Nvidia unveils $3,000 desktop AI computer for home researchers

Project DIGITS can run a local chatbot or other AI models up to 200B parameters in size.

On Monday, Nvidia announced Project DIGITS, a small desktop computer aimed at researchers, data scientists, and students who want to experiment with AI models—such as chatbots like ChatGPT and image generators—at home. The $3,000 device, which contains Nvidia's new GB10 Grace Blackwell Superchip, debuted at CES 2025 in Las Vegas. It will launch in May and can operate as a standalone PC or connect to a Windows or Mac machine.

At CES on Monday, Nvidia CEO Jensen Huang described the new system as "a cloud computing platform that sits on your desk." The company also designed Project DIGITS as a bridge between desktop development and cloud deployment. Developers can create and test AI applications locally on Project DIGITS, then move them to cloud services or data centers that use similar Nvidia hardware.

The GB10 chip inside the Project DIGITS computer combines an Nvidia Blackwell GPU with a 20-core Grace CPU based on Arm architecture. Nvidia developed the chip in partnership with MediaTek, and it connects to 128GB of memory and up to 4TB of storage inside the Project DIGITS enclosure.

Running AI models locally

Currently, many people use AI models that must run on remote data centers due to their computational requirements. Over time, there has been a movement to slim down some AI models so they can run effectively on local, personally owned hardware. Project DIGITS can provide some of that capability at home.

A single Project DIGITS unit can reportedly run AI models with up to 200 billion parameters, while two linked units can handle models with 405 billion parameters. In AI models, parameter count roughly corresponds to an AI model's neural network size and complexity, with more parameters requiring more memory and computational power to run. Also, parameter size approximates AI model capability, though different-sized AI models perform differently depending on how they were trained and architected.

Some smaller open-weights AI language models (such as Llama 3.1 70B, with 70 billion parameters) and various AI image-synthesis models like Flux.1 dev (12 billion parameters) could probably run comfortably on Project DIGITS, but larger open models like Llama 3.1 405B, with 405 billion parameters, may not. Given the recent explosion of smaller AI models, a creative developer could likely run quite a few interesting models on the unit.

DIGITS' 128GB of unified RAM is notable because a high-power consumer GPU like the RTX 4090 has only 24GB of VRAM. Memory serves as a hard limit on AI model parameter size, and more memory makes room for running larger local AI models.

The system runs on Nvidia's Linux-based DGX OS operating system and includes access to Nvidia's AI software tools, such as the NeMo framework (which aids AI model development) and RAPIDS libraries (used by developers to create AI applications). Users can also run common AI development tools like PyTorch, Python, and Jupyter notebooks.

How does Project DIGITS stack up to other local AI options? NVIDIA says its new computer starts at $3,000, which means a fully maxed-out unit could cost considerably more. In a news release from October, Apple wrote that a Mac with an M4 Max chip can feature up to 128GB of unified memory and potentially run AI models up to 200 billion parameters in size, similar to the Project DIGITS computer.

Right now, a MacBook Pro with an M4 Max and 128GB of unified memory sells for about $4,699 in the US, making DIGITS potentially comparable in price and AI capability, though the true differences in AI performance would have to be revealed in lab testing.

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