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    🇹🇼Taiwan·AI News·13 Oct 2026·via Pr Newswire Apac·Covered by 5 sources

    MSI Showcases Open Data Center and AI Infrastructure at 2026 OCP Global Summit

    MSI introduced new open data center and AI infrastructure solutions at the 2026 OCP Global Summit. The offerings include 21-inch ORv3 systems for high-density air- and liquid-cooled deployments, DC-MHS modular building blocks supporting AMD and Intel architectures, and NVIDIA MGX rack and GPU server platforms. A desktop AI supercomputer, the XpertStation WS300, was also showcased for local AI development.

    Nexa's Summary

    MSI's new infrastructure aims to provide flexibility in data center design, addressing the growing demands for compute density and AI workloads. The focus on open standards and modular platforms, as highlighted by General Manager Danny Hsu, suggests an effort to enable systems that can adapt to evolving requirements rather than locking customers into proprietary solutions. This approach could be particularly relevant for organizations looking to future-proof their investments amid rapid technological shifts.

    The technical specifications reveal a push for higher performance and efficiency. The ORv3 systems, powered by AMD EPYC 9006 Series processors, feature PCIe 6.0 and high memory speeds, indicating a focus on data-intensive applications. The availability of both air-cooled and direct liquid-cooled designs, supporting up to 600W TDP per node, reflects efforts to manage increasing power consumption and thermal loads, which are critical considerations for modern data centers.

    Beyond traditional data center racks, MSI is also addressing the need for scalable AI infrastructure, from rack-scale NVIDIA MGX systems to the desktop-based XpertStation WS300. This range suggests an understanding that AI development and deployment occur across various scales, from centralized accelerated computing to localized prototyping. The inclusion of liquid cooling and high-speed networking in these AI platforms underscores the intensive resource demands of current and future AI models.

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