alibaba/wan/2.2/text-to-video/turbo
Wan 2.2 Turbo is Alibaba's text-to-video AI model. Turn written scripts and prompts into professional-quality video clips with realistic motion, lighting, and scene composition.
Example output — click Run to generate your own
Send your first request
OpenAI-compatible endpoint with unified authentication and usage tracking.
https://api.sandbase.ai/v1/runalibaba/wan/2.2/text-to-video/turboInput Schema
4 parameters · 1 required · 3 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
prompt | string | Required | The text prompt to guide video generation. |
seed | integer | Optional | Random seed for reproducibility. If None, a random seed is chosen. |
resolution | string | Optional | Resolution of the generated video (480p, 580p, or 720p). · Options: 480p, 720p · Default: "720p" 480p720p |
aspect_ratio | string | Optional | The aspect ratio of the generated image. · Options: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16 21:916:93:24:35:41:14:53:42:39:16 |
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
Async Workflow
This model uses asynchronous execution. Submit a request and poll for the result.
- Submit — POST to /v1/run, receive an
id - Poll — GET /v1/run/{id} until status is
completed,failed, ortimeout - Retrieve — Read
outputsfrom the completed response
Code Examples
Ready-to-run snippets
# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "alibaba/wan/2.2/text-to-video/turbo",
"prompt": "A medium shot establishes a modern, minimalist office setting: clean lines, muted grey walls, and polished wood surfaces. The focus shifts to a close-up on a woman in sharp, navy blue business attire. Her crisp white blouse contrasts with the deep blue of her tailored suit jacket. The subtle texture of the fabric is visible—a fine weave with a slight sheen. Her expression is serious, yet engaging, as she speaks to someone unseen just beyond the frame. Close-up on her eyes, showing the intensity of her gaze and the fine lines around them that hint at experience and focus. Her lips are slightly parted, as if mid-sentence. The light catches the subtle highlights in her auburn hair, meticulously styled. Note the slight catch of light on the silver band of her watch. High resolution 4k",
"resolution": "720p"
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
Wan 2.2 Text to Video Turbo
Wan 2.2 Text to Video Turbo is the Wan 2.2 speed-oriented workflow for prompt-led video. It models visual appearance and time together so the route’s written direction, source imagery, speech, masks, or structural conditions influence one coherent result rather than a collection of disconnected frames or a generic endpoint response.
Choose this exact route when the available assets and deliverable specifically call for prompt-led video. Identify every subject and source, state the desired action or transformation, then describe camera behavior, pacing, environment, lighting, atmosphere, and preservation requirements; local schema fields handle resolution, duration, seed, and delivery separately from the creative brief.
Highlights
- 2.2 Fast Written-scene filmmaking. Builds subjects, action, setting, and shot language from a text brief.
- 2.2 Fast Temporal motion coherence. Maintains plausible movement and interaction across consecutive frames.
- 2.2 Fast Cinematic camera interpretation. Responds to framing, lens behavior, camera movement, and pacing.
- Turbo production synthesis. Uses the Wan 2.2 Turbo path for rapid scene generation in the route’s supported delivery modes.
Pricing
| Configuration | Billing unit | Price |
|---|---|---|
| 480p | Per request | $0.05 |
| 720p | Per request | $0.10 |
When to Use
| ✅ Good fit | ❌ Consider alternatives |
|---|---|
| The project needs this exact text-to-video workflow | The intended task belongs to a different media route |
| Available source media matches every required field | Required assets or usage rights are unavailable |
| The brief can define subject, action, camera, and style | Output must be deterministic at frame or pixel level |
| Supported duration, resolution, and framing fit delivery | Final placement requires unsupported specifications |
| An asynchronous generation job fits production | A live or frame-synchronous response is mandatory |
Prompt Guide
Describe the result as a shot or design brief: identify subjects and references, state the action or transformation, specify environment and composition, then add camera behavior, lighting, pacing, style, sound, and preservation constraints where relevant. Use exact reference identifiers exposed by the local schema.
{
"prompt": "A cinematic scene with clearly directed subject action, camera movement, lighting, pacing, and atmosphere",
"seed": 1,
"resolution": "480p",
"aspect_ratio": "21:9"
}
Technical Specs
| Spec | Value |
|---|---|
| Model ID | alibaba/wan/2.2/text-to-video/turbo |
| Input fields | seed (integer)<br>prompt (string)<br>resolution (string; 480p, 720p)<br>aspect_ratio (string; 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16) |
| Required input | prompt |
| Output fields | url, content_type |
| Execution | Asynchronous job |
Related Models
alibaba/wan/2.2/text-to-video— Compare this concrete local family route.alibaba/wan/2.2/text-to-video/lora— Compare this concrete local family route.alibaba/wan/2.2/5b/fast/text-to-video— Compare this concrete local family route.

