After months of optimization work, I managed to get modern AI models (Qwen3, Gemma3) running locally on iPhone/iPad with full functionality - voice interaction, document analysis with RAG, and real-time conversations. The interesting technical challenge was maintaining performance while keeping everything on-device. No simplified models or cloud fallbacks - just proper local inference with vector databases, speech recognition, and multi-modal capabilities. Why this matters: Privacy: Conversations never leave your device Accessibility: Works in remote areas, planes, secure facilities Cost: No per-token pricing or API dependencies Control: Users own their entire AI stack The broader question: Are we seeing a fundamental shift in AI deployment? Instead of centralizing in massive data centers, could we be moving toward distributed, personal AI? This feels similar to the shift from mainframes to personal computers - computing power moving from centralized systems to individual devices. App Store link: https://apps.apple.com/us/app/bastionchat/id6747981691 Happy to discuss the technical details or implications for the future of AI deployment.