What developer tools does Texterfly offer?

Texterfly offers 10 free developer tools: a JSON Formatter & Validator, an All-in-One Data Converter (JSON/CSV/XML/YAML), a JWT Decoder & Analyzer, a Cron Job Generator & Explainer, a QR Code Generator, a Password Generator, a Unix Timestamp Converter, a Lorem Ipsum Generator, an Interactive Data Visualization Builder, and a CSS Neumorphism Generator. All are free, browser-based, and require no signup.

How do I format and validate JSON online?

Paste your JSON into the JSON Formatter & Validator tool. It automatically detects syntax errors with precise line and column numbers, beautifies the output with proper indentation, and offers a minify option to compress the JSON for production use. You can also upload a .json file or fetch JSON from a URL.

How do I convert JSON to CSV (or CSV to JSON)?

Use the All-in-One Data Converter & Formatter. Paste your JSON or CSV, select the output format, and the conversion happens instantly. The tool also supports XML and YAML conversion, file upload, URL fetching, and JSONPath queries for extracting specific fields before converting.

How do I decode a JWT token?

Paste your JWT into the JWT Decoder & Analyzer. The tool instantly splits it into the header, payload, and signature sections, decodes the base64url encoding, checks expiration (exp claim), and detects common security issues like the "none" algorithm attack. For HS256 tokens, you can enter a secret key to verify the signature.

How do I write a cron job expression?

A cron expression has five fields: minute (0-59), hour (0-23), day of month (1-31), month (1-12), and day of week (0-7). Examples: "0 9 * * 1" runs every Monday at 9 AM; "0 0 * * *" runs daily at midnight; "*/15 * * * *" runs every 15 minutes. Use the Cron Job Generator to build and validate expressions visually with a real-time English translation.

What makes a password strong?

A strong password has: at least 16 characters (longer is better), a mix of uppercase and lowercase letters, numbers, and symbols, no dictionary words or predictable patterns, and is unique (never reused across accounts). The Password Generator creates cryptographically random passwords meeting all these criteria and shows an entropy-based strength score.

What is a Unix timestamp?

A Unix timestamp is the number of seconds elapsed since January 1, 1970, 00:00:00 UTC (the Unix Epoch). It is the universal standard for representing time in computing. A 10-digit number is seconds; 13 digits is milliseconds; 16 digits is microseconds; 19 digits is nanoseconds. Use the Timestamp Converter to convert between Unix time and human-readable dates.

What is neumorphism in CSS?

Neumorphism (also called Soft UI) is a design style that uses a combination of two box shadows — one light and one dark — on a background that matches the element's color to create a soft, extruded or pressed appearance. The CSS Neumorphism Generator creates the exact box-shadow CSS code for any color, size, and depth with a live preview.

What is the structure of a JWT?

A JWT (JSON Web Token) consists of three base64url-encoded parts separated by dots: Header.Payload.Signature. The Header specifies the token type (JWT) and signing algorithm (e.g. HS256). The Payload contains claims — statements about the user or session like "sub" (subject), "exp" (expiration), "iat" (issued at), and "iss" (issuer). The Signature verifies that the token was not tampered with.

Are these developer tools free?

Yes. All 10 developer tools on Texterfly are 100% free with no registration, subscription, or payment required.

Is my code or data private?

Yes. All processing runs entirely in your browser using JavaScript. Your JSON, JWT tokens, passwords, and data are never sent to any server or stored anywhere. This makes the tools safe for sensitive tokens, credentials, and confidential data.

Can I use these tools for commercial projects?

Yes. All Texterfly developer tools are free for both personal and commercial use. There are no licensing restrictions on how you use the output.

What is a token in AI language models?

A token is the basic unit of text that a language model processes — roughly a word, part of a word, or punctuation mark. Models like GPT don't read raw characters; they convert text into a sequence of tokens first using a method called Byte Pair Encoding (BPE). On average, one token is about 4 characters or 0.75 words of English text.

Why are Claude and Gemini token counts labeled as estimates?

Anthropic and Google do not publish an open-source, client-side tokenizer for Claude or Gemini the way OpenAI does with tiktoken. This tool uses a character-based approximation (roughly 1 token per 4 characters, adjusted for typical English text) for these models, clearly labeled as an estimate rather than an exact count.

Why does the same text have different token counts for different models?

Each model family uses its own vocabulary and encoding. GPT-3.5 and GPT-4 use the cl100k_base encoding (100,000 token vocabulary), while GPT-4o, GPT-4.1, and GPT-5 use the newer o200k_base encoding (200,000 token vocabulary), which is generally more efficient — the same text often produces fewer tokens under o200k_base than cl100k_base.

