DeepEval vs Promptfoo

Detailed side-by-side comparison to help you choose the right tool

DeepEval

🔴Developer

Testing & Quality

Open-source LLM evaluation framework with 50+ research-backed metrics including hallucination detection, tool use correctness, and conversational quality. Pytest-style testing for AI agents with CI/CD integration.

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Starting Price

Free

Promptfoo

🔴Developer

Testing & Quality

Open-source LLM testing and evaluation framework for systematically testing prompts, models, and AI agent behaviors with automated red-teaming.

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Starting Price

Free

Feature Comparison

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FeatureDeepEvalPromptfoo
CategoryTesting & QualityTesting & Quality
Pricing Plans62 tiers8 tiers
Starting PriceFreeFree
Key Features
  • 50+ Research-Backed Evaluation Metrics
  • Hallucination Detection
  • Tool Correctness Evaluation

    DeepEval - Pros & Cons

    Pros

    • Comprehensive LLM evaluation metric suite — 50+ metrics covering hallucination, relevancy, tool correctness, bias, toxicity, and conversational quality
    • Pytest integration feels natural for Python developers — LLM tests run alongside unit tests in existing CI/CD pipelines with deployment gating
    • Tool correctness metric specifically designed for validating AI agent behavior — checks correct tool selection, parameters, and sequencing
    • Open-source core (MIT license) runs locally at zero platform cost — only pay for LLM API calls used by metrics
    • Confident AI cloud offers low-cost tracing at $1/GB-month with adjustable retention — competitive pricing for the observability tier
    • Active development with frequent new metrics and features — grew from 14+ to 50+ metrics, backed by Y Combinator

    Cons

    • Metrics require LLM API calls (GPT-4, Claude) for evaluation — adds cost that scales with dataset size and metric count
    • Some metrics can be computationally expensive and slow for large evaluation datasets, especially multi-turn conversational metrics
    • Confident AI cloud required for collaboration, dataset management, monitoring, and dashboards — open-source alone lacks team features
    • Metric accuracy depends on the evaluator model quality — weaker models produce less reliable scores, creating cost pressure to use expensive models
    • Free tier of Confident AI is restrictive: 5 test runs/week, 1 week data retention, 2 seats, 1 project

    Promptfoo - Pros & Cons

    Pros

    • Comprehensive red-teaming fills a critical gap in LLM safety tooling
    • Free Community tier includes all core evaluation features
    • Declarative YAML config makes test suites maintainable and version-controllable
    • OpenAI acquisition suggests strong continued development and integration

    Cons

    • OpenAI acquisition may affect future open-source direction
    • CLI-focused interface may be less accessible for non-technical users
    • Enterprise pricing not publicly listed

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    🔒 Security & Compliance Comparison

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    Security FeatureDeepEvalPromptfoo
    SOC2🏢 Enterprise
    GDPR✅ Yes
    HIPAA🏢 Enterprise
    SSO🏢 Enterprise
    Self-Hosted✅ Yes
    On-Prem✅ Yes
    RBAC
    Audit Log
    Open Source✅ Yes
    API Key Auth✅ Yes
    Encryption at Rest✅ Yes
    Encryption in Transit✅ Yes
    Data Residency
    Data Retention
    🦞

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