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alt=\"gemma-4-26B-A4B-it No Python Required\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>Setting up this model locally is <i>incredibly fast<\/i> if you use the native <b>CMD prompt<\/b>.<\/p>\n<p>Kindly follow the <b>on-screen instructions<\/b> below.<\/p>\n<p> <\/p>\n<p><i>Hands-free setup: the system self-downloads the heavy model files.<\/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: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 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<b>26\u2011billion parameter<\/b> architecture with optimized inference performance. It leverages an <i>attention\u2011sparse<\/i> design that reduces computational load while maintaining high fidelity in both factual and creative tasks. The model supports a <b>2048\u2011token context window<\/b> and incorporates a refined instruction\u2011tuning pipeline that improves alignment with user intent. A comparison with peer models shows superior scores in reasoning, code generation, and multilingual understanding, as summarized below.  <\/p>\n<table>\n<tr>\n<th>Metric<\/th>\n<th>Value<\/th>\n<\/tr>\n<tr>\n<td>Parameters<\/td>\n<td>26\u202fB<\/td>\n<\/tr>\n<tr>\n<td>Context Length<\/td>\n<td>2048 tokens<\/td>\n<\/tr>\n<tr>\n<td>Training Data<\/td>\n<td>Web\u2011scale multilingual corpus<\/td>\n<\/tr>\n<tr>\n<td>Inference Speed<\/td>\n<td>~120\u202ftokens\/s on GPU<\/td>\n<\/tr>\n<\/table>\n<p>  Users can integrate the model into production environments via standard APIs, benefiting from its <i>balanced trade\u2011off<\/i> between size, speed, and capability.<\/p>\n<ul>\n<li>Setup utility for loading Llama-3.3 high-context models into LM Studio<\/li>\n<li>gemma-4-26B-A4B-it on AMD\/Nvidia GPU Local Guide<\/li>\n<li>Installer configuring automated VRAM defragmentation scheduling for persistent WebUIs<\/li>\n<li>How to Deploy gemma-4-26B-A4B-it Quantized GGUF 5-Minute Setup Windows<\/li>\n<li>Setup tool configuring complex multi-modal vision pipelines inside Ollama terminal<\/li>\n<li>Setup gemma-4-26B-A4B-it No Python Required<\/li>\n<li>Script downloading custom layout analysis models for local PDF processing<\/li>\n<li>How to Run gemma-4-26B-A4B-it Windows 11 One-Click Setup Windows FREE<\/li>\n<li>Setup utility linking external NVMe drives for model storage<\/li>\n<li>gemma-4-26B-A4B-it on Your PC Zero Config FREE<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Setting up this model locally is incredibly fast if you use the native CMD prompt. Kindly follow the on-screen instructions below. Hands-free setup: the system self-downloads the heavy model files. 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