Meta Muse Ember: the smallest Muse model, for tool calls and coding subtasks at $0.10 per million input tokens
What is it?
Muse Ember is the smallest and most efficient model in Meta's Muse family. It targets the work agents repeat all day: chained tool calls, coding subtasks, routing requests, extraction and reading long documents. It has a 1M-token context window and takes text, images, audio and video as input. It's available now on the Meta Model API at $0.10 per million input tokens and $0.50 per million output tokens. The weights are not released.
Why does it matter?
Most agent spend comes from running small steps hundreds of times. Meta says Ember matches Claude Haiku 5.5's best score at about a third of the cost per taskVendor claim. On the Artificial Analysis Intelligence Index it scores 36 at its top settingIndependent, second of the 32 models Artificial Analysis compares it with. If you're looking for a cheap model for sub-agents or routing, run it side by side with the small model you use now.
Maturity
GAGenerally available as a paid model on the Meta Model API. The weights are closed, and the cost figures for Ember in Meta's chart are estimates at proposed pricing.
How to track it
- Real cost: see how the Meta Model API docs spell out cache discounts and rate limits.
- Coding: check the Artificial Analysis coding index for how far it trails Haiku 5.5 on terminal coding tasks.
- Access: watch @AIatMeta for any word on open weights or putting Ember in the Meta AI app.