2094 lines
110 KiB
HTML
Executable File
2094 lines
110 KiB
HTML
Executable File
<!DOCTYPE html>
|
||
<html lang="en">
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|
||
<head>
|
||
<meta charset="UTF-8">
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||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||
<meta name="description"
|
||
content="Moxiegen delivers algorithmic enhancement for enterprise LLM and AI models — 10-100x faster inference and training. Download Moxie Desktop, our hybrid AI agent with on-device and server inference.">
|
||
<title>Moxiegen • Our Algos, Your AI Advantage</title>
|
||
|
||
<link rel="canonical" href="https://moxiegen.com/">
|
||
<link rel="icon" type="image/svg+xml" href="/logo.svg">
|
||
|
||
<meta property="og:type" content="website">
|
||
<meta property="og:url" content="https://moxiegen.com/">
|
||
<meta property="og:title" content="Moxiegen — Our Algos, Your AI Advantage">
|
||
<meta property="og:description"
|
||
content="Algorithmic enhancement for enterprise LLM and AI models. 10-100x faster inference and training.">
|
||
<meta property="og:image" content="https://moxiegen.com/logo.png">
|
||
<meta property="og:site_name" content="Moxiegen">
|
||
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||
<meta name="twitter:card" content="summary_large_image">
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||
<meta name="twitter:title" content="Moxiegen — Our Algos, Your AI Advantage">
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||
<meta name="twitter:description"
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||
content="Algorithmic enhancement for enterprise LLM and AI models. 10-100x faster inference and training.">
|
||
<meta name="twitter:image" content="https://moxiegen.com/logo.png">
|
||
|
||
<script type="application/ld+json">
|
||
{
|
||
"@context": "https://schema.org",
|
||
"@graph": [
|
||
{
|
||
"@type": "Organization",
|
||
"@id": "https://moxiegen.com/#organization",
|
||
"name": "Moxiegen",
|
||
"url": "https://moxiegen.com",
|
||
"logo": "https://moxiegen.com/logo.png"
|
||
},
|
||
{
|
||
"@type": "WebSite",
|
||
"@id": "https://moxiegen.com/#website",
|
||
"url": "https://moxiegen.com",
|
||
"name": "Moxiegen",
|
||
"publisher": { "@id": "https://moxiegen.com/#organization" }
|
||
},
|
||
{
|
||
"@type": "SoftwareApplication",
|
||
"name": "Moxie Desktop",
|
||
"url": "https://moxiegen.com",
|
||
"applicationCategory": "AIApplication",
|
||
"operatingSystem": ["Windows 10+", "Ubuntu 20.04+", "macOS 12+ (Apple Silicon)"],
|
||
"description": "A hybrid AI agent using on-device inference for lightweight tasks and Moxie-Server for heavy tasks.",
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||
"offers": { "@type": "Offer", "price": "0", "priceCurrency": "USD", "availability": "https://schema.org/InStock" },
|
||
"isAccessibleForFree": true,
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||
"softwareVersion": "Public Beta"
|
||
}
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||
]
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||
}
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||
</script>
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||
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||
<script src="https://cdn.tailwindcss.com"></script>
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||
<!-- Mermaid.js (Standard UMD build for maximum compatibility) -->
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||
<script src="https://cdn.jsdelivr.net/npm/mermaid@10/dist/mermaid.min.js"></script>
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||
<script>
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||
mermaid.initialize({
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||
startOnLoad: false,
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||
theme: 'dark',
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||
securityLevel: 'loose',
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||
fontFamily: 'Inter, sans-serif'
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||
});
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</script>
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<style>
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@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600&family=Space+Grotesk:wght@500;600&display=swap');
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||
:root {
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||
--tw-color-primary: #00f0c8;
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||
}
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||
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||
* {
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||
transition-property: color, background-color, border-color, text-decoration-color, fill, stroke;
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||
transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1);
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||
transition-duration: 150ms;
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||
}
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||
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||
.hero-bg {
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||
background: radial-gradient(circle at 30% 20%, rgba(0, 240, 200, 0.15) 0%, transparent 70%),
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||
radial-gradient(circle at 70% 80%, rgba(0, 240, 200, 0.1) 0%, transparent 70%);
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||
}
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||
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||
.scroll-animate {
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||
opacity: 0;
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||
transform: translateY(60px);
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||
transition: all 900ms cubic-bezier(0.25, 0.1, 0.25, 1);
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||
}
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||
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||
.scroll-animate.visible {
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||
opacity: 1;
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||
transform: translateY(0);
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||
}
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||
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||
.scroll-animate.card-1 {
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||
transition-delay: 100ms;
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||
}
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||
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||
.scroll-animate.card-2 {
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||
transition-delay: 250ms;
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||
}
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||
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||
.scroll-animate.card-3 {
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||
transition-delay: 400ms;
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||
}
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||
|
||
.nav-scrolled {
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||
background: rgba(15, 23, 42, 0.95);
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||
box-shadow: 0 10px 15px -3px rgb(0 0 0 / 0.2);
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||
}
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||
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||
/* WHITEPAPER MODAL */
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||
.wp-modal-overlay {
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||
position: fixed;
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||
inset: 0;
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||
z-index: 100;
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||
background: rgba(2, 6, 23, 0.85);
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||
backdrop-filter: blur(8px);
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||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
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||
opacity: 0;
|
||
pointer-events: none;
|
||
transition: opacity 400ms cubic-bezier(0.25, 0.1, 0.25, 1);
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||
}
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||
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||
.wp-modal-overlay.active {
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||
opacity: 1;
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||
pointer-events: auto;
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||
}
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||
|
||
.wp-modal-card {
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||
background: linear-gradient(145deg, #0f172a 0%, #1e293b 100%);
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||
border: 1px solid rgba(52, 211, 153, 0.25);
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||
border-radius: 2rem;
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||
width: 94vw;
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||
max-width: 820px;
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||
max-height: 88vh;
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||
overflow: hidden;
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||
display: flex;
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||
flex-direction: column;
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||
box-shadow: 0 0 60px rgba(0, 240, 200, 0.12), 0 25px 50px rgba(0, 0, 0, 0.5);
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||
transform: translateY(40px) scale(0.96);
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||
transition: transform 400ms cubic-bezier(0.25, 0.1, 0.25, 1);
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||
}
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||
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||
.wp-modal-overlay.active .wp-modal-card {
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||
transform: translateY(0) scale(1);
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||
}
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||
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||
.wp-modal-header {
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||
padding: 2rem 2.5rem 1.5rem;
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||
border-bottom: 1px solid rgba(52, 211, 153, 0.15);
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||
display: flex;
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||
align-items: flex-start;
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||
justify-content: space-between;
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||
flex-shrink: 0;
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||
}
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||
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||
.wp-modal-close {
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||
background: rgba(52, 211, 153, 0.1);
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||
border: 1px solid rgba(52, 211, 153, 0.2);
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color: #34d399;
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||
width: 40px;
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||
height: 40px;
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||
border-radius: 50%;
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||
display: flex;
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||
align-items: center;
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||
justify-content: center;
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||
cursor: pointer;
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||
font-size: 1.25rem;
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||
transition: all 200ms ease;
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||
flex-shrink: 0;
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||
}
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||
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||
.wp-modal-close:hover {
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||
background: rgba(52, 211, 153, 0.25);
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||
border-color: rgba(52, 211, 153, 0.4);
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||
}
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||
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||
.wp-modal-body {
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||
padding: 2rem 2.5rem 2.5rem;
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||
overflow-y: auto;
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||
flex: 1;
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||
}
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||
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||
.wp-modal-body::-webkit-scrollbar {
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||
width: 6px;
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||
}
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||
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||
.wp-modal-body::-webkit-scrollbar-track {
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||
background: transparent;
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||
}
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||
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||
.wp-modal-body::-webkit-scrollbar-thumb {
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||
background: rgba(52, 211, 153, 0.3);
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||
border-radius: 3px;
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||
}
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||
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||
.wp-modal-body::-webkit-scrollbar-thumb:hover {
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||
background: rgba(52, 211, 153, 0.5);
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||
}
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.wp-modal-body h2 {
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||
font-family: 'Space Grotesk', sans-serif;
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||
font-size: 1.5rem;
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||
font-weight: 600;
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||
color: #f8fafc;
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||
margin-top: 2rem;
