Visualizer (First 100 Tokens)
Analysis
Frequently Asked Questions
What is a Token?
A token is the fundamental unit that LLMs process. In English, 1 token is roughly 0.75 words or 4 characters. Common words like "the" are single tokens, while complex words like "authentication" may be 2-3 tokens.
Why do tokens matter for cost?
LLM providers (OpenAI, Anthropic, Google) charge per token. Fewer tokens = lower costs and faster responses. Optimizing your prompts can save 20-50% on API bills.
Is tokenization the same for all models?
No. GPT-4 uses a different tokenizer (cl100k_base) than Claude or Llama. This calculator uses the GPT tokenizer as a baseline, which is usually within 5-10% of other models.
Input vs Output tokens?
Input tokens are what you send (your prompt + context). Output tokens are what the AI generates. Output tokens typically cost 2-5x more than input tokens because generation is more compute-intensive.
How can I reduce token usage?
1. Remove filler words and redundant instructions. 2. Use concise examples. 3. Avoid repeating context. 4. Use shorter variable names in code prompts. 5. Set a max_tokens limit on responses.