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This paper introduces CF-World, a counterfactual benchmark to evaluate whether text-to-image models rely on causal reasoning or mere pattern matching. Experiments show all models degrade sharply in counterfactual settings, suggesting their understanding is limited to tightly coupled visual-textual patterns rather than genuine causal reasoning.