MAmmoTH

Math-specialized models: Trained on a curated math instruction-tuning dataset covering arithmetic, algebra, calculus, and contest-style problems.

Beats existing open math LLMs: Outperforms prior open-source math LLMs across a range of mathematical reasoning benchmarks at comparable parameter counts.

CoT + PoT hybrid data: Training data mixes chain-of-thought and program-of-thought traces, teaching the model both natural-language and code-aided reasoning.

Open family: Released in multiple sizes to let researchers study math-LLM scaling laws in the open-source ecosystem.