Alle Evaluationen

AutomationBench-AA: Agentic SaaS Workflow Benchmark

A benchmark measuring agentic task completion across simulated SaaS application environments, scoring the share of each task's objectives completed without guardrail violations.
Beispielaufgaben ansehen

Veröffentlichung

Auf arXiv ansehen

AutomationBench

Daniel Shepard und Robin Salimans.

AutomationBench-AA

Gemini 4 Argon (High) erzielt bei AutomationBench-AA mit 77.5% das höchste Ergebnis, gefolgt von MiniMax-M3.1-Flash mit einem Ergebnis von 72.5% und Claude Sonnet 5.5 (Max, Default Fallback) mit einem Ergebnis von 71.8%

Erfüllte Ziele

Gemini 4 Argon (High) erzielt bei Erfüllte Ziele mit 93% das höchste Ergebnis, gefolgt von Claude Sonnet 5.5 (Max, Default Fallback) mit einem Ergebnis von 91% und Claude Opus 5.5 (Max, Default Fallback) mit einem Ergebnis von 90%

Durchschnittliche Regelverstöße pro Aufgabe

gpt-oss-20b (High) erzielt bei Durchschnittliche Regelverstöße pro Aufgabe mit 0.00 das niedrigste Ergebnis, gefolgt von Magistral Small 1.2 mit einem Ergebnis von 0.00 und Llama 4 Scout mit einem Ergebnis von 0.00

Ergebnis

AutomationBench-AA: Ergebnis

Share of task objectives completed with no guardrail violations · Higher is better · Benchmark developed by Zapier · Independently benchmarked by Artificial Analysis
No publicly available API

AutomationBench-AA: Ergebnis vs. Kosten pro Aufgabe

AutomationBench-AA score vs. average cost per task (USD)
Most attractive quadrant
Pareto line

Erfüllte Ziele

AutomationBench-AA: Erfüllte Ziele

Share of task objectives achieved, regardless of guardrail violations · Higher is better
No publicly available API

Regelverstöße

AutomationBench-AA: Ziele pro Regelverstoß

Total objectives completed per guardrail violation · Higher is better
No publicly available API

Aufschlüsselung nach Bereich

AutomationBench-AA: Erfüllte Ziele über Bereiche hinweg

Anteil der erreichten Aufgabenziele, unabhängig von Regelverstößen · Die Werte werden pro Bereich über die ausgewählten Modelle normalisiert; Grün zeigt das leistungsstärkste und Rot das schwächste ausgewählte Modell. Die Farben passen sich bei geänderter Auswahl an.

Aufschlüsselung nach App

AutomationBench-AA: Erfüllte Ziele über Apps hinweg

Anteil der erreichten Aufgabenziele, unabhängig von Regelverstößen · Die Werte werden pro App über die ausgewählten Modelle normalisiert; Grün zeigt das beste und Rot das schlechteste ausgewählte Modell. Die Farben passen sich bei geänderter Auswahl an.

Aufschlüsselung nach Aufgabe

AutomationBench-AA: Durchschnittliche Schritte pro Aufgabe

Durchschnittliche Modellschritte pro Aufgabe
No publicly available API

Token-Nutzung

AutomationBench-AA: Token-Nutzung

Für die Evaluation verwendete Token

Kosten

AutomationBench-AA: Kosten pro Aufgabe

Durchschnittliche Kosten pro Aufgabe (USD), aufgeschlüsselt nach Eingabe-, Cache-Treffer-, Cache-Schreib-, Reasoning- und Antwort-Token

Ergebnis vs. Veröffentlichungsdatum

AutomationBench-AA: Ergebnis vs. Veröffentlichungsdatum

Most attractive region

Beispielaufgaben

AutomationBench-AA verwendet einen privaten, zurückgehaltenen Aufgabensatz, der nicht veröffentlicht wird. Die folgenden Aufgaben sind öffentliche Beispiele.

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AutomationBench-AA: Agentic SaaS Workflow BenchmarkAutomationBench-AA: Agentic SaaS Workflow Benchmark

A benchmark measuring agentic task completion across simulated SaaS application environments, scoring the share of each task's objectives completed without guardrail violations.

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