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MiniMax H3 Text-to-Video API

minimax/h3/text-to-video

MiniMax H3 Text to Video generates coherent 2K videos from text prompts, with flexible 5-15 second duration and adaptive or custom aspect ratios for cinematic scenes, creative videos, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Text to Video
Input

Idle

$0.1per run·~10 / $1

ExamplesView all

A young woman in a long pale coat walks toward a small stone chapel on a windswept cliff above the ocean. The opening frame is a cinematic long-lens medium-wide shot with tall coastal grass softly blurred in the foreground. She is illuminated by a break in the clouds while the chapel and dark ocean remain slightly subdued behind her. She stops halfway along the path when the chapel bell rings once. A man appears briefly in the doorway, then steps back into darkness. The camera slowly tracks through the foreground grass, keeping her centered in the moving composition, then gently pushes toward the chapel. Poetic romantic mystery, dramatic coastal light, strong depth separation, natural wind, restrained acting, cinematic European drama aesthetic.

Speeder chase across a cliff city (single continuous shot) From a monumental cliffside city carved into stone, the camera dives toward a tiny streak of light ripping along a narrow ledge-road. Lock-on: a speeder hugging the wall at insane speed. The camera slingshots ahead, whips back, then drops tight to the rear thrusters: heat haze, grit snapping off the ledge, warning lights flashing. A collapsing balcony rains debris; the rider snaps a last-inch swerve under a falling arch, then threads through hanging laundry lines and open windows in one fluid line. The camera darts through the same openings, staying glued to the motion. One final bend and sudden calm: the camera blasts outward into a reveal of the city opening onto a boundless waterfall-fed valley, mist turning into rainbow.

Related Models

README

MiniMax H3 Text-to-Video

MiniMax H3 Text-to-Video generates high-resolution videos from text prompts. Describe the video scene, action, camera movement, and visual style, then choose aspect ratio and duration to create a 2k video output.

Why Choose This?

  • Text-to-video generation
    Generate videos directly from natural-language prompts.

  • 2K video output
    Create high-resolution video outputs with the fixed 2k resolution tier.

  • Flexible aspect ratios
    Supports wide, landscape, square, portrait, and vertical formats including 21:9, 16:9, 4:3, 1:1, 3:4, and 9:16.

  • Selectable duration
    Generate videos from 4 to 15 seconds.

  • Simple generation workflow
    Provide a prompt, choose aspect ratio and duration, then generate the final video.

Parameters

ParameterRequiredDescription
promptYesText description of the video scene, action, camera movement, and style. Minimum length: 1 character.
aspect_ratioNoOutput aspect ratio: 21:9, 16:9, 4:3, 1:1, 3:4, or 9:16.
resolutionNoOutput video resolution. Supported values: 768p or 2k.
durationNoOutput video duration in seconds. Supported values: 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15.

How to Use

  1. Write your prompt — Describe the scene, subject, action, camera movement, lighting, mood, and visual style.
  2. Choose aspect ratio — Select the layout that matches your target format.
  3. Set duration — Choose a video length from 4 to 15 seconds.
  4. Submit — Generate the video and retrieve the output URL.

Pricing

Pricing is based on output resolution and generated video duration.

ResolutionPer second5s10s15s
768p$0.10$0.50$1.00$1.50
2K$0.14$0.70$1.40$2.10

Best Use Cases

  • Cinematic video generation — Create high-resolution video scenes from detailed text prompts.
  • Marketing and campaign videos — Generate polished video concepts for ads, brand visuals, and promotional content.
  • Social media content — Produce landscape, square, or vertical videos for different platforms.
  • Story and scene prototyping — Turn written ideas into short motion clips for creative planning.
  • Visual concept development — Explore camera movement, action, lighting, and mood before production.

Pro Tips

  • Use detailed prompts with subject, action, camera movement, lighting, style, and mood.
  • Choose 16:9 for widescreen video, 9:16 for vertical mobile content, and 1:1 for square layouts.
  • Use 21:9 for cinematic wide-frame scenes.
  • Use shorter durations for quick prompt testing and longer durations when the scene needs more time to develop.
  • Keep the prompt focused on visible motion and scene progression.

Related Models

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.

H3 Text To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/h3/text-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 H3 Text To Video 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",
    "aspect_ratio": "16:9",
    "resolution": "768p",
    "duration": 5
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/minimax/h3/text-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="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/h3/text-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "16:9",
        "resolution": "768p",
        "duration": 5
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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",
    "aspect_ratio": "16:9",
    "resolution": "768p",
    "duration": 5
}

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/h3/text-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 = 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)

H3 Text To Video API — Frequently asked questions

What is the H3 Text To Video API?

H3 Text To Video is a MiniMax model for video generation, exposed as a REST API on WaveSpeedAI. MiniMax H3 Text to Video generates coherent 2K videos from text prompts, with flexible 5-15 second duration and adaptive or custom aspect ratios for cinematic scenes, creative videos, and production workflows. 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 H3 Text To Video 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-h3-text-to-video.

How much does H3 Text To Video cost per run or per second?

H3 Text To Video starts at $0.1 per run or per second. 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 H3 Text To Video accept?

Key inputs: `prompt`, `aspect_ratio`, `resolution`, `duration`. 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-h3-text-to-video.

How long does H3 Text To Video take to generate?

Reported generation time on WaveSpeedAI is around 161 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 H3 Text To Video 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/h3/text-to-video for AI agents and LLMs