From the model card
Fields below are copied from the tags and counters on the HuggingFace repository Qwen/Qwen2.5-VL-7B-Instruct at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- Qwen
- Pipeline tag
- image-text-to-text
- Library
- Transformers
- Weight formats
- safetensors
- License tag
apache-2.0— read the license file in the repo before relying on it- Language tags
- English (en)
- Papers cited
- arXiv:2309.00071, arXiv:2409.12191, arXiv:2308.12966
- Downloads (HF counter at last fetch)
- 7,720,403
- Likes (HF counter at last fetch)
- 1,697
- Model card
- https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct
Use cases
- Visual document understanding and OCR-adjacent reasoning
- Image-grounded QA for e-commerce or medical imagery
- Video frame analysis with text query inputs
- Local multimodal assistant on single-GPU workstations
- Structured data extraction from visual documents
Pros
- Apache 2.0 license for commercial use
- Dynamic resolution handling for varied input sizes
- Strong OCR and document parsing performance relative to 7B scale
- Text-generation-inference compatible for production serving
Cons
- 7B VLM requires GPU with 16GB+ VRAM for comfortable inference
- Superseded by Qwen3-VL in the same family
- Video input handling adds memory overhead vs. image-only inference
- Accuracy gaps vs. larger VLMs (13B+) on complex spatial reasoning tasks
- Not a general-purpose text-only model — prompting must account for vision input
Tags
transformerssafetensorsqwen2_5_vlimage-text-to-textmultimodalconversationalenarxiv:2309.00071arxiv:2409.12191arxiv:2308.12966license:apache-2.0eval-resultstext-generation-inferenceendpoints_compatibleregion:usdeploy:azure