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    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.

    Description

    # 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 |

    |---|---|---|---|

    | fullgreed_i8_plain_comfy.safetensors | 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 |

    | fullgreed_f16.safetensors | 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: qwen_3_4b.safetensors → CLIPLoader, type *lumina2**

    - VAE: ae.safetensors (Flux 16-channel VAE)

    - Diffusion model: load via Load Diffusion Model (UNETLoader)

    - 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 (quality range 80–30)

    - CFG: 1–4 (sweet spot ≈ 1–3; real CFG and a negative prompt work)

    - Sampler / scheduler: res_multistep / simple (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: fullgreed_i8_plain_comfy 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 & 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). 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.

    FAQ

    Comments (1)

    xpnrtJun 11, 2026
    CivitAI

    can we have bf16 or if not, can you at least share an int8 version made with https://github.com/BobJohnson24/ComfyUI-INT8-Fast ; it is really fast on certain gpus

    Checkpoint
    ZImageBase

    Details

    Downloads
    288
    Platform
    CivitAI
    Platform Status
    Available
    Created
    5/31/2026
    Updated
    7/10/2026
    Deleted
    -

    Files

    alphgreed_fullgreedBaseV10.json

    Mirrors

    money_vae_f16.safetensors

    Available On (1 platform)

    Same model published on other platforms. May have additional downloads or version variants.