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PrismML's Bonsai-27B model achieves 99.2% on the Math 500 dataset, outperforming DeepSeek-R1 and Kimi K2.
This study introduces section-aware compression for reasoning traces, training models to drop filler narration while preserving compute and verification spans, matching or exceeding original accuracy while using 2-3 times fewer tokens.