Comparison
JSON Mode vs Structured Output
JSON Mode and Structured Output are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for JSON Mode
JSON Mode comes up when the question is fundamentally about inference.
OpenAI `response_format: { type: "json_object" }`.
When you would reach for Structured Output
Any time you need to programmatically parse model output — extraction, function arguments, classification, multi-step pipelines.
OpenAI Structured Outputs with a Pydantic / JSON Schema.
Frequently asked
What is the difference between JSON Mode and Structured Output?
JSON Mode: JSON mode is a provider-specific feature that forces the model to emit syntactically valid JSON. Stronger than asking nicely; weaker than full structured output with a schema. Structured Output: Structured output constrains an LLM to emit text matching a schema — usually JSON. The model can be guaranteed to produce valid output that your code can parse without retries.
When should I use JSON Mode vs Structured Output?
JSON Mode is the right concept when you are focused on inference. Any time you need to programmatically parse model output — extraction, function arguments, classification, multi-step pipelines.
Are JSON Mode and Structured Output the same thing?
No. JSON Mode is inference; Structured Output is inference. They are related but address different parts of the AI stack.