Nvidia Just Posted $96 Billion in a Single Quarter. It Thinks $108 Billion Is Next.
The chip maker's data center sales more than doubled in a year, driven by relentless demand for AI hardware. Consumer GPU buyers are feeling the squeeze.
Key points
- Nvidia reported record quarterly revenue of $96.2 billion for the quarter ending August 2026, up from roughly $86 billion the previous quarter.
- Data center revenue, sales of the specialised chips companies buy to build and run AI systems, reached $89 billion, more than double the figure from the same quarter a year earlier.
- Nvidia's quarterly profit more than doubled year-over-year to $59.7 billion.
- Nvidia is forecasting $108 billion in revenue for the next quarter, which would put it alongside Amazon, Apple and Alphabet as companies that regularly clear $100 billion in three months.
- Component shortages continue to push up prices for consumer graphics cards, and Nvidia has warned of further price increases on its AI chips.
Nvidia, the California company whose specialised chips power most of the world's artificial intelligence systems, just reported the largest quarterly revenue in its history: $96.2 billion in a single three-month period.
To put that in perspective, that is roughly the annual economic output of a mid-sized country, earned in ninety days.
Where is all that money coming from?
Nearly all of it comes from selling hardware to tech companies, cloud providers and governments racing to build AI infrastructure. Data center revenue, meaning sales of the high-powered chips that companies use to train and run AI models, hit $89 billion last quarter. That figure more than doubled compared with the same quarter a year ago.
Nvidia's consumer business, which covers the graphics cards, or GPUs, that gamers and home PC builders buy, told a much quieter story. That segment brought in $7.2 billion, about 7 percent of total revenue. Nvidia attributed slower consumer sales partly to high memory and component prices squeezing buyers out of the market.
| Segment | Q3 2026 Revenue | Year-over-year change |
|---|---|---|
| Data center | $89.0 billion | More than doubled |
| Consumer / edge computing | $7.2 billion | +27% |
| Total company | $96.2 billion | More than doubled |
| Net profit | $59.7 billion | More than doubled |
What does this mean for ordinary people?
If you want to upgrade your PC or buy a new graphics card, expect to keep paying elevated prices for now. Nvidia confirmed that component shortages are still pushing costs up on the consumer side. The company also warned ahead of this earnings report that prices on its AI chips are rising, a cost that will eventually filter through to the cloud services and AI tools that businesses and consumers use every day.
For anyone watching their electricity or broadband bill, it is worth knowing that every AI chatbot response, every AI-generated image, and every automated customer service interaction runs on hardware very much like what Nvidia sells. The more companies spend building that infrastructure, the faster AI tools tend to improve, but that spending also means higher operating costs that providers often pass on.
What happens next?
Nvidia is guiding for $108 billion in revenue next quarter. If accurate, that would be the first time Nvidia has crossed the $100 billion mark in a single quarter. Amazon, Apple and Alphabet have each done it multiple times. Whether demand at that scale holds depends largely on how aggressively the biggest tech companies keep building AI data centers, and that appetite, so far, shows no sign of cooling.
The earnings were first reported by The Verge AI.
Common questions
Why are graphics cards still so expensive if Nvidia is making record profits?
Shortages of key components like memory chips keep production costs high, and Nvidia's manufacturing partners cannot ramp supply instantly. High profits at the company level do not automatically translate to cheaper products at the checkout.
Will AI services become more expensive because of this?
Possibly, over time. When the chips used to run AI cost more, companies that sell AI tools often raise prices to protect their own margins. Competition between providers can slow that process, but it rarely stops it entirely.
