A tiny but capable vision-language model that punches above its weight class for its size. At 256M parameters, it processes both images and text, making it deployable in memory-constrained environments where larger models simply won't fit. The trade-off is clear: it handles multimodal tasks but with the limitations you'd expect from a very compact architecture.