Qwen Image Max Edit is an AI model for image editing with text prompts, supporting both Chinese and English languages. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.07per run·~14 / $1

Let the man in Figure 1 put on the sunglasses in Figure 2.
Qwen-Image-Max Edit is advanced AI-powered image editing model that transforms images based on text prompts. Supporting both Chinese and English inputs, it delivers precise edits while preserving the original style and quality.
Bilingual support Edit images using Chinese or English text prompts with equal accuracy.
Multi-image input Support up to 6 reference images for complex editing scenarios.
Flexible output sizing Maintains first image dimensions by default, or set custom size with preset aspect ratios.
Multiple output formats Export as JPEG, PNG, or WebP based on your needs.
Strong edit accuracy Understands context and object relationships for coherent modifications.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the desired edit (max 800 chars) |
| images | Yes | Reference images (1-6 images, 384-5000px) |
| size | No | Preset aspect ratio: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3 |
| width | No | Output width in pixels (256-1536, default: first image) |
| height | No | Output height in pixels (256-1536, default: first image) |
| seed | No | Random seed for reproducibility (-1 for random) |
| output_format | No | Output format: jpeg, png, webp (default: jpeg) |
| Output | Cost |
|---|---|
| Per image | $0.07 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image-max/edit 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 Max Edit below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image-max/edit" \
-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
}'
# 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-max/edit", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/qwen-image-max/edit",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputQwen Image Max Edit is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. Qwen Image Max Edit is an AI model for image editing with text prompts, supporting both Chinese and English languages. 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-max-edit.
Qwen Image Max Edit starts at $0.070 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`. 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-max-edit.
Average end-to-end generation time on WaveSpeedAI is around 115 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.