Patronus AI vs Promptfoo
A side-by-side comparison of Patronus AI and Promptfoo, two Eval tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Patronus AI | Promptfoo |
|---|---|---|
| Category | Eval | Eval |
| Pricing (differs) | FREEMIUM | FREE |
| License (differs) | Proprietary | Open source |
| Deployment (differs) | Cloud | — |
| Platforms (differs) | Web, API | CLI, macOS, Windows, Linux |
| Model support (differs) | Self-contained (on-device) | BYO key / model |
| Vendor (differs) | Patronus AI | Promptfoo |
The honest brief
Patronus AI
Ships trained evaluator models (Lynx, GLIDER, Percival) rather than only prompt-based LLM-judge scoring.
- Research-backed Lynx, GLIDER, and Percival models
- Covers hallucination, judging, and agent-trace debug
- Self-serve API with free credits
- Guardrails + monitoring across the lifecycle
- Cloud-only; no self-host
- Usage-based pricing can be opaque at scale
- Smaller OSS footprint than open eval tools
Promptfoo
Define evals in plain YAML and run one goldset across models in CI — a prompt regression fails the build like any other test.
- YAML-driven, version-controllable evals
- Runs in CI, model-agnostic
- Goldsets and rubric scoring
- Also does red-teaming/security scans
- CLI-first, less of a hosted UI
- Teams may want managed dashboards
- Config sprawl on large eval suites