{"id":2325,"date":"2026-09-20T22:16:21","date_gmt":"2026-09-20T13:16:21","guid":{"rendered":"https:\/\/localmodelwatch.tsuchitsuchi.com\/2026\/09\/20\/qwen-image-2-1-released\/"},"modified":"2026-10-05T00:11:26","modified_gmt":"2026-10-04T15:11:26","slug":"qwen-image-2-1-released","status":"publish","type":"post","link":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/20\/qwen-image-2-1-released\/","title":{"rendered":"Qwen-Image-2.1 Released: Open-Weight Image Gen &#038; Editing"},"content":{"rendered":"<p><em>Sample outputs are available on the <a href=\"https:\/\/huggingface.co\/Qwen\/Qwen-Image-2.1-PE-T2I\">model card<\/a>.<\/em><\/p>\n<p><!-- lmw:facts --><\/p>\n<h2>At a Glance<\/h2>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Item<\/th>\n<th>Value<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Repository<\/td>\n<td><a href=\"https:\/\/huggingface.co\/Qwen\/Qwen-Image-2.1-PE-I2I\">Qwen\/Qwen-Image-2.1-PE-I2I<\/a><\/td>\n<\/tr>\n<tr>\n<td>Family guide<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/model-qwen-qwen-image-2-1-en\/\">Qwen-Image-2.1 guide (3 articles)<\/a><\/td>\n<\/tr>\n<tr>\n<td>Publisher guide<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/publisher-alibaba-en\/\">Alibaba (Qwen): models and licenses<\/a><\/td>\n<\/tr>\n<tr>\n<td>Published<\/td>\n<td>2026-09-20<\/td>\n<\/tr>\n<tr>\n<td>License<\/td>\n<td>qwen-research<\/td>\n<\/tr>\n<tr>\n<td>Formats<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/format-safetensors-en\/\">safetensors<\/a><\/td>\n<\/tr>\n<tr>\n<td>Source type<\/td>\n<td>Primary source (the publisher itself)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p><em>Values determined by this site&#8217;s code when the information was collected. Dates are JST.<\/em><\/p>\n<p><!-- \/lmw:facts --><\/p>\n<h2>Overview<\/h2>\n<p>The Qwen team has released &#8220;Qwen-Image-2.1,&#8221; a new open-weight model that integrates text-to-image generation and image editing. This model combines a Text-to-Image function for generating high-quality images from text and an Image-Editing function for editing existing images according to instructions into a single model.<\/p>\n<p>Along with this, dedicated prompt rewriting models\u2014&#8221;Qwen-Image-2.1-PE-T2I&#8221; and &#8220;Qwen-Image-2.1-PE-I2I&#8221;\u2014have also been released as open source to rewrite short instructions and vague requests from users into detailed prompts that image generation and editing models can easily understand. These are fine-tuned models based on Qwen3.5-VL 9B, responsible for expanding short requests entered in any language into detailed English prompts and outputting them in JSON format along with recommendation information such as the optimal aspect ratio.<\/p>\n<h2>Specifications<\/h2>\n<p>The main specifications of the released model group and the base &#8220;Qwen-Image-2.1&#8221; are as follows.<\/p>\n<h3>Qwen-Image-2.1 (Image Generation and Editing Model)<\/h3>\n<ul>\n<li><strong>Number of Parameters<\/strong>: 7B parameters in the visual generation component<\/li>\n<li><strong>Architecture<\/strong>: 32-layer single-stream DiT (Diffusion Transformer)<\/li>\n<li><strong>Key Features<\/strong>:<\/li>\n<li><strong>Native Transparency (RGBA Support)<\/strong>: In addition to standard text-to-image generation, it can handle generating RGBA images with transparent backgrounds, editing transparent layers, and extracting subjects from photos (background removal) with a single model. &#8211; <strong>Advanced Image Editing<\/strong>: Supports up to 10 reference images. It supports local editing (partial editing) specifications using circles, painted annotations, or individual masks, enabling editing while preserving the identity (features) of people or products. &#8211; <strong>Efficiency Technologies<\/strong>: Achieves high image quality at low computational cost through a lightweight architecture adopting mixed-granularity attention and prefix KV cache reuse.<\/li>\n<\/ul>\n<h3>Qwen-Image-2.1-PE-T2I (Prompt Rewriting Model for Text Generation)<\/h3>\n<ul>\n<li><strong>Base Architecture<\/strong>: Qwen3.5-VL 9B (fine-tuned version)<\/li>\n<li><strong>Input<\/strong>: Short image generation requests in any language<\/li>\n<li><strong>Output<\/strong>: Outputs the following JSON format after the reasoning process via `&#8221;)<br \/>\nresult = json.loads(answer.strip())<\/li>\n<\/ul>\n<h1>Output example: {&#8220;rewritten_prompt&#8221;: &#8220;&#8230;&#8221;, &#8220;wh_ratio&#8221;: &#8220;&#8221;, &#8220;ratio_follow&#8221;: &#8220;<image1>&#8220;}<\/h1>\n<p>&#8220;`<\/p>\n<p><code>ratio_follow<\/code> included in this output indicates inheriting the aspect ratio of the editing source image as-is (performing in-place editing). By passing the obtained <code>rewritten_prompt<\/code> along with the original image <code>input_image<\/code> to <code>QwenImage21Pipeline<\/code>, an image with the specified edits applied is output.<\/p>\n<p>In addition, when inputting multiple images, you can place multiple image objects within the list of messages and specify <code>&lt;image1&gt;<\/code> or <code>&lt;image2&gt;<\/code> in the text instructions to have the PE model interpret complex instructions targeting specific images (e.g., &#8220;place the subject of <code>&lt;image1&gt;<\/code> into the background of <code>&lt;image2&gt;<\/code>&#8220;).