LITEON Showcases at NVIDIA MGX Ecosystem at OCP Highlighting 800 VDC Power Technologies to Advance Next-Generation AI Infrastructure

• LITEON participated in the NVIDIA MGX Ecosystem Ceremony, represented by John Chang, General Manager of LITEON Cloud Infrastructure Platform and Solution SBG, Bob Weng, General Manager of the AIDC Platform SBU, and Simon Ong, President of LITEON USA.
• At OCP Global Summit 2026, LITEON showcased AI data center power solutions based on the NVIDIA MGX architecture, including 800 VDC Power Rack and 800V-to-50V Power Brick, demonstrating key power technologies for next-generation AI infrastructure.
• As an NVIDIA MGX ecosystem partner, LITEON has continued to deepen its collaboration with NVIDIA and has been regularly invited to participate in the NVIDIA MGX Ecosystem Ceremony.
• At its OCP booth, LITEON demonstrated 330kW, 880kW, and 1.2MW power deployment scenarios, showcasing the evolution of energy architectures for megawatt-scale AI data centers.

LITEON Technology (2301.tw) is invited to participate in the NVIDIA MGX Ecosystem Ceremony held during the 2026 OCP Global Summit. Representing LITEON were John Chang, General Manager of LITEON Cloud Infrastructure Platform and Solution SBG, Bob Weng, General Manager of the AIDC Platform SBU, and Simon Ong, President of LITEON USA. The ceremony brought together NVIDIA and global ecosystem partners to celebrate the continued growth of the AI infrastructure ecosystem.

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During OCP Global Summit 2026, LITEON also showcased its NVIDIA 800 VDC Power Rack and 800V-to-50V Power Brick in the NVIDIA MGX ecosystem exhibit area, highlighting its key technological capabilities in next-generation AI power infrastructure. Covering solutions from rack-level power architectures to high-efficiency power conversion technologies, these offerings are designed with high efficiency and power density to meet the energy efficiency and scalability requirements of AI data centers. The solutions help establish a robust and scalable power foundation for the development of AI Factories.

LITEON has been a NVIDIA MGX ecosystem partner, continuously investing in power and thermal management innovation. Through the modular NVIDIA MGX architecture, LITEON helps customers accelerate the deployment of solutions ranging from single-node servers to rack-scale systems. In recent years, LITEON has been regularly invited to participate in the NVIDIA MGX Ecosystem Ceremony, underscoring the long-standing collaboration between the two companies and LITEON’s strategic role within the AI infrastructure ecosystem.

“AI workloads continue to grow in scale and power density, accelerating the transformation of data center power architectures,” said John Chang, General Manager of LITEON Cloud Infrastructure Systems & Platforms SBG. “Leveraging our expertise in power management and system integration, LITEON continues to deepen collaboration with NVIDIA and ecosystem partners. From rack-level power architectures to server-level power conversion technologies, we are working together to build highly efficient and scalable AI infrastructure that supports the next generation of AI Factories.”

As AI computing demand continues to grow rapidly, data centers are evolving toward higher power densities and megawatt-scale deployments. In addition to showcasing its comprehensive 800 VDC power architecture and thermal management solutions, LITEON also featured an interactive virtual rack experience at its booth, illustrating deployment scenarios at 330kW, 880kW, and 1.2MW power levels. The demonstration visualized the evolution of data center energy architectures, from single-rack deployments to megawatt-scale AI computing environments, highlighting LITEON’s end-to-end capabilities spanning rack-level power and thermal management to data center-scale energy infrastructure. Looking ahead, LITEON will continue working closely with NVIDIA and ecosystem partners to accelerate the adoption of 800 VDC architectures and next-generation energy infrastructure, enabling more efficient and resilient power architectures for megawatt-scale AI data centers.