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arXiv · 2610.37364

EmbeddingGemma 2: Unified and Efficient Multimodal Representations

Henrique Schechter Vera·Sahil Dua·Jovan Andonov·Sara Smoot·Sebastian Russo·Ivan Llanos·Max Matveev·Jae Hyeon Yoo·Kat Black·Shih-Cheng Huang·Josiah Aklilu·Maarten Grootendorst·Omar Sanseviero·Chandramouli Amarnath·Ian Ballantyne·Zhe Li·Daniel Salz·Ibrahim Alabdulmohsin·Ilya Philippov·Kristen Quan·Glenn Cameron·Edouard Yvinec·Luciano Martins·Doug Reid·Sindhu Raghuram Panyam·Weiyi Wang·Hengxuan Ying·Madhuri Shanbhogue·Tanmaya Dabral·Shanfeng Zhang·Juyeong Ji·Renjie Wu·Joe Zou·Xu Chen·Yunan Zhang·Yu-Hui Chen·Matthew Soulanille·Vinod Mamillapalli·Yi-Chun Kuo·Wai Hon Law·Matt Kreileder·Alice Zheng·Suril Shah·Mogan Shieh·Pooja Consul·Alberto Montes·Andreas Hess·Andres Sevilla·Babak Samari·Brendan McCloskey·Brian Potetz·Daniel Cer·Georgios Kathareios·Gustavo Hernández Ábrego·Hesen Zhang·Ji Ma·Jiaxing Wu·Keegan Mosley·Paul Suganthan·Rui Meng·Shen Gao·Shengcao Cao·Yi-Ting Chen·Yichang Chen·Zhongli Ding·Kendra Byrne·Cormac Brick·Olivier Lacombe·Qin Yin·Tris Warkentin·Armand Joulin·Tom Duerig·Mojtaba Seyedhosseini
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Abstract

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 modality encoder loading, adjustable vision token budgets, truncatable embedding dimensions, and quantized weights. We present ablations analyzing key decisions and release EmbeddingGemma 2 to promote further research.

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Henrique Schechter Vera, Sahil Dua, Jovan Andonov, Sara Smoot, Sebastian Russo, Ivan Llanos, Max Matveev, Jae Hyeon Yoo, Kat Black, Shih-Cheng Huang, Josiah Aklilu, Maarten Grootendorst, Omar Sanseviero, Chandramouli Amarnath, Ian Ballantyne, Zhe Li, Daniel Salz, Ibrahim Alabdulmohsin, Ilya Philippov, Kristen Quan, Glenn Cameron, Edouard Yvinec, Luciano Martins, Doug Reid, Sindhu Raghuram Panyam, Weiyi Wang, Hengxuan Ying, Madhuri Shanbhogue, Tanmaya Dabral, Shanfeng Zhang, Juyeong Ji, Renjie Wu, Joe Zou, Xu Chen, Yunan Zhang, Yu-Hui Chen, Matthew Soulanille, Vinod Mamillapalli, Yi-Chun Kuo, Wai Hon Law, Matt Kreileder, Alice Zheng, Suril Shah, Mogan Shieh, Pooja Consul, Alberto Montes, Andreas Hess, Andres Sevilla, Babak Samari, Brendan McCloskey, Brian Potetz, Daniel Cer, Georgios Kathareios, Gustavo Hernández Ábrego, Hesen Zhang, Ji Ma, Jiaxing Wu, Keegan Mosley, Paul Suganthan, Rui Meng, Shen Gao, Shengcao Cao, Yi-Ting Chen, Yichang Chen, Zhongli Ding, Kendra Byrne, Cormac Brick, Olivier Lacombe, Qin Yin, Tris Warkentin, Armand Joulin, Tom Duerig, Mojtaba Seyedhosseini. 2026-10-27. EmbeddingGemma 2: Unified and Efficient Multimodal Representations. https://arxiv.org/abs/2610.37364

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