DeepEval vs Ragas
DeepEval
deepeval.com
Ragas
ragas.ioSide by side
| Figure | DeepEval | Ragas |
|---|---|---|
| Price from | $200/mo | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 5 | 0 |
| Spec score · AI LLM Evaluation Tools | 9.4 (#1) | 7.2 (#26) |
| Spec score · LLM Evaluation Tools | 9.3 (#1) | 7.2 (#23) |
| Spec score · Llm Developer Tools | 9.3 (#1) | 7.1 (#22) |
| Customization | Metrics, prompts, judge models and evaluation templates can be customized. | Ragas documents options to customize metrics, test set generation, prompts, and model configuration. |
| Framework integrations | Official integrations include LangChain, LlamaIndex, CrewAI, OpenAI Agents, LangGraph, PydanticAI, Google ADK, AgentCore, Strands and OpenTelemetry. | Documented framework integrations include LangChain, LlamaIndex, Haystack, Griptape, and others. |
| Integrations | Listed integrations include LangChain, Pydantic AI, OpenAI Agents, LangGraph, AWS AgentCore, Strands, Google ADK, LlamaIndex, and CrewAI. | The documentation lists integrations with Arize, LangSmith, Amazon Bedrock, Google Gemini, OCI Gen AI, LangChain, LangGraph, LlamaIndex, and other frameworks. |
| Metrics | The project advertises more than 50 metrics spanning quality, agents, RAG, conversations, safety, voice and multimodal use cases. | Users can use available evaluation metrics or create custom metrics. |
| Model providers | Evaluation model integrations include OpenAI, Azure OpenAI, Ollama, OpenRouter, Anthropic, Amazon Bedrock, Gemini, DeepSeek, Vertex AI, Grok, Moonshot, Portkey, vLLM, LM Studio, and LiteLLM. | The quick start documents use with OpenAI, Anthropic, Google Gemini, Ollama, and OpenAI-compatible providers. |
| Purpose | DeepEval is an open-source LLM evaluation framework for building evaluation pipelines to test AI systems. | Ragas is a library for systematically evaluating AI and large language model applications. |
| Synthetic data | DeepEval includes synthetic dataset generation for difficult-to-collect edge cases. | The product site says Ragas can synthetically generate diverse evaluation data customized for user requirements. |
Plans
DeepEval
- DeepEvalFree
- FreeFree
- Starter$200 a month
- Team$2,000 a month
- EnterprisePriced on request
In their own words
DeepEval
DeepEval is a free, open-source framework for building evaluation pipelines to test AI systems. Its Pytest-native evaluations run in CI/CD or as Python scripts, and the framework lists more than 50 research-backed metrics, including checks for hallucination, faithfulness, answer relevancy, summarization, toxicity and bias. It evaluates text, images and audio, including conversational and voice interactions, using methods such as G-Eval, DAG, QAG and JevEval. DeepEval can generate synthetic goldens from a knowledge base and model conversations across user personas. It also traces agent steps so they can be graded and inspected in a terminal or test runner. Integrations cover agent frameworks including LangChain, Pydantic AI, OpenAI Agents, LangGraph, LlamaIndex and CrewAI, alongside a range of model providers. By default, it sends basic telemetry to PostHog, excluding personally identifiable information and stored results; users can opt out with an environment variable. The maker describes DeepEval OS as for pre-production testing, with results in local files and an engineer-owned test runner. Enterprise capabilities are offered through Confident AI Evals, with self-hosted or maker-cloud deployment options.