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
21

Qwen3.8 Max (0902)

Qwen
Text & chatVisionVideo
$2 / $61M tokensAPI only6View
22

Qwen3.8 2.4T A95B

Qwen
Text & chatReasoningAdjustable thinking
$2 / $61.05M tokensAPI only6View
23

Gemini 3.7 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
24

Grok 4.5

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
25

GPT-5.5

OpenAI
Text & chatVisionReasoning
$5 / $301.05M tokensAPI only30View
26

Claude Sonnet 5

Anthropic
Text & chatVisionReasoning
$2 / $101M tokensAPI only10View
27

GPT-5.6 Luna

OpenAI
Text & chatVisionReasoning
$0.2 / $1.21.05M tokensAPI only1.2View
28

DeepSeek V4 Pro 0813

DeepSeek
Text & chatReasoningAdjustable thinking
$1.0494 / $3.14821.05M tokensAPI only3.148View
29

DeepSeek V4 Flash 0731

DeepSeek
Text & chatVisionReasoning
$0.065 / $0.181.31M tokensAPI only0.18View
30

Gemini 3.6 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
31

Qwen3.8 27B

Qwen
Text & chatVisionVideo
$0.42 / $31M tokensAPI only3View
32

DeepSeek V4 Pro 0423

DeepSeek
Text & chatReasoningAdjustable thinking
$0.95526 / $1.910521.05M tokensAPI only1.911View
33

Claude Sonnet 4.6

Anthropic
Text & chatVisionReasoning
$3 / $151M tokensAPI only15View
34

Qwen3.7 Max

Qwen
Text & chatReasoningAdjustable thinking
$2.5 / $7.51M tokensAPI only7.5View
35

MiniMax M3

MiniMax
Text & chatVisionVideo
$0.3 / $1.21.05M tokensAPI only1.2View
36

GLM-5.1

Z.ai
Text & chatReasoningTool calling
$1.4 / $4.4200K tokensAPI only4.4View
37

Kimi K2.7 Code

Moonshot AI
Text & chatVisionCoding
$0.71 / $3.5262.1K tokensAPI only3.5View
38

Qwen3.7 Plus

Qwen
Text & chatVisionReasoning
$0.32 / $1.281M tokensAPI only1.28View
39

Grok 4.3

xAI
Text & chatVisionReasoning
$1.25 / $2.51M tokensAPI only2.5View
40

DeepSeek V4 Flash 0423

DeepSeek
Text & chatVisionReasoning
$0.088606 / $0.1772121.05M tokensAPI only0.177View

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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