EmbeddingGemma 2: a 744M-parameter unified embedding model for text, image, audio and video
burkov · x · 2026-10-30
EmbeddingGemma 2 is a 744M-parameter model that converts text, images, audio, video, and mixtures into a shared embedding space for retrieval, similarity matching, and classification — avoiding costly transcription pipelines while fitting high-throughput and on-device settings. Modality encoders can be loaded selectively, and outputs and weights can be shortened or compressed for constrained hardware.
Related event: Google Open-Sources EmbeddingGemma 2, a 744M Omni-Modal Embedding Model(13 posts)→
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