Wan 3.0 Image to Video animates a first-frame image into a cinematic video, with optional last-frame guidance, flexible 2-30 second duration, aspect ratio control, optional audio, and deep-thinking controls for high-quality motion and scene continuity. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.475per run·~21 / $10
The dragon slowly opens its eyes, leaves move from its breathing, glowing particles float around the forest, the ranger slowly steps forward and reaches out a hand. The camera slowly circles around both characters revealing the enormous scale difference.
Heavy rain pours through the bamboo forest. The samurai slowly turns his head, then in one lightning-fast motion draws his katana and slices a falling bamboo leaf in half mid-air. Water sprays from the blade, leaves swirl around him. The camera pushes in from a low angle. Sound of rain, rustling bamboo and the sharp ring of steel.
The giant jellyfish pulses gracefully, its bioluminescent bell glowing brighter with each beat, trailing tentacles drifting through the dark water. The diver slowly reaches out a gloved hand as tiny glowing particles swirl between them. The camera glides slowly around both, revealing the vast deep ocean. Muffled underwater ambience, deep resonant hum, rising bubbles.
Luxury watch commercial. A single drop of water falls onto the watch glass in slow motion and splashes into sparkling droplets. The second hand ticks forward as a beam of warm light sweeps across the polished steel bracelet. The camera slowly orbits the watch in a smooth macro move. Elegant minimal soundtrack with soft ticking.
The burner above the basket roars with a burst of flame, and the balloon rises gently over the canyon as dozens of colorful balloons drift in the golden sunrise. The woman leans on the basket edge, looks at the camera and says with a big smile: "Best morning of my life. Look at this view!" The camera slowly pulls back into a wide aerial shot of the canyon.
Wan 3.0 Image-to-Video animates a first-frame image into a coherent video with optional last-frame guidance, audio generation, and prompt expansion. It preserves the input image's subject and composition while adding prompt-guided motion, camera movement, and scene progression.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | First-frame image URL or Base64-encoded data. |
| last_image | No | Optional last-frame image used to guide the ending of the video. |
| prompt | Yes | Text prompt describing the desired motion, action, scene, camera movement, lighting, and style. |
| resolution | No | Output resolution: 480p, 720p, or 1080p. Default: 720p. |
| aspect_ratio | No | Output aspect ratio. If omitted, the output adapts to the input image. |
| duration | No | Output duration in seconds. Range: 2–30. Default: 5. |
| enable_prompt_expansion | No | Enable prompt expansion for more deliberate prompt interpretation. Default: false. |
| enable_audio | No | Include audio in the output. Default: true. |
| seed | No | Random seed from 0 to 2147483647. |
last_image when you want to control the final frame or ending direction.480p for lower-cost drafts, 720p for balanced output, or 1080p for higher quality.2 to 30 seconds.enable_audio enabled when audio is needed.enable_prompt_expansion for more complex motion or composition instructions.Pricing is based on output resolution and billed duration.
Billed duration is rounded up to the next whole second and clamped to the 2–30s range.
| Resolution | Per 5s | Per second |
|---|---|---|
| 480p | $0.25 | $0.05 |
| 720p | $0.50 | $0.10 |
| 1080p | $1.00 | $0.20 |
| Resolution | 2s | 5s | 10s | 30s |
|---|---|---|---|---|
| 480p | $0.10 | $0.25 | $0.50 | $1.50 |
| 720p | $0.20 | $0.50 | $1.00 | $3.00 |
| 1080p | $0.40 | $1.00 | $2.00 | $6.00 |
image and last_image to guide both the beginning and ending of the video.last_image when the final pose, composition, or ending frame matters.480p for quick drafts and 1080p for higher-quality output.enable_prompt_expansion for complex prompts with multiple movement or composition requirements.seed when you want more reproducible results.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/alibaba/wan-3.0/image-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Wan 3.0 Image To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"resolution": "720p",
"aspect_ratio": "16:9",
"duration": 5,
"enable_prompt_expansion": false,
"enable_audio": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/alibaba/wan-3.0/image-to-video" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/alibaba/wan-3.0/image-to-video";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"resolution": "720p",
"aspect_ratio": "16:9",
"duration": 5,
"enable_prompt_expansion": false,
"enable_audio": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"resolution": "720p",
"aspect_ratio": "16:9",
"duration": 5,
"enable_prompt_expansion": False,
"enable_audio": True
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/alibaba/wan-3.0/image-to-video", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Wan 3.0 Image To Video is a Alibaba model for video generation from images, exposed as a REST API on WaveSpeedAI. Wan 3.0 Image to Video animates a first-frame image into a cinematic video, with optional last-frame guidance, flexible 2-30 second duration, aspect ratio control, optional audio, and deep-thinking controls for high-quality motion and scene continuity. 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/alibaba/alibaba-wan-3.0-image-to-video.
Wan 3.0 Image To Video starts at $0.475 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`, `image`, `aspect_ratio`, `resolution`, `duration`, `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/alibaba/alibaba-wan-3.0-image-to-video.
Reported generation time on WaveSpeedAI is around 312 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Alibaba). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.