Google claims EmbeddingGemma 2 outperforms rival embedding models twice its size

Google released EmbeddingGemma 2, an open embedding model with 740 million parameters that converts text, images, video, audio, and code into vectors and runs on-device using about 191 MB of RAM. According to Google, EmbeddingGemma 2 outperforms some competing embedding models twice its size, and paired with a small open model like Gemma 4 it can power offline RAG apps without sending data to external servers.

Google released EmbeddingGemma 2, an open model with 740 million parameters that converts text, images, video, audio, and code into vectors. It runs on-device, needs only about 191 MB of RAM, and outperforms some competing models twice its size, according to Google. Paired with a small open model like Gemma 4, it can run offline RAG apps without sending data to external servers. The article Google claims EmbeddingGemma 2 outperforms rival embedding models twice its size https://the-decoder.com/google-claims-embeddinggemma-2-outperforms-rival-embedding-models-twice-its-size/ appeared first on The Decoder https://the-decoder.com .