Structured JSON output AI models: parse replies without a regex

Prices from official vendor price lists · October 2026
151 models that return responses matching a schema you define, so your code can parse them without cleanup. Output prices run from $0.1 to $180 per 1M tokens across the 143 models with a paid per-token price; 79 have a free tier and 69 ship open weights.
Structured JSON output
Services found: 151
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
41

GPT-5.4 Mini

OpenAI
Text & chatVisionReasoning
$0.75 / $4.5400K tokensAPI only4.5View
42

MiniMax M2.7

MiniMax
Text & chatReasoningTool calling
$0.3 / $1.2204.8K tokensAPI only1.2View
43

Gemini 3.5 Flash-Lite

Google
Text & chatVisionAudio
$0.3 / $2.51.05M tokensAPI only2.5View
44

Qwen3.6 27B

Qwen
Text & chatVisionVideo
$0.3 / $2262.1K tokensAPI only2View
45

GPT-5.4 Nano

OpenAI
Text & chatVisionReasoning
$0.2 / $1.25400K tokensAPI only1.25View
46

Claude Sonnet 4.5

Anthropic
Text & chatVisionReasoning
$3 / $151M tokensAPI only15View
47

Qwen3.5 397B A17B

Qwen
Text & chatVisionVideo
$0.55 / $3.5262.1K tokensAPI only3.5View
48

Claude Haiku 4.5

Anthropic
Text & chatVisionReasoning
$1 / $5200K tokensAPI only5View
49

Qwen3.5-122B-A10B

Qwen
Text & chatVisionVideo
$0.29 / $2.4262.1K tokensAPI only2.4View
50

Gemma 4 31B

Google
Text & chatVisionVideo
$0.09 / $0.34262.1K tokensAPI only0.34View
51

DeepSeek V3.1 Terminus

DeepSeek
Text & chatStructured JSON outputPrompt caching
$0.27 / $1163.8K tokensAPI only1View
52

Mistral Medium 3.5

Mistral AI
Text & chatVisionReasoning
$1.5 / $7.5256K tokensAPI only7.5View
53

Mistral Small 4

Mistral AI
Text & chatVisionReasoning
$0.15 / $0.6256K tokensAPI only0.6View
54

Qwen3 Coder Next

Qwen
Text & chatCodingReasoning
$0.12 / $0.8262.1K tokensAPI only0.8View
55

Mistral Large 3 2512

Mistral AI
Text & chatVisionReasoning
$0.5 / $1.5262.1K tokensAPI only1.5View
56

Devstral 2 2512

Mistral AI
Text & chatCodingStructured JSON output
$0.4 / $2262.1K tokensAPI only2View
57

Ministral 3 14B 2512

Mistral AI
Text & chatVisionReasoning
$0.2 / $0.2262.1K tokensAPI only0.2View
58

Ministral 3 8B 2512

Mistral AI
Text & chatVisionReasoning
$0.15 / $0.15262.1K tokensAPI only0.15View
59

Ministral 3 3B 2512

Mistral AI
Text & chatVisionReasoning
$0.1 / $0.1131.1K tokensAPI only0.1View
60

GPT-5.4

OpenAI
Text & chatVisionReasoning
$2.5 / $151.05M tokensAPI only15View

Browse by need

Reasoning models169 modelsCoding assistants17 modelsVision and images156 modelsLong context 1M+82 modelsFree tier available80 modelsOpen weights88 models

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

The 151 models below all support this capability. Prices are input and output per 1M tokens from the vendor official price list; for dirhams multiply by 3.6725. Tap a card to open the model page.

Claude Fable 5.1
#1
Anthropic
in $10out $501M tokens
GPT-6 Astra
#2
OpenAI
in $10out $501.05M tokens
GPT-6.1 Sol
#3
OpenAI
in $2out $101.05M tokens
GPT-6 Sol
#4
OpenAI
in $2out $101.05M tokens
GPT-6 Luna
#5
OpenAI
in $0.1out $0.51.05M tokens
Claude Opus 5.5
#6
Anthropic
in $4out $201M tokens
Claude Sonnet 5.5
#7
Anthropic
in $2out $101M tokens
Grok 4.7
#8
xAI
in $2out $6500K tokens

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.

Related filters

Tool calling166 models that call your functions
Batch API140 models with half-price async processing
Code execution47 models that run code in a sandbox
Low latency73 small, fast models for volume
All 239 modelsThe full rating with filters and prices

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.

Frequently searched

By capabilityReasoningCodingVisionLong context 1M+Free tierOpen weightsLow latencyRealtime voiceImage generation
By vendorAnthropic (13)OpenAI (30)Google DeepMind (17)xAI (8)Meta (6)DeepSeek (9)Mistral AI (11)Alibaba (Qwen) (34)Z.ai (12)Moonshot AI (5)
Popular modelsClaude Fable 5.1GPT-6 AstraClaude Opus 5Claude Fable 5GPT-5.6 SolGLM 5.3Grok 4.6Kimi K3GPT-5.6 Terra
By deliveryBatch APIPrompt cachingPriority tierFrontier tierProprietary APITool callingStructured JSONWeb searchMultilingual

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