Qwen-Image-3.0 gets put through layout-heavy tests against GPT-Image-2
Scobleizer · x · 2026-07-23
Qwen-Image-3.0 is being benchmarked against GPT-Image-2 on dense-layout tasks
A repost from Scobleizer compares Qwen-Image-3.0 with GPT-Image-2 on image-generation tasks that stress “useful” outputs rather than just pretty ones.
The test suite is based on Alibaba Qwen’s own claims for the model: rich multi-element layouts, legible text, and practical use cases such as newspaper PDFs, storyboards, exam papers, and product layouts.
Tasks tested
- Retail promo flyer with logo, offers, and price cards
- One-page fine-dining menu with photos
- Dark data-dashboard infographic
- Broadsheet newspaper-style column
- High-fashion magazine cover with pull-quote and credits
Early results mentioned in the thread
- Flyer: GPT won, 59s vs 2m02s
- Menu: GPT won, 1m05s vs 3m11s
- Infographic: GPT, but close, 1m08s vs 2m49s
The quoted Alibaba Qwen post says Qwen-Image-3.0 is a third-generation foundational image model built around one goal: “Real” — richer content, authentic details, and deeper knowledge, including support for 4.5k-token prompts, 10px-readable text, 12 languages, and realistic UI rendering.
Related event: Qwen-Image-3.0 Tested: Focus on Practical Generation and Typography(3 posts)→
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