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Pyyan / Compare / PaddleOCR vs dots.ocr vs Qwen3-VL

PaddleOCR vs dots.ocr vs Qwen3-VL

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OCR & Document AI · verified 13 Aug 2026

×PaddleOCRBaiducurrent
×dots.ocrXiaohongshucurrent
×Qwen3-VLAlibabacurrent
2 slots left
SpecificationPaddleOCRdots.ocrQwen3-VL
SummaryThe classical workhorse, still widely deployed.Small, multilingual, layout-aware.A general vision model that happens to lead OCR benchmarks.
OmniDocBench~82~93~93
Open weightsYesYesYes
HandlesText, tables, receiptsLayout, 100+ languagesDocuments, charts, video
LicenceApache 2.0MITApache 2.0
KindClassical engineVision language modelVision language model
CategoryOCR & Document AIOCR & Document AIOCR & Document AI
OfficialBaidu ↗Xiaohongshu ↗Alibaba ↗

Highlighted rows are where these differ.

PaddleOCR

  • Runs on CPU and mobile
  • Predates the VLM approach and still ships in production

Best for on-device and offline recognition.

Full spec sheet →

dots.ocr

  • Layout and content in one pass
  • Strong for its size

Best for multilingual layout parsing.

Full spec sheet →

Qwen3-VL

  • Not an OCR model, and beats most of them
  • Sizes from 2B to 235B

Best for one model for vision and documents.

Full spec sheet →