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Smart Token Reducer

Paste your prompt. Six analyzers find wasted tokens from whitespace, filler words, typos, emoji, and casing, then a rule-based rewrite tightens the rest — same meaning, fewer tokens. Everything runs in this tab; nothing is uploaded. Prompt still doesn't fit the window? Try Prompt Compressor →

Your prompt

0 characters · 0 words0 tokens

Reducers

Whitespace Diet
Collapse double spaces, tabs, and stacked blank lines
Filler Killer
Remove "please", "very", "kindly", "I would like you to"...
Fix Typos
Correct common misspellings — technical terms untouched
Emoji Diet
Remove emoji, or convert to a short text tag
CASE Diet
HELLO → Hello — preserves API, JSON, HTTP, ID...
Smart Rewrite
Rule-based condensing: cut wordy phrases, active voice

Optimized

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$0.00
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$0.00
Paste a prompt on the left to see wastage.

How It Works

1
Paste
Drop in your prompt, system message, or article.
2
Toggle a diet
Turn on the reducers you want — each shows its own token savings.
3
Copy & save
Copy the optimized text, same meaning, fewer tokens billed.
See it tokenize
Before
After

What Is a Token, and Why Do Typos Cost More?

A tokenizer breaks text into sub-word pieces from a fixed vocabulary learned during training. Common, correctly spelled words are usually a single token — beautiful is one token with GPT-4o's tokenizer. Misspell it, and the tokenizer has never seen beutiful as a whole word, so it falls back to smaller pieces — be + ut + iful, three tokens instead of one. Multiply that by every typo in a long prompt and the waste adds up fast — which is exactly what Fix Typos catches.

6 Hidden Token Wastes Killing Your API Bill

Waste typeExampleToken costFix
Whitespace"hello world"+1-3 tokens per run of spacesCollapse to single spaces
Filler words"could you please kindly..."+1 token per filler wordRemove — models don’t need politeness
Typos"libary" instead of "library"+1-3 tokens per typoFix common misspellings
Emoji"😂" or "👨‍👩‍👧"2-8+ tokens eachRemove or convert to a short tag
ALL CAPS"URGENT PLEASE READ"+1-2 tokens per wordUse normal casing
Wordy phrases"in order to", "due to the fact that"2-5 tokens per phraseSwap for the concise form

Best Practices to Reduce Tokens

  1. Never use double spaces or heavily indented system prompts.
  2. Lowercase everything except real acronyms (API, JSON, HTTP).
  3. Remove pleasantries — models don't need "please" or "kindly" to follow an instruction.
  4. Use active voice and direct commands: "Explain X" instead of "Could you please explain X".
  5. Replace emoji with a short [tag] if you need the sentiment, not the glyph.
  6. Once your prompt itself is lean, check its total budget against a model's context window with Token Counter, or tighten instruction-style prompts further with Prompt Enhancer.

How Much Can You Save?

Estimated at a typical 30% token reduction on the input side — your real number above may be higher or lower.

Before / month
$18.75
After / month
$17.63
Save $1.13/mo on GPT-4o

Approximate — verified against each provider's official pricing page as of August 31, 2026. Providers change prices without notice; check their page before a billing decision.

Frequently Asked Questions