An independent study running 260 controlled configurations across 6 benchmarks, 5 architectures and 3 model families found that multi-agent effects range enormously, from strongly positive on well-decomposable tasks to significantly negative on sequential planning tasks; gains shrink when single-agent scores are higher, and without central verification errors are amplified by a far greater factor than with verification.