alibaba/qwen-image/layered/lora

Name: Qwen Image Layered LoRA
Author: Alibaba

Qwen Image Layered Lora is Alibaba's intelligent image editing model. Transform, retouch, and reimagine existing images using text prompts - from background replacement to artistic style conversion.

Input

Prompt(string)

A caption for the input image.

Image URL or upload(string)

Upload

PNG, JPEG, WebP, or GIF · 20 MiB maximum

The URL of the input image.

This field is required.

Output Format(string)

The format of the generated image. Allowed values: png.

Loras(array)

List of LoRA weights to apply (maximum 3).

Num Layers(integer)

110

The number of layers to generate. Range: 1 to 10.

Seed(integer)

The same seed and the same prompt given to the same version of the model will output the same image every time.

Idle

Example output — click Run to generate your own

Production endpoint

Send your first request

OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/run

Model IDalibaba/qwen-image/layered/lora

Input Schema

6 parameters · 2 required · 4 optional

Parameter	Type	Required	Description
`image`	string	Required	The URL of the input image.
`prompt`	string	Required	A caption for the input image.
`seed`	integer	Optional	The same seed and the same prompt given to the same version of the model will output the same image every time.
`loras`	object[]	Optional	List of LoRA weights to apply (maximum 3). · Default: []
`num_layers`	integer	Optional	The number of layers to generate. · Min: 1 · Max: 10 · Default: 4
`output_format`	string	Optional	The format of the generated image. · Options: png · Default: "png" png

Output Schema

Field	Type	Description
`id`	string	Unique identifier for the generation task
`status`	string	Task status: pending, running, completed, failed, timeout
`model`	string	Model used for the generation
`outputs`	array	Array of output items
`outputs[].url`	string	URL of the generated artifact
`outputs[].content_type`	string	MIME type (e.g. image/png, video/mp4)
`error`	object \| null	Error details if failed, null on success
`error.type`	string	Machine-readable error type code
`error.message`	string	Human-readable error description

Async Workflow

This model uses asynchronous execution. Submit a request and poll for the result.

Submit — POST to /v1/run, receive an id
Poll — GET /v1/run/{id} until status is completed, failed, or timeout
Retrieve — Read outputs from the completed response

Code Examples

Ready-to-run snippets

# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
  "model": "alibaba/qwen-image/layered/lora",
  "image": "https://static.sandbase.ai/examples/alibaba/qwen-image/layered/lora/input_image_0.png",
  "loras": [],
  "num_layers": 4,
  "output_format": "png",
  "prompt": "a beautiful sunset over mountains"
}'

# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
  -H "Authorization: Bearer YOUR_API_KEY"

← Back to Qwen Image Layered LoRA

API README

Qwen Image Layered LoRA

Qwen Image Layered LoRA is the Qwen Image route for layer-aware image work. It uses Qwen’s combined visual-semantic and appearance modeling to interpret subjects, relationships, typography, spatial structure, and surface detail as a connected composition, giving this exact route a clearer production purpose than a generic image request.

Use Qwen Image Layered LoRA when the project specifically requires separable visual components and compositing flexibility. State the creative goal, then define composition, viewpoint, wording, materials, lighting, and finish; for edits, explicitly separate the intended transformation from identity, layout, or regions that must remain stable.

Highlights

Qwen Image Layer-aware image understanding. Separates foreground, background, subjects, text, and graphic elements conceptually.
Qwen Image Editable visual decomposition. Creates or organizes imagery into components suitable for downstream compositing.
Qwen Image Occlusion-aware separation. Preserves which elements sit in front of or behind one another.
Qwen Image Design-ready layer generation. Supports posters and visual layouts that benefit from independently editable parts. The configured adaptation adds task-specific learned behavior.

Pricing

Configuration	Billing unit	Price
Base generation	Per request	$0.06

When to Use

✅ Good fit	❌ Consider alternatives
The project needs this exact named workflow	The intended task belongs to another media route
All required reference or control media is available	Necessary assets or rights are unavailable
The brief can state transformation and preservation goals	Output must be deterministic at pixel or frame level
Supported duration, resolution, and format fit delivery	Final placement requires unsupported specifications
An asynchronous generated result fits production	A live frame-synchronous response is mandatory

Prompt Guide

Identify the primary subject and every source or condition, state the intended transformation or action, then describe composition, camera or viewpoint, lighting, materials, pacing, atmosphere, and exact preservation requirements. Refer to multiple inputs in their schema order.

{
  "prompt": "A precisely directed composition with explicit subject, transformation, camera or viewpoint, lighting, material, and preservation requirements",
  "image": "https://example.com/reference.png",
  "seed": 1,
  "loras": [],
  "num_layers": 4
}

Technical Specs

Spec	Value
Model ID	`alibaba/qwen-image/layered/lora`
Input fields	`seed` (integer)<br>`image` (string)<br>`loras` (array)<br>`prompt` (string)<br>`num_layers` (integer)<br>`output_format` (string; `png`)
Required input	`prompt`, `image`
Output fields	`url`, `content_type`
Execution	Asynchronous job

Related Models

alibaba/qwen-image
alibaba/qwen-image/edit
alibaba/qwen-image/max