Benchmarking Vietnamese Legal Knowledge of Large Language Models

The rapid advancement of large language models (LLMs) has expanded their potential in the legal domain. However, existing legal benchmarks remain largely English-centric and oriented toward common law, leaving a critical gap in evaluating LLMs for civil law systems that govern most jurisdictions worldwide. To address this gap, we introduce Vietnamese Legal Benchmark VietLegal, a cognitively grounded benchmark designed for the hierarchical and codified structure of Vietnamese law. Although instantiated in Vietnamese legislation, VietLegal provides a replicable evaluation framework for civil law systems characterized by complex statutory hierarchies and frequent amendments. Inspired by Bloom’s taxonomy, VietLegal assesses multiple levels of legal understanding through tasks that mirror real-world legal assistant use cases, including legal question answering, multi-step reasoning, and scenario-based problem solving. The benchmark contains 10,450 expert-annotated samples, each cross-validated against authoritative legal sources to ensure fidelity to practical legal workflows. By offering the first standardized legal benchmark for Vietnamese, VietLegal enables systematic assessment of LLMs in civil law contexts and supports the development of more reliable and interpretable AI-assisted legal systems.