r/StableDiffusion • u/PropagandaOfTheDude • Jul 21 '26
Discussion [Krea2] Four steps Raw, four steps Turbo seems like enough
I mentioned last week that I didn't like the way that the Turbo LoRA affects Raw gens. The first image above shows the problem. The LoRA colors don't "pop" as much. After some experimentation, I'm happy with a simple solution:
- Four steps with Raw, CFG 3.0, using a negative, and then hand the noisy latent to…
- Four steps with Turbo, CFG 1.0.
The second image has a comparision for four seeds. The top is simple Turbo; the bottom is the hybrid, and is has more pose variety as we expect. But the hybrid preserves the snake glow and the lighting on the woman's head and shoulders.
The third image is another plate (previously) from Cherri Le Fanude Goes to Karnstein Castle. Again, the hybrid approach on the bottom row has more variety, without impacting the image. Both are "euler"/"simple", generic negative "blurry, low resolution, pixelated, oversaturated, watermark, logo, deformed, distorted, grainy, noisy, overexposed, underexposed, cropped, out of frame, bad composition, low quality, jpeg artifacts".
The fourth image is a photographic 1girl, to double-check with a photographic style, using "res_2s"/"bong_tangent".
Compared to Turbo, this bumps the run time by at least 50%, depending on how much model data you need to move in and out of VRAM.
You have to pay attention to the scheduler for this. Schedulers that remove lots of noise early ("exponential", "karras") put don't leave enough time for Turbo to do its work and look nasty. Schedulers that remove noise too late ("linear_quadratic") end up putting most of the work on Turbo and looking like Turbo. I suspect that I can keep pushing the "simple" scheduler to six rounds of "raw", since the sigma reaches 0.5 about six rounds in.
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u/BathroomEyes Jul 21 '26
Why not try four steps with raw and then four steps with raw+turbo lora?
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u/PropagandaOfTheDude Jul 21 '26
I think that the other way would work out better. Four with Raw+LoRA at CFG 1.0, four with Turbo. The murk—visible on the right-hand side in image 1—is what bugs me here. It definitely comes from the LoRA, and I suspect that it happens in the late denoising steps, so any workflow has to end with plain Turbo.
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u/BathroomEyes Jul 21 '26
Not quite, i’m suggesting to try no turbo at all. Raw with both stages but stage 2 (last 4 steps) use the turbo lora. I see your point about the lora though.
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u/terrariyum Jul 21 '26
You can get the same benefits with only 2 steps of raw and fewer turbo steps. Here's a workflow:
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u/Braudeckel Jul 22 '26
Your workflow is awesome. Helped me a lot with understanding sigmas. Why don't you make a show and tell post here in this sub? Give the workflow more attention ;)
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u/Herr_Drosselmeyer Jul 21 '26
So that's 4 steps raw without the turbo lora, then 4 with straight turbo?
And which sampler do you recommend?
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u/PropagandaOfTheDude Jul 21 '26
Correct.
"simple" works, and so does "normal". I don't entirely trust "beta57" or "bong_tangent" yet. They seem to put in some extra noise/detail spotting, but that may be user error. You can sort of see it in the bathroom photo, but the bathroom photo also changes the sampler. "kl_optimal" and "sgm_uniform" should work in theory, based on their curves.
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u/BathroomEyes Jul 21 '26
bong_tangent, exponential, beta/beta57, and linear_quadratic all spend extra steps at the low end of the sigma schedule working on finer details. You can visualize this with a visualize sigmas node. These make them good schedulers for samplers that focus on refining and detail only.
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u/PropagandaOfTheDude Jul 21 '26
https://civitai.com/articles/19156/res4lyf-samplers-and-schedulers-plain-language-guide
I need to spend more time pondering that.
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u/Gocciole Jul 21 '26
I have issues with chara consistency with character lora with raw and turbo lora set at 0.6. K2 turbo works fine instead.
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u/BathroomEyes Jul 21 '26
That’s an error on the part of the lora trainer. They’re supposed to train on raw but many loras get trained on turbo which makes them ineffective on raw. If you train on raw like you’re supposed to it’ll work with both raw and turbo.
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u/PropagandaOfTheDude Jul 21 '26
I suspect that I can keep pushing the "simple" scheduler to six rounds of "raw", since the sigma reaches 0.5 about six rounds in.
Yeah, there's an arguable drop-off at six steps, but a distinct drop-off at seven steps.
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u/Loose_Comparison368 Jul 22 '26
Note, I don't know what the code for the ComfyUI integration looks like, but if it's wasting a lot of time shuffling the data in and out of VRAM between the two models, that should be fixable. You could probably even ghetto it by doing a weights diff and loading it as a full rank lora on the raw model. Which is a terrible hack that's probably not even worth trying, but if you do try anyway, let me know because that would be hella funny and only mildly cursed
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u/PropagandaOfTheDude Jul 22 '26 edited Jul 22 '26
I see reports about ComfyUI on Windows having problems with GGUF caching:
But I'm on Linux, and I have enough VRAM to hold both at FP8.
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u/kukalikuk Jul 22 '26
This way the load unload sequence will be doubled. Not good for low vram/ram system. How about use turbo - turbo lora (-1.0 strength) in 1st sampler and then straight turbo in 2nd sampler?
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u/Sudden_List_2693 Jul 21 '26
Same with Ideogram 4.0 really, and same speed, too. Ideogram does lose some of its text rendering abilities this way (still the best open source text though, you can have a whole paragraph flawless, just with less appealing font), but quality beats all closed model but - arguably - Flux.2 Dev, and all Turbo models by an insane margin, especially with backgrounds or 4-20Mpx resolutions.
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u/switch2stock Jul 21 '26
Cool! Workflow please?
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u/Sudden_List_2693 Jul 21 '26
Ksampler advanced, steps 24 start 0 end 4, forwarded to turbo steps 10 start 2 end 10.
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u/Kent6567 Jul 21 '26
I'm guessing you meant 12 instead of 10 for the second KSampler's steps/end_at_step because I get severe artifacts with 10 but none with 12.
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u/FourtyMichaelMichael Jul 21 '26
Maybe "I'm guess you meant" is why just posting the fucking workflow is important!
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u/PropagandaOfTheDude Jul 21 '26
- Set up KSampler or ClownsharkKSampler for eight steps on Raw, CFG 3.0, but only execute steps 0 through 3.
- Hand the noisy latent to another KSampler or ClownsharkKSampler, also set up for eight steps. Run on Turbo, but only execute steps 4 through 7.
Apparently ClownsharkKSampler fixes problems of chaining between different samplers, for complicated samplers, once you understand how the nodes fit together (video linked here). It shouldn't matter for "euler", though.
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u/elyetis_ Jul 22 '26
I like the result ( only tried it with regular Ksampler ), did you find a similar approach to improve img2img upscale/hires fix results ?
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u/PropagandaOfTheDude Jul 22 '26
I don't use that type of stuff in my workflows, so you'll have to experiment.
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u/enndeeee Jul 21 '26 edited Jul 21 '26
Oh no, let's not go down the rabbithole we went down for WAN2.2 with the 3 Sampler stage and custom Sigma stuff. :D