models.json

{
  "_meta": {
    "description": "Machine-readable catalog of the OCR recipes in this directory: script -> model, params, backend, support level, the tested Jobs launch config (the script's [tool.hf-jobs] header), 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": "2026-10-27",
    "run_pattern": "hf jobs uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/<script> <input-dataset> <output-dataset>  (hf CLI >= 1.32 reads image/flavor/secrets from the script's [tool.hf-jobs] header; add --timeout for long runs. Scripts without a `jobs` entry need --flavor/-s HF_TOKEN (and any --image in their docstring).)",
    "support_levels": {
      "core": "Maintained. Smoke-tested flagless on HF Jobs on 2026-09-23/24 with the pinned launch config in `jobs`.",
      "tool": "Maintained companion (judge, layout, text extraction), not a page-OCR recipe.",
      "legacy": "Works (smoke-tested 2026-09-23) but superseded or little used; no header yet. See support_note for the alternative.",
      "unsupported": "Known broken as of 2026-09-23; kept in the repo for now. See support_note.",
      "experimental": "Works in testing on HF Jobs with the launch config in `jobs`, but changes often and may break. See support_note for the stable alternative."
    }
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "flavor": "cpu-upgrade",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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
    },
    "support": "core",
    "jobs": {
      "flavor": "t4-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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"
    },
    "support": "legacy",
    "support_note": "Falcon-OCR v1; v1.5 work is in PR #110."
  },
  "smoldocling-ocr.py": {
    "model_id": "ds4sd/SmolDocling-256M-preview",
    "params": "256M",
    "backend": "transformers",
    "task": "ocr",
    "output": "DocTags",
    "languages": {
      "evidence": "english-only"
    },
    "support": "unsupported",
    "support_note": "Broken (2026-09-23): the DocTags-to-markdown converter is a stub, so rows are raw DocTags."
  },
  "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%."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.20.1",
      "python": "/usr/local/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/site-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "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."
    },
    "support": "legacy",
    "support_note": "PaddleOCR-VL 1.0; use paddleocr-vl-1.6.py."
  },
  "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."
    },
    "support": "unsupported",
    "support_note": "Broken (2026-09-23): every row is an [OCR ERROR] ('min_pixels' attribute removed in transformers 5). Use paddleocr-vl-1.6.py."
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "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"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "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"
    },
    "support": "legacy",
    "support_note": "Use ovis-ocr2-saturate.py (same model and server, adaptive concurrency, resumable)."
  },
  "ovis-ocr2-saturate.py": {
    "model_id": "ATH-MaaS/OvisOCR2",
    "params": "0.9B",
    "backend": "saturate (in-job vllm serve + saturate pump)",
    "image": "vllm/vllm-openai:v0.22.1",
    "task": "ocr",
    "output": "markdown + LaTeX + HTML tables",
    "license": "apache-2.0",
    "notes": "saturate companion of ovis-ocr2-server.py: same model/prompt/sampling/post-processing; the driver half (adaptive concurrency, retries, resumable parquet output, durable error rows) is the saturate library. SERVING dict at the top of the script is the machine-readable tuning prior.",
    "languages": {
      "evidence": "not-stated"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.22.1",
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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."
    },
    "support": "legacy",
    "support_note": "LightOnOCR v1; use lighton-ocr2.py."
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.22.1",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.22.1"
  },
  "lighton-ocr3.py": {
    "model_id": "lightonai/LightOnOCR-3-4B",
    "params": "4B (or 0.8B via --model)",
    "backend": "vllm",
    "task": "ocr",
    "output": "markdown; --mode grounding adds labelled layout blocks with 0-1000 boxes (layout_blocks JSON column)",
    "license": "apache-2.0",
    "languages": {
      "evidence": "not-stated",
      "notes": "LightOnOCR-3 cards give no language list (LightOnOCR-2 named 11)."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.30.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.30.0",
    "notes": "Also runs lightonai/LightOnOCR-3-0.8B. Not LightOnOCR-3-1B (Pixtral arch, different pins). vLLM 0.30.0 pinned: upstream reports 0.27.1 loops."
