The GLM 5.2 large language model has reached a new milestone by demonstrating accuracy in accounting tasks that closely approaches the capability of a human accountant. According to recent tests on the VAT (Value Added Tax) benchmark, this model proved its ability to handle complex professional tasks with extremely low error rates. This is considered a notable step forward in applying AI to high-precision fields such as finance and auditing.
Background & Causes
The accounting and tax industry has long been a major challenge for large language models due to strict data structures, constantly changing legal regulations, and the absolute requirement for zero errors. Previous tests with older generation AI models often suffered from hallucination, leading to incorrect calculations. GLM 5.2's high score on the VAT benchmark indicates that developers have focused on solving specialized data optimization and refining logical reasoning workflows.
Technical Analysis & Technology
To achieve human-like accuracy, GLM 5.2 is believed to have optimized its chain-of-thought reasoning architecture combined with external computing tools to mitigate arithmetic errors. The model's ability to understand invoice contexts, match VAT tax codes, and apply complex cost allocation rules has significantly improved. However, experts note that benchmarks are still static testing environments, which differ from the dynamic and heterogeneous nature of real-world documents.
Expert Opinions & Perspectives
Although the test results are very promising, technology analysts remain cautious about AI's ability to completely replace humans in the short term. Many believe that systems like GLM 5.2 should be operated as co-pilots for cross-checking rather than being granted full legal decision-making authority. The role of humans in final approval and legal liability before tax authorities remains mandatory.
Impact & Future
The development of GLM 5.2 opens up opportunities to reduce administrative burdens for small and medium-sized enterprises, where accounting departments are often overloaded during tax settlement periods. In Vietnam, the trend of invoice digitization and electronic tax filing will provide fertile ground for specialized AI models like this to deeply integrate into enterprise resource planning (ERP) systems in the coming years.