One continuous 5-second 16:9 shot in a cluttered basement laundry room. A chubby raccoon wearing oversized red headphones stands on a vibrating top-load washing machine and scratches a plain vinyl record with wet paws. Slow lateral dolly orbits the shuddering machine. Fluorescent flicker, soapy water sloshing. Native audio: washing-machine thumps, metal lid rattle, wet-paw vinyl scratches; no music bed, no speech. No logos, no readable text, no products, no packaging, no prices, no CTA, no advertising, no watermark, no brand marks.
Wan 3.0 Prime Text-to-Video API
alibaba/wan-3.0-prime/text-to-videoWan 3.0 Prime (Text-to-Video) transforms a text prompt into a continuous video up to 30 seconds, with native audio-visual sync, layered control for action and camera, and output up to 1080p. It follows ordered beats across the shot so subject motion, scene continuity, and timing stay readable from the written plan.
Input
Output
IdleYour generated video will appear here
Configure the required inputs, resolution, and duration, then run the task.
Continue with
Examples
REST API
Quick Start
Authenticate, submit a valid input object, then use task_id to retrieve the video.
Connect to the Vidgo API
Create an API key, keep it only on your server, and send Authorization: Bearer VIDGO_API_KEY.
- Endpoint
- POST
https://api.vidgo.ai/api/generate/submit - Authentication
- Authorization: Bearer VIDGO_API_KEY
Submit one generation task
Run the smallest valid payload for this workflow. A successful submission immediately returns task_id without waiting for the video.
REQUEST_BODY=$(cat <<'JSON'
{
"model": "alibaba/wan-3.0-prime/text-to-video",
"input": {
"prompt": "One continuous 5-second 16:9 shot in a cluttered basement laundry room. A chubby raccoon wearing oversized red headphones stands on a vibrating top-load washing machine and scratches a plain vinyl record with wet paws. Slow lateral dolly orbits the shuddering machine. Fluorescent flicker, soapy water sloshing. Native audio: washing-machine thumps, metal lid rattle, wet-paw vinyl scratches; no music bed, no speech. No logos, no readable text, no products, no packaging, no prices, no CTA, no advertising, no watermark, no brand marks.",
"duration": 5,
"resolution": "720p",
"aspect_ratio": "16:9",
"audio": true,
"enable_safety_checker": true
}
}
JSON
)
RESPONSE=$(curl --silent --show-error --fail-with-body \
--request POST \
--url "https://api.vidgo.ai/api/generate/submit" \
--header "Authorization: Bearer $VIDGO_API_KEY" \
--header "Content-Type: application/json" \
--data "$REQUEST_BODY")
CODE=$(printf '%s' "$RESPONSE" | jq -r '.code // empty')
if [ "$CODE" != "0" ] && [ "$CODE" != "200" ]; then
printf 'API error: %s
' "$RESPONSE" >&2
exit 1
fi
printf '%s
' "$RESPONSE"Wait for the result
Query with task_id, continue for not_started/running, and stop for finished/failed. On success, read data.files[].file_url.
Track status
GET https://api.vidgo.ai/api/generate/status/{task_id}Poll about every 2 seconds, then back off gradually. Continue only for not_started or running and stop on finished or failed. You can instead add callback_url to the same top-level request contract.
not_startedrunningfinishedfailed{
"code": 200,
"data": {
"task_id": "task-unified-...",
"status": "running",
"created_time": "2026-08-22T10:00:00Z"
}
}{
"code": 200,
"data": {
"task_id": "task-unified-...",
"status": "finished",
"files": [
{
"file_url": "https://storage.vidgo.ai/generated/video.mp4",
"file_type": "video"
}
],
"created_time": "2026-08-22T10:00:00Z",
"progress": 100,
"error_message": null
}
}Complete runnable example
Expand for a complete script with HTTP and business-code checks, task_id validation, polling, terminal-state handling, and a timeout boundary.
