Jensen Huang says ‘every edge device will become autonomous’ — Nvidia maps one computing pattern from the cloud to robotics

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Jensen Huang says 'every edge device will become autonomous' — Nvidia maps one computing pattern from the cloud to robotics

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The top RTX Spark part, internally N1X, pairs a 20-core Arm CPU built by MediaTek (10 Cortex-X925 performance cores and 10 Cortex-A725 efficiency cores) with a Blackwell GPU carrying 6,144 CUDA cores, up to 128GB of LPDDR5X unified memory, and a 600 GB/s NVLink-C2C link, all on TSMC's 3nm node. Huang justified these specs with the same impatience he applied to Vera, arguing that an agent driving the machine won’t wait, so the software it touches, from Adobe to Blender, "cannot be slow."

The platform is launching in a market that Qualcomm had effectively dominated until its Windows on Arm exclusivity with Microsoft lapsed . Fall 2026 laptops are confirmed from Microsoft , Dell , HP, ASUS, Lenovo, and MSI, with Acer and Gigabyte to follow, and Nvidia says anti-cheat engines, including Easy Anti-Cheat and Denuvo, run natively on the chip. Asked why Nvidia would enter a low-margin business it has steered clear of for years, Huang said, "We don't really have to choose. The real question is, can we make a contribution?"

Vera's 88 cores are Nvidia's own custom Olympus design, its first ground-up server core since the Denver and Carmel projects, while RTX Spark's 20 cores are Arm's off-the-shelf Cortex reference designs licensed through MediaTek, one of them already a generation old. Huang's "same pattern everywhere" runs, at the silicon level, on two different CPUs.

When asked whether the Olympus cores would come to Windows PCs, Huang declined to commit. "Our preference is to use off-the-shelf cores whenever we can, because Arm also builds good cores," he said, adding that Olympus was pushed toward single-thread speed in a way standard many-core Arm parts weren’t: "We wanted to push single-threaded performance as far as we could push it." The first PC chip using Nvidia's own cores isn’t expected until 2028. Meanwhile, Morgan Stanley estimates Vera at around $5,000 per socket inside a vertically integrated rack.

DRAM contract prices have climbed sharply through 2026 as makers divert wafers to high-bandwidth memory, and Nvidia remains short of supply even as it locks in capacity, by Huang's own account: "We have enough supply for very robust growth. However, we are supply constrained."

"One of the best ways to improve memory use is to use extremely, extremely low precision," Huang said, pointing to NVFP4, Nvidia's 4-bit floating-point format that scales between four, eight, 16, and 32 bits and roughly doubles the parameters that fit in a given memory pool, the trick that lets RTX Spark hold larger models in its 128GB. He paired it with neural texture compression that cuts game texture memory by up to eight times in Nvidia's demos. At SK hynix's booth during the show, Huang signed an HBM4E wafer with the words "Please Make More."

Luke James is a freelance writer and journalist.\u00a0 Although his background is in legal, he has a personal interest in all things tech, especially hardware and microelectronics, and anything regulatory.\u00a0 ","collapsible":{"enabled":true,"maxHeight":250,"readMoreText":"Read more","readLessText":"Read less"}}), "https://slice.vanilla.futurecdn.net/13-4-24/js/authorBio.js"); } else { console.error('%c FTE ','background: #9306F9; color: #ffffff','no lazy slice hydration function available'); } Luke James Social Links Navigation Contributor Luke James is a freelance writer and journalist. Although his background is in legal, he has a personal interest in all things tech, especially hardware and microelectronics, and anything regulatory.

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  1. Jensen Huang says ‘every edge device will become autonomous’ — Nvidia maps one computing pattern from the cloud to robotics
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  3. Jensen Huang says ‘every edge device will become autonomous’ — Nvidia maps one computing pattern from the cloud to robotics
  4. Jensen Huang says ‘every edge device will become autonomous’ — Nvidia maps one computing pattern from the cloud to robotics

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