Nvidia (NAS: NVDA) reported fiscal third-quarter revenue of $57 billion, up 22% sequentially, up 62% year over year, and ahead of guidance of $54 billion. Nvidia’s forecast for the January quarter of $65 billion would be ahead of the FactSet consensus estimate of $62 billion and be up 65% year over year.

Why it matters: Nvidia again delivered excellent revenue growth as artificial intelligence demand still exceeds supply. Results contrast with AI bubble fears, although we view the risks as longer-term in nature. Nvidia’s supply chain is expanding even faster than in prior quarters, allowing for revenue acceleration.

  • Data center revenue was $51.2 billion, up 66% year over year and up by $10 billion or 25% sequentially. Nvidia’s supply commitments are up 63% year over year, and the firm is preparing for even stronger growth with its latest Blackwell Ultra products.
  • Nvidia has reiterated its expectations of $500 billion of Blackwell and Rubin product revenue by the end of calendar 2026, which we think implies $300 billion-plus of data center revenue in calendar 2026. Nvidia still foresees $3 trillion-$4 trillion of annual AI infrastructure spending by 2030.

The bottom line: We raise our fair value estimate for wide-moat Nvidia to $240 from $225 as we lift our revenue estimates in the near term and beyond. We keep our Very High Morningstar Uncertainty Rating, given the fast-moving deals being made in AI. Shares rose about 6% after hours.

  • We still see Nvidia shares as undervalued and view recent AI bubble chatter as a buying opportunity. Longer-term concerns about AI funding and energy buildouts are valid in the medium to long term, but 2026 is shaping up to be another stellar AI year, in our view.

Coming up: Nvidia not only expects strong revenue growth in the January quarter, but also healthy gross margins in the 75% range. The firm is seeing higher input costs, but we anticipate that Nvidia’s strong pricing power will enable the firm to pass these costs on to customers.

No signs of a near-term AI bubble as Nvidia remains in a dominant position as an AI infrastructure supplier

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, or GPUs, 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, or CPUs, 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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Terms used in this article

Star Rating: Our one- to five-star ratings are guideposts to a broad audience and individuals must consider their own specific investment goals, risk tolerance, and several other factors. A five-star rating means our analysts think the current market price likely represents an excessively pessimistic outlook and that beyond fair risk-adjusted returns are likely over a long timeframe. A one-star rating means our analysts think the market is pricing in an excessively optimistic outlook, limiting upside potential and leaving the investor exposed to capital loss.

Fair Value: Morningstar’s Fair Value estimate results from a detailed projection of a company’s future cash flows, resulting from our analysts’ independent primary research. Price To Fair Value measures the current market price against estimated Fair Value. If a company’s stock trades at $100 and our analysts believe it is worth $200, the price to fair value ratio would be 0.5. A Price to Fair Value over 1 suggests the share is overvalued.

Moat Rating: An economic moat is a structural feature that allows a firm to sustain excess profits over a long period. Companies with a narrow moat are those we believe are more likely than not to sustain excess returns for at least a decade. For wide-moat companies, we have high confidence that excess returns will persist for 10 years and are likely to persist at least 20 years. To learn about finding different sources of moat, read this article by Mark LaMonica.