# ltx-video

> Run ltx-video by infsh online or via API. Pay per run, no setup.

**URL:** https://inference.sh/apps/infsh/ltx-video
**Last updated:** 2026-07-28

---

Create high-quality, realistic, and customizable videos quickly, with capabilities for producing detailed, high-resolution content.

- app: `infsh/ltx-video`
- maker: [infsh](https://inference.sh/apps/infsh.md)
- category: [video](https://inference.sh/apps/category/video.md)
- runs via: api, javascript and python sdk, belt cli, mcp

## ltx-video API Guide

### About
create high-quality, realistic, and customizable videos quickly, with capabilities for producing detailed, high-resolution content.

### 1. Calling the API

#### Install the Client

```bash
pip install inferencesh
```

#### Setup Your API Key
Set `INFERENCE_API_KEY` as an environment variable. Get your key from settings → api keys.

```bash
export INFERENCE_API_KEY="inf_your_key"
```

#### Run and Get Result

```python
import os
from inferencesh import inference

client = inference(api_key=os.environ["INFERENCE_API_KEY"])


result = client.run({
        "app": "infsh/ltx-video@4ka8p05v",
        "input": {
            "prompt": "prompt"
        }
    })

print(result["output"])
```

#### Stream Live Updates

```python
import os
from inferencesh import inference

client = inference(api_key=os.environ["INFERENCE_API_KEY"])


## stream=True yields updates as they arrive
for update in client.run({
        "app": "infsh/ltx-video@4ka8p05v",
        "input": {
            "prompt": "prompt"
        }
    }, stream=True):
    if update.get("progress"):
        print(f"progress: {update['progress']}%")
    if update.get("output"):
        print(f"output: {update['output']}")
```

### 2. Authentication
The API uses API keys for authentication. See the authentication docs for detailed setup instructions.

### 3. Files

#### Automatic Upload

```python
## local file paths are automatically uploaded
result = client.run({
    "app": "infsh/ltx-video@4ka8p05v",
    "input": {
        "image": "/path/to/local/image.png",  # detected & uploaded
        "audio": "https://example.com/audio.mp3",  # url passed through
    }
})
```

#### Manual Upload

```python
## upload and get a hosted URL
file = client.files.upload("/path/to/file.png")
print(file.uri)  # https://cloud.inference.sh/...
```

### 4. Schema

#### Input
- **prompt** (string) *required*: Text prompt to guide video generation
- **negative_prompt** (string): Negative prompt to specify undesired features
- **width** (integer): Width of the output video frames
- **height** (integer): Height of the output video frames
- **num_frames** (integer): Number of frames to generate
- **frame_rate** (integer): Frame rate for the output video
- **num_inference_steps** (integer): Number of denoising steps. Use 4,8,16 for distilled models
- **guidance_scale** (number): Scale for classifier-free guidance
- **seed** (integer): Random seed for reproducibility
- **conditioning_images** (array): List of conditioning images
- **offload_to_cpu** (boolean): Whether to offload to CPU
- **image_cond_noise_scale** (number): Scale of noise for conditioning
- **input_media** (string): Input video file for video-to-video generation
- **strength** (number): Strength of input video influence
- **enable_prompt_enhancement** (boolean): Explicitly enable or disable prompt enhancement. If None, will use word count threshold logic.

#### Output
- **video** (string): Video

## other video apps

- [VACE](https://inference.sh/apps/pruna/vace.md): $0.40/video
- [P-Video-Animate](https://inference.sh/apps/pruna/p-video-animate.md): $0.03/sec 720p, $0.06/sec 1080p
- [P-Video-Upscale](https://inference.sh/apps/pruna/p-video-upscale.md): Std: $0.01/sec 720p, $0.02 1080p, $0.04 2k, $0.08 4k; high fps 2x
- [P-Video-2-Pro-Avatar](https://inference.sh/apps/pruna/p-video-2-pro-avatar.md): $0.02/sec 480p, $0.04/sec 768p, $0.06/sec 1080p, $0.08/sec 2k, $0.12/sec 4k
- [P-Video-2-Pro-Reference](https://inference.sh/apps/pruna/p-video-2-pro-reference.md): Output: cost $0.015-$0.105/sec, speed $0.02-$0.115/sec. Ref video: $0.03-$0.06/sec. Ref img: $0.005/img. Ref audio: $0.0015-$0.0025/sec

## faq

### how much does ltx-video cost?

you pay per run from your inference shell credits, and the app shows its cost before each run. no subscription is required.

### how do I run ltx-video via api?

call infsh/ltx-video with the javascript or python sdk, the rest api, or `belt app run infsh/ltx-video` from a terminal. the api reference on this page lists every input.

### who makes ltx-video?

ltx-video is made by infsh and runs on inference shell. every infsh app is listed at https://inference.sh/apps/infsh.

### can my agent use ltx-video?

yes. agents call it as a tool through the inference shell mcp server (https://api.inference.sh/mcp), the belt cli or the sdk, and pay per run like you do.

### what are the alternatives to ltx-video?

other video apps on inference shell include VACE, P-Video-Animate, P-Video-Upscale, P-Video-2-Pro-Avatar. they run through the same api, so switching is a one-line change.