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Nvidia grew its data center revenue more than 10-fold in three years as AI spending ramped up.
The next three years could see more competition in the AI accelerator space.
That favors this one stock that currently trades at a great value relative to other AI chip stocks.
Just about every big tech company in the world is in a race to build more computing capacity than anyone else in order to meet the demands for large language model training and AI inference. The four biggest spenders alone are set to invest over $320 billion in capital expenditures this year, most of which will go toward data centers.
A handful of companies have been big beneficiaries of all that spending, not least of which is Nvidia (NASDAQ: NVDA). The chipmaker has seen its data center revenue climb more than 10-fold in three years as big tech buys up its graphics processing units (GPUs) as fast as it can make them. That's led to phenomenal earnings growth for the company and its investors.
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Demand continues to fuel growth at Nvidia, with expectations for 50% revenue growth in the second quarter.But competition is starting to catch up with the market leader and another AI giant could grow its AI chip revenue faster than Nvidia over the next three years. What's more, its stock trades at a much more attractive valuation, making it a great buy for investors looking to capitalize on the next round of growth in AI.
Nvidia faces competition from two main source: other GPU makers and custom chip designs.
When it comes to other sources for GPUs, Advanced Micro Devices (NASDAQ: AMD) is the only practical competitor for Nvidia. Nvidia has remained a top choice for hyperscalers, offering better performance even though the costs of its chips remain high. Nvidia's proprietary software, CUDA, gives it another way to lock in customers. And Nvidia offers better scaling solutions as well.
But AMD showed off new chips last month that aim to put many of those advantages to bed. Its MI400 chips, coming in 2026, offer a "rack-scale" system that allows a full rack of AMD chips to function like a single compute engine. That can offer better price performance than Nvidia, providing a legitimate contender for large data centers. It's already received commitments from OpenAI, Meta Platforms, and Microsoft, among others, for its newest series of chips.
The other source of competition is custom silicon designs from companies like Meta, Microsoft, Alphabet's Google, and Amazon (NASDAQ: AMZN). Those represent Nvidia's biggest customers, but they're all looking to fill their data centers with more of their custom-designed chips made in partnership with Broadcom (NASDAQ: AVGO) and Marvell Technology.
These application-specific integrated circuits (ASICs) aren't as flexible as GPUs for generative AI purposes. However, all four of the above have seen excellent results with AI training and inference on their custom solutions. And they're all trying to expand the use cases of those chips in future iterations. Importantly for Microsoft, Google, and Amazon, the cloud providers say their customers are able to generate better price performance with their own chip designs than Nvidia's. And they each have an incentive to sell their customers on custom silicon, since it will lock those customers into their respective ecosystems.
But none of the above-mentioned companies are in as good a position as another important AI infrastructure provider. And it can capitalize on the growing spending, no matter which chips customers ultimately decide to build with.
Image source: Getty Images.
When Nvidia, AMD, Broadcom, or Marvell want to actually take their designs and get them printed on silicon wafers, they need to contract with a manufacturer. And they all choose the same manufacturer for their needs: Taiwan Semiconductor Manufacturing (NYSE: TSM), otherwise known as TSMC.
TSMC has become a dominant force in semiconductor fabrication due to two key advantages: its scale and its technology. Both serve to feed one another. TSMC's leading technology means it wins the biggest contracts from the biggest chip designers. As a result, it builds out scale to meet that demand. It also takes that revenue and reinvests it into R&D to ensure it maintains its technology lead. As demand for more advanced chips increases, it's the only company that has the scale that can meet that demand.
In a market with booming demand, like we're seeing right now, TSMC can produce considerable returns on its capital spending. And while a down-cycle in demand will put a strain on its profits, management has historically done a good job at forecasting future demand, budgeting appropriately, and positioning for the next cycle.
Right now, though, TSMC could see its AI-related revenue more than triple from 2025 through 2027. Management said it's on track to double its AI-related revenue from 2024 this year alone, bringing it to around $26 billion. To triple, it would only need to grow a bit over 20% per year for 2026 and 2027.
But management expects 40% average annual growth over the five-year period from 2025 through 2029, implying an average of 28% growth in the next four years after doubling this year. So, even if management is overestimating its long-term prospects, it's still likely to at least triple AI-related revenue by 2027.
A key aspect of that growth will be the introduction of its 2nm and 1.6nm processes. TSMC is set to release both manufacturing nodes in quick succession, with the 2nm arriving later this year and the next generation arriving in late 2026. The company is reportedly charging $30,000 per wafer for 2nm chips compared to about $20,000 for 3nm chips. TSMC already has 2nm contracts lined up for AMD, Microsoft, Amazon, Google, and others.
While AI-related revenue remains a small portion of TSMC's total revenue, it should climb to about 30% of total revenue by the end of the decade based on management's long-term forecast. The company expects about 20% total revenue growth over the next five years, and it should be able to produce strong margins in that period as it ramps up 2nm and 1.6nm production. Overall, earnings growth should keep pace with revenue growth, bolstered by strong demand for AI chips.
Meanwhile, the stock trades for a forward PE ratio of less than 25 as of this writing. That makes it an incredible value compared to other AI stocks like Nvidia or AMD, which trade around 35 times earnings. With the strong position TSMC is in right now, it's worth adding to your portfolio.
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John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. Adam Levy has positions in Alphabet, Amazon, Meta Platforms, Microsoft, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Broadcom and Marvell Technology and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
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