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English(EN) 23 Gemma4-E4B models compared with abliterlitics: the most downloaded one is also the most broken

下载量最高的 Gemma 4 E4B 模型被发现存在问题

作者 PulseAugur 编辑部 · [1 个来源] ·

对 23 个 Gemma 4 E4B 模型进行的比较发现，下载量最高的模型 OBLITERATUS/gemma-4-E4B-it-OBLITERATED 完全损坏且性能极差。“异端”变体通常表现最佳，在保持模型能力的同时维持了高准确性。其他模型如 gemma-4-E4B-it-abliterix 则表现出高拒绝率，但牺牲了一部分能力。 AI

影响 强调了在开源模型方面，严格的基准测试比下载量更重要。

排序理由 这是一项对多个开源模型的比较分析，详细说明了它们的性能并指出了问题，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

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

下载量最高的 Gemma 4 E4B 模型被发现存在问题

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
Tool
这是一项对多个开源模型的比较分析，详细说明了它们的性能并指出了问题，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]
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
65 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

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

    23款 Gemma4-E4B 模型对比评测：下载量最高的也最易出错

    <!-- SC_OFF --><div class="md"><p>This is our <strong>biggest</strong> comparison yet. We've taken 23 Gemma 4 E4B models from huggingface and ran them through the <a href="https://github.com/dreamfast/abliterlitics">abliterlitics</a> gauntlet.</p> <p>We also have a new <a href="h…

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