alibaba/wan-2.7/video-edit

video-to-video

Wan 2.7 Video-edit API by Alibaba

alibaba/wan-2.7/video-edit

Video-edit

Edits videos using text instructions, reference images, and style transfer with multi-modal input support.

INPUT

Prompt

Negative Prompt

Video *

You can drag and drop a file or click to upload

MAX:1

Images(0/4)

You can drag and drop a file or click to upload

MAX:4

Audio

You can drag and drop a file or click to upload

MAX:1

Resolution

Aspect Ratio

Additional Settings

OUTPUT

Idle

Your generated videos will appear here

Configure your settings and click Run to get started

Your request will cost $0.1 per run. For $10 you can run this model approximately 100 times.

Here's what you can do next:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameters

Code Example
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/wan-2.7/video-edit",  # Required. Model name. options: alibaba/wan-2.7/video-edit
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Text instruction describing the desired edit
    "negative_prompt": "example_value",  # Text describing elements to exclude from the video
    "video": "example_value",  # Required. URL of the video to edit
    "images": [
        "https://example.com/image1.jpg"
    ],  # Reference image URLs for style or content guidance
    "audio": "example_value",  # Optional driving audio URL for the edited output
    "resolution": "1080P",  # Output video resolution. options: 720P | 1080P
    "ratio": "example_value",  # Aspect ratio of the output video. options: 16:9 | 9:16 | 1:1 | 4:3 | 3:4
    "duration": 0,  # Output video duration in seconds. (min: 0, max: 10)
    "prompt_extend": True,  # Whether to use AI to enhance the prompt for better video quality
    "seed": -1,  # Random seed for video generation. (min: -1, max: 2147483647)
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

Install

Install the required package for your language.

pip install requests

Authentication

All API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.

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

HTTP Headers

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Keep your API key secure

Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.

Submit a request

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Submit a Request

Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.

POST/api/v1/model/generateVideo

Request Body

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "alibaba/wan-2.7/video-edit",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Response

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Check Status

Poll the prediction endpoint to check the current status of your request.

GET/api/v1/model/prediction/{prediction_id}

Polling Example

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Status Values

processingThe request is still being processed.

completedGeneration is complete. Outputs are available.

succeededGeneration succeeded. Outputs are available.

failedGeneration failed. Check the error field.

Completed Response

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Upload Files

Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.

POST/api/v1/model/uploadMedia

Upload Example

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Response

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

The following parameters are accepted in the request body.

Total: 11Required: 2Optional: 9

modelstringrequired

Model name.

Default: "alibaba/wan-2.7/video-edit"

alibaba/wan-2.7/video-edit

promptstring

Text instruction describing the desired edit. Maximum length is 5000 characters.

negative_promptstring

Text describing elements to exclude from the video. Maximum length is 500 characters.

videostringrequired

URL of the video to edit. Supported formats: mp4, mov. Duration: 2–10 seconds. Maximum file size: 100 MB.

imagesarray[string]

Reference image URLs for style or content guidance. Up to 3 images. Supported formats: JPEG, JPG, PNG (transparent channel not supported), BMP, WEBP. Width and height must each be between 240 and 8000 pixels. Aspect ratio must be between 1:8 and 8:1. Maximum file size: 20 MB per image.

audiostring

Optional driving audio URL for the edited output. Supported formats: wav, mp3. Duration: 2–30 seconds. Maximum file size: 15 MB. The alias `audio_url` is also accepted.

resolutionstring

Output video resolution. Higher resolution increases cost.

Default: "1080P"

720P1080P

ratiostring

Aspect ratio of the output video. When omitted, the output follows the input video's aspect ratio.

16:99:161:14:33:4

durationinteger

Output video duration in seconds. Set to 0 or omit to match the input video duration. When set to a positive value, the output is clipped from the start of the input video. Range: 2–10.

Min: 0Max: 10

prompt_extendboolean

Whether to use AI to enhance the prompt for better video quality. Increases generation time.

Default: true

seedinteger

Random seed for video generation. Range: 0 to 2147483647. Use -1 for a random seed.

Default: -1Min: -1Max: 2147483647

Example Request Body

{
  "model": "alibaba/wan-2.7/video-edit",
  "video": "example_video",
  "resolution": "1080P",
  "prompt_extend": true,
  "seed": -1
}

Output Schema

The API returns a prediction response with the generated output URLs.

codeinteger

messagestring

dataunknown

Example Response

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integrates 400+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.

Supported Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ supported clients

Install

npx skills add AtlasCloudAI/atlas-cloud-skills

Setup API Key

Get your API key from the Atlas Cloud dashboard and set it as an environment variable.

