Overview

FLAME is an evaluation framework for testing language models in finance. The project is built around a simple question: if models are going to be used in financial workflows, what evidence do we need before trusting their knowledge, reasoning, and compliance behavior?

The framework is designed to compare models across the tasks that matter in practice rather than just measuring generic benchmark performance.

Benchmark Scope

FLAME covers several parts of the financial reasoning stack:

1. Financial knowledge and terminology
2. Numerical and multi-step reasoning
3. Regulatory and compliance understanding
4. Market analysis and portfolio judgment
5. Robustness under perturbations and adversarial inputs

Evaluation Design

The framework emphasizes repeatable evaluation rather than one-off demos.

1. Standardized task construction for consistent comparisons
2. Clear metrics for accuracy, calibration, and failure analysis
3. Controls for bias and evaluation leakage
4. Modular pipelines that can be extended to new models and task suites

Research Uses

FLAME supports several ongoing research threads:

1. Comparing frontier and open models on finance-specific tasks
2. Measuring the effect of fine-tuning and prompting strategies
3. Studying safety and misuse risks in high-stakes domains
4. Building stronger evidence for domain adaptation claims

Current Status

FLAME is still under active development. Initial benchmark suites are in place, comparisons across open and commercial models have started, and the next step is expanding coverage while tightening the reporting standard for financial model evaluation.