Knowledge distillation for financial large language models: a systematic review of strategies, applications, and evaluation

• Provides the first systematic survey integrating knowledge distillation with financial large language models, addressing a critical research gap. • Introduces a structured taxonomy for distillation strategies and an upstream–midstream–downstream framework for financial applications. • Constructs a multi-dimensional evaluation framework for distilled FinLLMs, emphasizing financial accuracy, reasoning fidelity, and robustness. • Demonstrates KD's role in reducing deployment costs and inference latency, enabling practical FinLLM deployment in resource-constrained environments.