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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8"/>
<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
<title>Matrix Lattice — Architecture Spec</title>
<style>
@import url('https://fonts.googleapis.com/css2?family=Share+Tech+Mono&family=Syne:wght@400;700;800;900&display=swap');

:root {
  --bg: #03070d;
  --card: #070e18;
  --border: #0f2035;
  --accent: #00d4ff;
  --accent2: #7b4dff;
  --accent3: #ff6b35;
  --gold: #f0b429;
  --text: #cdd8e8;
  --muted: #3d5a78;
  --glow: rgba(0,212,255,0.08);
}

* { box-sizing: border-box; margin: 0; padding: 0; }

body {
  background: var(--bg);
  font-family: 'Syne', sans-serif;
  color: var(--text);
  min-height: 100vh;
  overflow-x: hidden;
}

/* ── Grid background ── */
body::before {
  content: '';
  position: fixed;
  inset: 0;
  background-image:
    linear-gradient(rgba(0,212,255,0.03) 1px, transparent 1px),
    linear-gradient(90deg, rgba(0,212,255,0.03) 1px, transparent 1px);
  background-size: 48px 48px;
  pointer-events: none;
  z-index: 0;
}

.wrap { position: relative; z-index: 1; max-width: 1200px; margin: 0 auto; padding: 0 32px 80px; }

/* ── Hero ── */
.hero {
  padding: 80px 0 60px;
  text-align: center;
  position: relative;
}
.hero::after {
  content: '';
  position: absolute;
  bottom: 0; left: 50%;
  transform: translateX(-50%);
  width: 600px; height: 1px;
  background: linear-gradient(90deg, transparent, var(--accent), transparent);
}
.hero-badge {
  display: inline-block;
  padding: 5px 16px;
  border: 1px solid var(--accent2);
  border-radius: 2px;
  font-family: 'Share Tech Mono', monospace;
  font-size: 11px;
  color: var(--accent2);
  letter-spacing: 4px;
  margin-bottom: 28px;
  background: rgba(123,77,255,0.06);
}
.hero h1 {
  font-size: clamp(52px, 8vw, 96px);
  font-weight: 900;
  line-height: 0.92;
  letter-spacing: -2px;
  margin-bottom: 16px;
}
.hero h1 .matrix { color: var(--muted); }
.hero h1 .lattice {
  color: var(--accent);
  text-shadow: 0 0 60px rgba(0,212,255,0.4);
}
.hero-sub {
  font-size: 14px;
  color: var(--muted);
  letter-spacing: 3px;
  text-transform: uppercase;
  margin-bottom: 48px;
}
.hero-tags {
  display: flex;
  justify-content: center;
  flex-wrap: wrap;
  gap: 10px;
}
.tag {
  padding: 6px 16px;
  border: 1px solid var(--border);
  border-radius: 2px;
  font-family: 'Share Tech Mono', monospace;
  font-size: 11px;
  color: var(--muted);
  letter-spacing: 1px;
}
.tag.hot { border-color: var(--accent); color: var(--accent); background: var(--glow); }
.tag.purple { border-color: var(--accent2); color: var(--accent2); background: rgba(123,77,255,0.06); }
.tag.orange { border-color: var(--accent3); color: var(--accent3); background: rgba(255,107,53,0.06); }

/* ── Section headers ── */
.section { margin-top: 72px; }
.section-label {
  font-family: 'Share Tech Mono', monospace;
  font-size: 10px;
  color: var(--accent);
  letter-spacing: 5px;
  text-transform: uppercase;
  margin-bottom: 6px;
}
.section-title {
  font-size: 28px;
  font-weight: 800;
  color: #fff;
  margin-bottom: 28px;
}

/* ── Model tier cards ── */
.tier-grid { display: grid; grid-template-columns: repeat(3, 1fr); gap: 2px; }
.tier {
  background: var(--card);
  border: 1px solid var(--border);
  padding: 32px 24px;
  position: relative;
  overflow: hidden;
  transition: border-color 0.2s;
}
.tier::before {
  content: '';
  position: absolute;
  top: 0; left: 0; right: 0;
  height: 2px;
}
.tier.t120::before { background: linear-gradient(90deg, var(--accent2), transparent); }
.tier.t430::before { background: linear-gradient(90deg, var(--accent), transparent); }
.tier.t671::before { background: linear-gradient(90deg, var(--gold), transparent); }
.tier:hover { border-color: var(--accent); }

