MiniCPM-o 4.5 now runs efficiently on Apple Silicon with TyloQuant MFQ! 🥰

The team at @Tylogi_ai has released an MFQ-quantized build of MiniCPM-o 4.5, bringing efficient multimodal inference to local devices.

Rather than applying a single quantization format uniformly, TyloQuant MFQ uses neuron-aware mixed-format quantization to reduce memory usage while retaining MiniCPM-o 4.5’s vision, audio, and real-time interaction capabilities. 🤖

Highlights:
⚡ Native acceleration with Metal on Apple Silicon
📉 Multiple quantization levels for different memory and quality targets
🎥 Vision, audio, and full-duplex multimodal interaction
🛠️ MFQ-backed Metal and CUDA kernels with native C++ runtime components

This release shows how advanced mixed-format quantization can make powerful multimodal models more practical for private, local, and edge deployment.

🤖 MiniCPM-o 4.5 model:
https://t.co/bRcld16Jco

🔗 Explore the MFQ model:
https://t.co/FwqJ6CQoE5

📦 Download the MFQ model:
https://t.co/XJzs4WOXrJ