Nvidia announced that Taiwan’s system manufacturers are set to build Nvidia DGX Spark and DGX Station systems. Growing partnerships with Acer, Gigabyte and MSI will extend the availability of DGX Spark and DGX Station personal AI supercomputers. Powered by the Nvidia Grace Blackwell platform, DGX Spark and DGX Station will enable developers to prototype, fine-tune and inference models from the desktop to the data center. DGX Spark is equipped with the Nvidia GB10 Grace Blackwell Superchip and fifth-generation Tensor Cores. It delivers up to 1 petaflop of AI compute and 128GB of unified memory, and enables seamless exporting of models to Nvidia DGX Cloud or any accelerated cloud or data center infrastructure. Built for the most demanding AI workloads, DGX Station features the Nvidia GB300 Grace Blackwell Ultra Desktop Superchip, which offers up to 20 petaflops of AI performance and 784GB of unified system memory. The system also includes the Nvidia ConnectX-8 SuperNIC, supporting networking speeds of up to 800Gb/s for high-speed connectivity and multi-station scaling. DGX Station can serve as an individual desktop for one user running advanced AI models using local data, or as an on-demand, centralized compute node for multiple users. The system supports Nvidia Multi-Instance GPU technology to partition into as many as seven instances — each with its own high-bandwidth memory, cache and compute cores — serving as a personal cloud for data science and AI development teams. To give developers a familiar user experience, DGX Spark and DGX Station mirror the software architecture that powers industrial-strength AI factories. Both systems use the Nvidia DGX operating system, preconfigured with the latest Nvidia AI software stack, and include access to Nvidia NIM microservices and Nvidia Blueprints. Developers can use common tools, such as PyTorch, Jupyter and Ollama, to prototype, fine-tune and perform inference on DGX Spark and seamlessly deploy to DGX Cloud or any accelerated data center or cloud infrastructure.