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</head>
<body>

<header>
  <div class="logo">
    <div class="logo-icon">🧠</div>
    <div class="logo-text">
      <h1>LLM Explorer 2026</h1>
      <p>Size · Speed · Benchmarks · Price</p>
    </div>
  </div>
  <div class="header-meta">
    <div class="badge"><strong id="model-count">36</strong> models</div>
    <div class="badge"><strong>13</strong> providers</div>
    <div class="badge new">Updated <strong>May 2026</strong></div>
    <div class="badge">MMLU saturated — now featuring GPQA Diamond &amp; SWE-bench</div>
  </div>
</header>

<div class="stat-strip">
  <div class="stat-item">
    <div class="stat-label">Best GPQA Diamond</div>
    <div class="stat-value">94.3%</div>
    <div class="stat-sub">Gemini 3.1 Pro</div>
  </div>
  <div class="stat-item">
    <div class="stat-label">Best SWE-bench</div>
    <div class="stat-value">87.6%</div>
    <div class="stat-sub">Claude Opus 4.7</div>
  </div>
  <div class="stat-item">
    <div class="stat-label">Fastest API</div>
    <div class="stat-value">400 t/s</div>
    <div class="stat-sub">Gemini 2.5 Flash-Lite</div>
  </div>
  <div class="stat-item">
    <div class="stat-label">Cheapest Input</div>
    <div class="stat-value">$0.02</div>
    <div class="stat-sub">per 1M tokens (Qwen3.5 2B)</div>
  </div>
  <div class="stat-item">
    <div class="stat-label">Largest Context</div>
    <div class="stat-value">10M tok</div>
    <div class="stat-sub">Llama 4 Scout</div>
  </div>
</div>

<div class="main">
  <nav class="sidebar">
    <div class="sidebar-section">
      <div class="sidebar-title">Views</div>
      <div class="nav-item active" onclick="setView('benchmarks',this)"><div class="nav-dot" style="background:#f5a623"></div>Benchmarks</div>
      <div class="nav-item" onclick="setView('speed',this)"><div class="nav-dot" style="background:#3ecfcf"></div>Speed</div>
      <div class="nav-item" onclick="setView('price',this)"><div class="nav-dot" style="background:#3ecf8e"></div>Price</div>
      <div class="nav-item" onclick="setView('efficiency',this)"><div class="nav-dot" style="background:#a78bfa"></div>Efficiency</div>
      <div class="nav-item" onclick="setView('table',this)"><div class="nav-dot" style="background:#7a7f96"></div>All Models</div>
    </div>
    <div class="sidebar-section" id="bench-section">
      <div class="sidebar-title">Benchmark</div>
      <button class="bench-btn active" onclick="setBench('mmlu',this)">MMLU<div class="bench-sub">General knowledge (57 subjects)</div></button>
      <button class="bench-btn" onclick="setBench('gpqa',this)">GPQA Diamond<div class="bench-sub">PhD-level science questions</div></button>
      <button class="bench-btn" onclick="setBench('sweben',this)">SWE-bench Verified<div class="bench-sub">Real GitHub issue resolution</div></button>
      <button class="bench-btn" onclick="setBench('aime',this)">AIME 2025<div class="bench-sub">Math olympiad problems</div></button>
    </div>
    <div class="sidebar-section" id="price-section" style="display:none">
      <div class="sidebar-title">Price Type</div>
      <div class="toggle-group">
        <div class="toggle-btn active" onclick="setPriceType('input',this)">Input</div>
        <div class="toggle-btn" onclick="setPriceType('output',this)">Output</div>
      </div>
    </div>
    <div class="sidebar-section">
      <div class="sidebar-title">Model Type</div>
      <div class="toggle-group">
        <div class="toggle-btn active" id="type-all" onclick="setTypeFilter('all')">All</div>
        <div class="toggle-btn" id="type-open" onclick="setTypeFilter('open')">Open</div>
        <div class="toggle-btn" id="type-closed" onclick="setTypeFilter('closed')">Closed</div>
      </div>
    </div>
    <div class="sidebar-section">
      <div class="sidebar-title">Providers</div>
      <div id="provider-filters"></div>
    </div>
  </nav>

