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Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

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Description

Gemini 2.0 Pro stands as the pinnacle of Google DeepMind's AI advancements, engineered to master intricate tasks like programming and complex problem resolution. As it undergoes experimental testing, this model boasts an impressive context window of two million tokens, allowing for the efficient processing and analysis of extensive data sets. One of its most remarkable attributes is its ability to integrate effortlessly with external tools such as Google Search and code execution platforms, which significantly boosts its capacity to deliver precise and thorough answers. This innovative model signifies a major leap forward in artificial intelligence, equipping both developers and users with a formidable tool for addressing demanding challenges. Furthermore, its potential applications span various industries, making it a versatile asset in the evolving landscape of AI technology.

Description

Muse Ember is a multimodal AI model developed by Meta Superintelligence Labs to provide efficient reasoning and task execution for autonomous AI agents and enterprise applications. The model is optimized for high-volume workloads involving tool calls, coding subtasks, data extraction, document analysis, and automated business processes. Its one-million-token context window allows applications to process extensive software repositories, long documents, and large collections of business records in a single request. Muse Ember accepts text, images, audio, video, and PDF inputs, enabling developers to build AI systems that understand multiple forms of information without switching between specialized models. Its agentic capabilities allow applications to retrieve records, interact with software tools, execute sequential operations, and update information across connected systems. For software development, the model supports source code inspection, automated testing, targeted code modifications, and technical problem-solving within agent-driven development environments. Meta reports benchmark scores of 37.8% on AutomationBench-AA, 40.9% on Terminal-Bench 4.0, and 27.2% on FrontierCode 2.0-AA. The model can operate as a specialized execution component alongside larger models such as Muse Wonder and Muse Spark, reducing the cost of repeated operations in multi-agent workflows. Muse Ember is accessible through Meta Model API and Muse Code, with usage-based pricing of $0.10 per million input tokens, $0.004 per million cached input tokens, and $0.50 per million output tokens.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

C# Yes 
Cody Yes 
Elixir Yes 
F# Yes 
Gemini Yes 
Gemini Enterprise Agent Platform Yes 
Go Yes 
Google Yes 
Google Cloud Platform No 
Google Cloud SQL Yes 
JavaScript Yes 
Julia Yes 
Meta AI No 
Muse No 
Muse Code No 
Requesty Yes 
SQL Yes 
Scala Yes 
TypeScript Yes 
Visual Basic Yes 

Integrations

C# No 
Cody No 
Elixir No 
F# No 
Gemini No 
Gemini Enterprise Agent Platform No 
Go No 
Google No 
Google Cloud Platform Yes 
Google Cloud SQL No 
JavaScript No 
Julia No 
Meta AI Yes 
Muse Yes 
Muse Code Yes 
Requesty No 
SQL No 
Scala No 
TypeScript No 
Visual Basic No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$0.10 per 1M tokens (input)
$0.10 per million input tokens and $0.50 per million output tokens
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

deepmind.google/technologies/gemini/pro/

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

research.meta.ai/blog/muse-ember

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