AI Cost Intelligence

Token math, model trade-offs, and the real cost of running AI in production.

Every model provider publishes a per-token rate. Almost nobody publishes what their actual workload costs once you account for retries, context bloat, structured-output schemas, fine-tuning, and the difference between batch and real-time. We do.

Live tools
1
In build
2
Total planned
8

Tools

Why this category exists

  • Pricing changes every quarter

    Anthropic, OpenAI, and Google have each adjusted their pricing structure at least twice in the past 18 months. A calculator that doesn't track these changes is worse than no calculator.

  • Token counts are not intuitive

    A 500-word document is not 500 tokens. Whether you're paying for input, output, or cached context matters enormously. We expose all three.

  • Vendor calculators undercount

    Most vendor estimators show you the per-call cost of a single prompt and stop there. We model your monthly workload including retries, error budget, and the cost of switching providers later.

FAQ

How often is pricing data updated?
Every Monday we re-check the public pricing pages of OpenAI, Anthropic, Google, AWS Bedrock, and Azure OpenAI. The last verification date appears on each tool page.
Do you include cached input discounts?
Yes. Anthropic's prompt caching, OpenAI's batch API, and Gemini's context cache are all modeled in the relevant calculators.
What about open-source models on Together / Replicate?
Llama 3.x, Mistral, and Mixtral on Together AI and Replicate are included in the LLM cost calculator. DeepInfra and Groq coming next.

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