GREED

# Fullgreed — Z-Image Base Fine-tune (Photoreal)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. In practice this means Fullgreed keeps everything Z-Image is good at (bilingual prompt following, text rendering, composition) while adding its own photographic character — and it retains the base model's native reference-image editing ability (see Editing below).---## Files| File | What it is | Size | Use it when ||---|---|---|---|| <code>fullgreed_i8_plain_comfy.safetensors</code> | INT8 quantization, ComfyUI-native format | 6.3 GB | Recommended for most users — measured 0.03% average weight error vs the full model (visually identical output), half the size, half the memory, loads faster, and needs no custom nodes — runs on stock ComfyUI including ComfyUI Cloud || <code>fullgreed_f16.safetensors</code> | Full-precision model | 12.3 GB | Reference quality, LoRA training base, or any tool that doesn't support ComfyUI's quantized format |Both files produce the same images. If you're unsure, take the INT8.---## Requirements (ComfyUI)Standard Z-Image companion files (same as the official Comfy-Org release):- Text encoder: <code>qwen_3_4b.safetensors</code> → CLIPLoader, type *<code>lumina2</code>**- VAE: <code>ae.safetensors</code> (Flux 16-channel VAE)- Diffusion model: load via Load Diffusion Model (UNETLoader)- ModelSamplingAuraFlow node with shift = 3- Latent: EmptySD3LatentImageAlso runs in Draw Things (import as a Z-Image model) and anything else that supports Z-Image.## Recommended settings- Steps: 8–20 (quality range 80–30)- CFG: 1–4 (sweet spot ≈ 1–3; real CFG and a negative prompt work)- Sampler / scheduler: <code>res_multistep</code> / <code>simple</code> (euler also works)- Resolution: native around 1024×1024- 4024x4024 ---## 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.- INT8 note: <code>fullgreed_i8_plain_comfy</code> uses ComfyUI's native quantization format — no custom nodes or CUDA extensions, works on ComfyUI Cloud. It is not the same as older int8 builds that required a custom node to decode.## Credits &amp; license- Base model: Z-Image (Omni-Base) by Tongyi-MAI, Alibaba Group — see the [Z-Image technical report (arXiv 2511.22699)](<a target="_blank" rel="ugc" href="https://arxiv.org/abs/2511.22699">https://arxiv.org/abs/2511.22699</a>). This fine-tune inherits the base model's license terms.- Text encoder: Qwen3-4B (Alibaba). VAE: Flux VAE (Black Forest Labs).Please generate responsibly. Do not use this model to create images of real people without their consent.

greed_Int8.safetensors

Greed int8

Greed Bf16

v3 full

a z image base fine-tuned model I made for fun and it performs incredibly well.This model is intended for creative and artistic use. You are responsible for all content you generate.

Files with SHA256: 18326ab7269619d3511ed472b9e2858b7d556c949c029e4dcbe4c2a1bc5cffc7