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LLM token calculator

Estimate prompt tokens before the API bill arrives.

Compare providers from one wide workspace: OpenAI, Claude, Gemini, DeepSeek, Mistral, and Grok. Use it for planning, then verify production counts with provider token-counting or usage APIs.

Prompt shape
Numeric workload is saved locally in this browser for easier comparison. Prompt text is not saved.

Input tokens include system prompt, prompt text, and user message. Output tokens use the assistant response box.

Result
81estimated total tokens per request
Input tokens53
Output tokens28
Cost / request<$0.01
Monthly requests30,000
Input<$0.01
Cached input$0.00
Output<$0.01
Daily cost$1.11
Monthly cost$33.15

Planning estimate: provider tokenizers differ, so verify production counts with each provider's token counting or usage APIs.

Pricing checked 2026-05-09. GPT-5.5: input $5/1M, cached input $0.5/1M, output $30/1M tokens.

Cost insight: the largest cost driver is output tokens. Cutting output tokens by 50% would save about $12.60 per month.

Estimated planning result only. Prices can change, and provider bills may include taxes, minimums, feature-specific charges, or usage adjustments. Verify production spend in the official provider dashboard.

Try this workload inOpenAIClaudeGeminiDeepSeekRAGAI AgentEmbedding

How to use

How to estimate LLM tokens

  1. Paste the message shape

    Add system prompt, prompt text, user message, and the kind of assistant response you expect.

  2. Choose provider and model

    Select OpenAI, Claude, Gemini, DeepSeek, Mistral, or Grok to apply the matching planning price.

  3. Plan request volume

    Enter daily requests to see per-request, daily, and monthly budget estimates before building the feature.

LLM token guide

Use this as the starting point before choosing a provider calculator.

The wide token calculator is for early planning: paste the message shape, estimate request volume, and compare provider-level cost before you commit to one API.

How the estimate works
Input tokens

System prompt, prompt text, and user message are estimated together as input tokens because providers usually bill that context before generation starts.

Output tokens

Assistant response length is estimated separately, then multiplied by the selected model's output price.

Usage projection

Per-request cost is multiplied by requests per day and days per month so you can budget a feature, not just a single prompt.

Example workloads
Support chatbot

Estimate a short system prompt, one customer message, and a concise answer before comparing OpenAI, Claude, Gemini, and DeepSeek.

RAG answer planning

Add retrieval context to the prompt text field to see how document chunks can change the monthly token budget.

Agent task

Approximate one task by combining repeated instructions, user goal, and expected final response before moving to an agent-specific calculator later.

Cost optimization tips
  • Shorten stable instructions before optimizing anything else; repeated context compounds across every request.
  • Compare at least two models with the same workload before assuming the cheapest input price wins.
  • Use cached-input pricing only when the same prefix is reused often enough to matter.
  • Verify exact counts with provider token tools before production because this page uses a planning heuristic.
Common mistakes
  • Treating the estimate as an exact tokenizer result.
  • Ignoring output tokens when answers are long.
  • Forgetting system prompts, tool schemas, or retrieved context.
  • Entering requests per month into the daily requests field.

References

Built as a planning tool, not a fake exact tokenizer.

OpenAI Tokenizer OpenAI Cookbook token counting Claude Token Counting API Gemini Count Tokens API DeepSeek API pricing Mistral pricing xAI Grok model pricing

Token estimates use a transparent character-per-token heuristic for speed and privacy. No prompt text leaves the browser, no API key is requested, and exact provider tokenizer behavior should be checked before committing a production budget.

FAQ

LLM token calculator quick answers

What is an LLM token calculator?

An LLM token calculator estimates input tokens, output tokens, total tokens, and API cost before you send prompts to a model provider.

Which providers does this token calculator support?

It supports planning estimates for OpenAI, Claude, Gemini, DeepSeek, Mistral, and Grok models from one wide interface.

Does the calculator upload prompt text?

No. Prompt text stays in the browser. The page uses a local heuristic for speed and privacy, then you can verify exact counts with provider token-counting tools.