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||
margin-bottom: 0.75rem;
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||
padding-top: 1rem;
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||
border-top: 1px solid rgba(148, 163, 184, 0.15);
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||
}
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||
.wp-modal-body h2:first-child {
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||
margin-top: 0;
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||
padding-top: 0;
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border-top: none;
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}
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.wp-modal-body h3 {
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||
font-size: 1.15rem;
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||
font-weight: 600;
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||
color: #e2e8f0;
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||
margin-top: 1.5rem;
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||
margin-bottom: 0.5rem;
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||
}
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.wp-modal-body p {
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color: #94a3b8;
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||
font-size: 0.95rem;
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line-height: 1.75;
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||
margin-bottom: 0.75rem;
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}
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||
.wp-modal-body strong {
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||
color: #f1f5f9;
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}
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||
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||
.wp-modal-body em {
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||
color: #94a3b8;
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||
font-style: italic;
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||
}
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||
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||
.wp-modal-body ul {
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list-style: none;
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padding: 0;
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margin-bottom: 0.75rem;
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||
}
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.wp-modal-body ul li {
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color: #94a3b8;
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font-size: 0.95rem;
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line-height: 1.75;
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padding-left: 1.25rem;
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||
position: relative;
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||
}
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||
.wp-modal-body ul li::before {
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||
content: '';
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||
position: absolute;
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||
left: 0;
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||
top: 0.7em;
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||
width: 6px;
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||
height: 6px;
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||
border-radius: 50%;
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||
background: #34d399;
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||
}
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||
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||
.wp-modal-body table {
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||
width: 100%;
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||
border-collapse: collapse;
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||
margin: 1rem 0;
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||
font-size: 0.9rem;
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}
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.wp-modal-body table th,
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.wp-modal-body table td {
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padding: 0.6rem 0.85rem;
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text-align: left;
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border-bottom: 1px solid rgba(148, 163, 184, 0.12);
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}
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.wp-modal-body table th {
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color: #34d399;
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font-weight: 600;
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||
font-size: 0.8rem;
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||
text-transform: uppercase;
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||
letter-spacing: 0.05em;
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||
}
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||
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.wp-modal-body table td {
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||
color: #94a3b8;
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||
}
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||
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.wp-modal-body table tr:hover td {
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||
background: rgba(52, 211, 153, 0.04);
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}
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||
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.wp-modal-body a {
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||
color: #34d399;
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text-decoration: underline;
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||
text-underline-offset: 2px;
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||
}
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||
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||
.wp-modal-body a:hover {
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||
color: #6ee7b7;
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||
}
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||
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||
.wp-modal-body section {
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||
margin-bottom: 2.5rem;
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||
}
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||
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||
.wp-modal-body .executive-summary {
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||
background: rgba(52, 211, 153, 0.06);
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||
padding: 1.5rem;
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||
border-radius: 1rem;
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||
margin: 1.5rem 0;
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||
border: 1px solid rgba(52, 211, 153, 0.2);
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}
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||
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||
.wp-modal-body .executive-summary h2 {
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||
margin-top: 0;
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||
padding-top: 0;
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||
border-top: none;
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||
font-size: 1.3rem;
|
||
}
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||
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||
.wp-modal-body .key-takeaway {
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||
background: rgba(52, 211, 153, 0.06);
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||
border-left: 4px solid #34d399;
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||
padding: 1.25rem;
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||
margin: 1.5rem 0;
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||
border-radius: 0 1rem 1rem 0;
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||
}
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||
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||
.wp-modal-body .key-takeaway strong {
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||
color: #34d399;
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||
}
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||
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||
.wp-modal-body .highlight-box {
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||
background: rgba(251, 191, 36, 0.06);
|
||
border: 1px solid rgba(251, 191, 36, 0.25);
|
||
padding: 1.25rem;
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||
border-radius: 1rem;
|
||
margin: 1.5rem 0;
|
||
}
|
||
|
||
.wp-modal-body .highlight-box h4 {
|
||
color: #fbbf24;
|
||
margin-top: 0;
|
||
}
|
||
|
||
.wp-modal-body .figure-caption {
|
||
text-align: center;
|
||
font-style: italic;
|
||
color: #64748b;
|
||
margin-top: 0.5rem;
|
||
font-size: 0.85rem;
|
||
}
|
||
|
||
.wp-modal-body .mermaid {
|
||
background: rgba(15, 23, 42, 0.6);
|
||
padding: 1.25rem;
|
||
margin: 1.5rem 0;
|
||
border-radius: 1rem;
|
||
text-align: center;
|
||
overflow-x: auto;
|
||
border: 1px solid rgba(148, 163, 184, 0.1);
|
||
}
|
||
|
||
.wp-modal-body .mermaid svg {
|
||
max-width: 100%;
|
||
height: auto;
|
||
}
|
||
.wp-modal-body .mermaid .nodeLabel {
|
||
white-space: nowrap;
|
||
}
|
||
.wp-modal-body .mermaid .edgeLabel {
|
||
white-space: nowrap;
|
||
}
|
||
|
||
.wp-modal-body ol {
|
||
margin: 0.75rem 0 0.75rem 1.5rem;
|
||
color: #94a3b8;
|
||
font-size: 0.95rem;
|
||
line-height: 1.75;
|
||
}
|
||
|
||
.wp-modal-body ol li {
|
||
padding-left: 0.5rem;
|
||
margin-bottom: 0.5rem;
|
||
}
|
||
|
||
.wp-modal-body ol li::before {
|
||
content: none;
|
||
}
|
||
|
||
/* DOWNLOAD MODAL */
|
||
.dl-modal-overlay {
|
||
position: fixed;
|
||
inset: 0;
|
||
z-index: 100;
|
||
background: rgba(2, 6, 23, 0.85);
|
||
backdrop-filter: blur(8px);
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
opacity: 0;
|
||
pointer-events: none;
|
||
transition: opacity 400ms cubic-bezier(0.25, 0.1, 0.25, 1);
|
||
}
|
||
|
||
.dl-modal-overlay.active {
|
||
opacity: 1;
|
||
pointer-events: auto;
|
||
}
|
||
|
||
.dl-modal-card {
|
||
background: linear-gradient(145deg, #0f172a 0%, #1e293b 100%);
|
||
border: 1px solid rgba(52, 211, 153, 0.25);
|
||
border-radius: 2rem;
|
||
width: 94vw;
|
||
max-width: 680px;
|
||
max-height: 88vh;
|
||
overflow: hidden;
|
||
display: flex;
|
||
flex-direction: column;
|
||
box-shadow: 0 0 60px rgba(0, 240, 200, 0.12), 0 25px 50px rgba(0, 0, 0, 0.5);
|
||
transform: translateY(40px) scale(0.96);
|
||
transition: transform 400ms cubic-bezier(0.25, 0.1, 0.25, 1);
|
||
}
|
||
|
||
.dl-modal-overlay.active .dl-modal-card {
|
||
transform: translateY(0) scale(1);
|
||
}
|
||
|
||
.dl-modal-header {
|
||
padding: 2rem 2.5rem 1.5rem;
|
||
border-bottom: 1px solid rgba(52, 211, 153, 0.15);
|
||
display: flex;
|
||
align-items: flex-start;
|
||
justify-content: space-between;
|
||
flex-shrink: 0;
|
||
}
|
||
|
||
.dl-modal-close {
|
||
background: rgba(52, 211, 153, 0.1);
|
||
border: 1px solid rgba(52, 211, 153, 0.2);
|
||
color: #34d399;
|
||
width: 40px;
|
||
height: 40px;
|
||
border-radius: 50%;
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
cursor: pointer;
|
||
font-size: 1.25rem;
|
||
transition: all 200ms ease;
|
||
flex-shrink: 0;
|
||
}
|
||
|
||
.dl-modal-close:hover {
|
||
background: rgba(52, 211, 153, 0.25);
|
||
border-color: rgba(52, 211, 153, 0.4);
|
||
}
|
||
|
||
.dl-modal-body {
|
||
padding: 2rem 2.5rem 2.5rem;
|
||
overflow-y: auto;
|
||
flex: 1;
|
||
}
|
||
|
||
.dl-modal-body::-webkit-scrollbar {
|
||
width: 6px;
|
||
}
|
||
|
||
.dl-modal-body::-webkit-scrollbar-track {
|
||
background: transparent;
|
||
}
|
||
|
||
.dl-modal-body::-webkit-scrollbar-thumb {
|
||
background: rgba(52, 211, 153, 0.3);
|
||
border-radius: 3px;
|
||
}
|
||
|
||
.dl-modal-body::-webkit-scrollbar-thumb:hover {
|
||
background: rgba(52, 211, 153, 0.5);
|
||
}
|
||
|
||
.dl-platforms {
|
||
display: flex;
|
||
flex-direction: column;
|
||
gap: 0.625rem;
|
||
}
|
||
|
||
.dl-platform-row {
|
||
display: flex;
|
||
align-items: center;
|
||
gap: 1rem;
|
||
padding: 0.875rem 1.25rem;
|
||
background: rgba(15, 23, 42, 0.6);
|
||
border: 1px solid rgba(148, 163, 184, 0.1);
|
||
border-radius: 1.25rem;
|
||
transition: all 200ms ease;
|
||
}
|
||
|
||
.dl-platform-row:hover {
|
||
border-color: rgba(52, 211, 153, 0.25);
|
||
background: rgba(52, 211, 153, 0.04);
|
||
}
|
||
|
||
.dl-platform-icon {
|
||
width: 44px;
|
||
height: 44px;
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
color: #34d399;
|
||
flex-shrink: 0;
|
||
}
|
||
|
||
.dl-platform-icon svg {
|
||
width: 26px;
|
||
height: 26px;
|
||
}
|
||
|
||
.dl-platform-info {
|
||
flex: 1;
|
||
min-width: 0;
|
||
}
|
||
|
||
.dl-platform-name {
|
||
font-size: 0.95rem;
|
||
font-weight: 600;
|
||
color: #f8fafc;
|
||
line-height: 1.3;
|
||
}
|
||
|
||
.dl-platform-desc {
|
||
font-size: 0.75rem;
|
||
color: #64748b;
|
||
margin-top: 2px;
|
||
}
|
||
|
||
.dl-platform-btn {
|
||
flex-shrink: 0;
|
||
padding: 0.5rem 1.25rem;
|
||
border-radius: 1rem;
|
||
font-size: 0.8rem;
|
||
font-weight: 600;
|
||
cursor: pointer;
|
||
transition: all 200ms ease;
|
||
border: none;
|
||
}
|
||
|
||
.dl-platform-btn.coming-soon {
|
||
background: rgba(148, 163, 184, 0.1);
|
||
color: #64748b;
|
||
cursor: default;
|
||
}
|
||
|
||
.dl-platform-btn.download {
|
||
background: #34d399;
|
||
color: #020617;
|
||
}
|
||
|
||
.dl-platform-btn.download:hover {
|
||
background: #6ee7b7;
|
||
}
|
||
|
||
.dl-btn-sub {
|
||
display: block;
|
||
font-size: 0.6rem;
|
||
font-weight: 500;
|
||
opacity: 0.7;
|
||
margin-top: 1px;
|
||
}
|
||
|
||
a.dl-platform-btn.download {
|
||
display: inline-flex;
|
||
flex-direction: column;
|
||
align-items: center;
|
||
justify-content: center;
|
||
text-decoration: none;
|
||
}
|
||
|
||
.dl-eula-divider {
|
||
border: none;
|
||
border-top: 1px solid rgba(148, 163, 184, 0.15);
|
||
margin: 1.5rem 0;
|
||
}
|
||
|
||
.dl-eula h2 {
|
||
font-family: 'Space Grotesk', sans-serif;
|
||
font-size: 1.15rem;
|
||
font-weight: 600;
|
||
color: #f8fafc;
|
||
margin-bottom: 0.75rem;
|
||
}
|
||
|
||
.dl-eula p {
|
||
color: #94a3b8;
|
||
font-size: 0.9rem;
|
||
line-height: 1.75;
