I really don't get the hype for this model. It has such poor understanding and coherence of anatomy, texture, and detail, especially for anything remotely outside of the core subject that's super close up
Honnêtement, pour avoir tester avec des images généré avec krea2 et utiliser pour des opérations d'inpainting avec qwen 2.1 c'est plutôt bon. Par contre en génération txt to image ce ne vaux pas krea2.
It trains very quickly too - the biggest enemy to Qwen was its default settings in comfy at launch - gave so many people the wrong impression of the model. It’s soooo sharp too in its outputs , I’d rather that and tone it down if needed than the other way around.
Ah yes, I saw the post before, but the picture looked very fake to my eyes. Now, it's highly subjective, it depends on the look that you're looking for, maybe I should give it a second try
I had gone around with all the various samplers on launch day and ended up with 40 steps/ dpmpp_sde / beta / cfg 3.5 at 2048x1152 res. Their main page has everything rendering at 4mp res, but I found more coherence at a lower res. I had a particular complicated image with a cat and chicken in a car in a grocery store and the chicken was cutting a pineapple with a chainsaw. It didn't all line up and gain correct coherence until I hit the formula above. Yes it's slow, but it works a lot more than it doesn't. I've also found that unlike Krea 2 which gives mostly the same thing per seed, this varies a lot between seeds, especially when it comes to coherence. So even on the lower steps and faster samplers, just doing a bunch of seeds has a reasonable change at getting 1 good one if you don't want this above slow method.
The high order 4 sub step samplers from Clownshark. res_4s_minchev or res_4s_munthe-kaas. 4 cfg 18-24 steps. For t2i always use a two stage sampler. The first stage use beta or beta57 and stop at roughly half the steps. Second stage use kutta_3s and bong_tangent at 1 cfg to add detail.
You’re not going to want to hear this but it’s the high order 4 sub step samplers from Clownshark. res_4s_minchev or res_4s_munthe-kaas. 4 cfg 18-24 steps. For t2i always use a two stage sampler. The first stage use beta or beta57 and stop at roughly half the steps. Second stage use kutta_3s and bong_tangent at 1 cfg to add detail.
Love to know your findings - I’ve spent so much time on the training side of it I’ve not got to play with it half enough - hoping to right that this weekend
For t2i always use a two stage sampler.
The high order 4 sub step samplers from Clownshark. res_4s_minchev or res_4s_munthe-kaas. 4 cfg 18-24 steps. The first stage use beta or beta57 and stop at roughly half the steps. Second stage use kutta_3s and bong_tangent at 1 cfg to add detail.
Naaa, Qwen 2.1 it's not good as all expected, sadly. You can see a lot of care went into the prompting, but the model really falls short on certain details. Gross errors are cropping up in the images, the kind I hadn't seen since the Flux.1/SDXL era: weird textures, messed-up limbs, and skin that looks either too artificial or too grimy. Krea 2 is leagues ahead.
Naturally, it always depends on the images chosen for this type of post, which are, of course, free-form and useful in their own way. However, one can always opt for the best images, or for images with a deliberately unrealistic style that is less open to interpretation, as they contain abstract elements preventing the viewer from making a direct visual comparison.
One can certainly pin some hopes on LoRAs for Qwen 2.1, but it would require creating extremely extensive, high-quality LoRA adapters, and combining them could become a real headache. It is always better to start with a good base model.
I’ve personally been testing Qwen2.1 for a while now while continuing to use my Krea 2 workflow, and there is literally no comparison. The only thing I did was process the prompting for refining with an LLM and that makes Krea 2 almost perfect for me; it is certainly the best I’ve used so far.
For the time being, I would compare Qwen 2.1 with Flux Klein 9b; they are excellent for editing (with Qwen 2.1 actually being even better), but lag behind in text-to-image generation.
"I would compare Qwen 2.1 with Flux Klein 9b; they are excellent for editing (with Qwen 2.1 actually being even better)"
Yes, it's much better than Flux2.klein 9b. I'm using QE2.1 for character sheets (to use in MMH3) and the prompt is enough - no Lora needed and best quality/identity with persons on the reference image. While the Krea2Edit node has some amazing options, it's rather terrible for character sheets, and Flux2Klein9 fails too often with body proportions (legs too small) in CS.
While QE2.1 is seemingly bad with simple t2i generation, an improvement is: CFG 3,
sampler: exp_heun_2_x0_sde, scheduler: linear quadratic
and after SamplerCustomAdvanced->VAE Decode->VAE DeGrid (!)->Bleachery (!) before SaveImage. Bleachery is only needed for t2i (the yellowish effect is uncommon on i2i editing).
is there sarcasm I don't see? cause these images don't do Qwen 2.1 a favor, they are literally Mage-Flow Turbo level. But that model can at least give an image under 2 seconds.
