AI is happening. The future is updating.MiniCPM-V-4.6-Thinking-gguf
> **This repository hosts the GGUF (llama.cpp) quantized version of MiniCPM-V 4.6 Thinking.** For the original BF16 weights and the full model card, please refer to openbmb/MiniCPM-V-4.6-Thinking. **MiniCPM-V 4.6 Thinking** is the long chain-of-thought reasoning variant of MiniCPM-V 4.6. It generates an explicit reasoning trace before producing the final answer, substantially boosting performance on complex multimodal reasoning, math, and OCR-heavy tasks, while keeping the same edge-friendly architecture (SigLIP2-400M vision encoder + Qwen3.5-0.8B LLM) and the mixed 4x/16x visual token compression of MiniCPM-V 4.6. MiniCPM-V 4.6 can be deployed across three mainstream end-side platforms — **iOS, Android and HarmonyOS**. The clips below are raw screen recordings on phone devices without edition.
> **This repository hosts the GGUF (llama.cpp) quantized version of MiniCPM-V 4.6 Thinking.** For the original BF16 weights and the full model card, please refer to openbmb/MiniCPM-V-4.6-Thinking. **MiniCPM-V 4.6 Thinking** is the long chain-of-thought reasoning variant of MiniCPM-V 4.6. It generates an explicit reasoning trace before producing the final answer, substantially boosting performance on complex multimodal reasoning, math, and OCR-heavy tasks, while keeping the same edge-friendly architecture (SigLIP2-400M vision encoder + Qwen3.5-0.8B LLM) and the mixed 4x/16x visual token compression of MiniCPM-V 4.6. MiniCPM-V 4.6 can be deployed across three mainstream end-side platforms — **iOS, Android and HarmonyOS**. The clips below are raw screen recordings on phone devices without edition.