Structured JSON output AI models: parse replies without a regex

Structured JSON output
Services found: 151
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
61

GPT-5.3-Codex

OpenAI
Text & chatVisionCoding
$1.75 / $14400K tokensAPI only14View
62

GPT-Realtime-2.1

OpenAI
Text & chatVisionAudio
$4 / $24128K tokensAPI only24View
63

GPT-Realtime-2.1 Mini

OpenAI
Text & chatVisionAudio
$0.6 / $2.4128K tokensAPI only2.4View
64

Gemini 3.1 Flash-Lite

Google
Text & chatVisionAudio
$0.25 / $1.51.05M tokensAPI only1.5View
65

Nano Banana 2

Google
VisionImage generationStructured JSON output
API onlyView
66

Nano Banana 2 Lite

Google
VisionImage generationStructured JSON output
API onlyView
67

Nano Banana Pro

Google
VisionImage generationStructured JSON output
$2 / $12API only12View
68

Gemini Omni Flash

Google
Text & chatVisionAudio
$1.5 / $9API only9View
69

Gemini 3.5 Transcribe

Google
AudioAdjustable thinkingSpeech-to-text
API onlyView
70

Gemini 3.5 Transcribe Live

Google
AudioAdjustable thinkingSpeech-to-text
API onlyView
71

Grok 4.20 Reasoning

xAI
Text & chatVisionReasoning
$1.25 / $2.51M tokensAPI only2.5View
72

Grok 4.20 Non-Reasoning

xAI
Text & chatVisionReasoning
$1.25 / $2.51M tokensAPI only2.5View
73

Grok Build 0.1

xAI
Text & chatAdjustable thinkingWeb search grounding
$1 / $2256K tokensAPI only2View
74

DeepSeek V4 Pro

DeepSeek
Text & chatReasoningAdjustable thinking
1M tokensAPI onlyView
75

DeepSeek V4 Flash

DeepSeek
Text & chatVisionReasoning
1M tokensAPI onlyView
76

Codestral

Mistral AI
Text & chatCodingStructured JSON output
$0.3 / $0.9128K tokensAPI only0.9View
77

Devstral 2

Mistral AI
Text & chatCodingStructured JSON output
256K tokensAPI onlyView
78

Magistral Medium 1.2

Mistral AI
Text & chatStructured JSON outputPrompt caching
128K tokensAPI onlyView
79

Qwen3.8 Max

Alibaba
Text & chatReasoningAdjustable thinking
$2 / $61M tokensAPI only6View
80

Qwen3 VL Plus

Alibaba
Text & chatVisionReasoning
$0.2 / $1.6256K tokensAPI only1.6View

Browse by need

Structured output means the model is constrained to return JSON matching a schema you supply, so your code can parse the response without defensive cleanup, retries or regex. In production this is the difference between a demo and a pipeline.

151 models support it, spanning $0.25 to $50 per million output tokens. The feature is close to universal among major vendors, so the choice comes down to price and context. Note that schema constraints guarantee shape, not correctness: a model can return a perfectly formed object full of nonsense.

Shape, not truthA schema guarantees parseable output; it says nothing about whether the values are right.
Fewer retriesConstrained decoding removes the cleanup layer most teams write by hand.
Near universalEvery major vendor implements it, so price and context decide rather than availability.

Models with this capability

How to choose

  • Keep schemas shallow — deeply nested structures raise failure rates on smaller models.
  • Mark optional fields properly so the model can omit rather than invent.
  • Validate values after parsing; shape validation is not business validation.
  • Combine with reasoning when extraction requires judgement rather than pattern matching.

Common mistakes

Enormous schemasFifty fields in one call is slower and less accurate than two focused calls.
No fallback pathEven constrained models fail occasionally. Handle it rather than assume success.

Who this suits

Data pipelinesTurning documents and messages into rows without a parsing layer.
BackendsAny place a model output feeds directly into typed code.
AnalyticsConsistent categorisation across large volumes of free text.

Frequently asked questions

Does a schema guarantee correct answers?

No — only correct shape. A model can return a perfectly valid object full of wrong values.

Which vendors support it?

Effectively all the major ones: OpenAI, Anthropic, Google, Mistral, Alibaba, DeepSeek, Z.ai, Moonshot and MiniMax.

Is it slower than plain text output?

Marginally, and the trade is almost always worth it: no retries, no regex, no defensive parsing.

Does it slow generation down?

Marginally. The saving in retries and cleanup outweighs it in nearly every case.

Can I enforce enums?

Yes — constraining a field to a fixed set is the most reliable way to keep classification stable.

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