NVIDIA has released the Nemotron ColEmbed V2 models, designed for efficient multimodal document retrieval. These models utilize a late-interaction embedding approach to improve accuracy in handling text, images, and structured visual data. They perform well on the ViDoRe V3 benchmark, making them suitable for applications like multimedia search engines and conversational AI.

Qwen has released the Qwen3-VL-Embedding and Qwen3-VL-Reranker models, designed for advanced multimodal information retrieval and cross-modal understanding. These models support various inputs, including text and images, and enhance retrieval accuracy through a two-stage process of initial recall and precise re-ranking.