  <div class="content">
    <div class="view active" id="view-benchmarks">
      <div class="chart-header">
        <div class="chart-title" id="bench-chart-title">Model Parameters vs MMLU Score</div>
        <div class="chart-sub">Log x-axis · ◆ = MoE model · † = estimated params for closed models · hover for full details</div>
      </div>
      <div class="chart-wrap"><div id="chart-benchmarks" style="width:100%;height:100%"></div></div>
    </div>

    <div class="view" id="view-speed">
      <div class="chart-header">
        <div class="chart-title">Model Parameters vs Generation Speed</div>
        <div class="chart-sub">Tokens/second via provider API · Source: Artificial Analysis · ◆ = MoE · Log x-axis</div>
      </div>
      <div class="chart-wrap"><div id="chart-speed" style="width:100%;height:100%"></div></div>
    </div>

    <div class="view" id="view-price">
      <div class="chart-header">
        <div class="chart-title" id="price-chart-title">Model Parameters vs Input Price ($/1M tokens)</div>
        <div class="chart-sub">Log-log scale · Open-source prices via hosted APIs (Together, Fireworks, etc.)</div>
      </div>
      <div class="chart-wrap"><div id="chart-price" style="width:100%;height:100%"></div></div>
    </div>

    <div class="view" id="view-efficiency">
      <div class="chart-header">
        <div class="chart-title">Performance vs Price — Efficiency Frontier</div>
        <div class="chart-sub">GPQA Diamond score vs input price · Bubble size ∝ total parameters · Upper-left = best value</div>
      </div>
      <div class="chart-wrap"><div id="chart-efficiency" style="width:100%;height:100%"></div></div>
      <div class="eff-note">⬆ Upper-left = high performance + low cost. Bubble size ∝ total parameters. ◆ diamonds = MoE architectures (active params far smaller than total).</div>
    </div>

    <div class="table-view" id="view-table">
      <div class="table-controls">
        <input class="search-box" type="text" id="search-input" placeholder="Search models or providers…" oninput="renderTable()">
        <span class="sort-label">Sort by</span>
        <select class="sort-select" id="sort-col" onchange="renderTable()">
          <option value="gpqa">GPQA Diamond</option>
          <option value="sweben">SWE-bench</option>
          <option value="aime">AIME 2025</option>
          <option value="mmlu">MMLU</option>
          <option value="params">Params</option>
          <option value="speed">Speed</option>
          <option value="input_price">Input Price</option>
          <option value="output_price">Output Price</option>
          <option value="name">Name</option>
        </select>
      </div>
      <div class="table-wrap">
        <table>
          <thead><tr>
            <th onclick="sortTable('name')">Model</th>
            <th onclick="sortTable('provider')">Provider</th>
            <th onclick="sortTable('type')">Type</th>
            <th onclick="sortTable('params')">Params (B)</th>
            <th onclick="sortTable('mmlu')">MMLU</th>
            <th onclick="sortTable('gpqa')" class="sorted">GPQA ◆</th>
            <th onclick="sortTable('sweben')">SWE-bench</th>
            <th onclick="sortTable('aime')">AIME 2025</th>
            <th onclick="sortTable('speed')">t/s</th>
            <th onclick="sortTable('input_price')">In $/1M</th>
            <th onclick="sortTable('output_price')">Out $/1M</th>
            <th onclick="sortTable('context')">Ctx (K)</th>
          </tr></thead>
          <tbody id="table-body"></tbody>
        </table>
      </div>
    </div>
  </div>
</div>

<script>
const PROVIDERS={
  "OpenAI":   {color:"#10b981"},
  "Anthropic":{color:"#f97316"},
  "Google":   {color:"#60a5fa"},
  "Meta":     {color:"#a78bfa"},
  "Mistral":  {color:"#e879f9"},
  "Alibaba":  {color:"#fbbf24"},
  "DeepSeek": {color:"#f87171"},
  "Microsoft":{color:"#38bdf8"},
  "xAI":      {color:"#a3e635"},
  "Moonshot": {color:"#c084fc"},
  "Z.AI":     {color:"#fb923c"},
  "MiniMax":  {color:"#2dd4bf"},
  "IBM":      {color:"#93c5fd"}
};

