https://youtu.be/aCEuir7zy-w 
 
This workflow is the local batch restyle version of the Krea 2 RAW + Turbo refinement setup. It is designed for creators who want to process many source images on a local ComfyUI environment while preserving the original subject identity, pose, composition, lighting logic, color palette, and depth relationships. The goal is not to redraw everything from zero. It is a controlled image-to-image restoration and restyle pipeline for cleaning edges, improving material texture, increasing visual polish, and making a batch of images feel more consistent. 
 
The inspected graph uses two active Krea 2 UNET routes: `krea2_raw.safetensors` for the high-noise shaping stage and `krea2_turbo_fp8.safetensors` for the lower-noise convergence and refinement stages. The text route uses `qwen3vl_4b_fp8_scaled.safetensors` as the Krea2 CLIP encoder, and decoding is handled by `qwen_image_HDR_vae_fp32_comfy.safetensors`. Depth control is active in three stages through `depth-control-lora.safetensors`, with strengths 1.00, 0.85, and 0.65, so the workflow can keep source structure while still allowing the RAW stage to rebuild detail. 
 
The local batch version is built around a manual JSON prompt block, making it easier to keep a stable instruction across a folder of images. The active chain includes a 36-step RAW/Turbo sigma schedule, RAW high-noise shaping, Turbo source-resolution convergence, intermediate and final latent upscales to 1024 x 1024, a 10-step Turbo refinement pass, and an active 4x-UltraSharp image upscale route. Bypassed legacy KSampler and disconnected final scaling nodes are not treated as active features here. 
 
Main features: 
 
- Local batch Krea 2 restyle workflow 
- RAW high-noise shaping with Krea 2 Raw 
- Turbo low-noise refinement with Krea 2 Turbo FP8 
- Qwen3VL 4B FP8 Krea2 text encoder 
- Qwen Image HDR VAE route 
- Three-stage Krea2 depth control 
- Depth ControlNet LoRA strengths 1.00, 0.85, and 0.65 
- Manual JSON prompt block for batch consistency 
- 1024 x 1024 latent refinement stages 
- Active 4x-UltraSharp image upscale route 
- Best for local batch cleanup, restoration, and restyle tasks 
 
Suggested workflow: 
 
Prepare a folder of source images with similar quality targets, keep the JSON prompt direct, and use the source image as the authority for composition, identity, pose, lighting, and color. Start with the default prompt before adding stronger style language. If the output drifts too far from the original image, reduce creative wording and keep depth control strong. If the output is too conservative, loosen the prompt and let the RAW stage rebuild more detail. 
 
Related resources: 
 
Krea 2 Model Collection (Quark): https://pan.quark.cn/s/07bdc81784ce 
Krea 2 Raw: https://huggingface.co/krea/Krea-2-Raw 
Krea 2 Turbo: https://huggingface.co/krea/Krea-2-Turbo 
Krea 2 Depth ControlNet LoRA: https://huggingface.co/Patil/Krea-2-depth-controlnet 
 
RunningHub Workflow 
 
Try the workflow online right now - no installation required. 
Workflow: https://www.runninghub.ai/post/2080681468573085697?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 &amp; Asia-Pacific) 
 
If you are 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/BV1GBgi6JEwL/ 
 
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打开下方链接即可在线体验，无需安装。 
工作流：https://www.runninghub.ai/post/2080681468573085697?inviteCode=rh-v1111 
 
如果觉得效果理想，也可以在本地进行自定义部署。 
 
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Bilibili 更新（中国大陆及亚太地区） 
 
如果你在中国大陆或亚太地区，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/BV1GBgi6JEwL/ 
 
本期 Krea 2 相关模型资源： 
Quark: https://pan.quark.cn/s/07bdc81784ce 
Krea 2 Raw: https://huggingface.co/krea/Krea-2-Raw 
Krea 2 Turbo: https://huggingface.co/krea/Krea-2-Turbo 
Krea 2 Depth ControlNet LoRA: https://huggingface.co/Patil/Krea-2-depth-controlnet 
 
这些资源主要面向本地用户，方便进行创作与学习。

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