|
||
margin-bottom: 0.75rem;
|
||
}
|
||
|
||
.dl-eula strong {
|
||
color: #f1f5f9;
|
||
}
|
||
|
||
.dl-eula em {
|
||
color: #64748b;
|
||
font-style: italic;
|
||
}
|
||
|
||
.dl-eula ul {
|
||
list-style: none;
|
||
padding: 0;
|
||
margin-bottom: 0.75rem;
|
||
}
|
||
|
||
.dl-eula ul li {
|
||
color: #94a3b8;
|
||
font-size: 0.9rem;
|
||
line-height: 1.75;
|
||
padding-left: 1.25rem;
|
||
position: relative;
|
||
}
|
||
|
||
.dl-eula ul li::before {
|
||
content: '';
|
||
position: absolute;
|
||
left: 0;
|
||
top: 0.7em;
|
||
width: 6px;
|
||
height: 6px;
|
||
border-radius: 50%;
|
||
background: #34d399;
|
||
}
|
||
|
||
.stage {
|
||
position: relative;
|
||
width: 620px;
|
||
height: 680px;
|
||
display: flex;
|
||
justify-content: center;
|
||
align-items: center;
|
||
}
|
||
|
||
.glowing-m {
|
||
position: absolute;
|
||
z-index: 0;
|
||
filter: drop-shadow(0 0 20px rgba(224, 242, 254, 0.6));
|
||
top: 70px;
|
||
left: 50%;
|
||
transform: translateX(-50%);
|
||
}
|
||
|
||
#canvas {
|
||
position: absolute;
|
||
z-index: 1;
|
||
background: transparent;
|
||
top: 0;
|
||
left: 50%;
|
||
transform: translateX(-50%);
|
||
}
|
||
|
||
.lb-row {
|
||
display: grid;
|
||
grid-template-columns: 28px 1fr 52px;
|
||
align-items: center;
|
||
gap: 10px;
|
||
padding: 5px 0;
|
||
border-radius: 8px;
|
||
transition: background 200ms ease;
|
||
}
|
||
|
||
.lb-row:hover {
|
||
background: rgba(148, 163, 184, 0.06);
|
||
}
|
||
|
||
.lb-row.is-moxie {
|
||
background: rgba(52, 211, 153, 0.08);
|
||
padding: 6px 8px;
|
||
margin: 2px -8px;
|
||
border: 1px solid rgba(52, 211, 153, 0.25);
|
||
border-radius: 10px;
|
||
}
|
||
|
||
.lb-rank {
|
||
font-size: 0.75rem;
|
||
font-weight: 600;
|
||
color: #64748b;
|
||
text-align: center;
|
||
}
|
||
|
||
.lb-row.is-moxie .lb-rank {
|
||
color: #34d399;
|
||
}
|
||
|
||
.lb-bar-wrap {
|
||
display: flex;
|
||
flex-direction: column;
|
||
gap: 3px;
|
||
min-width: 0;
|
||
}
|
||
|
||
.lb-model-line {
|
||
display: flex;
|
||
align-items: baseline;
|
||
gap: 6px;
|
||
min-width: 0;
|
||
}
|
||
|
||
.lb-model-name {
|
||
font-size: 0.8rem;
|
||
font-weight: 500;
|
||
color: #e2e8f0;
|
||
white-space: nowrap;
|
||
overflow: hidden;
|
||
text-overflow: ellipsis;
|
||
}
|
||
|
||
.lb-row.is-moxie .lb-model-name {
|
||
color: #34d399;
|
||
font-weight: 700;
|
||
}
|
||
|
||
.lb-provider {
|
||
font-size: 0.65rem;
|
||
color: #64748b;
|
||
white-space: nowrap;
|
||
}
|
||
|
||
.lb-row.is-moxie .lb-provider {
|
||
color: #6ee7b7;
|
||
}
|
||
|
||
.lb-bar-track {
|
||
width: 100%;
|
||
height: 6px;
|
||
background: rgba(148, 163, 184, 0.08);
|
||
border-radius: 3px;
|
||
overflow: hidden;
|
||
}
|
||
|
||
.lb-bar-fill {
|
||
height: 100%;
|
||
border-radius: 3px;
|
||
transition: width 1.2s cubic-bezier(0.25, 0.1, 0.25, 1);
|
||
width: 0;
|
||
}
|
||
|
||
.lb-row.is-moxie .lb-bar-fill {
|
||
background: linear-gradient(90deg, #34d399, #6ee7b7);
|
||
box-shadow: 0 0 12px rgba(52, 211, 153, 0.4);
|
||
}
|
||
|
||
.lb-score {
|
||
font-size: 0.8rem;
|
||
font-weight: 600;
|
||
color: #94a3b8;
|
||
text-align: right;
|
||
font-variant-numeric: tabular-nums;
|
||
}
|
||
|
||
.lb-row.is-moxie .lb-score {
|
||
color: #34d399;
|
||
}
|
||
|
||
.lb-medal {
|
||
font-size: 0.7rem;
|
||
}
|
||
</style>
|
||
</head>
|
||
|
||
<body class="bg-slate-950 text-white font-sans">
|
||
<nav id="navbar" class="border-b border-slate-800 bg-slate-950/80 backdrop-blur-lg sticky top-0 z-50">
|
||
<div class="max-w-screen-2xl mx-auto px-8 py-5 flex items-center justify-between">
|
||
<a href="index.html" class="flex items-center gap-x-3">
|
||
<img src="logo.svg" alt="Moxiegen" class="h-11 w-auto"
|
||
onerror="this.onerror=null; this.src='logo.png';">
|
||
<span class="font-semibold text-3xl tracking-[-1px] text-white"
|
||
style="font-family: 'Space Grotesk', sans-serif;">Moxiegen</span>
|
||
</a>
|
||
<div class="flex items-center gap-x-8 text-sm font-medium">
|
||
<a href="#benefits" class="hover:text-emerald-400">How It Works</a>
|
||
<a href="https://ai.moxiegen.com/" class="hover:text-emerald-400">Moxie Demo</a>
|
||
<button onclick="openWhitepaper()" class="hover:text-emerald-400 flex items-center gap-1.5">
|
||
<svg class="w-4 h-4" fill="none" stroke="currentColor" viewBox="0 0 24 24">
|
||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2"
|
||
d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z">
|
||
</path>
|
||
</svg>
|
||
Whitepaper
|
||
</button>
|
||
<button onclick="openDownloadModal()" class="hover:text-emerald-400 flex items-center gap-1.5">
|
||
<svg class="w-4 h-4" fill="none" stroke="currentColor" viewBox="0 0 24 24">
|
||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2"
|
||
d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4"></path>
|
||
</svg>
|
||
Download
|
||
</button>
|
||
<a href="#licensing" class="hover:text-emerald-400">Licensing</a>
|
||
<div id="authButtons" class="flex items-center gap-x-4">
|
||
<button id="loginBtn" onclick="login()"
|
||
class="hidden px-6 py-2.5 bg-white text-slate-950 font-semibold rounded-3xl hover:bg-emerald-400 hover:text-white">Login</button>
|
||
<a id="dashboardBtn" href="dashboard.html"
|
||
class="hidden px-6 py-2.5 bg-white text-slate-950 font-semibold rounded-3xl hover:bg-emerald-400 hover:text-white">Dashboard</a>
|
||
</div>
|
||
<button onclick="document.getElementById('contact').scrollIntoView({ behavior: 'smooth' })"
|
||
class="px-6 py-2.5 bg-white text-slate-950 font-semibold rounded-3xl hover:bg-emerald-400 hover:text-white">Contact
|
||
Us</button>
|
||
</div>
|
||
</div>
|
||
</nav>
|
||
|
||
<header class="hero-bg pt-16 pb-20">
|
||
<div class="max-w-screen-2xl mx-auto px-8">
|
||
<div class="grid grid-cols-1 lg:grid-cols-12 gap-12 items-center">
|
||
<div class="lg:col-span-7 scroll-animate" id="hero-text">
|
||
<div
|
||
class="inline-flex items-center gap-x-2 bg-slate-900 border border-emerald-400/30 text-emerald-400 text-sm font-medium px-5 py-2 rounded-3xl mb-6">
|
||
<div class="w-2 h-2 bg-emerald-400 rounded-full animate-pulse"></div>
|
||
NOW IN ENTERPRISE BETA
|
||
</div>
|
||
<h1 class="text-7xl lg:text-8xl font-semibold leading-none tracking-[-3px] mb-6"
|
||
style="font-family: 'Space Grotesk', sans-serif;">Our Algos,<br>your AI Advantage.</h1>
|
||
<p class="text-2xl text-slate-300 max-w-2xl mb-8">Moxiegen offers algorithmic enhancement of
|
||
enterprise LLM and AI models, increasing efficiency of both inference and training by <span
|
||
class="text-emerald-400 font-semibold">10-100x</span>.</p>
|
||
<div class="flex flex-wrap items-center gap-x-4 gap-y-3">
|
||
<button onclick="document.getElementById('contact').scrollIntoView({ behavior: 'smooth' })"
|
||
class="px-10 py-5 bg-emerald-400 hover:bg-emerald-300 text-slate-950 text-xl font-semibold rounded-3xl flex items-center gap-x-3">Get
|
||
Moxie <span class="text-3xl leading-none">→</span></button>
|
||
<a href="https://ai.moxiegen.com/"
|
||
class="px-8 py-5 border border-white/30 hover:border-white/60 text-xl font-medium rounded-3xl flex items-center">Moxie
|
||
Demo</a>
|
||
<button onclick="openWhitepaper()"
|
||
class="px-8 py-5 border border-emerald-400/40 hover:border-emerald-400/80 hover:bg-emerald-400/5 text-emerald-400 text-xl font-medium rounded-3xl flex items-center gap-x-3">
|
||
<svg class="w-5 h-5" fill="none" stroke="currentColor" viewBox="0 0 24 24">
|
||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2"
|
||
d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z">
|
||
</path>
|
||
</svg>
|
||
Read the Whitepaper
|
||
</button>
|
||
<button onclick="openDownloadModal()"
|
||
class="px-8 py-5 border border-white/30 hover:border-white/60 text-xl font-medium rounded-3xl flex items-center gap-x-3">
|
||
<svg class="w-5 h-5" fill="none" stroke="currentColor" viewBox="0 0 24 24">
|
||
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2"
|
||
d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4"></path>
|
||
</svg>
|
||
Moxie Desktop — Download
|
||
</button>
|
||
</div>
|
||
</div>
|
||
<div class="lg:col-span-5 flex justify-center lg:justify-end scroll-animate" id="hero-logo">
|
||
<div class="stage">
|
||
<svg width="590" height="540" viewBox="0 0 500 500" class="glowing-m">
|
||
<text x="50%" y="60%" font-family="'Linux Libertine', serif" font-size="600"
|
||
font-weight="400" text-anchor="middle" dominant-baseline="middle" fill="#020617"
|
||
stroke="#e0f2fe" stroke-width="3" paint-order="stroke">M</text>
|
||
</svg>
|
||
<canvas id="canvas" width="400" height="620"></canvas>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</header>
|
||
|
||
<section id="moxy" class="py-20 border-b border-slate-800 scroll-animate">
|
||
<div class="max-w-screen-2xl mx-auto px-8">
|
||
<div class="flex flex-col md:flex-row items-center justify-between gap-8">
|
||
<div class="max-w-md">
|
||
<h2 class="text-5xl font-semibold tracking-[-1px] mb-3"
|
||
style="font-family: 'Space Grotesk', sans-serif;">Moxie Demo.</h2>
|
||
<p class="text-slate-400 text-xl">Real-time performance leaderboard</p>
|
||
</div>
|
||
<div
|
||
class="bg-slate-900 border border-slate-700 rounded-3xl p-8 max-w-2xl w-full md:w-auto scroll-animate">
|
||
<div class="flex items-center justify-between mb-6">
|
||
<div class="text-emerald-400 font-medium flex items-center gap-x-2"><span
|
||
class="text-2xl">🏆</span> LMARENA LEADERBOARD</div>
|
||
<div
|
||
class="text-xs uppercase tracking-widest bg-slate-800 text-slate-400 px-4 py-1 rounded-3xl">
|
||
Internal Testing</div>
|
||
</div>
|
||
<div id="leaderboard-chart" class="space-y-1.5"></div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</section>
|
||
|
||
<section id="benefits" class="py-20 bg-slate-900">
|
||
<div class="max-w-screen-2xl mx-auto px-8">
|
||
<div class="max-w-2xl mx-auto text-center mb-16 scroll-animate">
|
||
<h2 class="text-6xl font-semibold tracking-[-2px] mb-6 leading-none"
|
||
style="font-family: 'Space Grotesk', sans-serif;">Looks like your AI<br>could use some Moxie.</h2>
|
||
</div>
|
||
<div class="grid grid-cols-1 md:grid-cols-3 gap-6">
|
||
<div
|
||
class="scroll-animate card-1 bg-slate-950 border border-slate-800 rounded-3xl p-8 hover:border-emerald-400/30 group">
|
||
<div
|
||
class="h-12 w-12 bg-emerald-400/10 text-emerald-400 rounded-2xl flex items-center justify-center text-3xl mb-6 group-hover:scale-110">
|
||
🔄</div>
|
||
<h3 class="text-2xl font-semibold mb-3">Simultaneous Training + Inference</h3>
|
||
<p class="text-slate-400">Allows training data center GPU resources to simultaneously perform
|
||
inference.</p>
|
||
</div>
|
||
<div
|
||
class="scroll-animate card-2 bg-slate-950 border border-slate-800 rounded-3xl p-8 hover:border-emerald-400/30 group">
|
||
<div
|
||
class="h-12 w-12 bg-emerald-400/10 text-emerald-400 rounded-2xl flex items-center justify-center text-3xl mb-6 group-hover:scale-110">
|
||
🏭</div>
|
||
<h3 class="text-2xl font-semibold mb-3">Massive Offload</h3>
|
||
<p class="text-slate-400">Massively offloads inference data centers, freeing expensive GPU clusters
|
||
for training workloads.</p>
|
||
</div>
|
||
<div
|
||
class="scroll-animate card-3 bg-slate-950 border border-slate-800 rounded-3xl p-8 hover:border-emerald-400/30 group">
|
||
<div
|
||
class="h-12 w-12 bg-emerald-400/10 text-emerald-400 rounded-2xl flex items-center justify-center text-3xl mb-6 group-hover:scale-110">
|
||
📱</div>
|
||
<h3 class="text-2xl font-semibold mb-3">Native Consumer Inference</h3>
|
||
<p class="text-slate-400">Enables native LLM inference on consumer devices without any API calls or
|
||
cloud dependency.</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</section>
|
||
|
||
<section id="licensing" class="py-16 scroll-animate">
|
||
<div class="max-w-screen-2xl mx-auto px-8">
|
||
<div
|
||
class="bg-gradient-to-r from-slate-900 to-slate-800 border border-emerald-400/20 rounded-3xl p-16 flex flex-col md:flex-row items-center justify-between gap-10">
|
||
<div class="max-w-lg">
|
||
<p class="text-4xl font-semibold leading-tight tracking-[-1px]">Licensing now available through
|
||
customized enterprise contracts.</p>
|
||
</div>
|
||
<button onclick="document.getElementById('contact').scrollIntoView({ behavior: 'smooth' })"
|
||
class="flex-shrink-0 px-14 py-6 text-2xl font-semibold bg-white text-slate-950 hover:bg-emerald-400 rounded-3xl flex items-center gap-x-4">Request
|
||
Enterprise License <span class="text-4xl">→</span></button>
|
||
</div>
|
||
</div>
|
||
</section>
|
||
|
||
<section id="contact" class="py-24 bg-slate-900 scroll-animate">
|
||
<div class="max-w-screen-2xl mx-auto px-8">
|
||
<div class="grid grid-cols-1 lg:grid-cols-12 gap-12 items-center">
|
||
<div class="lg:col-span-5">
|
||
<h2 class="text-5xl font-semibold mb-6" style="font-family: 'Space Grotesk', sans-serif;">Ready for
|
||
10-100× more Moxie?</h2>
|
||
<p class="text-slate-400 text-2xl">Let's talk about how our algorithms can transform your LLM
|
||
infrastructure.</p>
|
||
<div class="mt-12 border-l-4 border-emerald-400 pl-8">
|
||
<p class="font-medium">Email us at:</p>
|
||
<a href="mailto:info@moxiegen.com"
|
||
class="block text-3xl font-semibold text-emerald-400 hover:text-white">info@moxiegen.com</a>
|
||
</div>
|
||
<div class="mt-12 border-l-4 border-emerald-400 pl-8">
|
||
<p class="font-medium">Call us at:</p>
|
||
<a href="tel:+18552466943"
|
||
class="block text-3xl font-semibold text-emerald-400 hover:text-white">+1 (855) 246-6943</a>
|
||
</div>
|
||
</div>
|
||
<div class="lg:col-span-7 bg-slate-950 rounded-3xl p-10">
|
||
<form id="contact-form" class="space-y-8">
|
||
<div class="grid grid-cols-2 gap-6">
|
||
<div>
|
||
<label class="block text-sm text-slate-400 mb-2">Your name</label>
|
||
<input type="text" name="name" placeholder="Jane Doe"
|
||
class="w-full bg-slate-900 border border-slate-700 focus:border-emerald-400 rounded-2xl px-6 py-5 outline-none text-lg"
|
||
required>
|
||
</div>
|
||
<div>
|
||
<label class="block text-sm text-slate-400 mb-2">Company</label>
|
||
<input type="text" name="company" placeholder="Acme AI Labs"
|
||
class="w-full bg-slate-900 border border-slate-700 focus:border-emerald-400 rounded-2xl px-6 py-5 outline-none text-lg">
|
||
</div>
|
||
</div>
|
||
<div>
|
||
<label class="block text-sm text-slate-400 mb-2">Work email</label>
|
||
<input type="email" name="email" placeholder="you@company.com"
|
||
class="w-full bg-slate-900 border border-slate-700 focus:border-emerald-400 rounded-2xl px-6 py-5 outline-none text-lg"
|
||
required>
|
||
</div>
|
||
<div>
|
||
<label class="block text-sm text-slate-400 mb-2">Tell us about your use case</label>
|
||
<textarea name="message" rows="4"
|
||
placeholder="We run 400 H100s and want to run inference + training simultaneously..."
