feat(frank-medium): swap MXFP4 -> FP8; add the one-command swap toolchain

Checkpoint: just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq ->
orcarouter/Qwen3.8-27B-Uncensored-FP8 (FP8 E4M3 block-wise, 30.9 GB / 7
shards, its own single-layer MTP head). The quantization-aware entrypoint
serves the plain FP8 path: --quantization fp8, ROCM_AITER_UNIFIED_ATTN, MTP
self-speculation (SPEC_METHOD=mtp, SPEC=8). Measured: MTP mean accept 5.66/8
(66.2% draft acceptance), KV pool auto-sized to 461,540 tokens (1.76x),
battery 85.9 t/s decode / 0.06 s TTFT / 179.7 burst-4 (vs MXFP4 92.4/0.22/
248.9). MXFP4 checkpoint stays on disk as the rollback target.

Streamlining: scripts/hf-manifest.py (generate a <filename> <size> <sha256>
manifest from the live repo tree), scripts/hf-fetch.sh (resumable, byte +
sha256 verified, idempotent fetch), scripts/swap-frank-medium.sh (generate
manifest -> download -> detect quantization -> edit the quadlet -> deploy).

Docs: new frank-medium-model-swap runbook; radiance runbook, both indexes,
AGENTS.md, and log.md flipped to the FP8 shape.

serverAppConfigs-docs/LLM/frank-medium-radiance-mxfp4.md

@@ -1,7 +1,7 @@
 ---
 type: configuration
 title: frank-medium vllm-radiance MXFP4 Runbook
-description: ACTIVE frank-medium runbook since 2026-09-20 — vllm-radiance MXFP4 serving just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq as ONE tensor-parallel process (TP=2) on Dankserver's two AMD Radeon AI PRO R9700 (gfx1201), with a DFlash2-FP8 drafter. Vision is served by the loaded checkpoint (verified on synthetic images 2026-09-20). The sections below describe the 2026-09-16 two-replica era.
+description: ACTIVE frank-medium runbook since 2026-09-20 — vllm-radiance serving orcarouter/Qwen3.8-27B-Uncensored-FP8 (FP8 E4M3 block-wise, MTP self-speculation) as ONE tensor-parallel process (TP=2) on Dankserver's two AMD Radeon AI PRO R9700 (gfx1201). The quantization-aware entrypoint serves the plain FP8 path; the MXFP4 checkpoint (just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq + the z-lab DFlash2-FP8 drafter) remains on disk as the rollback target. Model-swap process: [[frank-medium-model-swap]]. The sections below describe the 2026-09-16 two-replica era.
 tags:
   - frank-medium
   - dankserver
@@ -28,6 +28,16 @@ It replaced the mainline-llama.cpp layer-split deployment
 model had earlier run here as two single-GPU replicas, which is the shape most
 of this page describes.
 
+**Checkpoint swapped to FP8 on 2026-09-20.** The endpoint now serves
+`orcarouter/Qwen3.8-27B-Uncensored-FP8` (FP8 E4M3 block-wise, 30.9 GB / 7
+shards) with MTP self-speculation — the quantization-aware entrypoint reads
+`quant_method` from `config.json` and serves the plain FP8 path (no MXFP4
+patches, `--quantization fp8`, `ROCM_AITER_UNIFIED_ATTN`). The MXFP4
+checkpoint above remains on disk as the rollback target. The swap process,
+the toolchain, and the measured trade-off are in [[frank-medium-model-swap]];
+the "Deployed flags" table below still shows the MXFP4 shape (the rollback
+target).
+
 **Deployed shape since 2026-09-20: one rootless Quadlet, `--tensor-parallel-size 2`.**
 The ProArt B850-Creator WiFi NEO board swap put both R9700s on CPU GPP root
 ports (`00:01.1 → 03:00.0` and `00:01.3 → 07:00.0`), both Gen5 x8, every
@@ -43,8 +53,8 @@ From `dankserver/frank-medium/quadlet/frank-medium.container`:
 
 | Setting | Value |
 |---|---|
-| Model | `just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq` |
-| Speculative | `--speculative-config {"method":"dflash","model":"/models/draft","num_speculative_tokens":7}` (z-lab DFlash2-FP8) |
+| Model | `orcarouter/Qwen3.8-27B-Uncensored-FP8` (FP8 E4M3 block-wise 128×128, 30.9 GB / 7 shards) |
+| Speculative | `--speculative-config {"method":"mtp","num_speculative_tokens":8}` (the model's own single-layer MTP head; mean acceptance 5.66/8, 66.2% draft acceptance) |
 | Parallelism | `--tensor-parallel-size 2` (`ROCR_VISIBLE_DEVICES=0,1`) |
 | Context | `--max-model-len 262144` |
 | Concurrency | `--max-num-seqs 8`, chunk 8192 |
@@ -56,17 +66,17 @@ From `dankserver/frank-medium/quadlet/frank-medium.container`:
 | Multimodal | `--limit-mm-per-prompt '{"image": 8}'` |
 | Chat template | `qwen-fixed-v22.3.jinja` (patch dir bind-mounted, `MM_MERGE_ENGINE=AXROW_SEPARATE` for Gemma4 vision) |
 
-**The KV pool is auto-sized, not pinned.** The arm-R benchmark run used
-`KV_CACHE_MEMORY_MB=18563072000`, which bought exactly one 262,144-token
-sequence (262,720 tokens at 70,656 B/token — a profile inflated by the
-8192-chunk activation peak). Production ships no such pin: the pool came up at
-**943,581 tokens = 3.59× the full window**, and the boot line read
-`Available KV cache memory: 18.17 GiB → GPU KV cache size: 943,581 tokens`.
+**The KV pool is auto-sized, not pinned.** Production ships no `KV_MEM` pin
+(`KV_MEM=0`): the pool comes up at whatever VRAM the weights leave. The FP8
+checkpoint is bigger than the MXFP4 one (30.9 vs 19.4 GiB of weights), so it
+leaves less for the pool: the 2026-09-20 FP8 start auto-sized to **461,540
+tokens = 1.76× the full window** (`GPU KV cache size: 461,540 tokens`,
+`Maximum concurrency for 262,144 tokens per request: 1.76x`). The MXFP4
+rollback target auto-sized to 943,581 tokens (3.59×) on the same cards.
 Per-token cost in steady state is 19,673 B — fp8 KV across the model's 16
-full-attention layers plus the drafter's. Container RSS measured 28.4 GiB
-against the host's 62 GiB and stayed flat through a 4-way burst at 512-token
-max; host-wide swap 3.3 GiB, unchanged. The 2026-09-16 swap storm was the
-two-replica vision shape, not this one.
+full-attention layers plus the MTP drafter's. After the first healthy start,
+recalibrate with `calibrate-kv.sh` to use the extra VRAM on the 34.2 GiB
+cards.
 
 ## Prefix caching — measured granularity (2026-09-20)