Google Launches Gemini Embedding 2: A Breakthrough Native Multimodal Embeddings Model
product#embeddings📝 Blog|Analyzed: Apr 25, 2026 01:14•
Published: Apr 24, 2026 15:00
•1 min read
•Zenn MLAnalysis
Google has officially launched Gemini Embedding 2, marking a massive leap forward as their first native 多模态 嵌入 model. This innovative system empowers developers to seamlessly process text, images, video, audio, and PDFs within a single, unified vector space, which is a game-changer for advanced 检索增强生成 (RAG) applications. With expanded context limits and impressive multilingual support, it opens up incredible new possibilities for building highly responsive and intelligent search architectures.
Key Takeaways
- •Unified Vector Space: Seamlessly embeds text, images, video, audio, and PDFs together for next-generation search.
- •Expanded Capacity: Input limits have quadrupled from the previous version to a robust 8,192 tokens.
- •Highly Recommended for Japanese RAG: Positioned as the top candidate for Japanese text 检索增强生成 (RAG) systems.
Reference / Citation
View Original"初のネイティブ・マルチモーダル埋め込みモデルで、テキスト・画像・動画・音声・PDFを単一のベクトル空間に埋め込めます。"