How many images to parameters?

A developer training a latent diffusion model with 430 million parameters on 2 million images is considering scaling up parameters to improve quality, but is uncertain about the optimal ratio based on scaling laws and comparisons to Stable Diffusion's 860 million parameter models.

I’m training a latent diffusion model and wondering what the scaling laws were, I couldnt find much info online. My current is around 430M parameters training on around 2 Million images. I’m thinking of possibly scaling the parameters up a bit to increase the quality. Is this a good idea or should I scale down my images or parameters? Based on SD, they seemed to use billions for their models which were at 860M, half of mine