Fullgreed — Z-Image Base Fine-tune (Photoreal, INT8)
Fullgreed is a fine-tune of Alibaba Tongyi's Z-Image — 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 |
|---|---|---|
greed_int8.safetensors | INT8, ComfyUI-native quantization format | 6.3 GB |
fullgreed_bf16.safetensors | Full-precision BF16 (matches the official Z-Image dtype convention) | 12.3 GB |
Both files produce the same images — the INT8 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— the standard Flux 16-channel VAE repackaged in fp16 for a smaller download; interchangeable with the officialae.safetensorsworkflows/alphgreed_workflow.json— ready-made ComfyUI workflow (text-to-image + SeedVR2 upscale stage)
Loading (ComfyUI)
- Diffusion model: Load Diffusion Model (UNETLoader) →
greed_int8.safetensors - Text encoder: CLIPLoader →
qwen_3_4b.safetensors, typelumina2 - 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 by Tongyi-MAI, Alibaba Group — see the Z-Image technical report (arXiv 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.