What is FLUX.2 [klein]?
FLUX.2 [klein] is a small, fast Flux.2-family model that handles both image generation and instruction-based image editing in one model.
Lineup:
- 9B / 9B Base (FLUX Non-Commercial License; non-commercial use only)
- 4B / 4B Base (Apache 2.0)
It's a bit confusing, but the one without "Base" in its name is the distilled model. Base takes 20 steps, while Distilled can generate in 4.
There's no big difference in quality, so we'll mostly use the Distilled model for generation.
Recommended Settings
- Resolution
- Min: 64×64
- Max: 4MP (2048×2048)
- Both width and height must be multiples of 16
- Number of Reference Images
- Max: 4
Flux.2 [klein] 9B
Model Download (9B)
-
diffusion_models
-
text_encoders
-
vae
📂ComfyUI/
└── 📂models/
├── 📂diffusion_models/
│ ├── flux-2-klein-9b-fp8.safetensors
│ └── flux-2-klein-base-9b-fp8.safetensors
├── 📂text_encoders/
│ └── qwen_3_8b.safetensors
└── 📂vae/
└── flux2-vae.safetensors
text2image Base

The official workflow uses something called
Flux2Scheduler, but it doesn't make much difference, so I useSimpleto keep the workflow simple.
text2image Distilled

Change only the following parameters:
CFG: 1.0steps: 4
Image Editing Base

The basic recipe is "input image + instruction prompt."
- VAE Encode the input image and pass it to
ReferenceLatent.
Image Editing Distilled

Image Editing (Multi-Reference) Base
You can also feed in multiple images as references.

- Just chain
Reference Image → VAE Encode → ReferenceLatentblocks one after another. - 2 or 3 images both work. (The limit is 4.)
Image Editing (Multi-Reference) Distilled

Flux.2 [klein] 4B
Model Download (4B)
-
diffusion_models
-
text_encoders
-
vae
📂ComfyUI/
└── 📂models/
├── 📂diffusion_models/
│ ├── flux-2-klein-4b.safetensors
│ └── flux-2-klein-base-4b.safetensors
├── 📂text_encoders/
│ └── qwen_3_4b.safetensors
└── 📂vae/
└── flux2-vae.safetensors
Workflow
The basics are exactly the same as 9B. Just replace the model and text encoder with the 4B ones.
text2image
Image Editing
Image Editing (Multi-Reference)
Capabilities / Examples
These are just a few examples.
Changing the style or removing objects is only a tiny part of image editing. What counts as "image editing"? Depending on how you answer that, the possibilities are endless. Go ahead and come up with your own uses.
Single Image

ControlNet-like (Pose)
This doesn't actually use ControlNet's mechanism. By giving it a stick figure or depth map and asking for a realistic image based on it, you can do ControlNet-style tasks as an image edit.
A office lady sitting on outdoor stairs at dusk, matching the pose from the reference image. Evening ambient light, calm urban atmosphere. She wears a long skirt and a black camisole with frills. Natural, realistic photo









