Nvidia delivered another blockbuster quarter, reporting third-quarter earnings that exceeded Wall Street expectations as demand for its AI chips continues to surge. The chipmaking giant posted revenue of $35.08 billion, representing a stunning 94% year-over-year increase and beating consensus analyst estimates of $33.25 billion.
CEO Jensen Huang declared that “the age of AI is in full steam” as the company provided crucial updates on its highly anticipated Blackwell AI chip lineup. The next-generation Blackwell chips, designed to succeed the wildly popular Hopper architecture, are ramping up production with demand expected to exceed supply for several quarters into fiscal 2026, according to CFO Colette Kress.
For the fourth quarter, Nvidia forecast revenue of $37.5 billion (plus or minus 2%), aligning closely with analyst estimates of $37.1 billion. While the guidance met expectations, it fell short of the most optimistic projections, causing the stock to dip more than 1% in after-hours trading despite the company’s stellar performance. Nvidia’s stock has surged 194% in 2024, reflecting investor enthusiasm for AI infrastructure.
Huang emphasized that Blackwell demand is “coming from a lot of different places,” including foundation model makers scaling pre-training, post-training, and inference workloads. He highlighted the emergence of “physical AI” and robotics as particularly exciting growth areas, stating that “the age of robotics is coming” as investments in industrial robotics surge due to AI breakthroughs.
The company acknowledged that Blackwell production will pressure profit margins in the near term, with margins expected in the low 70% range. However, Kress projected margins could return to the mid-70s in the second half of next year as production fully ramps up.
Regarding potential challenges from the incoming Trump administration, Huang said Nvidia would “fully comply” with any new regulations and tariffs while continuing to compete in the marketplace, including China. The CFO noted that data center revenue in China “grew significantly” due to shipments of export-compliant Hopper products.
Huang described the current moment as the beginning of “two fundamental shifts in computing”: the transition from traditional CPU-based coding to GPU-powered machine learning, and the transformation of data centers into “AI factories” that generate artificial intelligence. He expects this modernization to continue for several years, with more foundation model makers, AI-native startups, and inference services emerging than ever before.
Key Quotes
Demand for Hopper and anticipation for Blackwell — in full production — are incredible as foundation model makers scale pretraining, post-training, and inference.
CEO Jensen Huang made this statement during the earnings call, emphasizing the sustained demand across the entire AI development pipeline. This matters because it shows AI companies aren’t just buying chips for initial training but for ongoing operations and inference, indicating long-term revenue stability for Nvidia.
Demand for Blackwell is expected to exceed supply for several quarters in fiscal 2026.
CFO Colette Kress provided this guidance, signaling that Nvidia’s supply constraints will persist well into next year. This is significant because it demonstrates that even with aggressive production scaling, the company cannot keep pace with customer demand, validating the strength of the AI market.
We’re at the beginning of two fundamental shifts in computing… from coding to machine learning… and these data centers are really AI factories.
Huang used this framing to explain why he expects the AI infrastructure buildout to continue for years. This matters because it positions the current AI boom not as a temporary trend but as a fundamental restructuring of computing infrastructure, justifying continued massive investments.
The age of robotics is coming… Investments in industrial robotics are surging due to breakthroughs in physical AI.
Huang highlighted robotics and physical AI as the next major growth driver beyond language models. This is significant because it expands Nvidia’s addressable market beyond cloud data centers into manufacturing, logistics, and industrial applications, potentially opening trillion-dollar opportunities.
Our Take
Nvidia’s results reveal a maturing but still explosive AI market. The slight stock dip despite stellar results suggests investors are becoming more discerning, looking beyond raw growth numbers to margin pressures and guidance. However, the fundamental story remains incredibly bullish: demand exceeds supply, new use cases are emerging, and the infrastructure buildout is far from complete.
The shift toward “physical AI” and robotics is particularly noteworthy. While much attention has focused on chatbots and generative AI, Huang is positioning Nvidia for the next wave where AI moves from screens into factories, warehouses, and autonomous systems. This could be even larger than the current boom.
The China dynamic bears watching closely. Despite export restrictions, Nvidia is growing its China business with compliant chips, but Trump-era tariffs could complicate this. How Nvidia navigates geopolitical tensions while maintaining growth will be crucial for investors and the broader AI ecosystem.
Why This Matters
This earnings report serves as a critical barometer for the entire AI industry’s health and trajectory. Nvidia has become the de facto infrastructure provider for the AI revolution, with its chips powering everything from ChatGPT to autonomous vehicles. The company’s performance directly reflects how much Big Tech and enterprises are investing in AI capabilities.
The Blackwell chip’s supply constraints signal that AI demand remains insatiable, despite concerns about potential slowdowns in AI spending. This validates the thesis that we’re still in the early innings of AI adoption, not approaching saturation. The fact that demand will exceed supply for multiple quarters suggests companies are racing to secure AI computing capacity before competitors.
Huang’s emphasis on “physical AI” and robotics points to the next frontier beyond chatbots and language models. This expansion into manufacturing, logistics, and industrial applications could represent a multi-trillion dollar opportunity that extends AI’s impact far beyond software into the physical world. For businesses and workers, this signals that AI transformation will accelerate across industries, requiring adaptation and investment in AI-powered tools and infrastructure.
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