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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 DiffusionGemma?

DiffusionGemma is a groundbreaking open model that delves into the phenomenon of text diffusion, offering an exceptionally quick approach to text generation. Licensed under Apache 2.0, this model features a staggering 26 billion parameters and utilizes a Mixture of Experts (MoE) architecture, pushing the boundaries beyond the conventional sequential token generation found in autoregressive models. Rather than generating tokens one by one, it is capable of producing complete blocks of text simultaneously, yielding generation speeds that can be up to four times quicker on GPUs. With foundations rooted in the parameter efficiency of the Gemma 4 family and insights from Gemini Diffusion research, DiffusionGemma boasts a distinctive diffusion head that significantly accelerates the generation process. Its design targets researchers and developers focused on optimizing local workflows that demand speed, such as in-line editing, rapid iterations, and complex narrative structures. By shifting the decoding bottleneck from memory bandwidth to computational capacity, the model can generate over 1,000 tokens per second on a single NVIDIA H100 and more than 700 tokens per second when utilizing an NVIDIA GeForce RTX 5090. This advancement not only enhances efficiency in text generation but also opens up new possibilities for various applications in the realm of natural language processing, paving the way for innovative developments in the field. Ultimately, the capabilities of DiffusionGemma could lead to transformative changes in how we approach text generation tasks.

Media

Media

Integrations Supported

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

Integrations Supported

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

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

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 DeepMind

Date Founded

2010

Company Location

United Kingdom

Company Website

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

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

blog.google/innovation-and-ai/technology/developers-tools/diffusion-gemma-faster-text-generation/

Categories and Features

Categories and Features

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