Extend AI in Converting a complex PDF into clean Markdown with a hosted API
Scenario-level performance from current published Results.
6 of 12 scenarios published
Where Extend AI failed
3 of 6 graded scenarios. Open a Result to see the conversation and the evidence.
A document containing a code block
Extend AI flattened the PDF’s two code snippets into ordinary text rather than preserving their line structure and indentation. Code characters also changed, and neither snippet would run as returned.
View Result →A document containing mathematical equations
Extend AI failed to keep equations as math markup or an honest fallback in Markdown. The returned Markdown turned equations (1) to (4) into garbled prose and never showed math markup or a stated fallback, even though the source equations were available in the PDF.
View Result →A document with styled headings and subheadings
Extend AI did not preserve the heading hierarchy in this PDF-to-Markdown conversion. In the one tested case, all 26 headings became Markdown headings, but every one was level three, so the three source tiers were flattened into a single level.
View Result →How Extend AI performed
Open a capability to explore its scenarios. Each row reports the test set in its published Result.
Code Extraction1 fail
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A document containing a code block | 0 Pass1 Fail0 Not gradable 1 of 1 test case failedWhat happenedExtend AI flattened the PDF’s two code snippets into ordinary text rather than preserving their line structure and indentation. Code characters also changed, and neither snippet would run as returned. | 1/1 assessed1/1 gradablePublished test set | View Result → |
Equations & Mathematical Notation1 fail
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A document containing mathematical equations | 0 Pass1 Fail0 Not gradable 1 of 1 test case failedWhat happenedExtend AI failed to keep equations as math markup or an honest fallback in Markdown. The returned Markdown turned equations (1) to (4) into garbled prose and never showed math markup or a stated fallback, even though the source equations were available in the PDF. | 1/1 assessed1/1 gradablePublished test set | View Result → |
Heading & Section Structure1 fail1 no Result yet
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A document with styled headings and subheadings | 0 Pass1 Fail0 Not gradable 1 of 1 test case failedWhat happenedExtend AI did not preserve the heading hierarchy in this PDF-to-Markdown conversion. In the one tested case, all 26 headings became Markdown headings, but every one was level three, so the three source tiers were flattened into a single level. | 1/1 assessed1/1 gradablePublished test set | View Result → |
| Footnotes at the bottom of the page | No published result | ||
Reading Order & Layout1 pass
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A page laid out in multiple columns | 1 Pass0 Fail0 Not gradable 1 of 1 test case passedWhat happenedExtend AI preserved the reading order of a two-column bulletin. It returned each page’s left column before its right column, without interleaving or inventing words. | 1/1 assessed1/1 gradablePublished test set | View Result → |
Scanned Document OCR1 pass1 no Result yet
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A cleanly scanned document | 1 Pass0 Fail0 Not gradable 1 of 1 test case passedWhat happenedExtend AI accurately recovered text from a cleanly scanned, image-only document. The one-page laboratory certificate was reproduced in Markdown with the letterhead, reference, date, six result rows, closing text, sign-off, and footer matching the page render. The results block also came back as a two-column HTML table with each label beside its value. | 1/1 assessed1/1 gradablePublished test set | View Result → |
| A document mixing digital and scanned pages | No published result | ||
Text Fidelity1 pass
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| An ordinary digital text document | 1 Pass0 Fail0 Not gradable 1 of 1 test case passedWhat happenedExtend AI passes the ordinary digital text scenario. The returned Markdown keeps the source text in order with no inserted or missing body words; one middle dot becomes a period, and running headers and page numbers stay separate from the body. | 1/1 assessed1/1 gradablePublished test set | View Result → |
Figures & Charts2 no Result yet
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A document with a data chart | No published result | ||
| A document with figures and captions | No published result | ||
Table Extraction2 no Result yet
Capability in this benchmark →
| Scenario | Published outcomes | Test coverage | Result |
|---|---|---|---|
| A simple, clearly formatted table | No published result | ||
| A table that continues across a page break | No published result | ||
Reading these Results
Published evidence and test coverage answer different questions.
Which scenarios have a Result?
A published Result is public evidence for this tool on one scenario. “No published result” does not say whether testing has taken place.
What does each Result cover?
Assessed includes Pass, Fail and Not gradable. Gradable includes Pass and Fail. Both use the pinned test count in that published Result.
Out of 12 scenarios
The summary counts each of the 12 scenarios once. A scenario fails when any of its published test cases failed. “No published Result yet” means nothing is public for that scenario; it does not say whether Extend AI was tested on it.