.tier-name {
  font-size: 13px;
  font-weight: 800;
  letter-spacing: 3px;
  margin-bottom: 6px;
  text-transform: uppercase;
}
.tier.t120 .tier-name { color: var(--accent2); }
.tier.t430 .tier-name { color: var(--accent); }
.tier.t671 .tier-name { color: var(--gold); }

.tier-params {
  font-size: 48px;
  font-weight: 900;
  color: #fff;
  line-height: 1;
  margin-bottom: 4px;
}
.tier-active {
  font-family: 'Share Tech Mono', monospace;
  font-size: 11px;
  color: var(--muted);
  margin-bottom: 24px;
}
.tier-stat { display: flex; justify-content: space-between; padding: 8px 0; border-top: 1px solid var(--border); font-size: 11px; }
.tier-stat .k { color: var(--muted); font-family: 'Share Tech Mono', monospace; letter-spacing: 1px; }
.tier-stat .v { color: var(--text); font-weight: 700; font-family: 'Share Tech Mono', monospace; }

/* ── Arch blocks ── */
.arch-row {
  display: grid;
  grid-template-columns: repeat(auto-fill, minmax(280px, 1fr));
  gap: 12px;
}
.arch-block {
  background: var(--card);
  border: 1px solid var(--border);
  border-left: 3px solid var(--accent);
  padding: 18px 20px;
}
.arch-block.purple { border-left-color: var(--accent2); }
.arch-block.orange { border-left-color: var(--accent3); }
.arch-block.gold { border-left-color: var(--gold); }
.arch-name {
  font-size: 12px;
  font-weight: 800;
  color: #fff;
  margin-bottom: 6px;
  letter-spacing: 0.5px;
}
.arch-desc {
  font-family: 'Share Tech Mono', monospace;
  font-size: 10px;
  color: var(--muted);
  line-height: 1.8;
}

/* ── Modules grid ── */
.modules-grid {
  display: grid;
  grid-template-columns: repeat(auto-fill, minmax(340px, 1fr));
  gap: 2px;
}
.module {
  background: var(--card);
  border: 1px solid var(--border);
  padding: 24px;
  position: relative;
  transition: all 0.15s;
}
.module:hover {
  border-color: var(--accent);
  background: #070f1c;
}
.module-num {
  font-family: 'Share Tech Mono', monospace;
  font-size: 10px;
  color: var(--muted);
  letter-spacing: 2px;
  margin-bottom: 8px;
}
.module-name {
  font-size: 14px;
  font-weight: 800;
  color: #fff;
  margin-bottom: 10px;
  letter-spacing: 0.3px;
}
.module-desc {
  font-family: 'Share Tech Mono', monospace;
  font-size: 10px;
  color: var(--muted);
  line-height: 1.9;
}
.module-badge {
  position: absolute;
  top: 16px; right: 16px;
  padding: 2px 8px;
  font-family: 'Share Tech Mono', monospace;
  font-size: 9px;
  letter-spacing: 1px;
  border-radius: 2px;
}
.mb-new { background: rgba(0,212,255,0.1); color: var(--accent); border: 1px solid var(--accent); }
.mb-eq { background: rgba(123,77,255,0.1); color: var(--accent2); border: 1px solid var(--accent2); }
.mb-safe { background: rgba(240,180,41,0.1); color: var(--gold); border: 1px solid var(--gold); }
.mb-agent { background: rgba(255,107,53,0.1); color: var(--accent3); border: 1px solid var(--accent3); }
.mb-mm { background: rgba(0,255,128,0.1); color: #00ff80; border: 1px solid #00ff80; }

