Documentation
README
Swap cheap, but guard the cases the cheap model loses
Every "the cheap model is 95% as good" claim hides a distribution: on most inputs the gap is invisible, and on a few specific cases the premium model isn't a few percent better, it's a different class. The canonical example (image generation, as of 2026-06): a cheap model like Wan runs ~7-8x cheaper per image than GPT-Image-2 and a normal viewer barely notices, except on text inside the frame, charts, dense layouts, and typography, where GPT-Image-2 leads its leaderboard by the largest margin recorded. A blind swap saves money and quietly ships garbled slides. Your job is to make the swap conditional and write the conditions down.
Steps
This is the opening of the README. Read the full README on GitHub.