Everything you want to know about Nvidia’s Project Digits AI Supercomputer

At CES 2025, Nvidia announced its first personal AI supercomputer, Project Digits. The rise of generative artificial intelligence 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 handle the lifecycle of generative AI models. From inference to fine-tuning to evolving agents, Digits has everything you need to build an end-to-end generative AI solution.

Here is an in-depth analysis of Project Figures:

With a price starting at $3000, the Nvidia Project Digits is a compact device powered by the innovative Nvidia GB10 Grace Blackwell Superchip. It empowers developers to prototype, tune and run massive AI models locally. This accessibility marks an important step towards democratizing AI training, making it more accessible to individuals and smaller organizations.

Independent software vendors can use Digits as an appliance to run their own AI-powered software hosted at a customer location. This reduces reliance on the cloud and provides unmatched privacy, confidentiality and compliance.

Hardware Features: AI Powerhouse on 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 CPUs are interconnected using NVLink-C2C technology, a high-speed, chip-to-chip interface that facilitates fast data transfer between the GPU and CPU. Think of it as a highway connecting two bustling cities, allowing smooth and efficient communication. This tight integration is central to Digits’ impressive performance, enabling it to handle complex AI tasks quickly and efficiently.

Here’s a rundown of key specs:

• Blackwell GPU: Includes fifth-generation CUDA cores and tensor cores for accelerating AI calculations.
• Nvidia Grace CPU: Features 20 power-efficient wing cores that complement the GPU for balanced AI workloads.
• NVLink-C2C connection: Provides a high-bandwidth, low-latency connection between the GPU and CPU for efficient data transfer.
• 128 GB of unified memory: Shared memory pool for CPU and GPU, eliminating data duplication and speeding up processing.
• High-speed NVMe storage: Provides quick access to data for AI model training and execution.
• 1 petaflop of AI performance: Handles complex AI tasks and large AI models.
• Energy efficient design: Works using a standard wall outlet.

Digits also boasts an impressive unified memory of 128GB. This means that the CPU and GPU share the same pool of memory, eliminating the need to copy data back and forth and significantly speeding up processing. This is particularly useful for AI workloads, which often involve large datasets and complex calculations. Digits includes high-speed NVMe storage to further improve performance, ensuring fast access to data required for AI model training and execution.

Despite its impressive performance capabilities, Digits is designed with energy efficiency in mind. Unlike traditional supercomputers that often require specialized power and cooling infrastructure, Digits can operate using a standard wall outlet. This makes it a practical and affordable solution for individuals and smaller teams that 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 integrate seamlessly into Nvidia’s extensive AI ecosystem, providing developers with a cohesive and efficient environment for AI development. Based on the Linux-based Nvidia DGX operating system, it provides a stable and powerful platform tailored for high-performance computing tasks. Preloaded with Nvidia’s comprehensive AI software stack, including the Nvidia AI Enterprise software platform, Project Digits provides instant access to a wide range of popular 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, empowers developers to use familiar environments for model development and experimentation. In addition, it supports the Nvidia NeMo framework, which enables the tuning of large language models, and the RAPIDS libraries, which accelerate data science workflows.

In terms of connectivity and scalability, Project Digits uses the Nvidia ConnectX network, enabling high-speed data transfer and efficient communication between systems. This feature allows two Project Digits units to be interconnected, effectively doubling the capacity to handle models with up to 405 billion parameters. This scalability ensures that as complex AI models grow, Project Digits can adapt to meet increasing computational demands.

Additionally, Project Digits is designed to seamlessly integrate cloud and data center infrastructures. Thanks to consistent architecture and software platforms across Nvidia’s ecosystem, developers can prototype and fine-tune AI models locally on devices and then deploy them to larger-scale environments without compatibility issues. This flexibility simplifies the transition from development to production, increasing efficiency and reducing time to deployment.

Nvidia Project Digits comes with the following suite of software:

• Nvidia DGX OS based on Linux: It runs on a robust, Linux-based operating system optimized for AI workloads, ensuring stability and performance.
• Pre-installed Nvidia AI software stack: Provides instant access to Nvidia’s extensive AI tools and frameworks, simplifying the development process.
• Nvidia AI Enterprise: It offers a range of AI and data analytics software, providing enterprise-grade support and security for AI workflows.
• Nvidia NGC catalog: It provides a rich repository of software development kits, frameworks and pre-trained models, facilitating efficient AI model development and deployment.
• Nvidia NeMo framework: It enables the arrangement 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 within familiar environments.

With its AI performance and integrated software suite, Project Digits can handle massive AI models with 200 billion parameters. This capability was previously limited to large-scale supercomputers, but Digits brings this power to the desktop, enabling developers to experiment and deploy more advanced 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 MediaTek, a leading semiconductor company without fab, in designing an energy-efficient CPU specifically for Digits. This partnership allowed Nvidia to leverage MediaTek’s expertise in low-power CPU design, contributing to Digits’ impressive power efficiency.

Huang also highlighted how Digits bridges the gap between Linux and Windows environments. While Digits itself runs on a Linux-based operating system, it is designed to integrate seamlessly with Windows PCs through the Windows Subsystem for Linux technology. This allows developers working primarily in Windows environments to easily leverage 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 empowers these users to prototype, tune, and run AI models on-premises, 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 desktop, Digits addresses the growing need for greater AI performance in a compact and accessible form factor. This allows individuals and smaller 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 wide and varied. Developers can use it to prototype new AI applications, tailor LLMs for specific tasks, generate AI-powered content, and research new AI algorithms and architectures. The ability to run large AI models locally opens up new opportunities for AI development, enabling faster iteration 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, further contributing to the democratization of AI development.

CONCLUSION

Nvidia Digits represents a significant step forward in AI technology. Combining a 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 smaller organizations. The ability to run large AI models locally and the flexibility to deploy in the cloud or in the 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 emerging from this powerful new platform.