ltx-2.3-quality/text-to-video

Texto a Video

Ltx 2.3 Quality Text-to-Video API

ltx-2.3-quality/text-to-video

Text-to-video

Generate high-quality video with audio from images using LTX-2.3

Entrada

Prompt *

Num frames

Resolución

Generar Audio

Semilla

Salida

Inactivo

Los videos generados se mostrarán aquí

Configura los parámetros y haz clic en ejecutar para comenzar a generar

Cada ejecución costará $0.002. Con $10 puedes ejecutar aproximadamente 5000 veces.

Puedes continuar con:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parámetros

Ejemplo de código
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-2.3-quality/text-to-video",  # Required. model name
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. Text description of the video to generate
    "num_frames": 121,  # Number of frames to generate. (min: 25, max: 257)
    "resolution": "landscape_16_9",  # Output video resolution preset. options: square_hd | square | portrait_3_4 | portrait_9_16 | landscape_4_3 | landscape_16_9
    "generate_audio": False,  # Whether to generate accompanying audio for the video
    "seed": 0,  # Random seed for reproducibility. (min: 0)
}

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()

Instalar

Instala el paquete de dependencias necesario.

pip install requests

Autenticación

Todas las solicitudes de API requieren autenticación mediante una clave de API. Puedes obtener tu clave de API desde el panel de Atlas Cloud.

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

Encabezados HTTP

import os

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

Mantén tu clave de API segura

Nunca expongas tu clave de API en código del lado del cliente ni en repositorios públicos. Usa variables de entorno o un proxy de backend en su lugar.

Enviar una solicitud

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())

Enviar una solicitud

Envía una solicitud de generación asíncrona. La API devuelve un ID de predicción que puedes usar para verificar el estado y obtener el resultado.

POST/api/v1/model/generateVideo

Cuerpo de la solicitud

import requests

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

data = {
    "model": "ltx-2.3-quality/text-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']}")

Respuesta

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

Verificar estado

Consulta el endpoint de predicción para verificar el estado actual de tu solicitud.

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

Ejemplo de polling

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)

Valores de estado

processingLa solicitud aún se está procesando.

completedLa generación está completa. Las salidas están disponibles.

succeededLa generación fue exitosa. Las salidas están disponibles.

failedLa generación falló. Verifica el campo de error.

Respuesta completada

{
  "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"
  }
}

Subir archivos

Sube archivos al almacenamiento de Atlas Cloud y obtén una URL que puedes usar en tus solicitudes de API. Usa multipart/form-data para subir.

POST/api/v1/model/uploadMedia

Ejemplo de carga

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}")

Respuesta

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

Schema de entrada

Los siguientes parámetros se aceptan en el cuerpo de la solicitud.

Total: 6Obligatorio: 2Opcional: 4

modelstringrequired

model name

Default: "ltx-2.3-quality/text-to-video"

promptstringrequired

Text description of the video to generate. Maximum 2,000 characters.

num_framesinteger

Number of frames to generate. Must be a multiple of 8 plus 1 (e.g. 25, 41, 81, 121, 161, 201, 241, 257).

Default: 121Min: 25Max: 257

resolutionstring

Output video resolution preset.

Default: "landscape_16_9"

square_hdsquareportrait_3_4portrait_9_16landscape_4_3landscape_16_9

generate_audioboolean

Whether to generate accompanying audio for the video.

Default: false

seedinteger

Random seed for reproducibility. Use the same seed and prompt to reproduce results.

Min: 0

Ejemplo de cuerpo de solicitud

{
  "model": "ltx-2.3-quality/text-to-video",
  "prompt": "A beautiful landscape",
  "num_frames": 121,
  "resolution": "landscape_16_9",
  "generate_audio": false
}

Schema de salida

La API devuelve una respuesta de predicción con las URL de salida generadas.

modelstring

model name

Default: "ltx-2.3-quality/text-to-video"

created_atstring

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

idstring

Unique identifier for the prediction.

outputsarray

Array of URLs to the generated videos. Null when status is not completed.

statusstring

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

Ejemplo de respuesta

{
  "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 integra más de 400 modelos de IA directamente en tu asistente de codificación con IA. Un solo comando para instalar y luego usa lenguaje natural para generar imágenes, videos y chatear con LLM.

Clientes compatibles

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clientes compatibles

Instalar

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurar clave de API

Obtén tu clave de API desde el panel de Atlas Cloud y configúrala como variable de entorno.

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

Funcionalidades

Una vez instalado, puedes usar lenguaje natural en tu asistente de IA para acceder a todos los modelos de Atlas Cloud.

Generación de imágenesGenera imágenes con modelos como Nano Banana 2, Z-Image y más.

Creación de videosCrea videos a partir de texto o imágenes con Kling, Vidu, Veo, etc.

Chat con LLMChatea con Qwen, DeepSeek y otros modelos de lenguaje de gran escala.

Carga de mediosSube archivos locales para flujos de trabajo de edición de imágenes e imagen a video.

Más información

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server conecta tu IDE con más de 400 modelos de IA a través del Model Context Protocol. Funciona con cualquier cliente compatible con MCP.

