AI API Budget & Monthly Cost Calculator
Project monthly and annual AI API costs across OpenAI, Anthropic, Google, and Groq based on your request volume.
Project your daily, monthly, and annual AI API spend across Anthropic, OpenAI, and Google Gemini models, with optional prompt caching and batch API discounts.
Usage Parameters
Total API calls per day
System prompt + context + message
Expected completion length
Compare models:
Lowest Cost Option
Claude Haiku 5.5
$6.000/mo
Daily Token Volume
0.80M
tokens processed per day
Highest Tier Option
gemini-4-argon
$120.00/mo
| Model | Provider | Per Request | Daily | Monthly (30d) | Yearly | Source |
|---|---|---|---|---|---|---|
| Claude Haiku 5.5Lowest | Anthropic | $0.000200 | $0.2000 | $6.000 | $73.00 | 2026-10-16 |
| gpt-6-luna | OpenAI | $0.000200 | $0.2000 | $6.000 | $73.00 | 2026-10-16 |
| gemini-3.8-flash | $0.001500 | $1.500 | $45.00 | $547.50 | 2026-10-16 | |
| Claude Sonnet 5.5 | Anthropic | $0.004000 | $4.000 | $120.00 | $1,460.00 | 2026-10-16 |
| gpt-6.1-sol | OpenAI | $0.004000 | $4.000 | $120.00 | $1,460.00 | 2026-10-16 |
| gemini-4-argon | $0.004000 | $4.000 | $120.00 | $1,460.00 | 2026-10-16 |
Prices checked on 2026-10-16 from official provider documentation ( Anthropic, OpenAI, Google Gemini).
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What is the AI API Budget & Monthly Cost Calculator?
The AI API Budget Calculator models monthly and annual cloud inference costs for production AI applications using verified October 2026 pricing. By inputting your daily request volume, average prompt/response sizes, cached-input hit rate, and batch mode usage, you can compare multi-model pricing side-by-side.
Who is the AI API Budget & Monthly Cost Calculator for?
Designed for engineering leads, startup founders, CTOs, and finance teams forecasting AI API budgets and evaluating model tier trade-offs.
How to Use the AI API Budget & Monthly Cost Calculator
- Enter your anticipated daily API request volume.
- Set average input tokens per request (system prompt + user input + retrieved context).
- Set average output tokens per request (model response length) and optional cached/batch toggles.
- Compare per-request, daily, monthly, and yearly cost projections across models.
Worked Calculation Example
Frequently Asked Questions
How can I reduce my monthly AI API costs?
Top cost optimization strategies include: 1) Tiered model routing (using nano/mini or flash models for classification and extraction), 2) Prompt prefix caching (up to 75–90% off cached input tokens), 3) Batch API processing (50% discount for asynchronous workloads), and 4) Constraining max output tokens.
What is prompt caching and how does it save money?
Providers like OpenAI, Anthropic, and Google offer discounted cached-input rates (up to 75–90% cheaper) on repeated prompt prefixes such as system instructions, few-shot examples, or shared document context.
How is monthly cost computed?
Monthly cost = (Daily Requests × Input Tokens × Input Rate / 1M + Daily Requests × Output Tokens × Output Rate / 1M) × 30 days.
Why is output token pricing higher than input token pricing?
Generating output tokens requires autoregressive sequential GPU inference, which consumes significantly more compute resources than processing input prompt tokens in parallel.
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