PrismML unveils Bonsai 2 27B, compresses Alibaba's Qwen3.8 27B to 5.9 GB for smartphones, retaining 98.2% of Qwen benchmark scores (Julie Bort/TechCrunch)
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| Source: Techmeme | Original article
PrismML's Bonsai 2 27B compresses Alibaba's Qwen3.8 27B model to 5.9 GB—small enough for smartphones—while preserving 98.2% of its benchmark performance.
PrismML has launched Bonsai 2 27B, a heavily compressed version of Alibaba’s Qwen 3.8 27B model. The new model fits into a 5.9 GB memory footprint – small enough to run on modern smartphones – while preserving 98.2 % of Qwen’s benchmark scores, according to a TechCrunch report by Julie Bort.
The breakthrough hinges on PrismML’s proprietary compression pipeline, which squeezes the 27‑billion‑parameter Qwen model without the dramatic loss of accuracy that typically accompanies such size reductions. By delivering near‑full performance in a mobile‑friendly package, Bonsai 2 27B could broaden access to high‑end language capabilities, enabling on‑device assistants, offline translation, and privacy‑preserving applications that previously required cloud‑based inference.
This release builds on the story we covered on 18 September 2026, when we first introduced Bonsai 2 27B’s ability to pack a 27 B model into 5.9 GB. The new data point – a 98.2 % retention of benchmark scores – confirms that the compression is not merely a proof of concept but a viable product ready for deployment.
What to watch next is how quickly developers adopt Bonsai 2 27B for edge use cases and whether other AI labs will follow suit with similar compression techniques. Industry observers will also be keen to see performance on real‑world tasks, potential licensing arrangements with Alibaba, and any subsequent hardware optimisations that could push the model’s footprint even lower. If the model lives up to its promise, it may accelerate a shift toward on‑device AI across the Nordic market and beyond.
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