Chandra OCR 2

Announcing Chandra OCR 2 - a 4B parameter OCR model that scores 85.9% on the olmOCR benchmark (state of the art) and 77.8% on our internal 43-language multilingual benchmark. It is smaller and more accurate than Chandra 1 (9B) across every category.

Highlights

• 4B parameters (down from 9B), 2x throughput improvement
• 85.9% olmOCR overall (up from 83.1%)
• 77.8% multilingual average across 43 languages (up from 69.4%), 72.7% across 90 languages
• 2 pages/sec on H100 with 96 concurrent requests
• 15+ layout block types with bounding boxes
• Structured output for diagrams (Mermaid), charts, and images

olmOCR Benchmark

Category	Chandra 1	Chandra 2	Change
ArXiv	82.2%	90.2%	+8.0
Old Scans Math	80.3%	89.3%	+9.0
Tables	88.0%	89.9%	+1.9
Multi column	81.2%	83.5%	+2.3
Overall	83.1%	85.9%	+2.8

Multilingual

43-language averages: Chandra 2 77.8%, Chandra 1 69.4%, Gemini 2.5 Flash 67.6%, GPT-5 Mini 60.5%.

90-language averages: Chandra 2 72.7%, Gemini 2.5 Flash 60.8%.

Largest improvements in South Asian scripts (Bengali +27.2, Kannada +42.6, Malayalam +46.2, Tamil +26.9, Telugu +39.1). Full 90-language results in FULL_BENCHMARKS.md.

New Capabilities

• Layout blocks: text, section-header, caption, footnote, table, form, list-group, image, figure, diagram, equation-block, code-block, chemical-block, bibliography, table-of-contents, page-header, page-footer, complex-block
• Mermaid diagrams: Flowcharts and process diagrams converted to Mermaid format
• Chart extraction: Structured data (values, categories, axis labels) from bar/line/pie charts
• Image captioning: Captions generated from visual content and surrounding context
• Chemistry detection: Molecular structure descriptions from chemical diagrams

Install

pip install chandra-ocr

# With vLLM (recommended)
chandra_vllm
chandra input.pdf ./output

# With HuggingFace
pip install chandra-ocr[hf]
chandra input.pdf ./output --method hf

Links

• GitHub: https://github.com/datalab-to/chandra
• HuggingFace: https://huggingface.co/datalab-to/chandra-ocr-2
• Blog post: https://www.datalab.to/blog/chandra-2

Render pdf images properly

v0.1.7

Flatten in annotation

Additional fixes

v0.1.6

Fix file output dir

VLLM fixes

v0.1.4

Fix vllm token

Fix attention setting

v0.1.3

Fix attn impl

Fix attention implementation

v0.1.2

Fix attn impl

Update model

Pin model to the stable repo version.

Initial release

Initial repo release!