Is it better to use Function Calling or JSON prompting for data extraction?

Function calling is generally better than JSON prompting for data extraction when available. Function calling (tool use) provides guaranteed schema validation, stronger type safety, and more reliable output structure. It eliminates ambiguity about expected format and reduces prompt engineering complexity. LLMs are fine-tuned specifically for function calling, improving reliability. Function calls integrate naturally with code through native data structures. However, JSON prompting offers more flexibility for dynamic schemas and complex nested structures. Function calling can be restrictive for variable output formats. JSON prompting works across all LLM providers, while function calling syntax varies. For production data extraction pipelines, prefer function calling for its reliability and validation. Use JSON prompting when schemas are dynamic or function calling unavailable. Combine approaches: use function calling for structured parts and JSON prompting for flexible sections. Validate all outputs with our JSON Editor at jsonconsole.com/json-editor regardless of method. Function calling reduces error rates by 50-80% versus prompting. Modern best practice favors function calling for critical applications.