How would you compare K-Means failure vs data non-clusterability?

K-Means failure occurs when structure exists but is mismatched; non-clusterability means no meaningful grouping exists.

If alternative algorithms (DBSCAN, GMM, spectral) produce meaningful structure, K-Means failure is due to model mismatch. If all methods fail and metrics remain poor, the dataset likely has no inherent cluster structure.