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Browse files- icon_assets/deepseek-color.svg +1 -0
- index.html +164 -53
- main.js +4 -2
- style.css +89 -13
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<p class="subtitle">Strategic Prompting, Agentic Workflows & Tooling</p>
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<p class="tagline">Practical approaches, templates, and decisions for frontend delivery</p>
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<div class="logo-row">
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<div class="logo-wrapper"><img src="../icon_assets/Google_Gemini_icon_2025.svg" alt="Gemini"
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class="logo-icon" title="Gemini"></div>
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<div class="logo-wrapper light-bg"><img src="../icon_assets/Anthropic Symbol SVG.svg"
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alt="Claude" class="logo-icon" title="Claude"></div>
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<div class="logo-wrapper"><img src="../icon_assets/Vscode.svg" alt="VS Code" class="logo-icon"
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title="VS Code"></div>
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<div class="logo-wrapper light-bg"><img src="../icon_assets/cursor.svg" alt="Cursor"
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class="logo-icon" title="Cursor"></div>
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<h2 class="slide-title">LLM Platforms & Your Preference</h2>
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<p class="slide-subtitle">Click to vote for your preferred LLM!</p>
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<div class="llm-card voting-card" data-llm="openai">
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<div class="llm-header">
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<div class="logo-wrapper light-bg"><img src="../icon_assets/OpenAI Symbol SVG.svg"
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alt="OpenAI" class="llm-icon"></div>
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<h3>OpenAI
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<div class="llm-header">
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<div class="logo-wrapper"><img src="../icon_assets/Google_Gemini_icon_2025.svg"
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alt="Gemini" class="llm-icon"></div>
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<h3>Google
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<span class="vote-count">0 votes</span>
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<div class="logo-wrapper"><span class="text-logo">+</span></div>
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<h3>Other / Local</h3>
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<p>Ollama, custom
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<!-- ==================== SLIDE 7: LLM Versions & Benchmarks ==================== -->
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<h2 class="slide-title">LLM
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<th>Best For</th>
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<div class="logo-wrapper-small light-bg"><img
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src="../icon_assets/Anthropic Symbol SVG.svg" alt="Anthropic"
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class="table-icon"></div>
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<strong>Claude Sonnet 4</strong>
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</tr>
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<strong>Gemini 2.5 Pro</strong>
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</tr>
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<div class="model-cell">
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<a href="https://www.swebench.com/" target="_blank" class="kpi-link">
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<span class="kpi-icon">🎯</span>
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<span>SWE-Bench</span>
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<small>Agentic coding
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</a>
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<a href="https://lmarena.ai/leaderboard" target="_blank" class="kpi-link">
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<span class="kpi-icon">🏆</span>
