[NEW]Boogu image & ideogram 4 in Workflows collection

RedCraft & DarkBeast workflows collection

[NEW] Image 2 Json (Gemini) 2 Image (Boogu+ideogram4) 06/20/2026

Feature Dimension: Boogu-Image-0.1

• Core Strength:​ Dense text rendering, photorealistic generation, integrated understanding system

• Text Rendering:​ ⭐⭐⭐⭐⭐ (Chinese/English dense text)

• Control Method:​ Instruction‑level control, diverse data‑driven

• Output Resolution:​ 1K/2K support

• Workflow Integration:​ ComfyUI‑Boogu, PyTorch native

Feature Dimension: Ideogram 4.0

• Core Strength:​ Structured JSON control, design workflow integration, native 2K output

• Text Rendering:​ ⭐⭐⭐⭐ (Excellent typography)

• Control Method:​ Structured JSON Prompt, precise layout control

• Output Resolution:​ Native 2K output

• Workflow Integration:​ ComfyUI native, Diffusers

Feature Dimension: Synergy Advantage

• Core Strength:​ Text precision + Design control = Professional‑grade design drafts

• Text Rendering:​ Boogu handles complex text content, Ideogram optimizes layout and typography

• Control Method:​ Complete control chain from content to layout

• Output Resolution:​ Complementary high‑resolution output capabilities

• Workflow Integration:​ Can be switched within the same workflow

Summary:​
The combination of these two models represents the current pinnacle of the open‑source text‑to‑image field—Boogu's advantages in content understanding and text precision, combined with Ideogram's expertise in design control and workflow integration, can meet the full creative needs from concept design to final output.

Boogu-Image-0.1 是由 Boogu 团队于 2026 年 6 月发布的开源统一图像生成与编辑模型系列，包含 Base、Turbo、Edit 等多个变体。该系列采用 Apache-2.0 开源协议，参数量约 100 亿（10B），支持高质量文本到图像生成、快速生成、图像编辑以及中英文文本渲染。Boogu-Image 的核心理念是构建一体化理解与生成系统，通过多样化的数据赋予用户更强的控制能力，而非依赖强化学习技术提升美学效果。该系列在 Boogu Arena 评测中位列所有开源与闭源系统中的顶尖水平，尤其在密集文字渲染、摄影逼真度和风格化生成方面表现突出。

Boogu-Image-0.1 is an open-source unified image generation and editing model series released by the Boogu team in June 2026, comprising Base, Turbo, and Edit variants. It is licensed under Apache-2.0 with approximately 10 billion parameters, supporting high‑quality text‑to‑image generation, fast inference, image editing, and Chinese/English text rendering. The core philosophy of Boogu‑Image is to build an integrated understanding‑and‑generation system that empowers users with stronger control through diverse data, rather than relying on reinforcement learning for aesthetic enhancement. The series ranks among the top performers in the Boogu Arena evaluation across both open‑source and closed‑source systems, excelling particularly in dense text rendering, photorealistic generation, and stylized creation.

特性维度 Boogu-Image-0.1+Ideogram 4.0 搭配优势核心优势密集文字渲染、摄影逼真度、一体化理解系统结构化 JSON 控制、设计工作流集成、2K 原生输出文字精度 + 设计控制 = 专业级设计稿文字渲染⭐⭐⭐⭐⭐（中英文密集文字）⭐⭐⭐⭐（优秀排版）

Boogu 处理复杂文字内容，Ideogram 优化版式布局控制方式指令级控制、多样化数据驱动结构化 JSON Prompt、精确布局控制从内容到版式的完整控制链

输出分辨率1K/2K 支持原生 2K 输出高分辨率输出能力互补工作流集成ComfyUI-Boogu、PyTorch 原生ComfyUI 原生、Diffusers可在同一工作流中切换使用

这两个模型的结合代表了当前开源文生图领域的最高水平——Boogu 在内容理解与文字精度上的优势，加上 Ideogram 在设计控制与工作流集成上的专长，能够满足从概念设计到成品输出的完整创意需求。

[NEW] Text 2 Json (Gemma4) 2 Image (ideogram4) 06/06/2026

ideogram4 is trained on structured JSON captions (scene summary, style block, background, and optional per-object descriptions with bounding boxes and hex color palettes). Official inference validates prompts against that schema. Guidance uses flow-matching with asymmetric classifier-free guidance (the unconditional pass drops text tokens)—not a separate negative prompt string.

NOTE: If you see "Image blocked by safety filter" it is because of safety training in the model itself, ComfyUI does not have any safety filter.

How to build prompts here

(a) Raw input: Paste or type directly into the subgraph. You may use plain natural language, but structured JSON (as in the subgraph default) gives the most predictable layout and style control.

(b) Model-assisted (LLM): Use the Ideogram4 Caption Prompt Template output with any LLM tools to obtain the JSON format prompt

关于模型无法正常审核提示词的问题提示

该模型（ideogram4）基于结构化JSON描述（场景摘要、风格块、背景，以及可选的带边界框和十六进制调色板的逐对象描述）进行训练。官方推理会根据该模式验证提示词。引导使用流匹配与非对称无分类器引导（无条件通道会丢弃文本标记）。

注意：如果你看到"图像被安全过滤器拦截"，这是由于模型本身的安全和训练规范所致，主要原因是提示词不符合JSON规范，并非NSFW拦截。

如何构建提示词

(a) 原始输入：直接粘贴或输入到子图中。并通过工作流内建的本地 Gemma4 模型输出结构化JSON（如子图默认格式）能提供最可预测的布局和风格控制。

(b) 模型辅助（LLM）：您也可以将 Ideogram4 Caption Prompt Template 的输出，配合任意 LLM 工具使用，以获取 JSON 格式的提示词

ideogram4 06/04/2026

Ideogram 4 is Ideogram's first open-source text-to-image model. It is a state-of-the-art foundation model trained from scratch — not a fine-tune of any existing model.

