# Ling-3.1-flash-1019 vs Baidu Unlimited-OCR-2 (slim)

> Ling-3.1-flash-1019 and Baidu Unlimited-OCR-2 score within a point of each other for open-weight models you run yourself, 54.8 and 54.2 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-unlimited-ocr-2.md (~10,350 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-unlimited-ocr-2.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-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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Ling-3.1-flash-1019 and Baidu Unlimited-OCR-2 score within a point of each other on agent readiness, 54.8 (C) and 54.2 (C). Baidu Unlimited-OCR-2 leads on agent interface. Both do open-weight models you run yourself.

- Ling-3.1-flash-1019: C 54.8, rank #126 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-1-flash-1019.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
- Ling-3.1-flash-1019, good for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding Ahead on Reach, 60 against 55; Documentation and upkeep, 56 against 50.
- 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 60.

| Category | Ling-3.1-flash-1019 | Baidu Unlimited-OCR-2 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 55 |
| Risk (20%) | 45 | 45 |
| Agent interface (10%) | 60 | 75 |
| Documentation and upkeep (10%) | 56 | 50 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Baidu Unlimited-OCR-2 |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Baidu |
| Licence | MIT | 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 | 2026-11-04 | 2026-10-26 |

Why the edge:
- Agent interface, Baidu Unlimited-OCR-2 +15: Ling-3.1-flash-1019 60 (Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning.); 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, Ling-3.1-flash-1019 +6: Ling-3.1-flash-1019 56 (Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claim…); 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, Ling-3.1-flash-1019 +5: Ling-3.1-flash-1019 60 (Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build.); 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.)