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<span>LLM Arena</span>
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<small>Community
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</a>
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<a href="https://
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<small>Open source models</small>
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</a>
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</div>
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</div>
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<p class="subtitle">Strategic Prompting, Agentic Workflows & Tooling</p>
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<p class="tagline">Practical approaches, templates, and decisions for frontend delivery</p>
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<div class="logo-row">
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<!-- LLM Icons -->
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<div class="logo-wrapper light-bg"><img src="../icon_assets/OpenAI Symbol SVG.svg" alt="OpenAI"
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class="logo-icon" title="OpenAI / ChatGPT"></div>
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<div class="logo-wrapper"><img src="../icon_assets/Google_Gemini_icon_2025.svg" alt="Gemini"
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class="logo-icon" title="Google Gemini"></div>
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<div class="logo-wrapper light-bg"><img src="../icon_assets/Anthropic Symbol SVG.svg"
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alt="Claude" class="logo-icon" title="Claude"></div>
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<div class="logo-wrapper light-bg"><img src="../icon_assets/X Symbol SVG.svg" alt="Grok"
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class="logo-icon" title="Grok"></div>
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<div class="logo-wrapper"><img src="../icon_assets/mistral-color.svg" alt="Mistral"
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class="logo-icon" title="Mistral"></div>
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<div class="logo-wrapper"><img src="../icon_assets/kimi.svg" alt="Kimi" class="logo-icon"
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title="Kimi K2"></div>
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<div class="logo-wrapper"><img src="../icon_assets/meta-color.svg" alt="Meta" class="logo-icon"
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title="Meta Llama"></div>
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<!-- Editor Icons -->
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<div class="logo-wrapper"><img src="../icon_assets/Vscode.svg" alt="VS Code" class="logo-icon"
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title="VS Code"></div>
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<div class="logo-wrapper light-bg"><img src="../icon_assets/cursor.svg" alt="Cursor"
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class="logo-icon" title="Cursor"></div>
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<div class="logo-wrapper"><img src="../icon_assets/antigravity.png" alt="Antigravity"
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class="logo-icon" title="Antigravity"></div>
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</div>
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</div>
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</section>
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<h2 class="slide-title">LLM Platforms & Your Preference</h2>
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<p class="slide-subtitle">Click to vote for your preferred LLM!</p>
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<div class="llm-platforms-grid compact">
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<div class="llm-card voting-card" data-llm="anthropic">
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<div class="llm-header">
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<div class="logo-wrapper light-bg"><img src="../icon_assets/Anthropic Symbol SVG.svg"
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alt="Anthropic" class="llm-icon"></div>
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<h3>Claude (Anthropic)</h3>
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</div>
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<p>Best agentic reasoning</p>
