Rohan Paul@rohanpaul_ai · XArena 的 AI 排行榜从 UC Berkeley 研究项目起步，通过让用户匿名对比两个模型答案并投票，积累了大规模人类偏好数据集。该平台随后将这一公开测试引擎包装为商业服务 AI Evaluations，为客户提供更深入的分析。模型厂商迫切需要高质量的人类偏好信号，因为微小的排名提升就能决定用户选择、企业合同和投资者关注。如今 Arena 已成为年化收入 1 亿美元的业务。
Arena's AI leaderboard has become a $100M annualized revenue business.
By turning public model comparisons into paid performance testing for AI labs and enterprises.
Arena began as a UC Berkeley research project that asked users to compare 2 anonymous model answers and vote for the better one.
That setup created a large human preference dataset， because every vote says something about what people value in AI responses.
Model labs care about those votes because benchmarks alone often miss the messy cases where users judge tone， reasoning， code quality， visual skill， or task completion.
Arena's commercial move was to package that public testing engine into AI Evaluations， a service that gives customers deeper analytics from the same community feedback loop.