Cryptopolitan
2026-09-04 02:23:56

Nvidia's N1X chip ships in two configurations starting in October

Nvidia will start selling RTX Spark systems based on its N1X chip in October. This will bring a compact AI PC to Windows users and the hardware makers that build for them. The launch takes Nvidia’s desktop AI expansion to consumer laptops, with Acer and Lenovo already lining up machines. Nvidia pairs up to 6,144 CUDA cores with 20 CPU cores The N1X will be available in two versions. The higher-end version pairs a 20-core CPU with 6,144 CUDA cores and 24GB to 128GB of unified memory, while the other pairs an 18-core CPU with 5,120 CUDA cores and 24GB to 32GB of unified memory. Unified memory means the pool is shared by the CPU and GPU. This is valuable when a machine has to load large AI models locally. CUDA core and CPU core specs from Nvidia’s own RTX Spark product page. Nvidia’s own product page describes the lineup as “the fusion of NVIDIA AI and RTX graphics in slim laptops and small desktops” for “creators, developers, and gamers.” The company is targeting notebooks and small desktops. Acer and Lenovo announced new Spark systems at IFA, the Berlin electronics trade show, heralding that partner hardware will come with the chip. GB10 Grace Blackwell chip is for developers Last year, Nvidia brought out the DGX Spark , which it claimed was the world’s smallest AI supercomputer. The machine is powered by the GB10 Grace Blackwell Superchip, delivers up to 1 petaflop of AI performance with 128GB of unified CPU-GPU memory, and boots up Nvidia’s Linux-based DGX OS. The DGX Spark was designed for developers. Users can run inference on models with up to 200 billion parameters and fine-tune models up to 70 billion parameters locally with the system, Nvidia said. Two units linked together can manage models as large as 405 billion parameters, Nvidia said. The RTX Spark, on the other hand, is made for Windows users and everyday AI-accelerated work. The fact that both products can hold up to 128GB of memory shows that they are from the same design family but are made for different customers. The smartest crypto minds already read our newsletter. Want in? Join them .

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