# Chandra OCR 2 vs Surya OCR 2.5 (slim)

> Surya OCR 2.5 scores 61 (C) to Chandra OCR 2's 54.7 (C) for ocr. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/chandra-ocr-2-vs-surya-ocr-2-5.md (~2,950 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/chandra-ocr-2-vs-surya-ocr-2-5.json · canonical https://www.anchorterminal.com/compare/chandra-ocr-2-vs-surya-ocr-2-5
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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Surya OCR 2.5 scores 61 (C) on agent readiness against Chandra OCR 2's 54.7 (C), and leads in 2 of 4 scored categories. Both do ocr.

- Chandra OCR 2: C 54.7, rank #127 of 160 open-weight models · https://www.anchorterminal.com/tools/chandra-ocr-2.min.md
- Surya OCR 2.5: C 61, rank #82 of 160 open-weight models · https://www.anchorterminal.com/tools/surya-ocr-2-5.min.md
- Chandra OCR 2, good for Small companies and researchers who need accurate document parsing on their own GPU and fit the licence
- Surya OCR 2.5, good for Small companies and researchers who need quick OCR with layout on a laptop or a small GPU and fit the licence Ahead on Reach, 90 against 65; Documentation and upkeep, 57 against 33.

| Category | Chandra OCR 2 | Surya OCR 2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 90 |
| Risk (20%) | 45 | 45 |
| Agent interface (10%) | 70 | 70 |
| Documentation and upkeep (10%) | 33 | 57 |

| Fact (where they differ) | Chandra OCR 2 | Surya OCR 2.5 |
| --- | --- | --- |
| Licence | Modified OpenRAIL-M (free for research, personal use and companies under $2M in revenue and funding) | Modified OpenRAIL-M (free for research, personal use and companies under $5M in revenue and funding) |
| Last release | 2026-06-26 | 2026-10-29 |

Why the edge:
- Reach, Surya OCR 2.5 +25: Chandra OCR 2 65 (Memory 30, the only build from Datalab is the BF16 safetensors file, 10.59 GB, and 10.59 GB × 1.2 = 12.7 GB, within 16 GB.); Surya OCR 2.5 90 (Memory 30, Datalab's own Q8_0 GGUF is 0.63 GB with a 0.21 GB projector, and 0.84 GB × 1.2 = 1.0 GB, within 16 GB.)
- Documentation and upkeep, Surya OCR 2.5 +24: Chandra OCR 2 33 (Model card 8, Intended use and the languages (over 90) are on the card.); Surya OCR 2.5 57 (Model card 17, Intended use, limitations, the architecture (a Qwen 3.5-style vision-language model with separate detection models), parameters (689M), the servi…)