Name: Luma Dream Machine Ray-2 API
Brand: Luma AI

Overview

What is Luma Dream Machine Ray-2 API?

Luma Ray-2 generates high-quality videos from text prompts or images with advanced AI techniques.

Technical Specifications
- Supported inputs: Image, Text
- Output: Video

Performance Benchmarks
[embed]

Luma Dream Machine Ray-2 API Pricing
- Pricing on request

Where to Use Luma Dream Machine Ray-2

Short-form video generation
Create clips for social, ads, and product demos from text or image prompts.

Previsualization and storyboards
Rapidly prototype motion concepts before committing to production.

Use cases

Product ideation and early concept visualization are documented use cases for Ray2, including rapidly creating video mockups of product ideas to speed decision-making and iteration.

Product promotion and brand storytelling are also listed uses, with Ray2 described as suitable for generating video clip content to showcase products or services.

Previsualization for film and entertainment workflows is another documented use case, including creating initial versions of special effects sequences, realistic green-screen backgrounds, and concept footage.

How to use Luma Dream Machine Ray-2 API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to luma/ray-2.

import requests, time

headers = {"Authorization": "Bearer " + AIMLAPI_KEY}
job = requests.post(
    "https://api.aimlapi.com/v2/video/generations",
    headers=headers,
    json={
      "model": "luma/ray-2",
      "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": "luma/ray-2",
    "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":"luma/ray-2","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.