const MODELS=[
  {name:"GPT-5.5",             provider:"OpenAI",    params:200, est:true,  moe:false,             mmlu:93.0,gpqa:88.0,sweben:85.0,aime:99.0,speed:20, input_price:5.75, output_price:46.00,context:1000, type:"closed"},
  {name:"GPT-5.4",             provider:"OpenAI",    params:200, est:true,  moe:false,             mmlu:92.5,gpqa:87.0,sweben:80.0,aime:98.0,speed:25, input_price:2.50, output_price:10.00,context:1000, type:"closed"},
  {name:"GPT-5.2",             provider:"OpenAI",    params:200, est:true,  moe:false,             mmlu:91.0,gpqa:85.0,sweben:78.0,aime:97.0,speed:35, input_price:1.75, output_price:14.00,context:128,  type:"closed"},
  {name:"GPT-5 mini",          provider:"OpenAI",    params:30,  est:true,  moe:false,             mmlu:85.0,gpqa:72.0,sweben:70.0,aime:85.0,speed:100,input_price:0.25, output_price:2.00, context:200,  type:"closed"},
  {name:"GPT-5 nano",          provider:"OpenAI",    params:8,   est:true,  moe:false,             mmlu:78.0,gpqa:60.0,sweben:58.0,aime:70.0,speed:160,input_price:0.05, output_price:0.40, context:128,  type:"closed"},
  {name:"Claude Opus 4.7",     provider:"Anthropic", params:200, est:true,  moe:false,             mmlu:92.0,gpqa:91.3,sweben:87.6,aime:96.0,speed:22, input_price:5.00, output_price:25.00,context:1000, type:"closed"},
  {name:"Claude Opus 4.6",     provider:"Anthropic", params:200, est:true,  moe:false,             mmlu:91.0,gpqa:89.0,sweben:80.8,aime:94.0,speed:25, input_price:5.00, output_price:25.00,context:200,  type:"closed"},
  {name:"Claude Sonnet 4.6",   provider:"Anthropic", params:70,  est:true,  moe:false,             mmlu:88.7,gpqa:84.0,sweben:79.6,aime:88.0,speed:55, input_price:3.00, output_price:15.00,context:1000, type:"closed"},
  {name:"Claude Haiku 4.5",    provider:"Anthropic", params:13,  est:true,  moe:false,             mmlu:80.0,gpqa:68.0,sweben:62.0,aime:72.0,speed:185,input_price:0.25, output_price:1.25, context:200,  type:"closed"},
  {name:"Gemini 3.1 Pro",      provider:"Google",    params:200, est:true,  moe:false,             mmlu:92.0,gpqa:94.3,sweben:80.6,aime:96.0,speed:80, input_price:2.00, output_price:12.00,context:2000, type:"closed"},
  {name:"Gemini 3 Flash",      provider:"Google",    params:30,  est:true,  moe:false,             mmlu:87.0,gpqa:78.0,sweben:78.0,aime:85.0,speed:250,input_price:0.50, output_price:3.00, context:1000, type:"closed"},
  {name:"Gemini 2.5 Pro",      provider:"Google",    params:100, est:true,  moe:false,             mmlu:89.0,gpqa:88.0,sweben:75.0,aime:92.0,speed:100,input_price:1.25, output_price:10.00,context:2000, type:"closed"},
  {name:"Gemini 2.5 Flash",    provider:"Google",    params:30,  est:true,  moe:false,             mmlu:85.0,gpqa:77.0,sweben:72.0,aime:82.0,speed:347,input_price:0.30, output_price:1.50, context:1000, type:"closed"},
  {name:"Gemini 2.5 Flash-Lite",provider:"Google",   params:10,  est:true,  moe:false,             mmlu:80.0,gpqa:65.0,sweben:60.0,aime:72.0,speed:400,input_price:0.10, output_price:0.40, context:1000, type:"closed"},
  {name:"Gemma 4 31B",         provider:"Google",    params:31,  est:false, moe:false,             mmlu:83.0,gpqa:84.3,sweben:70.0,aime:89.2,speed:90, input_price:0.03, output_price:0.09, context:256,  type:"open"},
  {name:"Gemma 3n E4B",        provider:"Google",    params:4,   est:false, moe:false,             mmlu:72.0,gpqa:55.0,sweben:44.0,aime:52.0,speed:300,input_price:0.02, output_price:0.06, context:32,   type:"open"},
  {name:"Grok 4",              provider:"xAI",       params:314, est:true,  moe:false,             mmlu:91.5,gpqa:88.0,sweben:79.0,aime:97.0,speed:30, input_price:3.00, output_price:15.00,context:256,  type:"closed"},
  {name:"Llama 4 Maverick",    provider:"Meta",      params:400, est:false, moe:true, ap:17,       mmlu:88.0,gpqa:82.3,sweben:73.0,aime:86.0,speed:80, input_price:0.20, output_price:0.80, context:1000, type:"open"},