  },
  "lighton-ocr3-bucket.py": {
    "model_id": "lightonai/LightOnOCR-3-4B",
    "params": "4B (or 0.8B via --model)",
    "backend": "vllm",
    "task": "ocr",
    "output": "one .md per image/PDF page in an output dir; --mode grounding adds a .json sidecar of layout blocks",
    "license": "apache-2.0",
    "languages": {
      "evidence": "not-stated",
      "notes": "LightOnOCR-3 cards give no language list (LightOnOCR-2 named 11)."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.30.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.30.0",
    "notes": "Bucket sibling of lighton-ocr3.py (same model, prompt, sampling). Input/output: hf://buckets/... URLs via bucketbag v0.3.1 (no mount) or directories. Reads .jp2; resume-by-skip."
  },
  "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."
    },
    "support": "legacy",
    "support_note": "Use lighton-ocr2-saturate.py (same model and server, adaptive concurrency, resumable)."
  },
  "lighton-ocr2-saturate.py": {
    "model_id": "lightonai/LightOnOCR-2-1B",
    "params": "1B",
    "backend": "saturate (in-job vllm serve + saturate pump)",
    "image": "vllm/vllm-openai:v0.22.1",
    "task": "ocr",
    "output": "markdown",
    "notes": "saturate companion of lighton-ocr2-server.py: same model/message shape/sampling; the driver half (adaptive concurrency, retries, resumable parquet output, durable error rows) is the saturate library. SERVING dict at the top of the script is the machine-readable tuning prior.",
    "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.22.1",
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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"
    },
    "support": "unsupported",
    "support_note": "Broken (2026-09-23): the pinned 1.0 revision fails on current vLLM/transformers. Use hunyuan-ocr-1.5.py."
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.24.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.24.0"
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "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"
    },
    "support": "legacy",
    "support_note": "Works; low adoption."
  },
  "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"
    },
    "support": "legacy",
    "support_note": "Works; low adoption and no declared model licence."
  },
  "nanonets-ocr.py": {
    "model_id": "nanonets/Nanonets-OCR-s",
    "params": "2B",
    "backend": "vllm",
    "task": "ocr",
    "output": "markdown (LaTeX, tables, forms)",
    "languages": {
      "evidence": "english-only"
    },
    "support": "legacy",
    "support_note": "Nanonets-OCR-s; use nanonets-ocr2.py."
  },
  "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"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "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."
    },
    "support": "legacy",
    "support_note": "Works on its pinned vllm/vllm-openai:v0.10.2 image; not header-migrated."
  },
  "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"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "jina-ocr-v1.py": {
    "model_id": "jinaai/jina-ocr-v1",
    "model_name": "jina-ocr-v1",
    "params": "3.4B (MoE, ~570M active)",
    "backend": "vllm",
    "task": "ocr",
    "output": "markdown",
    "license": "cc-by-nc-4.0",
    "notes": "DeepSeek-OCR fine-tune with a FastMTP speculative-decoding head; offline vLLM only (the checkpoint's register() must run in-process, no vllm serve path yet). Card: 91.14 OmniDocBench v1.6, 83.4 olmOCR-Bench.",
    "languages": {
      "evidence": "multilingual-unspecified",
      "notes": "Card metadata says multilingual; no per-language list or evidence in the card body."
    },
    "support": "unsupported",
    "support_note": "Broken (2026-09-23): vLLM 0.30 DeepEncoder kernel error; pinning vllm/vllm-openai:v0.29.0 likely fixes it (as for deepseek-ocr-vllm.py). CC-BY-NC-4.0 model.",
    "jobs": {
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ],
      "env": {
        "UV_TORCH_BACKEND": "auto"
      }
    }
  },
  "deepseek-ocr.py": {
    "model_id": "deepseek-ai/DeepSeek-OCR",
    "params": "4B",
    "backend": "transformers",
    "task": "ocr",
    "output": "markdown",
    "license": "mit",
    "languages": {
      "evidence": "multilingual-unspecified"
    },
    "support": "unsupported",
    "support_note": "Broken (2026-09-23): every output row is the string 'None' (model.infer returns None). Use deepseek-ocr-vllm.py."
