{"id":341,"date":"2026-07-11T09:12:21","date_gmt":"2026-07-11T01:12:21","guid":{"rendered":"https:\/\/numsimlab.com\/?p=341"},"modified":"2026-07-11T09:12:21","modified_gmt":"2026-07-11T01:12:21","slug":"%e5%a4%a7%e6%a8%a1%e5%9e%8b%e6%8e%a8%e7%90%86%e9%9b%b6%e5%9f%ba%e7%a1%80%e5%ae%8c%e6%95%b4%e6%95%99%e7%a8%8b","status":"publish","type":"post","link":"https:\/\/numsimlab.com\/?p=341","title":{"rendered":"\u5927\u6a21\u578b\u63a8\u7406\u96f6\u57fa\u7840\u5b8c\u6574\u6559\u7a0b"},"content":{"rendered":"\n<meta charset=\"UTF-8\">\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n<title>\u5927\u6a21\u578b\u63a8\u7406\u96f6\u57fa\u7840\u5b8c\u6574\u6559\u7a0b<\/title>\n<style>\n\/* \u7edf\u4e00\u539f\u7248\u89c6\u89c9\u53d8\u91cf\u4e0e\u57fa\u7840\u6837\u5f0f *\/\n*,*::before,*::after{box-sizing:border-box;margin:0;padding:0}\nhtml{scroll-behavior:smooth}\n:root{\n  --bg:#f8f9fa;--bg2:#fff;--ink:#1a1a2e;--muted:#6c7086;--rule:#e2e4eb;\n  --accent:#2563eb;--accent2:#16a34a;--accent3:#dc2626;--accent4:#d97706;--accent5:#7c3aed;\n  --card-bg:#fff;--code-bg:#f1f3f5;\n  --tag-g:#dcfce7;--tag-g-t:#166534;--tag-b:#dbeafe;--tag-b-t:#1e40af;\n  --tag-r:#fee2e2;--tag-r-t:#991b1b;--tag-y:#fef9c3;--tag-y-t:#713f12;--tag-p:#f3e8ff;--tag-p-t:#581c87;\n  --shadow:0 1px 3px rgba(0,0,.08);--radius:8px;--max-w:960px\n}\n[data-theme=\"dark\"]{\n  --bg:#0b0b1a;--bg2:#16162a;--ink:#e2e4f0;--muted:#7f8396;--rule:#26263e;\n  --accent:#60a5fa;--accent2:#4ade80;--accent3:#f87171;--accent4:#fbbf24;--accent5:#a78bfa;\n  --card-bg:#16162a;--code-bg:#1e2436;\n  --tag-g:#14532d;--tag-g-t:#bbf7d0;--tag-b:#1e3a5f;--tag-b-t:#bfdbfe;\n  --tag-r:#7f1d1d;--tag-r-t:#fecaca;--tag-y:#713f12;--tag-y-t:#fef08a;\n  --tag-p:#3b1f6e;--tag-p-t:#e9d5ff;\n  --shadow:0 1px 3px rgba(0,0,.3)\n}\nbody{\n  font-family:-apple-system,BlinkMacSystemFont,\"Segoe UI\",\"Noto Sans SC\",\"PingFang SC\",\"Microsoft YaHei\",sans-serif;\n  background:var(--bg);color:var(--ink);line-height:1.7;font-size:15px;\n  transition:background .3s,color .3s;\n}\n\/* \u5bfc\u822a\u680f *\/\nheader{\n  position:fixed;top:0;left:0;right:0;z-index:100;\n  background:var(--bg2);border-bottom:1px solid var(--rule);\n  backdrop-filter:blur(12px);-webkit-backdrop-filter:blur(12px);\n}\n.header-wrap{\n  max-width:var(--max-w);margin:0 auto;\n  display:flex;align-items:center;justify-content:space-between;\n  padding:0 1.2rem;height:56px;\n}\n.logo{\n  font-weight:700;font-size:.98rem;color:var(--accent);\n  display:flex;align-items:center;gap:.5rem;\n}\n.header-ctrl{display:flex;gap:.6rem;align-items:center}\n.lang-switch{display:flex;border:1px solid var(--rule);border-radius:6px;overflow:hidden}\n.lang-switch button{\n  border:none;background:transparent;color:var(--muted);\n  padding:.3rem .7rem;font-size:.8rem;cursor:pointer;\n  transition:.2s all;font-family:inherit;\n}\n.lang-switch button.active{background:var(--accent);color:#fff}\n.lang-switch button:hover:not(.active){background:var(--rule);color:var(--ink)}\n.theme-btn{\n  width:34px;height:34px;border:1px solid var(--rule);\n  background:transparent;border-radius:6px;color:var(--muted);\n  cursor:pointer;font-size:1rem;display:flex;align-items:center;justify-content:center;\n}\n.theme-btn:hover{background:var(--rule);color:var(--ink)}\n\n\/* \u4e3b\u4f53\u5bb9\u5668 *\/\nmain{max-width:var(--max-w);margin:0 auto;padding:80px 1.2rem 4rem}\n.lang-block{display:none}\n.lang-block.active{display:block}\n\n\/* \u6807\u9898\u6587\u672c *\/\n.hero{text-align:center;margin-bottom:2.5rem}\nh1{font-size:1.8rem;font-weight:800;margin-bottom:.4rem;letter-spacing:-.02em}\nh1 .desc-sub{display:block;font-size:.86rem;color:var(--muted);font-weight:400;margin-top:.3rem}\nh2{\n  font-size:1.3rem;font-weight:700;margin:2.2rem 0 .9rem;\n  padding-bottom:.4rem;border-bottom:2px solid var(--accent);\n}\nh3{font-size:1.05rem;font-weight:600;margin:1.4rem 0 .5rem;color:var(--accent)}\nh4{font-size:.96rem;font-weight:600;margin:.9rem 0 .3rem}\np{margin-bottom:.8rem}\na{color:var(--accent);text-decoration:none}\na:hover{text-decoration:underline}\n\n\/* \u6807\u7b7e *\/\n.tag{\n  display:inline-block;padding:.14rem .5rem;border-radius:4px;\n  font-size:.73rem;font-weight:600;margin-right:.3rem;white-space:nowrap;\n}\n.tag-g{background:var(--tag-g);color:var(--tag-g-t)}\n.tag-b{background:var(--tag-b);color:var(--tag-b-t)}\n.tag-p{background:var(--tag-p);color:var(--tag-p-t)}\n.tag-y{background:var(--tag-y);color:var(--tag-y-t)}\n.tag-r{background:var(--tag-r);color:var(--tag-r-t)}\n\n\/* \u5361\u7247\u3001\u63d0\u793a\u6846 *\/\n.card{\n  background:var(--card-bg);border:1px solid var(--rule);\n  border-radius:var(--radius);padding:1.3rem;margin-bottom:1.2rem;\n  box-shadow:var(--shadow);\n}\n.tip-box{\n  background:var(--bg);border-left:4px solid var(--accent);\n  padding:.9rem 1rem;margin:1rem 0;border-radius:0 var(--radius) var(--radius) 0;\n  font-size:.88rem;\n}\n.tip-box.warn{border-left-color:var(--accent4)}\n.tip-box.danger{border-left-color:var(--accent3)}\n.tip-box strong{color:var(--accent)}\n\n\/* \u76ee\u5f55 *\/\n.toc-box{\n  background:var(--card-bg);border:1px solid var(--rule);\n  border-radius:var(--radius);padding:1.2rem 1.4rem;margin-bottom:2.2rem;\n  box-shadow:var(--shadow);\n}\n.toc-box h3{margin:0 0 .6rem;font-size:.9rem;text-transform:uppercase;color:var(--muted)}\n.toc-box ol{padding-left:1.3rem}\n.toc-box