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alt=\"Qwen3.5-122B-A10B No Admin Rights\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>The <i>fastest method<\/i> for installing this model locally is by using <b>Docker<\/b>.<\/p>\n<p>Just follow the <b>guidelines<\/b> provided below.<\/p>\n<p> <\/p>\n<p><i>The client handles the setup, pulling gigabytes of data automatically.<\/i><\/p>\n<p> <\/p>\n<p>The installer will automatically analyze your hardware and <b>select the optimal configuration<\/b> for your system.<\/p>\n<table style=\"width:800px;max-width:800px;margin:0 auto 50px;border-collapse:collapse;border-radius:18px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#f4f4f5;box-shadow:0 14px 28px rgba(0,0,0,0.06);\">\n<tr>\n<td style=\"padding:45px 55px;text-align:center;font-size:19px;color:#27272a;line-height:2.3;letter-spacing:-0.01em;\">\n<div style=\"text-align: left;font-size:11px\">\n<div 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\/><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:29px;padding-left:24px;margin-left:0;\">\n<li><strong>Processor:<\/strong> Intel i7 \/ Ryzen 7 <strong>for heavy Quantized models<\/strong><\/li>\n<li><b>RAM:<\/b> high-speed <b>DDR5 memory<\/b> preferred for CPU offloading<\/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>Qwen3.5-122B-A10B is a <b>state\u2011of\u2011the\u2011art<\/b> language model featuring <b>122\u202fbillion<\/b> parameters and an <b>A10B<\/b> architecture. It leverages a massive <i>web\u2011scale training corpus<\/i> to achieve <b>exceptional<\/b> performance across a wide range of NLP tasks. The model incorporates advanced <b>attention mechanisms<\/b> and <i>multi\u2011layer decoder stacks<\/i> that enable deep contextual understanding and fluent generation. Benchmark evaluations place it among the top performers, delivering <b>record\u2011breaking<\/b> scores in reasoning, comprehension, and code synthesis. Its efficient <b>A10B<\/b> design balances computational demands with high\u2011quality output, making it suitable for both research and production environments. Ongoing fine\u2011tuning initiatives allow developers to customize the model for specialized domains while preserving its core capabilities.    <\/p>\n<table>\n<tr>\n<th><b>Parameter<\/b><\/th>\n<th><b>Value<\/b><\/th>\n<\/tr>\n<tr>\n<td><b>Model Name<\/b><\/td>\n<td>Qwen3.5-122B-A10B<\/td>\n<\/tr>\n<tr>\n<td><b>Parameters<\/b><\/td>\n<td>122\u202fB<\/td>\n<\/tr>\n<tr>\n<td><b>Architecture<\/b><\/td>\n<td>A10B<\/td>\n<\/tr>\n<tr>\n<td><b>Training Data<\/b><\/td>\n<td>Web\u2011scale corpus<\/td>\n<\/tr>\n<tr>\n<td><b>Key Features<\/b><\/td>\n<td>Advanced attention, multi\u2011layer decoder<\/td>\n<\/tr>\n<\/table>\n<ul>\n<li>Installer deploying deep semantic index tools requiring zero cloud configurations or lookups<\/li>\n<li>Setup Qwen3.5-122B-A10B Offline on PC<\/li>\n<li>Installer configuring local WebUI for Whisper-Large-V3-Turbo setups<\/li>\n<li>Qwen3.5-122B-A10B Offline on PC Zero Config Windows FREE<\/li>\n<li>Setup tool adjusting local model temperature and sampling parameters<\/li>\n<li>Install Qwen3.5-122B-A10B Locally via LM Studio 5-Minute Setup FREE<\/li>\n<li>Setup utility linking custom local LLM pipelines with federated LibreChat application nodes<\/li>\n<li>Run Qwen3.5-122B-A10B on AMD\/Nvidia GPU Direct EXE Setup FREE<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>The fastest method for installing this model locally is by using Docker. Just follow the guidelines provided below. The client handles the setup, pulling gigabytes of data automatically. The installer will automatically analyze your hardware and select the optimal configuration for your system. \ud83d\udd0d Hash-sum: 278b5b1eb08f7ad91b8bd6e862af5a65 | \ud83d\udd53 Last update: 2026-06-22 Verify Processor: Intel i7&#8230;<\/p>\n","protected":false},"author":12,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_joinchat":[],"footnotes":""},"categories":[178],"tags":[],"class_list":["post-2826","post","type-post","status-publish","format-standard","hentry","category-weights"],"_links":{"self":[{"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/posts\/2826","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/comments?post=2826"}],"version-history":[{"count":1,"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/posts\/2826\/revisions"}],"predecessor-version":[{"id":2827,"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/posts\/2826\/revisions\/2827"}],"wp:attachment":[{"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/media?parent=2826"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/categories?post=2826"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/serowax.com\/ru\/wp-json\/wp\/v2\/tags?post=2826"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}