Nvidia RTX Spark N1X Brings 128GB Unified Memory to October Arm PCs

As of Friday, September 4, 2026, Nvidia has put a much clearer shape around RTX Spark N1X, its Arm-based platform for upcoming Windows 11 laptops and compact desktops. The timing matters: Nvidia says RTX Spark Windows PCs are coming in October 2026, so this is still a launch-window preview rather than a retail availability story. The more interesting angle is what Nvidia is trying to change. Windows-on-Arm PCs have usually been framed around efficiency, thin designs and battery life, while RTX Spark N1X brings the conversation closer to local AI models, CUDA workflows, creator apps and RTX gaming features. Nvidia’s own RTX Spark page lists up to a 6,144-core Blackwell RTX GPU, up to a 20-core Grace CPU, up to 1 petaflop of FP4 AI performance and up to 128GB of unified memory. (blogs.nvidia.com)

The laptop version of RTX Spark N1X is listed in two main configurations. The higher-end option pairs a 6,144-core Nvidia Blackwell RTX GPU with a 20-core Nvidia Grace CPU, unified LPDDR5X memory up to 128GB, Windows 11 support and a configurable 45W to 80W TDP range. Nvidia also lists a second laptop configuration with a 5,120-core Blackwell RTX GPU, an 18-core Grace CPU, unified LPDDR5X memory up to 64GB and the same 45W to 80W laptop power range. For small desktops, Nvidia lists the 6,144-core GPU and 20-core CPU configuration with up to 128GB LPDDR5X and a 140W TDP. The platform also includes fourth-generation ray tracing cores, fifth-generation Tensor Cores, DLSS 5, Reflex 2, DirectX 12 Ultimate, Vulkan RT, OpenGL 4.6, PCIe Gen 5 support, 1x ninth-generation Nvidia encoder and 1x sixth-generation Nvidia decoder. (nvidia.com)

View NVIDIA DGX Spark Personal AI Desktop Supercomputer on partner website

The standout spec is not just the GPU core count; it is the memory model. A laptop with up to 128GB of unified LPDDR5X memory gives the CPU and integrated RTX GPU access to a shared memory pool instead of splitting system RAM and discrete GPU VRAM in the usual way. That does not automatically make every workload faster, and real performance will depend on the laptop design, power limits, cooling and software support. Still, it opens a practical path for heavier local AI work, larger creative projects and memory-hungry development tasks on a portable PC. Nvidia is positioning RTX Spark for local agents, AI development, video and 3D workflows, with CUDA running natively on the platform and support for RTX creator and gaming technologies. (nvidia.com)

See MacBook Pro M5 price as another high-memory creator laptop option

Lenovo has already announced two Yoga systems built around RTX Spark. The Lenovo Yoga Pro 9n (15-inch, 11) is the memory-led model, with up to 128GB of 9400 MT/s unified LPDDR5X memory, a 15.3-inch 2.5K PureSight Pro OLED display, up to 165Hz variable refresh rate, a 92.5Wh battery, Wi-Fi 7, Bluetooth 5.4, up to 4TB total storage, a 9.2MP MIPI IR camera and an 80W TDP design. The Lenovo Yoga 9n 2-in-1 (16-inch, 11) brings the platform to a convertible body, with up to 64GB of 9400 MT/s unified memory, a 16-inch 2.8K PureSight Pro OLED display, up to 120Hz variable refresh rate, a 99.9Wh battery, Wi-Fi 7, Bluetooth 5.4 and dual-surface pen input across the OLED display and haptic Force Pad. Lenovo has not announced final pricing or availability for those two laptops yet. (news.lenovo.com)

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Acer has shown an Acer SFF RTX Spark compact desktop design with up to a 6,144-core Blackwell RTX GPU, up to a 20-core Grace CPU, up to 1 petaflop of AI compute and up to 128GB of unified memory, but Acer says availability will be announced later. That is a useful reminder for the whole RTX Spark N1X story: the specs are now concrete, but shipping dates, prices, sustained performance, fan noise and battery life still need to be tested on finished systems. If the October rollout stays on track, RTX Spark N1X could become one of the more serious challengers in premium Arm PCs, sitting in a field that already includes Intel, AMD, Qualcomm and Apple approaches to AI-ready notebooks. For now, its biggest promise is simple: bring more local AI and RTX capability into thinner Windows machines without relying on a traditional discrete GPU memory setup. (news.acer.com)

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