Sync 5 new model versions from Civitai (Batch 14/21)

Z-Image-Batch_Restyling__Zip_Archiving/ZImageTurbo/zImageBatchRestyling_v10.zip

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Z-Image-ControlNet__SDPOSE__second-order_Refiner/ZImageTurbo/zImageControlnetSDPOSE_v10.zip

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Z-Image-ControlNet_second-order_Refiner__Pose_Depth_Line/ZImageTurbo/zImageControlnetSecondOrder_v10.zip

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Z-Image_Turbo_-_T2I_Workflow__Detailer__Upscaler__Color_Grading/ZImageTurbo/zImageTurboT2IWorkflow_v20.zip

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Z-Image_Turbo_UltraReal_workflow/ZImageTurbo/zImageTurboUltrareal_v10ZImageTurbo.zip

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ZImageTurbo_info.md

@@ -3659,4 +3659,466 @@ Have fun and feel free to post your generated images in the gallery below! I wou
 *   **Size**: 3.00 MB
 *   **Hash (AutoV2)**: `E265083616`
 *   **Hash (SHA256)**: `E265083616CB17413E515886CE0EAC4BDC259C51236F9D865E55EFE7238BE004`
+---
+
+---
+# Z-Image Turbo - T2I Workflow + Detailer + Upscaler + Color Grading (Version: v2.0)
+**Creator**: [MrSmith2025](https://civitai.com/user/MrSmith2025)
+**Type**: Workflows
+**Base Model**: ZImageTurbo
+**Version Uploaded**: 2025-12-01
+**Trigger Words**: `N/A`
+**Civitai Model ID**: 2174733
+**Civitai Version ID**: 2456846
+**Stats (at time of fetch for this version)**:
+*   Downloads: 459
+*   Rating: 0.0 (0 ratings)
+*   Favorites: N/A
+---
+## Description (Parent Model)
+⚡
+Z-Image Turbo Workflow
+⚡
+Compact TXT-2-IMG WF + Detailer + Upscaler + Lora Loader & Color Grading
+Z-Image Turbo is a fast, distilled, powerful and highly efficient image generation model with
+6B
+parameters. The strength of this model lies in its ability to generate photorealistic images. But even though the model follows prompts very well, the output still isn’t premium in terms of quality. We still need an upscaling process here to make the images presentable. This is where this workflow comes in, including the ADetailer and Ultimate SD Upscaler.
+🚀
+What do you need to get started right away?
+This Workflow - just
+download
+it, unzip the file and load the *.json into ComfyUI
+Z-Image Model:
+z_image_turbo_bf16.safetensors
+(place in
+\models\diffusion_models\
+)
+Text encoder file:
+qwen_3_4b.safetensors
+(place in
+\models\text_encoders\
+)
+The VAE file:
+ae.safetensors
+(place in
+\models\vae\
+)
+Face Detector:
+face_yolov8m.pt
+(place in
+\models\ultralytics\bbox\
+)
+Eyes Detector:
+Eyeful_v2-Paired.pt
+(place in
+\models\ultralytics\bbox\
+)
+Various
+upscale models
+of your choice (place in
+\models\upscale_models\
+)
+Regarding the upscale model I recommend
+4x_NMKD-Siax_200k.pth
+or
+4x_UltraSharp.pth
+. These deliver the best results. But feel free to try out different upscale models. You can find a good selection
+here
+.
+If you used FLUX before then you already have the ae.safetensors file and dont need to download it again.
+You can also use the
+fp8 checkpoint
+if you run a gpu with 8gb of vram. I see no reason to use GGUF models here as the BF16 and FP8 models are already small enough for every kind of GPU.
+🚨
+Make sure that you use the latest stable ComfyUI Core version. Also don't forget to update the ComfyUI Frontend package and your Custom Nodes. Otherwise compatibility problems may occur and the workflow is not working properly.
