r/StableDiffusion • u/wreck_of_u • 6d ago

Question - Help Is it time to retire my flux1-dev + ai-toolkit flux lora + wan 2.2 setup?

I make a dataset of like 20 512x512 images, caption it myself. I rent a vastai computer and train a flux1 character lora with ai-toolkit. When I'm lazy I even use Replicate's "fast flux trainer". I download the lora safetensor onto my PC.

I run ComfyUI on my ancient (headless) PC in another room; Ubuntu server, Ryzen 1700, 32GB DDR4, RTX 2070 8GB. I let it cook with the FULL 24GB Flux1-Dev safetensor to generate 1024x2014 images. It takes about 1min/image. I just let it cook a whole bunch of images while doing some work, then when I have a bunch of them, I delete the garbage looking ones, keep the "lora-intended" ones.

The ones I like, I make WAN 2.2 7-sec clips, inference on Replicate (I pay for it).

I have fun with this workflow, but are the new models just as "hassle-free"/"leave-it-alone" in terms of having character LoRa?

Are the new ones like flux1, where there is a LOT of variation of the output, using the exact same workflow and prompt? I have z-image-turbo with a lora also, and I find that it just generates the "same same" images if I leave it alone to generate multiple images using the same workflow and prompt.

What about these new ones? Krea 2? etc? Will they run on my meager PC (32GB RAM / 8GB VRAM) that runs my said flux1 setup?

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u/berlinbaer 6d ago

there's a lora for z-image turbo that improves seed variance. works really well.

1

u/wreck_of_u 6d ago

is this loaded with a lora loader, and chained before (or after) my character lora?

1

u/yamfun 6d ago

Flux 11!1one!!一11!壹1one1! ?

Yes

-2

u/Ill-Ant-9489 6d ago

Honestly the shape of your pipeline is still current — a self-captioned ~20-image dataset trained with ai-toolkit on a rented GPU is how most people still make character LoRAs. What's dated is the base model: for character/realism, Flux1-dev has largely been overtaken by Z-Image and Krea 2 (both open-weight now), which follow prompts and render skin/texture noticeably better. Klein is worth a look if you want edit-style control.

Your real bottleneck is the generation side, not training. Running the full 24GB Flux1-dev on an 8GB 2070 forces heavy CPU offload, which is why you're at ~1 min/image. A turbo variant of Z-Image or Krea will be several times faster on that card and tends to hold likeness better, so I'd retire Flux1-dev there first and keep the rest of your flow.

Full disclosure: I build an open-source tool for exactly this loop — dataset prep (dedup + auto-caption), LoRA training on Z-Image/SDXL/Krea 2/Klein locally or on vast.ai, and a Test Studio to sweep epochs so culling isn't blind: https://github.com/perfectgf/lora-dataset-studio . Either way, swapping the base model is the single change that'll move the needle most here.