Clientes compatibles

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clientes compatibles

Instalar

npx -y atlascloud-mcp

Configuración

Agrega la siguiente configuración al archivo de configuración de MCP de tu IDE.

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

Herramientas disponibles

atlas_generate_imageGenera imágenes a partir de indicaciones de texto.

atlas_generate_videoCrea videos a partir de texto o imágenes.

atlas_chatChatea con modelos de lenguaje de gran escala.

atlas_list_modelsExplora más de 400 modelos de IA disponibles.

atlas_quick_generateCreación de contenido en un solo paso con selección automática de modelo.

atlas_upload_mediaSube archivos locales para flujos de trabajo de API.

Más información

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        },
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        },
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "schema": {
              "type": "string",
              "description": "Request ID"
            },
            "required": true
          }
        ]
      },
      "x-api-name": "model_result"
    }
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "ltx-2.3-quality/text-to-video"
          },
          "prompt": {
            "description": "Text description of the video to generate. Maximum 2,000 characters.",
            "type": "string",
            "minLength": 1,
            "maxLength": 2000
          },
          "num_frames": {
            "description": "Number of frames to generate. Must be a multiple of 8 plus 1 (e.g. 25, 41, 81, 121, 161, 201, 241, 257).",
            "type": "integer",
            "default": 121,
            "minimum": 25,
            "maximum": 257,
            "x-ui-component": "slider"
          },
          "resolution": {
            "description": "Output video resolution preset.",
            "type": "string",
            "default": "landscape_16_9",
            "enum": [
              "square_hd",
              "square",
              "portrait_3_4",
              "portrait_9_16",
              "landscape_4_3",
              "landscape_16_9"
            ],
            "x-ui-component": "select",
            "x-enum-labels": {
              "square_hd": "Square HD (1024×1024)",
              "square": "Square (512×512)",
              "portrait_3_4": "Portrait 3:4",
              "portrait_9_16": "Portrait 9:16",
              "landscape_4_3": "Landscape 4:3",
              "landscape_16_9": "Landscape 16:9"
            },
            "x-enum-mapping": {
              "portrait_3_4": "portrait_4_3"
            }
          },
          "generate_audio": {
            "description": "Whether to generate accompanying audio for the video.",
            "type": "boolean",
            "default": false,
            "x-ui-component": "switch"
          },
          "seed": {
            "description": "Random seed for reproducibility. Use the same seed and prompt to reproduce results.",
            "type": "integer",
            "minimum": 0
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "num_frames",
          "resolution",
          "generate_audio",
          "seed"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "ltx-2.3-quality/text-to-video"
          },
          "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.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated videos. Null when status is not completed.",
            "items": {
              "type": "string"
            },
            "nullable": true,
            "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"
      }
    }
  }
}

Plantilla de Prompt Compatible con LLM

# ltx-2.3-quality/text-to-video

> Generate high-quality video with audio from images using LTX-2.3


## 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-2.3-quality/text-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-2.3-quality/text-to-video"`

- **`prompt`** (`string`, _required_):
  Text description of the video to generate. Maximum 2,000 characters.

- **`num_frames`** (`integer`, _optional_):
  Number of frames to generate. Must be a multiple of 8 plus 1 (e.g. 25, 41, 81, 121, 161, 201, 241, 257).
  - Default: `121`
  - Min: 25
  - Max: 257

- **`resolution`** (`string`, _optional_):
  Output video resolution preset.
  - Default: `"landscape_16_9"`
  - Options: "square_hd", "square", "portrait_3_4", "portrait_9_16", "landscape_4_3", "landscape_16_9"

- **`generate_audio`** (`boolean`, _optional_):
  Whether to generate accompanying audio for the video.
  - Default: `false`

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility. Use the same seed and prompt to reproduce results.
  - Min: 0



