Token Counter & Visualizer

Type or paste text to see how models like GPT-4o, Claude, and Llama tokenize it. Compare token counts, see cost estimates, and understand why tokenization matters for prompt engineering.

Switch tool:Text Chunk Visualizer RAG Pipeline Explorer Token Counter & Visualizer Embedding Similarity Playground

Tunable Model & Token Parameters

Select model tokenizer family and estimate multi-request cost

Active: GPT-4o (OpenAI)

Select LLM Architecture & Pricing4 models available

Simulate Daily Volume1,000 calls / day

100/day10k/day50k/day

Per-Request Cost$0.0004

Est. 30-Day Cost$11.25

Total Tokens

150

Characters

333

Chars / Token

2.2

Input Cost

$0.0004

Context Used

0.12%

Prompt / Document Text

Sample texts:

Token estimation uses subword approximation calibrated to each model's BPE vocabulary and character-to-token ratio.

Visualizer:

Hover or tap any piece to inspect details

Large Language Models process prompts as discrete tokens rather than characters or words. A token is typically 3 to 4 characters of English text, or roughly 0.75 words. Understanding token economics is essential for production AI: input tokens, output tokens, and context window limits directly dictate latency and cost per request.

Hover over any subword token above to view token index and character span.

150 tokens

GPT-4o

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