Token Counter Tool: Paste Text, See Token Count
Token Counter Tool: Paste Text, See Token Count
Tokens are the currency of AI. Every API call is charged per token, and every model has a token limit. Our token counter lets you paste any text and instantly see how many tokens it contains across different model tokenizers.
AI model comparisons are based on publicly available benchmarks and editorial testing. Results may vary by use case.
How to Use
- Paste your text into the input box (or upload a file).
- Select the tokenizer (Claude, GPT-4, Gemini, Llama, or auto-detect).
- See your results instantly: token count, word count, character count, and estimated cost.
Why Token Counts Matter
Billing
You pay per token for API usage. Knowing your token count before sending a request helps you predict costs accurately.
Context Window Limits
If your input exceeds the model’s context window, the request will fail. Check before sending large documents.
AI Model Context Window Comparison: 8K to 1M Tokens
Output Budgeting
Context window is shared between input and output. A 128K context window with 100K tokens of input leaves only 28K tokens for the response.
Token Basics
What Is a Token?
A token is a chunk of text that the model processes as a single unit. It is not exactly a word. Common English words like “the,” “is,” and “at” are single tokens. Longer or less common words are split into multiple tokens. Numbers, punctuation, and code syntax each have their own tokenization patterns.
Rules of thumb:
- 1 token is roughly 3/4 of a word (or 4 characters) in English
- 1,000 tokens is approximately 750 words
- 1 page of text is roughly 500-800 tokens
- Code tends to use more tokens per “word” than prose
How Tokenization Differs by Model
Different model families use different tokenizers:
| Tokenizer | Used By | Notes |
|---|---|---|
| cl100k_base | GPT-4, GPT-4o | OpenAI’s tokenizer |
| Claude tokenizer | Claude models | Anthropic’s tokenizer |
| SentencePiece | Llama, Mistral | Common in open-source models |
| Gemini tokenizer | Gemini models | Google’s tokenizer |
The same text may have slightly different token counts depending on the tokenizer. Differences are typically small (within 5-10%) for English text but can be larger for code or non-English text.
Examples
| Text | Approximate Tokens |
|---|---|
| ”Hello, world!“ | 3-4 |
| A tweet (280 chars) | 40-70 |
| An email (200 words) | 250-300 |
| A blog post (1,000 words) | 1,200-1,500 |
| A research paper (8,000 words) | 10,000-12,000 |
| A novel (80,000 words) | 100,000-120,000 |
| A large codebase (50 files) | 50,000-200,000 |
Cost Estimation
Our tool shows estimated costs for your text across multiple models:
| Token Count | Opus 4 (input) | Sonnet 4 (input) | Haiku 4 (input) | GPT-4o (input) |
|---|---|---|---|---|
| 1,000 | $0.015 | $0.003 | $0.00025 | $0.0025 |
| 10,000 | $0.15 | $0.03 | $0.0025 | $0.025 |
| 100,000 | $1.50 | $0.30 | $0.025 | $0.25 |
AI API Pricing Comparison: Cost Per Million Tokens
Pro Tips
- Check before sending large documents. A 100-page PDF might contain 80,000+ tokens. Make sure it fits in your model’s context window.
- Estimate output costs separately. Output tokens cost more than input tokens. Budget for both.
- Code uses more tokens than prose. Variable names, syntax, and formatting add tokens. A 100-line Python file might be 500-1,500 tokens.
- Non-English text varies. Some languages (e.g., Chinese, Japanese, Korean) use more tokens per character with certain tokenizers.
- System prompts count. Your system prompt is sent with every message and counts toward your input tokens and costs.
Key Takeaways
- Token count determines both your costs and whether your text fits within a model’s context window.
- One token is roughly 3/4 of an English word (4 characters).
- Different models use different tokenizers, so counts may vary slightly.
- Always check token counts before sending large documents to avoid context window errors and unexpected costs.
Next Steps
- Estimate your monthly costs: AI Cost Calculator: Estimate Your Monthly API Spend.
- Compare context windows across models: AI Model Context Window Comparison: 8K to 1M Tokens.
- Understand AI pricing in depth: AI Costs Explained: API Pricing, Token Limits, and Hidden Fees.
- Compare API pricing across providers: AI API Pricing Comparison: Cost Per Million Tokens.
This content is for informational purposes only and reflects independently researched comparisons. AI model capabilities change frequently — verify current specs with providers. Not professional advice.