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221 points lnyan | 2 comments | | HN request time: 0s | source
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rushingcreek ◴[] No.44397235[source]
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.

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Jackson__ ◴[] No.44397843[source]
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.

[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...

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vachina ◴[] No.44398084[source]
Huh, so orange tint = openAI output? Maybe their training process ended up causing the model to prefer that color balance.
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1. Jackson__ ◴[] No.44398560[source]
Here's an extreme example that shows how it continually adds more orange: https://old.reddit.com/r/ChatGPT/comments/1kawcng/i_went_wit...

It's really too close to be anything but a model trained on these outputs, the whole vibe just screams OAI.

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2. acheong08 ◴[] No.44399782[source]
That form of collapse might just be inherent to the methodology. Releasing the weights would be nice so people can figure out why