A compact vision-language model that punches at a small weight class, handling both text and image inputs despite its 2B parameter footprint. It processes visual and textual information together, making it accessible for deployment in resource-constrained environments. Its open-weight nature means practitioners can inspect, fine-tune, and run it locally without API dependencies.