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license: apache-2.0
library_name: diffusion-single-file
base_model: Tongyi-MAI/Z-Image
pipeline_tag: text-to-image
tags:
- text-to-image
- z-image
- comfyui
- int8
- photorealistic
---
# Fullgreed — Z-Image Base Fine-tune (Photoreal, INT8)
**Fullgreed** is a fine-tune of Alibaba Tongyi's **Z-Image (Omni-Base)** — the 6B-parameter Single-Stream Diffusion Transformer (S3-DiT) — tuned for photorealistic, phone-camera-authentic portraits and selfies: natural lighting, believable skin and hair texture, and outputs that read as real photos rather than "AI renders."
It is a surgical fine-tune: only the attention and feed-forward projection weights were trained, leaving the base model's norms, embedders, and timestep conditioning untouched. Fullgreed keeps everything Z-Image is good at (bilingual prompt following, text rendering, composition) while adding its own photographic character.
## Released model
| File | What it is | Size |
|---|---|---|
| `fullgreed_int8.safetensors` | INT8, ComfyUI-native quantization format | 6.3 GB |
The INT8 release is effectively lossless (measured 0.03% average weight error vs the full-precision weights — visually identical output) at half the size and memory, and it needs **no custom nodes**: it runs on stock ComfyUI, including ComfyUI Cloud.
Companion files are included in this repo for convenience:
- `qwen_3_4b.safetensors` — text encoder (Qwen3-4B)
- `money_vae_f16.safetensors` — VAE (16-channel)
- [`workflows/alphgreed_workflow.json`](./workflows/alphgreed_workflow.json) — ready-made ComfyUI workflow (text-to-image + SeedVR2 upscale stage)
## Loading (ComfyUI)
- **Diffusion model:** Load Diffusion Model (UNETLoader) → `fullgreed_int8.safetensors`
- **Text encoder:** CLIPLoader → `qwen_3_4b.safetensors`, type **`lumina2`**
- **VAE:** VAELoader → `money_vae_f16.safetensors`
- **ModelSamplingAuraFlow** node with **shift = 3**
- Latent: **EmptySD3LatentImage**
Also runs in **Draw Things** (import as a Z-Image model) and anything else that supports Z-Image.
## Recommended settings
- **Steps:** 8–20
- **CFG:** 1–4 (sweet spot ≈ 1–3; a negative prompt works)
- **Sampler / scheduler:** `res_multistep` / `simple` (euler also works)
- **Resolution:** native around 1024×1024, up to ~4K
## Tips
- Slight CFG restraint (≤4) preserves the photographic look; high CFG pushes toward an over-processed render feel.
- The model responds well to camera-language prompts: phone selfie, mirror shot, golden hour, indoor tungsten, shallow depth of field, etc.
- The INT8 file uses ComfyUI's **native** quantization format — no custom nodes or CUDA extensions. It is not the same as older int8 builds that required a custom node to decode.
## Credits & license
- Base model: **Z-Image (Omni-Base)** by Tongyi-MAI, Alibaba Group — see the [Z-Image technical report (arXiv 2511.22699)](https://arxiv.org/abs/2511.22699).
- Text encoder: Qwen3-4B (Alibaba). VAE: Flux VAE family (Black Forest Labs).
- License: **Apache-2.0**, matching the Z-Image base model.
*Please generate responsibly. Do not use this model to create images of real people without their consent.*
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