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Google DeepMind unveils EmbeddingGemma 2 multimodal model

By PulseAugur Editorial · [2 sources] ·

Google DeepMind has released EmbeddingGemma 2, a new open-source, natively multimodal model designed for on-device embeddings. This model expands beyond text to process and unify code, images, audio, and video within a shared space. With 740 million parameters, EmbeddingGemma 2 demonstrates competitive performance across various benchmarks, even surpassing some larger specialist models, and is available under the Apache 2.0 license. AI

IMPACT Enables on-device multimodal search and integration with other models for private RAG applications.

RANK_REASON Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=2 ai=1.0]

Read on X — Google DeepMind →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Google DeepMind unveils EmbeddingGemma 2 multimodal model

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4 / 100
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Significant
Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=2 ai=1.0]
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2 independent sources
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Topics
model release, product
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High
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Same-day
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COVERAGE [2]

  1. X — Google DeepMind TIER_1 English(EN) · GoogleDeepMind ·

    At 740M parameters, it’s competitive across benchmarks – even outperforming some specialist models more than twice its size.

    At 740M parameters, it’s competitive across benchmarks – even outperforming some specialist models more than twice its size. Developers can use it to add multimodal search to their apps – like finding moments in a video using a voice memo – or pair it with Gemma 4 for private, h…

  2. X — Google DeepMind TIER_1 English(EN) · GoogleDeepMind ·

    Meet EmbeddingGemma 2, our first natively multimodal open model for on-device embeddings.

    Meet EmbeddingGemma 2, our first natively multimodal open model for on-device embeddings. It expands beyond text to unify code, images, audio, and video in a shared space. 🧵 https://t.co/DC31z5viWD

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