li{margin-bottom:.3rem;font-size:.88rem}\n.toc-box a{color:var(--ink)}\n.toc-box a:hover{color:var(--accent);text-decoration:none}\n\n\/* \u4ee3\u7801\u3001\u7ec8\u7aef *\/\npre.code{\n  background:var(--code-bg);padding:.9rem 1rem;border-radius:var(--radius);\n  overflow-x:auto;font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;\n  font-size:.82rem;line-height:1.5;margin:.7rem 0;border:1px solid var(--rule);\n}\ncode.inline{\n  background:var(--code-bg);padding:.13rem .4rem;border-radius:4px;\n  font-family:monospace;font-size:.83rem;border:1px solid var(--rule);\n}\n.terminal{\n  background:#1a1a2e;color:#a8e6cf;padding:.9rem 1rem;border-radius:var(--radius);\n  font-family:monospace;font-size:.82rem;overflow-x:auto;margin:.7rem 0;\n  border:1px solid #333;line-height:1.6;\n}\n[data-theme=\"dark\"] .terminal{background:#08081a}\n\n\/* \u53cc\u5bf9\u6bd4\u680f *\/\n.compare-wrap{\n  display:grid;grid-template-columns:1fr 1fr;gap:1rem;margin:1.2rem 0;\n}\n.compare-item{\n  background:var(--card-bg);border:1px solid var(--rule);\n  border-radius:var(--radius);padding:1rem;box-shadow:var(--shadow);\n}\n.compare-item.bad h4{color:var(--accent3)}\n.compare-item.good h4{color:var(--accent2)}\n\n\/* \u547d\u4ee4\u5361\u7247\u7f51\u683c *\/\n.cmd-grid{\n  display:grid;grid-template-columns:repeat(auto-fit,minmax(260px,1fr));gap:.8rem;margin:1.2rem 0;\n}\n.cmd-card{\n  background:var(--card-bg);border:1px solid var(--rule);\n  border-radius:var(--radius);padding:.9rem;box-shadow:var(--shadow);\n}\n.cmd-card h4{margin:0 0 .4rem;font-size:.88rem;color:var(--accent)}\n.cmd-card .cmd-line{\n  display:block;background:var(--code-bg);padding:.3rem .5rem;border-radius:4px;\n  font-family:monospace;font-size:.8rem;margin-bottom:.3rem;overflow-x:auto;\n}\n.cmd-card .desc{font-size:.8rem;color:var(--muted)}\n\n\/* \u6b65\u9aa4\u5217\u8868 *\/\n.step-list{\n  list-style:none;counter-reset:step;margin:1.2rem 0;\n}\n.step-list li{\n  counter-increment:step;position:relative;padding:.9rem 1rem .9rem 3rem;\n  margin-bottom:.6rem;background:var(--card-bg);border-left:2px solid var(--rule);\n  border-radius:0 var(--radius) 0;box-shadow:var(--shadow);\n}\n.step-list li::before{\n  content:counter(step);position:absolute;left:-14px;top:.9rem;\n  width:28px;height:28px;border-radius:50%;background:var(--accent);\n  color:#fff;display:flex;align-items:center;justify-content:center;\n  font-size:.78rem;font-weight:700;\n}\n.step-list .cmd-line{\n  display:block;background:var(--code-bg);padding:.4rem .7rem;border-radius:5px;\n  font-family:monospace;margin:.4rem 0;overflow-x:auto;font-size:.82rem;\n}\n\n\/* \u8868\u683c *\/\n.table-box{overflow-x:auto;margin:1.2rem 0}\ntable{width:100%;border-collapse:collapse;font-size:.82rem}\nthead th{\n  background:var(--accent);color:#fff;padding:.6rem .5rem;text-align:center;\n  font-weight:600;\n}\nthead th:first-child{border-radius:6px 0 0 0}\nthead th:last-child{border-radius:0 6px 0 0}\ntbody td{padding:.6rem .5rem;border-bottom:1px solid var(--rule);vertical-align:middle}\ntbody tr:nth-child(even){background:var(--bg)}\ntbody td:first-child{text-align:left;font-weight:600}\n\n\/* \u5e95\u90e8 *\/\nfooter{\n  max-width:var(--max-w);margin:4rem auto 0;padding:2rem 1rem 3rem;\n  border-top:1px solid var(--rule);text-align:center;font-size:.82rem;color:var(--muted);\n}\n\n\/* \u79fb\u52a8\u7aef\u9002\u914d *\/\n@media (max-width:660px){\n  h1{font-size:1.45rem}\n  .compare-wrap{grid-template-columns:1fr}\n  .cmd-grid{grid-template-columns:1fr}\n  .step-list li{padding-left:2.5rem}\n  .step-list li::before{width:24px;height:24px;left:-12px;font-size:.7rem}\n  main{padding:74px 1rem 3rem}\n}\n<\/style>\n\n<header>\n  <div class=\"header-wrap\">\n    <div class=\"logo\"><span>\ud83e\udde0<\/span> \u5927\u6a21\u578b\u63a8\u7406\u96f6\u57fa\u7840\u5b8c\u6574\u6559\u7a0b<\/div>\n    <div class=\"header-ctrl\">\n      <div class=\"lang-switch\">\n        <button class=\"active\" onclick=\"switchLang('zh')\" id=\"btn-zh\">\u4e2d\u6587<\/button>\n        <button onclick=\"switchLang('en')\" id=\"btn-en\">English<\/button>\n      <\/div>\n      <button class=\"theme-btn\" onclick=\"toggleDark()\" title=\"\u5207\u6362\u660e\u6697\u4e3b\u9898\">\u263c<\/button>\n    <\/div>\n  <\/div>\n<\/header>\n<main>\n<!-- \u4e2d\u6587\u5185\u5bb9\u533a\u5757 -->\n<div class=\"lang-block active\" id=\"zh-content\">\n  <div class=\"hero\">\n    <h1>\u5927\u6a21\u578b\u63a8\u7406\u96f6\u57fa\u7840\u5b8c\u6574\u8bb2\u89e3\uff1a\u539f\u7406\u3001\u6d41\u7a0b\u3001KV\u7f13\u5b58\u3001\u90e8\u7f72\u4f18\u5316\u5168\u89e3<\/h1>\n    <div class=\"desc-sub\">\u533a\u5206\u8bad\u7ec3\u4e0e\u63a8\u7406\uff0c\u62c6\u89e3\u751f\u6210\u5168\u8fc7\u7a0b\uff0c\u5f04\u61c2\u5ef6\u8fdf\/\u541e\u5410\/\u51b7\u542f\u52a8\uff0c\u672c\u5730&#038;\u7ebf\u4e0a\u843d\u5730\u5168\u6307\u5357<\/div>\n  <\/div>\n\n  <div class=\"toc-box\">\n    <h3>\u76ee\u5f55\u5bfc\u822a<\/h3>\n    <ol>\n      <li><a href=\"#p1\">\u4e00\u3001\u4ec0\u4e48\u662f\u5927\u6a21\u578b\u63a8\u7406\uff1f\u751f\u6d3b\u5316\u7c7b\u6bd4<\/a><\/li>\n      <li><a href=\"#p2\">\u4e8c\u3001\u63a8\u7406 vs \u8bad\u7ec3 \u6838\u5fc3\u672c\u8d28\u533a\u522b<\/a><\/li>\n      <li><a href=\"#p3\">\u4e09\u3001\u63a8\u7406\u5b8c\u6574\u6267\u884c\u5168\u6d41\u7a0b\u62c6\u89e3<\/a><\/li>\n      <li><a