# Unified Text-Image Encoding

ColNomic Embed Multimodal 7B is a state-of-the-art multi-vector multimodal embedding model, excelling in visual document retrieval tasks with support for multilingual and unified text-image encoding.

A 7-billion-parameter multimodal embedding model specialized in visual document retrieval tasks, achieving outstanding performance on the Vidore-v2 benchmark

Nomic Embed Multimodal 3B is a cutting-edge multimodal embedding model focused on visual document retrieval tasks, supporting unified text-image encoding, achieving an outstanding performance of 58.8 NDCG@5 in the Vidore-v2 test.

ColNomic Embed Multimodal 3B is a 3-billion-parameter multimodal embedding model specifically designed for visual document retrieval tasks, supporting unified encoding of multilingual text and images.