olmOCR-bench / README.md
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metadata
license: odc-by
tags:
  - text
configs:
  - config_name: olmocr-bench
    data_files:
      - split: arxiv_math
        path:
          - bench_data/arxiv_math.jsonl
      - split: headers_footers
        path:
          - bench_data/headers_footers.jsonl
      - split: long_tiny_text
        path:
          - bench_data/long_tiny_text.jsonl
      - split: multi_column
        path:
          - bench_data/multi_column.jsonl
      - split: old_scans
        path:
          - bench_data/old_scans.jsonl
      - split: old_scans_math
        path:
          - bench_data/old_scans_math.jsonl
      - split: table_tests
        path:
          - bench_data/table_tests.jsonl
language:
  - en
pretty_name: olmOCR-bench
size_categories:
  - 1K<n<10K

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:

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.