Benchmarks
77.7% on Stanford’s LaborBench.
One complete run of Stonewall’s harness across all 1,647 statutory questions on 28 Oct 2026, above the published Lexis+ AI and Westlaw AI scores.
See the full resultStatutory research
LaborBench
- StonewallMeasured · 28 Oct 2026Accuracy77.7%F176.9%
- STARAAccuracy83%F181%
- Lexis+ AIAccuracy64%F141%
- Westlaw AIAccuracy58%F164%
Afane et al. · CSLAW 2026 · Table 1
Method and sources
Published study of 1,647 statutory questions, using the same uncorrected DOL labels. F1 balances precision and recall. These are study results, not a current-product retest; Westlaw received compressed context.
Stonewall’s result is measured, not estimated: one complete local Shelby harness run on 28 Oct 2026 with Claude Opus 5.5 at high effort, all 1,647 questions graded against the same DOL labels with the same metrics. 95% bootstrap intervals: accuracy 75.7–79.8%, F1 74.5–79.1%. This measures the harness, not the deployed application. Stonewall answered without a statute database. LaborBench has been public since May 2025, so the model may have seen it in training. The study rows are the study’s published results, not a same-day retest. STARA remains ahead.
Legal reasoning
LegalBench
- Claude Fable 5.188.51%
- GPT-5.6 Sol86.97%
- StonewallEvaluation pending
Method and sources
Published Vals reference results. A Stonewall result must use a comparable task set and scoring method before it can be ranked alongside them.
Stonewall’s measured score and projection are not yet published. An estimate will be labeled separately from a measured result.
Agent work
HLAB-Vals-1.1
- Claude Opus 5.59.17%
- GPT-6 Astra7.08%
- GPT-6.1 Sol6.25%
- StonewallEvaluation pending
Method and sources
Harvey created this benchmark; these are model scores, not a score for the Harvey product. Vals version 1.1 results are not comparable with the archived v1 board or the independent LAB-AA evaluation.
Stonewall’s measured score and projection are not yet published. An estimate will be labeled separately from a measured result.
Harvey’s own product evaluation uses a different method and cannot share this ranking.
Pattern graph
What travels together.
Pick a label to see what travels with it.
Pick a label
Ten demonstration labelsPick a label to see which others share its documents.
The names are stand-ins; the document counts are real. Arcs show how many documents carry each label. Ribbons show the documents two labels share, on the same scale; overlapping ends mean a document carries three or more labels. Pairs sharing fewer than two are not drawn.
Three readings. Each is computed from the same counts the graph draws.
-
Most partners
—
The label that shares two or more documents with the most other labels.
-
Least overlap
—
The label with the lowest share of documents in common with its closest partner.
-
Three labels at once
—
Labels whose shared counts show that some documents carry three or more labels.