面壁智能开源 MiniCPM-V 4.7 多模态模型系列

🚀 Introducing MiniCPM-V 4.7, our new open-source MLLM series!

Advancing the Performance–Efficiency Pareto Frontier.

It brings strong multimodal capabilities to iOS and Android devices with extreme efficiency.

Two new models:

🔹 MiniCPM-V 4.7 35B-A3B — Bring SOTA performance to local devices with newly introduced LES (Lookahead Expert Scheduling) technique, a new milestone of on-device multimodal AI.

🔹 MiniCPM-V 4.7 1B — Lightweight, efficient multimodal AI. Easier to deploy.

⚡ What's new?

SOTA performance: Competitive results across 34 benchmarks spanning multimodal understanding, STEM reasoning, OCR and long-video comprehension.

Fast on-device inference: LES predicts and preloads expert weights to reduce inference stalls, boosting 5× speedup on iPad Pro M4 (16GB) with byte-for-byte identical outputs. It enables MiniCPM-V 4.7 35B-A3B to achieve 17+ tokens/s on iPad Pro M4 (16GB) and 13+ tokens/s on iPhone 17 Pro Max, while costing only 3GB memory 🤯

Efficient visual processing: 4× and 16× hybrid visual token compression. Even at 16× compression, 35B-A3B scores 90.4 on OCRBench, 5.2 points ahead of Qwen3.6 35B-A3B.

Easier customization: We introduce Self-Replay Fine-Tuning, a simple way to customize new target capabilities at low cost while maintaining general performance.

Broad hardware support: Day-0 adaptations for Apple, Intel, AMD, Arm and Rockchip, with many more platforms supported through FlagOS!

Download, deploy, and build something we haven't imagined yet. 👀👇

🔗 GitHub: github.com/OpenBMB/MiniCPM-V

🤗 Hugging Face: huggingface.co/collections/o…