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AI CURATED HOT STORY · 10/29/2026

Google Releases EmbeddingGemma 2 for On-Device Multimodal AI

1 reports archived1 independent sourcesupdated 10/29/2026, 12:00:56
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Google has open-sourced EmbeddingGemma 2, a unified multimodal embedding model supporting text, code, images, audio, and video. With only 744M parameters, it outperforms models 2-12x larger while requiring just ~567MB RAM on a Pixel 11 Pro, enabling private on-device search.

LATEST/Google has open-sourced EmbeddingGemma 2, a unified multimodal embedding model supporting text, code, images, audio, and video. With only 744M parameters, it outperforms models 2-12x larger while requiring just ~567MB RAM on a Pixel 11 Pro, enabling private on-device search.

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Total 1 reports · Latest first
  1. Rohan Paul (@rohanpaul_ai)T2·85 pts

    Google Releases EmbeddingGemma 2 for On-Device Multimodal AI

    • Supports a unified vector space for text, code, images, audio, and video with an 8K token context window.
    • The 744M parameter model outperforms competitors 2-12x its size; direct speech embedding beats transcription-based retrieval.
    • Released under Apache 2.0, it requires only ~567MB RAM on a Pixel 11 Pro when quantized, ideal for on-device deployment.