Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Gemini 3.1 Flash-Lite represents Google’s newest addition to the Gemini 3 family, built specifically for speed and affordability at scale. Engineered for developers managing high-frequency workloads, the model balances performance and cost efficiency without sacrificing quality. It is competitively priced at $0.25 per million input tokens and $1.50 per million output tokens, making it accessible for large production deployments. Compared to Gemini 2.5 Flash, it delivers substantially faster responses, including a 2.5x improvement in time to first token and a 45% boost in output speed. Benchmark evaluations show strong results, with an Elo score of 1432 and leading scores in reasoning and multimodal understanding tests. The model rivals or surpasses similarly tiered competitors while even outperforming some previous-generation Gemini models. A key feature is its adjustable reasoning control, enabling developers to fine-tune how much computational “thinking” is applied to each request. This flexibility makes it ideal for both lightweight tasks like translation and more complex use cases such as dashboard generation or simulation design. Early enterprise adopters have praised its ability to follow instructions accurately while handling complex inputs efficiently. Gemini 3.1 Flash-Lite is currently rolling out in preview within Google AI Studio and Vertex AI for enterprise customers.
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
Yes
API Access
Has API
Yes
Integrations
Google Cloud Platform
Yes
Bind AI
Yes
Clojure
Yes
CometAPI
Yes
Gemini Code Assist
Yes
Gemini Enterprise Agent Platform
Yes
Gemini Enterprise Agent Platform Notebooks
Yes
Google Opal
Yes
HTML
Yes
Java
Yes
Integrations
Google Cloud Platform
Yes
Bind AI
No
Clojure
No
CometAPI
No
Gemini Code Assist
No
Gemini Enterprise Agent Platform
No
Gemini Enterprise Agent Platform Notebooks
No
Google Opal
No
HTML
No
Java
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
Founded
1998
Country
United States
Website
gemini.google.com
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
research.meta.ai/blog/muse-ember