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

Capabilities

Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.

Image GenerationGenerate images with models like Nano Banana 2, Z-Image, and more.

Video CreationCreate videos from text or images with Kling, Vidu, Veo, etc.

LLM ChatChat with Qwen, DeepSeek, and other large language models.

Media UploadUpload local files for image editing and image-to-video workflows.

Learn more

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server connects your IDE with 400+ AI models via the Model Context Protocol. Works with any MCP-compatible client.

Supported Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ supported clients

Install

npx -y atlascloud-mcp

Configuration

Add the following configuration to your IDE's MCP settings file.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

atlas_generate_imageGenerate images from text prompts.

atlas_generate_videoCreate videos from text or images.

atlas_chatChat with large language models.

atlas_list_modelsBrowse 400+ available AI models.

atlas_quick_generateOne-step content creation with auto model selection.

atlas_upload_mediaUpload local files for API workflows.

Learn more

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "alibaba/wan-2.7/video-edit",
            "enum": [
              "alibaba/wan-2.7/video-edit"
            ]
          },
          "prompt": {
            "description": "Text instruction describing the desired edit. Maximum length is 5000 characters.",
            "type": "string"
          },
          "negative_prompt": {
            "description": "Text describing elements to exclude from the video. Maximum length is 500 characters.",
            "type": "string"
          },
          "video": {
            "description": "URL of the video to edit. Supported formats: mp4, mov. Duration: 2–10 seconds. Maximum file size: 100 MB.",
            "type": "string"
          },
          "images": {
            "description": "Reference image URLs for style or content guidance. Up to 3 images. Supported formats: JPEG, JPG, PNG (transparent channel not supported), BMP, WEBP. Width and height must each be between 240 and 8000 pixels. Aspect ratio must be between 1:8 and 8:1. Maximum file size: 20 MB per image.",
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          "audio": {
            "description": "Optional driving audio URL for the edited output. Supported formats: wav, mp3. Duration: 2–30 seconds. Maximum file size: 15 MB. The alias `audio_url` is also accepted.",
            "type": "string"
          },
          "resolution": {
            "default": "1080P",
            "description": "Output video resolution. Higher resolution increases cost.",
            "enum": [
              "720P",
              "1080P"
            ],
            "type": "string"
          },
          "ratio": {
            "description": "Aspect ratio of the output video. When omitted, the output follows the input video's aspect ratio.",
            "enum": [
              "16:9",
              "9:16",
              "1:1",
              "4:3",
              "3:4"
            ],
            "type": "string"
          },
          "duration": {
            "minimum": 0,
            "maximum": 10,
            "description": "Output video duration in seconds. Set to 0 or omit to match the input video duration. When set to a positive value, the output is clipped from the start of the input video. Range: 2–10.",
            "type": "integer"
          },
          "prompt_extend": {
            "default": true,
            "description": "Whether to use AI to enhance the prompt for better video quality. Increases generation time.",
            "type": "boolean"
          },
          "seed": {
            "default": -1,
            "minimum": -1,
            "maximum": 2147483647,
            "description": "Random seed for video generation. Range: 0 to 2147483647. Use -1 for a random seed.",
            "type": "integer"
          }
        },
        "required": [
          "model",
          "video"
        ],
        "x-order-properties": [
          "model",
          "prompt",
          "negative_prompt",
          "video",
          "images",
          "audio",
          "resolution",
          "ratio",
          "duration",
          "prompt_extend",
          "seed"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer"
          },
          "message": {
            "type": "string"
          },
          "data": {
            "$ref": "#/components/schemas/PredictionData"
          }
        }
      },
      "PredictionData": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Unique ID of the generation task."
          },
          "model": {
            "type": "string",
            "description": "Model used for the generation."
          },
          "outputs": {
            "type": "array",
            "description": "Generated video results. Each item is a video URL.",
            "items": {
              "type": "string"
            }
          },
          "urls": {
            "type": "object",
            "properties": {
              "get": {
                "type": "string"
              }
            }
          },
          "status": {
            "type": "string",
            "description": "Current task status, such as created, processing, completed, unknown, or failed."
          },
          "created_at": {
            "type": "string",
            "format": "date-time"
          },
          "error": {
            "type": "string",
            "description": "Error message returned when the task fails."
          }
        }
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM-Friendly Prompt Template

# alibaba/wan-2.7/video-edit

> Edits videos using text instructions, reference images, and style transfer with multi-modal input support.


