OpenBMB Releases MiniCPM5-2B: A 2.52B Dense Model Averaging 53.9 Across 34 Benchmarks and Built to Run On Device

MarkTechPostSeptember 7, 2026en

MarkTechPost

AI Global Wire

OpenBMB has released MiniCPM5-2B, a dense causal language model with 2,516,756,480 parameters and a native 131,072 token context. It averages 53.9 across the 34 benchmarks in its model card, ahead of Qwen3.5-4B at 51.1, with its clearest leads in tool use, coding agents and long-context retrieval. Post-training pairs 400B tokens of deep-thinking SFT with RL teachers and on-policy distillation that merges 16 expert models into one checkpoint. The weights ship under Apache 2.0 alongside the pre-training, SFT and RL datasets and the intermediate Base, Midtrain and SFT-only checkpoints. GGUF builds start at 1.56 GB, and the standard LlamaForCausalLM architecture loads in vLLM, SGLang, llama.cpp,

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