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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<title>RunModels — Hugging Face Open API & Universal VRAM Engine</title>
<meta name="description" content="Calculate exact VRAM, System RAM, GQA KV Cache, and GPU hardware counts (H100, RTX 4090, DGX Spark) using the universal LLM memory algorithm." />
<meta name="keywords" content="VRAM calculator, LLM memory calculator, GPU sizing, Hugging Face models, GQA KV cache, quantization, H100, RTX 4090, DGX Spark, AI infrastructure" />
<meta name="author" content="RunModels" />
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<link rel="canonical" href="https://run-models.zydcode.in/" />
<meta property="og:title" content="RunModels — Hugging Face Open API & Universal VRAM Engine" />
<meta property="og:description" content="Calculate exact VRAM, System RAM, GQA KV Cache, and GPU hardware counts (H100, RTX 4090, DGX Spark) using the universal LLM memory algorithm." />
<meta property="og:type" content="website" />
<meta property="og:url" content="https://run-models.zydcode.in/" />
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<meta name="twitter:title" content="RunModels — Hugging Face Open API & Universal VRAM Engine" />
<meta name="twitter:description" content="Calculate exact VRAM, System RAM, GQA KV Cache, and GPU hardware counts (H100, RTX 4090, DGX Spark) using the universal LLM memory algorithm." />
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<script type="module" src="./js/app.js"></script>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "SoftwareApplication",
"name": "RunModels",
"url": "https://run-models.zydcode.in/",
"applicationCategory": "DeveloperApplication",
"operatingSystem": "Any",
"description": "Calculate exact VRAM, System RAM, GQA KV Cache, and GPU hardware counts (H100, RTX 4090, DGX Spark) using the universal LLM memory algorithm.",
"offers": {
"@type": "Offer",
"price": "0",
"priceCurrency": "USD"
}
}
</script>
<!-- Microsoft Clarity -->
<script type="text/javascript">
(function(c,l,a,r,i,t,y){
c[a]=c[a]||function(){(c[a].q=c[a].q||[]).push(arguments)};
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})(window, document, "clarity", "script", "xy73fg4v5u");
</script>
</head>
<body>
<!-- ==========================================
1. TOP PINK TICKER
========================================== -->
<div class="ticker-wrap ticker-wrap--pink" aria-hidden="true">
<div class="ticker-move">
<span class="ticker-item">HUGGING FACE OPEN API <i data-lucide="sparkles"></i> UNIVERSAL VRAM & RAM ENGINE <i data-lucide="asterisk"></i> RUNMODELS INFRASTRUCTURE DESK</span>
<span class="ticker-item">HUGGING FACE OPEN API <i data-lucide="sparkles"></i> UNIVERSAL VRAM & RAM ENGINE <i data-lucide="asterisk"></i> RUNMODELS INFRASTRUCTURE DESK</span>
<span class="ticker-item">HUGGING FACE OPEN API <i data-lucide="sparkles"></i> UNIVERSAL VRAM & RAM ENGINE <i data-lucide="asterisk"></i> RUNMODELS INFRASTRUCTURE DESK</span>
</div>
</div>
<!-- ==========================================
2. HERO SECTION WITH SPINNING MODEL CTA & PARALLAX
========================================== -->
<header class="hero-wrapper">
<!-- Floating Side Polaroid Cards with Parallax -->
<div class="hero-polaroid hero-polaroid--left parallax-element" data-speed="-0.15">
<div class="tape"></div>
<div class="polaroid-img">
<i data-lucide="cpu" style="width:36px;height:36px;color:#3b82f6;"></i>
<small style="font-family:var(--font-mono);font-size:0.75rem;color:#555;">HUGGING FACE API</small>
</div>
<div class="polaroid-caption">Open Model Hub</div>
</div>
<div class="hero-polaroid hero-polaroid--right parallax-element" data-speed="0.15">
<div class="tape"></div>
<div class="polaroid-img">
<i data-lucide="hard-drive" style="width:36px;height:36px;color:#ff2e93;"></i>
<small style="font-family:var(--font-mono);font-size:0.75rem;color:#555;">UNIVERSAL ENGINE</small>
</div>
<div class="polaroid-caption">GQA KV Cache Math</div>
</div>
<div class="hero-content reveal-on-scroll">
<p class="hero-eyebrow"><i data-lucide="search"></i> HUGGING FACE OPEN API & UNIVERSAL MEMORY MODEL</p>
<h1 class="hero-title-pixel">
VRAM<span class="amp">&</span><br>RAM SIZING
</h1>
<p class="hero-subtitle">
Accurate LLM memory engine: calculate model weights, GQA & MLA KV cache ($2 \cdot L \cdot H_{kv} \cdot d_{head} \cdot C \cdot B \cdot b$ / $L \cdot (d_c + d_R) \cdot C \cdot B \cdot b$), AWQ/GGUF quantization overhead, MoE active parameters, CUDA overhead, System RAM, and GPU cluster requirements.
