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
81

Gemma 4 26B A4B

Google
Text & chatVisionVideo
$0.07 / $0.34262.1K tokensAPI only0.34View
82

Qwen3.7 Flash

Qwen
Text & chatVisionVideo
$0.03 / $0.131M tokensAPI only0.13View
83

Qwen3.8 Flash

Qwen
Text & chatVisionVideo
$0.15 / $0.471M tokensAPI only0.47View
84

Kimi K2.6

Moonshot AI
Text & chatVisionReasoning
$0.95 / $4262.1K tokensAPI only4View
85

Claude Opus 4.6

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
86

GPT-5.6 Sol Pro

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
87

GPT-6 Astra Pro

OpenAI
Text & chatVisionReasoning
$10 / $501.05M tokensAPI only50View
88

Claude Opus 4.7

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
89

Qwen3.5-Flash

Qwen
Text & chatVisionVideo
$0.065 / $0.261M tokensAPI only0.26View
90

Kimi K2.5

Moonshot AI
Text & chatVisionReasoning
$0.45 / $2.25262.1K tokensAPI only2.25View
91

Qwen3.6 35B A3B

Qwen
Text & chatVisionVideo
$0.1 / $0.9262.1K tokensAPI only0.9View
92

GLM 4.7

Z.ai
Text & chatStructured JSON outputPrompt caching
$0.4 / $1.75204.8K tokensAPI only1.75View
93

GPT-5.2

OpenAI
Text & chatVisionReasoning
$1.75 / $14400K tokensAPI only14View
94

Qwen3.5-35B-A3B

Qwen
Text & chatVisionVideo
$0.3125 / $1.25262.1K tokensAPI only1.25View
95

GLM 5

Z.ai
Text & chatReasoningTool calling
$0.6 / $1.92204.8K tokensAPI only1.92View
96

Qwen3.5-9B

Qwen
Text & chatVisionVideo
$0.1 / $0.15262.1K tokensAPI only0.15View
97

Grok 4.20

xAI
Text & chatVisionReasoning
$1.25 / $2.52M tokensAPI only2.5View
98

Qwen3 VL 32B Instruct

Qwen
Text & chatVisionReasoning
$0.104 / $0.416131.1K tokensAPI only0.416View
99

MiniMax M2.5

MiniMax
Text & chatReasoningTool calling
$0.27 / $1.08204.8K tokensAPI only1.08View
100

Qwen3 VL 235B A22B Instruct

Qwen
Text & chatVisionReasoning
$0.21 / $1.9262.1K tokensAPI only1.9View

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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