SeeSee21/Z-Anime · Hugging Face

Source: https://huggingface.co/SeeSee21/Z-Anime

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%8E%8C-z-anime–full-anime-fine-tune-on-z-image-base🎌 Z-Anime | Full Anime Fine-Tune on Z-Image Base

Full Fine-Tune • Rich Aesthetics • Strong Diversity • Full Negative Prompt Support BF16 & FP8 & GGUF & AIO • Natural Language Prompts • 8GB VRAM

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%96%BC%EF%B8%8F-preview-gallery🖼️ Preview Gallery

https://huggingface.co/SeeSee21/Z-Anime#%E2%9C%A8-what-is-z-anime✨ What is Z-Anime?

Z-Animeis a full fine-tune of Alibaba’sZ-Image Basearchitecture —not a LoRA merge, but a fully trained anime-focused model family built from the ground up.

Built on theS3-DiT (Single-Stream Diffusion Transformer, 6B parameters), Z-Anime inherits the strong foundation of Z-Image Base: rich diversity, strong controllability, full negative prompt support, and a high ceiling for fine-tuning — now adapted for anime-style generation.

This repository contains the fullZ-Anime family:

VariantFocusBest For🎌Z-Anime BaseHighest qualityFinal renders, full control⚡Z-Anime Distill-8-StepSpeed + quality balanceEveryday generation🚀Z-Anime Distill-4-StepMaximum speedFast iteration, batches📦GGUF VariantsLower memory usageLow VRAM / CPU / AMD-friendly workflows📦AIO VariantsSingle-file convenienceEasy ComfyUI setup🐍Diffusers Folderfrom\_pretrained\(\)readyPython pipelines, further fine-tuning

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%8E%AF-key-features🎯 Key Features

• ✅ Full fine-tune on Z-Image Base —nota LoRA merge
• ✅ Rich anime aesthetics with strong style diversity
• ✅ Natural language prompting — works best with descriptive prompts, not tag lists
• ✅ High diversity across characters, poses, compositions, and layouts
• ✅ LoRA training ready — strong base for further fine-tuning
• ✅ Partially NSFW capable
• ✅ 8GB VRAM compatible
• ✅ GGUF variants available
• ✅ AIO variants available (Base, 4-Step, 8-Step)

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%97%BA%EF%B8%8F-z-anime-roadmap🗺️ Z-Anime Roadmap

https://huggingface.co/SeeSee21/Z-Anime#%E2%9C%85-released✅ Released

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%8E%8C-z-anime-base🎌 Z-Anime Base

Full fine-tune on Z-Image Base —BF16 & FP8

https://huggingface.co/SeeSee21/Z-Anime#%E2%9A%A1-z-anime-distill-8-step⚡ Z-Anime Distill-8-Step

BF16 & FP8— fast anime generation in8 steps,CFG 1.0

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%9A%80-z-anime-distill-4-step🚀 Z-Anime Distill-4-Step

BF16 & FP8— ultra-fast anime generation in4 steps,CFG 1.0

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%A6-gguf-variants📦 GGUF Variants

Available forlow VRAM,CPU inference, andAMD-friendlyworkflows.

• Z-Anime-Base-Q8_0— Q8_0 quantization (~6.73 GB)
• Z-Anime-Base-Q4_K_S— Q4_K_S quantization (~4.2 GB)

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%A6-aio-variants📦 AIO Variants

All-in-one checkpoints withimage model + VAE + Text Encoder integratedin a single file. Available forBase,Distill-4-StepandDistill-8-Step— each inBF16 & FP8.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%A7%A9-vae–text-encoder🧩 VAE & Text Encoder

The requiredVAE(ae\.safetensors) andText Encoder(qwen\_3\_4b\.safetensors) are also included in this repository for users running the standard (non-AIO) variants.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%90%8D-diffusers-folder🐍 Diffusers Folder

The fullDiffusers-format folder(diffusers/) is included — drop-in compatible withZImagePipeline\.from\_pretrained\(\)for Python users who want to run inference outside ComfyUI or use Z-Anime as a starting point for further fine-tuning.

More updates coming — follow to stay notified! 🎌

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%A6-versions-overview📦 Versions Overview

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%9F%A2-bf16-12gb🟢 BF16 (~12GB)

Maximum precision.BFloat16format with minimal quality compromise. Best for final renders, careful work, and LoRA training.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%9F%A1-fp8-6gb🟡 FP8 (~6GB)

Recommended for most users. Smaller files, faster downloads, and excellent quality with only minor tradeoffs compared to BF16.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%94%B5-gguf🔵 GGUF

Optimized for lightweight inference setups, especially useful for low VRAM, CPU inference, or alternative backends.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%9F%A3-aio🟣 AIO

All-in-one checkpoints withimage model + Text Encoder + VAE integratedinto a single file for the easiest setup. Available for Base, Distill-4-Step and Distill-8-Step.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%8E%8C-z-anime-base-1🎌 Z-Anime Base

The foundation of the Z-Anime family.

