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granite-docling-258M

Open Weights

IBM

Granite Docling is IBM Research's 258M-parameter image-text-to-text model for document conversion, released 17 September 2025 under Apache 2.0. It builds on the Idefics3 architecture, replacing the vision encoder with siglip2-base-patch16-512 and the language model with a Granite 165M LLM, and emits DocTags that convert directly into DoclingDocuments. Its instruction set covers full-page conversion plus targeted chart-to-table, formula-to-LaTeX, code and OTSL table extraction, along with bbox-guided region inference and question answering about document structure. It is intended to be used through the Docling library.

Strengths

  • Apache 2.0 licence, with an MLX build for Apple Silicon and an untied-weights branch for vLLM published alongside the main weights
  • 258M parameters (siglip2-base-patch16-512 encoder plus a Granite 165M LLM) keeps it runnable on modest hardware
  • Emits DocTags that convert into DoclingDocuments and onward to Markdown or HTML through docling-core
  • Instruction set covers full-page conversion, chart-to-table, formula-to-LaTeX, code-to-text and OTSL table extraction
  • Flexible inference modes including bbox-guided region inference and document-element QA about the presence and ordering of elements
  • Improves on its smoldocling-256m-preview predecessor across every published row: layout MAP 0.27 vs 0.23, full-page OCR F1 0.84 vs 0.80, OCRBench 500 vs 338
  • One-line use through the docling CLI, which downloads the model and converts files, URLs or whole directories

Caveats

  • The card lists English as the only supported language; Japanese, Arabic and Chinese support is explicitly labelled experimental
  • Absolute accuracy stays modest for a 258M model: OCRBench 500, MMStar 0.30, and full-page OCR edit distance still 0.45
  • IBM recommends using it only as part of the Docling library and pairing it with Granite Guardian for safety, rather than treating it as a general vision model
  • Current vLLM releases (including 0.10.2) break on the model's tied weights; you must serve the separate untied revision
  • Older GPUs without bfloat16 support, such as a Colab T4, emit only exclamation marks unless dtype is forced to float32; IBM also flags that smaller models may be more susceptible to hallucination
Vendor
IBM
License
Apache-2.0
Release Date
2025-09-17
Modalities
text
image
BenchmarkScoreMax
OCRBench500.01000.0
MMStar0.31.0
Full Page OCR F10.81.0
Layout MAP0.31.0

Capabilities

Vision
Audio
Video
Tool Use

Reviews

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