GIGABYTE Launches AI TOP Utility at CES 2026 for Secure Enterprise AI

GIGABYTE formalized its move toward practical local AI adoption at CES 2026 in Las Vegas. The showcase introduced the AI TOP ecosystem, a combination of specialized hardware and proprietary software designed specifically for the enterprise market. By enabling local execution, the company targets businesses looking for high performance without the risks of sensitive data leaving their own premises.

The core of the business value lies in the Private Brain concept powered by Retrieval Augmented Generation. Organizations can now process thousands of pages of sensitive research and development documents locally to create instant response internal knowledge bases. This capability ensures that proprietary data remains 100 percent sovereign while eliminating cloud latency and unpredictable recurring subscription costs.

Hardware solutions like the AI TOP ATOM feature a unique unified memory architecture to handle massive contexts. This compact powerhouse utilizes 128GB of memory to process datasets that would typically require expensive server rack infrastructure. For enterprises, this means high context AI tasks are now achievable on a much smaller physical footprint with significantly lower power requirements.

For more demanding applications, the flagship AI TOP 500 system integrates the latest NVIDIA GeForce RTX 5090 graphics. This high performance workstation allows teams to run models with up to 405 billion parameters with complete control. Such scalability provides a clear path for companies to grow their AI capabilities alongside their specific operational needs without external dependencies.

The proprietary AI TOP Utility software simplifies the technical hurdles of deploying AI on local Linux environments. It offers a user friendly interface that mirrors familiar cloud dashboards but executes entirely on local hardware. This reduction in technical complexity allows business teams to focus on actionable output rather than complex infrastructure management.

Transitioning to local AI provides a significant shift from operational expenses to capital investment. Businesses can avoid unpredictable token fees and network dependencies while gaining real time intelligence at local bus speeds. This financial model turns AI technology into a permanent corporate asset rather than a recurring service cost.