Open-weight models have closed the performance gap. GLM 5.2, Gemma 4, Kimi K3 and others now hold up against closed frontier alternatives on real benchmarks. What's left unanswered is cost: what it actually takes to run these models in production, at your volume, with your team maintaining them. Most comparisons stop at GPU cost versus API cost, which misses the real picture. This session walks through the six stages that determine true TCO: model choice, configuration search, autoresearcher, shadow-load testing, and ongoing optimization, and shows the breakeven math behind each one, where self-hosting wins and where it doesn't yet.
