have enabled us to surpass the transistor count growth predicted by Moore’s Law, its fundamental driver – the ever-growing need for greater computing power – remains more relevant than ever. This is evident in the rapid progress made by Meta Platforms CEO Mark Zuckerberg’s company.
The Llama 3 and Llama 4 Models
In April 2024, Meta released the Llama 3 model, which showcased an impressive increase in computation power over its predecessor. Even more astonishing was the announcement of the Llama 4 model, set to launch early this year, requiring a staggering 10 times greater computing power than its preceding version.
The Unrelenting Pace of Tech Advancements
The major tech companies in the US continue to invest heavily in increasing their capacity to cater to the escalating demand for computing power. Their reasoning is simple: obtaining a headstart in AI can significantly impact their competitiveness. Meta, for instance, invested $8.5 billion in the second quarter of last year when releasing the Llama 3 model – a 33% increase over the same period in the prior year.
Nvidia’s Dominant Market Share
As the company boasting an impressive 90% market share in GPUs, Nvidia is uniquely positioned to provide the significant computing power required by these tech giants. Given their reliance on this infrastructure, these companies cannot afford to slow down or risk falling behind their competitors.
Hedge Fund Interest in Nvidia
Nvidia ranks fifth on our latest list of the 30 Most Popular Stocks Among Hedge Funds. According to our database, 193 hedge fund portfolios held NVDA at the end of the third quarter, a notable increase from the 179 holdings recorded in the previous quarter. While we acknowledge the substantial potential of NVDA as a leading AI investment, our conviction lies in identifying stocks that hold greater promise for delivering higher returns within a shorter timeframe.
Why Nvidia Might Not be the Best AI Stock to Buy
If you’re looking for an AI stock with similar promise but trading at less than five times its earnings, we recommend exploring our report on the cheapest AI stock. While NVDA presents significant growth potential, there are other companies that offer comparable benefits without the substantial price tag.
Conclusion
Nvidia’s position as a leader in GPU manufacturing is undeniable, but it’s crucial to consider the underlying drivers of its revenue growth and the ever-evolving landscape of tech advancements. As investors, it’s essential to weigh the potential risks associated with the demand for AI infrastructure against the company’s significant market share.
References
- Insider Monkey: "Is Vertiv Holdings (VRT) The Best AI Stock to Buy For 2025?"
- Morgan Stanley: "$30 Trillion Opportunity: 15 Best Humanoid Robot Stocks to Buy"
- CNBC: "Jim Cramer Says NVIDIA ‘Has Become A Wasteland’"
