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AI Labs Focus on Larger Models, Leaving Smaller SOTA Options Scarce

By PulseAugur Editorial · [1 sources] ·

A discussion on Reddit's r/LocalLLaMA community highlights a perceived scarcity of new state-of-the-art (SOTA) large language models (LLMs) below the 15 billion parameter size. Users are questioning why major AI labs appear to be focusing on models of 24-27 billion parameters or larger, with a desire for more SOTA options in the sub-14 billion parameter range. AI

IMPACT Suggests a potential gap in the market for smaller, high-performing LLMs, which could impact accessibility and deployment on less powerful hardware.

RANK_REASON User discussion on Reddit about trends in LLM parameter sizes.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI Labs Focus on Larger Models, Leaving Smaller SOTA Options Scarce

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User discussion on Reddit about trends in LLM parameter sizes.
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model release
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Hot_Example_4456 ·

    Why do we have models under 15b so rarely anymore?

    <!-- SC_OFF --><div class="md"><p>Basically title. All labs seem to have agreed 24-27b is the minimum size they will go, nothing below that. I wonder when will we get the next sub 14b model from a SOTA lab</p> </div><!-- SC_ON --> &#32; submitted by &#32; <a href="https://www.red…

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