/* ── API block ── */
.api-block {
  background: #020608;
  border: 1px solid var(--border);
  border-radius: 4px;
  padding: 28px 32px;
  font-family: 'Share Tech Mono', monospace;
  font-size: 12px;
  line-height: 2;
  overflow-x: auto;
}
.kw { color: var(--accent2); }
.fn { color: var(--accent); }
.str { color: #86efac; }
.cm { color: var(--muted); }
.num { color: var(--gold); }

/* ── TPS chart ── */
.tps-grid { display: grid; grid-template-columns: repeat(3,1fr); gap: 2px; }
.tps-card {
  background: var(--card);
  border: 1px solid var(--border);
  padding: 24px;
}
.tps-model { font-size: 11px; font-weight: 800; letter-spacing: 3px; margin-bottom: 20px; }
.tps-card:nth-child(1) .tps-model { color: var(--accent2); }
.tps-card:nth-child(2) .tps-model { color: var(--accent); }
.tps-card:nth-child(3) .tps-model { color: var(--gold); }
.tps-row { margin-bottom: 14px; }
.tps-label { display: flex; justify-content: space-between; font-family: 'Share Tech Mono', monospace; font-size: 10px; margin-bottom: 5px; }
.tps-label .quant { color: var(--muted); }
.tps-label .val { color: #fff; font-weight: 700; }
.tps-bar { height: 5px; background: var(--border); border-radius: 1px; overflow: hidden; }
.tps-fill { height: 100%; border-radius: 1px; }
.bf16 { background: var(--muted); }
.int8 { background: var(--accent); }
.int4 { background: var(--gold); }

/* ── Footer ── */
.footer {
  margin-top: 80px;
  padding-top: 32px;
  border-top: 1px solid var(--border);
  display: flex;
  justify-content: space-between;
  align-items: center;
  font-family: 'Share Tech Mono', monospace;
  font-size: 10px;
  color: var(--muted);
  letter-spacing: 2px;
}
.footer-dots { display: flex; gap: 16px; }
.dot { display: flex; align-items: center; gap: 6px; }
.dot::before { content: '●'; font-size: 8px; }
.dot.cyan::before { color: var(--accent); }
.dot.purple::before { color: var(--accent2); }
.dot.gold::before { color: var(--gold); }

/* ── Timeline ── */
.timeline { display: flex; gap: 0; }
.tl-step {
  flex: 1;
  padding: 20px 24px;
  background: var(--card);
  border: 1px solid var(--border);
  border-right: none;
  position: relative;
}
.tl-step:last-child { border-right: 1px solid var(--border); }
.tl-step::after {
  content: '▶';
  position: absolute;
  right: -10px; top: 50%;
  transform: translateY(-50%);
  font-size: 10px;
  color: var(--muted);
  z-index: 2;
}
.tl-step:last-child::after { display: none; }
.tl-num { font-family: 'Share Tech Mono', monospace; font-size: 10px; color: var(--muted); letter-spacing: 2px; margin-bottom: 8px; }
.tl-title { font-size: 12px; font-weight: 800; color: #fff; margin-bottom: 6px; }
.tl-desc { font-family: 'Share Tech Mono', monospace; font-size: 10px; color: var(--muted); line-height: 1.7; }
</style>
</head>
<body>
<div class="wrap">

  <!-- Hero -->
  <div class="hero">
    <div class="hero-badge">MATRIX.CORP — FRONTIER SERIES</div>
    <h1>
      <span class="matrix">MATRIX </span><br>
      <span class="lattice">LATTICE</span>
    </h1>
    <div class="hero-sub">Agentic · Multimodal · 1M+ Context · MoE · API-First</div>
    <div class="hero-tags">
      <span class="tag hot">120B / 430B / 671B</span>
      <span class="tag hot">~22–47B ACTIVE PARAMS</span>
      <span class="tag purple">17 CUSTOM MODULES</span>
      <span class="tag purple">DEEPSEEK-V3 + LLAMA 4 LINEAGE</span>
      <span class="tag orange">INFERENCE PROVIDER READY</span>
      <span class="tag orange">OPENAI-COMPATIBLE API</span>
      <span class="tag">MLA ATTENTION</span>
      <span class="tag">MIXTURE OF DEPTHS</span>
      <span class="tag">SPECULATIVE DECODING</span>
    </div>
  </div>

