  In the near future, ultra deep observations of galaxy clusters with HST or
JWST will uncover $300-1000$ lensed multiple images, increasing the current
count per cluster by up to an order of magnitude. This will further refine our
view of clusters, leading to a more accurate and precise mapping of the total
and dark matter distribution in clusters, and enabling a better understanding
of background galaxy population and their luminosity functions. However, to
effectively use that many images as input to lens inversion will require a
re-evaluation of, and possibly upgrades to the existing methods. In this paper
we scrutinize the performance of the free-form lens inversion method Grale in
the regime of $150-1000$ input images, using synthetic massive galaxy clusters.
Our results show that with an increasing number of input images, Grale produces
improved reconstructed mass distributions, with the fraction of the lens plane
recovered at better than $10\%$ accuracy increasing from $40-50\%$ for
$\sim\!\!150$ images to $65\%$ for $\sim\!1000$ images. The reconstructed time
delays imply a more precise measurement of $H_0$, with $\lesssim 1\%$ bias.
While the fidelity of the reconstruction improves with the increasing number of
multiple images used as model constraints, $\sim 150$ to $\sim 1000$, the lens
plane rms deteriorates from $\sim 0.11''$ to $\sim 0.28''$. Since lens plane
rms is not necessarily the best indicator of the quality of the mass
reconstructions, looking for an alternative indicator is warranted.
