English(EN) Run GLM 5.2 Locally (2026): 2-bit on a 256GB Mac or 4090 box

GLM 5.2 模型现已通过量化在消费级硬件上运行

作者 PulseAugur 编辑部 · [3 个来源] · 2026-06-23 10:14

拥有 7530 亿参数和 100 万 token 上下文窗口的 GLM 5.2 模型现已可用于在消费级硬件上本地部署。虽然完整模型需要超过 1.5 TB 的存储空间，但量化版本可在至少拥有 256 GB RAM 的机器上运行。在 256 GB Mac Studio 或类似配置的强大 GPU 上运行 2 位量化模型是可行的，但性能可能限制在每秒 3-9 个 token。为了获得最佳质量和速度，建议使用 512 GB 系统运行 4 位量化模型，但用户须知，对于大多数应用而言，托管 API 解决方案通常更具成本效益且速度更快。 AI

影响使强大 LLM 的本地、私有或离线使用成为可能，惠及个人用户和技术爱好者。

排序理由社区驱动的努力，旨在通过量化权重在消费级硬件上本地运行大型模型。

在 dev.to — LLM tag 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。我们如何撰写摘要 →

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Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Research; 社区驱动的努力，旨在通过量化权重在消费级硬件上本地运行大型模型。
Source corroboration: 3 independent sources; Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics: model release, product; 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: 98 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.
Coverage growth since scoring: +1 source(s) since last score; New sources have picked up this story since our last re-score. Score will update on the next scoring pass.

完整方法见我们的编辑标准。

报道来源 [3]

r/LocalLLaMA TIER_1 English(EN) · /u/segmond · 2026-06-27 17:33

在预算硬件上运行 GLM5.2 < $2500。

<div class="md"><p>Too many times I hear people whine about not being ble to run SOTA models or claim it would require $50k, or $100k. </p> <p><a href="https://www.ebay.com/itm/398079051468">https://www.ebay.com/itm/398079051468</a> Epcy Motherboard & CPU - $46…
r/LocalLLaMA TIER_1 English(EN) · /u/phwlarxoc · 2026-06-25 15:22

GLM 5.2 运行在消费级硬件上

<div class="md"><p>I tried out the unsloth quants of GLM 5.2 on still "consumer-ish" hardware:</p> <p>32C Zen5 Threadripper Pro 9975 WX, Asus WRX90E-SAGE-SE PCIe Gen5, 512GB DDR5 ECC RAM @ 4800MHz, dual RTX 5090.</p> <p>This machine was put together pre-R…
dev.to — LLM tag TIER_1 English(EN) · Owen · 2026-06-23 10:14

本地运行 GLM 5.2 (2026)：256GB Mac 或 4090 盒式机上的 2 位

<blockquote> <p>Zhipu put the GLM 5.2 weights on HuggingFace under an MIT license, so the question stopped being "can I download a frontier coding model" and became "will it run on the machine I already own." For a single Mac Studio or a desktop with one GPU and a lot of RAM, the…

本文如何被排名

报道来源 [3]

在预算硬件上运行 GLM5.2 < $2500。

GLM 5.2 运行在消费级硬件上

本地运行 GLM 5.2 (2026)：256GB Mac 或 4090 盒式机上的 2 位

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