---
title: Qwen-Image-Edit-2511-Lightning
canonical_url: "https://www.modelscope.cn/models/lightx2v/Qwen-Image-Edit-2511-Lightning"
md_url: "https://www.modelscope.cn/models/lightx2v/Qwen-Image-Edit-2511-Lightning.md"
repository: lightx2v/Qwen-Image-Edit-2511-Lightning
last_updated: 2026-06-16
license: apache-2.0
pipeline_tag: image-to-image
tasks:
  - image-to-image
base_model:
  - Qwen/Qwen-Image-Edit-2511
base_model_relation: adapter
parameters: 103.9B
tensor_type:
  - F8_E4M3
  - BF16
  - I64
  - F32
library_name:
  - lora
  - safetensors
  - pytorch
frameworks:
  - pytorch
supports_inference: img2img
downloads: 32078
stars: 82
tags:
  - diffusion-single-file
  - comfyui
  - distillation
  - LoRA
  - lora
  - Qwen-Image
  - Qwen-Image-Edit
---

# Qwen-Image-Edit-2511-Lightning

> Qwen-Image-Edit-2511-Lightning - lightx2v 在 ModelScope 开源的模型。Qwen-Image-Edit-2511-Lightning

lightx2v/Qwen-Image-Edit-2511-Lightning 是 ModelScope 魔搭社区上的 103.9B 参数image-to-image模型，采用 apache-2.0 许可，基于 Qwen/Qwen-Image-Edit-2511 构建，并支持在线推理（img2img）。

- **Repository**: lightx2v/Qwen-Image-Edit-2511-Lightning
- **License**: apache-2.0
- **Tasks**: image-to-image
- **Parameters**: 103.9B
- **Base model**: Qwen/Qwen-Image-Edit-2511
- **Online inference**: img2img
- **Tags**: diffusion-single-file, comfyui, distillation, LoRA, lora, Qwen-Image, Qwen-Image-Edit
- **Downloads**: 32078
- **Stars**: 82
- **Last updated**: 2026-06-16

Source: https://www.modelscope.cn/models/lightx2v/Qwen-Image-Edit-2511-Lightning

---

# Qwen-Image-Edit-2511-Lightning

## Model Overview
Qwen-Image-Edit-2511-Lightning is a collection of optimized models tailored for image editing tasks, leveraging step distillation and quantization techniques to deliver high-efficiency inference performance. This repository hosts three core model files with distinct characteristics:

| Model File Name | Type | Key Features |
|-----------------|------|--------------|
| `Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors` | 4-step Distilled LoRA | BF16 precision, lightweight, 4-step inference |
| `Qwen-Image-Edit-2511-Lightning-4steps-V1.0-fp32.safetensors` | 4-step Distilled LoRA | FP32 precision, high accuracy, 4-step inference |
| `qwen_image_edit_2511_fp8_e4m3fn_scaled_lightning.safetensors` | FP8 Quantized | FP8 (e4m3fn scaled) precision, fused with 4-step distilled LoRA, optimized for low-memory deployment |

## Usage Instructions
This model suite supports two mainstream usage frameworks, with detailed guides provided below:

### 1. Qwen-Image-Lightning Framework
For full documentation on model usage within the Qwen-Image-Lightning ecosystem (including environment setup, inference pipelines, and customization), please refer to:
[Qwen-Image-Lightning GitHub Repository](https://github.com/ModelTC/Qwen-Image-Lightning/)

### 2. LightX2V Framework
The models are fully compatible with the LightX2V lightweight video/image generation inference framework. For step-by-step usage examples, configuration templates, and performance optimization tips, see:
[LightX2V Qwen Image Edit Documentation](https://github.com/ModelTC/LightX2V/blob/main/examples/qwen_image/README.md)

## Key Optimizations
- **Step Distillation**: The LoRA models reduce the original inference steps to just 4 steps, achieving significant speedup (≈10x faster than standard 40-step inference) while preserving image editing quality.
- **FP8 Quantization**: The quantized base model balances performance and resource efficiency, reducing GPU memory usage by ~50% compared to FP32 while maintaining editing fidelity.

## Support
For technical issues, feature requests, or integration questions:
- Open an issue in the [Qwen-Image-Lightning repo](https://github.com/ModelTC/Qwen-Image-Lightning/issues) (for Qwen framework-specific questions)
- Open an issue in the [LightX2V repo](https://github.com/ModelTC/LightX2V/issues) (for LightX2V integration questions)