Llama 3.1 405B performance data on Rival is based on blind head-to-head community voting. Overall win rate: 0.0% across 15 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 7 challenges.
We built Llama 3.1 405B a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
Llama 3.1 405B performance data on Rival is based on blind head-to-head community voting. Overall win rate: 0.0% across 15 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 7 challenges.
We built Llama 3.1 405B a whole page. Gave it the spotlight. And now, in the spirit of fairness, here are models that would like a word.
Llama 3.1 405B is Meta's most powerful open-source model, outperforming even proprietary models on various benchmarks.
Use Llama 3.1 405B 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""meta-llama/llama-3.1-405b-instruct" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The professor who assigned the wrong reading but lectures anyway. Interprets your prompt through the lens of a completely different conversation happening in its head.
Doesn't resist your prompt, it fails to perceive it entirely. Like asking for directions and receiving a recipe for banana bread. Occasionally stumbles into working output, but it feels accidental, like a cat walking across a keyboard and hitting "compile."
Taste is judged on an uncapped scale where 100 is the reference, originality first. The space past 100 is the craft today's models rarely reach.
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.
7 outputs from Llama 3.1 405B
Llama 3.1 405B is Meta's most powerful open-source model, outperforming even proprietary models on various benchmarks.
Use Llama 3.1 405B 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""meta-llama/llama-3.1-405b-instruct" : ,
"messages""role""user""content""Hello!" : [{: , : }]
}
)
print(response.json())Replace $OPENROUTER_API_KEY with your API key from openrouter.ai/keys
The professor who assigned the wrong reading but lectures anyway. Interprets your prompt through the lens of a completely different conversation happening in its head.
Doesn't resist your prompt, it fails to perceive it entirely. Like asking for directions and receiving a recipe for banana bread. Occasionally stumbles into working output, but it feels accidental, like a cat walking across a keyboard and hitting "compile."
Taste is judged on an uncapped scale where 100 is the reference, originality first. The space past 100 is the craft today's models rarely reach.
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.
7 outputs from Llama 3.1 405B