A full fine-tune with thehighest quality ceiling, thewidest creative range, andfull negative prompt support.

https://huggingface.co/SeeSee21/Z-Anime#recommended-settingsRecommended Settings

steps: 28-50
cfg: 3.0-5.0   # up to 9.0 possible
sampler: euler_ancestral
scheduler: beta
negative_prompt: strongly recommended

https://huggingface.co/SeeSee21/Z-Anime#cfg-guideCFG Guide

• 3.0–5.0→ sweet spot for balanced quality and creativity
• 5.0–7.0→ tighter prompt adherence
• 7.0–9.0→ maximum control, but watch for oversaturation
• Above 9.0→ not recommended

Negative prompts havefull effecton Z-Anime Base and are highly recommended.

https://huggingface.co/SeeSee21/Z-Anime#%E2%9A%A1-z-anime-distill-8-step-1⚡ Z-Anime Distill-8-Step

The sweet spot of the family.

Distilled from Z-Anime Base, this version delivers strong anime results in just8 stepswhile keeping most of the quality.

https://huggingface.co/SeeSee21/Z-Anime#recommended-settings-1Recommended Settings

steps: 8
cfg: 1.0   # max ~1.5
sampler: euler_ancestral
scheduler: beta
negative_prompt: limited effect

https://huggingface.co/SeeSee21/Z-Anime#cfg-guide-1CFG Guide

• Best atCFG 1.0
• Small increases to1.3–1.5are possible
• Donotgo above1.5— artifacts may appear

Negative prompts have onlylimited effectat this distillation level. If your workflow includesConditioningZeroOut, prefer that instead of a large negative prompt.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%9A%80-z-anime-distill-4-step-1🚀 Z-Anime Distill-4-Step

The fastest Z-Anime variant.

Built formaximum throughput— ideal for rapid prototyping, quick batch generation, and speed-focused workflows.

https://huggingface.co/SeeSee21/Z-Anime#recommended-settings-2Recommended Settings

steps: 4
cfg: 1.0   # max ~1.5
sampler: euler_ancestral
scheduler: beta
negative_prompt: limited effect

https://huggingface.co/SeeSee21/Z-Anime#tips-for-4-stepTips for 4-Step

• Stay atCFG 1.0for the most stable results
• Put the most important visual detailsearlyin the prompt
• An optional upscaler such as hires fix or SeedVR2 can help recover fine detail

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%90-resolution-guide📐 Resolution Guide

Use CaseResolutionPortrait / character art832 × 1216Landscape / scenes / backgrounds1216 × 832Square / general purpose1024 × 1024Tall / full body / wallpaper768 × 1344Cinematic / wide scenes1920 × 1088Detailed portraits1024 × 1536 Supported range:approximately512 × 512 to 2048 × 2048, any aspect ratio. All main variants are designed to run on8GB VRAM.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%92%A1-prompting-guide💡 Prompting Guide

Natural language works best — not tag lists.

https://huggingface.co/SeeSee21/Z-Anime#%E2%9C%85-good✅ Good

A young anime girl with long silver hair and golden eyes, wearing a traditional shrine maiden outfit with white haori and red hakama. She stands in a sunlit bamboo forest, cherry blossoms falling softly around her. Warm afternoon light filtering through the trees, detailed fabric shading, expressive face, calm serene expression, high quality anime illustration with fine line work.

https://huggingface.co/SeeSee21/Z-Anime#%E2%9D%8C-avoid❌ Avoid

anime girl, silver hair, shrine maiden, bamboo, cherry blossom, warm light

https://huggingface.co/SeeSee21/Z-Anime#character-portraitsCharacter Portraits

Detailed anime portrait of [character], soft rim lighting, expressive eyes with detailed reflections, fine hair strands, clean linework, professional anime illustration quality.

https://huggingface.co/SeeSee21/Z-Anime#action-scenesAction Scenes

Dynamic anime [scene], dramatic angle, motion energy, speed lines, particle effects, cinematic composition, detailed shading, high quality anime art.

https://huggingface.co/SeeSee21/Z-Anime#backgrounds–landscapesBackgrounds & Landscapes

Anime [location] at [time of day], [lighting], [atmosphere], beautiful background art, wallpaper quality, highly detailed environment.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%94%A7-installation🔧 Installation

https://huggingface.co/SeeSee21/Z-Anime#step-1–download-the-version-you-wantStep 1 — Download the version you want

Choose between:

