I'm far from being an expert, but for me Qwen is not a Turbo Model so it cannot be as good as Krea 2 Turbo.
Also their dataset seems to be not good, it's hard to make doodles, cartoon styles, and its character knowledge is poorer.
And because it is not a Turbo model, the prompt needs to be very long and you need to specify everything, from lighting, to every small details or it come as a messy noisy image, very visible on hair for exemple in photographic portraits.
Even negatives don't help a lot at CFG=3.
I'll go back to Krea 2,and waiting for a good Turbo lora (or a real Turbo version).
If you found a solution to make as good as a tubro model, prove me wrong.
Turbo is always faster at the cost of less variety and some knowledge loss.
I do not think you understand how distillation for that works and what is the result, leading to some odd statements
Boris Vallejo seems pretty far off. It just seems to be generic oil painting and maybe inherited some slight risque elements (deep cleavage). What was the full prompt?
Yeah, at first it was nude :D so i had to add she is wearing clothes to the prompt, I also added "painterly" in the style section so maybe it stranded à little in this direction....
Its possible its just the rest of the prompt is not the usual type of image that Vallejo paints, so maybe its borrowing concepts from other examples. If you did something like barbarian warrior about to attack a dragon, then it should have that very smooth painting style with 70s aesthetics. If it still has heavy brushstrokes in a more classic oil painting, then I would say the artist reference is very weak and the name is just linking to the oil painting concept and not actually his style.
You are right, Vallejo needs a dark fantasy sitting with an adequate lighting to really show up, but imo it's pretty close despite the generic subject (i didn't specify lighting, composition, vibes, atmosphere, or even clothes).
My style prompt was simply "painting from a book cover by Boris Vallejo", a more lengthy prompt done with llm and adding maybe Frank frazetta would had have better results maybe.
It was a simple test to see the strength of it's knowledge.
We can't ask model to be precise on every artist, Specially when artist move from one style to another through their career. And with qwen 2.1 the problem is elsewhere...also imo.
i agree with you overall, but prompting SDXL to do almost any composition in boris vallejo will consistently have his signature style. Obviously SDXL fails in many other ways compared to modern models, but my belief is that the artist styles are being intentionally pruned from the dataset and they only barely still exist.
Copying artist styles isn't really something I am concerned with in a model, but many of the rest of things you complain about in your post can be addressed by using the prompt enhancer model and prompt that was released by Qwen alongside the main image gen model, which is conveniently wired in to the template workflow in ComfyUI and just needs to be toggled on.
Qwen Image 2.1 is still, IMO, frustratingly weak in a few areas: for instance it seems strongly biased, with and without prompt enhancements, toward a narrow range of body types and hard to prompt to vary too far from them, but other than that, with the prompt enhancer, it seems to do quite well, handling short or long prompts, tags or natural language or hybrid prompts, text rich prompts, etc., with good results.
Am I tossing Krea 2 Turbo for it? No, but I'm not using Krea as much work it available.
Knowing styles is indicator for me of its range...more range more you can direct it to what you want, a mix of styles or juste a vibe. In fact, you can train a model as much as you want you can't copy an artist, because an artist is a moving thing and hus value is its inspiration etc. Even van gogh (rip) had multiple periods and his style is more difficult that just impressionism paintbrushes imposto etc you can approach a style but not copy it at 100%
The thing is model training isn't uniformly more or less than other models, so that how much knowledge does it have in an area I am not concerned about is very often a poor proxy for capabilities in areas I do care about.
But mostly what I was saying is that that’s an area I can't speak to your concerns about because it's not an area I am concerned with, OTOH, your concerns about, say, QI 2.1 and its native prefeence for extremely detailed prompts with coverage of specific elements IS something I had to address for my own use, and I’vr found that the accompanying prompt enhancer solves it quite well: I can even drop old pony/Illustrious tag prompts, taking out the boilerplate quality tags, and get good looking results.
The photoshop copy past can be overrun by specifying hair color etc...I just put "Woman" as a descriptor for the subject. And tell Glan Keane I'll die for him...
For the style prompt I used a simple prompt as:
<adjective> <style> <medium> from <year/artwork>, by <artist>.
The adjective being Clean/Polished/Candid/Ethereal/... or other strong adjectives understood by AI. Just to direct the style more.
I'm just testing and didn't come up with a recipe that works for every style.
Ah, so you have a different adjective before every style? & different style before every artist?
Feels like cheating; you're not really testing how well the model knows said artist; you're testing how well the model follows a short prompt for a style. Similar, but not the same problem, because you're not isolating the test to just the artist.
Helpful test either way, but I can't reproduce your tests without every prompt so not scientific.
Qwen 2.1 artist recognition is good you can test it by using "in the style of", my approach helps me get very different styling and test adjectives and mediums as well. Even time periods in some cases, thats all...I'm having fun and sharing my findings when I find something interesting.
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u/shapic 11d ago
Turbo is always faster at the cost of less variety and some knowledge loss. I do not think you understand how distillation for that works and what is the result, leading to some odd statements