Workload calculator
LLM API Cost Calculator
Estimate monthly API spend from tokens, requests, cache reuse, and batch pricing. Enter your workload first, or use a preset as a shortcut.
Usage preset
Choose a preset or scroll for custom input.
Explore benchmark scores to see which models perform best on specific tasks.
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Advanced options
Cost estimates use the generated model database last built on Aug 10, 2026. Pricing, lifecycle, and capability fields can be incomplete or provider-specific, so verify production decisions with the official provider.
How to use this page
Start with a simple preset, then change tokens and request volume to match your product. If you already know the workload type, the use-case pages give a more guided comparison.
How pricing is calculated
Costs are calculated as (tokens ÷ 1,000,000) × price per 1M tokens. Input and output tokens are priced separately — output is typically 3–5× more expensive. The cache hit rate reduces the effective input cost by applying a lower cached price to matched requests. The formula: total = (inputTokens × inputPrice + outputTokens × outputPrice) × requests × (1 − cacheDiscount).
Read the calculator examples guide for chatbot, RAG, summarization, and coding-agent inputs before changing the fields.
Check when a subscription is enough and when usage-based API pricing matters for product work.
Compare OpenAI, Anthropic, Google, Mistral, and DeepSeek across cheapest chat, mid-range, and reasoning model pricing.
See MMLU, GPQA, HumanEval, and other benchmark scores across providers to understand model quality beyond pricing.
Put 2-3 models next to each other to compare pricing, context windows, modalities, and capabilities.