Do AI models still keep getting better, or have they plateaued?
optimizedbyotto.com
The AI hype is based on the assumption that the frontier AI labs are producing better and better foundational models at an accelerating pace. Is that really true, or are people just in sort of a mass psychosis because AI models have become so good at mimicking human behavior that we unconsciously attribute increasing intelligence to them? I decided to conduct a mini-benchmark of my own to find out if the latest and greatest AI models are actually really good or not.\n

I tested 9 flagships (Claude 4.6, GPT-5.2, Gemini 3.1 Pro, Kimi K2.5, etc.) in my own mini-benchmark with novel tasks, web search disabled and zero training contamination and no cheating possible.

TL;DR: Claude 4.6 is currently the best reasoning model, GPT-5.2 is overrated, and open-source is catching up fast, in particular Moonshot.ai’s Kimi K2.5 seems very capable.

  • ExLisper@lemmy.curiana.netEnglish
    1·
    2 hours ago

    In my opinion the proper solution is to ask for the constraints. Similar to the “walk or drive to the car wash” problem LLMs still tend to get confused but a familiar format and don’t notice this problem doesn’t make sense. You can actually play around with different examples to see how crazy the problem has to get form an LLM to refuse to answer and what biases or constraints does it have. Even if they assume some constraints they fail to solve this puzzle surprisingly often (like I showed for Sonnet 4.6 in other comment).