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DeepSeek V4 Flash 性能测试：IQ2_S 比 IQ3_XXS-AS 更快

作者 PulseAugur 编辑部 · [1 个来源] ·

一位用户对 DeepSeek V4 Flash 模型进行了性能测试，使用了 fairydreaming/llama.cpp 分支，比较了两个量化级别（IQ3_XXS-AS 和 IQ2_S）。结果显示，尽管使用了更小的上下文窗口，IQ2_S 量化在初始提示评估和后续生成方面都更快。用户还发现，对于该模型，fairydreaming 分支相比 mainline llama.cpp 构建没有性能优势。 AI

影响 为在消费级硬件上运行 DeepSeek V4 Flash 的用户提供了实用的性能数据，有助于模型选择。

排序理由 用户进行的开源模型基准测试。[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 →

DeepSeek V4 Flash 性能测试：IQ2_S 比 IQ3_XXS-AS 更快

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
用户进行的开源模型基准测试。[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, 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.
Story freshness
104 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/CoplanarDimension ·

    DeepSeek V4 Flash | IQ3_XXS-AS & IQ2_S Bench | mainline b10064 vs fairydreaming | 1xRTX 3090 + 128GB DDR4 | 250PP/11TG on 50K CTX

    <!-- SC_OFF --><div class="md"><p>Hey all!</p> <p>Wanted to see how DeepSeek V4 Flash GGUFs in two different quants perform on my hardware and share the results.</p> <p>Tested two quants on the <strong>fairydreaming/llama.cpp dsv4 fork</strong>. As a bonus, I also ran the same mo…

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