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Guides & tutorials

  • Stop Wasting AI Tokens on File Converters, Diff Checkers, and Simple Transforms

    Every time you paste a CSV into ChatGPT to convert it to JSON, you burn tokens on a task a free browser tool does in milliseconds. Here is how to save your AI credits for work that actually needs intelligence.

  • Working with Large Datasets in AI: 10 Free Tools That Handle Heavy Data Without Choking

    Large CSVs, multi-MB JSON files, long documents — standard AI interfaces struggle with them. This guide covers the browser tools that pre-process, chunk, convert, and optimize large data for AI models so you stop hitting context limits.

  • Top 10 Free AI Productivity Tools You Can Run Entirely in Your Browser (2026)

    You don't need an API key, a subscription, or a server to supercharge your AI workflow. These 10 browser-based tools handle token counting, prompt engineering, large dataset conversion, and model comparison — all locally, all free.

More AI tools

See all AI tools →
  • AI Prompt Builder

    Build structured, high-quality prompts for ChatGPT, Claude, and Gemini. Define role, context, task, format, and constraints in a guided form.

  • JSON to AI Prompt

    Convert large JSON datasets into clean, token-efficient AI prompts. Perfect for feeding structured data to ChatGPT, Claude, or Gemini without wasting context.

  • CSV to AI Prompt

    Transform CSV files and large tabular datasets into AI-ready prompts. Control which columns to include, row limits, and output format to stay within token budgets.

  • System Prompt Generator

    Generate professional system prompts for AI assistants, chatbots, and agents. Choose persona, tone, domain, and constraints to produce a production-ready system prompt instantly.

  • Context Window Calculator

    Calculate whether your text fits within any AI model's context window. Compare token usage across GPT-4o, Claude 3.5, Gemini 1.5 Pro, Llama 3, and more.

  • AI Model Comparator

    Compare GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro, Llama 3, Mistral, and more side-by-side. Context window, pricing, strengths, speed, and best use cases.

Quick Tip: Coding

When working with URLs, always encode special characters to avoid breaking the link. A URL Encoder/Decoder is a must-have tool for web developers.

  1. Home
  2. Tools
  3. AI Token Counter

About this Tool

Every AI model has a context window — a hard limit on how many tokens it can process at once. Exceed it and your request gets cut off or errors out. The AI Token Counter shows you exactly how many tokens your text will consume across GPT-4o, Claude, Gemini, Llama, and Mistral simultaneously, with a visual progress bar and live cost estimate for each. Paste any amount of text — prompts, documents, code, data — and plan your token budget before hitting send.

The tool estimates token count using a cl100k_base approximation (the tokenizer used by OpenAI models), which gives ±5% accuracy for English text. It divides the input into approximate token units based on average word and character ratios, then checks each model's published context window limit to generate the progress bars and cost estimates.

  1. Paste your text, upload a file (.txt, .md, .json, .csv, .py, etc.), or paste from clipboard.
  2. View the instant token, character, word, and line count summary.
  3. Check the Context Window Usage table to see how your text fits each model.
  4. Use the estimated input cost column to compare model pricing before sending.
  • Checking whether a long document fits within Claude's 200,000-token context window before uploading.
  • Estimating the API cost of sending a large system prompt + data payload to GPT-4o.
  • Comparing which model is cheapest for a specific prompt length before switching providers.
  • Verifying a prompt template stays under a target token budget as you iterate on it.
  • Multi-model comparison: check token usage against 10+ models in one view.
  • Live cost estimates: input pricing per model based on current published rates.
  • File upload support: analyze .txt, .md, .json, .csv, .py, .js, .ts, .html, .xml files.
  • Character, word, and line counts alongside token estimates.
  • 100% browser-based: no text leaves your device.

LLMs don't process words — they process tokens, which are chunks of text (typically 3-4 characters for English). A tokenizer splits input into these chunks before processing. Different models use different tokenizers (cl100k_base for GPT, SentencePiece for Claude), so token counts vary slightly between providers. The context window is the total number of tokens a model can "see" at once, covering both the input and its output.

How accurate are the token estimates?

The tool uses a cl100k_base approximation that gives ±5% accuracy for standard English text. For exact counts, use the official tokenizer libraries (tiktoken for OpenAI, the Anthropic SDK tokenizer for Claude).

Why do different models show different token counts for the same text?

Each model family uses a slightly different tokenizer, which splits text differently. This tool shows an approximation; actual counts may vary ±5% depending on the model.

Are the cost estimates accurate?

Cost estimates are based on publicly listed input token pricing at the time the tool was last updated. Always verify current pricing on the provider's pricing page before making decisions.

All calculations and data processing for this tool are performed locally in your browser. UtilToolkits does not send any of your data to an external server, ensuring your information remains private and secure.

Credits:Next.js•React•Tailwind CSS•Lucide Icons

AI Token Counter

Paste any text — documents, prompts, code — and instantly see token counts for every major AI model. 100% browser-based, no data leaves your device.

Context Window Usage by Model

OpenAI
GPT-4o
0 / 128,000 tokens
GPT-4o mini
0 / 128,000 tokens
GPT-3.5 Turbo
0 / 16,385 tokens
Anthropic
Claude 3.5 Sonnet
0 / 200,000 tokens
Claude 3 Haiku
0 / 200,000 tokens
Claude 3 Opus
0 / 200,000 tokens
Google
Gemini 1.5 Pro
0 / 1,000,000 tokens
Gemini 1.5 Flash
0 / 1,000,000 tokens
Meta (via API)
Llama 3.1 405B
0 / 128,000 tokens
Mistral
Mistral Large
0 / 128,000 tokens

Token counts are estimates (±5%) using a cl100k_base approximation. For exact counts, use the official tokenizer libraries. Cost estimates are for input tokens only based on publicly listed pricing.