WorldModelGym is a benchmark that evaluates world models through decision-based fidelity, measuring how useful they are for real-world decision-making by testing whether agents can successfully rank action sequences. It uses a standardized interface across 100+ tracks in environments like Atari and Meta-World, with a normalized regret metric where models predict outcomes and select optimal plans.