olmOCR-bench

olmOCR-bench is a dataset of 1,403 PDF files, plus 7,010 unit test cases that capture properties of the output that a good OCR system should have. This benchmark evaluates the ability of OCR systems to accurately convert PDF documents to markdown format while preserving critical textual and structural information.

Quick links:

• 📃 Paper
• 🛠️ Code
• 🎮 Demo

Table 1. Distribution of Test Classes by Document Source

Document Source	Text Present	Text Absent	Reading Order	Table	Math	Total
arXiv Math	-	-	-	-	2,927	2,927
Headers Footers	-	753	-	-	-	753
Long Tiny Text	442	-	-	-	-	442
Multi Column	-	-	884	-	-	884
Old Scans	279	70	177	-	-	526
Old Scans Math	-	-	-	-	458	458
Table Tests	-	-	-	1,020	-	1,020
Total	721	823	1,061	1,020	3,385	7,010

Table 2. Document source category breakdown

Category	PDFs	Tests	Source	Extraction Method
arXiv_math	522	2,927	arXiv	Dynamic programming alignment
old_scans_math	36	458	Internet Archive	Script-generated + manual rules
tables_tests	188	1,020	Internal repository	gemini-flash-2.0
old_scans	98	526	Library of Congress	Manual rules
headers_footers	266	753	Internal repository	DocLayout-YOLO + gemini-flash-2.0
multi_column	231	884	Internal repository	claude-sonnet-3.7 + HTML rendering
long_tiny_text	62	442	Internet Archive	gemini-flash-2.0
Total	1,403	7,010	Multiple sources

Evaluation Criteria

• Text Presence: Checks if a short text segment (1–3 sentences) is correctly identified in the OCR output. Supports fuzzy matching and positional constraints (e.g., must appear in the first/last N characters). Case-sensitive by default.
• Text Absence: Ensures specified text (e.g., headers, footers, page numbers) is excluded. Supports fuzzy matching and positional constraints. Not case-sensitive.
• Natural Reading Order: Verifies the relative order of two text spans (e.g., headline before paragraph). Soft matching enabled; case-sensitive by default.
• Table Accuracy: Confirms that specific cell values exist in tables with correct neighboring relationships (e.g., value above/below another). Supports Markdown and HTML, though complex structures require HTML.
• Math Formula Accuracy: Detects the presence of a target equation by matching symbol layout (e.g., $\int$ to the left of $x$). Based on rendered bounding boxes and relative positioning.

📊 Benchmark Results by Document Source

Model	ArXiv	Base	Hdr/Ftr	TinyTxt	MultCol	OldScan	OldMath	Tables	Overall
GOT OCR	52.7	94.0	93.6	29.9	42.0	22.1	52.0	0.2	48.3 ± 1.1
Marker v1.6.2	24.3	99.5	87.1	76.9	71.0	24.3	22.1	69.8	59.4 ± 1.1
MinerU v1.3.10	75.4	96.6	96.6	39.1	59.0	17.3	47.4	60.9	61.5 ± 1.1
Mistral OCR API	77.2	99.4	93.6	77.1	71.3	29.3	67.5	60.6	72.0 ± 1.1
GPT-4o (Anchored)	53.5	96.8	93.8	60.6	69.3	40.7	74.5	70.0	69.9 ± 1.1
GPT-4o (No Anchor)	51.5	96.7	94.2	54.1	68.9	40.9	75.5	69.1	68.9 ± 1.1
Gemini Flash 2 (Anchored)	54.5	95.6	64.7	71.5	61.5	34.2	56.1	72.1	63.8 ± 1.2
Gemini Flash 2 (No Anchor)	32.1	94.0	48.0	84.4	58.7	27.8	56.3	61.4	57.8 ± 1.1
Qwen 2 VL (No Anchor)	19.7	55.5	88.9	6.8	8.3	17.1	31.7	24.2	31.5 ± 0.9
Qwen 2.5 VL (No Anchor)	63.1	98.3	73.6	49.1	68.3	38.6	65.7	67.3	65.5 ± 1.2
Ours (No Anchor)	72.1	98.1	91.6	80.5	78.5	43.7	74.7	71.5	76.3 ± 1.1
Ours (Anchored)	75.6	99.0	93.4	81.7	79.4	44.5	75.1	70.2	77.4 ± 1.0

License

This dataset is licensed under ODC-BY-1.0. It is intended for research and educational use in accordance with AI2's Responsible Use Guidelines.