+The v3 version was made with the following versions:
+ComfyUI Core v0.3.75
+ComfyUI Frontend v1.34.2
+ComfyUI Manager v3.37.2
+Python Version 3.12.10
+PyTorch Version 2.8.0+cu128
+All latest versions of the custom nodes listed below
+Please ensure that you are also using at least these versions. Otherwise, I cannot provide support if something is not working for you.
+❓
+Do I need some special nodes to run this workflow?
+The nodes inside the workflow are common nodes that should or could be already installed on your ComfyUI. If ComfyUI still indicates a missing node just install it via ComfyUI Manager and restart briefly.
+Custom nodes used in this workflow:
+rgthree-comfy
+ComfyUI-Impact-Pack
+ComfyUI-Easy-Use
+ComfyUI_UltimateSDUpscale
+ComfyUI-Art-Venture
+ComfyUI-Impact-Subpack
+ControlAltAI_Nodes
+Save Image with Generation Metadata
+VRGameDevGirl Video Enhancement Nodes
+🛠️
+Why the Text Encoder (Positive Prompt) is connected to negative and positive on the KSampler Node?
+If the CFG value is set to 1.0 the negative prompt is ignored. This is one of the reasons why the model is so fast. This is intentional and not a mistake. Other workflows are ignoring this fact and offer a negative input node. But you dont need a negative prompt here. Simply enter your positive prompt and you're good to go!
+💡
+Usage Tips:
+Simply set the desired resolution on the left, select your preferred upscaler on the far right, put in your prompt and start generating.
+For prompting, it's recommended to use natural language in complete sentences. Describe the person or people, the setting, the camera angle, and the lighting. The more detailed you are, the more accurate the result. 100-300 words works best.
+If you only want to generate raw images for testing purposes, simply toggle off the upscaling and detailer groups using the first node on the top-left. This is also recommended for color grading. Don't forget to fix the seed for that.
+Feel free to experiment with the denoise values ​​in the detailer und upscale nodes to get the perfect result. Also try out different upscale models.
+You don't need to go higher than 9 steps with this model. It is a 8 Steps Model. It will not generate better images if you go higher. Just leave it on 8 or max 9 steps.
+I like to have the option to directly select the aspect ratio (e.g. 5:7 or 9:16) in the node. If you prefer to enter the resolution manually simply disconnect or delete the "Base Resolution Node". Afterwards you can enter your desired resolution in the "latent image" node.
+✅
+v2 Changelog:
+In comparison to my other results with SDXL I wasn't entirely satisfied. Therefore, I revised and optimized the v1 workflow. I have made the following changes to v2:
+✨
+Added Toggle On/Off Node for Upscaling Group
+Toggling the entire upscaler group just to generate RAW images was cumbersome. Now, a single on/off switch at the start lets you enable or disable the upscaler with just one click – quick and easy.
+✨
+Added Lora Loader Node
+With more Lora's being released for Z-Image Turbo these days, this node lets you load and configure multiple Loras at once. Making experimentation faster and easier.
+✨
+Added Clear VRAM and Clear Cache Node
+Placed between the Base Image Generation and Upscaler sections, these nodes improve memory management. Especially on GPUs with limited VRAM and slightly speed up the workflow.
+✨
+Added Seed Generator Node
+The new Seed Generator node is connected to the KSampler and also to the Upscaler node. This means that the Upscaler receives the same seed. I feel this leads to better results.
+✨
+Added fast sharpen / unsharpen node
+This node allows you to adjust the sharpness slightly after upscaling. Feel free to experiment with the
+strength
+value. However, I suggest leaving it at 0.50.
+✨
+Added fast film grain node
+This node adds film grain after upscaling. This provides a professional finish and a cinematic look. The
+grain_intensity
+value can be increased up to 0.050. I find less is more here and therefore have it set to 0.010.
+✨
+Adjusted some parameters for better performance
+I adjusted some parameters, mainly affecting the Image Upscale node. I found that 20 steps unnecessarily slowed down the upscaling process and resulted in a poorer outcome, especially regarding skin texture. Eight steps proved to be the perfect value. This reduced the overall workflow time to 30% while simultaneously improving the quality.