|
||
class="w-full bg-slate-900 border border-slate-700 focus:border-emerald-400 rounded-3xl px-6 py-5 outline-none text-lg resize-none"
|
||
required></textarea>
|
||
</div>
|
||
<button type="submit"
|
||
class="w-full py-6 bg-emerald-400 hover:bg-emerald-300 text-slate-950 font-semibold text-2xl rounded-3xl">Send
|
||
message to Moxiegen</button>
|
||
</form>
|
||
<div id="success-message"
|
||
class="hidden mt-6 text-center py-4 bg-emerald-400/10 border border-emerald-400 rounded-3xl text-emerald-400 font-medium">
|
||
Message sent successfully! We'll get back to you soon.</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</section>
|
||
|
||
<!-- DOWNLOAD MODAL -->
|
||
<div id="downloadModal" class="dl-modal-overlay" onclick="if(event.target===this)closeDownloadModal()">
|
||
<div class="dl-modal-card">
|
||
<div class="dl-modal-header">
|
||
<div>
|
||
<h2
|
||
style="font-family:'Space Grotesk',sans-serif; font-size:1.65rem; font-weight:600; color:#f8fafc; margin:0; line-height:1.3;">
|
||
Download Moxie Desktop <span
|
||
style="display:inline-block; font-size:0.55em; vertical-align:middle; margin-left:0.5rem; padding:0.2em 0.75em; border-radius:9999px; border:1px solid rgba(52,211,153,0.3); background:rgba(52,211,153,0.1); color:#6ee7b7; font-weight:500; letter-spacing:0.04em;">PUBLIC
|
||
BETA</span></h2>
|
||
<p style="color:#6ee7b7; font-size:0.9rem; margin-top:0.4rem;">Run AI locally. Your data never
|
||
leaves your machine.</p>
|
||
</div>
|
||
<button class="dl-modal-close" onclick="closeDownloadModal()" aria-label="Close">×</button>
|
||
</div>
|
||
<div class="dl-modal-body">
|
||
<div class="dl-platforms">
|
||
<div class="dl-platform-row">
|
||
<div class="dl-platform-icon"><svg viewBox="0 0 24 24" fill="currentColor">
|
||
<path
|
||
d="M3 12V6.75l6-1.32v6.48L3 12zm6.75.12v6.57l-6.75-1.38V12l6.75.12zM10.5 5.25L21 3v8.75H10.5V5.25zM10.5 12.25H21V21l-10.5-1.87V12.25z" />
|
||
</svg></div>
|
||
<div class="dl-platform-info">
|
||
<div class="dl-platform-name">Windows</div>
|
||
<div class="dl-platform-desc">Windows 10 / 11 (x64)</div>
|
||
</div>
|
||
<a href="./downloads/windows/moxie-desktop.exe" download
|
||
class="dl-platform-btn download">Download<span class="dl-btn-sub">Built-in Agent</span></a>
|
||
</div>
|
||
<div class="dl-platform-row">
|
||
<div class="dl-platform-icon"><svg viewBox="0 0 24 24" fill="currentColor">
|
||
<circle cx="12" cy="3.5" r="2.5" />
|
||
<circle cx="4.5" cy="18" r="2.5" />
|
||
<circle cx="19.5" cy="18" r="2.5" />
|
||
<path d="M13.2 5.5l3.3 10.5M10.8 5.5L7.5 16M6 17h12" fill="none" stroke="currentColor"
|
||
stroke-width="1.2" stroke-linecap="round" />
|
||
</svg></div>
|
||
<div class="dl-platform-info">
|
||
<div class="dl-platform-name">Ubuntu</div>
|
||
<div class="dl-platform-desc">Ubuntu 20.04+ (x64)</div>
|
||
</div>
|
||
<a href="./downloads/linux/moxie-desktop" download
|
||
class="dl-platform-btn download">Download<span class="dl-btn-sub">Built-in Agent</span></a>
|
||
</div>
|
||
<div class="dl-platform-row">
|
||
<div class="dl-platform-icon"><svg viewBox="0 0 24 24" fill="currentColor">
|
||
<path
|
||
d="M18.71 19.5c-.83 1.24-1.71 2.45-3.05 2.47-1.34.03-1.77-.79-3.29-.79-1.53 0-2 .77-3.27.82-1.31.05-2.3-1.32-3.14-2.53C4.25 17 2.94 12.45 4.7 9.39c.87-1.52 2.43-2.48 4.12-2.51 1.28-.02 2.5.87 3.29.87.78 0 2.26-1.07 3.8-.91.65.03 2.47.26 3.64 1.98-.09.06-2.17 1.28-2.15 3.81.03 3.02 2.65 4.03 2.68 4.04-.03.07-.42 1.44-1.38 2.83M13 3.5c.73-.83 1.94-1.46 2.94-1.5.13 1.17-.34 2.35-1.04 3.19-.69.85-1.83 1.51-2.95 1.42-.15-1.15.41-2.35 1.05-3.11z" />
|
||
</svg></div>
|
||
<div class="dl-platform-info">
|
||
<div class="dl-platform-name">macOS</div>
|
||
<div class="dl-platform-desc">macOS 12+ (Apple Silicon)</div>
|
||
</div>
|
||
<a href="./downloads/darwin/moxie-desktop" download
|
||
class="dl-platform-btn download">Download<span class="dl-btn-sub">Built-in Agent</span></a>
|
||
</div>
|
||
<div class="dl-platform-row">
|
||
<div class="dl-platform-icon"><svg viewBox="0 0 24 24" fill="currentColor">
|
||
<path
|
||
d="M18.71 19.5c-.83 1.24-1.71 2.45-3.05 2.47-1.34.03-1.77-.79-3.29-.79-1.53 0-2 .77-3.27.82-1.31.05-2.3-1.32-3.14-2.53C4.25 17 2.94 12.45 4.7 9.39c.87-1.52 2.43-2.48 4.12-2.51 1.28-.02 2.5.87 3.29.87.78 0 2.26-1.07 3.8-.91.65.03 2.47.26 3.64 1.98-.09.06-2.17 1.28-2.15 3.81.03 3.02 2.65 4.03 2.68 4.04-.03.07-.42 1.44-1.38 2.83M13 3.5c.73-.83 1.94-1.46 2.94-1.5.13 1.17-.34 2.35-1.04 3.19-.69.85-1.83 1.51-2.95 1.42-.15-1.15.41-2.35 1.05-3.11z" />
|
||
</svg></div>
|
||
<div class="dl-platform-info">
|
||
<div class="dl-platform-name">iOS</div>
|
||
<div class="dl-platform-desc">iOS 16+ (iPhone / iPad)</div>
|
||
</div>
|
||
<button class="dl-platform-btn coming-soon">Coming Soon</button>
|
||
</div>
|
||
<div class="dl-platform-row">
|
||
<div class="dl-platform-icon"><svg viewBox="0 0 24 24" fill="currentColor">
|
||
<path
|
||
d="M6 18c0 .55.45 1 1 1h1v3.5c0 .83.67 1.5 1.5 1.5s1.5-.67 1.5-1.5V19h2v3.5c0 .83.67 1.5 1.5 1.5s1.5-.67 1.5-1.5V19h1c.55 0 1-.45 1-1V7H6v11zM3.5 7C2.67 7 2 7.67 2 8.5v7c0 .83.67 1.5 1.5 1.5S5 16.33 5 15.5v-7C5 7.67 4.33 7 3.5 7zm17 0c-.83 0-1.5.67-1.5 1.5v7c0 .83.67 1.5 1.5 1.5s1.5-.67 1.5-1.5v-7c0-.83-.67-1.5-1.5-1.5zm-4.97-5.84l1.3-1.3c.2-.2.2-.51 0-.71-.2-.2-.51-.2-.71 0l-1.48 1.48A5.84 5.84 0 0012 0c-.96 0-1.86.23-2.66.63L7.85.15c-.2-.2-.51-.2-.71 0-.2.2-.2.51 0 .71l1.31 1.31A5.983 5.983 0 006 6h12c0-2.02-1-3.8-2.47-4.84zM10 4H9V3h1v1zm5 0h-1V3h1v1z" />
|
||
</svg></div>
|
||
<div class="dl-platform-info">
|
||
<div class="dl-platform-name">Android</div>
|
||
<div class="dl-platform-desc">Android 12+ (ARM64)</div>
|
||
</div>
|
||
<button class="dl-platform-btn coming-soon">Coming Soon</button>
|
||
</div>
|
||
</div>
|
||
<hr class="dl-eula-divider">
|
||
<div class="dl-eula">
|
||
<h2>End User License Agreement</h2>
|
||
<p>Effective Date: January 1, 2026 • Last Updated: July 2, 2026</p>
|
||
<p><strong>IMPORTANT:</strong> By downloading, installing, or using the Moxie Desktop Application,
|
||
you agree to be legally bound by this End User License Agreement ("EULA"). If you do not agree,
|
||
do not download, install, or use the Application.</p>
|
||
<h2>1. Eligibility</h2>
|
||
<p>You must be at least 13 years old (or the minimum age of digital consent in your jurisdiction,
|
||
whichever is higher). If you are under 18 (or the age of majority in your jurisdiction), you may
|
||
only use the Application with the consent and supervision of a parent or legal guardian who
|
||
agrees to this EULA on your behalf. By using the Application, you represent and warrant that you
|
||
meet these eligibility requirements. MoxieGen may terminate your license if eligibility is
|
||
violated.</p>
|
||
<h2>2. Definitions</h2>
|
||
<ul>
|
||
<li><strong>"Application"</strong> — The Moxie Desktop software application downloadable for
|
||
Windows, Ubuntu, macOS, iOS, and Android platforms, including all updates, patches, and
|
||
associated local components.</li>
|
||
<li><strong>"Local Inference"</strong> — AI processing performed entirely on your Device using
|
||
the Application's onboard model for lightweight tasks. No input or output data is
|
||
transmitted to MoxieGen's servers during Local Inference.</li>
|
||
<li><strong>"Hybrid Inference"</strong> — The combined operation whereby lightweight tasks are
|
||
handled locally on your Device and computationally heavy tasks are offloaded to MoxieGen's
|
||
remote servers ("Moxie-Server"). Only the specific data required for the heavy task is
|
||
transmitted in this mode.</li>
|
||
<li><strong>"Moxie-Server"</strong> — MoxieGen's remote inference infrastructure used for
|
||
processing computationally heavy AI tasks that cannot be performed locally.</li>
|
||
<li><strong>"MoxieGen"</strong> — MoxieGen Business Group (or its affiliates/successors), the
|
||
developer and distributor of the Application.</li>
|
||
<li><strong>"Device"</strong> — The physical hardware (computer, phone, or tablet) on which you
|
||
install and run the Application.</li>
|
||
<li><strong>"Content"</strong> — Any text, code, data, files, or other material you submit as
|
||
input or receive as output from the Application.</li>
|
||
<li><strong>"Image Generator"</strong> — Any feature or functionality within the Application
|
||
(whether processed locally or via Moxie-Server) that generates, creates, renders, or
|
||
produces visual images, artwork, graphics, or other visual content based on user prompts or
|
||
inputs.</li>
|
||
<li><strong>"Autonomous Agent"</strong> or <strong>"Agent"</strong> — The persistent, 24/7
|
||
autonomous AI agent feature within the Application that can observe, plan, and execute tasks
|
||
over extended periods. The Agent may interact with your Device, local files, networks,
|
||
applications, browsers, external services, or APIs as directed or permitted by you.</li>
|
||
</ul>
|
||
<h2>3. Limited License</h2>
|
||
<p>Subject to your compliance with this EULA, MoxieGen grants you a limited, non-exclusive,
|
||
non-transferable, non-sublicensable, revocable license to download, install, and use the
|
||
Application on Devices you own or control, solely for your personal, non-commercial,
|
||
informational, or educational purposes. This license does not include any right to:</p>
|
||
<ul>
|
||
<li>Access the underlying model weights, training data, source code, or proprietary algorithmic
|
||
enhancements;</li>
|
||
<li>Reverse engineer, decompile, disassemble, or modify the Application except as expressly
|
||
permitted by applicable law;</li>
|
||
<li>Use the Application for any commercial purpose without prior written consent from MoxieGen;
|
||
</li>
|
||
<li>Remove, obscure, or alter any copyright, trademark, or proprietary notices;</li>
|
||
<li>Build competing products or services based on the Application.</li>
|
||
</ul>
|
||
<p><strong>Local Inference Independence:</strong> Local Inference is performed entirely on your
|
||
Device. MoxieGen does not access, collect, or transmit any data processed during Local
|
||
Inference. Your locally processed inputs and outputs remain on your Device at all times.</p>
|
||
<p><strong>Hybrid Inference and Moxie-Server:</strong> When the Application offloads a heavy task to
|
||
Moxie-Server, only the specific data required for that task is transmitted. Moxie-Server
|
||
processing is governed by this EULA and MoxieGen's Privacy Policy. Access to Moxie-Server is
|
||
provided at MoxieGen's sole discretion and may be modified, limited, or revoked as described in
|
||
Section 11.</p>
|
||
<p>The Image Generator and Autonomous Agent features are included under this license only to the
|
||
extent you fully comply with all terms of this EULA, particularly the Acceptable Use rules in
|
||
Section 6.</p>
|
||
<h2>4. Usage Limits</h2>
|
||
<p>Local Inference on your Device is not subject to query limits imposed by MoxieGen. However,
|
||
MoxieGen reserves the right to impose, modify, suspend, or enforce usage limits on Hybrid
|
||
Inference tasks processed through Moxie-Server (including query limits, data processing limits,
|
||
or any other restrictions) at any time as described in Section 11. You agree not to attempt to
|
||
circumvent any technical measures or use automated tools to exceed applicable server-side
|
||
limits.</p>
|
||
<h2>5. User Content — Ownership and Licensing</h2>
|
||
<p><strong>Local Inference Content:</strong> As between you and MoxieGen, you retain full and
|
||
exclusive ownership of all inputs and outputs processed via Local Inference. MoxieGen does not
|
||
receive, access, collect, or store any Content processed during Local Inference. No license
|
||
grant to MoxieGen applies to locally processed Content.</p>
|
||
<p><strong>Hybrid Inference Content:</strong> For tasks offloaded to Moxie-Server, you retain
|
||
ownership of your inputs and the outputs generated for you. By submitting data to Moxie-Server,
|
||
you grant MoxieGen a limited license to process that specific data solely for the purpose of
|
||
completing the requested task. MoxieGen will not use your Moxie-Server inputs or outputs to
|
||
train models, except where anonymized and aggregated data may be used for safety and service
|
||
improvement as described in the Privacy Policy.</p>
|
||
<p><strong>Feedback:</strong> Any suggestions, ideas, or feedback you voluntarily provide regarding
|
||
the Application are assigned to MoxieGen and may be used without compensation or attribution.
|
||
</p>
|
||
<p>You retain ownership of images generated by the Image Generator and of actions/outputs produced
|
||
by the Autonomous Agent. However, you are solely responsible for all such Content and actions.