## Overview

- **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**: `alibaba/wan-2.7/video-edit`


## 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: `"alibaba/wan-2.7/video-edit"`
  - Options: "alibaba/wan-2.7/video-edit"

- **`prompt`** (`string`, _optional_):
  Text instruction describing the desired edit. Maximum length is 5000 characters.

- **`negative_prompt`** (`string`, _optional_):
  Text describing elements to exclude from the video. Maximum length is 500 characters.

- **`video`** (`string`, _required_):
  URL of the video to edit. Supported formats: mp4, mov. Duration: 2–10 seconds. Maximum file size: 100 MB.

- **`images`** (`array[string]`, _optional_):
  Reference image URLs for style or content guidance. Up to 3 images. Supported formats: JPEG, JPG, PNG (transparent channel not supported), BMP, WEBP. Width and height must each be between 240 and 8000 pixels. Aspect ratio must be between 1:8 and 8:1. Maximum file size: 20 MB per image.

- **`audio`** (`string`, _optional_):
  Optional driving audio URL for the edited output. Supported formats: wav, mp3. Duration: 2–30 seconds. Maximum file size: 15 MB. The alias `audio_url` is also accepted.

- **`resolution`** (`string`, _optional_):
  Output video resolution. Higher resolution increases cost.
  - Default: `"1080P"`
  - Options: "720P", "1080P"

- **`ratio`** (`string`, _optional_):
  Aspect ratio of the output video. When omitted, the output follows the input video's aspect ratio.
  - Options: "16:9", "9:16", "1:1", "4:3", "3:4"

- **`duration`** (`integer`, _optional_):
  Output video duration in seconds. Set to 0 or omit to match the input video duration. When set to a positive value, the output is clipped from the start of the input video. Range: 2–10.
  - Min: 0
  - Max: 10

- **`prompt_extend`** (`boolean`, _optional_):
  Whether to use AI to enhance the prompt for better video quality. Increases generation time.
  - Default: `true`

- **`seed`** (`integer`, _optional_):
  Random seed for video generation. Range: 0 to 2147483647. Use -1 for a random seed.
  - Default: `-1`
  - Min: -1
  - Max: 2147483647



**Required Parameters Example**:

```json
{
  "model": "alibaba/wan-2.7/video-edit",
  "video": ""
}
```


**Full Example**:

```json
{
  "model": "alibaba/wan-2.7/video-edit",
  "prompt": "",
  "negative_prompt": "",
  "video": "",
  "images": [
    ""
  ],
  "audio": "",
  "resolution": "1080P",
  "ratio": "16:9",
  "duration": 0,
  "prompt_extend": true,
  "seed": -1
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):

- **`message`** (`string`, _optional_):

- **`data`** (`string`, _optional_):



**Example Response**:

