It doesn't seem to have open weights, which is unfortunate. One of Qwen's strengths historically has been their open-weights strategy, and it would have been great to have a true open-weights competitor to 4o's autoregressive image gen. There are so many interesting research directions that are only possible if we can get access to the weights.
If Qwen is concerned about recouping its development costs, I suggest looking at BFL's Flux Kontext Dev release from the other day as a model: let researchers and individuals get the weights for free and let startups pay for a reasonably-priced license for commercial use.
Jackson__ · 1h ago
It's also very clearly trained on OAI outputs, which you can tell from the orange tint to the images[0]. Did they even attempt to come up with their own data?
So it is trained off OAI, as closed off as OAI and most importantly: worse than OAI. What a bizarre strategy to gate-keep this behind an API.
It's really too close to be anything but a model trained on these outputs, the whole vibe just screams OAI.
echelon · 1h ago
The way they win is to be open. I don't get why China is shutting down open source. It was a knife at the jugular of US tech dominance.
Both Alibaba and Tencent championed open source (Qwen family of models, Hunyuan family of models), but now they've shut off the releases.
There's totally a play where models become loss-leader for SaaS/PaaS/IaaS and where they extinguish your closed competition.
Imagine spreading your model so widely then making the terms: "do not use in conjunction with closed source models".
diggan · 1h ago
> I don't get why China is shutting down open source [...] now they've shut off the releases
What are you talking about? Feels like a very strong claim considering there are ongoing weight releases, wasn't there one just today or yesterday from a Chinese company?
diggan · 1h ago
> One of Qwen's strengths historically has been their open-weights strategy [...] let researchers and individuals get the weights for free and let startups pay for a reasonably-priced license for commercial use.
But if you're suggesting they should do open weights, doesn't that mean people should be able to use it freely?
You're effectively suggesting "trial-weights", "shareware-weights", "academic-weights" or something like that rather than "open weights", which to me would make it seem like you can use them for whatever you want, just like with "open source" software. But if it misses a large part of what makes "open source" open source, like "use it for whatever you want", then it kind of gives the wrong idea.
rushingcreek · 1h ago
I am personally in favor of true open source (e.g. Apache 2 license), but the reality is that these model are expensive to develop and many developers are choosing not to release their model weights at all.
I think that releasing the weights openly but with this type of dual-license (hence open weights, but not true open source) is an acceptable tradeoff to get more model developers to release models openly.
diggan · 59m ago
> but the reality is that these model are expensive to develop and many developers are choosing not to release their model weights at all.
But isn't that true for software too? Software is expensive to develop, and lots of developers/companies are choosing not to make their code public for free. Does that mean you also feel like it would be OK to call software "open source" although it doesn't allow usage for any purpose? That would then lead to more "open source" software being released, at least for individuals and researchers?
rushingcreek · 25m ago
Yes, I think the same analogy applies. Given a binary choice of a developer not releasing any code at all or releasing code under this type of binary "open-code" license, I'd always take the latter.
diggan · 13m ago
> Given a binary choice of a developer not releasing any code at all
I mean it wasn't binary earlier, it was "to get more model developers to release", so not a binary choice, but a gradient I suppose. Would you still make the same call for software as you do for ML models and weights?
dheera · 25m ago
> One of Qwen's strengths historically has been their open-weights strategy
> let researchers and individuals get the weights for free and let startups pay for a reasonably-priced license for commercial use
I'm personally doubtful companies can recoup tens of millions of dollars in investment, GPU hours, and engineering salaries from image generation fees.
echelon · 1h ago
The era of open weights from China appears to be over for some reason. It's all of a sudden and seems to be coordinated.
Alibaba just shut off the Qwen releases
Tencent just shut off the Hunyuan releases
Bytedance just released Seedream, but it's closed
It's seems like it's over.
They're still clearly training on Western outputs, though.
I still suspect that the strategic thing to do would be to become 100% open and sell infra/service.
natrys · 1h ago
> Alibaba just shut off the Qwen releases
Alibaba from beginning had some series of models that are always closed-weights (*-max, *-plus, *-turbo etc. but also QvQ), It's not a new development, nor does it prevent their open models. And the VL models are opened after 2-3 months of GA in API.
Why? And can we really say that already? Wasn't the Qwen3 release still very recent?
logicchains · 1h ago
What do you mean Tencent just shut off the Hunyuan releases? There was another open weights release just today: https://huggingface.co/tencent/Hunyuan-A13B-Instruct . And the latest Qwen and DeepSeek open weight releases were under 2 months ago, there hasn't been enough time for them to finish a new version since then.
b0a04gl · 1h ago
image gets compressed into 256 tokens before language model sees it. ask it to add a hat and it redraws the whole face; because objects aren't stored as separate things. there's no persistent bear in memory. it all lives inside one fused latent soup, they're fresh samples under new constraints. every prompt tweak rebalances the whole embedding. that's why even small changes ripple across the image. i notice it like single shot scene synthesis, which is good for diff usecases
leodriesch · 1h ago
That's what I really like about Flux Kontext, it has similar editing capabilities to the multimodal models, but doesn't mess up the details. The editing with gpt-image-1 only really works for complete style changes like "make this ghibli", but not adding glasses to a photorealistic image and have it retain all the details.
hexmiles · 2h ago
While looking at the examples of editing the bear image, I noticed that the model seemed to change more things than were strictly asked.
