| Management number | 241248734 | Release Date | 2026/07/17 | List Price | US$857.70 | Model Number | 241248734 | ||
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The NVIDIA MFA7U10-H010 is a 400 Gbit/s active optical splitter cable designed to convert a single OSFP port into two independent 200 Gbit/s QSFP56 links. This integrated cable assembly eliminates the need for separate transceivers or patch cords, simplifying high-speed network connections. With a 10 meter fiber length, it supports data center layouts that require connections across adjacent racks or rows, delivering low latency and reliable signal integrity through active optical cable (AOC) technology.
Engineered for InfiniBand HDR environments, this splitter cable is ideal for high performance computing clusters, AI training systems, and storage fabrics that demand consistent bandwidth and deterministic performance. It enables network administrators to optimize port usage by breaking out a 400 Gbit/s switch port into two 200 Gbit/s links, facilitating flexible network topologies and efficient bandwidth allocation.
This splitter cable is designed to work seamlessly with network switches, adapters, and appliances that expose OSFP and QSFP56 ports. It supports InfiniBand HDR protocols, making it suitable for environments that require high bandwidth and low latency connections. The cable’s active optical design ensures compatibility with existing fiber infrastructure while reducing electromagnetic interference common in copper cabling.
This cable is well suited to data centers and high performance computing clusters where efficient port utilization and reliable high-speed connections are critical. It fits environments that require flexible cabling across racks or rows without the bulk of copper cables. Users managing dense GPU servers, scale-out storage, or composable infrastructures will find it simplifies network expansion and upgrades without hardware replacement.
By enabling two 200 Gbit/s links from a single 400 Gbit/s port, it supports balanced network topologies and targeted bandwidth increases, making it a strong choice for AI training systems, storage fabrics, and other demanding applications.
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