Meta发布Muse Ember，面向低成本智能体执行
Meta Superintelligence Lab发布Muse Ember，这是一款面向复杂推理和高频智能体任务的轻量AI模型，可处理工具调用、编码子任务、路由、信息提取及长文档解析。Meta将其定价为每百万输入token 0.10美元，并称其可在智能体框架中与Muse Wonder协同，处理文本、图像和音频输入。Meta援引Artificial Analysis的综合基准得分称，Muse Ember比Anthropic的Haiku和OpenAI的Luna更便宜且更智能，并与DeepSeek V4.1 Flash和GLM 5.3 Flash具有成本竞争力。相关比较未获所供报道独立确认。
Muse Ember较低的输入token定价瞄准大规模智能体执行，而其与Muse Wonder的协同分工体现了Meta让较大模型负责规划、由轻量模型处理重复任务的策略。
Today, we're introducing Muse Ember, our smallest and most efficient model designed for complex reasoning execution and the work agents repeat all day: tool calls, coding subtasks, routing, extraction, and long document parsing.
Muse Ember delivers more intelligence per dollar than Claude Haiku 5.5 or GPT-6 Luna at any reasoning setting: it matches Haiku's best score at about a third of the cost and beats every Luna setting. It also sits on the efficiency frontier of the full Artificial Analysis leaderboard: no model scores higher for less per task.
Intelligence vs. Cost Per Task
Artificial Analysis Intelligence Index against cost per task at each reasoning effort, from the raw Artificial Analysis results. Muse Ember costs are estimates at proposed pricing.
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- Muse Ember
- Claude Haiku 5.5
- GPT-6 Luna
#Meta#Muse Ember#Muse Wonder#Artificial Analysis#Anthropic Haiku#OpenAI Luna#DeepSeek V4.1 Flash#GLM 5.3 Flash