Like in the past several quarters, we think Nvidia will report results exceeding guidance while projecting even higher revenue in the October quarter. We still believe the firm is supply-constrained, and that its revenue is somewhat capped by the production availability of key manufacturers and partners.
The best indicator of Nvidia's AI GPU growth will be hyperscaler capex spending, and we received good news in late July. Microsoft (MSFT) still expects to have even higher capex in the next 12 months than what it just reported, and Meta Platforms (META) lifted the midpoint of its capex guidance to $38.5 billion from $37.5 billion. Amazon (AMZN) also expects to spend more on AI next year.
At the same time, both Alphabet (GOOGL) and Meta have conceded that it is far riskier to underinvest in AI than overinvest. This may bode well for Nvidia in the near term, but it increases the risk that there will be a crash in investment at some point once they secure adequate AI GPU supply.
Advanced Micro Devices (AMD) boosted its AI GPU guidance for 2024, albeit at far lower levels than what Nvidia is selling. Still, we think this is likely a good sign. Even if customers choose AMD because of availability, it means demand for Nvidia's GPUs must still be strong.
AI revenue is coming more into focus, as investors are rightfully questioning whether companies will generate enough to justify existing AI spending. We think these questions miss a portion of the AI investment – namely, R&D by startups, enterprises, and "moonshot" projects (robotics, genetics, autonomous driving), where we anticipate a good deal of investment, even if no explicit AI revenue is attached to it.
Still, investors are right to consider how and when these investments will pay off. In the best case, firms investing in AI will see significant revenue growth from it. However, we might see a host of firms that don't generate tons of AI revenue, but will at least protect their businesses from upstarts, while firms that fail to invest in AI become antiquated. In these latter cases, the high AI capex and R&D are still reasonable, even if the payoff is implicit rather than explicit.
Key Morningstar Metrics for Nvidia
• Fair Value Estimate: $105.00
• Morningstar Rating: 3 stars
• Morningstar Economic Moat Rating: Wide
• Morningstar Uncertainty Rating: Very High
Morningstar Fair Value Estimate for Nvidia
With its 3-star rating, we believe Nvidia's stock is fairly valued 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 thereafter 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 at some point in the medium term thereafter. Excluding this one-year blip that we model, we anticipate average annual DC growth of 10% thereafter and consider this to be a reasonable long-term growth rate as AI matures.
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Morningstar Economic Moat Rating For Nvidia
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.
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Nvidia's 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 for Nvidia Shares
We assign Nvidia a Morningstar Uncertainty Rating of Very High. The firm is an industry leader in GPUs used in training AI models, and it has carved 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 many tech leaders vying for Nvidia's leading AI position. We think it is inevitable that leading hyper-scale vendors will seek to reduce their reliance on Nvidia and diversify their semiconductor and software supplier base, including by developing in-house solutions. Among existing semiconductor 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 currently a leader in AI training software and tools, leading cloud vendors would likely prefer to see greater competition in this space, and they may shift to any alternative open-source tools that 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 Leona Murray
