Inspect AI vs OpenAI Evals
Both are alternatives to Braintrust. Here's how they stack up — verified facts, no spin.
Also searched as OpenAI Evals vs Inspect AI — same comparison, one verdict.
Inspect AI
The rigorous one, from the UK AI Safety Institute.
Inspect is the evaluation framework built by the UK AI Safety Institute for evaluating frontier models, released MIT. It is the most methodologically serious option here: first-class support for multi-turn agent evaluations, tool use, sandboxed execution and human grading, with a design that takes statistical validity seriously rather than producing a number that feels reassuring. If your evaluations need to withstand scrutiny — regulatory, academic or internal — this is the one.
OpenAI Evals
The original benchmark harness. Simple, standard, still useful.
OpenAI Evals is the framework and registry that popularised systematic LLM evaluation. It provides a standard harness for running benchmark-style evaluations and a public registry of existing ones, so comparing against a known suite is a command rather than a project. It is less actively developed than the others here and less suited to application-level regression testing, but for running or extending a standard benchmark it remains the shortest path. MIT licensed.
Side by side
| Inspect AI | OpenAI Evals | |
|---|---|---|
| Sovereignty Score | 93 | 85 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first | Yes | Yes |
| License | MIT | MIT |
| Pricing | Free, MIT, publicly funded. | Free, MIT. You pay for whatever model API the evals call. |
Inspect AI edges it on the Sovereignty Score, but the right pick depends on the trade-offs below.
Inspect AI
Strengths
- +Built for evaluations that have to survive real scrutiny
- +Strong agent, tool-use and sandboxed-execution support
- +Excellent log viewer for inspecting individual samples
- +MIT, from a public institute with no commercial upsell
Trade-offs
- −Aimed at model evaluation more than application regression testing
- −Steeper learning curve than Promptfoo for simple cases
- −Less oriented toward CI gating out of the box
OpenAI Evals
Strengths
- +Large registry of existing benchmark evaluations
- +Simple, well-understood format that many teams already know
- +Straightforward to extend with your own cases
- +MIT licensed
Trade-offs
- −Development pace has slowed relative to the alternatives
- −Oriented to benchmarks, not application regression testing
- −Weaker RAG and agent evaluation support than the others
Related alternative guides
Facts verified 2026-08-11. Licenses and pricing change — spotted something out of date? That's a correction we want.