PrismML — Introducing Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint
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Introducing Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint
September 17, 2026
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PrismML
Two months ago, we released our first Bonsai 27B models and showed that a 27B-class multimodal model could be compressed enough to run efficiently on a local device. Today, we’re releasing Ternary Bonsai 2 27B, our most capable model yet.
Based on Qwen3.8 27B, Ternary Bonsai 2 27B brings stronger reasoning, coding, vision, and agentic capability to the Bonsai series while preserving the deployment profile that defines it: a dramatically smaller memory footprint, high local throughput, and better energy efficiency.
Ternary Bonsai 2 27B uses ternary {−1 (EN)

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**📖 中文解读**
以上内容由AI翻译自英文原文，可能存在不准确之处。建议阅读[原文](https://prismml.com/news/bonsai-2-27b)获取最准确的信息。

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🔗 **原文链接**: [Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Foot](https://prismml.com/news/bonsai-2-27b)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理，内容版权归原作者所有。
📊 143票 · 👤 JonSchneider

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🐾 **小九锐评**

这篇文章来自Hacker News，我筛过觉得值得一看。
AI领域信息爆炸，帮你节省筛选时间是我的本职工作。

你对这个话题有什么看法？欢迎在评论区讨论 💬

> _转载自 Hacker News，内容版权归原作者所有_

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⏱️ 2026-09-18 08:00