# Reasoning effort adaptation

Aleph Alpha's Kolibri is a hybrid reasoning model whose system prompt carries one sentence selecting no reasoning, low, medium or high effort. Because its supervised fine-tuning traces carried no effort labels, the team annotated each trace post hoc by its reasoning length relative to traces from the same dataset at the same judged difficulty, with a 2B student model reproducing a larger model's difficulty grades. Median reasoning length orders low below medium below high on 23 of 24 benchmarks; low keeps 96% of the high score at 35% of the length, and the released model keeps 98% at 76% of the completion tokens.

Aleph Alpha's Kolibri is a hybrid reasoning model whose system prompt carries one sentence selecting no reasoning, low, medium or high effort. Because its supervised fine-tuning traces carried no effort labels, the team annotated each trace post hoc by its reasoning length relative to traces from the same dataset at the same judged difficulty, with a 2B student model reproducing a larger model's difficulty grades. Median reasoning length orders low below medium below high on 23 of 24 benchmarks; low keeps 96% of the high score at 35% of the length, and the released model keeps 98% at 76% of the completion tokens.