Qwen/Qwen3-VL-Embedding-2B
sentence-similarity model by Qwen
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
The Qwen3-VL-Embedding and Qwen3-VL-Reranker model series are the latest additions to the Qwen family, built upon the recently open-sourced and powerful Qwen3-VL foundation model. Specifically designed for multimodal information retrieval and cross-modal understanding, this suite accepts diverse inputs including text, images, screenshots, and videos, as well as inputs containing a mixture of these modalities. While the Embedding model generates high-dimensional vectors for broad applications like retrieval and clustering, the Reranker model is engineered to refine these results, establishing a comprehensive pipeline for state-of-the-art multimodal search. Qwen3-VL-Embedding-2B has the following features: For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our technical report, blog, GitHub. Results on the MMEB-V2 benchmark. All models except IFM-TTE have been re-evaluated on the updated VisDoc OOD…
Read the full model card ↗ · Preview checked 2026-10-30T07:34:37.535Z
Inside the original model card — Document outline
- Qwen3-VL-Embedding-2B
- Highlights
- Model Overview
- Qwen3-VL-Embedding and Qwen3-VL-Reranker Model list
- Model Performance
- Evaluation Results on MMEB-V2
- Evaluation Results on MMTEB
- Usage
- Sentence Transformers
- Using transformers
- Basic Usage Example
- vLLM Basic Usage Example
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
Qwen/Qwen3-VL-Embedding-2B is a sentence-similarity model repository published by Qwen on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 606,325
- Cumulative likes
- 491
- Hugging Face trending score
- 5
- Reported safetensors parameters
- 2,127,532,032
- Architecture
- Qwen3VLForConditionalGeneration
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-01-07T03:03:25.000Z
- Last modified
- 2026-04-16T08:54:25.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Qwen/Qwen3-VL-2B-Instruct
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:31.802Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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