What changed
Meta has introduced Muse Ember, its smallest and most efficient AI model to date. It is designed for the routine tasks AI agents handle all day, such as calling tools, handling small coding tasks, routing requests, extracting data, and processing long documents. The model handles text, images, audio, and video and can process up to one million tokens at once. It is available now through the Meta Model API and Muse Code at $0.10 per million input tokens and $0.50 per million output tokens.
What this means in practice
Muse Ember is positioned as a cost-effective solution for tasks that require frequent, repetitive processing. According to Meta, it delivers more intelligence per dollar at every reasoning level than Claude Haiku 5.5 or GPT-6 Luna. In the Artificial Analysis test, it costs about $0.14 per task, while the larger Muse Spark 1.3 costs $2.39 for a nearly identical score of 36 versus 37. Muse Ember leads in most of Meta's own tests, but Haiku outperforms it on real coding tasks in FrontierCode 2.0-AA, scoring 34.9 percent to Muse Ember's 27.2 percent. The model achieves a score of 36 on the Artificial Analysis Intelligence Index at a particularly low cost per task.
Limitations and availability
Muse Ember is available now through the Meta Model API and Muse Code. The model can process up to one million tokens at once. The supplied announcement does not specify the total or active parameter counts. The model handles text, images, audio, and video, but the exact hardware requirements or licensing conditions are not detailed in the source.
