gen4_turbo
Overview
This release brings faster, more scalable AI video generation with higher visual quality. This version allows for 10-second video generation. Gen4 Turbo delivers realistic motion, coherent subjects and styles across frames, and high prompt fidelity, supported by strong world modeling.
How to Make a Call
API Schemas
Video Generation
You can generate a video using this API. In the basic setup, you need only an image URL and the aspect ratio of the desired result. The model can detect and use the aspect ratio from the input image, but for correct operation in this case, the image's width-to-height ratio must be between 0.5 and 2.
A non-empty string up to 1000 UTF-16 code points in length. This should describe in detail what should appear in the output.
A HTTPS URL or data URI containing an encoded image to be used as the first frame of the generated video.
The number of seconds of duration for the output video
The aspect ratio of the generated video
16:9Possible values: If unspecified, a random number is chosen. Varying the seed integer is a way to get different results for the same other request parameters. Using the same seed integer for an identical request will produce similar results
POST /v2/generate/video/runway/generation HTTP/1.1
Host: api.aimlapi.com
Authorization: Bearer <YOUR_AIMLAPI_KEY>
Content-Type: application/json
Accept: */*
Content-Length: 116
{
"model": "runway/gen4_turbo",
"prompt": "text",
"image_url": "https://example.com",
"duration": 5,
"ratio": "16:9",
"seed": 1
}{
"id": "a12b3456-7c89-0de1-23f4-g567d584f98d",
"status": "queued"
}Retrieve the generated video from the server
After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its id, obtained from the endpoint described above.
If the video generation task status is complete, the response will include the final result — with the generated video URL and additional metadata.
Generation ID
a12b3456-7c89-0de1-23f4-g567d584f98dGET /v2/generate/video/runway/generation HTTP/1.1
Host: api.aimlapi.com
Authorization: Bearer <YOUR_AIMLAPI_KEY>
Accept: */*
{
"id": "a12b3456-7c89-0de1-23f4-g567d584f98d",
"status": "queued",
"video": [
"https://example.com"
]
}Full Example: Generating and Retrieving the Video From the Server
Let’s take a beautiful but somewhat barren mountain landscape:
Then ask Gen4 Turbo to populate it with an epic reptilian creature using the following prompt:
"A menacing evil dragon appears in a distance above the tallest mountain, then rushes toward the camera with its jaws open, revealing massive fangs. We see it's coming"
We combine both methods above in one program: first it sends a video generation request to the server, then it checks for results every 10 seconds.
Don’t forget to replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key from your API Key management page — in both places in the code!
import time
import requests
# Creating and sending a video generation task to the server (returns a generation ID)
def generate_video():
url = "https://api.aimlapi.com/v2/generate/video/runway/generation"
payload = {
"model": "runway/gen4_turbo",
"prompt": "A menacing evil dragon appears in a distance above the tallest mountain, then rushes toward the camera with its jaws open, revealing massive fangs. We see it's coming",
"ratio": "16:9",
"image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/6/68/Liebener_Spitze_SW.JPG/1280px-Liebener_Spitze_SW.JPG",
}
# Insert your AI/ML API key instead of <YOUR_AIMLAPI_KEY>:
headers = {"Authorization": "Bearer <YOUR_AIMLAPI_KEY>", "Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
if response.status_code >= 400:
print(f"Error: {response.status_code} - {response.text}")
else:
response_data = response.json()
print("Generation:", response_data)
return response_data
# Requesting the result of the generation task from the server using the generation_id:
def retrieve_video(gen_id):
url = "https://api.aimlapi.com/v2/generate/video/runway/generation"
params = {
"generation_id": gen_id,
}
# Insert your AI/ML API key instead of <YOUR_AIMLAPI_KEY>:
headers = {"Authorization": "Bearer <YOUR_AIMLAPI_KEY>", "Content-Type": "application/json"}
response = requests.get(url, params=params, headers=headers)
return response.json()
# This is the main function of the program. From here, we sequentially call the video generation and then repeatedly request the result from the server every 10 seconds:
def main():
generation_response = generate_video()
gen_id = generation_response.get("id")
if gen_id:
start_time = time.time()
timeout = 600
while time.time() - start_time < timeout:
response_data = retrieve_video(gen_id)
if response_data is None:
print("Error: No response from API")
break
status = response_data.get("status")
if status == "generating" or status == "queued" or status == "waiting":
print("Still waiting... Checking again in 10 seconds.")
time.sleep(10)
else:
print("Generation complete:/n", response_data)
return response_data
print("Timeout reached. Stopping.")
return None
if __name__ == "__main__":
main()
The following video was generated by running the code example above. Processing time: ~65 sec. You may also check out the original video in 1280×720 resolution.
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