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BhashaBench-Legal (BBL): Benchmarking AI on Indian Legal Knowledge

Overview

BhashaBench-Legal (BBL) is the comprehensive benchmark designed to rigorously evaluate AI models on Indian legal knowledge. Tailored for India's complex legal framework, constitutional structure, and diverse jurisprudential traditions, BBL draws from official judicial service exams, bar examinations, and legal education assessments to test models' ability to provide accurate, contextually relevant, and legally sound advice within the Indian legal system.

Key Features

• Languages: English and Hindi (with plans for more Indic languages)
• Exams: 50+ unique legal government and institutional exams across India
• Domains: 20+ legal and allied disciplines, spanning over 200 specialized topics
• Questions: 24,365 rigorously validated, exam-based questions
• Difficulty Levels: Easy (8,200), Medium (12,150), Hard (4,015)
• Question Types: Multiple Choice, Assertion-Reasoning, Match the Column, Rearrange the Sequence, Fill in the Blanks
• Focus: Practical, context-rich, jurisdiction-specific legal knowledge essential for Indian legal practice

Dataset Statistics

Metric	Count
Total Questions	24,365
English Questions	17,047
Hindi Questions	7,318
Subject Domains	20+
Government Exams Covered	50+

Dataset Structure

Test Set

The test set consists of the BhashaBench-Legal (BBL) benchmark, which contains approximately 24,365 multiple-choice questions across 2 Indic languages (English and Hindi).
We will add support for more Indic languages in upcoming versions.

Subjects spanning BBL

Subject Domain	Count
Civil Litigation & Procedure	7126
Constitutional & Administrative Law	3609
Criminal Law & Justice	2769
Corporate & Commercial Law	2700
General Academic Subjects	1756
Legal Theory & Jurisprudence	1421
Family & Personal Law	991
International & Comparative Law	962
Legal Skills & Communication	816
Real Estate & Property Law	629
Environmental & Energy Law	430
Interdisciplinary Studies	363
Tax & Revenue Law	231
Employment & Labour Law	175
Technology & Cyber Law	123
Intellectual Property Law	91
Consumer & Competition Law	75
Media & Entertainment Law	54
Healthcare & Medical Law	25
Human Rights & Social Justice	19

Usage

Since this is a gated dataset, after your request for accessing the dataset is accepted, you can set your HuggingFace token:

export HF_TOKEN=YOUR_TOKEN_HERE

To load the BBL dataset for a Language:

from datasets import load_dataset
language = 'Hindi'
# Use 'test' split for evaluation
split = 'test'
language_data = load_dataset("bharatgenai/BhashaBench-Legal", data_dir=language, split=split, token=True)
print(language_data[0])

Evaluation Results Summary

• 25+ models evaluated, including GPT-4o, Claude-3.5, and various specialized legal LLMs.

• Top accuracy:

  • English: 75%+ by best models
  • Hindi: 65–70%, showing need for enhanced Indic language legal reasoning

• Strong domains:

  • Constitutional Law, Legal Theory, Corporate Law (~80% accuracy)

• Weak domains:

  • Technology & Cyber Law, Environmental Law, Healthcare Law (<55%)

• Challenges:

  • Complex procedural questions and jurisdiction-specific cases remain challenging across models

For detailed results and analysis, please refer to our blog.

Citation

Please cite our benchmark if used in your work:

@misc{bhashabench-legal-2025,
  title  = {BhashaBench-Legal: Benchmarking AI on Indian Legal Knowledge},
  author = {BharatGen Research Team},
  year   = {2025},
  howpublished = {\url{https://huggingface.co/datasets/bharatgenai/bhashabench-legal}},
  note   = {Accessed: YYYY-MM-DD}
}

License

This dataset is released under the CC BY 4.0.

Contact

For any questions or feedback, please contact:

• Vijay Devane (vijay.devane@tihiitb.org)
• Mohd. Nauman (mohd.nauman@tihiitb.org)
• Bhargav Patel (bhargav.patel@tihiitb.org)
• Kundeshwar Pundalik (kundeshwar.pundalik@tihiitb.org)

Links

• GitHub Repository 💻
• Paper 📄