We consider inhomogeneous square random matrices of size $N$ with independent entries of mean 0 and finite variance. We assume that the variance profile of this matrix is doubly stochastic and has a band-like structure with an appropriately defined bandwidth $W$. We prove that when the entries have a bounded density and a subgaussian tail, then the empirical spectral measure for the eigenvalues of the matrix converges to the circular law as $N$ tends to infinity whenever $W\geq N^{1/2+c}$ for any $c>0$. In the special case of block band matrices the density assumption is not needed and the moment condition is relaxed. This establishes the circular law limit throughout the entire delocalization regime in 1-d: $W\geq N^{1/2+c}$ and extends the previous thresholds for the circular law limit with exponent $\frac{5}{6},\frac{8}{9},\frac{33}{34}$ in $N$. The main technical input is a new lower bound on the small-ish singular values via Green function estimates and a new lower bound on the least singular value with fewer moment conditions.