ltx/ltx-2.5-pro/image-to-video

image-to-video

PRO

LTX 2.5 Pro Image-to-Video API by LTX

ltx/ltx-2.5-pro/image-to-video

Image-to-video

LTX-2.5 Pro image-to-video (Lightricks LTX-2 native API): animate a first-frame image (optionally interpolating to a last frame), up to 4K at 24/48 fps (6–10s, top-quality, with synchronized audio).

Compare models

LTX 2.5 Pro Image-to-Video is developed by a third-party provider. 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

Image *

You can drag and drop a file or click to upload

MAX:1

Last Image

You can drag and drop a file or click to upload

MAX:1

Duration

Resolution

Aspect Ratio

Frame rate

Generate Audio

Camera motion

OUTPUT

Idle

Your generated videos will appear here

Configure your settings and click Run to get started

Your request will cost $0.12 per run. For $10 you can run this model approximately 83 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": "ltx/ltx-2.5-pro/image-to-video",  # Required. Model name
    "image": "example_value",  # Required. First-frame image: URL, Base64, or asset reference (asset://<ASSET_ID>)
    "last_image": "example_value",  # Optional last-frame image (URL / Base64 / asset://)
    "prompt": "The scene comes alive with gentle, natural motion and cinematic lighting.",  # Text prompt describing the desired motion, camera movement and atmosphere
    "duration": -1,  # Video length in seconds. options: -1 | 6 | 8 | 10
    "resolution": "720p",  # Output resolution tier. options: 720p | 1080p | 1440p | 4k
    "aspect_ratio": "16:9",  # Frame orientation: 16:9 landscape or 9:16 portrait. options: 16:9 | 9:16
    "fps": 24,  # Frames per second. options: 24 | 48
    "generate_audio": True,  # Whether to generate AI audio (ambience, effects, speech) matching the scene
    "camera_motion": "example_value",  # Optional camera movement directive applied to the shot
}

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": "ltx/ltx-2.5-pro/image-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: 10Required: 2Optional: 8

modelstringrequired

Model name.

Default: "ltx/ltx-2.5-pro/image-to-video"

imagestringrequired

First-frame image: URL, Base64, or asset reference (asset://<ASSET_ID>). The video starts from this image.

last_imagestring

Optional last-frame image (URL / Base64 / asset://). When set, the clip interpolates from the first frame to this frame.

promptstring

Text prompt describing the desired motion, camera movement and atmosphere. Optional but recommended.

Default: "The scene comes alive with gentle, natural motion and cinematic lighting."

durationinteger

Video length in seconds. Use -1 to let the model choose the duration automatically.

Default: -1

-16810

resolutionstring

Output resolution tier. Combined with aspect_ratio to select the exact frame size (720p→1280x720, 1080p→1920x1080, 1440p→2560x1440, 4k→3840x2160; portrait 9:16 swaps width/height). 1440p and 4k support 6–10s durations only.

Default: "720p"

720p1080p1440p4k

aspect_ratiostring

Frame orientation: 16:9 landscape or 9:16 portrait.

Default: "16:9"

16:99:16

fpsinteger

Frames per second. 48 fps is available only for durations ≤10s; at 1440p and 4k all durations are ≤10s regardless of fps.

Default: 24

2448

generate_audioboolean

Whether to generate AI audio (ambience, effects, speech) matching the scene.

Default: true

camera_motionstring

Optional camera movement directive applied to the shot.

dolly_indolly_outdolly_leftdolly_rightjib_upjib_downstaticfocus_shift

Example Request Body

{
  "model": "ltx/ltx-2.5-pro/image-to-video",
  "image": "example_image",
  "prompt": "The scene comes alive with gentle, natural motion and cinematic lighting.",
  "duration": -1,
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "fps": 24,
  "generate_audio": true
}

