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qwen3.8-flash-next-iq3_s 在基准测试中优于 -27B-GGUF:UD-Q4_K_XL

作者 PulseAugur 编辑部 · [1 个来源] ·

对两个语言模型 qwen3.8-flash-next-iq3_s 和 -27B-GGUF:UD-Q4_K_XL 进行了比较，使用了包括 AIME26、IFEval、BFCL v4 和 LiveCodeBench v6 在内的多个基准测试。在这些基准测试的总解决问题数方面，qwen3.8-flash-next-iq3_s 模型优于 -27B-GGUF:UD-Q4_K_XL 模型，正确答案数为 151 个，而后者为 145 个。虽然两个模型都遇到了 token 限制问题，但 -27B-GGUF:UD-Q4_K_XL 模型出现了更多不正确答案的实例。 AI

影响 提供了特定语言模型在各种基准测试上的比较性能数据。

排序理由 在基准测试上对两个语言模型进行比较。 [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 →

qwen3.8-flash-next-iq3_s 在基准测试中优于 -27B-GGUF:UD-Q4_K_XL

本文如何被排名

Signal score
4 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
在基准测试上对两个语言模型进行比较。 [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
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

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/politerate ·

    qwen3.8-flash-next-iq3_s vs -27B-GGUF:UD-Q4_K_XL

    <!-- SC_OFF --><div class="md"><p>Sampling: temp 1.0, top_p 0.95, top_k 20 for both. Run with evalscope over the OpenAI-compatible API: Qwen3.8-Next on Strata (MI50 32GB), Qwen3.8-27B on llama.cpp (RX 7900 XTX 24GB).</p> <p>Caveat: These are only a portion of the full sets, since…

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