FinanceBench
by Islam et al. / Patronus AI · free · Last verified 2026-03-17
FinanceBench is a benchmark designed to evaluate the financial question-answering capabilities of Large Language Models. It uses publicly available corporate documents like 10-K filings and earnings reports to test models on information retrieval, numerical reasoning, and multi-step financial calculations, providing a standardized testbed for financial AI.
https://github.com/patronus-ai/financebench ↗B
B—Above Average
Adoption: BQuality: AFreshness: B+Citations: B+Engagement: F
Specifications
- License
- CC BY-NC 4.0
- Pricing
- free
- Capabilities
- LLM Performance Evaluation, Numerical Reasoning over Financial Data, Information Retrieval from SEC Filings, Multi-hop Question Answering, Financial Statement Analysis, Quantitative Reasoning Assessment, Document-based Question Answering
- Integrations
- Use Cases
- [object Object], [object Object], [object Object], [object Object]
- API Available
- No
- Evaluated Models
- gpt-4o, claude-opus-4, gemini-2-5-pro
- Metrics
- accuracy, exact-match
- Methodology
- 150 questions derived from public company filings with ground-truth answers verified by financial professionals. Models are evaluated with retrieval-augmented (open-book) and closed-book configurations; exact-match and human-judged accuracy are reported.
- Last Run
- 2026-02-10
- Tags
- finance, rag, numerical-reasoning, earnings, qa, llm-benchmark, evaluation, sec-filings, 10-k, information-retrieval, financial-analysis
- Added
- 2026-03-17
- Completeness
- 0.85%
Index Score
62.8Adoption
68
Quality
88
Freshness
78
Citations
72
Engagement
0