  <!-- Model Tiers -->
  <div class="section">
    <div class="section-label">Model Family</div>
    <div class="section-title">Three Tiers, One Architecture</div>
    <div class="tier-grid">
      <div class="tier t120">
        <div class="tier-name">Lattice — Entry</div>
        <div class="tier-params">120B</div>
        <div class="tier-active">~22B active params · 64 experts · top-4</div>
        <div class="tier-stat"><span class="k">CONTEXT</span><span class="v">1M tokens</span></div>
        <div class="tier-stat"><span class="k">EXPERTS</span><span class="v">64 routed + 2 shared</span></div>
        <div class="tier-stat"><span class="k">HARDWARE</span><span class="v">4× H100 / 8× p300a</span></div>
        <div class="tier-stat"><span class="k">INT4 VRAM</span><span class="v">~60GB</span></div>
        <div class="tier-stat"><span class="k">TPS (INT4)</span><span class="v">~130</span></div>
        <div class="tier-stat"><span class="k">STATUS</span><span class="v" style="color:#f59e0b">🔴 PLANNED</span></div>
      </div>
      <div class="tier t430">
        <div class="tier-name">Lattice — Pro</div>
        <div class="tier-params">430B</div>
        <div class="tier-active">~38B active params · 128 experts · top-4</div>
        <div class="tier-stat"><span class="k">CONTEXT</span><span class="v">1M tokens</span></div>
        <div class="tier-stat"><span class="k">EXPERTS</span><span class="v">128 routed + 4 shared</span></div>
        <div class="tier-stat"><span class="k">HARDWARE</span><span class="v">8× H100 / 28× p300a</span></div>
        <div class="tier-stat"><span class="k">INT4 VRAM</span><span class="v">~215GB</span></div>
        <div class="tier-stat"><span class="k">TPS (INT4)</span><span class="v">~72</span></div>
        <div class="tier-stat"><span class="k">STATUS</span><span class="v" style="color:#f59e0b">🔴 PLANNED</span></div>
      </div>
      <div class="tier t671">
        <div class="tier-name">Lattice — Max</div>
        <div class="tier-params">671B</div>
        <div class="tier-active">~47B active params · 256 experts · top-4</div>
        <div class="tier-stat"><span class="k">CONTEXT</span><span class="v">1M tokens</span></div>
        <div class="tier-stat"><span class="k">EXPERTS</span><span class="v">256 routed + 8 shared</span></div>
        <div class="tier-stat"><span class="k">HARDWARE</span><span class="v">32× H100 / 48× p300a</span></div>
        <div class="tier-stat"><span class="k">INT4 VRAM</span><span class="v">~336GB</span></div>
        <div class="tier-stat"><span class="k">TPS (INT4)</span><span class="v">~50</span></div>
        <div class="tier-stat"><span class="k">STATUS</span><span class="v" style="color:#f59e0b">🔴 PLANNED</span></div>
      </div>
    </div>
  </div>

