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LLM Token & Cost Calculator

Estimate token count and API cost for your prompts across GPT-4, Claude 3.5/Opus, Gemini 1.5, and more. Helps budget AI projects before they run.

Paste Your Prompt or Text
Response Length Estimate
Requests per month1,000
11,000,000
estimated tokens in this prompt
Cost per 1,000 requests
GPT-4o (OpenAI)
GPT-4o mini
Claude Sonnet 4
Claude Opus 4
Gemini 1.5 Flash
Gemini 1.5 Pro
Llama 3 (via Groq)
Monthly Cost at Scale
Requests/month
GPT-4o monthly cost
Claude Sonnet monthly cost
GPT-4o mini monthly cost
Cheapest option
Token estimation uses ~0.75 tokens per word (standard approximation). Actual token counts vary by model tokenizer. Prices are approximate and may change — verify at each provider's pricing page before budgeting.
Frequently Asked Questions
How many tokens is 1000 words?

Approximately 1,333 tokens. The standard approximation is 0.75 words per token, or 1 token per ~4 characters. A typical A4 page (500 words) is roughly 667 tokens.

How much does GPT-4o cost per 1000 requests?

GPT-4o costs $5.00 per million input tokens and $15.00 per million output tokens. For a 500-token prompt with a 500-token response, each request costs about $0.01. 1,000 such requests cost approximately $10.

How much does the Claude API cost?

Claude Sonnet 4 costs $3.00 per million input tokens and $15.00 per million output tokens. Claude Opus 4 costs $15.00 input and $75.00 output per million tokens. Costs vary by model and usage.

What is the cheapest LLM API?

As of 2026, Llama 3 via Groq is among the cheapest at approximately $0.05 per million input tokens. GPT-4o mini at $0.15/M and Gemini 1.5 Flash at $0.075/M are also very cost-effective for high-volume applications.

How do I calculate API cost for my AI app?

Estimate tokens per request (input + expected output), multiply by price per token for your chosen model, then multiply by monthly request volume. This calculator does all steps automatically.

What is a token in AI/LLM context?

A token is a chunk of text — roughly a word or part of a word. The word "hamburger" might be 1-2 tokens. "hamburgers" might be 3 tokens. Spaces, punctuation, and capitalization all affect tokenization.

How do I reduce LLM API costs?

Use a cheaper model for simple tasks (GPT-4o mini, Gemini Flash). Shorten system prompts. Cache common responses. Use streaming to reduce timeout retries. Consider open-source models for predictable queries.