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Evaluation

Harvey Legal Agent Benchmark (LAB)

2026ActivePublished: 24 September 2026Updated: 24 September 2026Published
Key innovation
Instead of scoring criterion by criterion, it applies an all-pass standard: a single miss fails the whole task. This mirrors the reality of legal work, where a report identifying eight of ten risks is not 80% useful but materially incomplete.
Category
Evaluation
Abstraction level
System
Operation level
Agent runtimeSystem
Use cases
Evaluating AI agents for legal workComparing models on long-horizon document tasksTesting the production of review-ready work productsBuilding datasets for training and fine-tuning legal models

How it works

The agent receives an instruction phrased the way a law firm partner would phrase it, plus access to a file system mirroring a real working environment: client matter documents, virtual data rooms, templates and background materials. It has tools for working with documents, spreadsheets, presentations and the file system. The output should be a work product ready for partner or client review. Grading rests on an extensive rubric โ€” over 75,000 expert-written criteria โ€” but the decisive element is the aggregation rule: the all-pass standard requires every criterion to be met for the task to count. This yields markedly lower scores than the criterion-by-criterion scoring used in BigLaw Bench, but ones closer to the real demands of practice. Harvey publishes the dataset together with an execution harness under an open licence.

Problem solved

Earlier legal benchmarks measured short-horizon reasoning over a single document, which does not reflect work that requires reviewing a bundle of materials, extracting the relevant threads and producing a finished document. LAB moves evaluation to the level of a complete work product and a long task horizon.

Components

1,250+ tasks across 24 practice areasTest set

Covers transactional, advisory, regulatory and litigation work, embedded in synthetic client matters.

Over 75,000 rubric criteriaGrading basis

Expert-written criteria, itemized in detail for each task.

All-pass standardAggregation rule

A single unmet criterion fails the whole task โ€” no partial credit.

Law firm file environmentExecution context

Matter documents, virtual data rooms, templates and background materials available through file-system tools.

Implementation

Implementation pitfalls
Low absolute scoresHigh

The all-pass standard means even strong models land in the teens or twenties โ€” comparing those numbers with criterion-by-criterion benchmarks is misleading.

Fix:Compare only within LAB and do not put the figures directly alongside BigLaw Bench results.
Synthetic mattersMedium

Tasks are embedded in synthetic client matters, which removes confidentiality problems but does not reproduce the full messiness of real files.

Fix:Supplement the evaluation with a pilot on your own real matters before deployment.

Evolution

2024
BigLaw Bench โ€” the predecessor measuring short-horizon reasoning

In August 2024 Harvey published BigLaw Bench, scoring short legal tasks criterion by criterion.

2026
BigLaw Bench: Global and BigLaw Bench: Research

February 2026 brought the Global variant covering international jurisdictions, and March 2026 the Research variant for case law research.

2026
Legal Agent Benchmark launch
Inflection point

On 6 May 2026 Harvey released LAB: 1,250+ tasks, 24 practice areas, 75,000 criteria and the all-pass standard, as an open-source project without a leaderboard.