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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 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
AiAssistWorks
BLACKBOX AI
BaseRT
CSS
FriendliAI
Gemini
Gemini Enterprise
Google Colab
HTML
JavaScript
Julia
Kaggle
Ollama
OpenCode
R
Ruby
TypeScript
Visual Basic
scribe

Integrations Supported

Gemini Enterprise Agent Platform

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Free Version

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

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

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

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