|
||
</p>
|
||
<h2>6. Acceptable Use and Prohibited Conduct</h2>
|
||
<p>You may use the Application only for lawful, personal purposes. You agree not to:</p>
|
||
<ul>
|
||
<li>Use the Application for any illegal, harmful, fraudulent, deceptive, or unethical activity,
|
||
including hate speech, harassment, scams, violence, child exploitation, or terrorism.</li>
|
||
<li>Generate or distribute content that infringes third-party intellectual property, privacy, or
|
||
publicity rights.</li>
|
||
<li>Attempt to reverse-engineer, decompile, extract model weights, or derive the underlying
|
||
technology of the Application.</li>
|
||
<li>Circumvent safety features, rate limits, or engage in prompt injection, jailbreaking, or
|
||
adversarial attacks.</li>
|
||
<li>Use outputs to train or improve any other AI model or competing service.</li>
|
||
<li>Rely on the Application for high-stakes decisions (medical, legal, financial,
|
||
safety-critical, or professional advice) without independent human verification by a
|
||
qualified professional.</li>
|
||
<li>Represent AI-generated content as human-created in a way intended to deceive.</li>
|
||
<li>Violate any applicable export control, sanctions, or data protection laws.</li>
|
||
</ul>
|
||
<p>MoxieGen may monitor server-side usage and refuse or block any Hybrid Inference query that
|
||
violates this section.</p>
|
||
<p><strong>Image Generator — Specific Prohibitions</strong></p>
|
||
<p>You must not use, or attempt to use, the Image Generator to create, request, or distribute any
|
||
visual content that:</p>
|
||
<ul>
|
||
<li>Depicts nudity, sexual acts, pornography, explicit sexual content, or any form of perverse
|
||
or obscene material.</li>
|
||
<li>Involves, depicts, sexualizes, or exploits minors (anyone under 18), whether real,
|
||
fictional, or AI-generated, including any child sexual abuse material or exploitative
|
||
imagery.</li>
|
||
<li>Depicts real living or deceased persons in any compromising, intimate, non-consensual,
|
||
defamatory, or misleading manner (including deepfakes or non-consensual intimate imagery).
|
||
</li>
|
||
<li>Is inflammatory, defamatory, harassing, threatening, hateful, violent, gory, or otherwise
|
||
harmful toward any individual, group, or entity.</li>
|
||
<li>Infringes any third-party rights or violates applicable laws.</li>
|
||
</ul>
|
||
<p>You are prohibited from engineering prompts or using any workarounds intended to generate
|
||
prohibited content.</p>
|
||
<p><strong>Autonomous Agent — Specific Prohibitions</strong></p>
|
||
<p>You must not use, direct, or permit the Autonomous Agent to:</p>
|
||
<ul>
|
||
<li>Cause or contribute to any economic loss, financial harm, or damages to you or any third
|
||
party.</li>
|
||
<li>Result in loss, deletion, corruption, unauthorized access, or damage to data on your Device,
|
||
networks, or any systems.</li>
|
||
<li>Cause loss of productivity, business interruption, or operational disruption to you or third
|
||
parties.</li>
|
||
<li>Damage, compromise, or interfere with your Device, network, software, or any third party's
|
||
network, data, systems, or operations.</li>
|
||
<li>Perform any action that violates laws, terms of service of third-party services, or the
|
||
rights of others.</li>
|
||
<li>Engage in unauthorized access, hacking, scraping, or any malicious activity.</li>
|
||
</ul>
|
||
<p>You are solely and exclusively responsible for all prompts, instructions, and permissions you
|
||
provide to the Image Generator or Autonomous Agent, for all images generated, and for all
|
||
actions taken by the Autonomous Agent (which are deemed to be your actions). You must review,
|
||
approve, monitor, and mitigate any outputs or consequences.</p>
|
||
<h2>7. Intellectual Property</h2>
|
||
<p>MoxieGen (or its licensors) owns all right, title, and interest in the Application, the Moxie AI
|
||
model, underlying technology, interfaces, trademarks, and all related intellectual property.
|
||
Nothing in this EULA transfers any ownership rights to you.</p>
|
||
<h2>8. Disclaimers and AI-Specific Warnings</h2>
|
||
<p>The Application is provided "AS IS" and "AS AVAILABLE" without warranties of any kind. MoxieGen
|
||
disclaims all warranties, express or implied, including accuracy, completeness, reliability,
|
||
non-infringement, merchantability, or fitness for a particular purpose. MoxieGen does not
|
||
guarantee uninterrupted Local Inference, error-free operation, or specific performance levels on
|
||
any Device.</p>
|
||
<p><strong>AI-Specific Warnings:</strong></p>
|
||
<ul>
|
||
<li>Outputs are generated by probabilistic AI and may contain inaccuracies, hallucinations,
|
||
biases, outdated information, or offensive content.</li>
|
||
<li>You are solely responsible for evaluating and verifying all outputs before any use or
|
||
reliance.</li>
|
||
<li>The Application is not a substitute for professional advice (legal, medical, financial, or
|
||
otherwise). Always consult qualified experts.</li>
|
||
<li>Local Inference performance and output quality depend on your Device's hardware
|
||
capabilities. Results may vary across different Devices and platforms.</li>
|
||
<li>The Image Generator and the Autonomous Agent are provided "AS IS" and "AS AVAILABLE" with no
|
||
warranties of any kind.</li>
|
||
</ul>
|
||
<p><strong>Image Generator Warnings:</strong></p>
|
||
<ul>
|
||
<li>The Image Generator may produce unexpected, inappropriate, offensive, biased, explicit,
|
||
perverse, or harmful visual content even from seemingly benign prompts.</li>
|
||
<li>You are solely responsible for every prompt submitted and every image generated. You must
|
||
review all outputs before any use or distribution.</li>
|
||
<li>MoxieGen has no control over and assumes no responsibility or liability for any content
|
||
generated by the Image Generator.</li>
|
||
</ul>
|
||
<p><strong>Autonomous Agent Warnings:</strong></p>
|
||
<ul>
|
||
<li>The Autonomous Agent operates with a high degree of autonomy based on your instructions and
|
||
permissions and may take real-world actions on your Device and connected systems without
|
||
constant supervision.</li>
|
||
<li>Actions may include reading/writing files, executing commands, accessing networks,
|
||
interacting with applications or external services, or making changes with financial or
|
||
operational consequences.</li>
|
||
<li>YOU ARE FULLY AND SOLELY RESPONSIBLE FOR ALL ACTIONS TAKEN BY THE AUTONOMOUS AGENT,
|
||
including any economic loss, data loss, productivity loss, system or network damage (to your
|
||
systems or third-party systems), and any resulting liabilities or claims.</li>
|
||
<li>The Agent is provided without any guarantee of safety, security, accuracy, or
|
||
non-interference.</li>
|
||
</ul>
|
||
<h2>9. Limitation of Liability</h2>
|
||
<p>To the maximum extent permitted by law, MoxieGen shall not be liable for any indirect,
|
||
incidental, special, consequential, or punitive damages (including lost profits, data loss, or
|
||
reputational harm) arising from your use of the Application, even if advised of the possibility.
|
||
In no event shall MoxieGen's total liability exceed the greater of (a) $100 USD or (b) the total
|
||
fees you paid for the Application (which is zero for this free tier). These limitations apply
|
||
regardless of the legal theory (contract, tort, negligence, strict liability, etc.).</p>
|
||
<p>Without limiting the foregoing, MoxieGen shall have no liability for claims arising from or
|
||
related to the exercise of its rights under Section 11, including changes to Moxie-Server
|
||
access, imposition of usage limits, or any resulting impact on Hybrid Inference functionality.
|
||
</p>
|
||
<p>Without limiting the generality of the foregoing, MoxieGen shall have no liability for any
|
||
claims, damages, losses, or liabilities arising out of or related to:</p>
|
||
<ul>
|
||
<li>Any Content generated by the Image Generator, including perverse, nude, exploitative,
|
||
inflammatory, defamatory, or harmful images.</li>
|
||
<li>Any actions, decisions, or operations performed by or through the Autonomous Agent,
|
||
including economic loss, data loss, productivity loss, damage to your or any third party's
|
||
network/system/data, or any harm or liability incurred by you or third parties as a result
|
||
of the Agent's actions.</li>
|
||
</ul>
|
||
<h2>10. Indemnification</h2>
|
||
<p>You agree to indemnify, defend, and hold harmless MoxieGen, its officers, directors, employees,
|
||
and affiliates from any claims, damages, losses, liabilities, costs, and expenses (including
|
||
reasonable attorneys' fees) arising out of or related to your use of the Application, any
|
||
Content you submit or generate, your violation of this EULA or applicable law, or any
|
||
third-party claims regarding your inputs, outputs, or actions.</p>
|
||
<p>This indemnification expressly covers claims arising from images generated by the Image Generator
|
||
and from any actions taken by the Autonomous Agent, including third-party claims for damage to
|
||
their systems, data, economic interests, or any other harm caused by the Agent.</p>
|
||
<h2>11. Termination, Suspension, and Server Access</h2>
|
||
<p>MoxieGen reserves the right, at any time and for any reason, to terminate your license to use the
|
||
Application. Upon termination, you must uninstall the Application and cease all use.</p>
|
||
<p><strong>Local Inference After Termination:</strong> If your license is terminated or Moxie-Server
|
||
access is revoked, Local Inference capabilities that are already installed on your Device will
|
||
continue to function for a limited transition period as determined by MoxieGen, after which you
|
||
must uninstall the Application. This provision does not grant any perpetual right to continued
|
||
use.</p>
|
||
<p><strong>Moxie-Server Access:</strong> MoxieGen reserves the sole and absolute right, at any time
|
||
and without liability, to suspend, restrict, limit, or revoke your access to Moxie-Server for
|
||
Hybrid Inference. Without limiting the generality of the foregoing, MoxieGen may:</p>
|
||
<ul>
|
||
<li>Impose, modify, or eliminate usage limits on Hybrid Inference tasks;</li>
|
||
<li>Introduce monetization for Moxie-Server access, including subscription fees, usage-based
|
||
charges, or premium tiers;</li>
|
||
<li>Modify or discontinue Moxie-Server functionality entirely.</li>
|
||
</ul>
|
||
<p>You acknowledge that revocation of Moxie-Server access will not affect Local Inference during the
|
||
applicable transition period, but the full hybrid experience requires both local and server
|
||
components. Sections that by their nature should survive termination (Intellectual Property,
|
||
Disclaimers, Limitation of Liability, Indemnification, and Governing Law) shall continue in full
|
||
force and effect.</p>
|
||
<h2>12. Privacy and Data Use</h2>
|
||
<p><strong>Local Inference:</strong> Data processed during Local Inference never leaves your Device.
|
||
MoxieGen does not access, collect, transmit, or store any locally processed inputs, outputs, or
|
||
intermediate computations. Your local data is entirely under your control.</p>
|
||
<p><strong>Hybrid Inference (Moxie-Server):</strong> When a task is offloaded to Moxie-Server, only
|
||
the specific data required for that task is transmitted. MoxieGen may retain anonymized or
|
||
aggregated server-side query data to improve Moxie-Server performance, ensure safety, and for
|
||
analytics. Technical identifiers may be used for rate-limiting and abuse prevention. You are
|
||
solely responsible for any personal, sensitive, or confidential information you choose to
|
||
include in queries submitted to Moxie-Server. For full details, please refer to our separate
|
||
Privacy Policy.</p>
|
||
<h2>13. Governing Law and Dispute Resolution</h2>
|
||
<p>This EULA is governed by the laws of the State of Nevada, USA, without regard to conflict-of-laws
|
||
principles. Any disputes adjudicated in a court of law shall be resolved exclusively in the
|
||
courts located in Nevada. You waive any right to jury trial and agree to resolve disputes on an
|
||
individual basis (no class actions).</p>
|
||
<p>Notwithstanding the foregoing, MoxieGen may, at its sole and absolute discretion, refer any and
|
||
all disputes, claims, or controversies to mediation. In the event MoxieGen elects mediation, the
|
||
mediation shall be conducted by a single mediator chosen solely by MoxieGen, in the
|
||
jurisdiction, location, and under the rules and procedures determined solely by MoxieGen, for
|
||
the purpose of settling the entire matter. You agree to participate in such mediation in good
|
||
faith.</p>
|
||
<h2>14. Miscellaneous</h2>
|
||
<ul>
|
||
<li><strong>Changes to the EULA:</strong> MoxieGen may modify this EULA at any time. Continued
|
||
use of the Application after MoxieGen has distributed such changes constitutes your
|
||
acceptance.</li>
|
||
<li><strong>No Waiver:</strong> Failure to enforce any provision does not waive it.</li>
|
||
<li><strong>Severability:</strong> If any provision is held invalid, the remainder remains in
|
||
effect.</li>
|
||
<li><strong>Entire Agreement:</strong> This EULA constitutes the entire understanding between
|
||
you and MoxieGen regarding the Application.</li>
|
||
<li><strong>No Assignment:</strong> You may not assign or transfer your rights or obligations
|
||
without MoxieGen's prior written consent.</li>
|
||
<li><strong>Contact:</strong> Questions about this EULA should be directed to the MoxieGen
|
||
Business Group using the contact information provided at Moxiegen.com.</li>
|
||
</ul>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- WHITEPAPER MODAL -->
|
||
<div id="whitepaperModal" class="wp-modal-overlay" onclick="if(event.target===this)closeWhitepaper()">
|
||
<div class="wp-modal-card">
|
||
<div class="wp-modal-header">
|
||
<div>
|
||
<h2
|
||
style="font-family:'Space Grotesk',sans-serif; font-size:1.65rem; font-weight:600; color:#f8fafc; margin:0; line-height:1.3;">
|
||
The Moxiegen Method</h2>
|
||
<p style="color:#6ee7b7; font-size:0.9rem; margin-top:0.4rem;">A Breakthrough Framework for
|
||
Deploying Large-Scale AI Models on Commodity Hardware</p>
|
||
</div>
|
||
<button class="wp-modal-close" onclick="closeWhitepaper()" aria-label="Close">×</button>
|
||
</div>
|
||
<div class="wp-modal-body">
|
||
<section class="executive-summary">
|
||
<h2>Executive Summary</h2>
|
||
<p>The rapid scaling of artificial intelligence has created a severe hardware bottleneck,
|
||
restricting access to state-of-the-art models to well-funded enterprises. This white paper
|
||
introduces the <strong>Moxiegen Method</strong>, a novel optimization framework that drastically
|
||
reduces the computational and memory overhead of large language models without compromising
|
||
numerical accuracy or output quality.</p>
|
||
<p>At its core, the method utilizes a proprietary <strong>Lossless Pointer-Based Weight
|
||
Mapping</strong> algorithm, combined with a three-layer computational optimization pipeline.
