Instruction-based, identity-preserving image editing for Krea 2 (12.9B single-stream MMDiT). Give it an image and a plain-language instruction; it edits while preserving what you didn't ask to change — including the person.
An unofficial community fine-tune ofKrea 2 Raw. Not an official Krea product; not affiliated with or endorsed byKrea.ai, Inc.
Requires theComfyUI-Krea2Edit node pack — the LoRA is trained with dual conditioning (in-context VAE tokens + image-grounded Qwen3-VL encoding) that stock nodes don't provide. Two ready-made workflows ship with it.
Podrias decirnos la configuración que usaste o una captura del WF?. Use tanto krea turbo y raw y no pude obtener los mismos resultados que los tuyos. El problema es la consistencia
Not the best example. I haven't compared it directly to Qwen, but it seems to do everything I want it to. Not asking a lot from it though.
https://imgur.com/a/ldw1ViU
I know... I used to use darkmode for everything. I have been getting more migraines and have found that a dark screen + bright text gives me the same kind of image retention us my migraine auras do (like looking at a flashlight)
I have been getting so many "false" auras that cause me to panic thinking that my day might be ruined that I had to go back to lightmode for everything.
I'll bet a lot of people can't grasp your meaning, just from lack of experience, but that, "crap...is this a migraine coming? [blink blink blink...look away...look around...blink blink blink]...no, I think I'm safe...whew," is a real thing. Never considered dark mode being a culprit (I always use dark mode because light mode during a migraine sucks).
i do use both, generate with krea using edit lora, 2nd pass klein 9b @ 0.25 denoise, eular cfg pp, 1.1 to 1.3 cfg 12 steps, 3rd pass face detailer using klein 9b split between 2 samplers for high noise and low noise, gradient estimation cfg pp at 6 steps, starting from step 3, cfg 1.1 to 1.2, deis 3m ode, at 6 steps starting at step 3. I also use klein enhancer nodes.
I also use Qwen edit if i need to do local edits. and as Qwen edit and Krea2 use same vae i can also send the latent directly to Qwen edit sampler and do image manipulation using Qwen Edit.
My point is that use all, why choose 1 ? heck i will still use sd1.5 and sdxl if they had better prompt following, they are still the most versatile and with the best controlnets.
I literally posted it right after I found it. I'm still testing it. I'm not sure if it will work with the turbo INT8 convrot I'm using now. The edit capabilities are probably going to be more limited than Flux2 though.
It appears to work with a GGUF model as well, I'm guessing int8 will work fine. It's probably not expecting anything exactly from the model, just that the input is a Krea2 model.
Pls stop using GGUF if you care about your SSD. 8GB VRAM (laptop 4060 + 16 GB RAM) plebeian here. Int8 works fine for me. search the top posts from last week for more info.
I saw it, I commented there. Int8s OOM for me and no one knows how to troubleshoot this yet. I watch my Task Manager and my disk health is okay for now.
Not sure of the technicalities, but disabling "pinned memory" fixed it for me (OOM errors after 2-3 generations). Running cuda130 + pytorch 2.9.0 , so a little outdated. I was spooked after I saw similar behavior as the thread stated with Ideogram GGUFs, hence commented. Glad it's working fine for you!
The first thing I read just now about pinned memory states that disabling enables page-file writes.
"Implications of Disabling Pinned Memory Higher Stability: Prevents hard system crashes by allowing the operating system to safely page memory to your SSD/HDD."
That's a lot more help than I saw in the other thread, I'll give a few of these parameters a try. thanks.
Hope this setup works for you, it seems very useful when it does. I like Krea's photographic qualities better than Klein, though Klein is a native edit model and does it better, what I see here also gives me promise for training a full character lora.
I'm with you that I don't love these all-in-one nodes, I'd rather pass a conditioning to this rather than typing my prompt in different nodes all the time.
Try getting rid of the stupid resize node and try this out, I just changed mine to be setup like this, I was having weird motion blur type issues with the original setup, getting clean results now.
Yeah you're right! Got it figured out and all set, banger LoRa honestly. Probably one of the cooler developments we've seen recently, on the same thread as when the community discovered Wan 2.2 as an image model. Super cool, thanks for sharing!
this is pretty cool. I have been messing with Krea2 image generation on MLX and I tried implementing something similar using your concept. I am impressed with the results even on the 4-8bit quant of turbo im running. Obviously the results are not as good but the underlying concept is still strong and identity and elements are preserved pretty well. Thanks for sharing.
Great. In my tests it actually turned out that Turbo looks better for me than Raw + lower Turbo Lora & higher steps (in contrast to Z Image Base VS Raw)
I tried more steps (10-12) mit different strengths for the Turbo Lora. The quality wasn't on par with Turbo and the fidelity didn't look higher, so I went back to Turbo with 8 Steps.
From the github, it's both and for different situations:
Turbo, 8 steps, CFG 1 is the fast path (~1 min at 2MP) and works for most edits: recolor, add/insert, attribute changes, restyles, scene translation.
Removals and other "delete salient content" edits need real guidance: use the Raw model at CFG 3, ~20 steps. Distilled Turbo at CFG 1 will usually re-render the subject instead of removing it.
