Compare estimated LLM and AI API costs across multiple providers using your expected token usage and request volume. This calculator helps you quickly model monthly spend for prompts, completions, and optional cached or discounted input pricing.
An AI API cost calculator estimates how much you may spend based on request volume, average input tokens, and average output tokens. Since most LLM providers bill per million tokens, even small differences in pricing can create large monthly cost changes at scale.
A comparison calculator is useful because different providers may charge separate rates for input, output, and cached input tokens. By entering your own workload assumptions, you can compare realistic monthly costs instead of relying only on headline pricing tables.
This type of tool is especially helpful for teams planning production deployments, chatbot rollouts, document processing pipelines, or agent workflows. It can also support budgeting decisions by showing which provider has the lowest projected spend for your specific usage pattern.
It multiplies your monthly input and output token totals by each provider's price per 1 million tokens, then adds cached input pricing if applicable.
Cached input tokens are prompt tokens that some providers bill at a reduced rate when repeated context or reused prompt segments are served from cache.
Providers use different pricing models, model capabilities, latency targets, and infrastructure costs, so the cheapest option depends on your token mix and workload.
In 2026, raw per-token pricing is often less important than prompt-caching behavior. If your app sends large repeated system prompts, schemas, tool definitions, or long conversation prefixes, compare each provider’s cache discount, cache TTL, and what actually qualifies for a cache hit. A model that looks 20% more expensive on paper can end up cheaper in production if it reliably reuses 5k–20k prompt tokens. Common mistake: benchmarking with one-off prompts, then ignoring cache economics when estimating real monthly spend.