The first complete OCR solution combining fast, accurate parsing with reliable OCR quality assessment.
MiniCPM-OCR 1.0
MiniCPM-OCR 1.0 (1.3B) is the first OCR-specific model in the MiniCPM-V/o family. It focuses on text-centric document understanding, covering text, tables, formulas, charts, seals, and structured information extraction.
🏆 SOTA document parsing: MiniCPM-OCR 1.0 achieves a SOTA score of 93.68 on Real5-OmniDocBench, a benchmark for real-world document parsing, and demonstrates leading parsing capabilities on OmniDocBench v1.6, Wild-OmniDocBench, and olmOCR-Bench. It supports Chinese and English documents and PDFs, handling both standard documents and challenging capture conditions, including scans, curved pages, photographs, skewed pages, and recaptured documents.
⚡ Efficient inference. With DSpark decoding acceleration (DSpark-BF16, DSpark-GGUF), MiniCPM-OCR 1.0 improves end-to-end processing efficiency by 55%. Its throughput is approximately 1.49× that of PaddleOCR-VL-1.6 and 3.62× that of MinerU2.5 Pro, reducing the time needed for large-scale document parsing.
MiniCPM-OCR Jev
MiniCPM-OCR Jev is an OCR quality decision model for text, formulas, and tables. Given an image and its corresponding OCR result, it returns a quality score from 0 to 1 to help select reliable results and locate content that needs review.
Tianyu Yu
Ph.D. Student
Efficient MLLMs, trustworthy multimodal alignment, and LLM/MLLM post-training.