https://youtu.be/CU1UKxjWBRo

This workflow is the two-image editing setup for Krea 2 Identity Edit v1.2. It is built for edits where one reference image is not enough: replacing a person with another reference, transferring an outfit, combining a subject with a second visual cue, or building a scene from two separate inputs. The workflow gives creators a direct way to test multi-reference editing without manually rebuilding a complicated graph every time.

The inspected graph uses `krea2_turbo_fp8_scaled.safetensors` as the active UNET, `qwen3vl_4b_fp8_scaled.safetensors` as the Krea2 CLIP/text encoder, and `qwen_image_HDR_vae_fp32_comfy.safetensors` as the VAE. The active LoRA is `krea2_identity_edit_v1_2_fp16.safetensors`, enabled at strength 1.0. The main output path contains a 1024 x 1024 latent setup and a 10-step KSampler with CFG 1, euler/simple sampling, and denoise 1. The graph also includes preview outputs for checking each reference side before the final SaveImage output. A separate ImageScaleBy node exists in the file, but it is bypassed and not part of the active output path, so this description does not present it as an enabled upscale stage.

This version is most useful when image A provides the base scene or target composition and image B provides the identity, face, outfit, object, or visual feature you want to transfer. Keep the prompt explicit about which image supplies which part of the result. Short prompts often work well for replacement tasks, but clear role assignment is important: for example, replace the character in image A with the person from image B, or apply the outfit from image B to the subject in image A.

Main features:

- Two-image Krea 2 edit workflow
- Multi-reference input logic
- Krea 2 Turbo FP8 active UNET path
- Krea 2 Identity Edit v1.2 LoRA enabled at strength 1.0
- Qwen3VL 4B FP8 Krea2 text encoder route
- Qwen Image HDR VAE decode path
- 1024 x 1024 latent setup
- 10-step euler/simple KSampler
- CFG 1 and denoise 1 edit pass
- Multiple preview outputs before final save
- Best for replacement, outfit transfer, and two-reference scene edits

Suggested workflow:

Use image A as the base frame and image B as the reference you want to borrow from. In the prompt, clearly state the role of each image. If the result mixes the two references incorrectly, simplify the prompt and separate the instruction into base image, transferred feature, and final style. If identity matching is more important than style, keep the style language minimal and focus the prompt on the subject replacement or face/outfit transfer.

RunningHub Workflow

Try the workflow online right now - no installation required.
Workflow: https://www.runninghub.ai/post/2079971231356506114?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 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/BV1bJgy6eEei/

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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/2079971231356506114?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/BV1bJgy6eEei/

本期 Krea 2 相关模型资源：
https://pan.quark.cn/s/07bdc81784ce?pwd=FpDf#/list/share

这些资源主要面向本地用户，方便进行创作与学习。