(qwenlm.github.io)

221 points lnyan | 1 comments | 27 Jun 25 14:35 UTC | HN request time: 0s | source

Show context

rushingcreek ◴[27 Jun 25 14:51 UTC] 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.

replies(4): >>44397843 #>>44397858 #>>44397893 #>>44398602 #

Jackson__ ◴[27 Jun 25 16:01 UTC] No.44397843[source]▶

>>44397235 #

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...

replies(5): >>44397961 #>>44398084 #>>44398731 #>>44401456 #>>44418786 #

1. roenxi ◴[28 Jun 25 00:21 UTC] No.44401456[source]▶

>>44397843 #

There seem to be a lot of AI images on the web these days and it might have become the single most dominant style given that AI has created more images than any individual human artist. So they might have trained on them implicitly rather than in a synthetic way.

Although theory is not practice. If I were an AI company I'd try to leverage other AI company APIs.

↑

Qwen VLo: From “Understanding” the World to “Depicting” It