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<div class="vote-bar">
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<div class="vote-fill" data-votes="0"></div>
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</div>
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<span class="vote-count">0 votes</span>
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</div>
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<div class="llm-card voting-card" data-llm="openai">
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<div class="llm-header">
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<div class="logo-wrapper light-bg"><img src="../icon_assets/OpenAI Symbol SVG.svg"
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alt="OpenAI" class="llm-icon"></div>
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<h3>GPT (OpenAI)</h3>
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</div>
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<p>Reliable, wide ecosystem</p>
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<div class="vote-bar">
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<div class="vote-fill" data-votes="0"></div>
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</div>
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<div class="llm-header">
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<div class="logo-wrapper"><img src="../icon_assets/Google_Gemini_icon_2025.svg"
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alt="Gemini" class="llm-icon"></div>
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<h3>Gemini (Google)</h3>
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</div>
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<p>All-around champion</p>
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<div class="vote-bar">
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<div class="vote-fill" data-votes="0"></div>
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<span class="vote-count">0 votes</span>
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<div class="llm-card voting-card" data-llm="grok">
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<div class="logo-wrapper light-bg"><img src="../icon_assets/X Symbol SVG.svg" alt="Grok"
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<h3>Grok (xAI)</h3>
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<p>Strong reasoning</p>
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<div class="vote-fill" data-votes="0"></div>
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<span class="vote-count">0 votes</span>
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<div class="llm-card voting-card" data-llm="mistral">
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<div class="llm-header">
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<div class="logo-wrapper"><img src="../icon_assets/mistral-color.svg" alt="Mistral"
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class="llm-icon"></div>
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<h3>Mistral</h3>
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</div>
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<p>Large context, efficient</p>
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<div class="vote-bar">
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<div class="vote-fill" data-votes="0"></div>
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<span class="vote-count">0 votes</span>
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<div class="llm-card voting-card" data-llm="kimi">
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<div class="llm-header">
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<div class="logo-wrapper"><img src="../icon_assets/kimi.svg" alt="Kimi"
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<h3>Kimi K2</h3>
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</div>
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<p>99.1% non-agentic coding</p>
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<div class="llm-card voting-card" data-llm="deepseek">
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<div class="logo-wrapper"><span class="text-logo">DS</span></div>
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<h3>DeepSeek V3</h3>
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<p>Open-source, popular</p>
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<div class="logo-wrapper"><span class="text-logo">+</span></div>
