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English(EN) How do I improve my SWEBench run on 3090?

用户寻求本地LLM设置的SWEBench优化技巧

Reddit r/LocalLLaMA板块的一位用户正在寻求关于使用llama.cpp和量化后的Qwen3.8-27B模型优化其SWEBench性能的建议。他们遇到了包括LimitExceeded和TimeoutExpired在内的许多错误,导致大量测试失败。用户正在寻找特定的参数调整,以减少错误,提高已完成测试的成功率,并在保持大上下文窗口的同时提高整体速度。 AI

影响 此查询突显了在本地运行复杂AI基准测试的挑战,表明了更广泛采用的潜在基础设施和配置障碍。

排序理由 用户寻求关于优化特定工具性能的技术建议。

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 →

用户寻求本地LLM设置的SWEBench优化技巧

本文如何被排名

Signal score
5 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户寻求关于优化特定工具性能的技术建议。
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
product, 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
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/Ok_Warning2146 ·

    如何在3090上改进我的SWEBench运行?

    <!-- SC_OFF --><div class="md"><p>I am running SWEBench locally with llama.cpp and unsloth's Qwen3.8-27B using the following server command: </p> <p>./llama-server -m ~/gguf/Qwen3.8-27B-IQ4_NL.gguf --jinja -ngl 999 -fa 1 --load-mode mmap -np 1 --temp 1.0 --top_p 0.95 --top_k 20 -…