Nvidia has officially entered the PC processor market with the launch of RTX Spark, a new Arm-based superchip developed in collaboration with Microsoft. The processor will debut this fall in a new generation of Windows laptops and desktops from Microsoft, Dell, HP, ASUS, Lenovo, and MSI.
Announced by CEO Jensen Huang during Computex in Taiwan, RTX Spark combines Nvidia’s Blackwell GPU architecture with a custom Arm-based N1X CPU designed alongside MediaTek. The chip also includes up to 128GB of unified memory, bringing a design philosophy similar to Apple’s Silicon architecture to the Windows ecosystem.
According to Nvidia, the company plans to launch more than 30 laptop models and 10 desktop systems powered by the new processor. Initial devices will target creators, AI developers, and gamers seeking high-performance systems in thin and lightweight form factors.
Among the first products expected to use the platform is Microsoft’s next-generation Surface Laptop, which is reportedly being positioned as the company’s strongest competitor yet to Apple’s MacBook Pro lineup. The device is expected to feature a 15-inch Mini-LED display, expanded connectivity options, and up to one petaflop of local AI compute performance, enabling advanced AI models to run directly on the device.
The launch represents Nvidia’s most significant expansion beyond graphics processors and AI accelerators. While the company built its dominance through GPUs powering AI training and inference, it now sees CPUs as a critical component of future AI workloads. Nvidia executives have argued that CPUs are increasingly becoming bottlenecks as AI systems evolve toward agentic workflows that require constant coordination between models, applications, and data sources.
The RTX Spark chip will be manufactured using Taiwan Semiconductor Manufacturing Company’s advanced 3-nanometer process technology and is expected to arrive in commercial products later this year.
A New Challenge to Apple and Intel
The introduction of RTX Spark intensifies competition in a PC market already undergoing a major architectural shift. Apple’s success with its M-series processors demonstrated that Arm-based chips could outperform traditional x86 systems while delivering superior power efficiency and battery life.
Microsoft has spent several years encouraging hardware partners to adopt Arm-based designs as part of its effort to modernize Windows computing. Nvidia’s entry gives that strategy a powerful new ally and introduces CUDA support directly into AI-focused Windows PCs, potentially making the platform more attractive to developers and researchers.
The move also increases pressure on Intel and AMD, whose x86 processors have dominated personal computing for decades. As AI becomes a core feature of modern operating systems, processor vendors are increasingly competing not only on raw performance but also on AI acceleration and energy efficiency.
The AI PC Strategy
Nvidia’s PC push is part of a broader effort to build infrastructure across every layer of the AI stack, from data centers to personal devices. The company recently expanded into networking, CPUs, photonics, and enterprise AI software while maintaining its leadership in GPU computing.
At Computex, Huang also confirmed that Nvidia’s Vera CPU for AI data centers has entered full production. The processor is designed to support large-scale AI factories and is already being adopted by customers including Anthropic, OpenAI, xAI, Oracle, Dell, and CoreWeave.
By bringing its CPU and GPU technologies together in a unified architecture, Nvidia is positioning itself to benefit from the next phase of AI adoption, where powerful models increasingly run not only in cloud infrastructure but also directly on laptops, desktops, and edge devices. The strategy extends beyond processors. Just recently, Nvidia has committed at least $6.5 billion to photonics companies developing optical networking technologies that could improve data transfer speeds and reduce energy consumption across future AI systems. The launch of RTX Spark signals that the battle for AI computing is expanding beyond the data center and into the devices people use every day.
