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English(EN) Qwen3.8 27B on one RTX 5090: six inference engines benchmarked with and without DFlash2

Qwen3.8 27B 在 RTX 5090 上的六种推理引擎基准测试

一项基准比较测试了在单块 RTX 5090 GPU 上的六种推理引擎——llama.cpp、vLLM、SGLang、NInfer、velox-inferer 和 TensorSharp。测试重点关注吞吐量、长提示词下的延迟、并发请求以及图像输入能力。NInfer 在推测解码和总体吞吐量方面表现领先,而 llama.cpp 显示出最高的纯解码速率。TensorSharp、SGLang 和 velox-inferer 在 DFlash2 吞吐量方面表现相似。 AI

影响 提供了不同推理引擎性能差异的见解,帮助开发者选择最优配置以实现高效的 LLM 部署。

排序理由 对特定模型和硬件上的多种推理引擎进行的基准比较。[lever_c_demoted from research: ic=1 ai=0.7]

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 27B 在 RTX 5090 上的六种推理引擎基准测试

本文如何被排名

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8 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
对特定模型和硬件上的多种推理引擎进行的基准比较。[lever_c_demoted from research: ic=1 ai=0.7]
Source corroboration
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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
infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
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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/fuzhongkai ·

    Qwen3.8 27B 在单块 RTX 5090 上:六种推理引擎的 DFlash2 有无基准测试

    <!-- SC_OFF --><div class="md"><p>Disclosure: I’m the author of TensorSharp. This English summary was adapted and edited with LLM assistance from the <a href="https://claude.ai/artifact/2Jdw2gGRLbveNYMbhFnURN#2587fc59-b43b">full benchmark report</a>.</p> <p>The comparison covers …