Meta has introduced Muse Ember, which it describes as its smallest and most efficient AI model so far. The model targets routine agent work such as tool calls, small coding tasks, request routing, data extraction and long-document processing. Meta says it delivers more intelligence per dollar at every reasoning level than Claude Haiku 5.5 and GPT-6 Luna.
On the Artificial Analysis test, Meta puts the cost of a task at about $0.14 for Muse Ember, compared with $2.39 for the larger Muse Spark 1.3, which scores 37 to Ember's 36. Meta's own tests show Ember leading in most cases, but Haiku 5.5 scores higher on real coding tasks in FrontierCode 2.0-AA, at 34.9 percent to Ember's 27.2 percent.
The model accepts 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, priced at $0.10 per million input tokens and $0.50 per million output tokens.
Why it matters if you build agents
Teams running high-volume agent steps such as tool calls and request routing can compare per-task cost against larger models, where Meta's figures put Ember far lower. The FrontierCode coding gap means Ember should be tested on coding workloads before those tasks are routed to it. The prices and benchmark numbers come from Meta and Artificial Analysis, so they are worth checking against the original sources.
Get stories like this every weekday
One short email with the day's agent tooling news.