THE COMPARISON / A CLOSER LOOK
DeepEval vs Promptfoo
Compare the listed plans, useful capabilities, and practical tradeoffs.
Prices and features reflect editorial records. Check vendor terms before you buy; documentary checks do not imply hands-on testing.
DeepEval
🔴DeveloperTesting & Quality
DeepEval is the open-source, Pytest-style LLM evaluation framework from Confident AI.
SOURCE-CHECK COVERAGE
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Starting Price
FreePromptfoo
🔴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.
SOURCE-CHECK COVERAGE
No scoped source-check record shown. Check current pricing and vendor terms before buying.
Starting Price
FreeFeature Comparison
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The editorial take
Choose Promptfoo if you need a broader AI security testing surface that includes red teaming, guardrails, model security, MCP Proxy, and code scanning. Choose DeepEval if your main need is a developer-focused evaluation framework for LLM outputs and you do not need Promptfoo’s broader security platform positioning.
DeepEval - Pros & Cons
Pros
- ✓Real MIT-licensed library — evals stay with your code, no vendor lock-in
- ✓Pytest-first ergonomics — CI integration is a one-line command
- ✓50+ metrics grounded in published research (G-Eval, DAG, contextual precision)
- ✓Cheapest cloud tracing on the market at $1/GB-month
- ✓Companion DeepTeam framework handles red-teaming and adversarial evals
Cons
- ✗Python-first — Node/TS teams need to shell out or wrap the library
- ✗G-Eval and other judge metrics require LLM API tokens you pay for separately
- ✗Team/Enterprise pricing not published — sales conversation required
- ✗Free tier has limited cloud dashboards; paid tier unlocks the collaboration surface
- ✗Metric quality still depends on the judge model you configure
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
Not sure which to pick?
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