Full Fine-Tune • Rich Aesthetics • Strong Diversity • Full Negative Prompt Support BF16 & FP8 & GGUF & AIO • Natural Language Prompts • 8GB VRAM
🖼️ Preview Gallery
Z-Anime preview 1
Z-Anime preview 2
Z-Anime preview 3
Z-Anime preview 4
Z-Anime preview 5
Z-Anime preview 6
Z-Anime preview 7
Z-Anime preview 8
Z-Anime preview 9
✨ What is Z-Anime?
Z-Anime is a full fine-tune of Alibaba's Z-Image Base architecture — not a LoRA merge, but a fully trained anime-focused model family built from the ground up.
Built on the S3-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 full Z-Anime family:
Variant
Focus
Best For
🎌 Z-Anime Base
Highest quality
Final renders, full control
⚡ Z-Anime Distill-8-Step
Speed + quality balance
Everyday generation
🚀 Z-Anime Distill-4-Step
Maximum speed
Fast iteration, batches
📦 GGUF Variants
Lower memory usage
Low VRAM / CPU / AMD-friendly workflows
📦 AIO Variants
Single-file convenience
Easy ComfyUI setup
🐍 Diffusers Folder
from_pretrained() ready
Python pipelines, further fine-tuning
🎯 Key Features
✅ Full fine-tune on Z-Image Base — not a 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)
🗺️ Z-Anime Roadmap
✅ Released
🎌 Z-Anime Base
Full fine-tune on Z-Image Base — BF16 & FP8
⚡ Z-Anime Distill-8-Step
BF16 & FP8 — fast anime generation in 8 steps, CFG 1.0
All-in-one checkpoints with image model + VAE + Text Encoder integrated in a single file.
Available for Base, Distill-4-Step and Distill-8-Step — each in BF16 & FP8.
🧩 VAE & Text Encoder
The required VAE (ae.safetensors) and Text Encoder (qwen_3_4b.safetensors) are also included in this repository for users running the standard (non-AIO) variants.
🐍 Diffusers Folder
The full Diffusers-format folder (diffusers/) is included — drop-in compatible with ZImagePipeline.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! 🎌
📦 Versions Overview
🟢 BF16 (~12GB)
Maximum precision. BFloat16 format with minimal quality compromise. Best for final renders, careful work, and LoRA training.
🟡 FP8 (~6GB)
Recommended for most users. Smaller files, faster downloads, and excellent quality with only minor tradeoffs compared to BF16.
🔵 GGUF
Optimized for lightweight inference setups, especially useful for low VRAM, CPU inference, or alternative backends.
🟣 AIO
All-in-one checkpoints with image model + Text Encoder + VAE integrated into a single file for the easiest setup. Available for Base, Distill-4-Step and Distill-8-Step.
🎌 Z-Anime Base
The foundation of the Z-Anime family.
A full fine-tune with the highest quality ceiling, the widest creative range, and full negative prompt support.
Recommended Settings
yaml
1steps: 28-502cfg: 3.0-5.0# up to 9.0 possible3sampler: euler_ancestral
4scheduler: beta
5negative_prompt: strongly recommended
CFG 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 have full effect on Z-Anime Base and are highly recommended.
⚡ Z-Anime Distill-8-Step
The sweet spot of the family.
Distilled from Z-Anime Base, this version delivers strong anime results in just 8 steps while keeping most of the quality.
Recommended Settings
yaml
1steps:82cfg:1.0# max ~1.53sampler: euler_ancestral
4scheduler: beta
5negative_prompt: limited effect
CFG Guide
Best at CFG 1.0
Small increases to 1.3–1.5 are possible
Do not go above 1.5 — artifacts may appear
Negative prompts have only limited effect at this distillation level. If your workflow includes ConditioningZeroOut, prefer that instead of a large negative prompt.
🚀 Z-Anime Distill-4-Step
The fastest Z-Anime variant.
Built for maximum throughput — ideal for rapid prototyping, quick batch generation, and speed-focused workflows.
Recommended Settings
yaml
1steps:42cfg:1.0# max ~1.53sampler: euler_ancestral
4scheduler: beta
5negative_prompt: limited effect
Tips for 4-Step
Stay at CFG 1.0 for the most stable results
Put the most important visual details early in the prompt
An optional upscaler such as hires fix or SeedVR2 can help recover fine detail
📐 Resolution Guide
Use Case
Resolution
Portrait / character art
832 × 1216
Landscape / scenes / backgrounds
1216 × 832
Square / general purpose
1024 × 1024
Tall / full body / wallpaper
768 × 1344
Cinematic / wide scenes
1920 × 1088
Detailed portraits
1024 × 1536
Supported range: approximately 512 × 512 to 2048 × 2048, any aspect ratio.
All main variants are designed to run on 8GB VRAM.
💡 Prompting Guide
Natural language works best — not tag lists.
✅ 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.
Detailed anime portrait of [character], soft rim lighting, expressive eyes with detailed reflections, fine hair strands, clean linework, professional anime illustration quality.
1ComfyUI/models/clip/
2└── qwen_3_4b-bf16.safetensors # default (Z-Image standard, BF16)
3 or
4└── qwen_3_4b-fp8.safetensors # default (Z-Image standard, FP8)
5 or
6└── qwen_3_4b-engineer-v4-bf16.safetensors # alternative (Engineer V4, BF16)
7 or
8└── 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 .safetensors file (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 by BennyDaBall, drop-in compatible. Often produces more varied outputs from the same seed. See Credits below for the original repo.
VAE
text
1ComfyUI/models/vae/
2└── ae.safetensors
AIO variants
For the AIO versions, you only need the single checkpoint file — no extra VAE or Text Encoder required:
Use a standard Checkpoint Loader — no extra CLIP or VAE loading required.
📦 Custom Nodes
rgthree-comfy
ComfyUI-Lora-Manager
ComfyUI-GGUF(only for the GGUF variants)
ComfyUI-SeedVR2_VideoUpscaler(optional, only for SeedVR2 upscale)
🐍 Using the Diffusers Folder
For Python users, the full Diffusers-format folder is included under diffusers/ and can be loaded directly with the subfolder argument:
python
1import torch
2from diffusers import ZImagePipeline
34pipe = ZImagePipeline.from_pretrained(5"SeeSee21/Z-Anime",6 subfolder="diffusers",7 torch_dtype=torch.bfloat16,8).to("cuda")910image = pipe(11 prompt="A young anime girl with long silver hair and golden eyes, "12"shrine maiden outfit, sunlit bamboo forest, cherry blossoms, "13"professional anime illustration, fine line work.",14 num_inference_steps=40,15 guidance_scale=4.0,16).images[0]1718image.save("z-anime-output.png")
This format is also a clean starting point for further fine-tuning (LoRA or full fine-tune) with frameworks like OneTrainer, diffusers, or kohya-ss.
🧩 Official Workflow
Z-Anime Workflow
A ready-to-use ComfyUI workflow that supports all variants (Base / Distill-8 / Distill-4, BF16 / FP8 / GGUF / AIO) is included in workflows/Z-Anime-Workflow-v1.json.
It includes:
📦 Model switch (Diffusion / GGUF / AIO loaders — toggle one at a time)
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. 🎌
