Originally published on AI Tech Connect.
What you need to know Three levers do most of the work. Prompt caching, model routing with cascades, and batch processing each attack a different part of the bill. Stacked sensibly they reach a 50 to 70% reduction for typical workloads. Caching is about reuse, not magic. A cache read costs roughly a tenth of the base input rate, but the first write costs a premium. It only pays off when the same prefix is reused several times within the time-to-live. Routing means cheap-first, escalate-on-failure. Send each request to the cheapest tier that can plausibly handle it, validate the output deterministically, and escalate only when the validator fails. Batching halves the rest. For anything that does not need an answer this second, asynchronous batch processing is roughly 50% cheaper, and it…
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