| { |
| "_meta": { |
| "description": "Machine-readable catalog of the OCR recipes in this directory: script -> model, params, backend, required image pins, and what the model's own card claims about language coverage. Human-readable language notes: LANGUAGES.md. Language evidence levels, strongest first: per-language-benchmark | count-claim | named-list | multilingual-unspecified | english-only | not-stated | not-applicable. Claims come from model cards (compiled 2026-07-15) - treat as claims, not guarantees.", |
| "updated": "2026-07-15", |
| "run_pattern": "hf jobs uv run --flavor <flavor> -s HF_TOKEN https://huggingface.co/datasets/uv-scripts/ocr/raw/main/<script> <input-dataset> <output-dataset>" |
| }, |
| "tesseract-ocr.py": { |
| "model_id": null, |
| "model_name": "Tesseract 5", |
| "params": null, |
| "backend": "pytesseract (CPU)", |
| "task": "ocr", |
| "output": "plain text", |
| "license": "apache-2.0", |
| "languages": { |
| "evidence": "named-list", |
| "count": "125 traineddata packs (~100+ languages + script models)", |
| "list_url": "https://github.com/tesseract-ocr/tessdata_best", |
| "notes": "Broadest named coverage; script models (Latin, Cyrillic, Devanagari, ...) cover languages without a dedicated pack. Legacy baseline quality." |
| } |
| }, |
| "pp-ocrv6.py": { |
| "model_id": "PaddlePaddle/PP-OCRv6", |
| "params": "1.5M-34.5M", |
| "backend": "paddleocr", |
| "task": "ocr", |
| "output": "plain text", |
| "license": "apache-2.0", |
| "languages": { "evidence": "count-claim", "count": 48 } |
| }, |
| "falcon-ocr.py": { |
| "model_id": "tiiuae/Falcon-OCR", |
| "params": "0.3B", |
| "backend": "falcon-perception", |
| "task": "ocr", |
| "output": "markdown", |
| "license": "apache-2.0", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "smoldocling-ocr.py": { |
| "model_id": "ds4sd/SmolDocling-256M-preview", |
| "params": "256M", |
| "backend": "transformers", |
| "task": "ocr", |
| "output": "DocTags", |
| "languages": { "evidence": "english-only" } |
| }, |
| "surya-ocr.py": { |
| "model_id": "datalab-to/surya-ocr-2", |
| "params": "0.65B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai:v0.20.1", |
| "task": "ocr | layout | table", |
| "output": "markdown + surya_blocks (per-block HTML, bboxes, reading order)", |
| "license": "modified OpenRAIL-M", |
| "languages": { |
| "evidence": "per-language-benchmark", |
| "count": 91, |
| "benchmark_url": "https://github.com/datalab-to/surya/blob/master/static/docs/multilingual.md", |
| "notes": "38/91 languages score >=90%, 76/91 >=80%; weakest of top-15: Arabic 72.7%, Vietnamese 73.2%." |
| } |
| }, |
| "glm-ocr.py": { |
| "model_id": "zai-org/GLM-OCR", |
| "params": "0.9B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { |
| "evidence": "named-list", |
| "count": 8, |
| "named": ["zh", "en", "fr", "es", "ru", "de", "ja", "ko"], |
| "notes": "Declared in card metadata only; no per-language evidence in the card body." |
| } |
| }, |
| "paddleocr-vl.py": { |
| "model_id": "PaddlePaddle/PaddleOCR-VL", |
| "params": "0.9B", |
| "backend": "vllm", |
| "task": "ocr | table | formula | chart", |
| "output": "markdown", |
| "languages": { |
| "evidence": "count-claim", |
| "count": 109, |
| "notes": "Names scripts (Cyrillic, Arabic, Devanagari, Thai); claims handwriting + historical documents; no per-language numbers." |
| } |
| }, |
| "paddleocr-vl-1.5.py": { |
| "model_id": "PaddlePaddle/PaddleOCR-VL-1.5", |
| "params": "0.9B", |
| "backend": "transformers", |
| "task": "ocr (6 modes)", |
| "output": "markdown", |
| "languages": { |
| "evidence": "count-claim", |
| "count": "109+ (adds Tibetan, Bengali)", |
| "notes": "Claims improved rare-character and ancient-text recognition." |
| } |
| }, |
| "paddleocr-vl-1.6.py": { |
| "model_id": "PaddlePaddle/PaddleOCR-VL-1.6", |
| "params": "0.9B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { |
| "evidence": "count-claim", |
| "count": "109+ (inherited from 1.5, not restated)", |
| "notes": "Upgrade-focused card; language-specific claims are Chinese ancient documents and rare characters." |
| } |
| }, |
| "ovis-ocr2.py": { |
| "model_id": "ATH-MaaS/OvisOCR2", |
| "params": "0.9B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown + LaTeX + HTML tables", |
| "license": "apache-2.0", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "ovis-ocr2-server.py": { |
