{"id":502,"date":"2026-08-06T15:31:26","date_gmt":"2026-08-06T13:31:26","guid":{"rendered":"https:\/\/www.lukaswojcik.com\/?page_id=502"},"modified":"2026-08-06T16:36:40","modified_gmt":"2026-08-06T14:36:40","slug":"llm-ollama-vram-memory-estimator","status":"publish","type":"page","link":"https:\/\/www.lukaswojcik.com\/blog\/en\/toolbox\/llm-ollama-vram-memory-estimator\/","title":{"rendered":"LLM \/ Ollama VRAM &#038; Memory Requirement Estimator"},"content":{"rendered":"<div id=\"llm-tool-wrapper\" style=\"max-width: 100%; background: #1e293b; color: #f8fafc; padding: 28px; border-radius: 12px; font-family: system-ui, -apple-system, sans-serif; box-shadow: 0 4px 20px rgba(0,0,0,0.3); border: 1px solid #334155;\">\n<p>    <!-- Privacy Notice Banner --><\/p>\n<div style=\"display: flex; align-items: center; gap: 12px; background: rgba(56, 189, 248, 0.08); border: 1px solid rgba(56, 189, 248, 0.2); padding: 12px 16px; border-radius: 8px; margin-bottom: 24px; font-size: 0.85rem; color: #38bdf8; line-height: 1.4;\">\n        <svg style=\"width: 20px; height: 20px; flex-shrink: 0;\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" viewBox=\"0 0 24 24\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M12 15v2m-6 4h12a2 2 0 002-2v-6a2 2 0 00-2-2H6a2 2 0 00-2 2v6a2 2 0 002 2zm10-10V7a4 4 0 00-8 0v4h8z\"><\/path><\/svg><br \/>\n        <span><strong>Privacy Guarantee:<\/strong> No data entered here is stored on my server or transferred anywhere else. Everything runs 100% locally in your browser.<\/span>\n    <\/div>\n<h3 style=\"margin-top: 0; color: #38bdf8; font-size: 1.25rem; border-bottom: 1px solid #334155; padding-bottom: 12px; margin-bottom: 20px;\">LLM \/ Ollama VRAM &amp; Memory Estimator<\/h3>\n<div style=\"display: grid; grid-template-columns: repeat(auto-fit, minmax(220px, 1fr)); gap: 16px; margin-bottom: 24px;\">\n<div>\n            <label style=\"display: block; font-size: 0.85rem; color: #cbd5e1; margin-bottom: 6px;\">Model Size<\/label><br \/>\n            <select id=\"llm-size\" style=\"width: 100%; padding: 10px; background: #0f172a; border: 1px solid #475569; color: #fff; border-radius: 6px;\"><option value=\"7\">7B \/ 8B (Llama 3 \/ Mistral)<\/option><option value=\"14\" selected=\"\">13B \/ 14B (Qwen \/ Llama)<\/option><option value=\"32\">32B \/ 34B (CodeLlama)<\/option><option value=\"70\">70B \/ 72B (DeepSeek \/ Llama)<\/option><\/select>\n        <\/div>\n<div>\n            <label style=\"display: block; font-size: 0.85rem; color: #cbd5e1; margin-bottom: 6px;\">Quantization<\/label><br \/>\n            <select id=\"llm-quant\" style=\"width: 100%; padding: 10px; background: #0f172a; border: 1px solid #475569; color: #fff; border-radius: 6px;\"><option value=\"16\">FP16 (Uncompressed &#8211; Highest Quality)<\/option><option value=\"8\">Q8_0 (8-Bit Quantized)<\/option><option value=\"6\">Q6_K (6-Bit Recommended)<\/option><option value=\"4.5\" selected=\"\">Q4_K_M (4-Bit Popular Standard)<\/option><option value=\"3.5\">Q3_K_M (3-Bit High Compression)<\/option><\/select>\n        <\/div>\n<div>\n            <label style=\"display: block; font-size: 0.85rem; color: #cbd5e1; margin-bottom: 6px;\">Context Window<\/label><br \/>\n            <select id=\"llm-ctx\" style=\"width: 100%; padding: 10px; background: #0f172a; border: 1px solid #475569; color: #fff; border-radius: 6px;\"><option value=\"4\">4,096 Tokens<\/option><option value=\"8\" selected=\"\">8,192 Tokens (Standard)<\/option><option value=\"16\">16,384 Tokens<\/option><option value=\"32\">32,768 Tokens (Large)<\/option><\/select>\n        <\/div>\n<\/p><\/div>\n<p>    <!-- Output Summary --><\/p>\n<div style=\"background: #0f172a; border: 1px solid #334155; padding: 20px; border-radius: 8px; margin-bottom: 16px;\">\n<div style=\"font-size: 0.75rem; color: #94a3b8; text-transform: uppercase;\">Estimated GPU VRAM Requirement<\/div>\n<div id=\"llm-vram-text\" style=\"font-size: 2rem; color: #38bdf8; font-weight: 700; margin-top: 4px;\">0.00 GB VRAM<\/div>\n<div id=\"llm-recommendation\" style=\"font-size: 0.9rem; color: #cbd5e1; margin-top: 10px;\">Recommended GPU: 16 GB VRAM<\/div>\n<\/p><\/div>\n<div style=\"font-size: 0.8rem; color: #94a3b8; line-height: 1.5;\">\n        * Note: Includes model weights size + KV Cache overhead for the selected context window + 1.5 GB runtime CUDA overhead.\n    <\/div>\n<\/div>\n<p><script>\nfunction calcLlm() {\n    const size = parseFloat(document.getElementById('llm-size').value);\n    const bpw = parseFloat(document.getElementById('llm-quant').value);\n    const ctx = parseFloat(document.getElementById('llm-ctx').value);<\/p>\n<p>    \/\/ VRAM calculation\n    const baseVram = (size * 1000000000 * (bpw \/ 8)) \/ (1024 * 1024 * 1024);\n    const kvCache = (ctx \/ 8) * 0.4; \/\/ Approx GB per 8k context\n    const overhead = 1.5;\n    const total = baseVram + kvCache + overhead;<\/p>\n<p>    document.getElementById('llm-vram-text').innerText = total.toFixed(2) + ' GB VRAM';<\/p>\n<p>    let rec = '16 GB VRAM (e.g. RTX 4080 \/ RTX 4060 Ti 16GB)';\n    if (total <= 8) rec = '8 GB VRAM (e.g. RTX 3060 \/ 4060)';\n    else if (total <= 12) rec = '12 GB VRAM (e.g. RTX 3060 12GB \/ RTX 4070)';\n    else if (total > 16 && total <= 24) rec = '24 GB VRAM (e.g. RTX 3090 \/ RTX 4090)';\n    else if (total > 24) rec = 'Multi-GPU Setup or Apple Silicon Unified Memory (32GB \/ 64GB)';<\/p>\n<p>    document.getElementById('llm-recommendation').innerText = 'Hardware Profile: ' + rec;\n}<\/p>\n<p>document.querySelectorAll('#llm-tool-wrapper select').forEach(el => {\n    el.addEventListener('input', calcLlm);\n});\ncalcLlm();\n<\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Calculate GPU VRAM requirements and hardware recommendations for self-hosting local LLMs via Ollama, vLLM, or llama.cpp.<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":38,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-tool-base.php","meta":{"footnotes":""},"class_list":["post-502","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>LLM \/ Ollama VRAM &amp; 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