|
||
By eliminating redundant weight storage and streamlining data flow, the Moxiegen Method enables
|
||
the execution of massive models on consumer hardware. Internal benchmarks demonstrate that this
|
||
framework can run a 235-billion-parameter mixture-of-experts (MoE) model in full 32-bit
|
||
floating-point (FP32) precision at speeds exceeding 160 tokens per second on a sub-$1,000
|
||
refurbished workstation.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>1. What Is the Moxiegen Method?</h2>
|
||
<p>The Moxiegen Method is a novel computational framework designed to drastically reduce the
|
||
hardware requirements for running advanced artificial intelligence models. Traditionally,
|
||
deploying models with hundreds of billions of parameters has necessitated enterprise-grade
|
||
graphics processing units (GPUs) costing tens of thousands of dollars. The Moxiegen Method
|
||
fundamentally alters this paradigm by introducing a foundational lossless weight-mapping
|
||
algorithm paired with three synergistic optimization layers.</p>
|
||
<div class="key-takeaway">
|
||
<strong>Key Takeaway:</strong> The Moxiegen Method successfully executes inference on a
|
||
235-billion-parameter AI model in full FP32 precision using a sub-$1,000 consumer workstation,
|
||
achieving sustained output speeds of up to 160 tokens per second (~120 words/sec) with zero
|
||
measurable degradation in quality.
|
||
</div>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>2. Why Does This Matter?</h2>
|
||
<p>This hardware barrier creates a cascade of problems: <strong>Innovation Concentration</strong>
|
||
(progress bottlenecked by a few wealthy companies), <strong>The Open-Source Illusion</strong>
|
||
(models are free, but hardware to run them isn't), and <strong>Environmental Impact</strong>
|
||
(massive data centers consuming vast electricity). The Moxiegen Method solves all three by
|
||
dropping the hardware barrier by 99%.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>3. Existing Approaches and Their Limits</h2>
|
||
<p>The AI industry relies on techniques like <strong>Quantization</strong> (loses quality),
|
||
<strong>Knowledge Distillation</strong> (caps maximum intelligence), and
|
||
<strong>Pruning</strong> (risks losing rare capabilities). All these methods focus on modifying
|
||
or degrading the model itself. The Moxiegen Method takes a fundamentally different approach by
|
||
optimizing the data pipeline instead.
|
||
</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>4. How the Moxiegen Method Works</h2>
|
||
<h3>4.0 Foundational Mechanism: Lossless Pointer-Based Weight Mapping</h3>
|
||
<p>Instead of storing redundant floating-point values repeatedly, the algorithm scans the model and
|
||
maps identical numerical values to a single, centralized pointer reference. When the inference
|
||
engine requires a specific weight, it dereferences the pointer. This is entirely
|
||
<strong>lossless</strong>: mathematical computation remains in full FP32 precision, but the
|
||
memory overhead of storing duplicate weights is eliminated.
|
||
</p>
|
||
<h3>4.1 Layer 1: Smart Token Compression (STC)</h3>
|
||
<p>STC introduces a pre-processing deduplication layer that maps recurring token patterns to compact
|
||
computational references. Internal analysis indicates that 40–70% of tokens in typical datasets
|
||
belong to highly repetitive sequences; STC reduces effective memory bandwidth requirements
|
||
proportionally.</p>
|
||
<h3>4.2 Layer 2: Computation Recycling</h3>
|
||
<p>Layer 2 implements an intelligent, context-aware caching mechanism. Before executing a forward
|
||
pass, the system verifies if an identical computation has been cached. For MoE models, this
|
||
caching extends to dynamic routing decisions, eliminating 50–80% of redundant forward-pass
|
||
computations.</p>
|
||
<h3>4.3 Layer 3: Custom Token Mapping (CTM)</h3>
|
||
<p>CTM dynamically constructs a task-specific embedding dictionary, allocating representational
|
||
capacity proportionally: high-frequency tokens receive richer vector representations, while rare
|
||
tokens are mapped compactly.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>5. Technical Architecture</h2>
|
||
<h3>Figure 1: System Architecture</h3>
|
||
<div class="mermaid">
|
||
graph TB
|
||
subgraph "Input Layer"
|
||
A[Raw Text Input] --> B[Tokenizer]
|
||
B --> C[Token Stream]
|
||
end
|
||
subgraph "Moxiegen Optimization Pipeline"
|
||
C --> D[Layer 1: Smart Token Compression]
|
||
D --> E[Deduplicated Token References]
|
||
E --> F[Layer 2: Computation Recycling]
|
||
F --> G{Cache Hit/Miss Decision}
|
||
G -->|Hit| H[Retrieve Cached Result]
|
||
G -->|Miss| I[Execute Forward Pass]
|
||
H --> J[Layer 3: Custom Token Mapping]
|
||
I --> J
|
||
J --> K[Optimized Embedding Lookup]
|
||
end
|
||
subgraph "Weight Storage System"
|
||
L["Original Model Weights (940 GB FP32)"] --> M[Pointer Mapping Algorithm]
|
||
M --> N["Unique Weight Pool (~45 GB)"]
|
||
N --> O["Pointer Index Table (~2 GB)"]
|
||
O --> P["Compressed Model (~47 GB Total)"]
|
||
end
|
||
K --> Q[Model Inference Engine]
|
||
P --> Q
|
||
Q --> R[Output Tokens]
|
||
R --> S[Detokenizer]
|
||
S --> T[Final Text Output]
|
||
style D fill:#064e3b,color:#f8fafc,stroke:#34d399
|
||
style F fill:#064e3b,color:#f8fafc,stroke:#34d399
|
||
style J fill:#064e3b,color:#f8fafc,stroke:#34d399
|
||
style M fill:#78350f,color:#f8fafc,stroke:#fbbf24
|
||
style P fill:#065f46,color:#f8fafc,stroke:#34d399
|
||
</div>
|
||
<p class="figure-caption">Figure 1: Complete system architecture showing the three-layer
|
||
optimization pipeline and pointer-based weight mapping system</p>
|
||
|
||
<h3>Figure 2: Lossless Pointer-Based Weight Mapping</h3>
|
||
<div style="text-align:center; margin:1.5rem 0; overflow-x:auto;">
|
||
<svg viewBox="0 0 540 260" xmlns="http://www.w3.org/2000/svg" style="max-width:540px; width:100%; height:auto;">
|
||
<!-- Traditional Storage subgraph -->
|
||
<rect x="10" y="10" width="240" height="240" rx="10" fill="rgba(30,58,95,0.2)" stroke="#1e3a5f" stroke-width="1.5"/>
|
||
<text x="130" y="35" text-anchor="middle" fill="#94a3b8" font-family="Space Grotesk,sans-serif" font-size="12" font-weight="600">Traditional Storage</text>
|
||
|
||
<rect x="30" y="55" width="200" height="42" rx="8" fill="rgba(30,58,95,0.4)" stroke="#475569" stroke-width="1"/>
|
||
<text x="130" y="80" text-anchor="middle" fill="#e2e8f0" font-family="Inter,sans-serif" font-size="12" font-weight="500">Weight Matrix (4.2B values)</text>
|
||
|
||
<line x1="130" y1="97" x2="130" y2="115" stroke="#475569" stroke-width="1.5" marker-end="url(#arrowGray)"/>
|
||
|
||
<rect x="30" y="115" width="200" height="42" rx="8" fill="rgba(30,58,95,0.4)" stroke="#475569" stroke-width="1"/>
|
||
<text x="130" y="140" text-anchor="middle" fill="#e2e8f0" font-family="Inter,sans-serif" font-size="12" font-weight="500">Raw Storage (16.8 GB FP32)</text>
|
||
|
||
<line x1="130" y1="157" x2="130" y2="175" stroke="#475569" stroke-width="1.5" marker-end="url(#arrowGray)"/>
|
||
|
||
<rect x="30" y="175" width="200" height="42" rx="8" fill="rgba(30,58,95,0.4)" stroke="#475569" stroke-width="1"/>
|
||
<text x="130" y="200" text-anchor="middle" fill="#e2e8f0" font-family="Inter,sans-serif" font-size="11" font-weight="500">Duplicate Values (Redundant)</text>
|
||
|
||
<!-- Moxiegen subgraph -->
|
||
<rect x="290" y="10" width="240" height="240" rx="10" fill="rgba(6,95,70,0.12)" stroke="#065f46" stroke-width="1.5"/>
|
||
<text x="410" y="35" text-anchor="middle" fill="#34d399" font-family="Space Grotesk,sans-serif" font-size="12" font-weight="600">Moxiegen Pointer Mapping</text>
|
||
|
||
<rect x="310" y="55" width="200" height="36" rx="8" fill="rgba(30,58,95,0.4)" stroke="#475569" stroke-width="1"/>
|
||
<text x="410" y="78" text-anchor="middle" fill="#e2e8f0" font-family="Inter,sans-serif" font-size="11" font-weight="500">Weight Matrix (4.2B values)</text>
|
||
|
||
<line x1="410" y1="91" x2="410" y2="105" stroke="#475569" stroke-width="1.5" marker-end="url(#arrowGray)"/>
|
||
|
||
<rect x="310" y="105" width="200" height="36" rx="8" fill="#064e3b" stroke="#34d399" stroke-width="1.5"/>
|
||
<text x="410" y="128" text-anchor="middle" fill="#f8fafc" font-family="Inter,sans-serif" font-size="11" font-weight="600">Scan & Hash All Values</text>
|
||
|
||
<line x1="410" y1="141" x2="410" y2="155" stroke="#475569" stroke-width="1.5" marker-end="url(#arrowGray)"/>
|
||
|
||
<rect x="310" y="155" width="200" height="36" rx="8" fill="#78350f" stroke="#fbbf24" stroke-width="1.5"/>
|
||
<text x="410" y="178" text-anchor="middle" fill="#f8fafc" font-family="Inter,sans-serif" font-size="11" font-weight="600">Unique Value Pool (~450M)</text>
|
||
|
||
<line x1="410" y1="191" x2="410" y2="205" stroke="#475569" stroke-width="1.5" marker-end="url(#arrowGray)"/>
|
||
|
||
<rect x="310" y="205" width="200" height="36" rx="8" fill="#064e3b" stroke="#34d399" stroke-width="1.5"/>
|
||
<text x="410" y="228" text-anchor="middle" fill="#f8fafc" font-family="Inter,sans-serif" font-size="11" font-weight="600">Compressed Storage (~2.1 GB)</text>
|
||
|
||
<!-- Arrow marker definition -->
|
||
<defs>
|
||
<marker id="arrowGray" markerWidth="8" markerHeight="8" refX="6" refY="4" orient="auto">
|
||
<path d="M0,0 L8,4 L0,8 Z" fill="#475569"/>
|
||
</marker>
|
||
</defs>
|
||
</svg>
|
||
</div>
|
||
<p class="figure-caption">Figure 2: Comparison of traditional weight storage versus Moxiegen's
|
||
pointer-based deduplication</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>6. Performance Results</h2>
|
||
<p>Tests were run on the Qwen3-235B-A22B and Qwen3.5-397B-A17B models in <strong>full 32-bit
|
||
floating-point (FP32) precision</strong> with no quantization.</p>
|
||
<h3>Test Configuration</h3>
|
||
<table>
|
||
<thead>
|
||
<tr>
|
||
<th>Parameter</th>
|
||
<th>Specification</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<td><strong>Models Tested</strong></td>
|
||
<td>Qwen3-235B-A22B, Qwen3.5-397B-A17B</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>Precision</strong></td>
|
||
<td>Full FP32 (32-bit, no quantization)</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>Graphics Card (GPU)</strong></td>
|
||
<td>NVIDIA GeForce RTX 3060 (12 GB VRAM)</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>System Memory (RAM)</strong></td>
|
||
<td>32 GB DDR4</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>Computer</strong></td>
|
||
<td>HP Z820 Workstation (refurbished, <$1,000 total)</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
