If you were looking for your own personal AI supercomputer, Nvidia has you covered.
chip maker announced at ces It is launching a personal AI supercomputer called Project Digits in May. The heart of Project Digits is the new GB10 Grace Blackwell Superchip, which packs enough processing power to run sophisticated AI models, while being compact enough to fit on a desk and run from a standard power outlet (this kind of processing Power is used for very large requirements), systems that consume more power). This desktop-sized system can handle AI models with up to 200 billion parameters, and has a starting price of $3,000. The product itself looks Much like the Mac Mini,
“AI will be mainstream in every application for every industry. With Project Digits, the Grace Blackwell Superchip comes closer to millions of developers,” said Jensen Huang, Nvidia CEO, in a press release. “Putting an AI supercomputer on the desk of every data scientist, AI researcher, and student helps them engage and shape the era of AI.”
Each Project Digit system comes equipped with 128GB of integrated, coherent memory (by comparison, a good laptop might have 16GB or 32GB of RAM) and up to 4TB of NVMe storage. For even more demanding applications, two Project Digit systems can be linked together to handle models with up to 405 billion parameters (Meta's best model, Llama 3.1). There are 405 billion parameters,
The GB10 chip offers 1 petaflop AI performance (meaning it can perform up to 1 quadrillion AI calculations per second) at FP4 precision (which helps speed up calculations by inference), and the system features Nvidia's latest generation of CUDA cores and fifth-generation Tensor cores, connected via NVLink-C2C to a Grace CPU with 20 power-efficient Arm-based cores. MediaTek, known for its Arm-based chip designs, collaborated in the development of the GB10 to optimize its power efficiency and performance.
Users will also get access to Nvidia's AI software library, which includes development kits, orchestration tools, and pre-trained models available through the Nvidia NGC Catalog. The system runs on Linux-based Nvidia DGX OS and supports popular frameworks like PyTorch, Python, and Jupyter Notebook. Developers can fine-tune models using the NVIDIA NEMO framework and accelerate data science workflows with NVIDIA RAPIDS libraries.
Users can develop and test their AI models locally on Project Digit, then deploy them to cloud services or data center infrastructure using the same Grace Blackwell architecture and Nvidia AI enterprise software platform.
Nvidia offers a range of similar devices accessibility Style – In December, it announced a $249 version of its Jetson computer for AI applications, targeting hobbyists and startups, called the Jetson Orin Nano Super (this model handles up to 8 billion parameters,