Nanonets-OCR2-3B vs Baidu Unlimited-OCR-2

Nanonets-OCR2-3B 25

Model card 5, Intended use and the languages are on the card. Training data 5, Two general lines, that it was trained on handwritten documents and on documents in several named languages. Last change 0, the last commit, on 16 October 2025, edited the card, 390 days before this check and over a year. Responsiveness 0, none of the 15 most recent discussions that aren't pull requests (13 October 2025 to 21 October 2026) has a reply from a nanonets member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, the earlier Nanonets-OCR-s stays in its own repository and OCR2 came out in new ones, with no dated note on the older one that we read. File health 10, Config, template and card agree on the Qwen2.5-VL classes. 5 + 5 + 0 + 0 + 5 + 10 = 25.

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). Training data is described by mix and labelling with no datasets named and no cut-off (5). The card changed on 2 November 2026 and the SGLang wheel on 29 October (20). Baidu's uploader replied in 1 of the 5 Hub discussions, a few (5). The first model stays in its own repository without a note pointing here (5), and the files agree with the card (10).

Nanonets-OCR2-3B 40

File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the nanonets organisation, which the card ties to nanonets.com and Nanonets' GitHub cookbook repository is written for by the model's name (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, Nothing on text in a document that tries to instruct the reader, on what the model refuses or on safeguards to add. Licence risk 0, With no licence there is nothing to hold Nanonets to. Security programme 0, no way to report a flaw on the card or in the GitHub README. Our Nanonets listing found no security.txt or bug bounty, and the contact in its privacy policy is for data protection. 25 + 15 + 0 + 0 + 0 + 0 = 40.

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. Provenance gets 15 for files in Baidu's verified organisation, linked from its GitHub organisation, with hashes for every file. Licence risk keeps 15, since MIT has none of the deductions. Safety evaluation, agent guidance and the security programme score 0, with no safety results, no cautions about use and no security contact found.

Nanonets-OCR2-3B 70

Chat template 20, chat_template.jinja in the repository (1,017 characters), Qwen's ChatML format with image placeholders. Tool-calling format 25, Read for a document parser as what it takes and returns. Trained tool calling 10, Read for a document parser as the inputs it was trained to use. Structured output 15, Read for a document parser as typed outputs. Reasoning control 0, A document parser with no reasoning. Context 0, Nanonets states no context length for it. 20 + 25 + 10 + 15 + 0 + 0 = 70.

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. Baidu documents the page images, the prompt, the request settings and the block output, and ships a converter for the server's output (25). It was trained to read many pages in one request (20). The block format with classes, boxes and HTML tables, and its conversion to Markdown, are documented with how to get them (15). The prompt is built in code, with no Jinja template in the repository (10). Reasoning control scores 0, and the context 5, trained at up to 64K tokens.