A FinanceGPT Large Quantitative Model is a governed quantitative model system used for numerical finance. “Large” describes the quantitative problem and model system, not a marketing parameter count.
Models calculate. Evidence stays attached.
Financial data flows through quantitative methods and model modules, while evaluation, versioning, lineage and reproducibility evidence remain attached to the output.
The language model is not the calculator.
FinanceGPT separates language interpretation from quantitative calculation. Outputs can carry the model, inputs, assumptions, version and execution evidence used to produce them.
Take a governed LQM from training to an evidence-backed artifact.
The LQM developer workflow is designed around model lineage, evaluation, evidence and controlled publication rather than opaque model deployment.
Use the application designed for the work.
FinanceGPT supports financial creation; EquityGPT supports portfolio construction and management; FinanceGPT Labs provides the complete platform; FinanceGPT Developers provides APIs and model tooling; FinanceGPT Tools provides focused utilities; FinanceGPT Chat provides conversational finance.