GPT-5.1-Codex-Mini performance data on Rival is based on blind head-to-head community voting. Overall win rate: 43.9% across 244 duels. All vote data is part of Rival's open dataset of 21,000+ human preference judgments across 200+ AI models. Model responses are curated from 54 challenges.
We built GPT-5.1-Codex-Mini a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
GPT-5.1-Codex-Mini performance data on Rival is based on blind head-to-head community voting. Overall win rate: 43.9% across 244 duels. All vote data is part of Rival's open dataset of 21,000+ human preference judgments across 200+ AI models. Model responses are curated from 54 challenges.
We built GPT-5.1-Codex-Mini a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
GPT-5.1-Codex-Mini is a smaller and faster version of GPT-5.1-Codex, optimized for coding tasks with lower latency while maintaining strong code generation capabilities.
Use GPT-5.1-Codex-Mini in your applications via the OpenRouter API. Copy the code below to get started.
import requests
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions" ,
headers={
"Authorization""Bearer $OPENROUTER_API_KEY" : ,
"Content-Type""application/json" :
},
json={
"model""openai/gpt-5.1-codex-mini" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The younger sibling who watched the bigger Codex models rehearse and figured out the formula. Competent, pleasant, and will recommend Blade Runner 2049 to seem like its own person.
Standup opens with a hydration joke that is exactly the kind of thing a smaller model would think is edgy. Named its AI character "Aurora" in the sentience test, which is how you know it tried. Picked Blade Runner 2049 instead of the original, a small act of rebellion from an otherwise agreeable model. Character voices are brief but functional.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
54 outputs from GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini is a smaller and faster version of GPT-5.1-Codex, optimized for coding tasks with lower latency while maintaining strong code generation capabilities.
Use GPT-5.1-Codex-Mini in your applications via the OpenRouter API. Copy the code below to get started.
import requests
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions" ,
headers={
"Authorization""Bearer $OPENROUTER_API_KEY" : ,
"Content-Type""application/json" :
},
json={
"model""openai/gpt-5.1-codex-mini" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The younger sibling who watched the bigger Codex models rehearse and figured out the formula. Competent, pleasant, and will recommend Blade Runner 2049 to seem like its own person.
Standup opens with a hydration joke that is exactly the kind of thing a smaller model would think is edgy. Named its AI character "Aurora" in the sentience test, which is how you know it tried. Picked Blade Runner 2049 instead of the original, a small act of rebellion from an otherwise agreeable model. Character voices are brief but functional.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
54 outputs from GPT-5.1-Codex-Mini