Why Estimate Your LLM API Costs?

Building an "AI Wrapper" or integrating Large Language Models (LLMs) into your product is exciting, but API costs can scale exponentially if not monitored. This LLM API Token Cost Estimator helps developers and founders visualize their monthly "burn" before writing a single line of code.

How LLM Pricing Works (Tokens vs Words)

Most modern AI providers (OpenAI, Anthropic, Google) do not charge per request. Instead, they charge per 1 million tokens.

• What is a token? As a rule of thumb, 1,000 tokens is roughly equivalent to 750 words.
• Asymmetric Pricing: Providers charge significantly more for Output (completion) tokens than Input (prompt) tokens because generating text is more computationally expensive than reading it.

Comparison: GPT-4o vs Claude vs Gemini

Choosing the right model is a balance between intelligence and cost.

3 Tips to Reduce Your API Bill

1. Truncate Context: Don't send the entire conversation history every time. Only send the last 5-10 messages to save on input tokens.
2. Prompt Compression: Use concise system prompts and "few-shot" examples only when necessary. Every extra character in the prompt costs money on every single request.
3. Use "Mini" Models for Simple Tasks: Use GPT-4o Mini or Gemini Flash for basic classification, formatting, or summarization. Save the expensive models (Sonnet, GPT-4o) for complex reasoning.