Everything You Want To Know About Nvidia Project Digits AI Supercomputer

At CES 2025, Nvidia announcement its first personal AI supercomputer, Project Digits. The rise of generative AI requires access to a new generation of CPUs and GPUs for data scientists and AI engineers working on cutting-edge models and solutions. Digits is aimed at developers and data scientists looking for an affordable and accessible hardware and software platform to manage the lifecycle of generative AI models. From inference to fine-tuning to agent development, Digits has everything it takes to create an end-to-end generative AI solution.

Here is an in-depth analysis of Project Digits:

With pricing starting at $3,000, Nvidia Project Digits is a compact device driven by the innovative Nvidia GB10 Grace Blackwell superchip. It allows developers to prototype, refine, and run massive AI models locally. This accessibility marks an important step toward democratizing AI training, making it more accessible to individuals and small organizations.

Independent software vendors can use Digits as an appliance to run their AI-based software deployed at a customer’s site. This reduces reliance on the cloud and provides unparalleled privacy, confidentiality and compliance.

Hardware specs: an AI powerhouse on the desktop

At the heart of Digits is the Nvidia GB10 Grace Blackwell superchip, an engineering marvel that combines a powerful Blackwell GPU with a 20-core Grace CPU. These two powerhouses are interconnected using NVLink-C2C technology, a high-speed chip-to-chip interconnect that facilitates rapid data transfer between the GPU and CPU. Think of it as a highway connecting two bustling cities, allowing for seamless and efficient communication. This tight integration is crucial to Digits’ impressive performance, allowing it to handle complex AI tasks quickly and efficiently.

Here’s a look at the key specs:

• Blackwell GPU: Features fifth-generation CUDA cores and Tensor cores to accelerate AI calculations.
• Nvidia Grace processor: Includes 20 power-efficient Arm cores complementing the GPU for balanced AI workloads.
• NVLink-C2C interconnection: Provides a high-bandwidth, low-latency connection between GPU and CPU for efficient data transfer.
• 128 GB of unified memory: Shared memory pool for CPU and GPU, eliminating data copying and speeding up processing.
• High-speed NVMe storage: Ensures rapid access to data for training and running AI models.
• 1 petaflop of AI performance: Handles complex AI tasks and large AI models.
• Energy efficient design: Operates using a standard wall outlet.

Digits also has an impressive 128 GB of unified memory. This means that the CPU and GPU share the same memory pool, eliminating the need to copy data and significantly speeding up processing. This is particularly beneficial for AI workloads, which often involve large data sets and complex calculations. Digits integrates high-speed NVMe storage to further improve performance, ensuring rapid access to the data required for training and running AI models.

Despite its impressive performance capabilities, Digits is designed with energy efficiency in mind. Unlike traditional supercomputers which often require specialized power and cooling infrastructure, Digits can operate using a standard wall outlet. This makes it a practical and accessible solution for individuals and small teams who may not have access to the resources needed to run larger, more power-hungry systems.

Proven AI software stack powered by CUDA

Project Digits is designed to seamlessly integrate with Nvidia’s broad AI ecosystem, providing developers with a consistent and efficient environment for AI development. Based on Linux Nvidia DGX OS, it guarantees a stable and robust platform suitable for high-performance computing tasks. Preloaded with Nvidia’s full AI software stack, including the Nvidia AI Enterprise Software Platform, Project Digits provides immediate access to a wide range of familiar tools and frameworks essential to AI research and development.

The system’s compatibility with widely used AI frameworks and tools, such as PyTorch, Python, and Jupyter Notebooks, allows developers to use familiar environments for model development and experimentation. Additionally, it supports Nvidia NeMo Framewhich makes it possible to refine large language models, and the RAPIDS Librariesthat accelerate data science workflows.

In terms of connectivity and scalability, Project Digits employs Nvidia ConnectX networking, enabling high-speed data transfer and efficient communication between systems. This feature allows two Project Digits units to be interconnected, doubling the capacity to manage models with up to 405 billion parameters. This scalability ensures that as complex AI models develop, Project Digits can adapt to meet growing computing demands.

