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\" alt=\"Quick Run Qwen3.6-27B-int4-AutoRound Uncensored Edition\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>Using the <b>Windows Package Manager<\/b> is the <i>quickest way<\/i> to trigger the setup.<\/p>\n<p>Make sure you implement the <b>steps<\/b> mentioned below.<\/p>\n<p> <\/p>\n<p><i>The installer automatically pulls the model (could be multiple GBs).<\/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;box-shadow:0 12px 24px rgba(0,0,0,0.05);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: 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#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:27px;padding-left:22px;margin-left:0;\">\n<li><b>Processor:<\/b> 4.0 GHz+ <b>boost clock<\/b> recommended for CPU inference<\/li>\n<li><b>RAM:<\/b> 64 GB to <b>avoid OOM crashes<\/b> on large contexts<\/li>\n<li><b>Disk Space:<\/b> 100 GB for multi-modal model vision components<\/li>\n<li><strong>GPU:<\/strong> 16 GB+ video memory <strong>highly recommended<\/strong> for exl2 \/ AWQ formats<\/li>\n<\/ul>\n<\/div>\n<\/td>\n<\/tr>\n<\/table>\n<p><b>Qwen3.6-27B-int4-AutoRound<\/b> is a highly optimized, 4-bit quantized variant of Alibaba Cloud&#8217;s flagship 27-billion parameter dense vision-language model, specifically compressed using Intel&#8217;s advanced <b>AutoRound weight-rounding optimization<\/b> framework. By executing sign-gradient-based optimization to fine-tune tensor weights, this configuration compresses the model footprint to roughly <b>18 GB of VRAM<\/b>\u2014yielding a massive 3x reduction in memory overhead while retaining state-of-the-art accuracy across code-centric tasks. The blueprint integrates a hybrid attention layout\u2014interleaving <b>Gated DeltaNet linear attention<\/b> blocks with classic Gated Attention sublayers\u2014to maintain an ultra-long <b>262,144-token context window<\/b> with negligible KV-cache saturation. Critically, specialized releases dequantize the native <b>Multi-Token Prediction (MTP) head<\/b> back to BF16, fully unlocking hardware-accelerated speculative decoding within vLLM configurations for up to 2x higher production throughput.<\/p>\n<table>\n<tr>\n<th>Specification<\/th>\n<th>Detail<\/th>\n<\/tr>\n<tr>\n<td><b>Total Parameters<\/b><\/td>\n<td>27 Billion (Dense VLM Core)<\/td>\n<\/tr>\n<tr>\n<td><b>Quantization Scheme<\/b><\/td>\n<td>INT4 W4A16 Symmetric (Group Size 128 via AutoRound)<\/td>\n<\/tr>\n<tr>\n<td><b>VRAM Requirements<\/b><\/td>\n<td>~18 GB (Runs comfortably on a single consumer RTX 3090\/4090)<\/td>\n<\/tr>\n<tr>\n<td><b>Context Window<\/b><\/td>\n<td>262,144 tokens natively (Up to 1M via YaRN scaling)<\/td>\n<\/tr>\n<tr>\n<td><b>Architecture Mix<\/b><\/td>\n<td>Hybrid Gated DeltaNet + Gated Attention Layers<\/td>\n<\/tr>\n<tr>\n<td><b>Hardware Acceleration<\/b><\/td>\n<td>vLLM Native Speculative Decoding via preserved BF16 MTP Head<\/td>\n<\/tr>\n<tr>\n<td><b>Primary Use Cases<\/b><\/td>\n<td>Flagship-Level Agentic Coding, Multi-File Repository Engineering<\/td>\n<\/tr>\n<\/table>\n<ol>\n<li>Downloader pulling high-quality voice profiles for local Fish-Speech setups<\/li>\n<li>How to Setup Qwen3.6-27B-int4-AutoRound Quantized GGUF FREE<\/li>\n<li>Script fetching optimized terminal chat clients with markdown styling<\/li>\n<li>How to Autostart Qwen3.6-27B-int4-AutoRound Locally (No Cloud) No Python Required Complete Walkthrough<\/li>\n<li>Setup utility auto-detecting AMD ROCm setups for Linux desktop AI runtimes<\/li>\n<li>Quick Run Qwen3.6-27B-int4-AutoRound Windows 11 FREE<\/li>\n<li>Script fetching optimized Phi-4-Mini-Instruct weights for low-power edge deployment<\/li>\n<li>How to Deploy Qwen3.6-27B-int4-AutoRound with Native FP4 Full Method<\/li>\n<li>Installer automating ChatRTX model library installation and indexing<\/li>\n<li>Qwen3.6-27B-int4-AutoRound Locally (No Cloud)<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Using the Windows Package Manager is the quickest way to trigger the setup. Make sure you implement the steps mentioned below. The installer automatically pulls the model (could be multiple GBs). 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