LFM-1B-Math: Can Small Models Be Concise Reasoners?

Benchmark Model Rank Results
mathematical-reasoning-on-aime-2025LFM-1.3B-Distill (32K output budget)–Accuracy: 36.25
mathematical-reasoning-on-aime24LFM-1.3B-Distill (32K output budget)–Acc: 51.04
mathematical-reasoning-on-math-500LFM-1.3B-Distill (32K output budget)–Accuracy: 87.48
multiple-choice-question-answering-mcqa-on-gpqa-diamondLFM-1.3B-Distill (32K output budget)–Accuracy: 39.29