Krea 2:

The Krea 2 version tends to add noise to the prompt, which can enhance textures and detail, but can also end up too noisy at times. I swap between er_sde and sgm_uniform for noisier generations where I want more detail and euler_ancestral and linear_quadratic when it gets too noisy. Lowering the strength can also help tone down the noise and artifacts.

Overall, I think it's a little quirkier than my Z-Image Turbo version, but it definitely has an impact on generation look.

Z-Image Turbo:

I really enjoyed the style of images ChatGPT would produce for a fictional film, so I trained a Z-Image Turbo LoRa on some ChatGPT generated images with prompts provided by ChatGPT itself. It did pretty much exactly what I wanted it to do.

I use it around 0.5-0.9 strength and I'd also play with samplers and schedulers as they have a fairly significant impact on final product. I think dpmpp and beta has worked the best for me, but it's also much slower than other samplers.