  },
  "deepseek-ocr2-vllm.py": {
    "model_id": "deepseek-ai/DeepSeek-OCR-2",
    "params": "3B",
    "backend": "vllm (nightly)",
    "image": "vllm/vllm-openai:v0.29.0",
    "task": "ocr",
    "output": "markdown",
    "license": "apache-2.0",
    "languages": {
      "evidence": "multilingual-unspecified"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "unlimited-ocr2.py": {
    "model_id": "baidu/Unlimited-OCR-2",
    "params": "3.3B (MoE, 0.5B active)",
    "backend": "saturate (in-job SGLang from Baidu's wheel + saturate pump)",
    "image": "lmsysorg/sglang:v0.5.20-cu130",
    "task": "ocr (multi-page documents: folders of page images; cross-page continuations)",
    "output": "markdown per page + layout-grounded raw, one row per 16-page window",
    "license": "mit",
    "notes": "Sends 16 consecutive pages per request so the model keeps context across page breaks. Needs a >= 48 GB GPU (24 GB cards thrash the KV cache). Measured on 1771 Britannica: rtx-pro-6000 ~1,570 tok/s end to end. About 2% of dense 18th-century pages loop; unlimited-ocr2-saturate.py repairs them.",
    "languages": {
      "evidence": "multilingual-unspecified"
    },
    "support": "core",
    "jobs": {
      "image": "lmsysorg/sglang:v0.5.20-cu130",
      "flavor": "rtx-pro-6000",
      "timeout": "4h",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "unlimited-ocr2-saturate.py": {
    "model_id": "baidu/Unlimited-OCR-2",
    "params": "3.3B (MoE, 0.5B active)",
    "backend": "saturate (in-job SGLang from Baidu's wheel + saturate pump)",
    "image": "lmsysorg/sglang:v0.5.20-cu130",
    "task": "ocr (multi-page documents: book volumes, PDFs; cross-page continuations)",
    "output": "markdown per page and per window + layout-grounded raw",
    "license": "mit",
    "notes": "Tuned version of unlimited-ocr2.py: repair pass for looping pages (fixed 28/33 in testing), PDF input, Baidu's own Markdown post-processing, speed flags.",
    "languages": {
      "evidence": "multilingual-unspecified"
    },
    "support": "experimental",
    "support_note": "Use unlimited-ocr2.py unless you need the repair pass, PDFs or the extras.",
    "jobs": {
      "image": "lmsysorg/sglang:v0.5.20-cu130",
      "flavor": "rtx-pro-6000",
      "timeout": "4h",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "unlimited-ocr2-live.py": {
    "model_id": "baidu/Unlimited-OCR-2",
    "params": "3.3B (MoE, 0.5B active)",
    "backend": "saturate (in-job SGLang from Baidu's wheel + saturate pump)",
    "image": "lmsysorg/sglang:v0.5.20-cu130",
    "task": "ocr (multi-page documents) with a live view of the run",
    "output": "markdown per page + layout-grounded raw, one row per 16-page window",
    "license": "mit",
    "notes": "unlimited-ocr2.py plus --live-port: a dashboard served from the Job (start-up steps, the page being read with its text streaming in, finished pages, pages/min, GPU load) for watching or screen-recording a run. Measured on 1,456 Wellcome Library pages: ~130 pages/min on rtx-pro-6000.",
    "languages": {
      "evidence": "multilingual-unspecified"
    },
    "support": "experimental",
    "support_note": "Use unlimited-ocr2.py for normal runs; this adds a live view for demos.",
    "jobs": {
      "image": "lmsysorg/sglang:v0.5.20-cu130",
      "flavor": "rtx-pro-6000",
      "timeout": "4h",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "minicpm-ocr.py": {
    "model_id": "openbmb/MiniCPM-OCR-1.0",
    "params": "1.3B",
    "backend": "in-job vLLM (nightly) + OpenBMB's minicpm-ocr SDK (PP-DocLayoutV3 layout, per-region prompts, Markdown assembly)",
    "image": "cr.hf.co/davanstrien/minicpm-ocr:1.0-vllm-5d35ce3",
    "task": "ocr (page images -> Markdown; tables as HTML, formulas as LaTeX); Hub dataset or Bucket/folder I/O",
    "output": "dataset mode: markdown + markdown_status columns; Bucket/folder mode: one .md per image (failed pages not written, re-run retries)",
    "license": "apache-2.0",
    "notes": "A region reader behind a layout model, run through the vendor SDK unchanged. Custom public image (Dockerfile in images/minicpm-ocr/): the architecture is in vLLM main but not a release, and the SDK needs PaddlePaddle in its own venv. DSpark speculative decoding on by default (--no-dspark). Bucket I/O via bucketbag v0.3.1 (no mount), resume-by-skip. Smoke-tested 2026-10-27 on BHL pages (dataset mode) and 1771 Britannica .jp2 (Bucket mode), a10g-large.",
    "languages": {
      "evidence": "named-list",
      "count": 2,
      "named": [
        "zh",
        "en"
      ],
      "notes": "Card: 'Primary languages: Chinese and English'; card metadata lists en, zh. Card examples include historical scans; fine-tuning guide uses French handwriting."
