Xiaomi has released Xiaomi-OCR-0, an open-source 0.8B parameter document parsing model integrating text recognition, structure parsing, and QA.
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🔎 Xiaomi has released an open-source model for document parsing with a size of just 0.8 billion parameters. Xiaomi-OCR-0 integrates text recognition, document structure parsing, key information extraction, and question-answering based on document content. In other words, the model’s scope goes beyond simple "transcribing text from an image"—it helps transform documents into data that can be used for further processing. According to the developers: - It scores 95.24 points on Real5-OmniDocBench. - It achieves an average of 83.2 points across five benchmarks focused on text-recognition-based question-answering. - It ranks first among models with fewer than 1 billion parameters for document parsing quality on OmniDocBench v1.6. The model weights, inference code, an interactive demo, an MCP (Model Context Protocol) service, and an "Agent Skill" have all been made publicly available. The latter two components allow document processing capabilities to be integrated into AI agent workflows. Its compact size makes the model an attractive option for deployment within your own infrastructure. However, performance on specific types of scans, languages, or complex tables should be verified ind
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