set -euo pipefail
: "${VIDGO_API_KEY:?Set VIDGO_API_KEY in your environment}"
REQUEST_BODY=$(cat <<'JSON'
{
"model": "alibaba/wan-3.0-prime/text-to-video",
"input": {
"prompt": "One continuous 5-second 16:9 shot in a cluttered basement laundry room. A chubby raccoon wearing oversized red headphones stands on a vibrating top-load washing machine and scratches a plain vinyl record with wet paws. Slow lateral dolly orbits the shuddering machine. Fluorescent flicker, soapy water sloshing. Native audio: washing-machine thumps, metal lid rattle, wet-paw vinyl scratches; no music bed, no speech. No logos, no readable text, no products, no packaging, no prices, no CTA, no advertising, no watermark, no brand marks.",
"duration": 5,
"resolution": "720p",
"aspect_ratio": "16:9",
"audio": true,
"enable_safety_checker": true
}
}
JSON
)
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
--request POST \
--url "https://api.vidgo.ai/api/generate/submit" \
--header "Authorization: Bearer $VIDGO_API_KEY" \
--header "Content-Type: application/json" \
--data "$REQUEST_BODY")
TASK_ID=$(printf '%s' "$SUBMIT_RESPONSE" | jq -r '.data.task_id // .task_id // empty')
BUSINESS_CODE=$(printf '%s' "$SUBMIT_RESPONSE" | jq -r '.code // empty')
if [ "$BUSINESS_CODE" != "0" ] && [ "$BUSINESS_CODE" != "200" ]; then
printf 'Submit failed:
%s
' "$SUBMIT_RESPONSE" >&2
exit 1
fi
if [ -z "$TASK_ID" ]; then
printf 'Submit response did not include task_id:
%s
' "$SUBMIT_RESPONSE" >&2
exit 1
fi
START_TIME=$(date +%s)
POLL_DELAY=2
while true; do
if [ $(( $(date +%s) - START_TIME )) -ge 600 ]; then
printf 'Timed out after 600 seconds
' >&2
exit 1
fi
STATUS_RESPONSE=$(curl --silent --show-error --fail-with-body \
--url "https://api.vidgo.ai/api/generate/status/$TASK_ID" \
--header "Authorization: Bearer $VIDGO_API_KEY")
STATUS=$(printf '%s' "$STATUS_RESPONSE" | jq -r '.data.status // .status // empty')
BUSINESS_CODE=$(printf '%s' "$STATUS_RESPONSE" | jq -r '.code // empty')
if [ "$BUSINESS_CODE" != "0" ] && [ "$BUSINESS_CODE" != "200" ]; then
printf 'Status request failed:
%s
' "$STATUS_RESPONSE" >&2
exit 1
fi
case "$STATUS" in
finished)
printf '%s' "$STATUS_RESPONSE" | jq -r '(.data.files // .files // [])[]?.file_url'
break
;;
failed)
printf '%s' "$STATUS_RESPONSE" | jq -r '.data.error_message // .error_message // "Generation failed"' >&2
exit 1
;;
not_started|running)
sleep "$POLL_DELAY"
if [ "$POLL_DELAY" -lt 10 ]; then POLL_DELAY=$((POLL_DELAY + 1)); fi
;;
*)
printf 'Unexpected task status: %s
' "$STATUS" >&2
exit 1
;;
esac
doneInput parameters
These are the fields accepted inside input. The request example shows the required top-level model field.
| Field | Type | Required | Default | Description |
|---|---|---|---|---|
| prompt | string | Yes | — | 1–20,000 characters after trimming. |
| duration | integer | No | 5 | An integer from 2 through 30, inclusive. |
| resolution | string | No | 720p | 480p, 720p, or 1080p. |
| aspect_ratio | string | No | adaptive | adaptive, 16:9, 4:3, 1:1, 3:4, or 9:16. |
| audio | boolean | No | true | Whether to request an audio track; does not change the credit rate. |
| seed | integer | No | — | Optional integer from 0 through 2147483647. |
| enable_safety_checker | boolean | No | true | Whether to enable the safety checker. |
Response Fields
Submission returns task identity immediately. Status responses add progress, every output file, or a failure message.
| Field | Type | Description |
|---|---|---|
| code | integer | Application result code; successful responses use 0 or 200. |
| message | string | Human-readable message or error detail when present. |
| data.task_id | string | Task ID used in the status endpoint path. |
| data.status | string | not_started, running, finished, or failed. |
| data.created_time | string | Task creation time in date-time format. |
| data.progress | integer | Task progress from 0 to 100, when included in the response. |
| data.files[] | array | All output files from a successful task, in response order. |
| data.files[].file_url | string | Public URL for a generated video. |
| data.files[].file_type | string | File type, such as video. |
| data.error_message | string | null | Failure detail when status is failed. |
Task Lifecycle
Treat not_started and running as non-terminal states. finished and failed are terminal alternatives; stop polling when either is returned.
not_startedThe task was accepted and is waiting to begin.
runningGeneration is in progress. Continue polling the same task_id.
finishedGeneration succeeded. Read every video URL from data.files[].file_url.
failedGeneration stopped with an error. Read data.error_message and stop polling.
