Hunyuan Video is an Open video generation model with high visual quality, motion diversity, text-video alignment, and generation stability. This endpoint generates videos from text descriptions.

fal-ai/hunyuan-video

Hunyuan Video is an Open video generation model with high visual quality, motion diversity, text-video alignment, and generation stability. This endpoint generates videos from text descriptions.

Inference

Commercial use

Schema

LLMs

Playground API

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

fal-ai/hunyuan-video

Schema

LLMs

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

Input

Prompt*

Additional Settings

Customize your input with more control.

Your request will cost $0.4 per video.

Result

Idle

This generation takes approximately 4m.

What would you like to do next?

Your request will cost $0.4 per video.

Readme

Hunyuan Video - AI-Powered Video Generation

Transform static prompts into dynamic, high-quality videos with Hunyuan Video. This powerful open-source AI model enables developers and creators to generate engaging video content through a simple API interface.

Overview

Hunyuan Video is an Open video generation model with high visual quality, motion diversity, text-video alignment, and generation stability. This endpoint generates videos from text descriptions through the fal.ai platform. Whether you're building creative tools, content applications, or enterprise solutions, you can easily integrate video generation into your workflow.

Getting Started

Getting up and running with Hunyuan Video takes just a few minutes. Here's how to begin:

First, install your preferred SDK:

For JavaScript/TypeScript:

bash
npm install --save @fal-ai/client

For Python:

bash
pip install fal-client

Configure your authentication credentials:

JavaScript:

javascript
import { fal } from "@fal-ai/client";
fal.config({
  credentials: "YOUR_FAL_KEY_HERE"
});

Python:

python
import fal_client as fal
import os
os.environ["FAL_KEY"] = "YOUR_FAL_KEY_HERE"

Basic Usage

Generate your first video with this simple example:

JavaScript:

javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/hunyuan-video", {
  input: {
    prompt: "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse."
  }
});

console.log(result.data.video.url);

Python:

python
import fal_client as fal

result = fal.subscribe("fal-ai/hunyuan-video", {
    "prompt": "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse."
})

print(result.video.url)

API Parameters

Required Parameters

prompt: The text prompt to generate the video from

Optional Parameters

num_inference_steps: Number of inference steps (default: 30). Lower gets faster results, higher gets better results
seed: Seed for reproducible results (default: random)
pro_mode: Enable pro mode with 55 steps for higher quality (default: false). Costs 2x more billing units
aspect_ratio: Video aspect ratio - "16:9" or "9:16" (default: "16:9")
resolution: Video resolution - "480p", "580p", or "720p" (default: "720p")
num_frames: Number of frames - 129 or 85 (default: 129)
enable_safety_checker: Enable content safety checking (default: false)

Input Example

javascript
{
  "prompt": "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse.",
  "num_inference_steps": 30,
  "aspect_ratio": "16:9",
  "resolution": "720p",
  "num_frames": 129,
  "enable_safety_checker": true
}

Advanced Implementation

For production applications, consider this more robust implementation:

javascript
import { fal } from "@fal-ai/client";

async function generateVideo(prompt, options = {}) {
  try {
    const result = await fal.subscribe("fal-ai/hunyuan-video", {
      input: {
        prompt,
        num_inference_steps: options.steps || 30,
        pro_mode: options.proMode || false,
        aspect_ratio: options.aspectRatio || "16:9",
        resolution: options.resolution || "720p",
        num_frames: options.frames || 129,
        enable_safety_checker: options.safetyCheck || false
      }
    });
    
    return result;
  } catch (error) {
    console.error("Video generation failed:", error);
    throw new Error("Failed to generate video");
  }
}

Queue Management

For production applications, use the queue API:

javascript
// Submit request
const { request_id } = await fal.queue.submit("fal-ai/hunyuan-video", {
  input: {
    prompt: "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse."
  },
  webhookUrl: "https://optional.webhook.url/for/results"
});

// Check status
const status = await fal.queue.status("fal-ai/hunyuan-video", {
  requestId: request_id,
  logs: true
});

// Get result when complete
const result = await fal.queue.result("fal-ai/hunyuan-video", {
  requestId: request_id
});

Output Format

javascript
{
  "video": {
    "url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
    "content_type": "video/mp4",
    "file_name": "generated_video.mp4",
    "file_size": 2048576
  },
  "seed": 1234567890
}

Best Practices

To get the most out of Hunyuan Video:

Write clear, detailed prompts that specify both content and style
Include temporal elements in your prompts to guide video progression
Monitor processing time (approximately 4 minutes per generation)
Cache generated videos when possible to optimize performance
Implement error handling for API calls
Use pro mode for higher quality when extra time and cost are acceptable

Technical Specifications

Model Architecture:

Type: Open-source video generation model by Tencent
Parameters: 13 billion parameter diffusion transformer
Processing Time: ~4 minutes average
Commercial Use: Free for commercial use

Performance:

Video Length: 5 seconds (typical output)
Supported Resolutions: 480p, 580p, 720p
Aspect Ratios: 16:9, 9:16
Frame Options: 85 or 129 frames
Quality Modes: Standard (35 steps) and Pro (55 steps)

Model Variants

Performance Optimization

For optimal performance:

Keep your prompts focused and specific
Implement proper error handling and retries
Cache successful generations where appropriate
Monitor API usage through the fal.ai dashboard
Test different prompt structures to optimize results
Consider using pro mode only when higher quality is essential

Pricing and Usage

Cost: $0.4 per video
Pro Mode: Costs 2x more billing units for higher quality
Processing Time: This generation takes approximately 4m
Commercial Use: Free for commercial use (open-source model)
Billing: Pay only for successful generations

Support and Resources

Access comprehensive support through:

Documentation: docs.fal.ai
API Reference: fal.ai/models/fal-ai/hunyuan-video/api
Model Gallery: Browse all models at fal.ai/models
Support: support@fal.ai

Get started with Hunyuan Video today and bring your creative visions to life through dynamic, AI-generated video content.

