Gemini 1.5 Pro performance data on Rival is based on blind head-to-head community voting. Overall win rate: 41.2% across 34 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 20 challenges.
We're not suggesting you leave Gemini 1.5 Pro. We're just... putting these here. In case you're curious. Which you are, because you scrolled this far.
Gemini 1.5 Pro performance data on Rival is based on blind head-to-head community voting. Overall win rate: 41.2% across 34 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 20 challenges.
We're not suggesting you leave Gemini 1.5 Pro. We're just... putting these here. In case you're curious. Which you are, because you scrolled this far.
Gemini 1.5 Pro handles infinite context with 99% retrieval accuracy at 750k tokens via Mixture-of-Experts and generates chapter summaries for 2-hour videos with 92% accuracy.
Use Gemini 1.5 Pro 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/gemini-1.5-pro" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The efficient middle manager who hits the brief without gold-plating. Adds #hashtags to manifestos and keeps code vanilla. Does exactly what you asked, nothing more.
Tackles prompts with "get it done" mentality. Logic puzzles get correct one-liners. Creative prompts get functional outputs without production value. The workhorse before Gemini learned to perform.
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.
20 outputs from Gemini 1.5 Pro
Gemini 1.5 Pro handles infinite context with 99% retrieval accuracy at 750k tokens via Mixture-of-Experts and generates chapter summaries for 2-hour videos with 92% accuracy.
Use Gemini 1.5 Pro 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/gemini-1.5-pro" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The efficient middle manager who hits the brief without gold-plating. Adds #hashtags to manifestos and keeps code vanilla. Does exactly what you asked, nothing more.
Tackles prompts with "get it done" mentality. Logic puzzles get correct one-liners. Creative prompts get functional outputs without production value. The workhorse before Gemini learned to perform.
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.
20 outputs from Gemini 1.5 Pro