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alt=\"Full Deployment Qwen3.5-122B-A10B\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>The <i>shortest path<\/i> to running this model is by activating <b>Hyper-V features<\/b>.<\/p>\n<p>Make sure to <b>follow the instructions<\/b> below.<\/p>\n<p> <\/p>\n<p><i>The loader auto-caches the model archive (several GBs included).<\/i><\/p>\n<p> <\/p>\n<p>The setup file includes a feature that <b>instantly optimizes all configurations<\/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;box-shadow:0 16px 36px rgba(0,0,0,0.07);\">\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:#2B2B2B;font-family:'Anonymous 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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:30px;padding-left:25px;margin-left:0;\">\n<li><b>CPU:<\/b> AVX2\/AVX-512 instruction set <b>required for llama.cpp<\/b><\/li>\n<li><b>RAM:<\/b> 48 GB needed to <b>prevent memory swapping<\/b> to disk<\/li>\n<li><b>Disk Space:<\/b> 100 GB for multi-modal model vision components<\/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<h4>Unlocking the Power of Qwen3.5-122B-A10B<\/h4>\n<p>Qwen3.5-122B-A10B is a state-of-the-art language model that has revolutionized the field of Natural Language Processing (NLP). With its massive 122 billion parameters and A10B architecture, this model has achieved exceptional performance across a wide range of NLP tasks. The key to its success lies in its ability to leverage a massive web-scale training corpus, which enables it to learn from vast amounts of data and generate human-like responses. Additionally, the model&#8217;s advanced attention mechanisms and multi-layer decoder stacks allow for deep contextual understanding and fluent generation.<\/p>\n<h4>Key Features and Capabilities<\/h4>\n<ul>\n<li>Advanced attention mechanisms for improved contextual understanding<\/li>\n<li>Multi-layer decoder stacks for efficient and effective response generation<\/li>\n<li>Web-scale training corpus for comprehensive learning from vast amounts of data<\/li>\n<li>Exceptional performance across a wide range of NLP tasks, including reasoning, comprehension, and code synthesis<\/li>\n<\/ul>\n<table>\n<tr>\n<th><b>Feature<\/b><\/th>\n<th><b>Description<\/b><\/th>\n<\/tr>\n<tr>\n<td><b>Parameter Count<\/b><\/td>\n<td>122 billion parameters<\/td>\n<\/tr>\n<tr>\n<td><b>Architecture<\/b><\/td>\n<td>A10B architecture<\/td>\n<\/tr>\n<tr>\n<td><b>Training Data<\/b><\/td>\n<td>Web-scale corpus with vast amounts of data<\/td>\n<\/tr>\n<\/table>\n<h4>Customization and Fine-Tuning<\/h4>\n<p>The Qwen3.5-122B-A10B model is designed to be highly customizable, allowing developers to fine-tune the model for specialized domains while preserving its core capabilities. This enables researchers and practitioners to adapt the model to their specific needs and applications.<\/p>\n<h4>Conclusion<\/h4>\n<p>In conclusion, the Qwen3.5-122B-A10B language model is a powerful tool that has revolutionized the field of NLP. With its exceptional performance, advanced features, and customization capabilities, this model is poised to make a significant impact in a wide range of applications. Whether you&#8217;re a researcher or a practitioner, this model is definitely worth exploring further.<\/p>\n<h4>Getting Started with Qwen3.5-122B-A10B<\/h4>\n<p>To get started with the Qwen3.5-122B-A10B language model, simply download and install the pre-trained model. You can then use various tools and APIs to fine-tune the model for your specific needs. With its ease of use and flexibility, this model is perfect for researchers and practitioners looking to harness the power of AI in their work.<\/p>\n<ol>\n<li>Installer configuring automated VRAM defragmentation tools for local loops<\/li>\n<li>How to Deploy Qwen3.5-122B-A10B Uncensored Edition 5-Minute Setup<\/li>\n<li>Downloader pulling advanced upscaler model weights like SUPIR-v2 for Forge UI<\/li>\n<li>How to Setup Qwen3.5-122B-A10B No Python Required Direct EXE Setup Windows FREE<\/li>\n<li>Installer deploying local real-time text-to-speech channels via ChatTTS library nodes<\/li>\n<li>How to Run Qwen3.5-122B-A10B Locally via LM Studio Full Speed NPU Mode FREE<\/li>\n<li>Script downloading background removal masks for offline photo production pipelines layouts<\/li>\n<li>Qwen3.5-122B-A10B No Admin Rights No-Code Guide<\/li>\n<li>Script automating parallel down-streaming of sharded Hugging Face model chunks safely over networks<\/li>\n<li>How to Run Qwen3.5-122B-A10B No Python Required<\/li>\n<li>Downloader pulling lightweight specialized models for edge device testing<\/li>\n<li>Run Qwen3.5-122B-A10B Locally via Ollama 2 Full Speed NPU Mode For Beginners FREE<\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"<p>The shortest path to running this model is by activating Hyper-V features. Make sure to follow the instructions below. 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