TokenScope: Free AI Token Counter & Cost Calculator

If you build with LLM APIs, you already know the pain: you run a prompt, bill comes in, and you have no clue which call burned your credits. TokenScope solves that — in the browser, offline, free.

TokenScope is a tiny, zero-dependency web tool that counts tokens and estimates cost across every major AI model in 2026. Paste your prompt, pick a model, and you instantly see: token count, input cost, output cost projection, and which model is actually cheapest for your workload.

Try it now

👉 Open TokenScope → (loads in <1s, no backend).

Why we built TokenScope

We run NovAI, an AI API gateway. Every day a customer asks "why was this call so expensive?" The answer is always "you sent 12k tokens to Opus 4.7." But developers don't want to read BPE tables — they want one box, paste prompt, see the number.

Existing calculators are either behind signup walls, riddled with ads, or only support OpenAI models. TokenScope is different:

• ✅ Runs 100% in your browser — your prompts never leave your machine
• ✅ All 2026 models included — GPT-5.5, Claude Opus 4.7, DeepSeek V4, Gemini 3.1 Pro, Qwen-3, GLM-4.6V, MiniMax, Doubao
• ✅ Real BPE tokenizer — not a "1 word = 1.3 tokens" fake estimator
• ✅ Output cost projection — type expected output length, see total cost
• ✅ Open source — github.com/vvvvking/tokenscope

How token pricing actually works in 2026

Every major LLM API charges per token — not per word. And every model uses a different tokenizer, so the same sentence can cost different amounts. Here's the updated pricing landscape (May 2026):

Model	Input / 1M tok	Output / 1M tok	Context
GPT-5.5	$5.00	$30.00	400K
Claude Opus 4.7	$5.00	$25.00	1M
Gemini 3.1 Pro	$1.25	$10.00	2M
DeepSeek V4	$0.27	$1.10	128K
DeepSeek V3.2	$0.20	$0.40	128K
Qwen3-Max	$1.20	$6.00	256K
GLM-4.6V	$0.40	$1.20	200K
MiniMax-Text-01	$0.20	$1.60	1M

A single Hello, how are you? is 6 tokens in GPT, 5 in Claude, 4 in Qwen. Scale that to 10K API calls a day and the difference is real money.

The 3 ways developers lose money on tokens

1. System prompt bloat

A 3000-token system prompt you set once looks cheap. But it gets sent with every request. TokenScope shows you that 3K-token system prompt × 10K calls/day × $5/1M = $150/day — on input alone.

2. Over-provisioned max_tokens

Many developers set max_tokens=4096 "just in case." Opus 4.7 output is $25/1M. If your real answer is 200 tokens, you're not billed for unused output — but the reserved budget can trip rate limits and block parallelism. Right-size it.

3. Wrong model for the job

Classifying 10M user reviews with GPT-5.5 ($5 in + $30 out) when DeepSeek V3.2 ($0.20 + $0.40) handles it identically = 50x overpay. Paste a sample into TokenScope, see the cost side-by-side, switch.

TokenScope features (the ones that matter)

• Batch mode — paste 100 prompts, get total tokens + cost distribution
• Model compare — same prompt, 8 models, one table
• Chat history counter — drop in full messages[] array
• Output cost estimator — "assume 500-token response × 10K calls"
• Export JSON — CSV for finance, JSON for automation
• Keyboard shortcuts — Ctrl+Enter to count, Ctrl+D to dupe

Example: classifying a support ticket

Prompt: "Classify this ticket into {billing, bug, feature}.
Ticket: My invoice shows $127 but I only used $40 of credits..."

GPT-5.5         : 87 in, ~10 out  → $0.000735 / call
Claude Opus 4.7 : 79 in, ~9 out   → $0.000620 / call
DeepSeek V4     : 91 in, ~10 out  → $0.000035 / call  ← 21x cheaper
DeepSeek V3.2   : 91 in, ~10 out  → $0.000022 / call  ← 33x cheaper

At 1M tickets/year: GPT-5.5 costs $735, DeepSeek V3.2 costs $22. Same accuracy on a classification task that doesn't need frontier reasoning. That's what TokenScope helps you see in 30 seconds.

Pair it with a cheap API gateway

Once you know your numbers, you need an API that bills accurately. Most developers in Asia/Europe hit three pain points with native OpenAI/Anthropic:

1. Latency from US-East is 200-400ms for first token
2. OpenAI blocks Chinese phone numbers; Anthropic blocks most of APAC
3. Paying in USD with a foreign card eats 3-5% FX + card fees

NovAI fixes all three: Hong Kong servers (<80ms to most of Asia), OpenAI-compatible endpoint (drop-in base URL swap), USDT / Alipay / PayPal payments, and the same model pricing as OpenRouter or cheaper.

FAQ

Is TokenScope really free?

Yes. It's a static web tool. No login, no ads, no backend. Source is on GitHub (MIT license).

Does it work offline?

Yes, once loaded. Everything runs client-side — the tokenizer WASM is cached.

How accurate is the BPE tokenizer?

We ship the official tiktoken, anthropic-tokenizer, and qwen-tokenizer ports. For DeepSeek / GLM / MiniMax (no public tokenizer) we use an empirically-calibrated BPE — within ±2% on 10K random prompts.

Can I embed it in my app?

Yes. TokenScope is open source — vendor it, iframe it, or lift the tokenizer JS. See the repo for integration examples.

Why is my same prompt different token counts across models?

Each model's tokenizer is different. Claude's tokenizer splits on different byte-pair boundaries than GPT's. Chinese text especially — GPT-4 used 3-4 tokens per Chinese character, GPT-5.5 brought it down to ~1.3; DeepSeek is ~1.0. That's why TokenScope shows every count side-by-side.