Meta 发布 Muse Ember 小模型 主打智能体高频任务
Meta 推出迄今最小、最高效的模型 Muse Ember，专为智能体日常高频任务设计，覆盖工具调用、小型编码、请求路由、数据抽取与长文档处理。官方称其在各推理档位的每美元智能均优于 Claude Haiku 5.5 与 GPT-6 Luna，单任务成本约 0.14 美元，但真实编码基准 FrontierCode 2.0-AA 上落后于 Haiku。模型支持文本、图像、音频、视频与百万级上下文，已通过 Meta Model API 与 Muse Code 开放，定价为每百万输入 0.10 美元、输出 0.50 美元。
报道正文
Meta launches Muse Ember, a small AI model built for the repetitive work agents actually do
[Matthias Bastian](https://the-decoder.com/author/matthias-bastian/) [View the LinkedIn Profile of Matthias Bastian](https://www.linkedin.com/in/matthias-bastian-128b71b1/) Nov 9, 2026 Meta has introduced Muse Ember, its smallest and most efficient AI model to date.It's designed for the routine tasks AI agents handle all day: calling tools, handling small coding tasks, routing requests, extracting data, and processing long documents. Meta says Muse Ember delivers more intelligence per dollar at every reasoning level than Claude Haiku 5.5 or GPT-6 Luna. It costs about $0.14 per task in the Artificial Analysis test, while the larger Muse Spark 1.3 costs $2.39 for a nearly identical score of 36 versus 37. Muse Ember leads in most of Meta's own tests, but Haiku outperforms it on real coding tasks in FrontierCode 2.0-AA, scoring 34.9 percent to Muse Ember's 27.2 percent.
Meta’s Muse Ember achieves a score of 36 on the Artificial Analysis Intelligence Index at a particularly low cost per task. | Image: Meta via Artificial Analysis
The model handles text, images, audio, and video and can process up to one million tokens at once. It's available now through the Meta Model API and Muse Code at $0.10 per million input tokens and $0.50 per million output tokens.
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