Xiaomi unveils 0.8B unified OCR model Xiaomi-OCR-0, scoring 96.83 on OmniDocBench v1.6

[HF Papers] Xiaomi researchers introduced Xiaomi-OCR-0, a unified 0.8B model for document parsing and OCR-centric understanding, according to the paper "Xiaomi-OCR-0 Technical Report." The team said it built an approximately 170M-sample OCR-centric corpus using an automated data engine that combines expert consensus, render-based verification and targeted synthesis. Starting from Qwen3.5-0.8B, the progressive training recipe combines Q-Mask-based text anchoring, continued pretraining and mixed-task reinforcement learning (Mix-RL). The paper reports scores of 95.24 on Real5-OmniDocBench, 96.83 on OmniDocBench v1.6 and 87.94 on Wild-OmniDocBench, plus an average of 83.2 across five OCR-oriented VQA benchmarks. Ablations indicate that, with sufficient parsing training, OCR-centric understanding supervision provides additional gains for document parsing. The results come from a preprint and have not been peer-reviewed.