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English(EN) Qwen3.8-FN at NVFP4 ( Basalt vs cachy-flash vs ninfer-ext)

Basalt 引擎在 Qwen3.8-FN 推理速度测试中领先

对 NVIDIA RTX 5090 GPU 上 Qwen3.8-FN 模型的三种推理引擎——basalt、cachy-flash 和 ninfer-ext——的比较显示,basalt 通常提供更优越的性能。在各种上下文长度下,basalt 在预填充和解码操作中始终实现了更高的 tokens-per-second 速率。虽然 cachy-flash 在较短的上下文长度下显示出具有竞争力的预填充速度,但随着上下文长度的增加,basalt 保持了领先地位,而 ninfer-ext 则落后于两者。 AI

影响 优化推理引擎可以显著提高本地运行大型语言模型的速度和效率。

排序理由 特定模型的推理引擎基准比较。[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 →

Basalt 引擎在 Qwen3.8-FN 推理速度测试中领先

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特定模型的推理引擎基准比较。[lever_c_demoted from research: ic=1 ai=1.0]
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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
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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/giveen ·

    Qwen3.8-FN 在 NVFP4 (Basalt vs cachy-flash vs ninfer-ext)

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xcp0mf/qwen38fn_at_nvfp4_basalt_vs_cachyflash_vs/"> <img alt="Qwen3.8-FN at NVFP4 ( Basalt vs cachy-flash vs ninfer-ext)" src="https://preview.redd.it/t60qh98nz1xh1.png?width=640&amp;crop=smart&amp;auto=webp&…