| "model_id": "ATH-MaaS/OvisOCR2", |
| "params": "0.9B", |
| "backend": "vllm-server (in-job vllm serve + concurrent driver)", |
| "image": "vllm/vllm-openai:v0.22.1", |
| "task": "ocr", |
| "output": "markdown + LaTeX + HTML tables", |
| "license": "apache-2.0", |
| "notes": "Server-mode sibling of ovis-ocr2.py: ~1.7x its inference throughput, per-request failure isolation. See SERVING.md.", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "lighton-ocr.py": { |
| "model_id": "lightonai/LightOnOCR-1B-1025", |
| "params": "1B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { |
| "evidence": "named-list", |
| "count": 9, |
| "named": ["en", "fr", "de", "es", "it", "nl", "pt", "sv", "da"], |
| "notes": "Explicitly European / Latin-alphabet focused." |
| } |
| }, |
| "lighton-ocr2.py": { |
| "model_id": "lightonai/LightOnOCR-2-1B", |
| "params": "1B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { |
| "evidence": "named-list", |
| "count": 11, |
| "named": ["en", "fr", "de", "es", "it", "nl", "pt", "sv", "da", "zh", "ja"], |
| "notes": "Adds zh/ja over v1; declared, not benchmarked per language." |
| } |
| }, |
| "lighton-ocr2-server.py": { |
| "model_id": "lightonai/LightOnOCR-2-1B", |
| "params": "1B", |
| "backend": "vllm-server (in-job vllm serve + concurrent driver)", |
| "image": "vllm/vllm-openai:v0.22.1", |
| "task": "ocr", |
| "output": "markdown", |
| "notes": "Server-mode sibling of lighton-ocr2.py (the model card's own documented path): ~1.8x its inference throughput. See SERVING.md.", |
| "languages": { |
| "evidence": "named-list", |
| "count": 11, |
| "named": ["en", "fr", "de", "es", "it", "nl", "pt", "sv", "da", "zh", "ja"], |
| "notes": "Adds zh/ja over v1; declared, not benchmarked per language." |
| } |
| }, |
| "hunyuan-ocr.py": { |
| "model_id": "tencent/HunyuanOCR", |
| "revision": "f6af82ee007fe6091b29fb3bb287b491ead41c82", |
| "params": "1B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "license": "Hunyuan Community License (excludes EU/UK/KR)", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "hunyuan-ocr-1.5.py": { |
| "model_id": "tencent/HunyuanOCR", |
| "params": "1B", |
| "backend": "vllm", |
| "task": "ocr | 12 task types", |
| "output": "markdown", |
| "license": "Hunyuan Community License (excludes EU/UK/KR)", |
| "languages": { |
| "evidence": "multilingual-unspecified", |
| "notes": "Explicitly targets low-resource + ancient-script OCR as a design goal; nothing enumerated." |
| } |
| }, |
| "dots-ocr.py": { |
| "model_id": "rednote-hilab/dots.ocr", |
| "params": "1.7B", |
| "backend": "vllm", |
| "task": "ocr + layout", |
| "output": "markdown", |
| "languages": { |
| "evidence": "count-claim", |
| "count": 100, |
| "notes": "Explicit low-resource claim backed by in-house dots.ocr-bench (1,493 PDFs across 100 languages); aggregate scores only." |
| } |
| }, |
| "firered-ocr.py": { |
| "model_id": "FireRedTeam/FireRed-OCR", |
| "params": "2.1B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "license": "apache-2.0", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "abot-ocr.py": { |
| "model_id": "acvlab/ABot-OCR", |
| "params": "2B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai", |
| "task": "ocr", |
| "output": "markdown (text, LaTeX, HTML tables)", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "nanonets-ocr.py": { |
| "model_id": "nanonets/Nanonets-OCR-s", |
| "params": "2B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown (LaTeX, tables, forms)", |
| "languages": { "evidence": "english-only" } |
| }, |
| "dots-mocr.py": { |
| "model_id": "rednote-hilab/dots.mocr", |
| "params": "3B", |
| "backend": "vllm", |
| "task": "ocr | 8 prompt modes incl. SVG, layout + bbox", |
| "output": "markdown", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "nanonets-ocr2.py": { |
| "model_id": "nanonets/Nanonets-OCR2-3B", |
| "params": "3B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai:v0.10.2", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { |
| "evidence": "named-list", |
| "count": "11 named + 'many more'", |
| "named": ["en", "zh", "fr", "es", "pt", "de", "it", "ru", "ja", "ko", "ar"], |
| "notes": "Only card claiming multilingual handwriting; list illustrative, no per-language benchmark." |
| } |
| }, |
| "deepseek-ocr-vllm.py": { |
| "model_id": "deepseek-ai/DeepSeek-OCR", |
| "params": "4B", |
| "backend": "vllm", |
