AI Token Cost Calculator

What Are AI Tokens?

Tokens are the fundamental unit that large language models (LLMs) use to process text. A token is roughly 3–4 characters of English text, or about 75% of a word. The sentence "How much does GPT-4 cost?" is approximately 8 tokens. Every API call is billed based on the number of input tokens (your prompt) and output tokens (the model's response).

Different models tokenize text slightly differently, but the ~4 characters/token rule is a reliable estimate for English. Non-English languages, code, and structured data like JSON tend to use more tokens per character.

How AI API Pricing Works

AI providers charge per million tokens, with separate rates for input and output. Output tokens are always more expensive because generation requires more compute than reading. For example, Claude Sonnet 4 charges $3/M input and $15/M output — a 5:1 ratio. This means a long prompt with a short answer costs less than a short prompt with a long response.

Many providers offer discounts for prompt caching (reusing common prefixes across requests) and batch processing (submitting requests in bulk with slower turnaround). These can reduce costs 50–90% for eligible workloads.

Choosing the Right Model

More expensive models aren't always better for your use case. Here's a quick framework:

• Complex reasoning, coding, analysis — use frontier models (Claude Opus 4, GPT-4o, o3, Gemini 2.5 Pro)
• General chat, summarization, writing — mid-tier models (Claude Sonnet 4, GPT-4.1) offer the best cost/quality balance
• Classification, extraction, simple Q&A — small models (Claude Haiku 3.5, GPT-4.1 nano, Gemini 2.0 Flash) at a fraction of the cost
• High-volume production workloads — evaluate open-source models (Llama 4, DeepSeek V3) for self-hosting to eliminate per-token fees entirely

Tips to Reduce AI API Costs

• Use prompt caching. If your system prompt or context is the same across requests, enable caching to pay the input rate only once.
• Limit output tokens. Set a max_tokens parameter to prevent unexpectedly long responses.
• Route by complexity. Use a small/cheap model for simple tasks and only escalate to a frontier model when needed.
• Batch when possible. Anthropic and OpenAI offer 50% discounts on batch API calls that don't need real-time responses.
• Compress prompts. Remove redundant instructions, use concise examples, and strip unnecessary whitespace from injected context.

Frequently Asked Questions