</p>
<!-- Interactive Spinning CTA Buttons -->
<div class="hero-cta-group">
<button id="ctaSpinButton" class="hero-spin-cta" title="Click to size this target model!">
<span class="cta-spin-icon">⚡</span>
<span class="spin-text-wrapper">
<span id="ctaSpinText" class="spin-text">SIZE LLAMA 3.3 70B</span>
</span>
<i data-lucide="arrow-down-right" style="width:20px;height:20px;"></i>
</button>
<button id="ctaRandomButton" class="hero-random-cta" title="Pick a random top Hugging Face model">
<i data-lucide="dice-5" style="width:18px;height:18px;"></i>
<span>RANDOM MODEL ROLL</span>
</button>
</div>
</div>
</header>
<!-- ==========================================
3. YELLOW MARQUEE RIBBON
========================================== -->
<div class="ticker-wrap ticker-wrap--yellow">
<div class="ticker-move ticker-move--fast">
<a href="#nav" class="ticker-item text-link">✦ HF LIVE MODEL SEARCH</a>
<a href="#nav" class="ticker-item text-link">✦ UNIVERSAL VRAM MATH</a>
<a href="#nav" class="ticker-item text-link">✦ WEIGHT & KV QUANTIZATION</a>
<a href="#nav" class="ticker-item text-link">✦ GQA KV CACHE SIZING</a>
<a href="#nav" class="ticker-item text-link">✦ H100 / DGX SPARK COUNT</a>
<a href="#nav" class="ticker-item text-link">✦ HF LIVE MODEL SEARCH</a>
<a href="#nav" class="ticker-item text-link">✦ UNIVERSAL VRAM MATH</a>
<a href="#nav" class="ticker-item text-link">✦ WEIGHT & KV QUANTIZATION</a>
<a href="#nav" class="ticker-item text-link">✦ GQA KV CACHE SIZING</a>
<a href="#nav" class="ticker-item text-link">✦ H100 / DGX SPARK COUNT</a>
</div>
</div>
<!-- ==========================================
4. SKY & ROMAN COLUMNS SECTION
========================================== -->
<section class="sky-section">
<div class="sky-clouds"></div>
<!-- Greek/Roman Marble Pillars -->
<div class="roman-column roman-column--left"><div class="column-flutes"></div></div>
<div class="roman-column roman-column--right"><div class="column-flutes"></div></div>
<div class="sky-container">
<!-- Paper Note 1 -->
<article class="paper-note paper-note--tilted-left reveal-on-scroll reveal-slide-left">
<div class="tape"></div>
<h2 class="paper-note-title">
<span>Universal Memory Model</span>
<i data-lucide="calculator" style="color:#298eff;"></i>
</h2>
<div class="paper-note-body">
<div class="formula-card">
<span class="math-term math-term--vram">Total VRAM</span>
<span class="math-symbol">=</span>
<span class="math-term">Model Weights</span>
<span class="math-symbol">+</span>
<span class="math-term">KV Cache</span>
<span class="math-symbol">+</span>
<span class="math-term">CUDA Overhead</span>
</div>
<p class="formula-desc">Accurately calculates total memory requirements for vLLM, TensorRT-LLM, SGLang, and llama.cpp serving stack.</p>
</div>
</article>
<!-- Paper Note 2 -->
<article class="paper-note paper-note--tilted-right reveal-on-scroll reveal-slide-right">
<div class="tape"></div>
<h2 class="paper-note-title">
<span>GQA KV Cache & Quant</span>
<i data-lucide="layers" style="color:#ff2e93;"></i>
</h2>
<div class="paper-note-body">
Independent weight & KV cache quantization (FP16, FP8, INT4). Accounts for Grouped-Query Attention (8 KV heads in Llama 3.3) so concurrency batch scaling is 100% accurate.
