Promptfoo vs Galileo
Detailed side-by-side comparison to help you choose the right tool
Promptfoo
🔴DeveloperAI Evaluation
Open-source CLI and library for testing, evaluating, and red-teaming LLM prompts, models, and RAG pipelines — runs locally on your machine or in CI.
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FreeGalileo
🔴DeveloperAI Evaluation
Galileo review 2026: enterprise AI evals, observability, guardrails, and Luna evaluator models for RAG and agents — features, pricing, pros, cons.
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CustomFeature Comparison
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Promptfoo - Pros & Cons
Pros
- ✓Truly local — prompts and datasets never leave your machine
- ✓MIT licensed core means no vendor lock-in or runtime cost
- ✓Red-team mode generates real OWASP-aligned attack suites automatically
- ✓Excellent provider coverage including Bedrock, Vertex, and self-hosted models
- ✓Config-as-code fits cleanly into existing CI/CD pipelines
Cons
- ✗YAML configs get unwieldy for very large eval suites without discipline
- ✗LLM-as-judge assertions can be flaky without careful grader prompts
- ✗Cloud tier pricing is not transparent on the public site
- ✗Web UI is meant for local inspection, not multi-user dashboards
Galileo - Pros & Cons
Pros
- ✓Luna evaluators are dramatically cheaper than LLM-as-judge — eval coverage can stay on in production
- ✓End-to-end coverage: evals + traces + guardrails + agent root-cause from one vendor
- ✓Strong enterprise compliance posture (VPC, audit, SSO) suitable for regulated industries
Cons
- ✗No public pricing — every conversation starts with sales, which slows POC adoption
- ✗Heavier and more opinionated than open-source [/tools/langfuse](/tools/langfuse) or [/tools/arize-phoenix](/tools/arize-phoenix) — early-stage teams may find it overkill
- ✗Luna evaluators are proprietary — verify quality on your domain before assuming they replace LLM-judge in your stack
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