Readme

Hunyuan Video - AI-Powered Video Generation

Overview

Getting Started

Getting up and running with Hunyuan Video takes just a few minutes. Here's how to begin:

First, install your preferred SDK:

For JavaScript/TypeScript:

bash
npm install --save @fal-ai/client

For Python:

bash
pip install fal-client

Configure your authentication credentials:

JavaScript:

javascript
import { fal } from "@fal-ai/client";
fal.config({
  credentials: "YOUR_FAL_KEY_HERE"
});

Python:

python
import fal_client as fal
import os
os.environ["FAL_KEY"] = "YOUR_FAL_KEY_HERE"

Basic Usage

Generate your first video with this simple example:

JavaScript:

javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/hunyuan-video", {
  input: {
    prompt: "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse."
  }
});

console.log(result.data.video.url);

Python:

python
import fal_client as fal

result = fal.subscribe("fal-ai/hunyuan-video", {
    "prompt": "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse."
})

print(result.video.url)

API Parameters

Required Parameters

prompt: The text prompt to generate the video from

Optional Parameters

num_inference_steps: Number of inference steps (default: 30). Lower gets faster results, higher gets better results
seed: Seed for reproducible results (default: random)
pro_mode: Enable pro mode with 55 steps for higher quality (default: false). Costs 2x more billing units
aspect_ratio: Video aspect ratio - "16:9" or "9:16" (default: "16:9")
resolution: Video resolution - "480p", "580p", or "720p" (default: "720p")
num_frames: Number of frames - 129 or 85 (default: 129)
enable_safety_checker: Enable content safety checking (default: false)

Input Example

javascript
{
  "prompt": "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse.",
  "num_inference_steps": 30,
  "aspect_ratio": "16:9",
  "resolution": "720p",
  "num_frames": 129,
  "enable_safety_checker": true
}

Advanced Implementation

For production applications, consider this more robust implementation:

javascript
import { fal } from "@fal-ai/client";

async function generateVideo(prompt, options = {}) {
  try {
    const result = await fal.subscribe("fal-ai/hunyuan-video", {
      input: {
        prompt,
        num_inference_steps: options.steps || 30,
        pro_mode: options.proMode || false,
        aspect_ratio: options.aspectRatio || "16:9",
        resolution: options.resolution || "720p",
        num_frames: options.frames || 129,
        enable_safety_checker: options.safetyCheck || false
      }
    });
    
    return result;
  } catch (error) {
    console.error("Video generation failed:", error);
    throw new Error("Failed to generate video");
  }
}

Queue Management

For production applications, use the queue API:

javascript
// Submit request
const { request_id } = await fal.queue.submit("fal-ai/hunyuan-video", {
  input: {
    prompt: "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse."
  },
  webhookUrl: "https://optional.webhook.url/for/results"
});

// Check status
const status = await fal.queue.status("fal-ai/hunyuan-video", {
  requestId: request_id,
  logs: true
});

// Get result when complete
const result = await fal.queue.result("fal-ai/hunyuan-video", {
  requestId: request_id
});

Output Format

javascript
{
  "video": {
    "url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
    "content_type": "video/mp4",
    "file_name": "generated_video.mp4",
    "file_size": 2048576
  },
  "seed": 1234567890
}

Best Practices

To get the most out of Hunyuan Video:

Write clear, detailed prompts that specify both content and style
Include temporal elements in your prompts to guide video progression
Monitor processing time (approximately 4 minutes per generation)
Cache generated videos when possible to optimize performance
Implement error handling for API calls
Use pro mode for higher quality when extra time and cost are acceptable

Technical Specifications

Model Architecture:

Type: Open-source video generation model by Tencent
Parameters: 13 billion parameter diffusion transformer
Processing Time: ~4 minutes average
Commercial Use: Free for commercial use

Performance:

Video Length: 5 seconds (typical output)
Supported Resolutions: 480p, 580p, 720p
Aspect Ratios: 16:9, 9:16
Frame Options: 85 or 129 frames
Quality Modes: Standard (35 steps) and Pro (55 steps)

Model Variants

Performance Optimization

For optimal performance:

Keep your prompts focused and specific
Implement proper error handling and retries
Cache successful generations where appropriate
Monitor API usage through the fal.ai dashboard
Test different prompt structures to optimize results
Consider using pro mode only when higher quality is essential

Pricing and Usage

Cost: $0.4 per video
Pro Mode: Costs 2x more billing units for higher quality
Processing Time: This generation takes approximately 4m
Commercial Use: Free for commercial use (open-source model)
Billing: Pay only for successful generations

Support and Resources

Access comprehensive support through:

Documentation: docs.fal.ai
API Reference: fal.ai/models/fal-ai/hunyuan-video/api
Model Gallery: Browse all models at fal.ai/models
Support: support@fal.ai

Get started with Hunyuan Video today and bring your creative visions to life through dynamic, AI-generated video content.