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Promptfoo

Freemium
llmprompt engineeringtestingevaluationdeveloper toolopen sourceragaigenerative aidevops

An open-source testing and evaluation framework for developers to systematically compare and improve the quality of prompts, models, and RAG systems for Large Language Model (LLM) applications.

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Promptfoo is a specialized developer tool designed to bring a structured, engineering discipline to building with LLMs. It primarily serves AI engineers, developers, and data science teams who need to move beyond manual, ad-hoc prompt tuning. The platform allows users to define test cases in YAML or code to systematically evaluate different prompts and models from providers like OpenAI, Anthropic, and Google. Its key value proposition is in enabling data-driven decisions by providing a web-based UI to compare outputs side-by-side on metrics like quality, cost, and latency. This helps teams catch regressions, optimize performance, and ship more reliable AI products with confidence.

Pros

  • Vendor-agnostic, supporting a vast range of LLM providers including OpenAI, Anthropic, Google, and local models via Ollama.
  • Open-source core functionality is free and can be self-hosted, providing flexibility and control.
  • Enables comprehensive evaluation with custom assertion types for logic, structure, and factual consistency.
  • Integrates directly into CI/CD pipelines (e.g., GitHub Actions) for automated regression testing.
  • Provides a clear, side-by-side web viewer to visually compare the outputs of different prompts and models.

Cons

  • The primary workflow is config-file and command-line driven, which can present a learning curve for non-developers.
  • Advanced collaboration and management features are gated behind paid tiers.
  • While powerful, setting up complex test suites with programmatic assertions requires JavaScript/TypeScript knowledge.
  • The UI is more for viewing results than for creating or managing tests, which are done in code.

Key features

  • Command-line interface (CLI) for running evaluation jobs.
  • Side-by-side diff viewer to compare prompt outputs.
  • Support for defining test cases in YAML, JSON, CSV, or programmatically in JS/TS.
  • Built-in assertions for checking output quality (e.g., similarity, regex, JSON validity).
  • Model-graded evaluations where an LLM is used as the judge.
  • Support for Retrieval-Augmented Generation (RAG) evaluation.
  • Caching layer to reduce API costs during test runs.
  • Configuration of multiple LLM providers in a single test suite.

Integrations

OpenAIGoogle AI (Gemini)Anthropic (Claude)Mistral AIAzure OpenAIOllamaHugging FaceGroqLangChainGitHub

Target audience

AI Engineers, developers, and teams building applications on top of Large Language Models who require a systematic way to test, evaluate, and ensure output quality.

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Founded

2023

Headquarters

San Francisco, USA

Pricing Tiers

Hobby

For individuals & open-source projects. Includes unlimited local runs, CLI & Viewer, support for all models, and community support.

Free

Pro

For professional developers & small teams. Includes everything in Hobby, plus hosted evaluations, team collaboration, prompt & config management, and usage tracking.

$20/mo

Enterprise

For organizations needing advanced security & scale. Includes everything in Pro, plus SSO/SAML, on-premise/VPC deployment, dedicated support, and advanced security reviews.

Custom

Frequently Asked Questions

Top Alternatives to Promptfoo

LangSmith

Choose LangSmith if you need a holistic LLMOps platform focused heavily on observability and tracing complex agentic chains, not just prompt evaluation.

Arize AI

Arize is a better choice for teams focused on production monitoring, offering powerful tools to detect drift, data quality issues, and performance degradation in live LLM apps.

OpenAI Evals

A good option for those deeply embedded in the OpenAI ecosystem who need a basic, code-first framework for evaluation without requiring a UI or multi-provider support.

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