Braintrust vs LM Evaluation Harness
Both are eval frameworks tools. Here is how they actually differ on price, billing model and deployment.
Braintrust
The most complete eval-first platform - evals, experiments, CI/CD quality gates and observability in one system. The catch is a processed-data-GB billing meter that's uncapped and punishes verbose agents.
LM Evaluation Harness
EleutherAI's academic benchmarking framework and the backend behind the HuggingFace Open LLM Leaderboard. 60+ standard benchmarks, cited in hundreds of papers - and structurally unable to run multiple-choice tasks against chat-only APIs.
| Braintrust | LM Evaluation Harness | |
|---|---|---|
| Category | Eval Frameworks | Eval Frameworks |
| Our rating | 4/5 | 4/5 |
| Starting price | $249/mo | $0 (open source) |
| Billing meter | span | No usage metering |
| Free plan | Yes | Yes |
| Free self-hosting | No or paid tier only | Yes, free |
| Best for | Teams that want turnkey regression testing and CI/CD quality gates without assembling the eval orchestration themselves | Anyone benchmarking base models, comparing fine-tunes against published baselines, or producing numbers that need to line up with academic literature and the Open LLM Leaderboard. |
Our verdict on Braintrust
The best turnkey eval platform of the four - if regression testing and blocking bad merges is your priority, nothing else is this complete out of the box. The gotcha is the billing model - processed data is metered by the byte with no spending cap, so the verbose agents and large RAG contexts that most need observability are exactly what blows up the bill. Watch the meter, or the $249 plan won't stay $249.
Full Braintrust review →Our verdict on LM Evaluation Harness
LM Evaluation Harness is the standard for academic LLM benchmarking and should be your default whenever the question is how good is this model rather than how good is my application. It covers 60+ standard benchmarks with hundreds of subtasks, it is the backend behind the HuggingFace Open LLM Leaderboard, and it is cited in hundreds of papers - which means your numbers are directly comparable with published results instead of being your own private metric. It is actively maintained, with a 2026 release adding a proper subcommand CLI with YAML configs and modular installs. The critical limitation to understand before you plan around it is that loglikelihood is not supported for chat completions, because OpenAI does not expose prompt logprobs. That means multiple-choice benchmarks - a large share of the standard suite - cannot run against chat-only APIs at all. If you are evaluating open-weight models you serve yourself, this is a non-issue. If you intended to benchmark GPT-class endpoints on MMLU-style tasks, it is a wall.
Full LM Evaluation Harness review →Frequently Asked Questions
What is the main difference between Braintrust and LM Evaluation Harness?
Braintrust: Teams that want turnkey regression testing and CI/CD quality gates without assembling the eval orchestration themselves LM Evaluation Harness: Anyone benchmarking base models, comparing fine-tunes against published baselines, or producing numbers that need to line up with academic literature and the Open LLM Leaderboard. Both sit in Eval Frameworks, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Braintrust or LM Evaluation Harness?
It depends entirely on your workload shape, because they meter differently - Braintrust bills on span and LM Evaluation Harness bills on no usage metering. Published starting prices are $249/mo and $0 (open source) 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 Braintrust or LM Evaluation Harness?
Braintrust: No or paid tier only. LM Evaluation Harness: Yes, free. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.