Token planning guide
How to Calculate LLM Tokens and Estimate API Cost
Token counts drive most language-model API bills. A useful estimate separates prompt tokens from generated tokens, applies the correct model rates, and then scales one request across real traffic.
Estimate tokens before you call the API
A provider tokenizer is the source of truth, but a planning estimate of roughly four Unicode characters per token is useful for English prose. Code, tables, non-Latin languages, whitespace, and structured data can produce different ratios.
Include system instructions, retrieved context, conversation history, tool schemas, and formatting wrappers. Counting only the visible user message usually understates production input.
Convert token usage into cost
Input and output tokens usually have different rates. Calculate each side independently, add them for cost per request, then multiply by daily request volume.
A safety buffer is useful when response length and retrieved context vary. TokenMath applies the buffer before pricing so the projection remains internally consistent.
Worked example
GPT-4.1 mini: 1M input tokens + 1M output tokens
Using the versioned rates below, this example workload is estimated at $2.00. This isolates provider usage only and does not include taxes, regional premiums, retries, storage, network traffic, or unrelated infrastructure.
Current pricing references
These versioned records support the examples above. Check the date and provider source before using them in a production forecast.
| Provider / model | Input or unit | Output | Status | Source |
|---|---|---|---|---|
OpenAI GPT-4.1 mini | $0.40 per 1M tokens | $1.60 / 1M | Verified | OpenAI model pricing Checked Jun 21, 2026 |
Google Gemini Gemini 2.5 Flash | $0.30 per 1M tokens | $2.50 / 1M | Verified | Google Gemini API pricing Checked Jun 21, 2026 |
Anthropic Claude Sonnet 4.6 | $3.00 per 1M tokens | $15.00 / 1M | Verified | Anthropic Claude API pricing Checked Jun 21, 2026 |
Frequently asked questions
How accurate is four characters per token?
It is a planning heuristic, not a tokenizer replacement. Use provider token counts from representative production requests when precision matters.
Do output tokens usually cost more?
Many text models publish a higher output rate, which makes response length an important cost-control variable.
Related calculators and guides
Related glossary terms
Input tokens
Input tokens are the tokenized units sent to a model, including instructions, user content, conversation history, retrieved context, and tool definitions.
OpenOutput tokens
Output tokens are the tokenized units generated by a language model, including visible responses and any billable reasoning or thinking tokens defined by the provider.
OpenCost per request
Cost per request is the sum of all billable usage generated by one API call, commonly input token cost plus output token cost for a text model.
Open