Muse Ember: Meta's smallest model for high-volume agent work
Meta's smallest and most efficient model, built for the repetitive work agents do all day: tool calls, coding subtasks, routing, extraction, and long-document parsing.
Why it matters
Matches Claude Haiku 5.5's Artificial Analysis score of 36 at about a third of the cost per task ($0.14 vs $0.41), with a 1M-token context and $0.10/$0.50 per million tokens.
What you could build with it
A startup running a fleet of support agents could route its high-volume triage, extraction, and tool-call traffic to Ember while reserving a frontier model for planning, cutting inference spend without changing the workflow.
Does it hold up?
Too early to judge: launched a day ago, so real-world usage evidence is thin; the vendor-cited cost-per-task edge over Haiku 5.5 is the main signal so far.
Built with Muse Ember
- Meta Releases Muse Ember for Lower-Cost Agent and Coding Workunite.ai · Pricing, the Responses API, and how Ember pairs with Muse Wonder as the volume worker under a planner model.
- Meta introduces Muse Ember to power cost-efficient AI agentssiliconangle · Launch coverage with the Artificial Analysis comparison against Haiku 5.5 and GPT-6 Luna.
- Meta and Anthropic Push AI Models Into More Complex Workpymnts · Same-day context: Ember and Fable 5.2 launched together, both aimed at sustained, complex agent work.
Learn more
First spotted on article: source.
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