Polling and Errors
- AuthenticationA 401 response means the Bearer API key is missing or invalid. Correct it before retrying.
- ValidationA 400 response identifies an invalid field, unsupported media key, or insufficient credit balance. Correct the request before resubmitting.
- Network and timeoutA transport failure is different from a failed task. Retry status checks with a bounded timeout before deciding that the task failed.
- Polling intervalStart around every 2 seconds and increase the interval gradually for a long-running task.
- Terminal statesContinue only for not_started or running. Stop immediately on finished or failed.
- Callback optionProvide callback_url at the request top level to receive the final flat task object; polling remains available if delivery fails.
Endpoint limits
| Specification | Value | Details |
|---|---|---|
| Input mode | Text only | A prompt defines the scene, action, camera direction, and sound intent. |
| Output | Video task | The endpoint returns an asynchronous task ID. |
| Resolution | 480p / 720p / 1080p | resolution defaults to 720p when omitted. |
| Duration | 2–30 seconds | Every integer value in the inclusive range is valid; default is 5. |
| Aspect ratio | Adaptive + 5 fixed | adaptive, 16:9, 4:3, 1:1, 3:4, or 9:16. |
| Billing basis | Input video seconds + output seconds | 480p uses 13.6 credits/s; 720p uses 28 credits/s; 1080p uses 56 credits/s. |
Related Models
Wan 3.0 Prime Text To Video API — Frequently asked questions
What is the Wan 3.0 Prime Text-to-Video API?
Wan 3.0 Prime Text-to-Video is an Alibaba Tongyi Lab model for generating high-definition video from text. It creates high-fidelity videos up to 30 seconds at up to 1080p resolution with native synchronized audio from complex multi-layered prompts, featuring enhanced dynamic physical realism and precise cinematographic movement. Built on Wan 3.0 Prime's upgraded spatiotemporal reasoning architecture, it delivers exceptional character structural stability and natural camera fluidity across long cinematic takes. You can call it programmatically or try it from the playground above.
What performance enhancements does Wan 3.0 Prime Text-to-Video offer over Wan 3.0?
Wan 3.0 Prime delivers significant upgrades in character anatomy stability, fine-grained physics (such as liquid dynamics, fabric folds, and particles), and cinematographic lighting consistency over Wan 3.0. In complex multi-beat scenes, Prime follows layered action instructions more faithfully with reduced artifact distortion.
Can Wan 3.0 Prime Text-to-Video generate 30-second videos in a single task?
Yes. The model natively supports specifying any duration between 2 and 30 seconds (defaulting to 5 seconds). Across a 30-second single take, the model maintains consistent character identity, continuous motion trajectories, and natural temporal rhythm.
Is audio generated natively alongside video in Wan 3.0 Prime Text-to-Video?
Yes. Audio latents are co-synthesized within the multimodal diffusion framework alongside video frames. When audio is set to true (default), the model automatically infers environmental acoustics, Foley sounds, and action interactions from your prompt text.
How should I prompt multi-beat camera moves in Wan 3.0 Prime Text-to-Video?
We recommend organizing prompts into chronological stages using cues such as "first", "then", and "finally". Separate character choreography from camera movement instructions (e.g. low-angle tracking shot, slow push-in) to ensure the model executes each motion phase coherently.
Does Wan 3.0 Prime Text-to-Video support all major aspect ratios?
Yes. The model provides adaptive aspect ratio alongside 16:9 widescreen, 4:3 standard, 1:1 square, 3:4 portrait, and 9:16 vertical formats. Adaptive framing automatically selects the optimal composition based on scene content, while 9:16 targets vertical social feeds directly.
Can I draft prompts with Wan 3.0 Prime Text-to-Video in 480p to conserve credits?
Yes. The model offers 480p, 720p, and 1080p tiers. Generating at 480p consumes only 13.6 credits/s, making it ideal for verifying prompt choreography, scene staging, and camera pacing before committing to full 1080p production rendering.