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<h3>Other / Local</h3>
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</div>
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<p>Ollama, Llama, custom</p>
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<!-- ==================== SLIDE 7: LLM Versions & Benchmarks ==================== -->
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<section class="slide" data-slide="7">
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<div class="slide-content">
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<h2 class="slide-title">LLM Benchmark Comparison (2025)</h2>
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<p class="slide-subtitle">SWE-Bench Agentic Scores & Recommended Use Cases</p>
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<div class="benchmark-table-container">
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<thead>
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<tr>
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<th>Model</th>
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<th>Key Strength</th>
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<th>Score</th>
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<th>Best For</th>
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<div class="logo-wrapper-small light-bg"><img
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src="../icon_assets/Anthropic Symbol SVG.svg" alt="Anthropic"
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class="table-icon"></div>
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<strong>Claude Sonnet 4.5</strong>
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<td>Best for real-world agents, 30hr+ autonomous tasks</td>
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<td class="score-cell"><span class="score-badge high">82%</span></td>
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<td>Autonomous bug resolution, agent orchestration</td>
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src="../icon_assets/Anthropic Symbol SVG.svg" alt="Anthropic"
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<strong>Claude Opus 4.5</strong>
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</td>
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<td>Complex reasoning, 200K context</td>
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| 463 |
+
<td class="score-cell"><span class="score-badge high">80.9%</span></td>
|
| 464 |
+
<td>Architectural planning, deep code review</td>
|
| 465 |
+
</tr>
|
| 466 |
+
<tr>
|
| 467 |
+
<td>
|
| 468 |
+
<div class="model-cell">
|
| 469 |
+
<div class="logo-wrapper-small light-bg"><img
|
| 470 |
+
src="../icon_assets/OpenAI Symbol SVG.svg" alt="OpenAI"
|
| 471 |
+
class="table-icon"></div>
|
| 472 |
+
<strong>GPT 5.1</strong>
|
| 473 |
+
</div>
|
| 474 |
+
</td>
|
| 475 |
+
<td>Reliable code gen, wide ecosystem</td>
|
| 476 |
+
<td class="score-cell"><span class="score-badge medium">76.3%</span></td>
|
| 477 |
+
<td>API gen, high-volume code completion</td>
|
| 478 |
+
</tr>
|
| 479 |
+
<tr>
|
| 480 |
+
<td>
|
| 481 |
+
<div class="model-cell">
|
| 482 |
+
<div class="logo-wrapper-small"><img
|
| 483 |
+
src="../icon_assets/Google_Gemini_icon_2025.svg" alt="Gemini"
|
| 484 |
+
class="table-icon"></div>
|
| 485 |
+
<strong>Gemini 3 Pro</strong>
|
| 486 |
+
</div>
|
| 487 |
+
</td>
|
| 488 |
+
<td>Highest overall, Z-Score 1.38</td>
|
| 489 |
+
<td class="score-cell"><span class="score-badge medium">76.2%</span></td>
|
| 490 |
+
<td>General dev, multimodal apps</td>
|
| 491 |
+
</tr>
|
| 492 |
+
<tr>
|
| 493 |
+
<td>
|
| 494 |
+
<div class="model-cell">
|
| 495 |
+
<div class="logo-wrapper-small light-bg"><img
|
| 496 |
+
src="../icon_assets/X Symbol SVG.svg" alt="Grok"
|
| 497 |
+
class="table-icon"></div>
|
| 498 |
+
<strong>Grok 4</strong>
|
| 499 |
+
</div>
|
| 500 |
+
</td>
|
| 501 |
+
<td>Strong reasoning, complex problem-solving</td>
|
| 502 |
+
<td class="score-cell"><span class="score-badge medium">75%</span></td>
|
| 503 |
+
<td>Code planning, robustness-critical tasks</td>
|
| 504 |
</tr>
|
| 505 |
<tr>
|
| 506 |
<td>
|
|
|
|
| 511 |
<strong>Gemini 2.5 Pro</strong>
|
| 512 |
</div>
|
| 513 |
</td>
|
| 514 |
+
<td>All-around champion, highest Z-score</td>
|
| 515 |
+
<td class="score-cell"><span class="score-badge">Z: 1.38</span></td>
|
| 516 |
+
<td>Reliable general-purpose dev</td>
|
