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Those simple prompts produce nearly the exact same layout in the 2 different models?
by cloudking 6d ago
Those simple prompts produce nearly the exact same layout in the 2 different models?
- supermatt 6d agoEqually confused with this. They must be using a lot more guidance than just the provided prompt.
- howdareme 6d agoQwen is trained off of gpt’s outputs. This is both a positive and negative
- orbital-decay 6d agoTotally normal for modern models due to training on the same datasets supplied by third parties, dataset contamination, and mode collapse, especially for simple prompts that don't have enough semantic capacity. -isms are often very similar even without distillation, and tend to come and go in waves along with model generations.
- BoorishBears 6d agoQwen's latest image models have a ton of distillation from gpt-image, same with Grok Imagine. Even the artifacts are getting picked up.
- vunderba 6d agoAgreed. There's also a lot of bad tinging/yellow saturation that very much reminds me of early gpt-image outputs on a lot of the non-cherry picked stuff I've been seeing on Twitter/Reddit. A lot of people were putting ZiT as a refiner downstream in early Qwen-Image 1.0 workflows, so I'm wondering if we're going to see something similar with 2.1.
- jjcm 6d agoMy harness expands the prompt into a json representation that specifies layout much more rigorously, which is why you see such that amount of alignment between the two. That internal json backing helps significantly when you want to maintain consistent design system components/patterns across multiple pages. The aligned layout is it working as intended.