Additionally, Project Digits is designed to seamlessly integrate cloud and data center infrastructures. With consistent architecture and software platforms across Nvidia’s ecosystem, developers can prototype and refine AI models locally on the device, then deploy them in larger-scale environments without compatibility issues . This flexibility streamlines the transition from development to production, improving efficiency and reducing deployment times.

Nvidia Project Digits comes with the software stack below:

• Nvidia DGX operating system based on Linux: Runs on a robust Linux-based operating system optimized for AI workloads, ensuring stability and performance.
• Pre-installed Nvidia AI software stack: Provides immediate access to Nvidia’s extensive AI tools and frameworks, streamlining the development process.
• Nvidia AI Enterprise: Provides a suite of AI and data analytics software, ensuring enterprise-grade support and security for AI workflows.
• Nvidia NGC Catalog: Offers a rich repository of SDKs, frameworks and pre-trained models, facilitating the efficient development and deployment of AI models.
• Nvidia NeMo framework: Enables refinement and deployment of large language models, supporting advanced natural language processing tasks.
• Nvidia RAPIDS libraries: Accelerates data science workflows by leveraging GPU-optimized libraries for data processing and machine learning.
• Support for popular AI frameworks: Compatible with widely used tools such as PyTorch, Python and Jupyter Notebooks, allowing developers to work in familiar environments.

With its petascale AI performance and integrated software stack, Project Digits can manage massive AI models with 200 billion parameters. This capability was previously limited to large-scale supercomputers, but Digits brings this power to the desktop, allowing developers to experiment and deploy cutting-edge AI models locally.

Ecosystem Support for Project Figures

Nvidia CEO Jensen Huang shed light on the development of Digits and a key partnership that played a crucial role in its creation. He highlighted the collaboration with MediaTeka leading fabless semiconductor manufacturer, in designing an energy-efficient processor specifically for Digits. This partnership allowed Nvidia to leverage MediaTek’s expertise in low-power processor design, contributing to Digits’ impressive power efficiency.

Huang also highlighted how Digits bridges the gap between Linux and Windows environments. Although Digits itself runs on a Linux-based operating system, it is designed to integrate seamlessly with Windows PCs via the Windows Subsystem for Linux technology. This makes it easy for developers working primarily in Windows environments to use the power of Digits for their AI projects.

Target audience and use cases

Nvidia Digits is designed specifically for AI researchers, data scientists, students, and developers working with large AI models. It allows these users to prototype, refine and run AI models locally, in the cloud or within a data center, providing flexibility and control over their AI development workflows .

By bringing the power of an AI supercomputer to the office, Digits addresses the growing need for better AI performance in a compact, accessible form factor. This enables individuals and small teams to tackle complex AI challenges without relying on expensive cloud computing resources or large-scale supercomputing infrastructure.

The potential use cases for Digits are vast and varied. Developers can use it to prototype new AI applications, refine LLMs for specific tasks, generate AI-based content, and research new AI algorithms and architectures. The ability to run large AI models locally opens up new possibilities for AI development, enabling faster iterations and experimentation.

Nvidia Digits is expected to be available in May from Nvidia and its partners, with a starting price of $3,000. This competitive price makes it a viable option for a wider range of users, helping to democratize AI development.

Conclusion

Nvidia Digits represents a significant leap forward in AI technology. By combining powerful hardware, a comprehensive software stack, and a compact, energy-efficient design, Digits brings the capabilities of an AI supercomputer to the desktop. This could potentially democratize AI development, making it more accessible to individuals, researchers and small organizations. The ability to run large AI models locally and the flexibility to deploy in the cloud or data center gives developers unprecedented control and power over their AI workflows. As Digits becomes available, it will be exciting to witness the innovative applications and advancements that will emerge from this powerful new platform.