Meta 发布轻量模型 Muse Ember，面向智能体执行
Meta releases Muse Ember, a new lightweight model for agent execution
Meta Superintelligence Lab 发布轻量模型 Muse Ember，输入价格为每百万 token 10 美分，主打工具调用、编码子任务、路由、抽取和长文档解析等智能体高频工作。Meta 称其可与更大的 Muse Wonder 搭配，由后者规划、Ember 承担大批量执行，并支持文本、图像和音频输入。Ember 是 Muse 品牌下第四款模型，此前已有 Spark、开源版 Glimmer 和 Wonder。
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Meta 公布 Ember 的每百万 token 输入价格与多模态输入范围，读者可据此判断轻量模型在智能体流程中的分工位置。
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Meta Superintelligence Lab released a new AI model on Monday called Muse Ember, the lab’s lightest and most cost-efficient AI model yet. In its release, Meta said Ember was “designed for complex reasoning execution and the work agents repeat all day: tool calls, coding subtasks, routing, extraction, and long document parsing.”
Meta particularly emphasized Ember’s cost-per-task, using Artificial Analysis’s composite benchmark score to show Ember as cheaper and smarter than competitors like Anthropic’s Haiku and OpenAI’s Luna.
At 10 cents per million input tokens, Ember is significantly cheaper than frontier competitors like Haiku and Luna. Not only that, it’s cost-competitive with open-source competitors like DeepSeek V4.1 Flash and GLM 5.3 Flash.
Given the emphasis on low cost and accuracy at scale, Ember is designed to pair with a larger model like Meta’s Muse Wonder in an agentic harness. In the case of a customer-support agent, for instance, you might see a heavier model establishing rules for how to handle a particular issue, then sending a lighter-weight model to apply the rules across tens of thousands of cases. As Meta puts it in the announcement, “Muse Wonder plans, Muse Ember handles the volume.”
With volume-heavy use cases in mind, Meta also trained Ember to work well across different types of media, including text, images, and audio. The result makes the model surprisingly flexible in what kind of inputs it can handle. As Meta puts it in the announcement, “agents can read screenshots, charts, and scanned documents, or work from voice memos, meeting recordings, and video without a separate model.”
Ember is the fourth model released under Meta’s Muse brand, following the mid-weight Spark ( released in April ), Spark’s open-source twin Glimmer ( released in August ), and the Wonder frontier model ( released in October ). The flagship consumer AI product, the Muse Agent, was released in September to unexpected success , with new features like Spaces and video chat rolling out earlier this month.