| 517 |
+
</tr>
|
| 518 |
+
<tr>
|
| 519 |
+
<td>
|
| 520 |
+
<div class="model-cell">
|
| 521 |
+
<div class="logo-wrapper-small"><img src="../icon_assets/kimi.svg"
|
| 522 |
+
alt="Kimi" class="table-icon"></div>
|
| 523 |
+
<strong>Kimi K2 Thinking</strong>
|
| 524 |
+
</div>
|
| 525 |
+
</td>
|
| 526 |
+
<td>Non-agentic coding expert</td>
|
| 527 |
+
<td class="score-cell"><span class="score-badge high">99.1%*</span></td>
|
| 528 |
+
<td>Specialized non-agentic tasks</td>
|
| 529 |
+
</tr>
|
| 530 |
+
<tr>
|
| 531 |
+
<td>
|
| 532 |
+
<div class="model-cell">
|
| 533 |
+
<div class="logo-wrapper-small"><img
|
| 534 |
+
src="../icon_assets/mistral-color.svg" alt="Mistral"
|
| 535 |
+
class="table-icon"></div>
|
| 536 |
+
<strong>Mistral Large 3</strong>
|
| 537 |
+
</div>
|
| 538 |
+
</td>
|
| 539 |
+
<td>Top-tier reasoning, 32K context</td>
|
| 540 |
+
<td class="score-cell"><span class="score-badge">Top-Tier</span></td>
|
| 541 |
+
<td>Multilingual, function calling</td>
|
| 542 |
</tr>
|
| 543 |
<tr>
|
| 544 |
<td>
|
| 545 |
<div class="model-cell">
|
| 546 |
<div class="logo-wrapper-small light-bg"><img
|
| 547 |
+
src="../icon_assets/Anthropic Symbol SVG.svg" alt="Anthropic"
|
| 548 |
class="table-icon"></div>
|
| 549 |
+
<strong>Claude 3.5 Sonnet</strong>
|
| 550 |
</div>
|
| 551 |
</td>
|
| 552 |
+
<td>Versatile, speed + cost optimized</td>
|
| 553 |
+
<td class="score-cell"><span class="score-badge">High</span></td>
|
| 554 |
+
<td>Enterprise, cost-optimized agents</td>
|
| 555 |
</tr>
|
| 556 |
<tr>
|
| 557 |
<td>
|
| 558 |
<div class="model-cell">
|
| 559 |
+
<div class="logo-wrapper-small"><span class="mini-text-logo">DS</span>
|
| 560 |
</div>
|
| 561 |
+
<strong>DeepSeek V3</strong>
|
| 562 |
</div>
|
| 563 |
</td>
|
| 564 |
+
<td>Open-source, popular foundation</td>
|
| 565 |
+
<td class="score-cell"><span class="score-badge">N/A</span></td>
|
| 566 |
+
<td>Code gen, fine-tuning</td>
|
| 567 |
</tr>
|
| 568 |
</tbody>
|
| 569 |
</table>
|
| 570 |
+
<p class="table-note">* Non-agentic benchmark score</p>
|
| 571 |
</div>
|
| 572 |
|
| 573 |
<div class="kpi-links">
|
|
|
|
| 576 |
<a href="https://www.swebench.com/" target="_blank" class="kpi-link">
|
| 577 |
<span class="kpi-icon">🎯</span>
|
| 578 |
<span>SWE-Bench</span>
|
| 579 |
+
<small>Agentic coding</small>
|
| 580 |
</a>
|
| 581 |
<a href="https://lmarena.ai/leaderboard" target="_blank" class="kpi-link">
|
| 582 |
<span class="kpi-icon">🏆</span>
|
| 583 |
<span>LLM Arena</span>
|
| 584 |
+
<small>Community</small>
|
| 585 |
</a>
|
| 586 |
+
<a href="https://www.vellum.ai/llm-leaderboard" target="_blank" class="kpi-link">
|
| 587 |
+
<span class="kpi-icon">📈</span>
|
| 588 |
+
<span>Vellum AI</span>
|
| 589 |
+
<small>Full comparison</small>
|
|
|
|
| 590 |
</a>
|
| 591 |
</div>
|
| 592 |
</div>
|
main.js
CHANGED
|
@@ -14,11 +14,13 @@
|
|
| 14 |
|
| 15 |
// Voting state
|
| 16 |
const llmVotes = {
|
|
|
|
| 17 |
openai: 0,
|
| 18 |
gemini: 0,
|
| 19 |
-
|
| 20 |
-
meta: 0,
|
| 21 |
mistral: 0,
|
|
|
|
|
|
|
| 22 |
other: 0
|
| 23 |
};
|
| 24 |
|
|
|
|
| 14 |
|
| 15 |
// Voting state
|
| 16 |
const llmVotes = {
|
| 17 |
+
anthropic: 0,
|
| 18 |
openai: 0,
|
| 19 |
gemini: 0,
|
| 20 |
+
grok: 0,
|
|
|
|
| 21 |
mistral: 0,
|
| 22 |
+
kimi: 0,
|
| 23 |
+
deepseek: 0,
|
| 24 |
other: 0
|
| 25 |
};
|
| 26 |
|
style.css
CHANGED
|
@@ -829,11 +829,12 @@ body {
|
|
| 829 |
.benchmarks-section {
|
| 830 |
display: flex;
|
| 831 |
flex-direction: column;
|
| 832 |
-
gap:
|
| 833 |
}
|
| 834 |
|
| 835 |
.benchmark-table-container {
|
| 836 |
overflow-x: auto;
|
|
|
|
| 837 |
}
|
| 838 |
|
| 839 |
.benchmark-table {
|
|
@@ -898,34 +899,108 @@ body {
|
|
| 898 |
color: white;
|
| 899 |
}
|
| 900 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 901 |
.kpi-links {
|
| 902 |
background: var(--bg-card);
|
| 903 |
border: 1px solid var(--border-color);
|
| 904 |
-
border-radius:
|
| 905 |
-
padding:
|
| 906 |
}
|
| 907 |
|
| 908 |
.kpi-links h3 {
|
| 909 |
-
font-size:
|
| 910 |
font-weight: 600;
|
| 911 |
-
margin-bottom:
|
| 912 |
}
|
| 913 |
|
| 914 |
.kpi-grid {
|
| 915 |
display: grid;
|
| 916 |
-
grid-template-columns: repeat(
|
| 917 |
-
gap:
|
| 918 |
}
|
| 919 |
|
| 920 |
.kpi-link {
|
| 921 |
display: flex;
|
| 922 |
flex-direction: column;
|
| 923 |
align-items: center;
|
| 924 |
-
gap:
|
| 925 |
-
padding:
|
| 926 |
background: var(--bg-secondary);
|
| 927 |
border: 1px solid var(--border-color);
|
| 928 |
-
border-radius:
|
| 929 |
