Google发布EmbeddingGemma 2嵌入模型
Google claims EmbeddingGemma 2 outperforms rival embedding models twice its size
Google新发布的EmbeddingGemma 2体积小但性能强，适合在设备上运行RAG应用。
Google推出EmbeddingGemma 2，拥有7.4亿参数，可将文本、图像、视频、音频和代码转换为向量。该模型仅需约191MB内存，在设备上运行，性能超过某些体积两倍的竞争模型。搭配Gemma 4等小型开源模型，可离线运行RAG应用，无需将数据发送到外部服务器。
Google claims EmbeddingGemma 2 outperforms rival embedding models twice its size
Google released EmbeddingGemma 2, an open model with 740 million parameters that converts text, images, video, audio, and code into vectors. It runs on-device, needs only about 191 MB of RAM, and outperforms some competing models twice its size, according to Google. Paired with a small open model like Gemma 4, it can run offline RAG apps without sending data to external servers. The article Google claims EmbeddingGemma 2 outperforms rival embedding models twice its size appeared first on The Decoder .
