Nvidia has posted another record quarter in Q3 FY26, delivering strong revenue, massive data center growth, and a bold message from CEO Jensen Huang dismissing concerns about an “AI bubble.”
Q3 FY26 Highlights
| Metric | Q3 FY26 | Estimate | YoY | QoQ |
|---|---|---|---|---|
| Total Revenue | $57.01B | $55.19B | +62% | +22% |
| Adjusted EPS | $1.30 | — | +60% | +24% |
| Data Center Revenue | $51.2B | $49.34B | +66% | +25% |
The company continues to lead the global AI infrastructure boom, driven by cloud providers, enterprises, and AI-native startups scaling training and inference workloads.
Q4 FY26 Guidance
- Revenue: $65B ±2% (vs est. $61.98B)
- GAAP Gross Margin: ~74.8% ±50 bps
- Adjusted Gross Margin: ~75.0% ±50 bps
- GAAP OpEx: ~$6.7B
- Adjusted OpEx: ~$5.0B
Nvidia expects record AI infrastructure spending to continue into Q4.
Segment Revenue Breakdown
| Segment | Revenue | Estimate | YoY | QoQ |
|---|---|---|---|---|
| Data Center | $51.2B | $49.34B | +66% | +25% |
| Gaming | $4.3B | $4.42B | +30% | -1% |
| Professional Visualization | $0.76B | $0.61B | +56% | +26% |
| Automotive | $0.59B | $0.62B | +32% | +1% |
Demand for the Blackwell platform is hitting unprecedented levels, with 10x throughput-per-megawatt improvements for AI inference workloads.
Profitability & Cash Flow
| Metric | Value | YoY | QoQ |
|---|---|---|---|
| Adjusted Gross Margin | 73.6% | -1.4 pts | +0.9 pts |
| Adjusted OpEx | $4.22B | +38% | +11% |
| Adjusted Operating Income | $37.75B | +62% | +25% |
| Adjusted Net Income | $31.77B | +59% | +23% |
| Free Cash Flow | $22.09B | +32% | — |
Nvidia returned $37B to shareholders this year and retains $62.2B in buyback authorization.
Nvidia’s Q3 Revenue Is Highly Concentrated
In Q3, 61% of Nvidia’s total revenue came from just four major customers. Customer A contributed $12.54B (22%), Customer B $8.55B (15%), Customer C $7.41B (13%), and Customer D $6.27B (11%), highlighting how dependent Nvidia is on a small set of buyers.
Jensen Huang on the AI Bubble: “This Is Not a Bubble — It’s a Platform Shift”
Huang addressed the idea of an “AI bubble” directly. According to him, three major platform transformations are happening at the same time — something not seen since early semiconductor history:
1. From CPU to GPU Accelerated Computing
As Moore’s Law slows, workloads from science, engineering, analytics, and cloud computing are all shifting to GPUs for efficiency.
2. Generative AI Replacing Classical Machine Learning
GenAI is rapidly improving search results, ads, recommendations, content ranking, and enterprise automation — creating real, measurable revenue gains.
3. Rise of Agentic & Physical AI
Companies like OpenAI, Anthropic, Google, xAI, Replit, Cognition, Abridge, Harvey, and Tesla are building systems that can reason, plan, code, analyze, and self-drive.
Why Jensen Says AI Demand Is Not Speculative
• Real Revenue Impact
Meta’s generative AI-powered ad ranking improved Instagram conversions by 5% and Facebook feed conversions by 3% — proving GenAI drives revenue at scale.
• Performance per Watt = Revenue
Huang explained one hard limit: power.
“You still only have 1 gigawatt of power. Performance per watt translates directly to your revenues.”
• Massive Supply Chain Scale
“No company has ever grown at the scale we are talking about.”
Nvidia’s supply chain partners rely on its forecasts — allowing multi-year infrastructure planning.
FAQ
1. Did Nvidia beat Q3 FY26 estimates?
Yes. Nvidia reported $57.01B in revenue vs $55.19B estimated.
2. What drove Nvidia’s record Q3 results?
Massive demand for Blackwell GPUs powering training and inference workloads.
3. Is the AI sector a bubble?
Jensen Huang says no — the world is undergoing three simultaneous computing shifts with real revenue impact.
4. What is Nvidia’s Q4 FY26 outlook?
$65B ±2% revenue with strong margins.
Conclusion
Nvidia’s Q3 FY26 results confirm that AI infrastructure growth is accelerating globally. With unmatched GPU leadership, full-stack software ecosystems, and the world’s most advanced AI platform, Nvidia is positioned to remain the central force in the next generation of computing.
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