Which is more popular, Dolphin or olmocr?

olmocr has more GitHub stars (19,687 vs 9,059).

Which is more actively developed, Dolphin or olmocr?

Dolphin had more commits in the last 90 days (0 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

olmocr is growing faster: +413 GitHub stars in the last 30 days vs +28 for Dolphin.
Pick Dolphin for: the official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025. Pick olmocr for: toolkit for linearizing PDFs for LLM datasets/training.

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The official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025.

olmocropen-source

Toolkit for linearizing PDFs for LLM datasets/training

+Universal document parsing capability that handles both digital and photographed documents seamlessly
+Advanced two-stage architecture with document-type-aware parsing strategies optimized for different document formats
+Comprehensive 21-element detection including complex elements like formulas, code blocks, and tables with attribute field extraction

+Excellent handling of complex document layouts including equations, tables, handwriting, and multi-column formats with natural reading order preservation
+Cost-effective processing at under $200 per million pages, making it economical for large-scale dataset creation
+Continuous model improvements with recent releases showing significant performance gains and reduced hallucinations on blank documents

-Research-focused tool that may require significant technical expertise to implement and integrate
-Relatively new release with limited production use cases and community feedback
-Large model size (3B parameters) may require substantial computational resources for deployment

-Requires GPU resources due to 7B parameter model, making it computationally intensive and potentially expensive to run
-May require multiple retries for some documents to achieve optimal results
-Limited to image-based document formats (PDF, PNG, JPEG) and requires technical expertise for setup and optimization

•Academic research document digitization and content extraction from PDFs and scanned papers
•Enterprise document processing for complex reports, invoices, and forms with mixed content types
•Automated parsing of technical documentation containing code snippets, mathematical formulas, and diagrams

•Converting academic papers and research documents with complex equations and figures for LLM training datasets
•Processing legacy document archives with multi-column layouts and mixed content types into searchable text format
•Creating high-quality training data from technical manuals, textbooks, and scientific publications for domain-specific language models

Which is more popular, Dolphin or olmocr?: olmocr has more GitHub stars (19,687 vs 9,059).
Which is more actively developed, Dolphin or olmocr?: Dolphin had more commits in the last 90 days (0 vs 0).
Should I use Dolphin or olmocr?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.