• Standard / Distill modelsinBF16orFP8(+ VAE + Text Encoder)
• GGUF variantsfor low VRAM / CPU / AMD-friendly inference (+ VAE + Text Encoder)
• AIO variantsfor single-file convenience (no extra VAE / Text Encoder needed)

https://huggingface.co/SeeSee21/Z-Anime#step-2–place-the-filesStep 2 — Place the files

https://huggingface.co/SeeSee21/Z-Anime#standard-bf16–fp8-modelsStandard BF16 / FP8 models

ComfyUI/models/diffusion_models/
├── z-anime-base-bf16.safetensors
├── z-anime-base-fp8.safetensors
├── z-anime-distill-8step-bf16.safetensors
├── z-anime-distill-8step-fp8.safetensors
├── z-anime-distill-4step-bf16.safetensors
└── z-anime-distill-4step-fp8.safetensors

https://huggingface.co/SeeSee21/Z-Anime#gguf-variantsGGUF variants

ComfyUI/models/unet/
├── z-anime-base-q8_0.gguf
└── z-anime-base-q4_k_s.gguf

https://huggingface.co/SeeSee21/Z-Anime#text-encoderText Encoder

Two text encoders are included — pickone:

ComfyUI/models/clip/
└── qwen_3_4b-bf16.safetensors          # default (Z-Image standard, BF16)
   or
└── qwen_3_4b-fp8.safetensors           # default (Z-Image standard, FP8)
   or
└── qwen_3_4b-engineer-v4-bf16.safetensors   # alternative (Engineer V4, BF16)
   or
└── qwen_3_4b-engineer-v4-fp8.safetensors    # alternative (Engineer V4, FP8)

• Default (qwen\_3\_4b\-\*)— the standard Z-Image text encoder, repackaged as a single\.safetensorsfile (BF16 + FP8). This is what the model was trained against.
• Engineer V4 (qwen\_3\_4b\-engineer\-v4\-\*)— an alternative full fine-tune of the Z-Image text encoder byBennyDaBall, drop-in compatible. Often produces more varied outputs from the same seed. SeeCreditsbelow for the original repo.

https://huggingface.co/SeeSee21/Z-Anime#vaeVAE

ComfyUI/models/vae/
└── ae.safetensors

https://huggingface.co/SeeSee21/Z-Anime#aio-variantsAIO variants

For the AIO versions, you only need the single checkpoint file — no extra VAE or Text Encoder required:

ComfyUI/models/checkpoints/
├── z-anime-base-aio-bf16.safetensors
├── z-anime-base-aio-fp8.safetensors
├── z-anime-distill-8step-aio-bf16.safetensors
├── z-anime-distill-8step-aio-fp8.safetensors
├── z-anime-distill-4step-aio-bf16.safetensors
└── z-anime-distill-4step-aio-fp8.safetensors

https://huggingface.co/SeeSee21/Z-Anime#step-3–load-in-comfyuiStep 3 — Load in ComfyUI

https://huggingface.co/SeeSee21/Z-Anime#for-standard-bf16–fp8-versionsFor standard BF16 / FP8 versions

Use:

• Load Diffusion Modelfor the model file
• CLIP Loaderfor the text encoder
• VAE Loaderfor the VAE

https://huggingface.co/SeeSee21/Z-Anime#for-gguf-versionsFor GGUF versions

• Load theGGUF model from themodels/unet/folder
• Use the sameCLIPandVAEfiles as above

https://huggingface.co/SeeSee21/Z-Anime#for-aio-versionsFor AIO versions

Use a standardCheckpoint Loader— no extra CLIP or VAE loading required.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%A6-custom-nodes📦 Custom Nodes

• rgthree-comfy
• ComfyUI-Lora-Manager
• ComfyUI-GGUF*(only for the GGUF variants)*
• ComfyUI-SeedVR2_VideoUpscaler*(optional, only for SeedVR2 upscale)*

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%90%8D-using-the-diffusers-folder🐍 Using the Diffusers Folder

For Python users, the full Diffusers-format folder is included underdiffusers/and can be loaded directly with thesubfolderargument:

import torch
from diffusers import ZImagePipeline

pipe = ZImagePipeline.from_pretrained(
    "SeeSee21/Z-Anime",
    subfolder="diffusers",
    torch_dtype=torch.bfloat16,
).to("cuda")

image = pipe(
    prompt="A young anime girl with long silver hair and golden eyes, "
           "shrine maiden outfit, sunlit bamboo forest, cherry blossoms, "
           "professional anime illustration, fine line work.",
    num_inference_steps=40,
    guidance_scale=4.0,
).images[0]

image.save("z-anime-output.png")

This format is also a clean starting point for further fine-tuning (LoRA or full fine-tune) with frameworks likeOneTrainer,diffusers, orkohya-ss.

