# Kling v2.1 i2v Pro — Atlas Cloud API

> Balances generation speed and fidelity, producing sharp, fluid image-to-video results for general creative use.

This is the machine-readable API reference for **Kling v2.1 i2v Pro** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `kwaivgi/kling-v2.1-i2v-pro`
- **Built by**: Kuaishou
- **Modality**: Video
- **Model page**: https://www.atlascloud.ai/models/kwaivgi/kling-v2.1-i2v-pro
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.083 per second of generated video
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_video` with `model: "kwaivgi/kling-v2.1-i2v-pro"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate video kwaivgi/kling-v2.1-i2v-pro -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `kwaivgi/kling-v2.1-i2v-pro`


## 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:

- **`model`** (`string`, _required_):
  model name
  - Default: `"kwaivgi/kling-v2.1-i2v-pro"`

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation. max length 2500

- **`negative_prompt`** (`string`, _optional_):
  The negative prompt for the generation.

- **`image`** (`string`, _required_):
  First frame of the video; Supported image formats include.jpg/.jpeg/.png; The image file size cannot exceed 10MB, and the image resolution should not be less than 300*300px.

- **`guidance_scale`** (`number`, _optional_):
  The guidance scale to use for the generation.
  - Default: `0.5`
  - Min: 0
  - Max: 1

- **`duration`** (`integer`, _optional_):
  The duration of the generated media in seconds.
  - Default: `5`
  - Options: 5, 10



**Required Parameters Example**:

```json
{
  "model": "kwaivgi/kling-v2.1-i2v-pro",
  "prompt": "",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "kwaivgi/kling-v2.1-i2v-pro",
  "prompt": "",
  "negative_prompt": "",
  "image": "",
  "guidance_scale": 0.5,
  "duration": 5
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty when status is not completed).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "kwaivgi/kling-v2.1-i2v-pro",
  "prompt": "",
  "negative_prompt": "",
  "image": "",
  "guidance_scale": 0.5,
  "duration": 5
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/kwaivgi/kling-v2.1-i2v-pro)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

### Kling 2.1 Pro

**Kling 2.1 Pro** is a high-end extension of the Kling 2.1 image-to-video model, designed for professional creators seeking cinematic quality and control.

#### 🎥 Key Features

- **Enhanced Visual Fidelity**  
  Delivers sharper details, refined lighting, and more realistic rendering.

- **Precise Camera Movements**  
  Supports complex tracking, dolly, pan, and zoom effects for narrative depth.

- **Dynamic Motion Control**  
  Allows fine-tuned control over character and object motion for high-impact storytelling.

#### 🎬 Use Case

Perfect for creators, filmmakers, and studios aiming to generate cinematic sequences from images and prompts with a high degree of realism and directorial control.

---

**Kling 2.1 Pro** brings professional-grade visual storytelling to the next generation of generative video.

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/kwaivgi/kling-v2.1-i2v-pro · Docs: https://www.atlascloud.ai/docs