# MiniMax Hailuo-02 Standard Text-to-Video > Generate a short, cinematic 768p video from a text prompt with smooth, lifelike motion and strong prompt adherence. ## Overview - **Endpoint**: `https://queue.modelrunner.run/minimax/hailuo-02/standard/text-to-video` - **Model ID**: `minimax/hailuo-02/standard/text-to-video` - **Category**: text-to-video - **Kind**: inference - **Tags**: minimax, hailuo, hailuo-02, text-to-video, video-generation ## Pricing - **Price**: $0.045 per output second ## Request Lifecycle This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps: 1. **Submit** — `POST https://queue.modelrunner.run/minimax/hailuo-02/standard/text-to-video` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=` (exact key=value matches, AND-ed). The response carries request handles only (no output yet): ```json { "status": "IN_QUEUE", "request_id": "<21-char id>", "status_url": "https://queue.modelrunner.run/minimax/hailuo-02/standard/text-to-video/requests//status", "response_url": "https://queue.modelrunner.run/minimax/hailuo-02/standard/text-to-video/requests/", "cancel_url": "https://queue.modelrunner.run/minimax/hailuo-02/standard/text-to-video/requests//cancel" } ``` 2. **Poll status** — `GET ` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field. 3. **Read result** — `GET `. Returns the finished request, including the generated `output`: ```json { "id": "", "status": "COMPLETED", "output": ..., "input": ... } ``` The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow. ### Input Schema - **`prompt`** (`string`, _required_): Text description of the video to generate. - **`duration`** (`DurationEnum`, _optional_): Video duration in seconds. - Default: `"6"` - Options: `"6"`, `"10"` - **`prompt_optimizer`** (`boolean`, _optional_): Whether to use the model's prompt optimizer. - Default: `true` ### Output Schema _No `Output` schema properties are available._ ## Default Example **Input** ```json { "prompt": "A lone lighthouse on a rocky cliff sweeping its beam through drifting sea fog at night, waves crashing below, cinematic wide shot", "duration": "6", "prompt_optimizer": true } ``` **Output** ```json "https://media.modelrunner.ai/SQo2Q13EuofKVKNY7UgID.mp4" ``` ## Usage Examples ### cURL The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`. ```bash # 1. Submit the request (returns request handles, not the output) SUBMIT=$(curl --silent --request POST \ --url https://queue.modelrunner.run/minimax/hailuo-02/standard/text-to-video \ --header "Authorization: Key $MODEL_RUNNER_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A lone lighthouse on a rocky cliff sweeping its beam through drifting sea fog at night, waves crashing below, cinematic wide shot", "duration": "6", "prompt_optimizer": true }') STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url') RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url') # 2. Poll until the request leaves the queue / in-progress state while true; do STATUS=$(curl --silent --url "$STATUS_URL" \ --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status') echo "Status: $STATUS" case "$STATUS" in COMPLETED) break ;; FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;; esac sleep 1 done # 3. Read the finished request, including the generated output curl --silent --url "$RESPONSE_URL" \ --header "Authorization: Key $MODEL_RUNNER_KEY" ``` ### JavaScript ```javascript import { modelrunner } from "@modelrunner/client"; const result = await modelrunner.subscribe("minimax/hailuo-02/standard/text-to-video", { input: { "prompt": "A lone lighthouse on a rocky cliff sweeping its beam through drifting sea fog at night, waves crashing below, cinematic wide shot", "duration": "6", "prompt_optimizer": true } }); console.log(result.data); ``` ### Python ```python import asyncio import modelrunner_ai async def main(): response = await modelrunner_ai.submit_async( "minimax/hailuo-02/standard/text-to-video", arguments={ "prompt": "A lone lighthouse on a rocky cliff sweeping its beam through drifting sea fog at night, waves crashing below, cinematic wide shot", "duration": "6", "prompt_optimizer": true } ) result = await response.get() print(result["output"]) asyncio.run(main()) ``` ## Additional Resources - [Playground](https://modelrunner.ai/models/minimax/hailuo-02/standard/text-to-video) - [OpenAPI Schema](https://modelrunner.ai/models/minimax/hailuo-02/standard/text-to-video/openapi.json) - [LLM Instructions](https://modelrunner.ai/models/minimax/hailuo-02/standard/text-to-video/llms.txt)