homepage+docs: frank-archon runs our own GPTQ-w4 build, link our HF publication

shared/homepage/docs.html

@@ -113,9 +113,9 @@
 
   <h2>frank-archon — the big one <em>(api id: frank-primary)</em></h2>
   <ul>
-    <li><strong>Model:</strong> <a href="https://huggingface.co/Qwen/Qwen3.8-Flash-Next-FP8" target="_blank" rel="noopener">Qwen3.8-Flash-Next</a> at native FP8 precision (radiance, 173&nbsp;GiB) on twin AMD R9700s with more than 200&nbsp;GB of system RAM — the biggest brain on the network and the fastest runtime.</li>
+    <li><strong>Model:</strong> our own build — a GPTQ-w4 quant of <a href="https://huggingface.co/frank8465/Swift-1.5-Qwen3.8-Flash-Next-GPTQ-W4A8-Radiance-AMD-R9700" target="_blank" rel="noopener">Swift1.5-Qwen3.8-Flash-Next</a>, quantized and tuned in-house (radiance, ~114&nbsp;GiB) on twin AMD R9700s with more than 200&nbsp;GB of system RAM — the biggest brain on the network and the fastest runtime.</li>
     <li><strong>Equivalent:</strong> Claude Opus 4.8 / OpenAI-Terra (Summer 2026 frontier intelligence).</li>
-    <li><strong>Capacity:</strong> 200k-token context, two submissions at a time; sees images.</li>
+    <li><strong>Capacity:</strong> 200k-token context, three submissions at a time; sees images.</li>
     <li><strong>Inputs:</strong> text, image.</li>
     <li><strong>Best for:</strong> software engineering, system administration, and instruction tasks. <strong>&#9888; Ask Frank for permission before use</strong> &mdash; this is his primary model; he uses it more than anything else on the fleet.</li>
   </ul>