@TheAhmadOsman: Congrats to all the friends at Reflection We now have a SoTA American Opensource model

X AI KOLs Following Models

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Congrats to Reflection AI on releasing Beam, a highly efficient agentic open model with 501B total parameters and 23B active, advancing the Western open-source frontier in coding and agentic tasks.

Congrats to all the friends at Reflection We now have a SoTA American Opensource model 🦅
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Congrats to all the friends at Reflection

We now have a SoTA American Opensource model 🦅

Reflection (@reflection_ai): 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.

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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。