Model reference · open weights

Qwen-Image-Ed-2511-Lightning

Qwen-Image-Ed-2511-Lightning is an open-weight image model from lightx2v, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Image lightx2v 1 variants 355k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What Qwen-Image-Ed-2511-Lightning is

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: 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 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 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 (for Qwen framework-specific questions) - Open an issue in the LightX2V repo (for LightX2V integration questions)

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makerlightx2v
TypeImage models
Variants1
Runs withdiffusers
Based onQwen/Qwen-Image-Edit-2511
Released2025-12-22
Popularity355k downloads / month
Likes519
LicenceOpen weights

How it works

How image models work

Text promptwhat to makeText encoderunderstands itDiffusion stepsdenoise to pixelsImagePNG / JPEGA diffusion model starts from noise and denoises it, guided by your prompt, into a finished image.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
Qwen-Image-Edit-2511-LightningBF16Weights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys qwen-image-ed-2511-lightning for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen-image-ed-2511-lightning below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen-image-ed-2511-lightning","prompt":"a red bicycle","size":"1024x1024"}'

Details

Languages, data & research

Tags

diffusers safetensors diffusion-single-file comfyui distillation LoRA lora Qwen-Image Qwen-Image-Edit image-to-image

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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