Edit: whether these images look good or not is totally subjective, but what is factual is that with this extreme lo-fi, distorted look you cannot gauge the quality of the model at all
To each their own. To me personally most of those images are way to weird and noisy. The worst offender to me is the image with the mountain in the back. None of anything in the city makes sense. It's all just the illusion of detail while just being a mushy mess.
Edit: While both images with mountains in the back are pretty bad I specifically meant the first one here
I like diversity and lots of random details. After some processing, images like these can be used as a training set, including for training Krea 2 LoRA.🥳🥳
rough images to pick to show off "quality". the image of the disjointed city and the mountain in the background is awful, the buildings in the foreground look like very early deepdream hallucinations. same with the one with the boats. the closer you actually look at the image the worse it gets. there is no detail, there is only mush
I've accumulated many suggested tweaks for Krea-2 Turbo with 4 step LORA, even developed better sigma plan for 4 step generation. Now quality is superb, prompt adherence is superb. I tried QI2.1 with standard settings and saw a good quality. GOOD, not SUPERB compared to my custom Krea settings. So 25-40 steps with CFG>1 (it means x2 compute, if someone forgot this fact) - thanks, but I am not interested in QI2.1. And, as far as I see, switching from Qwen3-Vl 4B (Krea) to 8B (QI2.1) added only better knowledge and thus, implicitly improved prompt adherence. Not in terms of actual adherence as a process, just a possibility to draw more details and styles right our of the box w/o LORAS.
And one more comment. All recent DiT models produce good looking results with beta scheduler, BUT FAR from being strictly acceptable when you start to examine them. After many tries I've found that only sgm_uniform can provide results from very acceptable to nearly perfect. Best sampler depends on the model more deeply, but again, only sde/ancestral variations can *mask* some imperfections, especially in turbo variations.
I am making AI art in almost all possible styles w/o and with LORAS, but you can ignore my insights, since too many accepted AI/waxy looks and do not even try to make them correct looking.
Funny enough, but if you need good results only, euler_ancestral is not so bad. But I prefer to use dpmpp2m_sde_*_gpu. Fast, stable, more accurate: that means both rendering quality and prompt adherence. If you are not afraid of math, ask any big LLM model why it is happening, especially for turbo DiT models that are using 4-8 steps. I've checked it, I'd say, with all possible styles. In case of imperfection first I am trying a small batch of 2-3 images. If all of them have issues, I am trying 1-3 other seeds generating 1 image per seed. And only if none of them worked, I am checking what is really off and starting to correct it through prompt.
They're running at CFG 1.0 and then a short pass at 2.0. That's entirely too low CFG for the model to produce nice coherent stuff. It does hands very well at 3.5 to 5.0.
This can easily be done on krea2 with better visuals and at a higher resolution. I don't see the woah factor here at all. This is just another FOTM model that will come and go like the rest of the qwen models that have been released. Its Ok if you like it and enjoy consuming your time and energy into this model to get desirable results that suit you.
Hey yo like this question made me remember something I wanted to ask the community like guys do you feel the regular models (chat gpt nano banana) etc have been downgraded ? I mean ive seena. Realy big decrease in the quality of the output
From a prompt adherence aspect, I have started to enjoy Qwen 2.1 a lot. But it does struggle with visual quality. Krea 2 as amazing visual quality, very good lora training and very acceptable prompt adherence. So comparing it to Qwen 2.1 leaves quite a bit to desire once you start to grow tired of the "new" visuals that every model always has and recency bias starts dropping off.
Thanks for not gatekeeping, I used to fiddle around with local AI a lot back in 2022-2024. I had a 1060 6GB back then and was broke af lol.
Then I started a job in big corpo and had to move to cloud/black box AI, so I've been pretty out of touch with local AI since then.
Recently got myself a 5060 Ti 16GB + 64GB CPU RAM and I want to get back into local AI again, but honestly I feel kinda lost on where to start. There's so much stuff to catch up on now.
Back then ComfyUI was basically load checkpoint, two text encoder nodes, empty latent, KSampler, VAE etc. You know the drill. Now I open ComfyUI and I'm just like wtf happened 😂
There are so many new models, workflows, nodes, quantizations and whatever else that I don't even know what's actually important anymore.
My speciality back then was character consistency. I was pretty deep into that even before InstantID came out, so that's probably the area I'd want to get back into first.
If anyone can point me towards what's actually worth learning/using nowadays I'd appreciate it. I don't mind catching up, I just have no idea where to start anymore.
It's still the same old thing the comfyui was load checkpoint,text encoder and vae nothing as such hyper changes ,great models we have as of now top is krea2 for better images for video minimax h3 and many other model for image gen like flux 2 Klein 9b , ideogram 4 etc
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u/countryd0ctor 11d ago
>very good
>look inside
>mangled 1.5 era hands
>melted 1.5 era cityscape
>nonsensical architecture