Maximum benchmark performance.
GPT Image 2
OpenAILeads the supplied Arena image-generation comparison. Choose it when the highest benchmark score is the priority.
Choose your workload
Models for creating images from a text description and creative direction.
Maximum benchmark performance.
Leads the supplied Arena image-generation comparison. Choose it when the highest benchmark score is the priority.
A smarter performance-to-cost balance.
The lower approximate per-image reference price comes with a larger supplied benchmark score gap. Evaluate the tradeoff for your creative workload.
Arena · supplied snapshot·Supplied Arena snapshot · date pending·How we compare
Approximate comparison using supplied reference prices for one image. Actual settings and billing may vary. Arena scores and prices are from the supplied snapshot. The leaderboard source and snapshot date still need confirmation.
The same workload, with the details that help you choose.
| Comparison | GPT Image 2Best Performance | Qwen Image 2512Best Value |
|---|---|---|
| Arena score | 1383 Supplied Arena snapshot · date pending | 1125 Supplied Arena snapshot · date pending |
| Relative score | Performance reference | 18.7% lower Arena score |
| Billing rate | ~$0.06 / image | ~$0.02 / image |
| Arena difference | Performance reference | -258 / -18.7% |
| Cost difference | Price reference | ~66.7% lower cost |
| Supported modalities | text, image → image | text → image |
| Main reason to choose | Choose this when maximum benchmark performance matters more than inference cost. | Consider this for production workloads where the reference price matters. Evaluate the benchmark gap against your own workload. |
| Best fit | Image creation and editing when maximum benchmark performance matters | Creative variants and repeated image-generation workloads |
| Billing details | Approximate supplied reference price per image. Output settings and actual billing may vary. | Approximate supplied reference price per image. Output settings and actual billing may vary. |
Approximate comparison using supplied reference prices for one image. Actual settings and billing may vary.
Implementation
Copy a model test, replace the API key with your own, and run.
Copy the Python or cURL test for GPT Image 2. Replace the API-key placeholder with your own key and run.
GPT Image 2 · image generation · Creates one image and returns its base64 image data in the response.
import json
from urllib.error import HTTPError
from urllib.request import Request, urlopen
API_KEY = "YOUR_ROTEN_API_KEY"
def send(url, payload=None):
data = json.dumps(payload).encode("utf-8") if payload is not None else None
request = Request(url, data=data, headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"})
try:
with urlopen(request, timeout=180) as response:
return json.load(response)
except HTTPError as error:
raise SystemExit(f"HTTP {error.code}: {error.read().decode('utf-8')}")
payload = json.loads(r'''{
"prompt": "A simple indigo geometric cube on a plain white background.",
"n": 1,
"size": "1024x1024",
"quality": "medium",
"response_format": "b64_json",
"model": "gpt-image-2"
}''')
result = send("https://api.roten.ai/v1/images/generations", payload)
print(json.dumps(result, indent=2, ensure_ascii=False))API_KEY='YOUR_ROTEN_API_KEY'
curl --fail-with-body --silent --show-error 'https://api.roten.ai/v1/images/generations' \
-H "Authorization: Bearer $API_KEY" \
-H 'Content-Type: application/json' \
--data '{
"prompt": "A simple indigo geometric cube on a plain white background.",
"n": 1,
"size": "1024x1024",
"quality": "medium",
"response_format": "b64_json",
"model": "gpt-image-2"
}'Python tests use the standard library. Video cURL tests also use Python 3 to read task responses.
A clear reference point
Recommendations combine the supplied Arena scores with the supplied model prices. A benchmark score is one signal for choosing a model for your workload.
Arena · supplied snapshot·Supplied Arena snapshot · date pending·How we compare
Built for production
Talk to us about volume pricing, model selection and migration.