Directory / DeepEval
DeepEval
Verified
Pytest-oriented evaluation library for LLM systems.
DeepEval is an open-source evaluation framework with pytest-style metrics, datasets, and CI integration. Confident AI provides the commercial layer. Use it when verification is expressed as measurable agent outcomes.
- Model support
- Multi-model
- Deployment
- Self-hosted
- Open source
- Yes
- License
- Apache-2.0
- Pricing model
- Mixed
- Added / updated
- 19 Aug 2026 / 19 Aug 2026
www.deepeval.com · Docs · Source
Assessment
DeepEval suits teams that prefer pytest-style evaluation cases over YAML. Judge-model metrics need hold-out checks; they are not equivalent to a type checker. Promptfoo is the closest comparison for this workflow.
Strengths
- Apache-2.0 pytest-style workflow.
- Broad metric library.
- CI integration.
Limitations
- Judge-model metrics can be gamed.
- Confident AI is a separate commercial surface.
- Human review remains necessary.
Compare
- vs promptfoo : Two evaluation harnesses for software quality gates.