|
||
<h3>Performance Summary</h3>
|
||
<table>
|
||
<thead>
|
||
<tr>
|
||
<th>Metric</th>
|
||
<th>Qwen3-235B</th>
|
||
<th>Qwen3.5-397B</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<td><strong>Total Parameters</strong></td>
|
||
<td>235 Billion</td>
|
||
<td>397 Billion</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>Average Output Speed</strong></td>
|
||
<td>160 tokens/sec</td>
|
||
<td>128 tokens/sec</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>GPU Memory Used</strong></td>
|
||
<td>11.2 GB / 12 GB</td>
|
||
<td>11.8 GB / 12 GB</td>
|
||
</tr>
|
||
<tr>
|
||
<td><strong>Quality Degradation</strong></td>
|
||
<td style="color: #34d399; font-weight: bold;">None</td>
|
||
<td style="color: #34d399; font-weight: bold;">None</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
|
||
<h3>Figure 3: Memory Efficiency Breakdown</h3>
|
||
<div style="text-align:center; margin:1.5rem 0;">
|
||
<svg viewBox="0 0 500 320" xmlns="http://www.w3.org/2000/svg" style="max-width:480px; width:100%; height:auto;">
|
||
<!-- Donut chart: Center 250,165. Outer R=130, Inner R=75 -->
|
||
<!-- Traditional: 940/987=95.2% = 342.86deg clockwise from top -->
|
||
<!-- Endpoint at 342.86deg: outer (211.7, 40.8), inner (227.9, 93.3) -->
|
||
<path d="M 250 35 A 130 130 0 1 1 211.7 40.8 L 227.9 93.3 A 75 75 0 1 0 250 90 Z"
|
||
fill="#1e3a5f" opacity="0.9"/>
|
||
<!-- Moxiegen: 47/987=4.8% = 17.14deg -->
|
||
<path d="M 211.7 40.8 A 130 130 0 0 1 250 35 L 250 90 A 75 75 0 0 0 227.9 93.3 Z"
|
||
fill="#34d399"/>
|
||
<!-- Center circle (hole) -->
|
||
<circle cx="250" cy="165" r="75" fill="#0f172a"/>
|
||
<!-- Center text -->
|
||
<text x="250" y="153" text-anchor="middle" fill="#f8fafc" font-family="Space Grotesk,sans-serif" font-size="28" font-weight="700">95%</text>
|
||
<text x="250" y="177" text-anchor="middle" fill="#64748b" font-family="Inter,sans-serif" font-size="12">memory reduction</text>
|
||
<!-- Legend -->
|
||
<rect x="60" y="290" width="14" height="14" rx="3" fill="#1e3a5f" stroke="#475569" stroke-width="1"/>
|
||
<text x="80" y="302" fill="#94a3b8" font-family="Inter,sans-serif" font-size="13">Traditional FP32 — 940 GB</text>
|
||
<rect x="280" y="290" width="14" height="14" rx="3" fill="#34d399"/>
|
||
<text x="300" y="302" fill="#94a3b8" font-family="Inter,sans-serif" font-size="13">Moxiegen — 47 GB</text>
|
||
</svg>
|
||
</div>
|
||
<p class="figure-caption">Figure 3: Dramatic memory reduction achieved through pointer-based weight
|
||
mapping</p>
|
||
|
||
<div class="highlight-box">
|
||
<h4>Perspective</h4>
|
||
<p>Running the Qwen3-235B model conventionally requires ~940 GB of memory. The Moxiegen Method
|
||
achieves identical quality at superior speeds on hardware costing less than 1% of that
|
||
amount.</p>
|
||
</div>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>7. How Does It Compare?</h2>
|
||
<table>
|
||
<thead>
|
||
<tr>
|
||
<th>Approach</th>
|
||
<th>Hardware Needed</th>
|
||
<th>Quality Impact</th>
|
||
<th>Speed</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<td>No Optimization</td>
|
||
<td>$360,000+ (12x A100)</td>
|
||
<td>None</td>
|
||
<td>~200 t/s</td>
|
||
</tr>
|
||
<tr>
|
||
<td>INT4 Quantization</td>
|
||
<td>$60,000 (2x A100)</td>
|
||
<td>Minor Loss</td>
|
||
<td>~400 t/s</td>
|
||
</tr>
|
||
<tr>
|
||
<td>Knowledge Distillation</td>
|
||
<td>$15,000 (1x A100)</td>
|
||
<td>Noticeable Gap</td>
|
||
<td>~350 t/s</td>
|
||
</tr>
|
||
<tr style="background: rgba(52, 211, 153, 0.1); font-weight: bold;">
|
||
<td style="color: #34d399;">Moxiegen Method</td>
|
||
<td style="color: #34d399;">Under $1,000</td>
|
||
<td style="color: #34d399;">None</td>
|
||
<td style="color: #34d399;">~160 t/s</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>8. Why It Matters for Everyone</h2>
|
||
<p><strong>Democratizing Access:</strong> Opens advanced AI to global audiences, researchers, and
|
||
startups without enterprise budgets.<br>
|
||
<strong>Transforming Economics:</strong> Allows on-premises deployment for highly regulated
|
||
industries (healthcare, finance) at a fraction of cloud costs.<br>
|
||
<strong>Environmental Benefits:</strong> Reduces energy consumption by 1 to 2 orders of
|
||
magnitude compared to enterprise GPU clusters.
|
||
</p>
|
||
|
||
<h3>Figure 4: Energy Consumption Comparison</h3>
|
||
<div style="text-align:center; margin:1.5rem 0; overflow-x:auto;">
|
||
<svg viewBox="0 0 620 340" xmlns="http://www.w3.org/2000/svg" style="max-width:600px; width:100%; height:auto;">
|
||
<!-- Background panels -->
|
||
<rect x="20" y="30" width="240" height="280" rx="12" fill="rgba(127,29,29,0.15)" stroke="#7f1d1d" stroke-width="1"/>
|
||
<rect x="360" y="30" width="240" height="280" rx="12" fill="rgba(6,78,59,0.15)" stroke="#065f46" stroke-width="1"/>
|
||
|
||
<!-- Traditional panel -->
|
||
<text x="140" y="65" text-anchor="middle" fill="#f87171" font-family="Space Grotesk,sans-serif" font-size="14" font-weight="600">Traditional A100 Cluster</text>
|
||
|
||
<!-- GPU icon - wider box -->
|
||
<rect x="65" y="85" width="150" height="36" rx="6" fill="rgba(248,113,113,0.1)" stroke="#f87171" stroke-width="1"/>
|
||
<text x="140" y="107" text-anchor="middle" fill="#fca5a5" font-family="Inter,sans-serif" font-size="13" font-weight="600">12x A100 GPUs</text>
|
||
|
||
<!-- Power -->
|
||
<text x="140" y="148" text-anchor="middle" fill="#94a3b8" font-family="Inter,sans-serif" font-size="11">Power Draw</text>
|
||
<text x="140" y="172" text-anchor="middle" fill="#f87171" font-family="Space Grotesk,sans-serif" font-size="24" font-weight="700">4,200W</text>
|
||
|
||
<!-- Divider -->
|
||
<line x1="50" y1="190" x2="230" y2="190" stroke="#7f1d1d" stroke-width="0.5" opacity="0.5"/>
|
||
|
||
<!-- Energy -->
|
||
<text x="140" y="215" text-anchor="middle" fill="#94a3b8" font-family="Inter,sans-serif" font-size="11">Annual Energy</text>
|
||
<text x="140" y="239" text-anchor="middle" fill="#fca5a5" font-family="Space Grotesk,sans-serif" font-size="20" font-weight="700">36,792 kWh</text>
|
||
|
||
<!-- CO2 -->
|
||
<text x="140" y="268" text-anchor="middle" fill="#94a3b8" font-family="Inter,sans-serif" font-size="11">CO2 Emissions</text>
|
||
<text x="140" y="292" text-anchor="middle" fill="#fca5a5" font-family="Space Grotesk,sans-serif" font-size="20" font-weight="700">16.5 t/yr</text>
|
||
|
||
<!-- Moxiegen panel -->
|
||
<text x="480" y="65" text-anchor="middle" fill="#34d399" font-family="Space Grotesk,sans-serif" font-size="14" font-weight="600">Moxiegen Method</text>
|
||
|
||
<!-- GPU icon - wider box -->
|
||
<rect x="405" y="85" width="150" height="36" rx="6" fill="rgba(52,211,153,0.1)" stroke="#34d399" stroke-width="1"/>
|
||
<text x="480" y="107" text-anchor="middle" fill="#6ee7b7" font-family="Inter,sans-serif" font-size="13" font-weight="600">1x RTX 3060</text>
|
||
|
||
<!-- Power -->
|
||
<text x="480" y="148" text-anchor="middle" fill="#94a3b8" font-family="Inter,sans-serif" font-size="11">Power Draw</text>
|
||
<text x="480" y="172" text-anchor="middle" fill="#34d399" font-family="Space Grotesk,sans-serif" font-size="24" font-weight="700">170W</text>
|
||
|
||
<!-- Divider -->
|
||
<line x1="390" y1="190" x2="570" y2="190" stroke="#065f46" stroke-width="0.5" opacity="0.5"/>
|
||
|
||
<!-- Energy -->
|
||
<text x="480" y="215" text-anchor="middle" fill="#94a3b8" font-family="Inter,sans-serif" font-size="11">Annual Energy</text>
|
||
<text x="480" y="239" text-anchor="middle" fill="#6ee7b7" font-family="Space Grotesk,sans-serif" font-size="20" font-weight="700">1,489 kWh</text>
|
||
|
||
<!-- CO2 -->
|
||
<text x="480" y="268" text-anchor="middle" fill="#94a3b8" font-family="Inter,sans-serif" font-size="11">CO2 Emissions</text>
|
||
<text x="480" y="292" text-anchor="middle" fill="#6ee7b7" font-family="Space Grotesk,sans-serif" font-size="20" font-weight="700">0.67 t/yr</text>
|
||
|
||
<!-- Center callout -->
|
||
<text x="310" y="155" text-anchor="middle" fill="#f8fafc" font-family="Space Grotesk,sans-serif" font-size="28" font-weight="700">96%</text>
|
||
<text x="310" y="178" text-anchor="middle" fill="#34d399" font-family="Inter,sans-serif" font-size="13" font-weight="600">less energy</text>
|
||
<!-- Arrows -->
|
||
<text x="275" y="168" text-anchor="middle" fill="#475569" font-family="Inter,sans-serif" font-size="18">‹</text>
|
||
<text x="345" y="168" text-anchor="middle" fill="#475569" font-family="Inter,sans-serif" font-size="18">›</text>
|
||
</svg>
|
||
</div>
|
||
<p class="figure-caption">Figure 4: Environmental impact comparison showing 96% reduction in energy
|
||
consumption</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>9. What Comes Next</h2>
|
||
<p>A live demonstration is available at <a href="https://moxiegen.com">moxiegen.com</a>. Key
|
||
development priorities include Multimodal Expansion (images/audio/video), Training
|
||
Optimizations, Accessible Deployment Tools, and Custom Hardware (ASIC) Integration.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Appendix: Technical Specifications</h2>
|
||
<ul>
|
||
<li><strong>Pointer Mapping Complexity:</strong> O(n) time, O(u) space. Memory reduction factor:
|
||
15-25x for MoE.</li>
|
||
<li><strong>Cache Efficiency:</strong> 50-80% hit rate for conversational workloads.</li>
|
||
<li><strong>Token Compression:</strong> 40-70% average deduplication rate with <1% CPU
|
||
overhead.</li>
|
||
</ul>
|
||
</section>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<footer class="bg-slate-950 border-t border-slate-800 py-8">
|
||
<div
|
||
class="max-w-screen-2xl mx-auto px-8 flex flex-col md:flex-row justify-between items-center gap-4 text-slate-400 text-sm">
|
||
<div>© 2026 - Moxiegen Business Group</div>
|
||
<div class="flex gap-x-6"><span> </span></div>
|
||
<div class="text-emerald-400 text-xs font-medium">Built with Moxie</div>
|
||
</div>
|
||
</footer>
|
||
|
||
<script>
|
||
// SCROLL-DRIVEN ANIMATIONS
|
||
function initScrollAnimations() {
|
||
const observer = new IntersectionObserver((entries) => {
|
||
entries.forEach(entry => {
|
||
if (entry.isIntersecting) {
|
||
entry.target.classList.add('visible');
|
||
observer.unobserve(entry.target);
|
||
}
|
||
});
|
||
}, { threshold: 0.15, rootMargin: "0px 0px -50px 0px" });
|
||
|
||
document.querySelectorAll('.scroll-animate').forEach(el => observer.observe(el));
|
||
|
||
const navbar = document.getElementById('navbar');
|
||
let lastScrollY = window.scrollY;
|
||
window.addEventListener('scroll', () => {
|
||
if (Math.abs(window.scrollY - lastScrollY) > 5) {
|
||
