We present EmbeddingGemma 2, an open multimodal embedding model which natively represents text, images, audio, video, and combinations thereof in a unified space. Our approach introduces improvements
EmbeddingGemma 2 is an open multimodal embedding model that unifies text, images, audio, and video representations with efficient resource-flexible design and state-of-the-art benchmark performance.
We present EmbeddingGemma 2, an open multimodal embedding model which natively represents text, images, audio, video, and combinations thereof in a unified space. Our approach introduces improvements such as simplified per-layer embeddings and a multi-stage curriculum with modality and objective progression which ensure strong quality across unimodal, cross-modal, and mixed-modal evaluations. Notably, in comprehensive embedding benchmarks across all modalities, EmbeddingGemma 2 establishes a new Pareto frontier, outperforming both specialist models and models two to twelve times larger. Furthermore, our design offers flexibility for resource-constrained environments, supporting selective…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
EmbeddingGemma 2: Unified and Efficient Multimodal Representations was first seen on Hugging Face · Daily papers on Oct 28, 2026. Since then it has appeared in 20 checks on 3 different days. Its best position was #7 of 30, reached on Oct 30, 05:28 UTC. It dropped off the list after Oct 30, 07:28 UTC.
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#7 on Hugging Face · Daily papers, on Oct 30, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 28, 2026 and has been on the list on 3 days (20 checks) since.