Nvidia CEO Jensen Huang was greeted as a rock star this week CES in Las Vegas, following an artificial intelligence boom that’s made the chipmaker the second most-valuable company in the world.

At his nearly two-hour keynote on Monday kicking off the annual conference, Huang packed a 12,000-seat arena, drawing comparisons to the way Steve Jobs would reveal products at Apple events.

Huang concluded with an Apple-like trick: a surprise product reveal. He presented one of Nvidia’s server racks and, using some stage magic, held up a much smaller version, which looked like a tiny cube of a computer.

“This is an AI supercomputer,” Huang said, while donning an alligator skin leather jacket. “It runs the entire Nvidia AI stack. All of Nvidia’s software runs on this.”

Huang said the computer is called Project Digits and runs off a relative of the Grace Blackwell graphics processing units (GPUs) that are currently powering the most advanced AI server clusters. The GPU is paired with an ARM-based Grace central processing unit (CPU). Nvidia worked with Chinese semiconductor company MediaTek to create the system-on-a chip called GB10.

Formerly known as the Consumer Electronics Show, CES is typically the spot to launch flashy and futuristic consumer gadgets. At this year’s show, which started on Tuesday and wraps up on Friday, several companies announced AI integrations with appliances, laptops and even grills. Other major announcements included a laptop from Lenovo which has a rollable screen that can expand vertically. There were also new robots, including a Roomba competitor with a robotic arm.

Unlike Nvidia’s traditional GPUs for gaming, Project Digits isn’t targeting consumers. instead, it’s aimed at machine learning researchers, smaller companies, and universities that want to developed advanced AI but don’t have the billions of dollars to build massive data centers or buy enough cloud credits.

“There’s a gaping hole for data scientists and ML researchers and who are actively working, who are actively building something,” Huang said. “Maybe you don’t need a giant cluster. You’re just developing the early versions of the model, and you’re iterating constantly. You could do it in the cloud, but it just costs a lot more money.”

The supercomputer will cost about $3,000 when it becomes available in May, Nvidia said, and will be available from the company itself as well as some of its manufacturing partners. Huang said Project Digits is a placeholder name, indicating it may change by the time the computer goes on sale.

“If you have a good name for it, reach out to us,” Huang said.

Data center sales accounted for 88% of Nvidia’s $35 billion in revenue in the most recent quarter.

Wall Street is focused on Nvidia’s ability to diversify its business so that it’s less reliant on a handful of customers buying massive AI systems.

“It was a little scary to see Nvidia come out with something so good for so little in price,” Melius Research analyst Ben Reitzes wrote in a note this week. He said Nvidia may have “stolen the show,” due to Project Digits as well other announcements including graphics cards for gaming, new robot chips and a deal with Toyota.

Project Digits, which runs Linux and the same Nvidia software used on the company’s GPU server clusters, represents a huge increase in capabilities for researchers and universities, said David Bader, director of the Institute for Data Science at New Jersey Institute of Technology.

Bader, who has worked on research projects with Nvidia in the past, said the computer appears to be able to handle enough data and information to train the biggest and most cutting-edge models. He told CNBC Anthropic, Google, Amazon and others “would pay $100 million to build a super computer for training” to get a system with these sorts of capabilities.

For $3,000, users can soon get a product they can plug into a standard electrical outlet in their home or office, Bader said. It’s particularly exciting for academics, who have often left for private industry in order to access bigger and more powerful computers, he said.

“Any student who is able to have one of these systems that cost roughly the same as a high-end laptop or gaming laptop, they’ll be able to do the same research and build the same models,” Bader said.

Reitzes said the computer may be Nvidia’s first move into the $50 billion market for PC and laptop chips.

“It’s not too hard to imagine it would be easy to just do it all themselves and allow the system to run Windows someday,” Reitzes wrote. “But I guess they don’t want to step on too many toes.”

Huang didn’t rule out that possibility when asked about it by Wall Street analysts on Tuesday.

He said that MediaTek may be able to sell the GB10 chip to other computer makers in the market. He made sure to leave some mystery in the air.

“Obviously, we have plans,” Huang said.

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