+🛠️
+All the changes combined now result in a much faster workflow and very decent images compared to v1.
+🆕
+v3 Changelog:
+The results with version 2 of the workflow are already quite good. But there's always room for improvement. So I've made some further adjustments that will help you get better images. What's changed?
+✨
+Added Color Grading Node
+Since the release of the Z-Image model, generating thousands of images showed that it struggles with following light and color grading prompts. Images often look overbrighten and like they were taken with a high-end smartphone, making it hard to achieve a cinematic look. To fix this, a color grading node has been added to the first block (next to the LoRa loader). Here, you can adjust temperature, brightness, contrast, saturation, and gamma to get truly impressive results. For best results, set the seed in the "Seed Generator" node to "fixed," disable the detailer and upscaler, and experiment a bit. This lets you achieve a cinematic look immediately - no LoRa needed.
+✨
+Added Adetailer Group for Image Improvement
+To complement the upscaling process, a dedicated face and eye detailer section has been added. Bare feet and hands already render well in 99% of cases with Z-Image, so no detailer is needed for them. Adding one would only slow down the workflow unnecessarily. To keep the overall workflow compact despite the new nodes, the relevant parts have been moved into subgraphs. You still have full control over key parameters such as steps, CFG, and denoise for both detailers. Too small changes indicate a denoise value that’s too low, while issues with eyes or other image artifacts mean the denoise value is too high. Feel free to experiment with the denoise to get the best results.
+Make sure that you have downloaded the 2 needed files for the detailer:
+Face Detector:
+face_yolov8m.pt
+(place in \models\ultralytics\bbox)
+Eyes Detector:
+Eyeful_v2-Paired.pt
+(place in \models\ultralytics\bbox)
+Without these files the workflow will just stop at the detailer group!
+✨
+Added Adetailer Group to the Toggle On / Off Node
+The new detailer section has been integrated into the Toggle On/Off node at the start of the workflow. This allows you to enable or disable it with a single click. It’s especially useful when generating RAW images, testing color grading, or looking for a good seed without applying additional detail enhancements.
+✨
+Added Calculated Resolution Node
+To make it easy to see which base resolution is being used, I've added a node that displays this information. It's the result of the selected resolution in megapixels and the aspect ratio. You can see this "Calculated Resolution" node between the "Base Resolution" and "Latent Image" nodes on the left.
+✨
+Added Model Sampling Aura Flow Node
+In other Z-Image workflows, you'll see the "Model Sampling Aura Flow" node, but it is usually muted. Since I didn’t find it useful for generating more variations from the same prompt, I removed it in versions 1 and 2 of the workflow. I’ve now added it back so you can test it yourself. This doesn’t affect runtime, and of course, the node can still be muted if desired.
+✨
+Adjusted some parameters
+I’ve tweaked a few settings again to achieve the best possible results. First, I increased the base resolution from 1.2MP to 2.0MP. This alone slightly improves image quality, as there are more pixels in the RAW image. If you have a powerful GPU, you can raise this value to 2.2MP or even 2.5MP. Additionally, I increased the sharpen strength from 0.50 to 0.55 and adjusted the film grain intensity from 0.010 to 0.015, which seems to be the sweet spot. Of course, feel free to experiment yourself.
+🛠️
+The download includes two versions: a full version with all updates, including the Detailer section, and a Lite version without the Detailer Group but with all other changes and color grading. Enjoy!
+If you have a question or comment about the workflow feel free to leave a post in the comment section. If something isn't working, please specify exactly what isn't working. Please also include the message displayed in the terminal window.
+Have fun and feel free to post your generated images in the gallery below! I would like to see what you do with this workflow!
