A compact, no-frills embedding specialist that punches above its weight for its size. With only 3 layers and a 384-dimensional hidden size, it trades depth for speed, making it noticeably faster than larger siblings while still producing useful semantic representations. The tradeoff is real though — shallower architecture means it can miss nuance that bigger models catch.