Token Saver — Reduce AI Token Cost Before You Upload

Analyze your PDF before sending it to ChatGPT or Claude. Detect headers, footers & references, strip the noise, and cut token costs by up to 40%. 100% client-side — your file never leaves your browser.

Select PDF File

or drag and drop here — never uploaded to any server

🧹

Analysis Complete

Original Tokens

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Optimized Tokens

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Tokens Saved

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Reduction

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Estimated Cost Saved (Input Pricing)

GPT-4o ($5/1M tokens)

Per run cost saved

$0.00

Claude ($3/1M tokens)

Per run cost saved

$0.00

Detected Noise Lines Removed

0 lines

None detected.

No Upload Required 100% Client-Side Instant Results

Why Optimize Before Sending to an AI?

Every token you send costs money. A typical 100-page PDF can carry 20–40% junk tokens in headers, footers, and references. Token Saver strips it before you pay for it.

🔎 Smart Noise Detection

Automatically identifies repeated lines across every page — company logos, page numbers, "Confidential" stamps, and footer text.

First & last 3 lines of every page scanned
Lines appearing on ≥70% of pages flagged
Full preview of removed lines shown

📊 Accurate Token Estimation

No tokenizer library needed. We use the industry-standard 4-chars-per-token approximation used by OpenAI themselves for rough cost estimates.

Original vs. optimized token count
Exact % reduction calculated
Per-model cost saving breakdown

📚 Reference Section Control

Academic papers and legal documents can have hundreds of reference lines. Toggle whether to include or exclude them from your optimized output.

Auto-detects References / Bibliography
Works Cited & Appendix headings supported
Real-time token recalculation on toggle

How Token Saver Works in 4 Steps

All processing runs in your browser using pdf.js. Nothing is sent to any server.

Select PDF

Drop your PDF into the tool. The file is read locally — never uploaded anywhere.

Text Extraction

pdf.js extracts all text per page, preserving reading order and line structure.

Noise Detection

Repeated headers and footers are identified by frequency analysis across all pages and stripped automatically.

Token Report

Token counts are calculated, cost savings estimated for GPT-4o and Claude, and your clean text is ready to copy or download.

Frequently Asked Questions

Everything about tokens, PDF analysis, and data privacy.

What is a "token" in AI context?

AI models like GPT-4 and Claude process text in chunks called tokens. One token ≈ 4 characters or ¾ of a word. Every token you send in your prompt is billed by the model provider. A 200-page PDF can easily contain 80,000+ tokens — many of which are redundant headers and footers.

Is my PDF file uploaded to your servers?

No. Token Saver is 100% client-side. Your PDF is read directly in your browser using the pdf.js library. No file data leaves your device at any point.

How accurate is the token estimate?

We use the standard approximation of 1 token ≈ 4 characters, which is the same rough estimate OpenAI uses in their documentation for budgeting purposes. Actual token count depends on the specific model's tokenizer (BPE), so treat these as close estimates, not exact values.

What counts as "noise"?

Any line of text that appears on 70% or more of pages, found in the first 3 or last 3 lines of each page. This catches company names, page numbers ("Page 3 of 120"), "Confidential", copyright notices, and repeated header text — all content that adds zero informational value for an AI model.

Should I always remove reference sections?

Depends on your task. If you're asking an AI to summarize a paper, references add no value and cost tokens. If you're asking the AI to check your citation format, keep them. The toggle is OFF by default so you stay in control.

Can I use the optimized text directly in ChatGPT?

Yes. Copy the optimized text using the "Copy Optimized Text" button and paste it directly into your ChatGPT or Claude conversation. This is often better than uploading the full PDF, especially for cost-sensitive workflows.