Alibaba's Qwen image editing model for instruction-based image modifications and transformations
Example outputs coming soon
Details
qwen-image-edit
Starting from
Prices shown are in USD · Some prices estimated from per-megapixel or per-token pricing
See all providersProviders & Pricing (3)
Qwen Image Edit Latest is available from 3 providers, with per-image pricing starting at $0.03 through Alibaba Cloud.
alibaba/qwen-image-edit
fal/qwen-image-edit
replicate/qwen-image-edit
qwen-image-edit-plus API OpenAI-compatible
Use the Lumenfall OpenAI-compatible API to integrate Qwen Image Edit for automated text-to-image generation and complex image-to-image transformations within your applications.
https://api.lumenfall.ai/openai/v1
qwen-image-edit
Code Examples
Image Edit
/v1/images/editscurl -X POST \ https://api.lumenfall.ai/openai/v1/images/edits \ -H "Authorization: Bearer $LUMENFALL_API_KEY" \ -F "model=qwen-image-edit" \ -F "[email protected]" \ -F "prompt=Add a starry night sky to this image" \ -F "size=1024x1024"# Response:# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }import OpenAI from 'openai';import fs from 'fs';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://api.lumenfall.ai/openai/v1'});const response = await client.images.edit({ model: 'qwen-image-edit', image: fs.createReadStream('source.png'), prompt: 'Add a starry night sky to this image', size: '1024x1024'});// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }console.log(response.data[0].url);from openai import OpenAIclient = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.lumenfall.ai/openai/v1")response = client.images.edit( model="qwen-image-edit", image=open("source.png", "rb"), prompt="Add a starry night sky to this image", size="1024x1024")# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }print(response.data[0].url)Parameter Reference
Core Parameters
| Parameter | Type | Description | Modes |
|---|---|---|---|
prompt
|
string | Required. Edit instruction for the image |
Edit
|
negative_prompt
|
string | Negative prompt to guide generation away from undesired content |
Edit
|
seed
|
integer | Random seed for reproducibility |
Edit
|
Size & Layout
| Parameter | Type | Description | Modes |
|---|---|---|---|
size
|
string |
Image dimensions as WxH pixels (e.g. "1024x1024") or aspect ratio (e.g. "16:9")
WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.
|
Edit
|
aspect_ratio
|
string |
Aspect ratio of the output image (e.g. "16:9", "1:1")
Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.
|
Edit
|
resolution
|
string |
Output resolution tier (e.g. "1K", "4K")
Controls scale independently of shape. Higher tiers produce larger images and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.
|
Edit
|
size
Exact pixel dimensions
"1920x1080"
aspect_ratio
Shape only, default scale
"16:9"
resolution
Scale tier, preserves shape
"1K"
Priority when combined
size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.
How matching works
7:1 on a model with
4:1 and 8:1,
you get 8:1.
0.5K 1K 2K 4K)
or megapixel tiers (0.25 1).
If the exact tier isn't available, you get the nearest one.
Media Inputs
| Parameter | Type | Description | Modes |
|---|---|---|---|
image
|
file |
Required.
Input image(s) to edit
Supports PNG, JPEG, WebP.
|
Edit
|
Output & Format
| Parameter | Type | Description | Modes |
|---|---|---|---|
response_format
|
string |
How to return the image
url
b64_json
Default:
"url" |
Edit
|
output_format
|
string |
Output image format
png
jpeg
gif
webp
avif
Gateway converts to requested format if provider doesn't support it natively.
|
Edit
|
output_compression
|
integer | Compression level for lossy formats (JPEG, WebP, AVIF) |
Edit
|
n
|
integer |
Number of images to generate
Default:
1Gateway generates multiple images in parallel even if provider only supports 1.
|
Edit
|
Additional Parameters
| Parameter | Type | Description | Modes |
|---|---|---|---|
cfg_scale
|
number | Classifier-free guidance scale — higher values stick more closely to the prompt |
Edit
|
acceleration
fal
|
string |
The acceleration level to use.
