AI Prompt Token & Cost Estimator

Estimate prompt tokens and calculate API usage costs for OpenAI, Claude, and Gemini.

Calculated client-side using BPE approximations

Enter Prompt Text

Characters: 0Words: 0Est. Tokens: 0

Scale Cost Calculator

How many queries of this prompt size do you expect to execute? Adjust multiplier below to view projected bulk costs.

Number of Runs / Requests

Bulk Input Cost$0.0000

Bulk Output Cost$0.0000

Model Preset

Pricing Configuration

Input Cost (Per 1M Tokens)$2.500

Output Cost (Per 1M Tokens)$10.000

Current Cost Estimate

As Input Prompt$0.000000

As Output Completion$0.000000

How it Works

LLMs split text into fragments called tokens. For English text, 1 token is roughly 4 characters or 0.75 words. This estimator rounds character ratios to approximate token consumption rates client-side, giving you a zero-data leakage forecast of API execution costs.

How to Use

Paste Prompt Text

Input your system instructions, context, or dataset in the text box.

Choose LLM Model

Select standard templates (GPT-4o, Sonnet, Gemini) or customize rates.

Check Budgets

Review estimated token size and projected API fees in real-time.

Real-World Examples & Use Cases

API Integration Budget Planning

Developers building LLM-powered applications must estimate operating costs before scaling production traffic. Estimating token sizes for system instructions, few-shot examples, and expected user inputs helps model monthly API bills and choose cost-effective model architectures.

Prompt Engineering & Length Optimization

To stay within model context limits and minimize latency, prompt engineers optimize context lengths. Seeing how modifying system instructions or trimming prompt datasets cuts down token usage helps refine prompts without ballooning execution fees.

Model Pricing Comparison

Comparing the budget impact of running the same prompt across different providers (such as OpenAI GPT-4o, Anthropic Claude 3.5 Sonnet, and Google Gemini 1.5 Pro) helps determine the optimal performance-to-cost ratio for specific workloads.

How It Works

Tokenization and API Cost Estimation Formula: Language models do not process text character-by-character; instead, they break strings down into sub-word units called "tokens". On average, 1 token represents approximately 4 characters of English text, or about 0.75 words. The Cost Estimation formula is: Total Cost = (Input Tokens × Input Price per Token) + (Expected Output Tokens × Output Price per Token) Where: - Input Price per Token = Model's Input Price per 1 Million Tokens / 1,000,000 - Output Price per Token = Model's Output Price per 1 Million Tokens / 1,000,000 Our tool utilizes a fast, local client-side token count approximation (running on character-length and word-frequency bounds matching standard BPE encodings like cl100k_base) to calculate lengths, ensuring your prompts are never sent to external servers.

Frequently Asked Questions

What is an LLM token?▼

Tokens are the basic building blocks of text processed by language models. A token can be a whole word, a part of a word (like a syllable), or even single characters (like punctuation or emojis). For example, the word "amazing" might be parsed as a single token, whereas a rare technical term might be broken into three tokens.

Why are input and output tokens priced differently?▼

Input tokens (prompts) require less computational processing because the model reads them in parallel. Output tokens (completions) are generated auto-regressively, meaning the model must generate each token one-after-another in a sequential loop. This makes generating output tokens computationally heavier, resulting in prices that are typically 3x to 4x higher than input tokens.

How accurate is this local cost estimator?▼

This tool uses a highly accurate approximation of Byte-Pair Encoding (BPE) lengths. While exact counts can vary slightly depending on the specific model's proprietary vocabulary file, the estimate is typically within 2-5% of official API counts, making it excellent for budget modeling.

Why does ConvertWithMi calculate this offline?▼

Pasting raw system prompts or user contexts into online calculators sends that data to third-party servers, potentially leaking proprietary code, system instructions, or sensitive internal data. Our calculator processes the text entirely in your browser, preserving zero-trust security.

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