This research introduces Bio-benchmark, a novel framework for evaluating how large language models perform across diverse bioinformatics challenges using prompting techniques.

• Covers 30 different biological tasks to provide a more complete assessment than existing benchmarks
• Enables systematic comparison of different LLMs' capabilities in specialized biological knowledge domains
• Provides valuable insights for selecting appropriate models for specific biomedical applications
• Bridges the gap between general-purpose LLMs and specialized biological tasks

Why It Matters: For medical applications, this benchmark helps identify which language models can most effectively process clinical data, analyze electronic health records, and support biomedical research, potentially accelerating drug discovery and improving healthcare outcomes.

Benchmarking Large Language Models on Multiple Tasks in Bioinformatics NLP with Prompting