OpenAI Evals vs Langfuse

Side-by-side comparison of two AI agent tools

Short answer

  • Langfuse is growing faster: +1,812 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 Langfuse for: open-source LLM engineering platform for observability, evaluation, prompt and dataset management.

From GitHub data refreshed daily.

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

Langfuseopen-source

Open-source LLM engineering platform for observability, evaluation, prompt and dataset management

Metrics

OpenAI EvalsLangfuse
Stars19.5k35.3k
Star velocity /mo230.476190476190481.8k
Commits (90d)02.0k
Releases (6m)010
Overall score0.32547997031838470.9067292616632036

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
  • +Open source with MIT license allowing full customization and transparency, plus active community support
  • +Comprehensive feature set combining observability, prompt management, evaluations, and datasets in one platform
  • +Extensive integrations with major LLM frameworks and tools including OpenTelemetry, LangChain, and OpenAI SDK

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
  • -May require significant setup and configuration for self-hosted deployments
  • -Could be overwhelming for simple use cases that only need basic LLM monitoring
  • -Self-hosting requires technical expertise and infrastructure resources

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
  • •Production LLM application monitoring to track performance, costs, and identify issues in real-time
  • •Prompt engineering and management for teams collaborating on optimizing model prompts and tracking versions
  • •LLM evaluation and testing to measure model performance across different datasets and use cases

FAQ

Which is more popular, OpenAI Evals or Langfuse?
Langfuse has more GitHub stars (35,301 vs 19,542).
Which is more actively developed, OpenAI Evals or Langfuse?
Langfuse had more commits in the last 90 days (2,007 vs 0).
Should I use OpenAI Evals or Langfuse?
Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.