# Seedance 2.0 Fast

> Run Seedance 2.0 Fast by bytedance online or via API. $0.0033/1K tokens (with visual input), $0.0056/1K tokens (text-only). Tokens = (w*h*fps*(input_s+output_s))/1024, no setup.

**URL:** https://inference.sh/apps/bytedance/seedance-2-0-fast
**Last updated:** 2026-10-01

---

Fast multimodal video generation from text, images, video, and audio references using ByteDance's Seedance 2.0 Fast model via BytePlus ARK API. Supports text-to-video, image-to-video, and multimodal reference-to-video with synchronized audio.

- app: `bytedance/seedance-2-0-fast`
- maker: [bytedance](https://inference.sh/apps/bytedance.md)
- category: [video](https://inference.sh/apps/category/video.md)
- input → output: text → video, image → video, reference → video
- tasks: [text to video](https://inference.sh/apps/tag/text-to-video.md), [image to video](https://inference.sh/apps/tag/image-to-video.md), [reference to video](https://inference.sh/apps/tag/reference-to-video.md), [native audio](https://inference.sh/apps/tag/native-audio.md)
- price: $0.0033/1K tokens (with visual input), $0.0056/1K tokens (text-only). Tokens = (w*h*fps*(input_s+output_s))/1024
- runs via: api, javascript and python sdk, belt cli, mcp

## seedance-2-0-fast API Guide

### About
fast multimodal video generation from text, images, video, and audio references using bytedance's seedance 2.0 fast model via byteplus ark api. supports text-to-video, image-to-video, and multimodal reference-to-video with synchronized audio.

### Get an API Key
Create one in [settings → api keys](https://app.inference.sh/settings/keys). The examples read it from `INFERENCE_API_KEY`.

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

### 1. Calling the API

#### Install the Client

```bash
pip install inferencesh
```

#### Run and Get Result
Submit a request and wait for the final result.

```python
import os
from inferencesh import inference

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

## version @2mvgdevx pinned
result = client.run({
        "app": "bytedance/seedance-2-0-fast@2mvgdevx",
        "input": {
            "prompt": "@Image1 is the character reference. @Video1 provides the motion. A cat stretches lazily on a sunlit windowsill."
        }
    })

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

#### Stream Live Updates
Get real-time progress updates as the task runs.

```python
import os
from inferencesh import inference

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

## version @2mvgdevx pinned
## stream=True yields updates as they arrive
for update in client.run({
        "app": "bytedance/seedance-2-0-fast@2mvgdevx",
        "input": {
            "prompt": "@Image1 is the character reference. @Video1 provides the motion. A cat stretches lazily on a sunlit windowsill."
        }
    }, stream=True):
    if update.get("progress"):
        print(f"progress: {update['progress']}%")
    if update.get("output"):
        print(f"output: {update['output']}")
```

#### Run in the Background
Start the task and get its id back right away, then check on it with `GET /tasks/{id}`. It is done when `status` is 10 (completed), 11 (failed) or 12 (cancelled).

```python
import os
from inferencesh import inference, TaskStatus

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

## returns as soon as the task is created
task = client.run({
        "app": "bytedance/seedance-2-0-fast@2mvgdevx",
        "input": {
            "prompt": "@Image1 is the character reference. @Video1 provides the motion. A cat stretches lazily on a sunlit windowsill."
        }
    }, wait=False)

## later: read its current state
state = client.tasks.get(task["id"]).data
if state["status"] == TaskStatus.COMPLETED:
    print(state["output"])
```

### 2. Files

#### Automatic Upload

```python
## local file paths are automatically uploaded
result = client.run({
    "app": "bytedance/seedance-2-0-fast@2mvgdevx",
    "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/...
```

### 3. Schema

#### Input
- **prompt** (string) *required*: Text prompt describing the video content. Use @Image1, @Image2, @Video1, @Audio1 to reference inputs in order (e.g. '@Image1 is the style reference, @Video1 provides the motion'). Supports English, Japanese, Indonesian, Spanish, and Portuguese.
- **image** (string): First-frame image for image-to-video generation. Mutually exclusive with reference inputs.
- **end_image** (string): Last-frame image for first+last frame video generation. Requires image to be set as the first frame.
- **reference_images** (array): Reference images for multimodal generation (up to 9). Use prompt to describe how to use each, e.g. 'Image 1', 'Image 2'. Mutually exclusive with image/end_image.
- **reference_videos** (array): Reference videos for multimodal generation (up to 3). Max 15s each, total max 15s. Formats: mp4/mov. Mutually exclusive with image/end_image.
- **reference_audios** (array): Reference audios for multimodal generation (up to 3). Max 15s each, total max 15s. Formats: wav/mp3. Requires at least one image or video.
- **resolution** (string): Video resolution. Seedance 2.0 Fast supports 480p and 720p only.
- **ratio** (string): Aspect ratio. 'adaptive' auto-selects based on input content.
- **duration** (integer): Duration in seconds (4-15), or -1 for auto-select.
- **generate_audio** (boolean): Whether to generate synchronized audio with the video.
- **seed** (integer): Seed for reproducibility (-1 for random).
- **watermark** (boolean): Whether to add watermark to the output video.
- **safety_identifier** (string): Unique identifier of end user for platform safety policy. Must be fixed and unique per user, max 64 chars. Recommended: hash of username, user ID, or email.

#### Output
- **video** (string): The generated video file.

## 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 Seedance 2.0 Fast cost?

$0.0033/1K tokens (with visual input), $0.0056/1K tokens (text-only). Tokens = (w*h*fps*(input_s+output_s))/1024. you pay per run from your inference shell credits. no subscription is required.

### how do I run Seedance 2.0 Fast via api?

call bytedance/seedance-2-0-fast with the javascript or python sdk, the rest api, or `belt app run bytedance/seedance-2-0-fast` from a terminal. the api reference on this page lists every input.

### who makes Seedance 2.0 Fast?

Seedance 2.0 Fast is made by bytedance and runs on inference shell. every bytedance app is listed at https://inference.sh/apps/bytedance.

### can my agent use Seedance 2.0 Fast?

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 Seedance 2.0 Fast?

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.