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English(EN) 2 gaming PCs + an M4 Pro MacBook over Ethernet + 2 iPhone 17 Pro Maxes over USB-C: Qwen3.8 Flash Next at 37-39 tok/s at 60k context (262k layout in the works)

用户将Qwen3.8 Flash Next分布在5台设备上,实现39 tok/s

一位用户已成功将Qwen3.8 Flash Next大型语言模型分布在一台由五台设备组成的网络中,包括两台游戏PC、一台MacBook Pro和两台iPhone 17 Pro Max。该设置利用流水线式推断技术实现了令人印象深刻的令牌生成速度,在60k上下文长度下报告的速率为37-39 tokens/s。用户还在尝试262k上下文布局,挑战本地分布式LLM推理的可能性。 AI

影响 展示了运行大型模型本地推理的新型分布式推理技术。

排序理由 用户为现有模型创建的分布式推理设置。

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 →

用户将Qwen3.8 Flash Next分布在5台设备上,实现39 tok/s

本文如何被排名

Signal score
6 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户为现有模型创建的分布式推理设置。
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
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/StayLameBro ·

    2台游戏PC + 1台M4 Pro MacBook(通过以太网连接)+ 2台iPhone 17 Pro Max(通过USB-C连接):Qwen3.8 Flash Next在60k上下文下达到37-39 tok/s(262k布局正在开发中)

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1x8ley0/2_gaming_pcs_an_m4_pro_macbook_over_ethernet_2/"> <img alt="2 gaming PCs + an M4 Pro MacBook over Ethernet + 2 iPhone 17 Pro Maxes over USB-C: Qwen3.8 Flash Next at 37-39 tok/s at 60k context (262k lay…