This is the Windows app named Qwen3-VL-Embedding whose latest release can be downloaded as Qwen3-VL-Embeddingsourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Qwen3-VL-Embedding
DESCRIPTION:
Qwen3-VL-Embedding (with its companion Qwen3-VL-Reranker) is a state-of-the-art multimodal embedding and reranking model suite built on the open-sourced Qwen3-VL foundation, developed to handle diverse inputs including text, images, screenshots, and videos. The core embedding model maps such inputs into semantically rich vectors in a unified representation space, enabling similarity search, clustering, and cross-modal retrieval. The reranking model then precisely scores relevance between a given query and candidate documents, enhancing retrieval accuracy in complex multimodal tasks. Together, they support advanced information retrieval workflows such as image-text search, visual question answering (VQA), and video-text matching, while providing out-of-the-box support for more than 30 languages.
Features
- Unified multimodal embedding for text, images, and video
- High-precision reranking model for relevance scoring
- Support for single and mixed modality inputs
- Flexible vector dimensions with Matryoshka Representation Learning
- Multilingual support for global applications
- Easy integration into existing retrieval pipelines
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/qwen3-vl-embedding.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.