English(EN) Gave a try to Exllamav3 and it's great!

ExLlamaV3 因其出色的速度和性能而受到赞扬

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 23:24

一位 Reddit 用户分享了他们对新测试模型 ExLlamaV3 的积极体验。他们报告称，在 8x3090 配置上运行 GLM 5.3 Flash 时，预填充速度达到惊人的 700 tokens/秒，解码速度达到 42 tokens/秒。该用户还指出，该模型在处理超过 3000 万个 token 时表现良好，并对 ExLlamaV3 等社区驱动的项目表示感谢。 AI

影响展示了本地 LLM 部署的性能提升。

排序理由用户对特定模型实现的评论。

在 r/LocalLLaMA 阅读 →

ExLlamaV3

模型发布

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 3 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 用户对特定模型实现的评论。
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: 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]

r/LocalLLaMA TIER_1 English(EN) · /u/Leflakk · 2026-09-01 23:24

试用了 Exllamav3，效果很棒！

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1w4tejh/gave_a_try_to_exllamav3_and_its_great/"> <img alt="Gave a try to Exllamav3 and it's great!" src="https://preview.redd.it/6xbyv16kszmh1.png?width=640&crop=smart&auto=webp&s=45dafeef3c6c8cbf6…

本文如何被排名

报道来源 [1]

试用了 Exllamav3，效果很棒！

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