QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models
Factual evidence
What the source reports
Researchers introduced QuantEval, a benchmark of 1,575 expert-validated tasks to evaluate LLMs on quantitative finance workflows.
Related reporting
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Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 15 October 2026
- Collected by OneBench
- 16 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2601.08689v3 Announce Type: replace Abstract: Large Language Models (LLMs) have shown strong capabilities in finance-oriented question answering, yet their evaluation on professional quantitative workflows remains…
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OneBench interpretation
Institutional assessment
So what
Quantitative LLM benchmarks allow validation teams to measure model accuracy across realistic financial math and implementation workflows.
Do what
Review the QuantEval benchmark datasets with model risk and validation teams evaluating LLMs for quantitative analyst tasks.