alibaba/wan-3.0-prime/reference-to-video

video-to-video

Wan 3.0 Prime Reference-to-Video API by Alibaba

alibaba/wan-3.0-prime/reference-to-video

Reference-to-video

All-in-One Reference: keep subjects consistent from any mix of reference images, videos, and audio; pixel-level identity/voice/space alignment.

Wan 3.0 Prime Reference-to-Video is developed by Alibaba. Atlas Cloud (operated by Atlas Cloud AI LLC) provides access to it and does not own it. All trademarks belong to their respective owners.

INPUT

Prompt *

Reference Materials(0/20)

You can drag and drop a file or click to upload

MAX:20

Document

Deep thinking

Turn on Deep thinking to attach a document or web link. Anything you've already added is kept.

Resolution

[ Original ] keeps the model’s native render. [ SR ] is cost-efficient upscaling. [ ESR ] is Atlas’s enhanced pass — more fine detail and steadier motion, still below the cost of rendering natively. Learn More

Duration

Aspect Ratio

Audio

Seed

OUTPUT

Idle

Your generated videos will appear here

Configure your settings and click Run to get started

Your request will cost $0.061 per run. For $10 you can run this model approximately 163 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-3.0-prime/reference-to-video",  # Required. model name
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. The text prompt describing the scene and action for the referenced subjects (up to 20000 characters)
    "refers": [
        {
            "url": "example_url",
            "type": "example_type"
        }
    ],  # All-in-One Reference materials
    "resolution": "1080p",  # Output resolution
    "duration": 5,  # Video length in seconds (2-30)
    "ratio": "adaptive",  # The aspect ratio of the generated video. options: adaptive | 16:9 | 4:3 | 1:1 | 3:4 | 9:16
    "audio": True,  # Whether the output video includes an audio track
    "enable_thinking": True,  # Enable deep thinking mode
    "file": "example_value",  # Optional document input to parse (requires enable_thinking)
    "link": "example_value",  # Optional public webpage URL to parse (requires enable_thinking)
    "seed": 1,  # The random seed to use for the generation
}

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-3.0-prime/reference-to-video",
    "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-3.0-prime/reference-to-video"

promptstringrequired

The text prompt describing the scene and action for the referenced subjects (up to 20000 characters).

refersarray[object]

All-in-One Reference materials. Any mix of reference images (<=10), reference videos (<=5, total <=15s), and reference audio (<=5, total <=15s), each a public URL. 'type' is optional — inferred from the URL when omitted. Image: jpeg/jpg/png/bmp/webp; video: mp4/mov; audio: wav/mp3. Reference mode is mutually exclusive with first/last-frame mode.

Max items: 20

urlstringrequired

Public URL of the reference image / video / audio.

typestring

Media kind. Optional; inferred from the URL when omitted.

imagevideoaudio

resolutionstring

Output resolution. Native tiers: 480p, 720p, 1080p. ESR tiers: 720p-esr, 1080p-esr, 1440p-esr, 4k-esr.

Default: "1080p"

1080p720p480p720p-esr1080p-esr1440p-esr4k-esr

durationnumber

Video length in seconds (2-30). Pass -1 for smart-duration (the model picks the best length).

Default: 5

-123456789101112131415161718192021222324252627282930

ratiostring

The aspect ratio of the generated video. Use 'adaptive' to let the model choose from the references.

Default: "adaptive"

adaptive16:94:31:13:49:16

audioboolean

Whether the output video includes an audio track. Same price either way.

Default: true

enable_thinkingboolean

Enable deep thinking mode. Required when providing a file or link input (document / webpage parsing). Not recommended when no file/link is provided.

Default: true

filestring

Optional document input to parse (requires enable_thinking). Public URL. Formats: docx, doc, xlsx, xls, pptx, ppt, pdf, txt, key, pages, numbers, md; <= 100MB, <= 50 pages. Mutually exclusive with 'link'.

linkstring

Optional public webpage URL to parse (requires enable_thinking). Only pages that need no login. Mutually exclusive with 'file'.

seedinteger

The random seed to use for the generation. -1 means a random seed will be used.

Example Request Body

{
  "model": "alibaba/wan-3.0-prime/reference-to-video",
  "prompt": "A beautiful landscape",
  "resolution": "1080p",
  "duration": 5,
  "ratio": "adaptive",
  "audio": true,
  "enable_thinking": true
}

Output Schema

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

created_atstring

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

idstring

Unique identifier for the prediction, the ID of the prediction to get.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content (empty when status is not completed).

statusstring

Status of the task: created, processing, completed, or failed.

