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EmbeddingGemma

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

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.

Capabilities

Scatter plot titled 'MTEB (Multilingual, v2), Score by model size' comparing embedding models. The 'EmbeddingGemma' model is highlighted with a blue dot, showing a mean task score of approximately 61 at a model size of roughly 300M, outperforming similarly sized models like 'gte-multilingual-base'Scatter plot titled 'MTEB (Multilingual, v2), Score by model size' comparing embedding models. The 'EmbeddingGemma' model is highlighted with a blue dot, showing a mean task score of approximately 61 at a model size of roughly 300M, outperforming similarly sized models like 'gte-multilingual-base'

Get started with EmbeddingGemma

Try the model by generating embeddings in an interactive notebook.

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