A fast version of the hailuo-2.3 model. Delivers more expressive motion and produces visuals that are both more realistic and stable and introduces major improvements in the depiction of physical actions, stylization, and subtle character expressions, while also further refining its responsiveness to motion commands.
Setup your API Key
If you don’t have an API key for the AI/ML API yet, feel free to use our Quickstart guide.
How to Make a Call
Step-by-Step Instructions
Generating a video using this model involves sequentially calling two endpoints:
The first one is for creating and sending a video generation task to the server (returns a generation ID).
The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.
Below, you can find both corresponding API schemas.
API Schemas
Create a video generation task and send it to the server
post
Body
modelstring · enumRequiredPossible values:
promptstring · max: 2000Required
The text description of the scene, subject, or action to generate in the video.
image_urlstring · uriRequired
A direct link to an online image or a Base64-encoded local image that will serve as the first frame for the video.
Image specifications:
format must be JPG, JPEG, or PNG;
aspect ratio should be greater than 2:5 and less than 5:2;
the shorter side must exceed 300 pixels;
file size must not exceed 20MB.
resolutionstring · enumOptional
The dimensions of the video display. 1080p corresponds to 1920 x 1080 pixels, 768p corresponds to 1366 x 768 pixels.
Default: 768PPossible values:
durationinteger · enumOptional
The length of the output video in seconds.
Possible values:
enhance_promptbooleanOptional
If True, the incoming prompt will be automatically optimized to improve generation quality when needed. For more precise control, set it to False — the model will then follow the instructions more strictly.
Default: true
Responses
200Success
application/json
idstringRequired
The ID of the generated video.
Example: 60ac7c34-3224-4b14-8e7d-0aa0db708325
statusstring · enumRequired
The current status of the generation task.
Example: completedPossible values:
post
/v2/video/generations
200Success
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 completed, the response will include the final result — with the generated video URL and additional metadata.
import requests
import time
# Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
api_key = "<YOUR_AIMLAPI_KEY>"
base_url = "https://api.aimlapi.com/v2"
# Creating and sending a video generation task to the server
def generate_video():
url = f"{base_url}/video/generations"
headers = {
"Authorization": f"Bearer {api_key}",
}
data = {
"model": "minimax/hailuo-2.3-fast",
"prompt": "Mona Lisa puts on glasses with her hands.",
"image_url": "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/mona_lisa_extended.jpg",
"duration": "5",
}
response = requests.post(url, json=data, headers=headers)
if response.status_code >= 400:
print(f"Error: {response.status_code} - {response.text}")
else:
response_data = response.json()
return response_data
# Requesting the result of the task from the server using the generation_id
def get_video(gen_id):
url = f"{base_url}/video/generations"
params = {
"generation_id": gen_id,
}
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
response = requests.get(url, params=params, headers=headers)
return response.json()
def main():
# Running video generation and getting a task id
gen_response = generate_video()
print(gen_response)
gen_id = gen_response.get("generation_id")
print("Generation ID: ", gen_id)
# Try to retrieve the video from the server every 15 sec
if gen_id:
start_time = time.time()
timeout = 1000
while time.time() - start_time < timeout:
response_data = get_video(gen_id)
if response_data is None:
print("Error: No response from API")
break
status = response_data.get("status")
if status in ["waiting", "queued", "generating"]:
print(f"Status: {status}. Checking again in 15 seconds.")
time.sleep(15)
else:
print("Processing complete:\n", response_data)
return response_data
print("Timeout reached. Stopping.")
return None
if __name__ == "__main__":
main()
const https = require("https");
const { URL } = require("url");
// Replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key
const apiKey = "<YOUR_AIMLAPI_KEY>";
const baseUrl = "https://api.aimlapi.com/v2";
// Creating and sending a video generation task to the server
function generateVideo(callback) {
const data = JSON.stringify({
model: "minimax/hailuo-2.3-fast",
prompt: "Mona Lisa puts on glasses with her hands.",
image_url: "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/mona_lisa_extended.jpg",
duration: "5",
});
const url = new URL(`${baseUrl}/video/generations`);
const options = {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
"Content-Length": Buffer.byteLength(data),
},
};
const req = https.request(url, options, (res) => {
let body = "";
res.on("data", (chunk) => body += chunk);
res.on("end", () => {
if (res.statusCode >= 400) {
console.error(`Error: ${res.statusCode} - ${body}`);
callback(null);
} else {
const parsed = JSON.parse(body);
callback(parsed);
}
});
});
req.on("error", (err) => console.error("Request error:", err));
req.write(data);
req.end();
}
// Requesting the result of the task from the server using the generation_id
function getVideo(genId, callback) {
const url = new URL(`${baseUrl}/video/generations`);
url.searchParams.append("generation_id", genId);
const options = {
method: "GET",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
};
const req = https.request(url, options, (res) => {
let body = "";
res.on("data", (chunk) => body += chunk);
res.on("end", () => {
const parsed = JSON.parse(body);
callback(parsed);
});
});
req.on("error", (err) => console.error("Request error:", err));
req.end();
}
// Initiates video generation and checks the status every 15 seconds until completion or timeout
function main() {
generateVideo((genResponse) => {
if (!genResponse || !genResponse.id) {
console.error("No generation ID received.");
return;
}
const genId = genResponse.id;
console.log("Generation ID:", genId);
const timeout = 1000 * 1000; // 1000 sec
const interval = 15 * 1000; // 15 sec
const startTime = Date.now();
const checkStatus = () => {
if (Date.now() - startTime >= timeout) {
console.log("Timeout reached. Stopping.");
return;
}
getVideo(genId, (responseData) => {
if (!responseData) {
console.error("Error: No response from API");
return;
}
const status = responseData.status;
if (["waiting", "queued", "generating"].includes(status)) {
console.log(`Status: ${status}. Checking again in 15 seconds.`);
setTimeout(checkStatus, interval);
} else {
console.log("Processing complete:\n", responseData);
}
});
};
checkStatus();
})
}
main();
{'generation_id': '349872201343396:minimax/hailuo-2.3-fast', 'status': 'queued', 'meta': {'usage': {'credits_used': 399000}}}
Generation ID: 349872201343396:minimax/hailuo-2.3-fast
Status: queued. Checking again in 15 seconds.
Status: queued. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Processing complete:
{'id': '349872201343396:minimax/hailuo-2.3-fast', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/whale/inference_output%2Fvideo%2F2025-12-29%2Faa7d5360-0ef6-4bcd-ac65-2cf6b906cb71%2Foutput.mp4?Expires=1767003365&OSSAccessKeyId=LTAI5tAmwsjSaaZVA6cEFAUu&Signature=NDBDXmVZr3QX5XOxReOH3n8pwLQ%3D'}}
