Braintrust vs DeepEval
A side-by-side comparison of Braintrust and DeepEval, two Eval tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Braintrust | DeepEval |
|---|---|---|
| Category | Eval | Eval |
| Pricing | FREEMIUM | FREEMIUM |
| License (differs) | Proprietary | Open core |
| Deployment (differs) | Cloud | Hybrid |
| Platforms (differs) | Web, API | CLI, API |
| Model support | BYO key / model | BYO key / model |
| Vendor (differs) | Braintrust | Confident AI |
| Capabilities (differs) |
|
|
The honest brief
Braintrust
Eval-first: prompts are versioned objects and CI scorers block a merge when quality regresses.
- Eval workflow as the primary interface
- CI scorers block merges on regression
- Dataset versioning + OTel tracing
- Generous free tier
- Closed-source SaaS
- Self-hosting needs Enterprise contract
- Overkill for tiny single-file eval needs
DeepEval
Write LLM evals as Pytest-style assertions and run them in CI, backed by 50+ metrics across RAG, agents, and safety.
- Assertions run in your CI pipeline
- Metrics for RAG, agents, and safety
- Bring any judge model (BYO key)
- Integrates LangChain/CrewAI/OpenAI
- LLM-as-judge adds cost
- Dashboards need paid Confident AI
- Judge metrics can be noisy
When to pick which
Both cover LLM evaluation and LLM observability.
Pick Braintrust if you need Prompt management.
- Prompt management (secondary capability)
They also differ on:
- License
- Proprietary · Open core
- Deployment
- Cloud · Hybrid
- Platforms
- Web, API · CLI, API