# Kling v2.0 t2v Master — Atlas Cloud API

> The foundational cinematic model combining high-fidelity visuals with realistic human motion generation.

This is the machine-readable API reference for **Kling v2.0 t2v Master** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `kwaivgi/kling-v2.0-t2v-master`
- **Built by**: Kuaishou
- **Modality**: Video
- **Model page**: https://www.atlascloud.ai/models/kwaivgi/kling-v2.0-t2v-master
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.238 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-v2.0-t2v-master"`.
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-v2.0-t2v-master -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-v2.0-t2v-master`


## 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-v2.0-t2v-master"`

- **`prompt`** (`string`, _required_):
  Text prompt for generation; Positive text prompt; Cannot exceed 2500 characters.
  - Default: `"Capture a dynamic, high-speed chase scene featuring two motorcycles navigating through a bustling cityscape at night. The camera alternates between close-up shots of the riders' intense expressions, the glowing neon signs of the city, and the sleek lines of the motorcycles as they weave through traffic. The sound of revving engines and the hum of the city create an exhilarating atmosphere."`

- **`aspect_ratio`** (`string`, _optional_):
  Generated video aspect ratio.
  - Default: `"16:9"`
  - Options: "16:9", "9:16", "1:1"

- **`negative_prompt`** (`string`, _optional_):
  Negative text prompt; Cannot exceed 2500 characters.

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



**Required Parameters Example**:

```json
{
  "model": "kwaivgi/kling-v2.0-t2v-master",
  "prompt": "Capture a dynamic, high-speed chase scene featuring two motorcycles navigating through a bustling cityscape at night. The camera alternates between close-up shots of the riders' intense expressions, the glowing neon signs of the city, and the sleek lines of the motorcycles as they weave through traffic. The sound of revving engines and the hum of the city create an exhilarating atmosphere."
}
```


**Full Example**:

```json
{
  "model": "kwaivgi/kling-v2.0-t2v-master",
  "prompt": "Capture a dynamic, high-speed chase scene featuring two motorcycles navigating through a bustling cityscape at night. The camera alternates between close-up shots of the riders' intense expressions, the glowing neon signs of the city, and the sleek lines of the motorcycles as they weave through traffic. The sound of revving engines and the hum of the city create an exhilarating atmosphere.",
  "aspect_ratio": "16:9",
  "negative_prompt": "",
  "duration": "5"
}
```


### Output Schema

The API returns the following output format:


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

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

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

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

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

- **`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.



**Example Response**:

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


## 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-v2.0-t2v-master",
  "prompt": "Capture a dynamic, high-speed chase scene featuring two motorcycles navigating through a bustling cityscape at night. The camera alternates between close-up shots of the riders' intense expressions, the glowing neon signs of the city, and the sleek lines of the motorcycles as they weave through traffic. The sound of revving engines and the hum of the city create an exhilarating atmosphere.",
  "aspect_ratio": "16:9",
  "negative_prompt": "",
  "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-v2.0-t2v-master)

## About this model

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

### Kling 2.0 Key Features

#### Enhanced Prompt Adherence  

Kling 2.0 interprets complex user prompts with sequential actions more precisely than ever. It can accurately understand intricate character actions, delicate expressions, and advanced camera movements, allowing professional-grade control over visual sequences.

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#### Better Motion Dynamics  

Kling 2.0 supports a greater motion range with more natural and fluid character movements. It generates immersive sequences simulating complex motions with realistic detail.

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#### Improved Visual Aesthetics  

Kling 2.0 produces higher-quality videos featuring richer details and more accurate visual style control. It enables cinematic-level sequences with dramatic expressions and consistent styles using reference images.

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#### Multi-Elements Editor  

Kling 2.0 introduces a powerful video editor that allows users to add, swap, or delete video content using text or image inputs. Users can swap elements such as clothing or even entire subjects, enabling greater customization and creative control.

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/kwaivgi/kling-v2.0-t2v-master · Docs: https://www.atlascloud.ai/docs