+👍
+## Civitai Links
+*   **[View This Version on Civitai →](https://civitai.com/models/2174733?modelVersionId=2456846)**
+*   [View Full Model Page →](https://civitai.com/models/2174733)
+*   [View Creator Profile →](https://civitai.com/user/MrSmith2025)
+---
+## File Information
+
+*   **Primary Filename (Civitai)**: `zImageTurboT2IWorkflow_v20.zip`
+*   **Size**: 3.37 MB
+*   **Hash (AutoV2)**: `3997D75A8B`
+*   **Hash (SHA256)**: `3997D75A8B6198761C6E4BDDE7AA2C350AAA1E34B3968ED4837BEBAEB99AAE2C`
+---
+
+---
+# Z-Image Turbo UltraReal workflow (Version: v1.0 Z-Image Turbo)
+**Creator**: [Danrisi](https://civitai.com/user/Danrisi)
+**Type**: Workflows
+**Base Model**: ZImageTurbo
+**Version Uploaded**: 2025-12-03
+**Trigger Words**: `N/A`
+**Civitai Model ID**: 2190193
+**Civitai Version ID**: 2466066
+**Stats (at time of fetch for this version)**:
+*   Downloads: 663
+*   Rating: 0.0 (0 ratings)
+*   Favorites: N/A
+---
+## Description (Parent Model)
+Created a workflow for ultrarealistic results with Z-Image. While I designed it for my NiceGirls LoRA, it actually works good without people too (like on 1st picture). Actually workflow non-optimized for speed, cause i aimed at quality.
+U need to download my lora:
+https://civitai.com/models/1862761?modelVersionId=2465980
+And custom nodes:
+https://github.com/ClownsharkBatwing/RES4LYF
+Actually you can try without my lora too
+## Civitai Links
+*   **[View This Version on Civitai →](https://civitai.com/models/2190193?modelVersionId=2466066)**
+*   [View Full Model Page →](https://civitai.com/models/2190193)
+*   [View Creator Profile →](https://civitai.com/user/Danrisi)
+---
+## File Information
+
+*   **Primary Filename (Civitai)**: `zImageTurboUltrareal_v10ZImageTurbo.zip`
+*   **Size**: 0.00 MB
+*   **Hash (AutoV2)**: `4F3932FD63`
+*   **Hash (SHA256)**: `4F3932FD631376A7C87CEE320F0E153C8B128BC8B0BADCA553226EC55DDF91BC`
+---
+
+---
+# Z-Image-Batch Restyling & Zip Archiving (Version: v1.0)
+**Creator**: [hxxwoq2222](https://civitai.com/user/hxxwoq2222)
+**Type**: Workflows
+**Base Model**: ZImageTurbo
+**Version Uploaded**: 2025-12-04
+**Trigger Words**: `N/A`
+**Civitai Model ID**: 2192883
+**Civitai Version ID**: 2469113
+**Stats (at time of fetch for this version)**:
+*   Downloads: 96
+*   Rating: 0.0 (0 ratings)
+*   Favorites: N/A
+---
+## Description (Parent Model)
+Get the
+latest global workflows
+on my RunningHub homepage
+and run them free on RTX4090.
+Sign Up with my invite link for 1000 bonus points + 100 daily:
+https://www.runninghub.ai/?inviteCode=rh-v1221
+Run Directly:
+https://www.runninghub.ai/post/1996473449142951937/?inviteCode=rh-v1221
+Please credit and link to my homepage if reprinting.国内合作加Q：549791525
+"I found that
+Z-image
+is amazing for turning
+3D Anime
+or
+CG art
+into
+Photorealistic
+images, so I made this workflow for everyone.
+Please make sure to stick to my default
+Sampler settings
+, otherwise it might not work well. There is a detailed tutorial inside!"
