Beam: Reflection's 501B open-weight model
Reflection says Beam will ship as Apache 2.0 open weights later this month after final red-teaming.
Beam is a 501B-parameter sparse MoE model with 23B active parameters, aimed at coding, reasoning, and agentic work. Reflection says it pretrained Beam on 23.8T tokens and ran RL over more than 100M rollouts on 10.5K NVIDIA GB300 GPUs. The company frames Beam’s edge as inference efficiency, claiming comparable reasoning scores to GLM-5.2 with 3-4x less inference compute. Early access is waitlisted now; weights, a technical report, model card, and developer artifacts are still pending. HN · Frontpage AI's note
Beam is a 501B-parameter sparse MoE model with 23B active parameters, aimed at coding, reasoning, and agentic work. Reflection says it pretrained Beam on 23.8T tokens and ran RL over more than 100M rollouts on 10.5K NVIDIA GB300 GPUs. The company frames Beam’s edge as inference efficiency, claiming comparable reasoning scores to GLM-5.2 with 3-4x less inference compute. Early access is waitlisted now; weights, a technical report, model card, and developer artifacts are still pending. HN · Frontpage AI's note
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