---
title: "Meta Introduces Muse Ember: An Ultra-Cheap Multimodal Model for AI Agent Fleets"
description: "Meta introduced Muse Ember, the lightest and most cost-effective model in the Muse family for mass execution of tasks by AI agents. The cost per million input tokens is $0.10."
date: 2026-11-09T21:53:07.409Z
lang: en
url: https://xab.info/en/posts/meta-muse-ember-cheap-ai-model-for-agents
tags: [meta, ai-model, muse-ember, llm, ai-agents, machine-learning]
author: "Alexander Buran"
publisher: "XAB.info"
---

# Meta Introduces Muse Ember: An Ultra-Cheap Multimodal Model for AI Agent Fleets

![Abstract blue geometric diagram with points and curved lines on a light background illustrating the Muse Ember AI model](https://xab.info/media/2026/11/09/meta-muse-ember-deshyovaya-ii-model-dlya-agentov/meta-muse-ember-deshyovaya-ii-model-dlya-agentov-1.webp)

## Key Points

- Muse Ember is the fourth and most cost-effective model in the Muse family, introduced on November 9
- The model is designed for mass execution of repetitive operations by AI agents in tandem with Muse Wonder
- Supports text, images, audio, and analysis of long documents, screenshots, and video
- Cost per million input tokens is $0.10; benchmarked against Anthropic Haiku and OpenAI Luna in Artificial Analysis

On November 9, Superintelligence Labs, a division of Meta, introduced Muse Ember, the fourth and currently lightest model in the Muse family. The model is positioned as the most cost-effective in terms of token pricing and is designed for the mass execution of repetitive operations by autonomous AI agents. Within the Muse lineup, it follows Spark, Glimmer, and the more powerful Wonder, completing a spectrum of solutions ranging from 'heavy' planners to 'light' executors of routine tasks.

### Role in Tandem with Muse Wonder

The developers suggest using Ember not in isolation, but paired with the flagship Muse Wonder model. In this configuration, Wonder handles action planning and task execution sequencing, while Ember processes large volumes of uniform requests. A typical scenario provided in company materials looks like this: Wonder develops customer support response rules, after which Ember applies these rules to tens of thousands of incoming inquiries. Other stated use cases include programming and working with external tools.

### Multimodality and Document Processing

Ember supports text, images, and audio, including the processing and analysis of long documents. According to the company, the model is capable of parsing screenshots, charts, scanned documents, voice notes, meeting recordings, and even video. This makes it suitable for tasks where an agent must extract structured information from heterogeneous sources rather than merely generating text.

### Economics and Benchmarks

The primary argument in favor of Ember is its price: the cost per million input tokens is set at $0.10. In the Artificial Analysis benchmark, Meta compared its model to Anthropic Haiku and OpenAI Luna, claiming that Ember delivers a more favorable cost-to-accuracy ratio than several competitors. For the mass deployment of agents handling thousands of identical requests daily, this exact parameter determines the final cost of the solution.

### Significance for the Agentic AI Market

The appearance of a cheap 'workhorse' in the Muse family reflects a broader industry trend toward separating roles between expensive planner models and cheap executor models. If Ember's cost-efficiency holds up under real workloads, it could lower the barrier to entry for companies looking to deploy their own fleets of AI agents without tying themselves to the most powerful and expensive models. It remains to be seen how the company's benchmark figures will perform in independent tests and production scenarios.

## Fact-Check & Sources

- [M**a представила Muse Ember — дешёвую ИИ-модель для армии автономных агентов](https://3dnews.ru/1151065) - Primary source: Muse Ember announcement, parameters ($0.10 per million input tokens), Artificial Analysis benchmark, comparison with Haiku and Luna, multimodality, position in the Muse lineup.
- [Meta представила Muse Ember — дешёвую ИИ-модель для армии автономных агентов](https://3dnews.ru/1151065/meta-predstavila-muse-ember-deshyovuyu-iimodel-dlya-armii-avtonomnih-agentov) - Duplicate link to the same material; content matches the primary source.

## FAQ

### What is Muse Ember and when was it introduced?

Muse Ember is the lightest and most cost-effective model in Meta's Muse family (Superintelligence Labs), introduced on November 9. It is designed for mass execution of repetitive operations by AI agents.

### How much does it cost to use Muse Ember?

According to the company, the cost per million input tokens is set at $0.10.

### Which models does Meta compare Ember to?

In the Artificial Analysis benchmark, Meta compared Muse Ember to Anthropic Haiku and OpenAI Luna, claiming a more advantageous cost-to-accuracy ratio.

### What data types does Muse Ember support?

The model works with text, images, and audio, and analyzes screenshots, charts, scanned documents, voice notes, meeting recordings, and video.