Qwen-Image-Edit-2511 Multi-Image Editing
AI-KSK YouTube workflow videos near 1,000 views: full Chinese tests, workflow demos, and setup notes.
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https://www.youtube.com/watch?v=7EJqgHv2YaU
AI-KSK YouTube demo (j6EZ2I07fYs): Watch the full workflow video here: https://youtu.be/j6EZ2I07fYs
AI-KSK YouTube demo: https://youtu.be/j6EZ2I07fYs
This workflow is a multi-image edit/composition pipeline for Qwen-Image-Edit-2511. It loads the Qwen CLIP/vision encoder, the 2511 UNet, and the Qwen VAE, then (optionally) applies the Qwen-Image-Edit-2511 Lightning 4-step LoRA to run fast. You provide up to three reference images (image1/2/3) plus a text instruction (e.g. “a group photo of the three people”), and the node TextEncodeQwenImageEditPlus turns “text + images” into the conditioning the model will follow.
From there, the workflow sets the multi-reference latent method to index_timestep_zero, builds an empty latent at the target width/height (derived from the input image size), and runs a KSampler with a Lightning-style fast configuration (the included note recommends 4 steps / CFG 1.0 when Lightning is enabled). The result is decoded through the VAE (regular decode or tiled decode), then saved (with an optional A/B compare node). In practical use, you treat image1 as the strongest anchor (identity/detail you care about most), and image2/3 as supporting references for secondary elements.
🎥 YouTube Video Tutorial
Want to know what this workflow actually does and how to start fast?
This video explains what the tool is, how to launch the workflow instantly, and shares my core design logic — no local setup, no complicated environment.
Everything starts directly on RunningHub, so you can experience it in action first.
👉 YouTube Tutorial: https://youtu.be/8gpnO-0tJj8
Before you begin, I recommend watching the video thoroughly — getting the full context helps you understand the tool faster and avoid common detours.
⚙️ RunningHub Workflow
Try the workflow online right now — no installation required.
👉 Workflow: https://www.runninghub.ai/post/2004187543652499458/?inviteCode=rh-v1111
If the results meet your expectations, you can later deploy it locally for customization.
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📺 Bilibili Updates (Mainland China & Asia-Pacific)
If you’re in the Asia-Pacific region, you can watch the video below to see the workflow demonstration and creative breakdown.
📺 Bilibili Video: https://www.bilibili.com/video/BV1RHBRBgEo7/
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🎥 YouTube 视频教程
想了解这个工作流到底是怎样的工具,以及如何快速启动?
视频主要介绍 工具定位、快速启动方法 和 我的构筑思路。
我们会直接在 RunningHub 上进行演示,让你第一时间看到实际效果。
👉 YouTube 教程: https://youtu.be/8gpnO-0tJj8
开始前建议尽量完整地观看视频 —— 把握整体思路会更快上手,也能少走常见弯路。
⚙️ 在线体验工作流
现在就可以在线体验,无需安装。
👉 工作流: https://www.runninghub.ai/post/2004187543652499458/?inviteCode=rh-v1111
打开上方链接即可直接运行该工作流,实时查看生成效果。
如果觉得效果理想,你也可以在本地进行自定义部署。
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📺 Bilibili 更新(中国大陆及南亚太地区)
如果你在中国大陆或南亚太地区,可以通过下方视频查看该工作流的实测效果与构思讲解。
📺 B站视频: https://www.bilibili.com/video/BV1RHBRBgEo7/
我会在 夸克网盘 持续更新模型资源: 👉 https://pan.quark.cn/s/20c6f6f8d87b 这些资源主要面向本地用户,方便进行创作与学习。