Reflection AI Introduces Beam: A 501B Open-Weight MoE Model With 23B Active Parameters for Coding and Agentic Workloads
501B parameters, 23B active: Reflection AI's Beam matches reasoning capability of frontier models at a quarter of the compute cost.
Why it matters
Reflection AI released Beam, a sparse MoE open-weight model designed for coding and agentic work, claiming parity with GLM-5.2 on reasoning benchmarks while requiring 3-4x less inference compute. Apache 2.0 weights ship in October 2026, making this a capability and efficiency benchmark in the open-weight space.
The key facts
5 to know501B total parameters; 23B active parameters (sparse MoE architecture)
Claims to match GLM-5.2 reasoning performance at 3-4x lower inference compute
Open-weight release under Apache 2.0 license planned for October 2026
Positioned for coding and agentic workloads
Reflection AI is the builder (first open-weight model from the lab)
Go to the source
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Publisher excerpt: Reflection AI has introduced Beam, its first open-weight model. It is a 501B sparse Mixture-of-Experts model with 23B active parameters, built for coding and agentic work. Reflection says it matches GLM-5.2 on reasoning with 3 to 4x less inference compute. Apache 2.0 weights are due later in…