**Required Parameters Example**:

```json
{
  "model": "ltx-2.3-quality/text-to-video",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "ltx-2.3-quality/text-to-video",
  "prompt": "",
  "num_frames": 121,
  "resolution": "landscape_16_9",
  "generate_audio": false,
  "seed": 0
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"ltx-2.3-quality/text-to-video"`

- **`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.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated videos. Null 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
{
  "model": "ltx-2.3-quality/text-to-video",
  "created_at": "",
  "id": "",
  "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": "ltx-2.3-quality/text-to-video",
  "prompt": "",
  "num_frames": 121,
  "resolution": "landscape_16_9",
  "generate_audio": false,
  "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/ltx-2.3-quality/text-to-video)

A lone figure wearing a flowing desert cloak walks slowly across endless golden dunes beneath a colossal blazing sun. Powerful winds sweep across the landscape, sending fine sand spiraling into the air. The camera begins with an ultra-wide aerial shot, emphasizing the immense scale of the desert, then slowly descends into a cinematic tracking shot behind the traveler. Heat haze distorts the distant horizon while colossal dunes stretch endlessly into the distance. Monumental atmosphere, slow cinematic pacing, dramatic volumetric lighting, Denis Villeneuve style, IMAX scale, ultra realistic, masterpiece, 8K.

Cargando...

LTX 2.3 Quality Text-to-Video

LTX 2.3 Quality is a high-quality text-to-video model that generates cinematic videos from natural language prompts, with optional audio generation. Built on the LTX-Video architecture, it delivers smooth motion, strong prompt adherence, and flexible resolution presets.

🌟 Key Features

🎬 Cinematic Video Generation

Generates high-fidelity videos from descriptive text prompts with precise motion control, realistic lighting, and consistent style.

🔊 Optional Audio Generation

Optionally produce synchronized audio alongside the video in a single request — no separate audio pipeline required.

📐 Multiple Resolution Presets

Six aspect ratio presets cover every common layout, from square HD to widescreen landscape and vertical portrait formats.

🔁 Reproducible Results

Pin a seed value to reproduce or iterate on a specific generation, enabling systematic prompt and parameter refinement.

⚙️ Parameters

Parameter	Required	Description
`prompt`	✅	Text description of the video to generate. Maximum 2,000 characters.
`num_frames`	❌	Number of frames to generate (default: `121`). Must be a multiple of 8 plus 1.
`resolution`	❌	Output video resolution preset (default: `landscape_16_9`). See options below.
`generate_audio`	❌	Whether to generate accompanying audio (default: `false`).
`seed`	❌	Random seed for reproducibility. Omit for random results.

Resolution Options

Value	Description
`square_hd`	Square HD (1024×1024)
`square`	Square (512×512)
`portrait_3_4`	Portrait 3:4
`portrait_9_16`	Portrait 9:16
`landscape_4_3`	Landscape 4:3
`landscape_16_9`	Landscape 16:9

Frame Count Guide

`num_frames`	Approximate Duration (24fps)
25	~1 second
81	~3.4 seconds
121	~5 seconds
161	~6.7 seconds
257	~10.7 seconds

💲 Pricing

Billed at $0.0024075 per megapixel of generated video data (width × height × num_frames), rounded upward.

Example: landscape_16_9 (1280×720) at 121 frames ≈ 112 MP ≈ $0.27

💡 Prompt Tips

A drone shot sweeping over a misty mountain valley at dawn, golden light breaking through the clouds, cinematic slow motion, ultra-detailed.

Describe motion explicitly: "slowly panning left", "camera zooms in", "waves crashing".
Include lighting and atmosphere cues: "golden hour", "neon-lit rain", "overcast fog".
Reference a visual style: "cinematic 4K", "anime style", "photorealistic".
Use seed when iterating on prompt wording to isolate the effect of each change.

🎯 Use Cases

Creative Storytelling — Generate cinematic sequences and short films from script descriptions.
Marketing & Advertising — Produce dynamic video assets for campaigns without filming.
Social Media Content — Create engaging short-form video content at any aspect ratio.
Prototyping & Storyboarding — Rapidly visualize scene concepts before full production.
Music Visualization — Generate visuals to accompany audio tracks with generate_audio: false.

📝 Notes

prompt is the only required field.
num_frames must satisfy: (num_frames - 1) % 8 == 0 (e.g. 25, 33, 41, 81, 121, 161, 257).
Task status values: created, processing, completed, failed.
Generated video URLs are returned in outputs once status is completed.

Ltx 2.3 Quality Text-to-Video API

Entrada

Salida

Parámetros

Ejemplo de código

Instalar

Autenticación

Encabezados HTTP

Enviar una solicitud

Enviar una solicitud

Cuerpo de la solicitud

Respuesta

Verificar estado

Ejemplo de polling

Valores de estado

Respuesta completada

Subir archivos

Ejemplo de carga

Respuesta

Schema de entrada

Ejemplo de cuerpo de solicitud

Schema de salida

Ejemplo de respuesta

Atlas Cloud Skills

Clientes compatibles

Instalar

Configurar clave de API

Funcionalidades

MCP Server

Clientes compatibles

Instalar

Configuración

Herramientas disponibles

API Schema

Plantilla de Prompt Compatible con LLM

LTX 2.3 Quality Text-to-Video

🌟 Key Features

🎬 Cinematic Video Generation

🔊 Optional Audio Generation

📐 Multiple Resolution Presets

🔁 Reproducible Results

⚙️ Parameters

Resolution Options

Frame Count Guide

💲 Pricing

💡 Prompt Tips

🎯 Use Cases

📝 Notes

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HappyHorse-1.1 Image-to-video

HappyHorse-1.1 Reference-to-video

Gemini Omni Flash Reference-to-Video

Gemini Omni Flash Image-to-Video

Gemini Omni Flash Video Edit

Gemini Omni Flash Text-to-Video

Gemini Omni Flash Reference-to-Video Developer

Avatar Omni Human 1.5

Kling V3.0 Turbo Text-to-Video

Kling V3.0 Turbo Image-to-Video

Una sola API para toda la IA multimedia.

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Entrada

Salida

Parámetros

Ejemplo de código

Instalar

Autenticación

Encabezados HTTP

Enviar una solicitud

Enviar una solicitud

Cuerpo de la solicitud

Respuesta

Verificar estado

Ejemplo de polling