What is Promptfoo?
Promptfoo is an open-source tool for testing and evaluating LLM prompts. Think of it as a testing framework specifically designed for AI: you define test cases with expected outputs, run them against one or more models, and get a comparison showing how each prompt and model combination performed.
If you've ever changed a prompt, deployed it, and then discovered it broke something that used to work, Promptfoo is the tool that prevents that. It's the "write tests before you refactor" approach applied to prompt engineering.
Key Features
YAML-Based Test Configuration
You define your prompts, test cases, and assertions in YAML files. Each test case has an input and expected behavior, which can be an exact match, a substring check, a regex pattern, a semantic similarity threshold, or a custom function. No code required for basic setups.
A simple config might test whether your prompt correctly classifies customer support tickets. You define 50 sample tickets with their expected categories, run them against your prompt, and see the pass rate. Change the prompt, re-run, and compare.
Side-by-Side Model Comparison
Run the same test suite against multiple models simultaneously. Promptfoo generates a comparison table showing how Claude Sonnet, GPT-4o, GPT-4o mini, and Llama perform on your specific task. This is incredibly useful when you're deciding which model to use in production, because benchmarks don't always predict real-world performance on your data.
Assertion Types
Promptfoo supports a wide range of assertion types: exact match, contains, regex, JSON schema validation, cost thresholds, latency limits, and LLM-graded evaluations where you use one model to judge another's output. You can also write custom assertion functions in JavaScript or Python.
CI/CD Integration
Promptfoo runs from the command line and outputs results in formats compatible with CI systems. You can add prompt evaluation to your GitHub Actions, GitLab CI, or Jenkins pipeline. If a prompt change causes regressions, the build fails before it reaches production.
Red Teaming
Promptfoo includes a red teaming module that automatically generates adversarial inputs to test your prompts for jailbreaks, prompt injection, data leakage, and other security issues. For teams building customer-facing AI features, this catches vulnerabilities before users find them.
Pricing Breakdown
The core tool is open source under the MIT License. You can self-host it with all features at no cost. The cloud offering has a free tier for individual use. The Team plan at $50/month adds collaboration features, shared results, and team management. Enterprise pricing is custom.
Since Promptfoo calls LLM APIs during evaluation, you'll also pay for the API tokens used in your tests. Running 100 test cases against GPT-4o costs roughly $0.50-$2.00 depending on prompt length.
How It Fits the AI Stack
Promptfoo sits between your development workflow and production deployment. It works with any LLM provider: OpenAI, Anthropic, local models via Ollama, and models on Hugging Face. If you're using LangChain or LlamaIndex, Promptfoo can test the prompts those frameworks generate.
✓ Pros
- Open source and free for self-hosted use with no feature restrictions
- YAML-based config makes it easy to define test cases without writing code
- Side-by-side model comparison shows you exactly which model performs better for your use case
- CI/CD integration lets you catch prompt regressions before they reach production
✗ Cons
- Learning curve for setting up assertion types and custom evaluators
- Web UI is functional but not polished compared to commercial alternatives
- Documentation could use more real-world examples for complex evaluation setups
- Requires Node.js, which may not fit every team's stack
Who Should Use Promptfoo?
Ideal For:
- AI engineers shipping LLM features to production who need to test prompts systematically before deploying
- Teams comparing models (Claude vs GPT-4o vs Llama) for specific tasks with real data
- Prompt engineers who want to iterate on prompts with measurable results instead of gut feeling
- DevOps teams who want LLM evaluations in their CI/CD pipeline alongside regular tests
Maybe Not For:
- Non-technical prompt writers who need a visual no-code interface for prompt testing
- Teams that only use one model and one prompt where the evaluation overhead isn't worth it
- Developers not using Node.js who'd need to add it to their stack just for testing
Our Verdict
Promptfoo fills a gap that most AI teams don't realize they have until something breaks in production. It brings the discipline of unit testing to LLM prompts: define your test cases, set your assertions, run them against multiple models, and get a clear comparison table showing what works and what doesn't.
The YAML-based configuration is a strength. You can define hundreds of test cases without writing code, share them across the team, and run them in CI. The side-by-side model comparison alone is worth the setup time if you're deciding between Claude, GPT-4o, and open-source alternatives for a specific task. It's not the flashiest tool in the AI stack, but it might be the one that saves you from the most embarrassing production failures.