Seedance 2.0 (Image-to-Video) generates Hollywood-grade cinematic videos from reference images and text prompts with native audio-visual synchronization, director-level camera and lighting control, and exceptional motion stability. Built on Seed's unified multimodal architecture, it preserves the input image's subject and composition while adding expressive, physically accurate motion.
Idle
$0.6per run·~16 / $10
Low-angle wide shot, athletic blonde woman with low side braid, toned glistening abs covered in sweat, white sport sunglasses reflecting blue sky, thick white sweat wristbands on both wrists. She wears white racerback sports bra, unzipped lightweight black windbreaker, black high-waisted leggings. Dynamic slow subtle movement: right hand lifts to forehead to block harsh midday sun, left hand rests firmly on hip, head tilts slightly upward gazing far away. Bright scorching noon sunlight, hard high-contrast shadows, vivid saturated clear cerulean sky with wispy white clouds background. Vintage Kodak Gold 200 film texture, soft natural film grain, warm sharp highlights on glistening skin, natural skin texture, fast subtle camera slow pan right, crisp 4K 60fps, bright clean sport fashion aesthetic, upbeat energetic summer vibe, no text, no distortion.
5-second luxury watch commercial clip, slow smooth push-in camera movement, tropical beach background with palm tree, white parasol and clear turquoise sea, handsome european man with slick dark hair, pink knit zip polo shirt, resting cheek on hand, focus on pilot watch with brown leather strap on wrist, bright warm summer daylight, realistic fabric and metal texture, soft natural motion, 4K editorial fashion video, no flickering
Wide-angle first-person selfie skydiving footage, caucasian tandem pair leaping out of white WaveSpeed skydiving plane, background clear blue sky, sea of clouds and snow-capped alpine mountains; young blonde european woman in front with white helmet and clear goggles, grey-red jumpsuit, arms spread wide laughing and speaking excitedly; behind her european male instructor with backwards black cap and black sunglasses, red-black jumpsuit, stretching arm forward for selfie, shouting happily; natural lip movements for short excited dialogue, fast-paced dynamic smooth camera, subtle handheld shake to simulate free fall, bright harsh midday sunlight, vibrant realistic documentary aesthetic, ultra clear details of safety harnesses, "WaveSpeed" text on fuselage, mountain cloud layers, 4K 60fps cinematic travel adventure clip
Seedance 2.0 is Seed's latest video generation model, built on a unified multimodal architecture. The Image-to-Video mode generates production-grade cinematic videos from reference images and text prompts — preserving the input image's subject, composition, and style while adding expressive motion with native audio synchronization.
Unified multimodal architecture A single model that handles text, image, audio, and video inputs for comprehensive creative flexibility.
Image-faithful generation Preserves the reference image's subject identity, composition, lighting, and style while animating it into motion.
Multi-image reference support Guide generation with up to 4 reference images for consistent style, characters, or scenes.
Native audio-visual synchronization Generates video with synchronized audio in a single pass.
Director-level control Granular control over camera movement, lighting, shadows, and character performance through prompts.
Exceptional motion stability Industry-leading motion coherence with stable subjects, consistent physics, and fluid transitions.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Detailed description of the cinematic scene |
| image | Yes | Start image URL to guide the video generation |
| last_image | No | Last frame image URL for video continuation |
| duration | No | Video length in seconds: 4-15 (default: 5) |
| aspect_ratio | No | Output format: 16:9, 9:16, 4:3, 3:4, 1:1, 21:9 (default: adaptive) |
| resolution | No | Output resolution: 480p, 720p (default), 1080p, or 4k |
| Resolution | Duration | Cost |
|---|---|---|
| 480p | 5 s | $0.60 |
| 480p | 10 s | $1.20 |
| 480p | 15 s | $1.80 |
| 720p | 5 s | $1.20 |
| 720p | 10 s | $2.40 |
| 720p | 15 s | $3.60 |
| 1080p | 5 s | $3.00 |
| 4k | 5 s | $6.00 |
| 1080p | 10 s | $6.00 |
| 4k | 10 s | $12.00 |
| 1080p | 15 s | $9.00 |
| 4k | 15 s | $18.00 |
Prices scale linearly with duration (4-15 seconds).
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bytedance/seedance-2.0/image-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Seedance 2.0 Image To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"enable_web_search": false,
"generate_audio": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/bytedance/seedance-2.0/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=$(printf '%s' "$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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/bytedance/seedance-2.0/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"enable_web_search": false,
"generate_audio": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"enable_web_search": False,
"generate_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/bytedance/seedance-2.0/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 = 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)Seedance 2.0 Image To Video is a ByteDance model for video generation from images, exposed as a REST API on WaveSpeedAI. Seedance 2.0 (Image-to-Video) generates Hollywood-grade cinematic videos from reference images and text prompts with native audio-visual synchronization, director-level camera and lighting control, and exceptional motion stability. Built on Seed's unified multimodal architecture, it preserves the input image's subject and composition while adding expressive, physically accurate motion. 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 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/bytedance/bytedance-seedance-2.0-image-to-video.
Seedance 2.0 Image To Video starts at $0.60 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`, `enable_web_search`. 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/bytedance/bytedance-seedance-2.0-image-to-video.
Median end-to-end generation time on WaveSpeedAI is around 227 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (ByteDance). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.