Best Semiconductor Stocks to Buy and Hold Through 2030

Source The Motley Fool

Key Points

  • Nvidia is swiftly evolving into a platform business spanning GPUs, CPUs, networking equipment, and software.

  • Broadcom dominates the custom silicon landscape and continues to win major design deals with AI hyperscalers.

  • Taiwan Semiconductor sits in a lucrative position as the company stands to benefit no matter which chip architecture is favored.

  • 10 stocks we like better than Nvidia ›

As artificial intelligence (AI) hyperscalers invest hundreds of billions of dollars in infrastructure, demand for advanced processors, custom silicon, networking equipment, and semiconductor manufacturing capacity is accelerating. The biggest winners will be the companies that control the technologies stitching the AI ecosystem together.

For investors looking toward 2030, Nvidia (NASDAQ: NVDA), Broadcom (NASDAQ: AVGO), and Taiwan Semiconductor Manufacturing (NYSE: TSM) stand out as three compelling semiconductor stocks to buy and hold.

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AI chip powering a generative model.

Image source: Getty Images.

Nvidia: The platform powering AI factories

Nvidia is no longer simply a graphics processing unit (GPU) company. Its ecosystem now encompasses GPUs, CPUs, CUDA software, high-speed networking, and sophisticated systems that connect clusters of processors inside AI factories.

The company's financial performance reflects its dominance. In fiscal 2024, Nvidia's data center revenue totaled $47.5 billion. Through the second quarter of fiscal 2027, the company's data center business is operating on a run rate toward $328 billion. This level of growth underscores Nvidia's leadership position as hyperscalers race to build AI infrastructure.

Nvidia's next chapter could be even more interesting. The company's Vera Rubin CPU architecture creates new opportunities beyond traditional GPU design, while its networking portfolio is expanding through products such as NVLink, Spectrum-X Ethernet, and InfiniBand.

Nvidia is smartly forging partnerships across the semiconductor supply chain to broaden its reach. The company has made investments in and is collaborating on products with Nokia, Marvell Technology, Coherent, and Lumentum. These moves demonstrate how the company is expanding into telecommunications, custom silicon connectivity, and optical networking.

Meanwhile, Nvidia's technology stack increasingly supports next-generation use cases across autonomous vehicles, robotics, industrial automation, and even space-based computing ambitions. These markets have the potential to create additional growth opportunities beyond traditional data centers.

Nvidia's greatest competitive advantage isn't manufacturing faster processors. It's controlling the hardware and software layers that competitors struggle to replicate at scale.

Broadcom: Dominating the custom silicon opportunity

While Nvidia dominates the merchant GPU market, Broadcom is helping AI developers design specialized processors around their own AI workloads. These chips are known as application-specific integrated circuits (ASICs) and can offer attractive performance and efficiency for particular use cases.

Broadcom works with Alphabet on Google Cloud's Tensor Processing Units (TPUs), while its relationship with Meta Platforms supports the development of Meta Training and Inference Accelerators (MTIA). Moreover, the company is also working with OpenAI on its inference processor, called Jalapeño.

The financial opportunity behind custom silicon is substantial. Broadcom's leadership is guiding toward $58 billion in AI revenue for fiscal 2026, representing an 186% year-over-year increase. Given the company's secured supply and deployment visibility, AI revenue is expected to surge to $115 billion and $230 billion in fiscal 2027 and 2028, respectively. In other words, Broadcom's AI-driven growth is expected to double for three consecutive years.

Similar to Nvidia, Broadcom also benefits from the networking infrastructure required to connect systems within data centers. Its Ethernet switches, networking silicon, and connectivity technologies offer additional avenues to participate in the upside of AI infrastructure spending. As a result, Broadcom is positioned to benefit whether hyperscalers purchase Nvidia GPUs or embrace custom processors.

Taiwan Semi: The backbone of AI chip manufacturing

The common denominator connecting Nvidia, Advanced Micro Devices, Broadcom, and many other semiconductor designers is that they depend on Taiwan Semiconductor to manufacture their most advanced processors. TSMC operates the world's largest semiconductor foundry, helping transform chip designs into physical products. Taiwan Semi controls an estimated 72.5% of the global foundry market, compared with Samsung's 5.9%. That competitive advantage is difficult to overstate.

Whether a hyperscaler orders Nvidia GPUs, AMD accelerators, or custom silicon developed with Broadcom, Taiwan Semi frequently participates in the manufacturing process. The company also supplies advanced logic chips used alongside memory products from manufacturers such as Micron, enabling it to benefit from the ongoing memory supercycle. Unlike individual chip designers, Taiwan Semi doesn't need to predict which AI architecture ultimately dominates.

TSMC's financial results showcase its AI-driven momentum. During the third quarter, revenue reached approximately $46.7 billion, representing roughly 41% year-over-year growth in U.S. dollars. What's encouraging is that the company's catalysts extend beyond today's AI capex. Demand for advanced 2-nanometer manufacturing, sophisticated chip packaging, and increasingly complex AI processors should support years of expansion into the next decade as new applications move into production.

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Adam Spatacco has positions in Alphabet and Nvidia. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Broadcom, Coherent, Lumentum, Marvell Technology, Meta Platforms, Micron Technology, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.

Disclaimer: For information purposes only. Past performance is not indicative of future results.
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