This Open Compute Project (OCP) white paper surveys major OCS technologies, including robotic mechanisms, Micro-Electro-Mechanical-System (MEMS) beam steering, liquid‐crystal devices, piezo‐actuated systems, and silicon‐photonics switches, comparing trade‐offs in radix . This Open Compute Project (OCP) white paper surveys major OCS technologies, including robotic mechanisms, Micro-Electro-Mechanical-System (MEMS) beam steering, liquid‐crystal devices, piezo‐actuated systems, and silicon‐photonics switches, comparing trade‐offs in radix . By establishing on-demand end-to-end optical paths at the physical layer, OCS bypasses intermediate packet processing, achieving ultra-low latency, non-blocking bandwidth, and superior energy efficiency, thereby providing a new architectural alternative for AI training clusters and high-performance. By establishing on-demand end-to-end optical paths at the physical layer, OCS bypasses intermediate packet processing, achieving ultra-low latency, non-blocking bandwidth, and superior energy efficiency, thereby providing a new architectural alternative for AI training clusters and high-performance. OCS overcomes these challenges by providing fully transparent, photonic connections without Optical‐Electrical‐Optical (O-E-O) conversion, enabling ultra‐low latency, zero buffering, and protocol‐agnostic operation. These characteristics significantly reduce network power and jitter while improving. While Ethernet and InfiniBand remain the dominant networking technologies, the rapid adoption of 800G and the transition toward 1. As a result, Optical Circuit Switching (OCS) is gaining renewed. The rapid evolution of data-intensive applications, such as artificial intelligence (AI), machine learning, and high-performance computing, demands innovative networking solutions that deliver high bandwidth, low latency, and energy efficiency. This 4Q25 report is a continuation of and update to Cignal AI's previous OCS reports.