Evidently vs Promptfoo
Both are eval frameworks tools. Here is how they actually differ on price, billing model and deployment.
Evidently
An open-source ML and LLM evaluation framework with 100+ metrics spanning tabular data through to GenAI. Notably, release 0.7.17 moved previously closed functionality into open source - the opposite of the usual direction.
Promptfoo
The de-facto open-source CLI for LLM eval and red-teaming, driven by declarative YAML. MIT-licensed, ~23.5k stars, and acquired by OpenAI in March 2026 - still open source, now part of OpenAI Frontier.
| Evidently | Promptfoo | |
|---|---|---|
| Category | Eval Frameworks | Eval Frameworks |
| Our rating | 4/5 | 4/5 |
| Starting price | Not published | $0 |
| Billing meter | No usage metering | No usage metering |
| Free plan | Yes | Yes |
| Free self-hosting | Yes, free | Yes, free |
| Best for | Teams evaluating classical ML and LLM systems together, especially where data drift and data quality matter as much as output quality, and who want CI-integrated declarative testing. | Security and CI teams who want config-driven LLM eval plus serious red-teaming, from an OSS tool with no seat cost |
Our verdict on Evidently
Evidently is the broadest evaluation framework in this category and the only one that treats data quality, classical ML performance and LLM output as one continuous problem. That breadth is the reason to choose it. A team running recommender systems and a RAG assistant gets drift detection, ranking metrics and hallucination checks from one library with 100+ built-in metrics, where a purely LLM-native tool would cover a third of the surface. The design is also good - any Report becomes a Test Suite by adding pass/fail conditions, which makes CI gating a natural extension rather than a separate product. And release 0.7.17 moved previously closed functionality into open source, including the service for storing run logs and LLM-judge workflows, which is the opposite of the direction open-core vendors normally travel and deserves credit. The clear weakness is agents. There is no span-level evaluation for scoring individual steps like tool calls, no graph visualisation of execution paths, and agent evaluation needs custom work. If agents are your primary workload, look elsewhere.
Full Evidently review →Our verdict on Promptfoo
The clearest pick if red-teaming and security testing are part of your eval story, and its YAML-in-git approach fits CI cleanly. The OpenAI acquisition in March 2026 is the thing to weigh - the commitment to stay MIT is on the record, but you are now betting on OpenAI's stewardship of the project. For the free tier alone it is still an easy yes.
Full Promptfoo review →Frequently Asked Questions
What is the main difference between Evidently and Promptfoo?
Evidently: Teams evaluating classical ML and LLM systems together, especially where data drift and data quality matter as much as output quality, and who want CI-integrated declarative testing. Promptfoo: Security and CI teams who want config-driven LLM eval plus serious red-teaming, from an OSS tool with no seat cost Both sit in Eval Frameworks, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Evidently or Promptfoo?
It depends entirely on your workload shape, because they meter differently - Evidently bills on no usage metering and Promptfoo bills on no usage metering. Published starting prices are Not published and $0 respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host Evidently or Promptfoo?
Evidently: Yes, free. Promptfoo: Yes, free. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.