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

Nvidia released its second-quarter earnings report on Aug. 26. Here’s Morningstar’s take on Nvidia’s earnings and stock.

Key Morningstar Metrics for Nvidia

• Fair Value Estimate
  : $310.00
• Morningstar Rating
  : ★★★★
• Morningstar Economic Moat Rating
  : Wide
• Morningstar Uncertainty Rating
  : Very High

What We Thought of Nvidia’s Q2 Earnings

Nvidia 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.

The following are excerpts from Morningstar’s company report on Nvidia stock.

Fair Value Estimate for Nvidia

With its 4-star rating, we believe Nvidia’s stock is moderately undervalued compared with our long-term fair value estimate of $310. Our fair value estimate implies a fiscal 2027 (ending January 2027 or effectively calendar 2026) and fiscal 2028 price/adjusted earnings multiple of 33 times and 19 times, respectively. Nvidia’s data center business has achieved historic growth from $3 billion in fiscal 2020 to $194 billion in fiscal 2026, and we estimate it will be $385 billion in fiscal 2027, representing 99% annual growth.

We were amazed by Nvidia’s forecast for 70%-plus growth in fiscal 2028 (or effectively calendar 2027), but we think it’s achievable and we model $672 billion of data center revenue the following year. 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, so we model a flat revenue year in fiscal 2032.

Read more about Nvidia’s fair value estimate.

Economic Moat Rating

We assign Nvidia a wide economic moat rating. We believe Nvidia benefits from intangible assets around its graphics processing units and its networking and interconnectivity gear. Nvidia also maintains strong pricing power via high customer switching costs around its proprietary software, Cuda, for AI tools, which enables developers to use Nvidia’s GPUs to build AI models. We attribute at least a portion of Nvidia’s AI leadership to intangible assets associated with GPU design.

Further, we now view Nvidia as an “AI systems” company. Even if large tech companies develop enough in-house expertise to reduce their reliance on Nvidia, a host of smaller cloud vendors (neoclouds), governments, and enterprises will remain reliant on Nvidia’s full stack. For all of these reasons, we foresee Nvidia remaining at the head of the pack in AI for quite some time.

Read more about Nvidia’s economic moat.

Financial Strength

Nvidia is in outstanding financial health. As of October 2025, the company held $60.6 billion in cash and investments, as compared with $8.5 billion in short- 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 a cushion and flexibility to continue investing in research and development, which is necessary to maintain their competitive and technological positions.

Nvidia has more than enough of a cash cushion to handle downturns, and we struggle to foresee opportunities for the company to spend this excess cash other than stock buybacks. Nvidia’s dividend is virtually immaterial relative to its financial health and forward prospects.

Read more about Nvidia’s financial strength.

Risk and Uncertainty

We assign Nvidia an Uncertainty Rating of Very High due to the nascent nature of the AI market. In our view, Nvidia’s valuation will be tied to its ability to grow within AI, 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 involve running a model to make a prediction or output).

The biggest risk, in our view, is the pace of AI spending going forward. Nvidia prospered from exponential AI growth in recent years, but such spending comes from a handful of customers, and they all have an incentive to eventually optimize, if not reduce, their investments over time. Within these AI buildouts, we also think that tech leaders will turn to in-house chips for at least a portion of their workloads. Google’s TPUs and Amazon’s Trainium and Inferentia chips were designed with AI workloads in mind. Diversification is also possible, and among existing semiconductor vendors, AMD is quickly expanding its GPU lineup to serve these cloud leaders.

We also foresee geopolitical risk and uncertainty, most notably with US restrictions that have prevented Nvidia, at various times, from selling its AI products into China.

Read more about Nvidia’s risk and uncertainty.

NVDA 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.

NVDA 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 about a good return on AI investment, which might lead to a spending downturn.
• Geopolitics have entered the AI space, most notably limiting Nvidia’s AI opportunities in China.

This article was compiled by Irza Waraich.