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An API's input-token price alone is not the cost of a conversation. Include ordinary input, cache reads, cache writes and output. For one million total tokens with 40% ordinary input, 40% cache reads and 20% output, the scenario cost is 0.4 × input rate + 0.4 × cache-read rate + 0.2 × output rate. This is a stated scenario, not measured average usage.
Cost = (ordinary input tokens × input rate + cache-read tokens × read rate + cache-write tokens × write rate + output tokens × output rate) / 1,000,000. Do not count cached tokens twice.
The no-cache baseline for the 40/40/20 scenario is 0.8 × input rate + 0.2 × output rate. Both represent 1M total tokens and the same output share; the cache scenario excludes initial cache writes.
Include initial cache writes, misses and later reads from a representative set of requests. Effective cost per million total tokens = total cost / total tokens × 1,000,000. Compare providers using the same model, token mix and billing categories.
Open the documentation's cache-pricing table for current model-by-model scenario costs, then compare your estimate with Logs. A lower cache-read rate saves money only on tokens actually served from cache.
The scenario excludes cache writes, hosting, client subscriptions and other non-token charges. It is not a guarantee of cache hits. ApiClo's current rates and actual usage determine the charge; the formula supports comparison without promising the cheapest provider for every task.
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