Wan 2.7 — Text to Image
curl --request POST \
--url https://api.muvi.video/v1/jobs/submit \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "<string>",
"input": {
"prompt": "<string>",
"size": "<string>",
"num_images": "<string>",
"thinking_mode": true
}
}
'import requests
url = "https://api.muvi.video/v1/jobs/submit"
payload = {
"model": "<string>",
"input": {
"prompt": "<string>",
"size": "<string>",
"num_images": "<string>",
"thinking_mode": True
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: '<string>',
input: {
prompt: '<string>',
size: '<string>',
num_images: '<string>',
thinking_mode: true
}
})
};
fetch('https://api.muvi.video/v1/jobs/submit', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));{
"jobId": "<string>",
"status": "<string>",
"estimatedCompletionTime": "<string>",
"costMicroCents": 123
}Wan 2.7
Wan 2.7 — Text to Image
Generate text to image outputs using Alibaba+‘s Wan 2.7 model via PixelByte API
POST
/
v1
/
jobs
/
submit
Wan 2.7 — Text to Image
curl --request POST \
--url https://api.muvi.video/v1/jobs/submit \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "<string>",
"input": {
"prompt": "<string>",
"size": "<string>",
"num_images": "<string>",
"thinking_mode": true
}
}
'import requests
url = "https://api.muvi.video/v1/jobs/submit"
payload = {
"model": "<string>",
"input": {
"prompt": "<string>",
"size": "<string>",
"num_images": "<string>",
"thinking_mode": True
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: '<string>',
input: {
prompt: '<string>',
size: '<string>',
num_images: '<string>',
thinking_mode: true
}
})
};
fetch('https://api.muvi.video/v1/jobs/submit', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));{
"jobId": "<string>",
"status": "<string>",
"estimatedCompletionTime": "<string>",
"costMicroCents": 123
}Generate text to image outputs with Alibaba+‘s Wan 2.7 model. Submitted as an asynchronous job and delivered via webhook or polling.
| Property | Value |
|---|---|
| Provider | Alibaba+ |
| Model | Wan 2.7 |
| Capability | Text to Image |
| Base Cost | 30,000 micro-cents/image ($0.03/img) |
| Processing Time | ~30 seconds |
Request Body
string
required
Model slug. Use
alibaba-plus/wan-2.7/text-to-image for text to image generation.object
required
Input parameters for text to image generation.
string
HTTPS URL to receive a webhook notification when the job completes or fails.
Pricing
Base cost: 30,000 micro-cents per image ($0.03/img)finalCost = baseCost × num_images
| Factor | Option | Multiplier |
|---|---|---|
| Number of Images | 1 | 1x |
2 | 2x | |
3 | 3x | |
4 | 4x |
Default cost: 1 number of images = 30,000 × 1 = 30,000 micro-cents ($0.03)
Response
string
Unique identifier for the submitted job.
string
Initial job status. Always
"pending" on successful submission.string
ISO 8601 timestamp of the estimated completion time.
number
The cost of the job in micro-cents.
Code Examples
curl -X POST https://api.muvi.video/v1/jobs/submit \
-H "Authorization: Bearer $PIXELBYTE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "alibaba-plus/wan-2.7/text-to-image",
"input": {
"prompt": "A photorealistic portrait of a fox in a forest at golden hour",
"size": "2K",
"num_images": "1"
}
}'
import requests
response = requests.post(
"https://api.muvi.video/v1/jobs/submit",
headers={
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
json={
"model": "alibaba-plus/wan-2.7/text-to-image",
"input": {
"prompt": "A photorealistic portrait of a fox in a forest at golden hour",
"size": "2K",
"num_images": "1"
}
}
)
data = response.json()
print(data)
const response = await fetch("https://api.muvi.video/v1/jobs/submit", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
body: JSON.stringify({
model: "alibaba-plus/wan-2.7/text-to-image",
input: {
prompt: "A photorealistic portrait of a fox in a forest at golden hour",
size: "2K",
num_images: "1"
}
})
});
const data = await response.json();
console.log(data);