Scenario in benchmark · Version 1

A cleanly scanned document

A document is scanned and image-only, so its visible text must be recovered without relying on a text layer.

How the tools performed

Every in-scope tool is visible. Outcomes come from current published Results for this scenario and benchmark version.

Publication availability: 3 tools have a current published Result.

No published result does not tell you whether a tool has been tested. Test coverage is shown only for comparable published Results.

ToolPublished outcomesTest coverageResult
Published Results · alphabetical, not ranked
Extend AI
1 Pass0 Fail0 Not gradable
1 of 1 test case passed
1 of 1 assessed1 of 1 gradableView Result →
Mistral AI
1 Pass0 Fail0 Not gradable
1 of 1 test case passed
1 of 1 assessed1 of 1 gradableView Result →
Reducto
1 Pass0 Fail0 Not gradable
1 of 1 test case passed
1 of 1 assessed1 of 1 gradableView Result →
No published result · alphabetical
Adobe PDF Extract API——No published result
Firecrawl——No published result
GPT-5.6 terra——No published result
Landing AI——No published result
LlamaParse——No published result
Nutrient.io——No published result
PDF Vector——No published result
Tensorlake——No published result
Unstructured——No published result
Upstage AI——No published result

Assessed = Pass + Fail + Not gradable. Gradable = Pass + Fail. Both use the published Result’s pinned-test denominator. — means not publicly available.

Test design

Pinned test cases
1
Disclosure
1 public · 0 withheld
Capabilities exercised here
Scanned Document OCR

What this scenario evaluates

  • Whether the visible text from the scanned page is recovered accurately.
  • Whether the page is not silently skipped or treated as empty because no text layer exists.
  • Whether the output stays faithful to the visible content without inventing text.
  • Whether scanned pages are handled as real input, not hidden by omission.

Exact wording, inputs, fixture state, expected output and detailed grading remain at the test-case level and may be withheld while the benchmark version is active. The scenario and its evaluation intent are public.

How the results are graded

  • Pass: the test-case expectations hold.
  • Fail: an expectation demonstrably does not hold.
  • Not gradable: the evidence cannot establish the outcome.

Version 1 uses test-case expectations; no scenario rubric is pinned.

Benchmark methodology →
A cleanly scanned document in Converting a complex PDF into clean Markdown with a hosted API | AI Demos