AgentBench vs OpenAI Evals

Side-by-side comparison of two AI agent tools

Short answer

  • AgentBench has had no commit in 7 months; OpenAI Evals is actively maintained.
  • OpenAI Evals is growing faster: +230 GitHub stars in the last 30 days vs +76 for AgentBench.
  • Pick AgentBench for: a Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24). Pick OpenAI Evals for: evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

From GitHub data refreshed daily.

AgentBenchopen-source

A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

Metrics

AgentBenchOpenAI Evals
Stars3.8k19.5k
Star velocity /mo76.42105263157895230.21052631578948
Commits (90d)00
Releases (6m)00
Downloads (30d, npm + PyPI)—376
Overall score0.254392725652189570.31275929417567333

Pros

  • +Comprehensive evaluation across five diverse task domains with standardized metrics and reproducible containerized environments
  • +Function-calling integration with AgentRL framework enables end-to-end agent training and sophisticated multiturn interactions
  • +Active research community with public leaderboard, Slack workspace, and ongoing collaboration for benchmark improvements
  • +提供完整的LLM评估框架,包含丰富的预置基准测试注册表
  • +支持自定义评估开发,可针对特定业务场景和用例进行定制
  • +现在可直接在OpenAI Dashboard中运行,也支持本地部署,使用灵活

Cons

  • -Complex setup requiring multiple Docker images and external data dependencies like Freebase database
  • -Primarily research-focused with limited documentation for production deployment scenarios
  • -Resource-intensive containerized environment may require significant computational resources for full evaluation
  • -需要OpenAI API密钥和相关费用,运行评估可能产生不小的成本
  • -使用Git-LFS存储评估数据,增加了初始设置的复杂性
  • -主要针对OpenAI模型优化,对其他LLM供应商的支持可能有限

Use Cases

  • •Research teams evaluating and comparing different LLM agent architectures across standardized benchmark tasks
  • •AI companies developing autonomous agents who need systematic performance assessment before deployment
  • •Academic institutions studying agent capabilities in interactive environments, databases, and web-based scenarios
  • •测试不同OpenAI模型版本对特定业务工作流程的影响和性能差异
  • •为领域特定的LLM应用构建自定义基准测试和评估指标
  • •使用企业私有数据创建内部评估套件,而不暴露敏感信息

FAQ

Which is more popular, AgentBench or OpenAI Evals?
OpenAI Evals has more GitHub stars (19,548 vs 3,759).
Which is more actively developed, AgentBench or OpenAI Evals?
AgentBench had more commits in the last 90 days (0 vs 0).
Should I use AgentBench or OpenAI Evals?
Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.