1Why Small Models MatterSmall language models trade some breadth for speed, privacy, cost control, and fit, which often makes them the right tool for real work.Advanced 2Distillation & Quantization for EdgeHow to shrink models so they run near the user, with less latency, power, cost, and network dependence.Advanced 3On-Device Runtimes & NPUsA practical guide to how apps run artificial intelligence models locally, why neural processing units matter, and what trade-offs follow.Advanced 4Privacy & Offline InferenceOffline inference can reduce data exposure, but privacy still depends on what you collect, store, log, update, and govern.Advanced 5When Small Beats LargeA practical guide to choosing smaller AI models when speed, cost, control, and fit matter more than raw size.Advanced