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Nvidia CEO Huang says upcoming DGX Spark systems are powered by N1 silicon -- confirms GB10 Superchip and N1/N1X SoCs are identical
Yesterday, Nvidia and Intel lifted the curtain on a historic collaboration that will see the two chipmakers jointly develop a myriad of CPU and GPU products. While future solutions like the "Intel x86 RTX SoC" were the focus of the announcement, some clarification was also shed on existing projects. Chief among these was Nvidia CEO Jensen Huang saying that the upcoming, long-rumored N1 SoC is essentially the same as the GB10 Superchip that's been out for a while. For some context, Nvidia has never officially unveiled the N1/N1X SoCs, but speculation sparked from CES 2025's announcement of Project DIGITS, where the company revealed its collaboration with MediaTek. From that came the GB10 "Superchip," which is part of the company's DGX Spark lineup, and multiple vendors have already released their iterations of it. The GB10 is aimed squarely at AI workloads, offering supercomputer-like performance at home. It includes a 20-core ARM-based CPU developed in conjunction with MediaTek, along with a powerful Blackwell-based GPU chiplet. The N1 SoC shares the same specs, at least according to previous leaks and rumors, featuring 6,144 CUDA cores for its GPU - same as the desktop RTX 5070 - and a 20-core CPU split across two clusters, built using Nvidia's Grace architecture. Back in July, we saw a Geekbench score surface for the N1X, which allegedly confirmed these specs, giving credence to the fact that GB10 and N1 are intrinsically tied. Of course, just because two products are closely linked to each other doesn't mean they're the same, but all signs pointed toward identical chips being used across the board. That notion has just been legitimized by Jensen Huang, who said the following in a webcast last night, "We also have a new ARM product that's called N1. And that product is - that processor is going to go into the DGX Spark and many other versions of products like that. And so we're super excited about the ARM road map, and this doesn't affect any of that." According to Nvidia's CEO, the silicon powering the GB10 -- which itself is what powers DGX Spark -- is identical to the N1/N1X SoC. Especially the part about "many other versions" confirms that N1 could simply be a slightly lower-binned version of the full-fat GB10. After all, the latter is meant for client devices like laptops and desktops, whereas the GB10 targets professionals. The distinction matters because N1 represents Nvidia's first serious attempt at taking their in-house CPU cores mainstream (following Tegra). Unfortunately, that's the only statement pertaining to N1, so we still don't know when it will actually launch. But at least it's out there now that GB10, which should already be in the hands of some, is what Nvidia will eventually release in the future, just with a different target audience in mind. Given Nvidia's new deal with Intel, the interest in developing ARM-based products might collide with x86-based solutions that Intel specializes in. However, that's apparently not an issue, and both roadmaps will continue forward at full force, unaffected by each other. The N1 SoC has already been tested on Windows, which suggests that the chip is getting closer to its Windows-on-ARM destination day by day. The GB10, on the other hand, is not exactly intended for Microsoft's operating system; rather, it is a Linux-based DGX OS that's optimized for local AI, datacenter, and other professional workloads. With that said, since the N1 technically doesn't even exist yet, there is no confirmation for it eventually running on Windows (despite the obvious implication), and Jensen Huang did not comment on it either.
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Nvidia GB10 Equals N1 Arm CPU Superchip - cooperation with Intel will not affect Arm CPU development
Nvidia has finally cleared up the mystery around its newest processor. On a recent call about its partnership with Intel, CEO Jensen Huang said the GB10 chip -- previously known as the Grace Blackwell superchip -- is also officially called the "N1." This chip will show up first in DGX Spark, a desktop AI supercomputer, and later in more Nvidia products. The N1 isn't just another GPU. It's a mix of two parts: Nvidia's own GPU die and a CPU die designed with MediaTek. On the CPU side, it packs 20 Arm cores, split between 10 powerful Cortex-X925 cores and 10 efficient Cortex-A725 cores. For graphics and compute, it brings 6,144 CUDA cores to the table. To keep everything running smoothly, the chip also supports a 256-bit LPDDR5X memory interface, giving it the bandwidth needed for heavy AI and data workloads. Huang also made sure to point out that teaming up with Intel doesn't mean Nvidia is stepping away from its Arm CPU plans. The company is still fully invested in building its own Arm-based processors, and the roadmap that includes Grace and Blackwell chips remains unchanged. The partnership with Intel is more about working together in other areas, like data center CPUs, without taking focus away from Nvidia's own designs. In short, the N1 chip represents Nvidia's ongoing strategy: combine powerful GPUs with Arm CPUs to create flexible, high-performance solutions for AI computing. With MediaTek's contribution on the CPU side and Nvidia's strength in GPUs, the N1 looks set to push AI systems like DGX Spark into a new level of performance. This approach also shows that Nvidia isn't planning to rely on Intel -- or anyone else -- for its future in Arm-based chips. Instead, it's carving out its own path while still building partnerships where they make sense.
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Nvidia CEO Jensen Huang confirms that the long-rumored N1 SoC is identical to the GB10 Superchip, set to power DGX Spark systems. This powerful AI-focused chip combines ARM-based CPU and Blackwell-based GPU technologies, showcasing Nvidia's commitment to both ARM development and its new partnership with Intel.
Nvidia CEO Jensen Huang has finally lifted the veil on the company's long-rumored N1 system-on-chip (SoC), confirming that it is identical to the GB10 Superchip powering the upcoming DGX Spark systems. This revelation comes amidst Nvidia's historic collaboration announcement with Intel, shedding light on the chipmaker's strategy in the rapidly evolving AI hardware landscape
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.The N1 SoC, also known as the GB10 Superchip, is a formidable piece of silicon designed for AI workloads. It combines:
This architecture aims to deliver supercomputer-like performance for AI tasks in more accessible form factors, from desktops to laptops
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.The N1/GB10 chip will make its debut in the DGX Spark, Nvidia's desktop AI supercomputer. This system represents a significant step in democratizing high-performance AI computing, allowing professionals and enthusiasts to harness supercomputer-level capabilities in a more compact and accessible format
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.Despite the recent collaboration announcement with Intel, Huang emphasized that Nvidia remains committed to its ARM-based processor development. The CEO stated, "We're super excited about the ARM road map, and this doesn't affect any of that." This assurance indicates that Nvidia will continue to pursue its ARM-based strategies alongside its new partnership with Intel .
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While the GB10 is primarily designed for Linux-based DGX OS and professional workloads, there are indications that the N1 variant might target a broader market. Reports of the N1 SoC being tested on Windows suggest potential future compatibility with Microsoft's operating system, although Nvidia has not officially confirmed this
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.Nvidia's strategy of collaborating with Intel while simultaneously advancing its ARM-based designs showcases the company's multifaceted approach to maintaining its leadership in the AI hardware market. By leveraging partnerships and in-house innovations, Nvidia aims to cater to diverse computing needs across various platforms and use cases
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.As the AI hardware landscape continues to evolve, Nvidia's N1/GB10 chip represents a significant milestone in the company's quest to bring supercomputer-level AI performance to a wider range of devices and applications. The success of this chip could potentially reshape the AI computing market and accelerate the adoption of advanced AI technologies across various industries.
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