OpenBMB just open-sourced MiniCPM5-2B, a compact 2-billion-parameter dense model that punches above 4B-class models like Qwen3.5-4B across coding and math benchmarks. Weighing only around 5GB, it easily runs locally on consumer edge hardware, and the team also released the full high-quality dataset behind it.
ModelBest and OpenBMB just open-sourced MiniCPM-V 4.6, a 1.3B multimodal model designed to run on-device with just 6GB of RAM. Despite its small size, it beats rivals like Qwen3.5-0.8B in multi-benchmark tests while slashing token consumption to a fraction of the cost. Why it matters: It shows tiny edge models can deliver serious multimodal intelligence on everyday consumer devices.
OpenBMB just rolled out MiniCPM-o 4.5, a 9B omnimodal model that sees, listens, and speaks simultaneously in real time. Thanks to an end-to-end full-duplex design, it doesn't just wait its turn—it monitors inputs at 1Hz and can proactively interrupt with reminders. It matches Gemini 2.5 Flash on key multimodal tasks while running locally on a Mac or single GPU.
