Prompt flow vs promptfoo
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Open-source toolkit for building, testing, evaluating and deploying LLM apps, from prototype to production.
Open source · MIT
CLI and library for testing LLM prompts and red-teaming AI apps, with declarative configs.
The short answer
Choose Prompt flow if you need…
- Teams with existing Prompt flow applications that need to keep running until migration
- Developers who want to trace and evaluate LLM app behavior on datasets
- Engineers who want to run flow tests in CI/CD pipelines
- Developers who prefer a VS Code extension for visual flow editing
Choose promptfoo if you need…
- Developers building apps on top of LLM APIs who want repeatable prompt tests
- Teams comparing several models side by side on the same prompts
- People who want to run automated LLM checks in CI/CD pipelines
- Teams looking for a local, command-line way to scan LLM apps for security issues
Side-by-side
| Prompt flow | promptfoo | |
|---|---|---|
| Type | Dev tool | Dev tool |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 11.3k | 26.7k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Install with a package manager | Install with a package manager |
| Platforms | — | CLI, Web |
| Works with | — | GitHub, OpenAI, Anthropic |
| Main language | Python | TypeScript |
| Last code update | 6 days ago | 4 days ago |
What each one is
Prompt flow
Prompt flow is a set of development tools for building applications that use large language models (LLMs). You connect LLMs, prompts and Python code into a flow, then debug it, run it against larger datasets to evaluate quality, and deploy it. The README notes that Prompt flow is being retired by Microsoft on April 20, 2027, and is no longer recommended for new development.
promptfoo
Promptfoo is a command-line tool and library for evaluating LLM-based apps. You write a declarative config listing prompts, models, and test cases, then run it to compare outputs across providers such as OpenAI, Anthropic, and Ollama. It also includes red-teaming features that scan AI apps for security vulnerabilities.
Best for
Prompt flow
- Teams with existing Prompt flow applications that need to keep running until migration
- Developers who want to trace and evaluate LLM app behavior on datasets
- Engineers who want to run flow tests in CI/CD pipelines
- Developers who prefer a VS Code extension for visual flow editing
promptfoo
- Developers building apps on top of LLM APIs who want repeatable prompt tests
- Teams comparing several models side by side on the same prompts
- People who want to run automated LLM checks in CI/CD pipelines
- Teams looking for a local, command-line way to scan LLM apps for security issues
Strengths
Prompt flow
- Covers the full cycle from prototyping through testing, evaluation and deployment in one toolkit
- Includes a VS Code extension and a command-line interface for flow development
- Released under the MIT license with an active public repository
promptfoo
- The README states that evals run locally and prompts never leave your machine
- Works with many providers and any LLM API, according to the README
- Has a large community with about 26,500 stars and an MIT license
Not ideal for
Prompt flow
- Anyone starting a new project: the README says Prompt flow is no longer recommended for new development and suggests Microsoft Agent Framework instead
- Teams relying on Prompt flow runtime container images, which no longer receive security or package updates
- Non-developers, since setup uses the command line and a Python environment
promptfoo
- People who want a no-code, point-and-click tool, since the workflow centers on the command line and config files
- Projects that do not call any LLM APIs, because there is nothing for it to evaluate
- Anyone who needs a guaranteed security audit, since the README describes scanning as a tool rather than a complete assurance
Trade-offs
Prompt flow
- The README states retirement on April 20, 2027, and no new-development recommendation, so long-term support is limited
- Container images are no longer updated, which is a security concern for deployed workloads
- Setup and tutorials assume familiarity with Python and LLM API keys
promptfoo
- The README says the project is now part of OpenAI, which may matter to some users evaluating independence
- Requires API keys for most providers, which means usage costs from those providers
- Some claims in the README, such as usage by OpenAI and Anthropic and serving 10M+ users, are not independently verified here
Getting started
Prompt flow
Install the packages
pip install promptflow promptflow-toolspromptfoo
Install globally with npm
npm install -g promptfooCreate a starter example
promptfoo init --example getting-startedFrequently asked questions
What is the difference between Prompt flow and promptfoo?
Prompt flow: Open-source toolkit for building, testing, evaluating and deploying LLM apps, from prototype to production. promptfoo: CLI and library for testing LLM prompts and red-teaming AI apps, with declarative configs. Prompt flow suits teams with existing prompt flow applications that need to keep running until migration, while promptfoo suits developers building apps on top of llm apis who want repeatable prompt tests.
Are Prompt flow and promptfoo free?
Prompt flow: Free and open source. promptfoo: Free and open source.
Is Prompt flow or promptfoo more popular?
promptfoo has more GitHub stars (26.7k) than Prompt flow (11.3k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Prompt flow and promptfoo?
Other options people compare them with include LangChain, LlamaIndex, DSPy, Botpress, Composio.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.