Nvidia NVDA released its second-quarter 2026 earnings report on Aug. 27, 2025. Here’s Morningstar’s take on Nvidia’s earnings and outlook for the stock.

Key Morningstar metrics for Nvidia

  • Fair Value Estimate: $190
  • Morningstar Rating: ★★★
  • Morningstar Economic Moat Rating: Wide
  • Morningstar Uncertainty Rating: Very High

What we thought of Nvidia’s Q2 earnings

  • Demand for Nvidia’s AI products still exceeds supply, but such supply is expanding faster than we anticipated. We also think Nvidia has pricing power on its latest Blackwell Ultra products, boosting revenue even further. Our optimism around Nvidia’s US business offsets the volatility and ongoing restrictions around its China business.
  • The long-term picture continues to look bright for Nvidia as management stated that it foresees “$3 trillion to $4 trillion in AI infrastructure spend by the end of the decade.”
  • We remain impressed with Nvidia’s networking business, as its Ethernet-based products have reached a $10 billion annual run rate, while still seeing adoption of its proprietary InfiniBand products for high-performance computing.
  • Nvidia has steadily increased AI revenue by approximately $4 billion per quarter over the past eight quarters as new supply comes online. We’re encouraged that guidance points to a $7 billion boost in the third quarter, with the accelerating supply of Blackwell Ultra rack-scale products.
  • We raised our fair value estimate for wide-moat Nvidia to $190 per share from $170 and maintain our Very High Uncertainty Rating. Although we reduce and push out our estimates for China revenue, the increase in US supply leads us to boost our near- and medium-term growth rates.
  • We believe Nvidia, trading at around $167, is modestly undervalued.

Fair Value estimate for Nvidia

With its 3-star rating, we believe Nvidia’s stock is fairly valued compared with our long-term fair value estimate of $190 per share. Our fair value estimate and Nvidia’s stock price will be driven by its prospects in the data center, or DC, business and AI graphics processing units, for better or worse. Nvidia’s DC business has achieved exponential growth already, rising from $3 billion in fiscal 2020 to $115 billion in fiscal 2025.

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, so we model only 2% growth in fiscal 2030. Excluding this one-year blip that we model, we anticipate average annual DC growth of 10% to 12% thereafter and consider this to be a reasonable long-term growth rate as AI matures. In the long run, we think that cloud computing revenue at the hyperscalers can expand at a low-teens rate, and capital expenditures as a percentage of revenue remain at consistent levels at these hyperscalers, and thus we model Nvidia’s revenue growth to be on par with these cloud computing growth rates.

In gaming, which was formerly Nvidia’s largest business, we model $18 billion of revenue in fiscal 2026. We suspect that Nvidia may introduce a PC CPU in fiscal 2027, boosting revenue in this segment (if such revenue is in fact reported here) to $23 billion. We model 10% average annual revenue growth in gaming thereafter, bringing the total business to nearly $31 billion in fiscal 2030.

We have high hopes for Nvidia’s automotive business, as greater processing power will be required in active safety systems and autonomous driving. We model $2.6 billion of revenue in fiscal 2026 and revenue growing at a 20% compound annual growth rate over the next decade to $10.8 billion of revenue in fiscal 2035.

Economic Moat Rating

We assign Nvidia a wide economic moat rating, thanks to intangible assets around its graphics processing units and high customer switching costs around its proprietary software, Cuda, for AI tools, which enables developers to use Nvidia’s GPUs to build AI models.

In our view, the nature of parallel processing in GPUs is at the heart of Nvidia’s dominance in its various end markets. PC graphics were the initial key application, allowing for more robust and immersive gaming over the past couple of decades. In the past decade, however, the parallel processing of GPUs was also found to more efficiently run the matrix multiplication algorithms needed to power AI models.

Beyond Nvidia’s AI prowess today, which we believe is exceptionally strong, we think the company is making the proper moves to widen its moat even further. Nvidia’s software efforts with Cuda remain impressive, while Nvidia expanded into networking solutions, most notably with its acquisition of Mellanox for InfiniBand and, more recently, with its Spectrum Ethernet products. We don’t want to discount Nvidia’s know-how here, either. Many AI models don’t run on solo GPUs, but rather on a connected system of many GPUs running in tandem. Nvidia’s proprietary products, such as NVLink, do a good job of connecting Nvidia GPUs together to run these larger models.

Financial strength

Nvidia is in outstanding financial health. As of July 2025, the company held $57 billion in cash and investments, as compared with $8.5 billion in 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 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.

Risk and uncertainty

We assign Nvidia a Morningstar Uncertainty Rating of Very High because of the nascency 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.com’s AMZN Trainium and Inferentia chips were designed with AI workloads in mind. Diversification is also possible, and among existing semis vendors, Advanced Micro Devices 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.

NVDA bulls say

  • The AI infrastructure opportunity is massive, as over $1 trillion of infrastructure is likely already deployed today,and the company foresees up to $4 trillion more in spending through the rest of the decade.
  • 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 raising 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 has entered the AI space, most notably limiting Nvidia’s AI opportunities in China.

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