Project DIGITS

Project DIGITS is NVIDIA’s compact AI supercomputer for local model development, testing, and experimentation. If the name sounds unfamiliar, that is because Project DIGITS launched under that name and is now available as NVIDIA DGX Spark.

Instead of being a typical web app, this is a desktop AI system built for people who want serious local AI performance. It is designed for developers, researchers, data scientists, students, and technical teams that need to prototype, fine-tune, and run large AI models without depending entirely on the cloud.

What is Project DIGITS?

Project DIGITS, now branded as NVIDIA DGX Spark, is a small-form-factor AI workstation powered by the NVIDIA GB10 Grace Blackwell Superchip. NVIDIA describes it as a personal AI supercomputer built to bring advanced AI development to the desktop.

It comes with NVIDIA’s AI software stack preinstalled and gives users a way to build and test AI applications locally, then move those workloads to cloud or data center environments when needed. That makes it especially useful for teams that want faster iteration, more control over data, and a smoother path from prototype to production.

Who makes Project DIGITS?

Project DIGITS is developed by NVIDIA, the company behind many of the GPUs, AI platforms, and accelerated computing systems used across the AI industry. The product is part of NVIDIA’s broader DGX lineup, which focuses on high-performance AI development systems.

Main features

One of the biggest highlights is its desktop-friendly design. DGX Spark is compact, but it delivers up to 1 petaFLOP of FP4 AI performance, which is far beyond what most standard desktop systems offer for local AI work.

It includes 128 GB of coherent unified system memory and up to 4 TB of NVMe storage. According to NVIDIA, this allows users to run inference on models up to 200 billion parameters and fine-tune models up to 70 billion parameters on the device itself.

Another major advantage is the preinstalled NVIDIA AI software stack. Users can work with tools and frameworks from the NVIDIA ecosystem, including support for common AI workflows, Jupyter notebooks, PyTorch, NVIDIA NeMo, RAPIDS, NIM microservices, and other developer resources.

The system also supports scaling. Two DGX Spark systems can be linked with NVIDIA ConnectX networking to work with even larger models, up to 405 billion parameters.

What can you use it for?

Project DIGITS is aimed at technical AI work rather than casual content creation. Common use cases include building and testing local AI agents, fine-tuning open models on private or domain-specific data, running inference on large language models, accelerating machine learning and data science workflows, and developing edge AI applications for robotics, vision, and smart systems.

It can also be a strong fit for universities, research labs, startups, and enterprise teams that want local experimentation before deploying to larger infrastructure.

Who should use Project DIGITS?

This tool is best for AI developers, ML engineers, researchers, data scientists, advanced students, and technical teams that need high-performance local AI computing. It is not really built for beginners looking for a simple no-code AI tool.

If you mainly want to generate text, images, or video through a browser, this is probably more power than you need. But if you want to build, test, customize, and deploy AI systems with more control, it can be a very compelling option.

How to use Project DIGITS

The first step is to get the hardware through NVIDIA or one of its authorized partners. Since the product is now sold as DGX Spark, that is the name you will usually see on the official product page and reseller listings.

Once you have the system, set it up like a desktop workstation using its available ports, networking, and display connections. It runs NVIDIA DGX OS and includes the NVIDIA AI software stack, so the environment is designed to be ready for AI development out of the box.

From there, the typical workflow is straightforward. Start by choosing your framework or toolkit, such as PyTorch, Jupyter notebooks, RAPIDS, or NVIDIA NeMo. Then load or connect the model you want to test, prepare your data, and begin prototyping, inference, or fine-tuning locally.

After validating your workflow, you can scale or deploy using compatible NVIDIA cloud or data center infrastructure. This is one of the product’s biggest strengths: you can develop locally and then move to larger environments without rebuilding everything from scratch.

Pricing

Project DIGITS was initially announced with pricing starting at $3,000. Because it is now sold as NVIDIA DGX Spark and available through NVIDIA and partners, real-world pricing can vary by seller, region, configuration, and bundled support.

There is no free plan, and this is not a freemium tool. It is a paid hardware product. Some enterprise-related software and support options may also be offered separately depending on the setup.

Free plan or trial

No free plan is available. Since this is a physical AI workstation rather than a SaaS platform, access requires purchasing the device through NVIDIA or an authorized channel partner.

Supported platforms

Project DIGITS is a physical desktop system rather than a browser-based tool. It runs on NVIDIA DGX OS and is designed as a local AI workstation. Users interact with it through the included software stack, developer tools, and supported AI frameworks.

Integrations and ecosystem

Its biggest integration strength is the NVIDIA ecosystem. It supports NVIDIA AI software, NGC resources, NVIDIA NeMo, RAPIDS, NVIDIA NIM, Jupyter workflows, PyTorch-based development, and paths to cloud or data center deployment. For teams already working with NVIDIA infrastructure, this can make adoption much easier.

Why Project DIGITS stands out

What makes Project DIGITS interesting is that it brings powerful local AI development into a much smaller and more accessible desktop format. It gives developers more privacy, lower cloud dependence, faster experimentation, and a direct path to production-grade NVIDIA environments.

For the right user, it is less about being a simple AI tool and more about owning a serious local AI lab on your desk.

Final thoughts

Project DIGITS, now NVIDIA DGX Spark, is a specialized but exciting option for anyone doing advanced AI development. It is built for people who want to prototype, fine-tune, and run large models locally while staying connected to the broader NVIDIA AI ecosystem.

If you are an AI developer, researcher, or data scientist looking for a compact high-performance system for local AI work, Project DIGITS is worth a close look. Just keep in mind that this is a premium hardware platform, so it makes the most sense for users who truly need workstation-level AI power.