google/embeddinggemma-2 · Hugging Face

EmbeddingGemma 2 is an open multimodal embedding model developed by Google DeepMind. It maps various inputs, including text, code, images, video, and audio, into a unified 768-dimensional vector space. The model features 740M total parameters, comprising a 270M parameter text model, a 170M vision encoder, and a 300M audio encoder. A GGUF version is available from Unsloth.

This model is notable for its modular vision and audio encoders, unlike many multimodal models that use a single, monolithic architecture.