MiniMax H3 Open Weights Text to Video with custom LoRA support generates coherent videos from text prompts, with 480P / 540P / 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.
Idle
$0.125per run·~80 / $10
A street musician with a guitar on a sunny plaza looks into the camera and says: "This one's for everyone who kept walking. Stay a minute." Then he strums a warm chord. Natural light, light crowd murmur.
MiniMax H3 Text-to-Video LoRA Open Weights runs the open-weights edition of MiniMax H3 with LoRA support on WaveSpeedAI. This endpoint is separate from the official minimax/h3 API and uses its own 480p / 768p / 1080p resolution options and per-second pricing.
MiniMax H3 generates video and native stereo audio in a single pass. Describe both the visuals and the sound in one prompt, and the model produces an MP4 with synchronized dialogue, sound effects, music, or ambience.
Open-weights MiniMax H3 workflow
Use the open-weights edition of MiniMax H3 through WaveSpeedAI-hosted infrastructure.
Native stereo audio
Generate visuals and synchronized stereo audio together in one pass.
LoRA support
Load up to 3 LoRA weights per request, each with its own scale.
Text-to-video generation
Generate complete videos directly from text prompts.
Prompt-controlled soundtrack
Use an Audio: line in the prompt to guide music, dialogue, ambience, and sound effects.
Flexible aspect ratios
Supports landscape, vertical, square, classic, and cinematic aspect ratios.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Scene, action, camera movement, timing, and an Audio: line for soundtrack guidance. |
| aspect_ratio | No | Output aspect ratio: 16:9, 9:16, 1:1, 4:3, 3:4, 21:9, or 9:21. Default: 16:9. |
| resolution | No | Output resolution: 480p, 540p, 768p, or 1080p. Default: 480p. |
| duration | No | Output duration in seconds. Range: 3–15. Default: 5. |
| seed | No | Fixed seed for reproducible output. |
| loras | No | Up to 3 LoRA weights. Each item uses {path, scale}, where path is a LoRA file URL. |
480p for lower-cost generation, 540p for a mid-price step up, 768p for higher-resolution output, or 1080p for full-HD output.3 to 15 seconds.Pricing is based on generated video duration and selected resolution.
| Resolution | Per second | 5s | 15s |
|---|---|---|---|
| 480p | $0.05 | $0.25 | $0.75 |
| 540p | $0.075 | $0.375 | $1.125 |
| 768p | $0.10 | $0.50 | $1.50 |
| 1080p | $0.20 | $1.00 | $3.00 |
Duration is capped at 15 seconds for pricing. LoRA loading does not add a separate charge.
Audio: line to guide soundtrack, ambience, voice, and effects.seed when comparing LoRA scale or prompt variations.scale around 0.8–1.0, then adjust based on how strongly the LoRA affects the result.no subtitles, no extra text, or no extra people when needed.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/minimax-h3/text-to-video-lora with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Minimax H3 Text To Video Lora below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "480p",
"duration": 5
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(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="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
doneconst 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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "480p",
"duration": 5
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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));
}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
}
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 = 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)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 / 540P / 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.
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.
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.
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.
Median end-to-end generation time on WaveSpeedAI is around 39 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 (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.