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": "LTX-2.5 Pro image-to-video (Lightricks LTX-2 native API)."
  },
  "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"
    }
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "required": [
          "model",
          "image"
        ],
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "ltx/ltx-2.5-pro/image-to-video"
          },
          "image": {
            "type": "string",
            "description": "First-frame image: URL, Base64, or asset reference (asset://<ASSET_ID>). The video starts from this image."
          },
          "last_image": {
            "type": "string",
            "description": "Optional last-frame image (URL / Base64 / asset://). When set, the clip interpolates from the first frame to this frame."
          },
          "prompt": {
            "type": "string",
            "default": "The scene comes alive with gentle, natural motion and cinematic lighting.",
            "description": "Text prompt describing the desired motion, camera movement and atmosphere. Optional but recommended."
          },
          "duration": {
            "type": "integer",
            "default": -1,
            "enum": [
              -1,
              6,
              8,
              10
            ],
            "description": "Video length in seconds. Use -1 to let the model choose the duration automatically.",
            "x-ui-component": "slider"
          },
          "resolution": {
            "type": "string",
            "default": "720p",
            "enum": [
              "720p",
              "1080p",
              "1440p",
              "4k"
            ],
            "description": "Output resolution tier. Combined with aspect_ratio to select the exact frame size (720p→1280x720, 1080p→1920x1080, 1440p→2560x1440, 4k→3840x2160; portrait 9:16 swaps width/height). 1440p and 4k support 6–10s durations only."
          },
          "aspect_ratio": {
            "type": "string",
            "default": "16:9",
            "enum": [
              "16:9",
              "9:16"
            ],
            "description": "Frame orientation: 16:9 landscape or 9:16 portrait."
          },
          "fps": {
            "type": "integer",
            "default": 24,
            "enum": [
              24,
              48
            ],
            "description": "Frames per second. 48 fps is available only for durations ≤10s; at 1440p and 4k all durations are ≤10s regardless of fps."
          },
          "generate_audio": {
            "type": "boolean",
            "default": true,
            "description": "Whether to generate AI audio (ambience, effects, speech) matching the scene."
          },
          "camera_motion": {
            "type": "string",
            "enum": [
              "dolly_in",
              "dolly_out",
              "dolly_left",
              "dolly_right",
              "jib_up",
              "jib_down",
              "static",
              "focus_shift"
            ],
            "description": "Optional camera movement directive applied to the shot."
          }
        },
        "x-order-properties": [
          "model",
          "image",
          "last_image",
          "prompt",
          "duration",
          "resolution",
          "aspect_ratio",
          "fps",
          "generate_audio",
          "camera_motion"
        ]
      },
      "PredictionData": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Unique identifier for the prediction."
          },
          "urls": {
            "type": "object",
            "description": "Object containing related API endpoints."
          },
          "model": {
            "type": "string",
            "description": "Model ID used for the prediction."
          },
          "status": {
            "type": "string",
            "description": "Status: processing, completed, failed, or timeout."
          },
          "outputs": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "URLs to the generated video."
          },
          "created_at": {
            "type": "string",
            "format": "date-time",
            "description": "ISO timestamp of creation."
          },
          "completion_tokens": {
            "type": "integer",
            "description": "Tokens consumed for billing."
          },
          "total_tokens": {
            "type": "integer",
            "description": "Total tokens consumed."
          }
        }
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer"
          },
          "message": {
            "type": "string"
          },
          "data": {
            "$ref": "#/components/schemas/PredictionData"
          }
        }
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  }
}

LLM-Friendly Prompt Template

# ltx/ltx-2.5-pro/image-to-video

> LTX-2.5 Pro image-to-video (Lightricks LTX-2 native API): animate a first-frame image (optionally interpolating to a last frame), up to 4K at 24/48 fps (6–10s, top-quality, with synchronized audio).


## 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**: `ltx/ltx-2.5-pro/image-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: `"ltx/ltx-2.5-pro/image-to-video"`

- **`image`** (`string`, _required_):
  First-frame image: URL, Base64, or asset reference (asset://<ASSET_ID>). The video starts from this image.

- **`last_image`** (`string`, _optional_):
  Optional last-frame image (URL / Base64 / asset://). When set, the clip interpolates from the first frame to this frame.

- **`prompt`** (`string`, _optional_):
  Text prompt describing the desired motion, camera movement and atmosphere. Optional but recommended.
  - Default: `"The scene comes alive with gentle, natural motion and cinematic lighting."`

- **`duration`** (`integer`, _optional_):
  Video length in seconds. Use -1 to let the model choose the duration automatically.
  - Default: `-1`
  - Options: -1, 6, 8, 10

- **`resolution`** (`string`, _optional_):
  Output resolution tier. Combined with aspect_ratio to select the exact frame size (720p→1280x720, 1080p→1920x1080, 1440p→2560x1440, 4k→3840x2160; portrait 9:16 swaps width/height). 1440p and 4k support 6–10s durations only.
  - Default: `"720p"`
  - Options: "720p", "1080p", "1440p", "4k"

- **`aspect_ratio`** (`string`, _optional_):
  Frame orientation: 16:9 landscape or 9:16 portrait.
  - Default: `"16:9"`
  - Options: "16:9", "9:16"

- **`fps`** (`integer`, _optional_):
  Frames per second. 48 fps is available only for durations ≤10s; at 1440p and 4k all durations are ≤10s regardless of fps.
  - Default: `24`
  - Options: 24, 48

- **`generate_audio`** (`boolean`, _optional_):
  Whether to generate AI audio (ambience, effects, speech) matching the scene.
  - Default: `true`

- **`camera_motion`** (`string`, _optional_):
  Optional camera movement directive applied to the shot.
  - Options: "dolly_in", "dolly_out", "dolly_left", "dolly_right", "jib_up", "jib_down", "static", "focus_shift"



