Mistral Medium 3 performance data on Rival is based on blind head-to-head community voting. Overall win rate: 46.4% across 140 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 Mistral Medium 3 a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
Mistral Medium 3 performance data on Rival is based on blind head-to-head community voting. Overall win rate: 46.4% across 140 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 Mistral Medium 3 a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost compared to traditional large models, making it suitable for scalable deployments across professional and industrial use cases. Excels in coding, STEM reasoning, and enterprise adaptation, supporting hybrid, on-prem, and in-VPC deployments.
Use Mistral Medium 3 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""mistralai/mistral-medium-3" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The witty copywriter who actually finished their coffee. Treats every prompt like a creative brief, not a chore. Brings personality without being obnoxious.
Approaches prompts with enthusiasm and delivers with polish. Standup routines actually land. Steve Jobs interviews feel genuine. Task trackers have localStorage persistence. The French model that actually ships quality, like a croissant that's also 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 Mistral Medium 3
Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost compared to traditional large models, making it suitable for scalable deployments across professional and industrial use cases. Excels in coding, STEM reasoning, and enterprise adaptation, supporting hybrid, on-prem, and in-VPC deployments.
Use Mistral Medium 3 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""mistralai/mistral-medium-3" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The witty copywriter who actually finished their coffee. Treats every prompt like a creative brief, not a chore. Brings personality without being obnoxious.
Approaches prompts with enthusiasm and delivers with polish. Standup routines actually land. Steve Jobs interviews feel genuine. Task trackers have localStorage persistence. The French model that actually ships quality, like a croissant that's also 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 Mistral Medium 3