  <!-- Public Architectures -->
  <div class="section">
    <div class="section-label">Foundation</div>
    <div class="section-title">Public Architectures Integrated</div>
    <div class="arch-row">
      <div class="arch-block">
        <div class="arch-name">Multi-Head Latent Attention (MLA)</div>
        <div class="arch-desc">DeepSeek-V3 · KV cache compressed ~90% via<br>low-rank projection · Essential for 1M context</div>
      </div>
      <div class="arch-block purple">
        <div class="arch-name">Mixture of Experts (MoE)</div>
        <div class="arch-desc">DeepSeek-V3 style · Fine-grained expert segmentation<br>Auxiliary-free load balancing · No token dropping</div>
      </div>
      <div class="arch-block orange">
        <div class="arch-name">Mixture of Depths (MoD)</div>
        <div class="arch-desc">Google Research · Tokens skip up to 50% of layers<br>~30% compute reduction at same quality</div>
      </div>
      <div class="arch-block gold">
        <div class="arch-name">iRoPE / YaRN Scaling</div>
        <div class="arch-desc">Llama 4 + YaRN · NTK-aware RoPE for 1M+ context<br>Full attention every 4th layer · 8K sliding window</div>
      </div>
      <div class="arch-block">
        <div class="arch-name">Speculative Decoding</div>
        <div class="arch-desc">Paired draft model per tier (~4B params each)<br>3–5× inference speedup · Shared embedding weights</div>
      </div>
      <div class="arch-block purple">
        <div class="arch-name">Multimodal Vision Encoder</div>
        <div class="arch-desc">Llama 4 / InternVL lineage · ViT 6B params<br>Images, video, documents, charts · 4K via tiling</div>
      </div>
      <div class="arch-block orange">
        <div class="arch-name">Audio Encoder</div>
        <div class="arch-desc">Whisper-large-v3 lineage · Speech + sound understanding<br>Cross-attention injected into LM backbone</div>
      </div>
      <div class="arch-block gold">
        <div class="arch-name">Sliding Window Attention</div>
        <div class="arch-desc">Mistral · 8K window on non-full-attention layers<br>O(n) memory for most layers of the network</div>
      </div>
    </div>
  </div>

  <!-- 17 Modules -->
  <div class="section">
    <div class="section-label">Custom Architecture</div>
    <div class="section-title">17 Custom Modules</div>
    <div class="modules-grid">

      <div class="module">
        <div class="module-badge mb-eq">EQ V2</div>
        <div class="module-num">MODULE 01</div>
        <div class="module-name">EQ Engine V2</div>
        <div class="module-desc">Conversation-arc emotional tracking via persistent GRU.<br>12-emotion classification. Frustration trajectory<br>prediction. Per-user baseline calibration (3 turns).</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">CORE</div>
        <div class="module-num">MODULE 02</div>
        <div class="module-name">Lattice Router</div>
        <div class="module-desc">Hierarchical MoE routing: token → domain cluster →<br>expert group → expert. 8 domain clusters.<br>Experts self-label. Load-aware dispatch.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">API</div>
        <div class="module-num">MODULE 03</div>
        <div class="module-name">Confidence Calibration Head</div>
        <div class="module-desc">Parallel to LM head. Epistemic uncertainty [0–1]<br>per token. Aggregated per sentence. Exposed via<br>X-Lattice-Confidence header in streaming API.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-agent">AGENTIC</div>
        <div class="module-num">MODULE 04</div>
        <div class="module-name">Native Tool Schema Reasoner</div>
        <div class="module-desc">Dedicated attention heads for JSON Schema, OpenAPI,<br>GraphQL, SQL DDL. Tool call planner generates<br>multi-step plans. Parallel tool dispatch.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-agent">AGENTIC</div>
        <div class="module-num">MODULE 05</div>
        <div class="module-name">Multi-Agent Coordination Layer</div>
        <div class="module-desc">Structured agent message protocol. Role awareness:<br>orchestrator / subagent / critic / executor.<br>Shared scratchpad attention. Conflict resolution head.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">CONTEXT</div>
        <div class="module-num">MODULE 06</div>
        <div class="module-name">Hierarchical Context Compression</div>
        <div class="module-desc">Every 32K tokens compressed to summary + key-facts.<br>Meta-summary at 128K. Recent 32K always full-res.<br>~20:1 narrative · ~5:1 code compression ratio.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">OUTPUT</div>
        <div class="module-num">MODULE 07</div>
        <div class="module-name">Structured Output Enforcer</div>
        <div class="module-desc">Constrained decoding via token masking. Guaranteed<br>valid JSON, YAML, XML, Python, SQL, HTML.<br>Partial streaming of valid JSON as tokens generate.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">REASON</div>
        <div class="module-num">MODULE 08</div>
        <div class="module-name">Causal Reasoning Graph</div>
        <div class="module-desc">Builds explicit cause-effect graph during generation.<br>Graph attention on reasoning steps. Detects loops<br>and contradiction chains. Optional API trace output.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">TIME</div>
        <div class="module-num">MODULE 09</div>
        <div class="module-name">Temporal Awareness Module</div>
        <div class="module-desc">Dedicated temporal embeddings for absolute dates,<br>relative references, durations. Timeline builder.<br>Temporal consistency checker for event ordering.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">LANG</div>
        <div class="module-num">MODULE 10</div>
        <div class="module-name">Cross-Lingual Alignment Layer</div>
        <div class="module-desc">50+ languages. Language-agnostic semantic space.<br>Code-switching aware. CJK, Arabic RTL, Devanagari<br>native. Dialect modeling. Self-scoring translation head.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-safe">SAFETY</div>
        <div class="module-num">MODULE 11</div>
        <div class="module-name">Safety Reasoning Module</div>
        <div class="module-desc">Explicit safety chain before generation, not post-hoc.<br>47 harm categories with confidence scores.<br>Provider-configurable tiers. Structured audit log.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-mm">VISION</div>
        <div class="module-num">MODULE 12</div>
        <div class="module-name">Vision-Language Grounding</div>
        <div class="module-desc">Object-level text-to-region grounding. Chart/diagram<br>interpreter. Document layout understanding.<br>Screenshot-to-code. Video temporal grounding.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-agent">AGENTIC</div>
        <div class="module-num">MODULE 13</div>
        <div class="module-name">Long-Horizon Task Planner</div>
        <div class="module-desc">Task decomposition into DAGs. Dependency resolver.<br>Progress tracker across long sessions. Replanning<br>trigger. Integrates with MACL for multi-agent tasks.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-eq">PERSONA</div>
        <div class="module-num">MODULE 14</div>
        <div class="module-name">Persona Stability Enforcer</div>
        <div class="module-desc">Operator-defined persona as persistent embedding.<br>Style consistency loss during training. Factual<br>self-consistency checker. EQ-aware tone modulation.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">API</div>
        <div class="module-num">MODULE 15</div>
        <div class="module-name">API Telemetry & Observability</div>
        <div class="module-desc">Per-token latency, expert utilization, compression events,<br>confidence, module activation trace — all exposed as<br>structured SSE metadata alongside token stream.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-new">CODE</div>
        <div class="module-num">MODULE 16</div>
        <div class="module-name">Code Intelligence Engine</div>
        <div class="module-desc">AST-aware attention. Multi-file dependency graph.<br>Runtime simulation head. CVE bug pattern library.<br>Test generation. Build/exec tool integration.</div>
      </div>

