If you’re looking for your personal AI supercomputer, Nvidia has you covered.

The chipmaker announced at CES that it will launch a personal AI supercomputer called Project Digits in May. At the heart of Project Digits is the new GB10 Grace Blackwell superchip, which provides enough computing power to run sophisticated AI models while being compact enough to fit on a desk and run from a standard power outlet (for this type of computing power much greater computing power was previously required). , more power hungry systems). This desktop system can process AI models with up to 200 billion parameters and has a starting price of $3,000. The product itself closely resembles a Mac Mini.

“AI will become mainstream in every application and in every industry. “With Project Digits, the Grace Blackwell superchip comes to millions of developers,” Nvidia CEO Jensen Huang said in a press release. “Putting an AI supercomputer on the desk of every data scientist, AI researcher and student will enable them to get involved and help shape the age of AI.”

Each Project Digits system comes with 128GB of unified, coherent storage (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 Digits systems can be linked together to process models with up to 405 billion parameters (Meta’s best model, Llama 3.1, has 405 billion parameters).

The GB10 chip delivers up to 1 petaflop of AI performance (meaning it can perform 1 quadrillion AI calculations per second) with FP4 precision (which helps make calculations faster through approximations), and the system features via Nvidia’s latest generation CUDA cores and fifth generation Tensor cores, connected via NVLink-C2C to a Grace CPU with 20 energy-efficient Arm-based cores. MediaTek, known for its Arm-based chip designs, helped develop the GB10 to optimize its power efficiency and performance.

Users also gain access to Nvidia’s AI software library, including development kits, orchestration tools, and pre-trained models available in the Nvidia NGC catalog. The system runs on the Linux-based Nvidia DGX operating system and supports popular frameworks such as PyTorch, Python and Jupyter notebooks. Developers can refine models with the Nvidia NeMo framework and accelerate data science workflows with Nvidia RAPIDS libraries.

Users can develop and test their AI models locally on Project Digits, 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 number of similar devices in the same accessible style – in December, the company announced a $249 version of its Jetson computer for AI applications, aimed at hobbyists and startups, called the Jetson Orin Nano Super (he processes models with up to 8 billion parameters). .