high
none
regular
|
Edit
|
disable_safety_checker
replicate
|
boolean | Disable safety checker for generated images. |
Edit
|
enable_safety_checker
fal
|
boolean | If set to true, the safety checker will be enabled. |
Edit
|
go_fast
replicate
|
boolean | Run faster predictions with additional optimizations. |
Edit
|
num_inference_steps
fal
|
integer | The number of inference steps to perform. |
Edit
|
output_quality
replicate
|
integer | Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs |
Edit
|
sync_mode
fal
|
boolean | If `True`, the media will be returned as a data URI. |
Edit
|
Parameter Normalization
How we handle parameters across different providers
Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:
| Behavior | What happens | Example |
|---|---|---|
passthrough |
Sent as-is to the provider | style, quality |
renamed |
Same value, mapped to the field name the provider expects | prompt |
converted |
Transformed to the provider's native format | size |
emulated |
Works even if the provider has no concept of it | n, response_format |
Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.
Gallery
View all 1 imagesQwen Image Edit Latest FAQ
How much does Qwen Image Edit Latest cost?
Qwen Image Edit Latest starts at $0.03 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.
How do I use Qwen Image Edit Latest via API?
You can use Qwen Image Edit Latest through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "qwen-image-edit". Code examples are available in Python, JavaScript, and cURL.
Which providers offer Qwen Image Edit Latest?
Qwen Image Edit Latest is available through fal.ai, Replicate, and Alibaba Cloud on Lumenfall. Lumenfall automatically routes requests to the best available provider.
Overview
Qwen Image Edit is a specialized instruction-based image transformation model developed by Alibaba’s Qwen team. Unlike standard text-to-image generators, this model is designed to modify existing visual assets through natural language prompts, allowing for precise alterations without manual masking or complex layering. It sits within the broader Qwen ecosystem, leveraging large-scale multimodal pre-training to interpret spatial relationships and semantic changes within an image.
Strengths
- Instructional Precision: The model excels at following specific commands for object replacement, color grading, and style transfers while maintaining the underlying composition of the original image.
- Spatial Reasoning: It demonstrates a strong understanding of where objects are located relative to one another, which helps in preventing unintended distortions to the background during foreground edits.
- Semantic Consistency: When altering a subject—such as changing a character’s clothing or an object’s material—the model preserves the identity and perspective of the original subject effectively.
- Multi-Modal Input Processing: It handles the interplay between the reference image and the text instructions with high fidelity, reducing the “hallucination” of new elements that weren’t requested.
Limitations
- High-Frequency Detail: Like many diffusion-based editors, it may struggle with micro-textures or extremely fine text rendering during complex transformations.
- Drastic Structural Changes: While it handles local edits well, attempting to fundamentally change the camera angle or the core geometry of a scene can result in artifacts or loss of consistency with the source image.
- Large-Scale Inpainting: For tasks requiring the generation of massive amounts of new content in large empty spaces, dedicated outpainting or general-purpose generative models might offer more creative variety.
Technical Background
Qwen Image Edit is part of the Qwen multimodal family, utilizing an architecture that integrates vision encoders with language models to bridge the gap between pixels and prose. It likely employs a diffusion-based framework fine-tuned on instruction-following datasets, where the model is trained on pairs of “before” images, “after” images, and the specific text instructions that link them. This training approach emphasizes the delta between two states rather than just generating a static image from scratch.
Best For
This model is ideal for automated e-commerce workflows, such as changing the color or texture of products, and for creative direction where a user needs to iterate on a concept image without restarting the generation process. It is also well-suited for social media content creation and rapid prototyping of visual assets. Qwen Image Edit is available for integration and testing through Lumenfall’s unified API and interactive playground.
Try Qwen Image Edit Latest in Playground
Generate images with custom prompts — no API key needed.