# Hunyuan Video V1.5 > Hunyuan Video 1.5 is Tencent's latest and best video model ## Overview - **Endpoint**: `https://fal.run/fal-ai/hunyuan-video-v1.5/image-to-video` - **Model ID**: `fal-ai/hunyuan-video-v1.5/image-to-video` - **Category**: image-to-video - **Kind**: inference **Tags**: image-to-video ## Pricing - **Price**: $0.075 per seconds For more details, see [fal.ai pricing](https://fal.ai/pricing). ## 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: - **`prompt`** (`string`, _required_): The prompt to generate the video from. - Examples: "A stark starting line divides two powerful cars, engines revving for the challenge ahead. They surge forward in the heat of competition, a blur of speed and chrome. The finish line looms as they race for victory." - **`negative_prompt`** (`string`, _optional_): The negative prompt to guide what not to generate. Default value: `""` - Default: `""` - **`num_inference_steps`** (`integer`, _optional_): The number of inference steps. Default value: `28` - Default: `28` - Range: `1` to `50` - **`seed`** (`integer`, _optional_): Random seed for reproducibility. - **`aspect_ratio`** (`AspectRatioEnum`, _optional_): The aspect ratio of the video. Default value: `"16:9"` - Default: `"16:9"` - Options: `"16:9"`, `"9:16"` - **`resolution`** (`string`, _optional_): The resolution of the video. Default value: `"480p"` - Default: `"480p"` - **`num_frames`** (`integer`, _optional_): The number of frames to generate. Default value: `121` - Default: `121` - Range: `1` to `121` - **`enable_prompt_expansion`** (`boolean`, _optional_): Enable prompt expansion to enhance the input prompt. Default value: `true` - Default: `true` - **`image_url`** (`string`, _required_): URL of the reference image for image-to-video generation. - Examples: "https://v3.fal.media/files/panda/HnY2yf-BbzlrVQxR-qP6m_9912d0932988453aadf3912fc1901f52.jpg" **Required Parameters Example**: ```json { "prompt": "A stark starting line divides two powerful cars, engines revving for the challenge ahead. They surge forward in the heat of competition, a blur of speed and chrome. The finish line looms as they race for victory.", "image_url": "https://v3.fal.media/files/panda/HnY2yf-BbzlrVQxR-qP6m_9912d0932988453aadf3912fc1901f52.jpg" } ``` **Full Example**: ```json { "prompt": "A stark starting line divides two powerful cars, engines revving for the challenge ahead. They surge forward in the heat of competition, a blur of speed and chrome. The finish line looms as they race for victory.", "num_inference_steps": 28, "aspect_ratio": "16:9", "resolution": "480p", "num_frames": 121, "enable_prompt_expansion": true, "image_url": "https://v3.fal.media/files/panda/HnY2yf-BbzlrVQxR-qP6m_9912d0932988453aadf3912fc1901f52.jpg" } ``` ### Output Schema The API returns the following output format: - **`video`** (`File`, _required_): The generated video file. - Examples: {"url":"https://storage.googleapis.com/falserverless/example_outputs/hyvideo_v15_480p_output.mp4"} - **`seed`** (`integer`, _required_): The seed used for generation. **Example Response**: ```json { "video": { "url": "https://storage.googleapis.com/falserverless/example_outputs/hyvideo_v15_480p_output.mp4" } } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/hunyuan-video-v1.5/image-to-video \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A stark starting line divides two powerful cars, engines revving for the challenge ahead. They surge forward in the heat of competition, a blur of speed and chrome. The finish line looms as they race for victory.", "image_url": "https://v3.fal.media/files/panda/HnY2yf-BbzlrVQxR-qP6m_9912d0932988453aadf3912fc1901f52.jpg" }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/hunyuan-video-v1.5/image-to-video", arguments={ "prompt": "A stark starting line divides two powerful cars, engines revving for the challenge ahead. They surge forward in the heat of competition, a blur of speed and chrome. The finish line looms as they race for victory.", "image_url": "https://v3.fal.media/files/panda/HnY2yf-BbzlrVQxR-qP6m_9912d0932988453aadf3912fc1901f52.jpg" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/hunyuan-video-v1.5/image-to-video", { input: { prompt: "A stark starting line divides two powerful cars, engines revving for the challenge ahead. They surge forward in the heat of competition, a blur of speed and chrome. The finish line looms as they race for victory.", image_url: "https://v3.fal.media/files/panda/HnY2yf-BbzlrVQxR-qP6m_9912d0932988453aadf3912fc1901f52.jpg" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/hunyuan-video-v1.5/image-to-video) - [API Documentation](https://fal.ai/models/fal-ai/hunyuan-video-v1.5/image-to-video/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/hunyuan-video-v1.5/image-to-video) ### fal.ai Platform - [Platform Documentation](https://fal.ai/docs/documentation) - [Python Client](https://fal.ai/docs/api-reference/client-libraries/python) - [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript) ### Other agent-readable surfaces This file covers one model. To find anything else: - [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs - [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page - [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined - Any other model: `https://fal.ai/models//llms.txt`