https://github.com/ideogram-oss/ideogram4

https://github.com/Comfy-Org/ComfyUI

Dark Beast KLEIN 9b 🟦 V2.0 BFS 03/03/2026

DBK v2 BFS最佳换脸工作流，配套模型：
https://civitai.com/models/2242173?modelVersionId=2740209

Dark Beast KLEIN 9b BFS 🟦 V2.0 LoRA Edition
https://civitai.com/models/964312/redcraft-dark-beast-zandklein-exported-lora-edition

This is the next-level face-swap specialized evolution of the Dark Beast lineage, built on the lightning-fast FLUX.2 Klein 9B accelerated model from Black Forest Labs.

Engineered with targeted optimizations for face swapping practices, it integrates BFS (Best Face Swap) technology to completely eliminate the rigid, unnatural look that plagued earlier face replacements — delivering seamless, lifelike integrations with preserved identity, expression, and lighting.

It also fully fixes the portrait reference issue from the previous DB BlitZ versions

Special thanks to the scheme provider: https://github.com/alisson-anjos for the powerful BFS foundation that powers this breakthrough.🟦

The author's In-site link: https://civitai.com/user/NRDX

Important notes:

This version is exclusively designed around the Klein 9B accelerated edition — no base model exists.

Usage is identical to Black Forest Labs' official FLUX.2 Klein 9B accelerated release: ultra-low steps (e.g., 4-5), CFG=1 fixed, blazing inference speed on consumer hardware.

In one sentence: Dark Beast's ferocious soul meets BFS (Best Face Swap) technology — more natural, and truly unstoppable! 🟦

for more infomation about BFS (Best Face Swap) :

https://huggingface.co/Alissonerdx

Alternatively, it can be directly applied to the entire Klein 9b/Qwen Edit base and Fine-tune models, through LoRA Adapter parameter injection.

面部交换测试的源-人像来自Civitai用户图像和Moody Mix肖像风格。
Source faces for the face-swapping test originated from Civitai user images and Moody Mix portraits styles.

The gods have returned! KOLORS base model/Hyper 8steps/SDXL refinement/IPA Plus

众神归位！快手底模/字节加速/SDXL精修/IPA风格

Kolors DiT大模型COMFYUI工作流-AiARTiST

Kolors DiT（GLM）ComfyUI 放大精修工作流

7/8日 发布Kolors-DiT开源模型+ACG6XL放大精修-文生图工作流

7/9日 发布Kolors-DiT开源模型+ACG6XL放大精修-垫图生图工作流

7/10日 发布Kolors-DiT开源模型-单文件模型版+LoRA加速器+ACG6XL放大精修工作流

7/11日 支持IPA-Plus节点，单一样本垫图风格导入，模型和组件包请在网盘下载

原生采样器支持节点作者MinusZoneAI，非常感谢！

https://github.com/MinusZoneAI/ComfyUI-Kolors-MZ

单文件模型及存放路径已经上传至网盘，模型路径根据网盘路径存放

SDXL-Hyper-8steps 蒸馏加速器LoRA\ACG6Hyper SDXL精修模型 同上

增加 IPAdapter 模型及ComfyUI_IPAdapter_plus 组件包 存放路径 同上

IPAdapter 开源模型：

https://hf-mirror.com/h94/IP-Adapter

ComfyUI_IPAdapter_plus 项目：

https://github.com/cubiq/ComfyUI_IPAdapter_plus

项目开源地址：

https://huggingface.co/Kwai-Kolors/Kolors

ComfyUI 加载器封装组件项目地址：

https://github.com/kijai/ComfyUI-KwaiKolorsWrapper

Kolors：用于逼真文本到图像合成的扩散模型的有效训练

Kolors是由快手Kolors团队开发的一种基于潜在扩散的大规模文本到图像生成模型。经过数十亿对文本图像的训练，Kolors在视觉质量、复杂的语义准确性以及中文和英文字符的文本渲染方面比开源和专有模型都表现出显著优势。此外，Kolors同时支持中文和英文输入，在理解和生成中文特定内容方面表现出色。

开源Kolors，与开源社区合作，促进大型文本到图像模型的开发。该项目的代码是在Apache-2.0许可证下开源的。我们真诚地敦促所有开发者和用户严格遵守开源许可证，避免将开源模型、代码及其衍生物用于任何可能危害国家和社会的目的，或用于任何未经安全评估和注册的服务。请注意，尽管我们在训练过程中尽了最大努力确保数据的合规性、准确性和安全性，但由于生成内容的多样性和可组合性以及影响模型的概率随机性，我们无法保证输出内容的准确性和安全性，并且模型容易产生误导。对于因使用开源模型和代码而导致模型被误导、滥用、误用或不当使用而产生的任何数据安全问题、舆论风险或风险和责任，本项目不承担任何法律责任。

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1. 您不得将此模型及其衍生版本（如融合模型版本）托管于计划赚取收入或捐赠的网站/应用程序。

2. 您不得直接售卖此模型及其衍生版本（如融合模型版本），除非您对此模型进行了足够程度的人工修改，使其在法律意义上可以被完全判定为您的个人作品。如果您违反本条，所造成的一切法律后果由您个人承担，请恕本人概不负责。

3. 您不能使用该模型故意制作或共享非法或有害的内容传播和输出，请您遵守公序良德，将此模型用于积极正面的用途。