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Pyyan / Compare / Cohere Parse 5 vs dots.ocr vs Qwen3-VL

Cohere Parse 5 vs dots.ocr vs Qwen3-VL

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OCR & Document AI · verified 2 Sept 2026

×CCohere Parse 5Coherecurrent
×dots.ocrXiaohongshucurrent
×Qwen3-VLAlibabacurrent
2 slots left
SpecificationCohere Parse 5dots.ocrQwen3-VL
SummaryLoses the benchmark, wins the invoice. $1.50 per thousand pages.Small, multilingual, layout-aware.A general vision model that happens to lead OCR benchmarks.
OmniDocBench79.2 on ParseBench~93~93
Open weightsNoYesYes
HandlesTables as HTML, forms, diagrams, bounding boxesLayout, 100+ languagesDocuments, charts, video
LicenceProprietaryMITApache 2.0
KindVision language model, 2.3BVision language modelVision language model
CategoryOCR & Document AIOCR & Document AIOCR & Document AI
Official—Xiaohongshu ↗Alibaba ↗

Highlighted rows are where these differ.

Cohere Parse 5

  • 2.3B vision language model, about 4.6GB, that turns a page into clean Markdown
  • Scores 79.2 on Cohere's ParseBench, behind GPT-5.5 at 84.4 and Opus 4.8 at 84.3
  • $1.50 per thousand pages at 4.5 pages a second, which is where it actually wins

Best for documents at volume.

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 →