Experts suggest that an Arm chip utilizing the Blackwell GPU architecture could resolve long-standing compromises in Windows-on-Arm systems and challenge existing leaders in AI PC processors.
Nvidia is currently developing a system-on-chip (SoC) intended for Windows personal computers. Key original equipment manufacturers (OEMs) such as Dell and Lenovo are reportedly planning to integrate this processor into their upcoming notebooks and desktops later this year.
According to sources familiar with the situation, as reported by the Wall Street Journal, this new chip will be based on the GB10, a component Nvidia co-developed with MediaTek and initially released in October 2025.
Currently, the GB10 powers Linux-based AI workstations from various manufacturers, including Dell, Lenovo, Asus, MSI, and Gigabyte. These systems, priced between $3,000 and $4,000, are designed for machine learning researchers and developers working with AI models. Importantly, none of these existing systems operate on Windows.
While Nvidia has previously explored Arm-based chip designs for Windows PCs, the GB10 represents their most substantial move toward realizing that ambition to date.
Bridging the Engineering Divide
The GB10 was specifically engineered to execute large AI models within a developer workstation context. It combines a CPU tile designed by MediaTek, housing 20 Arm cores, with an Nvidia Blackwell GPU tile, collectively delivering up to one petaFLOP of AI performance at FP4.
With a power draw of 140 watts under peak load – approximately triple the thermal capacity of a high-end business laptop – this design was not conceived for typical notebook form factors.
According to Rishi Padhi, a principal analyst at Gartner, a PC-ready version would need to feature significantly reduced compute configurations.
“I would expect Nvidia’s product line to come with lower compute power to be more efficient on power consumption and also the heat generated, sufficient to be cooled by a laptop-based cooling system,” he said.
Padhi also noted that Nvidia would need to adopt a unified memory architecture to manage power consumption effectively, bringing it in line with rival platforms, “similar to how Apple achieves power efficiency gains through a unified memory architecture.”
Should Nvidia successfully deliver a power-efficient, Windows-compatible derivative to the market, analysts predict it will directly challenge the dominant players in PC silicon.
Challenge to Established Chip Manufacturers
Analysts suggest that Nvidia’s entry into the integrated PC silicon market presents a direct competitive threat to Qualcomm, Intel, and AMD. The most immediate impact is expected on Qualcomm, as Windows-on-Arm laptops have historically traded strong battery life for compromised graphics performance, a limitation Nvidia’s architecture aims to overcome.
“By fusing the performance compute of a Blackwell GPU directly onto an Arm die, Nvidia essentially nullifies the traditional trade-off associated with Windows-on-Arm machines,” Padhi said. “This will directly impact the share of Qualcomm’s offerings in AI PCs.”
For Intel and AMD, the analyst explained, the nature of the threat differs. High-performance mobile processors from both companies are frequently paired with discrete Nvidia GPUs in premium laptop configurations. “With Nvidia slated to launch a capable SoC of its own, it can prompt OEMs to consider purchasing a single integrated chip from Nvidia that offers better battery life and equivalent graphical performance to an x86 CPU plus Nvidia GPU combo,” Padhi said. “The economic and engineering incentives heavily favor the unified system-on-chip.”
Shreeya Deshpande, a senior analyst at Everest Group, commented that this development signifies a broader strategic shift. “Nvidia’s reported move into Arm-based PC SoCs marks a strategic shift from being primarily a GPU supplier to competing at the core platform level in Windows laptops,” she said. “If successful, it could materially intensify competition in the Windows-on-Arm ecosystem and increase pressure on incumbent PC silicon providers to further differentiate on AI performance and efficiency.”
The stakes are considerable. Gartner forecasts that AI PCs will constitute over 50% of all PC shipments by 2026. Beyond the competitive market dynamics, analysts suggest that Nvidia’s venture into PC silicon holds significant implications for businesses already utilizing Nvidia infrastructure in their data centers.
