Muse Ember: Smallest, Most Efficient AI Model
The gist
Meta released Muse Ember, a small AI model priced at $0.10 per million input tokens.
It targets cheap, repetitive agent steps, where cost per task decides adoption.
How it unfolded
- Nov 9, 2026Meta introduces Muse Ember, its smallest and most efficient model, built for agentic workloads such as tool calls, coding subtasks, routing, extraction and long document parsing.
- Nov 9, 2026Muse Ember becomes available on the Meta Model API as muse-ember-1.0 and in Muse Code, at $0.10 per million input tokens, $0.004 per million cached input tokens and $0.50 per million output tokens.
- Nov 9, 2026Artificial Analysis measures an Intelligence Index score of 36, tied with Claude Haiku 5.5 (max), at about $0.14 per task versus $0.41 for Haiku.
Key terms
- tokens
- A machine learning model trained on huge amounts of text to generate, summarize, translate, and analyze language.
- agentic workloads
- AI programs that can make decisions, pursue goals, and take actions independently, often used for coding tasks.
Source: Wikipedia