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@@ -55,108 +55,21 @@ offline-built search index.</p>
 <strong>Llama</strong>, <strong>OpenAI MoE</strong>, plus two 1-bit
 controls.</p>
 <table>
-<thead>
-<tr>
-<th>Model</th>
-<th>Architecture</th>
-<th>Params</th>
-<th>Vindex</th>
-<th>C4 (layer temp)</th>
-<th>Notes</th>
-</tr>
-</thead>
 <tbody>
-<tr>
-<td><strong>Gemma 4 E2B-it</strong></td>
-<td>Dense (Gemma 4)</td>
-<td>2B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/gemma-4-e2b-vindex">gemma-4-e2b-vindex</a></td>
-<td><strong>0.0407 ± 0.0004</strong> ✓</td>
-<td>3-seed validated; headline universal-constant model</td>
-</tr>
-<tr>
-<td>Qwen3-0.6B</td>
-<td>Dense (Qwen 3)</td>
-<td>0.6B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/qwen3-0.6b-vindex">qwen3-0.6b-vindex</a></td>
-<td>0.411</td>
-<td>Smallest published; Qwen3 family-elevated C4</td>
-</tr>
-<tr>
-<td>Qwen3-8B bf16</td>
-<td>Dense (Qwen 3)</td>
-<td>8B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/qwen3-8b-vindex">qwen3-8b-vindex</a></td>
-<td>0.804</td>
-<td>Architecture control for Bonsai</td>
-</tr>
-<tr>
-<td>Qwen3.6-35B-A3B</td>
-<td>MoE (Qwen 3.6)</td>
-<td>35B / 3B active</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/qwen3.6-35b-a3b-vindex">qwen3.6-35b-a3b-vindex</a></td>
-<td>—</td>
-<td>256 experts, 40 layers</td>
-</tr>
-<tr>
-<td>Ministral-3B</td>
-<td>Dense (Mistral 3)</td>
-<td>3B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/ministral-3b-vindex">ministral-3b-vindex</a></td>
-<td>0.265</td>
-<td>fp8 → bf16 reconstruction</td>
-</tr>
-<tr>
-<td>Llama 3.1-8B</td>
-<td>Dense (Llama 3.1)</td>
-<td>8B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/llama-3.1-8b-vindex">llama-3.1-8b-vindex</a></td>
-<td><strong>0.012</strong> ✓</td>
-<td>Llama family signature</td>
-</tr>
-<tr>
-<td>MedGemma 1.5-4B</td>
-<td>Dense (Gemma multimodal)</td>
-<td>4B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/medgemma-1.5-4b-vindex">medgemma-1.5-4b-vindex</a></td>
-<td><strong>1.898 ⚠</strong></td>
-<td>45× cohort anomaly — under investigation</td>
-</tr>
-<tr>
-<td>GPT-OSS 120B</td>
-<td>MoE (OpenAI)</td>
-<td>120B</td>
-<td><a
-href="https://huggingface.co/Divinci-AI/gpt-oss-120b-vindex">gpt-oss-120b-vindex</a></td>
-<td>—</td>
-<td>S[0] grows 117× with depth (L0=111 → final=13,056)</td>
-</tr>
-<tr>
-<td><strong>Bonsai 8B</strong></td>
-<td>1-bit (Qwen 3 base, post-quantized)</td>
-<td>8B</td>
-<td><em>vindex pending publish</em></td>
-<td>0.429</td>
-<td><strong>C5 = 1</strong> (circuit dissolved); var@64 = 0.093</td>
-</tr>
-<tr>
-<td><strong>BitNet b1.58-2B-4T</strong></td>
-<td>1-bit (Microsoft, native)</td>
-<td>2B</td>
-<td><em>vindex pending publish</em></td>
-<td>(Phase 2 pending)</td>
-<td><strong>var@64 = 0.111</strong> mean across 30 layers — n=2