text-decoration: none;
|
| 930 |
color: var(--text-primary);
|
| 931 |
text-align: center;
|
|
@@ -934,19 +1009,20 @@ body {
|
|
| 934 |
|
| 935 |
.kpi-link:hover {
|
| 936 |
border-color: var(--accent-primary);
|
| 937 |
-
transform: translateY(-
|
| 938 |
}
|
| 939 |
|
| 940 |
.kpi-icon {
|
| 941 |
-
font-size:
|
| 942 |
}
|
| 943 |
|
| 944 |
.kpi-link span {
|
| 945 |
font-weight: 600;
|
|
|
|
| 946 |
}
|
| 947 |
|
| 948 |
.kpi-link small {
|
| 949 |
-
font-size: 0.
|
| 950 |
color: var(--text-muted);
|
| 951 |
}
|
| 952 |
|
|
|
|
| 829 |
.benchmarks-section {
|
| 830 |
display: flex;
|
| 831 |
flex-direction: column;
|
| 832 |
+
gap: 1rem;
|
| 833 |
}
|
| 834 |
|
| 835 |
.benchmark-table-container {
|
| 836 |
overflow-x: auto;
|
| 837 |
+
max-height: 55vh;
|
| 838 |
}
|
| 839 |
|
| 840 |
.benchmark-table {
|
|
|
|
| 899 |
color: white;
|
| 900 |
}
|
| 901 |
|
| 902 |
+
.rank-cell {
|
| 903 |
+
font-size: 1.1rem;
|
| 904 |
+
text-align: center;
|
| 905 |
+
min-width: 40px;
|
| 906 |
+
}
|
| 907 |
+
|
| 908 |
+
.score-cell {
|
| 909 |
+
text-align: center;
|
| 910 |
+
}
|
| 911 |
+
|
| 912 |
+
.score-badge {
|
| 913 |
+
display: inline-block;
|
| 914 |
+
padding: 4px 12px;
|
| 915 |
+
border-radius: 100px;
|
| 916 |
+
font-weight: 600;
|
| 917 |
+
font-size: 0.85rem;
|
| 918 |
+
background: rgba(255, 255, 255, 0.1);
|
| 919 |
+
color: var(--text-secondary);
|
| 920 |
+
}
|
| 921 |
+
|
| 922 |
+
.score-badge.high {
|
| 923 |
+
background: linear-gradient(135deg, rgba(34, 197, 94, 0.2), rgba(34, 197, 94, 0.1));
|
| 924 |
+
color: var(--accent-success);
|
| 925 |
+
border: 1px solid rgba(34, 197, 94, 0.3);
|
| 926 |
+
}
|
| 927 |
+
|
| 928 |
+
.score-badge.medium {
|
| 929 |
+
background: linear-gradient(135deg, rgba(99, 102, 241, 0.2), rgba(139, 92, 246, 0.1));
|
| 930 |
+
color: var(--accent-primary);
|
| 931 |
+
border: 1px solid rgba(99, 102, 241, 0.3);
|
| 932 |
+
}
|
| 933 |
+
|
| 934 |
+
/* Compact table for more rows */
|
| 935 |
+
.benchmark-table.compact-table th,
|
| 936 |
+
.benchmark-table.compact-table td {
|
| 937 |
+
padding: 6px 10px;
|
| 938 |
+
font-size: 0.8rem;
|
| 939 |
+
}
|
| 940 |
+
|
| 941 |
+
.benchmark-table.compact-table .model-cell {
|
| 942 |
+
gap: 6px;
|
| 943 |
+
}
|
| 944 |
+
|
| 945 |
+
.benchmark-table.compact-table .logo-wrapper-small {
|
| 946 |
+
width: 20px;
|
| 947 |
+
height: 20px;
|
| 948 |
+
}
|
| 949 |
+
|
| 950 |
+
.table-note {
|
| 951 |
+
font-size: 0.7rem;
|
| 952 |
+
color: var(--text-muted);
|
| 953 |
+
margin-top: 5px;
|
| 954 |
+
font-style: italic;
|
| 955 |
+
}
|
| 956 |
+
|
| 957 |
+
/* Compact LLM grid for more cards */
|
| 958 |
+
.llm-platforms-grid.compact {
|
| 959 |
+
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
|
| 960 |
+
gap: 15px;
|
| 961 |
+
}
|
| 962 |
+
|
| 963 |
+
.llm-platforms-grid.compact .llm-card {
|
| 964 |
+
padding: 15px;
|
| 965 |
+
}
|
| 966 |
+
|
| 967 |
+
.llm-platforms-grid.compact .llm-header h3 {
|
| 968 |
+
font-size: 0.9rem;
|
| 969 |
+
}
|
| 970 |
+
|
| 971 |
+
.llm-platforms-grid.compact .llm-card>p {
|
| 972 |
+
font-size: 0.75rem;
|
| 973 |
+
margin-bottom: 10px;
|
| 974 |
+
}
|
| 975 |
+
|
| 976 |
.kpi-links {
|
| 977 |
background: var(--bg-card);
|
| 978 |
border: 1px solid var(--border-color);
|
| 979 |
+
border-radius: 12px;
|
| 980 |
+
padding: 12px 15px;
|
| 981 |
}
|
| 982 |
|
| 983 |
.kpi-links h3 {
|
| 984 |
+
font-size: 0.85rem;
|
| 985 |
font-weight: 600;
|
| 986 |
+
margin-bottom: 10px;
|
| 987 |
}
|
| 988 |
|
| 989 |
.kpi-grid {
|
| 990 |
display: grid;
|
| 991 |
+
grid-template-columns: repeat(3, 1fr);
|
| 992 |
+
gap: 10px;
|
| 993 |
}
|
| 994 |
|
| 995 |
.kpi-link {
|
| 996 |
display: flex;
|
| 997 |
flex-direction: column;
|
| 998 |
align-items: center;
|
| 999 |
+
gap: 4px;
|
| 1000 |
+
padding: 10px 8px;
|
| 1001 |
background: var(--bg-secondary);
|
| 1002 |
border: 1px solid var(--border-color);
|
| 1003 |
+
border-radius: 10px;
|
| 1004 |
text-decoration: none;
|
| 1005 |
color: var(--text-primary);
|
| 1006 |
text-align: center;
|
|
|
|
| 1009 |
|
| 1010 |
.kpi-link:hover {
|
| 1011 |
border-color: var(--accent-primary);
|
| 1012 |
+
transform: translateY(-2px);
|
| 1013 |
}
|
| 1014 |
|
| 1015 |
.kpi-icon {
|
| 1016 |
+
font-size: 1.25rem;
|
| 1017 |
}
|
| 1018 |
|
| 1019 |
.kpi-link span {
|
| 1020 |
font-weight: 600;
|
| 1021 |
+
font-size: 0.8rem;
|
| 1022 |
}
|
| 1023 |
|
| 1024 |
.kpi-link small {
|
| 1025 |
+
font-size: 0.65rem;
|
| 1026 |
color: var(--text-muted);
|
| 1027 |
}
|
| 1028 |
|