Establishing the convergence of splines can be cast as a variational problem which is amenable to a $Γ$-convergence approach. We consider the case in which the regularization coefficient scales with the number of observations, $n$, as $λ_n=n^{-p}$. Using standard theorems from the $Γ$-convergence literature, we prove that the general spline model is consistent in that estimators converge in a sense slightly weaker than weak convergence in probability for $p\leq \frac{1}{2}$. Without further assumptions we show this rate is sharp. This differs from rates for strong convergence using Hilbert scales where one can often choose $p>\frac{1}{2}$.