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guidesMay 9, 2026· 5 min read

How to cache LiteLLM LLM calls with Crowkis

Add a semantic cache to LiteLLM so repeated and reworded questions are served for free, no rewrite, self-hosted.

The cheapest token is the one you never spend twice. If you build with LiteLLM, most of that repetition is invisible in your code but very visible on your bill. A semantic cache in front of your model calls fixes it.

The lowest-friction path is the OpenAI-compatible gateway: point LiteLLM's base URL at Crowkis and every model call flows through a semantic cache. Repeated and reworded prompts are served from cache with no upstream call; new ones pass through and get cached.

LiteLLM + Crowkis gateway
# point LiteLLM at the Crowkis gateway
base_url = "http://127.0.0.1:6380/v1"   # semantic cache in front of your provider
In plain words: You don't restructure your LiteLLM app. You change where the calls go, and repeats stop costing money.

On repetitive workloads this cuts LLM costs up to 60-70% on repetitive workloads, and every hit comes back with a confidence score so reuse stays safe. Community edition ships at full power, free to run.