The Qwen image editing model, combined with the latest control model, produces explosive results. According to the official modifications, the specific parameters are the same as the official requirements and do not need any changes, and the workflow also has detailed parameter comparisons. However, a consistent issue with Qianwen is the high VRAM requirement, which is tested to need over 22GB of VRAM. If your local machine doesn't have enough, you can now try it online for free. Additionally, the workflow nodes may be a bit challenging to install, so it's recommended to test online first. If the results are satisfactory, you can download this advanced workflow and the corresponding model. Detailed parameters and tutorials are included in the online link below, so there's no need to worry about local computer specifications being insufficient. By registering through the link at <a target="_blank" rel="ugc" href="https://www.runninghub.ai/post/1959611533254930433/?inviteCode=rh-v1180">https://www.runninghub.ai/post/1959611533254930433/?inviteCode=rh-v1180</a>, you can obtain 1000 RH credits and earn an extra 100 credits daily, allowing you to generate about 200 images. Come and have a try!千问图像编辑模型加上最新出的控制模型，效果好到爆炸，根据官方流修改，具体的参数和官方的要求一样，不用修改即可，或者工作流中也有详细的参数对比。但是千问一惯的问题就是显存要求较大，实测需要22g以上显存，如果本地不够的话，现可免费在线体验，同时工作流节点可能有些难以安装，因此建议先在线测试。如果结果良好，那么下载这个高级工作流和对应的模型。具体的参数和教程也包含在下面的在线链接中 <a target="_blank" rel="ugc" href="https://www.runninghub.ai/post/1959611533254930433/?inviteCode=rh-v1180">https://www.runninghub.ai/post/1959611533254930433/?inviteCode=rh-v1180</a> ，无需担心本地电脑配置不够的问题 ，通过  ，并通过上方链接注册，可获得 1000 rh 积分，每天额外获得 100 积分，可生成约 200 张图片。快来试一试吧！

qwen series_image_edit+control千问图像转绘控制

cfg:2.5,step:20 <a target="_blank" rel="ugc" href="https://www.runninghub.ai/post/1959611533254930433/?inviteCode=rh-v1180">https://www.runninghub.ai/post/1959611533254930433/?inviteCode=rh-v1180</a>,

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