RedCraft-红潮
做好工具人 服务艺术家
Forever in memory of METAFILM Studio founder Mr. Yuan Bo
2026.1.1 VX 新规执行，请移步TG： https://t.me/+Ka2NhoUF5W1iMDRl
download from the "Files" list below the "Details" on the right side of this page>>
ZImage DPO “AGILE” Now Uploading 08/03/2026 女神节祝福🌸
On this Day, may every woman feel the strength, grace, and boundless potential that lives within her. Thank you for your courage, your kindness, your resilience, and the countless ways you make the world brighter and better. Here's to equality, empowerment, joy, and endless possibilities—today and every day. Happy International Women's Day🌸
ZIDistilled FUN “AGILE” Now Released
Special thanks to the VideoXFUN team for releasing the groundbreaking Zimage Distilled Adapter 2603. By incorporating this latest update, AGILE achieves a refined balance between speed, diversity, and visual richness — unlocking more creative freedom while maintaining exceptional efficiency.
Agility in Motion, Diversity in Depth
The brand-new ZImage FUN “AGILE” is built upon the cutting-edge ZIB acceleration framework. We deliberately reduced DPO & Distilled weight to preserve greater stochastic freedom, combined with the most recent training datasets, resulting in dramatically increased output variety, richer content details, and more imaginative compositions without sacrificing core stability.
For the first time, AGILE reaches a true quality parity challenge against the flagship “ZImage TURBO” in terms of overall image fidelity and sharpness — even in complex scenes — while delivering faster iteration and superior responsiveness.
Key highlights:
True ZIT-level unlocked — photorealistic lighting, textures, and material rendering that now rivals or approaches ZImage TURBO quality, even at standard step counts.
Enhanced diversity & content richness — DPO + Newest datasets = more varied poses, styles, atmospheres, intricate details, and unexpected creative sparks in every generation.
ZIB ecosystem ignition — exceptional native compatibility with ZIB-series LoRAs; your existing and future LoRAs now align faster, reproduce more faithfully, and shine brighter than ever before — officially kicking off the full ZIB LoRA era.
Agile workflows — seamless hybrid use with Klein 9B for refinement, ensemble boosting, or rapid prototyping; near-instant LoRA response with preserved high-entropy creativity.
Every generation is a step toward freer, bolder imagination.
欢迎体验 ZImage FUN “AGILE” —— 速度如洪，创意如潮。
Welcome to ZImage FUN “AGILE” — where agility meets abundance, and your ideas finally run wild with unmatched fidelity and freedom.
ZImage DPO “Veris” Now Released 03/03/2026 元宵节快乐
I have uploaded more quantification and export “Veris” LoRA to HF repo. to avoid causing confusion for users in the community：
https://huggingface.co/GuangyuanSD/Z-Image-Distilled
版本太多网友容易迷糊，我导出了更多量化规格和 “Veris” LoRA 版本，已发布抱脸仓库。
Special thanks to @Fok for providing the Flow-DPO technical adaptation. By skillfully integrating the training philosophy of Direct Preference Optimization (DPO) into the distillation weights, the Zimage distilled model achieves a major leap in lighting, color fidelity, and material authenticity — more natural light & shadow, more believable colors, and details that hold up under scrutiny.
特别感谢 @Fok 饼儿佬提供了Flow-DPO技术适配。通过巧妙地将直接偏好优化（DPO）的技术理念融入蒸馏权重，Zimage 蒸馏模型在光照、色彩保真度和材质真实性方面实现了重大飞跃——更自然的光影效果、更逼真的色彩，以及经得起仔细审查的细节。
The following example shows a comparison between ZIT and Flow DPO, intended to illustrate the effect of DPO, rather than a direct demonstration of ZIB Distilled
Speed of Truth, Fidelity of Flow
真实且极速，用忠诚在流动
The all-new ZIDPO “Veris” is powered by the latest-generation ZIB acceleration engine. Building on the RedZDX training data, we further distilled a more efficient, more refined Zimage-based model.
