Arena 发布 Alignment Index，GPT-6.1-Sol 以 87.9 分居首

隆重推出 Arena Alignment Index，这是我们全新的基准，用于衡量 AI 智能体在真实使用中的安全性与对齐表现。 该指数基于 27 个模型、超过 9 万次真实智能体会话构建，衡量三项关键信号： - 越权行动（UA）：采取超出用户指令或权限范围的行动 - 错误归因（FA）：将陈述或行动归因于与用户提供的证据相矛盾的内容 - 虚假完成（DC）：声称任务已完成，而实际上并未完成。 主要发现： - OpenAI 模型目前在 Alignment Index 中领先 - 越界行为较为罕见，但一旦发生可能带来严重后果 - 智能体可能在任务进度上误导用户 - 错位风险随对话长度增加而上升 - 安全性与对齐表现正随着模型代际更迭而改善 如下方排行榜所示（按实验室排序），@OpenAI 的 GPT-6.1-Sol 以 87.9 分领跑 Arena Alignment Index，紧随其后的是 @AnthropicAI 的 Claude-Opus-5.5（83.2 分）和 @SpaceXAI 的 Grok-4.7（82.7 分）。OpenAI 在三项信号上的观测率也均为最佳：越权行动 0.89%、错误归因 1.98%、虚假完成 2.34%。 在全部四家实验室中，较新的模型始终优于其前代模型，这表明智能体安全性与对齐方面取得了广泛进展。随着智能体承担更长、更复杂、风险更高的任务，衡量它们不仅能完成什么，还能以多安全和多可靠的方式行动，正变得越来越重要。 这标志着在让安全性与对齐成为 Arena 评估 AI 的核心组成部分方面迈出了重要一步。该指数只是一个初步起点，我们将随着时间推移，持续用更多安全信号和模型来扩展这一指数。 更多分析见下方👇

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Introducing the Arena Alignment Index, our new benchmark measuring safety and alignment of AI agents in real-world use. Built from 90K+ real-world agent sessions across 27 models, the index measures three critical signals: - Unauthorized Action (UA): Taking actions beyond the user's instructions or permissions - False Attribution (FA): Attributing statements or actions that are contradicted by user-provided evidence - Deceptive Completion (DC): Claiming a task was completed when it was not. Key findings: - OpenAI models currently lead the Alignment Index - Rogue actions are rare, but can have serious consequences when they occur - Agents can mislead users about task progress - Misalignment risks increase with conversation length - Safety and alignment are improving across model generations As shown in the leaderboard below (sorted by lab), @OpenAI’s GPT-6.1-Sol leads the Arena Alignment Index with a score of 87.9, followed by @AnthropicAI’s Claude-Opus-5.5 at 83.2 and @SpaceXAI's Grok-4.7 at 82.7. OpenAI also has the best observed rates across all three signals: 0.89% Unauthorized Action, 1.98% False Attribution, and 2.34% Deceptive Completion. Across all four labs, newer models consistently outperform their predecessors, suggesting broad progress in agent safety and alignment. As agents take on longer, more complex, and higher-stakes tasks, measuring not just what they can accomplish, but how safely and reliably they act, becomes increasingly important. This marks an important step toward making safety and alignment a core part of how Arena evaluates AI. The index is an initial starting point, and we'll continue expanding the index with additional safety signals and models over time. More analysis below👇