Output resolution
Supports 1k, 2k, 4k from the published endpoint schema.
3×3 multi-angle image grid; highest quality image output
curl -X POST https://runapi.ai/api/v1/wan/text_to_image \
-H "Authorization: Bearer $RUNAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "wan-2.7-image-pro",
"prompt": "Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel."
}'
import { WanClient } from "@runapi.ai/wan";
const client = new WanClient();
const result = await client.textToImage.run({
model: "wan-2.7-image-pro",
prompt: "Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel.",
});
import os
import requests
response = requests.post(
"https://runapi.ai/api/v1/wan/text_to_image",
headers={"Authorization": f"Bearer {os.environ['RUNAPI_API_KEY']}"},
json={"model":"wan-2.7-image-pro","prompt":"Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel."}
)
response.raise_for_status()
<?php
$client = curl_init("https://runapi.ai/api/v1/wan/text_to_image");
curl_setopt_array($client, [
CURLOPT_HTTPHEADER => ["Authorization: Bearer " . getenv("RUNAPI_API_KEY"), "Content-Type: application/json"],
CURLOPT_POSTFIELDS => json_encode([
'model' => 'wan-2.7-image-pro',
'prompt' => 'Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel.',
])
]);
$response = curl_exec($client);
RunApi client = new RunApi(System.getenv("RUNAPI_API_KEY"));
Task task = client.textToImage().run({"model":"wan-2.7-image-pro","prompt":"Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel."});
task.waitForResult();
require "runapi/wan"
client = RunApi::Wan::Client.new
result = client.text_to_image.run(
model: "wan-2.7-image-pro",
prompt: "Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel."
)
client := runapi.NewClient(os.Getenv("RUNAPI_API_KEY"))
task, err := client.textToImage.Run({"model":"wan-2.7-image-pro","prompt":"Generate a 5-second video of a cat jumping onto a bookshelf, natural indoor lighting, handheld camera feel."})
if err != nil { log.Fatal(err) }
task.Wait()
$ runapi generate \
--model wan-2.7-image-pro \
--endpoint text_to_image \
--wait
18 versions available
Pick any model and generate in seconds.
| Provider | Alibaba |
| Model ID | wan-2.7-image-pro |
| Modality | Image |
| Task types | Asynchronous |
| API endpoint | /api/v1/wan/text_to_image |
| Billing unit | call |
| Input parameters | aspect_ratio, output_resolution |
| Max resolution | 1k, 2k, 4k |
| Aspect ratios | 1:1, 16:9, 4:3, 21:9, 3:4, 9:16, 8:1, 1:8 |
| Catalog status | Operational |
Sign up for free and create an API key for wan-2.7-image-pro from the dashboard.
POST to /api/v1/wan/text_to_image with the wan-2.7-image-pro model slug and your parameters.
Poll the task or follow the callback to retrieve the completed wan-2.7-image-pro result.
Supports 1k, 2k, 4k from the published endpoint schema.
Configure 2 documented parameters, including aspect_ratio, output_resolution.
Exposes 1 public endpoint(s): text_to_image.
Metered by call with no subscription requirement.
aspect_ratioNo description available. (1:1, 16:9, 4:3, 21:9, 3:4, 9:16, 8:1, 1:8)
output_resolutionNo description available. (1k, 2k, 4k)
Auto-generate lifestyle product photos for e-commerce catalogs that lack studio photography.
Rapidly concept environments and characters before committing to final art.
Generate unique cover art and illustrations for blog posts and articles at scale.
Pass the model ID shown in the quickstart.
Per-key rate limits scale with your usage tier. The pricing page shows current limits. If you need higher throughput, contact support to discuss tier upgrades.
Yes. Variant is a parameter in the request. Switch by changing the model ID — no code changes, no re-authentication, no separate billing setup. All variants share the same API key and request shape.
Where streaming is available, RunAPI streams end-to-end. LLM models support token-level streaming. Media models use async task polling or webhook callbacks for result delivery.
Open an issue on the public GitHub repo or email support at [email protected]. Include the task ID and model ID so the team can investigate the specific generation.
No. Your RunAPI API key is enough to access this variant and every other model in the catalog. You do not need accounts with the underlying provider.
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