# MiniMax Hailuo 02 Pro — Text To Video > Try hailuo-02-pro on GPT Proto. Generate 1080p videos (up to 10s) from text/image with realistic physics, cinematic motions, and director-level camera control. ## Overview - **Endpoint**: `POST https://gptproto.com/api/v3/minimax/hailuo-02-pro/text-to-video` - **Result URL**: `GET https://gptproto.com/api/v3/predictions/{result_id}/result` — the submit response also returns the authoritative URL in `data.urls.get` - **Model ID**: `hailuo-02-pro` - **Vendor**: MiniMax - **Scene**: `text-to-video` - **Category**: text-to-video - **Modalities**: input text → output video - **Playground**: https://gptproto.com/model/minimax/hailuo-02-pro - **API documentation**: https://docs.gptproto.com/docs/allapi/MiniMax/hailuo-02-pro/gptproto-format/text-to-video - **Other scenes of this model**: `image-to-video` — same auth, different endpoint path and input schema ## Authentication Every request needs a GPTProto API key in the `Authorization` header. Create one at https://gptproto.com/dashboard/api-key, then export it: ```bash export GPTPROTO_API_KEY="your-api-key" ``` Header: `Authorization: Bearer $GPTPROTO_API_KEY` (plus `Content-Type: application/json` on POST). ## Pricing Platform price by tier (USD, already includes the GPTProto discount): - **0** — $0.441 per run Price range: $0.441 – $0.441 per generation. Prices may change. The model page always shows the live price: https://gptproto.com/model/minimax/hailuo-02-pro ## API Information The API is asynchronous: POST the endpoint to create a prediction, then poll its result URL until `status` is `completed` or `failed`. ### Input Schema The endpoint accepts the following JSON body parameters: - **`prompt`** (`string`, _required_): The positive prompt for the generation. - **`enable_prompt_expansion`** (`boolean`, _optional_): The model automatically optimizes incoming prompts to enhance output quality. This also activates the safety checker, which ensures content safety by detecting and filtering potential risks. - Default: `true` - Options: true, false **Required Parameters Example**: ```json { "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle" } ``` **Full Example**: ```json { "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "enable_prompt_expansion": true } ``` ### Output Schema Both submit and poll return the same envelope: - **`data.id`** (`string`): Prediction id. Use it as `result_id` when polling for the result. - **`data.status`** (`string`): One of `created`, `running`, `completed`, `failed`. See Status Values below. - **`data.outputs`** (`array of string`): Generated files. Empty until `status` is `completed`; then it holds the output URLs (or base64 strings when the model exposes a base64 option). - **`data.urls.get`** (`string`): Authoritative result URL for this prediction. Prefer it over building the poll URL yourself. - **`data.error`** (`string | null`): Failure reason when `status` is `failed`, otherwise `null`. - **`data.executionTime`** (`integer`): Total processing time in milliseconds. - **`data.timings.inference`** (`integer`): Model inference time in milliseconds. - **`data.hasNsfwContents`** (`array of boolean`): Per-output moderation flags. - **`message`** (`string`): `success` on a normal response, otherwise the error message. - **`code`** (`integer`): Business status code. `200` means the request was accepted. **Example Response — submit (task accepted)**: ```json { "data": { "id": "pred_example_01", "model": "hailuo-02-pro", "outputs": [], "urls": { "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result" }, "hasNsfwContents": [], "status": "created", "createdAt": "2026-01-01T12:00:00Z", "executionTime": 0, "timings": { "inference": 0 } }, "message": "success", "code": 200 } ``` **Example Response — poll (completed)**: ```json { "data": { "id": "pred_example_01", "model": "hailuo-02-pro", "outputs": [ "https://oss-us.gptproto.com/example/output.mp4" ], "urls": { "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result" }, "status": "completed", "error": null, "executionTime": 12345, "timings": { "inference": 12000 }, "has_nsfw_contents": [], "created_at": "2026-01-01T12:00:00Z" }, "message": "success", "code": 200 } ``` ### Status Values - `created` — Task accepted. Use `data.id` as `result_id` for polling. - `running` — Generation is in progress. Keep polling. - `completed` — Finished successfully. Generated files are in `data.outputs`. - `failed` — Generation failed. Read `data.error` for the reason. ## Usage Examples ### 1. Submit a request ```bash curl --request POST "https://gptproto.com/api/v3/minimax/hailuo-02-pro/text-to-video" \ --header "Authorization: Bearer $GPTPROTO_API_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "enable_prompt_expansion": true }' ``` ```python import os import requests url = "https://gptproto.com/api/v3/minimax/hailuo-02-pro/text-to-video" headers = { "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}", "Content-Type": "application/json" } payload = { "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "enable_prompt_expansion": True } response = requests.request("POST", url, headers=headers, json=payload) print(response.json()) ``` ```typescript const response = await fetch("https://gptproto.com/api/v3/minimax/hailuo-02-pro/text-to-video", { method: "POST", headers: { "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ prompt: "A tiny origami fox sailing a teacup across a moonlit puddle", enable_prompt_expansion: true, }), }); const data = await response.json(); console.log(data); ``` ### 2. Poll until the task finishes Replace `YOUR_RESULT_ID` with `data.id` from the submit response (or call `data.urls.get` directly), and keep polling every 1–3 seconds while `status` is `created` or `running`. ```bash result_id="YOUR_RESULT_ID" curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \ --header "Authorization: Bearer $GPTPROTO_API_KEY" ``` ```python import os import requests result_id = "YOUR_RESULT_ID" url = f"https://gptproto.com/api/v3/predictions/{result_id}/result" headers = { "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}" } response = requests.request("GET", url, headers=headers) print(response.json()) ``` ```typescript const result_id = "YOUR_RESULT_ID"; const response = await fetch(`https://gptproto.com/api/v3/predictions/${result_id}/result`, { method: "GET", headers: { "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`, }, }); const data = await response.json(); console.log(data); ``` ## Example Prompts - A skier glides downhill, carving turns that kick up clouds of snow. The camera follows steadily as he picks up speed along the slope. - Epic cinematic shot in an apocalyptic city at dusk. A lone cybernetic warrior stands on a collapsed bridge, wind tearing through his futuristic trench coat. Neon sparks dance across the fractured skyline as a massive storm brews in the distance, clouds swirling like a vortex. The… - The actor in the image shouts passionately and throws a chair across the stage, dramatic lighting, camera pushes forward and tilts for intensity ## HTTP Status Codes - `400` — malformed body, a parameter or value this model does not accept, or input blocked by the provider's content moderation - `401` — missing or invalid API key - `403` — insufficient credits - `413` — request body too large - `429` — rate limited; retry with backoff - `500` — An internal server error occurred - `502` — An internal server error occurred - `504` — Gateway timeout — upstream service did not respond in time; retry later ## Additional Resources - [Model playground](https://gptproto.com/model/minimax/hailuo-02-pro) - [API documentation](https://docs.gptproto.com/docs/allapi/MiniMax/hailuo-02-pro/gptproto-format/text-to-video) - [All models](https://gptproto.com/model) - [API keys](https://gptproto.com/dashboard/api-key) - [Platform overview for LLMs](https://gptproto.com/llm-full.txt) - Any other model: `https://gptproto.com/model/{vendor}/{model}/{scene}/llms.txt`