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

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "alibaba/wan-3.0-prime/reference-to-video"
          },
          "prompt": {
            "description": "The text prompt describing the scene and action for the referenced subjects (up to 20000 characters).",
            "type": "string"
          },
          "refers": {
            "description": "All-in-One Reference materials. Any mix of reference images (<=10), reference videos (<=5, total <=15s), and reference audio (<=5, total <=15s), each a public URL. 'type' is optional — inferred from the URL when omitted. Image: jpeg/jpg/png/bmp/webp; video: mp4/mov; audio: wav/mp3. Reference mode is mutually exclusive with first/last-frame mode.",
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "url": {
                  "type": "string",
                  "description": "Public URL of the reference image / video / audio.",
                  "x-ui-component": "uploaders"
                },
                "type": {
                  "type": "string",
                  "description": "Media kind. Optional; inferred from the URL when omitted.",
                  "enum": [
                    "image",
                    "video",
                    "audio"
                  ]
                }
              },
              "required": [
                "url"
              ]
            },
            "maxItems": 20,
            "x-accept": ".jpeg,.jpg,.png,.bmp,.webp,.mp4,.mov,.wav,.mp3",
            "x-media-limits": {
              "image": {
                "maxItems": 10
              },
              "video": {
                "maxItems": 5,
                "maxTotalDuration": 15,
                "maxDuration": 15,
                "minDuration": 1
              },
              "audio": {
                "maxItems": 5,
                "maxTotalDuration": 15,
                "maxDuration": 15,
                "minDuration": 1
              }
            },
            "x-ui-component": "uploaders"
          },
          "resolution": {
            "default": "1080p",
            "description": "Output resolution. Native tiers: 480p, 720p, 1080p. ESR tiers: 720p-esr, 1080p-esr, 1440p-esr, 4k-esr.",
            "enum": [
              "1080p",
              "720p",
              "480p",
              "720p-esr",
              "1080p-esr",
              "1440p-esr",
              "4k-esr"
            ],
            "type": "string",
            "x-ui-component": "select"
          },
          "duration": {
            "default": 5,
            "description": "Video length in seconds (2-30). Pass -1 for smart-duration (the model picks the best length).",
            "enum": [
              -1,
              2,
              3,
              4,
              5,
              6,
              7,
              8,
              9,
              10,
              11,
              12,
              13,
              14,
              15,
              16,
              17,
              18,
              19,
              20,
              21,
              22,
              23,
              24,
              25,
              26,
              27,
              28,
              29,
              30
            ],
            "x-enum-labels": {
              "-1": "Smart"
            },
            "type": "number",
            "totalMaximum": 30,
            "inputMaximum": 15,
            "x-ui-component": "select"
          },
          "ratio": {
            "default": "adaptive",
            "description": "The aspect ratio of the generated video. Use 'adaptive' to let the model choose from the references.",
            "enum": [
              "adaptive",
              "16:9",
              "4:3",
              "1:1",
              "3:4",
              "9:16"
            ],
            "type": "string",
            "x-ui-component": "select"
          },
          "audio": {
            "default": true,
            "description": "Whether the output video includes an audio track. Same price either way.",
            "type": "boolean",
            "x-ui-component": "switch"
          },
          "enable_thinking": {
            "default": true,
            "description": "Enable deep thinking mode. Required when providing a file or link input (document / webpage parsing). Not recommended when no file/link is provided.",
            "type": "boolean",
            "x-ui-component": "switch"
          },
          "file": {
            "description": "Optional document input to parse (requires enable_thinking). Public URL. Formats: docx, doc, xlsx, xls, pptx, ppt, pdf, txt, key, pages, numbers, md; <= 100MB, <= 50 pages. Mutually exclusive with 'link'.",
            "type": "string",
            "x-ui-component": "uploaders",
            "x-accept": ".docx,.doc,.xlsx,.xls,.pptx,.ppt,.pdf,.txt,.key,.pages,.numbers,.md",
            "x-max-size-mb": 100
          },
          "link": {
            "description": "Optional public webpage URL to parse (requires enable_thinking). Only pages that need no login. Mutually exclusive with 'file'.",
            "type": "string",
            "x-ui-component": "input"
          },
          "seed": {
            "description": "The random seed to use for the generation. -1 means a random seed will be used.",
            "type": "integer"
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "allOf": [
          {
            "if": {
              "properties": {
                "enable_thinking": {
                  "const": true
                }
              },
              "required": [
                "enable_thinking"
              ]
            },
            "else": {
              "properties": {
                "file": {
                  "x-hidden": true
                },
                "link": {
                  "x-hidden": true
                }
              }
            }
          },
          {
            "if": {
              "properties": {
                "enable_thinking": {
                  "const": true
                },
                "file": {
                  "type": "string",
                  "minLength": 1
                }
              },
              "required": [
                "enable_thinking",
                "file"
              ]
            },
            "then": {
              "properties": {
                "link": {
                  "x-hidden": true
                }
              }
            }
          },
          {
            "if": {
              "properties": {
                "enable_thinking": {
                  "const": true
                },
                "link": {
                  "type": "string",
                  "minLength": 1
                }
              },
              "required": [
                "enable_thinking",
                "link"
              ]
            },
            "then": {
              "properties": {
                "file": {
                  "x-hidden": true
                }
              }
            }
          }
        ],
        "x-order-properties": [
          "model",
          "prompt",
          "refers",
          "resolution",
          "duration",
          "ratio",
          "audio",
          "enable_thinking",
          "file",
          "link",
          "seed"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).",
            "format": "date-time",
            "type": "string"
          },
          "id": {
            "description": "Unique identifier for the prediction, the ID of the prediction to get.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/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": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    },
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$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"
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM-Friendly Prompt Template