href=\"#p4\">\u56db\u3001\u4e24\u5927\u6838\u5fc3\u9636\u6bb5\uff1aPrefill\u9884\u586b\u5145 &#038; Decode\u89e3\u7801<\/a><\/li>\n      <li><a href=\"#p5\">\u4e94\u3001\u63a8\u7406\u6838\u5fc3\u4f18\u5316\uff1aKV\u7f13\u5b58\u539f\u7406<\/a><\/li>\n      <li><a href=\"#p6\">\u516d\u3001\u91c7\u6837\u53c2\u6570\uff1a\u63a7\u5236\u56de\u7b54\u521b\u610f\u4e0e\u4e25\u8c28<\/a><\/li>\n      <li><a href=\"#p7\">\u4e03\u3001\u7ebf\u4e0a\u63a8\u7406\u670d\u52a1\u5173\u952e\u6307\u6807<\/a><\/li>\n      <li><a href=\"#p8\">\u516b\u3001\u4e3b\u6d41\u63a8\u7406\u4f18\u5316\u6280\u672f<\/a><\/li>\n      <li><a href=\"#p9\">\u4e5d\u3001\u63a8\u7406\u90e8\u7f72\u5b8c\u6574\u6807\u51c6\u6d41\u7a0b<\/a><\/li>\n      <li><a href=\"#p10\">\u5341\u3001\u65b0\u624b\u63a8\u7406\u9ad8\u9891\u8e29\u5751\u6e05\u5355<\/a><\/li>\n    <\/ol>\n  <\/div>\n\n  <h2 id=\"p1\">\u4e00\u3001\u4ec0\u4e48\u662f\u5927\u6a21\u578b\u63a8\u7406\uff1f\u751f\u6d3b\u5316\u7c7b\u6bd4<\/h2>\n  <div class=\"card\">\n    <h4>\u96f6\u57fa\u7840\u901a\u4fd7\u5b9a\u4e49<\/h4>\n    <p><span class=\"tag-b\">\u5927\u6a21\u578b\u63a8\u7406\uff08LLM Inference\uff09<\/span>\uff1a\u6a21\u578b\u5b8c\u6210\u9884\u8bad\u7ec3\u3001\u5fae\u8c03\u4e4b\u540e\uff0c\u6743\u91cd\u5168\u90e8\u56fa\u5b9a\u51bb\u7ed3\uff0c\u63a5\u6536\u7528\u6237\u8f93\u5165Prompt\uff0c\u9010Token\u751f\u6210\u6587\u672c\u7684\u6b63\u5411\u8ba1\u7b97\u8fc7\u7a0b\u3002<\/p>\n    <p>\u751f\u6d3b\u5316\u7c7b\u6bd4\uff1a\n    <br><span class=\"tag-g\">\u8bad\u7ec3<\/span> = \u5b66\u751f\u591a\u5e74\u4e0a\u8bfe\u5237\u9898\uff0c\u6301\u7eed\u4fee\u6b63\u81ea\u5df1\u7684\u77e5\u8bc6\u50a8\u5907\uff08\u8fed\u4ee3\u66f4\u65b0\u6a21\u578b\u6743\u91cd\uff09\uff1b\n    <br><span class=\"tag-y\">\u63a8\u7406<\/span> = \u5b66\u751f\u6bd5\u4e1a\u4e4b\u540e\u62ff\u5230\u5168\u65b0\u9898\u76ee\uff0c\u76f4\u63a5\u5199\u51fa\u7b54\u6848\uff0c\u4e0d\u518d\u4fee\u6539\u81ea\u5df1\u8111\u5b50\u91cc\u7684\u77e5\u8bc6\uff08\u6743\u91cd\u6c38\u4e45\u4e0d\u53d8\uff09\u3002\n    <\/p>\n    <p>\u65e5\u5e38\u4f7f\u7528ChatGPT\u3001\u672c\u5730Ollama\u3001\u4ee3\u7801\u52a9\u624b\u3001AI\u5ba2\u670d\uff0c\u5e95\u5c42\u8fd0\u884c\u7684\u5168\u90e8\u90fd\u662f\u63a8\u7406\u903b\u8f91\u3002<\/p>\n  <\/div>\n  <div class=\"tip-box\">\n    <strong>\u5173\u952e\u533a\u5206\uff1a<\/strong>\u63a8\u7406\u9636\u6bb5\u4e0d\u4f1a\u66f4\u65b0\u4efb\u4f55\u6a21\u578b\u53c2\u6570\uff0c\u4ec5\u6267\u884c\u524d\u5411\u7f51\u7edc\u8ba1\u7b97\uff0c\u65e0\u53cd\u5411\u4f20\u64ad\uff0c\u7b97\u529b\u6d88\u8017\u8fdc\u4f4e\u4e8e\u8bad\u7ec3\u4efb\u52a1\u3002\n  <\/div>\n\n  <h2 id=\"p2\">\u4e8c\u3001\u63a8\u7406 vs \u8bad\u7ec3 \u6838\u5fc3\u672c\u8d28\u533a\u522b<\/h2>\n  <div class=\"compare-wrap\">\n    <div class=\"compare-item bad\">\n      <h4>\u6a21\u578b\u8bad\u7ec3\uff08\u9884\u8bad\u7ec3\/\u5fae\u8c03\uff09<\/h4>\n      <ul>\n        <li>\u8f93\u5165\u6d77\u91cf\u6587\u672c\u6570\u636e\u96c6\uff0c\u6bcf\u8f6e\u8fed\u4ee3\u66f4\u65b0\u6a21\u578b\u6743\u91cd<\/li>\n        <li>\u540c\u65f6\u6267\u884c\u524d\u5411\u4f20\u64ad+\u53cd\u5411\u4f20\u64ad\uff0c\u7b97\u529b\u5f00\u9500\u6781\u5927<\/li>\n        <li>\u79bb\u7ebf\u6279\u91cf\u4efb\u52a1\uff0c\u5355\u6b21\u8fd0\u884c\u8017\u65f6\u6570\u5929\u4e43\u81f3\u6570\u5468<\/li>\n        <li>\u4f18\u5316\u76ee\u6807\u4e3a\u6570\u636e\u603b\u541e\u5410\uff0c\u4e0d\u5173\u6ce8\u5355\u6761\u8bf7\u6c42\u5ef6\u8fdf<\/li>\n        <li>\u4f9d\u8d56\u591a\u673a\u591a\u5361\u9ad8\u901f\u4e92\u8054\u96c6\u7fa4\uff0c\u786c\u4ef6\u6210\u672c\u6781\u9ad8<\/li>\n        <li>\u663e\u5b58\u9700\u8981\u5b58\u653e\u6743\u91cd\u3001\u68af\u5ea6\u3001\u4f18\u5316\u5668\u7f13\u51b2\uff0c\u5360\u7528\u5de8\u5927<\/li>\n      <\/ul>\n    <\/div>\n    <div class=\"compare-item good\">\n      <h4>\u6a21\u578b\u63a8\u7406\uff08\u7ebf\u4e0a\u670d\u52a1\/\u672c\u5730\u8fd0\u884c\uff09<\/h4>\n      <ul>\n        <li>\u4ec5\u63a5\u6536\u5355\u6761\u7528\u6237\u63d0\u95ee\uff0c\u6240\u6709\u6743\u91cd\u56fa\u5b9a\u51bb\u7ed3<\/li>\n        <li>\u53ea\u6267\u884c\u524d\u5411\u8ba1\u7b97\uff0c\u65e0\u68af\u5ea6\u3001\u65e0\u53cd\u5411\u4f20\u64ad\u6d41\u7a0b<\/li>\n        <li>7\u00d724\u5c0f\u65f6\u6301\u7eed\u5728\u7ebf\uff0c\u5b9e\u65f6\u54cd\u5e94\u7528\u6237\u8bf7\u6c42<\/li>\n        <li>\u6838\u5fc3\u4f18\u5316\u6307\u6807\uff1a\u4f4e\u9996\u5b57\u5ef6\u8fdf\u3001\u9ad8\u5e76\u53d1\u541e\u5410<\/li>\n        <li>\u5355\u673a\u5355\u5361\u5373\u53ef\u90e8\u7f72\uff0c\u652f\u6301\u5f39\u6027\u6269\u5bb9\u7f29\u5bb9<\/li>\n        <li>\u663e\u5b58\u5360\u7528\u4ec5\u5305\u542b\u6a21\u578b\u6743\u91cd + KV\u7f13\u5b58\u7f13\u51b2\u533a<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <div class=\"table-box\">\n    <table>\n      <thead>\n        <tr>\n          <th>\u5bf9\u6bd4\u7ef4\u5ea6<\/th>\n          <th>\u8bad\u7ec3<\/th>\n          <th>\u63a8\u7406<\/th>\n        <\/tr>\n      <\/thead>\n      <tbody>\n        <tr>\n          <td>\u53c2\u6570\u72b6\u6001<\/td>\n          <td>\u6bcf\u6279\u6b21\u66f4\u65b0\u6743\u91cd<\/td>\n          <td>\u6240\u6709\u6743\u91cd\u6c38\u4e45\u51bb\u7ed3<\/td>\n        <\/tr>\n        <tr>\n          <td>\u8ba1\u7b97\u6d41\u7a0b<\/td>\n          <td>\u524d\u5411 + \u53cd\u5411\u4f20\u64ad<\/td>\n          <td>\u4ec5\u524d\u5411\u4f20\u64ad<\/td>\n        <\/tr>\n        <tr>\n          <td>\u8fd0\u884c\u6a21\u5f0f<\/td>\n          <td>\u79bb\u7ebf\u6279\u91cf\u4efb\u52a1<\/td>\n          <td>\u5728\u7ebf\u5b9e\u65f6API\u670d\u52a1<\/td>\n        <\/tr>\n        <tr>\n          <td>\u4f18\u5316\u76ee\u6807<\/td>\n          <td>\u6700\u5927\u5316\u6570\u636e\u5904\u7406\u901f\u5ea6<\/td>\n          <td>\u7f29\u77ed\u7528\u6237\u7b49\u5f85\u3001\u627f\u8f7d\u9ad8\u5e76\u53d1<\/td>\n        <\/tr>\n        <tr>\n          <td>\u663e\u5b58\u5f00\u9500<\/td>\n          <td>\u6743\u91cd+\u68af\u5ea6+\u4f18\u5316\u5668\u7f13\u5b58<\/td>\n          <td>\u6743\u91cd+KV\u7f13\u5b58<\/td>\n        <\/tr>\n      <\/table>\n  <\/div>\n\n  <h2 id=\"p3\">\u4e09\u3001\u63a8\u7406\u5b8c\u6574\u6267\u884c\u5168\u6d41\u7a0b\u62c6\u89e3<\/h2>\n<pre class=\"code\">\n# \u7528\u6237\u8f93\u5165\u793a\u4f8bPrompt\n\u7528\u6237\u63d0\u95ee\uff1a\u5199\u4e00\u6bb5Python\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u4ee3\u7801\n<\/pre>\n  <ol class=\"step-list\">\n    <li><strong>Token\u5206\u8bcd\uff08Tokenizer\uff09<\/strong>\uff1a\u5c06\u81ea\u7136\u6587\u672c\u5207\u5272\u4e3a\u6700\u5c0f\u8bcd\u5143\uff0c\u6620\u5c04\u4e3a\u6570\u5b57ID\uff1b\n    <div class=\"cmd-line\">\u793a\u4f8b\uff1a\u5199 \u2192 324\uff0c\u4e00\u6bb5\u4ee3\u7801 \u2192 987<\/div>\n    <\/li>\n    <li><strong>Prefill\u9884\u586b\u5145<\/strong>\u4e00\u6b21\u6027\u5e76\u884c\u8ba1\u7b97\u5168\u90e8\u8f93\u5165Token\uff0c\u751f\u6210\u7b2c\u4e00\u4e2a\u8f93\u51fa\u8bcd\u5143\u5e76\u7f13\u5b58KV\u5f20\u91cf\uff1b<\/li>\n    <li><strong>Decode\u89e3\u7801\u5faa\u73af<\/strong>\u4f9d\u6258\u5b8c\u6574\u4e0a\u4e0b\u6587\uff0c\u9010\u6b21\u9884\u6d4b\u4e0b\u4e00\u4e2aToken\uff1b<\/li>\n    <li><strong>\u6982\u7387\u91c7\u6837\u7b5b\u9009<\/strong>\u6839\u636e\u8f93\u51fa\u6982\u7387\u5206\u5e03\u6311\u9009\u5408\u7406\u8bcd\u5143\uff1b<\/li>\n    <li><strong>\u7ec8\u6b62\u5224\u65ad<\/strong>\u547d\u4e2dEOS\u7ed3\u675f\u7b26\u6216\u8fbe\u5230\u6700\u5927\u957f\u5ea6\u5219\u505c\u6b62\u751f\u6210\uff1b<\/li>\n    <li><strong>\u53cd\u5206\u8bcd\u8fd8\u539f\u6587\u672c<\/strong>\u6570\u5b57ID\u8f6c\u56de\u81ea\u7136\u8bed\u8a00\uff0c\u8fd4\u56de\u7ed9\u524d\u7aef\u7528\u6237\u3002<\/li>\n  <\/ol>\n  <div class=\"tip-box warn\">\n    <strong>\u73b0\u8c61\u89e3\u91ca\uff1a<\/strong>\u804a\u5929\u754c\u9762AI\u9010\u5b57\u6253\u5b57\u7684\u6d41\u5f0f\u6548\u679c\uff0c\u672c\u8d28\u662fDecode\u4e32\u884c\u5faa\u73af\u6bcf\u8f6e\u53ea\u751f\u62101\u4e2aToken\u3002\n  <\/div>\n\n  <h2 id=\"p4\">\u56db\u3001\u4e24\u5927\u6838\u5fc3\u9636\u6bb5\uff1aPrefill\u9884\u586b\u5145 &#038; Decode\u89e3\u7801<\/h2>\n  <div class=\"cmd-grid\">\n    <div class=\"cmd-card\">\n      <h4>Prefill \u9884\u586b\u5145\uff08\u8f93\u5165\u5904\u7406\uff09<\/h4>\n      <div class=\"desc\">\u5e76\u884c\u5904\u7406\u6574\u6bb5\u7528\u6237Prompt\uff0c\u7b97\u529b\u5bc6\u96c6\uff0c\u590d\u6742\u5ea6O(n\u00b2)\uff0c\u9996\u5b57\u5ef6\u8fdfTTFT\u4e3b\u8981\u7531\u8be5\u9636\u6bb5\u51b3\u5b9a\u3002<\/div>\n      <div class=\"tag tag-r\">\u74f6\u9888\uff1aGPU\u7b97\u529b<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>Decode \u89e3\u7801\uff08\u751f\u6210\u9636\u6bb5\uff09<\/h4>\n      <div class=\"desc\">\u4e32\u884c\u9010\u8bcd\u8f93\u51fa\uff0c\u663e\u5b58\u5e26\u5bbd\u5bc6\u96c6\uff0c\u590d\u7528\u5386\u53f2KV\u7f13\u5b58\uff0c\u5355\u6b21\u8ba1\u7b97\u590d\u6742\u5ea6O(n)\u3002<\/div>\n      <div class=\"tag tag-y\">\u74f6\u9888\uff1a\u663e\u5b58\u5e26\u5bbd<\/div>\n    <\/div>\n  <\/div>\n  <div class=\"card\">\n    <h4>\u9636\u6bb5\u901a\u4fd7\u5bf9\u6bd4<\/h4>\n    <p>Prefill\uff1a\u4e00\u6b21\u6027\u8bfb\u5b8c\u6574\u4e2a\u95ee\u9898\uff0c\u68b3\u7406\u5b8c\u6574\u4e0a\u4e0b\u6587\u51c6\u5907\u4f5c\u7b54\uff1b<\/p>\n    <p>Decode\uff1a\u4e00\u4e2a\u5b57\u4e00\u4e2a\u5b57\u4e66\u5199\u7b54\u6848\uff0c\u6bcf\u5199\u4e00\u6b65\u90fd\u56de\u770b\u524d\u6587\u5185\u5bb9\u3002<\/p>\n    <p>\u5de5\u4e1a\u4f18\u5316\u65b9\u6848\uff1aPrefill\/Decode\u5206\u79bb\u90e8\u7f72\u67b6\u6784\uff0c\u7b97\u529b\u5361\u5904\u7406\u8f93\u5165\u3001\u5e26\u5bbd\u5361\u8d1f\u8d23\u751f\u6210\uff0c\u786c\u4ef6\u5229\u7528\u7387\u5927\u5e45\u63d0\u5347\u3002<\/p>\n  <\/div>\n\n  <h2 id=\"p5\">\u4e94\u3001\u63a8\u7406\u6838\u5fc3\u4f18\u5316\uff1aKV\u7f13\u5b58\u539f\u7406<\/h2>\n  <div class=\"card\">\n    <h4>\u4e3a\u4ec0\u4e48\u5fc5\u987b\u4f7f\u7528KV\u7f13\u5b58\uff1f<\/h4>\n    <p>\u82e5\u65e0KV\u7f13\u5b58\uff0c\u6bcf\u751f\u62101\u4e2aToken\u90fd\u9700\u8981\u91cd\u65b0\u8ba1\u7b97\u5168\u90e8\u5386\u53f2\u4e0a\u4e0b\u6587\u7684Key\u3001Value\u5f20\u91cf\uff0c\u4ea7\u751f\u5de8\u91cf\u91cd\u590d\u8ba1\u7b97\uff0c\u63a8\u7406\u901f\u5ea6\u6781\u6162\u3002<\/p>\n    <p><span class=\"tag-p\">KV\u7f13\u5b58<\/span>\uff1a\u628aPrefill\u3001\u6bcf\u8f6eDecode\u8ba1\u7b97\u51fa\u7684K\/V\u77e9\u9635\u5b58\u5165\u663e\u5b58\uff0c\u540e\u7eed\u751f\u6210\u76f4\u63a5\u590d\u7528\u5df2\u6709\u7f13\u5b58\uff0c\u8ba1\u7b97\u91cf\u5927\u5e45\u964d\u4f4e\uff0c\u901f\u5ea6\u63d0\u5347\u6570\u500d\u81f3\u6570\u5341\u500d\u3002<\/p>\n  <\/div>\n<pre class=\"code\">\n# \u65e0\u7f13\u5b58\u4f4e\u6548\u6d41\u7a0b\n\u6bcf\u751f\u62101\u4e2aToken \u2192 \u5168\u91cf\u91cd\u7b97\u6240\u6709\u5386\u53f2KV\u5f20\u91cf\n\n# KV\u7f13\u5b58\u6807\u51c6\u4f18\u5316\u6d41\u7a0b\n1. \u4e00\u6b21\u6027\u8ba1\u7b97\u5168\u90e8\u8f93\u5165Token\u7684KV\u5e76\u5b58\u663e\u5b58\n2. \u540e\u7eed\u5faa\u73af\u4ec5\u8ba1\u7b97\u65b0\u589eToken KV\uff0c\u62fc\u63a5\u65e7\u7f13\u5b58\n<\/pre>\n  <div class=\"info-box danger\">\n    <strong>\u663e\u5b58\u75db\u70b9\uff1a<\/strong>\u5bf9\u8bdd\u4e0a\u4e0b\u6587\u8d8a\u957f\uff0cKV\u7f13\u5b58\u5360\u7528\u663e\u5b58\u8d8a\u5927\uff0c\u6781\u6613\u89e6\u53d1OOM\u663e\u5b58\u6ea2\u51fa\uff1b\u89e3\u51b3\u65b9\u6848\uff1a\u5206\u9875KV\u7f13\u5b58\u3001KV\u91cf\u5316\u538b\u7f29\u3002\n  <\/div>\n\n  <h2 id=\"p6\">\u516d\u3001\u91c7\u6837\u53c2\u6570\uff1a\u63a7\u5236\u56de\u7b54\u521b\u610f\u4e0e\u4e25\u8c28<\/h2>\n  <div class=\"table-box\">\n    <table>\n      <thead>\n        <tr>\n          <th>\u53c2\u6570\u540d\u79f0<\/th>\n          <th>\u4f5c\u7528\u8bf4\u660e<\/th>\n          <th>\u63a8\u8350\u53d6\u503c\u533a\u95f4<\/th>\n        <\/tr>\n      <\/thead>\n      <tbody>\n        <tr>\n          <td>Temperature \u6e29\u5ea6<\/td>\n          <td>\u63a7\u5236\u8f93\u51fa\u968f\u673a\u6027\uff0c\u6570\u503c\u8d8a\u9ad8\u60f3\u8c61\u529b\u8d8a\u5f3a\u3001\u8d8a\u4e0d\u7a33\u5b9a<\/td>\n          <td>\u4ee3\u7801\/\u6570\u5b66\uff1a0.1~0.3\uff1b\u6587\u6848\u521b\u4f5c\uff1a0.7~1.0<\/td>\n        <\/tr>\n        <tr>\n          <td>Top-p<\/td>\n          <td>\u4ec5\u4fdd\u7559\u7d2f\u8ba1\u6982\u7387\u9608\u503c\u4e4b\u4e0a\u5019\u9009\u8bcd<\/td>\n          <td>0.3 ~ 0.95<\/td>\n        <\/tr>\n        <tr>\n          <td>Top-k<\/td>\n          <td>\u4ec5\u4fdd\u7559\u6982\u7387\u6700\u9ad8\u524dk\u4e2a\u8bcd\u5143<\/td>\n          <td>20 ~ 100<\/td>\n        <\/tr>\n        <tr>\n          <td>Max_tokens<\/td>\n          <td>\u9650\u5236\u8f93\u51fa\u6700\u5927\u957f\u5ea6\uff0c\u9632\u6b62\u65e0\u9650\u751f\u6210<\/td>\n          <td>256 \/ 1024 \/ 4096 \u6309\u9700\u914d\u7f6e<\/td>\n        <\/tr>\n      <\/tbody>\n    <\/table>\n    <div class=\"tip-box\">\n      <strong>\u751f\u4ea7\u89c4\u8303\uff1a<\/strong>\u4ee3\u7801\u3001\u77e5\u8bc6\u5e93\u95ee\u7b54\u3001\u6570\u5b66\u63a8\u7406\u964d\u4f4e\u6e29\u5ea6\uff0c\u51cf\u5c11AI\u5e7b\u89c9\uff1b\u5c0f\u8bf4\u3001\u6587\u6848\u7c7b\u4efb\u52a1\u8c03\u9ad8\u6e29\u5ea6\u63d0\u5347\u521b\u610f\u3002\n    <\/div>\n  <\/div>\n\n  <h2 id=\"p7\">\u4e03\u3001\u7ebf\u4e0a\u63a8\u7406\u670d\u52a1\u5173\u952e\u6307\u6807<\/h2>\n  <div class=\"cmd-grid\">\n    <div class=\"cmd-card\">\n      <h4>TTFT \u9996\u5b57\u5ef6\u8fdf<\/h4>\n      <div class=\"desc\">\u53d1\u9001\u63d0\u95ee\u5230\u8fd4\u56de\u7b2c\u4e00\u4e2aToken\u7684\u8017\u65f6\uff0c\u7528\u6237\u4f53\u9a8c\u6838\u5fc3\u6307\u6807\u3002<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>TPOT \u5355Token\u95f4\u9694<\/h4>\n      <div class=\"desc\">\u76f8\u90bb\u751f\u6210\u8bcd\u5143\u7684\u95f4\u9694\uff0c\u51b3\u5b9a\u6d41\u5f0f\u6253\u5b57\u6d41\u7545\u5ea6\u3002<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>\u541e\u5410\u91cf TPS<\/h4>\n      <div class=\"desc\">\u5355GPU\u6bcf\u79d2\u5904\u7406Token\u603b\u91cf\uff0c\u8861\u91cf\u670d\u52a1\u5668\u5e76\u53d1\u4e0a\u9650\u3002<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>\u7f13\u5b58\u547d\u4e2d\u7387<\/h4>\n      <div class=\"desc\">\u4e0a\u4e0b\u6587\u7f13\u5b58\u590d\u7528\u6bd4\u4f8b\uff0c\u6570\u503c\u8d8a\u9ad8\u7b97\u529b\u6d88\u8017\u8d8a\u4f4e\u3001\u901f\u5ea6\u8d8a\u5feb\u3002<\/div>\n    <\/div>\n  <\/div>\n  <div class=\"info-box warn\">\n    <strong>\u51b7\u542f\u52a8\u95ee\u9898\uff1a<\/strong>\u670d\u52a1\u95f2\u7f6e\u91ca\u653eGPU\u540e\uff0c\u65b0\u8bf7\u6c42\u9700\u8981\u91cd\u65b0\u52a0\u8f7d\u6a21\u578b\uff0cTTFT\u98d9\u5347\u81f3\u6570\u5341\u79d2\uff1b\u4f18\u5316\u624b\u6bb5\uff1a\u9884\u70ed\u5b9e\u4f8b\u6c60\u3001\u6a21\u578b\u6d41\u5f0f\u52a0\u8f7d\u3002\n  <\/div>\n\n  <h2 id=\"p8\">\u516b\u3001\u4e3b\u6d41\u63a8\u7406\u4f18\u5316\u6280\u672f<\/h2>\n  <div class=\"two-col\">\n    <div class=\"compare-col good\">\n      <h4>\u663e\u5b58\u8282\u7ea6\u65b9\u6848<\/h4>\n      <ul>\n        <li>\u91cf\u5316\u538b\u7f29\uff1aFP16 \/ INT8 \/ INT4<\/li>\n        <li>PagedAttention \u5206\u9875KV\u7f13\u5b58<\/li>\n        <li>\u524d\u7f00\u7f13\u5b58\uff1a\u590d\u7528\u56fa\u5b9a\u7cfb\u7edf\u63d0\u793a\u8bcdKV<\/li>\n        <li>GQA\/MQA \u5206\u7ec4\u6ce8\u610f\u529b\u7f29\u51cfKV\u4f53\u79ef<\/li>\n      <\/ul>\n    <\/div>\n    <div class=\"compare-col good\">\n      <h4>\u5e76\u53d1\u8c03\u5ea6\u65b9\u6848<\/h4>\n      <ul>\n        <li>Continuous Batching \u8fde\u7eed\u6279\u5904\u7406<\/li>\n        <li>Prefill\u4e0eDecode\u5206\u79bb\u90e8\u7f72<\/li>\n        <li>\u9884\u70ed\u6c60\u6d88\u9664\u51b7\u542f\u52a8\u5ef6\u8fdf<\/li>\n        <li>GPU\u5f39\u6027\u81ea\u52a8\u6269\u7f29\u5bb9<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n\n  <h2 id=\"p9\">\u4e5d\u3001\u63a8\u7406\u90e8\u7f72\u5b8c\u6574\u6807\u51c6\u6d41\u7a0b<\/h2>\n  <ol class=\"step-list\">\n    <li>\u4e0b\u8f7d\u5b98\u65b9\u6a21\u578b\u6743\u91cd\uff0c\u6267\u884c\u91cf\u5316\u538b\u7f29\u964d\u4f4e\u663e\u5b58\u5360\u7528\uff1b<\/li>\n    <li>\u9009\u62e9\u751f\u4ea7\u7ea7\u63a8\u7406\u5f15\u64ce\uff1avLLM \/ llama.cpp \/ TGI\uff1b<\/li>\n    <li>\u914d\u7f6eKV\u7f13\u5b58\u4e0a\u9650\u3001\u6700\u5927\u5bf9\u8bdd\u4e0a\u4e0b\u6587\u7a97\u53e3\uff1b<\/li>\n    <li>\u5c01\u88c5HTTP\/GRPC\u63a5\u53e3\uff0c\u589e\u52a0\u6d41\u91cf\u9650\u6d41\u961f\u5217\uff1b<\/li>\n    <li>\u642d\u5efa\u9884\u70edGPU\u5b9e\u4f8b\u6c60\uff0c\u89e3\u51b3\u51b7\u542f\u52a8\u5ef6\u8fdf\u5cf0\u503c\uff1b<\/li>\n    <li>\u63a5\u5165\u76d1\u63a7\u9762\u677f\uff1aTTFT\u3001\u541e\u5410\u91cf\u3001\u663e\u5b58\u4f7f\u7528\u7387\uff1b<\/li>\n    <li>\u5206\u5c42\u9650\u6d41\uff0c\u6d41\u91cf\u9ad8\u5cf0\u542f\u7528\u6392\u961f\u964d\u7ea7\u7b56\u7565\uff1b<\/li>\n    <li>\u538b\u529b\u6d4b\u8bd5\u9a8c\u8bc1\u5e76\u53d1\u4e0a\u9650\uff0c\u5b8c\u6210\u4e0a\u7ebf\u53d1\u5e03\u3002<\/li>\n  <\/ol>\n\n  <h2 id=\"p10\">\u5341\u3001\u65b0\u624b\u63a8\u7406\u9ad8\u9891\u8e29\u5751\u6e05\u5355<\/h2>\n  <div class=\"info-box danger\">\n    <strong>\u57511\uff1a\u5bf9\u8bdd\u4e0a\u4e0b\u6587\u65e0\u9650\u5236\uff0c\u5f15\u53d1\u663e\u5b58OOM\u5d29\u6e83<\/strong>\n    <p>\u957f\u5bf9\u8bdd\u6301\u7eed\u7d2f\u79efKV\u7f13\u5b58\uff1b\u89e3\u51b3\uff1a\u8bbe\u7f6e\u6700\u5927\u4e0a\u4e0b\u6587\u957f\u5ea6\u3001\u6ed1\u52a8\u7a97\u53e3\u6dd8\u6c70\u7f13\u5b58\u3002<\/p>\n  <\/div>\n  <div class=\"info-box danger\">\n    <strong>\u57512\uff1a\u6e29\u5ea6\u53c2\u6570\u8bbe\u7f6e\u8fc7\u9ad8\uff0cAI\u5927\u91cf\u7f16\u9020\u5e7b\u89c9\u5185\u5bb9<\/strong>\n    <p>\u4ee3\u7801\u3001\u4e8b\u5b9e\u7c7b\u95ee\u7b54\u6e29\u5ea6\u5fc5\u987b\u63a7\u5236\u57280.3\u4ee5\u5185\u3002<\/p>\n  <\/div>\n  <div class=\"info-box warn\">\n    <strong>\u57513\uff1a\u4f7f\u7528\u9759\u6001\u6279\u5904\u7406\uff0cGPU\u5927\u91cf\u7a7a\u95f2\u7b97\u529b\u6d6a\u8d39<\/strong>\n    <p>\u66f4\u6362\u652f\u6301\u8fde\u7eed\u6279\u5904\u7406\u7684vLLM\u7b49\u63a8\u7406\u5f15\u64ce\u63d0\u5347\u5e76\u53d1\u627f\u8f7d\u3002<\/p>\n  <\/div>\n  <div class=\"info-box warn\">\n    <strong>\u57514\uff1a\u672a\u914d\u7f6e\u9884\u70ed\u6c60\uff0c\u6d41\u91cf\u9ad8\u5cf0\u5927\u91cf\u51b7\u542f\u52a8\u8d85\u65f6\u62a5\u9519<\/strong>\n    <p>\u957f\u671f\u4fdd\u7559\u9884\u52a0\u8f7d\u6a21\u578b\u7684\u5e38\u9a7b\u9884\u70ed\u5b9e\u4f8b\u3002<\/p>\n  <div class=\"info-box\">\n    <strong>\u57515\uff1a\u65e0\u663e\u5b58\u4e0e\u7f13\u5b58\u76d1\u63a7\uff0c\u9ad8\u5e76\u53d1\u4e0b\u670d\u52a1\u76f4\u63a5\u5361\u6b7b<\/strong>\n    <p>\u5b9e\u65f6\u76d1\u63a7GPU\u5185\u5b58\uff0c\u9650\u5236\u8bf7\u6c42\u961f\u5217\u957f\u5ea6\uff0c\u62e6\u622a\u8d85\u957fPrompt\u8f93\u5165\u3002\n  <\/div>\n<\/div>\n\n<!-- \u82f1\u6587\u5b8c\u6574\u5185\u5bb9\u533a\u5757\uff0c\u6392\u7248\u3001\u7ec4\u4ef6\u3001\u7ae0\u8282\u5b8c\u5168\u5bf9\u9f50\u4e2d\u6587 -->\n<div class=\"lang-block\" id=\"en-content\">\n  <div class=\"hero\">\n    <h1>LLM Inference Full Beginner Tutorial: Principles, KV Cache &#038; Production Deployment Optimization<\/h1>\n    <div class=\"desc-sub\">Distinguish training vs inference, full generation workflow, latency\/throughput\/cold start explained, local &#038; cloud deployment guide<\/div>\n  <\/div>\n\n  <div class=\"toc-box\">\n    <h3>Table of Contents<\/h3>\n    <ol>\n      <li><a href=\"#e1\">1 What Is LLM Inference? Real-life Analogy<\/a><\/li>\n      <li><a href=\"#e2\">2 Core Differences Between Inference and Training<\/a><\/li>\n      <li><a href=\"#e3\">3 Complete End-to-End Inference Pipeline<\/a><\/li>\n      <li><a href=\"#e4\">4 Two Core Stages: Prefill &#038; Decode<\/a><\/li>\n      <li><a href=\"#e5\">5 Core Acceleration: KV Cache Mechanism<\/a><\/li>\n      <li><a href=\"#e6\">6 Sampling Parameters: Creativity &#038; Fact Control<\/a><\/li>\n      <li><a href=\"#e7\">7 Key Metrics For Online Inference Service<\/a><\/li>\n      <li><a href=\"#e8\">8 Popular Inference Optimization Methods<\/a><\/li>\n      <li><a href=\"#e9\">9 Standard Production Deployment Workflow<\/a><\/li>\n      <li><a href=\"#e10\">10 Common Mistakes For New Engineers<\/a><\/li>\n    <\/ol>\n  <\/div>\n\n  <h2 id=\"e1\">1 What Is LLM Inference? Real-life Analogy<\/h2>\n  <div class=\"card\">\n    <h4>Plain Language Definition<\/h4>\n    <p><span class=\"tag-b\">LLM Inference<\/span> refers to the forward computation process where a fully pre-trained and fine-tuned model uses frozen weights to generate text token by token after receiving user prompts.<\/p>\n    <p>Simple analogy for beginners:\n    <br><span class=\"tag-g\">Training<\/span> = A student studies and practices for years, constantly updating his knowledge system (iteratively update model weights).\n    <br><span class=\"tag-y\">Inference<\/span> = After graduation, the student answers new exam questions without changing his internal knowledge (weights stay frozen permanently).\n    <\/p>\n    <p>All mainstream AI products like ChatGPT, local Ollama, code assistants and AI customer chatbots run inference logic on the backend.<\/p>\n  <\/div>\n  <div class=\"tip-box\">\n    <strong>Core Difference:<\/strong> Inference never updates model parameters. It only runs forward neural network calculation without backpropagation, consuming much less compute resources than training jobs.