LLM API Cost Calculator
Calculate the cost of GPT-5, Claude, Gemini and Grok API calls from token counts and daily request volume. See cost per request, per day and per month instantly.
How Is LLM API Cost Calculated?
Large language model APIs like GPT, Claude, Gemini and Grok are not billed per request, they are billed per token. Every call consumes two kinds of tokens: the input (prompt) tokens you send to the model, and the output (completion) tokens the model generates. Providers price these separately, and output tokens are almost always 4 to 8 times more expensive than input tokens, because generating text costs far more compute than reading it.
This tool computes cost per request as: (input tokens / 1,000,000 x input price) + (output tokens / 1,000,000 x output price). Daily cost multiplies that by your daily request count, and monthly cost multiplies the daily figure by 30. By entering your real production traffic (average prompt length, average response length, daily request volume) you can estimate your monthly API bill before shipping a feature. To measure token counts precisely, try our Token Counter tool.
Model Price Table (per 1 Million Tokens, USD)
The prices below are approximate as of 2026 and providers can change them without notice. Always confirm current pricing on the provider's official pricing page before making a decision.
| Model | Input ($/1M) | Output ($/1M) |
|---|---|---|
| GPT-5 | 1.25 | 10 |
| GPT-5 mini | 0.25 | 2 |
| Claude Opus 4.8 | 5 | 25 |
| Claude Sonnet 5 | 3 | 15 |
| Claude Haiku 4.5 | 1 | 5 |
| Gemini 2.5 Pro | 1.25 | 10 |
| Gemini 2.5 Flash | 0.30 | 2.50 |
| Grok 4 | 3 | 15 |
Frequently Asked Questions
How does LLM API pricing work?
LLM providers price input (prompt) and output (response) tokens separately; output tokens are usually several times more expensive than input tokens because generating text costs more compute than reading it. Prices are typically quoted in USD per 1 million tokens.
What is a token, roughly how many characters is it?
A token is the small chunk of text a model processes. In English text, one token is roughly 4 characters, or about 0.75 words. Other languages can tokenize at a different rate. For an exact count, use our Token Counter tool.
How can I reduce LLM API cost?
Shorten prompts, trim unnecessary context or chat history, switch to a cheaper mini/flash model, cap output length (max tokens), use prompt caching, and cache repeated requests. These changes typically cut API cost significantly.