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Bonsai 2 27B near-lossless compression model

The gist

PrismML released Ternary Bonsai 2 27B, a 5.9GB model keeping 98.2% of Qwen3.8 27B's benchmark score.
The tradeoff is uneven: vision and tool-calling lose the most.

How it unfolded

  1. Jul 15, 2026GIGAZINE reported the previous Bonsai 27B release, a smaller version of Qwen3.6-27B using only 3.9GB of memory and compatible with iPhones.
  2. Sep 17, 2026PrismML released Ternary Bonsai 2 27B, based on Qwen3.8 27B, with ternary {-1, 0, +1} weights, FP16 group-wise scaling, 1.76 effective bits per weight, a 5.9GB footprint, a 262K-token context window, multimodal text-and-image input, and an Apache 2.0 license.
  3. Sep 17, 2026PrismML reported the model scores 83.9 overall versus 85.4 for Qwen3.8 27B and 83.6 for Qwen3.6 27B, and said it is more than 9x smaller than its full-precision counterpart while retaining 98.2% of aggregate benchmark performance.

Sources

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