Muse Spark 开启
Muse Spark Open

原始链接: https://research.meta.ai/blog/muse-spark-open

Meta发布了Muse Spark开源,这是一个针对个人超算优化的开放权重AI模型。它原生支持Apple Silicon,通过MLX运行,两台Mac Studio M5 Ultra联合提供1TB统一内存和1.2 TB/s带宽,可完全在桌面端处理大型模型。发布内容包括自定义的Helion GPU内核,集成于SGLang中,可在NVIDIA/AMD显卡上实现高达3.95倍的内核级加速,并在AMD MI350上实现3%的端到端性能提升。安全的后训练确保符合Meta的超智能扩展框架,该模型采用Muse模型许可证,广泛支持非商业用途。现已在Hugging Face上线,用户可使用PyTorch的TorchTitan进行自定义,或原生在Mac上运行。该发布展示了实际的代理工作流案例,包括iOS开发和DaVinci Resolve视频处理,并邀请社区在Hugging Face论坛分享。

黑客新闻 新 | 过去 | 评论 | 提问 | 展示 | 工作 | 提交 登录 Muse Spark Open, 迄今最强美国开源权重模型 (meta.ai) 70 点 by meetpateltech 1 小时 ago 隐藏 | 过去 | 收藏 | 1 条评论 帮助 dang 16 分钟 ago [–] 评论已移至 https://news.ycombinator.com/item?id=50107379. 回复 考虑申请 YC 的 Winter 2027 批次!申请截止至 11 月 2 日。 准则 | 常见问题 | 列表 | API | 安全 | 法律 | 申请 YC | 联系 搜索:
Meta发布了Muse Spark Open,一个816B参数的开放权重模型,针对Apple Mac Studio M5 Ultra硬件进行了优化。该模型需要大量计算资源:两台配备M5 Ultra和512GB统一内存的Mac Studio(总计1TB)才能运行,费用约为28,000至30,000美元。虽然被宣传为“开放权重”,但许可证限制要求商业用途需联系Meta。该模型支持Unsloth和MLX等多种推理引擎,但社区讨论指出其极端的硬件要求使其对大多数用户不可及。与DeepSeek和Qwen等竞争对手的比较表明在某些方面性能持平,尽管许可证条款将其与真正的开放模型区分开来。Meta通过产品整合强调Muse的“粘性”,尽管用户基于成本和复杂性争论其实际可行性。此次发布代表Meta在开放权重领域的持续推进,尽管面临类似Llama的先前许可证限制。
相关文章

原文

Key Benchmarks

For more details about our evaluations, see the evaluation methodology report.

Optimized for Apple Silicon

Leveraging the latest version of MLX, Muse Spark Open was optimized to run on Mac Studio with M5 Ultra, and together they’re the best way to run a powerful model on your own desktop.

Apple’s unified memory architecture lets the M5 Ultra's integrated GPU use up to 512 GB per Mac Studio, so two machines can hold an entire model. And the chip’s 1.2 TB/s of memory bandwidth is fast enough to read the small slice each token needs. The result is two Mac Studios behave like one supercomputer with a terabyte of unified memory.

We tested a range of agentic workflows running entirely on-device, using Muse Code powered by Muse Spark Open, including shipping real iOS changes to Ice Cubes (an open-source Mastodon client) — bug fixes, new features, full build — and driving DaVinci Resolve end to end, with the model reviewing footage frame by frame to find the strongest moments and crop them vertically.

Available Now

We’re sharing this work because we want everyone to have access to the best models. The open-weight version of Muse Spark ships with custom, auto-tunable Helion GPU kernels in SGLang, delivering 1.03-3.95× kernel-level speedups on NVIDIA and AMD GPUs, and a 3% end-to-end speedup on AMD MI350.

Safety and Preparedness

Releasing open-weight models is part of how we bring the benefits of personal superintelligence to everyone, and part of how safety work advances across the field.

Open weights also carry their own considerations, and Muse Spark Open has additional safety post-training for that reason. The results demonstrate strong safeguards across risk categories measured.

We evaluated the model in line with our Meta Superintelligence Scaling Framework, covering the most severe risks, and it met the thresholds our framework requires for release. Detailed results are in the Muse Spark Open model card, with a full evaluation report available soon.

License

We’re releasing the weights under the Muse Model License with limited commercial terms, which allow many developers to use the model for free.

Get Started

You can customize Muse Spark Open for your use case by leveraging PyTorch’s TorchTitan to further tune the model. To run it on Apple silicon, use MLX, which pulls the weights directly from Hugging Face.

Muse Spark Open is available now through Hugging Face: https://huggingface.co/collections/meta-models/muse-spark-open

MLX Adapter for running Muse Spark Open on Mac Studio.

Hosted Inference Partners: Together AI, Fireworks, Baseten, Modal, Groq, Nebius, and OpenRouter.

Built or published something with Muse Spark Open? Share with us on the Hugging Face Forums — we’d love to see what you create.

联系我们 contact @ memedata.com