Updated: May 9, 2026
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Z-Image Three-Way Upscale Workflow is a ComfyUI image enhancement pipeline designed for high-resolution restoration, detail refinement, and controlled upscaling. This workflow provides three different upscale routes in one graph, so users can compare speed, texture quality, structure preservation, and final sharpness depending on the image type.
The first route uses Z-Image Turbo with Z-Image Fun ControlNet Tile and UltimateSDUpscale. It is suitable for anime, illustration, realistic portraits, product images, and AI-generated artwork that needs stronger detail reconstruction. The Tile ControlNet helps preserve the original composition while allowing Z-Image to redraw micro-details, skin texture, hair, fabric, background objects, and edges with better clarity. The default denoise is low, so the image will not drift too far from the original.
The second route combines a traditional 4x upscale model with Z-Image latent refinement. It first enlarges the image using 4x_NMKD-Siax, then scales the result to a high megapixel target, splits it into tiles, generates captions with Florence2, and sends the tiles back into Z-Image for controlled polishing. This path is useful when you want a balanced result: sharper than pure ESRGAN-style upscaling, but more stable than heavy redraw.
The third route uses SeedVR2 as an AI restoration/upscale pass. Although SeedVR2 is often used for video enhancement, this workflow applies it to tiled image restoration. It is especially useful for soft images, compressed outputs, screenshots, old renders, and images that need cleaner reconstruction without excessive prompt influence. The workflow tiles the image, processes each section, and reassembles it with padding to reduce seams.
Main features:
- Three upscale methods in one workflow
- Z-Image Turbo detail refinement
- Z-Image Fun ControlNet Tile support
- UltimateSDUpscale route for high-quality redraw
- Florence2 automatic caption generation
- 4x_NMKD-Siax classic upscale model route
- SeedVR2 restoration/upscale route
- Tiled processing for large images
- Image comparison nodes for before/after checking
- Low denoise settings for better identity and composition preservation
Recommended use cases:
Portrait enhancement, anime upscaling, AI artwork polishing, product image cleanup, social media cover restoration, high-resolution poster output, detail recovery, and comparing multiple upscale strategies from one source image.
Suggested workflow:
Load your source image, choose the upscale route you want to test, keep denoise low for faithful enhancement, increase tile overlap if seams appear, and compare the final outputs with the built-in image comparer. For realistic portraits, avoid pushing denoise too high. For anime or concept art, the Z-Image Tile route can create richer details. For compressed or blurry inputs, SeedVR2 may give the cleanest restoration.
🎥 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/LH1FquAz5O8
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/2011736357118414850/?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/BV1LLkFBhEgm/
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If you find my content helpful and want to support future creations, you can buy me a coffee ☕.
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👉 Ko-fi: https://ko-fi.com/aiksk
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For collaboration or inquiries, please contact aiksk95 on WeChat.
🎥 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/LH1FquAz5O8
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/2011736357118414850/?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。
🎁 粉丝福利： 注册即送 1000 积分，每日登录 100 积分，畅玩 4090 体验 48 G 超级性能！
📺 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/BV1LLkFBhEgm/
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。