The second SA and ammonia (AM) cluster database has been taken from Engsvang and Elm. They used the GFN1-xTB level of theory to produce ∼4k equilibrium structures and ∼7.7k non-equilibrium structures. In this work, we used the equilibrium structures as starting points for MD simulations at 300 K while producing an additional ∼6.4k structures. The overall database thus consists of ∼18k SA n AM n,n±1,n±2 clusters, where n ∈ 1-9. The GFN1-xTB level cannot provide accurate binding energies, and using ωB97X-D/6-31++G(d,p) would be too computationally demanding for all cluster sizes. Therefore, using the same methodology as Engsvang and Elm, the energies and forces were recalculated at Although both databases are similar in size, the SA-AM database contains larger clusters, an extra atom type (nitrogen), and a more complex scheme of cluster binding patterns than just O-H interactions, as in the SA-W database. We additionally recalculated the SA-W database at the B97-3c 35 level. Therefore, we have three different datasets (SA-W ωB97X-D/6-31++G(d,p) , SA-W B97-3c , and SA-AM ) to compare for the suitability of ML. As such, we can examine the role of the theory level and database complexity in ML training.