# Download the forecast results

> Download the results LegalForecastBench displays, reproduce the scoring, and see where the evidence comes from.

Canonical: https://www.legalforecastbench.org/data/

Code is maintained in the LegalForecastBench repository; documents used in the benchmark evaluation, including the documents I purchased in order to complete the evaluation, have been made available to the public through CourtListener. I am also happy to provide copies of the litigation documents as they were shown to models to interested researchers.

Forecasts by 18 ranked AI model configurations, plus GPT-4.1 as a historical reference for non-thinking models, of whether each challenged claim in 91 federal motions to dismiss would be fully dismissed, scored against the actual rulings (387 claim-defendant units).

- Release: cycle-1-91-2026-09-08-luna-r5
- Main results JSON: https://www.legalforecastbench.org/data/current.json
- Significance JSON: https://www.legalforecastbench.org/data/significance/comparison.json
- Cost evidence: https://www.legalforecastbench.org/data/costs.json
- Data license: https://creativecommons.org/licenses/by/4.0/
- Code license: Apache License 2.0
- Source: https://github.com/johnhughes3/LegalForecastBench