TokelyPractical ways to cut LLM API spend: per-model discounts, prompt caching billed correctly, lowest-cost routing, right-sized models and hard budgets per key.
By TokelyReviewed The biggest savings come from model choice, prompt caching and price per token. Tokely publishes per-model rates that are often below the developer's list price, bills cached prefixes at the cache-read rate, can route each request to its cheapest healthy supplier and enforces budgets per account and key.
Many Tokely rates are below the developer's published price for the exact same model, with no platform fee. Compare your model in the price table and calculator before changing anything else.
Agents and chat apps resend the same system prompt, tools and documents. With prompt caching, the repeated prefix is billed at the cache-read rate, a fraction of normal input. Tokely records cache reads and writes per request and never bills cached tokens a second time as regular input.
Lowest-cost routing sends each request to the cheapest healthy route for the same model. Use it for batch-like and background workloads; keep Balanced or Fixed where latency or a specific supplier matters.
Use small models for classification, extraction and routing, and reserve frontier models for hard reasoning. One key and one balance make it cheap to test a smaller model on a slice of traffic.
Give each service its own API key with a budget and an allowed model list. Requests that would exceed a limit are rejected before they run. Set max_tokens deliberately: Tokely reserves against it.
It depends on how much of each request repeats. For coding agents with long, stable context, most input tokens can be cache reads billed at roughly a tenth of the input rate.
No. You pay the published per-model rate from a prepaid balance; payment-network costs are shown at checkout.
Check the model, compare the rate, and connect with a Tokely key.