Released on Oct 13, 2026
The first open-source MoE of OpenBMB's MiniCPM-V series: 35.2B total parameters, ~3B active per token, multi-image and video understanding with early visual-token compression (LLaVA-UHD v4). First open-source MoE with fluid on-device decoding — 13+ tok/s on 3GB of RAM on an iPhone 17 Pro Max — thanks to Lookahead Expert Scheduling (llama.cpp-omni), fine per-level quantization and DSpark speculative sampling. Day-0 support for Rockchip, Houmo, Intel, AMD and Arm; runs on Ollama, llama.cpp, vLLM and SGLang.
Prima variante MoE della serie MiniCPM-V: 35,2B totali / ~3B attivi, LES + quantizzazione per livello + DSpark, 13+ tok/s on-device con 3GB di RAM.
Visit the official site to download, learn more and start using MiniCPM-V 4.7 35B-A3B (MoE).
DeepSeek's MoE model with 552B total parameters and 8-16B active per token. 1M-token context, MIT license: free commercial use. Built for online serving, too large for local use on a single PC.
The most advanced open image model: excellent prompt adherence, solid anatomy, full fine-tuning. The standard for serious work.
Very few steps, high quality, and strong text rendering. The distilled FLUX variant, built for speed.
