README.md

---
license: apache-2.0
language:
- en
pipeline_tag: text-to-image
base_model: Tongyi-MAI/Z-Image
tags:
- gguf
- safetensors
- text-to-image
- rundiffusion
- z-image
---

<div align="center">

<a href="https://www.rundiffusion.com/?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=header_logo">
  <img src="https://huggingface.co/RunDiffusion/Juggernaut-Z-Image/resolve/main/assets/RD_Mark.png" alt="RunDiffusion" width="110" />
</a>

<h1>Juggernaut Z by RunDiffusion</h1>

<p><i>A cinematic fine-tune of Z-Image Base — tuned for presentation-ready output.</i></p>

<p>
  <a href="https://www.rundiffusion.com/juggernaut-z?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=cta_primary"><img alt="Try Juggernaut Z" src="https://img.shields.io/badge/%E2%96%B6%20Try%20Juggernaut%20Z-7C3AED?style=for-the-badge&labelColor=7C3AED"></a>&nbsp;<a href="https://www.rundiffusion.com/juggernaut-z-prompt-guide?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=prompt_guide_badge"><img alt="Prompt Guide" src="https://img.shields.io/badge/Prompt%20Guide-1f1f23?style=for-the-badge"></a>&nbsp;<a href="https://huggingface.co/Tongyi-MAI/Z-Image"><img alt="Base Model: Z-Image" src="https://img.shields.io/badge/%F0%9F%A4%97%20Base%20Model-Z--Image-FFD21E?style=for-the-badge&labelColor=1f1f23"></a>&nbsp;<img alt="License: Apache 2.0" src="https://img.shields.io/badge/License-Apache%202.0-2ea44f?style=for-the-badge">
</p>

</div>

<p align="center">
  <img src="https://www.rundiffusion.com/images/juggernaut-z/hero-image.jpg" alt="Juggernaut Z hero" />
</p>

> Juggernaut Z is a fine-tune of **Z-Image Base** by **Team Juggernaut**, trained by **KandooAI**, and released through **RunDiffusion**. It is tuned for stronger lighting, sharper focus, more refined skin texture, and more cinematic atmosphere — out of the box.

This repository hosts the official RunDiffusion release artifacts: full-precision weights, FP16 and FP8 variants, and a full set of GGUF quantizations.

---

## Highlights

- More dramatic, cinematic **lighting** out of the box
- Sharper **focus** and a more deliberate camera feel
- Cleaner **portraits** with more natural skin texture
- Improved **anatomy** and structural integrity
- Better representation across **ethnicities** by default
- Tuned for editorial, concept, and cinematic work

## Comparisons

All sets below show **Juggernaut Z (left)** vs **Z-Image Base (right)**. Source: the [RunDiffusion Juggernaut Z announcement](https://www.rundiffusion.com/juggernaut-z?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=comparison_source).

### Lighting

More dramatic, cinematic lighting out of the box.

![Lighting 1](https://www.rundiffusion.com/images/juggernaut-z/lighting-1.png)
![Lighting 2](https://www.rundiffusion.com/images/juggernaut-z/lighting-2.png)
![Lighting 3](https://www.rundiffusion.com/images/juggernaut-z/lighting-3.png)
![Lighting 4](https://www.rundiffusion.com/images/juggernaut-z/lighting-4.png)
![Lighting 5](https://www.rundiffusion.com/images/juggernaut-z/lighting-5.jpg)
![Lighting 6](https://www.rundiffusion.com/images/juggernaut-z/lighting-6.jpg)

### Skin & Texture

Cleaner, more natural-looking skin — especially in close-up portraits.

![Skin 1](https://www.rundiffusion.com/images/juggernaut-z/skin-1.png)
![Skin 2](https://www.rundiffusion.com/images/juggernaut-z/skin-2.png)
![Skin 3](https://www.rundiffusion.com/images/juggernaut-z/skin-3.png)
![Skin 4](https://www.rundiffusion.com/images/juggernaut-z/skin-4.png)

### Anatomy

Cleaner anatomy and more consistent structural detail across a wide range of subjects.

