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MiniMax H3 Open Weights Text to Video with custom LoRA support generates coherent videos from text prompts, with 480P / 768P output, native stereo audio, 5-15 second duration, flexible aspect ratios, and per-second billing. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

lora-support
Input

Idle

$0.25per run·~40 / $10

ExamplesView all

The big fluffy grey rabbit strolls through the sunny meadow, stops under a large tree, looks up at a butterfly fluttering around his nose and breaks into a warm smile. Bright daylight, vivid colors, gentle camera pan. Audio: light-hearted orchestral score, birdsong and a soft breeze.

Related Models

README

MiniMax H3 Text-to-Video LoRA (Open Weights)

Run the open-weights edition of MiniMax H3 on WaveSpeedAI's own GPU infrastructure. This endpoint is separate from the official minimax/h3 API: same model family, independently hosted, with its own 480p/768p resolutions and per-second pricing.

MiniMax H3 is an omni-modal video model that generates picture and native stereo audio in a single pass — dialogue, sound effects, and music are produced together during generation, never added as a separate dubbing step. Describe both the visuals and the sound in one prompt and the model delivers a finished MP4 with a matching soundtrack.

How to Write a Great Prompt

H3 responds to prompts written as a timeline with a schedule, not a one-line description. The strongest prompts layer these blocks:

  1. Style — visual language up front: era, palette, texture, mood (e.g. "warm 1970s film look, soft grain, amber tones").
  2. Timeline — timestamped beats across the duration: "[0s-2s] wide establishing shot … [2s-4s] slow push-in to the face …". A clip sliced into beats hits every beat on schedule; one moment stretched across the whole duration looks static.
  3. Camera — state the movement explicitly, including when it should not move: "slow dolly-in, no cuts, no handheld".
  4. Audio — put every sound in an Audio: line with entrance cues: "Audio: soft piano from 0s, a cello joins at 4s, gentle room tone throughout." Omit this and the model picks a soundtrack for you.
  5. On-screen text — spell out every readable word in quotes: "the title reads 'SUNRISE'", then add "do not misspell, do not add other text, no subtitles." Text you only describe comes back as letter-shaped noise.

Tips

  • Verbs beat adjectives — write the action ("she turns and smiles"), not just the vibe.
  • Iterate at 5s (composition and sound resolve there), then deliver at your final length.
  • A short negative list ("no dissolves, no captions, no extra people") is free and prevents default drift.

Parameters

ParameterRequiredDescription
promptYesScene, action, camera movement, and an Audio: line for the soundtrack.
aspect_ratioNo16:9, 9:16, 1:1, 4:3, 3:4, 21:9, or 9:21. Default: 16:9.
resolutionNo480p (faster, lower cost) or 768p (native canvas). Default: 480p.
durationNoOutput length in seconds, 315. Default: 5.
seedNoFixed seed for reproducible output.
lorasNoUp to 3 LoRA weights, each {path, scale}; path is a LoRA file URL.

Specifications

ItemDetail
OutputMP4 with native stereo audio
Frame rate24 fps
Resolution480p or 768p
Duration315 seconds (snaps to the model's frame grid, so a 5s request lands at ~5.2s)
SeedSupported

Pricing

Billed per generated second:

ResolutionPrice per second5s15s
480p$0.05$0.25$0.75
768p$0.10$0.50$1.50

Explore the MiniMax H3 Open Weights Family

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.

Minimax H3 Text To Video Lora API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/minimax-h3/text-to-video-lora 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 Minimax H3 Text To Video Lora 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": "480p",
    "duration": 5,
    "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/minimax-h3/text-to-video-lora" \
  -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/wavespeed-ai/minimax-h3/text-to-video-lora";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "16:9",
        "resolution": "480p",
        "duration": 5,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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));
}
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": "480p",
    "duration": 5,
    "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/minimax-h3/text-to-video-lora", 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)

Minimax H3 Text To Video Lora API — Frequently asked questions

What is the Minimax H3 Text To Video Lora API?

Minimax H3 Text To Video Lora is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. MiniMax H3 Open Weights Text to Video with custom LoRA support generates coherent videos from text prompts, with 480P / 768P output, native stereo audio, 5-15 second duration, flexible aspect ratios, and per-second billing. 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 Minimax H3 Text To Video Lora 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/wavespeed-ai/minimax-h3-text-to-video-lora.

How much does Minimax H3 Text To Video Lora cost per run?

Minimax H3 Text To Video Lora starts at $0.25 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 Minimax H3 Text To Video Lora accept?

Key inputs: `prompt`, `aspect_ratio`, `resolution`, `duration`, `seed`, `loras`. 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/minimax-h3-text-to-video-lora.

How do I get started with the Minimax H3 Text To Video Lora API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Minimax H3 Text To Video Lora outputs commercially?

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.

MiniMax H3 Text-to-Video Open Weights LoRA | Custom LoRA Video API on WaveSpeedAI