Nvidia (NVDA.NAS) reported fiscal second-quarter revenue of $96 billion, up 106% year over year and ahead of guidance of $91 billion. Nvidia expects October-quarter revenue of $108 billion, up 89% year over year and ahead of FactSet consensus estimates of $105 billion.

Why it matters: The showstopper, in our view, was Nvidia’s stunning forecast of 70% revenue growth next year (fiscal 2028), implying close to $700 billion in total revenue versus our prior estimates and FactSet consensus estimates of around $570 billion.

  • Nvidia said this 70% growth rate is supply constrained, meaning its forecast could be conservative if its suppliers expand faster than anticipated. Given Nvidia’s view into artificial intelligence demand and its consistent “beat-and-raises,” we think this forecast will prove to be conservative.
  • The only blemish to the earnings report was Nvidia’s reset on gross margin, forecasting a decline from 75% in the July quarter to 74% in October, 71.5% in January, and 72.5% for fiscal 2028, due to the sharp rise in memory prices, which are key components in Nvidia’s AI racks.

The bottom line: We raise our fair value estimate for wide-moat Nvidia to $310 from $280 as demand for Nvidia’s industry-leading AI gear will likely be higher for longer. Shares rose 4% on the news but still appear undervalued to us, as the market appears skeptical about future AI spending.

  • Nvidia forecasted that its top five US hyperscaler customers will spend $1.3 trillion on AI capital expenditures next year, whereas we think the market was estimating $1.0 trillion, and perhaps less. We’re amazed that AI demand has yet to peak but is instead accelerating.
  • AI token usage is still rising exponentially, and high GPU rental prices suggest the market for AI accelerators, such as Nvidia’s GPUs and rack-scale solutions, remains a constraint for AI labs.

Big picture: We were also pleased with Nvidia’s disclosures and rationale across a variety of commitments and guarantees.

Nvidia foresees higher AI computing growth for longer as it anticipates 70%-plus growth in 2027

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, hardware, software, and networking 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 these efforts will, at best, only chip away at Nvidia’s AI dominance.

Nvidia’s GPUs run parallel processing workloads, using many cores to efficiently process data at the same time. In contrast, central processing units, such as Intel’s processors for PCs and servers, or Apple’s processors for its Macs and iPhones, process the data of “0’s and 1’s” in a serial fashion. The wheelhouse of GPUs has been the gaming market, and Nvidia’s GPU graphics cards have long been considered best of breed.

More recently, parallel processing has emerged as a near-requirement to accelerate AI workloads. Nvidia took an early lead in AI GPU hardware, but more importantly, developed a proprietary software platform, Cuda, and these tools allow AI developers to build their models with Nvidia. We believe Nvidia not only has a hardware lead but also benefits from high customer switching costs around Cuda, making it unlikely for another chip designer to emerge as a leader in AI training. Nvidia’s expansion into networking has been impressive, allowing customers to cluster AI GPUs together for AI training.

We think Nvidia’s prospects will be tied to the AI market, for better or worse, for quite some time. We expect leading cloud vendors to continue to invest in in-house, while AMD is also working on GPUs and AI accelerators for the data center. However, we view Nvidia’s GPUs and Cuda as the industry leaders, and the firm’s massive valuation will hinge on the pace of AI buildouts in the years ahead.

Bulls Say

  • The AI infrastructure opportunity is massive, and Nvidia foresees $3 trillion-$4 trillion of annual AI infrastructure spending by 2030.
  • Nvidia’s data center GPUs and Cuda software platform have established the company as the dominant vendor for AI model training and inference.
  • Nvidia is expanding nicely within AI, not just supplying industry-leading GPUs but also moving into networking, software, and services to tie these GPUs into even more-powerful clusters.

Bears Say

  • Nvidia’s customers are a handful of the largest Tech companies in the world, and they all have an incentive to eventually diversify away from Nvidia to some extent.
  • AI infrastructure spending has been impressive but revenue and use cases are less certain, perhaps providing doubts that there is a good return on investment on AI that might lead to a spending downturn at some point in the future.
  • Geopolitics have entered the AI space, most notably limiting Nvidia’s AI opportunities in China.

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