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English(EN) Ling 3.0 Tiny is the strongest, fastest and greatest model on my low end PC!

Ling 3.0 Tiny 模型因在低端PC上的速度而受到赞扬

Reddit 的 r/LocalLLaMA 社区的一位用户称赞了 Ling 3.0 Tiny 模型,强调了它在低端硬件上令人印象深刻的性能。该模型拥有 80 亿参数,其中 13 亿处于活动状态,据报道速度达到每秒 36 个 token,在速度方面优于 Qwen 3.5 9b 和 Gemma 12 等其他模型。用户表达了对更多此类高效、快速的开源模型的渴望。 AI

影响 强调了在消费级硬件上实现高效、高性能模型的潜力,鼓励该领域进一步发展。

排序理由 用户对特定模型在消费级硬件上性能的赞扬。

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 →

Ling 3.0 Tiny 模型因在低端PC上的速度而受到赞扬

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户对特定模型在消费级硬件上性能的赞扬。
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
52 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

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/cosmos_hu ·

    Ling 3.0 Tiny 是我低端 PC 上最强大、最快、最棒的模型!

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vqx6nd/ling_30_tiny_is_the_strongest_fastest_and/"> <img alt="Ling 3.0 Tiny is the strongest, fastest and greatest model on my low end PC!" src="https://preview.redd.it/odokmi38qyjh1.png?width=640&amp;crop=sm…