DeepEval
8.3#1 in llm evaluation toolsFrom $200 a monthFree planWebAPILinuxmacOS
VisitDeepEval vs OpenAgent Eval
OpenAgent Eval
5.9#23 in ai agent evaluation toolsAPILinuxmacOSSelf-hosted
VisitWhat both publish
| Fact | DeepEval | OpenAgent Eval |
|---|---|---|
| Integrations | Listed integrations include LangChain, Pydantic AI, OpenAI Agents, LangGraph, AWS AgentCore, Strands, Google ADK, LlamaIndex, and CrewAI. | Documented LLM providers include OpenAI, Anthropic, Gemini, Groq, OpenRouter, Ollama, and a mock provider. |
| License | The repository and package identify DeepEval as Apache Software License 2.0. | The project is licensed under Apache License 2.0. |
| Local operation | DeepEval can run entirely locally without Confident AI or an account. | The project says it runs on the user's machine without telemetry or required network calls. |
| Metrics | The project advertises more than 50 metrics spanning quality, agents, RAG, conversations, safety, voice and multimodal use cases. | Built-in metrics cover retrieval, generation, latency, and token cost. |
| Purpose | DeepEval is an open-source LLM evaluation framework for building evaluation pipelines to test AI systems. | OpenAgent Eval is an open-source, local-first framework for evaluating RAG systems and AI agents. |
DeepEval plans
- DeepEvalFree
- FreeFree
- Starter$200 a month
- Team$2,000 a month
- EnterprisePriced on request
OpenAgent Eval plans
No prices published.
Pick DeepEval if…
DeepEval suits developers building repeatable AI evaluations in Python or CI/CD, especially those testing multiple modalities or agent workflows. Its free OS offering is for pre-production testing rather than production evaluation.
Pick OpenAgent Eval if…
It suits developers evaluating RAG systems or AI agents in Python-based test suites. Local and offline operation fits teams that want data to remain on their machines.