This is an automated archive made by the Lemmit Bot.

The original was posted on /r/stablediffusion by /u/371830 on 2024-09-19 17:53:26+00:00.

After using Flux for over a month now, I’m curious what’s your combo for best image quality? As I started local image generation only last month (occasional MJ user before), it’s pretty much constant learning. One of the things that took me time to realize is that not just selection of the model itself is important, but also all the other bits like clip, te, sampler etc. so I thought I’ll share this, maybe other newbies find it useful.

Here is my current best quality setup (photorealistic). I have 24GB, but I think it will work on 16 GB vram.

• flux1-dev-Q8_0.gguf

• clip: ViT-L-14-TEXT-detail-improved-hiT-GmP-TE-only-HF.safetensors - until last week I didn’t even know you can use different clips. This one made big difference for me and works better than ViT-L-14-BEST-smooth. Thanks u/zer0int1

• te: t5-v1_1-xxl-encoder-Q8_0.gguf - not sure if it makes any difference vs t5xxl_fp8_e4m3fn.safetensors

• vae: ae.safetensors - don’t remember where I got this one from

• sampling: Forge Flux Realistic - best results from few sampling methods I tested in forge

• scheduler: simple

• sampling steps: 20

• DCFG 2-2.5 - with PAG below enabled it seems I can bump up DCFG higher before the skin starts to look unnatural

• Perturbed Attention Guidance: 3 - this adds about 40% inference time, but I see clear improvement in prompt adherence and overall consistency so always keep it on. When going above 5 the images start looking unnatural.

• Other optional settings in forge did not give me any convincing improvements, so don’t use them.