A compact, quantized vision-language model that trades some precision for dramatically reduced memory footprint through 4-bit weight quantization. It handles both text and image inputs, making it multimodal despite its small size. The quantization means it runs efficiently on constrained hardware, though the weight compression can introduce minor quality trade-offs compared to full-precision variants.