Braintrust vs Judgment Labs
A side-by-side comparison of Braintrust and Judgment Labs, two Eval tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Braintrust | Judgment Labs |
|---|---|---|
| Category | Eval | Eval |
| Pricing | FREEMIUM | FREEMIUM |
| License (differs) | Proprietary | Open core |
| Deployment (differs) | Cloud | Hybrid |
| Platforms | Web, API | Web, API |
| Model support | BYO key / model | BYO key / model |
| Vendor (differs) | Braintrust | Judgment Labs |
| 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
Judgment Labs
Scores entire agent trajectories — tool calls, memory, long reasoning — and turns that production data into RL/SFT post-training, not just pass/fail evals.
- Open-source judgeval framework (Apache-2.0)
- Trajectory-level, not just output, evals
- Feeds production data into RL/SFT
- MCP integration with coding agents
- Hosted platform pricing not public
- Young company (founded 2026)
- Geared to complex 'deep' agents
When to pick which
Both cover LLM evaluation and LLM observability.
Pick Braintrust if you need Prompt management.
- Prompt management (secondary capability)
Pick Judgment Labs if you need MCP server.
- MCP server (secondary capability)
They also differ on:
- License
- Proprietary · Open core
- Deployment
- Cloud · Hybrid