How Many Pages Are X Tokens?

    Estimate how many words and pages a token count equals (100 tokens ≈ 75 words, 500 words per page). Approximate - each model's tokenizer counts differently.

    Enter a whole number such as 8000, 8,000 or 128k. Maximum: 1,000,000 tokens.

    1000
    Tokens
    750
    Words
    2
    Pages

    Page Visualization

    Scroll down to see all 2 pages

    Forgetting any so made getting showed it kept learning thought these forgot was does. Gave finding tearing be wanted this led other wanting. Set let telling take found going made which swearing for grew moved standing if. Shaking set been became showing paying gotten she. Taking on shining me took rang who stood him can spent done has then said hurt been. Becoming swam sleeping reading bringing stood working laying understood hurting. Swimming did done first when or an gave fighting showing did opened put says came laid struck. But given turning like setting given working stopping sinking. But stood won thinking i well now looking holding other then no. Stood people forgetting fighting swam way drew waking hiding because his me after. Showed shut was want say seeing or saying taking up rang hit fought fell feeding throwing. Going told and well knew made when went like in gone saw sending stuck paid caught an. Cutting could sleeping from how only needed shooting paid writing. Rising bringing spending then because stealing grew standing did from called keeping drinking speaking was won. Left out saying know who spoke saw swore shaking felt shot asking can us what showed. Ran sold these do other you them knowing said let have trying reading give meeting needed buying choosing. His we swearing work eating at thinking after sending gave in sinking walked come not way swam sending opening. Lay set so a were caught leading hurt. Us became lost woke all only moving seen out new working losing forgot seeing felt drank driving becoming. Knew hung read brought paid hung leaving seemed building paid they. Set understanding work stuck leaving freezing out stopped want choosing an standing rising keeping set. Ringing to asked going lost paying me than seeming wanting given swept who doing wearing going there gave seeing opening. Paying working like setting won saying growing people gone told becoming. Thinking choosing would reading wanted turned an learned telling. Trying after feeding new opened hanging put can after rode in sitting starting needed slept thinking having running. Giving eating felt taken sang thinking could swept freezing showed taught fell take us walked. Some sitting sending on becoming leading have the thinking you sweeping saying rising lived showing knowing over swinging. Making shut seen letting year won froze what lived know shooting standing. Swinging hanging ran swung taking getting seemed wearing spending opening were growing shone slept most spoke. Some you throwing said are seeming stuck laid day saying just into year flying do only will these. Turning leading hurting make shone led give drank built losing work set rode moving. Showed wearing flying left leading it started his closing knew of driving told sending thinking becoming. Won taken lost when walked hitting bringing take now spoke waking feeling cutting hurt took meeting. Riding how seeing sticking thought not got becoming spent grew built putting stopping sat made we most. Put only came time made eating catching looked new held finding any. Showing
    Page 1
    spoke stopped people asked writing swearing that taken looked. Out going make when cutting him any be two leaving understanding seeing two her. Would went bringing she it struck was thought ringing slept he cutting about closing first gone. Fought said knew wearing learning got fighting swore standing like came lay. Hit finding wanted made of became says will slept when took sinking. Its sat hanging any her thinking meeting built shooting. Needed told drew were seeing spent put drank like. Sitting hung working worked over also will work year built wrote first trying sent have in sleeping them tried gone. Moved hiding using cutting one fought give gone sweeping. Put showing has shooting from hurting have stole freezing finding running closed the could met so said thought we losing. See doing standing my or thinking stood and told so drove fed shot there because. Thinking looking brought running speaking growing to paying thinking good of opening growing. Any shut not sweeping for putting lived her. Use seeming made could drawing sending throwing riding drove stood doing. Wanting built so threw rang is tore falling that cut hid putting then. There forgetting threw led went seen drew setting then hid other grew put stuck. Led spending because putting paying sank when fought grew just telling like walked done losing telling their shot said. Give is having stood in sitting ran swinging putting or what closing understanding ran so spoke to used. Told now swore eating ate threw moved their done.
    Page 2

    About This Tool

    This free token visualizer helps you understand how many pages a given token count represents. It's useful for estimating document length, understanding AI model context limits, and planning content.

    Important Note: The word and page figures are estimations from a rule of thumb for English text, not tokenizer counts. Real counts depend on the model and the language: Google puts 100 Gemini tokens at about 60-80 English words, and Anthropic says its token counting is an estimate that follows the tokenizer of the model you choose. For OpenAI models you can check an exact count with TikTokenizer.

    Tokens to pages at a glance

    Common token counts converted with the same ratios as the calculator. Query: tokens to pages.

    TokensWordsPages
    1,0007502
    4,0003,0006
    8,0006,00012
    32,00024,00048
    128,00096,000192
    200,000150,000300

    How It Works

    • Uses OpenAI's English estimate: 100 tokens ≈ 75 words (1 token ≈ 0.75 words). See OpenAI token help.
    • Estimates pages at 500 words per page on US letter, rounded up to whole pages. That is a planning assumption, not a printer measurement.
    • Runs entirely in your browser - no data is sent to any server
    • Supports token counts up to 1,000,000 tokens

    Use Cases

    • Estimate document length for AI model context windows
    • Plan content length for GPT, Claude, or other AI models
    • Visualize token limits and understand model capabilities
    • Convert between tokens, words, and pages