3 ms·

Well, the results are in, at least for text-to-image (the editing bench will come later). Qwen-Image 2.1 is definitely a pretty big leap over the last open-wei

Well, the results are in, at least for text-to-image (the editing bench will come later). Qwen-Image 2.1 is definitely a pretty big leap over the last open-weight version, Qwen-Image 1.0, released back in August of last year and managed to score 7 out of 15 as opposed to its predecessor which scored 4 out of 15. Even though it's significantly smaller, 7b vs 20b, it's multimodal (so you don't need a separate image-to-image model like you did with Qwen-Edit), more coherent, and significantly faster even when outputting at higher 2K resolutions. However, in my testing, I found that I had to play with dialing up the CFG depending on the complexity of the prompt. I've also added a progress dropdown under Model Performance so you can see how cloud vs. local models have been trending since 2024. Spoiler: June of this year released some of the biggest bangers (Krea 2, Ideogram 4, and the kind of slept-on Boogu-Image 0.1). Downsides: - It was clearly trained on at least some level of synthetic training data, and it shows in some of the subpar outputs in terms of fidelity. Some of this you might be able to iron out with a refiner model downstream or a custom LoRA but time will tell. - They've moved away from the permissive Apache license. Commercial usage is only allowed by request. Comparisons: https://genai-showdown.specr.net https://genai-showdown.specr.net If you just want to compare local models only: http://genai-showdown.specr.net/?models=local http://genai-showdown.specr.net/?models=local

chr15m 5d ago
What's to stop somebody using the output at scale on local hardware to distill their own model and then making that available open weights?
- gspr 5d ago
  This is the fundamental problem with where the AI race is heading, IMHO. Broadly, there are two possible legal interpretations (to my layman's mind): * A model is derived work of its training data. This seems sane to me. Open, but copyrighted, works (like FOSS) remain protected from abuse. There's some legal moat around AI models. But on the other hand it seems unlikely that there's enough liberally licensed (or public domain) training data to go around. The little guy's status quo remains, the frontier labs' work slows down massively. * A model is not derived work of its training data. This seems to me insane, but a lot of the world seems to hold this view (including the frontier labs). Stuff like FOSS or indie art is under huge threat of copyrightwashing. But on the other hand, there's also zero legal moat around the models. The little guy is eviscerated, but so are the frontier labs. Neither interpretation seems, to me, to be capable of sustaining the last couple of years' developments. But what do I know.
  - skykooler 5d ago
    If a model is derived work of its training data, surely all the existing frontier models that have been training on copyrighted work have a big legal issue, and therefore so does anything produced with them?
    - gspr 5d ago
      Yes. Of course. They'd have to be rebuilt with acceptably licensed training data. And since there might not be a enough of it, the model owners are screwed. My point is that they're also screwed in the opposite scenario, because they rely on the same legal protection (against deriving works) as the works they trained on. That's why I don't understand how any of this can be sustained.
  - dale_glass 5d ago
    > A model is not derived work of its training data. This seems to me insane, but a lot of the world seems to hold this view Why insane? Models don't take the content as-is, they take measurements. I don't owe you royalties just because I used your photo to get the proportions and coloring of a duck right. Go watch artist streams, you'll often see people to go Google Images for references. I've never seen that result in credit or payments. The alternative is that we hand out lots of money to a few large companies specializing in content archives, and there's really no benefit to anyone else anyway. On the long term I would expect a few fat cats to get fatter, the small guy to get nothing, and AI still work but get there slowly. I don't see the point or the benefit.
    - gspr 5d ago
      > Models don't take the content as-is, they take measurements. At some point, enough measurements constitute a copy. If I redistribute the average value of all the pixels in your photo, I'm obviously not in violation of your copyright. If I measure and redistribute 90% of its DCT coefficients (i.e. make a slightly compressed JPEG), I am. The interesting stuff happens between those extremes. We cannot just take as a given that all LLMs always are on the safe side. It is not at all obvious.
    - 5d ago
SV_BubbleTime 5d ago
> and the kind of slept-on Boogu-Image 0.1 Not slept on at all. It was absolute trash, and I’m super curious why people pretend otherwise. There isn’t a single thing that model did better than any temporal peer.
meherabhossain 5d ago
[flagged]

chr15m 5d ago

What's to stop somebody using the output at scale on local hardware to distill their own model and then making that available open weights?

gspr 5d ago
This is the fundamental problem with where the AI race is heading, IMHO. Broadly, there are two possible legal interpretations (to my layman's mind): * A model is derived work of its training data. This seems sane to me. Open, but copyrighted, works (like FOSS) remain protected from abuse. There's some legal moat around AI models. But on the other hand it seems unlikely that there's enough liberally licensed (or public domain) training data to go around. The little guy's status quo remains, the frontier labs' work slows down massively. * A model is not derived work of its training data. This seems to me insane, but a lot of the world seems to hold this view (including the frontier labs). Stuff like FOSS or indie art is under huge threat of copyrightwashing. But on the other hand, there's also zero legal moat around the models. The little guy is eviscerated, but so are the frontier labs. Neither interpretation seems, to me, to be capable of sustaining the last couple of years' developments. But what do I know.
- skykooler 5d ago
  If a model is derived work of its training data, surely all the existing frontier models that have been training on copyrighted work have a big legal issue, and therefore so does anything produced with them?
  - gspr 5d ago
    Yes. Of course. They'd have to be rebuilt with acceptably licensed training data. And since there might not be a enough of it, the model owners are screwed. My point is that they're also screwed in the opposite scenario, because they rely on the same legal protection (against deriving works) as the works they trained on. That's why I don't understand how any of this can be sustained.
- dale_glass 5d ago
  > A model is not derived work of its training data. This seems to me insane, but a lot of the world seems to hold this view Why insane? Models don't take the content as-is, they take measurements. I don't owe you royalties just because I used your photo to get the proportions and coloring of a duck right. Go watch artist streams, you'll often see people to go Google Images for references. I've never seen that result in credit or payments. The alternative is that we hand out lots of money to a few large companies specializing in content archives, and there's really no benefit to anyone else anyway. On the long term I would expect a few fat cats to get fatter, the small guy to get nothing, and AI still work but get there slowly. I don't see the point or the benefit.
  - gspr 5d ago
    > Models don't take the content as-is, they take measurements. At some point, enough measurements constitute a copy. If I redistribute the average value of all the pixels in your photo, I'm obviously not in violation of your copyright. If I measure and redistribute 90% of its DCT coefficients (i.e. make a slightly compressed JPEG), I am. The interesting stuff happens between those extremes. We cannot just take as a given that all LLMs always are on the safe side. It is not at all obvious.
  - 5d ago

SV_BubbleTime 5d ago

> and the kind of slept-on Boogu-Image 0.1 Not slept on at all. It was absolute trash, and I’m super curious why people pretend otherwise. There isn’t a single thing that model did better than any temporal peer.

meherabhossain 5d ago

[flagged]