  {name:"Llama 4 Scout",       provider:"Meta",      params:109, est:false, moe:true, ap:17,       mmlu:83.0,gpqa:69.0,sweben:62.0,aime:78.0,speed:200,input_price:0.11, output_price:0.34, context:10000,type:"open"},
  {name:"Llama 3.3 70B",       provider:"Meta",      params:70,  est:false, moe:false,             mmlu:86.0,gpqa:71.0,sweben:68.0,aime:78.0,speed:50, input_price:0.35, output_price:0.40, context:128,  type:"open"},
  {name:"DeepSeek V4",         provider:"DeepSeek",  params:1000,est:false, moe:true, ap:32,       mmlu:91.0,gpqa:90.1,sweben:80.6,aime:90.0,speed:40, input_price:0.14, output_price:0.30, context:1000, type:"open"},
  {name:"DeepSeek V3.2",       provider:"DeepSeek",  params:671, est:false, moe:true, ap:37,       mmlu:91.0,gpqa:81.0,sweben:78.0,aime:90.0,speed:40, input_price:0.28, output_price:0.42, context:128,  type:"open"},
  {name:"DeepSeek R1",         provider:"DeepSeek",  params:671, est:false, moe:false,             mmlu:90.8,gpqa:83.0,sweben:77.0,aime:97.3,speed:20, input_price:0.55, output_price:2.19, context:128,  type:"open"},
  {name:"Kimi K2.6",           provider:"Moonshot",  params:1000,est:false, moe:true, ap:32,       mmlu:88.0,gpqa:90.5,sweben:80.2,aime:96.4,speed:45, input_price:0.95, output_price:3.00, context:256,  type:"open"},
  {name:"GLM-5.1",             provider:"Z.AI",      params:744, est:false, moe:true, ap:40,       mmlu:89.0,gpqa:83.0,sweben:77.8,aime:92.0,speed:55, input_price:0.10, output_price:0.30, context:200,  type:"open"},
  {name:"MiniMax M2.5",        provider:"MiniMax",   params:200, est:true,  moe:false,             mmlu:87.0,gpqa:78.0,sweben:80.2,aime:82.0,speed:60, input_price:0.30, output_price:1.20, context:128,  type:"open"},
  {name:"Qwen3.5 Plus",        provider:"Alibaba",   params:235, est:false, moe:true, ap:22,       mmlu:90.0,gpqa:85.0,sweben:76.0,aime:93.0,speed:55, input_price:0.50, output_price:1.50, context:128,  type:"open"},
  {name:"Qwen3.5 32B",         provider:"Alibaba",   params:32,  est:false, moe:false,             mmlu:86.0,gpqa:80.0,sweben:72.0,aime:88.0,speed:85, input_price:0.10, output_price:0.30, context:128,  type:"open"},
  {name:"Qwen3.5 9B",          provider:"Alibaba",   params:9,   est:false, moe:false,             mmlu:84.0,gpqa:81.7,sweben:65.0,aime:83.2,speed:130,input_price:0.05, output_price:0.15, context:128,  type:"open"},
  {name:"Qwen3.5 4B",          provider:"Alibaba",   params:4,   est:false, moe:false,             mmlu:80.0,gpqa:72.0,sweben:57.0,aime:74.0,speed:200,input_price:0.03, output_price:0.09, context:128,  type:"open"},
  {name:"Qwen3.5 2B",          provider:"Alibaba",   params:2,   est:false, moe:false,             mmlu:74.0,gpqa:62.0,sweben:48.0,aime:62.0,speed:345,input_price:0.02, output_price:0.06, context:128,  type:"open"},
  {name:"Mistral Large 3",     provider:"Mistral",   params:130, est:true,  moe:false,             mmlu:86.0,gpqa:78.0,sweben:68.0,aime:80.0,speed:50, input_price:2.00, output_price:6.00, context:128,  type:"open"},
  {name:"Mistral Medium 3.5",  provider:"Mistral",   params:128, est:true,  moe:false,             mmlu:84.0,gpqa:75.0,sweben:77.6,aime:78.0,speed:70, input_price:0.40, output_price:1.20, context:128,  type:"open"},
  {name:"Mistral Small 4",     provider:"Mistral",   params:22,  est:true,  moe:false,             mmlu:80.0,gpqa:65.0,sweben:58.0,aime:68.0,speed:100,input_price:0.10, output_price:0.30, context:128,  type:"open"},
  {name:"Phi-4",               provider:"Microsoft", params:14,  est:false, moe:false,             mmlu:84.8,gpqa:72.0,sweben:63.0,aime:75.0,speed:90, input_price:0.07, output_price:0.28, context:16,   type:"open"},
  {name:"Granite 3.3 8B",      provider:"IBM",       params:8,   est:false, moe:false,             mmlu:74.0,gpqa:58.0,sweben:50.0,aime:60.0,speed:387,input_price:0.05, output_price:0.15, context:128,  type:"open"}
];

