Meta releases Muse Ember, a small model for repeatable agent work

Meta released Muse Ember, its smallest and most efficient model, built for the work agents repeat all day. Think tool calls, coding subtasks, routing, extraction, and parsing long documents.

You can use it today in Muse Code and through the Meta Model API as muse-ember-1.0. It has a 1M-token context window with up to 512K output tokens, supports the Responses API, and natively understands text, images, audio, and video. Pricing is $0.10 per million input tokens, $0.004 per million cached input tokens, and $0.50 per million output tokens.

It's the first model trained using Muse Wonder Full. Meta now positions Muse Wonder for the hardest problems, Muse Spark for coding and agentic workflows, and Muse Ember for repeatable tasks at scale. By Meta's numbers it runs about $0.14 per Artificial Analysis task against $2.39 for Muse Spark 1.3, matches Claude Haiku 5.5's best Artificial Analysis score at about a third of the cost, and beats every GPT-6 Luna setting. Meta suggests pairing it with Muse Wonder, which plans while Ember handles the volume.