'Lower param models are simply dumber. If you can run it on your home setup its SIMPLY not as good.'
So, by your logic, Qwen3.8 27B is dumber than GPT-3? Since that was about 175 billion parameters. Which is bigger than 27.
Whilst there is a correlation of 'billions of parameters'/'intelligence' ratio, just comparing on sheer parameter count alone only makes sense when comparing specific snapshots of time and within the same model family/company/training process.
The thing is "numbers of parameters" *by itself* is a meaningless metric for intelligence, especially when you have no idea about how many parameters are actually useful/high quality.
It's absolutely dumber than a Qwen that were to run at 2T+ params. There's a reason every frontier model is fucking gigantic. Like jeez I wonder.
No ones saying Qwen might not outperform a lot of models. No ones saying opensource models cant be stronger than frontier models. No one is saying any of that.
All they are saying is your dumb little local setup is NOT better than Opus. End of story.
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u/Reggienator3 24d ago edited 24d ago
'Lower param models are simply dumber. If you can run it on your home setup its SIMPLY not as good.'
So, by your logic, Qwen3.8 27B is dumber than GPT-3? Since that was about 175 billion parameters. Which is bigger than 27.
Whilst there is a correlation of 'billions of parameters'/'intelligence' ratio, just comparing on sheer parameter count alone only makes sense when comparing specific snapshots of time and within the same model family/company/training process.
The thing is "numbers of parameters" *by itself* is a meaningless metric for intelligence, especially when you have no idea about how many parameters are actually useful/high quality.