Qwen Image 2.0 Pro scores 80 on our photo-anchored scale (95% interval 69–94), where a real photograph is 100. In blind pairwise tests on 48 commercial scenes it was clearly ahead of Qwen Image 2.0, the non-Pro version, and clearly behind GPT Image 2. Its largest lead over Qwen Image 2.0 came on people scenes and on-image typography.
A real photograph is pinned at 100, and every model sits by how often it won blind comparisons — the further left, the less often. Scroll sideways to see the rest of the ruler.
Prompt used:Two young women working together at a home-office desk. The one on the left, in a light blue pinstripe shirt with her dark hair tied back, leans in and points with her index finger at a large silver all-in-one monitor; the screen shows a photo-editing application with dark grey panels, a colour picker and a warm candlelit still-life open in the canvas. The second woman, seen from behind over her shoulder in the right foreground, out of focus, holds a stylus over a graphics tablet. On the wooden desktop: a wide black keyboard, a mouse, a camera body, a lens cap, potted plants on the windowsill, an angled desk lamp glowing warm, a window with white venetian blinds behind them.
A real generational step: the Pro version sits between its own predecessor and GPT Image 2, exactly where the ladder bracketed it. I would move everyday Qwen work to it, especially people and layouts with text, and still finish the most demanding hero asset a rung higher.
Strengths
Clearly ahead of Qwen Image 2.0 on believability
Widest lead over Qwen Image 2.0 on people scenes and typography
Honoured the requested size and seed on every generation
Weaknesses
Clearly behind GPT Image 2
Wide score interval, 69 to 94
Lowest category scores on typography and people scenes
Prices are for one 1024×1024 image at standard settings, checked 25 September 2026; the price at the top of the page is the average of the providers listed. Workroom pricing is on the pricing page.
Qwen Image 2.0 Pro is Alibaba's model, available through the Alibaba Cloud Model Studio API. Terms for generated images are set by the service you generate them in.
Frequently asked questions
Yes, clearly. On believability the gap is +0.45 with a 95% interval from +0.21 to +0.72, which excludes zero. The Pro version won 47% of believability judgements against Qwen Image 2.0, which won 24.8%; the rest were ties. The lead was widest on people scenes and on-image typography.
Clearly behind. The believability gap is 0.64 in GPT Image 2's favour, with a 95% interval from 0.42 to 0.86. On believability GPT Image 2 won 50.6% of judgements against the Pro version, which won 19.7%; the rest were ties. On the scale that is 104.4 against 80.
The Pro version was placed on an absolute scale, which is a harder measurement than comparing two models head to head. Its interval, 69 to 94, still sits between the two rungs it was paired with: Qwen Image 2.0 at 64.5 and GPT Image 2 at 104.4. The head-to-head gaps to both rungs are clear.
Both are true. The gain is measured against Qwen Image 2.0, which was weakest on exactly those categories, so the Pro version closed the widest gap there. The category score is measured against the real photograph, and typography and people scenes remain the hardest categories for every model on the ladder.
It got the same 48 commercial scenes and prompts as the ladder, three generations per scene, and every generation was paired blind with Qwen Image 2.0 and GPT Image 2. Each pair was judged three times on three questions. The score uses believability only, because prompts were written from the reference photographs.
No. Workroom is an AI router that gives access to third-party models, including Qwen Image 2.0 Pro, and is not affiliated with Alibaba. The judgement-level data behind this card is published by Everypixel research under CC BY 4.0, so every number on this page can be checked against the source dataset.
About Workroom
Workroom is an AI router: we give access to third-party models, including Qwen Image 2.0 Pro, and we are not affiliated with Alibaba. We have no stake in any single vendor winning; the router is only useful if it sends each brief to the right model. The judgement-level data behind this card is published by Everypixel research under CC BY 4.0 and linked below, so every number here can be checked independently.
How we tested
Between 11 and 22 September 2026 Qwen Image 2.0 Pro was placed on our quality ladder. It got the same 48 commercial scenes and prompts as the ladder, three generations per scene, and each generation was paired blind with two fixed rungs, Qwen Image 2.0 and GPT Image 2: 288 pairs and 863 judgements. Each pair was judged three times on three questions: which image follows the prompt better, which is more believable as a real photograph, and which is more attractive.
How the scale is built
Pairwise comparisons are fitted with a Bradley–Terry model; intervals come from bootstrapping over scenes. The rungs of the scale are frozen from the baseline study, so every new model lands on the same scale. The score uses believability only:
score = 100 + (strength − strength_reference) / a
model strength fitted against frozen anchor strengths from the v3 baseline; the calibration line is pinned at the photograph = 100 Category positions are fitted the same way on the 6 scenes of each category, with a real photograph pinned at 100 on every one of them.
The scale reproduced
The frozen gap between the two rungs was 0.83; this session measured 1.09 with a 95% interval of 0.78 to 1.39. The frozen value falls inside that interval.
Direct blind tests
The pairs Qwen Image 2.0 Pro was judged against directly — where its place on the scale comes from.
Data: CC BY 4.0. Images: All rights reserved; provided for verification only.
Read these before reusing the data
Prompt adherence is biased against photography. Prompts were written by describing the reference photographs, so a model executing text literally scores better than a photograph containing incidental detail. The absolute score is therefore built on believability alone.
Tie share keeps rising: 25.4% in the original ladder study, 28.4% for Seedream 4.0, 34.1% here. Part of this is expected — Qwen Image 2.0 Pro sits between the two anchors, so more pairs are genuinely close. But the interface also changed between the first study and the later ones, so the two causes cannot be separated from these data alone.
Rater agreement is low by the usual yardstick. Conclusions hold at the level of the whole corpus, not for a single scene.
<blockquote cite="https://workroom.everypixel.com/models/qwen-image-2-0-pro">
<p>Qwen Image 2.0 Pro scores 80 on our photo-anchored scale (95% interval 69–94), where a real photograph is 100.</p>
<footer>— <a href="https://workroom.everypixel.com/models/qwen-image-2-0-pro">Qwen Image 2.0 Pro benchmark: blind pairwise test</a>, Everypixel Workroom, September 2026</footer>
</blockquote>