**Required Parameters Example**:

```json
{
  "model": "ltx/ltx-2.5-pro/image-to-video",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "ltx/ltx-2.5-pro/image-to-video",
  "image": "",
  "last_image": "",
  "prompt": "The scene comes alive with gentle, natural motion and cinematic lighting.",
  "duration": -1,
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "fps": 24,
  "generate_audio": true,
  "camera_motion": "dolly_in"
}
```


### 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": "ltx/ltx-2.5-pro/image-to-video",
  "image": "",
  "last_image": "",
  "prompt": "The scene comes alive with gentle, natural motion and cinematic lighting.",
  "duration": -1,
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "fps": 24,
  "generate_audio": true,
  "camera_motion": "dolly_in"
}'

# 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/ltx/ltx-2.5-pro/image-to-video)

The spacecraft descended slowly, kicking up dust and sand.

1. Introduction

LTX-2.5 Pro Image-to-Video is served through the native Lightricks LTX-2 API (api.ltx.io). This README covers a single API model identifier:

ltx/ltx-2.5-pro/image-to-video

LTX-2 is Lightricks' second-generation diffusion-transformer video model, generating video up to 4K at cinematic frame rates (24 and 48 fps). This is the LTX-2.5 Pro tier: it generates 6–10 second clips and supports synchronized audio generation. Requests are processed asynchronously (submit + poll) and every generation is delivered as a finished MP4 hosted on AtlasCloud storage.

2. Key Features

Image-to-Video: Animate a first-frame image; optionally set last_image to interpolate precisely from the first frame to a chosen last frame.
Native Audio-Video: Produces a matched soundtrack (ambience, effects, speech) aligned to the visuals; set generate_audio: false for a silent clip.
Up to 4K, 24/48 fps: Renders at 720p / 1080p / 1440p / 4K in landscape (16:9) or portrait (9:16).
Top-Quality Rendering: Prioritizes visual fidelity, motion coherence and prompt adherence, with 6–10s single-pass duration.
Camera Control: Optional camera_motion directive (dolly, jib, focus shift, static).

3. Support Matrix

Resolution	Landscape	Portrait	FPS	Duration (s)
720p	1280x720	720x1280	24, 48	6, 8, 10
1080p	1920x1080	1080x1920	24, 48	6, 8, 10
1440p	2560x1440	1440x2560	24, 48	6, 8, 10
4K	3840x2160	2160x3840	24, 48	6, 8, 10

duration: -1 (automatic) is available on LTX-2.5 tiers only. Audio generation is supported.

4. Parameters

The request body matches this model's schema exactly:

Parameter	Type	Required	Default	Notes
`image`	string	Yes		First-frame image: URL, Base64, or asset reference (asset://<ASSET_ID>). The video starts from this image.
`last_image`	string	No		Optional last-frame image (URL / Base64 / asset://). When set, the clip interpolates from the first frame to this frame.
`prompt`	string	No	`The scene comes alive with gentle, natural motion and cinematic lighting.`	Text prompt describing the desired motion, camera movement and atmosphere. Optional but recommended.
`duration`	integer	No	`-1`	One of: `-1`, `6`, `8`, `10`. Video length in seconds. Use -1 to let the model choose the duration automatically.
`resolution`	string	No	`720p`	One of: `720p`, `1080p`, `1440p`, `4k`. Output resolution tier. Combined with aspect_ratio to select the exact frame size (720p→1280x720, 1080p→1920x1080, 1440p→2560x1440, 4k→3840x2160; portrait 9:16 swaps width/height). 1440p and 4k support 6–10s durations only.
`aspect_ratio`	string	No	`16:9`	One of: `16:9`, `9:16`. Frame orientation: 16:9 landscape or 9:16 portrait.
`fps`	integer	No	`24`	One of: `24`, `48`. Frames per second. 48 fps is available only for durations ≤10s; at 1440p and 4k all durations are ≤10s regardless of fps.
`generate_audio`	boolean	No	`true`	Whether to generate AI audio (ambience, effects, speech) matching the scene.
`camera_motion`	string	No		One of: `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `focus_shift`. Optional camera movement directive applied to the shot.

5. Intended Use & Applications

Product & Brand Video: Animate a product still into a polished, on-brand showcase.
Photo Animation: Bring a single image to life with natural, controllable motion.
First/Last-Frame Control: Pin a start and end frame (image + last_image) for precise transitions.
Social & Vertical Content: Native 9:16 portrait output for short-form platforms.

LTX 2.5 Pro Image-to-Video API by LTX

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

1. Introduction

2. Key Features

3. Support Matrix

4. Parameters

5. Intended Use & Applications

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One API for All Media AI.

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