Takes 3 minutes (for a prompt resulting in a set of 4 images) on my 1080 as well. Really astonished that it takes GP about the same time using just a CPU. Seems like the older generation of GPUs isn't much better than CPUs in regards to ML stuff.

> Really astonished that it takes GP about the same time using just a CPU.

GP talks about generating a single image while you talk about generating 4.

A 1070 isn’t very powerful for ML compared to more recent GPUs, so several minutes sounds about right.

To add another data point, my GTX1080 takes ~60 sec to generate a pair of 500x500 images using txt2img. Haven't tried img2img yet as the UI package I went with is a bit buggy with it

also on a 1070, I can generate an image in ~15 seconds, surely you're doing something wrong.

What settings are you using it the people with 1080s above you are taking 3 minutes?

I'm using lstein's repository which loads the models and keeps them in memory. Then, for some diffusers 16 steps is enough to come up with a usable image (and using more steps will only add details, most of the time won't change much).

This is for the initial "exploration" step of the process. Once I like an image I typically play with the settings, then in the final step run with a large number of steps (and maybe even use upscaling).

So, default 512x512 size, 16 steps and default for the rest of the settings (I believe 7.5 scale, 0.75 strength).

Having said that, I also tried the official Docker image for stable diffusion and with the default values it generated an image in about 40 seconds.