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DEI introduces a distributed Quality-Diversity search framework using heterogeneous LLMs as mutation operators, showing that model diversity improves performance over homogeneous parallel approaches. Evaluated on the Core War domain, a four-node heterogeneous ensemble achieves significant gains in QD-Score and coverage.