OCRBench
OCRBench - comprehensive OCR capability evaluation benchmark.
Category
Document Understanding
Score type
percent
Scale
100%
higher is better
Models tested
4
What is OCRBench?
OCRBench is a benchmark for reading and parsing real documents. The official description says: "OCRBench - comprehensive OCR capability evaluation benchmark". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
OCRBench measures reading and parsing real documents. In detail, it checks:
- extracting structured text from scans, PDFs and photos
- keeping tables, headings and reading order intact
- answering comprehension questions about the document content
- handling noisy layouts, handwriting and multi-page documents
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Official methodology note: OCRBench - comprehensive OCR capability evaluation benchmark.
Frequently asked questions
What is the OCRBench benchmark?
OCRBench is a benchmark for reading and parsing real documents. The official description says: 'OCRBench - comprehensive OCR capability evaluation benchmark'. Below we describe in simple words what benchmarks of this type generally examine.
What does OCRBench test?
OCRBench mainly measures reading and parsing real documents. Concretely, it checks: extracting structured text from scans, PDFs and photos; keeping tables, headings and reading order intact; answering comprehension questions about the document content.
How is the OCRBench score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get OCRBench data and scores?
The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/ocrbench-new/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Model scores 4 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
|
92.1%
|
01.02.2026 | Report | Verified |
| 2 |
Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
|
91%
|
01.02.2026 | Report | Unverified |
| 3 |
Qwen3.5-27B
Qwen Team (Alibaba Cloud)
|
89.4%
|
01.02.2026 | Report | Unverified |
| 4 |
Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
|
87.5%
|
01.02.2026 | Report | Unverified |