Beam announcement, open model with 501B parameters and 23B active, full weights to be released later this month, undergoing final red-teaming and evaluations, focus on coding and agentic performance

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Summary

Beam 发布了一款 5010 亿参数、230 亿活跃参数的开放模型,主打编码与 agentic 性能,声称效率比 GLM 5.2 高 3-4 倍、比西方领先开源模型高 4 倍以上,完整权重将于本月晚些时候在最终红队测试与评估后发布。

3-4x more efficient than GLM 5.2 and over 4x more efficient than leading Western open models (completes tasks faster and cheaper)
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Beam: Reflection's 501B open-weight model

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Reflection AI introduced Beam, a 501B-parameter sparse MoE open-weight model (23B active) built for coding, reasoning, and agentic workloads, pretrained on 23.8T tokens and scaled with a high-compute RL run on 10.5K GB300 GPUs. Beam is positioned as advancing the Western open-weight frontier, approaching GLM 5.2 and Qwen 3.8-Max on coding/agentic tasks while using 3–4× less inference compute, with weights and a technical report due later this month.

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Reflection AI 推出 Beam:一款 5010 亿总参数(230 亿激活)的稀疏混合专家开源模型,面向编码、推理与智能体工作负载。

reflection/Beam-1.0-501B-A23B · Hugging Face

Reddit r/LocalLLaMA

Reflection 发布开源模型 Beam-1.0-501B-A23B,采用稀疏 MoE 架构(501B 总参数/23B 激活参数),支持 1M token 上下文,主打 token 高效推理、软件工程与智能体工具调用能力,提供 BF16、FP8、NVFP4 多种数值精度版本,采用 Apache 2.0 许可。