Google EmbeddingGemma 2
Updated
About Google EmbeddingGemma 2
Google EmbeddingGemma 2 is an open embedding model that maps text, code, images, video and audio into a single shared space.
Developers and builders use this to create search and retrieval features that work across different types of content in a single query. It's built to run on-device on phones and other resource-constrained hardware, keeping data private without needing cloud infrastructure.
- Maps text, code, images, video and audio into one embedding space
- Runs on-device with 191MB RAM for text-only or 567MB for full multimodal
- Modular encoders you can load separately to save memory
- 8K token context, handles about 5.5 minutes of audio or 29 images
- Vectors shrink from 768 to 128 dimensions for smaller storage needs
Good to know: Open source under Apache 2.0 license with weights available on Hugging Face and Kaggle.
Key features
- Multimodal in one space: A text query can find photos, and a voice memo can retrieve video clips from the same embedding space.
- Runs locally on phones: The full model uses only 567MB RAM on a Pixel 11 Pro, keeping all data on-device without cloud uploads.
- Modular and memory-efficient: Load only the encoders you need, with options as small as 270M parameters for text and code alone.
At a glance
- Category: AI Research
- Type: AI model & API platform
- Jobs: Build Sites & Apps
- Evidence: New launch on Product Hunt (a few reviews)
- AIME Score: 57 of 100
- Launched: Oct 12, 2026 on Product Hunt · 100+ upvotes
- Website: blog.google
Alternatives to Google EmbeddingGemma 2
- Azure OpenAI Service (AIME Score 65)
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Sources: Found on Product Hunt (launched Oct 2026) · Details checked on the tool’s own website · Researched by AI Made Easy
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