      <div class="module">
        <div class="module-badge mb-safe">TRUST</div>
        <div class="module-num">MODULE 17</div>
        <div class="module-name">Knowledge Boundary Detector</div>
        <div class="module-desc">Hallucination risk scorer per claim. Claim classification:<br>known / uncertain / hallucination-risk / out-of-training.<br>3-pass self-consistency check on uncertain outputs.</div>
      </div>

    </div>
  </div>

  <!-- TPS -->
  <div class="section">
    <div class="section-label">Performance</div>
    <div class="section-title">Estimated Inference Throughput</div>
    <div class="tps-grid">
      <div class="tps-card">
        <div class="tps-model">LATTICE-120B</div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">BF16</span><span class="val">~35 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill bf16" style="width:27%"></div></div>
        </div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">INT8</span><span class="val">~70 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill int8" style="width:54%"></div></div>
        </div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">INT4</span><span class="val">~130 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill int4" style="width:100%"></div></div>
        </div>
      </div>
      <div class="tps-card">
        <div class="tps-model">LATTICE-430B</div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">BF16</span><span class="val">~18 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill bf16" style="width:25%"></div></div>
        </div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">INT8</span><span class="val">~38 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill int8" style="width:53%"></div></div>
        </div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">INT4</span><span class="val">~72 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill int4" style="width:100%"></div></div>
        </div>
      </div>
      <div class="tps-card">
        <div class="tps-model">LATTICE-671B</div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">BF16</span><span class="val">~12 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill bf16" style="width:24%"></div></div>
        </div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">INT8</span><span class="val">~26 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill int8" style="width:52%"></div></div>
        </div>
        <div class="tps-row">
          <div class="tps-label"><span class="quant">INT4</span><span class="val">~50 TPS</span></div>
          <div class="tps-bar"><div class="tps-fill int4" style="width:100%"></div></div>
        </div>
      </div>
    </div>
  </div>

