Name: Veo 2 Text-to-Video API
Brand: Google

Overview

Veo 2 Text-to-Video Description

Overview:

Veo2 is Google’s cutting-edge AI model designed to generate highly realistic and cinematic video content from textual prompts or a combination of text and images. Leveraging advanced machine learning techniques, Veo2 excels in creating videos with natural motion, realistic physics, and professional-grade visual fidelity.

Key Features:

Text-to-Video (T2V): Converts descriptive text into dynamic video content.
High Resolution Support: Generates videos up to 4K resolution for professional-grade outputs.
Multimodal Input Encoding: Integrates text and image inputs seamlessly for creative flexibility.

Intended Use:

Veo2 is ideal for applications such as:

Marketing campaigns requiring visually engaging content.
Filmmaking and storyboarding with dynamic visuals.
Educational videos for interactive learning experiences.
Content creation for social media platforms

Language Support:

Veo2 supports multilingual text prompts, including English and other major languages.

Technical Details

Architecture:

Veo2 employs a hybrid architecture combining:

UL2 Encoder: Processes textual prompts into latent embeddings for video generation.
Latent Diffusion Model: Converts the embedded representations into compressed video frames efficiently while maintaining high visual fidelity.

Training Data:

The model was trained on a massive dataset derived from YouTube’s video library and other proprietary sources, ensuring diversity in motion patterns, visual styles, and real-world physics.

Diversity and Bias:

Google has implemented safeguards to minimize biases in generated content by diversifying the training data across cultures and contexts. However, some biases may persist due to the inherent limitations of the dataset.

Performance Metrics:

Usage

Code Samples

The model is available on the AI/ML API platform as "Veo2 Text-to-Video" .

Params:

prompt [str]: The text prompt describing how the image should be animated
aspect_ratio [9:16, 16:9]: Aspect ratio of the generated video
duration [5, 6, 7, 8]: The duration of the generated video in seconds

To get the generated video

API Documentation

Detailed API Documentation is available here.

Ethical Guidelines

Google has integrated safety filters into Veo2 to prevent the generation of harmful or inappropriate content. Developers are encouraged to use the model responsibly in alignment with ethical guidelines for AI-generated media.

Licensing

Veo2 is currently available through Google Labs’ VideoFX platform under a commercial license

‍

Get Veo2 Text-to-Video API here.

Use cases

Social media content creation (Instagram, TikTok, LinkedIn videos)
Marketing and advertising campaign content
Internal presentations and explainer video generation
Creative projects and artistic video production
Rapid prototyping of video concepts and visual storytelling
E-commerce and product videos showcasing dynamic visuals

How to use Veo 2 Text-to-Video API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to google/veo2.

import requests, time

headers = {"Authorization": "Bearer " + AIMLAPI_KEY}
job = requests.post(
    "https://api.aimlapi.com/v2/video/generations",
    headers=headers,
    json={
      "model": "google/veo2",
      "prompt": "A serene timelapse of clouds over a mountain range"
    },
).json()
gid = job["id"]

while True:
    res = requests.get(f"https://api.aimlapi.com/v2/video/generations?generation_id={gid}", headers=headers).json()
    if res.get("status") in ("completed", "error"):
        break
    time.sleep(5)
print(res["video"]["url"])

const headers = {
  Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
  "Content-Type": "application/json",
};
const job = await (await fetch("https://api.aimlapi.com/v2/video/generations", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "model": "google/veo2",
    "prompt": "A serene timelapse of clouds over a mountain range"
  }),
})).json();

let res;
do {
  await new Promise((r) => setTimeout(r, 5000));
  res = await (await fetch(`https://api.aimlapi.com/v2/video/generations?generation_id=${job.id}`, { headers })).json();
} while (!["completed", "error"].includes(res.status));
console.log(res.video.url);

# submit the generation — the response contains the job "id"
curl -X POST https://api.aimlapi.com/v2/video/generations \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/veo2","prompt":"A serene timelapse of clouds over a mountain range"}'

# then poll until status is "completed" — video.url holds the result
curl "https://api.aimlapi.com/v2/video/generations?generation_id={id}" -H "Authorization: Bearer $AIMLAPI_KEY"

OpenAI-compatible — swap the base URL and it works with your existing SDK.