Processes a 12-page scanned paper end-to-end and reaches SUCCESS after extracting the page content and figure/table outputs.
What was measured
Complex Document Handling
Maintains quality across long, multi-section, and mixed-content documents without degradation.
decisive for this rankingtransformation
The subject explicitly says complex PDF, so sustained quality across long, mixed-content documents is central to the tool’s ability to do the job. (3 of 3 judges)
What was given, what came back
Test input: Scanned Research Paper · pdf · group: scanned-research-paper
Input — what we sent
An image-only scanned research paper used to stress OCR and layout recovery in a multi-column academic document with figures, charts, tables, captions, and references.
Why this input is hard
- · OCR on scanned pages
- · Multi-column reading order
- · Figure and chart handling
- · Table reconstruction from scans
- · Caption association
- · Reference extraction
- · Overall document structure retention
Output — unretouched
Loading file...
Also checked on this input — same tool, 6 other criteria
Reading Order & Structure✓ WorkedReflows a two-column scanned page into a single coherent reading order while preserving section-to-body flow.Table Preservation✓ WorkedPreserves the harvest-diameter table's rows and aligned columns in the extracted output.Table Preservation✗ FailedFails to faithfully reconstruct grouped headers in a multi-level stand-effects table, making parent-child column relationships ambiguous.Table Preservation✓ WorkedPreserves a nested treatment table with the 7-inch, 10-inch, 12-inch, 100-leave-tree, and clearcut columns and the acres/live-lodgepole rows.Text & OCR Completeness✓ WorkedRecovers dense readable prose from a scanned page-image source, including the section heading and multiple long paragraphs.Visual Content Retention◐ MixedConverts a bar chart into a structured table, preserving the legend/value mapping but not keeping the chart as a visual chart.
Provenance
- Observation
- 9f0d06be-7ecb-4732-933c-ea6d52a1cc16
- Evidence run
- 6e3160de-fe46-4b45-b071-72560b5c5d0e
- Study
- Convert a Complex PDF into Clean Markdown with an API
- Research task
- 86b9h7t37
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "llamaparse",
scenario: "scanned-research-paper"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 6 other tools
measured on Complex Document Handling
Adobe API⚠ StruggledRequires splitting an oversized scanned paper into two PDFs before processing, because the web interface rejects uploads over 1 MB.Extend AI✓ WorkedHandles the scanned research paper end-to-end, including multi-column prose, tables, charts, and handwritten marginalia, while still producing parsed markdown.Mistral AI✓ WorkedThe tool processes a scanned multi-column research paper end-to-end and returns OCR text, tables, and embedded chart assets in page-wise markdown output.Nutrient.io✓ WorkedProcesses an image-only scanned research paper end to end and returns a parsed markdown output plus preview, showing it can handle a multi-page scanned document.Reducto⚠ StruggledHandles the 12-page scan in 10.6 seconds with no truncation, but the densest 17-column table has unreadable stretches with injected glyphs and run-on numbers.Tensorlake◐ MixedOn the scanned research paper, section flow and chart extraction work, but hierarchical tables degrade, so mixed-content handling is uneven rather than consistently robust.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com