Reasoning AI models: they think before answering, and bill for it

Reasoning
Services found: 169
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
41

Qwen3.7 Plus

Qwen
Text & chatVisionReasoning
$0.32 / $1.281M tokensAPI only1.28View
42

Grok 4.3

xAI
Text & chatVisionReasoning
$1.25 / $2.51M tokensAPI only2.5View
43

DeepSeek V4 Flash 0423

DeepSeek
Text & chatVisionReasoning
$0.088606 / $0.1772121.05M tokensAPI only0.177View
44

GPT-5.4 Mini

OpenAI
Text & chatVisionReasoning
$0.75 / $4.5400K tokensAPI only4.5View
45

Nemotron 3 Ultra

NVIDIA
Text & chatReasoningTool calling
$0.625 / $3.125262.1K tokensAPI only3.125View
46

MiniMax M2.7

MiniMax
Text & chatReasoningTool calling
$0.3 / $1.2204.8K tokensAPI only1.2View
47

Gemini 3.5 Flash-Lite

Google
Text & chatVisionAudio
$0.3 / $2.51.05M tokensAPI only2.5View
48

Qwen3.6 27B

Qwen
Text & chatVisionVideo
$0.3 / $2262.1K tokensAPI only2View
49

GPT-5.4 Nano

OpenAI
Text & chatVisionReasoning
$0.2 / $1.25400K tokensAPI only1.25View
50

Claude Sonnet 4.5

Anthropic
Text & chatVisionReasoning
$3 / $151M tokensAPI only15View
51

Qwen3.5 397B A17B

Qwen
Text & chatVisionVideo
$0.55 / $3.5262.1K tokensAPI only3.5View
52

Claude Haiku 4.5

Anthropic
Text & chatVisionReasoning
$1 / $5200K tokensAPI only5View
53

Qwen3.5-122B-A10B

Qwen
Text & chatVisionVideo
$0.29 / $2.4262.1K tokensAPI only2.4View
54

Mistral Medium 3.5

Mistral AI
Text & chatVisionReasoning
$1.5 / $7.5256K tokensAPI only7.5View
55

Nemotron 3.5 Lightning

NVIDIA
Text & chatReasoningTool calling
$0.08 / $0.2262.1K tokensAPI only0.2View
56

Nemotron 3 Super

NVIDIA
Text & chatReasoningTool calling
$0.085 / $0.4262.1K tokensAPI only0.4View
57

Mistral Small 4

Mistral AI
Text & chatVisionReasoning
$0.15 / $0.6256K tokensAPI only0.6View
58

Trinity Large Thinking

Arcee Ai
Text & chatReasoningTool calling
$0.25 / $0.8262.1K tokensAPI only0.8View
59

Qwen3 Coder Next

Qwen
Text & chatCodingReasoning
$0.12 / $0.8262.1K tokensAPI only0.8View
60

Mistral Large 3 2512

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

Browse by need

A reasoning model works through a problem before it answers, generating hidden thinking tokens along the way. Those tokens bill as output, which is why reasoning costs more than plain generation and why the price spread here - $0.25 to $50 per million - matters more than it looks.

169 models expose reasoning, including every current flagship: Claude Fable 5.1, GPT-6 Astra, Claude Opus 5. Use them for maths, multi-step analysis and code review. For lighter tasks a reasoning model is an expensive way to be slow. Filter for Adjustable thinking as well - 72 models let you cap how long the model deliberates.

Thinking bills as outputThe hidden deliberation is charged at the output rate, which is why the same prompt costs more here.
Depth is adjustableMost current reasoning models let you cap how long they think, turning quality into a dial.
Not always betterOn extraction and classification a reasoning model is slower and dearer for identical results.

Models with this capability

How to choose

  • Use reasoning where the first plausible answer is often wrong: maths, analysis, code review, planning.
  • Prefer models with an adjustable depth control so you can tune cost per task.
  • Watch output limits — deliberation plus answer can hit the max output ceiling on long tasks.
  • Compare on your own hard cases, not on benchmark scores.

Common mistakes

Leaving thinking on maximumDefault depth is rarely optimal. Most tasks finish just as well at a lower setting.
Using reasoning for formattingReshaping text into JSON needs structured output, not deliberation.

Who this suits

AnalystsMulti-step financial and legal reasoning where a missed condition is expensive.
Engineering teamsCode review, migration planning and debugging across many files.
Research workSynthesis across conflicting sources, where the model must weigh rather than summarise.

Frequently asked questions

Why do reasoning models cost more?

They generate hidden thinking tokens before the visible answer, and those tokens bill at the output rate. A hard question can produce several times more billed tokens than its answer suggests.

Can I limit how much a model thinks?

Yes on 72 of them. Claude, Grok, Qwen3 and DeepSeek V4 expose a depth control; DeepSeek switches thinking off entirely.

When is reasoning not worth it?

Classification, routing, extraction and summarising short text. A fast model does these as well for a tenth of the price.

Do reasoning tokens appear in the response?

No — you pay for them but do not see them. Some vendors expose a summary of the reasoning instead.

Is a reasoning model slower?

Noticeably. Expect seconds rather than milliseconds, which rules it out of autocomplete-style features.

Frequently searched

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