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
1

Claude Fable 5.1

Anthropic
Text & chatVisionReasoning
$10 / $501M tokensAPI only50View
2

GPT-6 Astra

OpenAI
Text & chatVisionReasoning
$10 / $501.05M tokensAPI only50View
3

GPT-6.1 Sol

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
4

GPT-6 Sol

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
5

GPT-6 Luna

OpenAI
Text & chatVisionReasoning
$0.1 / $0.51.05M tokensAPI only0.5View
6

Claude Opus 5.5

Anthropic
Text & chatVisionReasoning
$4 / $201M tokensAPI only20View
7

Claude Sonnet 5.5

Anthropic
Text & chatVisionReasoning
$2 / $101M tokensAPI only10View
8

Grok 4.7

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
9

DeepSeek V4.1 Flash

DeepSeek
Text & chatVisionReasoning
$0.3 / $1.21M tokensAPI only1.2View
10

Qwen3.8 Max Prime

Qwen
Text & chatReasoningLong context 1M+
$3.36 / $10.081M tokensAPI only10.08View
11

GLM 5.3 FlashX

Z.ai
Text & chatVisionVideo
$0.37 / $1.251M tokensAPI only1.25View
12

Ember-1

Fireworks AI
Text & chatVisionReasoning
$3 / $151.04M tokensAPI only15View
13

Claude Opus 5

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
14

Claude Fable 5

Anthropic
Text & chatVisionReasoning
$10 / $501M tokensAPI only50View
15

GPT-5.6 Sol

OpenAI
Text & chatVisionReasoning
$4 / $201.05M tokensAPI only20View
16

GLM 5.3

Z.ai
Text & chatReasoningTool calling
$1.4 / $4.41.31M tokensAPI only4.4View
17

Grok 4.6

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
18

Kimi K3

Moonshot AI
Text & chatVisionVideo
$3 / $151.05M tokensAPI only15View
19

GPT-5.6 Terra

OpenAI
Text & chatVisionReasoning
$2 / $121.05M tokensAPI only12View
20

Claude Opus 4.8

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View

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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