<div data-youtube-video="https://youtu.be/P2bt83Op9bY"><iframe src="https://www.youtube.com/embed/P2bt83Op9bY" width="853" height="480" allowfullscreen></iframe></div> 
 
FLUX 3 Image Klein layout-controlled editing workflow. Every element gets a box: you say where it comes from in the reference and where it should land in the output. 
 
Main features: 
 
- Built on the distilled FLUX 3 Image Klein checkpoint (flux3_image_klein_sd_int8_convrot + qwen3vl_4b text encoder + flux2 VAE) 
- CreateBoundingBoxes defines src_bbox / tgt_bbox pairs on a 0-1000 normalised grid, so the same box works at any output resolution 
- Flux3LayoutPrompt converts those boxes into the caption syntax the model expects (&lt;object_1&gt;, &lt;object_2&gt;, ...) 
- ReferenceMultiLatent keeps the source image conditioning alive while regions move 
- 16 steps, no classifier-free guidance, euler/simple, denoise 1.0 
 
Suggested workflow: 
 
1. Load the reference image and draw a source box on the element you want to move, plus a target box where it should end up. 
2. Pin everything you do not want to move by giving it an identical src and tgt box - an unmoved box is a "keep" instruction. 
3. Write the caption around the boxes and run. Bounding boxes bias placement strongly but are not a hard mask, so expect small drift. 
 
Dependencies: 
 
- flux3_image_klein_sd_int8_convrot.safetensors (distilled UNET) 
- qwen3vl_4b_int8_convrot.safetensors (text encoder / CLIP) 
- flux2-vae.safetensors (VAE) 
- CreateBoundingBoxes, Flux3LayoutPrompt, ReferenceMultiLatent (custom nodes) 
 
RunningHub workflow page: https://www.runninghub.ai/zh-cn/user-center/1846601088051884033/webapp?inviteCode=rh-v1111 
 
Bilibili tutorial video: https://www.bilibili.com/video/BV1btJb6LEGS/ 
 
RunningHub registration with invite code rh-v1111: https://www.runninghub.ai/?inviteCode=rh-v1111

FLUX 3 Klein BBox Layout Edit

<div data-youtube-video="https://youtu.be/P2bt83Op9bY"></div> 
 
FLUX 3 Image Klein layout-controlled editing workflow. Every element gets a box: you say where it comes from in the reference and where it should land in the output. 
 
Main features: 
 
- Built on the distilled FLUX 3 Image Klein checkpoint (flux3_image_klein_sd_int8_convrot + qwen3vl_4b text encoder + flux2 VAE) 
- CreateBoundingBoxes defines src_bbox / tgt_bbox pairs on a 0-1000 normalised grid, so the same box works at any output resolution 
- Flux3LayoutPrompt converts those boxes into the caption syntax the model expects (&lt;object_1&gt;, &lt;object_2&gt;, ...) 
- ReferenceMultiLatent keeps the source image conditioning alive while regions move 
- 16 steps, no classifier-free guidance, euler/simple, denoise 1.0 
 
Suggested workflow: 
 
1. Load the reference image and draw a source box on the element you want to move, plus a target box where it should end up. 
2. Pin everything you do not want to move by giving it an identical src and tgt box - an unmoved box is a "keep" instruction. 
3. Write the caption around the boxes and run. Bounding boxes bias placement strongly but are not a hard mask, so expect small drift. 
 
Dependencies: 
 
- flux3_image_klein_sd_int8_convrot.safetensors (distilled UNET) 
- qwen3vl_4b_int8_convrot.safetensors (text encoder / CLIP) 
- flux2-vae.safetensors (VAE) 
- CreateBoundingBoxes, Flux3LayoutPrompt, ReferenceMultiLatent (custom nodes) 
 
RunningHub workflow page: https://www.runninghub.ai/zh-cn/user-center/1846601088051884033/webapp?inviteCode=rh-v1111 
 
Bilibili tutorial video: https://www.bilibili.com/video/BV1btJb6LEGS/ 
 
RunningHub registration with invite code rh-v1111: https://www.runninghub.ai/?inviteCode=rh-v1111

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