# H3 Max 16-bit Pixel

> Generates 768p video with audio in a 16-bit pixel-art style from text prompts or an optional first-frame image. Supports durations of 5–15 seconds.


## Overview

- **Endpoint**: `https://fal.run/minimax/h3-max/styles/16bit-pixel`
- **Model ID**: `minimax/h3-max/styles/16bit-pixel`
- **Category**: text-to-video
- **Kind**: inference
**Tags**: pixel-art, 16-bit, animation, stylized



## Pricing

Billing is calculated per second of video generated. Video at **768p** costs **$0.08 per second**, with audio included. A **5-second** video costs **$0.40**, and a **15-second** video costs **$1.20**.

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_):
  Describe the scene, action, camera and sound. The 16-bit pixel style is applied automatically.
  - Examples: "A young bicycle courier pedals through a sunlit flower market. Medium side view, steady tracking camera, measured pedaling. Bicycle chain clicks and gentle market ambience."

- **`image_url`** (`string`, _optional_):
  Optional first-frame image. Use pixel artwork for the most consistent style. When provided, its aspect ratio determines the output canvas.

- **`duration`** (`integer`, _optional_):
  Requested video duration in seconds. Default value: `5`
  - Default: `5`
  - Range: `5` to `15`

- **`aspect_ratio`** (`AspectRatioEnum`, _optional_):
  Video aspect ratio for text-only generation. Ignored when image_url is provided. Default value: `"16:9"`
  - Default: `"16:9"`
  - Options: `"21:9"`, `"16:9"`, `"4:3"`, `"1:1"`, `"3:4"`, `"9:16"`

- **`seed`** (`integer`, _optional_):
  Random seed. Omit to choose one automatically.



**Required Parameters Example**:

```json
{
  "prompt": "A young bicycle courier pedals through a sunlit flower market. Medium side view, steady tracking camera, measured pedaling. Bicycle chain clicks and gentle market ambience."
}
```

**Full Example**:

```json
{
  "prompt": "A young bicycle courier pedals through a sunlit flower market. Medium side view, steady tracking camera, measured pedaling. Bicycle chain clicks and gentle market ambience.",
  "duration": 5,
  "aspect_ratio": "16:9"
}
```


### Output Schema

The API returns the following output format:

- **`video`** (`File`, _required_):
  Generated 768P pixel-animation video with audio.

- **`seed`** (`integer`, _required_):
  Seed used for this generation.



**Example Response**:

```json
{
  "video": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  }
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/minimax/h3-max/styles/16bit-pixel \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "A young bicycle courier pedals through a sunlit flower market. Medium side view, steady tracking camera, measured pedaling. Bicycle chain clicks and gentle market ambience."
   }'
```

### 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(
    "minimax/h3-max/styles/16bit-pixel",
    arguments={
        "prompt": "A young bicycle courier pedals through a sunlit flower market. Medium side view, steady tracking camera, measured pedaling. Bicycle chain clicks and gentle market ambience."
    },
    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("minimax/h3-max/styles/16bit-pixel", {
  input: {
    prompt: "A young bicycle courier pedals through a sunlit flower market. Medium side view, steady tracking camera, measured pedaling. Bicycle chain clicks and gentle market ambience."
  },
  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/minimax/h3-max/styles/16bit-pixel)
- [API Documentation](https://fal.ai/models/minimax/h3-max/styles/16bit-pixel/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=minimax/h3-max/styles/16bit-pixel)

### 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/<endpoint-id>/llms.txt`