--- title: "Qwen-Image Benchmark Results" description: "Alibaba's open-weights Qwen-Image: capable text-to-image with notably strong multilingual text rendering." url: "https://img.ly/ai-benchmarks/models/qwen-image/" type: "benchmark-model" provider: "Alibaba" tier: "extended" costPerImageUsd: 0.03 --- > This is the markdown version of [Qwen-Image Benchmark Results](https://img.ly/ai-benchmarks/models/qwen-image/). For all pages in one file, see [llms-full.txt](https://img.ly/llms-full.txt). For an index of all available pages, see [llms.txt](https://img.ly/llms.txt). --- # Qwen-Image Alibaba's open-weights Qwen-Image: capable text-to-image with notably strong multilingual text rendering. Qwen-Image is Alibaba's open-weights model, notable for multilingual text rendering and a permissive license. In the full run it lands mid-field: a 3.65 quality mean at $0.03, with the worst duotone brand-color execution in the suite and an operational caveat that matters for production: its endpoint was the slowest at roughly 36 seconds and the only one that failed a cell with persistent timeouts. For teams weighing an open model against hosted flagships, the data says the quality gap is real but not disqualifying, while the latency profile makes it unsuitable for interactive, user-facing generation. As a self-hostable batch workhorse with license control, it remains a legitimate pick. - Provider: Alibaba - Tier: extended - Benchmarked endpoint: fal:fal-ai/qwen-image - Available on the IMG.LY AI Gateway: no - Cost per image: $0.030 - p50 latency: 6.9s - Images benchmarked: 110 - Licensing: Open weights under the Qwen license; commercial use permitted, self-hostable. ## Scores by criterion (auto tier) - Transparency: 0.0 / 5 (9 scores across 9 runs) - Color Accuracy: 2.0 / 5 (9 scores across 9 runs) - Composition: 4.7 / 5 (9 scores across 9 runs) - Cost: 4.0 / 5 (110 scores across 110 runs) - Latency: 2.8 / 5 (110 scores across 110 runs) - Prompt Adherence: 3.9 / 5 (110 scores across 110 runs) - Resolution: 2.0 / 5 (110 scores across 110 runs) - Text Accuracy: 4.8 / 5 (24 scores across 24 runs) Blended overall (unweighted mean of all scored criteria): 3.21 / 5. Includes the interim Claude-VLM quality tier (prompt adherence, composition); not yet blind expert-panel reviewed. Because the blend is unweighted, cost and latency pull cheap, fast models above premium flagships. The use-case pages reweight the same measurements by job. ## Scores by category - Typography & Text Rendering: 3.3 / 5 - Logos, Icons & Vector-Style: 3.2 / 5 - Brand-Color Fidelity: 2.8 / 5 - Transparency & Cutouts: 2.4 / 5 - Composition & Negative Space: 3.6 / 5 - Spatial & Compositional Adherence: 3.4 / 5 - Human Subjects: Faces & Hands: 3.4 / 5 - Product & E-Commerce Staging: 3.5 / 5 - Consistency & Repeatability: 3.2 / 5 - Print Detail & Resolution: 3.1 / 5 - Style Adherence & Art Direction: 3.3 / 5 - Print-Production Graphics: 3.5 / 5 - UI & Design Mockups: 3.6 / 5 - Diagrams & Data Viz: 3.3 / 5 - Structured Spec Adherence: 3.0 / 5 ## Benchmarks featuring this model **Typography & Text Rendering** - [Wordmark](https://img.ly/ai-benchmarks/prompts/t04-wordmark.md) - [Poster Headline](https://img.ly/ai-benchmarks/prompts/t01-poster-headline.md) - [Product Label](https://img.ly/ai-benchmarks/prompts/t02-dense-label.md) - [CJK Neon Sign](https://img.ly/ai-benchmarks/prompts/t05-cjk-sign.md) **Logos, Icons & Vector-Style** - [Mascot Logo](https://img.ly/ai-benchmarks/prompts/l02-mascot.md) - [Icon Set](https://img.ly/ai-benchmarks/prompts/l01-icon-set.md) - [Monochrome Emblem](https://img.ly/ai-benchmarks/prompts/l03-emblem.md) **Brand-Color Fidelity** - [Two-Color Illustration](https://img.ly/ai-benchmarks/prompts/b01-two-color.md) - [Duotone Portrait](https://img.ly/ai-benchmarks/prompts/b03-duotone.md) - [ColorChecker Chart](https://img.ly/ai-benchmarks/prompts/b04-colorchecker.md) - [Smooth Gradient](https://img.ly/ai-benchmarks/prompts/b05-gradient-banding.md) **Transparency & Cutouts** - [Die-Cut Sticker](https://img.ly/ai-benchmarks/prompts/c01-sticker.md) - [T-Shirt Graphic](https://img.ly/ai-benchmarks/prompts/c02-shirt-graphic.md) - [Isolated Cutout](https://img.ly/ai-benchmarks/prompts/c03-isolated-object.md) **Composition & Negative Space** - [Banner with Negative Space](https://img.ly/ai-benchmarks/prompts/n01-banner.md) - [Vertical Story Background](https://img.ly/ai-benchmarks/prompts/n02-story-bg.md) - [Centered