let activeView='benchmarks',activeBench='mmlu',priceType='input',typeFilter='all',sortAsc=false;
let providerFilter=Object.keys(PROVIDERS).reduce((a,k)=>{a[k]=true;return a},{});

const BENCH_LABELS={mmlu:'MMLU (%)',gpqa:'GPQA Diamond (%)',sweben:'SWE-bench Verified (%)',aime:'AIME 2025 (%)'};
const BENCH_TITLES={
  mmlu:'Model Parameters vs MMLU Score (general knowledge)',
  gpqa:'Model Parameters vs GPQA Diamond (PhD-level science)',
  sweben:'Model Parameters vs SWE-bench Verified (real coding tasks)',
  aime:'Model Parameters vs AIME 2025 (math olympiad)'
};

function getFiltered(){
  return MODELS.filter(m=>(typeFilter==='all'||m.type===typeFilter)&&providerFilter[m.provider]);
}

function hov(m,yKey,yLabel){
  const ps=m.est?`${m.params}B (est.†)`:m.moe?`${m.params}B total / ${m.ap}B active (MoE)`:`${m.params}B`;
  return[
    `<b style="color:#f5a623">${m.name}</b>`,
    `${m.provider} · ${m.type}${m.moe?' · MoE':''}`,
    `Params: ${ps}`,
    `${yLabel}: <b>${m[yKey]}</b>`,
    `MMLU ${m.mmlu} · GPQA ${m.gpqa} · SWE ${m.sweben} · AIME ${m.aime}`,
    `Speed: ${m.speed} t/s · $${m.input_price}/$${m.output_price} per 1M · Ctx: ${m.context}K`
  ].join('<br>');
}

function blo(yLabel,yRange,xType='log'){
  return{
    paper_bgcolor:'rgba(0,0,0,0)',plot_bgcolor:'rgba(0,0,0,0)',
    font:{family:"'JetBrains Mono',monospace",color:'#7a7f96',size:11},
    xaxis:{showgrid:true,gridcolor:'#1c1f27',zeroline:false,showline:true,linecolor:'#2a2d38',
      tickfont:{color:'#7a7f96',size:10},type:xType,
      title:{text:'Parameter Count (Billions) — Log Scale',font:{color:'#7a7f96',size:11},standoff:10}},
    yaxis:{showgrid:true,gridcolor:'#1c1f27',zeroline:false,showline:true,linecolor:'#2a2d38',
      tickfont:{color:'#7a7f96',size:10},range:yRange,
      title:{text:yLabel,font:{color:'#7a7f96',size:11},standoff:10}},
    legend:{bgcolor:'rgba(19,21,26,0.9)',bordercolor:'#2a2d38',borderwidth:1,font:{color:'#7a7f96',size:10}},
    margin:{l:62,r:18,t:18,b:52},
    hoverlabel:{bgcolor:'#13151a',bordercolor:'#383c4a',font:{family:"'JetBrains Mono',monospace",color:'#e8eaf0',size:11}},
    hovermode:'closest',showlegend:true
  };
}
const CFG={responsive:true,displayModeBar:false};