# alibaba/wan-3.0-prime/reference-to-video

> All-in-One Reference: keep subjects consistent from any mix of reference images, videos, and audio; pixel-level identity/voice/space alignment.


## 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-3.0-prime/reference-to-video`


## 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-3.0-prime/reference-to-video"`

- **`prompt`** (`string`, _required_):
  The text prompt describing the scene and action for the referenced subjects (up to 20000 characters).

- **`refers`** (`array[object]`, _optional_):
  All-in-One Reference materials. Any mix of reference images (<=10), reference videos (<=5, total <=15s), and reference audio (<=5, total <=15s), each a public URL. 'type' is optional — inferred from the URL when omitted. Image: jpeg/jpg/png/bmp/webp; video: mp4/mov; audio: wav/mp3. Reference mode is mutually exclusive with first/last-frame mode.
  - Max items: 20
  - Item properties:
    - **`url`** (`string`, _required_):
      Public URL of the reference image / video / audio.

    - **`type`** (`string`, _optional_):
      Media kind. Optional; inferred from the URL when omitted.
      - Options: "image", "video", "audio"


- **`resolution`** (`string`, _optional_):
  Output resolution. Native tiers: 480p, 720p, 1080p. ESR tiers: 720p-esr, 1080p-esr, 1440p-esr, 4k-esr.
  - Default: `"1080p"`
  - Options: "1080p", "720p", "480p", "720p-esr", "1080p-esr", "1440p-esr", "4k-esr"

- **`duration`** (`number`, _optional_):
  Video length in seconds (2-30). Pass -1 for smart-duration (the model picks the best length).
  - Default: `5`
  - Options: -1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30

- **`ratio`** (`string`, _optional_):
  The aspect ratio of the generated video. Use 'adaptive' to let the model choose from the references.
  - Default: `"adaptive"`
  - Options: "adaptive", "16:9", "4:3", "1:1", "3:4", "9:16"

- **`audio`** (`boolean`, _optional_):
  Whether the output video includes an audio track. Same price either way.
  - Default: `true`

- **`enable_thinking`** (`boolean`, _optional_):
  Enable deep thinking mode. Required when providing a file or link input (document / webpage parsing). Not recommended when no file/link is provided.
  - Default: `true`

- **`file`** (`string`, _optional_):
  Optional document input to parse (requires enable_thinking). Public URL. Formats: docx, doc, xlsx, xls, pptx, ppt, pdf, txt, key, pages, numbers, md; <= 100MB, <= 50 pages. Mutually exclusive with 'link'.

- **`link`** (`string`, _optional_):
  Optional public webpage URL to parse (requires enable_thinking). Only pages that need no login. Mutually exclusive with 'file'.

- **`seed`** (`integer`, _optional_):
  The random seed to use for the generation. -1 means a random seed will be used.



