Promptfoo vs DeepEval
Both are alternatives to Braintrust. Here's how they stack up — verified facts, no spin.
Also searched as DeepEval vs Promptfoo — same comparison, one verdict.
Promptfoo and DeepEval are closely matched on ownership (94 vs 92) — this one comes down to pricing and to which trade-offs below you can live with.
Promptfoo
TOP PICKPrompt regressions fail the build. Declarative evals that live in CI.
Promptfoo defines evaluations as YAML: your prompts, your test cases, your assertions, versioned in the repository next to the code they test. It runs from the CLI or in CI, compares outputs across models and prompt variants side by side, and fails the build when a change regresses. It also includes red-teaming for prompt injection and jailbreak testing. MIT licensed with no seat limits, which matters because everyone who edits a prompt should be running it.
DeepEval
Evals as pytest tests, with the research metrics already implemented.
DeepEval brings LLM evaluation into pytest, so an eval is a test function and your existing test runner, CI integration and reporting all work unchanged. It ships implementations of the metrics people actually cite — answer relevancy, faithfulness, contextual precision and recall, hallucination, bias, toxicity — including several LLM-as-judge metrics done carefully. Apache-2.0, from Confident AI, who sell an optional hosted platform.
Side by side
10 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| Promptfoo | DeepEval | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 94 | 92 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first data | Yes | Yes |
| License | MIT | Apache-2.0 |
| Pricing | Free and MIT, unlimited seats. An enterprise tier exists for larger organisations. | Free and Apache-2.0; optional paid cloud dashboard. |
| RAM to run it wellThe figure that actually matters, not the vendor's minimum. | 2 GB | — |
| Realistic running costWhat the box costs each month if you run it yourself. | $0. It runs in CI on hardware you already pay for. | — |
| Setup timeHonest first-install estimate, not the marketing quickstart. | 1 hour for the first ten test cases | — |
| Ongoing maintenanceThe part nobody budgets for. | Low. The suite grows with your prompts. | — |
Promptfoo is Macrostack's recommended Braintrust alternative, so it's our pick here.
Weighing both against staying on Braintrust? Is Braintrust free? What it actually costs →
Promptfoo
Strengths
- +Evals live in your repo and run in CI — a regression blocks the merge
- +Side-by-side model and prompt comparison out of the box
- +Includes red-teaming for injection and jailbreak testing
- +MIT, no seat limits, nothing leaves your infrastructure by default
Trade-offs
- −YAML configuration gets long on large test suites
- −Reporting UI is lighter than a hosted platform's
- −Trace history is yours to store and manage
DeepEval
Strengths
- +Pytest-native — your existing CI and reporting just work
- +Large library of implemented, research-backed metrics
- +Synthetic test-case generation for cold-start coverage
- +Apache-2.0 with no seat cost
Trade-offs
- −LLM-as-judge metrics cost tokens on every run
- −Assumes a Python codebase
- −Best dashboard experience is the paid hosted one
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose Promptfoo
if a lower exit cost matters more to you than any single feature, and evals live in your repo and run in CI — a regression blocks the merge.
Choose DeepEval
if pytest-native — your existing CI and reporting just work.
Neither, yet
if both carry a real cost you should weigh first — yAML configuration gets long on large test suites, and lLM-as-judge metrics cost tokens on every run. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
What it takes to run these yourself
Real requirements and honest running costs, not the vendor quickstart.
Promptfoo vs DeepEval — common questions
Is Promptfoo a better fit than DeepEval for llm evaluation & testing?
It depends on what you are optimising for, and the honest split is this: Promptfoo scores 94 to DeepEval's 92 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. DeepEval earns its place on a different axis — pytest-native — your existing CI and reporting just work. Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
Promptfoo keeps its data local or in open formats, so leaving is an export rather than a negotiation. DeepEval is still self-hostable, so the files stay on your server either way — but it is not local-first by design, so check what its export produces before you rely on it.
Can I self-host Promptfoo or DeepEval?
Both can be self-hosted. The difference is what it costs you in time rather than whether it is possible — see the setup and maintenance rows above.
Are Promptfoo and DeepEval both alternatives to Braintrust?
Yes — both appear in our Braintrust comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off Braintrust and now choosing between the two replacements, which is a narrower and much easier question.
Related alternative guides
Facts verified 2026-08-11. Licenses and pricing change — spotted something out of date? That's a correction we want.