战略与运营指数
评估模型在战略与运营领域的表现。评估的能力包括商业与管理、会计、企业与市场等领域知识,以及战略与规划、客户支持、记录管理等。
查看代表性工作流The Artificial Analysis Strategy & Ops Index combines performance across benchmarks chosen for strategy, operations, and office administration. We map common tasks from O*NET occupational classifications, then select benchmarks that represent this real-world work. Weights are derived from how often capabilities appear across those tasks.
This composite metric provides a single score for tracking model performance across operations and administrative work. 所有底层基准测试均由 Artificial Analysis 独立运行。有关评测的实施方式,请参阅我们的智能基准测试方法论。
| 能力 | 权重 | 评测 |
|---|---|---|
| 智能体知识工作 | 35% | GDPval-AA v2.1和AA-Briefcase v1.1 |
| 商业知识 | 30% | AA-Omniscience 商业准确率 |
| 智能体工具使用 | 30% | AutomationBench-AA 运营、人力资源、营销、销售和支持 |
| 长上下文 | 5% | LCR和GDP.pdf |
得分
Artificial Analysis 战略与运营指数
Artificial Analysis 战略与运营指数:能力明细
能力明细
Artificial Analysis 战略与运营指数:商业知识
代表性工作流
这些真实工作流重点检验 战略与运营指数 中权重最高的能力。
示例:Assess a mid-market SaaS company's competitive position from market-share data, analyst reports, and win/loss notes, work through a Porter's Five Forces and SWOT read, and formulate three prioritized strategic options with the trade-offs of each.
示例:Scan 3,000 invoices of different formats before month-end and extract line-items into structured fields to add to the general ledger.
示例:Absorb a 40% support surge after a product recall in a CRM ticketing queue with 20-minute hold times to triage incoming tickets by SLA, de-escalate frustrated customers in live chat, and follow the approved recall script verbatim.
示例:Reconcile an executive's schedule when they're triple-booked across a full week of calendars in a scheduling tool, including external stakeholders with limited availability, to weigh free/busy windows, propose conflict resolutions ranked by stakeholder seniority, and draft rescheduling notes.
示例:Clean up a stalled month-end close where multiple departments coded the same expenses to different GL accounts across hundreds of invoices to propose a consistent chart-of-accounts mapping, identify entries needing reclassification, and draft adjusting journal entries.
示例:Consolidate five years of training records split across paper files and two unindexed document systems for a regulatory request to build one audit-ready manifest, flag missing records with supporting evidence, and propose a retention schedule for the next cycle.
成本
Artificial Analysis 战略与运营指数:单任务成本
Artificial Analysis 战略与运营指数 与单任务成本
速度
Artificial Analysis 战略与运营指数:单任务耗时
输出 token
Artificial Analysis 战略与运营指数:单任务输出 token
发布日期
Artificial Analysis 战略与运营指数 与发布日期
常见问题
根据 Artificial Analysis 战略与运营指数,目前在战略与运营工作上表现最佳的 AI 模型是 Claude Opus 5.5 (Max, Default Fallback) (64)、Claude Opus 5.5 (Xhigh, Default Fallback) (62)和Claude Fable 5.1 (Max, Default Fallback) (60)。新模型发布后,排行榜会随之更新。
有。Artificial Analysis 战略与运营指数 是一项独立基准测试,用于衡量 AI 模型在战略与运营工作上的表现。它评估商业知识、智能体知识工作、在业务应用中的智能体工具使用以及长上下文分析等能力。
战略与运营指数 是 Artificial Analysis 推出的综合基准测试,用于评估模型在战略与运营领域的表现。评估能力包括商业与管理、会计、企业与市场等专业知识,以及战略与规划、客户支持、档案管理等。
战略与运营指数 按各项能力子分数的加权平均值计算。各项子分数及其权重为:商业知识 (30%)、智能体知识工作 (35%)、智能体工具使用 (30%)和长上下文 (5%)。
战略与运营指数 包含 AA-Omniscience 商业准确率、GDPval-AA v2.1、AA-Briefcase v1.1、AutomationBench-AA 运营、人力资源、营销、销售和支持、LCR和GDP.pdf。
在已公布结果的模型中,Claude Opus 5.5 (Max, Default Fallback) 目前以 64 分位居 战略与运营指数 榜首。 查看模型
战略与运营指数 得分越高,表示模型在构成该指数的各项基准测试中整体表现越强。对于特定用例,单项基准测试结果可能比综合得分更具参考价值。