{"slug": "google-embeddinggemma-2", "title": "Google EmbeddingGemma 2", "summary": "Google released EmbeddingGemma 2, a 740M-parameter multimodal embedding model that maps text, code, images, video, and audio into a single unified embedding space under an Apache 2.0 license. The model offers flexible output dimensions from 768 down to 128 via Matryoshka Representation Learning and an 8K context window, four times larger than the text-only EmbeddingGemma, and is optimized for on-device use with modular encoders.", "body_md": "Introducing EmbeddingGemma 2! 🚀\nOur lightweight, multimodal embedding model maps text, code, images, video, and audio into a single, unified embedding space. Optimized for on-device use cases, it features:\n- 740M parameter form factor with modular encoders\n- Flexible dimension sizes (768dim-128dim) via Matryoshka Representation Learning (MRL)\n- 8K context window (4x larger than text-only EmbeddingGemma)\n- A commercially permissive Apache 2.0 license\n\n00:00", "url": "https://wpnews.pro/news/google-embeddinggemma-2", "canonical_source": "https://twitter.com/googlegemma/status/2107502533992464482", "published_at": "2026-10-06 21:20:45+00:00", "updated_at": "2026-10-06 21:49:11.602131+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "ai-research", "ai-tools", "natural-language-processing"], "entities": ["Google", "EmbeddingGemma 2", "EmbeddingGemma", "Matryoshka Representation Learning"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/google-embeddinggemma-2", "markdown": "https://wpnews.pro/news/google-embeddinggemma-2.md", "text": "https://wpnews.pro/news/google-embeddinggemma-2.txt", "jsonld": "https://wpnews.pro/news/google-embeddinggemma-2.jsonld"}}