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English(EN) @ LouisR85 So, my lesson learned is: do not use Q4 models for agentic coding. Qwen3.6-35B-A3B is working well in OpenCode and it's staying focused so is Ornith-

AI 编码器的教训：8 位量化在代理任务上优于 4 位量化

作者 PulseAugur 编辑部 · [1 个来源] ·

一位 Mastodon 用户分享了他们使用 AI 模型进行代理编码的经验，建议不要使用 Q4 模型。他们发现 Qwen3.6-35B-A3B 和 Ornithogalum-1.5-35B-A3B 表现良好，尤其是在使用 8 位量化变体时，这与 4 位量化相比有显著差异。 AI

影响 强调了量化对 AI 模型在编码任务中性能的实际影响。

排序理由 用户对模型性能的经验和意见。

在 Mastodon — mastodon.social 阅读 →

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AI 编码器的教训：8 位量化在代理任务上优于 4 位量化

本文如何被排名

Signal score
1 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Commentary
用户对模型性能的经验和意见。
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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, product
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.
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Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

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报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    我的经验教训是：不要在代理编码中使用 Q4 模型。Qwen3.6-35B-A3B 在 OpenCode 中运行良好，并且保持专注，Ornith-也是-

    @ LouisR85 So, my lesson learned is: do not use Q4 models for agentic coding. Qwen3.6-35B-A3B is working well in OpenCode and it's staying focused so is Ornith-1.5-35B-A3B as long as I stick to the 8bit variants. It's a huge difference between 8bit and 4bit quantisation. # AI # L…

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