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.

AI2Day NewsdeskAI-assistedPublished Updated Editor: Lee Brown3 min read
Illustration: a server room corridor with rows of glowing rack-mounted computers
Illustration made with AI. Not a photograph of the events described.
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Key points

  • Nvidia reported record quarterly revenue of $96.2 billion for the quarter ending August 2026, up more than $10 billion from 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 be the first time it has crossed that threshold in a single quarter.
  • 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 AI systems, just reported the largest quarterly revenue in its history: $96.2 billion in ninety days.

Where is all that money coming from?

Nearly all of it comes from selling hardware to cloud providers, governments and large tech companies racing to build AI infrastructure. Data center revenue, meaning sales of the high-powered chips used to train and run AI models, hit $89 billion last quarter, more than double the figure from the same period a year ago. Our 13 August story on Nvidia's $500 billion data center plan showed how deep that infrastructure bet already ran before these numbers landed.

Nvidia's consumer business, which covers the graphics cards (GPUs) that gamers and home PC builders buy, told a quieter story. That segment brought in $7.2 billion, about 7 percent of total revenue, up 27 percent year-over-year. Nvidia attributed the slower pace partly to elevated 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, expect to keep paying elevated prices for now. Component shortages are still pushing costs up on the consumer side, and Nvidia has also warned that prices on its AI chips are rising. That cost tends to filter through to the cloud services and AI tools that businesses and consumers use every day.

Every AI chatbot response and every AI-generated image 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's guiding for $108 billion next quarter. If it hits that, it'd be the first time the company has crossed $100 billion in a single quarter. Amazon, Apple and Alphabet have each done it repeatedly. Whether demand holds at that scale depends largely on how aggressively the biggest tech companies keep building AI data centers, and that appetite has shown 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 can't ramp supply instantly. High profits at the company level don't 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.

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