Nvidia’s Jensen Huang Says “Crazy Good” Q4 Ahead After Big Q3 Beat, Easing AI Bubble Fears
Nvidia posted a blockbuster fiscal third quarter, sending shares higher as CEO Jensen Huang pushed back on “AI bubble” talk and forecast a “crazy good” fourth quarter driven by broad adoption of its chips and software.
Key takeaways
- Q3 sales jumped 62%, the first acceleration in seven quarters and a clear beat of Street forecasts.
- Bold Q4 guidance: management expects roughly $65 billion in revenue, above consensus, and ~75% adjusted gross margin.
- Data-center dominance: data-center revenue reached $51.2 billion, underscoring AI-driven demand for GPUs.
- Management confidence: Jensen Huang pushed back on bubble talk and reported strong revenue visibility into 2026.
What Nvidia reported
Nvidia said sales in its fiscal third quarter jumped 62% from a year earlier, marking a notable pick-up in growth after months of slowing demand. The results beat Wall Street forecasts and showed unusually strong momentum in the company’s core business.
Management issued aggressive guidance: Nvidia projects revenue near $65 billion for the fourth quarter, ±2%, versus a LSEG consensus of about $61.66 billion. The company also expects an adjusted gross margin near 75% for the period and plans to keep margins in the mid-70s through fiscal 2027.
CEO Jensen Huang on the AI bubble
On the earnings call, CEO Jensen Huang addressed market concerns that AI could be a speculative bubble. He pushed back, saying:
“There’s been a lot of talk about an AI bubble. From our vantage point, we see something very different.”
Huang emphasized that demand is coming from real business needs — chips and software deployed across clouds, data centers and developer tools — and that Nvidia’s platform helps move projects from idea to product.
Data-center strength
Most of Nvidia’s revenue now comes from the data-center segment. For the quarter ended Oct. 26, that unit posted $51.2 billion in sales, outpacing the expected $48.62 billion and reflecting heavy adoption of GPUs for AI training and inference by cloud providers, enterprises and research labs.
Executives said many enterprise customers are buying systems for production use rather than experiments. CFO Colette Kress told investors the company has visibility to roughly half a trillion dollars in revenue through 2026 — a projection that, if realized, would rank Nvidia among the largest U.S. companies by revenue.
Market reaction
Nvidia’s beat and strong guidance sparked gains across chipmakers and cloud names, as investors took the data as evidence of sustainable demand for AI hardware. Analysts said the results helped calm fears about the AI boom’s durability in the near term.
But caution remains: some market watchers highlighted risks including competition, pricing pressure, and the timeline for enterprise AI projects to generate recurring revenue.
Dividend and shareholder moves
Nvidia announced a small quarterly cash dividend of $0.01 per share, payable Dec. 26, 2025, to shareholders of record Dec. 4, 2025. The move signals returning cash while the company continues heavy reinvestment in capacity and R&D.
Analysts characterized the dividend as largely symbolic given Nvidia’s capital needs to expand its compute infrastructure and software ecosystem.
Analyst views and caution
Many analysts praised Nvidia’s execution, highlighting the company’s pricing power for high-end GPUs and its growing software stack. Yet some warned that elevated expectations are already priced into the stock; any future misses could reverse sentiment quickly.
Other risks cited include supply-chain constraints, competition from firms such as AMD or custom chips from cloud providers, and the pace at which enterprise software turns AI prototypes into revenue-generating services.
Implications for Los Angeles, California
Nvidia’s results have local implications across L.A.’s tech, media, academic and public sectors. Below are key areas where stronger Nvidia momentum could affect the region.
Economic boost to local tech and media industries
Hollywood studios and post-production houses increasingly use AI tools for special effects, editing and content creation. Greater availability of Nvidia GPUs could lower rendering times and costs, accelerating production pipelines for local visual effects and media firms.
Startups and venture activity
L.A.’s cluster of AI startups — in media, health tech, logistics and ad tech — may attract more venture capital as compute becomes more accessible and confidence in the AI market grows. Local accelerators and university labs at UCLA and USC could see increased partnerships and grants tied to Nvidia-backed projects.
Jobs and workforce training
Stronger demand for AI infrastructure can create openings for engineers, data scientists and operations staff. Community colleges, boot camps and universities may expand AI programs to help residents access well-paying roles without moving to Silicon Valley.
Film and television production
Faster, cheaper real-time rendering and AI-assisted workflows powered by Nvidia hardware could shift how visual effects budgets are allocated and which projects move forward, benefiting mid-size production houses competing for studio work.
Public sector and civic use
City agencies exploring AI for traffic, public safety analytics or permitting may find more supplier options and clearer cost models as Nvidia’s ecosystem grows. Civic deployments will still require strong attention to privacy, equity and oversight.
Real estate and data centers
Rising GPU demand may spur new data-center investments in Southern California, supporting construction jobs and tax revenue but raising concerns about energy use and air quality. Local planners and utilities may need to evaluate permitting and grid upgrades.
Academic research and partnerships
Universities such as UCLA, USC and Caltech that collaborate with tech firms on AI research could see more partnerships, grants and shared infrastructure as Nvidia’s roadmap and revenue visibility support long-term projects.
Cautions for local leaders
While Nvidia’s results reduce near-term bubble fears, city leaders and investors should plan for cycles. Many AI projects take years to reach profitability; workforce programs should pair technical skills with ethics and soft skills, and energy planners must prepare for increased electricity demand if data-center growth continues.
Sources and transparency
This report draws on Nvidia’s investor materials and earnings call, market data from LSEG, and coverage by major outlets. Key sources:
- Nvidia investor news and press releases
- Nvidia earnings materials and SEC filings
- LSEG (formerly Refinitiv) market data
- Reuters coverage of Nvidia and markets
- CNBC coverage and market reaction
- Seeking Alpha earnings call transcripts
Reporting note
All figures and quotations attributed to company executives come from Nvidia’s public materials and earnings-call transcripts. Analyst estimates and comparisons referenced in this article are based on LSEG data and widely reported market coverage.