\n  <\/div>\n\n  <h2 id=\"e2\">2 Core Differences Between Inference and Training<\/h2>\n  <div class=\"compare-wrap\">\n    <div class=\"compare-item bad\">\n      <h4>Model Training (Pretrain \/ Fine-tune)<\/h4>\n      <ul>\n        <li>Feed massive text datasets, update weights every iteration<\/li>\n        <li>Execute forward and backward propagation together with heavy compute cost<\/li>\n        <li>Offline batch job, runs for days or weeks at a time<\/li>\n        <li>Optimizes overall data throughput, ignores single request latency<\/li>\n        <li>Requires multi-GPU cluster with high-speed interconnection<\/li>\n        <li>Huge VRAM usage for weights, gradients and optimizer buffers<\/li>\n      <\/ul>\n    <\/div>\n    <div class=\"compare-item good\">\n      <h4>Model Inference (Online \/ Local Runtime)<\/h4>\n      <ul>\n        <li>Only accepts single user prompt, all weights locked statically<\/li>\n        <li>Forward pass only, no gradient or backpropagation<\/li>\n        <li>7\u00d724 online service responding to real-time requests<\/li>\n        <li>Key targets: low TTFT, high concurrent throughput<\/li>\n        <li>Works on single GPU, supports elastic scaling up\/down<\/li>\n        <li>VRAM only occupied by model weights and KV cache buffers<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <div class=\"table-box\">\n    <table>\n      <thead>\n        <tr>\n          <th>Dimension<\/th>\n          <th>Training<\/th>\n          <th>Inference<\/th>\n        <\/tr>\n      <\/thead>\n      <tbody>\n        <tr>\n          <td>Parameter State<\/td>\n          <td>Update weights per batch<\/td>\n          <td>All weights frozen permanently<\/td>\n        <\/tr>\n        <tr>\n          <td>Calculation Flow<\/td>\n          <td>Forward + Backward Pass<\/td>\n          <td>Forward Pass Only<\/td>\n        <\/tr>\n        <tr>\n          <td>Running Mode<\/td>\n          <td>Offline Batch Task<\/td>\n          <td>Real-time Online API Service<\/td>\n        <\/tr>\n        <tr>\n          <td>Optimization Target<\/td>\n          <td>Maximize data processing speed<\/td>\n          <td>Short user waiting time &#038; support high concurrency<\/td>\n        <\/tr>\n        <tr>\n          <td>VRAM Consumption<\/td>\n          <td>Weights + Gradients + Optimizer Cache<\/td>\n          <td>Weights + KV Cache<\/td>\n        <\/tr>\n      <\/tbody>\n    <\/table>\n  <\/div>\n\n  <h2 id=\"e3\">3 Complete End-to-End Inference Pipeline<\/h2>\n<pre class=\"code\">\n# Sample user prompt\nUser Input: Write Python code to read Excel files\n<\/pre>\n  <ol class=\"step-list\">\n    <li><strong>Tokenizer<\/strong>: Split natural language into minimal tokens and map to numeric IDs;\n    <div class=\"cmd-line\">Example: write \u2192 324, code snippet \u2192 987<\/div>\n    <\/li>\n    <li><strong>Prefill Stage<\/strong>: Parallel compute all input tokens, generate first token and cache KV tensors;<\/li>\n    <li><strong>Decode Loop<\/strong>: Predict next token iteratively based on full conversation context;<\/li>\n    <li><strong>Token Sampling<\/strong>: Select proper tokens from probability distribution;<\/li>\n    <li><strong>Termination Check<\/strong>: Stop generation when EOS token or max length reached;<\/li>\n    <li><strong>Detokenization<\/strong>: Convert numeric IDs back to human-readable text for users.<\/li>\n  <\/ol>\n  <div class=\"tip-box warn\">\n    <strong>Explanation:<\/strong> The word-by-word streaming typing animation on chat UI comes from serial Decode loop which generates only one token per iteration.\n  <\/div>\n\n  <h2 id=\"e4\">4 Two Core Stages: Prefill &#038; Decode<\/h2>\n  <div class=\"cmd-grid\">\n    <div class=\"cmd-card\">\n      <h4>Prefill (Input Processing)<\/h4>\n      <div class=\"desc\">Process full prompt in parallel, compute-bound with O(n\u00b2) complexity. TTFT latency mainly comes from this phase.<\/div>\n      <div class=\"tag tag-r\">Bottleneck: GPU Compute<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>Decode (Generation Stage)<\/h4>\n      <div class=\"desc\">Generate tokens serially, VRAM bandwidth bound, reuse cached KV tensors with O(n) complexity.<\/div>\n      <div class=\"tag tag-y\">Bottleneck: VRAM Bandwidth<\/div>\n    <\/div>\n  <\/div>\n  <div class=\"card\">\n    <h4>Simple Stage Comparison<\/h4>\n    <p>Prefill: Read the whole question at once and organize context before writing answers;<\/p>\n    <p>Decode: Write text word by word and review previous content every iteration.<\/p>\n    <p>Industry optimization: Disaggregated Prefill\/Decode deployment. Separate compute-heavy and bandwidth-heavy GPUs to boost hardware utilization rate.<\/p>\n  <\/div>\n\n  <h2 id=\"e5\">5 Core Acceleration: KV Cache Mechanism<\/h2>\n  <div class=\"card\">\n    <h4>Why KV Cache Is Indispensable<\/h4>\n    <p>Without KV cache, every new token requires recalculating all historical Key &#038; Value tensors, causing massive redundant computation and extremely slow inference speed.<\/p>\n    <p><span class=\"tag-p\">KV Cache<\/span>: Store precomputed K\/V matrices in VRAM during Prefill and each Decode round. Reuse cached data directly to cut computation cost and speed up inference several times.<\/p>\n  <\/div>\n<pre class=\"code\">\n# Low efficiency workflow without KV cache\nGenerate each token \u2192 recalculate all historical KV tensors\n\n# Standard optimized KV cache workflow\n1. Compute KV for all input tokens and store in VRAM\n2. Only calculate new token KV each loop and append to cache\n<\/pre>\n  <div class=\"info-box danger\">\n    <strong>VRAM Issue:<\/strong> Longer conversation takes larger KV cache space, easily triggers OOM crash. Solutions: PagedAttention, KV quantization compression.