BREAKING NEWS
Nvidia CEO Jensen Huang Predicts 70% Growth
Nvidia CEO Jensen Huang spoke at the Goldman Sachs conference, explaining why he expects the company's revenue to grow by 70% next year.
QuickTool Team
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Sep 10, 2026•3 min read•Source: TechCrunchAI-assisted summary · Automatically reviewed by the QuickTool Quality Pipeline
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⚡ In Short
- Jensen Huang expects Nvidia's revenue to grow by 70% next year.
- A major computer system combining 36 Grace CPUs and 72 Blackwell GPUs shows 27% month-to-month sales growth.
- Huang defended Nvidia's investments, citing $100 billion in verified customer contracts.
What Happened?
At the Goldman Sachs Communacopia + Technology conference, Nvidia founder and CEO Jensen Huang outlined his revenue projections for the artificial intelligence hardware leader. Despite growing competition from hyperscalers like Amazon, Microsoft, and Google, as well as chip startups like Cerebras and Etched, Huang reiterated that Nvidia anticipates a 70% year-over-year revenue increase. He noted that orders for a specific system combining 36 Grace CPUs and 72 Blackwell GPUs are seeing 27% month-to-month sales growth. Huang also addressed questions regarding circular investments, stating that Nvidia ensures partner companies have real contracts generating customer revenue before investing.
Key Highlights
1
Jensen Huang expects Nvidia's revenue to grow by 70% next year.
2
A major computer system combining 36 Grace CPUs and 72 Blackwell GPUs shows 27% month-to-month sales growth.
3
Huang defended Nvidia's investments, citing $100 billion in verified customer contracts.
Why It Matters
The discussion sheds light on the ongoing expansion of the artificial intelligence infrastructure market. With analysts projecting fiscal year revenue to reach about $400 billion, a 70% increase would scale next year's figures significantly, impacting the entire technology supply chain from memory chip makers to data center shell builders.
💡 Related AI Tools
The broader artificial intelligence landscape relies heavily on specialized hardware platforms like Graphics Processing Units (GPUs) and Tensor Core architectures to train and run large language models and neural networks.
Conclusion
While Huang remains highly optimistic about sustained market dominance, the long-term trajectory will depend on how the artificial intelligence industry matures and handles infrastructure efficiency.
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