As an example, when asked to change the background, it also completely changed the bear (it has the same shirt but the fur and face are clearly different), and also: when it turned the bear in a balloon, it changed the background (removing the pavement) and lost the left seed in the watermelon.
It is something that can be fixed with better prompting, or is it a limitation of the model/architecture?
veltas · 58m ago
Rather I think machine learning has made a lot more progress 'depicting' the world than 'understanding' it.
ivape · 35m ago
Why do you think humans understand the world any better? We have emotion about the world but emotions do not grant you understanding, where “understanding” is still something you would still need to define.
“I get it” - is actually just some arbitrary personal benchmark.
skybrian · 2h ago
I tried the obligatory pelican riding a bicycle (as an image, not SVG) and some accordion images. It has a bit of trouble with fingers and wth getting the black keys right. It’s fairly fast.
To my eyes, all these images hit the uncanny valley. All the colors and the shadows are just off.
djaychela · 2h ago
How do you stop the auto reading out? Why can't websites just sit there and wait until I ask for them to do something? It full screen auto played a video on watch and then just started reading?
Firefox on ios ftr
frotaur · 2h ago
Anybody knows if there is a technical report for this, or for other models that generate images in a similar way? I'd really like to understand the architecture behind 4o-like image gen.
aredox · 2h ago
It don't think these words mean what they think they do...
If Qwen is concerned about recouping its development costs, I suggest looking at BFL's Flux Kontext Dev release from the other day as a model: let researchers and individuals get the weights for free and let startups pay for a reasonably-priced license for commercial use.
So it is trained off OAI, as closed off as OAI and most importantly: worse than OAI. What a bizarre strategy to gate-keep this behind an API.
[0]
https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VLo/cas...
https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VLo/cas...
https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VLo/cas...
It's really too close to be anything but a model trained on these outputs, the whole vibe just screams OAI.
Both Alibaba and Tencent championed open source (Qwen family of models, Hunyuan family of models), but now they've shut off the releases.
There's totally a play where models become loss-leader for SaaS/PaaS/IaaS and where they extinguish your closed competition.
Imagine spreading your model so widely then making the terms: "do not use in conjunction with closed source models".
What are you talking about? Feels like a very strong claim considering there are ongoing weight releases, wasn't there one just today or yesterday from a Chinese company?
But if you're suggesting they should do open weights, doesn't that mean people should be able to use it freely?
You're effectively suggesting "trial-weights", "shareware-weights", "academic-weights" or something like that rather than "open weights", which to me would make it seem like you can use them for whatever you want, just like with "open source" software. But if it misses a large part of what makes "open source" open source, like "use it for whatever you want", then it kind of gives the wrong idea.
I think that releasing the weights openly but with this type of dual-license (hence open weights, but not true open source) is an acceptable tradeoff to get more model developers to release models openly.
But isn't that true for software too? Software is expensive to develop, and lots of developers/companies are choosing not to make their code public for free. Does that mean you also feel like it would be OK to call software "open source" although it doesn't allow usage for any purpose? That would then lead to more "open source" software being released, at least for individuals and researchers?
I mean it wasn't binary earlier, it was "to get more model developers to release", so not a binary choice, but a gradient I suppose. Would you still make the same call for software as you do for ML models and weights?
> let researchers and individuals get the weights for free and let startups pay for a reasonably-priced license for commercial use
I'm personally doubtful companies can recoup tens of millions of dollars in investment, GPU hours, and engineering salaries from image generation fees.
Alibaba just shut off the Qwen releases
Tencent just shut off the Hunyuan releases
Bytedance just released Seedream, but it's closed
It's seems like it's over.
They're still clearly training on Western outputs, though.
I still suspect that the strategic thing to do would be to become 100% open and sell infra/service.
Alibaba from beginning had some series of models that are always closed-weights (*-max, *-plus, *-turbo etc. but also QvQ), It's not a new development, nor does it prevent their open models. And the VL models are opened after 2-3 months of GA in API.
> Tencent just shut off the Hunyuan releases
Literally released one today: https://huggingface.co/tencent/Hunyuan-A13B-Instruct
As an example, when asked to change the background, it also completely changed the bear (it has the same shirt but the fur and face are clearly different), and also: when it turned the bear in a balloon, it changed the background (removing the pavement) and lost the left seed in the watermelon.
It is something that can be fixed with better prompting, or is it a limitation of the model/architecture?
“I get it” - is actually just some arbitrary personal benchmark.
https://chat.qwen.ai/s/0f9d558c-2108-4350-98fb-6ee87065d587?...
Firefox on ios ftr
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