A compact multimodal model that punches above its weight by activating only 3B parameters despite having 35B total, making it surprisingly capable for its computational footprint. It handles both text and image inputs, offering vision-language understanding in an efficient mixture-of-experts style architecture. The int4 quantization further reduces memory requirements, though this comes with the usual trade-offs in precision that quantized models carry.