Meta 开源 816B 参数模型 Muse Spark Open，适配 Apple MLX 在 Mac 上运行

Meta在Huggingface上发布了Muse Spark Open的权重，这是一个拥有816B参数的模型，专为编程和智能体工作而构建。 开源版本与Muse Spark 1.3共享相同的基础模型，并额外进行了安全后训练，以抵御在没有系统护栏的情况下作为独立模型被滥用，这逆转了Meta自4月以来首个专有、闭权重前沿模型的策略。 其62层中的每一层都包含256个专家网络，并将每个token路由通过8个专家，因此部署需要816B参数模型的内存，但以42B模型的速度运行。 这一存储成本解释了与Apple的合作，因为M5 Ultra提供1.2 TB/s的统一内存带宽，而一台Mac Studio最多可搭载512GB。 在512GB M3 Ultra上测试的3-bit量化版本占用约344 GB，在短提示下生成速度约为21 tok/s。

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Meta released the weights of Muse Spark Open, on Huggingface, an 816B-parameter model built for coding and agentic work. The open version shares the same base model as Muse Spark 1.3, with additional safety post-training to resist misuse as a standalone model without system guardrails, reversing Meta’s first proprietary, closed-weight frontier model strategy from April. Each of its 62 layers holds 256 expert networks and routes every token through 8, so deployment needs the memory of an 816B-parameter model but runs at the speed of a 42B model. That storage bill explains the Apple tie-up, because the M5 Ultra pushes 1.2 TB/s of unified memory and a Mac Studio can carry up to 512GB. A 3-bit quant tested on a 512GB M3 Ultra took about 344 GB and ran at about 21 tok/s generation on a short prompt.