MianBi Intelligence has recently launched MiniCPM 3.0, a high-performance AI model that operates on devices with just 2GB of memory, heralding a new era of edge AI experience. The MiniCPM 3.0 model features 4 billion parameters and outperforms GPT-3.5, providing AI services on mobile devices comparable to those of GPT-3.5. This allows users to enjoy fast, secure, and feature-rich local AI services without relying on cloud processing, ensuring a smoother and more private intelligent interaction experience.

The latest version 2.6 of WallFacer’s MiniCPM-V series has rapidly climbed to the Top 3 on GitHub and HuggingFace trends, surpassing ten thousand stars. Since its release in February, it has accumulated over a million downloads, becoming a benchmark for on-device model capabilities. MiniCPM-V2.6 achieves performance enhancements for on-device multimodal models with 8 billion parameters, including real-time video understanding, multi-image joint understanding, and multi-image in-context learning, with a quantized backend memory of only 6GB and an inference speed of up to 18 tokens.

"MiniCPM-V2.6" is an edge-side multimodal artificial intelligence model that, with only 8B parameters, has achieved SOTA (State of the Art) results in single image, multiple images, and video understanding, all under 20B parameters, significantly enhancing edge AI's multimodal capabilities and being fully comparable to GPT-4V.

One of the major highlights of MiniCPM-Llama3-V2.5 is its efficient energy consumption. When running on mobile devices, it requires only 8GB of VRAM in combination with the NVIDIA GeForce RTX 4070 graphics card to achieve rapid inference and extremely fast operation speed. Additionally, the image encoding speed has been improved by 150 times, marking the first realization of system-level multimodal acceleration on the edge. Even more impressive, this model supports over 30 languages, providing robust support for multilingual environments.