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Cohere Parse 5 vs Qwen3-VL vs DeepSeek-OCR

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OCR & Document AI · verified 2 Sept 2026

×CCohere Parse 5Coherecurrent
×Qwen3-VLAlibabacurrent
×DeepSeek-OCRDeepSeekcurrent
2 slots left
SpecificationCohere Parse 5Qwen3-VLDeepSeek-OCR
SummaryLoses the benchmark, wins the invoice. $1.50 per thousand pages.A general vision model that happens to lead OCR benchmarks.Compresses pages into far fewer vision tokens.
OmniDocBench79.2 on ParseBench~93~92
Open weightsNoYesYes
HandlesTables as HTML, forms, diagrams, bounding boxesDocuments, charts, videoDense text, tables
LicenceProprietaryApache 2.0MIT
KindVision language model, 2.3BVision language modelVision language model
CategoryOCR & Document AIOCR & Document AIOCR & Document AI
Official—Alibaba ↗DeepSeek ↗

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 →

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 →

DeepSeek-OCR

  • Treats the page image as compressed context
  • Notable for cost per page rather than raw accuracy

Best for long documents on a budget.

Full spec sheet →