| ★ | infinity-parser2-pro Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for infly/Infinity-Parser2-Pro. Source: Infinity Parser technical report / HF leaderboard entry; metric: Accuracy.; PWC evaluation id 4945; paper: Infinity-Parser2-Pro | 87.6% | paperswithcode-public-api |
| 2 | chandra-2 Mapped from PWC olmOCR-Bench Accuracy.; Chandra OCR 2 (5B params, Qwen3.5 backbone) reported on olmOCR-Bench in the HF model card; Overall score 85.9 +/- 0.8. Sub-categories on the same benchmark: ArXiv 90.2, Old Scans Math 89.3, Tables 89.9, Old Scans 49.8, Headers and Footers 92.5, Multi column 83.5, Long tiny text 92.1, Base 99.6. Source: own benchmarks, reported in the chandra-ocr-2 HF model card.; PWC evaluation id 1165; paper: Chandra OCR 2 | 85.9% | paperswithcode-public-api |
| 3 | dots.mocr Mapped from PWC olmOCR-Bench Accuracy.; Overall score on olmOCR-Bench from the dots.mocr Hugging Face model card (section 1.2). 3B image-text-to-text VLM; page-header and page-footer cells deleted from the result markdown per the card's note; metric source: olmocr plus internal evaluations.; PWC evaluation id 1148; paper: Multimodal OCR: Parse Anything from Documents | 83.9% | paperswithcode-public-api |
| 4 | LightOnOCR-2-1B Mapped from PWC olmOCR-Bench Accuracy.; Overall score on olmOCR-Bench reported on the Hugging Face model card. Score excludes the Headers/Footers (H&F) sub-test because that category rewards omission rather than transcription, while LightOnOCR-2 is trained for full-page transcription and intentionally preserves headers/footers.; PWC evaluation id 1147; paper: LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model for State-of-the-Art OCR | 83.2% | paperswithcode-public-api |
| 5 | chandra-ocr-0.1.0 Fetched from CodeSOTA API on 2026-04-20 | 83.1% | codesota-api |
| 6 | chandra Mapped from PWC olmOCR-Bench Accuracy.; Reported in the datalab-to/chandra Hugging Face model card on olmOCR-Bench. Overall score 83.1 +/- 0.9; sub-category scores from the same table: ArXiv 82.2, Old Scans Math 80.3, Tables 88.0, Old Scans 50.4, Headers and Footers 90.8, Multi column 81.2, Long tiny text 92.3, Base 99.9. Source: own benchmarks.; PWC evaluation id 1327; paper: Chandra | 83.1% | paperswithcode-public-api |
| 7 | infinity-parser-7b Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for infly/Infinity-Parser-7B. Source: Infinity Parser technical report / HF leaderboard entry; metric: Accuracy.; PWC evaluation id 4946; paper: Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing | 82.5% | paperswithcode-public-api |
| 8 | olmocr-v0.4.0 Fetched from CodeSOTA API on 2026-04-20 | 82.4% | codesota-api |
| 9 | olmocr-2-7b-1025-7b Mapped from PWC olmOCR-Bench Accuracy.; PWC evaluation id 679; paper: olmOCR 2: Unit Test Rewards for Document OCR | 82.4% | paperswithcode-public-api |
| 10 | falcon-ocr Mapped from PWC olmOCR-Bench Accuracy.; olmOCR-Bench accuracy reported by tiiuae/Falcon-OCR model card (arXiv:2603.27365, Apr 2026). 'Average' across 8 category splits: ArXiv Math 80.5, Base 99.5, Headers/Footers 94.0, Long Tiny Text 78.5, Multi Column 87.1, Old Scans 43.5, Old Scans Math 69.2, Tables 90.3. Inference via Layout + OCR two-stage pipeline (PP-DocLayoutV3 layout detection + Falcon-OCR category-prompted VLM).; PWC evaluation id 1156; paper: Falcon Perception | 80.3% | paperswithcode-public-api |
| 11 | paddleocr-vl Mapped from PWC olmOCR-Bench Accuracy.; PWC evaluation id 86; paper: PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B
Ultra-Compact Vision-Language Model | 80% | paperswithcode-public-api |
| 12 | Qianfan-OCR Mapped from PWC olmOCR-Bench Accuracy.; End-to-end OCR on olmOCR-Bench; overall 79.8 (Arxiv Math 80.1, Old Scans Math 73.1, Table Tests 81.6, Old Scans 42.0, Multi Column 80.4, Long Tiny Text 89.1, Headers Footers 92.2).; PWC evaluation id 1196; paper: Qianfan-OCR: A Unified End-to-End Model for Document Intelligence | 79.8% | paperswithcode-public-api |
