prompt-cache
Cut LLM costs by up to 80% and unlock sub-millisecond responses with intelligent semantic caching.A drop-in, provider-agnostic LLM proxy written in Go with sub-millisecond response
Not yet testedsource: GitHubhomepageGoMITcommit 9fc9025dd148
Go, MIT licensed. The project labels itself: ai, badgerdb, cache, claude, cost optimization, go, langchain and llm.
prompt-cache has not been verified yet.
Measured by Argusic on a fresh machine every time. Every number links to its evidence.
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
No recorded runs.
Topics (from GitHub)
aibadgerdbcacheclaudecost-optimizationgolangchainllmmiddlewaremistralopenaiperformanceragrag-aisemantic-searchvector-database
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/prompt-cache)Questions
- Does prompt-cache run?
- prompt-cache has not been fully verified yet. No recorded run has produced a verdict yet.
- How did Argusic test prompt-cache?
- On a fresh, disposable machine, with every command recorded. 0 attempts are recorded, and the full method is on the methodology page.
- Where is the evidence for prompt-cache?
- All 0 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.