Reflection AI 发布开源智能体模型 Beam，总参数 501B、激活 23B，宣称在编码和智能体任务上推进西方开源前沿，完整权重将于本月以 Apache 2.0 发布并附带 FP8 和 NVFP4 版本。
作者在转发基础上补充了效率估算口径和 headline 图表外的对比数据，帮助读者更冷静地看待 Beam 对 GLM-5.2 的领先说法。
The much anticipated open-source model from Reflection AI just dropped.
Beam now becomes the strongest western open model, rivals GLM-5.2 while using 3-4x less inference compute.
> The 3-4x efficiency edge over GLM-5.2 rests on estimated forward-pass FLOPs (2 × active parameters × generated tokens), which leave out prefill, attention and serving overhead, so it is not a measured cost.
> A sparse mixture-of-experts model with 501B total and 23B active parameters, pretrained on 23.8T tokens in under 4 weeks on 6,144 GB300 GPUs, with a 1M-token effective context.
> The RL run used 10.5K GB300 GPUs for 4 weeks, produced over 100M rollouts across nearly 1M environments and about 1.3B sandboxes, and ended with no sign of a plateau.
> Beam nearly ties GLM-5.2 at 80.1 versus 81.0 on Terminal Bench v2.1, but trails DeepSeek V4.1 Flash at 90.6 and Kimi K3 at 88.3, neither of which appears in the headline chart.
and Reflection will also ship FP8 and NVFP4 builds under Apache 2.0.
Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advances the Western open frontier on coding & agentic tasks - Trained end-to-end from scratch Full weights release this month. Learn more about Beam: http://reflection.ai/beam在 X 查看被引用的帖子
来源：Rohan Paul · x.com