Thinking of (seemingly) very different complexity of finding a solution to a NP problem and verifying it as the basis of practical cryptography, I am wondering if such separation is possible among deterministic polynomial class problems (P, FP, BPP).
For instance, solving a system of linear equations in n variables (by Gaussian elimination) has time complexity $C_s=O(n^3)$. However, verifying a solution obviously requires only $C_v=O(n^2)$.
Similarly for linear programming problems: $C_s=O(n^{3.5})$ for solving, $C_v=O(n^2)$ for verifying.
What are other polynomial problems with this property with respect to the best known solving and verifying algorithms? Are there any problems with much larger gap, e.g. $C_s=\Theta(C_v^2)$ or more?
More generally, which problems have the best known polynomial-time algorithms with complexity $\Theta(n^6)$ or more, where $n$ is the input size?