# Hailuo 2.3 t2v Pro — Atlas Cloud API > Professional-grade text-to-video model delivering advanced motion, physics realism and film-style output for VFX and marketing. This is the machine-readable API reference for **Hailuo 2.3 t2v Pro** on Atlas Cloud, a unified API platform for 400+ AI models across text, image, video, audio and 3D. - **Model ID**: `minimax/hailuo-2.3/t2v-pro` - **Built by**: MiniMax - **Modality**: Video - **Model page**: https://www.atlascloud.ai/models/minimax/hailuo-2.3/t2v-pro - **API key**: https://www.atlascloud.ai/console/api-keys - **Docs**: https://www.atlascloud.ai/docs ## Pricing on Atlas Cloud - $0.49 per second of generated video - Pay-as-you-go. No minimum spend, no subscription required. > **These are the authoritative Atlas Cloud rates for this model.** Any price that > appears in the vendor description further down refers to a different platform or > a different model variant and does not apply here. ## Use this model from an AI agent Atlas Cloud ships three first-party integration surfaces. All three authenticate with the same API key via the `ATLASCLOUD_API_KEY` environment variable. ### MCP server The official MCP server (`atlascloud-mcp`) exposes this model to any MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose, Claude Desktop. One-line install: ```bash # Claude Code claude mcp add atlascloud -- npx -y atlascloud-mcp # OpenAI Codex CLI codex mcp add atlascloud -- npx -y atlascloud-mcp # Gemini CLI gemini mcp add atlascloud -- npx -y atlascloud-mcp export ATLASCLOUD_API_KEY="your-api-key" ``` Then ask in plain English; the agent calls `atlas_generate_video` with `model: "minimax/hailuo-2.3/t2v-pro"`. The server fetches each model's schema and validates parameters before submitting, so invalid requests fail fast without spending credits. MCP docs: https://www.atlascloud.ai/docs/mcp-server ### Agent Skills `atlas-cloud-skills` is a portable skill package (API reference, code templates in Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and 12+ other agents: ```bash npx skills add AtlasCloudAI/atlas-cloud-skills export ATLASCLOUD_API_KEY="your-api-key" ``` Skills docs: https://www.atlascloud.ai/docs/skills ### CLI The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs are polled and downloaded automatically (use `--no-download` when a script only needs the output URLs): ```bash # Install (Homebrew, npm, or shell installer) brew install AtlasCloudAI/tap/atlascloud # npm install -g atlascloud-cli # curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh atlas auth login atlas generate video minimax/hailuo-2.3/t2v-pro -p "Your prompt here" ``` CLI docs: https://www.atlascloud.ai/docs/cli ## HTTP API reference - **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id` - **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes - **Model ID**: `minimax/hailuo-2.3/t2v-pro` ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`model`** (`string`, _required_): model name - Default: `"minimax/hailuo-2.3/t2v-pro"` - **`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` **Required Parameters Example**: ```json { "model": "minimax/hailuo-2.3/t2v-pro", "prompt": "" } ``` **Full Example**: ```json { "model": "minimax/hailuo-2.3/t2v-pro", "prompt": "", "enable_prompt_expansion": true } ``` ### Output Schema The API returns the following output format: - **`created_at`** (`string`, _optional_): ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”). - **`has_nsfw_contents`** (`array[boolean]`, _optional_): Array of boolean values indicating NSFW detection for each output. - **`id`** (`string`, _optional_): Unique identifier for the prediction, the ID of the prediction to get. - **`model`** (`string`, _optional_): Model ID used for the prediction. - **`outputs`** (`array[string]`, _optional_): Array of URLs to the generated content (empty when status is not completed). - **`status`** (`string`, _optional_): Status of the task: created, processing, completed, or failed. - **`urls`** (`object`, _optional_): Object containing related API endpoints. **Example Response**: ```json { "created_at": "", "has_nsfw_contents": [], "id": "", "model": "", "outputs": [ "" ], "status": "", "urls": {} } ``` ## Usage Examples ### cURL ```bash # Step 1: Start generation (async) curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \ -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "minimax/hailuo-2.3/t2v-pro", "prompt": "", "enable_prompt_expansion": true }' # Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}} # Step 2: Poll for result (replace {prediction_id} with the id returned above) curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \ -H "Authorization: Bearer $ATLASCLOUD_API_KEY" # Keep polling until status is "completed", "succeeded" or "failed" # When completed, outputs will contain the generated content URL(s) ``` ## Additional Resources ### Documentation - [Model Playground](https://www.atlascloud.ai/models/minimax/hailuo-2.3/t2v-pro) ## About this model _Vendor-supplied description. Any pricing or endpoint mentioned below refers to_ _other platforms — use the Atlas Cloud values above._ ### MiniMax Hailuo 2.3 — Text-to-Video (T2V) Pro **Hailuo 2.3 Pro** is the **premium text-to-video model** from **MiniMax**, engineered for creators who demand cinematic realism, dynamic motion, and superior visual coherence. It transforms text prompts into richly detailed 5-second 1080p videos — merging professional-grade quality with cutting-edge physical simulation. --- #### Why It Looks Great * **Cinematic Fidelity** – Generates ultra-smooth motion, realistic lighting, and lifelike shadows in every frame. * **Advanced Physics & Scene Logic** – Accurately models object dynamics, reflections, and camera movement. * **High Prompt Accuracy** – Faithfully interprets natural-language descriptions with exceptional semantic precision. * **Consistent Characters** – Maintains subject identity and spatial layout throughout the clip. * **Refined Aesthetic** – Tuned for film-like color grading, depth, and atmosphere. --- #### Limits and Performance * **Input:** text prompt only * **Output duration:** fixed — **5 seconds** * **Resolution:** up to **1080p** * **Processing time:** approximately **40–70 seconds** per job (depending on complexity and queue load) --- #### How to Use 1. Write a clear **text prompt** describing your scene, characters, lighting, and motion. *Example:* “A traveler walks through a neon-lit rainy street at night, reflections glowing on wet pavement.” 2. Submit your job — no reference image required. 3. Wait for processing (typically under 1 minute). 4. Download your completed 5-second cinematic video. --- #### Pro Tips * Use **film-style language** — include camera direction (*wide shot*, *slow zoom*, *tracking*). * Mention **lighting type** (*sunset glow*, *neon reflections*, *soft cinematic light*). * Keep prompts concise (1–2 sentences) for best fidelity. * For stable subjects, include descriptors like *same person* or *consistent background*. --- Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/minimax/hailuo-2.3/t2v-pro · Docs: https://www.atlascloud.ai/docs