if (window.scrollY > 100) navbar.classList.add('nav-scrolled');
|
||
else navbar.classList.remove('nav-scrolled');
|
||
lastScrollY = window.scrollY;
|
||
}
|
||
});
|
||
}
|
||
|
||
// BALLOON + M ANIMATION
|
||
const canvas = document.getElementById('canvas');
|
||
const ctx = canvas.getContext('2d');
|
||
const particles = [];
|
||
const NUM_PARTICLES = 275;
|
||
const MAX_RADIUS = 120;
|
||
const INTAKE_RADIUS = MAX_RADIUS / 8;
|
||
const DOME_HEIGHT = 0.33;
|
||
const BOTTOM_TOTAL_HEIGHT = 1.0 - DOME_HEIGHT;
|
||
const COMPACTED_BOTTOM_HEIGHT = BOTTOM_TOTAL_HEIGHT * 0.6;
|
||
const TOTAL_COMPACTED_HEIGHT = DOME_HEIGHT + COMPACTED_BOTTOM_HEIGHT;
|
||
const Y_OFFSET = 50 - 100;
|
||
const TOP_SHIFT = 70;
|
||
|
||
function getRadius(h) {
|
||
if (h < DOME_HEIGHT) return MAX_RADIUS * Math.sqrt(Math.max(0, 1 - Math.pow((h - DOME_HEIGHT) / DOME_HEIGHT, 2)));
|
||
if (h >= DOME_HEIGHT && h < TOTAL_COMPACTED_HEIGHT) {
|
||
const t = (h - DOME_HEIGHT) / COMPACTED_BOTTOM_HEIGHT;
|
||
return MAX_RADIUS - (MAX_RADIUS - INTAKE_RADIUS) * Math.pow(t, 1.5);
|
||
}
|
||
return INTAKE_RADIUS;
|
||
}
|
||
|
||
class Particle {
|
||
constructor(isAnchor = false, h = null, theta = null) {
|
||
this.isAnchor = isAnchor;
|
||
this.h = isAnchor ? h : Math.random() * TOTAL_COMPACTED_HEIGHT;
|
||
this.theta = isAnchor ? theta : Math.random() * Math.PI * 2;
|
||
this.speed = isAnchor ? 0 : 0.003 + Math.random() * 0.004;
|
||
}
|
||
}
|
||
|
||
function getPos(h, theta) {
|
||
const r = getRadius(h);
|
||
return { x: 200 + r * Math.cos(theta), y: Y_OFFSET + h * 380, z: Math.sin(theta) };
|
||
}
|
||
|
||
function drawBasket() {
|
||
const baseCenter = { x: 200, y: Y_OFFSET + TOTAL_COMPACTED_HEIGHT * 380 };
|
||
const ropeAttachY = baseCenter.y - 10.8;
|
||
const basketTopY = baseCenter.y + 20;
|
||
const w1 = 36;
|
||
const angleRad = 10 * Math.PI / 180;
|
||
const topXOffset = 22 * Math.cos(angleRad);
|
||
const bottomXOffset = (w1 / 2) - (w1 * 0.05);
|
||
|
||
ctx.shadowColor = '#e0f2fe'; ctx.shadowBlur = 8;
|
||
ctx.strokeStyle = 'rgba(224, 242, 254, 0.2)'; ctx.lineWidth = 1.5;
|
||
ctx.beginPath();
|
||
ctx.moveTo(baseCenter.x - topXOffset, ropeAttachY); ctx.lineTo(baseCenter.x - bottomXOffset, basketTopY);
|
||
ctx.moveTo(baseCenter.x + topXOffset, ropeAttachY); ctx.lineTo(baseCenter.x + bottomXOffset, basketTopY);
|
||
ctx.stroke();
|
||
|
||
ctx.shadowBlur = 10; ctx.fillStyle = 'rgba(2, 6, 23, 0.9)'; ctx.strokeStyle = '#e0f2fe'; ctx.lineWidth = 1.5;
|
||
const bH = 8.5;
|
||
const widths = [w1, w1 * 0.9, (w1 * 0.9) * 0.9];
|
||
for (let i = 0; i < 3; i++) {
|
||
ctx.beginPath(); ctx.roundRect(baseCenter.x - widths[i] / 2, basketTopY + (i * (bH + 2)), widths[i], bH, 3);
|
||
ctx.fill(); ctx.stroke();
|
||
}
|
||
ctx.shadowBlur = 0;
|
||
}
|
||
|
||
function initBalloon() {
|
||
particles.length = 0;
|
||
particles.push(new Particle(true, 0, 0));
|
||
for (let i = 0; i < 5; i++) particles.push(new Particle(true, TOTAL_COMPACTED_HEIGHT, (i / 5) * Math.PI * 2));
|
||
for (let i = 0; i < NUM_PARTICLES; i++) particles.push(new Particle());
|
||
animateBalloon();
|
||
}
|
||
|
||
function animateBalloon() {
|
||
ctx.clearRect(0, 0, 400, 620);
|
||
ctx.save();
|
||
ctx.translate(0, TOP_SHIFT);
|
||
particles.forEach(p => { if (!p.isAnchor) p.theta += p.speed; });
|
||
drawBasket();
|
||
ctx.lineWidth = 0.4;
|
||
for (let i = 0; i < particles.length; i++) {
|
||
for (let j = i + 1; j < particles.length; j++) {
|
||
const p1 = getPos(particles[i].h, particles[i].theta);
|
||
const p2 = getPos(particles[j].h, particles[j].theta);
|
||
if (Math.hypot(p1.x - p2.x, p1.y - p2.y) < 30) {
|
||
const alpha = 0.05 + (((p1.z + p2.z) / 2) + 1) * 0.05;
|
||
ctx.strokeStyle = `rgba(52, 211, 153, ${alpha})`;
|
||
ctx.beginPath(); ctx.moveTo(p1.x, p1.y); ctx.lineTo(p2.x, p2.y); ctx.stroke();
|
||
}
|
||
}
|
||
}
|
||
particles.forEach(p => {
|
||
const pos = getPos(p.h, p.theta);
|
||
ctx.fillStyle = `rgba(52, 211, 153, ${0.3 + (pos.z + 1) * 0.35})`;
|
||
ctx.beginPath(); ctx.arc(pos.x, pos.y, 1.2, 0, Math.PI * 2); ctx.fill();
|
||
});
|
||
ctx.restore();
|
||
requestAnimationFrame(animateBalloon);
|
||
}
|
||
|
||
function openDownloadModal() {
|
||
document.getElementById('downloadModal').classList.add('active');
|
||
document.body.style.overflow = 'hidden';
|
||
}
|
||
function closeDownloadModal() {
|
||
document.getElementById('downloadModal').classList.remove('active');
|
||
document.body.style.overflow = '';
|
||
}
|
||
|
||
function openWhitepaper() {
|
||
const modal = document.getElementById('whitepaperModal');
|
||
modal.classList.add('active');
|
||
document.body.style.overflow = 'hidden';
|
||
|
||
// Robust Mermaid rendering trigger
|
||
if (window.mermaid) {
|
||
setTimeout(() => {
|
||
const elements = modal.querySelectorAll('.mermaid:not([data-processed="true"])');
|
||
if (elements.length > 0) {
|
||
window.mermaid.run({ nodes: elements }).catch(err => console.error("Mermaid render error:", err));
|
||
}
|
||
}, 150);
|
||
}
|
||
}
|
||
|
||
function closeWhitepaper() {
|
||
document.getElementById('whitepaperModal').classList.remove('active');
|
||
document.body.style.overflow = '';
|
||
}
|
||
|
||
document.addEventListener('keydown', (e) => {
|
||
if (e.key === 'Escape') { closeWhitepaper(); closeDownloadModal(); }
|
||
});
|
||
|
||
async function initAuth() {
|
||
try {
|
||
if (typeof moxieAuth !== 'undefined') {
|
||
await moxieAuth.init();
|
||
updateAuthUI();
|
||
}
|
||
} catch (error) {
|
||
console.error('Auth init error:', error);
|
||
document.getElementById('loginBtn').classList.remove('hidden');
|
||
}
|
||
}
|
||
|
||
function updateAuthUI() {
|
||
const loginBtn = document.getElementById('loginBtn');
|
||
const dashboardBtn = document.getElementById('dashboardBtn');
|
||
if (typeof moxieAuth !== 'undefined' && moxieAuth.isAuthenticated) {
|
||
loginBtn.classList.add('hidden');
|
||
dashboardBtn.classList.remove('hidden');
|
||
} else {
|
||
loginBtn.classList.remove('hidden');
|
||
dashboardBtn.classList.add('hidden');
|
||
}
|
||
}
|
||
|
||
async function login() {
|
||
try {
|
||
if (typeof moxieAuth !== 'undefined') {
|
||
await moxieAuth.login(window.location.origin + '/dashboard.html');
|
||
}
|
||
} catch (error) {
|
||
console.error('Login error:', error);
|
||
alert('Failed to login. Please try again.');
|
||
}
|
||
}
|
||
|
||
function initContactForm() {
|
||
const form = document.getElementById('contact-form');
|
||
const successDiv = document.getElementById('success-message');
|
||
form.addEventListener('submit', async function (e) {
|
||
e.preventDefault();
|
||
const data = {
|
||
name: form.name.value.trim(),
|
||
email: form.email.value.trim(),
|
||
company: form.company.value.trim() || null,
|
||
message: form.message.value.trim()
|
||
};
|
||
if (!data.name || !data.email || !data.message) { alert('Please fill in all required fields.'); return; }
|
||
const btn = form.querySelector('button[type="submit"]');
|
||
const originalText = btn.textContent;
|
||
btn.disabled = true; btn.textContent = 'Sending...';
|
||
try {
|
||
const response = await fetch('/api/contact', {
|
||
method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify(data)
|
||
});
|
||
const result = await response.json();
|
||
if (response.ok && result.success) {
|
||
successDiv.classList.remove('hidden'); form.reset();
|
||
setTimeout(() => { successDiv.classList.add('hidden'); }, 6000);
|
||
} else { alert(result.message || 'Something went wrong. Please try again.'); }
|
||
} catch (error) { alert('Network error. Please check your connection and try again.'); }
|
||
finally { btn.disabled = false; btn.textContent = originalText; }
|
||
});
|
||
}
|
||
|
||
function initLeaderboard() {
|
||
const data = [
|
||
{ rank: 1, model: 'Claude Opus 4.7 Thinking', provider: 'Anthropic', score: 1503 },
|
||
{ rank: 2, model: 'Claude Opus 4.6 Thinking', provider: 'Anthropic', score: 1502 },
|
||
{ rank: 3, model: 'Claude Opus 4.6', provider: 'Anthropic', score: 1498 },
|
||
{ rank: 4, model: 'Gemini 3.1 Pro Preview', provider: 'Google', score: 1492 },
|
||
{ rank: 5, model: 'Claude Opus 4.7', provider: 'Anthropic', score: 1491 },
|
||
{ rank: 6, model: 'Muse Spark', provider: 'Meta', score: 1490 },
|
||
{ rank: 7, model: 'Moxie', provider: 'Moxiegen', score: 1488 },
|
||
{ rank: 8, model: 'Gemini 3 Pro', provider: 'Google', score: 1486 },
|
||
{ rank: 9, model: 'GPT-5.5 High', provider: 'OpenAI', score: 1484 },
|
||
{ rank: 10, model: 'Grok 4.20 Beta', provider: 'xAI', score: 1480 },
|
||
{ rank: 11, model: 'GPT-5.2 Chat', provider: 'OpenAI', score: 1477 },
|
||
{ rank: 12, model: 'GPT-5.4 High', provider: 'OpenAI', score: 1477 },
|
||
{ rank: 13, model: 'Grok 4.20 Reasoning', provider: 'xAI', score: 1477 },
|
||
{ rank: 14, model: 'GPT-5.5', provider: 'OpenAI', score: 1475 },
|
||
{ rank: 15, model: 'ERNIE 5.1', provider: 'Baidu', score: 1474 },
|
||
];
|
||
const minScore = 1470, maxScore = 1505, range = maxScore - minScore;
|
||
const medals = ['🥇', '🥈', '🥉'];
|
||
const barColors = ['linear-gradient(90deg, #fbbf24, #f59e0b)', 'linear-gradient(90deg, #d1d5db, #9ca3af)', 'linear-gradient(90deg, #d97706, #b45309)'];
|
||
const container = document.getElementById('leaderboard-chart');
|
||
if (!container) return;
|
||
container.innerHTML = data.map((item, i) => {
|
||
const isMoxie = item.provider === 'Moxiegen';
|
||
const pct = ((item.score - minScore) / range) * 100;
|
||
const medal = i < 3 ? `<span class="lb-medal">${medals[i]}</span>` : '';
|
||
const barBg = isMoxie ? '' : (i < 3 ? `background:${barColors[i]};` : 'background:rgba(148,163,184,0.25);');
|
||
return `
|
||
<div class="lb-row${isMoxie ? ' is-moxie' : ''}">
|
||
<div class="lb-rank">${medal || item.rank}</div>
|
||
<div class="lb-bar-wrap">
|
||
<div class="lb-model-line"><span class="lb-model-name">${item.model}</span><span class="lb-provider">${item.provider}</span></div>
|
||
<div class="lb-bar-track"><div class="lb-bar-fill" data-width="${pct}" style="${barBg}"></div></div>
|
||
</div>
|
||
<div class="lb-score">${item.score}</div>
|
||
</div>`;
|
||
}).join('');
|
||
requestAnimationFrame(() => {
|
||
setTimeout(() => {
|
||
container.querySelectorAll('.lb-bar-fill').forEach(bar => { bar.style.width = bar.dataset.width + '%'; });
|
||
}, 200);
|
||
});
|
||
}
|
||
|
||
window.addEventListener('load', () => {
|
||
initScrollAnimations();
|
||
initBalloon();
|
||
initAuth();
|
||
initContactForm();
|
||
initLeaderboard();
|
||
});
|
||
</script>
|
||
<script src="js/config.js"></script>
|
||
<script src="js/auth.js"></script>
|
||
</body>
|
||
|
||
</html> |