Open-source models

The first complete OCR solution combining fast, accurate parsing with reliable OCR quality assessment.

MiniCPM-OCR 1.0 parses Chinese and English documents and PDFs, balancing quality and efficiency across challenging inputs such as scans, photographs, curved pages, and recaptured documents. MiniCPM-OCR Jev evaluates OCR results at the region level, distinguishing problematic regions from reliable ones.

The first open-source MoE to run smoothly on-device without compromising performance. A new performance–efficiency Pareto frontier.

Ultra-Efficient Architecture. MiniCPM-V 4.6 reduces the visual encoding computation FLOPs by more than 50%. It also supports mixed 4x/16x visual token compression rate, allowing flexible switching between accuracy and speed.

The first full-duplex omni-modal large language model. It can continuously receive video and audio while generating speech and text, enabling real-time interactions that see, hear, and speak simultaneously.

Earlier MiniCPM-V/o Models

MiniCPM-V 4.0, MiniCPM-o 2.6, MiniCPM-V 2.6, and other earlier releases.

Efficient High-FPS and Long Video Understanding. Powered by a new unified 3D-Resampler over images and videos, MiniCPM-V 4.5 can now achieve 96x compression rate for video tokens, where 6 448x448 video frames can be jointly compressed into 64 video tokens (normally 1,536 tokens for most MLLMs).