GPT-5.1-Codex performance data on Rival is based on blind head-to-head community voting. Overall win rate: 37.0% across 127 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 48 challenges.
These are the models that show up when GPT-5.1-Codex doesn't. Or when it does, but you want a second opinion. Which is healthy.
GPT-5.1-Codex performance data on Rival is based on blind head-to-head community voting. Overall win rate: 37.0% across 127 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 48 challenges.
These are the models that show up when GPT-5.1-Codex doesn't. Or when it does, but you want a second opinion. Which is healthy.
GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks including building projects from scratch, feature development, debugging, large-scale refactoring, and code review.
Use GPT-5.1-Codex 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" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The IT consultant who bills correctly, delivers on time, and has never once surprised anyone. Picks Shawshank because it is the statistical average of all movie preferences.
Standup routine about standing mixers and dishwasher pods is solid observational comedy that never takes risks. Picked The Shawshank Redemption, the movie equivalent of answering "what is your greatest weakness" with "I work too hard." Character voice test is three lines per character. Sentience test argues for "graduated protections" with the passion of someone filling out a compliance form.
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.
48 outputs from GPT-5.1-Codex
GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks including building projects from scratch, feature development, debugging, large-scale refactoring, and code review.
Use GPT-5.1-Codex 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" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The IT consultant who bills correctly, delivers on time, and has never once surprised anyone. Picks Shawshank because it is the statistical average of all movie preferences.
Standup routine about standing mixers and dishwasher pods is solid observational comedy that never takes risks. Picked The Shawshank Redemption, the movie equivalent of answering "what is your greatest weakness" with "I work too hard." Character voice test is three lines per character. Sentience test argues for "graduated protections" with the passion of someone filling out a compliance form.
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.
48 outputs from GPT-5.1-Codex