For which problems Krylov subspace methods are preffered over multigrid methods?

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As multigrid methods are known to have grid independent convergence rates with $O(N)$ computational cost, then why would one be interested in using Krylov subspace methods at all, for which convergence rates deteriorate with grid refinement? Are there any problems where Krylov solvers perform better than MG methods?