Tokenizer & Token Counter
Use the built-in estimator for a fast answer, then jump to official lab tools when you need an exact or model-specific count. This page is intentionally honest: our on-site counter is quick and useful, but it is still an estimate.
Characters
0
Words
0
Estimated tokens
0
Lines
0
How the on-site estimate works
Different labs use different tokenizers, so exact counts vary by model and request format. The built-in counter uses the common English rule of thumb for quick budgeting:
Treat the estimate as a fast budgeting tool, not a billing guarantee. Providers often add system formatting, tool wrappers, or other hidden tokens at request time.
Official token tools
Verified provider links for exact or provider-native token counting workflows.
OpenAI
OpenAI Tokenizer
Interactive tokenizer for checking how OpenAI text models split a prompt into tokens.
Useful for quick prompt inspection and token-by-token debugging.
Anthropic
Claude token counting
Count Claude message tokens before sending a request, including tools, images, and PDFs.
Anthropic documents this as an estimate that can differ slightly from the final billed request.
Gemini countTokens
Run the Gemini tokenizer against text, chat history, files, tools, and system instructions.
Google exposes token counting through the Gemini API rather than a standalone public playground.
xAI
xAI Tokenizer
Use the xAI Console tokenizer or the Tokenize Text API to estimate Grok prompt usage.
xAI notes that actual consumption can be higher because system-added tokens are applied at inference time.
Cohere
Cohere tokenize
Tokenize text with Cohere using the tokenizer associated with a chosen model.
Cohere also documents local tokenizer downloads for some model families.
Cost estimates (input side)
What this text would cost as input tokens across different models. Output tokens are usually billed separately and often cost more.
| Model | Input $/1M | Cost for this text |
|---|
Context window check
Does your text fit within a few common context-window tiers?