Free tool

LLM API cost calculator

Estimate your monthly spend for any model and token volume — then see equal-or-better models that cost less. Prices refresh daily across every major provider and host.

Enter volumes in millions of tokens (e.g. 10 = 10,000,000). Uses provider list prices per 1M tokens; cached-input discounts and tiered rates aren’t applied.

Estimated monthly cost

$110

gpt-5.5 · OpenAI

Equal-or-better coding, lower cost

  • google/gemini-2.5-pro

    DeepInfra · 83.1% coding

    $32.50/mo

    save $77.50 (70%)

  • o3

    OpenAI · 76.9% coding

    $36.00/mo

    save $74.00 (67%)

  • deepseek-v3.2

    DeepSeek · 74.2% coding

    $3.60/mo

    save $106 (97%)

  • moonshotai/Kimi-K2-Instruct

    DeepInfra · 59.1% coding

    $9.00/mo

    save $101 (92%)

Track this automatically

Prices updated 11 July 2026. See the full LLM API Pricing Index.

How the calculator works

How is the LLM cost calculated?
Monthly cost = (input price per 1M tokens × your input millions) + (output price per 1M tokens × your output millions), using provider list prices refreshed daily. Cached-input discounts, batch rates, and long-context surcharges are not applied, so it is a conservative list-price estimate.
How do I find a cheaper model without losing quality?
Pick your current model and volume, and the calculator lists models with an equal-or-better Aider polyglot coding score that cost less for the same usage — ranked by score, with the monthly saving. Switching to a cheaper host of the same open-weight model is a zero-quality-risk saving.
Are these real, current prices?
Yes — prices come from the StackSpend LLM Pricing Index, synced daily from public sources across OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, and inference hosts like Groq, Together AI, Fireworks, and DeepInfra.

Stop estimating. Track what you actually spend.

StackSpend connects read-only to your AI providers, turns every model into one daily cost signal, and flags cheaper equal-quality swaps against your real usage — not a guess.