OpenBMB · Small Reasoning Model

MiniCPM5-2B

A dense 2.52B model, 1.98B excluding embeddings, over 42 layers with grouped-query attention at 16 query and 2 key-value heads, a 131,072-token context and an Apache-2.0 licence. On OpenBMB's own table it averages 53.9 against LFM2.5-2.6B at 33.2, Qwen3.5-2B at 28.0, Gemma-4-E2B-it at 24.6, Qwen3.5-4B at 51.1 and granite-4.2-3B at 42.7, with 86.5 on AIME 2025, 69.1 on LiveCodeBench and 70.8 on MMLU-Pro. Post-training used reinforcement learning and on-policy distillation, and the UltraData training corpus is open-sourced alongside. All comparisons vendor-reported.