**Required Parameters Example**:

```json
{
  "model": "alibaba/wan-3.0-prime/reference-to-video",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "alibaba/wan-3.0-prime/reference-to-video",
  "prompt": "",
  "refers": [
    {
      "url": "",
      "type": "image"
    }
  ],
  "resolution": "1080p",
  "duration": 5,
  "ratio": "adaptive",
  "audio": true,
  "enable_thinking": true,
  "file": "",
  "link": "",
  "seed": 0
}
```


### 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”).

- **`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": "",
  "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": "alibaba/wan-3.0-prime/reference-to-video",
  "prompt": "",
  "refers": [
    {
      "url": "",
      "type": "image"
    }
  ],
  "resolution": "1080p",
  "duration": 5,
  "ratio": "adaptive",
  "audio": true,
  "enable_thinking": true,
  "file": "",
  "link": "",
  "seed": 0
}'

# 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-3.0-prime/reference-to-video)

Transform the visual style into a cartoon or anime style.

Wan 3.0 Prime Reference-to-Video

Wan 3.0 Prime Reference-to-Video is the "all-in-one reference" mode: give it any mix of reference images, videos, and audio, and it keeps those subjects, props, voices, and spatial relationships consistent throughout a new clip driven by your prompt. This is pixel-level identity preservation — not "close enough," but faithful replication of the reference details.

Why Choose This?

Mix four modalities Combine reference images, reference videos, and reference audio in one request.
Pixel-level consistency Characters, props, voices, and spatial relationships stay aligned across the whole clip.
Multi-subject scenes Reference several subjects at once and direct them with your prompt.
Native long-form + audio Up to 30 seconds with a synchronized audio track.
Flexible aspect ratios adaptive, 16:9, 4:3, 1:1, 3:4, or 9:16.

Parameters

Parameter	Required	Description
prompt	Yes	Text description of the scene and action for the subjects (up to 5000 chars)
refers	Yes	Array of reference materials, each `{ "url": "...", "type": "image\|video\|audio" }`. `type` is optional (inferred from the URL)
resolution	No	Output quality: 1080P (default), 720P, 480P
duration	No	Output length in seconds: 5 (default), 2–30. Pass -1 for smart-duration
ratio	No	Aspect ratio: adaptive (default), 16:9, 4:3, 1:1, 3:4, 9:16
audio	No	Whether the output has an audio track: true (default) / false
enable_thinking	No	Deep thinking mode: false (default). Required for file/link parsing
file	No	Document to parse (requires enable_thinking): docx/doc/xlsx/xls/ppt/pdf/txt/key/pages/numbers/md , ≤100MB, ≤50 pages. Mutually exclusive with link
link	No	Public webpage URL to parse (requires enable_thinking; no-login pages only). Mutually exclusive with file

Reference limits

Kind	Max count	Notes
Image	10	jpeg/jpg/png (no alpha)/bmp/webp, single edge 240–8000px, ratio ≤ 8:1, ≤ 20MB
Video	5	mp4/mov, total ≤ 15s, each 1–15s, single edge 240–4096px, ≤ 100MB
Audio	5	wav/mp3, total ≤ 15s, each 1–15s, ≤ 15MB

`refers` example

"refers": [
  { "url": "https://.../subject1.jpg", "type": "image" },
  { "url": "https://.../subject2.png" },
  { "url": "https://.../clip.mp4", "type": "video" },
  { "url": "https://.../beat.mp3", "type": "audio" }
]

How to Use

Add your references — any mix of images, videos, and/or audio.
Write your prompt — describe the scene, action, and camera movement for the subjects.
Set resolution, duration, and ratio.
Run — submit and download your video.

Best Use Cases

Character Consistency — Keep the same character across shots.
Product Placement — Feature a specific product in generated scenes.
Branded Content — Maintain a consistent mascot or spokesperson.
Audio-driven Motion — Sync the action to a reference beat.

Pro Tips

Give one clean image per subject when combining several subjects.
Describe the new scene and action, not the reference materials themselves.
Supply a reference audio track to drive the timing/beat of the motion.

Notes

prompt and at least one reference are required.
Reference mode is mutually exclusive with first/last-frame mode — do not mix reference materials with image/last_image; use Image-to-Video for strict frame control.
file and link require enable_thinking = true and are mutually exclusive.
Negative prompts are not supported on Wan 3.0.
Ensure all reference URLs are publicly accessible.
Generation is asynchronous — submit, then poll for the finished video.

Wan 3.0 Text-to-Video — Generate video directly from a text prompt.
Wan 3.0 Image-to-Video — Animate a first frame (optionally with a last frame).

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