Prompt Caching
Also written: Prompt Caching Optimization
Prompt caching saves money and time by storing and reusing previous AI responses to identical prompts.
Imagine you ask an AI a question, and it gives you an answer. If you ask the exact same question again later, the AI has to figure out the answer all over again. Prompt caching is like giving the AI a notepad where it can write down the answers to common questions.
When you ask a question that's already on the notepad, the AI just looks up the answer instead of thinking it through from scratch. This makes getting the answer much faster and cheaper, especially if you ask the same things many times. For example, if you're using an AI to help write code and you frequently ask it to explain a specific function, prompt caching can store that explanation so you get it instantly on future requests.
Prompt caching is an optimization technique that stores the output generated by a language model for a given input prompt. When the same prompt is encountered again, the system retrieves the cached response instead of performing a new inference pass. This significantly reduces latency and computational cost, particularly for applications with repetitive queries or long, stable contexts.
The effectiveness of prompt caching depends on the frequency of identical prompts and the cost of inference. Tradeoffs include the memory overhead for storing the cache and the potential for stale responses if the underlying model is updated without invalidating the cache.
Prompt caching is gaining attention as AI labs focus on cost efficiency and performance. Companies are highlighting methods to reduce computational load and speed up responses, especially for recurring tasks or conversations. This optimization is crucial for making advanced AI models more accessible and affordable for developers and users.
- Агент AntigravityGoogle · Gemini Models ·
- Best Practices GuidexAI · xAI Docs: Guides ·
- Stop Overpaying for Intelligence | DevDay 2026OpenAI · OpenAI on YouTube ·
- Antigravity-AgentGoogle · Gemini Models ·
- Antigravity AgentGoogle · Gemini Models ·
- Optimizing for cost and intelligenceAnthropic · Model Overview ·
- OpenAI Cookbook: Add GPT-5.6 disclaimer to Prompt Caching 201 (#2845)OpenAI · OpenAI Cookbook ·
- Introducing GPT-5.1 for developersOpenAI · OpenAI News ·
- Anthropic Claude
- Anthropic mentions prompt caching as a method to optimize costs for Claude AI.
- Google Gemini
- Google's Antigravity Agent appears to use prompt caching principles to automate complex tasks more efficiently.
- OpenAI ChatGPT
- OpenAI has provided examples and disclaimers for prompt caching in its developer resources, and mentioned extended caching with GPT-5.1.
- xAI Grok
- xAI Grok suggests using its Responses API to retain reasoning history, which functions similarly to prompt caching for multi-turn interactions.
- Response Streaming
- This sends back the AI's answer piece by piece as it's gener
- Context Window Management
- This involves deciding what information to keep in th
- Fine-tuning
- This retrains a model on new data to change its behavior, rather th
The concept of caching is fundamental in computer science to speed up data retrieval. For large language models, prompt caching specifically emerged as a practical optimization strategy within the AI development community to address the high cost and latency of repeated inferences.
In a chat interface with an AI like ChatGPT or Claude, ask it a specific question, for example, 'What is the capital of France?'. Then, ask the exact same question again. Notice if the second answer appears faster than the first. If you were using an API, you could observe the latency difference more directly.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- Cost tipImplement Prompt Caching for AI Cost ReductionCache AI prompts to avoid redundant computations and save money. · 30 min
- Cost tipUse prompt caching to cut agent loop costs significantlyImplement prompt caching to reduce agent loop costs by up to 5.3x and triage agent bills by 88%. · 15 min
- Cost tipGPT-5.1 prompt caching reduces costExtended prompt caching for GPT-5.1 makes follow-up questions cheaper by reusing context. · 2 min
- Setting tipExtend GPT-5.1 prompt cache retention to 24 hoursUse prompt_cache_retention='24h' for faster, cheaper follow-up questions. · 1 min
- PromptRole-play a student struggling with math for AI tutor simulationSimulate a student's math struggles and uncertainty for AI tutor evaluation. · 5 min
Questions people ask
- Does prompt caching make the AI smarter?
- No, prompt caching doesn't make the AI itself smarter. It's a shortcut that saves time and money by reusing previous answers, not by improving the AI's understanding.
- When is prompt caching most useful?
- It's most useful when you or your application repeatedly ask the AI the same questions or provide identical prompts, especially in scenarios where speed and cost are important.
First seen on Subvolts Nov 13, 2025. Updated Oct 18, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.