Opik vs Promptfoo
Side-by-side comparison of two AI agent tools
Short answer
- Promptfoo is growing faster: +1,110 GitHub stars in the last 30 days vs +606 for Opik.
- Pick Opik for: debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive. Pick Promptfoo for: open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps.
From GitHub data refreshed daily.
Opikopen-source
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Promptfooopen-source
Open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps
Metrics
| Opik | Promptfoo | |
|---|---|---|
| Stars | 22.3k | 25.7k |
| Star velocity /mo | 606 | 1.1k |
| Commits (90d) | 1.1k | 920 |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 160.4K | 3.0M |
| Overall score | 0.8395960884989896 | 0.8639349362705032 |
Pros
- +提供端到端的 AI 应用可观测性，包括详细的链路追踪和性能监控，帮助开发者快速定位问题
- +支持自动化评估和优化，能够自动改进提示词和工具配置，降低手动调优的工作量
- +完全开源且拥有活跃社区支持，提供灵活的部署选项和定制化能力
- +Comprehensive testing suite covering both performance evaluation and security red teaming in a single tool
- +Multi-provider support with easy comparison between OpenAI, Anthropic, Claude, Gemini, Llama and dozens of other models
- +Strong CI/CD integration with automated pull request scanning and code review capabilities for production deployments
Cons
- -作为相对较新的工具，可能在某些企业级功能和集成方面还需要进一步完善
- -学习曲线可能较陡，需要开发者具备一定的 AI 应用开发和监控经验
- -Requires API keys and credits for multiple LLM providers, which can become expensive for extensive testing
- -Command-line focused interface may have a learning curve for teams preferring GUI-based tools
- -Limited to evaluation and testing - does not provide actual LLM application development capabilities
Use Cases
- •RAG 聊天机器人的性能监控和优化，追踪检索质量和回答准确性
- •代码助手应用的链路分析，监控代码生成质量和响应时间
- •复杂智能体工作流的调试和评估，跟踪多步骤推理过程的执行效果
- •Automated testing and evaluation of prompt performance across different models before production deployment
- •Security vulnerability scanning and red teaming of LLM applications to identify potential risks and compliance issues
- •Systematic comparison of model performance and cost-effectiveness to optimize AI application architecture
FAQ
- Which is more popular, Opik or Promptfoo?
- Promptfoo has more GitHub stars (25,665 vs 22,349).
- Which is more actively developed, Opik or Promptfoo?
- Opik had more commits in the last 90 days (1,062 vs 920).
- Should I use Opik or Promptfoo?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.