AI Models

AI Models is the track to read when you need to choose between GPT-4o, Claude Sonnet, Gemini 2.5, Llama 4, Mistral Large, DeepSeek, Qwen, or one of the smaller open-weight alternatives for a real project. Benchmarks tell you a narrow story; the real decisions turn on context-window pricing, latency at your token sizes, hallucination behavior on your domain, safety-tuning differences, fine-tuning availability, and licensing. We cover each major model family and the tradeoffs that benchmark leaderboards hide.

A theme running through this track is that the best model is rarely the biggest one. Teams that ship reliably tend to route between multiple models, using a smaller faster cheaper model for the majority of work and reserving the flagship model for the fraction of queries that justify its cost and latency. We cover routing design, evaluation setups that let you compare models honestly on your own data, and the practical steps for migrating from one model family to another without breaking existing behavior.