Beyond the Cloud: Nvidia’s Mini Supercomputer Brings AI on-Premise

Nvidia’s new mini artificial intelligence supercomputer has the potential to put unprecedented computing power into the hands of researchers, developers and academics.

However, experts say it can also be an enabler for business innovation, especially for those in heavily regulated industries who want to own their own AI systems for security purposes.

Project Digits is the personal supercomputer with Nvidia’s new GB10 Grace Blackwell Superchip, combining a GPU and CPU. It delivers a petaflop of AI computing power, or 1 quadrillion calculations per second, and can run AI models with up to 200 billion parameters.

With a $3,000 price tag, Project Digits represents a fundamental shift in AI development. By bringing supercomputer-grade AI capabilities to individuals at a relatively affordable price, Nvidia is betting that the next breakthrough in AI might come not from a massive research lab but from an office cubicle, a student’s dorm room or a researcher’s home office.

Bringing AI Innovation to Businesses

“Nvidia’s Project Digits represents a major leap forward in democratizing AI capabilities,” DeepBrain AI Chief Financial Officer Michael Jung told PYMNTS in an interview. “The compact form factor and immense computational power make it a game changer, not just for researchers, but also for businesses.”

“For businesses, this means the ability to develop advanced AI models without needing access to traditional supercomputing resources,” he added. “It lowers the barrier to entry for small and medium enterprises looking to integrate AI-driven insights into their operations.”

The mini supercomputer “has the potential to broaden AI innovation across industries, allowing organizations of all sizes to harness the power of generative AI to improve efficiency, create more personalized customer experiences, and stay competitive in the digital economy,” he said.

Each mini supercomputer comes equipped with 128GB of unified memory and can be expanded. For those needing even more power, two units can be linked together to handle models with up to 405 billion parameters. It also uses a standard wall electrical outlet. Nvidia said it has balanced performance with power efficiency in this innovation.

Project Digits is part of a trend in organizations building, deploying and owning their own AI systems, AI Squared co-founder Jacob Renn told PYMNTS in an interview.

“While proprietary models serve many customers well, organizations with stringent compliance and security requirements often face barriers to their adoption,” Renn said. “Project Digits addresses this gap by enabling businesses to train and deploy advanced AI systems outside the cloud, even in fully disconnected environments.”

Hitachi Vantara Chief Technology Officer for AI Jason Hardy told PYMNTS in an interview that while he would not go so far as to call it a game changer, Project Digits is a “significant enabling event” for business.

“Accessibility of this technology — specifically GPUs — has always been limited due to cost, infrastructure scale and power demand,” he said. But now, Nvidia is making this technology more accessible to the masses.

“It’s important to note that this won’t replace the need for data center or large-scale compute environments; however, it will enable the further development of new and creative ideas that can utilize GPU resources,” Hardy said.

Making AI Easy to Use

The supercomputer can bridge the gap between personal development and enterprise deployment. Developers can prototype and fine-tune their AI models locally, then deploy them to cloud or data center infrastructure. Smaller companies can now prototype AI solutions without massive cloud computing budgets. Academic researchers can run sophisticated models without waiting for shared computing resources. Students can learn by experimenting with state-of-the-art AI models on their own machines.

Online Games CEO Marin Christian Ovidiu told PYMNTS in an interview that Project Digits makes “powerful AI easy to use and cheaper. Small businesses can train and use AI models without big data centers or high costs. For example, in games, we can make smarter characters and better worlds faster.”

Project Digits also uses less power, which helps the planet since AI is notorious for being a power guzzler, he said.

The system, which ships in May, comes with access to Nvidia’s extensive AI software ecosystem, including development tools, frameworks and pre-trained models. Developers can use familiar tools like PyTorch and Jupyter notebooks, accelerate their data science work with Nvidia Rapids libraries and fine-tune models using the Nvidia NeMo framework.

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