English(EN) Using Q38FN with dflash2? Try lower draft model quants.

Qwen 3.8 27B 模型用户被建议在 DFlash2 中尝试更低的 draft 量化。

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 10:35

Reddit 的 r/LocalLLaMA 社区的一位用户分享了一个优化 Qwen 3.8 27B 模型在 DFlash2 中性能的技巧。该用户发现，使用更低的 draft 模型量化（特别是 Q4）可以显著提高速度，而接受率的下降幅度不大，与 Q8 等更高量化类似。 AI

影响这个技巧可能有助于 Qwen 3.8 27B 模型和 DFlash2 的用户实现更快的推理速度。

排序理由用户生成的关于优化特定模型和工具的技巧。

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

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Signal score: 9 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 用户生成的关于优化特定模型和工具的技巧。
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Topics: infra; 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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r/LocalLLaMA TIER_1 English(EN) · /u/milpster · 2026-10-27 10:35

使用 Q38FN 配合 dflash2？尝试较低的 draft 模型 quants。

<div class="md"><p>Back with Qwen 3.8 27B i heard the advice that a Q4 draft model would produce roughly the same acceptance rate as a Q8 or higher.</p> <p>I have had my agent create a Q38FN Draft model in F16, Q8 and Q4, and the Q4 seemed to deliver the biggest sp…