Should You Forget Nvidia and Buy These 2 Artificial Intelligence (AI) Stocks Instead?

Up by about 26,000% over the past decade (as of this writing), Nvidia (NASDAQ: NVDA) has been a monster stock for investors. Its market capitalization has grown to about $3.5 trillion, making it one of the two most valuable companies in the world, neck-and-neck with Microsoft.

The stock's performance, meanwhile, has been well justified. The company's sales and earnings have grown explosively over that decade -- and particularly in the past few years as its graphics processing units (GPUs) have become the backbone of the artificial intelligence (AI) infrastructure build-out. The company's ongoing spectacular growth could be seen in its fiscal Q1 results: The $39.1 billion in data center revenue it booked was more than 9 times the $4.3 billion in data center revenue it generated in its Q1 just two years prior.

Make no mistake, Nvidia remains one of the best-positioned companies to continue to benefit from the ongoing AI boom. However, the company is now massive, and as the base used to measure its growth gets bigger, the percentage gains are likely to get smaller because comparisons will get tougher. Investors shouldn't be surprised if percentage growth rates decline.

For investors looking to diversify their AI infrastructure exposure or find investments with potentially more upside than Nvidia, Advanced Micro Devices (NASDAQ: AMD) and Broadcom (NASDAQ: AVGO) are two strong alternatives. Here's why.

Image source: Getty Images

AMD: Carving a niche in AI inference

While Nvidia's GPUs dominate the market for AI training chips, AMD has carved out a niche in AI inference, which is expected to become the much larger market over time. Nvidia's CUDA platform gives it a clear edge in AI model training, thanks to its broad hardware support, strong documentation, developer loyalty, and a deep library of AI tools that are already built and optimized to boost its GPU performance. However, once models are trained, running them (inference) is more about cost, latency, and efficiency.

AMD's ROCm software has steadily improved, and while it still lags far behind CUDA for training, it's generally considered good enough for running inference workloads. That's important because inference demand is starting to accelerate, and cost-effectiveness plays a much bigger role in chip selection.

On its latest earnings call, AMD said one of the largest AI model companies is now using its GPUs to handle a significant share of its daily inference traffic. Major cloud computing providers are also turning to AMD's GPUs to power search, recommendations, and generative AI tasks. Importantly, AMD won't need to take a massive share of the market from Nvidia to see big results. Its data center GPU revenue base is comparatively small, so even modest market share gains could drive strong growth.

Beyond GPUs, AMD has become a leader in the market for data center central processing units (CPUs). While this market is smaller than the GPU market, CPUs -- the "brains" of the server -- remain critical, and AMD should continue to see solid overall data center CPU growth as AI infrastructure spending continues to increase.

If AI workloads continue shifting toward inference, AMD is well-positioned to see faster growth and potentially outperform, especially given its much smaller revenue base. The biggest risk is if AI spending begins to slow and if the company's hardware continues to remain an afterthought to Nvidia's. That said, the setup looks good for AMD to outperform.

Broadcom: A custom chip, networking, and virtualization winner

Broadcom is both a hardware and software AI growth story. On the hardware side, Broadcom makes critical components for AI clusters, including Ethernet switches, optical receivers, DSPs, and NICs, which are all essential for moving huge amounts of data across large AI systems. As AI clusters grow in size and complexity, the offerings in Broadcom's networking portfolio are becoming increasingly valuable. In fact, its AI networking revenue jumped 170% last quarter and now makes up 40% of its AI revenue.

The bigger prize, though, is in application-specific integrated circuits (ASICs). These custom chips are designed for specific use cases, offering their buyers better performance and lower power usage than off-the-shelf GPUs. As such, some larger companies are beginning to turn to custom AI chips to supplement their GPUs.

Broadcom first helped Alphabet design its tensor processing units (TPUs), which were specifically developed to optimize AI workloads within Google Cloud's TensorFlow framework. Those chips' success has inspired more customers (including Apple) to turn to Broadcom to help them develop their own custom AI chips.

Needless to say, this opportunity appears massive. In the past, Broadcom has said its three most advanced AI chip customers could each deploy 1 million AI chip clusters by 2027, representing a total addressable opportunity of up to $90 billion. While production of Alphabet's ASICs is fully ramped up, other large customers are just getting started. As such, Broadcom is looking at a potential multiyear revenue surge.

While much of the attention around Broadcom revolves around its hardware business, its VMware unit is also quietly benefiting from AI. VMware's Cloud Foundation platform, which helps customers manage AI workloads across public clouds and their own on-premises servers, is seeing strong adoption as enterprises move toward hybrid and multicloud AI environments. Broadcom has also been transforming VMware (which it acquired in late 2023) by streamlining its product offerings and shifting it to a subscription sales model.

Between its networking portfolio, custom AI chips, and VMware, Broadcom is well-positioned to achieve strong AI-related revenue growth in the coming years.

Two strong stock alternatives

If Nvidia is the AI infrastructure king, then AMD and Broadcom are its best challengers on the chessboard. AMD is building momentum in AI inference and remains a leader in data center CPUs. Broadcom, meanwhile, is powering AI infrastructure through its combination of networking hardware, custom chips, and enterprise virtualization software.

Both companies offer unique angles on the AI build-out, and both stocks have strong growth potential. For investors looking to bet on the AI trend without simply buying more shares of Nvidia, AMD and Broadcom are two high-quality, high-upside stocks to consider.

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Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Geoffrey Seiler has positions in Alphabet. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Apple, Microsoft, and Nvidia. The Motley Fool recommends Broadcom 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.