![Anatomy 1](https://www.rundiffusion.com/images/juggernaut-z/anatomy-1.png)
![Anatomy 2](https://www.rundiffusion.com/images/juggernaut-z/anatomy-2.png)
![Anatomy 3](https://www.rundiffusion.com/images/juggernaut-z/anatomy-3.png)
![Composition 3](https://www.rundiffusion.com/images/juggernaut-z/composition-3.png)

### Composition

Improved subject and object placement within scenes, with further work planned for v2.

![Composition 1](https://www.rundiffusion.com/images/juggernaut-z/composition-1.png)
![Composition 2](https://www.rundiffusion.com/images/juggernaut-z/composition-2.png)
![Anatomy 4](https://www.rundiffusion.com/images/juggernaut-z/anatomy-4.png)

### Diversity

More balanced results across ethnic backgrounds, with better representation by default.

![Diversity 1](https://www.rundiffusion.com/images/juggernaut-z/diversity-1.png)
![Diversity 2](https://www.rundiffusion.com/images/juggernaut-z/diversity-2.png)
![Diversity 3](https://www.rundiffusion.com/images/juggernaut-z/diversity-3.png)
![Diversity 4](https://www.rundiffusion.com/images/juggernaut-z/diversity-4.png)

### Architecture

Cleaner structural lines and more coherent material rendering.

![Architecture 1](https://www.rundiffusion.com/images/juggernaut-z/arch-new-1.jpg)
![Architecture 2](https://www.rundiffusion.com/images/juggernaut-z/arch-new-2.jpg)

## Recommended Settings

| Parameter | Default | Range |
| --- | --- | --- |
| CFG | `6` | `6 – 9` |
| Steps | `35` | `25 – 45` |

## Good Fit For

- Portraits with cleaner facial detail and stronger focus
- Cinematic scenes with strong lighting and atmosphere
- Concept development and visual exploration
- Editorial and fashion work that benefits from a polished finish

## Files In This Repo

| File | Format | Notes |
| --- | --- | --- |
| `Juggernaut_Z_V1_by_RunDiffusion.safetensors` | safetensors (bf16) | Original release weights |
| `Juggernaut_Z_V1_by_RunDiffusion_fp16.safetensors` | safetensors (fp16) | Half-precision |
| `Juggernaut_Z_V1_FP8_e4m3fn.safetensors` | safetensors (fp8 e4m3fn) | Lower VRAM footprint |
| `Juggernaut_Z_V1_by_RunDiffusion_q8_0.gguf` | GGUF · q8_0 | Highest-quality quant |
| `Juggernaut_Z_V1_by_RunDiffusion_q6_k-004.gguf` | GGUF · q6_k | |
| `Juggernaut_Z_V1_by_RunDiffusion_q5_k_m-003.gguf` | GGUF · q5_k_m | |
| `Juggernaut_Z_V1_by_RunDiffusion_q5_k_s-005.gguf` | GGUF · q5_k_s | |
| `Juggernaut_Z_V1_by_RunDiffusion_q4_k_m-002.gguf` | GGUF · q4_k_m | |
| `Juggernaut_Z_V1_by_RunDiffusion_q4_k_s-001.gguf` | GGUF · q4_k_s | Smallest footprint |

Use the `.safetensors` variants with the workflow that matches your local inference stack. Use the `.gguf` variants with a GGUF-compatible runtime.

## Links

- **Run Juggernaut Z on RunDiffusion** → [rundiffusion.com/juggernaut-z](https://www.rundiffusion.com/juggernaut-z?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=footer_run)
- **Prompt guide** → [Juggernaut Z Prompt Guide](https://www.rundiffusion.com/juggernaut-z-prompt-guide?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=footer_prompt_guide)
- **Base model** → [Tongyi-MAI/Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image)

## Attribution

Juggernaut Z is built on Z-Image Base — credit for the upstream base model belongs to the Z-Image team. This fine-tuned release is by **Team Juggernaut**, with training by **KandooAI**, published by **RunDiffusion**.

## License

Released under the **Apache 2.0** license.