Multimodal Embedding & Reranker Models with Sentence Transformers
Hugging Face Blog
Sentence Transformers library version 5.4 now enables users to encode and compare text, images, audio, and video using a unified API for embedding and reranking tasks. The Qwen3-VL-Embedding-2B model requires approximately 8 GB of GPU VRAM, with 20 GB needed for 8B variants. This multimodal capability allows new applications such as visual document retrieval, cross-modal search, and retrieval-augmented generation pipelines that combine different input types.