Chinese Grammatical Error Correction (CGEC) aims to correct errors in Chinese text with minimal edits.When applied to grammatical error correction,Large Language Models (LLMs) often mistakenly apply erroneous correction patterns to similar sentences or tend to over-correct.To address these issues,this paper proposes a Multi-Perspective Coordination LLM Method (Multi-PC) for CGEC.Unlike conventional LLM decoding,which focuses only on local token-level confidence,Multi-PC considers all tokens in a sentence to holistically assess grammatical issues.It leverages reasoning results from multiple perspectives of LLMs and recalculates the overall sentence confidence using a sequence joint probability method that excludes irrelevant tokens,ultimately inferring a globally credible correction.This method requires no additional training cost and can effectively mitigate over-correction and incorrect pattern matching.Experimental results on CGEC datasets demonstrate that the proposed method is both simple and effective.