Developer Tools
LLM Token Counter
Paste any text and get an instant estimate of how many tokens a model will use, how much it costs, and how close you are to the context limit. Pick from GPT, Claude, Gemini, and Llama presets. Everything runs in your browser.
Estimated tokens
0
Words
0
Characters
0
Est. cost
$0.0000
Estimate only — exact counts come from each provider's own tokenizer.
What makes this tool different
Multi-model presets
Switch between OpenAI GPT, Anthropic Claude, Google Gemini, and Meta Llama with per-model token rules and pricing.
Instant estimates
Token counts update live as you type, with a progress bar showing how much of the context window you would use.
Cost estimation
See the approximate cost for input and output tokens based on each model's published pricing.
100% in-browser privacy
Everything is computed locally. Your prompts and documents never leave your device.
About this tool
LLM Token Counter: everything you need to know
Tokens are the fundamental unit of every LLM conversation — models read and generate text in tokens, are limited by token context windows, and are billed per token. Yet most people only find out how many tokens they are using after the fact. An LLM token counter gives you that number before you send, so you can stay inside limits and control cost.
This tool estimates tokens for the major model families — OpenAI GPT, Anthropic Claude, Google Gemini, and Meta Llama. Each preset applies that model's typical token density, its context window limit, and its published input and output pricing. Paste text, pick a model, and see the estimate update live as you type.
The estimate is useful for three things: staying under a context window so long documents do not get truncated, predicting API cost before a batch job, and comparing prompts to see which version uses fewer tokens. A usage bar shows at a glance how much of the selected model's window your text would occupy.
For developers, token counts also matter when building pipelines — chunking documents, trimming conversation history, or optimizing prompts. With this tool you can measure before you write the code, then choose chunk sizes and history limits that fit your model's budget.
Privacy is built into the design. Token estimation runs entirely in your browser — your prompts, documents, and code never leave your device. Open the DevTools Network tab and you will see zero requests.
Note that exact counts come from each provider's own tokenizer. This tool uses the same heuristics model families are known for, so estimates are reliable for budgeting, planning, and comparing prompts without the overhead of calling a paid API.
FAQ
LLM Token Counter — frequently asked questions
What is token counting in LLMs?
Tokens are the chunks of text that large language models read and generate. Token counting estimates how many tokens a piece of text consumes — roughly 4 characters per token for English, but fewer for code and CJK languages. Models are billed and limited in tokens, so counting before you send is important.
How much text is 1000 tokens?
For English, 1000 tokens is roughly 750 words or about 4000 characters. Code and CJK text differ — code is denser per token, and CJK characters often map one-to-one to tokens. Use the token counter with your actual text to get an accurate estimate.
llm में टोकन गिनती क्या है?
टोकन वे छोटे टुकड़े होते हैं जिनमें लार्ज लैंग्वेज मॉडल टेक्स्ट को पढ़ता और लिखता है। टोकन गिनती यह अनुमान लगाती है कि किसी टेक्स्ट में कितने टोकन हैं — अंग्रेजी में लगभग हर 4 अक्षर एक टोकन होता है। मॉडल की बिलिंग और सीमाएं टोकन में होती हैं, इसलिए अनुमान लगाना जरूरी है।
1000 टोकन कितना टेक्स्ट है?
अंग्रेजी में 1000 टोकन लगभग 750 शब्द या 4000 अक्षर के बराबर होते हैं। कोड और चीनी जैसी भाषाओं में यह अलग होता है — कोड हर टोकन में ज्यादा जानकारी रखता है। सटीक अनुमान के लिए अपने टेक्स्ट को टोकन काउंटर में डालकर देखें।
What is ChatGPT's token limit?
It depends on the model. GPT-4o supports a 128K context window, GPT-4.1 up to 1M, and older GPT-4 models 8K or 32K. The token counter shows the limit for your selected model and a progress bar for your text.
How do I reduce my token usage and cost?
Trim boilerplate, remove repeated instructions, compress verbose output, and split large documents into relevant chunks. Because billing is per token, cutting input length directly cuts cost — estimate your text here first to see the impact.
Does the token counter work for Claude and Gemini too?
Yes. The tool includes presets for Anthropic Claude and Google Gemini models with their own token rules, context limits, and pricing, alongside OpenAI and Llama presets.
Is the token count exact?
It is an accurate estimate based on each model family's typical tokenizer behavior. Exact counts come from the provider's own tokenizer. For planning budgets, context limits, and cost, the estimate here is more than close enough.
Is the LLM token counter free and private?
Yes. It is completely free, requires no signup, and computes everything in your browser — your prompts and documents never leave your device.
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