Qwen-Image 3.0 vs GPT‑Image 2: Side‑by‑Side Test Across Six Design Scenarios
The author evaluates Qwen-Image 3.0 against GPT‑Image 2 by generating images for six typical design tasks—data‑visualization dashboard, TikTok live screen, app UI, poster, badge icons, and portfolio website—and finds that Qwen‑Image 3.0 generally matches Chinese aesthetic preferences better, though it still trails GPT‑Image 2 in some areas and may improve with further iterations.
Introduction
The author, after a long wait, tests the newly released Qwen‑Image 3.0 and asks whether it can challenge the dominance of GPT‑Image 2. Six representative design prompts are used to compare the two models.
1. Data‑Visualization Dashboard
The test begins by selecting the Qwen‑Image 3.0 option (the default is 2.0) and prompting the model to create a data‑visualization dashboard.
The resulting image aligns well with typical Chinese visual preferences.
For comparison, the same prompt is run on GPT‑Image 2, producing a denser, more cluttered layout.
The author notes that Qwen‑Image 3.0’s output feels significantly cleaner.
2. TikTok Live Interface
Prompt: Create a TikTok live‑stream screenshot.
The image generated by Qwen‑Image 3.0 resembles a realistic TikTok screen, whereas the GPT‑Image 2 result looks less authentic.
3. App UI Design
Prompt: Design a food‑delivery app home page UI.
The author initially praises the Qwen output for its style but then remarks that it looks overly “Taobao‑like” and overly orange, suggesting the aesthetic feels generic.
4. Poster Design
When asked to create a poster, GPT‑Image 2 produces a more visually appealing result, while Qwen‑Image 3.0’s output is described as monotonous, with small, hard‑to‑read fonts and lacking clear visual benefits.
5. Badge Icon Set
Prompt: Design a set of six animal badge icons.
The generated icons are shown below.
6. Portfolio Website Homepage
Prompt: Create a portfolio website homepage design.
The Qwen‑Image 3.0 result is displayed below.
Conclusion
The author concludes that Qwen‑Image 3.0 still has a gap to fully catch up with GPT‑Image 2, but it performs well on data‑visualization dashboards and shows promise in other scenarios. With more iterative refinements, the quality could improve further. For low‑budget projects, the author suggests using Qwen‑Image 3.0 via the free Qwen Studio platform.
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