    },
    "support": "experimental",
    "jobs": {
      "image": "cr.hf.co/davanstrien/minicpm-ocr:1.0-vllm-5d35ce3",
      "flavor": "a10g-large",
      "timeout": "2h",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:unlimited-ocr",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "nuextract3.py": {
    "model_id": "numind/NuExtract3",
    "params": "4B",
    "backend": "vllm",
    "image": "vllm/vllm-openai:v0.29.0",
    "task": "ocr | schema-guided extraction",
    "output": "markdown or JSON",
    "languages": {
      "evidence": "multilingual-unspecified"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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."
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "olmocr2-vllm.py": {
    "model_id": "allenai/olmOCR-2-7B-1025-FP8",
    "params": "7B",
    "backend": "vllm",
    "task": "ocr",
    "output": "markdown",
    "languages": {
      "evidence": "english-only"
    },
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "rolm-ocr.py": {
    "model_id": "reducto/RolmOCR",
    "params": "7B",
    "backend": "vllm",
    "task": "ocr",
    "output": "plain text",
    "languages": {
      "evidence": "not-stated"
    },
    "support": "unsupported",
    "support_note": "Broken (2026-09-23): no KV cache room on a 24 GB L4 with the default settings. Use olmocr2-vllm.py."
  },
  "numarkdown-ocr.py": {
    "model_id": "numind/NuMarkdown-8B-Thinking",
    "params": "8B",
    "backend": "vllm",
    "task": "ocr (reasoning)",
    "output": "markdown",
    "languages": {
      "evidence": "not-stated"
    },
    "support": "legacy",
    "support_note": "8B reasoning model; works, little used."
  },
  "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."
    },
    "support": "legacy",
    "support_note": "Works; nuextract3.py and lift-extract.py cover image-to-JSON extraction."
  },
  "lfm2-extract.py": {
    "model_id": "LiquidAI/LFM2-1.2B-Extract",
    "params": "1.2B",
    "backend": "vllm",
    "image": "vllm/vllm-openai:v0.29.0",
    "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)."
    },
    "support": "tool",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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"
    },
    "support": "core",
    "jobs": {
      "flavor": "a100-large",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "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"
    },
    "support": "tool",
    "jobs": {
      "flavor": "t4-small",
      "secrets": [
        "HF_TOKEN"
      ]
    }
  },
  "glm-ocr-v2.py": {
    "variant_of": "glm-ocr.py",
    "notes": "Adds checkpoint/resume for very large jobs.",
    "support": "legacy",
    "support_note": "Superseded by glm-ocr.py for most runs; kept for its resume support."
  },
  "glm-ocr-bucket.py": {
    "variant_of": "glm-ocr.py",
    "notes": "Reads images/PDFs from a mounted bucket, writes one .md per page.",
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  },
  "falcon-ocr-bucket.py": {
    "variant_of": "falcon-ocr.py",
    "notes": "Reads images/PDFs from a mounted bucket, writes one .md per page.",
    "support": "legacy",
    "support_note": "Falcon-OCR v1; v1.5 work is in PR #110. --max-samples counts files, not pages."
  },
  "surya-ocr-bucket.py": {
    "variant_of": "surya-ocr.py",
    "notes": "Bucket-to-bucket structured OCR (--io-mode mount|copy), resumable.",
    "support": "core",
    "jobs": {
      "image": "vllm/vllm-openai:v0.20.1",
      "python": "/usr/local/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/site-packages"
      },
      "flavor": "a10g-small",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.20.1"
  },
  "ocr-vllm-judge.py": {
    "model_id": "configurable",
    "task": "pairwise OCR-quality judging (VLM-as-judge)",
    "languages": {
      "evidence": "not-applicable"
    },
    "support": "tool",
    "jobs": {
      "image": "vllm/vllm-openai:v0.29.0",
      "python": "/usr/bin/python3",
      "env": {
        "PYTHONPATH": "/usr/local/lib/python3.12/dist-packages"
      },
      "flavor": "a100-large",
      "secrets": [
        "HF_TOKEN"
      ]
    },
    "image": "vllm/vllm-openai:v0.29.0"
  }
}