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What is TranslateGemma?

TranslateGemma represents a groundbreaking suite of open machine translation models developed by Google, grounded in the Gemma 3 architecture, which enables effective communication among people and systems in 55 languages by delivering superior AI translations while promoting efficiency and extensive deployment alternatives. Available in configurations of 4 B, 12 B, and 27 B parameters, TranslateGemma consolidates advanced multilingual capabilities into efficient models that operate seamlessly on mobile devices, personal laptops, local systems, or cloud platforms, all while maintaining high levels of accuracy and performance; evaluations suggest that the 12 B model can outperform larger baseline counterparts while utilizing less computational resources. The creation of these models employed a unique two-phase fine-tuning strategy that combines top-tier human and synthetic translation datasets, leveraging reinforcement learning techniques to improve translation precision across diverse language families. This revolutionary approach guarantees that users have access to a wide range of languages and enjoy quick and dependable translations, making it an essential tool for global communication. Ultimately, TranslateGemma's design not only enhances language accessibility but also streamlines the translation process for various applications.

What is Gemma?

Gemma encompasses a series of innovative, lightweight open models inspired by the foundational research and technology that drive the Gemini models. Developed by Google DeepMind in collaboration with various teams at Google, the term "gemma" derives from Latin, meaning "precious stone." Alongside the release of our model weights, we are also providing resources designed to foster developer creativity, promote collaboration, and uphold ethical standards in the use of Gemma models. Sharing essential technical and infrastructural components with Gemini, our leading AI model available today, the 2B and 7B versions of Gemma demonstrate exceptional performance in their weight classes relative to other open models. Notably, these models are capable of running seamlessly on a developer's laptop or desktop, showcasing their adaptability. Moreover, Gemma has proven to not only surpass much larger models on key performance benchmarks but also adhere to our rigorous standards for producing safe and responsible outputs, thereby serving as an invaluable tool for developers seeking to leverage advanced AI capabilities. As such, Gemma represents a significant advancement in accessible AI technology.

Media

Media

Integrations Supported

Gemini Enterprise Agent Platform
AiAssistWorks
Atomic Chat
Cake AI
DiffusionGemma
GaiaNet
Gemma
HTML
Hugging Face
Kaggle
Kotlin
Nutanix Enterprise AI
Ollama
Onyxium
PaliGemma 2
Ruby
TensorFlow
TranslateGemma
Undrstnd
WebLLM

Integrations Supported

Gemini Enterprise Agent Platform
AiAssistWorks
Atomic Chat
Cake AI
DiffusionGemma
GaiaNet
Gemma
HTML
Hugging Face
Kaggle
Kotlin
Nutanix Enterprise AI
Ollama
Onyxium
PaliGemma 2
Ruby
TensorFlow
TranslateGemma
Undrstnd
WebLLM

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

blog.google/innovation-and-ai/technology/developers-tools/translategemma/

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

ai.google.dev/gemma

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