RedCraft-红潮 ModelFused

做好工具人 服务艺术家
Forever in memory of METAFILM Studio founder Mr. Yuan Bo

No Mosaics. 无码 2倍速
KREA 2 赤佬 Bastard3 Edition
REDZ 2 红潮 造相2 HDEdition

INT8/INT4 Convrot for ComfyUI 0.27 [Native 原生节点支持] Uploaded
File name: Krea2RedMix1.1-INT8-Convrot-ComfyUI (original native)
File name: Krea2RedMix2.1-INT8-Convrot-ComfyUI (no mosaics)
File name: Krea2RedMix3.1-INT8/INT4-Convrot-ComfyUI (visual effects)
File name: REDZimageTurbo2.0-INT8-Convrot-ComfyUI (ZIT-HD 2026)
File name: Krea2RedMix1.2-INT4-Convrot-ComfyUI (by Wikee Yang)

Hardcore version:

KREA 2 赤佬 黑兽3.0 Dark Beast 3 Krea2 Edition (Enhance Anatomy)

KREA2 GPT 逼真版 Grand PUSSY Truth | MIST2

REDZ-imageTurbo2 造相2.0 HD 高清版 05/07/2026 8 Steps

基于INT8 Convrot规格重制的商用高清图像处理引擎

作为ZimageTurbo模型家族的最新成员，这一版本红潮（byMetaFilm元影制作组）专为商业级高清图像处理需求而设计，选用海量商广正版4k/8K高清训练集，在性能、效率和输出质量方面均实现了突破性提升。

核心技术突破：完全基于INT8 Convrot量化重制

完全基于INT8 Convrot（卷积旋转）规格的架构重制。这一革命性的设计将传统的浮点运算转换为8位整数运算，在保持图像处理精度的同时，大幅降低了计算复杂度和内存占用。INT8 Convrot 技术通过优化卷积核的旋转机制，实现了更高效的张量运算路径。

性能飞跃：处理速度提升至2倍

得益于 INT8 Convrot 规格的深度优化，REDZ HD 2026 在处理速度上实现了质的飞跃。相比前代版本，新版本在相同硬件配置下能够将处理速度提升至2倍，这意味着商业用户现在可以在更短的时间内完成大量高清图像的处理任务，显著提升了工作流程效率。无论是批量图像增强、实时滤镜应用还是复杂特效渲染，都能提供前所未有的响应速度。

素材质量：精选商用高清素材库

其内置的精选商用高清素材库。这一素材库经过专业团队精心筛选和优化，包含了数十万种高质量的商业级图像资源，涵盖自然风光、城市景观、人物肖像、产品展示等多个类别。所有素材均经过严格的版权审查和质量控制，确保用户能够安全、合法地将其用于商业项目。素材库的智能匹配算法还能根据用户需求推荐最合适的图像资源，进一步提升创作效率。

应用场景广泛

红潮 ZimageTurbo HD 2026基于开放式商用协议发布，适用于多种商业应用场景：

• 广告设计与营销材料制作

• 电子商务产品图像优化

• 社交媒体内容创作

• 影视后期制作与特效处理

• 游戏开发中的纹理生成与优化

• 虚拟现实与增强现实内容创作

技术优势总结

红潮 2.0 HD 2026不仅是一次技术升级，更是图像处理工作流的重新定义。其INT8 Convrot架构带来的2倍速度提升，结合精选商用高清素材库，为专业用户提供了前所未有的创作自由度和效率保障。这一版本标志着ZimageTurbo模型在商业化应用道路上迈出了坚实的一步，为数字内容创作行业树立了新的技术标杆。

ZimageTurbo HD 2026: Commercial-Grade High-Definition Image Processing Engine with INT8 Convrot Architecture

ZimageTurbo HD 2026 represents a significant leap forward in image processing technology. As the latest member of the ZimageTurbo model family, this version is specifically designed for commercial-grade high-definition image processing needs, achieving breakthrough improvements in performance, efficiency, and output quality.

Core Technological Breakthrough: Complete INT8 Convrot Architecture Redesign

The core innovation of ZimageTurbo HD 2026 lies in its complete architectural redesign based on INT8 Convrot (Convolution Rotation) specifications. This revolutionary design transforms traditional floating-point operations into 8-bit integer operations, significantly reducing computational complexity and memory usage while maintaining image processing precision. The INT8 Convrot technology optimizes the rotation mechanism of convolution kernels, enabling more efficient tensor operation pathways and laying a solid foundation for real-time high-definition image processing.

Performance Leap: 2x Processing Speed Improvement

Thanks to the deep optimization of INT8 Convrot specifications, ZimageTurbo HD 2026 achieves a qualitative leap in processing speed. Compared to previous versions, the new version can increase processing speed by 2x under the same hardware configuration. This means commercial users can now complete large-scale high-definition image processing tasks in significantly less time, dramatically improving workflow efficiency. Whether for batch image enhancement, real-time filter application, or complex special effects rendering, ZimageTurbo HD 2026 delivers unprecedented response speeds.

