# DeepSeek-OCR 2 vs Baidu Unlimited-OCR-2 (slim)

> Baidu Unlimited-OCR-2 scores 54.2 (C) to DeepSeek-OCR 2's 49.2 (D) for ocr. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/deepseek-ocr-2-vs-unlimited-ocr-2.md (~7,200 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/deepseek-ocr-2-vs-unlimited-ocr-2.json · canonical https://www.anchorterminal.com/compare/deepseek-ocr-2-vs-unlimited-ocr-2
- 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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Baidu Unlimited-OCR-2 scores 54.2 (C) on agent readiness against DeepSeek-OCR 2's 49.2 (D), and leads in 2 of 4 scored categories. DeepSeek-OCR 2 leads on reach and risk. Both do ocr.

- DeepSeek-OCR 2: D 49.2, rank #147 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-ocr-2.min.md
- Baidu Unlimited-OCR-2: C 54.2, rank #133 of 160 open-weight models · https://www.anchorterminal.com/tools/unlimited-ocr-2.min.md
- DeepSeek-OCR 2, good for Teams that want an Apache 2.0 OCR model on a small GPU and already run vLLM Ahead on Reach, 65 against 55; Risk, 50 against 45.
- Baidu Unlimited-OCR-2, good for Pipelines with an NVIDIA GPU that need long scanned or rendered documents parsed in one pass, with page order, cross-page tables and boxes kept Ahead on Agent interface, 75 against 35; Documentation and upkeep, 50 against 22.

| Category | DeepSeek-OCR 2 | Baidu Unlimited-OCR-2 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 55 |
| Risk (20%) | 50 | 45 |
| Agent interface (10%) | 35 | 75 |
| Documentation and upkeep (10%) | 22 | 50 |

| Fact (where they differ) | DeepSeek-OCR 2 | Baidu Unlimited-OCR-2 |
| --- | --- | --- |
| Vendor | DeepSeek | Baidu |
| Licence | Apache-2.0 | MIT (Hub metadata; the Hugging Face repository has no LICENSE file, and the GitHub code repository's LICENSE is the MIT text, copyright 2026 Baidu) |
| Last release | 2026-02-03 | 2026-10-26 |

Why the edge:
- Agent interface, Baidu Unlimited-OCR-2 +40: DeepSeek-OCR 2 35 (Chat template 10, no Jinja template in the repository and none in tokenizer_config.json.); Baidu Unlimited-OCR-2 75 (Read for a document parser, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns.)
- Documentation and upkeep, Baidu Unlimited-OCR-2 +28: DeepSeek-OCR 2 22 (Model card 2, Intended use is there, as the two prompts.); Baidu Unlimited-OCR-2 50 (The card covers intended use and the new attention, and misses limitations, parameters, context length, languages and a cut-off (5).)
- Reach, DeepSeek-OCR 2 +10: DeepSeek-OCR 2 65 (Memory 30, the only build from DeepSeek is the BF16 safetensors file, 6.78 GB, and 6.78 GB × 1.2 = 8.1 GB, within 16 GB.); Baidu Unlimited-OCR-2 55 (Memory earns the full 30, since the only build is 6.69 GB of BF16 weights that need about 8 GB with the fifth added.)
- Risk, DeepSeek-OCR 2 +5: DeepSeek-OCR 2 50 (File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented way to load it is trust_remote_code, which runs the rep…); Baidu Unlimited-OCR-2 45 (File safety gets 15, safetensors only but loaded with trust_remote_code or through a prebuilt SGLang wheel from the repository.)