Update index.html: Kimi-K2 (complete), DeepSeek-V4-Flash (1B running), DeepSeek-V4-Pro (queued)

index.html

@@ -52,7 +52,8 @@ offline-built search index.</p>
 <h2 id="published-vindexes">Published vindexes</h2>
 <p>Cross-family evidence in hand: <strong>Gemma</strong>,
 <strong>Qwen3</strong>, <strong>Mistral</strong>,
-<strong>Llama</strong>, <strong>OpenAI MoE</strong>, plus two 1-bit
+<strong>Llama</strong>, <strong>OpenAI MoE</strong>,
+<strong>Moonshot MoE</strong>, <strong>DeepSeek-V4 MoE</strong>, plus two 1-bit
 controls.</p>
 <table>
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@@ -65,6 +66,9 @@ controls.</p>
 <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>Kimi-K2-Instruct</strong></td><td>MoE fp8-native (DeepSeek-V3 style)</td><td>1T / 32B active</td><td><a href="https://huggingface.co/Divinci-AI/kimi-k2-instruct-vindex">kimi-k2-instruct-vindex</a></td><td><strong>0.0938</strong> (MoE median)</td><td>60 MoE layers; 42.28 GB gate_proj binary; broader L52–L60 secondary rise than initial dome SVD suggested</td></tr>
+<tr><td><strong>DeepSeek-V4-Flash</strong></td><td>MoE MXFP4 (DeepSeek-V4)</td><td>43L / 256 experts / 6 active</td><td><em>publishing soon</em></td><td>—</td><td><strong>Phase 1B running</strong>; first-peak L17 + double-bend profile (distinct from Kimi smooth dome); MXFP4 unpacker added to builder</td></tr>
+<tr><td><strong>DeepSeek-V4-Pro</strong></td><td>MoE MXFP4 (DeepSeek-V4)</td><td>61L / 384 experts / 6 active</td><td><em>queued</em></td><td>—</td><td>Queued; same scale as Kimi-K2 (60–61 layers × 384 experts × 7168 hidden); MXFP4 expert weights</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>
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