Crowkis vs Gemini context caching: renting memory by the hour
Google bills cached context per token per hour — a parking meter for your own prompts. Compare that with a cache you simply own.
Gemini's context caching has a distinctive billing model: you pay to store cached tokens per hour, like a parking meter running on your own context. For mega-prompts reused heavily within a window, the math can work. But it frames the relationship clearly — your cache is a rental, priced and bounded by the provider, gone when you stop feeding the meter.
As with every provider-side scheme, the scope is inputs: the model still runs, latency is still seconds, output tokens still bill at full price, and only verbatim context qualifies. The dominant waste in production apps — semantically repeated questions with different words — passes through untouched.
A reservoir you own vs a meter you feed.
Crowkis inverts the ownership. The cache lives on your disk, in your container, with no hourly meter and no provider lock. It stores answers, not just contexts, and matches them by meaning with confidence and trust gates. When you change providers — or run three at once — the corpus comes with you, and the cross-provider bridge keeps serving it.
The bottom line
Pay the parking meter when a giant context genuinely earns it. For everything else, owning your memory beats renting it — especially when the owned version is also the smarter one.