Skip to content
View original post on X: OpenBMBOfficial
Published
52/100

OpenBMB releases MiniCPM-V 4.7 for on-device multimodal inference

AIOpenBMB presents MiniCPM-V 4.7, a 35B MoE multimodal model that it says can run on a phone with about 3GB of memory. The post says the 35B-A3B model uses LES (Lookahead Expert Scheduling) for mobile MoE inference, and a 1B variant targets resource-constrained hardware.
OpenBMBVerified on XOfficial
@OpenBMB
View on X

🎬 35B MoE multimodal AI. On your phone. With just 3GB of memory. 🤯

This is MiniCPM-V 4.7 in action: reading real-world signs, planning around constraints, parsing complex documents, and reasoning over visual data.

Powered by LES (Lookahead Expert Scheduling), the 35B-A3B model brings efficient MoE inference to mobile devices, while the lightweight 1B variant delivers capable multimodal understanding on resource-constrained hardware.

🛠️ With Self-Replay Fine-Tuning (SRFT), developers can customize models for new tasks while maintaining general performance.

From iOS to Android, MiniCPM-V 4.7 makes powerful multimodal AI more practical to run locally.

Try it 👇
🔗 http://github.com/OpenBMB/MiniCPM-V
🤗 http://huggingface.co/collections/openbmb/minicpm-v-47
Self-Replay Fine-Tuning: http://openbmb.cn/en/blog/self-replay-fine-tuning

Source details

OpenBMB · x.comPublished · added here

Original title: 🎬 35B MoE multimodal AI. On your phone. With just 3GB of memory. 🤯