Model comparison
Nanonets-OCR-s vs o3
Capability radar, value bars, and side-by-side posture.
Nanonets-OCR-s
Not scored
value score
o3
93
value score
Nanonets-OCR-s ctx
—
o3 ctx
200K
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- o393
Attribute tape
| Field | Nanonets-OCR-s | o3 |
|---|---|---|
| Developer | nanonets | OpenAI |
| Context | — | 200K |
| Modalities | Text, Code | |
| Openness | — | Proprietary Model |
| Speed | — | — |
| Price | — | $10/1M in · $40/1M out |
| Value score | — | 93 |
| Summary | Nanonets-OCR-s is an open-weight vision-language model that converts scanned documents, PDFs, and document images into structured Markdown, preserving layout elements such as tables, equations, signatures, watermarks, and checkboxes. It is designed to produce LLM-ready structured output for downstream AI and RAG workflows. | OpenAI reasoning model focused on hard problems. |