The Diffusion Model outperformed Vanilla GAN and WGAN by several orders of magnitude in minimizing variance across lattice parameters, lattice angles, space group number, and fractional coordinate variances as well as the agreement between absolute and relative fractional coordinates and pairwise distance matrix difference. The Vanilla GAN was orders of magnitude worse than both the WGAN and Diffusion Models. We hypothesized that low variances across parameters, angles, space group number, and fractional coordinates and low differences between relative and absolute fractional coordinates would correspond to better performance in other metrics as well.