AlignBench
AlignBench is a comprehensive multi-dimensional benchmark for evaluating Chinese alignment of Large Language Models. It contains 8 main categories: Fundamental Language Ability, Advanced Chinese Understanding, Open-ended Questions, Writing Ability, Logical Reasoning, Mathematics, Task-oriented Role Play, and Professional Knowledge. The benchmark includes 683 real-scenario rooted queries with human-verified references and uses a rule-calibrated multi-dimensional LLM-as-Judge approach with Chain-of-Thought for evaluation.
Qwen2.5 72B Instruct from Alibaba Cloud / Qwen Team currently leads the AlignBench leaderboard with a score of 0.816 across 4 evaluated AI models.
What AlignBench measures
AlignBench is a text benchmark that evaluates large language models on reasoning, roleplay, general, language, math, writing, and creativity tasks. LLM Stats tracks 4 models on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.8, with the leader reaching 0.8.
Compare leaders on the best AI for reasoning, best AI for roleplay, best AI for general, best AI for language, best AI for math, best AI for writing and best AI for creativity leaderboards.
Publication
- Paper
- AlignBench: Benchmarking Chinese Alignment of Large Language Models
- Authors
- Xiao Liu, Xuanyu Lei, Shengyuan Wang, Yue Huang, and 14 others
- Published
- arXiv
- 2311.18743
Abstract
Alignment has become a critical step for instruction-tuned Large Language Models (LLMs) to become helpful assistants. However, the effective evaluation of alignment for emerging Chinese LLMs is still largely unexplored. To fill in this gap, we introduce AlignBench, a comprehensive multi-dimensional benchmark for evaluating LLMs' alignment in Chinese. We design a human-in-the-loop data curation pipeline, containing eight main categories, 683 real-scenario rooted queries and corresponding human verified references. To ensure the correctness of references, each knowledge-intensive query is accompanied with evidences collected from reliable web sources (including URLs and quotations) by our annotators. For automatic evaluation, our benchmark employs a rule-calibrated multi-dimensional LLM-as-Judge~\cite{zheng2023judging} approach with Chain-of-Thought to generate explanations and final ratings, ensuring high reliability and interpretability. All evaluation code, data, and LLM generations are available at \url{https://github.com/THUDM/AlignBench}. Since its release, AlignBench has been adopted by top (Chinese) LLMs for evaluating their alignment capabilities in Chinese, including ChatGLM, Qwen, DeepSeek, Yi, Baichuan, and Abab.
Qwen2.5 72B Instruct leads with 81.6%, followed by 
DeepSeek-V2.5 at 80.4% and Qwen2.5 7B Instruct at 73.3%.
Progress Over Time
Interactive timeline showing model performance evolution on AlignBench
AlignBench Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 73B | — | — | ||
| 2 | DeepSeek | 236B | — | — | ||
| 3 | Alibaba Cloud / Qwen Team | 8B | — | — | ||
| 4 | Alibaba Cloud / Qwen Team | 8B | — | — |
FAQ
Common questions about AlignBench.
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