| 13 | Qwen3-VL-4B Fetched from CodeSOTA API on 2026-04-20 | 79.2% | codesota-api |
| 14 | PaddleOCR-VL-1.5 Fetched from CodeSOTA API on 2026-04-20 | 79.1% | codesota-api |
| 15 | dots-ocr-3b Fetched from CodeSOTA API on 2026-04-20 | 79.1% | codesota-api |
| 16 | dots-ocr Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for rednote-hilab/dots.ocr. Source: dots.ocr technical report / HF leaderboard entry; metric: Accuracy.; PWC evaluation id 4947; paper: dots.ocr: Multilingual Document Layout Parsing in a Single Vision-Language Model | 79.1% | paperswithcode-public-api |
| 17 | mistral-ocr-3 Fetched from CodeSOTA API on 2026-04-20 | 78% | codesota-api |
| 18 | mineru-2.5 Mapped from PWC olmOCR-Bench Accuracy.; PWC evaluation id 93; paper: MinerU2.5: A Decoupled Vision-Language Model for Efficient
High-Resolution Document Parsing | 77.5% | paperswithcode-public-api |
| 19 | marker-1.10.0 Fetched from CodeSOTA API on 2026-04-20 | 76.5% | codesota-api |
| 20 | deepseek-ocr-2 Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for deepseek-ai/DeepSeek-OCR-2. Source: HF leaderboard entry and DeepSeek-OCR-2 arXiv-linked model card; metric: Accuracy.; PWC evaluation id 4948; paper: DeepSeek-OCR 2: Visual Causal Flow | 76.3% | paperswithcode-public-api |
| 21 | marker-1.10.1 Fetched from CodeSOTA API on 2026-04-20 | 76.1% | codesota-api |
| 22 | lightonocr-1b-1025 Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for lightonai/LightOnOCR-1B-1025. Source note: Headers & Footers category excluded; metric: Accuracy.; PWC evaluation id 4949; paper: LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model for State-of-the-Art OCR | 76.1% | paperswithcode-public-api |
| 23 | MonkeyOCR-pro-3B Fetched from CodeSOTA API on 2026-04-20 | 75.8% | codesota-api |
| 24 | deepseek-ocr Fetched from CodeSOTA API on 2026-04-20 | 75.7% | codesota-api |
| 25 | DeepSeek-OCR Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for deepseek-ai/DeepSeek-OCR. Source: olmOCR-Bench GitHub leaderboard entry and DeepSeek-OCR arXiv-linked model card; metric: Accuracy.; PWC evaluation id 4950; paper: DeepSeek-OCR: Contexts Optical Compression | 75.7% | paperswithcode-public-api |
| 26 | olmocr Mapped from PWC olmOCR-Bench Accuracy.; Paper Table 4, olmOCR-Bench overall unit-test pass rate for Ours (v0.1.75 Anchored). Category scores reported in the paper: AR 74.9, OSM 71.2, TA 71.0, OS 42.2, HF 94.5, MC 78.3, LTT 73.3, Base 98.3.; PWC evaluation id 4979; paper: olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models | 75.5% | paperswithcode-public-api |
| 27 | mineru-2.5 Fetched from CodeSOTA API on 2026-04-20 | 75.2% | codesota-api |
| 28 | GLM-OCR Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for zai-org/GLM-OCR. Source note: Headers & Footers category excluded; evaluated via ZAI API; metric: Accuracy.; PWC evaluation id 4951; paper: GLM-OCR Technical Report | 75.2% | paperswithcode-public-api |
| 29 | mistral-ocr-api Fetched from CodeSOTA API on 2026-04-20 | 72% | codesota-api |
| 30 | firered-ocr Mapped from PWC olmOCR-Bench Accuracy.; Overall score reported on the official Hugging Face olmOCR-bench leaderboard for FireRedTeam/FireRed-OCR. Source note: Headers & Footers category excluded; metric: Accuracy.; PWC evaluation id 4952; paper: FireRed-OCR Technical Report | 70.2% | paperswithcode-public-api |
| 31 | gpt-4o-anchored Fetched from CodeSOTA API on 2026-04-20 | 69.9% | codesota-api |
| 32 | nanonets-ocr2-3b Fetched from CodeSOTA API on 2026-04-20 | 69.5% | codesota-api |
| 33 | gemini-flash-2 Fetched from CodeSOTA API on 2026-04-20 | 63.8% | codesota-api |