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English(EN) Gemma 4 26B A4B: The Open-Weight AI Model That Wakes Only 4B Params — Day 8/30

Gemma 4 26B A4B 使用MoE仅激活4B参数,提升效率

Gemma 4 26B (A4B) 模型采用了混合专家(MoE)架构,在其总计260亿参数中,每个token仅激活约40亿参数。这种设计使其在保持接近小型模型的计算效率和速度的同时,拥有大型模型的知识容量,适合内存充足但计算能力有限的硬件。测试表明该模型在推理和代码相关任务上表现良好,但在严格的JSON格式化方面存在一些小问题,并且与数学提示相比,代码提示的token生成速度较慢。 AI

影响 混合专家(MoE)架构使大型模型能够在计算需求较低的硬件上运行,从而可能降低先进AI的入门门槛。

排序理由 该条目描述了一个特定的AI模型架构及其在基准测试上的性能,属于研究类别。[lever_c_demoted from research: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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Gemma 4 26B A4B 使用MoE仅激活4B参数,提升效率

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该条目描述了一个特定的AI模型架构及其在基准测试上的性能,属于研究类别。[lever_c_demoted from research: ic=1 ai=1.0]
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  1. dev.to — LLM tag TIER_1 English(EN) · AI Explore ·

    Gemma 4 26B A4B:仅唤醒 4B 参数的开放权重 AI 模型 — 第 8/30 天

    <blockquote> <p><strong>TL;DR —</strong> Gemma 4 26B (A4B) is a 26-billion-parameter Mixture-of-Experts model that only activates about 4 billion parameters per token, which is why it's cheap and fast despite its size. Probes show it nailing interval-merging code and a two-pump m…