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minimax/hailuo-02/t2v-standard

Hailuo 02 is a text-to-video model on MiniMax, fine-tuned to output responsive 768P videos even for complex physics-driven scenes. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Text to Video
Input
The model automatically optimizes incoming prompts to enhance output quality. This also activates the safety checker, which ensures content safety by detecting and filtering potential risks.

Idle

$0.28per run·~35 / $10

Next:

ExamplesView all

A golden retriever runs joyfully along a sunny beach at sunset, waves rolling onto the sand, slow tracking shot.

A confident woman walking alone through an upscale lounge bar, wearing a black slit gown, subtle flirtatious expressions, cinematic camera sweep

A realistic video of a young man walking down a busy city street, sunlight reflecting on glass buildings, natural footsteps, slight camera shake, people passing by, realistic lighting and shadows, the man glances around casually and adjusts his jacket, cinematic urban atmosphere

a realistic video of a woman sitting by the window in a coffee shop, typing on her laptop, soft natural light on her face, steam rising from a cup of coffee, shallow depth of field, gentle background motion, natural breathing and subtle head movements

Related Models

README

Hailuo 02 — Text-to-Video (T2V Standard)

minimax/hailuo-02/t2v-standard converts pure text into cinematic video with strong prompt adherence, believable physics, and smooth scene transitions. Built on MiniMax’s evolving framework, it balances quality, speed, and cost for everyday creative production.

Why it works

  • 768p output — crisp frames, ready for editing.
  • 6s / 10s clips — fast ideation or trailer-style beats.
  • Enhanced motion & physics — debris, cloth, water, camera shake look natural.
  • Cinematic continuity — fewer artifacts; smoother temporal flow.
  • Repeatable — low randomness for the same prompts.

Limits & Performance

  • Resolution: 768p
  • Durations: 6s or 10s
  • Runtime: ~30–90 s per clip (scene complexity & queue dependent)

Pricing

DurationResolutionPrice
6 seconds768p$0.28
10 seconds768p$0.56

Pricing is per generated video, based on the selected duration.

How to Use

  1. Prompt — Describe scene, lighting, motion, and camera.
  2. Duration — Choose 6s or 10s.
  3. (Optional) Prompt expansion — Enable for smarter parsing & safety.
  4. Run — Review, tweak prompt/seed, and iterate.

Pro Tips

  • Write like a director: shot type, camera move, lighting, mood.
  • Use action verbs: dolly in, orbit, rack focus, particles swirl.
  • Start with 6s for quick iterations; assemble multiple clips for longer stories.
  • Add your own music/VO for complete narratives.
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.

Hailuo 02 T2v Standard API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/hailuo-02/t2v-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 T2v 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/t2v-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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/minimax/hailuo-02/t2v-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "duration": 6,
        "enable_prompt_expansion": false
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  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/t2v-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 = 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", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Hailuo 02 T2v Standard API — Frequently asked questions

What is the Hailuo 02 T2v Standard API?

Hailuo 02 T2v Standard is a MiniMax model for video generation, exposed as a REST API on WaveSpeedAI. Hailuo 02 is a text-to-video model on MiniMax, fine-tuned to output responsive 768P videos even for complex 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.

How do I call the Hailuo 02 T2v 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 Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/minimax/minimax-hailuo-02-t2v-standard.

How much does Hailuo 02 T2v Standard cost per run?

Hailuo 02 T2v Standard starts at $0.28 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 T2v Standard accept?

Key inputs: `prompt`, `duration`, `enable_prompt_expansion`. 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-t2v-standard.

How long does Hailuo 02 T2v Standard take to generate?

Reported generation time on WaveSpeedAI is around 89 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.

Can I use Hailuo 02 T2v Standard outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (MiniMax). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — minimax/hailuo-02/t2v-standard for AI agents and LLMs