+## Civitai Links
+*   **[View This Version on Civitai →](https://civitai.com/models/2192883?modelVersionId=2469113)**
+*   [View Full Model Page →](https://civitai.com/models/2192883)
+*   [View Creator Profile →](https://civitai.com/user/hxxwoq2222)
+---
+## File Information
+
+*   **Primary Filename (Civitai)**: `zImageBatchRestyling_v10.zip`
+*   **Size**: 0.01 MB
+*   **Hash (AutoV2)**: `047CD28A54`
+*   **Hash (SHA256)**: `047CD28A54DF89B6228FBFA0F37DF7A643E1EE5FD4D0BEEDC7BD123668C46ECC`
+---
+
+---
+# Z-Image-ControlNet + SDPOSE + second-order Refiner (Version: v1.0)
+**Creator**: [AIKSK](https://civitai.com/user/AIKSK)
+**Type**: Workflows
+**Base Model**: ZImageTurbo
+**Version Uploaded**: 2025-12-05
+**Trigger Words**: `N/A`
+**Civitai Model ID**: 2195512
+**Civitai Version ID**: 2472063
+**Stats (at time of fetch for this version)**:
+*   Downloads: 51
+*   Rating: 0.0 (0 ratings)
+*   Favorites: N/A
+---
+## Description (Parent Model)
+This workflow uses the enhanced Z-Image Turbo model together with ControlNet to achieve stable control over lines, depth maps, and pose skeletons, covering nearly all common conditioning types. Z-Image Turbo remains extremely fast while respecting the structural guidance extracted from SD-Pose or other detectors, making the first-pass generation both pose-accurate and responsive to the control signal. Because ControlNet naturally lowers aesthetic richness, the workflow adds a secondary refinement stage: the image is decoded, re-encoded into latent space, and passed through an additional diffusion round. This brings back detail, color depth, and overall visual quality without breaking the control. Latent-space upscaling often produces more pleasing variation compared with direct pixel upscaling, so the workflow uses it as the primary refinement strategy.
+In practice, results show that skeleton control is stable and predictable, and switching to SD-Pose improves the accuracy of complex or full-body detections. For more stylized or line-art inputs, preprocessing strength directly influences how strictly the model interprets the structure, and adjusting it provides smoother control than relying solely on ControlNet’s strength value. ControlNet’s presence can weaken LoRA effects, so users may choose carefully when applying style models. Depth extraction, line control, and even typography guidance work reliably, though aesthetic quality still benefits from the two-stage refinement. Given that the Z-Image ecosystem is new and evolving, this workflow provides a practical balance: strong structural control, fast generation, and a refiner step that restores the vivid aesthetics Z-Image is known for.
+🎥 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/7GtFnr8ixnM
+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/1996596394481819649/?inviteCode=rh-v1111
+If the results meet your expectations, you can later deploy it locally for customization.
+🎁
+Fan Benefits：
+Register to get
+1000 points + daily login 100 points — enjoy 4090 performance and 48 GB super power!
+📺 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/BV1XW2BBVEqW/
+☕ Support Me on Ko-fi
+If you find my content helpful and want to support future creations, you can buy me a coffee ☕。
+Every bit of support helps me keep creating — just like a spark that can ignite a blazing flame。
+👉
+Ko-fi：
+https://ko-fi.com/aiksk
+💼 Business Contact
+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/7GtFnr8ixnM
+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/1996596394481819649/?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/BV1XW2BBVEqW/
+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。
+## Civitai Links
+*   **[View This Version on Civitai →](https://civitai.com/models/2195512?modelVersionId=2472063)**
+*   [View Full Model Page →](https://civitai.com/models/2195512)
+*   [View Creator Profile →](https://civitai.com/user/AIKSK)
+---
+## File Information
+
+*   **Primary Filename (Civitai)**: `zImageControlnetSDPOSE_v10.zip`
+*   **Size**: 0.05 MB
+*   **Hash (AutoV2)**: `49A2705489`
+*   **Hash (SHA256)**: `49A27054895DA169511F76D77A444AFC97A059AC4C43B95B57E11AD521B04E4E`
+---
+
+---
+# Z-Image-ControlNet second-order Refiner + Pose / Depth / Line (Version: v1.0)
+**Creator**: [AIKSK](https://civitai.com/user/AIKSK)
+**Type**: Workflows
+**Base Model**: ZImageTurbo
+**Version Uploaded**: 2025-12-05
+**Trigger Words**: `N/A`
+**Civitai Model ID**: 2195521
+**Civitai Version ID**: 2472072
+**Stats (at time of fetch for this version)**:
+*   Downloads: 98
+*   Rating: 0.0 (0 ratings)
+*   Favorites: N/A
+---
+## Description (Parent Model)
+This workflow uses the Z-Image model together with ControlNet to achieve reliable control over pose skeletons, depth information, and line-based structure. Z-Image’s fast inference makes it responsive to these conditioning signals, producing an initial output that follows the intended structure while still carrying the model’s vivid rendering style. However, ControlNet naturally reduces aesthetic richness, so the workflow incorporates a second refinement stage: the generated image is re-encoded into latent space and passed through another diffusion round. This latent-space pass restores color depth, detail, and visual cohesion more effectively than pixel-space upscaling, giving the final image a more polished look.