</div>
</article>
<!-- Mission Card -->
<div class="mission-card reveal-on-scroll reveal-pop-in">
<div class="tape"></div>
<div class="mission-target-icon">
<i data-lucide="target" style="width:36px;height:36px;"></i>
</div>
<h2 class="mission-title">INFRASTRUCTURE MISSION</h2>
<p class="mission-desc">
Empower AI engineers, research teams, and cluster admins to precisely size GPU VRAM, System RAM, and node clusters before downloading or deploying any model from Hugging Face.
</p>
</div>
</div>
</section>
<!-- ==========================================
5. ACTION PLAN SECTION (Dark + Gold + Arches)
========================================== -->
<section class="action-section">
<div class="action-header reveal-on-scroll">
<p class="action-subtitle">THE INFRASTRUCTURE ROADMAP</p>
<h2 class="action-title-gold">ACTION PLAN</h2>
</div>
<div class="arch-grid">
<!-- Arch Card 1 -->
<a href="#nav" class="arch-card arch-card--clickable reveal-on-scroll delay-1">
<span class="arch-num">1.</span>
<h3 class="arch-title">SEARCH & SELECT</h3>
<p class="arch-desc">
Search any model ID directly via Hugging Face Open API or pick from curated top open-weights models.
</p>
</a>
<!-- Arch Card 2 -->
<a href="#nav" class="arch-card arch-card--clickable reveal-on-scroll delay-2">
<span class="arch-num">2.</span>
<h3 class="arch-title">CONFIGURE QUANT</h3>
<p class="arch-desc">
Configure weight precision (FP16, FP8, INT4) and KV cache precision independently to simulate modern serving engines.
</p>
</a>
<!-- Arch Card 3 -->
<a href="#nav" class="arch-card arch-card--clickable reveal-on-scroll delay-3">
<span class="arch-num">3.</span>
<h3 class="arch-title">GPU SIZING</h3>
<p class="arch-desc">
Get instant node hardware recommendations—from workstation RTX 4090s and H100/H200 enterprise clusters to DGX Spark nodes.
</p>
</a>
</div>
</section>
<!-- ==========================================
6. PINK STATS MARQUEE
========================================== -->
<div class="ticker-wrap ticker-wrap--pink-stats">
<div class="ticker-move">
<span class="ticker-item"><span class="ticker-badge ticker-badge--lime">HUGGING FACE OPEN API</span> DIRECT FETCH</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--yellow">UNIVERSAL MEMORY MATH</span> LIVE ENGINE</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--cyan">WEIGHT & KV QUANT</span> INDEPENDENT</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--lime">DGX SPARK READY</span> CLUSTER SIZING</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--lime">HUGGING FACE OPEN API</span> DIRECT FETCH</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--yellow">UNIVERSAL MEMORY MATH</span> LIVE ENGINE</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--cyan">WEIGHT & KV QUANT</span> INDEPENDENT</span>
<span class="ticker-item"><span class="ticker-badge ticker-badge--lime">DGX SPARK READY</span> CLUSTER SIZING</span>
</div>
</div>
<!-- ==========================================
7. BLUE GINGHAM SECTION (Interactive Desk) WITH #nav ANCHOR
========================================== -->
<section class="gingham-section" id="nav">
<div class="gingham-container" id="calculatorDesk">
<div class="calculator-desk-paper reveal-on-scroll reveal-pop-in">
<div class="tape"></div>
<div class="desk-header">
<div class="desk-stamp">
<i data-lucide="calculator"></i> VRAM & RAM INFRASTRUCTURE DESK
</div>
<p class="desk-note">Search Hugging Face models & configure weight/KV precision settings.</p>
</div>
