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[doc] standardize diffusion cookbook model pages (#34247)

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Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
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Mick
2026-08-21 10:25:40 +08:00
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co-authored by Claude Opus 5
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docs/cookbook/diffusion/Qwen-Image/Qwen-Image-Edit.mdx
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@@ -7,22 +7,13 @@ metatags:
import { DiffusionModelTags } from '/src/snippets/diffusion/model-tags.jsx';
import { QwenImageEditDeployment } from '/src/snippets/diffusion/qwen-image-edit-deployment.jsx';
<DiffusionModelTags tags={["image", "image editing", "text rendering", "character consistency"]} />
<DiffusionModelTags tags={["image editing", "text replacement", "character consistency", "multi-person", "20B"]} />
## 1. Model Introduction
[Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) is an enhanced version over Qwen-Image-Edit-2509, featuring multiple improvements—including notably better consistency. Built upon the 20B Qwen-Image model, Qwen-Image-Edit-2511 successfully extends Qwen-Image's unique text rendering capabilities to image editing tasks, enabling precise text editing.
[Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) is the 20B editing counterpart to Qwen-Image. It is strongest at changing text, materials, lighting, viewpoint, or composition while reducing drift in regions that were not requested to change.
Key Enhancements in Qwen-Image-Edit-2511:
- **Mitigate Image Drift**: Reduces unwanted changes in non-edited regions of the image.
- **Improved Character Consistency**: The model can perform imaginative edits based on an input portrait while preserving the identity and visual characteristics of the subject.
- **Multi-Person Consistency**: Enhanced consistency in multi-person group photos, enabling high-fidelity fusion of two separate person images into a coherent group shot.
- **Integrated LoRA Capabilities**: Selected popular community-created LoRAs are integrated directly into the base model, unlocking their effects without extra tuning (e.g., lighting enhancement, viewpoint generation).
- **Enhanced Industrial Design Generation**: Special attention to practical engineering scenarios, including batch industrial product design and material replacement for industrial components.
- **Strengthened Geometric Reasoning**: Stronger geometric reasoning capability for generating auxiliary construction lines for design or annotation purposes.
For more details, please refer to the [official Qwen-Image-Edit-2511 HuggingFace page](https://huggingface.co/Qwen/Qwen-Image-Edit-2511), the [Blog](https://qwenlm.github.io/blog/qwen-image-edit-2511/), and the [Tech Report](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf).
Choose it for identity-sensitive portrait edits, multi-person composition, typography replacement, and geometry-aware design work. It is substantially heavier than small specialist editors, and consistency is improved rather than guaranteed; evaluate untouched-region drift on the actual editing workload.
## 2. SGLang-diffusion Installation
docs/cookbook/diffusion/Qwen-Image/Qwen-Image.mdx
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@@ -7,13 +7,13 @@ metatags:
import { DiffusionModelTags } from '/src/snippets/diffusion/model-tags.jsx';
import { QwenImageDeployment } from '/src/snippets/diffusion/qwen-image-deployment.jsx';
<DiffusionModelTags tags={["image", "text-to-image", "text rendering", "NVFP4"]} />
<DiffusionModelTags tags={["image", "text-to-image", "bilingual typography", "complex layouts", "NVFP4"]} />
## 1. Model Introduction
[Qwen-Image](https://huggingface.co/Qwen/Qwen-Image) is a text-to-image diffusion model developed by the Qwen team.
[Qwen-Image](https://huggingface.co/Qwen/Qwen-Image) is a 20B text-to-image model built for strong prompt following and precise rendering of English and Chinese text. It is especially useful for posters, signs, diagrams, and dense layouts where typography and spatial relationships matter as much as general image quality.
For more details, please refer to the [official Qwen-Image HuggingFace page](https://huggingface.co/Qwen/Qwen-Image), the [Blog](https://qwenlm.github.io/blog/qwen-image/), and the [Tech Report](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf).
This page covers generation rather than editing: use Qwen-Image-Edit when an existing image, subject identity, or untouched region must be preserved. The full checkpoint is memory-heavy, while the validated ModelOpt NVFP4 release provides a supported low-precision deployment option with an expected quality tradeoff.
## 2. SGLang-diffusion Installation