Qwen-Image: Crafting with Native Text Rendering

Qwen-Image: Crafting with Native Text Rendering | Qwen

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Qwen-Image: Crafting with Native Text Rendering August 4, 2025 · 6 min · 1229 words · Qwen Team | Translations: 简体中文

GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD We are thrilled to release Qwen-Image , a 20B MMDiT image foundation model that achieves significant advances in complex text rendering and precise image editing. To try the latest model, feel free to visit Qwen Chat and choose “Image Generation”. The key features include: Superior Text Rendering : Qwen-Image excels at complex text rendering, including multi-line layouts, paragraph-level semantics, and fine-grained details. It supports both alphabetic languages (e.g., English) and logographic languages (e.g., Chinese) with high fidelity. Consistent Image Editing : Through our enhanced multi-task training paradigm, Qwen-Image achieves exceptional performance in preserving both semantic meaning and visual realism during editing operations. Strong Cross-Benchmark Performance : Evaluated on multiple public benchmarks, Qwen-Image consistently outperforms existing models across diverse generation and editing tasks, establishing a strong foundation model for image generation.

Performance # We present a comprehensive evaluation of Qwen-Image across multiple public benchmarks, including GenEval, DPG, and OneIG-Bench for general image generation, as well as GEdit, ImgEdit, and GSO for image editing. Qwen-Image achieves state-of-the-art performance on all benchmarks, demonstrating its strong capabilities in both image generation and editing. Furthermore, results on LongText-Bench, ChineseWord, and TextCraft show that it excels in text rendering—particularly in Chinese text generation—outperforming existing state-of-the-art models by a significant margin. This highlights Qwen-Image’s unique position as a leading image generation model that combines broad general capability with exceptional text rendering precision. Demo # One of Qwen-Image’s outstanding capabilities is its ability to achieve high-fidelity text rendering in different scenarios. Let’s take a look at the following Chinese rendering case: 宫崎骏的动漫风格。平视角拍摄，阳光下的古街热闹非凡。一个穿着青衫、手里拿着写着“阿里云”卡片的逍遥派弟子站在中间。旁边两个小孩惊讶的看着他。左边有一家店铺挂着“云存储”的牌子，里面摆放着发光的服务器机箱，门口两个侍卫守护者。右边有两家店铺，其中一家挂着“云计算”的牌子，一个穿着旗袍的美丽女子正看着里面闪闪发光的电脑屏幕；另一家店铺挂着“云模型”的牌子，门口放着一个大酒缸，上面写着“千问”，一位老板娘正在往里面倒发光的代码溶液。

The model not only accurately captures Miyazaki’s anime style, but also features shop signs like “云存储” “云计算” and “云模型” as well as the “千问” on the wine jars, all rendered realistically and accurately with the depth of field. The poses and expressions of the characters are also perfectly preserved. Let’s look at another example of Chinese rendering: 一副典雅庄重的对联悬挂于厅堂之中，房间是个安静古典的中式布置，桌子上放着一些青花瓷，对联上左书“义本生知人机同道善思新”，右书“通云赋智乾坤启数高志远”， 横批“智启通义”，字体飘逸，中间挂在一着一副中国风的画作，内容是岳阳楼。

The model accurately drew the left and right couplets and the horizontal scroll, applied calligraphy effects, and accurately generated the Yueyang Tower in the middle. The blue and white porcelain on the table also looked very realistic. So, how does the model perform on English? Let’s look at an English rendering example: Bookstore window display. A sign displays “New Arrivals This Week”. Below, a shelf tag with the text “Best-Selling Novels Here”. To the side, a colorful poster advertises “Author Meet And Greet on Saturday” with a central portrait of the author. There are four books on the bookshelf, namely “The light between worlds” “When stars are scattered” “The slient patient” “The night circus”

In this example, the model not only accurately outputs “New Arrivals This Week”, but also accurately generates the cover text of four books: “The light between worlds”, “When stars are scattered”, “The slient patient”, and “The night circus”. Let’s look at a more complex case of English rendering: A slide featuring artistic, decorative shapes framing neatly arranged textual information styled as an elegant infographic. At the very center, the title “Habits for Emotional Wellbeing” appears clearly, surrounded by a symmetrical floral pattern. On the left upper section, “Practice Mindfulness” appears next to a minimalist lotus flower icon, with the short sentence, “Be present, observe without judging, accept without resisting”. Next, moving downward, “Cultivate Gratitude” is written near an open hand illustration, along with the line, “Appreciate simple joys and acknowledge positivity daily”. Further down, towards bottom-left, “Stay Connected” accompanied by a minimalistic chat bubble icon reads “Build and maintain meaningful relationships to sustain emotional energy”. At bottom right corner, “Prioritize Sleep” is depicted next to a crescent moon illustration, accompanied by the text “Quality sleep benefits both body and mind”. Moving upward along the right side, “Regular Physical Activity” is near a jogging runner icon, stating: “Exercise boosts mood and relieves anxiety”. Finally, at the top right side, appears “Continuous Learning” paired with a book icon, stating “Engage in new skill and knowledge for growth”. The slide layout beautifully balances clarity and artistry, guiding the viewers naturally along each text segment.

In this case, the model needs to generate 6 submodules, each with its own icon, title, and corresponding introductory text. Qwen-Image has completed the layout. What about smaller text? Let us test it: A man in a suit is standing in front of the window, looking at the bright moon outside the window. The man is holding a yellowed paper with handwritten words on it: “A lantern moon climbs through the silver night, Unfurling quiet dreams across the sky, Each star a whispered promise wrapped in light, That dawn will bloom, though darkness wanders by.” There is a cute cat on the windowsill.

In this case, the paper is less than one-tenth of the entire image, and the paragraph of text is relatively long, but the model still…