OpenAI Evals vs Mastra
Side-by-side comparison of two AI agent tools
Short answer
- Mastra is growing faster: +968 GitHub stars in the last 30 days vs +230 for OpenAI Evals.
- Pick OpenAI Evals for: evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks. Pick Mastra for: from the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents.
From GitHub data refreshed daily.
OpenAI Evalsfree
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Mastrafree
From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.
Metrics
| OpenAI Evals | Mastra | |
|---|---|---|
| Stars | 19.5k | 28.5k |
| Star velocity /mo | 230.21052631578948 | 968.3684210526316 |
| Commits (90d) | 0 | 4.1k |
| Releases (6m) | 0 | 10 |
| Downloads (30d, npm + PyPI) | 376 | 3.1M |
| Overall score | 0.31275929417567333 | 0.8983723604743185 |
Pros
- +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
- +统一的多提供商接口支持 40+ AI 模型提供商，避免供应商锁定
- +完整的 AI 应用工具链包括代理、工作流、人机交互和上下文管理
- +TypeScript 原生支持和现代技术栈集成，开发体验优秀
Cons
- -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
- -作为相对较新的框架，生态系统和社区资源可能有限
- -多功能集成可能带来学习曲线，需要时间掌握各个组件
- -文档和最佳实践可能还在完善中，缺少大规模生产案例
Use Cases
- •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
- •构建需要多个 AI 模型协作的复杂智能代理系统
- •开发需要人机交互审批流程的自动化工作流应用
- •快速原型验证 AI 产品概念并扩展到生产环境
FAQ
- Which is more popular, OpenAI Evals or Mastra?
- Mastra has more GitHub stars (28,525 vs 19,548).
- Which is more actively developed, OpenAI Evals or Mastra?
- Mastra had more commits in the last 90 days (4,109 vs 0).
- Should I use OpenAI Evals or Mastra?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.