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[–] 1 point 1 month ago (-1 children)

Looking at LLM benchmarks over time, there was still doubling of benchmark scores as of 2024 to mid-2025, then it inflected to more modest, incremental improvements, so sigmoid seems about right. Now we are seeing open models rapidly catching up now that the frontier has significantly slowed.

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  • [+] 1 point 1 month ago
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  • [–] 2 points 1 month ago (-1 children)

    I saw this article today summarizing a Mozilla report that open weight models are about 4 months behind the frontier: https://arstechnica.com/ai/2026/09/exclusive-open-chinese-models-close-gap-with-silicon-valleys-frontier-ai-models/

    Progress has slowed at the frontier and open weight is right on their heels. The general advice is that Fable and the like are best for niche use cases and to make an open weight model your daily driver because they’re almost as good and are a lot cheaper. In my case for personal use, I’m perfectly happy with Qwen 3.8 27B running locally and don’t care to deal with data collection or huge bills to get a bit stronger of a model.

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