Token Cost Calculator

A token cost calculator converts raw token counts into real-world API cost estimates across language model providers. Unlike a token counter (which takes raw text as input), a token cost calculator accepts token quantities you already know — from your tokenizer, prompt template, or API response metadata — and translates them into per-call and projected monthly expenses. This makes it the ideal tool for developers who already have token measurements and need to quickly compare costs across OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, and other providers using a single interface.

1. Enter your token counts: Input the number of input tokens (your prompt) and output tokens (the expected response). Use the sliders for fast adjustment or type exact values from your tokenizer output.
2. Configure cost optimizations: Toggle cached input tokens to model prompt caching or context caching savings. Cached tokens are billed at a significantly reduced rate on supported models (typically 75–90% cheaper than standard input).
3. Set your workload volume: Enter your expected requests per period (daily, monthly, or yearly) to see projected total spending. The cost-per-call and total forecasts update instantly as you adjust inputs.
4. Compare and filter: Use the provider filter, sort controls, and the cost-effective toggle to narrow down the comparison table. Click any row to set it as your primary model and see its detailed cost breakdown. Add custom models with your own rates to benchmark private deployments.

• Standard Input Cost: Uncached prompt tokens billed at each model's published input rate per million tokens.
• Cached Input Cost: Tokens served from prompt cache or context cache, billed at a discounted rate (typically 10–25% of the standard input rate) on supported models.
• Output Cost: Response tokens generated by the model, billed at the output rate — typically 3× to 8× higher than the input rate depending on the provider.
• Projected Period Cost: Per-call cost multiplied by your request volume and the selected time period (daily, monthly, or yearly) to produce accurate spending forecasts.

To reduce your API costs: (1) Use this token cost calculator to identify lower-cost models that can handle your task — for extraction, classification, and summarization, models like GPT-4o mini, Claude 3.5 Haiku, or Gemini 2.5 Flash often perform comparably to expensive flagship models. (2) Enable prompt caching for static content like system instructions, few-shot examples, or reference documents to cut input costs by up to 90%. (3) Keep output tokens lean — shorter, more precise responses drastically reduce billing since output rates are 3–8× higher than input rates. (4) Revisit your workload estimates regularly in this token cost calculator as model prices change frequently.