llm(frank-archon): swap payload to the publisher's iq4r .rad, shape verbatim

Model swap on the radiance endpoint: MODEL_FILE moves from the in-house
qwen4exp-swift15-w4dn8-i8-hc8m.rad (116,416 MiB) to the engine author's
published qwen3.8-next-flash-fp8-iq4r-moe.rad (116,322 MiB, official
Qwen3.8-Flash-Next bf16 -> 4-bit non-uniform codebook experts + int8
trunk, card KL 0.0789 / top-1 92.85 % vs bf16). NO argument changed:
25600/5120 vram pair, 44928 host pool, fp8 KV, 3 x 200000, MTP depth 2,
wht6, MNBT 2048, froggeric v22.5 — the 2026-10-13 shape carries verbatim.

New fetch script scripts/download-frank-archon-iq4r.sh (hfget + exact
byte count 121,969,901,568 + LFS sha256, --verify-only default, ungated,
no token on the command line). Unit/serve/deployer lore re-keyed; the
seam pins the new payload id + sha256 and keeps the w4dn8 rollback
provenance. Homepage card points at the publisher repo.

Rollback: revert this commit (w4dn8 .rad stays on disk). The fp8-native
rad was deleted from dankserver 2026-10-15 (Frank's one-time rm, volume
for this payload); rebuild path documented.

shared/homepage/services.json

@@ -366,13 +366,13 @@
     "model": {
       "unit": "archon",
       "role": "Frank's strongest and fastest model runtime",
-      "hf": "https://huggingface.co/frank8465/Swift-1.5-Qwen3.8-Flash-Next-GPTQ-W4A8-Radiance-AMD-R9700",
+      "hf": "https://huggingface.co/StillDeadcode/qwen3.8-next-flash-fp8-iq4r-moe",
       "tagline": "...Power Overwhelming...",
       "sfx": [
         "archon-power.ogg"
       ],
       "equiv": "Equivalent to Claude Opus 4.8 / OpenAI-Terra (Summer 2026 frontier intelligence).",
-      "spec": "Our own build: a GPTQ-w4 quant of Swift1.5-Qwen3.8-Flash-Next, quantized and tuned in-house (radiance, ~114 GiB) on twin AMD R9700s with more than 200 GB of system RAM — 200k-token context, three submissions at a time; sees images.",
+      "spec": "The engine author's published quant: 4-bit codebook experts + int8 trunk of Qwen3.8-Flash-Next (radiance, ~114 GiB) on twin AMD R9700s with more than 200 GB of system RAM — 200k-token context, three submissions at a time; sees images.",
       "inputs": [
         "text",
         "image"