A compact, quantized multimodal model that trades some numerical precision for reduced memory footprint through 4-bit weight quantization with 16-bit activations. It handles both text and image inputs, making it versatile for vision-language tasks. The quantization means it runs on more modest hardware than its full-precision counterpart, though with potential minor quality trade-offs.