Meta Launches Muse Ember Small Model for Agent Workloads
Meta has launched Muse Ember, its smallest and most efficient model yet, purpose-built for the routine work AI agents do all day: tool calling, small coding tasks, request routing, data extraction and long-document processing. Meta claims it delivers more intelligence per dollar at every reasoning level than Claude Haiku 5.5 or GPT-6 Luna, at roughly $0.14 per task, though Haiku still leads on real coding benchmarks. The multimodal model handles up to one million tokens and is available now via the Meta Model API and Muse Code at $0.10 per million input tokens and $0.50 per million output tokens.
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Meta launches Muse Ember, a small AI model built for the repetitive work agents actually do
[Matthias Bastian](https://the-decoder.com/author/matthias-bastian/) [View the LinkedIn Profile of Matthias Bastian](https://www.linkedin.com/in/matthias-bastian-128b71b1/) Nov 9, 2026 Meta has introduced Muse Ember, its smallest and most efficient AI model to date.It's designed for the routine tasks AI agents handle all day: calling tools, handling small coding tasks, routing requests, extracting data, and processing long documents. Meta says Muse Ember delivers more intelligence per dollar at every reasoning level than Claude Haiku 5.5 or GPT-6 Luna. It costs about $0.14 per task in the Artificial Analysis test, 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.
Meta’s Muse Ember achieves a score of 36 on the Artificial Analysis Intelligence Index at a particularly low cost per task. | Image: Meta via Artificial Analysis
The model handles text, images, audio, and video and can process up to one million tokens at once. It's available now through the Meta Model API and Muse Code at $0.10 per million input tokens and $0.50 per million output tokens.
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