Meta Releases Small Model Muse Ember, Supporting 1M Token Context and Multimodal Input
Meta has released its smallest and most efficient model, Muse Ember, aimed at complex reasoning execution and everyday agent work; it can take on workflows across applications, call tools in sequence, run tests, and make targeted code fixes. The model has a 1M token context window and natively understands text, images, audio, and video. Muse Ember is now available on the Meta Model API, at $0.10 per million input tokens and $0.50 per million output tokens; Meta says it performs comparably to Claude Haiku 5.5 on the Artificial Analysis Intelligence Index, at about one-third the per-task cost of the latter.
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Meta has published the pricing and third-party benchmark comparisons for the small model Muse Ember, which can be used to judge the cost trade-offs for lightweight agent tasks.
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Today we're introducing Muse Ember, our smallest and most efficient model, built for complex reasoning execution and everyday agent work.
Muse Ember can carry workflows across apps, call tools in sequence, run tests and make targeted code fixes. With a 1M-token context window and native understanding of text, images, audio and video, it can also work across large document sets and varied inputs.