Edge assistants have been forced to choose between a responsive first word and a thoughtful complete answer. The round‑trip to a cloud model routinely adds several seconds, shattering the illusion of a conversational partner. A new study shows that a model an order of magnitude smaller can seed the answer locally, letting a cloud model finish without the user noticing the handoff. Before this work, on‑device language models were limited: even the smallest 100 M‑parameter models were reported to exceed the power and compute constraints of many wearables, as noted in the study. Consequently, many systems rely on pure cloud inference despite its latency penalty, or on rule‑based generators that can produce stilted replies. Researchers have noted that even the smallest 100 M‑parameter models strain smartwatch CPUs, and cloud APIs dominate latency budgets, as reported in the paper [1] .…