  We qualitatively examine the accuracy and fidelity between two
diffusion-based image generation systems, namely DALL-E 2 and Luna, which have
massive differences in training datasets, algorithmic approaches, prompt
resolvement, and output upscaling. The methodology used is a qualitative
benchmark created by Saharia et al. and in our research we conclude that DALL-E
2 significantly edges Luna in both alignment and fidelity comparisons.

Computer Vision and Pattern Recognition