Prompt caching AI models: send the same prefix twice, pay once

Prompt caching
Services found: 147
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
61

GPT-5.4

OpenAI
Text & chatVisionReasoning
$2.5 / $151.05M tokensAPI only15View
62

GPT-5.3-Codex

OpenAI
Text & chatVisionCoding
$1.75 / $14400K tokensAPI only14View
63

GPT-Realtime-2.1

OpenAI
Text & chatVisionAudio
$4 / $24128K tokensAPI only24View
64

GPT-Realtime-2.1 Mini

OpenAI
Text & chatVisionAudio
$0.6 / $2.4128K tokensAPI only2.4View
65

Gemini 3.1 Flash-Lite

Google
Text & chatVisionAudio
$0.25 / $1.51.05M tokensAPI only1.5View
66

Gemini Omni Flash

Google
Text & chatVisionAudio
$1.5 / $9API only9View
67

Grok 4.20 Reasoning

xAI
Text & chatVisionReasoning
$1.25 / $2.51M tokensAPI only2.5View
68

Grok 4.20 Non-Reasoning

xAI
Text & chatVisionReasoning
$1.25 / $2.51M tokensAPI only2.5View
69

Grok Build 0.1

xAI
Text & chatAdjustable thinkingWeb search grounding
$1 / $2256K tokensAPI only2View
70

DeepSeek V4 Pro

DeepSeek
Text & chatReasoningAdjustable thinking
1M tokensAPI onlyView
71

DeepSeek V4 Flash

DeepSeek
Text & chatVisionReasoning
1M tokensAPI onlyView
72

Codestral

Mistral AI
Text & chatCodingStructured JSON output
$0.3 / $0.9128K tokensAPI only0.9View
73

Devstral 2

Mistral AI
Text & chatCodingStructured JSON output
256K tokensAPI onlyView
74

Magistral Medium 1.2

Mistral AI
Text & chatStructured JSON outputPrompt caching
128K tokensAPI onlyView
75

Qwen3.8 Max

Alibaba
Text & chatReasoningAdjustable thinking
$2 / $61M tokensAPI only6View
76

Qwen3 VL Plus

Alibaba
Text & chatVisionReasoning
$0.2 / $1.6256K tokensAPI only1.6View
77

Qwen3 VL Flash

Alibaba
Text & chatVisionReasoning
$0.05 / $0.4256K tokensAPI only0.4View
78

GLM 5.2

Z.ai
Text & chatReasoningTool calling
$0.966 / $3.0361.05M tokensAPI only3.036View
79

DeepSeek V3.2

DeepSeek
Text & chatStructured JSON outputPrompt caching
$0.269 / $0.4163.8K tokensAPI only0.4View
80

GPT-5.6 Luna Pro

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

Browse by need

Prompt caching stores an identical prompt prefix between calls, so repeated context is charged at a fraction of the base input rate - typically 10%, and as little as 2.5% on Claude Fable 5.1. If your application sends the same lengthy system prompt with every request, this is usually the biggest saving available to you.

147 models support it. The saving applies to input only, so the effect is largest where prompts are long and answers are short - support bots with detailed instructions, agents with big tool catalogues, RAG systems that resend the same corpus. Cache entries expire, so the economics favour high request frequency against a stable prefix.

Input onlyThe discount never touches output, so it favours long prompts and short answers.
Prefix must match exactlyOne changed character at the start invalidates the whole cached block.
Frequency beats sizeA modest prompt reused constantly saves more than a huge one called twice a day.

Models with this capability

How to choose

  • Put everything stable at the very front: system prompt, tool definitions, reference documents.
  • Keep user-specific content after the cached prefix.
  • Check the cache lifetime — short TTLs punish low-traffic applications.
  • Account for write cost: some vendors charge a premium to create the entry.

Common mistakes

Interleaving variables into the prefixA timestamp at the top of the prompt destroys the cache on every call.
Assuming it helps everywhereShort prompts gain almost nothing.

Who this suits

Agent platformsLarge tool catalogues resent with every step.
RAG systemsThe same corpus queried repeatedly by many users.
Support botsDetailed instructions in front of every short question.

Frequently asked questions

How much does caching save?

Cache reads typically cost 10% of base input, and 2.5% on Claude Fable 5.1. The saving applies to input only.

What has to stay identical?

The prefix — system prompt, tool definitions, reference documents. Anything after the cached portion can vary freely.

When is caching pointless?

Short prompts, or requests spaced far enough apart that the cache expires between them.

How much can I realistically save?

On a long stable prefix, up to 90% of the input portion of the bill.

Does caching change answers?

No. It changes billing and latency, not the computation.

Frequently searched

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