Company Reports

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, or GPUs, hardware and software tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but most likely, these efforts will chip away at, but not supplant, Nvidia’s AI dominance.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, or GPUs, hardware and software tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but most likely, these efforts will chip away at, but not supplant, Nvidia’s AI dominance.

Wide-moat Nvidia once again reported stellar quarterly results and provided investors with even rosier expectations for the upcoming quarter, as the company remains the clear winner in the race to build out generative artificial intelligence capabilities. We’re encouraged by management’s commentary that demand for its upcoming Blackwell products should exceed supply into calendar 2025, and we see no signs of AI demand slowing either.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, or GPUs, hardware and software tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but most likely, these efforts will chip away at, but not supplant, Nvidia’s AI dominance.

Nvidia’s GTC conference keynote address introduced the company’s latest artificial intelligence graphics processor, or AI GPU, Blackwell, along with its associated platform and GPU clusters to enable AI workloads. Just as important, GTC showcased the efforts of the company’s wide range of partners in areas such as robotics and automotive, among many others. We don’t foresee these partners slowing their investments anytime soon, which supports our healthy growth estimates for Nvidia in the years ahead.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, or GPUs, hardware and software tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but most likely, these efforts will chip away at, but not supplant, Nvidia’s AI dominance.

Wide-moat Nvidia reported another quarter of outstanding revenue and earnings while providing investors with a forecast for the April quarter that was well ahead of our expectations. Leading cloud computing companies plan to boost their capital expenditures to satisfy demand for artificial intelligence training and inference, and it appears that virtually all this spending will fall into Nvidia’s pockets. More importantly, we anticipate healthy growth for Nvidia’s data center revenue beyond 2024, as Nvidia’s Cuda software should contribute to strong customer stickiness for existing AI models and workloads.

We met with Nvidia's management team at CES 2024 in Las Vegas and came away from the investor-only event with modestly more confidence in our existing assumptions that the company will deliver another year of exceptional data center revenue growth in fiscal 2025, which is effectively calendar 2024. We maintain our $480 fair value estimate for wide-moat Nvidia, and shares appear modestly overvalued after a recent runup in share price. We also maintain our Very High fair value uncertainty rating as Nvidia's valuation will remain closely tied to the rapidly evolving artificial intelligence market in the years to come.

Wide-moat Nvidia reported predictably outstanding results for the October quarter that were ahead of guidance, while the company’s fiscal fourth quarter outlook was also ahead of our prior expectations. Nvidia is clearly the dominant provider of graphics processing units deployed in data centers, and we don’t foresee the company losing its supremacy any time soon. We maintain our $480 fair value estimate and view shares as fairly valued. We also maintain our Very High Uncertainty Rating, as the timing and magnitude of future artificial intelligence GPU growth remains unclear to us, especially given recent U.S. restrictions on chip sales into China. That said, Nvidia’s earnings report gives us a small confidence boost that the firm can reach our projection of $100 billion of data center revenue in fiscal 2028, as compared with just $15 billion last fiscal year and our estimate of $46 billion this year.

We maintain our $480 fair value estimate for wide-moat Nvidia despite an announcement by the U.S. Department of Commerce that will further restrict the shipment of various semiconductors and related equipment into China. This policy will likely include a portion of Nvidia’s fast-growing business of selling graphics processing units into data centers for artificial intelligence. As of now, we think the restrictions will at worst provide some modest long-term headwinds to Nvidia’s exponential growth; they will not be a death blow. We reiterate our Very High Uncertainty Rating, as Nvidia’s valuation will hinge on the nascent and skyrocketing AI GPU end market.

Wide-moat Nvidia’s results and outlook were well ahead of our expectations and FactSet consensus estimates, as the company is a dominant supplier of artificial intelligence accelerators into cloud computing providers. We raise our fair value estimate to $480 from $300 and lift our Uncertainty Rating to Very High. We are now much more optimistic about the rise of AI workloads and how Nvidia’s wide moat should cement itself as an AI chip leader.

Nvidia has a wide economic moat, thanks to its clear leadership in graphics processing units, or GPUs, hardware and software tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but most likely, these efforts will chip away at, but not supplant, Nvidia’s AI dominance.