| "task": "ocr | 5 resolution + 5 prompt modes", |
| "output": "markdown", |
| "license": "mit", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "deepseek-ocr.py": { |
| "model_id": "deepseek-ai/DeepSeek-OCR", |
| "params": "4B", |
| "backend": "transformers", |
| "task": "ocr", |
| "output": "markdown", |
| "license": "mit", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "deepseek-ocr2-vllm.py": { |
| "model_id": "deepseek-ai/DeepSeek-OCR-2", |
| "params": "3B", |
| "backend": "vllm (nightly)", |
| "image": "vllm/vllm-openai", |
| "task": "ocr", |
| "output": "markdown", |
| "license": "apache-2.0", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "unlimited-ocr-vllm.py": { |
| "model_id": "baidu/Unlimited-OCR", |
| "params": "3.3B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai:unlimited-ocr", |
| "task": "ocr (layout-grounded markdown; single-image batch)", |
| "output": "markdown", |
| "license": "mit", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "nuextract3.py": { |
| "model_id": "numind/NuExtract3", |
| "params": "4B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai", |
| "task": "ocr | schema-guided extraction", |
| "output": "markdown or JSON", |
| "languages": { "evidence": "multilingual-unspecified" } |
| }, |
| "qianfan-ocr.py": { |
| "model_id": "baidu/Qianfan-OCR", |
| "params": "4.7B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { |
| "evidence": "count-claim", |
| "count": 192, |
| "notes": "Headline claim; no list or per-language numbers." |
| } |
| }, |
| "olmocr2-vllm.py": { |
| "model_id": "allenai/olmOCR-2-7B-1025-FP8", |
| "params": "7B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "markdown", |
| "languages": { "evidence": "english-only" } |
| }, |
| "rolm-ocr.py": { |
| "model_id": "reducto/RolmOCR", |
| "params": "7B", |
| "backend": "vllm", |
| "task": "ocr", |
| "output": "plain text", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "numarkdown-ocr.py": { |
| "model_id": "numind/NuMarkdown-8B-Thinking", |
| "params": "8B", |
| "backend": "vllm", |
| "task": "ocr (reasoning)", |
| "output": "markdown", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "lfm2-vl-extract.py": { |
| "model_id": "LiquidAI/LFM2.5-VL-1.6B-Extract", |
| "params": "1.6B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai", |
| "task": "schema-guided extraction (image -> JSON)", |
| "output": "JSON", |
| "languages": { |
| "evidence": "english-only", |
| "notes": "Vision card declares en only; the text sibling's 9-language list does NOT carry over." |
| } |
| }, |
| "lfm2-extract.py": { |
| "model_id": "LiquidAI/LFM2-1.2B-Extract", |
| "params": "1.2B", |
| "backend": "vllm", |
| "image": "vllm/vllm-openai", |
| "task": "schema-guided extraction (text -> structured); chain after any OCR recipe", |
| "output": "JSON / XML / YAML", |
| "languages": { |
| "evidence": "named-list", |
| "count": 9, |
| "named": ["en", "ar", "zh", "fr", "de", "ja", "ko", "pt", "es"], |
| "notes": "Text-only model (not OCR). Card prose names 9 incl. Portuguese; card YAML lists 8 (pt missing)." |
| } |
| }, |
| "lift-extract.py": { |
| "model_id": "datalab-to/lift", |
| "params": "9B", |
| "backend": "transformers | vllm", |
| "task": "schema-guided extraction (image or multi-page PDF -> JSON)", |
| "output": "JSON", |
| "license": "modified OpenRAIL-M", |
| "languages": { "evidence": "not-stated" } |
| }, |
| "pp-doclayout.py": { |
| "model_id": "PaddlePaddle/PP-DocLayout-L", |
| "params": "123M", |
| "backend": "paddleocr", |
| "task": "layout detection (no text extraction)", |
| "output": "bounding boxes + region classes", |
| "languages": { "evidence": "not-applicable" } |
| }, |
| "glm-ocr-v2.py": { "variant_of": "glm-ocr.py", "notes": "Adds checkpoint/resume for very large jobs." }, |
| "glm-ocr-bucket.py": { "variant_of": "glm-ocr.py", "notes": "Reads images/PDFs from a mounted bucket, writes one .md per page." }, |
| "falcon-ocr-bucket.py": { "variant_of": "falcon-ocr.py", "notes": "Reads images/PDFs from a mounted bucket, writes one .md per page." }, |
| "surya-ocr-bucket.py": { "variant_of": "surya-ocr.py", "notes": "Bucket-to-bucket structured OCR (--io-mode mount|copy), resumable." }, |
| "ocr-vllm-judge.py": { "model_id": "configurable", "task": "pairwise OCR-quality judging (VLM-as-judge)", "languages": { "evidence": "not-applicable" } } |
| } |
|
|
