There's a pattern I see every release cycle: a new budget-friendly model ships, the discourse explodes with hot takes, and within 48 hours half my feed has declared it a drop-in replacement for everything. The claim might even be true. But here's what nobody posting those takes can tell you: whether it's true for your specific workload. And most of the time, that's the only question that matters.
A healthier mental model: stop treating model selection as a one-time shopping decision and start treating it as a runtime policy. Route work to the inexpensive option by default, check the output with something that isn't a model, and only pay for the heavyweight option when the check fails. Below is a working implementation of that policy, plus the measurement discipline that turns it from a hunch into an auditable system.
Two lanes, not two opinions
My configuration is deliberately boring:
Lane A (try first): the current low-cost or free option. I'm intentionally not naming a specific checkpoint in this article — model names decay faster than the code below does, and you should be re-benchmarking against whatever shipped this month anyway.
