Any model with publicly known benchmark scores and inference costs goes, not just OpenAI's o series.

I will consider a model to be "o3-equivalent or better" if it scores ≥25% on FrontierMath (o3 scored 25.2%) and performs similarly on other benchmarks.

(Note that o3's exact inference costs in the configuration used for benchmarking are currently unknown IIUC, though this market description will be updated with exact figures if they become public. This market can still resolve even without exact figures if e.g. OpenAI announce an o4 that's "10x cheaper" for roughly the same performance.)