Nvidia Unveils Project Denver, A Personal AI Supercomputer

At the 2025 Consumer Electronics Show (CES) in Las Vegas, Nvidia made a groundbreaking announcement that is set to revolutionize the field of artificial intelligence. The company unveiled Project Digits, a compact personal AI supercomputer that provides access to its advanced Grace Blackwell hardware platform.

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What is Project Digits?

Project Digits is designed for AI researchers, data scientists, and students who need a powerful computing platform on their desks. It packs Nvidia’s new GB10 Grace Blackwell Superchip, which delivers up to a petaflop of computing performance for prototyping, fine-tuning, and running AI models.

Key Features of Project Digits

Cloud Computing Platform: Project Digits is a cloud computing platform that sits on your desk, providing access to Nvidia’s advanced hardware and software stack.
Workstation Capability: With its high-performance computing capabilities, Project Digits can be used as a workstation for demanding tasks such as AI model development and training.
GB10 Grace Blackwell Superchip: The GB10 features an Nvidia Blackwell GPU connected to a 20-core Nvidia Grace CPU, providing up to a petaflop of computing performance.
128GB Memory Pool: Project Digits comes with a 128GB pool of memory for efficient data processing and storage.
4TB Flash Storage: The device also features up to 4TB of flash storage for storing large datasets and models.

How Does Project Digits Work?

Project Digits can run standalone or connect to a primary Windows or Mac PC, providing users with flexibility in their workflow. According to Nvidia, two Project Digits machines can be linked together to run up to 405-billion-parameter models if needed.

Pricing and Availability

Project Digits machines will be available starting in May from top partners for $3,000 each. While this may seem like a steep price point, Nvidia CEO Jensen Huang believes that there is a market for this product. "With Project Digits, the Grace Blackwell Superchip comes to millions of developers," he said in a statement. "Placing an AI supercomputer on the desks of every data scientist, AI researcher and student empowers them to engage and shape the age of AI."

Benefits of Project Digits

Project Digits offers several benefits for AI researchers, data scientists, and students:

Increased Productivity: With its high-performance computing capabilities, Project Digits can significantly boost productivity in tasks such as model development, fine-tuning, and training.
Improved Accuracy: By running large-scale AI models with ease, users can achieve higher accuracy and better results in their projects.
Enhanced Collaboration: Project Digits enables seamless collaboration among team members by providing a shared computing platform that can be accessed remotely.

Conclusion

Nvidia’s Project Digits is a groundbreaking innovation that brings advanced AI capabilities to the desktop. Its compact form factor, high-performance computing power, and flexibility make it an attractive option for AI researchers, data scientists, and students who need to run demanding tasks on their desks. While its price point may be steep, Nvidia believes that there is a market for this product, which can empower millions of developers to engage in the age of AI.

Frequently Asked Questions (FAQs)

Q: What is Project Digits?

A: Project Digits is a personal AI supercomputer developed by Nvidia that provides access to its advanced Grace Blackwell hardware platform.

Q: Who is Project Digits designed for?

A: Project Digits is designed for AI researchers, data scientists, and students who need a powerful computing platform on their desks.

Q: What are the key features of Project Digits?

A: Project Digits features a cloud computing platform, workstation capability, GB10 Grace Blackwell Superchip, 128GB memory pool, and up to 4TB flash storage.

Q: How does Project Digits work?

A: Project Digits can run standalone or connect to a primary Windows or Mac PC, providing users with flexibility in their workflow. Two machines can be linked together to run up to 405-billion-parameter models if needed.