The Allen Institute for Artificial Intelligence (AI2) has released an open-source large language model OLMoE, aimed at providing high performance and low-cost solutions. This model employs a Sparse Mixture of Experts (MoE) architecture with 7 billion parameters, but through an intelligent routing mechanism, only 1 billion parameters are used per input token, achieving efficient computation. OLMoE includes both general and instruction-tuned versions, supporting a context window of 4096 tokens. Its training data is sourced from a wide range, including Common Crawl, Dolma CC, and Wikipedia.