garak vs langwatch

Side-by-side comparison of two AI agent tools

g
garakopen-source

the LLM vulnerability scanner

The platform for LLM evaluations and AI agent testing

Metrics

garaklangwatch
Stars9.4k4.9k
Star velocity /mo782.8333333333334276.89839572192517
Commits (90d)2251.6k
Releases (6m)410
Overall score0.64300299394517730.7708652991634155

Pros

    • +End-to-end agent simulation capabilities that test against full stack including tools, state, and user interactions with detailed failure analysis
    • +Open standards approach with OpenTelemetry/OTLP support ensuring no vendor lock-in and framework-agnostic compatibility
    • +Integrated workflow combining tracing, evaluation, prompt optimization, and monitoring in a single platform eliminating tool sprawl

    Cons

      • -As a specialized platform, may require learning curve and setup time for teams new to LLM evaluation workflows
      • -Self-hosting option available but may require infrastructure management for teams preferring on-premises deployment

      Use Cases

        • •Regression testing of AI agents before production deployment using realistic scenario simulations to identify breaking points
        • •Production monitoring and observability of LLM-powered applications with detailed tracing and performance evaluation
        • •Collaborative prompt engineering and optimization with domain expert annotations and version control integration

        FAQ

        Which is more popular, garak or langwatch?
        garak has more GitHub stars (9,394 vs 4,891).
        Which is more actively developed, garak or langwatch?
        langwatch had more commits in the last 90 days (1,556 vs 225).
        Should I use garak or langwatch?
        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.