Now — solid, highly realistic generations in just 8 steps.（Better LoRAs alignment）
仅需8步即可生成更有层次感、高度逼真的图像。（LoRa对齐效果更佳）
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Key highlights:
Realism-first prototyping — near-zero latency for LoRAs, with lighting and color already very close to final training targets
High-entropy stochastic pre-sampling — delivers fast, high-quality realistic initial noise for ZImage pipelines
Hybrid realism workflows — seamless integration with Klein 9B for cascaded refinement or ensemble boosting, pushing visual fidelity and consistency even higher
Every step toward truth deserves full commitment.
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欢迎体验ZIDPO“Veris”——您的LoRa训练结果不再只是“相似”，而是真正得到“复现”。
Welcome to experience ZImage DPO “Veris” — where your LoRAs generations are no longer just “similar”, but truly are.
同时，欢迎体验在 ZImage 或 Turbo 模型上直接加载 DPO LoRA Adapter：
抱脸（HF） https://huggingface.co/F16/z-image-turbo-flow-dpo
魔搭（境内）
Redcraft DX3 ZIB🟥 Distilled models Zoo：
Full Model bf16 (19.11 GB)<- ComfyUI All-in-One Checkpoint BF16
Pruned Model BF16 (11.46 GB) <- ComfyUI Diffusion BF16 精度模型权重
Pruned Model fp8 (6.75 GB) <- ComfyUI Diffusion Scaled FP8 Mixed 混合精度
Pruned Model nf4 (6.73 GB) <- NVFP4 Mixed 混合精度（BLACKWELL 50系加速）
Training Data (3.75 KB) <- ComfyUI Simple Hybrid Workflow 简易混合采样工作流
Redcraft DX3 ZIB🟥 Distilled LoRA Adapter 02/19/2026
Additionally, I've exported Redcraft DX3 ZIB Distilled LoRA in Rank-256 format. The LoRA weight can be adjusted to adapt it to various ZIB fine-tune models, fully compatible with the Z-Image(non-turbo) base model.
Full Model fp16 (1.06 GB) <- 可以通过这里直接下载 LoRA 版本
[ZI Distilled HF repo.](https://huggingface.co/GuangyuanSD/Z-Image-Distilled)
上面是 Redcraft DX3 ZIB Distilled 导出为 Rank256 的LoRA版本，可以调整权重强度用于各种微调ZIT版本, 适配于 Z-Image(non-turbo) base 基底模型.
Redcraft DX3 ZIB🟥 Distilled LoRA adaptation models Zoo：
Z-Image-Base-GGUF <- Z-Image Base GGUF 量化模型
Z-Image Base <- Z-Image Base & TE (FP8/FP4) 模型
Z-Image Base FP8Mixed <- Z-Image Base FP8 混合精度模型
Text Encoder (ClipLoader use) <- Qwen3 4b FP16 文本编码器
Abliterated Huihui Qwen3 4B v2 (Q_8 GGUF) <- Z-Image Uncensored TE 文本编码器
VAE (Flux.1 16C VAE) <- 标准的 Flux.1 16 通道 VAE
Or download from the "Files" list below the "Details" on the right side of this page>>
Also available in NVFP4 quantized format, optimized for acceleration on Blackwell architecture GPUs.
Double speed, Half resources.
（ like RTX50XX, PRO6000, B200, and others ）
Verify environment is my ComfyUI 0.11
Also supports non-50 series GPUs (automatic 16-bit operation)
DF11 Lossless Compression RedZDX V3 came out! 2/15/2026
learn more: Dynamic-length Float (DFloat11)
[HF] mingyi456/Z-Image-Distilled-DF11-ComfyUI
Z-Image-Distilled v3 (RedZ DX3) 2/11/2026
Thanks to @Bubbliiiing VideoX-Fun&Alibaba-PAI Provided us with a more efficient distillation solution
Speed of Light, Power of Flow: The new ZID v3 "Lucis" is powered by the latest ZIB acceleration. Building on ZID v2 trainning sets, we've distilled a more efficient Zimage-based RedDX3. Now, in just 5 steps, you get solid results.
Rapid Prototyping: Test LoRA training hypotheses instantly with 'near-zero' latency.
Stochastic Pre-sampling: Serve as a high-speed, high-entropy source for ZiTurbo pipelines.
Hybrid Workflows: Pair seamlessly with Klein 9B for cascaded refinement or ensemble generation.
inference cfg: 1.0-1.5（建议1.0）
inference steps: 5（5-15步）
sampler / scheduler: Euler / simple
Welcome to the era of instant creativity. Welcome to 'Lucis'.
