Show Notes
Small local models can now answer most everyday AI queries, but the real efficiency win comes from routing between device and cloud rather than local hardware winning outright. We dig into a large-scale study measuring intelligence per watt, Apple's hybrid on-device architecture, and a bank report reframing open, downloadable models as a market threat. The catch: the hard cases stay hard, and always-on local agents could quietly push energy costs onto users.
In this episode: - Routing to the best local model handles nearly 89% of single-turn chat and reasoning queries - The efficiency gain is smart local-cloud routing, not local hardware beating the cloud - Local viability jumped sharply from 2023 to 2025, with intelligence per watt up 5.3x - Local models cover creative tasks well but struggle with technical fields and the hardest reasoning - Apple and open-weight model releases show big players building local-first, hybrid architectures - A rebound-effect caveat: always-on local agents may raise total energy use, shifting costs onto consumers
Sources: WWDC26: Apple unveils next generation of Apple Intelligence, Siri AI, powerful parental controls, and an expansive set of software improvements — https://www.apple.com/uk/newsroom/2026/06/apple-unveils-next-generation-of-apple-intelligence-siri-ai-and-more/ Intelligence per Watt: Measuring Intelligence Efficiency of Local AI — https://arxiv.org/pdf/2511.07885 MAI-Thinking-1: Building a Hill-Climbing Machine — https://microsoft.ai/pdf/mai-thinking-1.pdf Open-source AI 101: the battle for the future of AI — https://www.dbresearch.com/PROD/IE-PROD/PDFVIEWER.calias?pdfViewerPdfUrl=PROD0000000000634010&rwnode=REPORT Computer Environments Elicit General Agentic Intelligence in LLMs — https://arxiv.org/pdf/2601.16206
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