Meta 在 Hugging Face 开放 816B 参数模型 Muse Spark Open 的权重，定位编码与 Agent 工作，与 Muse Spark 1.3 共享基座并附加安全后训练。
梳理了该开放权重模型在 Mac 上的部署门槛、稀疏结构和许可条款，读者可据此评估本地运行超大开源模型的可行性。
After years of rivalry, Meta and Apple join hands to deliver open-weight AI to the Mac.
Meta released the weights for Muse Spark Open, an 816B-parameter model that runs on 2 linked Mac Studios.
Apple tuned the release for its MLX framework. Only 42B parameters fire per token because the model routes each token to 8 of 256 experts, so every step reads a small slice of memory.
Holding the whole model is the hard part, since the 4-bit NVFP4 version needs at least 700GB of GPU memory.
Each M5 Ultra Mac Studio gives its GPU up to 512GB of unified memory, so 2 machines hold the model while 1.2TB/s of bandwidth feeds each token.
On the benchmarks, Muse Spark Open does top the MCP-Atlas tool-use test at 89.2, which suits the coding agents Meta built it for.
The license allows free commercial use but requires a “Built with Muse Spark Open” label, plus a separate Meta deal for API model sellers with over $20M in 12-month revenue.
Apple hasn’t priced the 512GB Mac Studio, and a cluster of 4 machines with 256GB each costs roughly $38,000.
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.在 X 查看被引用的帖子
来源：Rohan Paul · x.com