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Hailuo 02 Standard

minimax /

Hailuo 02 is an AI video-generation model delivering 768P output with fast responsiveness and strong handling of complex physics scenes. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
Input

Inattivo

$0.23per esecuzione·~43 / $10

Successivo:

EsempiVedi tutto

A kitten chases a bouncing rubber ball across a polished wooden floor, sliding slightly and bumping into a potted plant.

Soft spotlight hits a ballerina as she twirls gracefully on a dusty wooden stage, particles swirling around her feet.

A woman rides a hoverbike across a cracked desert highway, dust trailing behind her, while abandoned mechs lie rusting under the harsh sun.

A young elephant balances on a large rubber ball in a dusty circus ring, flapping its ears for balance as children cheer.

A golden retriever puppy runs across a bright green meadow filled with dandelions, ears flapping, sunlight bouncing off its fur in slow motion.

Modelli correlati

README

minimax/hailuo-02/standard

Hailuo 02 Standard is the unified model on MiniMax’s framework. It generates cinematic clips with 768p clarity, strong prompt adherence, believable physics, and smooth temporal transitions. Use it as pure T2V (text only) or guided I2V (add a start image, optional end image for a planned transition).

Why creators like it

  • One endpoint, two modes — Text-to-Video or Image-guided Video.
  • Native 768p — crisp frames, not upscaled.
  • 6s / 10s clips — quick iteration or trailer pacing.
  • Physics & motion — debris, cloth, water, handheld shake look natural.
  • Stable & repeatable — good consistency across re-runs.

Parameters

NameDescription
prompt*Describe scene, lighting, motion, and camera.
image(Optional) Use a reference/first frame (JPG/PNG) to lock composition & style.
end_image(Optional) Target frame for a guided transition.
duration6s or 10s.
enable_prompt_expansionAuto-refines prompt and runs a safety check.

Pricing

DurationCost per jobResolution
6 s$0.23768p
10 s$0.56768p

How to use (short)

  1. Write a prompt (include camera + motion + lighting).
  2. (Optional) Add image (and end_image for a transition).
  3. Pick duration (6s/10s), keep prompt expansion on.
  4. Run → review → tweak prompt → re-run.

Example prompts

  • A boy and his dog race along the beach at sunset; camera tracks low and wide, warm reflections on wet sand, gentle spray, cinematic grade.
  • Slow orbit around a neon-lit street food stall in the rain; steam and bokeh, handheld vibe, rack focus to the chef’s hands.
Nota:Questo sito web utilizza modelli di intelligenza artificiale forniti da terze parti.

Hailuo 02 Standard API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/hailuo-02/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 Standard 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",
    "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/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
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/minimax/hailuo-02/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "duration": 6,
        "enable_prompt_expansion": false
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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));
}
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",
    "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/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 Standard API — Frequently asked questions

What is the Hailuo 02 Standard API?

Hailuo 02 Standard is a MiniMax model for video generation from images, exposed as a REST API on WaveSpeedAI. Hailuo 02 is an AI video-generation model delivering 768P output with fast responsiveness and strong handling of complex physics 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.

How do I call the Hailuo 02 Standard 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/minimax/minimax-hailuo-02-standard.

How much does Hailuo 02 Standard cost per run?

Hailuo 02 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.

What inputs does Hailuo 02 Standard accept?

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-standard.

How long does Hailuo 02 Standard take to generate?

Median end-to-end generation time on WaveSpeedAI is around 106 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 Hailuo 02 Standard outputs commercially?

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.

Hailuo 02 Standard | Fast Image-to-Video API | WaveSpeedAI