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%A7%A9-official-workflow🧩 Official Workflow

A ready-to-use ComfyUI workflow that supportsall variants(Base / Distill-8 / Distill-4, BF16 / FP8 / GGUF / AIO) is included inworkflows/Z\-Anime\-Workflow\-v1\.json.

It includes:

• 📦 Model switch (Diffusion / GGUF / AIO loaders — toggle one at a time)
• 📖 Optional LoRA loader
• ✍️ Positive + Negative prompt nodes (with default anime negative)
• 📐 Resolution presets
• 🎨 Generate + 🔼 Optional 1.5× upscale with side-by-side compare
• 📚 Built-in MarkdownNote guide with settings per variant

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%81-repository-structure📁 Repository Structure

Z-Anime/
├── README.md
├── config.json
│
├── diffusion_models/
│   ├── z-anime-base-bf16.safetensors
│   ├── z-anime-base-fp8.safetensors
│   ├── z-anime-distill-8step-bf16.safetensors
│   ├── z-anime-distill-8step-fp8.safetensors
│   ├── z-anime-distill-4step-bf16.safetensors
│   └── z-anime-distill-4step-fp8.safetensors
│
├── gguf/
│   ├── z-anime-base-q8_0.gguf
│   └── z-anime-base-q4_k_s.gguf
│
├── aio/
│   ├── z-anime-base-aio-bf16.safetensors
│   ├── z-anime-base-aio-fp8.safetensors
│   ├── z-anime-distill-8step-aio-bf16.safetensors
│   ├── z-anime-distill-8step-aio-fp8.safetensors
│   ├── z-anime-distill-4step-aio-bf16.safetensors
│   └── z-anime-distill-4step-aio-fp8.safetensors
│
├── text_encoder/
│   ├── qwen_3_4b-bf16.safetensors                  # default
│   ├── qwen_3_4b-fp8.safetensors                   # default
│   ├── qwen_3_4b-engineer-v4-bf16.safetensors      # alternative (BennyDaBall)
│   └── qwen_3_4b-engineer-v4-fp8.safetensors       # alternative (BennyDaBall)
│
├── vae/
│   └── ae.safetensors
│
├── diffusers/
│   ├── model_index.json
│   ├── scheduler/
│   ├── tokenizer/
│   ├── text_encoder/
│   ├── transformer/   (sharded safetensors + index)
│   └── vae/
│
├── images/
│   ├── cover.png
│   ├── workflow-cover.png
│   ├── workflow-overview.png
│   ├── 1.png
│   ├── 2.png
│   ├── 3.png
│   ├── 4.png
│   ├── 5.png
│   ├── 6.png
│   ├── 7.png
│   ├── 8.png
│   └── 9.png
└── workflows/
    └── Z-Anime-Workflow-v1.json

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%93%88-version-history📈 Version History

https://huggingface.co/SeeSee21/Z-Anime#v10–initial-releasev1.0 — Initial Release

• Z-Anime Basereleased inBF16 & FP8
• Z-Anime Distill-8-Stepreleased inBF16 & FP8
• Z-Anime Distill-4-Stepreleased inBF16 & FP8
• GGUF variants added- Z-Anime-Base-Q8_0— Q8_0 quantization (~6.73 GB) - Z-Anime-Base-Q4_K_S— Q4_K_S quantization (~4.2 GB)
• AIO variants added— Base, Distill-4-Step and Distill-8-Step (each in BF16 & FP8)
• VAE(ae\.safetensors) andText Encoder(qwen\_3\_4b\.safetensors) included
• Optimized foreuler_ancestral,euler + beta, and simple practical use across the family

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%94%97-links🔗 Links

• CivitAI Page:civitai.red/models/2483351
• Base Model:Tongyi-MAI/Z-Image
• Author:SeeSee21 on Hugging Face

https://huggingface.co/SeeSee21/Z-Anime#%F0%9F%99%8F-credits🙏 Credits

• **Base Architecture:**Tongyi Lab (Alibaba) — Z-Image
• **Fine-Tune:**SeeSee21
• **License:**Apache 2.0
• **Architecture:**S3-DiT (Single-Stream Diffusion Transformer, 6B parameters)
• Base Model:Tongyi\-MAI/Z\-Image
• Engineer V4 Text Encoder:BennyDaBall/Qwen3\-4b\-Z\-Image\-Engineer\-V4— full fine-tune with SMART training, included as alternative text encoder

https://huggingface.co/SeeSee21/Z-Anime#%E2%9D%A4%EF%B8%8F-notes❤️ Notes

Z-Anime is an experimental anime-focused model family built to explore what a full fine-tune on Z-Image Base can achieve in this space.

It is already strong for anime aesthetics, character work, and fast iteration, and future versions will continue to improve diversity, character handling, prompting flexibility, and overall quality.

Z-Anime — anime at its finest, powered by Z-Image Base. 🎌