The invention discloses a semantic fuzzy search method based on a sentence-level deep learning language model. According to the method, the fuzzy degree is high, a deep learning language model is introduced, the semantic problem is fully considered, statements with high semantic similarity with target statements can be retrieved, and the semantic similarity between the statements is efficiently judged in a layered semantic similarity calculation mode; the operation speed is high, vectorization processing is used for replacing a conventional text cyclic traversal processing mode, all semantic matching task units are ensured to be processed in parallel, and the search speed is greatly increased; the search recall ratio is high, and implication indexes are utilized, so that the robustness ofthe system to grammar interference is better, and the search recall ratio is effectively improved; the system is flexible, the mechanisms of semantic comprehension, fuzzy query, accurate information positioning and the like are fused, and then the whole algorithm module is subjected to interface encapsulation, so that convenience is brought to a user to call.