function mkTraces(data,yKey,yLabel){
  const byP={};
  data.forEach(m=>{if(!byP[m.provider])byP[m.provider]=[];byP[m.provider].push(m);});
  return Object.entries(byP).map(([p,ms])=>({
    name:p,type:'scatter',mode:'markers',
    x:ms.map(m=>m.params),y:ms.map(m=>m[yKey]),
    hovertemplate:ms.map(m=>hov(m,yKey,yLabel)+'<extra></extra>'),
    marker:{color:PROVIDERS[p].color,size:ms.map(m=>m.moe?14:11),
      symbol:ms.map(m=>m.moe?'diamond':'circle'),
      line:{color:'rgba(0,0,0,0.35)',width:1},opacity:0.9}
  }));
}

function drawBenchmarks(){Plotly.react('chart-benchmarks',mkTraces(getFiltered(),activeBench,BENCH_LABELS[activeBench]),blo(BENCH_LABELS[activeBench],[20,100]),CFG);}
function drawSpeed(){Plotly.react('chart-speed',mkTraces(getFiltered(),'speed','Tokens/sec'),blo('Generation Speed (tokens/sec)',[0,430]),CFG);}
function drawPrice(){
  const pk=priceType==='input'?'input_price':'output_price';
  const pl=priceType==='input'?'Input Price ($/1M tokens)':'Output Price ($/1M tokens)';
  const lo=blo(pl+' — Log Scale',null);lo.yaxis.type='log';
  Plotly.react('chart-price',mkTraces(getFiltered(),pk,pl),lo,CFG);
}
function drawEfficiency(){
  const data=getFiltered();
  const byP={};data.forEach(m=>{if(!byP[m.provider])byP[m.provider]=[];byP[m.provider].push(m);});
  const traces=Object.entries(byP).map(([p,ms])=>({
    name:p,type:'scatter',mode:'markers+text',
    x:ms.map(m=>m.input_price),y:ms.map(m=>m.gpqa),
    text:ms.map(m=>m.name.length>16?m.name.slice(0,14)+'…':m.name),
    textposition:'top center',textfont:{color:'#7a7f96',size:8},
    hovertemplate:ms.map(m=>hov(m,'gpqa','GPQA Diamond')+'<extra></extra>'),
    marker:{color:PROVIDERS[p].color,
      size:ms.map(m=>Math.max(9,Math.min(28,Math.log2(Math.max(m.params,1))*3))),
      symbol:ms.map(m=>m.moe?'diamond':'circle'),
      line:{color:'rgba(0,0,0,0.35)',width:1},opacity:0.85,sizemode:'diameter'}
  }));
  const lo={...blo('GPQA Diamond (%)',[50,97],'log'),
    xaxis:{type:'log',showgrid:true,gridcolor:'#1c1f27',zeroline:false,showline:true,linecolor:'#2a2d38',
      tickfont:{color:'#7a7f96',size:10},
      title:{text:'Input Price ($/1M tokens) — Log Scale',font:{color:'#7a7f96',size:11},standoff:10},
      range:[Math.log10(0.015),Math.log10(55)]}};
  lo.margin={l:62,r:18,t:28,b:52};
  Plotly.react('chart-efficiency',traces,lo,CFG);
}
function drawAllCharts(){
  if(activeView==='benchmarks')drawBenchmarks();
  else if(activeView==='speed')drawSpeed();
  else if(activeView==='price')drawPrice();
  else if(activeView==='efficiency')drawEfficiency();
}

