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English(EN) M5 Ultra 96GB vs M5 Max 128GB — is 2x bandwidth worth losing 32GB of RAM, with Qwen3.8-Flash-Next dropping tomorrow?

Mac Studio M5 Ultra 对比 M5 Max:本地 AI 推理的内存与带宽之争

一位用户正在为本地 AI 模型推理在两种 Apple Mac Studio 配置之间进行权衡:一种配备 M5 Ultra 芯片(96GB 内存,1.2 TB/s 带宽),另一种配备 M5 Max 芯片(128GB 内存,614 GB/s 带宽)。这一决定取决于即将发布的 Qwen3.8-Flash-Next 模型,该模型需要大量内存。M5 Ultra 提供双倍带宽和 GPU 核心,可能有利于多智能体推理,但其 96GB 内存可能不足以支持新模型的全部上下文。M5 Max 虽然速度较慢,但可以容纳上下文较少的模型,但其带宽可能未被充分利用。 AI

影响 硬件选择直接影响本地运行大型语言模型的可行性和性能。

排序理由 用户正在比较本地 AI 推理的硬件配置,而非新模型发布或重大行业事件。

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 →

Mac Studio M5 Ultra 对比 M5 Max:本地 AI 推理的内存与带宽之争

本文如何被排名

Signal score
2 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户正在比较本地 AI 推理的硬件配置,而非新模型发布或重大行业事件。
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
infra, 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
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

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/Mxmtm ·

    M5 Ultra 96GB 对比 M5 Max 128GB — 2倍带宽是否值得牺牲32GB内存,而 Qwen3.8-Flash-Next 明日发布?

    <!-- SC_OFF --><div class="md"><p>I’ve been going back and forth on this for a week and I can’t settle it, so I’m hoping someone here has hands-on numbers.<br /> The two configs (German prices, dealer quote, incl. VAT):</p> <table><thead> <tr> <th>Config</th> <th>Price</th> </tr>…