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Artificial Analysis更新于 10月16日 23:14

Reflection 首个模型 Beam 发布,智能指数 30 分位列美国开源权重模型第二

Reflection’s first model, Beam, scores 30 on the Artificial Analysis Intelligence Index, placing it #2 among US open weights models

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Reflection 发布首个模型 Beam,在 Artificial Analysis 智能指数上得分 30,位列美国开源权重模型第二,仅次于 Meta 的 Muse Spark Open(39),高于前一天发布的 NVIDIA Nemotron 3.5 Super VL(26)。Beam 为开源权重模型,总参数 501B、激活参数 23B,已在 Hugging Face 发布,上下文窗口 1M tokens,仅支持文本。其每个智能指数任务约消耗 26k 输出 token,约为 K2 Horizon(52k)的一半;AutomationBench-AA 得分 48.5%,但 Terminal-Bench 4.0 仅 3.0%,AA-Omniscience 正确率 33%、幻觉率 47%。

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AI 评分 60

第三方评测给出 Beam 在开源模型中的位置与 token 效率对比,也点出终端任务和幻觉率上的短板。

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Reflection’s first model, Beam, scores 30 on the Artificial Analysis Intelligence Index, placing it #2 among US open weights models

Beam is an open weights model with 501B total and 23B active parameters, released on @huggingface

Congratulations to @reflection_ai on the release!

Key takeaways:

➤ Second among US open weights models: Beam scores 30, behind only Meta's Muse Spark Open (39) and ahead of yesterday’s NVIDIA Nemotron 3.5 Super VL (26) release. Outside China, only Muse Spark Open and the UAE's K2 Horizon (31) score higher

➤ Token efficient for its intelligence: Beam uses ~26k output tokens per Intelligence Index task compared to K2 Horizon, one point ahead, which uses twice as many (~52k). Proprietary models still set the frontier, with GPT-6 Astra (max) scoring 53 on the same budget (~27k)

➤ Strong on agentic workflows, weaker in the terminal: Beam scores 48.5% on AutomationBench-AA, 11 percentage points ahead of K2 Horizon (37.2%) and level with Qwen3.8 27B (48.2%). Terminal-Bench 4.0 is a weak point, where Beam scores 3.0%, behind Qwen3.8 27B (5.6%) and Muse Spark Open (8.1%)

➤ Knows more, guesses more: On AA-Omniscience it answers 33% of questions correctly, well ahead of K2 Horizon (18%) and Qwen3.8 27B (16%). But its hallucination rate is 47%, against 26% for K2 Horizon and 30% for Qwen3.8 27B, giving Beam a net index score of 1.5, ahead of both peers (−3.0 and −10.0)

Other model details Context window: 1M tokens Modalities: Text Parameters: 501B / 23B

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Artificial Analysis