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Nathan Lambert更新于 10月16日 11:30

Nathan Lambert:美国首个接近前沿智能体能力的开源权重模型将带来快速采用

If it performs roughly what like the scores indicate, adoption of this model is going to go gangbusters. First open-weigh model in the US with near frontier age

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Nathan Lambert 评论称,如果 muse spark open 的表现大致符合分数所示,这款模型的采用速度会非常快。他认为这是美国首个具备接近前沿智能体能力的开源权重模型,并指出此前 GLM 5.2 与 Kimi K3 是中国模型的那次跃升,而美国模型往往能获得极高采用率。他所引用的 Alexandr Wang 推文称 muse spark open 是迄今最强的美国开源权重模型,816B 总参数、42B 激活参数、1M token 上下文,原生多模态,面向编码与长周期任务等智能体工作。

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Nathan Lambert 对比中美开源模型在智能体能力上的差距,并判断美国开源模型一旦接近前沿会带来快速采用。

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Alexandr Wang

@alexandr_wang

1/ muse spark open is the most capable US open-weight model to date. 816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning. america! 🇺🇲 https://t.co/NjtOB7aY9D

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当前显示原文,中文全文译文尚未就绪。

If it performs roughly what like the scores indicate, adoption of this model is going to go gangbusters. First open-weigh model in the US with near frontier agentic capabilities (GLM 5.2 + Kimi K3 was that step change from China). US models get crazy adoption.

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Nathan Lambert