Reflection AI Introduces Beam: A 501B Open-Weight MoE Model With 23B Active Parameters for Coding and Agentic Workloads

תקציר מקורי באנגליתReflection AI has introduced Beam, its first open-weight model. Beam is a sparse Mixture-of-Experts (MoE) model with 501B total parameters and 23B active per token, built for coding, reasoning and agentic workloads. As per the Reflection AI team, Beam directly competes with larger open models like GLM 5.2 while using 3 to 4x less inference compute on reasoning benchmarks. Is it deployable today? Not for self-hosting yet. Beam is in final red-teaming. Early access runs through a waitlist on the Reflection platform . What is Reflection Beam? Beam is a general agent model trained from scratch by Reflection AI. It targets enterprise coding and agentic workloads. Reflection positions Beam as advancing the Western open-weight frontier. The research team is candid about the gap. Kimi K3 stays ahe