Key Morningstar Metrics for Nvidia
- : USD 310Fair Value Estimate
- : ★★★★Morningstar Rating
- : WideMorningstar Economic Moat Rating
- : Very HighMorningstar Uncertainty Rating
What We Thought of Nvidia’s Earnings
Nvidia NVDA reported fiscal second-quarter revenue of USD 96 billion, up 106% year over year and ahead of guidance of USD 91 billion. Nvidia expects October-quarter revenue of USD 108 billion, up 89% year over year and ahead of FactSet consensus estimates of USD 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 USD 700 billion in total revenue versus our prior estimates and FactSet consensus estimates of around USD 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 USD 310 from USD 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 USD 1.3 trillion on AI capital expenditures next year, whereas we think the market was estimating USD 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.
