Going Into Earnings, Is Nvidia Stock a Buy, a Sell, or Fairly Valued?

Fair Value Estimate for Nvidia

With its 2-star rating, we believe Nvidia’s stock is overvalued compared to our long-term fair value estimate of $105 per share, which implies an equity value of roughly $2.5 trillion. Our fair value estimate implies a fiscal 2025 (ending January 2025, or effectively calendar 2024) price/adjusted earnings multiple of 37 times and a fiscal 2026 forward price/adjusted earnings multiple of 27 times.

Our fair value estimate, and Nvidia’s stock price, will be driven by its prospects in the data center and AI GPUs, for better or worse. Nvidia’s DC business has achieved exponential growth already, rising from $3 billion in fiscal 2020 to $15 billion in fiscal 2023 and more than tripling to $47.5 billion in fiscal 2024. DC revenue appears to be supply-constrained, and we think that Nvidia will continue to steadily boost revenue in each of the four quarters in fiscal 2025 as more supply comes online. Based on Nvidia’s strong forecast start for fiscal 2025, we model DC revenue rising 133% to $111 billion in fiscal 2025. We model a 23% compound annual growth rate for the three years thereafter, as we anticipate strong growth in capital expenditures in data centers at leading enterprise and cloud computing customers. We think it is reasonable that Nvidia may face an inventory correction or a pause in AI demand in the medium term. Excluding this one-year blip that we model, we anticipate an average annual DC growth of 10% and consider this a reasonable long-term growth rate as AI matures.

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Economic Moat Rating

We assign Nvidia a wide moat, thanks to intangible assets around its graphics processing units and, increasingly, switching costs around its proprietary software, such as its Cuda platform for AI tools, which lets developers use the firm’s GPUs to build AI models.

Nvidia was an early leader and designer of GPUs, originally developed to offload graphic processing tasks on PCs and gaming consoles. The firm has emerged as the clear market share leader in discrete GPUs (over 80% share, per Mercury Research). We attribute this leadership to intangible assets associated with GPU design, as well as the associated software, frameworks, and tools developers need to work with these GPUs. In our view, recent introductions like ray-tracing technology and the use of AI tensor cores in gaming applications are signs Nvidia has not lost its GPU leadership. A quick scan of GPU pricing in gaming and DC shows the firm’s average selling prices can often be twice as high as its closest competitor, Advanced Micro Devices AMD.

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Financial Strength

Nvidia is in outstanding financial health. As of April 2024, the company held $31.4 billion in cash and investments, as compared with $9.7 billion in short-term and long-term debt. Semiconductor firms tend to hold large cash balances to help them navigate the cycles of the chip industry. During downturns, this provides them with a cushion and flexibility to continue investing in research and development, which is necessary to maintain their competitive and technology positions. Nvidia’s dividend is virtually immaterial relative to its financial health and forward prospects, and most of the firm’s distribution to shareholders comes in the form of stock buybacks.

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Risk and Uncertainty

We assign Nvidia with a Morningstar Uncertainty Rating of Very High. In our view, Nvidia’s valuation will be tied to its ability to grow within the data center and AI sectors, for better or worse. Nvidia is an industry leader in GPUs used in AI model training, while carving out a good portion of demand for chips used in AI inference workloads (which involves running a model to make a prediction or output).

We see a host of tech leaders vying for Nvidia’s leading AI position. We think it is inevitable that leading hyperscale vendors, such as Amazon’s AWS, Microsoft, Google, and Meta Platforms will seek to reduce their reliance on Nvidia and diversify their semiconductor and software supplier base, including the development of in-house solutions. Google’s TPUs and Amazon’s Trainium and Inferentia chips were designed with AI workloads in mind, while Microsoft and Meta have announced semiconductor design plans. Among existing semis vendors, AMD is quickly expanding its GPU lineup to serve these cloud leaders. Intel also has AI accelerator products today and will likely remain focused on this opportunity.

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NVDA Bulls Say

• Nvidia’s GPUs offer industry-leading parallel processing, which was historically needed in PC gaming applications, but has expanded into crypto mining, AI, and perhaps future applications too.
• Nvidia’s data center GPUs and Cuda software platform have established the company as the dominant vendor for AI model training, which is a use case that should rise exponentially in the years ahead.
• The firm has a first-mover advantage in the autonomous driving market that could lead to widespread adoption of its Drive PX self-driving platform.

NVDA Bears Say

• Nvidia is a leading AI chip vendor today, but other powerful chipmakers and tech titans are focused on in-house chip development.
• Although Cuda is a leader in AI training software and tools today, leading cloud vendors would likely prefer to see greater competition in this space and may shift to alternative open-source tools if they were to arise.
• Nvidia’s gaming GPU business has often seen boom-or-bust cycles based on PC demand and, more recently, cryptocurrency mining.

This article was compiled by Kayleigh Hall.

The author or authors do not own shares in any securities mentioned in this article. Find out about Morningstar's editorial policies.