How do I count tokens for GPT-4o and Claude?

Use the free token counter above. Paste your text and see instant token counts plus cost estimates across 42 models. Different models tokenize text differently — GPT-4o uses cl100k_base encoding while Claude uses a similar BPE tokenizer. Our tool estimates tokens using a ~4 characters per token approximation which is accurate for English text.

How much does it cost to process 1 million tokens?

Costs vary by model. Budget models like Gemini 2.5 Flash-Lite ($0.10/M input) or DeepSeek V4 Flash ($0.14/M) are cheapest. Mid-tier models like Claude Sonnet 4.6 ($3/M) or GPT-5 ($1.25/M) offer better quality. Premium models like Claude Opus 4.8 ($5/M) or GPT-5.5 ($5/M) are most expensive but most capable. Use the calculator above to compare exact costs for your text.

What is a token and how is it counted?

A token is a chunk of text that AI models process. For English text, 1 token is roughly 4 characters or 0.75 words. 'Hello world' is approximately 2 tokens. Different models use different tokenizers — GPT models use BPE (Byte Pair Encoding) while Claude uses a similar but distinct tokenizer. Numbers, code, and non-English text may tokenize differently.

AI Token Counter & Cost Calculator

Paste your text to count tokens and see how much it costs across 42 AI models. Free, instant, no signup required.

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Cheapest Model

💰 Cost Comparison Across 42 Models

💡 How Token Counting Works

What is a token? Tokens are the basic units AI models use to process text. For English, ~4 characters ≈ 1 token. "Hello world" ≈ 2 tokens.

Different models, different tokenizers. GPT models use BPE (Byte Pair Encoding), Claude uses a similar but distinct tokenizer. Exact counts vary by ±5-10%.

This tool estimates tokens using character-based approximation (÷4 for English). For exact counts, use the provider's tokenizer directly. Our estimates are within 10% for most English text.

💡 Tips to Reduce Token Costs

Use Shorter Prompts

Remove filler words, be specific, and use bullet points. A concise prompt can save 30-50% of input tokens without losing quality.

Choose the Right Model

Not every task needs GPT-5.5 or Claude Opus. Classification, extraction, and simple Q&A work great with budget models at 10-50x lower cost.

Set max_tokens

Always set max_tokens to limit output length. Without it, models may generate longer responses than needed, increasing output costs.

Batch Requests

Combine multiple items into one prompt when possible. "Analyze these 5 reviews" is cheaper than 5 separate API calls.

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