Gemma 3 27B performance data on Rival is based on blind head-to-head community voting. Overall win rate: 39.3% across 331 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 55 challenges.
We built Gemma 3 27B a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
Gemma 3 27B performance data on Rival is based on blind head-to-head community voting. Overall win rate: 39.3% across 331 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 55 challenges.
We built Gemma 3 27B a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 131072 tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to Gemma 2.
Use Gemma 3 27B 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""google/gemma-3-27b-it" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
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.
55 outputs from Gemma 3 27B
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 131072 tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to Gemma 2.
Use Gemma 3 27B 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""google/gemma-3-27b-it" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
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.
55 outputs from Gemma 3 27B