<\/p>\n<p><!-- lmw:runnability --><\/p>\n<h2>Can You Run It Locally?<\/h2>\n<p>The publisher distributes this model as safetensors.<\/p>\n<p><strong>License \u2014 <code>qwen-research<\/code> (Commercial use prohibited):<\/strong> Alibaba&#8217;s Qwen Research License. <strong>Limited to research and evaluation<\/strong>; commercial use requires a separate license (Sections 1.i and 2.b).<\/p>\n<p><em>Compiled by this site&#8217;s code from the published formats and the license field. License summaries are not legal advice \u2014 check the publisher&#8217;s original terms before relying on them.<\/em><\/p>\n<p><!-- \/lmw:runnability --><\/p>\n<p><!-- lmw:lab --><\/p>\n<h2>Our Own Measurements<\/h2>\n<h3>Measurements We Did Not Take<\/h3>\n<p>This model&#8217;s license (<code>qwen-research<\/code>) does not permit commercial use. Because this site carries advertising, we did not run the model (no CPU run, answers, quantization comparison, conversion or generation).<\/p>\n<p><!-- \/lmw:lab --><\/p>\n<p><!-- lmw:related --><\/p>\n<h2>Related Articles<\/h2>\n<ul>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/10\/05\/qwen-3-8-flash-next-released\/\">Qwen3.8-Flash-Next Multimodal MoE Model: ~402GB Memory<\/a><\/li>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/26\/qwen3-8-27b-overview-specs-performance\/\">Qwen3.8-27B Vision-Language Model: Our Test Answers, 8GB+ VRAM<\/a><\/li>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/30\/qi-2-1-anyangle-camera-control-lora\/\">QI_2.1_AnyAngle Camera Angle Control LoRA: 48GB+ VRAM, File List<\/a><\/li>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/21\/hacker-news-discussion-on-qwen-image-21\/\">Hacker News Discussion on Open-Weight Qwen-Image-2.1<\/a><\/li>\n<\/ul>\n<p><!-- \/lmw:related --><\/p>\n<p><!-- lmw:files --><\/p>\n<h2>Distributed Files<\/h2>\n<p><em>Weight files published in <a href=\"https:\/\/huggingface.co\/Qwen\/Qwen-Image-2.1-PE-I2I\/tree\/main\">Qwen\/Qwen-Image-2.1-PE-I2I<\/a>, listed by this site from the Hugging Face API. Sizes are the actual file sizes.<\/em><\/p>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>File<\/th>\n<th>Size<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><code>model-00001.safetensors<\/code><\/td>\n<td>5.07GB<\/td>\n<\/tr>\n<tr>\n<td><code>model-00002.safetensors<\/code><\/td>\n<td>5.09GB<\/td>\n<\/tr>\n<tr>\n<td><code>model-00003.safetensors<\/code><\/td>\n<td>5.09GB<\/td>\n<\/tr>\n<tr>\n<td><code>model-00004.safetensors<\/code><\/td>\n<td>3.57GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p><!-- \/lmw:files --><\/p>\n<p><!-- lmw:next-steps --><\/p>\n<h2>What to Read Next<\/h2>\n<ul>\n<li><strong>Explore the same model family<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/model-qwen-qwen-image-2-1-en\/\">Qwen-Image-2.1 family overview (3 articles)<\/a><\/li>\n<li><strong>Formats this model is available in<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/format-safetensors-en\/\">Safetensors format guide and models<\/a><\/li>\n<li><strong>Learn about the publisher<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/publisher-alibaba-en\/\">Alibaba (Qwen): models, licenses and articles<\/a><\/li>\n<li><strong>Other models for the same task<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/models-by-task-en\/#task-image\">Other image generation models<\/a><\/li>\n<\/ul>\n<p><!-- \/lmw:next-steps --><\/p>\n<h2>Sources<\/h2>\n<ul>\n<li><a href=\"https:\/\/huggingface.co\/Qwen\/Qwen-Image-2.1-PE-T2I\">Qwen\/Qwen-Image-2.1-PE-T2I<\/a><\/li>\n<li><a href=\"https:\/\/huggingface.co\/Qwen\/Qwen-Image-2.1-PE-I2I\">Qwen\/Qwen-Image-2.1-PE-I2I<\/a><\/li>\n<\/ul>\n<p><!-- lmw:updates --><\/p>\n<h2>Update History<\/h2>\n<ul>\n<li>2026-09-24: Rebuilt the article: Added a &#8220;can you run it locally?&#8221; verdict from the distribution formats, converted builds, engine registries, license terms and measured compression<\/li>\n<\/ul>\n<p><!-- \/lmw:updates --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Explore Qwen-Image-2.1, an open-weight model integrating text-to-image and image editing, with dedicated prompt rewriting models.<\/p>\n","protected":false},"author":1,"featured_media":2324,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[203],"tags":[1833,520,1835,1837,1547,377,753,1839],"class_list":["post-2325","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-image-video-and-audio","tag-dit-en","tag-qwen-en","tag-qwen-image-2-1-en","tag-qwen-image-2-1-pe-t2i-en","tag-verified","tag--en"],"lang":"en","translations":{"en":2325,"ja":2323},"_links":{"self":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts\/2325","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/comments?post=2325"}],"version-history":[{"count":20,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts\/2325\/revisions"}],"predecessor-version":[{"id":9805,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts\/2325\/revisions\/9805"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/media\/2324"}],"wp:attachment":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/media?parent=2325"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/categories?post=2325"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/tags?post=2325"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}