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What is Gemma 3?

Gemma 3, introduced by Google, is a state-of-the-art AI model built on the Gemini 2.0 architecture, specifically engineered to provide enhanced efficiency and flexibility. This groundbreaking model is capable of functioning effectively on either a single GPU or TPU, which broadens access for a wide array of developers and researchers. By prioritizing improvements in natural language understanding, generation, and various AI capabilities, Gemma 3 aims to advance the performance of artificial intelligence systems significantly. With its scalable and durable design, Gemma 3 seeks to drive the progression of AI technologies across multiple fields and applications, ultimately holding the potential to revolutionize the technology landscape. As such, it stands as a pivotal development in the continuous integration of AI into everyday life and industry practices.

What is Gemma 2?

The Gemma family is composed of advanced and lightweight models that are built upon the same groundbreaking research and technology as the Gemini line. These state-of-the-art models come with powerful security features that foster responsible and trustworthy AI usage, a result of meticulously selected data sets and comprehensive refinements. Remarkably, the Gemma models perform exceptionally well in their varied sizes—2B, 7B, 9B, and 27B—frequently surpassing the capabilities of some larger open models. With the launch of Keras 3.0, users benefit from seamless integration with JAX, TensorFlow, and PyTorch, allowing for adaptable framework choices tailored to specific tasks. Optimized for peak performance and exceptional efficiency, Gemma 2 in particular is designed for swift inference on a wide range of hardware platforms. Moreover, the Gemma family encompasses a variety of models tailored to meet different use cases, ensuring effective adaptation to user needs. These lightweight language models are equipped with a decoder and have undergone training on a broad spectrum of textual data, programming code, and mathematical concepts, which significantly boosts their versatility and utility across numerous applications. This diverse approach not only enhances their performance but also positions them as a valuable resource for developers and researchers alike.

Media

Media

Integrations Supported

C
CSS
Clojure
F#
Gemini Enterprise Agent Platform
Google AI Studio
Google Colab
Hugging Face
Java
JavaScript
Julia
Kaggle
Kotlin
MedGemma
Nebius Token Factory
PyTorch
R
Rust
SQL
Scala

Integrations Supported

C
CSS
Clojure
F#
Gemini Enterprise Agent Platform
Google AI Studio
Google Colab
Hugging Face
Java
JavaScript
Julia
Kaggle
Kotlin
MedGemma
Nebius Token Factory
PyTorch
R
Rust
SQL
Scala

API Availability

API Availability

Has API

Pricing Information

Free
Open source
Free Version

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

deepmind.google/models/gemma/

Company Facts

Organization Name

Google

Company Location

United States

Company Website

ai.google.dev/gemma

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

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