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What is Muse Ember?

Muse Ember is an efficient multimodal artificial intelligence model developed by Meta Superintelligence Labs for autonomous agent execution, coding assistance, complex reasoning, and large-scale business automation. The model is designed to handle the frequent, structured operations performed by AI agents, including tool calls, information retrieval, workflow routing, document extraction, and software development subtasks. It supports a context window of one million tokens and can generate up to 512,000 output tokens, allowing applications to process large repositories, extensive documents, and complex task histories. Muse Ember natively processes text, images, audio, video, and PDF content, enabling multimodal analysis without requiring separate models for each supported input type. Its visual understanding capabilities allow agents to interpret screenshots, charts, scanned documents, and interface elements while supporting computer-based automation workflows. Software engineering capabilities include reading source files, running tests, analyzing repositories, implementing targeted fixes, and completing programming tasks within autonomous coding environments. The model also supports enterprise automation workflows that involve retrieving information, evaluating records, executing tools in sequence, and updating data across connected business applications. Meta trained Muse Ember using Muse Wonder Full, creating a specialized model intended to combine strong reasoning capabilities with lower inference costs for frequently repeated tasks. Published evaluation results include 37.8% on AutomationBench-AA, 61.6% on Agents' Last Exam, 40.9% on Terminal-Bench 4.0, and 80.6% on PerceptionBench with tools. Muse Ember can be combined with larger models such as Muse Wonder and Muse Spark, allowing advanced models to handle planning and complex decisions while Ember performs high-volume execution tasks.

What is Amazon Nova 2 Omni?

Nova 2 Omni represents a groundbreaking advancement in technology, as it effectively combines multimodal reasoning and generation, enabling it to understand and produce a variety of content types such as text, images, video, and audio. Its impressive ability to handle extremely large inputs, which can range from hundreds of thousands of words to several hours of audiovisual content, allows for coherent analysis across different formats. Consequently, it can simultaneously process extensive product catalogs, lengthy documents, customer feedback, and complete video libraries, equipping teams with a single solution that negates the need for multiple specialized models. By consolidating mixed media within a cohesive workflow, Nova 2 Omni opens doors to new possibilities in both creative endeavors and operational efficiency. For example, a marketing team can provide product specifications, brand guidelines, reference images, and video materials to effortlessly craft a comprehensive campaign encompassing messaging, social media posts, and visuals, all through a simplified process. This remarkable efficiency not only boosts productivity but also encourages innovative approaches to marketing strategies, transforming the way teams collaborate and execute their plans. With such capabilities, organizations can look forward to enhanced creativity and streamlined operations like never before.

Media

Media

Integrations Supported

Google Cloud Platform
Meta AI
Muse
Muse Code

Integrations Supported

Amazon Bedrock
Amazon Nova
Amazon Nova Forge
Amazon Web Services (AWS)

API Availability

Has API

API Availability

Has API

Pricing Information

$0.10 per 1M tokens (input)
$0.10 per million input tokens and $0.50 per million output tokens

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

research.meta.ai/blog/muse-ember

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/nova/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

AI Video Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

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