Hailuo 02 by Hailuo AI is an image-to-video model delivering ultra-clear 768P video with responsive handling of physics-driven scenes. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
待機中
$0.231回あたり·~43 / $10
An epic scene, a colossal ancient dragon perched atop a jagged volcanic peak, smoke billowing, lava flowing, storm clouds gathering, dramatic lighting, fantasy art, cinematic, highly detailed scales, breathtaking.
The girl in the image begins performing a graceful ballet solo on a grand theater stage, she twirls and lifts one leg into an arabesque, soft spotlight follows her every move, cinematic lighting, slow camera pan from left to right, elegant and fluid motion
The girl in the image starts moving gracefully through a misty forest, twirling slowly, extending her arms as leaves swirl around her, camera rotates gently around her body, cinematic lighting, realistic motion
The girl in the image performs a powerful contemporary dance on a dimly lit stage, her arms sweep dramatically, her body spins and contracts with emotion, moody spotlight and rotating camera, fast yet expressive motion
The boy in the image breaks into a high-energy hip-hop dance on an urban rooftop, spinning, body popping, footwork fast and rhythmic, wide-angle drone camera sweeps across the scene, cinematic tone
The dancer in the image gracefully moves across the stage with a flowing silk ribbon, spinning and leaping, ribbon twirls through the air, elegant camera dolly-in, warm stage lighting
The man in the image performs a slow and controlled Tai Chi sequence in a misty mountain setting, his hands flow like water, camera slowly zooms and pans, peaceful and meditative motion
A playful puppy, excitedly chasing a rolling ball across a lush green park. Its ears flap in the wind, and its tail wags furiously. Low-angle tracking shot, bright daylight, energetic and cheerful ambiance.
Pixel art style,An inquisitive squirrel, busily burying nuts in a sun-dappled forest floor. Leaves crunch softly under its tiny paws, and dappled light filters through the canopy. Close-up, natural lighting, peaceful and lively ambiance.
Masterpiece, ultra-detailed, photorealistic portrait of an ancient wise wizard with glowing eyes, dramatic volumetric lighting, cinematic, studio shot, sharp focus, 8k, award-winning photography.
Close-up, high-definition shot of a rusty, weathered vintage car in a desolate desert, cinematic dust clouds, harsh sunlight, intricate textures, dust particles in air, 100mm lens, professional automotive photography.
Hailuo 02 (Standard, I2V) is Hailuo AI’s image-to-video model built on MiniMax’s evolving framework. It’s fine-tuned for ultra-clear 768p output, high prompt responsiveness, and robust physics—even in chaotic, action-heavy scenes.
| Duration | Price |
|---|---|
| 6 s | $0.23 |
| 10 s | $0.56 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/hailuo-02/i2v-standard with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Hailuo 02 I2v Standard below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"duration": 6,
"enable_prompt_expansion": false
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/minimax/hailuo-02/i2v-standard" \
-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/minimax/hailuo-02/i2v-standard";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"duration": 6,
"enable_prompt_expansion": false
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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 = {
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"duration": 6,
"enable_prompt_expansion": False
}
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/minimax/hailuo-02/i2v-standard", 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)Hailuo 02 I2v Standard is a MiniMax model for video generation from images, exposed as a REST API on WaveSpeedAI. Hailuo 02 by Hailuo AI is an image-to-video model delivering ultra-clear 768P video with responsive handling of physics-driven scenes. 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/minimax/minimax-hailuo-02-i2v-standard.
Hailuo 02 I2v Standard starts at $0.23 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`, `duration`, `enable_prompt_expansion`, `end_image`. 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/minimax/minimax-hailuo-02-i2v-standard.
Median end-to-end generation time on WaveSpeedAI is around 108 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 (MiniMax). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.