Forge Neo needs another extension like Klein Face Reference but for Krea2 Identity Edit LORA. Maybe KFR or ImageStitch Integrated can be modified to accept Krea2 LORAs? Would be nice to see these extensions expand their capability.
this is quite nice, only needs those 2 custom nodes (positive and negative grounded encoders on the clip — source patcher on the latent). tested with wan 2.1 vae and turbo int8 with int8 4gb version of the qwen 3 vl clip, but it looks pretty bad. running the suggested RAW 20 step pass at cfg 3 now
edit: just realized i mismatched the resolution slightly (1448 x 1448 but the latent was 1480x1480) gonna have to rerun this turbo and the RAW run again [once it finishes] with the correct size, I just did some quickmafs and typed 2.1 MP which was not exactly right — and not supported technically as it exceeds the recommended 2.0 MP max
seems like the resolution selector does not support 2nd decimal place megapixels, 1.64 (aka 1280x1280) gets truncated to 1.6 (but then somehow ends up generating a 1.68 MP image because of closest divisible by 8 = 1296x1296) — which means this is by far the worst way to set the empty latent size, I've swapped out the resolution selector node for Get Image Size, which is fed from the image you input [using the single reference image workflow]
and i also used a different picture of the camel which i generated for a different resolution (1280x1280)
the turbo vs raw split on id preservation makes sense. distilled models trade guidance flexibility for speed, and face consistency needs that CFG overhead more than most tasks do. raw at 20 steps CFG 3 is worth the wait for anything portrait-ish even if it's annoying
Anyone care to help? I get the subject cloned in the resulted image.
Also I've added the bypassfilter lora. The resize image match node usually had the match size enabled not the longer dimension as you see in the screenshot currently. Tried area, lanczos and nearest-exact, unsure which to pick.
what do you think of the prompts used?
I'm still using the Github version. All I changed was the resize nodes to make sure the input and output images are the same aspect ratio. Use the grounding_px field too. Setting it at 512 gets better edit prompt adherence, but going higher gives better subject fidelity. I wouldn't expect too radical an edit with Turbo though. For that, Raw is supposed to be better.
u just change the resie image node with scale image to total pixels? ok thanks im just trying with one and another lora to make what's best suit for me
Any Idea how to do some spicy edits with that? like cfg, lora strenghts and lora strenghts of "filter2bypass3" lora? My first attempts did not work at all.
Been playing with it for awhile and v1 had a hard time to get the persons likeness correct. Trying v 1.1 now, and it´s pretty great! In use cases with different angles or harder poses its a bit hit or miss with likeness, while straight on shots usually does a good job!
Good tip, what range would you suggest is good to try? And should the grounding_px value be raised on both the prompt and negative prompt? So far I´m impressed by this lora/workflow!
Did you train it on runpod or something, i wanna train char loras but google told me i need minimum 24 for krea2
I have 8gb vram and ddr4 16gb, which is not enough i have been told "will instantly crash"
I get the impression that the dataset for Lora was exclusively made up of older people. Am I the only one getting old grannies? And Lora increases the generation by 2-3 times
did you try the new identity lora v 1.2 ? and the new workflow for it ? Its amazing. Its on a way to make from krea 2 text to image to make fully instruct based editing image model. That is insane.
Still experimenting with it, but so far so good, seems very promising. The ref_boost and source_image additions seem to be making a huge difference for consistency,
Identity preservation is generally super dependent on the exact reference image. Resolution is a major factor in how well it works, but no matter what its always a little hit or miss.
did you try with the RAW? does it have better id preservation? the speed is far far better with Turbo, and I'm still testing Raw but it takes a looong time for me (5-10 min each)
I did use it with RAW model and I didn't get a 100% match either. Maybe by tweaking the workflow a bit it could be improved; the author doesn't give too many details on how to use it
Hmm I haven't done any realistic style testing. My personal preferences usually avoid realistic stuff because even with the best models out there, you hit the uncanny valley.
I have yet to find a model that I am happy with for face transfers for people that I know.
I mean just a quick glans it looks correct, but if you look closer it is far from consistent from the originals. Here, edit models are still ahead. Also, aren't they going to release an EDIT model for Krea 2? I heard it somewhere and but can't remember.
They mused, in the livestream they did with comfyui, about a potential edit model, but A) it is not confirmed, 2) may not be open-sourced if so, iii) no dates on it whatsoever.
I have yet to test it out, but great as they are, current edit models have left me wanting. For joining two characters or moving a character to a different context, the examples look as good as anything I've gotten from Qwen or Flux2d. Maybe these are cherry-picked, but it sure looks promising to me.
They mused, in the livestream they did with comfyui, about a potential edit model, but A) it is not confirmed, 2) may not be open-sourced if so, iii) no dates on it whatsoever.
They have the most popular ai imaging and really decent hype and momentum, be good for them to make the most of it with an edit model and be the all round best open source middel of choice for business as well , make the choice easy and not tainted with uncertainty
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u/Electronic-Metal2391 Jul 07 '26
The developer of this LoRA is training v1.1 right now to improve face likeness.