```json
{
  "code": 0,
  "message": "",
  "data": null
}
```


## 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": "alibaba/wan-2.7/video-edit",
  "prompt": "",
  "negative_prompt": "",
  "video": "",
  "images": [
    ""
  ],
  "audio": "",
  "resolution": "1080P",
  "ratio": "16:9",
  "duration": 0,
  "prompt_extend": true,
  "seed": -1
}'

# 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/alibaba/wan-2.7/video-edit)

Turn the source clip into a cinematic product shot with smooth camera movement and richer studio lighting.

Apply a clean fashion campaign style while preserving the original subject motion.

Enhance the clip with high-detail texture, stable edges, and a polished commercial look.

Wan 2.7 Video-edit

Wan 2.7 Video-edit edits an input video from text instructions and optional reference media. Use it for style transfer, subject-preserving edits, commercial polish, and short creative transformations.

Highlights

Video editing with text control: Provide a source video and describe the target look or action.
Optional reference media: Add a single reference image, multiple reference images, or driving audio when the edit needs extra visual or motion guidance.
Native output tiers: Choose 720P or 1080P for Wan 2.7 native video-edit output.
Common aspect ratios: Supports 16:9, 9:16, 1:1, 4:3, and 3:4.

Parameters

Parameter	Required	Description
`model`	Yes	`alibaba/wan-2.7/video-edit`
`prompt`	Yes	Text instruction describing the edit.
`negative_prompt`	No	Text describing what to avoid.
`video`	Yes	Input video URL to edit.
`image`	No	Single reference image URL. The alias `first_frame` is also accepted.
`images`	No	Reference image URLs for style, subject, or object guidance.
`audio`	No	Driving audio URL. The aliases `audio_url` and `driving_audio` are also accepted.
`resolution`	No	`720P` or `1080P`. Defaults to native `1080P`.
`ratio`	No	`16:9`, `9:16`, `1:1`, `4:3`, or `3:4`. Defaults to `16:9`.
`duration`	No	Output duration in seconds. Defaults to `5`.
`prompt_extend`	No	Enable upstream prompt expansion. Defaults to `true`.
`watermark`	No	Whether to add the upstream provider watermark when supported.
`seed`	No	Random seed. `-1` means random.

Resolution Tiers

Request value	Path	Price multiplier
`720P`	Native Wan 2.7	1.0x
`1080P`	Native Wan 2.7	1.5x

Omitted resolution uses native 1080P.

How To Use

curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $AIP_API_KEY" \
  -H "Content-Type: application/json" \
  --data-raw '{
    "model": "alibaba/wan-2.7/video-edit",
    "prompt": "Enhance the clip with high-detail texture, stable edges, and a polished commercial look.",
    "video": "https://static.atlascloud.ai/media/videos/af3ce4416487e61f8b299c5dc42642e3.mp4",
    "resolution": "1080P",
    "ratio": "16:9",
    "duration": 5,
    "prompt_extend": true,
    "seed": -1
  }'

Notes

Generation is asynchronous. Poll /api/v1/model/prediction/{request_id} for the final video URL.
Native 1080P uses the upstream Wan 2.7 1080P path.

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HappyHorse-1.0 Image-to-video

Animates a first-frame image into video with optional prompt guidance, 720P or 1080P output, and durations from 3 to 15 seconds.

HappyHorse-1.0 Text-to-video

Generates videos from text prompts with HappyHorse 1.0, supporting 720P or 1080P output, flexible aspect ratios, and durations from 3 to 15 seconds.

HappyHorse-1.0 Reference-to-video

Generates videos from one to nine reference images and a text prompt, supporting 720P or 1080P output, flexible aspect ratios, and durations from 3 to 15 seconds.

HappyHorse-1.0 Video-edit

Edits an input video with text instructions and optional reference images, supporting 720P or 1080P output.

Wan-2.7 Image-to-video

Animates images into videos with first-frame, first-and-last-frame, video continuation, and audio-driven modes.

Wan-2.7 Text-to-video

Generates videos from text prompts with multi-shot narrative, audio generation, and sound-image synchronization.

Wan-2.7 Reference-to-video

Generates character-driven videos from reference images and videos, with multi-subject and voice-cloning support.

Wan-2.2 Image-to-video Lora

Open and Advanced Large-Scale Video Generative Models.

Wan-2.2 Image-to-video

Open and Advanced Large-Scale Video Generative Models.

From

$0.03/SEC

image-to-video

Wan-2.2-spicy Image-to-video

Open and Advanced Large-Scale Video Generative Models.

From

$0.03/SEC

image-to-video

Wan-2.2-spicy Image-to-video Lora

Open and Advanced Large-Scale Video Generative Models.

Wan-2.6 Image-to-video Flash

Wan2.6 image to video flash, faster and more cost-effective generation. Intelligent shot scheduling enables multi‑camera storytelling, supports stable multi‑speaker dialogue with more natural and realistic vocal timbres.

Wan-2.6 Video-to-video

A speed-optimized video-to-video option that prioritizes lower latency while retaining strong visual fidelity. Ideal for iteration, batch generation, and prompt testing.

From$0.1/SEC

$0.07/SEC

-30%

One API for All Media AI.

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Wan 2.7 Video-edit API by Alibaba

INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body

Output Schema

Example Response

Atlas Cloud Skills

Supported Clients

Install

Setup API Key

Capabilities

MCP Server

Supported Clients

Install

Configuration

Available Tools

API Schema

LLM-Friendly Prompt Template

Wan 2.7 Video-edit

Highlights

Parameters

Resolution Tiers

How To Use

Notes

Explore Similar Models

HappyHorse-1.1 Reference-to-video

HappyHorse-1.1 Text-to-video

HappyHorse-1.1 Image-to-video

HappyHorse-1.0 Image-to-video

HappyHorse-1.0 Text-to-video

HappyHorse-1.0 Reference-to-video

HappyHorse-1.0 Video-edit

Wan-2.7 Image-to-video

Wan-2.7 Text-to-video

Wan-2.7 Reference-to-video

Wan-2.2 Image-to-video Lora

Wan-2.2 Image-to-video

Wan-2.2-spicy Image-to-video

Wan-2.2-spicy Image-to-video Lora

Wan-2.6 Image-to-video Flash

Wan-2.6 Video-to-video

One API for All Media AI.

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INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body