English(EN) Why do we have models under 15b so rarely anymore?

AI实验室聚焦大型模型，导致小型SOTA选项稀缺

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-16 13:28

Reddit的r/LocalLLaMA社区的一场讨论突显了人们认为150亿参数以下的新型最先进（SOTA）大型语言模型（LLMs）稀缺的现象。用户们在质疑为什么主要的AI实验室似乎专注于240亿-270亿参数或更大的模型，并渴望在140亿参数以下范围内有更多SOTA选项。 AI

影响暗示了小型高性能LLM可能存在的市场空白，这可能会影响在性能较低硬件上的可访问性和部署。

排序理由用户在Reddit上讨论LLM参数规模的趋势。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Commentary; 用户在Reddit上讨论LLM参数规模的趋势。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: model release; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

r/LocalLLaMA TIER_1 English(EN) · /u/Hot_Example_4456 · 2026-10-16 13:28

为什么我们现在很少看到 150 亿参数以下的模型了？

<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>   submitted by   <a href="https://www.red…