How accurate is the API cost estimate?

The cost estimate is based on published per-model pricing at the time this tool was last updated, calculated against your exact (or estimated) token count. AI provider pricing changes periodically — always verify current rates on the provider's official pricing page before making budget decisions.

Is my text sent to any server when I use this tool?

No. Tokenization happens entirely in your browser using a JavaScript library. Your text is never uploaded or transmitted anywhere.

Back to Developer Tools

Token Counter

Count exact tokens for GPT-5, GPT-4o, GPT-4, and GPT-3.5, plus estimated counts for Claude and Gemini — with a visual token breakdown and API cost estimate. Free, no sign-up.

Word Counter

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Your Text

163 chars · 28 words

Type some text to see the token breakdown

Model

OpenAI (Exact)

Anthropic (Estimated)

Google (Estimated)

Token Count

tokens

—

chars/token

128,000

context limit

Context window used0%

Expected output tokens

Input (0 tok × $2.5/1M)$0.000000

Output (500 tok × $10/1M)$0.005000

Total estimate$0.005000

Pricing is an approximate snapshot and changes over time — always verify current rates on the provider's pricing page before budgeting.

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Free Token Counter — Exact GPT Tokenization, Visual Breakdown, Cost Estimate

This Token Counter uses gpt-tokenizer, a JavaScript implementation of the exact Byte Pair Encoding (BPE) that powers OpenAI's own tiktoken library. For GPT-5, GPT-4.1, GPT-4o, GPT-4, GPT-3.5 Turbo, and the o1/o3 reasoning models, the token counts shown here are exact — not approximated — because tokenization runs entirely in your browser using the real production encoding tables.

Claude and Gemini don't have an open, client-side tokenizer published by their providers, so counts for those models are clearly labeled estimates based on character and word ratios typical for English text. Need to count words or characters instead? Try the Word Counter.

What Is a Token?

Language models don't read text character-by-character or word-by-word — they process tokens, chunks of text produced by an algorithm called Byte Pair Encoding (BPE). A token might be a whole word ("hello"), part of a word ("token" + "izer"), a single character, or even a punctuation mark. On average, one token is roughly 4 characters or 0.75 words of English text — but this varies significantly by language, formatting, and content type (code and non-English text often use more tokens per character).

Every model has a fixed context window — the maximum number of tokens it can process in a single request, including both your prompt and its response. Understanding your token count helps you stay within these limits and estimate API costs, since providers charge per token, not per character or per request.

Model Encodings Explained

Encoding	Vocabulary Size	Used By	Notes
o200k_base	~200,000	GPT-5, GPT-4.1, GPT-4o, o1, o3	Newer, generally more token-efficient
cl100k_base	~100,000	GPT-4, GPT-4 Turbo, GPT-3.5 Turbo	Standard encoding since GPT-3.5/4

This is why the same text can produce a different token count depending on which model you select — try switching models above and watch the count change.

Frequently Asked Questions

Are the GPT token counts exact or estimated?

Exact for OpenAI models. This tool uses gpt-tokenizer, a JavaScript port of the same Byte Pair Encoding used by OpenAI's official tiktoken library — the counts for GPT-5, GPT-4.1, GPT-4o, GPT-4, GPT-3.5, and o1/o3 are the real production token counts, not approximations.

Why are Claude and Gemini shown as estimates?

Anthropic and Google haven't published an open-source client-side tokenizer the way OpenAI has with tiktoken. This tool uses a character-and-word-based approximation for those models, clearly labeled as an estimate rather than an exact count.

Why does the same sentence use a different token count on different models?

Each model family has its own vocabulary. GPT-4o and GPT-5 use a newer 200k-token vocabulary (o200k_base) that's generally more efficient, while GPT-4 and GPT-3.5 use an older 100k-token vocabulary (cl100k_base). The same text can encode into fewer tokens under the newer encoding.

Is my text uploaded anywhere when I use this tool?

No. Tokenization runs entirely in your browser using a JavaScript library — your text never leaves your device or gets sent to any server.

How accurate is the cost estimate?

The cost calculation is exact given the token count and the pricing shown, but the pricing itself is a snapshot that can go stale as providers update their rates. Always check the official pricing page for the model you're using before budgeting for production use.

Need Words or Characters Instead?

Word Counter gives you word count, character count, reading time, and more for any text.

Word Counter

Working with API Payloads?

JSON Formatter & Validator cleans up and validates JSON before you tokenize or send it to an API.

JSON Formatter & Validator

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