Qwen Image Edit LoRA: Lora Support

Edit any image with a custom-trained LoRA style applied on top of Qwen Image Edit. Precise, fine-tuned edits via a simple REST API. Try free — pay per generation, no subscription.

Interactive model controls

Qwen Image Edit LoRA is a fine-tuned image editing model with custom LoRA support. Modifying or adding elements with fine-tuned styles.

📝

Overview

About this model

Qwen Image Edit LoRA is Qwen Image Edit with custom LoRA support layered on top, letting you apply a fine-tuned style, character, or product look while modifying or adding elements to an input image. Provide a single source image, a text prompt describing the edit, and up to 3 LoRA weight files with individual scale multipliers.

1Branded product edits: Apply a trained brand-style LoRA while editing product photography.
2Character consistency: Keep a fine-tuned character or persona style consistent across edited images.
3Style-consistent retouching: Blend a custom aesthetic LoRA into standard image edits.
4Custom art direction: Combine multiple LoRA weights to achieve a specific, repeatable visual style.
💰

Pricing & Value

Cost analysis

muapiapp$0.04 per generation

Flat per-generation price regardless of how many LoRA weights are applied.

Fal.ai$0.05 per generation

Muapiapp is roughly 20% cheaper for comparable Qwen Image Edit LoRA generations.

Replicate$0.05 per generation

Usage-based pricing comparable to Fal.ai; muapiapp remains the cheaper option.

** Competitor pricing is estimated based on similar model architectures and usage tiers.

⚙️

Technical Details

Configuration schema

Promptstring

Text prompt describing the image edits.

Default ValueA cinematic ocean wave at sunrise, highly detailed
Image URLstring

URL of the input image.

Default Valuehttps://d3adwkbyhxyrtq.cloudfront.net/ai-images/186/902675646946/c0951838-8bc5-4598-8e8e-941df16446fa.jpg
Aspect RatioEnum (9 options)

Aspect ratio of generated image.

Default Value1:1
LoRAsarray

List of LoRAs to apply (maximum 3).

Default Value[object Object]
Output FormatEnum (3 options)

Format of the output image.

Default Valuejpeg
📖

Implementation Guide

Developer documentation

How to Use Qwen Image Edit LoRA

  1. Provide the Source Image

    • Set image_url to the image you want to edit.
  2. Write the Edit Prompt

    • Describe the change you want, e.g. "add a red scarf and change the background to a snowy street."
  3. Apply LoRA Weights (Optional)

    • Add up to 3 entries to loras, each with a path (URL to a .safetensors file) and a scale (0–4, default 1) controlling its strength.
  4. Set Output Options

    • Choose aspect_ratio and output_format (jpeg, png, or webp).
  5. Submit via the API

curl -X POST https://api.muapi.ai/api/v1/qwen-image-edit-lora \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Add a red scarf and change the background to a snowy street.",
    "image_url": "https://example.com/source.jpg",
    "loras": [{"path": "https://example.com/my-style.safetensors", "scale": 1}]
  }'
  1. Poll and Download
    • Poll GET /api/v1/predictions/{request_id}/result until status is completed, then retrieve the image URL from output.
❓

Common Questions

Frequently asked

What does Qwen Image Edit LoRA do?

It edits a single input image according to your text prompt, while applying up to 3 custom LoRA weight files to steer the result toward a trained style, character, or look.

Where do the LoRA weights come from?

Any publicly reachable `.safetensors` URL — including one produced by a muapiapp LoRA trainer endpoint, or a third-party host like Hugging Face.

How many LoRAs can I apply at once?

Up to 3, each with its own `scale` multiplier (0–4, default 1) to control how strongly it influences the output.

How is this different from qwen-image-edit-2511-lora?

This endpoint takes a single `image_url`. The 2511 variant accepts up to 3 reference images via `images_list` and offers stronger multi-image edit consistency.

What output formats are supported?

`jpeg`, `png`, or `webp`, set via `output_format`.