Prompt caching proxy · Founding price $49/mo

Stop Paying 100% Price for 90% Repeated Prompts.

Drop in 1 line of code to auto-cache system prompts, RAG context, and agent memory at the edge.

BEFOREBurning money

import OpenAI from 'openai';
const openai = new OpenAI();

AFTERInstant 80% Cache Savings

import { CacheFlowOpenAI } from '@cacheflow/sdk';
const openai = new CacheFlowOpenAI({ autoCache: true });

Calculate your instant savings using our free estimator below

Edge prefix matching reuses KV state without an extra round trip on cache hits.

Stable system + RAG blocks are reordered to maximize provider cache hit rates.

One SDK surface for OpenAI, Anthropic, Gemini, and DeepSeek cache economics.

Repeated attention prefixes stay warm. Only the varying suffix is recomputed and billed at full input rates.

[cached] system prompt · tools · RAG corpus

[cached] agent memory · policies

[fresh] user turn · tool results · delta

Attention savings

Cache reads are billed at a fraction of input rates (often 50–90% off). CacheFlow keeps the stable prefix identical so providers keep hitting.

Free · Client-side

Paste a system prompt, RAG block, or schema. Token counts run in your browser (o200k_base approximation for non-OpenAI models).

System prompt / RAG / schema

Model

Requests / day10,000

Avg. output tokens400

Total input tokens

245

Live in-browser count

Monthly uncached

$1,384

Full input every request

Monthly with caching

$1,292

Prefix cache read rate

Waste score

$91.87

7% of spend is redundant

Prompt waste

Repeating system tokens are billed at full input rates without caching. At 10,000 req/day on GPT-4o, that burns $91.87/mo.

You are burning $91.87/mo on redundant system tokens. Eliminate this with CacheFlow's 1-line proxy SDK.