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.
Muse Ember is a small Meta model with a 1M-token context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → and native text, image, audio and video input, aimed at multi-step tool useA model's ability to call external functions — run code, search the web, edit files — instead of only generating text.Full definition → and test-and-fix coding agents. It is a lower-cost option to evaluate for AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → workloads.
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
multimodal — A model that works with more than text — reading images, audio, or video, and sometimes generating them too.
tool use — A model's ability to call external functions — run code, search the web, edit files — instead of only generating text.
