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English(EN) M4 Pro vs M5 Pro (24GB): Qwen 3.8 Flash Next IQ3 with MoEShift at 374 tok/s prefill, 14.7 tok/s decode, 8.5GB peak memory

Qwen 3.8 Flash Next 125B 基准测试在 Apple Silicon 上表现强劲

一位用户在两台配备 24GB 统一内存的 Apple Silicon Mac 上,使用 MoEShift 后端对 Qwen3.8-Flash-Next 125B 模型进行了基准测试。M5 Pro 表现出更优越的性能,短提示解码速度达到 14.69 token/秒,长提示预填充速度达到 374.15 token/秒,而两台机器的峰值内存使用量均保持在 8.5GB。尽管内存有限,但这一性能使其适用于聊天和代理应用,并凸显了 MoEShift 在内存受限设备上运行大型模型的潜力。 AI

影响 展示了在消费级硬件上高效运行大型模型的性能,可能为更强大的本地 AI 应用提供支持。

排序理由 用户在特定硬件上对特定模型版本的基准测试。[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 →

Qwen 3.8 Flash Next 125B 基准测试在 Apple Silicon 上表现强劲

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Tool
用户在特定硬件上对特定模型版本的基准测试。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/dave-tro ·

    M4 Pro 对决 M5 Pro (24GB):Qwen 3.8 Flash Next IQ3 采用 MoEShift,预填充速度 374 tok/s,解码速度 14.7 tok/s,峰值内存 8.5GB

    <!-- SC_OFF --><div class="md"><p>I benchmarked <strong>Qwen3.8-Flash-Next 125B</strong> ISTA-DASLab's GSQ-RCO IQ3_XXS quant (76GB on disk), on two Macs with 24GB unified memory using <a href="https://github.com/davide-troiani/moeshift">MoEShift</a> backend:</p> <table><thead> <t…