FLUX.2 KLEIN9B — Custom Merge
Model Overview
A custom merged model based on FLUX.2 [klein] 9B by Black Forest Labs. This model has been tested and optimized for high-quality realistic image generation with exceptional detail in textures, lighting, and atmospheric effects.
Key Features
Photorealistic skin rendering with natural subsurface scattering, visible pores, and subtle imperfections
Exceptional water and wet surface handling — droplets, reflections, refraction, and flow patterns
Advanced lighting capabilities including volumetric god rays, golden hour, rim lighting, and chiaroscuro
Superior hair detail with individual strand rendering and natural backlighting effects
Rich material textures — velvet, linen, silk, leather, wood, metal, and stone
Strong atmospheric effects — fog, mist, steam, rain, and environmental depth
Anatomical accuracy for both portrait and full-body generation
Recommended Settings
Optimal Configuration (Tested):
CFG Scale: 2.0
Steps: 15
Scheduler: Euler Ancestral (EulerA)
Quick Previews:
CFG Scale: 1.5
Steps: 8-10
Scheduler: EulerA
Complex Scenes (Landscapes, Materials):
CFG Scale: 2.0-2.5
Steps: 15-20
Scheduler: EulerA
Resolution: 1024x1536 (portrait) or 1536x1024 (landscape)
Best Use Cases
Photorealistic portraits and character art
Environmental and landscape photography
Fashion and material studies
Cinematic and atmospheric scenes
Fine art nude photography (artistic interpretation)
Macro detail shots
Water and weather effects
Known Limitations
Transparent/translucent fabrics may require LoRA or enhanced prompting for proper rendering
Text rendering is readable but not perfect — acceptable for most use cases
Complex multi-element scenes may require 2-3 generations for optimal results
Official 4-step inference is too low for detailed work — 15 steps recommended
Technical Details
Base Model: FLUX.2 [klein] 9B by Black Forest Labs
Architecture: Rectified Flow Transformer
Type: Step-distilled model (optimized for speed)
License: Refer to original FLUX.2 license terms
Performance Notes
This model excels at organic, natural scenes with complex lighting. The EulerA scheduler at 15 steps provides the best balance between speed and quality. While the official recommendation is 4 steps at CFG 1.0, extensive testing shows 15 steps at CFG 2.0 delivers significantly better results for detailed work without sacrificing the speed advantage of distilled models.
Credits
Base model by Black Forest Labs. Custom merge and testing by community contributors.
Enjoy creating! If you generate something amazing, consider sharing it in the images section. 🎨
Description
must works more coreectly, tested only in ForgeNEO
FAQ
Comments (13)
Can confirm this does work in Forge Neo, seems ok to me but I'm no expert with Klein.
Does version 3 work with comfyui?
Who knows, tested ForgeNEO
Any plans for Klein 4B version?
You want an honest answer, right? I'm so fed up with these models, they're so crude and clumsy that I'm giving up. All the customization tools are crap, and as soon as you get to the bare minimum, some idiot shows up and starts giving negative ratings, and that's completely demotivating.
Understand you, had the samilar feelings with couple my IRL projects.
@FASCIUM 100% positive reaction on this model
This works but Klein 9B seems odd in Forge, still. It only works with the gigantic BF16 Text Enconder so speed is super slow on my 5060Ti.
Do you have any recommendations how to make this model work efficiently and well because even with a LoRa i cannot get it to do the same as the N S F W sample someone made
There is no recommendation yet, the model is very crude, there are no good customization tools
I use GGUF Q5 Text encoder and have no problems with 9B on 3050. Check your hardware.
@mphobbit I don't have any problems either, I use the Q8 version. I only have 16 GB of shared RAM. When Text Encoder is finished, it is thrown out of the VRAM, so it shouldn't affect the actual generation. Forge sucks, you should consider switching to ComfyUI—the performance is the same, if not better. I know this because I've tested every tool imaginable with my potato Mac.
@CupRunethOverWithLSD try to use FP8 instead Q8. Idk about you but in my case GGUFs work much slower than corresponding safetensors (I also have 16 gigs). I'm not a speciallist but by general impession it could be connected with that the machine spends time and memory to unpack from gguf all necessary for generation thus you have two proccesses: ungguf -> generation itself.
@mphobbit Unfortunately, Metal (Apple) does not currently support Float 8, which is why I am limited to GGUF models. However, I will be upgrading my hardware soon.
You probably have 16GB VRAM? I'm talking about shared memory. ARM architecture, like on my M3, shares RAM and VRAM. That's pretty crappy, to put it simply. 😂