Confident AI vs Confident AI (DeepEval)
Both are eval frameworks tools. Here is how they actually differ on price, billing model and deployment.
Confident AI
The commercial cloud layer over DeepEval. It recently moved from per-seat to flat per-organisation pricing at $200 and $2,000 a month - a change most third-party reviews have not caught up with.
Confident AI (DeepEval)
The pytest for LLM apps - write test cases, run "deepeval test run" in CI. The OSS framework is Apache-2.0 and free; the Confident AI cloud has a steep pricing cliff from $200/mo to $2,000/mo.
| Confident AI | Confident AI (DeepEval) | |
|---|---|---|
| Category | Eval Frameworks | Eval Frameworks |
| Our rating | 4/5 | 4/5 |
| Starting price | $200/mo per org | $200/mo |
| Billing meter | gb-month | No usage metering |
| Free plan | Yes | Yes |
| Free self-hosting | No or paid tier only | Yes, free |
| Best for | Teams already using DeepEval who need shared datasets, persistence, online evaluation and collaboration, and who are large enough that unlimited seats on a flat plan beats per-seat competitors. | Python teams who want pytest-style LLM evals in CI/CD and can either live in the OSS framework or absorb the cloud's pricing steps |
Our verdict on Confident AI
Confident AI is the managed layer over DeepEval, and the most useful thing to know about it right now is that its pricing changed and most of the internet has not noticed. It now bills flat per organisation - $200 a month for Starter with unlimited seats and 5 GB-months, $2,000 for Team with 75 GB-months - having previously used a per-seat model that third-party reviews still quote at figures like $19.99 or $49.99 per seat. If you are comparison shopping from review sites you are working from stale numbers. The new model is genuinely favourable for larger teams, because unlimited seats on a flat plan beats per-seat pricing badly once you have more than a handful of engineers, and traces are unlimited on every tier with billing on stored data instead. The underlying DeepEval framework is Apache 2.0 and free, so your evaluation logic stays portable, and a self-hosted option exists. The main structural criticism is the 10x gap between Starter and Team with nothing published in between.
Full Confident AI review →Our verdict on Confident AI (DeepEval)
If your team writes Python and thinks in tests, DeepEval is the most natural eval framework there is - it really does feel like pytest for LLM apps, and the OSS core is free under Apache-2.0. The friction is the cloud. The Free tier is stingy at 5 test runs a week, and the jump from $200/mo Starter to $2,000/mo Team is a real 10x cliff. Watch the API bills too - almost every metric is LLM-as-judge.
Full Confident AI (DeepEval) review →Frequently Asked Questions
What is the main difference between Confident AI and Confident AI (DeepEval)?
Confident AI: Teams already using DeepEval who need shared datasets, persistence, online evaluation and collaboration, and who are large enough that unlimited seats on a flat plan beats per-seat competitors. Confident AI (DeepEval): Python teams who want pytest-style LLM evals in CI/CD and can either live in the OSS framework or absorb the cloud's pricing steps Both sit in Eval Frameworks, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Confident AI or Confident AI (DeepEval)?
It depends entirely on your workload shape, because they meter differently - Confident AI bills on gb-month and Confident AI (DeepEval) bills on no usage metering. Published starting prices are $200/mo per org and $200/mo 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 Confident AI or Confident AI (DeepEval)?
Confident AI: No or paid tier only. Confident AI (DeepEval): Yes, free. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.