  <!-- API -->
  <div class="section">
    <div class="section-label">Integration</div>
    <div class="section-title">OpenAI-Compatible API</div>
    <div class="api-block">
<span class="kw">from</span> openai <span class="kw">import</span> OpenAI<br><br>
client = <span class="fn">OpenAI</span>(<br>
&nbsp;&nbsp;&nbsp;&nbsp;base_url=<span class="str">"https://api.provider.com/v1"</span>,<br>
&nbsp;&nbsp;&nbsp;&nbsp;api_key=<span class="str">"your-key"</span><br>
)<br><br>
response = client.chat.completions.<span class="fn">create</span>(<br>
&nbsp;&nbsp;&nbsp;&nbsp;model=<span class="str">"matrix-lattice-671b"</span>,<br>
&nbsp;&nbsp;&nbsp;&nbsp;messages=[{<span class="str">"role"</span>: <span class="str">"user"</span>, <span class="str">"content"</span>: <span class="str">"..."</span>}],<br>
&nbsp;&nbsp;&nbsp;&nbsp;tools=[...],<br>
&nbsp;&nbsp;&nbsp;&nbsp;extra_body={<br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"lattice"</span>: {<br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"expose_confidence"</span>: <span class="kw">True</span>,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="cm"># X-Lattice-Confidence per chunk</span><br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"expose_reasoning_graph"</span>: <span class="kw">False</span>,&nbsp;&nbsp;<span class="cm"># Causal graph trace</span><br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"expose_module_trace"</span>: <span class="kw">True</span>,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="cm"># Which modules fired</span><br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"safety_tier"</span>: <span class="str">"standard"</span>,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="cm"># standard | strict | minimal</span><br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"agent_role"</span>: <span class="str">"orchestrator"</span>,&nbsp;&nbsp;&nbsp;<span class="cm"># orchestrator | subagent | critic</span><br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class="str">"persona"</span>: <span class="str">"helpful-assistant"</span>&nbsp;&nbsp;<span class="cm"># Persona Stability Enforcer</span><br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;}<br>
&nbsp;&nbsp;&nbsp;&nbsp;}<br>
)<br><br>
<span class="cm"># Response extensions:</span><br>
<span class="cm"># response.lattice.confidence_scores</span><br>
<span class="cm"># response.lattice.active_modules</span><br>
<span class="cm"># response.lattice.hallucination_risk</span><br>
<span class="cm"># response.lattice.expert_clusters_used</span>
    </div>
  </div>

  <!-- Training Timeline -->
  <div class="section">
    <div class="section-label">Training Plan</div>
    <div class="section-title">Four-Phase Training Strategy</div>
    <div class="timeline">
      <div class="tl-step">
        <div class="tl-num">PHASE 01</div>
        <div class="tl-title">Foundation</div>
        <div class="tl-desc">Mixed distillation from DeepSeek-V3, R1, Llama 4. Web + code + science + multimodal. Context curriculum 8K→1M.</div>
      </div>
      <div class="tl-step">
        <div class="tl-num">PHASE 02</div>
        <div class="tl-title">Module Integration</div>
        <div class="tl-desc">All 17 modules trained with auxiliary losses. Frozen in sequence as each converges.</div>
      </div>
      <div class="tl-step">
        <div class="tl-num">PHASE 03</div>
        <div class="tl-title">Agentic SFT</div>
        <div class="tl-desc">Tool use, MACL, long-horizon planning. Synthetic agentic trajectories. GRPO on task completion.</div>
      </div>
      <div class="tl-step">
        <div class="tl-num">PHASE 04</div>
        <div class="tl-title">Alignment</div>
        <div class="tl-desc">Safety module fine-tuning. Constitutional AI self-critique. Red-team adversarial tuning.</div>
      </div>
    </div>
  </div>

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  <div class="footer">
    <span>MATRIX.CORP — LATTICE SPEC V1.0 — 🔴 PLANNED</span>
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