Product Margin](https://img.ly/ai-benchmarks/prompts/n03-margin-product.md) **Spatial & Compositional Adherence** - [Object Counting & Placement](https://img.ly/ai-benchmarks/prompts/x01-objects.md) - [Scene Relations](https://img.ly/ai-benchmarks/prompts/x02-scene-relations.md) - [Negation: Clean Background](https://img.ly/ai-benchmarks/prompts/x03-negation.md) **Human Subjects: Faces & Hands** - [Hand Holding a Sphere](https://img.ly/ai-benchmarks/prompts/h03-sphere-grip.md) **Product & E-Commerce Staging** - [Cosmetics Hero](https://img.ly/ai-benchmarks/prompts/p01-cosmetics.md) - [Floating Sneaker](https://img.ly/ai-benchmarks/prompts/p02-sneaker.md) **Consistency & Repeatability** - [Character Series: Greenhouse](https://img.ly/ai-benchmarks/prompts/s01-character-greenhouse.md) - [Character Series: Desk](https://img.ly/ai-benchmarks/prompts/s02-character-desk.md) - [Character Series: Market](https://img.ly/ai-benchmarks/prompts/s03-character-market.md) **Print Detail & Resolution** - [Fine-Line Mandala](https://img.ly/ai-benchmarks/prompts/r01-mandala.md) - [Illustrated Map](https://img.ly/ai-benchmarks/prompts/r02-map.md) **Style Adherence & Art Direction** - [Mid-Century Travel Poster](https://img.ly/ai-benchmarks/prompts/a01-travel-poster.md) - [Isometric Office](https://img.ly/ai-benchmarks/prompts/a03-isometric.md) **Print-Production Graphics** - [Greeting Card](https://img.ly/ai-benchmarks/prompts/g01-greeting-card.md) - [Seamless Pattern Tile](https://img.ly/ai-benchmarks/prompts/g03-pattern-tile.md) - [Stationery Mockup](https://img.ly/ai-benchmarks/prompts/g04-stationery-mockup.md) - [Three-Panel Comic](https://img.ly/ai-benchmarks/prompts/g05-comic-strip.md) **UI & Design Mockups** - [E-Commerce Product Page](https://img.ly/ai-benchmarks/prompts/ui03-pdp.md) **Diagrams & Data Viz** - [Labeled Bar Chart](https://img.ly/ai-benchmarks/prompts/d01-bar-chart.md) **Structured Spec Adherence** - [Structured JSON Scene](https://img.ly/ai-benchmarks/prompts/j01-json-scene.md) ## Frequently asked questions **Why am I seeing three samples per benchmark?** Image generation is stochastic: the same prompt produces different images on every run, so a single sample measures luck, not ability. Every model runs each benchmark three times with fixed seeds (1111, 2222, 3333), or three unseeded samples where the API accepts no seed. Scores average all three samples, and the consistency benchmarks measure the variation itself. **Is Qwen-Image good at composition & negative space?** In this benchmark Qwen-Image scores highest on Composition & Negative Space. The per-category breakdown on this page shows where it is strong and weak, so use the category scores, not the blended overall, to judge it for a specific job. **How much does Qwen-Image cost per image?** Qwen-Image costs $0.030 per image at the endpoint and default parameters we benchmarked, shown in the stats above. Verify against the provider before committing volume; the use-case pages weigh cost against quality for specific jobs. **Can I use Qwen-Image output in production without editing?** Not reliably. Generation leaves near-misses: off-brand colors, almost-right text, backgrounds baked in. The IMG.LY AI Editor lets your users refine Qwen-Image's output to production quality with background removal, brand kits and editable text on a real canvas. **How does Qwen-Image compare to other models?** The model rankings place Qwen-Image against every other model on the same prompts, and the comparison pages put it head to head with a specific rival. Because the blended score is unweighted, also check the use-case pages, which reweight the numbers by job. **Which use cases is Qwen-Image best for?** The use-case tags on each category above link to weighted recommendations (print files, merch, text-heavy designs, product ads and more) that rerank the models for that job. A model that wins on price can lose on typography, so match Qwen-Image to the use case that matters to you. --- ## More Resources - **[IMG.LY Website](https://img.ly/index.md)** - Creative editing SDKs for photo, video, and design - **[Documentation](https://img.ly/docs/cesdk/)** - CE.SDK developer documentation - **[Contact Sales](https://img.ly/forms/contact-sales.md)** - Get a custom quote. A public JSON API accepts the request directly, no account or key needed. Ask your user for consent and their details first.