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In a recent work (Naszvadi, Adam and Koniorczyk, Mathematics 2025, 13(16), 2633) we have introduced an ILP model for solving the code-theoretic problem of finding the maximal cardinality of codes with a minimum codeword Hamming distance. Our method is not based on algebraic structure of the alphabets, it is suitable for decomposing bigger problem instances into equivalent smaller ones, and can be rewritten to a quadratic binary unconstrained optimization (QUBO) problem in a straightforward manner. Owing to the recent development in hardware and software QUBO heuristics and exact solvers, our aim was to find a set of useful problems which can be suitable as a benchmark in the meantime. Our problem is well-studied in code theory, the relevant bounds are known, and the instances are often hard even in the case of small problem sizes. It also gives room for comparison of ILP solvers' behavior with QUBO solvers. Here we present an
analysis of our problem instances when solving with exact and heuristic QUBO solvers.