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
121

Claude Opus 4.5

Anthropic
Text & chatVisionReasoning
$5 / $25200K tokensAPI only25View
122

Nex-N2.5-Pro

Nex Agi
Text & chatVisionReasoning
No public price list262.1K tokensAPI onlyView
123

LFM2.5-2.6B

Liquid
Text & chatReasoningTool calling
No public price list65.5K tokensAPI onlyView
124

Qwen3 VL 8B Instruct

Qwen
Text & chatVisionReasoning
$0.117 / $0.455262.1K tokensAPI only0.455View
125

Seed-2.0-Mini

Bytedance Seed
Text & chatVisionVideo
$0.1 / $0.4262.1K tokensAPI only0.4View
126

Qwen3.6 Flash

Qwen
Text & chatVisionVideo
$0.1875 / $1.1251M tokensAPI only1.125View
127

Qwen3.5-27B

Qwen
Text & chatVisionVideo
$0.195 / $1.56262.1K tokensAPI only1.56View
128

Qwen3 Next 80B A3B Instruct

Qwen
Text & chatReasoningAdjustable thinking
$0.09 / $1.1262.1K tokensAPI only1.1View
129

Qwen3 VL 30B A3B Instruct

Qwen
Text & chatVisionReasoning
$0.15 / $0.6262.1K tokensAPI only0.6View
130

GLM 5V Turbo

Z.ai
Text & chatVisionVideo
$1.2 / $4202.8K tokensAPI only4View
131

Qwen3 Max

Qwen
Text & chatReasoningAdjustable thinking
$0.78 / $3.9262.1K tokensAPI only3.9View
132

Qwen3 Coder Flash

Qwen
Text & chatVisionCoding
$0.195 / $0.9751M tokensAPI only0.975View
133

GLM 5 Turbo

Z.ai
Text & chatReasoningTool calling
$1.2 / $4202.8K tokensAPI only4View
134

Seed 1.6 Flash

Bytedance Seed
Text & chatVisionVideo
$0.075 / $0.3262.1K tokensAPI only0.3View
135

Kimi K2 Thinking

Moonshot AI
Text & chatReasoningTool calling
$0.6 / $2.5262.1K tokensAPI only2.5View
136

GPT-5.2-Codex

OpenAI
Text & chatVisionCoding
$1.75 / $14400K tokensAPI only14View
137

Qwen3.5 Plus 2026-02-15

Qwen
Text & chatVisionVideo
$0.26 / $1.561M tokensAPI only1.56View
138

Qwen3.5 Plus 2026-04-20

Qwen
Text & chatVisionVideo
$0.3 / $1.81M tokensAPI only1.8View
139

Seed-2.0-Lite

Bytedance Seed
Text & chatVisionVideo
$0.25 / $2262.1K tokensAPI only2View
140

Granite 4.0 Micro

IBM
Text & chatReasoningTool calling
$0.017 / $0.112131K tokensAPI only0.112View

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

Ratings 0

Avg. score 0

Rate this page

Help us improve