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WAN 2.5 converts text or images into videos (480p/720p/1080p) with synced audio, faster and more affordable than Google Veo3. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
Input

Idle

$0.25per run·~40 / $10

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ExamplesView all

A confident woman in her 40s stands on a stage with a microphone. The background shows a large LED screen with abstract visuals. She smiles and begins speaking to the audience: “Good evening everyone. Tonight, I want to share three powerful lessons about leadership and innovation.” Her lip movements match her voice, and she uses expressive hand gestures while speaking.

A young man sits still on a subway train, surrounded by blurred figures moving rapidly. [Close-up] His eyes, barely blinking, intensify the sense of loneliness.

A man in his 30s jogging along a riverside path at dawn. His breathing is heavy, footsteps rhythmic, and the distant sound of water flowing adds to the calm. Between breaths, he says: 'One more mile… I can do this.' Birds begin to sing as the sun rises in the background.

Anime style, reminiscent of Makoto Shinkai. A high school boy and girl meet for the first time on a train platform during a gentle spring rain shower. Cherry blossom petals are falling and sticking to the wet ground. The world is reflected in the puddles. Sunlight breaks through the clouds, creating breathtaking light rays (crepuscular rays). Emotional, detailed background art, vibrant colors, cinematic lighting.

The mountain biker leans into a steep rocky descent, tires kicking up dust as the sunset casts long shadows over the valley. The wide angle camera follows the rider’s dynamic fast motion, gloves gripping handlebars tightly, golden light intensifying across the mountainous terrain. Quick moving footage.

Related Models

README

WAN 2.5 Image-to-Video Model

WAN 2.5 is an advanced image-to-video model on Cloud’s DashScope. It generates high-quality videos from images and supports output resolutions of 480p, 720p, and 1080p.

What makes it stand out?

  • More affordable: Wan 2.5 is more streamlined and cost-effective - reducing creator expenses and offering more options.
  • One-pass A/V sync: Wan 2.5 creates a fully synchronized video (audio/voiceover + lip-sync) from a single, well-structured prompt - no separate recording or manual alignment required.
  • Multilingual friendly: Wan 2.5 reliably processes like Chinese prompts for A/V-synced videos.
  • Longer duration & more video size options: Wan 2.5 delivers up to 10 seconds and 6 aspect/size options, enabling more storytelling room and publishing flexibility.
  • Custom Voice: Add your own audio or let the model generate one for you. Plug-and-play, easy to swap!

Designed For

  • Marketing teams: Fast, polished demos/tutorials—low cost, consistent style.
  • Global enterprises: Multilingual, lip-synced videos with subtitles for efficient localization.
  • Storytellers & YouTubers: Immersive narratives while maintaining cadence and quality—driving growth.
  • Corporate training teams: HD videos over docs—clearer key points, better communication.
  • Custom Voice: Add your own audio or let the model generate one for you. Plug-and-play, easy to swap!

Pricing

ResolutionPrice per second
480p$0.05
720p$0.10
1080p$0.15

How to Use

  1. Write your prompt.
  2. Upload an audio file (optional) for voice/music.
  3. Choose the video size (resolution/aspect).
  4. Select the video duration (e.g., 5s / 10s).
  5. Submit and wait for processing.
  6. Preview and download the result.

Note

Audio limits

  • Formats: wav, mp3
  • Length: 3–30 seconds
  • File size: ≤ 15 MB

Over-limit handling

  • If the audio exceeds the target duration (5s or 10s), the model keeps only the first 5s/10s; the rest is discarded.
  • If the audio is shorter than the video duration, the extra video part is silent.

Image Upload

  • If you did not upload the image locally, please ensure that the image URL is accessible! A successfully accessible image will display a preview in the interface.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Wan 2.5 Image To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/alibaba/wan-2.5/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 2.5 Image To Video below.

HTTP example
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",
    "duration": 5,
    "enable_prompt_expansion": false,
    "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/alibaba/wan-2.5/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=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/alibaba/wan-2.5/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "resolution": "720p",
        "duration": 5,
        "enable_prompt_expansion": false,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
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",
    "duration": 5,
    "enable_prompt_expansion": False,
    "seed": -1
}

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-2.5/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 = task.get("urls", {}).get("get") or 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"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Wan 2.5 Image To Video API — Frequently asked questions

What is the Wan 2.5 Image To Video API?

Wan 2.5 Image To Video is a Alibaba model for video generation from images, exposed as a REST API on WaveSpeedAI. WAN 2.5 converts text or images into videos (480p/720p/1080p) with synced audio, faster and more affordable than Google Veo3. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Wan 2.5 Image To Video API?

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 production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/alibaba/alibaba-wan-2.5-image-to-video.

How much does Wan 2.5 Image To Video cost per run?

Wan 2.5 Image To Video starts at $0.25 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.

What inputs does Wan 2.5 Image To Video accept?

Key inputs: `prompt`, `image`, `audio`, `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-2.5-image-to-video.

How long does Wan 2.5 Image To Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 51 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Wan 2.5 Image To Video outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Alibaba). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Wan 2.5 Image to Video | Fast Image-to-Video API on WaveSpeedAI