MiniMax H3 Open Reference to Video API: AI Image-to-Video

MiniMax H3 Open Reference to Video API Reference

Endpoint

POST https://api.muapi.ai/api/v1/minimax-h3-open-reference-to-video

Submit a job with your MuApi API key in the x-api-key header, then poll https://api.muapi.ai/api/v1/predictions/{request_id}/result until status is completed.

Parameters

Name	Type	Required	Description
prompt	string	Yes	Text description referencing <Picture 1..9>, <Video 1..3>, <Audio 1..3>. Native stereo audio is generated with the video.
images_list	array	No	Reference image URLs. Up to 9 images.
videos_list	array	No	Reference video URLs (up to 3, 480p). Total reference video duration up to 15s.
audios_list	array	No	Standalone reference audio URLs (up to 3, trimmed to 15s each).
aspect_ratio	string	No	Options: 16:9, 9:16, 1:1, 4:3, 3:4, 21:9, 9:21Default: "16:9"
resolution	string	No	Options: 480p, 768pDefault: "480p"
duration	integer	No	Options: 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15Default: 5

cURL example

REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/minimax-h3-open-reference-to-video \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"<prompt>"}' | jq -r .request_id)

curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY"

Python example

import os, time, requests

API = "https://api.muapi.ai/api/v1"
headers = {"x-api-key": os.environ["MUAPI_API_KEY"]}

r = requests.post(f"{API}/minimax-h3-open-reference-to-video", headers=headers, json={"prompt":"<prompt>"})
request_id = r.json()["request_id"]

while True:
    res = requests.get(f"{API}/predictions/{request_id}/result", headers=headers).json()
    if res["status"] == "completed":
        print(res["outputs"]); break
    if res["status"] == "failed":
        raise RuntimeError(res.get("error"))
    time.sleep(3)

Full docs and agent/MCP integration: llms.txt. Get an API key at muapi.ai/access-keys.