PentAGI vs Promptfoo

Side-by-side comparison of two AI agent tools

P
PentAGIopen-source

Fully autonomous AI Agents system capable of performing complex penetration testing tasks

Promptfooopen-source

Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and

Metrics

PentAGIPromptfoo
Stars25.1k25.6k
Star velocity /mo2.1k1.1k
Commits (90d)324895
Releases (6m)210
Overall score0.76015251940104380.8054365104809726

Pros

    • +Comprehensive testing suite covering both performance evaluation and security red teaming in a single tool
    • +Multi-provider support with easy comparison between OpenAI, Anthropic, Claude, Gemini, Llama and dozens of other models
    • +Strong CI/CD integration with automated pull request scanning and code review capabilities for production deployments

    Cons

      • -Requires API keys and credits for multiple LLM providers, which can become expensive for extensive testing
      • -Command-line focused interface may have a learning curve for teams preferring GUI-based tools
      • -Limited to evaluation and testing - does not provide actual LLM application development capabilities

      Use Cases

        • •Automated testing and evaluation of prompt performance across different models before production deployment
        • •Security vulnerability scanning and red teaming of LLM applications to identify potential risks and compliance issues
        • •Systematic comparison of model performance and cost-effectiveness to optimize AI application architecture
        View PentAGI DetailsView Promptfoo Details

        FAQ

        Which is more popular, PentAGI or Promptfoo?
        Promptfoo has more GitHub stars (25,597 vs 25,148).
        Which is more actively developed, PentAGI or Promptfoo?
        Promptfoo had more commits in the last 90 days (895 vs 324).
        Should I use PentAGI or Promptfoo?
        Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.