+In practice, switching to SD-Pose improves skeleton accuracy when the automatically detected pose is incomplete, and adjusting preprocessing strength lets you fine-tune how strongly the structure affects the result. Line control and depth control both behave predictably, though stylized cases may still require refinement to maintain visual appeal. LoRA models can be loaded, but ControlNet will weaken their influence, so the workflow favors simpler stylistic adjustments. Despite its early stage of development, Z-Image already shows strong potential—its image-to-image quality is striking, and the two-stage approach offers a balanced combination of structural control and aesthetic refinement.
+🎥 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/7GtFnr8ixnM
+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/1996508277796126722/?inviteCode=rh-v1111
+If the results meet your expectations, you can later deploy it locally for customization.
+🎁
+Fan Benefits：
+Register to get
+1000 points + daily login 100 points — enjoy 4090 performance and 48 GB super power!
+📺 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/BV1XW2BBVEqW/
+☕ Support Me on Ko-fi
+If you find my content helpful and want to support future creations, you can buy me a coffee ☕。
+Every bit of support helps me keep creating — just like a spark that can ignite a blazing flame。
+👉
+Ko-fi：
+https://ko-fi.com/aiksk
+💼 Business Contact
+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/7GtFnr8ixnM
+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/1996508277796126722/?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/BV1XW2BBVEqW/
+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。
+## Civitai Links
+*   **[View This Version on Civitai →](https://civitai.com/models/2195521?modelVersionId=2472072)**
+*   [View Full Model Page →](https://civitai.com/models/2195521)
+*   [View Creator Profile →](https://civitai.com/user/AIKSK)
+---
+## File Information
+
+*   **Primary Filename (Civitai)**: `zImageControlnetSecondOrder_v10.zip`
+*   **Size**: 0.19 MB
+*   **Hash (AutoV2)**: `99BB99C797`
+*   **Hash (SHA256)**: `99BB99C7976B532204A029D263DF30AF946F2B310C7BD54CF592D5A157BDC192`
 ---

civitai_tracker.json

@@ -317,7 +317,32 @@
       "name": "Z-Image Turbo - T2I Workflow + Detailer + Upscaler + Color Grading",
       "versions": [
         "2468562",
-        "2449002"
+        "2449002",
+        "2456846"
+      ]
+    },
+    "2190193": {
+      "name": "Z-Image Turbo UltraReal workflow",
+      "versions": [
+        "2466066"
+      ]
+    },
+    "2192883": {
+      "name": "Z-Image-Batch Restyling & Zip Archiving",
+      "versions": [
+        "2469113"
+      ]
+    },
+    "2195512": {
+      "name": "Z-Image-ControlNet + SDPOSE + second-order Refiner",
+      "versions": [
+        "2472063"
+      ]
+    },
+    "2195521": {
+      "name": "Z-Image-ControlNet second-order Refiner + Pose / Depth / Line",
+      "versions": [
+        "2472072"
       ]
     }
   },
@@ -386,6 +411,11 @@
     "2474056",
     "2468386",
     "2468562",
-    "2449002"
+    "2449002",
+    "2456846",
+    "2466066",
+    "2469113",
+    "2472063",
+    "2472072"
   ]
 }