We tested five open-source PDF-to-Markdown libraries on the same three mixed PDFs — a hybrid annual report, a table-heavy financial filing, and a scanned research paper — to compare text preservation, table reconstruction, chart handling, image retention, reading order, and OCR behavior.
The strongest overall open-source option here: it kept text, tables, headings, and reading order very well across all three PDFs, but it still dropped charts and standalone images.
The tool does not turn charts into usable content; in both chart-heavy tests, the visuals were simply removed instead of being translated into values or a faithful description, so this is a core failure.
The evidence-backed checks show the shape of the field; coverage explains the gaps.
Columns, left to right: Bonus: Unique or Anomalous Behaviors · Caption/Figure Association · Chart Reconstruction · Document Hierarchy · Image Retention · Long/Complex Document Robustness · Reading Order Preservation · Table Reconstruction · Text Preservation
Pick the tools you care about, then compare what they returned or how they scored.
It handled the annual report’s text, tables, headings, footnotes, and form checkbox well, but it dropped charts and images and got a little messy on one multi-column list.
docling-docling-input1-hybridearnings-financial--8a3362cde025.png
Strong on prose, headings, reading order, and caption placement, but the chart is dropped to a placeholder, tables lose some structure, and image handling is only nominal.
liteparse-liteparse-input1-hybridearnings-financia-d6a350ffc82b.png
It handles the clean annual report well: text, tables, heading structure, reading order, and footnotes stay solid, but charts lose their plotted form and standalone images are dropped.
pymupdf4llm-pymupdf4llm-input1-hybridearnings-chart--d7b12acca715.png
It does well on prose and section titles, but the charts, tables, images, and multi-column page all come out badly, so the report is only partly usable.
doc2mark-doc2mark-input1-hybridearnings-output-74fb906e225f.md
It gets the prose out, but the charts, tables, heading levels, images, and two-column flow are mostly broken, so the report is only usable as loose text.
markitdown-markitdown-input1-hybridearnings-output-70f5b1faf73c.md
All 9 recorded checks per tool. Open a tool to inspect every finding.
It has a few standout quirks: it can preserve form state and financial parentheses correctly, but it also hoovers up scan artifacts as if they were real text. That mix is notable enough to earn a strong but not perfect score.
The report explicitly lists the tool as free/open source, with pricing given as `Free - $0 - Open Source`.
permalink to this finding →Captures scanned-page library stamps and barcode-like artifacts directly into the OCR text flow, adding noise such as `186153` and `CSX` to the title region.
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Extracts interactive form checkboxes and preserves their checked state, including the SEC Form 10-K mark-one field being rendered as selected in the parsed output.
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Preserves negative numbers in parentheses in financial tables without treating them as markdown syntax, including percentage changes and negative balance-sheet values.
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docling is the overall winner from these scorecards: it has the strongest hierarchy handling and long-document robustness, while also scoring well on text preservation, caption-figure association, and table reconstruction. The trade-off is clear: it is weak at keeping images and charts in place, so it is not the best pick when visual fidelity matters. liteparse is the closest alternative for native-digital prose and structure, with solid text and reading order, but it gives up some robustness and table fidelity. pymupdf4llm is a reasonable choice for clean digital text and tables, but it is less reliable on reading order, hierarchy, and complex or scanned layouts. doc2mark fits native-digital prose and headings, but its table output is especially inconsistent and it is weak on images and scans. markitdown is the simplest route for pulling plain text from native PDFs, but structural parsing is uneven and scanned PDFs need external OCR.
The tools we tested for this use case — each card opens its full tested review.
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