WAN 2.1 T2V 480p Ultra-Fast turns text prompts into unlimited 480p AI videos with ultra-fast throughput and reliable 480p output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Siap
$0.125per run·~80 / $10
A man on top of a jumping bull at a rodeo party, he is dressed as a cowboy with a cowboy hat.
Ultra realistic 8k miniature world scene with mini Easter bunnies working on building a giant chocolate egg. Some bunnies are on ladders decorating the egg with colorful candies, others are driving tractors and carts carrying chocolate pieces. There are shovels and toy tools scattered around. The environment is cheerful, with flowers, giant carrots in the background, blue sky and spring weather. Cute, magical, detailed and cinematic style.
Guerra celestial entre anjos com espada no céu com relâmpagos.
the girl is talking and smiling
"A esposa de Ló, contra o aviso dos anjos, olha para trás e é instantaneamente transformada em uma estátua de sal. Seu corpo petrificado, com expressão de terror, permanece no deserto, enquanto Ló e suas filhas fogem, sem ousar voltar."
An ancient Japanese temple nestled in a bamboo forest, misty morning, traditional architecture, harmonious colors, peaceful ambiance, volumetric lighting, digital painting.
A majestic lion roaring, golden mane flowing, against a backdrop of the African savanna, dust rising, golden hour, wildlife photography, powerful, dynamic.
A steampunk city at night, with glowing gears and steam plumes rising from intricate clockwork towers. Airships with brass propellers drift lazily across a starry sky. The streets are wet from rain, reflecting the neon signs.
An elderly artisan with calloused hands meticulously carving intricate details into a wooden sculpture in his sunlit workshop. Wood shavings curl around his tools, and a faithful dog naps peacefully by his feet.
A tranquil mountain lake at dawn, mist gently rising from the glassy surface. A lone wooden rowboat drifts slowly near the shore, reflecting the soft pastel colors of the rising sun and the distant snow-capped peaks
An elderly couple dancing slowly and gracefully on a seaside promenade at sunset, their silhouettes against the fiery orange sky. The gentle ocean breeze plays with their clothes, and the waves softly lap the shore in the background.
A curious red fox tiptoeing through a snow-covered winter wonderland. Its fluffy tail brushes the fresh powder, and its keen eyes scan the silent landscape for movement. Sunlight sparkles on the snow.
Wan 2.1 T2V 480p Ultra Fast is a text-to-video model optimized for speed and iteration. Write a prompt, pick a duration, and generate a short 480p video quickly—ideal for rapid concept testing, storyboard previews, and high-volume variations.
| Output | Duration | Price per video | Price per second |
|---|---|---|---|
| 480p T2V Ultra Fast | 5s | $0.125 | $0.0250/s |
| 480p T2V Ultra Fast | 10s | $0.1875 | $0.01875/s |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-480p-ultra-fast with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Wan 2.1 T2v 480p Ultra Fast below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"guidance_scale": 5,
"flow_shift": 3,
"seed": -1
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-480p-ultra-fast" \
-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/wavespeed-ai/wan-2.1/t2v-480p-ultra-fast";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"guidance_scale": 5,
"flow_shift": 3,
"seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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",
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"guidance_scale": 5,
"flow_shift": 3,
"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/wavespeed-ai/wan-2.1/t2v-480p-ultra-fast", 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 2.1 T2v 480p Ultra Fast is a WaveSpeedAI model for video generation, exposed as a REST API on WaveSpeedAI. WAN 2.1 T2V 480p Ultra-Fast turns text prompts into unlimited 480p AI videos with ultra-fast throughput and reliable 480p output. 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 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/wavespeed-ai/wan-2.1-t2v-480p-ultra-fast.
Wan 2.1 T2v 480p Ultra Fast starts at $0.13 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`, `duration`, `size`, `seed`, `guidance_scale`, `num_inference_steps`. 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/wavespeed-ai/wan-2.1-t2v-480p-ultra-fast.
Median end-to-end generation time on WaveSpeedAI is around 111 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 (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.