ML Engineering Tools

LLM Token Count & Cost Estimator

Enter text character count and monthly request volume to estimate token count and API cost across GPT-4, Claude 3, and open-source models.

Calculations run locally in your browser

Example — Representative default scenario — characters 5000 · chars per token 4.

Tokens per request
1,250
5000 chars ÷ 4 chars/token
Cost per request
$0.0005
GPT-4o mini blended pricing ($0.375/M)
Monthly cost
$46.88
100,000 requests
Cost per 1K reqs
$0.47

LLM Token Count & Cost Estimator

The LLM Token Count & Cost Estimator computes token count from character length and monthly API cost from request volume across major LLM providers.

• Estimate monthly OpenAI API cost before launch

• Compare GPT-4o vs Claude 3.5 Sonnet cost

• Calculate context window cost for a RAG pipeline

• Model LLM cost at different usage tiers

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What does this tool tell you?
The LLM Token Count & Cost Estimator computes token count from character length and monthly API cost from request volume across major LLM providers.
What affects the result most?
~4 chars/token for English prose, ~2-3 chars/token for code, ~1-2 chars/token for whitespace-heavy text. Context window cost: long contexts cost proportionally — 100K token context = 100× 1K context cost. Prompt caching: Anthropic/OpenAI offer cache discounts for repeated prompt prefixes — up to 90% off.
How should I use the result?
The calculation is deterministic — the same inputs always produce the same output — so the most useful workflow is to vary one input at a time and see which factor moves the result most. That tells you where to focus your attention before committing to a decision.
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