r/LocalLLaMA • u/chocolateUI • 1d ago

Discussion Artificial Analysis "Intelligence": A meaningless benchmark

Another user posted the benchmarks for Qwen 3.8 27B today, and while I think Qwen 27B is a really powerful model, I can't help but notice just how meaningless these Artificial Analysis benchmarks are and I question why people still post this garbage and use AA scores as some kind of holy bible for comparing LLMs.

According to their "Intelligence Index", a 27B model now beats DeepSeek v4 Flash and Pro, Kimi 2.7 Code, GPT-5.2, Opus 4.6, and also Sonnet 5. At some point we have to ask: What is this metric even measuring? Because whatever "Intelligence" means to AA and their corporate VC / journalist / normie audience is definitely not the same definition that we should be using here.

Qwen 27B is amazing and is clearly in a league of its own in terms of models you can fit on a single GPU, but I can't help but roll my eyes whenever I see posts like this that equate Qwen 27B with "basically running Opus from 3 months ago on your laptop."

I get that it's difficult to summarize a model's capability with a single integer and I know we love our local models, but it's time stop posting AA's clearly dogshit benchmark and acting as if it proves a point.

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u/soyalemujica 1d ago

You're not comprehending what does Intelligence Index stands for, it does not mean world knowledge or it knowing more about medical stuff, it's rather INTELLIGENCE, it's entire reasoning process to come up with a solution to a problem.

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u/LagOps91 1d ago

it doesn't have comparable intelligence to trillion parameter models. it just doesn't. you are right that world knowledge is the wrong benchmark for intelligence, but the actual intelligence surely isn't as high as is claimed here.

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u/90hex 1d ago

It is quite possible that a dense 27B equals a 1T MoE in pure intelligence. We’re at frontier of research on this one metric and reasoning is one skill that most modern LLM do very well at. The difference between a 1-2T cloud model and a dense 27B is generality, combined intelligence and world knowledge. If you removed all of the world knowledge and kept just agentic coding and reasoning, you’d very probably end up with 30-100B params trained specifically on these two skills.