Gemma 3
Multimodal capabilities and wide language support in developer-friendly sizes.
A collection of lightweight, state-of-the-art open models built from the same technology that powers our Gemini models*
A family of lightweight models with multimodal understanding and unparalleled multilingual capabilities for more intelligent applications.
Our powerful and efficient open model designed to run locally on phones, tablets, and laptops.
Our most advanced open models help developers create AI applications that run wherever users need them — from workstations to laptops and even phones.
Multimodal capabilities and wide language support in developer-friendly sizes.
Mobile-first architecture optimized for low-latency audio and visual understanding.
Text embedding model optimized for on-device use cases.
Encoder-decoder models that provide a strong quality-inference efficiency tradeoff.
Gemma 3 variant optimized for medical text and image comprehension.
Designed to improve the efficiency of therapeutic development.
Safety content classifier models designed to detect harmful content in AI models’ text inputs and outputs.
Vision-language models that can interpret text and image inputs.
Language model that uses dolphin audio to help scientists study how dolphins communicate.
A novel recurrent architecture for faster processing of long sequences.
Interpretability tools built to help researchers understand the inner workings of Gemma 2.
Gemma 2 models that integrate retrieval techniques to ground responses in real-world data.
Powerful, lightweight models that can perform a variety of coding tasks.
Discover the latest advancements in Gemma, Google's family of lightweight, state-of-the-art open models.
Hear how the Gemma research team unveil the architecture, design principles, and innovations behind Google's family of lightweight, state-of-the-art open models.
Explore the development of intelligent agents using Gemma models, with core components that facilitate agent creation, including capabilities for function calling, planning, and reasoning.
Building multilingual AI applications is crucial for reaching global audiences, and varied language proficiency remains a top developer priority.
Large Language Models (LLMs), such as Gemma, may sometimes provide inaccurate or offensive content that doesn’t represent Google’s views.
Use discretion before relying on, publishing, or otherwise using content provided by LLMs.
Don’t rely on LLMs for medical, legal, financial, or other professional advice. Any content regarding those topics is provided for informational purposes only and is not a substitute for advice from a qualified professional.