Material Quality: Curated Commercial High-Definition Asset Library

Another standout feature of ZimageTurbo HD 2026 is its built-in curated commercial high-definition asset library. This library has been carefully selected and optimized by a professional team, containing thousands of high-quality commercial-grade image resources across multiple categories including natural landscapes, urban scenes, portrait photography, and product displays. All materials undergo rigorous copyright review and quality control, ensuring users can safely and legally incorporate them into commercial projects. The library's intelligent matching algorithm can also recommend the most suitable image resources based on user needs, further enhancing creative efficiency.

Wide Range of Application Scenarios

ZimageTurbo HD 2026 is suitable for various commercial application scenarios:

• Advertising design and marketing material creation

• E-commerce product image optimization

• Social media content creation

• Film and video post-production and special effects processing

• Texture generation and optimization in game development

• Virtual reality and augmented reality content creation

Technical Advantages Summary

ZimageTurbo REDZ2.0 HD 2026 is not just a technical upgrade but a redefinition of image processing workflows. The 2x speed improvement brought by its INT8 Convrot architecture, combined with the curated commercial high-definition asset library, provides professional users with unprecedented creative freedom and efficiency assurance. This version marks a solid step forward in the commercialization journey of the ZimageTurbo model, establishing a new technological benchmark for the digital content creation industry.

Krea2-RED-Mix2 赤佬无码版 01/07/2026 8 Steps

INT8 Convrot for ComfyUI 0.27 [Native 原生节点支持] Uploaded
File name: Krea2RedMix1.1-INT8-Convrot-ComfyUI (original native)
File name: Krea2RedMix2.1-INT8-Convrot-ComfyUI (no mosaics)

Usage ：ER_SDE/Euler | Simple | CFG=1 | 8 Steps

链接： Dark Beast | 黑兽 🐱‍👤Krea2赤佬无码版 已发布 06/28/2026

ERNIE-Red-Mix 26/04/2026 10Steps Fine-Tuning

ERNIE-Image is an open text-to-image generation model developed by the ERNIE-Image team at Baidu. It is built on a single-stream Diffusion Transformer (DiT) and paired with a lightweight Prompt Enhancer that expands brief user inputs into richer structured descriptions.

With only 8B DiT parameters, it achieves state-of-the-art performance among open-weight models. The model emphasizes both visual quality and controllability, making it highly effective for real-world generation tasks where precision matters.

ERNIE-Red-Mix adopts mixed-precision SFT (Supervised Fine-Tuning) with reference-based alignment, covering both AIO and DiT variants. It is trained on the mature RedCraft dataset, enabling broader generation flexibility, fewer constraints, and the ability to unlock novel visual styles beyond the base model.

Usage ：EULER/DEIS | Simple | CFG=1 | 10Steps

🇨🇳 中文

ERNIE-Red-Mix 采用混合精度 SFT（参考式微调，对齐优化），覆盖 AIO / DiT 双版本，基于成熟的 RedCraft 训练集进行训练，在一定程度上解除生成限制，并显著提升风格扩展能力，可用于生成全新视觉风格。

🇯🇵 日本語

ERNIE-Red-Mix は、混合精度による SFT（参照ベースのファインチューニング）を採用し、AIO / DiT の両バージョンに対応しています。成熟した RedCraft データセットで学習されており、生成制約の緩和とともに、新しいスタイル生成能力を拡張します。

🇹🇼 繁體中文

ERNIE-Red-Mix 採用混合精度 SFT（參考式微調），涵蓋 AIO / DiT 雙版本，基於成熟的 RedCraft 訓練集進行優化，在一定程度上解鎖生成限制，並提升風格拓展能力，可生成全新視覺風格。

ERNIE-Red-Mix Highlights:​

• Optimized speed ♥ Accelerated to 10 steps (CFG 1) while preserving BASE quality.

• Compact but strong ♥ Performance on par with substantially larger models, with stable and accurate details and materials.

• Text rendering preserved ♥ Fine-tuning does not compromise text rendering capability (posters, infographics, UI visuals).

• Instruction following maintained ♥ Unaffected ability to reliably handle complex prompts with multiple objects.

• Structured generation ♥ Continues to excel in posters, comics, and storyboards.

• Broader style coverage ♥ More realistic photography and improved aesthetic outputs.

• Lower VRAM footprint ♥ Mixed precision supports consumer GPUs with 8–12GB VRAM.

Limitations:​

• Complex limbs prone to artifacts — An inherent ERNIE issue; generating more samples can help mitigate this.

• Anatomical accuracy — Body anatomy and organ rendering still need further optimization and refinement.

• Mixed precision impacts text rendering — Mixed precision has a noticeable negative effect on text quality; for text-heavy content, the BF16 BASE model is recommended.

Sample Images：

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） https://modelscope.cn/models/FFFFFFoo/z-image-turbo-flow-dpo

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