Llama 4 Scout vs Maverick - Image Understanding Comparison
Compare image understanding capabilities of LLaMA 4 Scout and Maverick using a visual workflow that analyzes home decor scene descriptions.
~14.62s
~$0.0017
1import requests
2import time
3import json
4
5api_key = "YOUR_API_KEY"
6url = "https://api.segmind.com/workflows/68137e1d6f6ddb5db5716fd4-v2"
7
8data = {
9 "image": "https://segmind-inference-inputs.s3.amazonaws.com/c9e50a96-3d21-45e2-8204-23e3cd74a8e8-ChatGPT Image Apr 26, 2025, 02_23_03 PM.png",
10 "Your_Question": "Describe all the home furnishing and home decor items in this image."
11}
12
13def poll_for_result(poll_url):
14 """Poll the API until the generation is complete"""
15 while True:
16 response = requests.get(
17 poll_url,
18 headers={'Authorization': f'Bearer {api_key}'}
19 )
20 result = response.json()
21
22 if result['status'] == 'COMPLETED':
23 # Parse the output (it's a JSON string)
24 outputs = json.loads(result['output'])
25 return outputs
26 elif result['status'] == 'FAILED':
27 raise Exception(result.get('error', 'Generation failed'))
28
29 # Wait 7 seconds before polling again
30 time.sleep(7)
31
32# Make the initial request
33response = requests.post(
34 url,
35 json=data,
36 headers={
37 'Authorization': f'Bearer {api_key}',
38 'Content-Type': 'application/json'
39 }
40)
41
42if response.status_code == 200:
43 result = response.json()
44 print('Request queued:', result)
45
46 # Start polling for results
47 outputs = poll_for_result(result['poll_url'])
48 print('Generation complete:', outputs)
49else:
50 print(f"Error: {response.status_code}")
51 print(response.text)
1import requests
2import time
3import json
4
5api_key = "YOUR_API_KEY"
6url = "https://api.segmind.com/workflows/68137e1d6f6ddb5db5716fd4-v2"
7
8data = {
9 "image": "https://segmind-inference-inputs.s3.amazonaws.com/c9e50a96-3d21-45e2-8204-23e3cd74a8e8-ChatGPT Image Apr 26, 2025, 02_23_03 PM.png",
10 "Your_Question": "Describe all the home furnishing and home decor items in this image."
11}
12
13def poll_for_result(poll_url):
14 """Poll the API until the generation is complete"""
15 while True:
16 response = requests.get(
17 poll_url,
18 headers={'Authorization': f'Bearer {api_key}'}
19 )
20 result = response.json()
21
22 if result['status'] == 'COMPLETED':
23 # Parse the output (it's a JSON string)
24 outputs = json.loads(result['output'])
25 return outputs
26 elif result['status'] == 'FAILED':
27 raise Exception(result.get('error', 'Generation failed'))
28
29 # Wait 7 seconds before polling again
30 time.sleep(7)
31
32# Make the initial request
33response = requests.post(
34 url,
35 json=data,
36 headers={
37 'Authorization': f'Bearer {api_key}',
38 'Content-Type': 'application/json'
39 }
40)
41
42if response.status_code == 200:
43 result = response.json()
44 print('Request queued:', result)
45
46 # Start polling for results
47 outputs = poll_for_result(result['poll_url'])
48 print('Generation complete:', outputs)
49else:
50 print(f"Error: {response.status_code}")
51 print(response.text)
API Endpoint
POST
https://api.segmind.com/workflows/68137e1d6f6ddb5db5716fd4-v2
Parameters
image
optionalstring (uri)
Image
Default:
"https://segmind-inference-inputs.s3.amazonaws.com/c9e50a96-3d21-45e2-8204-23e3cd74a8e8-ChatGPT Image Apr 26, 2025, 02_23_03 PM.png"
Your_Question
optionalstring
Your Question
Default:
"Describe all the home furnishing and home decor items in this image."
Response Format
Returns: Polling-based asynchronous response
Initial request returns a poll_url. Poll every 7 seconds until status is COMPLETED.
Common Error Codes
The API returns standard HTTP status codes. Detailed error messages are provided in the response body.
400
Bad Request
Invalid parameters or request format
401
Unauthorized
Missing or invalid API key
403
Forbidden
Insufficient permissions
404
Not Found
Workflow not found
406
Insufficient Credits
Not enough credits to process request
429
Rate Limited
Too many requests
500
Server Error
Internal server error
502
Bad Gateway
Service temporarily unavailable
504
Timeout
Request timed out