ltx-2.3-quality/text-to-video

text-till-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

Inmatning

Prompt *

Num frames

Upplösning

Generera Ljud

Seed

Utmatning

Vilande

Dina genererade videor visas här

Konfigurera parametrar och klicka på Kör för att börja generera

Varje körning kostar $0.002. För $10 kan du köra cirka 5000 gånger.

Du kan fortsätta med:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parametrar

Kodexempel
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()

Installera

Installera det nödvändiga paketet för ditt programmeringsspråk.

pip install requests

Autentisering

Alla API-förfrågningar kräver autentisering via en API key. Du kan hämta din API key från Atlas Cloud-instrumentpanelen.

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

HTTP-huvuden

import os

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

Håll din API key säker

Exponera aldrig din API key i klientkod eller publika arkiv. Använd miljövariabler eller en backend-proxy istället.

Skicka en förfrågan

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())

Skicka en förfrågan

Skicka en asynkron genereringsförfrågan. API:et returnerar ett prediction ID som du kan använda för att kontrollera statusen och hämta resultatet.

POST/api/v1/model/generateVideo

Förfrågningsinnehåll

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']}")

Svar

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

Kontrollera status

Polla prediction-endpointen för att kontrollera den aktuella statusen för din förfrågan.

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

Polling-exempel

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)

Statusvärden

processingFörfrågan bearbetas fortfarande.

completedGenereringen är klar. Utdata är tillgängliga.

succeededGenereringen lyckades. Utdata är tillgängliga.

failedGenereringen misslyckades. Kontrollera error-fältet.

Slutfört svar

{
  "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"
  }
}

Ladda upp filer

Ladda upp filer till Atlas Cloud-lagring och få en URL som du kan använda i dina API-förfrågningar. Använd multipart/form-data för uppladdning.

POST/api/v1/model/uploadMedia

Uppladdningsexempel

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}")

Svar

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

Input Schema

Följande parametrar accepteras i förfrågningsinnehållet.

Totalt: 6Obligatorisk: 2Valfri: 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

Exempel på förfrågningsinnehåll

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

Output Schema

API:et returnerar ett prediction-svar med de genererade utdata-URL:erna.

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.

Exempelsvar

{
  "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 integrerar 400+ AI-modeller direkt i din AI-kodassistent. Ett kommando för att installera, sedan använd naturligt språk för att generera bilder, videor och chatta med LLM.

Stödda klienter

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ stödda klienter

Installera

npx skills add AtlasCloudAI/atlas-cloud-skills

Konfigurera API Key

Hämta din API key från Atlas Cloud-instrumentpanelen och ställ in den som en miljövariabel.

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

Funktioner

När det är installerat kan du använda naturligt språk i din AI-assistent för att komma åt alla Atlas Cloud-modeller.

BildgenereringGenerera bilder med modeller som Nano Banana 2, Z-Image och fler.

VideoskapandeSkapa videor från text eller bilder med Kling, Vidu, Veo m.fl.

LLM-chattChatta med Qwen, DeepSeek och andra stora språkmodeller.

MediauppladdningLadda upp lokala filer för bildredigering och bild-till-video-arbetsflöden.

Läs mer

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server ansluter din IDE med 400+ AI-modeller via Model Context Protocol. Fungerar med alla MCP-kompatibla klienter.

Stödda klienter

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ stödda klienter

Installera

npx -y atlascloud-mcp

Konfiguration

Lägg till följande konfiguration i din IDE:s MCP-inställningsfil.

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

Tillgängliga verktyg

atlas_generate_imageGenerera bilder från textpromptar.

atlas_generate_videoSkapa videor från text eller bilder.

atlas_chatChatta med stora språkmodeller.

atlas_list_modelsBläddra bland 400+ tillgängliga AI-modeller.

atlas_quick_generateInnehållsskapande i ett steg med automatiskt modellval.

atlas_upload_mediaLadda upp lokala filer för API-arbetsflöden.

Läs mer

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"
      }
    }
  }
}

LLM-vänlig Promptmall

# 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.

Laddar...

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

Inmatning

Utmatning

Parametrar

Kodexempel

Installera

Autentisering

HTTP-huvuden

Skicka en förfrågan

Skicka en förfrågan

Förfrågningsinnehåll

Svar

Kontrollera status

Polling-exempel

Statusvärden

Slutfört svar

Ladda upp filer

Uppladdningsexempel

Svar

Input Schema

Exempel på förfrågningsinnehåll

Output Schema

Exempelsvar

Atlas Cloud Skills

Stödda klienter

Installera

Konfigurera API Key

Funktioner

MCP Server

Stödda klienter

Installera

Konfiguration

Tillgängliga verktyg

API Schema

LLM-vänlig Promptmall

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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Sync.so Lipsync v3

VEED Lipsync

Seedance 2.0 Mini Reference-to-Video

Seedance 2.0 Mini Image-to-Video

Seedance 2.0 Mini Text-to-Video

HappyHorse-1.1 Text-to-video

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

Ett API för all media-AI.

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Inmatning

Utmatning

Parametrar

Kodexempel

Installera

Autentisering

HTTP-huvuden

Skicka en förfrågan

Skicka en förfrågan

Förfrågningsinnehåll

Svar

Kontrollera status

Polling-exempel