DeepEval vs Prompt flow
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
DeepEval
Unit testing framework for LLM outputs
VS
Prompt flow
Build and evaluate LLM application flows
| Feature | DeepEval | Prompt flow |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | Apache-2.0 | MIT |
| Language | Python | Python |
| Setup difficulty | Medium | Medium |
| Min. RAM | 1,024 MB | 2,048 MB |
| Deployment | source | docker, source |
| GitHub stars | ★ 17,471 | ★ 11,216 |
| First released | 2023 | 2023 |
| Replaces | LangSmith, Braintrust | LangSmith, Vertex AI |
Why pick each one
Choose DeepEval if…
- Released under the Apache-2.0 license
- Mature project with 17.5k GitHub stars
- Written in Python
Choose Prompt flow if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 11.2k GitHub stars
- Written in Python
Frequently asked questions
Is DeepEval or Prompt flow better?
Neither is universally better. DeepEval has the larger community; both share a medium setup difficulty, so the decision comes down to features and licensing.
Are DeepEval and Prompt flow free and open-source?
Yes. DeepEval is licensed under Apache-2.0 and Prompt flow under MIT. Both can be self-hosted at no software cost.
Can I run DeepEval and Prompt flow with Docker?
DeepEval: check the project docs for container support. Prompt flow: yes.