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What is Gemma 3n?

Meet Gemma 3n, our state-of-the-art open multimodal model engineered for exceptional performance and efficiency on devices. Emphasizing responsive and low-footprint local inference, Gemma 3n sets the stage for a new era of intelligent applications that can be deployed while on the go. It possesses the ability to interpret and react to a combination of images and text, with upcoming plans to add video and audio capabilities shortly. This allows developers to build smart, interactive functionalities that uphold user privacy and operate smoothly without relying on an internet connection. The model features a mobile-centric design that significantly reduces memory consumption. Jointly developed by Google's mobile hardware teams and industry specialists, it maintains a 4B active memory footprint while providing the option to create submodels for enhanced quality and reduced latency. Furthermore, Gemma 3n is our first open model constructed on this groundbreaking shared architecture, allowing developers to begin experimenting with this sophisticated technology today in its initial preview. As the landscape of technology continues to evolve, we foresee an array of innovative applications emerging from this powerful framework, further expanding its potential in various domains. The future looks promising as more features and enhancements are anticipated to enrich the user experience.

What is DataGemma?

DataGemma represents a revolutionary effort by Google designed to enhance the accuracy and reliability of large language models, particularly in their processing of statistical data. Launched as a suite of open models, DataGemma leverages Google's Data Commons, an extensive repository of publicly accessible statistical information, ensuring that its outputs are grounded in actual data. This initiative unveils two innovative methodologies: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG technique integrates real-time data validation throughout the content creation process to uphold factual correctness, while RAG aims to gather relevant information before generating responses, significantly reducing the likelihood of inaccuracies often labeled as AI hallucinations. By employing these approaches, DataGemma seeks to provide users with more trustworthy and factually sound answers, marking a significant step forward in the battle against misinformation in AI-generated content. Moreover, this initiative not only highlights Google's dedication to ethical AI practices but also improves user engagement by building confidence in the material presented. By focusing on the intersection of data integrity and user trust, DataGemma aims to redefine the standards of information accuracy in the digital landscape.

Media

Media

Integrations Supported

Gemini
Gemini Enterprise
Gemini Nano
Gemini Enterprise Agent Platform
Gemma
Google AI Edge
Google AI Edge Gallery
Google AI Studio
Google Cloud Platform
Hugging Face
JAX
Keras
Ollama
OpenCode
PyTorch

Integrations Supported

Gemini
Gemini Enterprise
Gemini Nano
Gemini 1.5 Flash
Gemini 1.5 Pro
Gemini 2.0
Gemini Pro
Google AI Plus

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Google DeepMind

Date Founded

2010

Company Location

United Kingdom

Company Website

deepmind.google/models/gemma/gemma-3n/

Company Facts

Organization Name

Google

Date Founded

1994

Company Location

United States

Company Website

blog.google/technology/ai/google-datagemma-ai-llm/

Categories and Features

AI Models

Not specified

Multimodal Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

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