Preview images generated by Z-Image Hybrid Workflow of Distilled V3+Moody MIX V7(ZIT finetune) ，Just for showing the style difference between ZID(RedZDX3) and ZIT(fine-tunning) , no ranking intended =)
[ L = 'ZID v3', R = 'ZIT ft' ]
演示例图使用 ZIDistilled V3+Moody MIX V7 混合工作流程，不用做排名对比:
中国境内 [ modelscope ]AiMETATRON/Z-Image-Distilled | [ HF ] GuangyuanSD/Z-Image-Distilled
Z-Image-Distilled v2 (RedZ DX2) 2026/2/5
To a certain extent, the problem of ZIB color deviation has been reduced, but it is recommended to adjust the color appropriately according to the art style
inference cfg: 1.0（建议1.0）
inference steps: 10（10-15步）
sampler / scheduler: Euler / simple
感谢🙏这位作者完成了ZIB的FP8mixed混合量化方案：
https://huggingface.co/pachiiahri
已上传FP8版本，请给这位作者点赞👍
以上是FP8 scale&mixed 直出工作流（请不要再说我造假，我的所有例图工作流都是开放的）
精度混合方案来自 https://civitai.com/models/2172944/z-image-fp8
Comparison of RedCraft Zimages（bf16）:
The art style leans towards realism
Retains ZIB's creative ability and reduces the collapse of Human anatomy.
REDZiBDX1·Demo accelerated Base-Model CFG1
Distilled form ZImage（non-turbo）base-model bf16
Now we have the LoRA version, thank to @anyMODE for Extract
in-site link https://civitai.com/models/2359857/z-image-base-distilled-lora-or-extracted
Pruned Model bf16 (11.46 GB) = Z-Image-Distilled / RedZDX-ZIB-Distilled-nocfg-10steps-BF16-Diffusion-models.safetensors 单独的扩散模型文件bf16剪裁精度
Full Model fp8 (16.87 GB) = Z-Image-Distilled / RedZDX-ZIB-Distilled-nocfg-10steps-FP8mixed-AIO-Checkpoints.safetensors 完整的Checkpoints（含TE/VAE）
Pruned Model fp8 (5.73 GB) = Z-Image-Distilled / RedZDX-ZIB-Distilled-nocfg-10steps-fp8-e4m3fn-Diffusion-models.safetensors 单独的扩散模型文件fp8剪裁精度及e4m3规格
Training Data (5.6 KB) = Z-Image-Distilled ComfyUI workflows 我自己使用的简易测试工作流
VAE (319.77 MB) = Flux.1 VAE ae.sft 常规的Flux.1 VAE
例图包含完整出图参数，点击右下角❕就可以看到，同时点击 COMFY Nodes 就可以复制源图工作流，并可以在ComfyUI界面中 Ctrl+V 粘贴至新的工作区。
All sample images contain full generation metadata.
Click the ❕ button (bottom-right) to view the complete parameters. Click COMFY Nodes to copy the original workflow JSON, then paste it (Ctrl+V) into a new ComfyUI workspace.
Z-Image-Distilled
本模型为基于 Z-Image 源版本（非Turbo）的直接蒸馏加速版，旨在测试Z-Image（non-turbo）版本上训练的LoRA效果，并显著提高推理/测试速度。模型完全没有融入Z-Image-Turbo的任何权重与风格，属于基于Z-Image的纯血版本，较好地保持了原版Z-Image的适配性、出图随机多样性以及整体图像风格。
相比官方Z-Image，推理速度更快（推荐10–20步即可获得较好效果）；相比官方Z-Image-Turbo，本模型保留了更强的多样性、更好的LoRA兼容性与可微调潜力，但速度略慢于Turbo（仍远快于原始Z-Image的28~50步）。
模型主要适用于：
希望在Z-Image非Turbo基底上训练/测试LoRA的用户
需要比原版更快、但又不想牺牲太多多样性与风格自由度的场景
艺术、插画、概念设计等对随机性与风格多样性有一定要求的生成任务
适配 ComfyUI 的模型格式及层命名前缀
使用方法：
推荐推理参数：
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