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

תקציר מקורי באנגליתOpenBMB has released MiniCPM5-2B , the second checkpoint in the MiniCPM5 series and the follow-up to MiniCPM5-1B . It is a dense causal language model with 2,516,756,480 parameters, of which 1,981,982,720 sit outside the embeddings. It uses 42 layers, grouped-query attention with 16 query heads and 2 key/value heads, and a native context window of 131,072 tokens. The architecture is standard LlamaForCausalLM , so mainstream engines load it with no custom kernels and no model-code fork. Is it deployable? Yes. The weights are Apache 2.0 and run through vLLM, SGLang, Transformers, llama.cpp, Ollama, LM Studio, MLX and FlagOS. What the benchmark table actually shows OpenBMB compares MiniCPM5-2B against LFM2.5-2.6B, Qwen3.5-2B and Gemma-4-E2B-it in the same size class, and lists Qwen3.5-4B, gra