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EmbeddingGemma

Gemma

A collection of lightweight, state-of-the-art open models built from the same technology that powers our Gemini models

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Introducing Gemma 3 270M: The compact model for hyper-efficient AI

Our most advanced open models help developers create AI applications that run wherever users need them — from workstations to laptops and even phones.

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We’re exploring applications for Gemma as a code generator, in healthcare support roles, and even as a research tool in the animal kingdom.

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Hugging Face Transformers

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A GitHub repository, collecting quickstart guides and code examples.

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Revisit past Developer Days, I/O sessions and other events where we’ve shared updates, and highlighted new opportunities for developers using our open models.

Building intelligent agents with Gemma 3

Explore the development of intelligent agents using Gemma models, with core components that facilitate agent creation, including capabilities for function calling, planning, and reasoning.

Welcome to Gemma 3

Discover the latest advancements in Gemma, Google's family of lightweight, state-of-the-art open models.

Deepdive into Gemma 3

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.

A truly multilingual Gemma 3

Building multilingual AI applications is crucial for reaching global audiences, and varied language proficiency remains a top developer priority.

Explore the Gemmaverse

A vast ecosystem of community-created Gemma models and tools, ready to spark imagination and power innovation.

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EmbeddingGemma

EmbeddingGemma

A best-in-class text embedding model optimized for on-device use cases

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EmbeddingGemma generates high-quality embeddings with reduced resource consumption, enabling on-device Retrieval Augmented Generation (RAG) pipelines, semantic search, and generative AI applications that can run on everyday devices.

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Capabilities

  • Engineered for efficiency

    A 308M parameter model that can run on less than 200MB of RAM with quantization

  • Strong multilingual performance

    Trained on over 100 languages, providing best-in-class text understanding for its size

  • Fast and flexible

    Leverages Matryoshka Representation Learning (MRL) for customizable embedding dimensions

Performance

EmbeddingGemma is the highest ranking open multilingual text embedding model under 500M parameters on the Massive Text Embedding Benchmark (MTEB).

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Explore the model in an interactive Colab notebook.

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