ARES
5.6#21 in llm evaluation toolsAPILinuxSelf-hosted
VisitARES vs DeepEval
What both publish
| Fact | ARES | DeepEval |
|---|---|---|
| License | The GitHub repository identifies its license as Apache-2.0. | The repository and package identify DeepEval as Apache Software License 2.0. |
| Model integrations | The README gives examples using OpenAI and TogetherAI API keys and shows local model execution with vLLM. | Supported judge-model providers include OpenAI, Azure OpenAI, Ollama, OpenRouter, Anthropic, Bedrock, Gemini, DeepSeek, Vertex AI, Grok, Moonshot, Portkey, vLLM, LM Studio and LiteLLM. |
| Purpose | ARES is an automated framework for evaluating retrieval-augmented generation (RAG) systems. | DeepEval is an open-source LLM evaluation framework for building evaluation pipelines to test AI systems. |
ARES plans
No prices published.
DeepEval plans
- DeepEvalFree
- FreeFree
- Starter$200 a month
- Team$2,000 a month
- EnterprisePriced on request
Pick ARES if…
It suits teams evaluating RAG quality, custom retrieval systems, or competing RAG configurations. It is appropriate for users able to provide evaluation datasets and self-host the required compute.
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.