Structured outputs and JSON mode across LLM APIs
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Contents
Short answer. Every major provider can force JSON, but they differ in whether the output is guaranteed to match a schema. Prefer schema-constrained modes or a tool call with a schema; fall back to JSON mode plus validation and a retry.
Comparison
| Provider | Mechanism | Schema-enforced |
|---|---|---|
| OpenAI | response_format: { type: "json_schema", strict: true } or strict tools |
Yes |
| Anthropic | Tool use with an input_schema (force with tool_choice) |
Yes, via tool schema |
| Google Gemini | responseMimeType: application/json + responseSchema |
Yes |
| Open models (vLLM, llama.cpp, Ollama) | Grammar or JSON-schema constrained decoding | Yes where supported |
Practical rules
- Ask for exactly the fields you need; unbounded free text inside JSON invites truncation.
- Always parse and validate; a "guaranteed" schema still allows semantically wrong values.
- Keep an
explanationfield out of strict schemas unless you want longer outputs.
Sources
- OpenAI Structured outputs, Anthropic Tool use, Google Structured output (checked 2026-09-10).