Enterprise AI trends toward model routers, not one giant model
ingliguori · x · 2026-10-08
Ingo Dil argues bigger models won't win every workload: while the industry obsessed over training, enterprises will obsess over inference, which repeats millions or billions of times with a cost per call. The best model for a workload is the smallest one that completes it reliably. He sketches a stack — small models for routine classification, specialist models for domain tasks, frontier models for hard reasoning, local models for sensitive data — concluding that future AI architecture looks less like one giant model and more like a model router. Intelligence becomes an allocation problem.
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