This is a deep dive into benchmarking methodologies for medical LLM and NLP models comparing accuracy, reliability, and applicability across Azure Health AI, AWS Comprehend Medical, GCP Healthcare Natural Language API, OpenAI’s GPT 4.5, Claude Sonnet 3.7, and John Snow Labs’ Medical LLMs. We’ll survey benchmarks covering some of the most popular real‑world applications of medical language models, including:

• Information extraction from clinical documentation
• Anonymization and de-identification
• Summarizing patient histories
• Patient risk adjustment and HCC coding