Qwen-Image-Edit-Plus (2509) is a 20B MMDiT image editor with multi-image editing, single-image consistency and native ControlNet support. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.02per run·~50 / $1

Put a Santa hat on the puppy

Color the Spider-Man and change his pose to the fighting stance.

The woman in image 2 adopts the pose from image 1.

Change the background to the seaside

The girl in picture 1 poses according to the posture in picture 2.

Put a Santa hat on the puppy
A next-gen image editing model built on Qwen-Image 20B. It delivers precise bilingual (Chinese & English) text editing, supports both appearance-level and semantic-level edits, and preserves the original style.
Dual-mode editing
Appearance editing: add/remove/modify elements while keeping all other regions pixel-accurate and unchanged.
Semantic editing: higher-level changes—IP creation, pose/rotation, style transfer—allow global pixel updates while keeping semantic intent.
Precise text editing (CN/EN) Edit on-image text directly (add/delete/replace) while retaining the original font, size, kerning, and style.
Style preservation Maintains palette, lighting, brushwork, and overall look even under substantial edits.
Strong benchmark results Evaluated across multiple public editing benchmarks with state-of-the-art performance.
在桌面右上角添加一杯拿铁,不改变其他区域。Turn the product into a cyberpunk style while keeping the brand logo and layout consistent.Replace the headline "Summer Sale" with "Autumn Sale" and keep the same font and size.Just $0.02 per image !!!
If you did not upload the image locally, please ensure that the image URL is accessible! A successfully accessible image will display a preview in the interface.
| Aspect Ratio | Exact (W×H) | Exact Pixels | Rounded (W×H, ÷64) | Rounded Pixels |
|---|---|---|---|---|
| 1:1 | 1448 × 1448 | 2,096,704 | 1408 × 1408 | 1,982,464 |
| 3:2 | 1773 × 1182 | 2,095,686 | 1728 × 1152 | 1,990,656 |
| 4:3 | 1672 × 1254 | 2,096,688 | 1664 × 1216 | 2,023,424 |
| 16:9 | 1936 × 1089 | 2,108,304 | 1920 × 1088 | 2,088,960 |
| 21:9 | 2212 × 948 | 2,096,976 | 2176 × 960 | 2,088,960 |
| 1:1 | 1024 × 1024 | 1,048,576 | 1024 × 1024 | 1,048,576 |
| 3:2 | 1254 × 836 | 1,048,344 | 1216 × 832 | 1,011,712 |
| 4:3 | 1182 × 887 | 1,048,434 | 1152 × 896 | 1,032,192 |
| 16:9 | 1365 × 768 | 1,048,320 | 1344 × 768 | 1,032,192 |
| 21:9 | 1564 × 670 | 1,047,880 | 1536 × 640 | 983,040 |
| 1:1 | 323 × 323 | 104,329 | 320 × 320 | 102,400 |
| 3:2 | 397 × 264 | 104,808 | 384 × 256 | 98,304 |
| 4:3 | 374 × 280 | 104,720 | 448 × 320 | 143,360 |
| 16:9 | 432 × 243 | 104,976 | 448 × 256 | 114,688 |
| 21:9 | 495 × 212 | 104,940 | 576 × 256 | 147,456 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/edit-plus with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Qwen Image Edit Plus below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/edit-plus" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/qwen-image/edit-plus", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/qwen-image/edit-plus",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
}
)
print(output["outputs"][0]) # → URL of the generated outputQwen Image Edit Plus is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. Qwen-Image-Edit-Plus (2509) is a 20B MMDiT image editor with multi-image editing, single-image consistency and native ControlNet support. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/qwen-image-edit-plus.
Qwen Image Edit Plus starts at $0.020 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `images`, `seed`, `enable_base64_output`, `enable_sync_mode`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/qwen-image-edit-plus.
Average end-to-end generation time on WaveSpeedAI is around 8 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.