function renderTable(){
  const q=(document.getElementById('search-input').value||'').toLowerCase();
  const col=document.getElementById('sort-col').value;
  let data=getFiltered().filter(m=>m.name.toLowerCase().includes(q)||m.provider.toLowerCase().includes(q));
  data.sort((a,b)=>{const av=a[col],bv=b[col];if(typeof av==='string')return sortAsc?av.localeCompare(bv):bv.localeCompare(av);return sortAsc?av-bv:bv-av;});
  document.getElementById('table-body').innerHTML=data.map(m=>{
    const c=PROVIDERS[m.provider].color;
    const ps=m.est?`${m.params}<span class="td-est">†</span>`:m.moe?`${m.params}<span class="td-est"> (${m.ap}a)</span>`:m.params;
    return`<tr>
      <td class="td-name">${m.name}</td>
      <td class="td-provider" style="color:${c}">${m.provider}</td>
      <td><span class="${m.type==='open'?'td-open':'td-closed'}">${m.type}</span>${m.moe?'<span class="td-moe">MoE</span>':''}</td>
      <td class="mono">${ps}</td>
      <td class="mono">${m.mmlu}</td>
      <td class="td-score">${m.gpqa}<span class="score-bar" style="width:${m.gpqa*0.44}px"></span></td>
      <td class="mono">${m.sweben}</td>
      <td class="mono">${m.aime}</td>
      <td class="mono">${m.speed}</td>
      <td class="mono">$${m.input_price}</td>
      <td class="mono">$${m.output_price}</td>
      <td class="mono">${m.context}K</td>
    </tr>`;
  }).join('');
  document.getElementById('model-count').textContent=data.length;
}

function sortTable(col){
  if(document.getElementById('sort-col').value===col)sortAsc=!sortAsc;
  else{document.getElementById('sort-col').value=col;sortAsc=false;}
  renderTable();
}

function buildProviderFilters(){
  const counts={};MODELS.forEach(m=>counts[m.provider]=(counts[m.provider]||0)+1);
  document.getElementById('provider-filters').innerHTML=Object.keys(PROVIDERS).map(p=>`
    <div class="filter-item" onclick="toggleProvider('${p}')">
      <div class="filter-check checked" id="chk-${p}">✓</div>
      <div class="filter-dot" style="background:${PROVIDERS[p].color}"></div>
      <span>${p}</span><span class="filter-count">${counts[p]||0}</span>
    </div>`).join('');
}

function toggleProvider(p){
  providerFilter[p]=!providerFilter[p];
  const el=document.getElementById(`chk-${p}`);
  el.classList.toggle('checked',providerFilter[p]);el.textContent=providerFilter[p]?'✓':'';
  drawAllCharts();if(activeView==='table')renderTable();
}

function setView(v,el){
  activeView=v;
  document.querySelectorAll('.nav-item').forEach(n=>n.classList.remove('active'));
  if(el)el.classList.add('active');
  document.querySelectorAll('.view,.table-view').forEach(e=>e.classList.remove('active'));
  document.getElementById(`view-${v}`).classList.add('active');
  document.getElementById('bench-section').style.display=v==='benchmarks'?'':'none';
  document.getElementById('price-section').style.display=v==='price'?'':'none';
  if(v==='table')renderTable();else setTimeout(drawAllCharts,0);
}

function setBench(b,el){
  activeBench=b;
  document.querySelectorAll('.bench-btn').forEach(e=>e.classList.remove('active'));
  if(el)el.classList.add('active');
  document.getElementById('bench-chart-title').textContent=BENCH_TITLES[b];
  drawBenchmarks();
}

function setPriceType(t,el){
  priceType=t;
  document.querySelectorAll('#price-section .toggle-btn').forEach(e=>e.classList.remove('active'));
  if(el)el.classList.add('active');
  const lbl=t==='input'?'Input Price ($/1M tokens)':'Output Price ($/1M tokens)';
  document.getElementById('price-chart-title').textContent=`Model Parameters vs ${lbl}`;
  drawPrice();
}

function setTypeFilter(t){
  typeFilter=t;
  ['all','open','closed'].forEach(id=>document.getElementById(`type-${id}`).classList.toggle('active',id===t));
  drawAllCharts();if(activeView==='table')renderTable();
}

buildProviderFilters();
drawBenchmarks();

window.addEventListener('resize',()=>{
  if(activeView!=='table'){const el=document.getElementById(`chart-${activeView}`);if(el)Plotly.Plots.resize(el);}
});
</script>
</body>
</html>