<!-- HF Search & Preset Selector Fieldset -->
<fieldset class="desk-fieldset">
<legend class="desk-legend"><i data-lucide="search"></i> 1. Model Selection & HF API</legend>
<div class="controls-grid">
<!-- HF Search Bar -->
<div class="control-group search-control-group">
<label class="control-label" for="hfSearchInput">
<i data-lucide="search"></i> Search Hugging Face Hub
</label>
<div class="search-input-wrapper">
<input type="text" id="hfSearchInput" class="control-input" placeholder="Type HF model ID (e.g., meta-llama/Llama-3.3-70B-Instruct)..." autocomplete="off" />
<i data-lucide="search" class="search-input-icon"></i>
</div>
<div id="searchResultsDropdown" class="search-results-dropdown"></div>
</div>
<!-- Preset Selector Dropdown -->
<div class="control-group">
<label class="control-label" for="presetSelect">
<i data-lucide="list"></i> Top Popular HF Models
</label>
<select id="presetSelect" class="control-select"></select>
</div>
</div>
</fieldset>
<!-- Quantization & Context Controls Fieldset -->
<fieldset class="desk-fieldset">
<legend class="desk-legend"><i data-lucide="sliders"></i> 2. Model Precision & Context Engine</legend>
<div class="interactive-controls-row">
<!-- Weight Precision Pills -->
<div class="control-group">
<label class="control-label"><i data-lucide="sliders"></i> Model Weight Precision</label>
<div class="precision-pill-group" id="weightPrecisionGroup">
<button class="precision-pill active" data-prec="FP16">FP16</button>
<button class="precision-pill" data-prec="BF16">BF16</button>
<button class="precision-pill" data-prec="FP8">FP8</button>
<button class="precision-pill" data-prec="INT8">INT8</button>
<button class="precision-pill" data-prec="GGUF_Q8_0">GGUF Q8_0</button>
<button class="precision-pill" data-prec="GGUF_Q6_K">GGUF Q6_K</button>
<button class="precision-pill" data-prec="GGUF_Q5_K_M">GGUF Q5_K_M</button>
<button class="precision-pill" data-prec="GGUF_Q4_K_M">GGUF Q4_K_M</button>
<button class="precision-pill" data-prec="AWQ_4BIT">AWQ 4-bit</button>
<button class="precision-pill" data-prec="GPTQ_4BIT">GPTQ 4-bit</button>
<button class="precision-pill" data-prec="GGUF_Q3_K_M">GGUF Q3_K_M</button>
<button class="precision-pill" data-prec="GGUF_Q2_K">GGUF Q2_K</button>
<button class="precision-pill" data-prec="INT4">INT4</button>
</div>
</div>
<!-- KV Cache Precision Pills -->
<div class="control-group">
<label class="control-label"><i data-lucide="database"></i> KV Cache Precision</label>
<div class="precision-pill-group" id="kvPrecisionGroup">
<button class="precision-pill active" data-kvprec="FP16">FP16</button>
<button class="precision-pill" data-kvprec="BF16">BF16</button>
<button class="precision-pill" data-kvprec="FP8">FP8</button>
<button class="precision-pill" data-kvprec="INT8">INT8</button>
<button class="precision-pill" data-kvprec="INT4">INT4</button>
</div>
</div>
<!-- Context Length Slider -->
<div class="control-group">
<div class="slider-label-header">
<label class="control-label" for="contextSlider"><i data-lucide="braces"></i> Context Length</label>
<span id="contextSliderVal" class="slider-val-badge">128,000 tokens</span>
</div>
<input type="range" id="contextSlider" class="control-range" min="2048" max="131072" step="2048" value="128000" />
<div class="context-presets">
<button class="ctx-btn" data-ctx="4096">4K</button>
<button class="ctx-btn" data-ctx="8192">8K</button>
<button class="ctx-btn" data-ctx="32768">32K</button>
<button class="ctx-btn" data-ctx="65536">64K</button>