Nvidia is the top designer of discrete graphics processing units that enhance the visual experience on computing platforms. The firm's chips are used in a variety of end markets, including PC gaming and data centers. Traditional GPU uses include professional visualization applications that require realistic rendering, including computer-aided design, video editing, and special effects. Nvidia has experienced success in focusing its GPUs in burgeoning markets such as artificial intelligence (deep learning) and self-driving vehicles. Hyperscale cloud vendors have leveraged GPUs in training neural networks for uses such as image and speech recognition, large language models (ChatGPT), and other forms of generative AI.

Wide-moat Nvidia reported first-quarter sales ahead of management’s guidance, while providing guidance for the second quarter significantly above our prior estimates. Management expects second-quarter revenue to be at a midpoint of $11 billion, which would be up 64% year over year and 53% sequentially.

Nvidia is the top designer of discrete graphics processing units that enhance the visual experience on computing platforms. The firm's chips are used in a variety of end markets, including PC gaming and data centers. Traditional GPU uses include professional visualization applications that require realistic rendering, including computer-aided design, video editing, and special effects. Nvidia has experienced success in focusing its GPUs in burgeoning markets such as artificial intelligence (deep learning) and self-driving vehicles. Hyperscale cloud vendors have leveraged GPUs in training neural networks for uses such as image and speech recognition, large language models (ChatGPT), and other forms of generative AI.

Wide-moat Nvidia reported fiscal 2023 fourth-quarter sales consistent with management’s guidance, with gaming slightly ahead of our expectations and data center a bit weaker. We foresee healthy growth for the data center segment, thanks to the firm's newest H100 data center graphics processing unit. The H100 is 9 times faster than its predecessor in artificial intelligence training and up to 30 times faster in AI inferencing for transformer-based large language models like Open AI’s ChatGPT (generative pretrained transformer). We believe AI models like ChatGPT use thousands of GPUs to be trained, with competition among Microsoft, Google, and others supporting our forecast for Nvidia’s data center segment to grow at a 19% CAGR over the next five years.

Nvidia is the top designer of discrete graphics processing units that enhance the visual experience on computing platforms. The firm's chips are used in a variety of end markets, including PC gaming and data centers. Traditional GPU uses include professional visualization applications that require realistic rendering, including computer-aided design, video editing, and special effects. Nvidia has experienced success in focusing its GPUs in burgeoning markets such as artificial intelligence (deep learning) and self-driving vehicles. Hyperscale cloud vendors have leveraged GPUs in training neural networks for uses such as image and speech recognition, large language models (ChatGPT), and other forms of generative AI.

Nvidia is the top designer of discrete graphics processing units that enhance the visual experience on computing platforms. The firm's chips are used in a variety of end markets, including high-end PCs for gaming and data centers. Traditional GPU uses include professional visualization applications that require realistic rendering, including computer-aided design, video editing, and special effects. Nvidia has experienced success in focusing its GPUs in nascent markets such as artificial intelligence (deep learning) and self-driving vehicles. Hyperscale cloud vendors have leveraged GPUs in training neural networks for uses such as image and speech recognition.

Wide-moat Nvidia reported third-quarter sales slightly ahead of management’s guidance, with gaming modestly ahead of our expectations, whereas the data center segment was negatively affected by the recent U.S. government export restrictions on certain products (A100 and H100 data center graphics processing units) to China. The gaming segment remains challenged following the crash in cryptocurrency prices and associated mining demand for GPUs in addition to weaker macroeconomic conditions and COVID-19 lockdowns in China. Shares are trading at a discount to our unchanged $200 fair value estimate, and we think long-term investors should find Nvidia attractive, as we believe the firm’s data center business will prove more resilient to macroeconomic challenges.

On Aug. 26, Nvidia announced that the U.S. government imposed a new license requirement for certain Nvidia data center graphics processing units, or GPUs, (the current generation A100 and upcoming H100) exported to China or Russia. We note Nvidia hasn't been selling products to customers in Russia since the outset of the Russia-Ukraine war. Nvidia’s major cloud customers include Chinese firms such as Alibaba, Tencent, and Baidu for a variety of applications such as natural language processing, image recognition, and deep recommendation engines. The purpose of the new license agreement is to address risks related to military end use for Nvidia’s AI-related GPUs in the escalating U.S.-China tensions. In an SEC filing, Nvidia highlighted its fiscal third-quarter revenue outlook included about $400 million in potential revenue to China that could be subject to the new license requirement. We believe many of the end use applications for Nvidia’s data center GPUs at Chinese customers are consumer-centric, and thus we think the firm should be able to attain licenses for these customers.