{"id":5145,"date":"2026-02-03T23:58:35","date_gmt":"2026-02-04T05:58:35","guid":{"rendered":"https:\/\/ykim.synology.me\/wordpress\/?p=5145"},"modified":"2026-02-03T23:58:43","modified_gmt":"2026-02-04T05:58:43","slug":"token-in-ai","status":"publish","type":"post","link":"https:\/\/ykim.synology.me\/wordpress\/token-in-ai-5145\/","title":{"rendered":"Token in AI"},"content":{"rendered":"\n

[Copilot]<\/p>\n\n\n\n

A \u201ctoken\u201d in AI is simply a small unit of text<\/strong> that a language model reads, processes, and generates.
It\u2019s not exactly a word\u2014it’s more like a chunk of text.<\/p>\n\n\n\n

Here\u2019s the clearest way to think about it:<\/p>\n\n\n\n

\ud83d\udd39 What a token is<\/strong><\/h3>\n\n\n\n

A token can be:<\/p>\n\n\n\n

    \n
  • a whole word (\u201capple\u201d)<\/li>\n\n\n\n
  • part of a word (\u201cap\u201d, \u201cple\u201d)<\/li>\n\n\n\n
  • punctuation (\u201c,\u201d)<\/li>\n\n\n\n
  • a space (\u201c \u201d)<\/li>\n<\/ul>\n\n\n\n

    Models don\u2019t see sentences the way humans do.
    They see streams of tokens<\/strong>, like building blocks.<\/p>\n\n\n\n

    \ud83d\udd39 Why tokens matter<\/strong><\/h3>\n\n\n\n

    Tokens determine:<\/p>\n\n\n\n

      \n
    • How long your input is<\/strong><\/li>\n\n\n\n
    • How long the model\u2019s output can be<\/strong><\/li>\n\n\n\n
    • How much computation is needed<\/strong><\/li>\n\n\n\n
    • How much the request costs<\/strong> (for paid APIs)<\/li>\n<\/ul>\n\n\n\n

      \ud83d\udd39 Examples<\/strong><\/h3>\n\n\n\n

      Sentence:
      \u201cI love AI models.\u201d<\/strong><\/p>\n\n\n\n

      Possible tokenization (depends on the model):<\/p>\n\n\n\n

        \n
      • \u201cI\u201d<\/li>\n\n\n\n
      • \u201c love\u201d<\/li>\n\n\n\n
      • \u201c AI\u201d<\/li>\n\n\n\n
      • \u201c models\u201d<\/li>\n\n\n\n
      • \u201c.\u201d<\/li>\n<\/ul>\n\n\n\n

        That\u2019s 5 tokens, even though it\u2019s 4 words.<\/p>\n\n\n\n

        \ud83d\udd39 Why AI uses tokens instead of words<\/strong><\/h3>\n\n\n\n

        Because:<\/p>\n\n\n\n

          \n
        • Many languages don\u2019t separate words cleanly<\/li>\n\n\n\n
        • Subword tokens handle rare or new words better<\/li>\n\n\n\n
        • It makes training more efficient and flexible<\/li>\n<\/ul>\n\n\n\n

          For example, a new word like \u201chyperquantumflex\u201d can be split into known pieces:<\/p>\n\n\n\n

            \n
          • \u201chyper\u201d<\/li>\n\n\n\n
          • \u201cquantum\u201d<\/li>\n\n\n\n
          • \u201cflex\u201d<\/li>\n<\/ul>\n\n\n\n

            The model can still understand and generate it.<\/p>\n\n\n\n

            \ud83d\udd39 In short<\/strong><\/h3>\n\n\n\n

            A token is the atomic unit of text<\/strong> that AI models use to think.
            Humans see words; models see tokens.<\/p>\n\n\n\n

            If you want, I can also explain:<\/p>\n\n\n\n

              \n
            • how many tokens typical sentences use<\/li>\n\n\n\n
            • how token limits affect prompts<\/li>\n\n\n\n
            • how different models tokenize text differently<\/li>\n\n\n\n
            • how to estimate tokens in your own prompts<\/li>\n<\/ul>\n
              <\/div>
              <\/div>","protected":false},"excerpt":{"rendered":"

              [Copilot] A \u201ctoken\u201d in AI is simply a small unit of text that a language model reads, processes, and generates.It\u2019s not exactly a word\u2014it’s more like a chunk of text. Here\u2019s the clearest way to think about it: \ud83d\udd39 What a token is A token can be: Models don\u2019t see sentences the way humans do.They…<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"_kadence_starter_templates_imported_post":false,"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","yasr_overall_rating":0,"yasr_post_is_review":"","yasr_auto_insert_disabled":"","yasr_review_type":"","fifu_image_url":"","fifu_image_alt":"","iawp_total_views":1,"footnotes":""},"categories":[10,291],"tags":[],"class_list":["post-5145","post","type-post","status-publish","format-standard","hentry","category-software-slug","category-ai-prompt-slug"],"yasr_visitor_votes":{"stars_attributes":{"read_only":false,"span_bottom":false},"number_of_votes":0,"sum_votes":0},"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/posts\/5145","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/comments?post=5145"}],"version-history":[{"count":1,"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/posts\/5145\/revisions"}],"predecessor-version":[{"id":5146,"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/posts\/5145\/revisions\/5146"}],"wp:attachment":[{"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/media?parent=5145"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/categories?post=5145"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ykim.synology.me\/wordpress\/wp-json\/wp\/v2\/tags?post=5145"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}