SmolVLM Grows Smaller – Introducing the 256M & 500M Models!

honestly? making models smaller is a necessary evil, but the performance hit is brutal. those 256m and 500m models are fine for simple classification tasks, but they're often just dumbed-down versions of larger models. we're trading raw capability for speed, and for most complex enterprise needs, that trade-off is unacceptable. it works for specific edge cases, not general intelligence.