Skip to main content
PaperAI Agentsv1.0

AgentBench: Evaluating LLMs as Agents

by Tsinghua University · free · Last verified 2026-03-17

Introduces AgentBench, the first systematic benchmark for evaluating LLMs as autonomous agents across eight distinct environments spanning operating systems, databases, knowledge graphs, digital games, and web browsing. The benchmark reveals a large performance gap between commercial and open-source models on real-world agent tasks.

https://arxiv.org/abs/2308.03688
B
BAbove Average
Adoption: B+Quality: AFreshness: BCitations: AEngagement: F

Specifications

License
Apache-2.0
Pricing
free
Capabilities
agent-evaluation, multi-environment, benchmarking, tool-use-assessment
Integrations
Use Cases
agent-evaluation, research, model-comparison
API Available
No
Tags
benchmark, agents, evaluation, tool-use, multi-environment
Added
2026-03-17
Completeness
100%

Index Score

68.4
Adoption
78
Quality
86
Freshness
65
Citations
80
Engagement
0

Put AI to work for your business

Deploy this paper alongside autonomous AaaS agents that handle tasks end-to-end — no babysitting required.

Explore the full AI ecosystem on Agents as a Service