Open FinLLM Leaderboard: Towards Financial AI Readiness
Not on the map. Why?
Abstract (arXiv)
Financial large language models (FinLLMs) with multimodal capabilities are envisioned to revolutionize applications across business, finance, accounting, and auditing. However, real-world adoption requires robust benchmarks of FinLLMs' and FinAgents' performance. Maintaining an open leaderboard is crucial for encouraging innovative adoption and improving model effectiveness. In collaboration with Linux Foundation and Hugging Face, we create an open FinLLM leaderboard, which serves as an open platform for assessing and comparing AI models' performance on a wide spectrum of financial tasks. By demoncratizing access to advances of financial knowledge and intelligence, a chatbot or agent may enhance the analytical capabilities of the general public to a professional level within a few months of usage. This open leaderboard welcomes contributions from academia, open-source community, industry, and stakeholders. In particular, we encourage contributions of new datasets, tasks, and models for continual update. Through fostering a collaborative and open ecosystem, we seek to promote financial AI readiness.
Key facts. Cited by 6 papers in the map (data through 13 Oct 2026). First posted on arXiv 19 Jan 2025.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 5; 2026: 1.
6 papers.
- 2025Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarkingcited by 21
- 2026RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?cited by 9
- 2025FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domaincited by 8
- 2025Interpretable LLMs for Credit Risk: A Systematic Review and Taxonomycited by 5
- 2025Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attentioncited by 2
- 2025Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agentscited by 2
- 2026RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?6 Feb 2026
- 2025Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents20 Oct 2025
- 2025FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domain17 Oct 2025
- 2025Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention18 Aug 2025
- 2025Interpretable LLMs for Credit Risk: A Systematic Review and Taxonomy4 Jun 2025
- 2025Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking16 May 2025