# Topaz Frame Interpolation

> Run Topaz Frame Interpolation by topaz online or via API. $0.0714/credit, no setup.

**URL:** https://inference.sh/apps/topaz/frame-interpolation
**Last updated:** 2026-08-04

---

video frame interpolation — slowmo and fps boost with apollo, chronos, and aion models

- app: `topaz/frame-interpolation`
- maker: [topaz](https://inference.sh/apps/topaz.md)
- category: [video](https://inference.sh/apps/category/video.md)
- tasks: [frame interpolation](https://inference.sh/apps/tag/frame-interpolation.md), [video enhancement](https://inference.sh/apps/tag/video-enhancement.md)
- price: $0.0714/credit
- runs via: api, javascript and python sdk, belt cli, mcp

## frame-interpolation API Guide

### About
video frame interpolation — slowmo and fps boost with apollo, chronos, and aion models

### 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": "topaz/frame-interpolation@2z2ta3ww",
        "input": {
            "video": "https://example.com/file.png"
        }
    })

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": "topaz/frame-interpolation@2z2ta3ww",
        "input": {
            "video": "https://example.com/file.png"
        }
    }, 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": "topaz/frame-interpolation@2z2ta3ww",
    "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
- **video** (string) *required*: input video file
- **model** (string): interpolation model: apollo (best quality), apollo-fast (speed), chronos (optical flow), chronos-fast (fast optical flow), aion (large motion)
- **slowmo** (number): slowmo factor (1-16)
- **target_fps** (number): target frame rate (15-240)
- **remove_duplicates** (boolean): remove duplicate frames before interpolation
- **duplicate_threshold** (number): duplicate detection threshold (0.001-0.1)

#### Output
- **video** (string): interpolated 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 Topaz Frame Interpolation cost?

$0.0714/credit. you pay per run from your inference shell credits. no subscription is required.

### how do I run Topaz Frame Interpolation via api?

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

### who makes Topaz Frame Interpolation?

Topaz Frame Interpolation is made by topaz and runs on inference shell. every topaz app is listed at https://inference.sh/apps/topaz.

### can my agent use Topaz Frame Interpolation?

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 Topaz Frame Interpolation?

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.