\n  <\/div>\n\n  <h2 id=\"e6\">6 Sampling Parameters: Creativity &#038; Fact Control<\/h2>\n  <div class=\"table-box\">\n    <table>\n      <thead>\n        <tr>\n          <th>Parameter<\/th>\n          <th>Function<\/th>\n          <th>Recommended Range<\/th>\n        <\/tr>\n      <\/thead>\n      <tbody>\n        <tr>\n          <td>Temperature<\/td>\n          <td>Control output randomness; higher value brings more imaginative but unstable text<\/td>\n          <td>Code\/Math: 0.1~0.3; Writing: 0.7~1.0<\/td>\n        <\/tr>\n        <tr>\n          <td>Top-p<\/td>\n          <td>Filter tokens below cumulative probability threshold<\/td>\n          <td>0.3 ~ 0.95<\/td>\n        <\/tr>\n        <tr>\n          <td>Top-k<\/td>\n          <td>Only keep top-k tokens with highest probability<\/td>\n          <td>20 ~ 100<\/td>\n        <\/tr>\n        <tr>\n          <td>Max_tokens<\/td>\n          <td>Hard limit of output length to avoid infinite generation<\/td>\n          <td>256 \/ 1024 \/ 4096 based on business needs<\/td>\n        <\/tr>\n      <\/tbody>\n    <\/table>\n    <div class=\"tip-box\">\n      <strong>Production Rule:<\/strong> Lower temperature for code and factual QA to reduce hallucinations; raise temperature for creative writing tasks.\n    <\/div>\n  <\/div>\n\n  <h2 id=\"e7\">7 Key Metrics For Online Inference Service<\/h2>\n  <div class=\"cmd-grid\">\n    <div class=\"cmd-card\">\n      <h4>TTFT (Time To First Token)<\/h4>\n      <div class=\"desc\">Time interval from request to first token, the most critical user experience metric.<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>TPOT (Time Per Output Token)<\/h4>\n      <div class=\"desc\">Interval between generated tokens, decides streaming smoothness.<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>Throughput (TPS)<\/h4>\n      <div class=\"desc\">Total tokens processed per GPU per second, measures maximum concurrency capacity.<\/div>\n    <\/div>\n    <div class=\"cmd-card\">\n      <h4>Cache Hit Ratio<\/h4>\n      <div class=\"desc\">Context reuse percentage; higher ratio reduces compute cost and latency.<\/div>\n    <\/div>\n  <\/div>\n  <div class=\"info-box warn\">\n    <strong>Cold Start Problem:<\/strong> Idle GPU resources are released, new requests take tens of seconds to load weights. Fix: warm instance pool, streaming model loading.\n  <\/div>\n\n  <h2 id=\"e8\">8 Popular Inference Optimization Methods<\/h2>\n  <div class=\"two-col\">\n    <div class=\"compare-col good\">\n      <h4>VRAM Saving Solutions<\/h4>\n      <ul>\n        <li>Quantization: FP16 \/ INT8 \/ INT4<\/li>\n        <li>PagedAttention Paged KV Cache<\/li>\n        <li>Prefix Cache for fixed system prompts<\/li>\n        <li>GQA\/MQA to shrink KV memory size<\/li>\n      <\/ul>\n    <\/div>\n    <div class=\"compare-col good\">\n      <h4>Concurrency Scheduling<\/h4>\n      <ul>\n        <li>Continuous Dynamic Batching<\/li>\n        <li>Disaggregated Prefill &#038; Decode Service<\/li>\n        <li>Warm pool to eliminate cold start latency<\/li>\n        <li>Elastic GPU auto scaling for traffic spike<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n\n  <h2 id=\"e9\">9 Standard Production Deployment Workflow<\/h2>\n  <ol class=\"step-list\">\n    <li>Download official model weights and apply quantization to cut VRAM usage;<\/li>\n    <li>Choose production inference engine: vLLM \/ llama.cpp \/ TGI;<\/li>\n    <li>Configure KV cache limit and maximum conversation window;<\/li>\n    <li>Wrap model as HTTP\/GRPC API with rate limit queue;<\/li>\n    <li>Build warm GPU pool to resolve cold start latency spike;<\/li>\n    <li>Add real-time monitor for TTFT, throughput, VRAM usage;<\/li>\n    <li>Multi-layer traffic throttling and downgrade rules for peak hours;<\/li>\n    <li>Run pressure test and launch service online after verification.<\/li>\n  <\/ol>\n\n  <h2 id=\"e10\">10 Common Mistakes For New Engineers<\/h2>\n  <div class=\"info-box danger\">\n    <strong>Mistake 1: Unlimited conversation leads to OOM crash<\/strong>\n    <p>KV cache grows infinitely without limit. Fix: set max context length + sliding cache eviction.<\/p>\n  <\/div>\n  <div class=\"info-box danger\">\n    <strong>Mistake 2: Too high temperature causes heavy hallucination<\/strong>\n    <p>Set temperature below 0.3 for code and factual question answering.<\/p>\n  <\/div>\n  <div class=\"info-box warn\">\n    <strong>Mistake 3: Static batching wastes idle GPU compute<\/strong>\n    <p>Switch to engines supporting continuous batching like vLLM to improve concurrency.<\/p>\n  <\/div>\n  <div class=\"info-box warn\">\n    <strong>Mistake 4: No warm pool causes timeout errors during traffic peak<\/strong>\n    <p>Keep persistent warm instances preloaded with model weights.<\/p>\n  <div class=\"info-box\">\n    <strong>Mistake 5: Missing VRAM &#038; cache monitoring leads to service breakdown under high load<\/strong>\n    <p>Monitor GPU memory in real time, limit queue length and block ultra-long prompts.<\/p>\n  <\/div>\n<\/div>\n<\/main>\n<footer>\n  <p>LLM Inference Beginner Tutorial | Unified UI Component Style<\/p>\n<\/footer>\n\n<script>\nfunction switchLang(lang){\n  document.querySelectorAll('.lang-block').forEach(el=>el.classList.remove('active'));\n  document.getElementById(lang+'-content').classList.add('active');\n  document.querySelectorAll('.lang-switch button').forEach(btn=>btn.classList.remove('active'));\n  document.getElementById('btn-'+lang).classList.add('active');\n  document.documentElement.lang = lang === 'zh' ? 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