EmbeddingGemma 2Google
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MarengoTwelveLabs
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About
EmbeddingGemma 2 is an open, lightweight multimodal embedding model designed to map text, code, images, video, and audio into a shared embedding space for search, retrieval, classification, routing, and RAG applications. Built on the Gemma 4 architecture and released under the Apache 2.0 license, it has 740 million parameters and is optimized for on-device inference. Its modular design can use as little as 270M parameters for text-only workloads, with optional vision and audio encoders for full multimodal support. Matryoshka Representation Learning lets developers reduce output vectors from 768 dimensions to 512, 256, or 128, lowering storage and memory requirements for local vector databases. The model supports an 8K-token context window and can process up to 5.5 minutes of audio, 29 images, 58 video frames, or interleaved combinations on local hardware.
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About
Marengo is a multimodal video foundation model that transforms video, audio, image, and text inputs into unified embeddings, enabling powerful “any-to-any” search, retrieval, classification, and analysis across vast video and multimedia libraries. It integrates visual frames (with spatial and temporal dynamics), audio (speech, ambient sound, music), and textual content (subtitles, overlays, metadata) to create a rich, multidimensional representation of each media item. With this embedding architecture, Marengo supports robust tasks such as search (text-to-video, image-to-video, video-to-audio, etc.), semantic content discovery, anomaly detection, hybrid search, clustering, and similarity-based recommendation. The latest versions introduce multi-vector embeddings, separating representations for appearance, motion, and audio/text features, which significantly improve precision and context awareness, especially for complex or long-form content.
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Platforms Supported
Windows
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Mac
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Linux
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Cloud
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On-Premises
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iPhone
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iPad
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Android
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Chromebook
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Developers and AI teams wanting to build private, efficient, on-device multimodal search, retrieval, RAG, and semantic indexing systems
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Audience
Media companies, AI researchers, and platforms searching for a tool to build smart search engines, content discovery tools, recommendation systems, or video-analysis workflows
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Support
Phone Support
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24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
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API
Offers API
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API
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Pricing
No information available.
Free Version
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Free Trial
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Pricing
$0.042 per minute
Free Version
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Free Trial
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Reviews/
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Training
Documentation
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Webinars
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Live Online
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In Person
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Training
Documentation
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Webinars
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Live Online
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In Person
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Company InformationGoogle
Founded: 1998
United States
blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/
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Company InformationTwelveLabs
Founded: 2021
United States
www.twelvelabs.io/product/models-overview#marengo
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TwelveLabs
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