AI API cost review path for prompt caching and tool calls

An AI tool pricing note should record the checked date, pricing unit, model name, and source link before it compares providers or plans.

AI pricing pages change. They may also use different units: per million tokens, per request, per minute, per image, per tool call, per container, or per seat. A note that says one tool is cheaper than another without the unit is not reusable. The comparison may be wrong as soon as the usage pattern changes.

A durable source trail has a small table: provider, product, model or plan, input unit, cached input unit if available, output unit, non-token charges, region or data-residency modifier, checked date, and source URL. It should also name the expected workload: chat support, code review, document extraction, voice session, image generation, or offline classification.

The checked date matters because pricing is not a timeless fact. The official page may be updated, a model may be retired, or a provider may add a new caching or priority tier. Keeping the date lets a reader know whether to trust the comparison or refresh it.

The note should avoid a universal winner claim. A provider can be cheaper for cached long prompts and more expensive for short interactive answers. Another can be attractive for delayed jobs but unsuitable for a real-time product. The cost question is always tied to workload shape.

The best practical output is not a ranking. It is a reproducible comparison: same task, same expected volume, same quality bar, same latency requirement, same date. That makes later corrections easier and prevents pricing discussions from becoming screenshots without context.

A source trail for AI tool pricing should record the checked date and pricing unit

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