---
title: "PrismML shrinks a 27B model to 5.9GB with little quality loss"
url: https://www.parallelquant.com/posts/prismml-shrinks-a-27b-model-to-5-9gb-with-little-quality-loss-9f02b2
source_name: "MarkTechPost"
source_url: https://www.marktechpost.com/2026/09/18/prismml-releases-ternary-bonsai-2-27b-a-5-9-gb-apache-2-0-model-retaining-98-2-of-qwen3-8-27b-performance/
published: 2026-09-18T18:06:36.000Z
topics: ["open source", "llms"]
publisher: "Parallel Quant"
---

# PrismML shrinks a 27B model to 5.9GB with little quality loss

*2026-09-18 · Source: [MarkTechPost](https://www.marktechpost.com/2026/09/18/prismml-releases-ternary-bonsai-2-27b-a-5-9-gb-apache-2-0-model-retaining-98-2-of-qwen3-8-27b-performance/)*

PrismML released Ternary Bonsai 2 27B, a ternary-weight compressed version of Qwen3.8 27B that occupies 5.93GB versus 53.80GB for the FP16 original, while retaining 98.2% of the parent model's average performance across 20 benchmarks. It handles text and images with a 262K-token context, released under Apache 2.0.

**Why it matters:** Roughly 9x compression with minimal quality loss is significant for running capable models on consumer hardware, extending a broader trend toward extreme quantization that makes frontier-adjacent capability accessible outside data centers.

**Topics:** open source, llms

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Read the original: https://www.marktechpost.com/2026/09/18/prismml-releases-ternary-bonsai-2-27b-a-5-9-gb-apache-2-0-model-retaining-98-2-of-qwen3-8-27b-performance/
Canonical: https://www.parallelquant.com/posts/prismml-shrinks-a-27b-model-to-5-9gb-with-little-quality-loss-9f02b2
Published by Parallel Quant — https://www.parallelquant.com