Hugging Face (Twitter)

RT @Alibaba_Qwen: 🚀 Introducing Qwen3-VL-Embedding and Qwen3-VL-Reranker – advancing the state of the art in multimodal retrieval and cross-modal understanding!
✨ Highlights:
✅ Built upon the robust Qwen3-VL foundation model
✅ Processes text, images, screenshots, videos, and mixed modality inputs
✅ Supports 30+ languages
✅ Achieves state-of-the-art performance on multimodal retrieval benchmarks
✅ Open source and available on Hugging Face, GitHub, and ModelScope
✅ API deployment on Alibaba Cloud coming soon!

🎯 Two-stage retrieval architecture:
📊 Embedding Model – generates semantically rich vector representations in a unified embedding space
🎯 Reranker Model – computes fine-grained relevance scores for enhanced retrieval accuracy

🔍 Key application scenarios:
Image-text retrieval, video search, multimodal RAG, visual question answering, multimodal content clustering, multilingual visual search, and more!

🌟 Developer-friendly capabilities:
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