For business inquires, commercial licensing, custom models, and consultation contact me under juggernaut@rundiffusion.com

Hello everyone,

It has been almost exactly one year since the last Juggernaut version (Ragnarok). After some downtime, TongyLab and BlackForest Lab provided us with two excellent community models (Z-Image, FluxKlein) at the end of last year.

I am presenting the first output of this here: Juggernaut Z, a fine-tune of the Z-Image base.

The checkpoints are available in all standard formats (bf16, fp8, and various GGUF versions). If I missed a specific format you need, just let me know in the comments. Also, a quick heads-up: if you already have the Z-Image Base running on your setup, there is no need to download the Text Encoder and VAE again, you can simply reuse your existing ones

I will keep this brief. This is version 1, so naturally, not everything is perfect yet. It will take 2-3 versions to fully integrate everything we have planned. Please be patient, as work is simultaneously underway on the Juggernaut variants for FluxKlein 4B and 9B.

Our main focus for this first release was killing the glossy "AI plastic" look of the base model. You will notice much better micro-contrasts, actual skin pores, and physically accurate lighting. We also improved the structural logic to reduce hallucinated geometry.

A Quick Word on Prompting: Please actually read the Prompt Guide. If you stick to the old SDXL tag-style prompting (just throwing comma-separated keywords at it), you might get a lucky shot here and there, but you will mostly run into errors and broken concepts. Juggernaut Z thrives on semantic prompting, talk to it in natural, descriptive sentences. If you are not used to this yet, I highly recommend using your favorite LLM (GPT, Gemini, Claude, etc.) to help structure your ideas into proper sentences.

I have included a ComfyUI workflow, which should ensure problem-free generation.

I recommend following Settings with the Workflow:

Resolution: 960*1440 or something similiar with that Pixelsize. "Low Res like 1024*1024" will sometime looks to grainy/noisy First pass

Steps: 22
Denoise: 1.00
Sampler: Res_2s
Scheduler: Beta

Second pass

Steps: 3
Denoise: 0.15
Sampler: Res_2s
Scheduler: Normal The foundational workflow was created by nsfwVariant. It was only minimally modified for our purposes, so credit goes to him. Please show him some support.

Also you can find a couple of Comparison Shots in my Profile and also on the RunDiffusion Juggernaut Z Page mentioned above :) Any LoRA trained on the Z-Image Base is fully compatible with Juggernaut Z. At least, every single one I’ve tested so far worked flawlessly.

Finally, have fun generating. We will be back soon with a FluxKlein fine-tune and Version 2 of Juggernaut Z.

Juggernaut Z [by KandooAI] - v1.0 bf16