<button class="ctx-btn active" data-ctx="128000">128K</button>
<button class="ctx-btn" data-ctx="129000">129K</button>
</div>
</div>
<!-- Batch Size Select -->
<div class="control-group">
<label class="control-label" for="batchSelect"><i data-lucide="users"></i> Batch Size (Concurrent Requests)</label>
<select id="batchSelect" class="control-select">
<option value="1">1 Sequence (Single User)</option>
<option value="2">2 Sequences</option>
<option value="4" selected>4 Sequences (Standard Serve)</option>
<option value="8">8 Sequences</option>
<option value="16">16 Sequences</option>
<option value="32">32 Sequences (High Throughput)</option>
</select>
</div>
</div>
</fieldset>
<!-- Metric Outputs Fieldset -->
<fieldset class="desk-fieldset">
<legend class="desk-legend"><i data-lucide="cpu"></i> 3. Memory Metrics & Hardware Recommendation</legend>
<!-- Metric Output Cards Grid (6 Main Boxes) -->
<div class="metrics-six-grid">
<article class="metric-box reveal-on-scroll delay-1">
<i data-lucide="binary"></i>
<span class="metric-label">Parameters</span>
<strong id="paramsOut" class="metric-value">—</strong>
</article>
<article class="metric-box reveal-on-scroll delay-1">
<i data-lucide="braces"></i>
<span class="metric-label">Context Window</span>
<strong id="contextOut" class="metric-value">—</strong>
</article>
<article class="metric-box reveal-on-scroll delay-2">
<i data-lucide="database"></i>
<span class="metric-label">Weights Memory</span>
<strong id="weightsVramOut" class="metric-value">—</strong>
</article>
<article class="metric-box reveal-on-scroll delay-2">
<i data-lucide="layers"></i>
<span class="metric-label">KV Cache VRAM</span>
<strong id="kvCacheVramOut" class="metric-value">—</strong>
</article>
<article class="metric-box reveal-on-scroll delay-3">
<i data-lucide="hard-drive"></i>
<span class="metric-label">Total VRAM Required</span>
<strong id="totalVramOut" class="metric-value metric-value--highlight">—</strong>
</article>
<article class="metric-box reveal-on-scroll delay-3">
<i data-lucide="memory-stick"></i>
<span class="metric-label">System RAM Required</span>
<strong id="systemRamOut" class="metric-value">—</strong>
</article>
</div>
<!-- Hardware & GPU Accelerator Count Breakdown -->
<div class="hardware-recommendation-card reveal-on-scroll">
<div class="hw-icon-badge">
<i data-lucide="server"></i>
</div>
<div class="hw-info">
<span class="hw-eyebrow">ACCELERATOR SIZING & RECOMMENDATION</span>
<h3 id="hwGpuNameOut" class="hw-title">4× H100 80GB / 4× RTX PRO 96GB</h3>
<p id="hwNodeTypeOut" class="hw-subtitle">4-Way Enterprise Server Cluster Node</p>
</div>
<div class="hw-stats">
<div class="hw-stat-item">
<span class="hw-stat-label">H100 80GB Count</span>
<strong id="h100Out" class="hw-stat-val">4 GPUs</strong>
</div>
<div class="hw-stat-item">
<span class="hw-stat-label">DGX Spark Units</span>
<strong id="sparkUnitsOut" class="hw-stat-val">3 Units</strong>
</div>
<div class="hw-stat-item">
<span class="hw-stat-label">CUDA Overhead</span>
<strong id="overheadOut" class="hw-stat-val">~29.5 GB</strong>
</div>
</div>
</div>
</fieldset>
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<i data-lucide="table-2"></i> HUGGING FACE MODEL VRAM MATRIX
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<th>Model Name / HF Repo ID</th>
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<th>VRAM (INT4)</th>
<th>System RAM</th>
<th>Recommended Hardware</th>
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