-confirmation of dissolution</td>
-</tr>
+<tr><td><strong>MODEL</strong></td><td><strong>ARCHITECTURE</strong></td><td><strong>PARAMS</strong></td><td><strong>VINDEX</strong></td><td><strong>C4 (LAYER TEMP)</strong></td><td><strong>NOTES</strong></td></tr>
+<tr><td><strong>Gemma 4 E2B-it</strong></td><td>Dense (Gemma 4)</td><td>2B</td><td><a href="https://huggingface.co/Divinci-AI/gemma-4-e2b-vindex">gemma-4-e2b-vindex</a></td><td><strong>0.0407 ± 0.0004</strong> ✓</td><td>3-seed validated; headline universal-constant model</td></tr>
+<tr><td>Qwen3-0.6B</td><td>Dense (Qwen 3)</td><td>0.6B</td><td><a href="https://huggingface.co/Divinci-AI/qwen3-0.6b-vindex">qwen3-0.6b-vindex</a></td><td>0.411</td><td>Smallest published; Qwen3 family-elevated C4</td></tr>
+<tr><td>Qwen3-8B bf16</td><td>Dense (Qwen 3)</td><td>8B</td><td><a href="https://huggingface.co/Divinci-AI/qwen3-8b-vindex">qwen3-8b-vindex</a></td><td>0.804</td><td>Architecture control for Bonsai</td></tr>
+<tr><td>Qwen3.6-35B-A3B</td><td>MoE (Qwen 3.6)</td><td>35B / 3B active</td><td><a href="https://huggingface.co/Divinci-AI/qwen3.6-35b-a3b-vindex">qwen3.6-35b-a3b-vindex</a></td><td>—</td><td>256 experts, 40 layers</td></tr>
+<tr><td>Ministral-3B</td><td>Dense (Mistral 3)</td><td>3B</td><td><a href="https://huggingface.co/Divinci-AI/ministral-3b-vindex">ministral-3b-vindex</a></td><td>0.265</td><td>fp8 → bf16 reconstruction</td></tr>
+<tr><td>Llama 3.1-8B</td><td>Dense (Llama 3.1)</td><td>8B</td><td><a href="https://huggingface.co/Divinci-AI/llama-3.1-8b-vindex">llama-3.1-8b-vindex</a></td><td><strong>0.012</strong> ✓</td><td>Llama family signature</td></tr>
+<tr><td>MedGemma 1.5-4B</td><td>Dense (Gemma multimodal)</td><td>4B</td><td><a href="https://huggingface.co/Divinci-AI/medgemma-1.5-4b-vindex">medgemma-1.5-4b-vindex</a></td><td><strong>1.898 ⚠</strong></td><td>45× cohort anomaly — under investigation</td></tr>
+<tr><td>GPT-OSS 120B</td><td>MoE (OpenAI)</td><td>120B</td><td><a href="https://huggingface.co/Divinci-AI/gpt-oss-120b-vindex">gpt-oss-120b-vindex</a></td><td>—</td><td>S[0] grows 117× with depth (L0=111 → final=13,056)</td></tr>
+<tr><td><strong>Bonsai 8B</strong></td><td>1-bit (Qwen 3 base, post-quantized)</td><td>8B</td><td><em>vindex pending publish</em></td><td>0.429</td><td><strong>C5 = 1</strong> (circuit dissolved); var@64 = 0.093</td></tr>
+<tr><td><strong>BitNet b1.58-2B-4T</strong></td><td>1-bit (Microsoft, native)</td><td>2B</td><td><em>vindex pending publish</em></td><td>(Phase 2 pending)</td><td><strong>var@64 = 0.111</strong> mean across 30 layers — n=2 confirmation of dissolution</td></tr>
 </tbody>
 </table>
+
 <hr />
 <h2 id="whats-a-vindex">What's a vindex?</h2>
 <p>Standard model weights tell you <em>what</em> a model computes. A